# Monsanto Petitions ( 10

- 188

- 01p and 12

- 185

- 01p) for Determinations of Nonregulated Status for Dicamba

R esistant Soybean and Cotton Varieties

Final Environmental Impact Statement

December 201 4

A g en c y Co n tac t :

Sid Abel Biotechnology Regulatory Services 4700 River Road USDA, APHIS Riverdale, MD 20737 Fax: (301) 734

- 6352

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– W, Whitten Building, 1400 Independence Avenue, SW, Washington, DC 20250

– 9410 or call (202) 720

– 5964 (voic e and TDD). USDA is an equal opportunity provider and employer.

Mention of companies or commercial products in this report does not imply recommendation or endorsement by the U.S. Department of Agricult ure over others not mentioned. USDA neither guarantees nor warrants the stan dard of any product mentioned. Product names are mentioned solely to report factually on available data and to provi de specific information.
This publication reports research involving pesticides. All uses of pesticides must be registered by appropriate State and/or Federal agencies before they can be recommended.

C A U TIO N : P e s t i c id e s c a n b e in j u r

io u s to h u m a n s, d o m e st i c an i m a l s , de sir a b le p la n t s , an d f i sh and o t he r w il d l i f e

— if t he y ar e no t hand led o r app li e d prope r l y

. U se a ll pe s t i cid e s s e le ct i ve ly an d c are f u ll y

. Foll o w re c o mme nde d label p r a ct i c e s

### Executive Summary

The U.S. Department of Agriculture (USDA), Animal and Plant Health Inspection Service (APHIS) received two requests (petitions) from Monsanto Company, St. Louis, MO (Monsanto) seeking determinations of nonregulated status for genetically engineered (GE) plant varieties referred to as MON 8 7708 soybean and MON 88701 cotton, that have been engineered to be resistant to the herbicide dicamba ( Monsanto, 2012b ; 2012a ) . These GE plant varieties are currently regulated by APHIS, and Monsanto requests that APHIS grant the petitions ( Petition 10

- 188

- 01p for MON 87708 soybean and Petition 12

- 185

- 01p for MON 88701 cotton )

, so that these varieties can be grown without any APHIS regulatory oversight. Since these two GE plant varieties are currently under APHIS regulatory oversight, the Agency requires Monsanto to comply with a full range of safeguarding measures to ensure that these regulated GE plant varieties do not transfer or spread from their APHIS

- approved outdoor planting sites. APHIS authorization is also required to move these regulated varieties intersta te.

Once a developer of a GE plant has obtain ed sufficient information to conclude that its regulated GE plant is unlikely to cause injury, damage, or disease to plants or plant products ( i.e., pose a plant pest risk ), it may submit a p etition to APHIS to no longer regulate the organism . This is referred to as seeking nonregulated status

. If a petition for nonregulated status is approved by APHIS, permits or notifications are no longer required by the Agency to grow or ship the GE plant throughout the United States and its territories. If APHIS determines that nonregulated status is appropriate for one or both the Monsanto GE varieties, they will no longer be subject to any regulations pursuant to Part 340.

Regulatory Authority

APHIS regu lates certain GE organisms under the authority of the PPA of 2000 as amended ( 7 U.S.C. §§ 7701

– 7772 ) , and by APHIS regulations codified in Title 7, part 340 of the U.S. Code of Federal Regulations (7 CFR part 340). The APHIS part 340 regulations govern a GE organism in the following circumstances: if it is a plant pest (such as certain microorganisms or insects that can cause injury or damage to plants); if it is created using an organism that is itself a plant pest; if APHIS does not have sufficient inf ormation to determine if the GE organism is or may be a plant pest

. Any party can petition APHIS for “nonregulated status” of a GE organism (that is, to discontinue regulating a GE organism that falls under its regulations) through the procedures described in 7 CFR § 340.6. APHIS regulates such a GE organism until a request for nonregulated status is made. The agency then evaluates whether it m eets the PPA definition of a plant pest

, and it concludes on the basis of scientific evidence t hat the GE organism is unlikely to pose a plant pest risk by determining that the potential for the GE organism to cause plant disease or damage is unlikely. The petitioner must provide data, including information obtained from confi ned field tests regulated by APHIS, to help inform Agency decisionmakers. APHIS analyzes the data from the petitioner, researches current scientific findings, and prepares a Plant Pest Risk Assessment (PPRA ) that documents whether or not the GE organism is likely to cause disease or damage. If APHIS concludes that the GE organism does not pose plant pest risk, APHIS must then issue a iregulatory decision of non

- regulated status

, since the A gency does not have regulatory authority to regulate organisms that are not plant pests. When a determination of nonregulated status has been issued, the GE organism may be introduced into the environment without APHIS regulatory oversight under Part 340 . In the case of the GE soybean and cotton varieties that are the subject of this environmental impact statement (EIS) , if nonregulated status is determined to be appropriate for them, Monsanto w ill be allowed to sell the GE seeds to farmers, and growers will be able to grow, harvest, and move their crop into commerce for food and feed without any authorization from APHIS.

Two other agencies, the Federal Drug Administration (FDA) and the Environmental Protection Agency (EPA), provide oversight of GE plants . The relative roles of the USDA (through APHIS), the FDA, and the EPA are described by the “Coordinated Framework

, ” a 1986 policy statement from the Office of Science and Technology Policy that describes the comprehensive Federal policy for ensuring the s afety of biotechnology research and products ( US

- OSTP, 1986 )

.
The FDA’s regulation of GE plants is based upon its authority to regulate food safety under the Federal Food, Drug, and Cosmetic Act (FFDCA ) 21 U.S.C. §§ 301

– 399. The FDA implements a voluntary consultation process to ensure that human food and animal feed safety issues or other regulatory issues, such as labeling, are resolved before commercial distribution of food derived from GE products.

The EPA regulates the use, sale, and labeling of pesticides pursuant to its authority under the F ederal Insecticide, Fungicide, and Rodenticide Act (FIFRA ) (7 U.S.C. §§ 136

– 136y). EPA’ s actions under FIFRA directly a ffect the production methods used on herbicide

- resistant (HR) GE plants. An he rbicide must first be “registered” by the EPA before it can be distributed or sold in the U.S. (7 U.S.C. §§ 136a(a),136j(a)(2)(F)). The EPA registration process starts with the herbicide manufacturer providing the EPA with information about the herbicide ( 7 U.S.C

. § 136a(c)(1)(C), (F)). The agency then evaluates the adverse effects it may have on humans and the environment in accordance with the proposed label . On the basis of this evaluation, the EPA then determines if it will allow use of the herbicide on a plant, and, if so, under what conditions and in what quantity. The EPA sets the conditions for herbicide use and places them in labeling instructions that a user must follow ( See 7 U.S.C. 136j(a)(2)(G)). The EPA reevaluates all pesticides, which includes herbicide s, every fifteen years (or shorter) to ensure they meet current standards for continued safe use ( 7 U.S.C. § 136a(g)(1)(A)(iv)). Under FIFRA, the EPA also regulates plant

- incorporated protectants (PIPs) which are pes ticidal substances produced by plants and the genetic material necessary for the plant to produce the substance.

The varieties that are the subject of this EIS

, MON 87708 soybean and MON 88701 cotton

, are both resistant to the herbicide dicamba

. MON 88701 cotton is also resistant to the herbicide glufosinate. The EPA is currently reviewing proposed changes in the registered use s of dicamba on these s oybean and cotton varieties. If approved by the EPA

, these label changes will allow for the direct applicatio n of dicamba to MON 87708 soybean and MON 88701 cotton

. Following the

iiEPA ’s approval, dicamba herbicide products that could be used on MON 87708 soybean and MON 88701 cotton could include low er volatility dicamba formulations based on the diglycolamine (DGA) salt

, as well as those based on the BAPMA 1 salt. These proposed label changes were requested by Monsanto based on the standard that the new uses of this herbicide would not cause any unreasonable adverse environmental effects and a reasonable certain ty of no harm to humans, so long as it was applied in accordance with its labeling instructions. Monsanto is not requesting any changes to the current EPA

- approved uses for glufosinate for MON 88701
cotton ; thus, no new review of the label by the EPA is re quired. The EPA does not regulate MON 87708 soybean and MON 88701 cotton plants because these plant s are not plant incorpo r ated protectants

. Purpose of MON 87708 Soybean and MON 88701 Cotton

Monsanto has developed these two GE plant varieties as alternati ves to currently available GE herbicide

- resistant ( HR ) soybean and cotton varieties ( Monsanto, 2012a ; 2012b )

. The primary purpose of MON 87708 soybean and MON 88701 cotton is to provide growers with additional and enhanced pre

- emergence and in

- crop weed management opti ons in soybean and cotton cultivation to control a broad spectrum of broadl eaf weeds, including glyphosate

- resistant ( GR ) broadleaf weed species

. Each of the se varieties has a trait that makes the plant resistant to dicamba, an active ingredient in many he rbicide formulations . MON 87708 soybean and MON 88701 cotton can be treated with dicamba after sprouting , killing competing weeds but not the developing soybean or cotton seedlings. MON 88701 cotton is also resistant to glufosinate, so both herbicides may be used on this cotton variety after planting. If MON 87 708 soybean and MON 88701 cottonare no longer regulated they would also be available for cross

- breeding with all other GE varieties that are no longer regulated by APHIS . For the technical details on these
t wo GE plant cultivars , see the petitions submitted by Monsanto which are available on the APHIS website ( USDA

- APHIS, 2014f )

. Purpose and Need for Agency Action

APHIS regulations require that APHIS make decisions on the petitions it rec eives for nonregulated status. The Agency can choose to approve a petition in whole or in part , or it can deny the petition. As previously mentioned, t he APHIS deci sion is based on a PPRA for the GE plants that are the subject of the petition. Plant pest risks are those risks caused by plant pest s that can cause injury, damage, or diseas e to plants or plant products. Consistent with the APHIS authority under the PPA, m arket acceptance of a pr oduct is not a plant pest risk.

The purpose of the petition process and the decisions made under the regulations is to protect plant health. Developers who can demonstrate through this process that their products do not cause plant pest risks can enter their products into commerce without restrictions. APHIS must make a decis ion that is consistent with the Agency’s statutory and regulatory authority.

1 N, N

- Bis

- (aminopropyl) methylamine

iiiIn response to the receipt of the t wo Monsanto petitions, APHIS prepared P PRAs to assess the plant pest risk for each plant variety. In addition to the PPRAs, APHIS must also prepare an environmental analysis consistent with its obligations under the National En vironmental Policy Act (NEPA ). Under NEPA regulations , an agency conducts an e nvironmental a ssessment (EA) to d etermine if a major federal agency action will cause significant en vironmental impacts (40 CFR § 1501.4). If the agency concludes in its EA that its action will not significantly impact the environment, the agency issues a “Finding of No Significant Impact ” (FONSI) and the agency can proceed with its proposed action without preparing a more thorough EIS. If th e EA concludes that the proposed action may significantly affect the environment, the agency must prepare an E IS

. However, an agency may determine tha t significant impacts are possible without formally preparing an EA and proceed to the preparation of an EIS.

Public Involvement

APHIS sought comments for the petitions that are the subject of this EIS in a Federal Register notice dated July 13, 2012

, and February 27, 2013 . Comments received for the petitions were influential, though not the sole basis, for the Agency’s decision to prepare this EIS. In reviewing the petitions for determinations of nonregulated status of crop cultivars genetically engineere d to be resistant to various herbicides, APHIS has identified the potential selection of HR weeds as a potential environmental impact. As part of its scoping process to identify issues to address in this EIS, APHIS also published a Notice o f Intent (NOI) to prepare an EIS and sought public input during a comment period (May 10 to July 17, 2013). Comments were submitted by individuals, academic researchers, non

- government organizations, and industry representatives. The majority of comments s ubmitted by non

- government organizations and individuals were opposed to determinations of nonregulated status for the petitions. The majority of comments submitted by industry and academia supported determinations of nonregulat ed status for MON 87708 soyb ean and MON 88701 cotton. These comments are summarized in Appendix 2.

The draft EIS (DEIS) was made available for public comment for 45 days from August 11 through September 25, 2014; the comment period was further extended to October 10, 2014. APHIS held a virtual public meeting on the DEIS on September 11, 2014. At the end of the 60

- day comment period (October 10, 2014), APHIS reviewed and evaluated all of the comments received. APHIS received 4,693 submissions to the EIS docket (APHIS 2013

- 0043) with th e majority of commenters supporting determinations of nonregulated status for MON 87708 soybean and MON 88701 cotton. A summary of public comments on the DEIS and responses to those comments are presented in Appendix 11.

Alternatives Analyzed

In this EIS, APHIS consider ed four alternatives for its response to the two Monsanto petitions for nonregulated status . The four alternatives a re: 1) continue to regulate MON 87708 soybean and MON 88701 cotton (i.e., n o a ction ) ; 2) approve the petitions for nonregulated status of MON 87708 soybean and MON 88701 cotton; 3) approve the petition for nonregulated status for MON 88701 cotton only ; and 4) approve the petition for nonregulated status for MON 87708 soybean only

. These alternatives ar e further described here and in Section 2.1.
ivAlternative 1: No Action Alternative

— Continuation as Regulated Articles

Under the No Action Alternative, APHIS would deny the t wo petitions because the two varieties that are the subject of the petitions would p resent a plant pest risk and would continue to be regulated by APHIS. Permits issued or notifications acknowledged by APHIS would still be required for the introduction of MON 87708 soybean and MON 88701 cotton , and measures to
ensure p hysical and reproductive confinement wou ld continue to be implemented. This

a lternative is not the Preferred Alternative because APHIS has concluded in its PPRAs that MON 87708 soybean and MON 88701 cotton are unlikely to pose p lant pe st risks ( USDA

APHIS, 2014d ; 2014e )

. Therefore, choosing this alternative would not be consistent with the scientific evidence before the A gency regarding lack of plant pest risk and thus would not fully satisfy the purpose and need of making the required regulatory determination under the PPA and 7 CFR part 340.6.

Alternative 2: Determination of Nonregulated Status of MON 87708 S oybean and MON 88701 Cotton (Preferred Alternative)

Under this alternative , MON 87708 soybean and MON 88701cotton and their progeny would no longer be subject to APHIS biotechnology regulations (7 CFR part 340) as they have been determined unlikely to pose p lant pest risk s . Permits issued or notificatio ns acknowledged by APHIS would no longer be required for introductions of these varieties. This alternative meets the purpose and need to respond appropriately to the petitions for nonregulated status ( Monsanto, 2012a ; 2012b )

, the requirements in 7 CFR p art 340, and the Agency’s regulatory authority under the plant pest provisions of the PPA, because APHIS has concluded in its PPRAs that these varieties are unlikely to pose p lant pest risks ( USDA

- APHIS, 2014d ; 2014e )

. Therefore, this is the Preferred Alternative because approving the petitions for nonregulated status for both varieties is consistent with the scientific evidence before the A gency regarding lack of plant pest risk and would satisfy the purpose and ne ed of making the required regulatory determination under the PPA and 7 CFR part 340.6

. Alternative 3: Approve the P etition for a Determination of Nonregulated Status Only for MON 88701 Cotton Only

Under this alternative , only MON 88701 cotton and progeny derived from its cultivation would no longer be subject to APHIS biotechnology regulations (7 CFR part 340) as it has been determined unlikely to pose a plant pest risk . Permits issued or notifications acknowledged b y APHIS would no longer be required for this co tton variety and its progeny. This alternative meets the purpose and need to respond appropriately to the petition for nonregulated status for MON 88701 cotton ( Monsanto, 2012b ) , the requirements in 7 CFR part 340 and the Agency’s regulatory authority under the plant pest provisions of the PPA because A PHIS has concluded in its PPRA that it is unlikely to pose a plant pest risk ( USDA

- APHIS, 2014e )

. Therefore, approving the petition for a determination of nonregulated status for MON 88701 cotton is consistent with the plant pest provisions of the PPA and the regulations codified in 7 CFR part 340. However

, because APHIS has concluded in its PPRA that MON 87708 s oybean is also unlikely to pose a plant pest risk ( USDA

- APHIS, 2014d ) , choosing this alternative is

vin consistent with the scientific evidence before the agency regarding lack of plant pest risk and would not satisfy the purpose and need of making the required regulatory determination under the PPA and 7 CFR part 340.6

.
Alt ernative 4: Approve the Petition for a Determination of Nonregulated Status Only for MON 87708 Soybean

Under this alternative , only MON 87708 soybean and progeny derived from its cultivation would no longer be subject to the APHIS bio technology regulations (7 CFR part 340) as it has been determined unlikely to pose a plant pest risk . Permits issued or notifications acknowledged by APHIS would no longer be required for its introduction and progeny derived from it . Th is alternative meets the purpose and need to respond appropriately to the petition for nonregulated status for MON 87708 soybean ( Monsanto, 2012a ) , the requirements in 7 CFR part 340 and the Agency’s regulatory authority under the plant pest provisions of the PPA, because APHIS has concluded in its PPRA that it is unlikely to pose plant pest risk ( USDA

- APHIS, 2014d )

. Therefore, approving the petition for a determ ination of nonregulated status for MON 87708 soybean is consistent with the plant pest provisions of the PPA and the regulations codified in 7 CFR part 340. However, because APHIS has concluded in its PPRA that MON 88701cotton is also unlikely to pose plan t a p lant pest risk ( USDA

- APHIS, 2014e ) , choosing this alternative would be in consistent with the scientific evidence be fore the agency regarding lack of plant pest risk and would not satisfy the purpose and need of making the required regulatory determination under the PPA and 7 CFR part 340.6

.
Affected Environment

T o determine the extent of the potential environmental imp acts that could result from any APHIS decision related to the regulation of MON 87708 soybean and MON 88701 cotton , APHIS used information provided by the USDA National Agricultural Statistics Service (USDA

- NASS) to identify those regions of the country where soybeans and cotton are grown. To describe the ecological features of soybean and cotton regions, APHIS compared these growing areas to maps that group regions having similar ecological attributes such as soi l, landform, or major vegetation types ( CEC, 2009 )

. These regions are termed ecoregions and are identified as regions A through M in this EIS. To identify the types of land cover and crops grown in each region, APHIS analyzed information in the USDA

- NASS on line tool “Cropscape

, ” an information source that compiles these data from satellite imagery.

Potential Environmental Consequences of Alternatives

Environmental issues are assessed individually in Chapter 4 (Potential Environmental Consequences). As stated previously, APHIS has regulatory authority based on the plant pest potential of MON 87708 soybean and MON 88701 cotton cultivars; the EPA has regulatory authority over pesticide products and uses , such as dicamba . The scope of this EIS analyzes the potential for direct and indirect impacts that might result from the cultivation and use of these GE crop varieties.

viThe EPA regulates the use of herbicides under FIFRA and is making a separate decision which may or may not allow new uses of dicamba

. While MON 87708 soybean and MON 88701 cotton are engineered to resist damage from the application of dicamba , selection of a particular alternative by APHIS does not allow the new uses of dicamba on these soybean and cotton varieties. The EPA, in its registration process, is considering any direct and indirect impacts from the proposed new uses of dicamba on these varieties. The dicamba product proposed for

re gistration for use for treating dicamba

- resistant soybean and cotton is the M1691 h erbicide formulation (EPA Reg. No. 524

- 582) which is in the form of the diglycolamine salt of dicamba. APHIS will not duplicate the assessments prepared by the EPA.

APHIS e mphasizes that its decision to prepare an EIS in this case was discretionary

. The agency’s decision was based on a perceived need for the level of thoroughness afforded by the EIS process because of the complexity of issues that needed to be addressed. The se issues initially include d the potential environmental impacts associated with the increased use of certain herbicides and possible selection for and spread of weeds resistant to the herbicide dicamba combined with resistance to other herbicides (multipl e resistance)

. APHIS considers these in detail in Chapter 5 which considers potential cumulative impact s that may result if APHIS recognizes nonregulated status for MON 87708 soybean and MON 88701 cotton, and if the EPA registers the proposed new uses of dicamba on these crop varieties.

APHIS determined that the direct impacts on the environment from the cultivation of MON 87708 soybean and MON 88701 cotton would not differ from those caused by the cultivation of other soybean and cotton varieties , because these GE varieties are not agronomically different from non

- GE soybean and cotton cultivars or other GE soybean or cotton cultivars that are no longer regulated by the Agency. These two GE plant varieties do not directly affect natural (e

. g. , soil, water, air) or biological (e

. g. , animal, insect, plant) resources . However, the agricultural management practices (e.g., tillage practice s) associated with their cult ivation may indirectly impact natural and biological resources. For example , the need for tillage , which may adversely affect soil, water, and air quality

, and greenhouse gas emissions , is likely to stabilize in conjunction with the wee d management alternatives presented by the cultivation of MON 87708 soybean and MON 88701 cotton.
Potential Cumulative Impacts

Chapter 5 of this EIS includes an environmental analysis of potential cumulative impact s, including h ow herbicide use may change

, if APHIS approves the petitions for nonregulatory status of MON 87708 soybean and MON 88701 cotton and the EPA approves the proposed registration changes for dicamba. As part of its analysis, APHIS conside red the potential effects of the development of dicamba

- resistant weeds if the EPA approves the new dicamba use s on MON 87708 soybean and MON 88701 cotton. In particular, APHIS evaluated the impacts of dicamba

- resistant weeds on the cultivation of crops, other than soybean and cotton, on which dicamba is used currently ( see Appendix 4, Table s 4

- 8 and 4

- 12 for more details )

. The availability of dicamba

- resistant soybean and cotton in conjunction with EPA’s approval of the new uses of dicamba on these new v arieties w ould result in growers who adopt the varieties
viichang ing management practices . For instance, dicamba use may increase to levels greater than what might occur if these varieties were not available

. Another anticipated change is that dicamba could b e used over a wider part of the growing season. Both changes in management practices would be expected to increase the pressure for selection of dicamba

- resistant weeds. Growers themselves can influence this selection pressure by the management practices t hey choose. For example, rotating crops, rotating types of herbicides, using cover crop s, scouting for weeds and using mechanical tillage to prevent weeds from flowering, are just some of the practices that can be followed to reduce or delay the selection of HR weeds. Groups such as the Weed Science Society of America (WSSA), university extension agents, crop consultants, and industry representatives , have made a concerted effort to increase grower awareness of best management practices for managing the development of HR weeds ( see Section 5.7.2 for a detailed review of this topic ).

The EPA has noted the increasing problems and economic issues growers are facing from the emergence of HR weeds. In 2014, a s part of the registration of Dow’ s Enlist Duo (a 2,4

- D choline salt and glyphosate premix), EPA impos ed a new, robust set of requirements on the registrant. These requirements include extensive surveying and reporting to EPA, grower education and remediation plans. The registration will e xpire in six years, allowing EPA to revisit the issue of resistance. In the future, the agency intends to apply this approach to weed resistance management for all existing and new herbicides used on herbicide tolerant crops

. 2 Therefore, APHIS expects the EPA to implement similar requirements , including an herbicide resistance management plan

, as part of the registration of the M1691 dicamba formulation for application to MON 87708 soybean and MON 88701cotton

. Additionally, APHIS assumes t hat growers will adhere to the EPA label requirements.

Dicamba

- resistant weeds might become more prevalent as a result of dicamba use on MON 87708 soybean and MON 88701 cotton if growers fail to diversify weed management practices in a comprehensive strate gy (i.e., best management practices) to mitigate weed resistance development. As a result , growers of other crops that rely on dicamba f or weed control might have to modify management practices to control additional weeds that become resistant to dicamba. The se necessary management changes c ould increase the complexity and cost of weed
managem ent programs for some of these growers. Because the use of dicamba on MON 87 708 soybean and MON 88701 cotton does not require a single specific set of agronomic practi ces, the magnitude of the effects would depend on the adoption rates of various practices by growers.

In the cumulative impact s assessment, the selection pressure for dicamba

- resistant weeds is expected to be greater under the Preferred Alternative, while the selection pressure for GR weeds is expected to be greater under the No Action Alternative. This is because the cropping system s that use dicamba potentially decrease growe r reliance on glyphosate by including an additional type of herbicide in the weed management system. The continued emergence of GR weeds under

2 h ttp://yosemite.epa.gov/opa/admpress.nsf/bd4379a92ceceeac8525735900400c27/72fde554930f3f6985257d720059 1180!OpenDocument

viiithe No Action Alternative will itself require modification of crop management pr actices to address these weeds.

G rowers will likely continue to use glyphosate because it is still effective on hundreds of weed species. However, farmers are also expected to depend on additional chemical and non

- chemical methods to control GR weeds. Changes in management practices are e xpected to include more use of non

- glyphosate herbicides and adjustments to crop rotation and tillage practice s ( Owen et al. , 2011 ) . Use of herbicides that kill weeds by mechanisms (referred to as sites of action; see Appendix 3 for details) that differ from that of glyphosate are expect ed to increase as growers alter methods to manage GR weeds.

Selection for GR weeds is expected to continue under all the alternatives . Effects of this trend can be minimized if best management practices incorporating a diversity of weed control methods are used by growers

. Areas where GR weeds are expected to remain a serious problem include the Southeast, Great Plains and Northern Crescent. Weed resistance to other non

glyphosate herbicides has also be come prevalent in many regions (see Appendix 6 for more details). For example, a total of 146 species worldwide show resistance to ALS inhibitors ( Heap, 2014d ) , including the five classes Imidazolinones, Pyrimidinylthiobenzoates, Sulfonylaminocarbonyltriazolinone, Sulfonylureas, and Triazolopyrimidines; ALS resistance in Palmer amaranth includes seventeen US reports and more will likely develop

. As a result, herbicide options for weed management may become less attractive under the No Action Alternative and growers may be forced to re turn to more aggressive tillage systems to maintain productive soybean yields (Conley, 2013).

When co nsidering cumulative impact s u nder the Preferred Alternative, APHIS assumed that the EPA approves the proposed new uses of dicam ba on these crops and dicamba use is expected to increase relative to the No Action Alternative. However, increases in the use of other herbicide sites of action under the Preferred Alternative are expected to be less than under the No Action Alternative b ecause dicamba is expected to be preferentially adopted if approved for use on these crops by EPA. The availability of inexpensive and effective herbicides may delay the adoption of

non

- chemical management strategies under the Preferred Alternative. Fewer growers would be expected to adopt aggressive tillage when herbicides remain both cost effective and efficacious for weed control. Selection of weeds resistant to glyphosate, and non

- glyphosate herbicides will continue to occur under the Preferred Alternat ive

. The selection pressure for HR weeds under the Preferred Alternative relative to the No Action Alternative will depend on the management practices chosen and cannot be predicted. Under the No Action Alternative, natural resources are expected to be neg atively impacted by th e continued trend of a return to more aggressive tillage practice s. If conventional tillage continues to increases to control GR/HR weeds, several negative impacts are likely: reduced soil quality from increased erosion; reduced air quality from increased air particulates and increased exhaust emissions from farm equipment; reduced water quality from the release and mobilization of sediments, nutrients, and other chemic als into surface and groundwater ; increased greenhouse gases from burning additional fossil fuels and releases of sequestered carbon from disrupted soil; and reduced biodiversity from habitat loss. The total acreage that may be impacted by such increases in tillage would be based on the extent of resistant weeds present in a field and the weed management strategy chosen by a grower. ixAdoption of MON 87708 soybean and MON 88701 cotton and t he new approved use of dicamba on these varieties can provide growers with an alternative broadleaf herbicide to suppl ement glyphosate, and provid e multiple effective herbicides for specific weeds , which will both benefit weed control plans . In some cases, these HR crops and the new use of dicamba on them will provide growers with an alternative to intensive tillage practice s that may be used to manage HR weeds. However, the development of more resistant weed species to more types of herbicides could reduce the long

- term use of dicamba and any associated benefits to natural resources. The magnitude of this impact is uncertain because of the difficulty of characterizing the variability of the decisions made by c rop production managers and individual growers.

x

## Table of Contents

LIST OF FIGURES

................................ ................................ ................................ .................. XVII

LIST OF TABLES

................................ ................................ ................................ ..................... XIX

LIST OF APPENDICES

................................ ................................ ................................ ............ XXI

ACRONYMS AND ABBREVI ATIONS

................................ ................................ ................. XXII

1 PURPOSE AND NEED

................................ ................................ ................................ ........... 1

1.1 Introduction

................................ ................................ ................................ ............... 1

1.2 APHIS Re gulatory Authority

................................ ................................ .................... 2

1.3 Requirement for This Document

................................ ................................ ............... 2

1.4 Purpose of These Products

................................ ................................ ........................ 3

1.4.1 MON 87708 Soybean

................................ ................................ ................................ 4

1.4.2 MON 88701 Cotton

................................ ................................ ................................ ... 5

1.5 Coordinated Regulatory Framework for Genetically

- Engineered Organisms

.......... 6

1.5.1 USDA

- APHIS

................................ ................................ ................................ ............ 6

1.5.2 Enviro nmental Protection Agency

................................ ................................ ............. 7

1.5.3 Food and Drug Administration

................................ ................................ .................. 8

1.6 Purpose and Need for this APHIS Action

................................ ................................ . 8

1.7 Public Involvement

................................ ................................ ................................ .... 9

1.7.1 Public Comments for Petitions 10

- 188

- 01p and 12

- 185

- 01p

................................ .. 10

1.7.2 Public Comment Period for Draft EIS

................................ ................................ ..... 10

1.7.3 Issues Considered in This EIS

................................ ................................ ................. 12

2 ALTERNATIVES

................................ ................................ ................................ .................. 13

2.1 Alternative Considered and Selected for Further Evaluation for This EIS

............. 13

2.1.1 Alternative 1: No Action Alternative

- Continuat ion as Regulated Articles

........... 13

xi

## Table of Contents

2.1.2 Alternative 2: Determination of Nonregulated Status of MON 87708 Soybean and MON 88701 Cotton (Preferred Alternative)

................................ ........................... 13

2.1.3 Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton, Only

................................ ................................ ................................ ......................... 14

2.1.4 Alternative 4: Determination of Nonregulated Status for MON 87708 S oybean, Only

................................ ................................ ................................ ......................... 14

2.2 Alternatives Considered but Not Selected for Further Evaluation

.......................... 14

2.2.1 Prohibit Any MON 87708 Soybean and MON 88701 Cotton from Being Released 15

2.2.2 Approve the Petition(s) in Part

................................ ................................ ................ 15

2.2.3 Production/Geographical Restrictions to Isolate MON 87708 Soybean and MON 88701 Cotton from Non

- GE Soybean or Cotton

................................ ..................... 15

2.2.4 Requirement of Testing for MON 87708 Soybean and MON 88701 Cotton

.......... 16

2.3 Comparison of Alternatives

................................ ................................ ..................... 16

3 AFFECTED ENVIRONMENT

................................ ................................ ............................. 24

3.1 U.S. Cotton and Soybean Economics

................................ ................................ ...... 24

3.1.1 U.S. Cotton Economics

................................ ................................ ............................ 24

3.1.2 U.S. Soybean Economics

................................ ................................ ......................... 27

3.2 U.S. Cotton and Soybean Production

................................ ................................ ...... 29

3.2.1 Major U.S. Cotton and Soybean Production Regions

................................ ............. 29

3.2.2 Ecoregions of the Affected Environment

................................ ................................ 29

3.3 Physical Environment

................................ ................................ .............................. 32

3.3.1 Physical Terrain and Climate

................................ ................................ ................... 32

3.3.2 Soil Resources

................................ ................................ ................................ .......... 38

3.3.3 Water Resources

................................ ................................ ................................ ...... 40

3.3.4 Air Quality

................................ ................................ ................................ ............... 46

3.3.5 Climate Change

................................ ................................ ................................ ........ 49
xii

## Table of Contents

3.3.6 La nd Resources

................................ ................................ ................................ ........ 52

3.4 Biological Resources

................................ ................................ ............................... 60

3.4.1 Animal Communities

................................ ................................ ............................... 60

3.4.2 Plant Communities

................................ ................................ ................................ ... 68

3.4. 3 Microorganisms

................................ ................................ ................................ ....... 69

3.5 Agronomic Practices in Cotton and Soybean Production

................................ ....... 70

3.5.1 Tillage

................................ ................................ ................................ ...................... 71

3.5.2 Crop Rotation

................................ ................................ ................................ ........... 73

3.5.3 Ag ronomic Inputs

................................ ................................ ................................ .... 77

3.5.4 Organic Cotton and Soybean Production

................................ ................................ . 86

3.5.5 GE Cotton and Soybean

................................ ................................ ........................... 91

3.6 Health and Safety for Humans and Livestock

................................ ......................... 92

3.6.1 Worker Safety

................................ ................................ ................................ .......... 94

3.6.2 Public Health

................................ ................................ ................................ ............ 97

3.7 Cotton and Soybean Production as Related to the Affected Environment

.............. 98

4 POTENTIAL ENVIRONMEN TAL CONSEQUENCES

................................ ................... 100

4.1 No Action Alternative

................................ ................................ ........................... 100

4.1.1 Land Use and Acreage

................................ ................................ ........................... 100

4.1.2 Socioeconomics

................................ ................................ ................................ ..... 103

4.1.3 Agronomic Practices in Cotton and Soybean Production

................................ ...... 109

4.1.4 Health and Safety for Livestock and Humans

................................ ....................... 117

4.1.5 Animal Communities

................................ ................................ ............................. 119

4.1.6 Plant Communities

................................ ................................ ................................ . 120

4.1. 7 Soil Microorganisms

................................ ................................ .............................. 122

xiii

## Table of Contents

4.1.8 Water

................................ ................................ ................................ ...................... 123

4.1.9 Air Quality

................................ ................................ ................................ ............. 124

4.1.10 Climate Change

................................ ................................ ................................ ...... 124

4.2 Pr eferred Alternative

................................ ................................ ............................. 124

4.2.1 Land Use

................................ ................................ ................................ ................ 125

4.2.2 Socioeconomics

................................ ................................ ................................ ..... 125

4.2.3 Agronomic Practices in Cotton and Soybean Production

................................ ...... 126

4.2.4 Health and Safety for Livestock and Humans

................................ ....................... 128

4.2.5 Biological Resources

................................ ................................ ............................. 130

4.2.6 Physical Environment

................................ ................................ ............................ 132

4.3 Potential Environmental Consequences

- Alternative 3

................................ ........ 133

4.4 Potential Environmental Consequences

- Alternative 4

................................ ........ 133

5 CUMULATIVE IMPACTS

................................ ................................ ................................ . 135

5.1 Cumulative Impacts Methodology

................................ ................................ ........ 136

5.2 Geographic Boundaries for the Analysis of Cumulative Effects

.......................... 136

5.3 Proposed New Dic amba Uses and EPA Risk Assessments

................................ .. 136

5.4 No Action Alternative. Current Management Practices Considered in the Analysis of Cumulative Impacts

................................ ................................ .......................... 138

5.5 Assumptions

................................ ................................ ................................ .......... 141

5.6 Preferred Alternative: Cumulative Impact

................................ ........................... 142

5.6.1 Land Use and Acreage

................................ ................................ ........................... 143

5.6.2 Agronomic Practices

................................ ................................ .............................. 143

5.6.3 Socioeconomics

................................ ................................ ................................ ..... 156

5.6.4 Health and Safety for Livestock and Humans

................................ ....................... 171

xiv

## Table of Contents

5.6.5 Biological Resources

................................ ................................ ............................. 172

5.6.6 Physical Environment

................................ ................................ ............................ 193

5.7 Cumulative Impacts

- Alternative 3

................................ ................................ ....... 194

5.7.1 Agronomic Practices

................................ ................................ .............................. 194

5.7.2 Health and Safety Aspects for Livestock and Humans

................................ .......... 195

5.7.3 Biological Resources

................................ ................................ ............................. 195

5.7.4 Physical Environment

................................ ................................ ............................ 195

5.8 Cumulative Impacts

- Alternative 4

................................ ................................ ....... 196

5.8.1 Agronomic Practices

................................ ................................ .............................. 196

5.8.2 Health and Safety Aspects for Livestock and Humans

................................ .......... 196

5.8.3 Biological Resources

................................ ................................ ............................. 196

5.8.4 Physical Environment

................................ ................................ ............................ 197

6 OTHER IMPACTS AND MI TIGATION MEASURES

................................ ..................... 198

6.1 Unavoidable Impacts

................................ ................................ ............................. 198

6.2 Short Term Versus Long Term Effects

................................ ................................ . 198

6.3 Irreversible Resource Commitments

................................ ................................ ..... 198

6.4 Mitigation Measures

................................ ................................ .............................. 199

7 TH REATENED AND ENDANGE RED SPECIES

................................ ............................ 200

7.1 Requirements for Federal Agencies

................................ ................................ ...... 200

7.2 Potential Effects of MON 88701 Cotton and MON 87708 Soybean on TES

....... 201

7.2.1 Potential Effects of MON 88701 Cotton on TES Plant Species

............................ 202

7.2.2 Potential Effects of MON 88701 Cotton on TES Animal Species

........................ 205

7.2.3 Summary of Potential Effects of MON 88701 Cotton on TES Species

................ 208

7.2.4 Potential Effects of MON 87708 Soybean on TES Plant Species

......................... 208

xv

## Table of Contents

7.2.5 Potential Effects of MON 87708 Soybean on TES Animal Species

..................... 210

7.2.6 Summary of Potential Effects of MON 87708 Soybean on TES

........................... 211

8 CONSIDERATION OF EXECUTIVE ORDERS, ST ANDARDS, AND TREATIE S RELATING TO ENVIRONM ENTAL IMPACTS

................................ ...................... 213

8.1 Executive Orders with Domestic Implications

................................ ...................... 213

8.2 International Implications

................................ ................................ ...................... 216

8.3 Compliance with Clean Water Act and Clean Air Act

................................ .......... 218

8.4 Impacts on Unique Characteristics of Geographic Areas

................................ ...... 218

8.5 National Historic Preservation Act (NHPA) of 1966 as Amended

....................... 219

9 LIST OF PREPARERS

................................ ................................ ................................ ........ 220

10 DISTRIBUTION LIST FO R THIS F EIS

................................ ................................ ............ 225

11 BIBLIOGRAPHY

................................ ................................ ................................ ................ 227

12 INDEX 276

xvi

## List **of Figures**
Figure 1. Upland Cotton 2012 Yield per Harvested Acre by County for Selected States.

........... 27

Figure 2. Soybeans 2012 Yield per Harvested Acre by County for Selected States.

................... 29

Figure 3. Major Soybean and Cotton Cultivation Regions in the United States.

......................... 30

Figure 4. Ecoregions of the Conterminous United States.

................................ ............................ 31

Figure 5. U.S. Croplands with High Erosion Rates.

................................ ................................ ..... 40

Figure 6. Examples of Cotton Irrigation Systems: A=furrow, B=drip method, C=low energy precision application.

................................ ................................ ................................ .................... 41

Figure 7. Irrigated Cotton Acreage in the United States in 2007.

................................ ................. 42

Figure 8. Irrigated Soybean Acreage in the United States in 2007.

................................ ............. 43

Figure 9. Cropping Patterns for Soybeans and Cotton in the United States.

................................ 75

Figure 10. States of the United States Reported to Have Populations of Dicamba

- , 2,4

- D

- , and Glufosinate

- Resistant Weeds.

................................ ................................ ................................ ....... 82

Figure 11. Cotton Water Use and Average Water Use Efficiency Compared to Other Crops, 2003/2004

. ................................ ................................ ................................ ................................ .... 84

Figure 12. A Recent Compilation of Drought Affected Areas in the United States.

.................... 85

Figure 13. Acres of Upland and Pima Cotton Planted and Harvested from 1993 to 2013.

........ 101

Figure 14. Acres of Soybeans Planted and Harvested from 1993 to 2013.

................................ 102

Figure 15. Domestic Mill Use and Exports of U.S. Upland Cotton with Projections Through 2022.

................................ ................................ ................................ ................................ ............ 104

Figure 16. Projections of U.S. S oybean Domestic Use and Exports to 2023.

............................ 105

Figure 17. Projections of Global Cotton Exports to 2023.

................................ ......................... 106

Figure 18. Projections of Global Cotton Imports to 2023.

................................ ......................... 107

Figure 19. Projected U.S. Global Exports of Soybeans, Soybean Meal, and Soybean Oil.

....... 107

Figu re 20. Projections of Global Soybean Exports to 2023.

................................ ....................... 108

Figure 21. Projections of Global Soybean Imports to 2023.

................................ ....................... 108

xviixviii

## List **of Tables**
Table 1. Summary of Issues and of Potential Impacts of the Alternatives.

................................ .. 17

Table 2. Location of Major Cotton and Soybean Production Areas.

................................ ............ 32

Table 3. Dominant and Major Sec ondary Soil Types by Region.

................................ ................ 38

Table 4. Total Farm Diesel Fuel Consumption by Tillage Method.

................................ ............. 48

Table 5. Comparison of NLCD 2006 Land Cover Groups with Classes in This Document.

....... 52

Table 6. Land Cover Composition by Region.

................................ ................................ ............. 54

Table 7. Major Cultivated Crops by Region in 2012 1

. ................................ ................................ . 57

Table 8. Ma jor Arthropod Pests of Soybean.

................................ ................................ ................ 63

Table 9. Major Arthropod Pests of Cotton.

................................ ................................ ................... 65

Table 10. Major Beneficial Arthropods in Soybean and Cotton

................................ .................. 67

Table 11. Commonly Used Insecticides for Cotton Pests.

................................ ............................ 78

Table 12. Summary of Trends in U.S. Cotton and Soybean Production, Resource Use and Impact from 1980

- 2011.

................................ ................................ ................................ ........... 99

Table 13. Tillage Practices by Crop, 2007.

................................ ................................ ................. 110

Table 14. Comparison of Water Needs and Drought Sensitivity for Some Globally Important Crops.

................................ ................................ ................................ ................................ .......... 123

Table 15. Status of Import Approvals of MON 88701 Cotton in Key U.S. Cotton Export Markets.

................................ ................................ ................................ ...................... 126

Table 16. Status of Import Approvals of MON 87708 Soybean in Key U.S. Soybean Export Markets.

................................ ................................ ................................ ...................... 126

Table 17. Summary of Dicamba Use on U.S. Agricultural Crops.

................................ ............. 139

Table 18. Acres and Percentages of Cotton Acres Treated with Non

- Glyphosate Herbicides.

.. 149

Table 19. Rotational Practices Following Soybean Production in the United States.

................ 154

Table 20. R otational Practices Following Cotton Production in the United States.

................... 155

xixTable 21. Percent of Regional Cropland Devoted to Crops on which Dicamba is Used in Each EcoRegion.

................................ ................................ ................................ ................. 158

Table 22. Post

- emergence Broadleaf Herbicides Commonly Used in Pastures and Rangeland. 160

Table 23. Changes in Dicamba Application to Crops 2006

- 2012.

................................ ............. 161

Table 24. Post

- emergence Broadlea f Herbicides Currently Approved for Use in Wheat, Barley, Oats, and Rye.

................................ ................................ ................................ ............ 162

Table 25. Herbicides Available for Use on Fallow and for Burndown.

................................ ..... 165

Table 26. Post

- emergence Broadleaf Herbicides Currently Available for Use on Sorghum.

.... 167

Table 27. Known Weed Resistance in the Southern United States. 1

................................ .......... 179

Table 28. Known Weed Resistan ce in the Midwestern United States.

................................ ....... 180

Table 29. Auxin

- Resistant Weeds.

................................ ................................ .............................. 185

Table 30. Novel Proteins Associated with MON 87708 Soybean and MON 88701 Cotton.

..... 202

xx

## List **of Appendices** 
Appendix 1. USDA Notifications and States Appr oved for Environmental Releases of MON 88701 Dicamba

- and Glufosinate

- R esistant Cotton and MON 87708 Dicamba

R esistant Soybean

Appendix 2. Summary of Public Comments

Appendix 3. Weed Management and Herbicide Use

Appendix 4. Herbicide Use Trends and Predicted Dicamba Use on Dicamba

- Resistant Soybean and Cotton

Appendix 5. Common Weeds in Cotton and Soybean

Appendix 6. Herbicide Resistance

Appendix 7. Off

- Target Pesticide Movement

Appendix 8. EPA Assessment of Herbicides Used on MON 87708 Soybean and MON 88701 Cotton

Appendix 9. Monsanto Tillage Report

Appendix 10. EPA Resistance Management Requirements for Registration of Dow Agrosciences Enlist Duo TM

Appendix 11. Response to Comments on the DEIS

xxi

## A **cronyms and A**  **bbreviations**

§ section 2,4

- D 2,4

- dichlo rophenoxyacetic acid

ae acid equivalent a.i. active ingredient ALS acetolactate synthase AMS Agricultural Marketing Service (USDA) APHIS Animal and Plant Health Inspection Service (USDA) AQI Air Quality Index ARMS Agricultural Resource Management Survey ARS Agricultural Research Service (USDA) BMPs best management practices BNF biotechnology notification file BRS Biotechnology Regulatory Services (USDA) Bt Bacillus thuringiensis CBD Convention on Biological Diversity CEC Canada

- Mexic o

- U.S. Commission for Environmental Cooperation CFR Code of Federal Regulations DAS Dow AgroSciences DCSA 3,6

- dichlorosalicylic acid DEIS Draft Environmental Impact Statement DGA diglycolamine DMA dimethylamine DMO dicamba mono

- oxygenase DNA deoxyribonucleic acid EA environmental assessment EFED Environmental Fate and Effects Division (EPA) EIS environmental impact statement EPA U.S. Environmental Protection Agency EPSPS 5

- enolpyruvylshikimate

- 3

- phosphate synthase ER environmental report prod uced by the petitioner for nonregulated status ERS Economic Research Service (USDA) ESA Endangered Species Act EO Executive Order FDA U.S. Food and Drug Administration FFDCA Federal Food, Drug, and Cosmetic Act F IFRA Federal Insecticide, Fungicide, and Rodenticide Act fl oz/A fluid ounces per acre FQPA Food Quality Protection Act FSANZ Food Standards Australia New Zealan d GE genetically engineered GHG greenhouse gases GR glyphosate resistant

xxiiHED Health Effects Division (EPA) HPPD 4

- hydroxyphenylpyruvate dioxygenase HR herbicide resistant HRAC Herbicide Resistance Action Committee IPCC Intergovernmental Panel on Climate Change IPM Integrated Pest Management IPPC International Plant Protection Convention IWM integrated weed management MGI mesotrione, glufosinate, isoxaflutole MOA mode of action MOU memorandum of understanding MCPA (4

- chlo ro

- 2

- methylphenoxy) acetic acid/ 2

- Methyl

- 4

- chlorophenoxyacetic acid NASS National Agricultural Statistics Service (USDA) NEPA National Environmental Policy Act NHPA National Historic Preservation Act NLCD National Land Cover Dataset NO 2 nitrogen dioxide NOI Notice of Intent NOP National Organic Program NPS nonpoint source NRC National Research Council NRCS Natural Resources Conservation Service NTSR non

- target site

- specific resistanc e OECD Organi z ation for Economic Co

- operation and Development OPP Office of Pesticide Programs (EPA) PAT phosphinothricin acetyltransferase PM particulate matter PM 2.5 particulate matter with aerodynamic diameter of 2.5 micrometer or less PM 10 particulate matter with aerodynamic diameter of 10 micrometer or less POST postemergence in

- crop use PPA Plant Protection Act PPE personal protective equipment
p pm parts per million PPO protoporphyrinogen oxidase PPRA pla nt pest risk assessment PRA pest risk analysis PRE pre

- plant/pre

- emergence application to the crop PSII Photosystem II SOA site of action SOM soil organic matter TES t hreatened and e ndangered s pecies Tg CO 2 Eq teragrams of CO 2 Equivalent USDA U.S. Department of Agriculture

xxiiiUSFWS United States Fish and Wildlife Service USGS United States Geological Survey WSSA Weed Science Society of America

xxiv

### 1 PURPOSE AND NEED

This document is intended to ensure compliance with the National Environmental Policy Act (NEPA ). NEPA requires agencies to prepare an environmental impact statement (EIS) to be included in “every recommendation or report on pro posals for legislation and other major Federal actions significantly affecting the quality of the human environment” ( 42 U.S.C. §4332(2)(C) )

.
The United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) is currentl y engaged in decisionmaking relevant to its statutory authority to regulate two genetically engineered (GE) varieties as potential plant pest s . The Agency has determined that there are possible environmental impacts associated with what ever regulatory decision it renders

. Therefore, this document has been prepared as part of this APHIS decisionmaking process.

1.1 Introduction

Summarized as “Protecting American Agriculture,” the mission of USDA APHIS 3 is: “To protect the health and value of American agriculture and natural resources.” To achieve its mission, APHIS regulates plant and animal health. It integrates these regulatory functions to protect and promote United States domestic agricultural produ ction, commodities, and trade in agricultural products in a manner that prevents or minimizes impacts on the environment.

To implement its plant protection mission, the Agency establishes policies and measures to prevent the in troduction of plant pest s into the U nited S tates

. It also promotes management of those plants, animals, and microorganisms that currently occur within the U.S. and cause economic losses to U.S. agriculture, including commercial and non

- commercial production of crops and ornamental plants. Its mission enc ompasses all practices and technologies that have the potential to impact plant pest risks, either by increasing or reducing them.

One practice overseen by the APHIS plant protection mission is the use of genetic engineering to modify plant agronomic prope rties

. The Agency has regulatory authority to ensure that applications of genetic engineering technology are unlikely to pose a plant pest risk

Principles of biochemistry and molecular biology underlie the current understanding of gene tic inheritance. The mechanisms involved provide the theoretical framework for modern biotechnology. Genetic engineering is one application of biotechnology. It enables the precise manipulation ( insertion or deletion) of one or more selected genetic traits (genes) into the genome of an organism without sole dependence on the secual compatibility of traditional breeding ( cross

- breeding principles of classical Mendelian genetics of inheritance ) . As a result, modern biotechnology makes possible the transfer of highly specific, individual, beneficial

3 F or more details about the APHIS mission, visit http://www.aphis.usda.gov/abo ut_aphis/

1genetic traits between unrelated species. As part of its statutory and regulatory authority to regulate plant pest s, APHIS must examine and determine that a certain GE (genetically engineered) or ganism or product, which is a plant pests or which there is reason to believe is a plant pest, is unlikely to pose a greater plant pest risk than the unmodified organism from which it was derived

.
The APHIS regulatory authority (see Section 1.2 for a gene ral summary) over GE organisms is limited to those with the potential to be plant pest s. The Agency performs extensive, science

based analyses to evaluate the plant pest potential of each organism regulated for which a petition for nonr egulated status has been submitted . Results are documented in a p lant p est r isk

a ssessment (PPRA ). If the conclusion of the PPRA is that a GE organism is unlikely to pose a plant pest risk , the Agency must determine that it does not regulate that organism as a plant pest.

Regardless of its decision (either not to regulate or continue regulating) for a particular article (i.e., organism) that has not been released previously into the environ ment, the Agency also assesses whether or not its decision is likely to cause an environmental impact(s), and if so, examines the environmental impacts of its determination to comply with regulations codified under NEPA . The results of the examination APHIS has performed, relevant to two new GE organisms it currently regulates, are the subject of this document.

1.2 APHIS Regulatory Authority

The Plant Protection Act of 2000 (PPA), as amended ( 7 U.S.C. §§ 7701

– 7772 ) , provides the legal author ization for the APHIS plant protection mission. It authorizes the Agency to regulate the introduction of potential plant pest s into the territorial boundaries of the U.S., and their interstate movement within U.S. boundaries by establis hing quarantine, eradication and control programs. Implementing rules, regulations and guidelines for this enabling legislation (PPA) are codified in Title 7 of the U.S. Code of Federal Regulations (CFR). Rules that implement this authority specific to GE organisms have been published in 7 CFR part 340.

1.3 Requirement for This Document

When APHIS receives a petition for nonregulated status of an article currently regulated under its PPA authority codified in 7 CFR part 340

, the Agency is required to make a dec ision. As a Federal agency, APHIS must also comply with applicable U.S. environmental laws and regulations because a decision on a petition for nonregulated status , whether positive or negative, is a final Agency action that might cause environmental impac t(s).

This document addresses both of these requirements relevant to decisionmaking for two petitions submitted by Monsanto Company, St. Louis, Missouri (henceforth referred to as Monsanto) : APHIS Petition 10

- 188

- 01p for MON 87708 soybean ( Monsanto, 2012a ) and APHIS Petition 12

- 185

- 01p for MON 88701 cotton ( Monsanto, 2012b ) . Each petition seeks a determination of

2nonregulated status respectively for two new GE cultivars: a soybean and a cotton variety
eng ineered for resistance 4 to certain herbicides. Monsanto has presented data in these petitions to support its claims that each variety does not present a plant pest risk, so should not be regulated by APHIS un der the PPA and 7 CFR part 3 40.

Both varieties described here are currently regulated under 7 CFR part 340. Interstate movement and field trials of each (MON 87708 soybean and MON 88701 cotton) were conducted under permits issued or notifications acknowledged by APHIS between 2005 an d 2012. The field trials were conducted within selected growing areas in the U.S. (see Appendix 1 for a list of notifications and states approved for environmental releases for each of the petitions). Data from field trials of each variety are reported in the petitions ( Monsanto, 2012a ; 2012b ) and analyzed in separate PPRAs prepared by APHIS ( USDA

- APHIS, 2014d ; 2014e )

. If APHIS makes a determination of nonregulated status for each of these GE varieties, they will cease to be subject to the PPA and regulations in 7 CFR part 340. If they are no longer regulated,

non

- regulated status will extend to crosses between these varieties and conventional (non

- GE) cultivars, and other biotechnology

- derived varieties classified previously by APHIS as not subject to regulation as plant pest s under the PPA and 7 CFR part 340. Those not subject to regulation are those for which a petition for nonregulated status was submitted, and which were classified as nonregulated, and those for w hich a letter of inquiry was submitted and over which APHIS decided the agency had no jurisdiction.

1.4 Purpose of These Products

Monsanto has developed herbicide

- resistant (HR) MON 87708 soybean that is tolerant to dicamba herbicide and MON 88701 cotton that is tolerant to dicamba and glufosinate

. Dicamba provides effective control of more than 95 annual and biennial weed species, and suppression of over 100 perennial broadleaf and woody plant species. Dicamba is efficacious on broadleaf weeds that are difficult to control with glyphosate (e.g., com mon lambsquarters, hemp sesbania, morning glory species, nightshade, Pennsylvania smartweed, prickly sida, velvetleaf, waterhemp and wild buckwheat). Hard

- to

- control weeds generally require a higher treatment rate and/or more frequent applications at a sma ller growth stage in order to consistently achieve commercially acceptable control. See the Roundup WeatherMax ® label ( U.S. EPA Reg. No. 524

- 537 ) for a listing of these weeds.

4 “Resistance” is defined by the Herbicide Resistance Action Committee (HRAC) as the inherited ability of a plant population to survive and reproduce following repeated exposure to a dose of herbicide normally lethal to the wild type ( Herbicide

- Resistance

- Action

- Committee, 2013 ) Resistance may be induced by genetic engineering or selection of variants produced by tissue culture or mutagenesis ( Herbicide

- Resistance

- Action

- Committee, 2013 ) HRAC applies a different meaning to the term “tolerance,” defining it as the inherent ability of a plant to survive and reproduce after herbicide
treatm ent. Survival of a tolerant plant implies that there was no selection or genetic manipulation to make it tolerant; it is naturally tolerant ( Herbicide

- Resistance

- Action

- Committee, 2 013 )

. These terms are sometimes used interchangeably. For this document, the term “herbicide resistance” has been used consistent with that of HRAC. It can be construed as synonymous with the term “herbicide tolerance” as used in the petitioner’s docum ents. HRAC (2013) . G uideline to the management of herbicide resistance." h ttp://www.hracglobal.com/Education/ManagementofHerbicideResistance.aspx

3Dicamba also provides effective control of HR weeds, including GR weeds such as mares tail, common ragweed, giant ragweed, palmer pigweed, and waterhemp. HR weeds are those listed on the International Survey of Resistant Weeds website ( www.weedscience.org ).

MON 87708 soybean and MON 88701 cotton wo uld provide growers with alternatives to currently available GE HR soybean and cotton varieties ( Monsanto, 2012a ; 2012b )

. Most GE HR crops in the U nited S tates have historically included only a glyphosate

- resistant (GR) trait for weed control. This has limited the diversity of herbicides used for weed management, and resulted in intense reliance on glyphosate. This has been accompanied by a corresponding increas e in GR weeds that commonly occur in soybean, cotton, and other crops ( USDA

APHIS, 2014d ; 2014e ) . Each of these varieties (MON 87708 soybean and MON 88701 cotton ) will increase weed

- management options available to g rowers. These additional options for weed control and flexibility will provide more diverse strategies for growers to control HR weeds. More details about these new varieties follow.

1.4.1 MON 87708 Soybean

APHIS Petition 10

- 188

- 01p is for a GE soybean ( Glycine max ) variety designated as MON 87708 soybean. It is engineered for increased resistance to the broadleaf herbicide dicamba (3,6

- dichloro

- 2

- methoxybenzoic acid). MON 87708 soybean contains a gene from Stenotrophomonas maltophilia (an aerobic gram

- negative b acillus that is found in soil, water and plants) that
expresses a mono

- oxygenase enzyme that rapidly demethylates dicamba rendering it inactive, thereby conferring resistance to dicamba. Th is dicamba mono

- oxygenase ( DMO ) protein rapidly demethylates dicamba to the herbicidally inactive metabolite 3,6

- dichlorosalicylic acid (DCSA), a known soybean, soil, and livestock metabolite of dicamba.

MON 87708 soybean offers growers an expanded use of dicamba in soybean production from the current preplant and preharvest labeled uses. MON 87708 dicamba

- resistant soybean will allow growers to make pre

- emergence applications up to crop emergence. Postemergence applications through the early reproductive (R1/R2) growth stages (R1/R2; b eginning to full flowering) will also be allowed.

Monsanto has request ed a registration from the EPA for the expanded use pattern of dicamba described here for MON 8 7 70 8 soybean , an establishment of new tolerances for dicamba in soybean forage and hay and the inclusion of DCSA in the residue definitions for these ( Monsanto, 201 2a )

. M odification of the current soybean seed 10 ppm tolerance is not being requested.

As indicated in Section 1.3, i f MON 87708 soybean is no longer regulated, non

- regulated status will extend to crosses between MON 87708 soybean and conventional (non

- GE) soybean cultivars, and those GE soybean varieties no longer subject to regulation as plant pest s under the PPA and 7 CF R part 340. Monsanto has indicated it intend s to cross MON 87708 soybean with MON 89788 (Roundup Ready 2 Yield soybean) utilizing traditional breeding techniques

, producing a soybean variety with resistance to both dicamba and glyphosate ( Monsanto, 2012a )

.

41.4.2 MON 88701 Cotton

APHIS Petition 12

- 185

- 01p is for a GE cotton ( Gossypium hirsutum ) variety designated as event MON 88701 cotton that is engineered to express resistance to the herbicides dicamba and glufosinate

. MON 88701 provides a wider dicamba window of application beyond the current preplant cotton uses and glufosinate application rates and timings that are equivalent to current commercial glufosinate

- tolerant cotton. The combined effects of these two traits enable MON 88701 cotton to outcompete weed species, which increases productivity of cotton fiber.

MON 88701 cotton contains a demethylase gene from Stenotrophomonas maltophilia that expresses a dicamba mono

- oxygenase (DMO) protein to confer resistance to dicamba. The DMO protein rapidly demethylates dicamba to the herbicidally inactive metabolite DCSA. DCSA has previously been identified as a metabolite of dicamba in cotton, soybean, livestock, and soil ( Reeves and Weihrauch, 1979 ) . DCSA, in addition to dicamba, is included in the current 10 ppm pesticide residue tolerance for soybean seed that supports the existing uses of dicamba on commercial soybean (40 CFR § 180.227). Even with th e expanded use of dicamba on MON 87708, compared to commercial soybean uses, the rapid metabolism of dicamba results in residues in dicamba

- treated MON 87708 cotton seed, including the DCSA metabolite, that are well below the established 10 ppm tolerance, and therefore no modification to the existing soybean seed tolerance is needed. Consequently, Monsanto has requested of EPA only approval for the expanded use pattern of dicamba on MON 87708 cotton

.
MON 88701 cotton will extend the application window beyon d the current EPA preplant cotton uses of dicamba

. If the EPA approves the new uses of dicamba on MON 88701 cotton ( Monsanto, 2014b ) , in

- crop applications of dicamba would be allowed from preemergence to seven days preharvest

.

Monsanto has r equested a re gistration from the EPA for the expanded uses of dicamba described here for MON 88701 cotton , an increase in the dicamba residue tolerance for cottonseed, the establishment of a tolerance for cotton gin by

- products, and the inclusion of DCSA in the residue definitions for both cottonseed and gin by

- products. No other revisions to the dicamba pesticide residue tolerances are necessary, including those for animal products such as meat, eggs, and milk ( Monsanto, 2012b )

.
MON 88701 cotton also contains a bialaphos resistance (bar) gene from Streptomyces hygroscopicus that expresses the phosphinothricin N

- acetyltransferase (PAT) protein to confer resistan ce to glufosinate. The PAT (bar 1 ) protein acetylates the free amino group of glufosinate to produce non

- herbicidal N

- acetyl glufosinate. G lufosinate application rates and timings on MON 88701 cotton would be equivalent to the existing uses approved for glufosinate

- resist ant cotton. G lufosinate applications for broad spectrum weed control would continue to be allowed from emergence through early bloom growth stage. There fore, no changes in the existing glufosinate label will be requested by Monsanto. Monsanto is not seek ing any changes in glufosinate residue tolerances.

5As indicated in Section 1.3, if MON 88701 cotton is no longer regulated, non

- regulated status will ext end to crosses between MON 88701 cotton and conventional (non

- GE) cotton cultivars, and those GE cotton varieties no longer subject to regulation as plant pest s under the PPA and 7 CFR part 340. Monsanto has indicated plans to stack MON 88701 cotton wit h Roundup Ready Flex Cotton and Bollgard II (MON 88913 and MON 15985) ( Monsanto, 2013a ) . Roundup Ready Flex Cotton (MON 88913) is GE to exhibit resistance to glyphosate. Bollgard II (MON 15985) contains the Cry1Ac and Cry2Ab insecticidal proteins providing protection from feeding by a range of Lepi dopteran species including : tobacco budworm (Heliothis virescens), pink bollworm (Pectinophora gossypiella), cotton bollworm (Helicoverpa zea), cabbage looper (Trichoplusia ni), saltmarsh caterpillar (Estigmene acrea), cotton leaf perforator (Bucculatrix t hurbeiella), soybean looper (Pseudoplusia includens), beet armyworm (Spodoptera exigua), fall armyworm (Spodoptera frugiperda), yellowstriped armyworm (Spodoptera ornithogolli) and European corn borer (Ostrinia nubilalis) ( Convention on Biological Diversity, 2014 )

.
1.5 Coordinated Regulatory Framework for Genetically

- Engineered Organisms

T he U.S. government has regulated GE organisms since 1986 under a Federal policy statement published in the Federal Register ( 51 FR 23302 ; 57 FR 22984 ) entitled “The Coordinated Framework for the Regulation of Biotechnology” (henceforth referred to here as the Coordinated Framework). The Coordinated Framework, published by the Office of Science and Technology Policy, describes the comprehensive Federal regulatory policy for ensuring the safety of biotechnology research and products. It also explains how Federal agencies will use existing Federal statutes to ensure public health and environmental safety, while maintaining regulatory flexibility to avoid impeding the growth of the biotechnology industry.

Three central guiding principles form the basis for the Coordinated Framework. Agencies:

1) should define those transgenic organisms subject to review to the extent permitted by their respective statut ory authorities;

2) are required to focus on the characteristics and risks of a biotechnology product, not the process by which it was created; and

3) are intended to exercise oversight of GE organisms when there is evidence of “unreasonable” risk.

The Coordinat ed Framework explains the regulatory roles and authorities for the three major agencies involved in regulating GE organisms: USDA APHIS, the EPA, and the U.S. Food and Drug Administration (FDA). A summary of each agency’s role follows.

1.5.1 USDA

- APHIS

As noted in Section 1.2, the PPA authorizes APHIS to regulate, manage and control plant pest s. The PPA includes regulatory authority over the introduction (i.e., importation, interstate movement, or release into the environment) of certain GE or ganisms and products. A GE

6organism is considered a regulated article if the donor organism, recipient organism, vector, or vector agent used in engineering the organism belongs to one of the taxa listed in the regulation ( 7 CFR part 340.2 ) and is also considered a plant pest. A GE organism is also regulated under 7 CFR part 340, when APHIS has reason to believe that the GE organism may be a plant pest, or APHIS does not have sufficient information to determine if the GE organism is unlikely to pose a plant pest risk. A GE organism is no longer subject to the plant pest provisions of the PPA or to the regulatory requirements of 7 CFR part 340, when APHIS determines that it is unlikely to pose a plant pest risk.

An individual may petition the Agency for a determination that a particular regulated article is unlikely to pose a plant pest risk, and should not be regulated under the plant pest provisions of the PPA or the regulations at 7 CFR part 340. Under §340.6(c)(4), the p etitioner must provide information related to plant pest risk that the Agency can use to determine whether or not a regulated article is a plant pest risk. A GE organism or other regulated article is subject to the regulatory requirements of 7 CFR part 340 of the PPA until APHIS determines that it is unlikely to be a plant pest risk.

1.5.2 Environmental Protection Agency

The EPA is authorized under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA ) ( 7 U.S.C. 136 et seq. ) to regulate the sale, distribution, and use of pesticides. Its authority includes herbicides and those that are expressed by an organism modified using techniques of modern biotechn ology. The latter are classified by the EPA as plant

- incorporated protectants. The EPA also regulates certain biological control organisms under the Toxic Substances Control Act ( 15 U.S.C. 53 et seq. ) . Before planting a crop containing plant

- incorporated protectants , an individual or company must seek an experim ental use permit from EPA. Commercial production of crops containing plant

- incorporated protectants for purposes of seed increase and sale requires a FIFRA Section 3 registration with the EPA.

Under FIFRA ( 7 U.S.C. 136 et seq. )

, the EPA requires registration of all pesticide products for all specific uses prior to distribution for sale. Before granting a registration, the EPA evaluates the following: toxicity of the ingredients of a pesticide product; the particular site or crop on which it is to be used; the amount, frequency, and timing of its use; storage and disposal requirements. Prior to registration for a new use for a new or previously register ed pesticide

, the EPA must determine through specified test protocols conducted by the applicant that the pesticide does not cause unreasonable adverse effect s on humans, the environment, an d non

target species, when used in accordance with label instructions. The EPA is authorized under FIFRA to make these determinations on the basis of benefits exceeding associated risks of a pesticide. The EPA establishes restrictions that ensure that this test is met by approving specific language used on the pesticide label in accordance with 40 CFR part 158.

Once registered, a pesticide may only be legally used in accordance with directions and restrictions on its label. The purpose of the label is to pr ovide clear directions for effective product performance, while minimizing risks to human health and the environment. The Food Quality Protection Act (FQPA ) of 1996, ( Pub. L. No. 104

– 170 ) amended FIFRA

, requiring the
7EPA to implement periodic registration reviews of pesticides to ensure they are meeting current scientific and regulatory standards of safety and continue to have no unreasonable adver se effect s ( US

- EPA, 2011d )

.
The EPA also sets tolerances (maximum residue levels) or establishes an exemption from the requirement for a tolerance, under the Federal Food, Drug, and Cosmetic Act (FFDCA ). A tolerance is the amount of pesticide residue that can remain on or in food for human consumption or animal feed. Before establishing a pesticide tolerance

, the EPA is required to reach a safety determination based on a finding of reasonable certainty of no harm under the FFDCA, as amended by the FQPA

.

1.5.3 Food and Drug Administration

The FDA enforces pesticide tolerance s set by EPA. The FDA also oversees marke t introduction of GE foods under the authority of the FFDCA ( 21 U.S.C. 301 et seq ) . The FDA published its policy statement concerning oversight for products derived from new plant varieties, including those derived from genetic engineering, on May 29, 1992 ( 57 FR 22984 ) . Under this policy, the FDA implements a voluntary consultation process to ensure that human food and animal feed safety issues or other regulatory issues, such as labeling, are resolved before commercial distribution of food derived from GE products. This voluntary consulta tion process provides a way for developers to receive assistance from the FDA to comply with obligations under Federal food safety laws prior to marketing.

In June 2006, the FDA also published recommendations in “Guidance for Industry: Recommendations for the Early Food Safety Evaluation of New Non

- Pesticidal Proteins Produced by New Plant Varieties Intended for Food Use” ( US

- FDA, 2014 (updated) ) . This establishes voluntary food safety evaluations for ne w non

- pesticidal proteins produced by new plant varieties intended to be used as food, including GE plants. Early food safety evaluations help ensure that potential food safety issues related to a new protein in a new plant variety are addressed early in d evelopment. These evaluations are not intended as a replacement for a biotechnology consultation with the FDA, but the information may be used later in the biotechnology consultation.

1.6 Purpose and Need for this APHIS Action

APHIS is required to respond, con sistent with its PPA authority and regulations at 7 CFR part 340.6

, to two petitions submitted by Monsanto. As noted previously in Section 1.3, each petition is for a different GE HR event : APHIS Petition 10

- 188

- 01p for MON 87708 soybean ( Monsanto, 2012a ) and APHIS Petition 12

- 185

- 01p for MON 88701 cotton ( Monsanto, 2012b )

. In its submissions, the petitioner has provided information consistent with that described in §340.6(c)(4), which APHIS requires to inform it of the full range of biological and chemical properties of GE organisms, so the Agency can assess the plant pest risk(s) of each, and determine if they are unlikely to be a greater plant pest risk than the unmodified organisms from which they were derived. Therefore, APHIS must respond to the petitions from Monsanto that
8are the subject of this document . If the Agency determines that each GE

- regulated article is unlikely to be a plant pest risk, it is no longer subject to the p rovisions of the PPA as implemented by the regulations of 7 CFR part 340.

As noted in Section 1.1, under the provisions of NEPA as amended ( 42 U.S.C. 4321 et seq )

, prior to implementation, Federal agencies must examine the potential impact s of proposed major actions that may significantly affect the quality of the human environment. In accordance with NEPA, regulations of the Council on Environmental Quality (CEQ) for implementing the procedural provisions of NEPA ( 40 CFR parts 1500

- 1508 ) , USDA regulations implement ing NEPA ( 7 CFR part 1 b ) , and the NEPA Implementing Procedures ( 7 CFR pa rt 372 ) of APHIS, the Agency has considered how to properly examine the potential environmental impacts of its decisions for petitions for determination of nonregulated status.

For most petitions for a determination of nonregulated status of GE organism s that APHIS has evaluated previously, it has prepared an e nvironmental a ssessment (EA) to provide the APHIS decisionmaker with a review and analysis that identifies whether there may be any significant environmental impacts. If the Agency makes a finding of no significant impact (FONSI)

, the NEPA process stops and a decision is issued. If significant environmental impacts are identified, the process continues with the preparation of an EIS before a determination is made.

For MON 87708 soybean and MON 88701 cotton, APHIS did not decide, a priori , to prepare an EIS based on the finding of significant environmental impact

. Instead, as noted in the Notice of Intent to Prepare an EIS, the decision was discretionary on the part of APHIS based on public concerns about the potential environmental impacts associated with the increased use of certain herbicides and possible selecti on for and spread of weeds resistant to the herbicide dicamba alone or weeds resistant to dicamba and other herbicides with different modes of action (multiple resistance). Because of the likely socioeconomic impact s that woul d result in the event that dicamba

- resistant weeds would be selected for from the potential increased use of dicamba, APHIS concluded these impacts were at minimum uncertain and perhaps significant in certain areas under certain conditions. Therefore, APHI S decided that, for the Monsanto varieties that are the subject of this analysis an EIS would be prepared to further analyze the potential for selection of dicamba

- resistant weeds and other potential impacts that might occur from making determinations of n onregulated status for these varieties. This EIS limits its analysis of herbicide

use to the potential cumulative impact s that may occur from the selection for herbicide resistant weeds and the changes in ma nagement practices that may result. This EIS provides Agency decisionmakers with a mechanism for examining the potential broad and cumulative impacts on the quality of the human environment that may result from determinations of nonregulated status. APHIS has prepared this EIS to be consistent with NEPA /CEQ regulations and USDA

- APHIS NEPA

- implementing regulations and procedures (7 CFR part 1 b, 7 CFR part 372, 40 CFR parts 1500

- 1508).

1.7 Public Involvement

APHIS seeks public comment on petitions it receives that request a decision of non

- regulatory status for GE organisms. When the Agency decides to prepare an EIS as part of its 9decisionmaking process for a petition, prior to preparation, it also seeks public comments a s part of its advance scoping process. Details about the public involvement process for the petitions that are the subject of this document follow.

1.7.1 Public Comments for Petitions 10

- 188

- 01p and 12

- 185

- 01p

APHIS sought comments for the petiti ons that are the subject of th e EIS in a Federal Register notice dated July 13, 2012 and February 27, 2013 . Comments received for the petitions were influential, though not the sole basis, for the Agency’s decision to prepare this D EIS. As part of its scop ing process to identify issues to address in this EIS, APHIS also published a Notice of Intent (NOI) to prepare th e EIS and sought public input during a comment period (May 10 to July 17, 2013).

Comments were submitted by individuals, acade mic researchers, non

- government organizations, and industry representatives. The majority of comments submitted by non

- government organizations and individuals were opposed to determinations of nonregulated status for the petitions. The majority of comment s submitted by industry and academia supported determinations of nonregulation for MON 87708 soybean and MON 88701 cotton.

Issues most frequently cited in public comments on the petitions included the nature of agronomic inputs associated with these two ne w traits, potential impacts to plants from off

- target herbicide drift, management of HR weeds, human health impacts of exposure to herbicides, and domestic and international economic impacts associated with the development and marketin g of new HR products. A more detailed summary of these comments is provided in Appendix 2.

1.7.2 Public Comment Period for Draft EIS

APHIS issued the draft EIS (DEIS) for the petitions for a determination of nonregulated status for MON 87708 soybean and MON 88701 cotton and sought public comments on the DEIS through publication of a Notice of Availability (NOA) for the DEIS in the Feder al Register on August 11, 2014 (79 FR 46799). The NOA explained how interested agencies, organizations, and individuals could access the DEIS for review and comment. The NOA also explained the process for submitting comments on the DEIS to APHIS. The DEIS was made available for public comment for 45 days from August 11 through September 25, 2014; the comment period was further extended to October 1 0 , 2014. APHIS held a virtual public meeting on the DEIS on September 11, 2014. At the end of the 60

- day commen t period (October 10, 2014), APHIS reviewed and evaluated all of the comments received. APHIS received 4,710 comments on the D EIS docket (APHIS 2013

- 0043)

. Of these, 3,716 supported and 941 opposed the use of MON 87708 soybean and MON 88701 cotton

. There w as substantive information provided in public comments that was considered in the preparation of this final EIS. The Response to Comments that we have prepared addressing the comments received on the DEIS can be found in Appendix 11.

In general, the comme nts received fell into three broad categories. A brief summary follows, accompanied by the APHIS response to each :
101) Many commenters expressed t he concern that natural and biological resources would be adversely impacted by the increased amounts of dicamba t hat would be used on soybean and cotton, if MON 87708 soybean and MON 88701 cotton were no longer regulated by APHIS

.
The A PHIS response is that the direct and indirect impacts of herbicide use are outside the scope of this EIS because the authority to regulate herbicide resides w ith the EPA under FIFRA and does not reside with USDA

- APHIS. The USDA

- APHIS authority comes from the P PA, which limits APHIS authority to the re gulation of plant pest s and noxious weeds. Under APHIS regulations (7 CFR part 340)

, the Agency can only consider plant pest risks when making a determ ination of nonregulated status.

APHIS has no authority to regulate herbicide use or mitigate the impacts that may result from that use. The EPA r egistration process under FIFRA ensures that pesticides will be properly labeled

, and that, if used in accordance with label specifications will meet the EPA’s safety standards of no unreasonable adverse effect on the environment and a reasonable certainty of no harm to humans. More details about the EPA regulatory responsibilities are provided in Section 1. 5 .2. The risk assessment process used by the EPA is explained in Section 5.4.

2) Some commenters emphasized that growers need MON 87708 soybean and MON 88701
cotton to manage GR weeds already present on many U.S. farms.

APHIS considers the impacts of GR weeds in the No Action Alternative ( Section 4.1. 3 ). APHIS also considers possible cumulative impact s if it makes a determination to no longer regulate MON 87708 soybean and MON 88701 cotton, and the EPA makes a de cision to allow the new registered uses of dicamba for these varieties in C hapter 5 of this EIS

. 3) Some commenters expressed concern that increased use of dicamba on MON 87708 soybean and MON 88701 cotton would promote selecti on of dicamba

- resistant weeds.

APHIS notes that it has identified the possible selection of HR weeds resulting from the change in management practices associated with the adoption of MON 87708 soybean and MON 88701
cotton as a potential environmental impac t. This impact is a cumulative impact (see Chapter 5) because it would only result if APHIS approves the petitions to no longer regulate the GE varieties that are the subject of this EIS, and the EPA approves the proposed new use s of dicamba on them. However, APHIS notes that the potential for dicamba resistance already exists, and would continue to exist even if MON 87708 soybean and MON 88701 cotton are not approved because dicamba is currently registered for use on varieties of cotton and soybean already available, and several other major U.S. crops. This potential will be influenced not only by current uses of dicamba, but also the degree to which growers adopt the diversity of available alternative weed co ntrol methods as part of a coordinated system of best management practices

.
If dicamba

- resistant weeds were to develop as a result of dicamba use on MON 87708 soybean and MON 88701 cotton coupled with a failure by growers to adopt best management practices, growers who rely on dicamba for weed control could face increased socioeconomic impact s

. These impacts socioeconomic impacts associated with the increase in dicamba

- resistant weeds

11would not be a direct impact of th e determination of nonregulated status, but from grower decisions, and for these users, may result in potentially more costly and restrictive weed control alternatives.

1.7.3 Issues Considered in This EIS

The list of resource areas considered by APHIS in this d ocument were identified in part from a review of: comments received for the petitions and the NOI; relevant concerns and issues cited in comments submitted by the public and various stakeholders in response to previous petitions and EAs for GE organisms; c oncerns identified in previous unrelated lawsuits. The following list includes the resource areas APHIS identified during this process, which are considered in this EIS:

• Land Use

• Domestic Use of Soybeans and Cotton

• Exports of Soybeans and Cotton

• Food and F eed Safety

• Worker Safety

• Animal and Plant Communities

• Biodiversity

• Soil Quality

• Water Quality

• Air Quality

• Climate Change

12

### 2 ALTERNATIVES

This document analyzes the potential environmental consequences of a determination of nonregulated status of MON 87708 soybean and MON 88701 cotton. In responding to the petitions, APHIS must assess the plant pest risks associated with MON 87708 soybean and MON 88701 cotton

. Based on its PPRAs ( USDA

- APHIS, 2014e ; 2014d )

, APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose plant pest risks. Following the conclusion of the plant pest risk analysis process, APHIS considered possible alternatives and selected those appropriate for further evalu ation in this EIS

.
2.1 Alternative Considered and Selected for Further Evaluation for This EIS

APHIS evaluated four Alternatives in this EIS: 1) No Action Alternative; 2) determination of nonregulated status of MON 87708 soybean and MON 88701 cotton (Preferre d Alternative); 3) determination of nonregulated status only for MON 88701 cotton ; 4) determination of nonregulated status only for MON 87708 soybean . APHIS has assessed the potential for environmental impacts for each Alternative in the Environmental Cons equences chapter of this document

.

2.1.1 Alternative 1: No Action Alternative

- Continuation as Regulated Articles

Under the No Action Alternative, APHIS would deny the two petitions ( Monsanto, 2012a ; 2012b )

. MON 87708 soybean and MON 88701 cotton

, and progeny derived from these even t lines would continue to be regulated articles under the regulations at 7 CFR part 340. APHIS would still require permits or notifications for their introduction, and would continue to implement measures to ensure physical and reproductive confinement. AP HIS could choose this Alternative if it determined that both of these cultivars were plant pest s, or that there were insufficient data for APHIS to completely evaluate the potential plant pest risks associated with the unconfined cultiv ation of them. T his Alternative is not the Preferred Alternative because APHIS evaluated the data and has concluded in its PPRAs that MON 87708 soybean and MON 88701 cotton are unlikely to pose plant pest risk s ( USDA

- APHIS, 2014e ; 2014d )

. Therefore, choosing this Alternative would be inconsistent wit h the scientific evidence before the a gency regarding plant pest risk, the purpose and need stated in the plant pest provisions of the PPA, and the regulations codified in 7 CFR part 340

.

2.1.2 Alternative 2: Determination of Nonregulated Status of MON 87708 S oy bean and MON 88701 Cotton (Preferred Alternative)

Under this Alternative, MON 87708 soybean and MON 88701 cotton and progeny derived from their cultivation would no longer be subject to APHIS biotechnology regulations. APHIS would no longer require permits or notifications for introductions of these varieties because they are unlikely to pose plant pest risks ( USDA

- APHIS, 2014e ; 2014d )

. Therefore, this is the Preferred Alternative because a determination of nonregulated status for both varieties, MON 87708 soybean and MON 88701 cotton

, would be consistent with the scientific evidence before the

13agency regarding plant pest risk

, the purpose and need stated in the plant pest provisions of the PPA, and the regulations codified in 7 CFR part 340

.

2.1.3 Alternative 3: Determination of Nonregulate d Status for MON 88701 C otton , Only

Under this Alternative, only MON 88701 cotton and progeny derived from its cultivation would no longer be subject to regulations. MON 87708 soybean would continue to be regulated as described under Alternative 1. APHIS would no longer require permits or notifications for introductions of MON 88701 cotton and progeny derived from this event because it is unlikely to pose a plant pest ris k ( USDA

- APHIS, 2014e )

. APHIS would choose this Alternative if it determined that MON 87708 soybean was a plant pest itself or if available data were not sufficient to complete an evaluat ion of potential plant pest risks associated with the unconfined cultivation of MON 87708 soybean. However, APHIS has concluded as part of its plant pest risk
assessment process that this variety is unlikely to pose a plant pest ris k. Therefore, such a choice would be inconsistent with the scientific evidence before the agency regarding plant pest risk, the purpose and need of the plant pest provisions of the PPA, and the regulations codified in 7 CFR part 340

.

2.1.4 Alternative 4: Determination of Nonregulated Status for MON 87708 S oybean , Only

Under this Alternative, only MON 87708 soybean, and progeny derived from its cultivation would no longer be subject to regulations. MON 88701 cotton would continue to be regulated as describ ed under Alternative 1. APHIS would no longer require permits or notifications for introductions of MON 87708 soybean and progeny derived from this variety because it is unlikely that it poses a plant pest risk or increase existing ones ( USDA

- APHIS, 2014d )

. APHIS would choose this Alternative if it determined that MON 88701 cotton was a plant pes t or if available data were not sufficient to complete an evaluation of potential plant pest risk from the unconfined cultivation of MON 88701 cotton. However, APHIS has concluded as part of its plant pest risk assessment process th at this variety is unlikely to pose a plant pest risk. Therefore, such a choice would be inconsistent with the scientific evidence before the agency regarding plant pest risk, the purpose and need of the plant pest provisions of the PPA, and the regulation s codified in 7 CFR part 340.

2.2 Alternatives Considered but Not Selected for Further Evaluation

APHIS assembled a list of a lternatives considered for MON 87708 soybean and MON 88701 cotton. The Agency evaluated these a lternatives in accordance with its authority under the plant pest provisions of the PPA and the regulations at 7 CFR part 340. In this evaluation APHIS considered environmental safety, efficacy, and practicality to identify those a lternatives the

a gency would further con sider for MON 87708 soybean and MON 88701 cotton. Based on this evaluation, APHIS rejected several a lternatives. These a lternatives are described briefly below with the specific reasons for rejecting each.

142.2.1 Prohibit Any MON 87708 S oybean and MON 88701 C otto n from Being Released

In response to public comments that stated a preference that no GE organisms enter the marketplace, APHIS considered prohibiting the release of MON 87708 soybean and MON 88701 cotton, including denial of any permits associated with fi eld testing. APHIS determined that this Alternative is not appropriate because APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose a plant pest risk ( USDA

- APHIS, 2014d ; 2014e )

. Therefore, there is no scientific basis for prohibiting the release of these v arieties under the regulations at 7 CFR part 340.

In enacting the PPA, Congress included findings in Section 402(4) that: “decisions affecting imports, exports, and interstate movement of products regulated under this title [i.e., the PPA] shall be based o n sound science ;

... ”

On March 11, 2011, in a Memorandum for the Heads of Executive Departments and Agencies, the White House Emerging Technologies Interagency Policy Coordination Committee established principles consistent with Executive Order 13563 to guide agencies in the de velopment and implementation of policies for oversight of emerging technologies such as genetic engineering that included the following guidance:

“Decisions should be based on the best reasonably obtainable scientific, technical, economic, and other inform ation, within the boundaries of the authorities and mandates of each agency;

... ”

Consistent with this guidance and based on the findings and scientific data evaluated for the PPRAs ( USDA

- APHIS, 2014a ; 2014b ) , APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose a plant pest risk. Therefore, there is no scien tific basis for prohibiting the release of these varieties under the regulations at 7 CFR part 340

.

2.2.2 Approve the Petition(s) in Part

The regulation s at 7 CFR part 340.6(d)(3)(i) state that APHIS may “approve the petition in whole or in part.” However, APHIS has concluded that MON 87708 soybean and MON 88701
cotton are unlikely to pose plant pest risk s ( USDA

- APHIS, 2014e ; 2014d )

, so there is no scien tific basis for prohibiting the r elease of these varieties under the regulations at 7 CFR part 340

.

2.2.3 Production/Geographical Restrictions to Isolate MON 87708 S oybean and MON 88701 C otton from Non

- GE Soybean or Cotton

In response to public concerns of gene movement between GE and non

- GE plants, APHIS considered requiring isolation distance s separating MON 87708 soybean and MON 88701 cotton from non

- GE soybean or cotton production. However, because APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose plant pest risks ( USDA

- APHIS, 2014a ; 2014b ) , an a lternative based on requiring isolation distances would be inconsistent with

15the Agency’s statutory authority under the plant pest provisions of the PPA and regulations in 7 CFR part 340.

APHIS also considered geographically restricting the production of MON 87708 soybean and MON 88701 cotton based on the location of organic production systems of non

- GE soybean and cotton, or production systems for GE

- sensitive markets in response to public concerns regarding possible gene movement between GE and non

- GE plants. However, as presented in the APHIS PPRA ( USDA

- APHIS, 2014a ; 2014b )

, there are no geographic differences associated with any identifiable plant pest risks for MON 87708 soybean and MON 88701 cotton. This Alternative was not analyzed in detail because APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose plant pest risk s in any geographic area. Therefore, there is no scien tific basis for prohibiting the release of these varieties under the regulations at 7 CFR part 340

. Individuals might choose

, on their own

, to geographically isolate their non

- GE soybean or cotton production systems from MON 87708 soybean and MON 88701 cotton, or to use isolation distance s and other management prac tices to minimize gene movement between soybean and
cotton fields. Information to assist growers in making informed management decisions to effectively isolate their crop varieties from other varieties (including MON 87708 soybean and MON 88701 cotton ) is available from the American Organization of Seed Certifying Agencies ( AOSCA, 2010 )

.

2.2.4 Requirement of Testing for MON 87708 S oybean and MON 88701 C otton

During the comment periods for other petitions for nonregulated status, some commenters requested that USDA require and provide testing for GE products in non

- GE production systems. However, because APHIS has concluded that MON 87708 soybean and MON 88701 cotton are unlikely to pose plant pest risk s ( USDA

- APHIS, 2014a ; 2014b )

, testing requirements are inconsistent with the plant pest provisions of the PPA, the regulations at 7 CFR part 340 and the biotechnology regulatory policies of the Coordinated Framework. Therefore, there is no scientific basis for prohibiting or regulating releases of these varieties under the regulations at 7 CFR part 340.

2.3 Comparison of Alternatives

Table 1 includes a summary of the potential environmental consequences associated with selection of one of the Alternatives evaluated in this EIS. The environme ntal consequences assessment is presented in Chapter 4 of this EIS. The cumulative impact s are presented in Chapter 5.

16Table 1 . Summary of Issues and of Potential Impacts of the Alternatives.

At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

Meets Purpose and N eed No Yes No No

Land Use Acreage of s oybean plantings are anticipated to increase somewhat through 2020 ( USDA

- OCE, 2013 )

. Cotton plantings are anticipated to fluctuate as market prices change. Locations of soybean and
cotton production are not expected to change. Acreage of p lantings
gene rally the same as Alternative 1.

The nonregulated varieties might replace other soybean or cotton varieties currently grown in the U.S. Locations of production unchanged. Acreage of p lantings generally the same as Alternative 1.

The nonregulated cotton

var iety might replace other varieties currently grown in the U.S. Locations of production unchanged. Acreage of p lantings generally the same as Alternative 1.

The nonregulated soybean variety might replace other varieties currently grown in the U.S.

Locations of production unchanged.

Economic Aspects The U.S. will continue to be an exporter of soybeans and
cotton

. It is the responsibility of food and feed manufacturers to ensure that the products they market are safe and labeled properly. The percentage of GE varieties in the market is not expected to change. Monsanto has submitted or is planning to submit requests for regulatory approvals in the main expo rt markets for these varieties of soybean and cotton

. These traits and varieties are not substantially different from what is already in

commerce. Their presence in exported commodities will not affect trade dif ferently than that of other currently approved GE traits in commerce. Monsanto has submitted or is planning to submit requests for regulatory approvals in the main export markets for this variety of
cotton.

This trait and variety is not substantially different fro m what is already in

commerce. Its presence in exported commodities will not affect trade differently than that of other currentl y approved GE traits in commerce. Monsanto has submitted or is planning to submit requests for regulatory approvals in the main export markets for this variety of soybe an.
This trait and variety is not substantially different fro m what is already in

commerce. Its presence in exported commodities will not affect trade differently than that of other currently approved GE traits in commerce.

17At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

The percentage of GE varieties in the market is not expected to change. The percentage of GE varieties in the market is not expected to change. The percentage of GE varieties in the market is not expected to change.
Agronomic Practices Weeds resistant to glyphosate and other herbicides will continue to increase. As HR weeds become more prevalent, growers are expected to shift to more costly alter native weed control measures or
ot her herbicide

- resistant crops that are economically viable. Conventional growers are likely to use additional herbicides and/or abandon conservation tillage practices and ret urn to more aggressive conventional tillage systems to maintain yields. Use of dicamba in soybean and dicamba and glufosinate in cotton cropping systems is expected to increase , but dicamba use is contingent on EPA’s decision to approve the new uses of dicamba on these crop varieties More efficient weed control is expected to reduce the need for more aggressive tillage. Conventional growers are likely to continue the use of herbicides and retain or increase conservation tillage practice s , if resistant weeds do not develop over time. Use of dicamba and glufosinate in cotton is expected to increase , but dicamba use is contingent on EPA’s decision to approve the new use of dicamba on this cotton variety.

More efficient weed control i s expected to reduce the need for more aggressive tillage. More efficient weed control is expected to reduce the need for more aggressive tillage. Conventional growers are likely to continue use of herbicides and retain or increase conservation tillage practice s , if resistant weeds do not develop over time. Use of dicamba in soybean is expected to increase , but this is contingent on EPA’s decision to approve the new use of dicamba on this soybean variety.

. Conventional growers are likely to continue use of herbicides and retain or increase conservation tillage practice s , if resistant weeds do not develop over time.

Organic Production Systems Planting of orga nic soybeans and cotton is not likely to change

. Planting of organic soybeans and cotton is not likely to change

. Planting of organic cotton is not likely to change

. Planting of organic soybeans is not likely to change

.

Use of GE C rops: H erbicide and R esistant Planting of GE HR crops is likely to remain at current levels with adoption of GE Planting of GE HR crops is likely to remain at current levels with adoption of GE Planting of GE HR crops is likely to remain at current levels with adoption of GE Planting of GE HR crops is likely to remain at current levels with adoption of GE 18At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

W eed A spects crops high. crops high. crops high. crops high

. Human Health and Safety Soybean and c otton varieties are associated with all the normal risks of agricultural production.

The EPA label use restrictions are designed to protect humans during herbicide use in soybean and
cotton cro pping systems to achieve a standard of a “reasonable certainty of no harm”. These varieties do not present any additional risks to workers.

The revised EPA label use restrictions for soybean and
cotton are designed to achieve the same level of human health and safety as those that currently exists for

non

- GE varieties. This variety does not present any additional risks to workers.

The revised EPA label use restrictions for cotton are designed to achieve the same level of human health and safety as those that currently exists for non

- GE varieties. This variety does not present any additional risks to workers.

The revised EPA label use restrictions for soybean are designed to achieve the same level of human health and safety as those that currently exists for non

- GE varieties.

Biological Diversity Cropping systems generally are not expected to change, so biodiversity in regions where soybean and cotton are produced will not change.

Herbicide us e may decrease weed prevalence or modify the weed s pecies complex in some regions. These changes could modify the species complex of organisms that rely on these weeds as a food source or habitat. Crop biodiversity is not

ex pected to change rela tive to the No Action Alternative substantially

. Use of these varieties will allow for stab le levels of conservation tillage, which will not decrease biodiversity and might increase it. Use of these crops will likely not require increased overall herbicide use , which will not reduce biodiversity and might increase it. Selection pressure for dicamba and glufosinate Crop biodiversit y is not expected to change rela tive to the No Action Alternative substantially

. Use of this cotton variety will allow for stable levels of conse rvation tillage, which will not decrease biodiversity and might increase it. Use of this cotton variety will likely not require increased overall herbicide

use , which will not reduce biodiversity and might increase it. Selection press ure for Crop biodiversity is not expected to change realtive to the No Action Alternative substantially

. Use of this soybean variety will allow for stable levels of conservation tillage, which will not decrease biodiversity and might increase it. Use of this soybean variety will likely not require increased overall herbicide

use , which will not reduce biodiversity and might increase it.

19At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

resistance in weed populations may modify the weed s pecies complex in some regions, which might modify the species complex of organisms that rely on these weeds as a food source or habitat. dicamba and glufosinate resistance in weed populations may modify the weed s pecies complex in some regions, which might modify the species complex of organisms that rely on these weeds as a food source or habitat. Selection pressure for dicamba resistance in weed populations may modify the weed s pecies complex in some regions, which might modify the species complex of organisms that rely on these weeds as a food source or habitat.

Animal Communities Cultivated soybean and
cotton currently provide limited food and habitat for wildlife in regular cropping situations. Expected to be the same as Alternative 1 because toxicological studies and studies of allergenicity of the added traits did not reveal any impacts on animals. Expected to be the same as Alternative 1 because toxicological studies and studies of allergenicity of the added trait did not reveal any impacts on animals. Expected to be the same as Alternative 1 because toxicological studies and studies of allergenicity of the added trait did not reveal any impacts on animals.

Plant Communities / Weed Complexes Currently cultivated s oybean and cotton varieties are not potential plant pest s because they do not compete with native plant species, so do not adversely impact natural plant communities. Selection pressure for HR weed development will continue. These varie ties are not potential plant pest s because they do not compete with native plant species and lack the potential to do so, so will not adversely impact natural plant communities. Selection pressure to develop dicamba and glufosinate resi stance in weed populations will increase, including the potential for development of weeds with multiple resistance to more than one This variety is not a potential plant pest s because it does do not compete wi th native plant species and lacks the potential to do so, so will not adversely impact natural plant communities. Selection pressure to develop dicamba and glufosinate resistance in weed populations will increase, including the potential for development of weeds with multiple resistance to more than one This variety is not a potential plant pest s because it does do not compete with native plant species and lacks the potential to do so, so will not adversely impact natural plant communities. Selection pressure to develop dicamba resistance in weed populations will increase, including the potential for development of weeds with multiple resistance to more than one herbicide.

20At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

herbicide mode of action. herbicide.
Soil Quality Increased tillage to manage herbicide resistant weeds may occur in soybean and
cotton cropping systems and cause decreased soil quality from increased soil erosion. New options to avoid tillage would be accompanied by decreased soil erosion.

These varieties are not
expec ted to change the existing composition of soil microflora in cropping systems. New options to avoid tillage would be accompanied by decreased soil erosion. This variety is not expected to change the existing composition of soil microflora in cropping syste ms. New options to avoid tillage would be accompanied by decreased soil erosion. This variety is not expected to change the existing composition of soil microflora in cropping systems. Water Quality Increased tillage to manage HR weeds may occur in soybean and cotton cropping systems. This could increase evaporative water loss and demand on water resources for irrigation, and cause increased soil erosion accompanied by diminished water quality from sediment ation. These varieties will support continued use of current conservation tillage practice s in the short term. In the long term, development of more HR weeds may be accompanied by increased tillage with negative impacts (as descr ibed in the No Action Alternative). This variety will support continued use of current conservation tillage practice s in the short term. In the long term, development of more HR weeds may be accompanied by increased tillage with negative impacts (as described in the No Action Alternative). This variety will support continued use of current conservation tillage practice s in the short term. In the long term, development of more HR weeds may be accompanied by increased tillage with negative impacts (as described in the No Action Alternative).
Air Quality Increased tillage to manage HR weeds may occur in soybean and cotton cropping systems. T his could reduce air quality from increased air particulates and exhaust from farm equipment.

Increased use of herbicides may occur to manage HR Use of these varieties is expected to stabilize current tillage. This will be accompanied by a reduction in airborne particulates and exhaust emissions, which will increase air quality

. Overall use of herbicides will remain the same or be Use of this variety is expected to stabilize current tillage. This will be

a ccompanied by a reduction in airborne particulates and exhaust emissions, which will increase air quality

. Overall use of herbicides will remain the same or be Use of this variety is expected to stabilize current tillage. This will be accompanied by a reduction in airborne particulates and exhaust emissions, which will inc rease air quality

. Overall use of herbicides will remain the same or be 21At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

weeds. This would increase drift from herbicides that would reduce air quality. reduced by better management of HR weeds. Drift from herbicides will remain the same or be reduced, resulting in no change or improved air quality. reduced by better management of HR weeds. Drift from herbicides will remain the same or be reduced, resulting in no change or improved air quality. reduced by better management of HR weeds. Drift from herbicides will remain the same or be reduced, resulting in no change or improved air quality.
Climate Change Increased tillage to manage HR weeds may occur in soybean and cotton cropping systems. This would Increase the release of GHGs (primarily CO 2 and methane). Use of these varieties is expected to stabilize current conservation tillage. This will be accompanied by a reduction in the release of GHGs (primarily CO 2 and methane). Use of this variety is expected to stabilize current conservation tillage

. This will be accompanied by a reduction in the release of GHGs (primarily CO 2 and metha ne). Use of this variety i s expected to stabilize current conservation tillage. This will be accompanied by a reduction in the release of GHGs (primarily CO 2 and methane).

Other U.S. R egulatory Approvals:

FDA C onsultations and EPA R egistrations Consult ations with the FDA and changes to the EPA registrations would be
unnecessary. Monsanto completed consultations with the FDA for MON 87708 soybean on October 11, 2011 (BNF No. 00125) and for MON 88701 cotton on April 24, 2013 (BNF No. 000135).

The EPA rere gistration decision for dicamba was issued in 2006 ( US

- EPA, 2006a ) . EPA concluded that dicamba and its metabolites were below the Agency’s level of concern for all registered uses of dicamba Monsanto completed its consultation with FDA for MON 88701 cotton on April 24, 2013 (BNF No. 000135).

The EPA reregistration decision for dicamba was issued in 200 6 ( US

- EPA, 2006a )

. The EPA concluded that dicamba and its metabolites we re below the Agency’s level of concern for all registered uses of dicamba including cotton ( US

- EPA, 2009b )

. Monsanto completed its consultation with FDA for MON 87708 soybean on October 11, 2011 (BNF No. 00125).

The EPA reregistration decision for dicamba was issued in 200 6 ( US

- EPA, 2006a )

. The EPA concluded that dicamba and its metabolites were below the Agency’s level of concern for all registered uses of dicamba including soybean

22At tribute/Measure Alternative 1: No Action (Deny Both Petitions) Alternative 2: Preferred Alternative

Determination of Nonregulated Status for

MON 87708 Soybean and MON 88701 Cotton Alternative 3: Determination of Nonregulated Status for MON 88701 Cotton Only Alternative 4: Determination of Nonregulated Status for

MON 87708 S oybean Only

including soybean and
cotton ( US

- EPA, 2009b )

. The EPA registration decision for glufosinate was issued in 200 0 fo r crop use ( US

- EPA, 2008 )

. The EPA is currently evaluating the proposed new uses of dicamba for MON 87708 soybean and MON 88701 cotton

. The EP A registration decision for glufosinate was issued in 200 0 for crop use ( US

- EPA, 2008 )

. The EPA is currently evaluating the proposed new uses of dicamba for M ON 87708 soybean and MON 88701 cotton

. ( US

- EPA, 2009b )

. The EPA registration decision for glufosinate was issued in 200 0 for crop use ( US

- EPA, 2008 )

. The EP A is currently evaluating the proposed new uses of dicamba for MON 87708 soybean and MON 88701 cotton

.

Applicable U.S. L aws Compliant Compliant Compliant Compliant

23

### 3 A FFECTED ENVIRONMENT

C otton and soybean production regions of the conterminous U.S. m ay be affected by a determination of nonregulated status for MON 87701 cotton and MON 8 8708 soybean . T his chapter includes a review of the prevailing conditions in the human environment in th os e regions. Background information about the economics and production practice s associated with cotton and soybean production is provided followed by descriptions of twelve major components of the human environment and how they might be affected if MON 87701 cotton and/or MON 8 8708 soybean were no longer regulated as plant pest s.
Relevant components of the physical environment , biological resources, human health , animal feed, and socioeconomic resources are considered

. They include soil, water and air quality

, climate change , land cover and land use s, cotton and soybean production practice s, animal communities, food and feed uses, worker safety and agricultural markets.

3.1 U.S. Co tton and Soybean Economics

The many and varied products derived from cotton and soybe an are why these crops are important both domestically and as export commodities. This section describes some of the economics and production practice s associated with these two crops.

3.1.1 U.S. Cotton Economics

Cott on ( Gossypium spp.) is the world’s most widely grown textile fiber crop, accounting for over 40% of fiber production in the world ( Meyer et al. , 2007 ) . The major cotton by

- products include an edible oil from seeds, as well as the use of chaff (hulls and linters), high

- protein cake, and flour as livestock feed ( OECD, 2008a )

. The most commonly cultivated species in the U.S. is upland cotton ( G. hirsutum ), comprising 97% of the cotton crop, ranging in 17 states from Virginia to California ( USDA

- NASS, 2014a )

. Upland cotton is also known as short staple cotton based on the relative length of the cotton fibers ( Rude, 1984 )

. The remainder is Pima (extra

- long staple [ELS] or Egyptian) cotton ( G. barbadense ) cultivated in Arizona, California, New Mexico, and Texas ( Pleasants and Wendell, 2005a ; USDA

- NASS, 2014a ) . The U.S. is the third largest producer of cotto n after China and India ( USDA

- FAS, 2014 )

. Cotton is cultivated in tropical and subtropical zones ( OECD, 2008a ) . It is a perennial plant cultivated as an annual ( Smith and Cothren, 1999 ; Boyd et al. , 2004b ) . It is geographically more limited than other major crops in the U.S. because its growth requires a minimum of 180 frost

free days per year ( Rude, 1984 ; Smith and Cothren, 1999 ; OECD, 2008a )

. Cotton is generally grown in deep arable soils with good drainage and a high moisture

- retention capacity ( OECD, 2008a ) . Ideal cotton production requires at least 500 millimeters (mm) rainfall during the growing season for non

- irrigated upland crops. However, it is also grown as an irrigated crop, where careful timing of irrigation optimizes flowering and boll production ( OECD, 2008a )

. Good cotton management allows the plant to produce a high yield at a reasonable cost by channeling energy into harvestable seed cotton within the limitations imposed by soil, leng th of

24season, and production cost ( Rude, 1984 )

. Particularly in upland varieties, boll maturation is dominant over vegetative growth and formation of new flower buds (called “squares”)

, once the plant begins to s et bolls

. If too few of the ovules are fertilized, the fruit drops within 10 days of flowering . D uring the post

- harvest ginning process

, longer cotton lint fibers are separated from the harvested seed cotton

. Unfertilized ovules within a fruit that fully develops remain as contaminants or “motes” within the lint . S horter fuzz fibers (called linters ) remain attached to the seed after ginning ( Rude, 1984 ; Boyd et al. , 2004b ) , and cottonseed oil processing begins with these materials.

The recent Agricultural Outlook Forum summarized recent economic aspects of cotton production ( Johnson et al. , 2014 ) :

“U.S. all

- cotton production in 2013/14 is estimated at 13.2 million bales, 24% lower than last season’s crop. Cotton planted acreage decreased 15% (nearly 2 million acres) in 2013 as relative crop prices favore d the planting of alternative crops. Cotton area this season was its lowest since 2009. Severe drought conditions continued for much of the Southwest in 2013, keeping U.S. abandonment near 25% for a second consecutive season, compared with the 10

- year average of 14%. In 2013, the U.S. yield averaged 826 pounds per harvested acre, below 2012’s record of 887 pounds but the second highest since 2007. Upland production is currently estimated at about 12.6 million bales

— approximately 4 milli on below 2012

— with an average yield of 807 pounds per harvested acre, well below 2012’s 869

- pound record. The extra

- long staple (ELS) crop (also known as Pima cotton) also is estimated lower

— at 636,000 bales

— as smaller area and a lower yield reduced the cr op to its smallest in three seasons.

“Compared with last season, 2013/14 upland cotton production was lower in each of the Cotton Belt regions. Production decreased in the Southwest as lower area more than offset a higher yield. With 2013 Southwest cotton plantings at 6 million acres, the region accounted for 59% of the total U.S. upland plantings and the largest since 1980. Southwest harvested area approached 3.4 million acres, below the 5

- year average, as above

- average abandonment

--- 44%

--- occurred for the third consecutive season. As a result, the Southwest upland crop reached 4.5 million bales in 2013/14, accounting for 36% of upland production. “For the Southeast, planted acreage in 2013 was about unchanged at nearly 2.7 million acres. A yield of 811 pounds per harvested acre is considerably lower than 2012’s record yield of 1,033 pounds. The 2013/14 Southeast crop only approached 4.5 million bales, the lowest in three seasons. For the Delta, 2013 planted area decreased to a record low of 1.2 million acres, 39% below 2012. Although a record yield of 1,085 pounds per harvested acre helped offset some of the area decline, the 2013/14 Delta crop of 2.7 million bales was the second lowest in three decades.

“In the West, 2013 upland area declined to 292,000 acres, the second lowest behind the 2009 season. With an average yield of 1,470 pounds per harvested acre, upland production in the West decreased to 870,000 bales, one of the lowest on record. The ELS crop remains concentrated in the West, and with ELS p roduction at 636,000 bales, total cotton production in the West region reached 1.5 million bales.”

25U.S. Cotton Area, Abandonment, Yield, and Production

2009/10 2010/11 2011/12 2012/13 2013/14

Planted acres (million acres) 9.2 11.0 14.7 12.3 10.4

Harvested

acres (million acres) 7.5 10.7 9.5 9.4 7.7

Abandonment rate (percent) 17.7 2.5 35.8 23.9 26.4

Yield (lb/acre harvested) 777 812 790 887 826

Production (millions of bales) 12.2 18.1 15.6 17.3 13.2

According to the 2007 Census of Agriculture, upland cotton was harvested in 631 U.S. counties or county equivalents (20%) ( USDA

- NASS, 2009d ) ( Figure 1 ). Production occurs in Alabama, Arizona, Arkansas, California, Florida, Georgia, Kansas, Kentucky, Louisiana, Mississippi, Missouri, New Mexico, North Carolina, South Carolina, Tennessee, Texas, and Virginia ( USDA

- NASS, 2009d ) . Five of these states (Texas, Georgia, Arkansas, North Carolina, and Mississippi) account for approximately 75% of the total U.S. crop ( USDA

- NASS, 2009d )

. Limited cotton production also occurs in Puerto Rico for breeding and as a seed crop ( Monsanto, 2004 ; Bayer, 2006 ) . Naturalized or feral populations of cotton grow in Florida, Hawaii, Puerto Rico, and the Virgin Islands ( Fryxell 1984 ; Bates, 1990 ; Coile and Garland, 2003 ; Wunderlin and Hansen, 2008 ; USDA

- NRCS, 2012c )

.

26Figure 1

. Upland Cotton 2012 Yield per Harvested Acre by County for Selected States. Source: ( USDA

- NASS, 2013i )

3.1.2 U.S. Soybean Economics

Soybean ( Glycine max (L.) Merr.) is an economically important leguminous crop, providing oil and protein from processed seed. It is the most important oil

- seed

- producing crop in the world. It accounts for 58% of global oil

- seed production ( ASA, 2011 )

. According to the 2007 Census of Agriculture, soybeans were harvested in 2,039 U.S. counties or county equivalents (66 % ) ( USDA

- NASS, 2009d )

. U.S. soybean production totaled 3.29 billion bushels in 2013, an increase of 8 % from 2012. This is the third largest yield on record ( USDA

NASS, 2014a )

. The average yield per acre i s estimated at 43.3 bushels, which is 3.5 bushels more than the 2012 yield ( USDA

- NASS, 20 14a )

. The harvested area of 85.9 million acres, although the fourth highest on record, was slightly less than 2012 acreage ( USDA

- NASS, 2014a )

. The value of U.S. soybean production for beans exceeded $43 billion in 2012 ( USDA

- NASS, 2013f ) , which was 23% of the total value of field and miscellaneous crops in 2012. The U.S. heartland ( Illinois, Indiana, Iowa, Kentucky, Minnesota, Missouri, and Ohio) accounted for more than 58% of the total U.S. crop value in 2012. There is substantial variation in yields and costs across soybean production regions.

Soybean exports in the form of bulk be ans, meal, and oil are a major share of the total agricultural exports for the U.S., representing 16.1% of the total value of U.S. agricultural
27exports. Bulk soybeans accounted for $17.59 billion of the total U.S. agricultural exports ($136 billion in 2011 ) ( USDA

- ERS, 2013c )

, ranking first among all agricultural commodities. Soybean meal ($3.2 billion) and soybean oil ($1.3 billion), ranked 11th and 22nd, respectively ( USDA

ERS, 2012c ) . As a percentage of global exports, the U.S. accounted for 38% of bulk soybeans, 13% of soybean meal, and 11% of soybean oil in 2011/12 ( USDA

- ERS, 2012c )

. In 2011/12 soybean meal represented 67% of the protein meal produced worldwide, although soybea n oil ranked behind palm oil in terms of worldwide vegetable oil production ( USDA

- ERS, 2012c )

. In terms of consump tion, soybeans yielded the largest share of protein meal consumed worldwide, mainly as animal feed. As a vegetable oil source, soybean oil consumption was second only to palm oil ( USDA

- FAS, 2013b )

. In 2011/12, the U.S. w as responsible for 35% of the world’s soybean production, 21% of world’s soybean meal production, and 21% of the world’s soybean oil production ( USDA

- FAS, 2013a )

. The U.S., China, Argentina, and Brazil are the major producers of bulk soybeans, so ybean meal, and soybean oil ( USDA

- FAS, 2013a )

.
From 1990

- 2013, U.S. acreage planted with soybeans increased from 59 million to more than 77 million acres ( Figure 2 ). It is now the second most widely planted crop in the U.S. after corn. The increase in soybean acreage is related to strong prices, the absence of acreage set

- aside programs, increased types of crop rotation strategies, and op timum soybean planting conditions. The top five soybean producing states (Iowa, Illinois, Minnesota, Indiana, and Nebraska) accounted for more than half of the total U.S. crop in 2012 ( USDA

- NASS, 2013f )

. Soybeans yield both solid (meal) and liquid (oil) products. Soybean meal is high in protein and is used for products such as tofu, soymilk, meat replacements, and protein powder. It also provides a natural source of dietary fiber ( USB, 2009 ) . Nearly 98% of soybean meal produced in the U.S. is used as animal feed. Less than 2% is used to produce soybean flour and proteins for human consumption ( Soyatech, 2011 ) . Poultry consume more than 45% of domestic soybean meal (about 590 million bushels of the U.S. crop). Soybean oil is used increasingly to repla ce animal fats and oils in broiler diets ( USB, 2011 ) . Soybean can be the dominant component of livestock diets (e.g., about 66% of protein in poultry diets is derived from soybeans ( Waldroup and Smith, 2008 ) ).

Other animals fed domestic soybean (by crop volumes consumed) include swine (26%), beef cattle (12%), dairy cattle (9%), farm

- raised fish (3%), and household pets (2%) ( Soy Stats, 2010 ; USB, 2011 )

. Soybean plant material is also used as forage , hay , and silage for livestock ( Blount et al. , 2009 ) . Specific varieties of soybean exist for grazing and hay, but the whole plant has feeding value ( Weiderholt and Albrecht, 2003 ) Specific varieties of soybean exist for grazing and hay, but the whole plant has feeding value ( Weiderholt and Albrecht, 2003 )

. Soybean liquids are used to produce salad and cooking oils, baking and frying fat, and margarine. Soybean oil is low in saturated fats, high in poly

- and monounsaturated fats, and contains essential omega

- 3 fatty acids. Soybean oil comprises nearly 70% of the oils consumed in U.S . households ( Soy St ats, 2010 )

.

28Figure 2

. Soybeans 2012 Yield per Harvested Acre by County for Selected States

. Source: ( USDA

- NASS, 2013h )

.
3.2 U.S. Cotton and Soybean Production

Most U.S. soybean acreage is located in the Midwes t and along the e ast c oast . Cotton is confined
to the s outhern tier of the count r y.

3.2.1 Major U.S. Cotton and Soybean Production Regions

Major cotton

- and soybean

- growing regions in the continental U.S are shown in Figure 1 a nd Figure 2 , respectively. L ittle or no cotton and/ or soybean production occurs in Hawaii, Alaska,

an d the U

. S

. t erritories, so these regions are not included in th e figures ( Figure 1 and Figure 2 )

. The data in Figure 1 and Figure 2 were used to identify the criteri a described in Section 3.2.2 and define the ecoregions of the affected environment ( Figure 3 )

. The primary locations of cotton and soybean cultivation within Regions A to M are described in Table 2 . For each of these cotton or soybean producing regions, the corresponding L evel I ecoregion is used to describe the physical terrain and climate. These are broad descriptions based on the ecoregion’s characteristics, and demonstrate the wide range of soil types, land

, and climatic features.

3.2.2 Ecor egions of the Affected Environment

The 13 regions (A

- M) of the affected environment ( Figure 3 ) reviewed in this document represent the principal U.S. cotton

- and soybean

- growing areas. The R egions (A

- M; Figure 3 ) are based on the identification of contiguous groups of counties that exceed a threshold . The
29threshold used to determine if a county was included in a region was the number of cotton or soybean acres ( USDA

- NASS, 2009d ) multiplied by a constant (100) a nd the percent age of total cropland in that county that the crop covers. If th e result exceed ed 100,000 and the county was contiguous with another county that exceeded the 100

- thousand threshold, then the county was i ncluded a s part of the affected environment reviewed in this document . Idle cropland was excluded from the calculations.

Figure 3

. Major Soybean and Cotton Cultivation Regions in the U nited S tates. For example, if 20,000 acres of cotton w ere harvested in a cou nty, and this represented 6% of the total cropland in th at county, the index number is 120 thousand. If the county was contiguous with another count y with an index exceeding 100 thousand , then the county was included as part of the affected environment rev iewed in this document.

Using this method, o ver 90% of the total soybean and cotton acreage harvested in 2007 ( USDA

NASS, 2009d ) was included in the regions identified in Fig ure 3 and considered as part of the affected environment here.

The affected environment includes a number of ecological regions (ecoregions) defined by the EPA and the Canada

- Mexico

- U

. S

. Co mmission for Environmental Cooperation (CEC)

. Ecoregions are areas that are similar in type, quality, and quantity of environmental resources ( CEC, 2009 )

. The CEC uses a hierarchical system to classify ecoregions into three different levels. The broadest on e is Level I

. It divides North America into 15 ecological regions

. These are subdivided into 50 Level II ecoregions that are then further subdivided into 182 Level III subregions

. Each Level III subregion is defined by a variety of physical, biological, an d human factors

. These include location, climate, terrain, hydrology, vegetation, wildlife, and land use 30associated with human activities. The U.S. EPA ecoregions correspond to the CEC Level III subregions . A map of the Lev el III subregions of the conterminous U nited S tates is shown in Figure 4

.

Figure 4

. Ecoregions of the Conterminous U nited S tates

. Source: ( CEC, 2006 )

C ommercial cotton or soybean production occur s in the 1 3 regions (labeled A

- M) of the affected environment in the conterminous U.S. Most are in Level I ecoregions (i.e., EPA/CEC Ecoregions 8 [ Eastern Temperate Forests ] and 9 [ Great Plains ]). Ecoregion 8 covers most of the eastern half of the conterminous U.S. and is distinguished by i ts moderate to mildly humid climate, diverse forest cover, and high density of human inhabitants, industry, and agriculture. Ecoregion 9 covers most of the central conterminous U.S. and is distinguished by its sub

- humid to semiarid climate, grasslands with little topographic relief, high density of agriculture and much lower (than Ecoregion 8) density of human inhabitants

. Ecoregion 9 is among the largest farming and ranching areas in the world.

For cotton, a small portion of the affected environment also occurs in Level I ecoregion 10 (North American Deserts) and 11 (Mediterranean California)

. Although these two ecoregions combined account for only about 4% of total U

. S

. u pland cotton cultivation, cotton production is locally important in both regions

. Within the continental U.S. , the regions of soybean and cotton

31cultivation are non

- overlapping with the exceptions of the Mississippi R iver V alley and the S outheast ( see Table 2 ; Figure 1 and Figure 2 )

. The general descriptions of the physical and biological environments for each region th at follow are based on the CEC combined with U.S. EPA Level III descriptions for ecoregions

. These are supplemented by the U.S. EPA Level IV descriptions, unless otherwise cited ( US

- EPA, 2 010a ; CEC, 2011 )

.
3.3 Physical Environment

The physical environment is defined for the purposes of this document as the location and physical terrain within each region, its soil and water resources , air quality

, and climate

. The locations of cotton and soybean cultivation within Regions A

- M are described in Table 2

.

3.3.1 Physical Terrain and Climate

For each of these cotton or soybean producing regions, the corresponding Level I ecoregion is used to describe the physical terrain and climate

. These are broad descriptions based on the ecoregion characteristics that include soil type, land and climatic features.

Table 2

. Location of Major Cotton and Soybean Production Areas

.

Region CEC/EPA Ecoregion Location of Soybean and Cotton Cultivation Area (sq. miles) Percent of U.S

. Harvest 1

Soybean Cotton

A

(Mixed Wood Plains, central portion) 8.1.1/83 8.1.3/60 Upstate NY 5,184 0.3% 0%

B

(Mixed Wood Plains, western portion) 8.1.4/51 8.1.5/52 8.1.6/56 Northwestern IL

Northern IN

Northeastern IA

Central and southern MI

Central MN

Central and western WI 60,802 5.2% 0%

C

(Central USA Plains; Erie 8.2.1/53 8.2.2/57 8.2.3/54 8.2.4/55 Northern and central IL

Eastern, central and northwestern IN 102,899 18.4% 0%

32Region CEC/EPA Ecoregion Location of Soybean and Cotton Cultivation Area (sq. miles) Percent of U.S

. Harvest 1

Soybean Cotton

Drift Plain) 8.1.10/61

8.4.3/70 (northwestern) Eastern MI

OH (most)

Northwestern PA

Southeastern WI

D

(Southeastern USA Plains, eastern and southern portion; Appalachian Forests, northeastern portion; Southeast USA Coastal Plains) 8.3.1/64

8.3.4/45

(east

- central)

8.3.5/65 (eastern, south

central)

8.4.1/67 (northern)

8.5.1/63

8.5.3/75 (northwestern)

8.5.4/84 (southern) Southern AL

DE

Northwestern FL panhandle

Southern and east

- central GA

MD (most)

Central and southwestern NJ

Eastern and central NC

Southeastern PA

No rtheast to southwest SC

Eastern VA 133,875 5.4% 19.7%

E

(Southeastern USA Plains, northwestern portion) 8.3.2/71 8.3.3/72

8.4.5/40 (northern, along 8.3.2 border) North

- central AL

Western and southern IL

Southwestern IN

Southeastern edge IA

Central and western KY

Eastern edge and central MO

Southwestern edge OH

North

- central and south

central TN 97,017 9.4% 0.7%

33Region CEC/EPA Ecoregion Location of Soybean and Cotton Cultivation Area (sq. miles) Percent of U.S

. Harvest 1

Soybean Cotton

F

(Mississippi Alluvial Plains; Southeastern USA Plains, western portion) 8.3.5/65 (northwestern)

8.3.6/74

8.3.7/35

(Red River only)

8.5.2/73

9.5.1/34 (eastern) Eastern and southwestern AR

Western KY

Northeastern, northwestern and central LA

Western and northern MS

Southeastern MO

Western TN 78,430 11.7% 15.3%

G

(Temperate Prairies) 9.2.1/46

9.2.2/48

9.2.3/47

9.2.4/40 IA (most)

Eastern KS

Western and southern MN

Northern and western MO

Eastern NE

Eastern and north

- central ND

Northeastern OK

Eastern SD 201,400 38.7% 0%

H

(West

- Central Semi

- Arid Prairies, eastern portion) 9.3.1/42 North

- central NE (small area)

Central and south

- central ND

Central SD 30,487 2.3% 0%

I

(South

- Central Semi

- Arid Prairies, northeastern 9.4.2/27 (northern)

9.4.4/28 Central KS

South

- central NB

North

- central OK 70,597 5.8% 0.2%

34Region CEC/EPA Ecoregion Location of Soybean and Cotton Cultivation Area (sq. miles) Percent of U.S

. Harvest 1

Soybean Cotton

portion)

J

(South

- Central Semi

- Arid Prairies, south

central portion) 9.4.1/25 (southern)

9.4.2/27 (southern) 9.4.3/26 (south

eastern) Southwestern OK

Northwestern TX 63,765 0% 47.1%

K

(Western Gulf Coastal Plain) 9.5.1/34 Central Gulf Coast of TX 22,863 0% 5.2%

L

Warm Deserts (central portion) 10.2.2/81

10.2.4/24 (AZ only) Southwestern AZ 35,352 0% 1.5%

M

(Central California Valley) 11.1.2/7 (southern) San Joaquin Valley CA 10,270 0% 2.8% 2

CEC = Canada

- Mexico

- E.S. Commission for Environmental Cooperation (CEC) EPA = U.S. Environmental Protection Agency
1 Based on USDA

- NASS CropScape land cover data for 2012 ( USDA

- NASS, 2013j )

. Upland cotton represented more than 97% of total cotton acreage harvested from 2007

- 2012 ( USDA

- NASS, 2009d ; 2013g )

. 2 Crop S cape does not distinguish between upland and Pima cotton, so the percentage listed for Region M includes Pima co tton production

. Pima cotton averaged 60% of the harvested cotton acreage in California ( USDA

- NASS, 2013g ) . 90% of the harvested Pima cotton acreage in the U.S. came from California in 2007

- 2012.
Region A is characterized by level to rolling terrain and open valleys with a variety of deep glacial and marine deposits

, and some bedrock outcrops. It has a mid

- latitude humid continental climate marked by warm summers and cold, snowy winters with a mean annual temperature of 5

- 9 degrees Celsius ( °C ). The fros t

- free period ranges from 130 to 200 days. Annual precipitation ranges from 720 mm to 1,200 mm

. Locations that are in closer proximity to the Great Lakes experience a longer growing season, more winter cloudiness, and greater snowfall.

Region B is characte rized by rolling plains formed by glacial outwash and deposits . S ome are complex deposits of drift, rolling to hilly moraines, deeply dissected plateau s , lacustrine basins,

35and meltwater channels

. It has a mid

- latitude, humid continental climate

, and winte rs with no dry season. The mean annual temperature ranges from 5

- 10°C with a frost

- free period of 130

- 200 days

. Annual precipitation is 600

- 990 mm.

Region C is characterized by flat to rolling glacial plains, with some clay plains, outwash plains, sand dun es, and moraines, with areas of wetlands. The southeastern edge in Ohio was not covered by a glacier, so it has the form of a dissected plateau with some rugged hills

. It has a mid

- latit ude, humid continental climate with mean annual temperatures of 7

- 13°C

. The frost

- free period ranges from 140

- 200 days. Annual precipitation is 700

- 1150 mm, increasing from north to south.

Region D is characterized by features, ranging from low rounded or irregular hills, ridges, irregular plains and rolling or open valleys in the north and west ( CEC/EPA Ecoregions 8.3.1, 8.3.4, northern 8.4.1), and flatter, rolling to smooth coastal plains to the south and east ( CEC/EPA Ecoregions 8.3.5 and 8.5.1). It has a mild mid

- latitude humid subtropical climate with hot humid summers a nd mild winters, except for the northern areas ( CEC/EPA Ecoregions 8.3.1 and northern 8.4.1)

, which have severe mid

- latitude climates or are transitional areas and have cold winters . M ean annual temperatures range from 8

- 19°C . T he frost

- free period ranges from 145

- 300 days, increasing from north to south and west to east

. Annual precipitation ranges from 900

- 1650 mm, generally increasing from north to south and west to east.

Region E is characterized by wide, flat

- bottomed terraced valleys, valley slopes, a nd river bluffs to the north and west ( CEC/EPA Ecoregion 8.3.2), with dissected glacial till plains in Illinois and Indiana , and by a broader variety of landforms to the east and south ( CEC/EPA Ecoregion 8.3.3), including gently sloping, rolling and irregular plains, dissected plateaus, and tablelands and open hills. The climate also varies from a severe mid

- latitude humid continental climate with hot summers and cold winters in the north and west to a mi ld mid

- latitude humid subtropical climate with hot summers and mild winters with no pronounced dry season in the south and east. Mean annual temperatures range from 10

- 16°C and the frost

- free period ranges from 160

- 220 days. Annual precipitation ranges fro m 850

- 1470 mm, with noticeably more precipitation to the south and east.

Region F is characterized by a variety of landforms, from a mostly broad and flat alluvial plain with river floodplains, terraces, swales, levees, oxbow lakes, and back swamps to the west ( CEC/EPA Ecoregions 8.5.2 and 8.3.7), to irregular plains with some gently rolling hills to the east ( CEC/EPA Ecoregions 8.3.6 and northwestern 8.3.5)

. Thick deposits of sandy to clayey alluvium occur in the west, thick deposits of loess in the centra l part of the region, and fine

textured clayey sand and some loess to the east and north. The region has a mild mid

- latitude humid subtropical climate with hot and humid summers and mild winters. Mean annual temperatures rang e from 13°C in the north to 21 ° C in the south, while the frost

- free ranges from 200

- 300 days, but approaches 350 days near the Gulf of Mexico. Annual precipitation ranges from 1140 mm to 1650 mm, increasing from north to south, and is fairly evenly distributed throughout the year.

Regi on G is characterized by flat to gently rolling glacial till plains with thick beds of lake sediments on top, and by hilly loess plains with thick layers of loess. The southernmost part of the region is topographically hillier than the rest. The region has a severe, mid

- latitude, humid
36continental climate, with a milder humid subtropical climate in the southernmost area ( CEC/EPA Ecoregion 9.2.4). It is marked by short warm summers and long cold winters with nearly continuous snow cover to the north, and by longer hot summers and cold to mild winters further south. The mean a nnual temperature ranges from 3°C in the north to 16 °C in the south, and the frost

- free period ranges from 90 to 225 days. Annual precipitation ranges from 400

- 1145 mm, increasing from n orthwest to southeast, with most precipitation occurring during the growing

season.
Region H is characterized by rolling hills and gentle plains mantled almost entirely by moraine, outwash, and glaciolacustrine sediments. It has a dry, mid

- latitude steppe climate with warm to hot summers and cold winters. The mean a nnual temperature ranges from 3 °C in the north to 9°C in the south, and the frost

- free period ranges from 100 to 160 days. Annual precipitation ranges from 250 mm to 550 mm.

Region I is primaril y characterized by smooth and level to slightly irregular plains, with broad alluvial valleys and some hillier dissected plains in the central part of the region ( CEC/EPA Ecoregion 9.4.2)

, r olling hills

, and relatively narrow ste ep valleys to the east (CEC /EPA Ecoregion 9.4.4). The c limate varies both north to south and west to east. The west has a mid

latitude steppe climate while the east has a mid

- latitude humid continental climate. Summers are hot and winters are cold in the north becoming milder moving south. Mean annual temperatures range from 10°C in the north to 15°C in the south, with 135

- 200 frost

- free days. Annual precipitation ranges from 450 mm to 1000 mm and is much higher in the easternmost part of the region ( CEC/EPA Ecoregion 9.4.4) than e lsewhere.

Region J is characterized by nearly level to irregular plains that are lightly to moderately dissected. It has a mild mid

- latitude humid to dry steppe climate moving from east to west, marked by hot summers and mild winters. The mean annual temp erature ranges from 13°C to 18°C and the frost

- free period is 190 to 260 days ( USDA

- NRCS, 2006b ) . Annual precipitation ranges from 300 to 660 mm , increasing from west to east ( USDA

- NRCS, 2006b )

. Region K is characterized by flat to gently sloping coastal plains in the agricultural areas, with sediments of marine sand, silt, and clay. It has a mild, mid

- latitude, humid subtropical climate marked by hot summers and mild winters. The mean annual temperature ranges from 20°C to 25°C, with a frost

- free period of 270

– 365 days. The mean annual precipitation ranges from 600 mm to 1625 mm, increasing rapidly from southwest to northeast.

Region L is characterized by mountain ranges to the north, scattered low mountains, and alluvial fans and valleys. It has a dry, subtropical desert climate marked by hot summers and mild winters. The mean annual temperature ranges from 15°C to 23°C. The frost

- free period ranges from 200

- 365 days, decreasing in length with increasing elevations. Mean annual precipitation ranges from 75 mm to 500 mm, with winter rainfall decreasing from west to east and summer rainfall decreasing from east to west. Evaporation rate s are high.

Region M is characterized by flat fluvial plains filled with deep and well

- drained loamy or clayey soils formed by deposits washed down from the surrounding mountains. It has a warm and mild Mediterranean climate, with long, hot dry summers and mild, slightly wet winters. The mean annual temperature ranges from 15°C to 20°C, with a frost

- free period of 280 to 365 days,

37decreasing with increasing elevation and latitude. The mean annual precipitation ranges from 125 mm in the south to 300 mm in th e northern margins.

3.3.2 Soil Resources

Soils are an admixture of weathered minerals, organic matter, air and water

. They are formed mainly by the weathering of rocks, the decaying of plant matter, and the deposition of materials such as chemical and biological fertilizers that are derived from other origins.

Particle size, texture and color are important attributes used to classify a soil type into one of twelve taxonomic orders

. Properties such as organic matter content and degree of soil profile development a re also used ( Brady and Weil, 1996 ) to systemat ically classify soils according to relationships that define their character ( USDA

- NRCS, 1999b )

. Eight soil ord ers ( Table 3 ) are predominant in areas where cotton and soybean are grown.

Table 3

. Dominant and Major Secondary Soil Types by Region

. Soil Order Description Region

Alfisols A dark surface horizon mineral soil, similar to mollisols however, lacking the

same level of fertility and more acidic. A, B, C, D, E, F, G, I, J, K, M

Aridisols These soils are found in the arid regions of the US. Typically high in calcium, Magnesium, potassium and sodium. The soils have an alkaline pH. J, L, M

Entisols This soil order is relatively un

- weathered. These soils have no diagnostic horizon development. Often found on floodplains, glacial outwash areas and other areas receiving alluvial materials. B, C, D, E, F, H, I, J, L, M

Histosols Dominated by organic soil materials,

some consist of a thin layer of organic materials over a root

- limiting layer or fragmental materials; commonly called bogs, peats, mucks B

Inceptisols Soils of the humid and sub humid region. Weathering has created minimal diagnostic differentiation in the soil column. B, C, D, E, F, J

Mollisols Dark colored mineral soils developed under grassland conditions. Rich in nutrients, very fertile. Associated with the corn belt. B, C, E, G, H, I, J, M

Ultisols Highly weathered soils found in hot, D, E, F
38Soil Order Description Region

moist regions. Typically acidic and low in available nutrients.

Vertisols Soils having major amounts of expanding clay content. Soils typically crack when dry and swell when wet. F, G, H, J, K, M

Source: ( USDA

- NRCS, 1999b )
Soil proper ties are dynamic

. Temperature, pH, soluble salts, amount of organic matter, the carbon

- nitrogen ratio, numbers of microorganisms, and soil fauna all vary seasonally, and shifts in these parameters also occurs over broader extended periods ( USDA

- NRCS, 1999b )

. Soil texture and organic matter levels directly influence shear strength, nutrient holding capacity, and
per meability ( McCauley et al. , 2005 ) . Soil types also influence susceptibility to erosion by wind and water and the capacity to att enuate flooding ( McCauley et al. , 2005 )

. Soil erosion is a naturally occurring event and the erosion rates are relatively slow; however, human activity ca n greatly accelerate the rate of erosion

. In general, wind and/or water erosion are important soil resource concerns along with wetness and maintenance of organic matter content in the U.S. cotton

- and soybean

- growing regions ( USDA

- FSA, 2010 )

. Figure 5 is a map of erosion exceeding the soil loss tolerance rate on cropland in the U nited States ( USDA

- NRCS, 2011 )

. Excessively eroding cropland soils are concentrated in the Midwest and the S outhern H igh P lains of Texas ( R egions G and J). From 1980

- 2011, the reported total soil erosion in U.S. cotton production areas decreased by 42%, and decreased in soybean production areas by 28% ( Field

- to

- Market, 2012 )

. Conservation tillage and no

- till practices reduc e soil erosion, and the amount of reduction depends on the existing soil structure, making quantification of the impacts on soil erosion difficult ( NRC, 2010a )

. Cotton can be produced in a wide variety of soil types, provided sufficient nutrition and moisture is available throughout the growing season. In general, loam and clay loam soils are more productive where annual rainfall is less th an 20 inches per year, because these soil types are able to store more water, in comparison to coarse

- textured soils that provide better internal drainage and are more productive where rainfall exceeds 30 inches per year ( Graneto et al. , 2013 )

. Soybean production is best suited to fertile, well

- drained, medium

- textured loam s oils, yet they can also be grown in a wide range of soil types ( National Soybean Research Laboratory ; Berglund and Helms, 2003 )

.

39Figure 5

. U.S. Croplands with High Erosion Rates. Source: ( USDA

- NRCS, 2011 )

3.3.3 Water Resources

R esources analyzed in this section include the quality and quantity of water in surface a nd groundwater . Impacts from human consumption , particularly water for irrigating agricultural production, are also reviewed.

Surface water in rivers, streams, creeks, lakes, and reservoirs provides water for drinking and bathing, irrig ation , industrial, and recreational uses. About 66% of wate r used in the U.S. in 2005 (about 410 billion gallons per day) was from fresh surface water sources ( USDA

- FSA, 2 010 )

. Surface runoff from rain, snowmelt, or irrigation can affect water quality by depositing sediment, minerals, and contaminants into streams, rivers, lakes, wetlands, and coastal waters. The amount of surface runoff is influenced by meteorological f actors (such as rainfall intensity and duration), and physical factors (such as vegetation, soil type, and topography).

Groundwater flows underground, substantially contributes water to streams and rivers, is stored in natural geologic formations called aq uifers, and sustains ecosystems by releasing a constant supply of water. In 2005, groundwater contributed about 19% of the freshwater used in the U.S. ( USDA

- FSA, 2010 )

. App roximately 47% of the U.S. population depends on groundwater for its drinking water supply ( McCray, 2012 ) . Both groundwater and surface water can be used for

40irrigation , which accounted for approximately 28% of withdrawals from fresh surface water

sources ( USDA

- FSA, 2010 )

. Based on 2005 data, the largest use of groundwater in the U.S. is irrigation , representing approximately 67% of all the groundwater pum ped each day ( USDA

- FSA, 2010 ; McCray, 2012 ) . More than 90% of the areas irrigated in Mississippi and Missouri used groundwater ( USDA

- FSA, 2010 )

. Wells replenished from groundwater often are the only source of ir rigation in many locations in the Great Plains ( US

- EPA, 2012a )

. Groundwater sources are especially important for irrigation in Arizona, Arkansas, California, Nebraska, and Texas, accounting for nearly 60% of total groundwater withdrawals for irrigatio n in 2005. In three of these states (Arkansas, Nebraska, and Texas) fresh groundwater accounted for 75%

- 96% of all irrigation
water. Irrigation maintains adequate moisture for a crop, so it contributes to agriculture by increasing yields per acre, and by making more acreage (i.e., dry lands) usable . Irrigation a lso moderates fluctuations in product and seed quality. This is because m oisture requirements for most crops tend to vary during development , and a n adequate water supply allows crop growth during critical periods of the growing cycle . In this way, irrigation can optimize both quality and yield ( US

- EPA, 2012a )

. A variety of irrigation technologies are available ( Figure 6 ) ( Cantrell, 2006 ) . Efficient irrigation can redu ce runoff and deep percolation (leaching) losses ( TAMU, 2014 )

. In addition to irrigation, w ater is used in agriculture for pesticide and fertilizer applications, c rop cooling (e.g., light irrigation), and frost control ( US

- CDC, 2013 )

.

Figure 6

. Examples of Cotton Irrigation Systems: A=furrow , B=drip method , C=low energy precision application. Source: ( Cantrell, 2006 )
Irrigation is especially important to cotton agriculture in the western U.S. and the Mississippi River Valley ( Figure 7 ). Most irrigation in California ( R egion M) is used for alfalfa, cotton, orchards, an d vegetables ( USDA

- NASS, 2009a ) . Nationally, less than 10% of soybean acres and approximately 40 % of cotton acres are irrigated. However, soybean accounts for about 25 % of irrigated acres in the eastern 31 states, particularly in the Mississippi River Valley ( R egion F) ( USDA

- NASS, 2009b ; 2009c ; Schaible and Aillery, 2012b ) . Cotton is heavily irrigated in California, Arizona, western Texas, Georgia, and the Mississippi River Val ley (Regions D, F, J, L, and M). Soybean is heavily irrigated in central Nebraska (Region I) ( USDA

- NASS, 2007b ; 2007c ) ( Figure 8 ).

41Figure 7

. Irrigated Cotton Acreage in the U nited S tates in 2007. Source: USDA National Agricultural Statistics Service Map # 07

- M080 ( USDA

- NASS, 2007b )

.

42Figure 8

. Irrigated Soybean Acreage in the U nited S tates in 2007. Source: USDA National Agricultural Statistics Service Map #07

- M194 ( USDA

- NASS, 2007c )

. Information from the U.S. Geological Survey ( Konikow, 2013 ) is combined with the Level III and Level IV Ecoregion descriptions to further describe the water resources in the regions identified as the Affected Environment:

Region A contains perennial streams, Lake Ontario, the Finger Lakes a nd some smaller lakes, and abundant wetlands in some areas.

Region B has many perennial streams, with wetlands and lakes more common in northern areas. The northern Mississippi River runs through the region and groundwater is abundant and is the major source of irrigation water in Minnesota and Wisconsin ( USDA

- FSA, 2010 )

. Region C has a low to medium density of perennial streams, which are often intermitt ent in the more southern portions of the region. Some areas have lakes and abundant groundwater , which serve as the major source of irrigation water in Illinois and Wisconsin, and wetlands are abundant in the east ( CE C/EPA Ecoregion 8.1.10). Drainage has been greatly modified in CEC/EPA Ecoregions 8.2.2 and 8.2.3, and stream chemistry, turbidity, and habitat have been affected by agriculture.

43Region D has a moderate to dense network of streams and rivers, with few natu ral lakes but some reservoirs to the north and numerous swamps and marshes to the south. The Roanoke, Savannah, and Susquehanna Rivers, among others, run through the region.

Region E has numerous perennial streams and rivers in CEC/EPA Ecoregion 8.3.2, wit h silt and sand dominating lowland channels while upland streams are rockier. There are both perennial and intermittent streams and numerous springs in CEC/EPA Ecoregion 8.3.3, with higher nutrient, alkalinity and hardness levels than the streams in CEC/EP A Ecoregion 8.3.2. In the Western Pennyroyal region of Kentucky and Tennessee there are also many sinkholes, ponds and well developed underground drainage such that soils are quick to dry. The Illinois, Missouri, Mississippi, Ohio, Tennessee and Wabash Riv ers all run through the region.

Region F is dominated by the Mississippi River and used to contain one of the largest continuous wetland systems in North America. However, extensive areas have now been modified by channelization and navigation and flood c ontrol engineering. The Red River also runs through the region, and oxbow lakes, backswamps, and ponds occur. To the east there is a moderate to dense network of perennial and intermittent streams and rivers, including the Tombigbee River, but few lakes. G roundwater from the Mississippi Alluvial Valley alluvial aquifer is the major source for irrigation water in this region ( USDA

- FSA, 2010 )

. Water withdrawals from the aquifer greatly exceed recharge from surface waters ( Konikow, 2013 )

. Region G has a low density of rivers and intermittent and perennial streams through most of the region, with a higher density and several large rivers in the south, including the Des Moines, Kansas, and Missouri Rivers. The Minnesota River and the Red River of the North are the major rivers in the north. Many streams and rivers have been channelized. Abundant temporary and seasonal wetlands occur in the north, creating favorable conditions for waterfowl nesting and migration, and a few large reservoirs occur to the south. Groundwater is highly mineralized in some areas and surface and groundwater contamination from fertilizer and pesticide applications as well as from concentrated livestock production is a regional issue in the central portions o f this region ( CEC/EPA Ecoregion 9.2.3).

Region H has mostly intermittent streams, with some perennial streams and larger rivers, most notably the Missouri River which runs along the western boundary of most of the region. In some areas a high concentratio n of semi

- permanent and seasonal wetlands can be found.

Region I has mostly intermittent and ephemeral streams to the west and intermittent and perennial steams to the east. There are a few larger rivers (Arkansas, Platte, and Kansas and its tributaries) a nd some springs, but few lakes. The Ogallala A quifer underlies large portions of the ecoregion and is the major source for irrigation water in this region ( USDA

- FSA, 2010 )

. Water withdrawals from the aquifer greatly exceed recharge from surface waters ( Konikow, 2013 ; Steward et al. , 2013 )

. Region J has few to no streams. Surface water occurs in numerous ephemeral pools or playas which serve as recharge areas for the Ogallala A quifer, which is essential for cultivated agriculture in the region. However, water withdrawals from the aquifer usually exceed recharge.

44Region K has intermittent and perennial streams, some of which are channelized. There are numerous wetlands in the ea stern part of the region.

Region L has ephemeral and intermittent streams, with few surface waters other than the Colorado River, which has a mountainous, distant source. Some springs and a few reservoirs are present. Water resource use is intense, both fr om rivers and ground water.

Region M the San Joaquin flows through the region. Streams are mostly intermittent and dry during the summer months. The region has an extensive network of water diversions, channelization, and drainage, and irrigation water management is a priority ( USDA

- NRCS, 2006d )

. Groundwater from the Central Valley Aquifer is a major source of irrigation water, though secondary to surface water for this purpose, and groundwater withdrawals exceed recharge rates ( Konikow, 2013 ) . Groundwater contamination from heavy use of agri cultural chemicals is a concern. Water in lowland streams is often degraded by sediments and salts from agricultural irrigation and drainage and municipal and industrial waste discharges.

Water Quality

Natural features (i.e., the physical and chemical prop erties) of the land surrounding a water body have the greatest impact on quality. The topography, soil type, vegetative cover, minerals, and climate also influence water quality. Regions of the U.S. identified as part of the Affected Environment continue t o experience diminished water quality. For example, in Region C, drainage has become greatly modified, while in Region F, extensive areas are modified by channelization, navigation, and flood control engineering. Further, in Region G, groundwater is highly mineralized in some areas and there is groundwater contamination from fertilizer and pesticide applications. Finally, in Region M, groundwater contamination from heavy use of agricultural chemicals is a concern. Water in lowland stream s can be degraded by sediments and salts from agricultural irrigation , drainage, municipal, and industrial waste discharges.

Sediments flowing into water bodies can affect the health of fish, aquatic invertebrates, and other wildlife. Se diments reduce light penetration into water, which can adversely impact aquatic plant growth and survival. Fertilizer runoff can contribute to chemical and mineral toxicity, higher water turbidity, algal blooms, and oxygen depletion in water resources

. Soil erosion

- mediated sedimentation can increase fertilizer runoff causing similar impacts ( US

- EPA, 2005 ; TAMU, 2014 )

. Major sources of pollutants include storage tanks, septic systems, hazardous waste sites, and landfills. Widespread use of road salts, fertilizers, pesticides and other agricultural chemicals are also important sources. All surface water pollutants have the pote ntial to be transported into groundwater . According to an EPA Report on the Environment for 2008, groundwater also was seriously affected by various nutrients and pesticides ( USDA

- FSA, 2010 )

. Agricultural pollution is the leading source of impacts on surveyed rivers and lakes. It is also the third largest source of impairment of water quality in estuaries, and a major source of contamination of groundwater and wetlands ( USDA

- NRCS, 2011 )

. The most common types of agricultural pollutants include excess sediment, fertilizers, animal manure, and pesticides. Management pra ctices that contribute to water contamination include the type of crop cultivated, plowing and tillage, and irrigation . Safe and appropriate storage, handling, and 45application of agricultural chemicals and wastes reduce the risks of wate r contamination ( TAMU, 2014 ) . Irrigation depletes available water and reduces quality by increasing erosion and sedimentation, nutrients dissolved in runoff, and chemicals adsorbed onto soil particulates washed into surface water. Some of these pollutants eventually contaminate groundwater by leaching.

Pesticide use introduces chemicals into water through spray drift , the cleaning of pesticide

a pplication equipment, soil erosion, and subsequent filtration through soil into groundwater ( US

EPA, 2012c )

. Consequently, fertilizers and pesticides are in excess in many water bodies in the U.S. ( USDA

- FSA, 2010 ) . The EPA documented over 3 million acres of water bodies and over 75,000 miles of rivers and streams, large areas of bays and wetlands with excess levels of nitrogen and phosphorus. Excess of these two nutrients create harmful blooms of algae and other
aq uatic flora which deplete oxygen that can result in many detrimental effects including fish kills.

Nonpoint source (NPS) pollution comes from many diffuse sources. NPS pollution accumulates as runoff from rainfall or snowmelt moves over the ground, picks up, and then carries natural and human

- made pollutants. NPS pollution increases sedimentation in surface waters following soil erosion by surface runoff. These pollutants may eventually be transported into various types of permanent water resources , such as streams, rivers, and lakes. This is in contrast to a point source of pollution which has a discernible, confined, and discrete source.

In addition to conservation tillage that leaves crop residue to absorb water, two other import ant

a gronomic methods of controlling runoff include furrow diking and use of center

- pivot irrigation systems. The mechanical tillage operation called f urrow diking prevent s runoff by placing mounds of soil at intervals across the furrow between crop rows to form small water storage basins. Rainfall or irrigation water is trapped and stored in the basins until it soaks into the soil, rather than running off . Center pivot systems irrigate in a circular pattern that can improve water distrib ution . In these systems, r unoff is reduced by changing the speed to adapt the precipitation rate to the soil infiltration rate ( New and Fipps, 2000 )

.

3.3.4 Air Quality

The Clean Air Act (CAA) (amended in 1990) requires States to comply with the National Ambient Air Quality Standards (NAAQSs) established by the EPA for six principal pollutants, called criter ia pollutants

. The intention of these standards is to protect public health and the environment from these pollutants. The six criteria pollutants are: ozone (O 3 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), lead (Pb), and inhalable particulate matter (PM) . T here are three subgroups of particulates based on particle size ( Cambra

- Lopez et al.

, 2010 )

. They are PM (coarse particulate matter greater than 10 μm [micrometers]), PM 10 (particulates 2.5

- 10 μm), and PM 2.5 , (fine particles less than 2.5 μm) ( US

- EPA, 2013c )

. Air quality monitoring data is collected and reviewed by EPA, state, and local regulatory agencies, and is available to the public

. This dat a is often published with respect to a local air quality index (AQI)

. The AQI is a measurement (from zero to 500) of the level of criteria pollutants in the atmosphere

. An AQI above 100 indicates that air quality conditions may be unhealthy for certain sensitive groups of people. An AQI over 300 represents air quality that is

46hazardous to everyone. AQI values below 100 indicate pollutant levels are at satisfactory levels ( AirNow, 2013 )

. Agricultural operations can affect air quality by releasing particulates, gases, and other chemicals into the air. Particulates may be released through a variety of cropping practices including the burning of crop residues or animal carcasses ( Yang and Sheng, 2003 ; Lemieux et al. , 2004 )

. Burning releases smoke, exhaust from motorized equipment may release criteria pollutants, and cropping activiti es (such as planting, tillage, and harvesting ) generate airborne soil particulates when growers use motorized equipment ( Lemieux et al. , 2004 )

. Gases, such as carbon dioxide ( CO 2 )

, hydrocarbons, other volatil e organic compounds

, and methane, are released through equipment exhaust (particularly diesel exhaust) , disturbance of the soil inducing population changes among the microbial flora, and animal production facilities, while fertilizer applications are associated with release of oxides of nitrogen, particularly during their manufacture ( USDA

NRCS, 2006a ; Zhao, 2007b ; Aneja et al. , 2009 ; Cambra

- Lopez et al. , 2010 ; US

- EPA, 2011b )

. Burning releases smoke, exhaust from motorized equipment may release criteria pollutants, and cropping activities (such as p lanting, tillage, and harvesting ) generate airborne soil particulates when growers use motorized equipment ( Lemieux et al. , 2004 )

. Gases, such as carbon dioxide ( CO 2 )

, hydrocarbons, other volatile organic compounds

, and methane, are released through equipment exhaust (particularly diesel exhaust) , disturbance of the soil inducing population changes among the microbial flora, and animal production facilities, while fertilizer applications are associated with release of oxides of nitrogen, particularly during their manufacture ( USDA

NRCS, 2006a ; Zhao, 2007b ; Aneja et al. , 2009 ; Cambra

- Lopez et al. , 2010 ; US

- EPA, 2011b )

. Aerosols from herbicide, pesticide and fertilizer applications to c rops are another source of molecules that impact air quality

. The effects of aerosols are complex because these various molecules can: (1) drift from the target site, (2) volatilize to increase the area impacted, and (3) adsorb onto soil particles ( Felsot, 2005 ; Hernandez

- Soriano et al. , 2007 )

. Tillage and wind

induced erosio n may lead to suspended soil partic les in the air and adsorbed aerosols becoming airborne ( Felsot, 2005 ; Hernandez

- Soriano et al. , 2007 ) . Vapor aerosol particles contribute to the formation of haze and decrease visibility ( Zhao, 2007a )

. Cotton and soybean fields typically are tilled just prior to planting ( Albers and Reinbott, 1994 )

. Tillage releases particulate matter into the air ( Madden et al.

, 2009 ) as soil is disturbed. Reductions in tillage generate fewer suspended particulates (dust) and lower rates of soil wind erosion ( Lyles and Woodruff, 1962 )

. Tillage also is associated with increased emissions from farm equipment burning fossil fuels

. Reducing the number of times tillage is done thro ugh a growing season reduces these vehicle emissions

. Both of these benefits to air quality are variable and are affected by factors such as soil moisture and the specific tillage regime employed

. The ability of reduced tillage to minim ize the burning of fossil fuels is illustrated in Table 4 , based on the Natural Resource Conservation Service (NRCS) Energy Estimator: Tillage Tool ( USDA

NRCS, 2013a )

. This tool estimates potential fuel savings of 3,010 gallons or 60 % savings per year based upon producing 1,000 acres of no

- till soybean compared to conventional till soybean

47in the Urbana, Illinois, postal code. 5 NRCS is careful to note that this estimate is only approximate because many variables affect an individual operation’s actual savings

. This example, however, illustrates the magnitude of the contribution of minimum tillage to reducing the impact of agriculture on air quality.

Table 4

. Total Farm Diesel Fuel Consumption by Til lage Method

.

Estimate for 1,000

- Acre Soybean Crop (Urbana, Illinois) Consumption by Tillage Method (gallons per year)

Conventional Tillage Mulch

- till Ridge

- till No

- till

Total fuel use 4,980 4,110 3,330 1,970

Potential fuel savings over conventional tillage -- 870 1,650 3,010

Total savings

-- 17% 33% 60%

Source: ( USDA

- NRCS, 2013a )
Prescribed burning is a land treatment, used under controlled conditions, to accomplish resource management objectives

. Open combustion produces particles of widely ranging size, depending to some extent on the rate of energy release of the fire ( US

- EPA, 2011a )

. The extent to which agricultural and other prescribed burning may occur is regulated by individual State Implementation Plans to achieve compliance with the NAAQS

. Prescribed burning of fields is likely occurring only as a pre

- planting option, based on individual farm characteristics.

Growers typically apply pesticides to conventionally grown cotton and soybean by ground spray equipment or aircraft. Both may affect air quality through drift and volatilization to the atmosphere ( Owen, 2008 )

. Drift is defined by the EPA as, “the movement of pesticide through air at the time of application or soon thereafter, to any site other than tha t intended for application” ( Kiely et al. , 2004 ) . Small, lightweight droplets are produced by equipment nozzles; many droplets are small enough to remain suspended in air for long periods of time allowing them to be moved by air currents, until they adhere to a surface or drop to the ground

. The amount of drift varies widely and is influenced by a range of factors, including weather conditions, topography, the crop or area being sprayed, application equipment and methods, and other practices followed by the applicator ( Kiely et al. , 2004 ) . For example, the fine droplet size of p esticides applied through center

- pivot irrigation systems can lead to evaporation and drift unless minimized by addition of Low Elevation Spray Applic ation applicators or Low Energy Precision Application irrigation methods ( New and Fipps, 2000 )

.

5 Postal codes are used in the NRCS Energy Estimator to estimate diesel fuel use and costs in the production of key crops for an area.

48The EPA defines volatilization as the point “when pesticide surface residues change from a solid or liquid to a gas or vapor after an application of a pesticide has occurred.” 6 Volatilization of herbicides and pesticides from soil and plant surfaces introduces the se chemicals into the air

. A long

- term USDA Agricultural Research Service (ARS) study to identify factors that affect pesticide levels in the Chesapeake Bay Region airshed ( USDA

- ARS, 2011 ) has determined that volatilization is highly dependent on exposure of disturbed loose and unstratified (unconsolidated) soils, and variability in measured compound levels is correlated with temperature and wind conditions

. Another ARS study of volatilization of certain herbicides after application to fields has found moisture in dew and soils in higher temperature regimes substantially increases volatilization rates ( USDA

- ARS, 2011 )

. The EPA’s Office of Pesticide Programs (OPP), which regulates the use of pesticides , including herbicides

, in the United States , introduced initiatives to help pesticide applicators minimize of f

target drift

. Currently, EPA

- OPP is evaluating new regulations for pesticide drift labeling, and developing voluntary best management practices (BMPs) to aid in reducing drift, as well as identifying scientific issues surrounding field volatility of conv entional pesticides ( US

- EPA, 2010b ) . Additional information on off

- target movement of pesticides is included in Appendix 7.

Other conservation practices may allow growers to qualify for crop insurance, federal loans, and other beneficial programs ( USDA

- ERS, 2009 )

. Using conservation practices can effectively reduce crop production impacts to air quality through the deployment of windbreaks, shelterbelts, reduced tillage, and cover crop s that promote soil protection on highly erodible lands.

The aspects of air quality discussed in this section, and water in Section 3.3.4, focused on the relatively small

- scale activities occurring in and around cotton and soybean fields. We combine issues related to wa ter and air with a broader, long

- term perspective in the next section by examining aspects of climate change

.

3.3.5 Climate Change

Climate change represents a statistical change in global climate conditions, including shifts in the frequen cy of extreme weather ( Cook et al. , 2008 ) . Agriculture is estimated to contribute roughly six percent of all human

- induced greenhouse gases (GHG ) in the U.S. ( US

- EPA, 2011b ) . The EPA identified CO 2 , methane, and nitrous oxide as the key GHGs affecting climate change ( US

EPA, 2011c )

. Agricultural practices are associated with the production and sequestration of GHG

. Emissions of GHG released during the use of agric ultural equipment (e.g., irrigation pumps and tractors) include carbon monoxide, nitrogen oxides, methane, reactive organic gases, particulate matter, and sulfur oxides ( US

- EPA, 2011b )

. Additional emissions arise from the production a nd delivery of fuels to farms ( West and Marland, 2002 )

. Nitrogen

- based fertilizers a re the largest source of

6 http://www.epa.gov/pesticides/about/intheworks/volatilization.htm

49U.S. nitrous oxide emissions ( US

- EPA, 2011b )

. Nitrous oxide is naturally produced in soils through microbial nitrification and denit rification, and it can be dramatically influenced by fertilization, grazing animals, cultivation of nitrogen

- fixing crops and forage (e.g., alfalfa), retention of crop residues (i.e., no

- till conservation), irrigation, and th e fallowing of land ( US

EPA, 2011b )

. These same agricultural practices can influence the decomposition of carbon

containing organic matter sequestered in soil, resulting in conversion to carbon dioxide and subsequent loss to the atmosphere ( US

- EPA, 2011b )

. A gricultural sources of m ethane emissions are associated primarily with enteric emissions of gas from cattle and manure management . The

c onversion of cropland to p asture increase s carbon and nitrogen sequestration in soils ( US

- EPA, 2011c )

. Agricultural lands afford great opportunities for sequestering carbon (reducing carbon dioxide levels) and r educing or mitigating emissions of other GHGs

. T o a great extent, t he contribution of agricultur al activities to climate change depends on the production practice s employed to grow various commodities, th e region in which the commodities are grown, and the indiv idual choices made by growers.

Three sources of c arbon emissions from tillage practice s have been identified . First is exhaust from machinery for cultivating the land, seco nd is the application of fertilizers and pesticides. The third source is the soil organic carbon that is oxidized following soil disturbance ( West and Marland, 2002 )

. Tillage contributes to GHG emissions by releasing CO 2 previously sequestered in soil. Disruption and exposure of soil promotes CO 2 production by the oxidation of soil organic matter ( Baker et al. , 2005 )

. The carbon footprint for any crop is directly affected by the associated cultivation practice s. For example, cotton cultivation is estimated to produce higher total CO 2 emissions than soybeans ( Nelson et al. , 2009 )

. On

- site emissions can be reduced by half for

some crops by replacing convention al with no

- till systems agriculture ( Nelson et al. , 2009 ) . In general, conservation tillage may decrease the rate of loss of s oil organic carbon ; however, CO 2 emissions during pesticide and fertilizer application may negate the increased carbon sequestered in soils ( West and Marland, 2002 ) . The uncertainty inherent in these comparisons a rises from industry

- wide estimates based on production being juxtaposed against estimates based on
grower

- reported practices.

The EPA identified regional differences in GHG emissions associated with agricultural practices on differ ent soil types, noting that carbon emission rates differ between mineral soils and organic soils ( US

- EPA, 2011b ) . Mineral soils contain from 1 to 6% organic carbon by weight in their natural state, but organic soils may contain as much as 20% carbon by weight ( US

- EPA, 2011b )

. Up to 50% of the soil organic carbon in mineral soils can be released to the atmosphere when land is initially converted to crop production. Over time, the soil establishes a new equilibrium that reflects a balance between carbon from decaying plant matter and organic amendments, and carbon released by microbial decomposition. On

- site emissions can be reduced by half for some
crops by replacing conventional with no

- till systems agriculture ( Nelson et al. , 2009 ) . In general, conservation tillage may decrease the rate of loss of soil organic carbon, however, carbon emitted during pesticide and fertilizer inputs may negate the increased c arbon sequestered in soils ( West and Marland, 2002 ; US

- EPA, 2011b )

. Organic soils continue to release carbon to the atmosphere for a longer period of time than mineral

- based soils ( US

- EPA, 2011b ) . Mineral soils contain from 1 to 6% organic carbon by 50weight in their natural state, but organic soils may contain as much as 20% carbon by weight ( US

- EPA, 2011b ) . EPA estimated that mineral soil

- based cropland areas sequestered over 45.7 Tg CO 2 Eq 7 in 2008. Carbon emissions from croplands with organic soils were estimated to be 27.7 Tg CO 2 Eq ( US

- EPA, 2011b ) . The highest rates of carbo n sequestration occurred under conservation tillage, particularly in Midwest regions where mineral

- based soils prevail ( US

- EPA, 2011b )

. Between 1980 and 2011, total GHG are reported to have increased by 10% for cotton production and 13% for so ybean production ( Field

- to

- Market, 2012 )

. Agriculture

- related GHG production will not change considerably unless large amounts of crop plantings produce changes in measureable concentrations of these gases ( US

- EPA, 2011b ) . For example, the EPA identified a net decline in the sequestration of carbon in soil over an 18

- year period. The EPA attributed this to the impact of the Conservation Reserve Program which encouraged growers to take marginal lands out of production ( US

- EPA, 2011b )

. To a certain extent, the EPA also noted that adoption of conservation tillage resulted in increases in carbon sequestration on those croplands ( US

- EPA, 2011b ) . The highest rates of carbon sequestration in mineral soils occurred in the Midwest, which is the region with the largest area of cropland managed with conservation tillage ( US

EPA, 2011b ) . This is in contrast to the highest emission rates from organic soils noted in the southeastern coastal region, the areas around the Great Lakes, and the central and northern agricultural a reas along the West Coast ( US

- EPA, 2011b )

. However, conclusions about total carbon sequestration remain somewhat questionable , since the use of uniform protocol s for measurement of changes may reduce the significan ce of some of the differences that have been observed ( Baker et al. , 2007 ; Maraseni and Cockfield, 2011 )

.
Global climate change may also affect agricultural crop production ( Backlund, 2008 )

. These potential impacts on the agro

- environment and individual crops may be direct, including changing patt erns in precipitation, temperature, and duration of growing season, or may cause indirect impacts influencing weed and pest pressure ( Rosen zweig et al. , 2001 ; Schmidhuber and Tubiello, 2007 )

. A recent Intergovernmental Panel on Climate Change (IPCC) forecast ( IPCC, 2007 ) for aggregate North American impacts on agriculture from climate change proj ects yield increases of 5 to 20% for this century. The IPCC report notes that certain regions of the U.S. will be more adversely impacted because water resources may be substantially reduced. In a ddition, the current range of weeds and pests of agriculture is expected to change in response to climate change ( USGCRP, 2009 )

. While agricultural impacts on existing crops may be substantial, North Ameri can production is expected to adapt with improved cultivars and responsive farm management ( IPCC, 2007 )

. Climate change may have a positive impact on agriculture

. However, the extent of positive effects on agriculture from climate cha nge is highly speculative, and will not be observed in all growing regions. For example, the IPCC indicates that certain regions of the U.S. will be

7 The global warming potential of greenhouse gases is measured against the reference gas CO 2 ; reported as teragrams (millions of metric tons) of CO 2 Equivalent ( Tg CO 2 Eq )

.

51negatively impacted by a substantive decline in available water resources . The IPCC also predicts potential climate change in North America may increase crop yields by 5 to 20 percent during the current century ( Field et al. , 2007 )

.

3.3.6 Land Resources

According to the Food and Agricultural Organization of the United Nations (FAO), land cover is the observed physical cover on the surface of the earth as seen from the ground or through remote sensing. It includes vegetation (natural or planted) and human constructions such as buildings and roads ( FAO, 1997 )

.
Land use refers to the function or the purpose of the land. Therefore, land use can be defined as

an activity or series of activities undertaken to produce one or more goods or services ( FAO, 1997 )

. The FAO also indicates that a given land use may take place on one or more parcels, and several different uses may occur on a single parcel. This definition provides a b asis for precise and quantitative economic and environmental impact analyses of different uses.

Land cove r data were obtained for each Level III ecoregion using USDA

- NASS CropScape ( USDA

- NASS, 2013j ) . The statistical estimates for acreage as generated by CropScape are considered as raw numbers requiring a correction factor to account for statistical bias ( USDA

NASS, 2013j ) . However, the bia s in estimates of area for different land covers is proportionately equal, enabling comparisons of the area of different land cover classes relative to each other.

USDA

- NASS uses the 2006 USGS National Land Cover Dataset ( USGS

- NLCD, 2006 ) to help identify non

- agricultural land cover ( USDA

- NASS , 2013j )

. Table 5 compares the land cover groups and classes used by the National Land Cover Dataset to those used in this analysis, and lists the class number use d in each categorization. De finitions of land classes can be found in NLCD, 2013 ( National Land Cover Database, 2014 )

.
Table 5

. Comparison of NLCD 2006 Land Cover Groups with Classes in This Document. National Land Cover Dataset ( NLCD 2006 ) This Document

Water : Open water (11) Perennial ice/snow (12) Water (1)

Water (1)
Developed : Open space (21) Low Intensity (22) Medium Intensity (23) High Intensity (24) Developed (2)

Developed (2)

Barren (31) Barren (3)

52National Land Cover Dataset ( NLCD 2006 ) This Document

Forest : Deciduous (41) Evergreen (42) Mixed (43) Fores t : Deciduous (4a) Evergreen (4b) Mixed (4c)

Shrubland (52) Shrubland (5)

Herbaceous: Grassland/Herbaceous (71) Herbaceous: Grassland/Herbaceous (6)

_____ Pasture and Hay (7) (excluding alfalfa)

Planted/Cultivated : Pasture/Hay (81)

(including alfalfa) Cultivated Crops (82)

(including orchards; vineyards) Cropland : Orchards/ Vineyards (8a) Row crops (8b) (including alfalfa; non

- forestry trees) Fallow (8c)

Wetlands : Woody (90) Herbaceous (95) Wetlands (9)

Dominant vegetation types vary throughout the United States; these are described by region in the summary that follows:

Region A: cropland and forest are co

- dominant, accounting for one

- third of land co ver each, followed by pasture/hay and developed land at roughly 10 % each

. Region B: cropland is dominant, accounting for one

- third of land cover, forest covers 27 % , and pasture/hay , developed land, and wetlands each cover about 10 %.

Region C: cropland is dominant, accounting for more than 50 % of land cover, with roughly equal amounts of forest and developed land (15 % ), followed by pasture/hay at 11 %.

Region D: forest is dominant, accounting for nearly 40 % of land cover, followed by cropland and wetlands at approximately 15 % each and developed land at 11 %.

Region E: forest is dominant, accounting for about 40 % of land cover, while cropland and pasture/hay each account for approximately 25 % of land cover

. Region F: cropland is dominant, accounting for slightly less than 40 % of land cover, while forest covers 20 % and wetland covers 17 % of the region.

Region G: cropland is dominant, accountin g for about 55 % of land cover, while pasture/hay and grassland account for about 10 % each

.

53Region H: grassland and cropland dominate land cover, accounting for more than 40 % each

. Region I: cropland is dominant, accounting for about 45 % of land cover, while pasture/hay accounts for 30 % and grassland for about 15 %.

Region J: shrubland is slightly dominant, accounting for slightly more than 35 % of land cover, followed closely by cropland at slight ly more than 30% and grassland at 25%.

Region K: Cropland and pasture/hay are co

- dominant, each accounting for slightly less than 25 % of land cover, followed by shrubland, grassland, and wetland at roughly 12 % each

. Region L: Desert shrubland is over whelmingly dominant, accounting for 85 % of land cover, while developed land accounts for 5 % and cropland for about 3 %.

Region M: Cropland is dominant, accounting for 70 % of land cover, followed by grassland at about 20% of land cover

. Land cover compositio n varies across the affected environment ( Table 6 ). For example, developed land ranges from 5 to 15 % of land cover among the regions, accounting for 10 % or more of the land cover in R egions A, B, C, D, and K. Central plains R egions H, I, J, and L in the Central Plains, Texas, and Arizona have much lower amounts of developed land

. Wetlands account for 17 % of the Mississippi Alluvial ( R egion F), and 16 % of coastal R egion D, and 13 % of coastal R egion K, but are present in much lower amounts in all other regions.

Table 6

. Land Cover Composition by Region. Land Cover Composition Percent* Composition by Region
Region

A B C D E F G H I J K L M

1. Water 3 3 1 2 2 3 2 4 1 <1 2 <1 <1
2. Developed 10 10 15 11 8 6 7 4 5 5 13 5 9

3. Barren <1 <1 <1 <1 <1 <1 <1 <<1 <<1 <1 1 2 1

4a. Deciduous 26 26 16 15 38 13 7 1 3 1 2 <<1 <<1
4b. Evergreen 1 1 <1 22 1 5 <<1 <<1 <<1 1 1 <<1 <<1

4c. Mixed 2 <1 <<1 2 < 1 2 <1 <<1 <<1 <<1 <1 <<1 <<1

5. Shrubland 5 <1 <<1 5 <1 5 <<1 <<1 <<1 37 12 85 <1

6. Grassland 0 5 1 4 1 <1 11 43 13 25 11 1 18

7. Pasture/hay 10 11 11 6 23 11 13 6 31 <<1 23 <1 <1

54Land Cover Composition Percent* Composition by Region
Region

A B C D E F G H I J K L M

8a. Orchards 1 <1 <<1 <1 <<1 <1 <<1 <<1 <<1 <<1 <1 <1 27

8b. Row crops 33 33 53 15 25 34 56 40 43 30 18 3 30

8c. Fallow 1 <1 <<1 3 <<1 4 <1 1 3 2 5 2 13

9. Wetlands 7 9 2 16 1 17 4 2 1 <<1 13 1 2

*Rounded to nearest whole percent; totals may not add to 100 % because of rounding errors. Source: USDA

- NASS CropScape land cover data for 2012 ( USDA

- NASS, 2013e )

. The major land use s of the affected environment are agriculture (including crop cultivation, pasture and rangeland, animal production, forestry and logging), industrial, housing/residential (including urban, suburban and rural), and recreational and tourism. Wildlife habitat loss and urban sp rawl are en vironmental concerns throughout the country. Th e relative proportions of major land uses vary between and within regions , as described below and in Table 7

. Data on

an imal production is from the 2007 Census of Agriculture ( USDA

- NASS, 2009d )

. Region A : Principal crops include corn, soybean, and alfalfa. Grain production is primarily for dairy cattle. Hay and alfalfa cultivation are roughly equivalent. Orchards, vineyards and vegetable farming (particularly cabbage) are also important in New York. Other major land use s include urban deve lopment, industry, recreation, and tourism.

Region B : Agricultural uses include cultivated cropland, pasture, livestock and dairy farming. Corn, soybean, and alfalfa are the principal crops, along with some wheat. P otatoes and
vege tables are other important crops in the eastern part of the region. Dairy farming is prevalent in Wisconsin. Other land use s peat harvesting, industrial sand and gravel mining, suburban and residential land uses, recreation and tourism ( USGS, 2013 )

. Region C : Agriculture and cropland is extensive throughout the region. The predominant crops

are corn and so ybeans. Less abundant crops include wheat, alfalfa, dry beans, and squash. In Wisconsin, most of the cropland is devoted to forage and feed grains to support dairy operations. Livestock and egg production are common. There are several large urban and industrial centers. Smaller urban, suburban and rural residential land use s occur throughout the region.

Region D : In the north, l and use is primarily agriculture with urban and suburban industrial uses. Soybeans, feed, and forage crops are prevalent. Hay production areas are approximately equivalent to corn production areas. Nurseries for horticultural products and Christmas tree farms oc cupy some areas. Pine plantations are particularly prevalent to the south. Predominant crops in the region are soybean, corn, cotton, wheat, and peanuts. Other important crops include tobacco, pecans, sweet potatoes, peaches, and watermelon. The remainder of the region includes a mosaic of cropland, pasture, woodland and forests. There is also a high density of

55poultry and hog production in some parts of the region. Land use in coastal areas within the region is characterized by a high density of urban and suburban development with recreation and tourism.

Region E : Land use in the north and west is dominated by cropland agriculture and pasture. The east and south tends to have a higher diversity of land use s that includes cropland, pasture, forest, and woodlots with some expanding urban areas. Corn and soybean are the predominant crops. Wheat is also an important crop in the region, and tobacco is a major crop in Kentucky. Livestock production, poultry farming, and egg prod uction are also common. Mineral extraction is important in some parts of the region. This includes some oil and gas production in the south and east. Surface and underground coal mining are important industries in western Kentucky, southern Illinois and In diana ( USGS, 2013 )

, and these areas are associated with substantially degraded downstream wetland habitat and water quality.

Region F : Except for the southern

- most portion of the Mississippi Alluvial Plain (CEC/EPA Ecoregion 8.5.2), most of the region is cropland or pasture. Soybean is the predominant crop. Rice is another major crop. More than 70% of U.S. rice is produced in this region. Other important crops include corn, cotton, wheat, suga rcane, and sweet potatoes. About 85% of U.S. aquaculture is conducted in this region. Principal products are catfish and crawfish from commercial ponds. Important minerals are ball clay mined in western Kentucky and Tennessee ( USGS, 2013 ) , and oil and gas production in the southern part of the region.

Region G: This is one of the most productive agricultural areas in the world. Cropland is extensive, exceeding 75 % of land use in some parts of the region. Principal crops are corn and soybean. Other important crops include wheat, canola and rapeseed, sunflower, hay and alfalfa, sugar beets, dry beans and peas, and flaxseed. Hog, cattle, and egg production are also prominent in the region.

Region H : The primary land use s in this region are rangeland for cattle grazing and cropland. The dominant crop is wheat. Other major crops are corn, soybean, sun flower, alfalfa, flaxseed, and lentils. Hay production acreage is about 85 % of that used in corn production.

Region I : Cropland (dryland and irrigated) and rangeland for cattle grazing are the principal land

use s. Wheat and corn are the primary crops. Soybean and sorghum are also important. Livestock cattle production also is common.

Region J : Most of the region is devoted to cropland, pasture, and rangeland. Major crops include wheat and cotton. Other major crops are corn and sorghum. Oil and gas production are prominent in the southwest portion of the region, largely non

- overlapping with crop cultivation, and concentrated animal feeding operations (primarily cattle) are also economically importan t ( USDA

- NRCS, 2006d )

. Region K : Much of the region is cropland. Sorghum is the dominant crop. Cotton, corn, rice, and citrus are also important. Grasslands and shrub rangeland provide fodder for livestock grazing . Salt ( USGS, 2013 ) , oil and gas are important mineral production activities. Increased urbanization and industrialization are recent trends in the region.

56Region L : M ultiple areas of intensive, irrigated cropland are dominated by alfalfa

, cotton , and wheat production . The region is also a major producer of lettu ce, celery, melons, and greens despite being highly susceptible to droughts

. Much of the land is federally owned, either as military lands or national parks, monuments, and wildlife refuges. R apid urbanization around the larger communities is greatly reducing cropland acreage.

Region M : Land use is dominated by agriculture. Nearly half the land in the region is cropland. Three quarters of it is irrigated. A very wide variety of crops are grown. The major crops by land area are almonds, wheat, alfalfa, cotton, corn, and grapes. Other major crops, often constituting more than 50% of U.S. production, include walnuts and pistachios, pomegranates, nectarines, garlic, tomatoes, camelina, melons, lettuce, and olives. Cattle a nd dairy production is largely feedlot based. Urban areas and oil and gas production are also important.

Table 7

. Major Cultivated Crops by Region in 2012 1

.

Region Crop Cropland

As a Percent of Total Cropland Acreage in the Region 2 In Region As a Percent of Total

U.S. Acreage



### A Corn Soybean Alfalfa Wheat Apples Cabbage 48% 18% 18% 6% 3% 1% 1% <1%

1% <1% 8% 38%



### B Corn Soybean Alfalfa Wheat Potatoes Asparagus Cucumbers Celery 53% 26% 15% 3% 1% <1% <1% <1% 8% 5% 13% 1% 10% 35%

29%



### C Corn Soybean Wheat Alfalfa Dry beans Cucumbers Gourds Pumpkins 53% 40% 3% 3% 1% <1% <1% <1% 19% 18% 2% 6% 11% 47% 39% 33%

57Region Crop Cropland

As a Percent of Total Cropland Acreage in the Region 2 In Region As a Percent of Total

U.S. Acreage



### D Soybean Corn Cotton Wheat Peanuts Tobacco Pecans Sweet Potatoes Peaches Watermelon 32% 28% 21% 15% 10% 1% 2% <1% <1% <1% 5% 4% 20% 3% 79% 76% 63% 45% 42% 32%



### E Corn Soybean Wheat Cotton Alfalfa Gourds 52% 46% 7% 1% <1% <1% 8% 9% 2% 1% <1% 59%



### F Soybean Corn Cotton Rice Wheat Sweet Potatoes Sugarcane 51% 20% 12% 11% 10% <1%

1% 12% 4% 15% 70% 3% 36% 22%



### G Corn Soybean Wheat Alfalfa Canola Sugarbeets Dry beans Flaxseed 45% 40% 8% 2% 1% 1% 1% <1% 34% 39% 11% 8% 61% 54% 41% 37%



### H Wheat Corn Soybean Sunflower Alfalfa Flaxseed Lentils 34% 26% 20% 6% 3% 2% 1% 5% 2% 2% 29% 2% 47% 28%

58Region Crop Cropland

As a Percent of Total Cropland Acreage in the Region 2 In Region As a Percent of Total

U.S. Acreage



### I Wheat Corn Soybean Sorghum Alfalfa 33% 34% 23% 9% 3% 12% 7% 6% 26% 4%



### J Cotton Wheat Sorghum Corn Peanuts 54% 39% 6% 2% <1% 47% 8% 11% <1% 2%



### K Sorghum Cotton Corn Rice Citrus 48% 26% 13% 6% 6% 19% 5% <1% 6% 9%



### L Alfalfa Cotton Wheat Lettuce Barley Celery Misc. Fruit/Vegetable Honeydew melons Greens 40% 25% 12% 6% 6% <1% 2% <1%

1% 2% 2% <1% 65% 2% 59% 30% 30% 25%

59Region Crop Cropland

As a Percent of Total Cropland Acreage in the Region 2 In Region As a Percent of Total

U.S. Acreage



### M Almonds Wheat Alfalfa Grapes Cotton Corn Pomegranates Pistachios Nectarines Garlic Tomatoes Camelina Cantaloupes Walnuts Honeydew Melons Lettuce Olives 21% 14% 13% 13% 10% 9% 1% 5% <1% <1% 5% 3% <1% 2% <1% <1%

1% 69% 1% 3% 42% 3% <1% 97% 94% 85% 84% 53% 52% 45% 43% 36% 32% 25%

1 Statistics for hay not included

. 2 Som e regional totals may be less than or more than 100 % because of rounding error s or double cropping

practices.
By i dentifying land use s and the underlying soil parameters within the affected environment we can understand how to manipulate these environmental features to produce crops. Growers must use the land resources available to them and modify that environment to successfully produce crops. In Section 3.5, we review major agronomic methods important for cotton and soybean production. These include aspects of tillage, crop rotation , and agronomic inputs such as pesticides.

3.4 Biological Resources

Biological resources include the animal and plant communities associated with the major cotton and soybean cultivation areas within Regions A

- M, as described in Table 2 . Soil microorganisms are also reviewed in this section.

3.4.1 Animal Communities

Animal communities in this discussion include wildlife species and their habitats. Wildlife refers to both native and introduced species of mammals, birds, amphibians, reptiles, invertebrates, and fish/shellfish

. Wildlife may feed on cotton and soybean plants in the field and/or use the habitat surrounding cultivated fields for nesting and refuge

. Mammals and birds may seasonally
60consume soybean and occasionally cotton; invertebrates can feed on the plant during the entire growing season

. The function and integrit y of ecosystems and the wildlife populations they support influences how agricultural and other lands are managed.

The environment surrounding soybean and cotton fields may serve as important food sources and habitat for mammals, birds, fish, and insects. Soybean fields may be bordered by other soybean fields, or they may be surrounded by other agricultural crops, woods, pasture/grassland, or aquatic environments. Regardless of the agricultural operation, animals and insects in adjacent environments have th e potential to be impacted directly by fertilizers, pesticides, and erosion or indirectly from the effects on the habitat surrounding the agricultural fields.

There are several crop management strategies that can increase the value of crop fields to wildli fe including conservation tillage and no

- till practices. Conservation tillage practice s benefit biodiversity on agricultural land due to decreased soil erosion, improved surface water quality, retention of vegetative cover, increa sed food sources from crop residues, and increased populations of invertebrates ( Landis et al. , 2005 ; Sharpe, 2010b ) . Crop rotations also can reduce the likelihood of crop disease, insect and weed pests, and pesticide use which can benefit wildlife ( University of California, 2008b )

. Birds, Mammals, and Reptiles Agricultural fields have the potential to provide foo d, water, and habitat for birds but each landowner’s farming practices and the crop type determines the value of these lands to wildlife

. In the Cotton Belt, birds generally avoid cotton fields, although some generalist species (geese, egrets, gulls, and blackbirds) may periodicall y be observed in cotton fields ( Butcher et al. , 2007 )

. Geese (Canada [ Branta c anadensis ] , snow [ Chen caerulescens ] , and greater white

- fronted [ Anser albifrons ] geese} and the northern pintail ( Anas acuta ) have been observed foraging in fallow or disked cotton fields that were flooded to enhance habitat for nonbreeding waterfowl during the fall or winter ( Fleskes et al. , 2003 ; Butcher et al. , 2007 )

. Cattle egrets ( Bubulcus ibis ) use cotton fields in the summer, which could be in response to increased invertebrate densities ( Mora, 1997 )

. Waterbirds (e.g., geese, cranes, and shorebirds) and landbirds (e.g., red

- winged blackbirds ( Agelaius phoeniceus ), purple martins ( Progne subis ), and bank swallows ( Riparia riparia ) are common visitors to soybean fields

. Migratory birds have been observed feeding on spilled soybeans following crop harvest ( Galle et al. , 2009 ) . H owever, the energy value of soybeans is low, so most birds only use soybeans to supplement their diet

. Preferred diets include the consumption of nearby agricultural crops, especially corn and sunflower seeds, and the consumption of invertebrates and weed seeds in the soybean fields ( Butcher et al. , 2007 )

. Migratory birds may be present in soybean fields year

- round.

Some birds occurring within the affected environment that tend to be more localized include :

• Region A: wild turkey, waterfowl, ruffed grouse, woodpecker, warbler, screech owl

• Region B: wild turkey, turkey vulture

• Region C: Canada goose, sandpiper, sparrow

• Region D: wild turkey, herons, cardinal

61• Region E: cardinal, bobwhite quail, Carolina chickadee

• Region F: wild turkey, migratory waterfowl, mourning dove, Carolina wren, wood thrush, cormorants, egrets, herons ( widespread loss of forest and wetland habitat , has reduced bird populations but this region remains a major migrat ory flyway)

• Region G: Canada goose, bobwhite quail, sharp

- tailed grouse, pheasants ( this region is a major breeding habitat for waterfowl and other birds )

• Region H: golden eagle, ferrugin ous hawk, sage grouse

• Region I: numerous waterfowl (this is a major migratory flyway)

• Region J: turkey vulture

• Region K: waterfowl, geese, oriole, prairie chicken

• Region L: migratory waterfowl, chickadee, falcon, raven, thrasher

• Region M: wintering waterfo wl, Nuttall’s woodpecker, yellow

- billed magpie

Rodents, such as mice or squirrels, may seasonally feed on soybean seeds

. During the winter months, leftover and unharvested soybeans provide a food source for wildlife. White

- tailed deer and groundhogs ( Marmo ta monax ) feed on soybeans and cause soybean damage, while eastern cottontail ( Sylvilagus floridanus ), raccoon ( Procyon lotor ), squirrels, and other rodents (such as ground squirrel s ) also feed on soybeans, but their damage is of less substan ce ( MacGowan et al.

, 2006 )

. Deer may cause dama ge by browsing in soybean fields for forage , and in some areas, the state may issue licenses to kill deer outside the hunting season to reduce crop damage ( Garrison and Lewis, 1987 ; Berk A, 2008 )

. Deer also may feed on seed left after harvest

. In Georgia, feral hogs ( Sus scrofa ) have damaged soybean fields through rooting and feeding ( Kammermeyer et al. , 2003 ) . S everal mammals are widespread through many or most of the affected environment

. These include white

- tailed deer ( R egions A

- I; K)

, mule deer ( R egions L and M), coyotes ( R egions A

- C ; G

- M), foxes ( R egions A

- G ; I), raccoons ( R egions A

- G; J), red and/or gray squirrels ( R egions A

- D ; F

- H), bobcats ( R egions C

- F; H

- L), and cottontail rabbits and/or jackrabbits ( R egions D ; G

- J, M).

Some mammals occurring within the affected environment that tend to be more localized include :

• Region A: black bear, chipmunk, woodchuck, wolf in northern areas, beaver in the south

• Region B: beaver, otter, mink

• Region D: black bear, chipmunk

• Region E: badger, weasel in the north and west

• Region G: badger and skunk in southern areas

• Region H: pronghorn antelope and prairie dogs

• Region I: pronghorn antelope

• Region J: ringtail cat, armadillo, skunk, gopher

• Region K: ringtail cat, armadillo, ocelots

• Region L: pronghorn antelope, elk, coug ar, chipmunk, pika, bats

• Region M: pronghorn antelope, elk, kit fox, ground squirrels, kangaroo rat

Some reptiles occurring within the affected environment that tend to be more localized include :

• Region D: box turtle , garter snake, rattlesnake 62• Region E: snapping and box turtles, rattlesnake, copperbelly water snake

• Region G: this region is a major breeding habitat for waterfowl and other birds, including Canada goose, bobwhite quail, sharp

- tailed grouse, and pheasants

• Region H: rattlesnakes

• Reg ion J: Texa s horned lizard

• Region K: alligator

• Region M: giant garter snake

Invertebrates Invertebrate communities in agricultural fields represent a diverse assemblage of feeding strategies including predators, crop

- feeders, saprophages, parasites, and polyphages ( Stevenson et al. , 2002 )

. Numerous insects and related arthropods perform valuable functions: they pollinate plants, contribute to the decay and processing of organic matter, reduce weed seed populations through predation, cycle soil nutrients, and attack other insects and mites that are considered to be pests. Although many arthropods in agricultural settings are considered pests, there are many beneficial arthropods which are natural enemies of both weeds and insect pests ( Landis et al.

, 2005 )

. Terrestrial invertebrate food sources are likely impacted by insecticides used in soybean fields (including nontarget invertebrates)

. H owever, crop insect pests are considered less problematic than weeds in U.S. soybean production ( USDA

- NASS, 2009e )

. For the purposes of environmental risk assessment , some high

- profile or representative invertebrate species, such as honey bees, earthworms, and butterflies, are gener ally studied more thoroughly than others

. Risk is a function of the toxicity of the compound to a given species and its exposure to the compound.

In order of importance, the most damaging arthropod pests in soybean in 2012 in the southern U.S. were corn ea rworm, soybean looper, and stink bugs ( Musser et al. , 2013 )

. The soybean cyst nematode is a roundworm which is an important pest of soybean fie lds in several states, especially Nebraska and Minnesota ( University

- of

- Minnesota

- Extension, 2011 )

. Major arthropod insect pests of soybean and the states in whi ch they are distributed are shown in Table 8

.
Table 8 . Major Arthropod Pests of Soybean

. Pest Scientific Name States Armyworm, beet Spodoptera exigua AR, NC, SC, TX, VA Armyworm, fall Spodoptera frugiperda AR, SC, TN, VA Armyworm, southern Persectania ewengii AR Armyworm, yellowstriped Spodoptera ornithogallii AR, NC, VA Armyworms Noctuidae MI, ND Beetle, bean leaf Cerotoma trifurcata AR, IA, IL, IN, KS, KY, MI, MN, MO, NC, ND, NE, OH, SC, SD, TN, VA Beetle, Japanese P opillia japonica IA, IL, IN, KY, MN, MO, NY, OH, PA, SC, TN

63Pest Scientific Name States Beetle, Mexican bean Epilachna varivestris IL, IN, KY, MO, NC, OH, PA, TN, VA Beetle, seed corn Stenolophus lecontei IN, KS Beetle, spotted cucumber Diabrotica undecimpunctata AR Beetles, blister Epicauta spp. AR, IA, IL, KS, MO, TN, VA Beetles, Colaspis Colaspis spp. AR, IA, MO, NC Beetles, flea Chrysomelidae KS, ND Borer, common stalk Busseola fusca VA Borer, lesser cornstalk Elasmopalpus lignosellus NC, SC, TX Borer, soybean stem Dectes texanus AR, IA, KS, NC, NE, SC, TX, VA Bug, kudzu bug Megacopta cribraria VA Bug, tarnished plant Lygus lineolaris ND Bugs, stink Pentatomidae AR, IA, IN, KY, MO, NC, NE, SC, TN, TX, VA Caterpillar, alfalfa Colias eurytheme AR, NE Caterpillar, saltmarsh Estigmene acrea AR, MN, NC, TX, VA Caterpillar, thistle Vanessa cardui AR, IA, MN, ND, NE Caterpillar, velvetbean Anticarsia gemmatalis NC, ND, SC Caterpillar, woolly bear Pyrrharctia isabella MN, TX, VA Caterpillar, yellow woolly bear Spilosoma virgnica NE Corn earworm Helicoverpa zea AR, IL, MO, NC, SC, TN, TX, VA Cutworms Noctuidae AR, IA, IL, IN, KY, MI, MN, ND, TN, TX, VA Grasshoppers Acrididae AR, IL, IN, KY, MI, MN, MO, NC, ND, OH, SC, SD, TN, VA Green cloverworm Hypena scabra AR, IN, KY, MI, MN, MO, NC, ND, NE, OH, PA, SC, TN, VA Imported longhorn weevil Calomycterus setarius NE Looper, cabbage Trichoplusia ni MO, ND, NE Looper, soybean Pseudoplusia includens AR, IA, KY, MI, NC, SC, TN, VA Potato leafhopper Empoasca fabae IL, IN, MN, ND, NE, VA Seed corn maggot Delia platura IA, IN, KS, KY, MI, MN, MO, ND, NY, PA, VA

64Pest Scientific Name States Silverspotted skipper Epargyreus clarus NC, VA Soybean aphid Aphis glycines IA, IL, IN: KS, KY, MI, MN, ND, NE, NY, OH, SD, TN, VA Soybean leaf miner Odontota horni IA, NE Spider mites Tetranychidae IA,IL, IN, KY, MI, MN, MO, ND, NE, NY, OH, SC, SD, VA Threecornered alfalfa hopper Spissitulus festinus AR, KY, SC, TN, TX, VA Thrips, especially soybean thrips Thysanoptera IN, MO, NC, NE, SD, VA Tobacco budworm Heliothis virescens SC Variegated leafroller Platynota flavedana AR Webworm, alfalfa Loxostege commixtalis ND Webworm, garden Achyra rantalis AR, MN, MO White grubs Larvae of Scarabaeidae AR, IN,MN, MO, NC Whiteflies Aleyrodidae NE Wireworms Elateridae IN, MI, ND
Sources: ( Thomas, 1993 )

, ( Station, No Date )

, ( Moechnig et al. , 2013 )

, ( University of Nebraska, 2013 )

, ( University of Kentucky )

, ( Service, 1999 )

, ( University

- of

- Illinois

- Extension )

, ( Knodel et al. , 2013 )

, ( Tennessee, 2014 )

, ( Herbert et al. , No Date )

, ( Whitworth et al. , 2014 )

, ( Service, No Date )

, ( Greene, 2014b )

, ( Gouge et al. , No Date )

, ( Akin, 2009b ) ; ( Extension, 2013 ) ; ( Gesell and Calvin, 2000 ) ; ( Hammond et al. , 2009 )
The most damaging arthropod pests in cotton fields in the U nited S tates in 2012 were:

1. Thrips (>8 million acres infested); 2. Bollworms and budworms (>6 million acres infested); 3. Lygus spp. (>5 million acres infested): 4. Aphids (> 5 million acres infested); 5. Cotton fleahopper (> 4 million acres infested) ( Mississippi State University, 2013 )

. Major arthropod pests of cotton and the states in which they are distributed are shown in Table 9

.
Table 9

. Major Arthropod Pests of Cotton

. Pests Scientific name States Aphid, cotton Aphis gossypii AR, AL, CA, FL, LA, MO, MS, NM, OK, SC, TX Aphid, cowpea Aphis craccivora AZ, CA, NC Armyworm, Beet Spodoptera exigua AR, AL, CA, GA, LA, MO, MS, NC, NM, OK, SC, TX Armyworm, fall Spodoptera frugiperda AR, AL, GA, LA, MO, MS, NC, SC, TX
65Pests Scientific name States Armyworm, southern Spodoptera eridania AR Armyworm, yellowstriped Spodoptera ornithogalli AR, AL, MO, MS, NC, TX Boll weevil Athonomus grandis grandis AL, GA, MS, NC, OK, TX Bollworms Helicoverpa punctigera, Helicoverpa armigera AR, GA, KS, LA, MO, MS, NC, NM, OK, TX Common stalk borer Papaipema nebris AL Corn earworm Helicoverpa zea AL, GA, SC Cotton fleahopper Pseudatomoscelis seriatus KS, LA, MO, OK, SC, TX Cotton leaf perforator Bucculatrix thurberiella TX Cotton square borer Strymon melinus TX Cotton stainer Dysdercus suterellus TX Cutworms Agrotis spp. AL, GA, LA, MO, MS, NC, TX European corn borer Ostrinia nubilalis AL, MO, MS Flea beetles Chrysomelidae AZ, MO Grasshoppers Brachystola magna, Melanoplus spp. AR, NM, OK, TX Leafroller, omnivorous Platynota stultana TX Leafroller, variegated Platynota flavedana MO Leafworm, Brown Cotton Acontia dacia TX Leafworm, cotton Alabama argillacea AL, TX Loopers Geometridae AR, AL, GA, LA, MO, MS, NC, OK Pink bollworm Pectinophora gossypiella CA, MS, TX Plant bug, clouded Neuroculpus nubilus AR, TX Plant bug, tarnished Lygus lineolaris AR, AL, AZ, CA, FL, GA, KS, LA, MO, MS, NC, NM, OK, SC, TX Saltmarsh caterpillar Estigmene acrea AR, MO, TX Spider mites Tetranychidae AR, AL, CA, GA, LA, MO, MS, NC, OK, SC, TX Stink bugs Reduviidae AR, AL, CA, LA, MO, MS, NM: SC, TX

66Pests Scientific name States Thrips Frankliniella fusca, others AR, AL, CA, GA, KS, LA, MO, NC, NM, OK, SC, TX Tobacco budworm Heliothis virescens AL, LA, MO, MS, NC, NM, OK, SC, TX Vegetable weevil Listroderes costrirostris obliquus AR Whiteflies Bemisia tabaci , others AZ, AL, CA, GA, LA, MO, MS, NM, SC, TX Whitefringed beetles Naupactus spp. FL
Sources: ( Akin, 2009a )

, ( Bohmfalk et al. , 2011a )

, ( Carlson and LaForest, 2010 )

, ( North

- Carolina

- Cooperative

Extension, 1994 )

, ( Mossler, 2013 )

, ( Williams, 2013b )

, ( University

- of

- Arizona

- Cooperative

- Extension, 2001 )

, ( Schowalter, 2014 ) ; ( Entomology ) ; ( Greene, 2014a ) ; ( Boyd et al. , 2004a ) ; ( Freeman, 2012 ) ; ( Franke e t al. )
Insect pests are managed during the growth and development of both crops to enhance yield ( Higley and Boethel, 1994 ; Aref and Pike, 1998 ) . This includes scouting for pests, establishing action thresholds beyond which treatment is required, and spraying with insecticides

. In 2013, approximately 77% of acreage planted in cotton was sprayed with insecticide ( Williams, 2013a )

. Insects and other invertebrates can be beneficial to soybean and cotton production, providing services such as nutrient cycling and preying on plant pest s

. Table 10 lists the major beneficial arthropods in soybean and cotton fields.

Table 10

. Major Beneficial Arthropods in Soybean and Cotton
Cotton Soybeans Species or family Controls Species or family Controls Honey bee ( Apis mellifera) Pollinator

Predators Predators Ants (Formicidae) Bollworm eggs and larvae Ground beetles (Carabidae) Aphids

Ambush and assassin bugs (Reduviidae) Aphids, bollworm eggs, larvae Mite ( Phytoseiulus persimilis ) Spider mites

Bigeyed bugs ( Geocoris spp.) Aphids, bollworm eggs, larvae Spined soldier bug ( Podisus maculiventris) Mexican bean beetle

Pirate bugs (Anthocoridae) Aphids, bollworm eggs, larvae, thrips, whiteflies, spider mites Pirate bugs (Anthocoridae) Aphids

Damsel bugs (Nabidae) Aphids, bollworm eggs, larvae Lacewing larvae (Chyrsopidae) Aphids, bollworm eggs, larvae Lacewings (Chrysopidae) Aphids

Ladybird beetles (Coccinellidae) Aphids, spider mites, bollworm eggs, budworm eggs Ladybird beetles (Coccinellidae) Aphids

67Cotton Soybeans Species or family Controls Species or family Controls Ant, Fire ( Solenopsis spp) Immature boll weevils, bollworm eggs, budworm eggs Cotton fleahopper Bollworm eggs, budworm eggs Spiders
Parasitoids Parasitoids

. Parasitic wasps (Trichogramma spp.) Bollworm eggs Hover flies (Syrphidae) Aphids

Parasitic wasps ( Cardiochiles spp.) Budworm eggs Braconid wasp ( Meteorus communis) Aphids

Braconid wasp ( Glyptapanteles militari) Aphids

Source: ( Bohmfalk et al. , 2011b ; Herbert et al. ; Mississippi State Univers ity, 2014 )
Aquatic Animal Communities Aquatic ecosystems potentially impacted by agricultural activities include water bodies adjacent to or downstream from crop field, including impounded bodies, such as ponds, lakes, and reservoirs, and flowin g waterways, such as streams or rivers

. If near coastal areas, aquatic habitats affected by agricultural production may also include marine ecosystems and estuaries

. Aquatic species that may be exposed to sediment from soil erosion and, nutrients and pesti cides from runoff and atmospheric deposition include freshwater and estuarine/marine fish and invertebrates, and freshwater amphibians

. Although some ecological research has shown that farming practices can be detrimental to stream health ( Genito et al. , 2002 )

, recently some research suggests that agricultural lands may support diverse and compositionally different aquatic invertebrate communities when compared to nearby urbanized areas ( Lenat and Crawford, 1994 ; Wang et al. , 2000 ; Stepenuck et al. , 2002 )

.
Common fish found in each region include:

• Region A: northern pike, walleye, carp, bass, trout

• Region B: trout, perch, catfish

• Region F: alligator gar, pallid sturgeon, other “big river” species

• Region G: walleye, perch

• Region L: trout

• Region M: Chinook salmon, delta smelt

3.4.2 Plant Communities

Plant communities vary by region. In a previous Section (3.3.7) land cover in each of the 13 regions of the affecte d environment was reviewed. Dominant vegetation types among the regions

are summarized in S ection 3.3.7. The vegetation types can include forest, shrubland, cropland,

68pastures, and grasslands. Table 6 and Table 7 provide descriptions of land cover in each of the regions.

Weeds have been estimated to cause a potential yield loss of 37% in world

- wide soybean production ( Heatherly et al. , 2009 ) . Weeds compete with soybean for light, nutrients, and soil moisture. They can also harbor insects and diseases, and interfere with harvest, causing extra wear on harvest equipment ( Loux et al. , 2008 ) . In addition to w eed density, the time that weeds compete with the soybean crop influences the level of yield loss. The later the weeds emerge, the less impact they will have on yield. Soybean plants withstand early season weed competition because the soybean canopy closes earlier ( Boerboom, 2000 ) . The extent of canopy closure restricts the light available for weeds and other plants growing under the crop. In addition, canopy closure occurs more quickly when soybean is drilled or planted in narrow rows ( Boerboom, 1999 ) . However, in some studies it has also been observed that, depending on factors such as weed species, environmental conditions (i.e., rainfall amounts) and soybean cultivar, soybeans are able to compete with weeds with no resulting yield reduction ( Krausz et al. , 2001 )

. In addition to the generally described land cover in an area, plant communities in agricultural fields incl ude a range of weeds that influence and are influenced by agricultural practices. For example, cotton plant ed at too high a density forces the plants to compete for sunlight, water, and nutrients which limits each plant’s production ( Rude, 1984 ) , even though a high density of crop plants also reduces competition from weeds. Common weeds growing in the regions of the affected environment are identified in Appendix 5.

3.4.3 Microorganisms

The ability of animals to move in and out of fields can re duce their exposure to the crop production system. In contrast, soil microorganisms and plants living within cotton and soybean fields are simultaneously exposed to all of the agronomic practices affecting the crops. This section is a brief review of micro bial components of the affected environment.

Inorganic and organic matter in soil supports a diversity of fungi, bacteria, and arthropods that are important components of the growth medium for terrestrial plant life ( USDA

- NRCS, 2004 )

. Soil microorganisms are critical for soil structure formation, decomposition of organic matter, toxin removal, nutrient cycling, and most biochemical soil proces ses ( Young and Ritz, 2000 ; Jasinski et al. , 2003 ; Garbeva et al. , 2004 )

. They also suppress soil

- borne plant disease s and
pro mote plant growth ( Doran et al. , 1996 )

. Soil resilience considers the capability of the soil to return to a pre

- perturbation condition, and not as an intrinsic capacity to resist displacement from an initial equilibrium st ate ( Welbaum et al. , 2004 )

. Soil resilience is affected by the main factors affecting microbial population size and diversity

. These include plant type (providers of specific carbon and energy sources into the soil), soil type (texture, structure, organic matter, aggregate stability, pH, and nutrient content), and agricultural management practices (crop rotation , tillage, herbicide and fertilizer application, and irrigation ) ( Young and Ritz, 2000 ; Garbeva et al. , 2004 )

. Plant roots release a variety of compounds into the soil that create a unique environment for microorganisms in the rhizosphere ( Garbeva et al.

, 2004 )

. Reduced

- tillage practice s enhance soil stability and reduce erosion in comparison to

69conventional tillage systems . All of t hese effects enhance soil microbial diversity. Although the total species diversity in the soil appears constant, organic matter decomposition continues to

occur

. This leads to the sequential colonization of niche specialists using different substrates as they present themselves over time

. Consequently, changes in the relative abundance of a soil species is juxtaposed with aggregate variability in the overall abundance and biomass of the microbial community ( Wel baum et al. , 2004 )

.
The soil microflora includes mycorrhizal fungi, nitrogen

- fixing bacteria, and some free

- living microbes that evolved together with plants to supply nutrients to the plant while obtaining food from their plant hosts ( USDA

- NRCS, 2004 ) . Th is extensive microbial diversity in the rhizosphere differs from the microbial community in the bulk soil ( Garbeva et al. , 2004 ) because the root

- specific exudates are the food sources used by these organisms to mainta in and increase their populations. Tillage accelerates succession among microorganisms, and crop rotation can change soil conditions to favor different microbial communities ( Papendick and Moldenhauer, 1995b )

. Inoculants are used to ensure adequate populations of “rhizobia” or Bradyrhizobium japonicum establish in soybean fields. This bacterium, in association with soybean roots, fixes atmospheric nitrogen into forms (ammonia or ammonium) the plant can use for growth and development ( Alberton et al. , 2006 ) . Successful inoculation leads to nodulation on the soybean root, and excess fixed nitrogen remains in the soil to become available for subsequent crops or weeds ( Alberton et al. , 2006 )

. Growers inoculating soybean fields can improve soybean yield by an average of 1 bushel/acre ( Conley and Christmas, 2005 ) . This organism can be added to fields in many forms in cluding: non

- sterile peat powder applied to the seed at planting, sterile carriers, inoculants with adhesives to stick to seed, liquid carriers, concentrated frozen products, pre

inoculants, and inoculants with extended biofertilizer and biopesticidal prop erties ( Jawson et al.

, 1989 ; Conley and Christmas, 2005 )

. Another group of soil microorganisms that can affect soil quality , resilience, and crop growth are nematodes. These microscopic worms also can be pathogens that feed on the roots of various plants, including both cotton and soybeans . Many nematode species are difficult to control because it is difficult to find suitable molecules that can penetrate the soil, kill the microscopic pests, and not persist or have deleterious effects on other organisms

.
3.5 Agronomic Practices i n Cotton and Soybean Production

Modern agriculture coordinates a wide variety of ecosystem inputs to maximize crop yield and wisely use the land, vegetation, and environmental resources. Cotton and soybean production uses specific equipment for each crop’s activities from pre

- plant soil preparation to harv est and ginning ( Weersink et al. , 1992 ; Mitchell et al. , 2012 ) . For example, c otton may be harvested with spindle pickers, roller gins, or saw ginni ng depending on the variety ( Rude, 1984 ; Anonymous, 2007 ) . Tillage, crop rotation , and inputs such as pesticides are selected from a range of options by each grower to achieve their desired outcomes of yi eld and environmental stewardship

.

703.5.1 Tillage

Prior to planting, soil is typically prepared by eliminating weeds that would otherwise compete with the crop for space, water, and nutrients. Field preparation often is accomplished through a variety of tillage systems, with each system defined by the remaining plant residue on the field ( USDA

- ARS, 1995 )

. Crop residues are materials left in an agricultural field after the crop has been harvested, including stubble (stems), leaves, and seed ( USDA

- NRCS, 2005 ) . These residues aid in conserving soil moisture and reduce wind and water

- induced soil erosion ( Papendick and Moldenhauer, 1995b ; USDA

- ERS, 1997 ; USDA

- NRCS, 2005 ; Heatherly et al. , 2009 )

. Residue on the soil surface breaks the impact of raindrops, improves water infiltration into the soil, and reduces evaporation and runoff ( TAMU, 2014 )

.
Conventiona l tillage is associated with intensive plowing and leaving less than 15 % crop residue in the field ( US

- EPA, 2010 b )

. In contrast, conservation and reduced tillage practice s include: mulch

- till, eco

- fallow, strip

- till, ridge

- till, zero

- till, and no

- till ( Jia et al. , 2007 ) . Reduced tillage is associated with 15

- 30 % crop residue. Conservation tillage, including no

- till practices requiring herbicide application on the plant residue from the previous season, is associated with at least 30% crop residue and substantially less soil erosion than other tillage practices ( US

- EPA, 2010b )

. Additionally, a number of different tillage and planting systems are used in soybean production, including primary or secondary tillage ( Ji a et al. , 2007 ) . Pre

- plant tillage activities in cotton may include smoothing the soil or creating raised ridges for permanent or semi

permanent beds ( Rude, 1984 ; Albers and Reinbott, 1994 ; Mitchell et al. , 2012 )

. Increases in total acres dedicated to conservation tillage may be facilitated in part by an increased use of herbicide

- resistant GE crops, reducing the need for mechanical weed control ( USDA

- NRCS, 2010a ; Fernandez

- Cornejo et al. , 2014a )

. Land management practices for crop cultivation also affect soil quality . Soil quality is related to its suitability for chosen uses ( Welbaum et al. , 2004 ) . Tillage can affect soil properties after cultivation depending on the soil type ( Papendick and Moldenhauer, 1995b )

. Several concerns relating to soil and agricultural practices include increased erosion, soil com paction, degradation of soil structure, nutrient loss, increased salinity, change in pH, and reduced biological activity ( USDA

- NRCS, 2010b )

. Conventional tillage removes essentially all plant residues and weeds from the soil surface prior to planting. Conventional tillage practice s may continue cultivation as the crop develops to control late emerging weeds ( National Corn Growers Association, 2007 ) particularly in cotton crops ( Frans and Chandler, 1989 ) . This practice in creases the potential for soil loss from wind and water erosion ( NCGA, 2007 ) . Additionally, soil compaction associated with tillage machinery moving across fields may damage young, developing cotton crops ( Rude, 1984 ; Mitchell et al. , 2012 ) . The act of mixing soil during tillage increases seed bed homogeneity while simultaneously destroying the diversity of microsites in the soil profile, consequently, tillage reduces both structural and functional diversity of the soil microbial community ( Welbaum et al. , 2004 )

. In general, soil conservation practices, such as conservation tillage, reduce field tillage and corresponding soil loss ( Tyler et al. , 19 94b ; Papendick and Moldenhauer, 1995a ; USDA

- NRCS, 2006b ) . Conservation tillage relies on methods that result in less soil disruption and leaves at
71least 30% of crop residue on the surf ace in soybeans ( Peet, 2001 ) . No

- till farming only disturbs the soil between crops. The new crop is planted into residue or in narrow strips of tilled soil ( Peet, 2001 ) , which results in less soil disruption. Under no

- till practices, there is no turning of the soil to break up compacted areas ( USDA

- NRCS, 1996a ) . Reducing tillage may also enhance conditions for development of economically important pest populations that normally are efficiently managed with conventional tillage practice s ( NRC, 2010a )

. For example, cotton aphids migrate into fields using conservation tillage and consistently reach peak p opulation densities more rapidly than in conventionally tilled fields ( Leonard, 2007 )

. Conservation tillage is highly valued as a means to enhance soil quality and preserve soil moisture, but it also presents potential challenge s for disease and pest management ( Rude, 1984 ; Tyler et al. , 1994a ; Papendick and Moldenhauer, 1995b ) . The surface residues may se rve as an inoculum source for certain disease

- causing organisms ( Robertson et al. , 2009 ) . This can become problematic for growers using crop rotation schemes with minimal tillage ( Robertson et al.

, 2009 )

. Cotton production systems generally rely on multi ple

- pass tillage, which is costly in labor, time, maintenance of specialized equipment, and fuel ( El

- Zik et al. , 1989 ; Frans and Chandler, 1989 ; Albers and Reinbott, 1994 ; Mitchell et al. , 2012 )

. Despite incentives to reduce tillage, such as the USDA NRCS Environmental Quality Incentives Program, most cotton continues to be produc ed under traditional, multiple

- pass tillage practice s ( Mitchell et al. , 201 2 )

.

In traditional cotton cultivation, after the prior crop is harvested, the surface material is shredded and roots are undercut and mixed with the soil ( Albers and Reinbott, 1994 ; Mitchell et al. , 2012 )

. A series of diskings provides a host

- free period that is usually needed to reduce pink bollworm

. There may be more than five field operations prior to seeding the cotton crop (plow under weeds, incorporate herbicides, break

- up soil clods, shape the uniform planting beds, prepare for furrow irrigation and /or dry mulch) ( Albers and Reinbott, 1994 ; Mitchell et al. , 2012 )

. Shallow cultivation using rolling harrow implements can kill weeds and even out surface soil moisture

. Soil types prone to compaction can be loosened or fractured to reduce root restriction in hard soil layers ( Mitchell et al. , 2012 )

. Since the 1990s, tractor traffic zones were separated from crop growth zones to create strip and vertical tillage systems where only the crop seed line is tilled

. Improvements in equipment reduced tractor traffic, energy costs, and the soil compaction by combining tillage tools onto a single frame. Reducing the number of tillage passes reduce s tim e , fuel use, the amount of dust generated (soil erosion) , and can improve various aspects of water quality ( Tyler et al. , 1994a ; Mitchell et al. , 2012 )

. Effective pink bollworm and nematode control in cotton require tillage operations to reduce soil

borne populations of these pests ( Kirkpatrick and Thomas ; Mitchell et al. , 2012 ) . These pests and others overwinter in the soil , and then infect or infest the new crop . Disease control measures include cultivation of resistant hybrids, crop rotation , and careful balancing of conservation tillage with residue man agement ( Robertson et al. , 2009 )

. Information provided b y Monsanto on the trends in tillage practice s for cotton showed variation across the country in the last five years ( Monsanto, 2013d )

. According to the survey data, growers in the Western U.S. did not tend to increase use of conventional tillage practices , in contrast to those in the Mid

- South

. The survey revealed that growers adopt specific tillage
72practices based on the cost of production, commodity price, need for seed bed preparation, and to manage excessive crop residue or weeds ( see A ppendix 9 ).

Tillage in soybean production systems is used to prepare a seedbed, address soil compaction, incorporate fertilizers and herbicides, manage water movement both within and out of a production field, and control weeds ( Heatherly et al. , 2009 )

. A soybean grower’s choice of tillage system may be based on factors such as: crop rotation , soil characterist ics, nutrient management, herbicide program, planting equipment, and management ability and risk ( Randall et al. , 2002b )

. No

- till soybean production is not suitable for all producers or areas. For example,

no

- till soybean production is less successful in heavier, cooler soils more typical of northern latitudes ( Kok et al. , 1997 ; Committee on the Impact of Biotechnology on Farm

- Level Economics and Sustainability; National Research Council, 2010 )

. Introduction of improved herbicides and planters in the mid

- 1980s facilitated better weed control and good seed pla cement in no

- tillage systems, which some farmers began to adopt at that time ( Randall et al. , 2002a ; Owen et al. , 2011 )

. Adoption of conservation tilla ge systems in general accelerated in the 1990s after soil conservation policy was incorporated into the Food Security Act of 1985 ( NRC, 2010b ) . The introduction of GR soybeans in 1996 fit into the ongoing trend of increasing adoption of conservation tillage by allowing growers to control weeds without the need for tillage ( Carpenter and Gianessi, 1999 ; NRC, 2010b )

. Between 1996 and 2008, adoption of conservation tillage practice s by soybean farmers increased from 51

- 63%, and the adoption of no

- till increased from 30

- 41% by 2013 ( CTIC, 2011 )

. In an early study of the relationship between the adoption of HR soybeans and the adoption of conservation tillage practices using data from 1997, researchers found that soybean farmers using no

- till practices had a higher probability of adoption of HR soybeans. However, adoption of HR soybeans did not appear to affect no

- till adoption rates ( Fernandez

- Cornejo and McBride, 2002 ) . A later study using data from 2002 found that farmers who adopted no

- till practices were more likely to adopt HR soybeans, and that adopters of HR soybeans were more likely to adopt

no

- till systems ( Mensah, 2007 )

. In a review of the studies of long

- term relationship between the adoption of conservation tillage, and adoption of HR soybean with herbicide use both events are correlated, but “in most cases examined, it appears that adopting HT crops facilitates the use of conservation tillage systems and vice versa ( Fernandez

- Cornejo and McBride, 2002 ; Fernandez

Cornejo et al. , 2013 ) .”

3.5.2 Crop Rotation

Crop rotation is the successive planting of different crops in the same field over a specific number of years. Goals of crop rotation include maximizing economic returns and sustaining the productivity of the agricultural system ( Hoeft et al. , 2000 ) . Sustaining the agricultural system is achieved by rotating crops that may improve soil health and fertility with more commercially beneficial “cash crops.” Because soybeans fix nitrogen in soil, the yield of some crops following a soybean crop, such as corn or wheat, may increase ( Berglu nd and Helms, 2003 ) . Moreover, the rotation of crops can effectively reduce disease, pest incidence, weediness , and selection pressure for weed resistance to herbicides ( USDA

- ERS, 1997 ; Berglund and Helms, 2003 ) . Crop rotation
may also include fallow periods, or sowing with cover crop s to prevent soil erosion and to provide livestock forage between cash crops ( Hoeft et al. , 2000 ; USDA

- NRCS, 2010a )

. 73Maximizing economic returns is realized by rotating crops in a sequence that efficiently produces the most net returns for a producer over a single

- or multi

- year peri od.

Many factors at the individual farm level affect the crop rotation system chosen, including the soil type present in an individual field, the expected commodity price, the need to hire labor, the price of fuel, the availability of funding to buy seed, and the price of agricultural inputs ( Langemeier, 1997 ; Hoeft et al. , 2000 ; Duffy, 2011 )

. Figure 9 shows the cropping patterns of soybeans and cotton in the U.S. The benefits of rotation to soybean ( Al

- Kaisi et al. , 2003 ) include:

• Improved yield and profitability of one or both crops;

• Decreased need for additional nitrogen on the crop following soybean;

• Increased residue cover resulting in reduced soil erosion;

• Mitigation or disruption of disease, insect, and weed cycles;

• Increased soil organic matter;

• Improved soil tilth and soil physical properties;

• Reduced runoff of nutrients, herbi cides, and insecticides.

Crop rotation is not commonly used for cotton in the Cotton Belt, where over 60% of the planted acres are commonly described as a cotton monoculture ( Hake et al. , 1991 ; USDA

- ERS, 2011a )

. The remaining acreage generally is planted to a rotation with small grains / sorghum or other
crops ( El

- Zik et al. , 1989 ; USDA

- ERS, 2011a )

. For example, cotton

- tomato rotations are successfully used in California when irrigation is available to set the transplants after planting ( Mitchell et al. , 2012 )

. Preceding or followin g cotton with crops such as wheat or triticale may work well in conservation tillage systems, if seeding operations ensure adequate stands

. Rotational sequences with sorghum, soybean, or alfalfa are reported to reduce the incidence of some soil

- borne disea ses ( El

- Zik et al. , 1989 )

. Silage corn, which leaves relatively few soil residues , may be s uitable for crop rotation with cotton ( Mitchell et al. , 2012 )

. Since 2000, an increasing percentage of land cropped to cotton was left fallow ( USDA

- ERS, 2011a )

. A dry fallow rotation can control perennial weeds such as field bindweed, bermudagrass, J ohnsongrass, and nutsedges while providing increased water for irrigation on other fields ( Hake et al. , 1991 ) . Regardless of which crop is grown, sustained conservation tillage production system s require detailed planning t o avoid causing soil compaction ( Mitchell et al. , 2012 )

.

74Figure 9

. Cropping Patterns for Soybeans and Cotton in the U nited S tates

. Source: ( USDA

- ERS, 2011a )
Where it could be grown, cotton became a dominant crop because continuous monoculture of cotton provided more income per acre than soybeans, corn, rice, and wheat ( Hake et al. , 1991 )

. Cover crop rotation s typically consist of planting a winter cereal or legume in the fall followed by cotton next spring

. These rotations create an economic control strategy for soilborne diseases, interacting nematodes, and resistant weeds

. Typically, cover crop rotations provide erosion control, improved soil tilth, a nd suppress diseases

. Diversification increases economic stability when profitable crops are rotated with cotton, but rotation out of monoculture may not be needed if pests can be otherwise managed ( Hake et al. , 1991 )

. Growers must carefully adhere t o label use requirements because some herbicides used in cotton production may leave soil residues that can injure subsequent rotation crops, and many cotton varieties are sensitive to pesticides used in other crops ( Rude, 1984 )

. 75After over 100 years of continuous planting on Pacolet fine sandy loam soil, the oldest continuous cotton experiment in Alabama demonstrated cotton lint yield nearly three times higher when cotton is rotated with legumes as opposed to un

- rotated plots ( AUDAS, 2004 )

. Yet cotton lint yield response to crop rotation is relatively small in comparison to other crops. Rotation with wheat

- soybean shows the largest benefit from crop rotation ( Hake et al. , 1991 )

. But most of this benefit is attributed to decreasing disease a nd nematode populations in the soil, as opposed to supplying nutritional needs. Cotton's relatively low nutritional needs are attributed to its deep root system, associations with soil microorganisms , and warm season growth habit

. Consequently, when cotton is grown in rotations it is the needs of the other crops that determine the amounts of phosphorus, potassium and micronutrients that must be added ( Hake et al. , 1991 )

. Effective nematode and disease suppression through crop rotation is a long

- term management strategy that depends on the host range of the pathogen, the type of rotational crop used, and the length of the rotation

. The goal of the rotation is to reduce pathogen populations below their threshold level by not plantin g crops that are susceptible to the disease present in the field ( Kirkpatrick and Thomas ; Hake et al. , 1991 )

. For example, rotation to a monocot crop can suppress seedling diseases in subsequently planted cotton, but rotation to a legume cover crop is not likely to reduce cotton seedling disease ( Hake et al. , 1991 )

. Intercropping alfalfa as a trap

cro p for lygus bugs was attempted, i nstead of a rotation, but found impractical ( El

- Zik et al.

, 1989 )

. An effective rotational management strategy must be economically feasible, practical, and compatible with herbicide programs ( Kirkpatrick and Thomas )

. Crop rotation is a common practice on U.S. soybean fields. Soybeans are often rotated with such crops as corn, winter wheat, spring cereals, and dry beans ( OECD, 2000 ) , the selection of which varies regionally. Corn is the most commonly rotated crop with soybeans . USDA Agricultural Resource Management Survey (ARMS) results for corn and soybean indicate a small increase in corn in rotation and continuous corn over the past decade ( Ebel, 2012 )

. Soybean itself may be a cover crop in short rotations for its ability to contribute nitrogen to subsequent crops ( Hoorman et al. , 2009 )

. Continuous soybean production is sometimes practiced, but yield can be reduced the second or later years, and pest and disease incidence may increase ( Pedersen et al. , 2001 ; Monsanto, 2010 )

.

In a survey of major corn/soybean production states, corn and soybean were alternated on 72 to 80% of acreage, other rotations were grown on 16

- 20% of acreage, and soybean was grown continuousl y on 5

- 12% of acreage between 1996

– 2002 ( USDA

- ERS, 2006 )

. In 2006, the last
year for which USDA survey data are available, 72% of soybean acreage was planted on acreage planted to corn in the previous year, soybean (13%), cotton (0.5%), s mall grains (8.1%), other crops (5.9%) and fallow (0.4%) ( USDA

- ERS, 2013b )

.
Double

- cropping soybeans is also an option to increase returns. Soybean is frequently planted in winter wheat stubble to produce a crop in the same growing season. Double

- cropping maximizes profits if high commodity prices can support it, but careful management to achieve uniform stands to sustain high yields is needed: the selection of appropriate varieties, a higher seeding rate, closer row spacing, and adequate mo isture for germination are important variables affecting profitability ( McMahon, 2011 )

. 763.5.3 Agronomic Inputs

Crop production typically involves the extensive use of ag ronomic inputs to maximize yield ( Ritchie et al. , 2008 ) . In general, a gronomic inputs include fertilizers to supplement available nutrients in the soil; pesticides to reduce weed, insect, microbial, and nematode populations

, and water to ensure normal plant growth and development ( Rude, 1984 ; El

- Zik et al. , 1989 ; Ellington et al. , 2007 )

.
Fertilizer s Commercially available fertilizers usually contain a mixture of the macronutrients nitrogen, phosphorus, and potassiu m which are essential for plant growth ( Vitosh, 1996 ) . To fill specific crop needs in soils that are deficient, various concentrations of micronutrients may be included in fertilizer formulations ( Jones and Jacobsen, 2003 ) . Fertility needs also can be met by applying organic matter which may alter the soil’s naturally occurring level of nutrients that are available for plant growth ( Jones and Jacobsen, 2003 ) . Nevertheless, a bout half of the nitrogen applied in a chemical form is not taken up by plants but is lost to the atmosphere and to above

- and below

ground water supplies ( Ellington et al. , 2007 ) . Nevertheless, a bout half of t he nitrogen applied in a chemical form is not taken up by plants but is lost to the atmosphere and to above

- and below

ground water supplies ( Ellington et al. , 2007 )

. The nutritional needs for cotton are generally recognized as lower than other major crops. Nevertheless, t he nutrients needed in the largest amounts are nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur ( Rude, 1984 ) . Other essential nutrients needed in very small amounts are iron, boron, manganese, zinc, molybdenum, copper, and chlorine ( Rude, 1984 )

. I ncreased cotton growth and yield under higher nitrogen regime s can be offset in value by increase d populations of pest insects leading to reduced lint quality ( El

- Zik et al. , 1989 ; Ellington et al

. , 2007 ) . Efficient fertilizer use in cotton requires there to be no excessive nitrogen at the end of the season because nitrogen applied too late triggers the need for extra applications of defoliants ( Rude, 1984 ; El

- Zik et al. , 1989 )

. Cotton plants produce more flowers than can be grown to maturity, so they typically shed excess squares and bolls when under carbohydrate
stress ( Rude, 1984 )

.
Efficient fertilizer use in cotto n requires there to be no excessive nitrogen at the end of the season because nitrogen applied too late triggers the need for extra applications of defoliants ( Rude, 1984 ; El

- Zik et al. , 1989 )

. Cotton plants produce more flowers than can be grown to maturity, so they typically shed excess squares and bolls when under carbohydrate stress ( Rude, 1984 )

. Nitrogen is not frequently added to soybean fields because the plants have a microbia l relationship that fixes atmospheric nitrogen into a form the plant can use for growth ( Alberton et al. , 2006 ) . A 2006 survey reported by USDA National Agricultural Statistics Service (NASS) ( USDA

- NASS, 2009d ) found that among 19 select states, nitrogen was applied to 18 % of the planted soybean acreage in those states at an average rate of 16 pounds ( lb ) /acre per year, and phosphate w as applied to 23 % of the planted acres at an annual average rate of 46 lb/acre. Potash was applied to 25 % of the planted acreage at an average annual rate of 80 lb/acre, and sulfur was applied to 3 % of the planted acres at an average annual rate of 11 lb/a cre ( USDA

- NASS, 2009d )

.

77Other micronutrient supplements such as zinc, iron, and magnesium were applied as needed to soybean production ( Whitney, 1997 ; USDA

- NASS, 2007a ; NSRL, N o Date )

.
Insecticides

Pesticides that kill

, inhibit, or control insect populations are called insecticides

. A wide variety of insecticides are registered for use in cotton, but gro wers typically scout for pests and apply insecticides only when economic thresholds are met ( Rude, 1984 ; Benedict et al. , 1989 ; Higgins, 1997 )

. Some of the currently re gistered in s ecticides for use in cotton are listed in Table 11

, however, this listing is provided for comparison purposes and should not be construed as a recommendation.

Table 11

. Commonly Used Insecticides for Cotton Pests

. Cotton Pest Insecticidal Products 1
Aphids acetamiprid, clothianidin, flonicamid, imidacloprid, and thiamethoxam Beet and Fall Armyworms chlorantraniliprole, emamectin benzoate (R), flubendiamide, indoxacarb, methomyl (R), methoxyfenozide, novaluron, spinosad, and thiodicarb

Bollworm b ifenthrin (R), chlorantraniliprole, cyfluthrin (R), beta

- cyfluthrin (R), gamma

- cyhalothrin, lambda

- cyhalothrin (R), cypermethrin (R),
zeta

- cypermethrin, zeta

- cypermethrin/bifenthrin, emamectin benzoate (R), esfenvalerate (R), flubendiamide, indoxacarb, methomyl (R), novaluron, profenofos, spinosad, and thiodicarb Tobacco Budworm (in Varieties Containing Bt Genes) 2 chlorantraniliprole, emamectin benzoate (R), flubendiamide, indoxacarb, methomyl (R), novaluron, profenofos, spino sad, and thiodicarb

Cutworms acephate, bifenthrin, chlorpyrifos, cyfluthrin, lambda

- cyhalothrin,
gamma

- cyhalothrin, cypermethrin, zeta

- cypermethrin, zeta

cypermethrin / bifenthrin, and esfenvalerate Cotton Fleahopper and Tarnished Plant Bug acephate, cl othianidin, dicrotophos (R), flonicamid, imidacloprid, novaluron, oxamyl (R), and thiamethoxam

Soybean Looper and Cabbage Looper emamectin benzoate (R), flubendiamide, indoxacarb, methoxyfenozide, novaluron, spinosad, and thiodicarb

Spider Mites abamecti n, bifenthrin (R), chlorpyrifos, dicofol, etoxazole, fepyroximate, propargite, and spiromesifen Stink Bugs n on

- pyrethroids: acephate, dicrotophos, methyl parathion, novaluron, and oxamyl.
p yrethroids: bifenthrin (R), cyfluthrin (R), beta

- cyfluthrin (R), lambda

- cyhalothrin (R), gamma

- cyhalothrin (R), cypermethrin (R),
zeta

- cypermethrin (R), zeta

- cypermethrin/bifenthrin (R), and esfenvalerate (R) Thrips (at Planting) aldicarb (R), imidacloprid, and thiamethoxam

Thrips (Foliar Sprays) acephate, dicrotopho s (R), and dimethoate

78Cotton Pest Insecticidal Products 1

Whiteflies acephate, acetamiprid, imidacloprid, pyriproxyfen, and thiamethoxam

1 (R) = use. Pre

- mixed or co

- packaged products also may be available when there are multiple pests requiring simultaneous treatment.
2 Bt

- Insect resistant crops (Bt crops) contain a gene from a soil bacterium, Bacillus thuringiensis (Bt), which produces a protein that is toxic to specific lepidopteran insects. Source: ( Greene, 2012 )

. Insect injury in soybean seldom reaches levels that cause important economic loss, as indicated by the low percentage ( 18 percent) of soybean acreage that receive insecticide treatments ( USDA

- NASS, 2012b )

. Of the 27 reported insecticides applied to soybean acreage in 2012 , the four most common ly applied were lambda

- cyhalothrin, dimethoate, chlorpyrifos, and lambda

cyhalothrin ( USDA

- NASS, 2009d ) . Insect infestation levels indicate when insecticide applications are actually necessary ( Higgins, 1997 )

. When insect infestations found in field sampling surveys and/or during standard defoliation exceed specific levels, the thresholds are
met

. The National Information System of the Regional Integrated Pest Management Centers in pest management strategic pl ans provide a number of insect thresholds ( USDA

- AMS, 2011a )

. Other methods of addressing insect infestations include the introduction of beneficial pests that prey on targeted insects obtained from commercial suppliers, as we ll as crop rotation and tillage.

A wide variety of pests hinder crop production, and many require applications of agricultural pesticides to keep pest populations below economic thresholds . The development of pest populations with res istance to various classes of insecticides requires growers to wisely coordinate the compounds used at various times during the production of a crop. For example, insecticide seed treatments that increase planting efficiency in cotton may use neonicotinoid s and

over

- the

- top foliar sprays used later in the season may include non

- selective organophosphates. Many cotton aphid populations are resistant to these chemistries, so while other pests are controlled, the cotton aphid populations increase ( Leonard, 2007 )

. Several groups and types of insects feed on foliage, seed pods

, and /or roots of the soybean plant leading to reductions in yield if these pests are not adequately controlled ( Lorenz et al. , 2006 ; Whitworth et al. , 2011 )

.
Herbicides The following section provides a brief background of herbicide use in cotton and soybeans in the U.S. It is provided to give the context for the analyses related to HR weed selection. Further information is presented in Appendices 3

- 8.

Pesticides that are used to control undersirable vegetation are termed herbicides. In selecting an herbicide, a grower must consider, among other factors, whether it can be used on the crop (herbicides are registered by the EPA for specific uses/crops), the potential adverse effects on the crop, residual effects that can limit crops that can be grown in rotation, effectiveness on expected weeds, and cost. Herbicides have different ways of acting on plant physiology (i.e., modes of action) to affect the health of a given plant (see Appendix 3 ). Some common modes of herbicide action include: auxin growth regulators like 2,4

- D; amino acid inhibitors such as glyphosate; photosynthesis inhibitors such as atrazine; lipid biosynthesis inhibitors like quizalofop; glutamine synthase in hibitors such as glufosinate ( UW

- NPMP, No Date ) (see Appendix 3 ).

79Herbicides have been the primary tactic used to manage weed communities in soybeans since the mid

- 1960s and are likel y to continue to be an important feature of row crop weed management for the foreseeable future. As aptly noted by Crespo ( Crespo, 2011 ) , “ Herbicides have become the primary means of weed control in all o f the major row crops in the U.S

. Herbicides have allowed farmers to reduce the amount and intensity of tillage operations once used to control weeds. ” One study, which examined aggregated data on crop yield losses and herbicide use

, estimated that even if additional tillage and hand weeding labor replaced the use of herbicides, U.S. crop produ ction would decline by 20% with a $16 billion loss in value if herbicides were not used ( Gianessi and Reigner, 2007 )

. GR crops have become adopted widely since their introduction in the 1990s for several reasons. Glyphosate works non

- selectively on a wide range of plant species, is a relatively low

- cost herbicide, enhances ‘no

- till’ farming practices, a nd has minimal animal toxicological and environmental impacts ( USDA

- APHIS, 2010 ) . However, increased selection pressure resulting from the wide

- spread adoption of GR crops, with the reductions in the use of other herbicides and weed management practices, has resulted in both weed population shifts and growing numbers of GR individuals among some weed popu lations ( Owen, 2008 ; Duke and Powles, 2009 )

. Herbicide use varies with each crop based on both the types of herbicides used and the variety of herbicide sites of action 8 (see Appendix 3 ). Cotton establishment takes longer to close the canopy than soybeans, so cotton becomes more susceptible to competition by early season weed s ( Frans and Chandler, 1989 )

. Cotton may be planted in wider rows than soybeans, and the resulting light penetration into an unclosed canopy allows weed germination and growth over a longer period of time than in soybeans ( Frans and Chandler, 1989 ) . For these reasons, post

emergent applications of herbicides are more common in cotton crops than in soybeans , but there may be fewer herbicide options

.
To obtain the best cotton yie lds, growers manage weeds with a diversification of weed control strategies ranging from mechanical choppers and cross

- cultivation to hand

- labor and modern herbicides ( Frans and Chandler, 1989 ) . The rotation of combinations of herbicide treatments can reduce the undesirable ecological shifts to new weed species or herbicide

- resistant weed species ( Frans and Chandler, 1989 ) . Herbicid e residues from organic arsenicals have been a concern in cotton seed, particularly if applications occurred during early reproductive growth stages ( Frans and Chandler, 1989 ) . Cotton is partic ularly sensitive to drift from phenoxy herbicides used on nearby crops ( Frans and Chandler, 1989 )

. Until recently, soybean growers relied almost exclusively on glyphosate for weed control. Pri or to the adoption of GR soybean, growers relied heavily on herbicides with a mode of action called

“ acetolactate synthase (ALS) inhibitors” or “ acetohydroxyacid synthase (AHAS) inhibitors”

. With the adoption of GR soybean, glyphosate was used on greater than 95% of soybean acreage and for 75% of soybean growers, glyphosate represented the only herbicide mode of action used. As GR weeds have become more prevalent, the trend among soybean growers is to use more

8 The site off action is the location within the plant where the herbicide impacts the development process.

80modes of action including 2,4

- D
, chloroacetami des, p rotoporphyrinogen oxidase (PPO), and ALS inhibitors.

Growers choose pesticides based on weed, insect and disease pressures, cost of seed and other inputs, technology fees, human safety , potential for crop injury, and ease and fl exibility of the production system ( Heiniger, 2000 ; Farnham, 2001 )

. The continued emergence of GR weeds will likely require modifications of crop management practices to address thes e weeds. Herbicide use may increase to meet the need for additional integrated weed management tactics to mitigate HR weeds in different cropping systems ( Owen and Zelaya, 2005 ; Culpepper, 2008 ; Heap, 2014d )

.

In selecting an herbicide, a grower must conside r, among other factors, whether an herbicide can be used on the crop (herbicides are registered by the EPA for specific uses/crops), the potential adverse effects on the crop, residual effects that can limit crops that can be grown in rotation, effectiveness on expected weeds, and cost. Herbicides have different ways of acting on plant physiology (i.e., modes of action) to affect the health of a given plant (see Appendix 3). Some common modes of herbicide action include auxin growth regulators li ke 2,4

- D; amino acid inhibitors such as glyphosate; photosynthesis inhibitors such as atrazine; lipid biosynthesis inhibitors like quizalofop; and glutamine synthase inhibitors such as glufosinate (UW

- NPMP, No Date ) (see Appendix 3 ). Applications of herbicides to a crop may occur pre

- plant (i.e., burndown), pre

- emergence, or post

- emergence ( Schneider and Strittmatter, 2003 )

. Weeds are estimated to cause a potential yield loss of 37 % in world

- wide soybean production ( Heatherly et al. , 2009 ) . Weeds compete with soybean for light, nutrients, and soil moisture

. They can also harbor insects , plant disease s , and interfere with harvest, causing extra wear on harvest equipment ( Loux et al. , 2008 )

. In addition to weed density, the time that weeds compete with the soyb ean crop influences yield

. The later weeds emerge, the less impact they will have on yield. Soybean plants withstand early season weed competition longer than most other crops because the soybean canopy closes earlier ( Boerboom, 2000 )

. The extent of canopy closure restricts the light available for weeds and other plants growing below the soybean

. In addition, canopy closure occurs more quickly when soy bean is drilled or planted in narrow rows ( Boerboom, 1999 ) ; however, in some studies it has also been observed that, depending on factors such as weed species, environmental conditions (i.e., rainfall am ounts) and soybean cultivar, soybeans are able to compete with weeds with no resulting yield reduction ( Krausz et al. , 2001 )

. Herbicides have been the primary tactic used to manage weed communities in soybeans since the mid

- 1960s and are likely to continue to be an important f eature of row crop weed management for the foreseeable future

. One study, which examined aggregated data on crop yield losses and herbicide use , estimated that even if additional tillage and hand weeding labor replaced the use of herb icides, U.S. crop production would decline by 20 % with a $16 billion loss in value if herbicides were not used ( Gianessi and Reigner, 2007 )

.

HR crops have become adopted widely since their introduction in the mid

- late 1990s for several

reasons . I ncreased selection pressure caused by wide

- spread adoption of HR crops and reduction in the use of other herbicides and weed management practices, resulted in both weed population shifts and growing numbers of HR individuals among some weed populations ( Owen, 2008 ; Duke and Powles, 2009 )

. Figure 10 depicts states reported to have dicamba

- , 2,4

- D

- , and glufo sinate

- resistant weeds.
81Figure 10 . States of the U nited S tates Reported to Have Populations of Dicamba

- , 2,4

- D

- , and Glufosinate

- Resistant Weeds. Source: ( Heap, 2014d )

As HR weeds increase in prevalence, costs of weed control may also increase if additional compounds, applications, or equipment must be used

. Growers may be able to control HR weeds without increasing costs if less expensive chemicals or multi

- chemical formulations are available.

Extension weed scien tists estimated the increased cost of the additional herbicides needed to control glyphosate

- resistant weeds in soybean to be as much as $42/acre (for Palmer amaranth in Tennessee), with most estimates of the increased costs falling in the range of up to $ 20 to $30/acre ( Carpenter et al. , 2002 ) . These costs will vary depending on the specific weed species present in any particular field. However, as resist ance to glyphosate and other herbicides has developed and spread in weed populations, these costs may have increased since these estimates were made

. For example, there are waterhemp populations in Iowa corn and soybean production fields with resistance to five herbicide sites of action ( Owen, 2012 )

. Growers choose certain pesticides based on weed, insect and disease pressures, cost of seed and other inputs, technology fees, human safety , potential for crop injury, and ease and flexibility of the production system ( Heiniger, 2000 ; Farnham, 2001 ; University of California, 2008a )

. G rowers have traditionally used multiple herbicides for weed control. For pre

- plant application

82herbicides that have residual activity are typically used (see Append ix 3) . For more details about herbicides used for cotton and soybean production see Appendi x

. Water Use in Cotton and Soybean Production

Soil is the storage site for water available to plants, and the primary factors in determining water

holding capacity of soil is its texture and depth of the root zone ( TAMU, 2014 )

. Roots grow in moist soil, not in saturated or dry soil ( Brown et al. , 2002 )

. Several factors can affect soil moisture variability, including soil type and intrinsic heterogeneity, plant growth variation, rainfall interception, reduced application efficiency and uniformity in irrigation ( Muñoz

- Carpena et al. , 2006 )

.
Cotton varieties are now br ed to be a relatively drought tolerant plant s (see Figure 11 ) , so t he majority of U.S. cotton uses supplemental irrigation to optimize production ( TAMU, 2014 )

. F rom 1980 to 2011 , t he proportion of irrigated cotton acreage remained relatively constant at approximately 32 % ( Fiel d

- to

- Market, 2012 ) , even though the total irrigated acreage increased because of the increase in total land use d for cotton production during that interval. Between 1980 and 2011, total irrigation water applied for U.S. cotton decreased 35 % (1.4 % compound annually); total water use was 95.5 million acre inches in 1980 and 62.9 million acre inches in 2011 ( Field

- to

- Market, 2012 )

. On average worldwide, at least 500 mm of rainfall (about 2 0 inches) is required during the growing season for dryland (non

- irrigated) cotton crops ( OECD, 2008a )

.

83Figure 11 . Cotton Water Use and Average Water Use Efficiency Compared to Other Crops, 2003/2004

. The “water use efficiency” is calculated from the marketable crop yield divi ded by crop water use. Source: ( Cantrell, 2006 )
The water supply for cotton germination and seedling development can be met either by preplant irrigation or by “irrigating up” after planting ( Rude, 1984 ; El

- Zik et al. , 1989 ) . The amount of water depends on rainfall and the nature of the soil pr ofile ( Rude, 1984 )

. The need for w ater increases dramatically from less than 1 inch per week at emergence to 2 inches per week at first bloom . The critical period to avoid water stress is during flowering and boll development when
p eak w ater use occurs . Drought during this interval causes the plant to shed small squares first

. Continued water stress leads to larger squares and then bolls being shed ( Rude, 1984 ; TAMU, 2014 )

. The need to avoid water stress during the flowering period must be balanced against the likelihood of boll rot epidemics ( Rude, 1984 )

. Proper t iming for the final irrigation provide s adequate moisture for the last harvestable bolls to ma ture even though the plant’s water needs dropped considerably by harvest ( TAMU, 2014 )

. Irrigating too late can delay the opening of mature bolls, may increase lodg ing, and complicated defoliation by promoting late season growth and regrowth ( Rude, 1984 )

. An over

- supply of water and/or nitrogen is associated with lanky or “rank” growth with excessive foliage and stems and reduced yield ( Rude, 1984 )

. Cotton

84will continue to grow and fruit until weather conditions are no longer favorable for growth ( Cantrell, 2006 )

.
Established c otton plants metabolic ally adapt to cope with periods of water loss

, but w ater stress can cause the shedding of leaves , flowers, and bolls; upset osmosis regulators ; and reduce photosynthesis in cotton plants ( El

- Zik et al. , 1989 )

. As water stress increases, cotton plants put more biomass into reproductive growth , and this sequence can be manipulated by growers to increase yield ( El

- Zik et al. , 1989 ; Gibbs et al. , 2005 )

. I n certain cotton varieties, stem color is an indicator of water stress. Crops treated by a growth regulator may exhibit different stem coloring; plant wilting or flowering at their tops also can be used to identify water stress ( Rude, 1996 ; McGuire, 2006 )

. Ongoing drought in the U.S. limits water allotment for agricultural use ( Figure 12 ). I ncreasing costs of irrigation and labor also are incentives for growers to seek efficient ways to conserve and reuse water. Water availability for cotton crops can be improved with conservation tillage ( TAMU, 2014 ) . Conservation tillage must be carefully managed in cotton production because crop residues on cotton fields after harvest can provide a source for pest spread and volunteer
cotton over a large surrounding area ( McGuire, 2006 )

. A prompt, thorough plowdown is essential for cotton crops

. Plowdown involves the shredding and burial of all crop debris immediately after harvest, to a depth of 6 inches ( Rude, 1984 ; 1996 )

.

Figure 12 . A Recent Compilation of Drought Affected Areas in the U nited S tates

. Source: ( Rippey, 2004 )
The soils and climate in the Eastern, Midwestern, and portions of the Great Plains region of the U.S. retain sufficient water supplies under normal climatic conditions to produce a soybean crop. In regions of the U.S. that experience low amounts of rainfall during the growing season or during drought, soybean yields benefit from proper irrigation . Soybeans require approximately 8520 to 25 inches of water during the growing season to produce a relatively high yield of 40 to 50 bushels per acre ( Hoeft et al. , 2000 ; University of Arkansas, 2006 ; Nafziger, 2007 ) . In 2006 and 2008, approximately 9% of the planted acres of soybeans in the U.S. were irrigated ( USDA

NASS, 2010a ; USDA

- ERS, 2011e ) . In 2007, when approximately 6% of the total soybean crop was irrigated, over 92% of the irrigation supply was from groundwater supply ( USDA

- ERS, 2012d )

.

A majority (approximately 73%) of irrigated soybean acreage occurs in the Missouri and Lower Mississippi Water Resource Regions, and soybean acreage i n the states of Nebraska, Arkansas, Mississippi, Missouri, and Kansas accounts for 85% of all irrigated acres ( USDA

- NASS, 2011d )

. In 2006, approximately 8.4 inches of water per irrigated acre were used, producing an average of more than 51 bushels per irrigated acre ( USDA

- ERS, 2011e )

. This yield was approximately 19.8% higher than the national average (42.9 bushels per acre) for that year ( USDA

- NASS, 2011a )

. Many residual herbicides require adequate rainfall or irrigation water to be activated ( Hager et al. , 2011 ) . In 2012, only 90% control of palmer amaranth was achieved under both furrow and sprinkler irrigation systems using residual herbicides, lea ding to recommendations that residual herbicides should be applied every 2 to 3 weeks until canopy formation to minimize the number of escapes that must be removed using other weed control measures ( Riar et al. , 2012 )

.

3.5.4 Organic Cotton and Soybean Production

National Organic Program and Organic Soybean Farming In the U.S., only products produced using specific methods and certified under the USDA’s Agricultural Marketing Se rvice (AMS) National Organic Program (NOP ) definition of organic farming can be marketed and labelled as “organic ” ( USDA

- AMS, 2010 )

. Organic certification is
a process

- based certification, not a certification of the end product; the certification process specifies and audits the methods and procedures by which the product is produced.

In accordance with NOP , an accredited organic certifying agent conducts an annual review of the certified operation’s organic system plan and makes on

- site inspections of the certifie d operation and its records. Organic growers must maintain records to show that production and handling procedures comply with USDA organic standards.

The NOP regulations preclud e the use of excluded methods. The NOP provides the following guidance under 7 CFR §205.105

—

To be sold or labeled as “100 percent organic,” “organic,” or “made with organic (specified ingredients or group(s)),” the product must be produced and handled without the use of: (a) Synthetic substances and ingredients

,... (e) Excluded methods,...

Excluded methods are th en defined at 7 CFR §205.2 as

—

86A variety of methods used to genetically modify organisms or influence their growth and development by means that are not possible under natural conditions or processes and are not considered compa tible with organic productio n. Such methods include cell fusion, microencapsulation and macroencapsulation, and recombinant DNA [ deoxyribonucleic acid ] technology (including gene deletion, gene doubling, introducing a foreign gene, and changing the positions of genes when achieved b y recombinant DNA technology). Such methods do not include the use of traditional breeding, conjugation, fermentation, hybridization, in vitro fertilization, or tissue culture.

The NOP has recognized the feasibility of prote cting organically

- produced crops from accidental contamination by GE crops by requiring that organic production plans include practical methods to protect organically produced crops

— Organic crops must be protected from contamination by prohibited substanc es used on adjoining lands (for example, drifting pesticides, fertilizer

- laden runoff water, and pollen drift from genetically engineered crops ...) ( National Center for Appropriate Technology, 2003 )

.

T he NOP require s organic production operations to have a management plan approved by an accredited certifying agent , that may include measures such as distinct, defined boundaries and buffer zone s to prevent unintended contact with excluded methods from adjoining land that is not under organic manageme nt. Organic production operations also must develop and maintain an organic production system plan approved by their accredited certifying agent to prevent genetic commingling due to pollen flow, as well as post

- harvest commingling

. Plans under the approve d operating system enable the production operat or to achieve and document compliance with the National Organic Standards, including the prohibition o n the use of excluded methods. In NOP organi c systems, the use of GE crops is exclude d ( USDA

- AMS, 2010 )

.

EPA

- registered synthetic pesticides are prohibited in organic production; however, there is the potential for inadvertent or indirect contact from neighboring convention al farms or shared handling facilities. As long as the operator has not directly applied prohibited pesticides and has documented efforts to minimize exposure to them, the USDA organic regulations allow for residues of prohibited pesticides at or below 5 p ercent of the EPA tolerance ( USDA

- AMS, 2012 )

. Although the National Organic Standards preclude the use of excluded methods, they do not require testing of inputs or products for the presence of excluded methods. The presence of a detectable residue of a product of excluded methods alone does not necessarily constitute a violation of the National Organic Standards ( USDA

- AMS, 2011b )

. The current NOP regulations do n ot specify an acceptable threshold level for the adventitious presence of GE materials in an organic

- labeled product

. Manufacturers and retailers that sell organic products may use GE product tolerance levels set by the private sector in the U.S. The non

- p rofit third party verification ‘Non

- GMO Project Verified’ is widely used. International governments may set lowest level presence standards (LLP) based on PCR testing for GE DNA; buyers may set higher or even zero standard s. Rejection of U.S. organic products due to commingled GE content has

87occurred; soybean has been rejected in Taiwan and Korea containing an identifiable GE commodity.

The unintentional presence of the products of excluded methods will not affect the statu s of an organic product or operation when the operation has not used excluded methods and has taken reasonable steps to avoid contact with the products of excluded methods as detailed in their approved organic system plan ( USDA

- AMS, 2011b )

. U.S. Organic Cotton Production Cotton grown without synthetic chemicals such as pes ticides and fertilizers is referred to as “organic” ( OTA, 2010 ; Ba bu et al. , 2013 ) and is certified under the National Organics Program ( TOCMC, 2014 ) . Production of orga nic cotton includes the use of natural defoliants; beneficial insects for pest control; compost, manure, and crop rotation s for fertilizers; hand

- weeding ; mechanical cultivation ; cover crop s and mulching for weed control. A comparison of conventional cotton and organic fibers showed that morphologically and chemically, the two types of cotton are similar ( Babu et al. , 2013 )

. Organic cotton has been produced in the U.S. since 1991 ( Funtanilla et al. , 2009 ) . In 2012, t he majority of the U.S. organic cotton crop was planted to upland cotton, with pima cotton representing fewer than 1,000 planted acres ( OTA, 2014 )

. Acreage planted in organic cotton increased 36% from 2009 to 2010 ( OTA, 2014 ) . According to USDA, in 2011, approximately 12,000 acres of certified organic cotton were planted; this acreage represents 0.08 percent of cotton acreage in the United States ( USDA

- ERS, 2013a )

. Organic cotton production is centered in West Texas with additional acreage in Arizona, California, New Mexico, and North Carolina ( USDA

- AMS, 2013 ) . The Organic Trad e Association, projects a two percent increase in organic cotton acreage or approximately 16,406 acres for 2012. A total of 16,716 a cres of organic cotton, representing an additional two percent gain over the next five years, is forecasted to be planted ( OTA, 2014 )

. Limitations on t he growth of the U.S. organic cotton industry are tied to challenges also faced by growers of conventional cotton, including weather, geography, weeds, drought, and pests. Also, there is reported to be a limited availability of organic seeds and not much w ork dedicated to improving cottonseed by traditional breeding techniques ( OTA, 2014 )

.
O ne of the main organic production regions is t he South Plains ar ea of Texa s ( TOCMC, 2011 )

. Organic cotton production in this area benefits from w inter temperatures that are cold enough to limit insect pressure and to provide a hard freeze to defoliate the cotton plants prior to harvesting, as well as a sunny climate and quick

- drying soils to facilitate timely mechanical weed control

. As many of these farmers do not irrigate, yields are heavily dependent upon rainfal l ( TOCMC, 2011 )

. American organic cotton typically commands premium prices over conventionally grown cotton; organic cotton growers indicated they received $1.40 per pound for organic upland cotton and $2.15 for organic pima cotton in 2012 ( OTA, 2014 ) . These prices are slightly lower than those from previous years due to global competition and weather

- related quality issues with the 2012
crop ( OTA, 2014 )

. According to USDA’s Agricultural Marketing Service, prices for organic cottonseed ranged from $500 to $650 per ton , while conventional cottonseed is $210 to $320 per

88ton. Most of the cottonseed is sold to organic dairies, wi th some saved for replanting ( USDA

AMS, 2013 )

. However, organic cotton production is typically about 50% more expensive than conventional cotton production ( ATTRA, 2003 ) . Higher production cost s are due to factors such as han d hoeing and weeding labor ( ATTRA, 2003 ; TOCMC, 2014 ) ; gins and mills must be operated separately for organic cotton; higher dyestuff costs; small run penalties ( TOCMC, 2014 ) ; more seed used/acre; higher energy costs due to more water typically used in organic cotton fields; loss in production for three years while converting conventional fields to organic fields ( Funtanilla et al. , 2009 ) ; crop loss due to defoliation; and costs of organically acceptable disease and insect management ( ATTRA, 2003 ) . In addition to higher production costs, organic cotton yields are typically lower than conventional cotton yields ( Funtanilla et al. , 2009 ; Chaudhry et al. , 2012 ; TOCMC, 2014 ) , as much as 30% lower ( Funtanilla et al. , 2009 )

. Most U.S. organic cotton growers sell their cotton products through a marketing cooperative, the largest of which is the Texas Organic Cotton Marketing Cooperative ( TOCMC ) , with approximately 30 member s ( TOCMC, 2011 ; OTA, 2012 ) . C ottonseed is marketed to organic dairies for fe ed ( TOCMC, 2011 )

. According to a survey cond ucted by OTA, organic cotton growers’ biggest barriers to planting more organic cotton are finding a market willing to pay the added costs of organic products, production challenges such as weed and insect control, and labor costs. Growers have indicated c hallenges due to competition from international organic cotton producers, as well as the cost of transition to organi c ( OTA, 2010 )

. Organic cotton represents about 1.1% of global cotton production, and world production and sales have increased steadil y, with world sales rising from $4 billion in 2009 to $5.3 billion in 2010 ( Memon, 2012 ) . As of 2012, the U nited S tates was the sixth

- ranking producer of organic
cotton in the world, behind India, Syria, Turkey, China, and Tanzania ( Memon, 2012 )

. Upland and Pima cotton are mostly self

- pollinated, but insect pollination does occur via insects or pollen disp ersion in wind ( Hutmacher et al. , 2006 ) . Organic cotton production systems must therefore be isolated from GE cotton by both space and time to ensure cross

- pollination will not occur. As stated above, these distances would be established with the organic certifying agent. A recent multi

- year pollen mediated gene flow study in commercial cotton production from GE cotton fields found sporadic pollen media ted gene flow beyond 30 meters, between 0.01% and 0.1% from 200 to 1625 meters in the presence of pollinators ( Van Deynze et al. , 2005 ) . In the absence of pollinators, pollen mediated gene flow was not identified beyond 10 meters ( Van Deynze et al

. , 2005 )

. U.S. Organic Soybean Production In 2011, U.S. acreage in organic soybean s totaled 132,411 acres. The states with the most acreage, in descending order, were Minnesota, Iowa, Michigan, Arkansas, Missouri, New York, Wis consin, Nebraska and Ohio ( USDA

- ERS, 2011b ) . U.S. acreage has increased steadily since 1995, when 47,200 acres were dedicated to organic soybean ( USDA

- ERS, 2011b )

. Typically, two types of organic soybean s are grown in the U.S.: food

- grade, used for products such as tofu, miso, and soymilk, and feed

- grade, for livestock ( University

- of

- Minnesota

89Extension ; Delate, 2003 ) . Many organic food

- grade soybean products are for export to Japan and other countries ( Delate, 2003 )

.
Because of major price premiums paid for organic soybean ( Place et al. , 2009 ) , it can be profitable for growers to produce organic rather than conventional soybeans ( ATTRA, 2003 )

. For example, in 2006, a bushel of organic soybeans sold for about $9 more than a bushel of conventional soybeans ( McBride and Green, 2008 ) , and in 2013, the projected price for organic soybean was $19.73/bushel compared with $9.73/bushel for conventional soybeans ( Clark and Alexander, 2010 ) . For the week of March 7

- 15, 2014, the price ran ge of organic soybean was $26.50

- 29.71/bushel; for organic feed

- grade soybeans it was $24.00

- 26.50/bushel ( USDA, 2014 ) . However, without price premiums, organic soybeans had net market returns about the same as for conventional soybeans ( McBride and Green, 2008 ) . With a high depen dence on fertilizers and pesticides, conventional soybean growers spend more money on chemicals than do organic soybean growers, but organic growers dedicate more operating funds to fuel and labor than do conventional soybean growers ( McBride and Green, 2008 ) . Operating costs for o rganic soybean production are about $0.82/bushel higher than for conventional soybean production ( McBride and Green, 2008 )

. In addition, crop yields for organic soybeans are generally lower than for conventional soybeans ( University of Kentucky ; McBr ide and Green, 2008 ; Place et al.

, 2009 ; Baldock et al. , 2012 ) , as much as 15% lower ( Clark and Alexander, 2010 ) . Organic soybeans ar e more likely to be grown on smaller, family

- owned farms ( McBride and Green, 2008 )

. To grow organic soybean s, growers need to be certified by the USDA National Organic Program (NOP ) ( De late, 2003 ) , and must use only organic seed ( University of Minnesota ) . Organic soybeans need to be segregated from conventional soybeans during all aspects of planting, harvesting, and storage ( Delate, 2003 ) . Highest premiums are obtained by planting Clear

- Hilum food

- grade seed ( Delate, 2003 ) . Growers of organic soybean may utilize various risk management strategies to compensate for the lack of chemical control. For example, most organic growers tend to plant 1

- 2 weeks after conventional growers to reduce weed populations; however, this may t hen lead to lower yields ( University of Minnesota ) . In order to provide better competition with weeds which can substantially depress yields ( Place et al. , 2009 ) , organic growers frequently use higher seeding rates than conventional growers: from 175,000 to 200,000 seeds/acre for organic fields compared with 100,000 seeds/acre for conventional fields ( University of Minnesota ; Delate, 2003 ; Place et al. , 2009 ) . More soybean seedlings/acre may help with shading out weeds ( Place et al. , 2009 ) . Increasing row space to accommodate cultivators and other machinery to control weeds is also used frequently by organic soybean growers, but may also reduce yield ( Baldock et al. , 2012 )

. Organic soybean producers use production practice s designed to prevent commingling of their value

- added crop with neighboring crops treated with herbicides and other pesticides or that may be using plant varietie s produced by excluded methods. A ddition ally

, well

- established practices help avoid spray drift from neighboring fields

, includ ing isolation zones, use of buffer rows surrounding the organic crop, adjust ed planting dates, and varietal selectio n ( Kuepper, 2006 )

. The efficacy of management practices utilized to avoid pollen movement from a GE crop to organic soybean production operations is facilitated by the nature of soybean pollination

. Soybean is a highly self

- pollinated species and exhibits a very low level of outcrossing.
90Outcrossing most commonly r esults from cross

- po llination

. Since soybean is highly self

pollinating, organic or conventional soybean producers can and have effectively implemented practices (e.g., isolation during the growing season, equipment cleaning during harvest, and post

harvest separation of harvested seed) that allow them to reasonably avoid GE soybean and maintain organic or conventional production statu s ( Brookes and Barfoot, 2004 )

.

3.5.5 GE Cotton and Soybean

Growers can choose from a large number of cotton and s oybean hybrids generated either from traditional breeding or GE systems. Large

- scale field testing of GE crops began in the 1980s, but it was not until ten years later the first generation of GE soybean varieties became commercially available.

Plantings of GE HR cotton expanded from about 10% of U.S. acreage in 1997 to 96% in 2014 ( USDA

- ERS, 2014a ) . Plantings of insect

- resistant (HR plus insect resistant) cotton also expanded rapidly, from 15% of U.S. cott on acreage in 1997 to 84% in 2014 ( USDA

- ERS, 2014a )

. Seed choices of both Roundup Ready (glyphosate resistant) and Liberty Link (glufosinate resistant) varieties are available from four major seed providers, as well as several smaller ones ( U SDA

- AMS, 2014 )

. Since GE soybeans’ initial commercial availability in 1996, plantings of GE HR soybean increased from 54 percent of U.S. soybean acreage in 2000 to 94 percent in 2014 ( USDA

- ERS, 2014a )

. Although other varieties are available for selection by growers, the Roundup Ready ® GR varieties continue to dominate the market (see, e.g., ( Tarter, 2011 ) ). Another cultivated HR soybean variety is the LibertyLink ® soybean (a GE soybean that is resistant to glufosinate

ammon ium herbicide and was granted nonregulated status in 1996) and STS (a conventionally bred sulfonylurea

- resistant soybean first introduced in 1993). As of 2012, 3.9% of U.S. soybean acres planted were glufosinate

- resistant ( DAS, 2013a ) . Additional GE traits, such as lepidopteran resistance, high oleic acid content, improved fatty acid profile, and increased stearidonic acid have nonregulated status ( USDA

- APHIS, 2014c ) . Of these, at this time, only high oleic acid content soybean has been commercialized, in a limited launch. Ot her GE traits with nonregulated status may be made available for commercial production in the future.

GR soybeans were first commercialized in 1996, and adoption by growers was rapid, reaching 54% already by 2000 and more than 90% by 2007 ( U SDA

- NASS, 2013c )

. While some potential herbicide cost savings may have driven adoption, early studies recognized the primary reason that growers adopted the technology as the simplicity and flexibility of a weed control program that relied heavily on a single herbicide to control a broad spectrum of weeds without crop injury or crop rotation restrictions. The increased cost of GE HR seed was outweighed by the often lower cost of glyphosate

- based weed control programs, although this cost advantage was quickly eroded by reductions in the prices of other conventional herbicides. The glyphosate

- resistant soybean weed control program reinforced on

- going trends towards post

- emergence weed control and the adoption of conservation tillage programs ( Carpenter and Gianessi, 1999 )

. For 1997, USDA estimated that herbicide

- resis tant soybeans led to a 3% increase in yields and a reduction in weed control costs (including, application, scouting, cultivation, herbicides, and technology fees) of $3.50/acre (10.65 % ) in the Heartland ( Pric e et al. , 2003 )

.

91The simplicity and flexibility of the glyphosate

- resistant soybean program has resulted in reduced management time. The time savings related to adoption of HR soybeans was estimated to be 14.5 % in 2002 ( Gardner et al. , 2009 ) . Off

- farm income has been found to be an important source of household income for many soybean producers, with approximately two

- thirds of soybean

- growing farm fam ilies receiving income from off

- farm work ( Foreman and Livezey, 2002 )

. The adoption of GE soybean varieties has been associated with increases in off

- farm income due to reduced on

- farm managerial time requirements. In an analysis of soybean producing households between 1996 and 2004, a 16% increase in off

- farm income was associated with a 10% increase in the probability of ad opting HR soybean ( Fernandez

- Cornejo, 2007 )

. The reduction in management time is one of the non

- pecuniary benefits that influence farmer adoption decisions, but are not direct contributors to increased profits. In a study of GR so ybean in the U.S. in 2002, nonmarket valuation techniques were used to estimate farmer valuation of three non

- pecuniary characteristics: increased farmer and worker safety

, environmental safety, and convenience. Convenience was most h ighly valued, followed by environmental safety, and operator and worker safety ( Marra and Piggott, 2006 ) . These results are reinforced by an analysis of nationwide survey results from 2007, which found that growers rated characteristics such as consistency of control, crop safety, and family and employee health as very important more often than herbicide cost. In addition, health and environmental concerns, yield concerns, and herbicide

- application concerns were found to influence grower decisions ( Hurley et al. , 2009 )

. Synthetic herbicides have provided growers with practical and economical weed control strategies for nearly 70 years. The later development of glyphosate resistant crops h as been highly successfuland provides substantial benefits to growers . Increasing populations of GR weeds ha ve however threatened the utility and sustai nability of these benefits. HR weeds can reduce crop yields and increase costs of weed control. However, if growers use best management practices incorporating a diversity of weed control practices , herbicides should remain a viable strategy long into the future. New developments in weed management that include new types of herbicides and possibly ne w technologies are likely to enhance sustainability.

HR weeds are discussed more fully in Appendix 6. Genetically modified crops with herbicide resistance are a major part of conventional commodity agriculture in the U nited S tates , and comprise the majorit y of corn, soybeans and cotton products consumed by humans and livestock. In this country, people rely on a network of legal and procedural requirements designed to reduce risk to acceptable levels and assure the health and safety of themselves and their l ivestock. In the next section, we discuss health and safety issues related to cotton and soybean production with a focus on worker safety and public health.

3.6 Health and Safety for Human s and Livestock

Cotton seed and associated linter s are processed to produce cottonseed oil and cottonseed meal which is used for human food and animal feed

. In the U.S., cottonseed oil annual production
averag es more than 1 billion pounds

, rank ing behind soybean and corn oil in volume, and representing about 5 to 6% of the total domestic fat and oil supply ( National Cottonseed Products Association, 2002 ) . C ottonseed o il is primarily used as a salad or cooking oil . It is among the most unsaturated of food oils

, and is rich in natural antioxidants called tocoph erols ( NCPA, 922002 ) . Others, however, view cottonseed oil as unhealthy bec ause they consider it too high in saturated fat and too low in monounsaturated fat ( Weil, 2008 ) . They believe it may contain natural toxins and unacceptably high levels of pesticide residues ( Weil, 2008 )

. Processed soybeans are the world's largest source of animal protein feed and the second largest source of vegetable oil. Soybean meal is high in protein and is used in food products such as tofu, soymilk, meat replacements, and p rotein powder; it provides a natural source of dietary fiber ( USB, 2009 )

. Nearly 98 % of soybean meal produced in the U.S. is used as animal feed, while less than 2 % is used to produce soybean flour and proteins for food use ( Soyatech, 2011 )

. Soybean s can be the dominant component of livestock die ts, such as in poultry, where nearly
two

- thirds of their protein intake is derived from soy beans ( Waldroup and Smith, 2008 )

. Poultry consume more than 45 % of domestic soybean meal or 590 million bushels of the U.S. soyb ean crop, with soy bean oil increasingly replacing animal fats and oils in broiler diets ( USB, 2011 )

. Other animals fed domestic soybean s (by crop volumes consumed) include swine (26 % ), beef cattle (12 % ), dairy cattle (9 % ), other (e.g., poultry, farm

- raised fish 3 % ), and household pets (2 % ) ( Soy Stats, 2010 ; USB, 2011 )

. Soybean liquids produce salad and cooking oils, baking and frying fat, and margarine

. Soybean oil is low in saturated fats, high in poly

- and monounsaturated fats, and contains essential omega

3 fatty acids

. Soybean oil comprises nearly 70 % of the oils consumed in U.S. households ( Soy Stats, 2010 )

. Soybeans comprise about 90 % of U.S. oilseed production, while other oilseeds (peanuts, sunflower seed, canola, and flax) make up the remainder 10 % ( USDA

- ERS, 2014e )

. Although the current soybean market is dominated by seed production

, soybean has a long history as n utritious grazing forage , hay , and silage for livestock ( Blount et al.

, 2009 ) . Soybean may be harvested for hay or grazed from the flowering stage to near maturity; the best soybean for forage is produced in the beginning of the pod stage ( Owen et al. , 2011 )

. For silage, harvesting should be at maturity before leaf loss . Then the soybean matter should be mixed with a carbohydrate source, such as corn, for optimal fermentation characteristics ( Blount et al.

, 2009 )

. There are v arieties of soybean specifically developed for grazing and hay, but use of the standard grain varieties often is recommended because of the whole plant feeding value ( Weiderholt and Albrecht, 2003 )

.

Non

- GE soybean varieties, both those developed for conventional use and for use in organic production systems, are not evaluated by any regulatory agency in the U.S. for human food or animal feed safety prior to release in the market. Under the FFDCA , it is the responsibility of food and feed manufacturers to ensure that the products they market are safe and properly labe led. Food and feed derived from any GE crop events must be in compliance with all applicable legal and regulatory requirements.

Food safety reviews frequently compare the compositional characteristics of the GE crop with

non

- transgenic, conventional varieties of that crop (see e.g., ( Aumaitre et al. , 2002 ; FAO, 2009 ) ). Moreover, this comparison also evaluates the composition of the modified crop under actual agronomic conditions , including various agronomic inputs ( Monsanto, 2012a ; 2012b )

. Composition characteristics evaluated in these comparative tests include moisture, protein, fat, carbohydrates, ash, minerals, dietary fiber, essential and non

- essential amino acids, fatty acids, vitamins, and anti

- nutrients ( Monsanto, 2012a ; 2012b )

. 93Anti

- nutrients represent an important element of food safety comparisons that follow US

- FDA’s guidelines ( DAS, 2013a )

. Anti

- nutrients are compounds produced by a plant that interfere with the absorption and metabolism of the consumed vegetable as well as other foods in the digestive
tract ( Cordain, 1999 )

. Anti

- nutrients commonly found in raw soybean include trypsin inhibitors and lectins ( US

- FDA, 2011b )

. Some plant constituents are toxins, such as g ossypol

. Exce pt for varieties bred to suppress the trait, it is produced in glands on cotton stems, true leaves, bolls, and other plant parts

. Gossypol is toxic to humans, pigs, chickens, and some other animals

, so its presence reduces the value of cottonseed for food and feed

. Gossypol

- producing varieties have been shown to reduce rabbit and rodent feeding o n cotton ( Rude, 1984 )

. There are multiple ways in which org a nisms can be genetically modified through human intervention

. T raditional methods include breeding or crossing an organism to elicit the expression of a desired trait, while more contemporary approaches include the use of biotechnology such as genetic engineering to produce new organisms ( Committee on Identifying and Assessing Unintended Effects of Genetically Engineered Foods on Human Health, 2004 ) . As noted by the National Research Council (NRC), unexpected and unintended compositional changes arise with all forms of genetic modification, including both conventional hybridizing and genetic engineering ( NRC, 2004 )

. The NRC also noted in its 2004 report that no adverse human health effects attributed to genetic engineering have been documented. Reviews on the nutritio nal quality of GE foods generally have concluded that there are no biologically meaningful nutritional differences in conventional versus GE plants for food or animal feed ( Aumaitre et al. , 2002 ; Faust, 2002 ; Van Deynze et al. , 2005 )

. More recently, the NRC found the cultivation of GE crops resulted in changes in pesticide application practices ( NRC, 2010b ) . For example, this included applications of fewer pesticides or using pesticides wi th lower environmental toxicity. Consequently the cultivation of HR crops is advantageous because of their superior efficacy in pest control and concomitant economic, environmental, and presumed personal health advantages ( NRC, 2010b )

. Human health topics associated with GE crops include the potential toxicity of the introduced genes and their products, the expression of new antigenic proteins, and altered levels of existing allergens ( Malarkey, 2003 ; Dona and Arvanitoyannis, 2009 )

. Under the FFDCA , it is the responsibility of food and feed manufacturers to ensure that the products they market are s afe and labeled properly

. Food and feed derived from GE organisms must be in compliance with all applicable legal and regulatory requirements. GE organisms for food and feed may undergo a voluntary consultation process with the FDA prior to release onto th e market. The PAT protein, conferring resistance to glufosinate, has already been evaluated by FDA; soybean s (and other crops) containing the pat gene are already in commerce.

3.6.1 Worker S afety

Approximately 3.1 million people in the United States are reported as farm workers, representing approximately 1 percent of the total U.S. population ( EPA, 2014 )

. Agriculture is one of the most hazardous industries for U.S. workers. Farmers and, in some instances, family members who share the work and live on the premises, are at a very high risk for fatal and nonfatal injuries.

94Worker hazards in farming are common to all types of agricultural production, and include hazards associated with operation of farm machinery and common agricultural management practices, such as pesticide application. Cuts, bruises, loss of fingers and limbs are exampl es of injuries resulting from mechanical hazards.

As a result, in 1990, Congress directed the National Institute of Occupational Safety and Health to develop a n agricultural safety and health program to address the high risks of injuries and illnesses experienced by agricultural workers and families. NIOSH supports and funds programs conducting research on agricultural injuries, as well as pesticide exposure, pulmonary disease, musculoskeletal disorders, hearing loss, and stress.

Pesticides, which inclu de insecticides and herbicides, are used on most U.S. soybean and cotton fields to manage weeds and pests

. Agricultural workers, including pesticide applicators, may be exposed to pesticides through mixing, loading, or applying chemicals, or by entering a previously treated field. As discussed in Subsection 1.5, Coordinated Framework Review and Regulatory Review, all pesticides labeled for use on crops in the United States must first be registered by the EPA and used in acc ordance with label instructions. A mong other elements, the EPA pesticide registration process involves the design of use restrictions that, if followed, have been determined to be protective of worker health . Worker safety precautions an d use restrictions are noted clearly on pesticide registration labels. These restrictions provide instructions as to the appropriate levels of personal protection required for agricultural workers to use herbicides. These may include instructions on person al protective equipment, specific handling requirements, and field reentry. Used in accordance with the EPA label, registered herbicides are determined to not p resent a health risk to workers.

In consideration of the risk of pesticide exposure to field wor kers, EPA’s Worker Protection Standard (WPS) (40 CFR Part170) was published in 1992 to require actions to reduce the risk of pesticide poisonings and injuries among agricultural workers and pesticide handlers

. The EPA Worker Protection Standard (WPS) (40 C FR Part 170) provides occupational protections to over 2 million agricultural workers and pesticide applicators at more than 600,000 agricultural establishments (farms, forests, nurseries and greenhouses) ( US

- E PA, 2014b ) . The WPS contains requirements on pesticide safety training, notification of pesticide applications, use of personal protective equipment, restricted entry intervals following pesticide application, decontamination suppl ies, and emergency medical assistance. Under the WPS, the EPA requires the pesticide label to specify personal protective equipment and restricted entry intervals that wil l p rovide an appropriate level o f pr otection, based on the properties of the product. F urthermore, the Occupational Safety and Health Administration (OSHA) require all employers to protect their employees from hazards associated with pesticides and herbicides.

On February 20, 2014, the US

- EPA announced proposed changes to the agricultural WPS to increase protections from pesticide exposure for agricultural workers and their families 9

. The EPA is proposing to strengthen the protections provided to agricultural workers and handlers under the WPS by improving elements of the existing regulatio n, such as training, notification

,

9 For the proposed changes see: http://www.epa.gov/oppfead1/safety/workers/proposed/index.html

95communication materials, use of personal protective equipment, and decontamination supplies. The proposed changes to the current WPS requirements, specifically improved training on reducing pesticide residues brought from the treated area to the home on workers and handlers' clothing and bodies and establishing a minimum age for handlers and early entry workers, other than those covered by the immediate family exemption, mitigate the potential for chi ldren to be exposed to pesticides directly and indirectly. The EPA expects the revisions, once final, to prevent unreasonable adverse effect s from exposure to pesticides among agricultural workers and pesticide handlers ; vulnerable groups, such as minority and low

- income populations, child farmworkers, and farmworker families; and the general public.

To register a pesticide product, the EPA evaluates the potential risks to humans and the environment using various scientific studies designed to determine whether a potential product has the potential to cause adverse effects on wildlife, fish, humans (including acute, chronic, reproductive, and carcinogenic risk), and plants (including endangered species and other non

target organisms). The EPA requires reregistration of products with active ingredients registered prior to November 1, 1984, under the amended FIFRA in 1988

. Du ring the reregistration and registration renewal processes, the EPA thoroughly reviews the scientific database s underlying registrations for pesticides to ensure consistency with current scientific and regulatory standards

.
To determine the risks to workers from dicamba and glufosinate, the EPA evaluated exposure data in occupational worker safety evaluations and risk assessment s. For dicamba, the EPA completed the reregistration process and a Registration Eligibility Decision (RED) was issued in 2006. It was subsequently amended in 2008 and 2009 (US

- EPA, 2009). The EPA concluded
current dicamba uses were eligible for reregistration based on findings in three areas. First, the available data is adequate to support the continued registration of dicamba products and uses. Second, the worker exposure to dicamba for all registered agricultural uses, including exposures associated with the current preemergence cotton uses, meets the "no unreasonable adverse effec t s" criteria of FIFRA . Third, t here is a reasonable certainty that no harm will result to the general population, or to infants and children, as a result of aggregate exposure to dicamba residues ( US

- EPA, 2009a )

. The EPA assessed the safety of using glufosinate (as an active ingredient) to control broadleaf weeds on many crops, including cotton and soybeans, in a 2003 human health risk assessment in support of registration review ( US

- EPA, 2003 ) . The EPA performed a second human health risk assessment for registration of glufosinate use on citrus, pome, and stone fruits, olives and sweet

corn ( US

- EPA, 2012b ) . In 2013, the EPA updated their occupational assessment for glufosinate to include: (1) handler exposure and risk estimates for spot/directed treatments to citrus, pome, stone fruits, and olives, (2) handler exposure and risk estimates for the representative crops of

c orn, cotton, sorghum, and canola, and (3) a new summary of estimated post

- application risks for various crops ( US

- EPA, 2013b ) . Based on the most recent EPA review, glufosinate is currently registered for use on apples, berries, canola, citrus, corn, cotton, currants, grapes, grass grown for seed, olives, pome fruit, potatoes, rice, soybeans, stone fruit, sugar bee ts, and tree nuts with preplant and post

- emergent applications ( US

- EPA, 2013a )

. The EPA pesticide registration process involves the development of use restrictions that protect worker health regardless of changes in acreage, crops, farming practices, the amounts and types of pesticides, and concomitant risks to workers. Growers are required t o use pesticides in a
96manner consistent with the application instructions as provided on the EPA

- approved pesticide labels. Worker safety precautions and use restrictions are clearly noted on pesticide registration labels. These restrictions provide instru ctions for the appropriate levels of personal protection required for agricultural workers to use herbicides. These instructions may include requirements for personal protective equipment, specific handling requirements, and field reentry procedures. Used in accordance with the EPA label, registered herbicides are determined to not present a health risk to workers ( US

- EPA, 2009a ; 2013b )

. The current labels for both dicamba and glufosinate include label use restrictions intended to protect humans, including PPE to be worn during mixing, loading, applications and handling; equipment specifications to control pesticide application; and reentry periods that establish a safe duration between pesticide application and exposure to the pesticide in the field. Used in accordance with the EPA label, these herbicides are determined to not present a health risk to humans ( US

- EPA, 2013b )

. The greatest risk to human safety in agriculture is associated with physical injuries. These typically occur during maintenance and use of farm machinery. Cuts, bruises, loss of fingers and limbs are examples of injuries resulting from mechanical hazards.

3.6.2 Public Health

Health effects to the general public, including children in the vicinity of the cotton and soybean fields may arise from pesticide exposures via incidental ingestion, inhalation, and dermal contact. Pesticide exposures may occur from drift or accidental entry to the field during pesticide application. A dverse health effects to the general public, however, are not anticipated because of the pesticide label directions and restrictions, the EPA required agricultural workers trainings on proper pesticides uses, and restricted entry signage.

Health effects t o consumers may arise from pesticide exposure through the consumption of harvested cotton and soybean food products

. The EPA protects consumer health by setting tolerances (maximum residue levels), or establishing an exemption from the requirement for a
to lerance, under the FFDCA . A tolerance is the amount of pesticide residue that can remain on or in food for human consumption or animal feed. Before establishing a pesticide tolerance

, the EPA is required to reach a safety determination based on a finding of reasonable certainty of no harm under the FFDCA, as amended by the FQPA

. Consumers of cottonseed oil and/or processed soybeans may become exposed to residual levels of pesticides in these processed products or in animal

- based food products . The FDA controls pesticide residue limits (known as tolerances) in both cotton and soybean harvested food products, while the EPA established tolerances (the maximum pesticide residue levels can remain on food and feed products or commodities) protec t consumers from harmful levels of pesticides on food. For example, the EPA

- established dicamba residue tolerance of 0.2 ppm for cottonseed supporting the current uses of dicamba on cotton is the result of combining residue tolerances for both the parent d icamba and its metabolite 5

- hydroxy dicamba (40 CFR § 180.227). The EPA

- established glufosinate residue tolerances are 4.0 ppm and 15.0 ppm for cottonseed and gin by

- products, respectively (40 CFR § 180.473). Both of these tolerances include the combined residues of parent glufosinate and its metabolites N

- acetyl glufosinate

97and 3

- methylphosphinico

- propionic acid. Any adverse health effects from exposure to pesticide residues for cottonseed oil and processed soybean consumers are minimized by FDA residue

m onitoring and EPA tolerance requirements.

A variety of opinions exist on the human health safety of genetically modified foods. The American Association for the Advancement of Science concluded that consuming food containing ingredients derived from genetically modified crops is not riskier than consuming the same food containing ingredients f rom crops modified by conventional plant breeding techniques. The NRC ( NRC, 2004 ) found that no adverse health effects attributed to genetic engineeri ng had been documented in the human population . They also indicated the contribution of genetically engineered food to the genetic vulnerability of some individuals to some compounds is unclear ( NRC, 2004 )

. A European Union

- (EU) funded GMO research ( Commission, 2010 ) concluded at le ast equal assurance of the safety of GM foods compared to conventional counterparts. The World Health Orga nization concluded that GM foods currently available on the international market are not likely to present risks for human health based on risk assessment results. These risk assessments evaluate five types of d irect health effects: (1) any tendencies to provoke allergic reactions, (2) specific components thought to have nutritional or toxic properties, (3) the stability of the inserted gene, (4) nutritional effects associated with genetic modification, and (5) a ny unintended effects resulting from the gene insertion ( WHO, 2014 )

. ( Lendman, 2014 ) GE organisms used for food or feed purposes undergo a voluntary consultation process with the FDA prior to release to the U.S. market ( US

- FDA, 2001 ) . The FDA established this voluntary consultation process to review the safety of foods and feeds derived from GE crops for human and animal consumptions

. During the consultation, FDA evaluates the scientific and regulatory assessment s ummary of the food and feed safety of a product submitted by a developer, and responds to the developer by letter ( US

- FDA, 2014 ) . De veloper s intending to commercialize a bioengineered food meet with the FDA to identify and discuss relevant safety, nutritional, or other regulatory issues regarding the bioengineered food . They submit a summary of their scientific and regulatory assessment of the food includin g: ( 1) an evaluation of the amino acid sequence introduced into the food crop to confirm whether the protein is related to known toxins and allergens, ( 2) an assessment of the protein’s potential for digestion, and ( 3) an evaluation of the history of safe use in food ( Hammond and Jez, 2011 ) . The genetically engineered MON 88701 cotton and MON 87708 soybean completed the FDA consultation process with no further questions ( US

- FDA, 2011b ; 2013 )

.
3.7 Cotton and So ybean Production as Related to the Affected Environment

Some of the trends in U.S. cotton and soybean production from 1980 to 2011 are summarized in Table 12 ( Field

- to

- Market, 2012 )

. Th e cotton information was derived by combining seed and lint information at the percentages of production (83% lint and 17% seed). The total production for both crops increased through 2011. While soybean production continues to increase, cotton production decreased in the past few years ( USDA

- OCE, 2014a )

. From 1980 to 2011, the land

use trends showed an increase in efficiency based on the incre ased yield combined with reductions in the acres per unit of production. Soil erosion and irrigation efficiency increased during the interval, probably as a result of the adoption of conservation tillage and improved irrigation technolog ies by growers. While overall CO 2 emission equivalents increased, the 98concomitant decreases in emissions per unit of production suggest awareness of agricultural contributions to GHG may be leading to conservation efforts.

Table 12

. Summary of Trends in U.S. Cotton and Soybean Production, Resource Use and Impact from 1980

- 2011

. Soybean Cotton

Indicator Percent Change 1 Indicator Percent Change

Trend 2 Entire Period Compound Annual Trend Entire Period Compound Annual Crop Yield Total Production ↑ 96 2.2 Total Production ↑ 55 1.4

Land Use Total Planted

Acres ↑ 24 0.7 Total Planted

Acres ↑ 11 0.3

Acres per

Bushel ↓ (35) (1.4) Acres per Pound ↓ (30) (1.2)

Soil Eroded Total Tons ↓ (28) (1.0) Total Tons ↓ (42) (1.7) Tons per

Bushel ↓ (66) (3.5) Tons per Pound ↓ (68) (3.6)

Irrigate Water Total Volume ↑ 271 4.3 Total Volume ↓ (35) (1.4)

Volume per Bushel ↓ (42) (1.8) Volume per Pound ↓ (75) (4.4)

GHG:

CO 2 Total Pounds ↑ 13 0.4 Total Pounds ↑ 10 0.3

Pounds per Bushel ↓ (41) (1.7) Pounds per Pound ↓ (30) (1.1)

1 Percent change results are based on a least squares trends analyses from 1980

- 2011. Source: ( Field

- to

- Market, 2012 ) citing: (1) U SDA, NASS, Census of Agriculture, Farm and Ranch Irrigation Survey http://www.agcensus.usda.gov/Publications/index.php

. (2) USDA, Economic Research Service (ERS), (ARMS) http://www.ers.usd a.gov/Briefing/ARMS/Access.htm; (3) USDA, National Resources Conservation Service (NRCS), National Resource Inventory (NRI) Reports http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/technical/nra/nri
2 Trend direction: ↑ = Increasing, ↓ = Decreasing.

99

### 4 POTENTIAL ENVIRONMEN TAL CONSEQUENCES

This chapter examines the environmental effects associated with the alternatives on the affected environment (as identified in Chapter 2). In this chapter, APHIS only examines t he direct and indirect effects of its decision regarding the regulatory status of MON 88701 cotton and MON 87708 soybean. While the Agency recognize s that these varieties were engineered to be resistant to applications of the herbicide dicamba, the EPA has the regulatory authority to approve new

uses of all pesticides, including those for dicamba on MON 88701 cotton and MON 87708 soybean. The EPA is currently evaluating the proposed new uses of dicamba for these varieties

, and is the Federal agency which de termines possible human health and environmental
consequences of dicamba use in agriculture. The EPA registers herbicide use when consistent with a conclusion of no unreasonable environmental impacts

. In this chapter, we assume that any use of dicamba should be discussed as a cumulative effect of APHIS ’ action combined with future actions that may be taken by the EPA or other a gencies. Thus, the analysis of these possible cumulati ve effects is discussed in Section 5 of the EIS.

4.1 No Action Alternative

Under the No Action Alternative, APHIS would not approve the petitions for deregulation. This alternative represents the status quo, or the situation that would occur if APHIS denies the petitions. This section describes the effects of cotton and soybean production on the human environment that are occurring and are anticipated to continue to occur if APHIS selects the No Action Alternative. The analysis examines the effects of cotton and soybean production on physical, natural and biological resources to allow meaningful comparison to the other

a lternatives reviewed in this document

.

4.1.1 Land Use and Acreage

Cotton
In the U.S., cotton is grown exclusively in the southern states because this is the only U.S. region with a growing season long enough for cotton to mature

. During the past 10 years, total U.S. cotton acreage has varied from approximately 9.15 to 15.77 million acres, with the lowest
acreage reco rded in 2009 and the highest in 2001 (See Figure 13 ) ( USDA

- NASS, 2014a )

. In 2013, the harvested acreage for all types of cotton was 7.66 million acres, a reduction of 18 percent from the previous year ( USDA

- NASS, 2014a )

. The most recent USDA projections for cotton anticipate an increase to 11 million acres in 2014 ( USDA

- OCE, 2014b ) . Prices for competing crops are projected to fall more than cotton prices, making cott on cultivation more favorable. The trend for cotton acreage planti ngs over the projection period shows a decrease to 10 million acres in 2015 and remains near that level for the remainder of the projection period, as a result of projected world and U.S. cotton prices below the recent 5

- year average ( USDA

- OCE, 2014b )

. Under the No Action Alternative, the projected acreage of cotton production is not expected to change over the next decade

.

100Figure 13

. Acres of U pland and P ima C otton P lanted and H arvested from 1993 to 2013. Source: ( USDA

- NASS, 2014e )
Soybean During the last two decades, the number of acres planted to soybeans increased because of favorable prices ( USDA

- ERS, 2012a ) (see Figure 14 ). This increase in soybean production was accompanied by decreases in other crops, including upland cotton, corn grown for silage , spring and specialty wheat, and oats ( USDA

- ERS, 2011c )

. In 2013, 75.9 million acres of soybeans were harvested in the U.S., a slight decrease f rom the 75.9 m illion acres harvested in 2012. However, the 2013 soybean harvest was the fourth highest on record, and production was up 8 percent from 2012 ( USDA

- NASS, 2014a )

. The most recent USDA projections are for U.S. soybean plantings to remain near 78 million acres through 2023 ( USDA

- OCE, 2014b ) . The expected growth in the demands for soybean for domestic use and export will result in price increases, allowing soybeans to compete with corn and other crops for la nd use ( USDA

- OCE, 2014b ) . Under the No Action Alternative, the projected acreage of soybean production is not expe cted to change over the next decade.

101Figure 14

. Acres of S oybeans P lanted and H arvested from 1993 to 2013. Source: ( USDA

- NA SS, 2014e )

G enetically E ngineered Cotton and Soybean
Under the No Action Alternative, the current trend of adoption of GE cotton and soybean varieties by U.S. farmers is likely to continue

. However, continued adoption in the future will depend on whethe r growers continue to derive benefits from GE crops and will be dependent on the ability of farmers to adopt best management practices to avoid resistance issues, the ability of biotech companies to develop new GE varieties, and consumer acceptance of prod ucts from GE

sources ( Fernandez

- Cornejo et al. , 2014b )

.
Growers can choos e from a large number of cotton or soybean hybrids produced from conventional bre eding or GE practices . Like other major commodit ies , GE varieties of cotton and soybean have been adopted during the past decade. Large

- scale field testing of GE crops began i n the 1980s, but it was not until 10 years later that the first generation of GE varieties became commercially available ( Fernandez

- Cornejo and Caswell, 2006 )

. Since commercial introduction in 2000, GE cotton h as expanded to approximately 90 percent of U.S. cotton acreage in 2011 ( USDA

- ERS, 2014a )

. Of that number, 15 percent of the U.S. cotton cro p was GE HR, 17 percent was insect

- resistant, and 58 percent was stacked with both GE herbicide resistance and insect resistance ( USDA

- ERS, 2014a )

. Since GE soybeans became commercially available in 1996, their use has expanded to greater than 90 percent of the total U.S. soybean acreage ( USDA

- ERS, 2014a ) . Although other varieties are available for selection by growers, the Roundup Ready ® GR varieties continue to dominate the market ( Tarter, 2011 ) . Other cultivated HR soybeans include the LibertyLink ® soybean varieties (a GE soybean that is resistant to glufosinate ammonium herbicide and was granted nonregulated status in 1996) and STS (a conventionally bred sulfonylurea

- resistant soybean first introduced in 1993). As of 2012, 3.9 percent of U.S. soybean acres planted were glufosinate

resistant ( DAS, 2013a )

. Varieties with other GE traits, such as lepidopteran resistance, high oleic acid content, improved fatty acid profile, and increased stearidonic acid have since been granted
102nonregulated status ( USDA

- APHIS, 2014c ) . Of these, at this time, only high oleic acid content soybean has been commercialized.

4.1.2 Socioecon o mics

Domest ic Cotton and Soybean Production Under the No Action Alternative, MON 88701 cotton and MON 87708 soybean will continue to be regulated articles under 7 CFR Part 340. Growers and other parties who are involved in production, handling, processing, or consumption of cotton and soybean will continue to have access to nonregulated GE and non

- GE cotton and soybean varieties. Domestic growers will continue to utilize GE and non

- GE cotton and soybean varieties based upon availabi lity and market demand.

Management practices associated with cotton and soybean production, including uses of agronomic inputs, vary from grower to grower, and would not be affected under the No Action Alternative. Farm income is positively impacted by GE cotton and soybean by reducing production cost s (e.g., reduced tillage for weed management and, potentially, reduced herbicide

use ). While growers are expected to continue benefiting from the adoption and cultivation of currently deregulated GE crops, growers in some U.S. regions with HR wee d problems may incur increased costs because of the increased need for more pesticide treatmen ts and/or increased tillage. These trends are unaffected under the No Action Alternative.

Cotton

In 2014, the area planted for all cotton is expected to total 11.1 million acres, 7 percent above 2013 acreage ( USDA

- NASS, 2014b )

. This increase is anticipated because of the lower prices expected for competing crops as compared to cotton prices ( USDA

- OCE, 2014b ) . Upland cotton area is expecte d to total 10.9 million acres, up 7 percent from 2013; Pima cotton area is expected to total 158,000 acres, a 21 percent decrease from 2013 ( USDA

- NASS, 2014b ) . Cotton acreage in 2015 is projected to fall to 10 million and remain near that level through 2023 with both world and U.S. cotton prices projected below the recent 5

- year average ( USDA

- OCE, 2014b )

. In 2013, all cotton production in the U.S. is estimated at 13.2 million 48 0

- pound bales, a decrease of 24 percent from 2012. Cotton yield is estimated at 826 pounds per acre, 61 pounds per acre less than last year ( USDA

- NASS, 2014b )

. As a result of both higher planted acreage and expected lower abandonment, the U.S. cotton crop is projected to rise sharply to 16.3 million bales in 2014/15 ( Johnson et al. , 2014 )

. U.S. mill use fell to a low of 3.3 million bales in 2011, but has moved higher and is estimated at 3.7 million bales for 2014 ( National Cotton Council of America, 2014 ) . U.S. mill use of upland cotton is projected to rise moderately, while cotton exports appear likely to remain level after 2016/17 ( USDA

- OCE, 2013 ) ( Figure 15 ). With the help of the Economic Adjustment Assistance Program that began with the 2008 Farm Bill

, and is continued under the 2014 Farm Bill, new investments and expansions within the U.S. cot ton industry are reported with companies upgrading existing facilities and/or building new facilities. New plants are scheduled to open beginning in early 2015 ( Adams et al. , 2014 ) . The 2014/15 marketing year average price received by U.S. cotton producers is projected to range between 65 and 70 cents per pound, 103which is below the 2013/14 mid

- point estimate of 76 cents per pound. Supporting the lower price projection s are December 2014 cotton futures, which as of early February, were around 77 cents per pound ( Johnson et al. , 20 14 )

.

Figure 15

. Domestic M ill U se and E xports of U.S. U pland C otton with P rojections T hrough 2022. Source: ( USDA

- OCE, 2013 )
Soybean

U.S. soybean production in 2013 totaled 3.29 billion bushels, an 8 percent increase from 2012 and the third largest on record ( USDA

- NASS, 2014a ) . According to USDA

- NASS, the average yield per acre for 2013 is estimated at 43.3 bushels, 3.5 bushels per acre more than 2012 yield ( USDA

- NASS, 2014a ) . USDA forecasts an increase in soybean planted area for 2014 at a record high of 81.5 million acres, a 6 percent increase from 2013 ( USDA

- NASS, 2014b ) . Projections for U.S. soybean plantings through 2023 indicate plantings remaining near 78 million acres over most of the projection period ( USDA

- OCE, 2014b )

. Soybean prices are expected to increase from growth in both domestic use and export demand (see Figure 16 ), and are projec ted to remain historically high ( above pre

- 2007 levels ) ( USDA

OCE, 2014b ) . The average U.S. on

- farm ma rket price for soybeans for the 2012

- 13 marketing year increased to $14.40 per bushel, compared to $12.50 per bushel for the 2011

- 12 and $11.30 per bushel for the 2010

- 11. On

- farm soybean market prices for the 2013

- 14 marketing year are estimated by USDA t o fall from the previous year’s high to an average $12.70 per bushel ( Corn and Soybean Digest, 2014 ) . Soybean prices are then estimated to rise moderately after 2015

- 16, as a result of increasing demand for soybeans and soybean products ( USDA

- OCE, 2014b )

.

104Figure 16

. Projections of U.S. S oybean D omestic U se and E xports to 2023

. Source: ( USDA

- OCE, 2014b )
These trends in domestic production and uses for cotton and soybean are not expected to change under the No Action Alternative.

Foreign Trade U.S. crop e xports have experienced steady growth in recent years. From 2009

- 2013

, the value of agricultural exports in the U.S. increased from $96.3 to $141.0 billion. Fiscal year (FY) 2015 agricultural exports are projected to be $144.5 billion ( USDA

- ERS, 2014c ) . The FY 2015 export forecast for oilseeds and products is projected at $29.7 billion, and for cotton $4.1 billion ( USDA

- ERS, 2014c ) . Exports for both soybean and cotton are expected to increase through 2023 under the No Action Alternative, although the 37.6% U

. S

. share of the world soybean exports will decline slightly by 2023, and the 26.7% share of world cotton will also decline slightly ( USDA

- OCE, 2014b )

. The USDA anticipates world cotton production will exceed consumption for the fifth consecutive season. Production throughout the world is expected to rise by l ess than 1 percent to 117.0 million bales

, resulting from lower production in China, Brazil, and Australia being offset by an increase in U.S. production. Global 2013/14 cotton p roduction is expected to fall 5 percent from the previous year to 116.7 millio n bales. The harvested area is estimated at 33.1 million hectares, down 3.5 percent from last year. World average yield is 766 kilograms ( kg ) /hectare, down 2 percent ( Johnson et al. , 2014 )

.
World trade is forecast down 18 percent from last season, the large fall in imports by China masks strong demand elsewhere

. Imports in the rest of the world are forecast to increase 7 percent ( Johnson et al. , 2014 ) . Improved textile demand and lower cotton price volatility is anticipated to support a slight recovery in cotton’s fiber share ( Johnson et al. , 2014 )

. U.S. exports are forecast to rise in 2013/14 and appear likely to level off after 2016/17 ( USDA

- OCE, 2013 ) 105( Figure 15 ). Exports for most other major exporters will remain near 2013/14 levels ( Johnson et al. , 2014 )

. Overall, USDA projects that world cotton trade will trend upward at a growth rate of 3.8 percent between 2014/15 and 2023/24 (see Figure 17 ) ( USDA

- OCE, 2014b )

.

Figure 17

. Projections of G lobal C otton E xports to 2023

. Source: ( USDA

- OCE, 2014b )
An increase in U.S. cotton acreage coupled with high worldwide reserves is considered likely to reduce prices in the medium term, primarily due to the lag between cotton production and cotton demand ( AgriMoney, 2014 ) . World stocks more than doubled, mainly due to cotton policies in China. USDA projects that lower China domestic support leve ls, higher stocks outside of China, and falling grain and oilseed prices could reduce the world cotton price to a 5

- year low ( John son et al. , 2014 )

. H igher world ‘free’ stocks and lower price projections for the 2014 corn and soybean crops will also affect U.S. cotton prices ( Johnson et al. , 2014 )

. Soybean exports in the form of bulk beans, meal, and oil are a major share of the total agricultural exports for the U.S. ( Figure 18 and Figure 19 ).The U.S. was responsible for 35 percent of world soybean production, 21 percent of world soybean meal prod uction, and 21 percent of soybean oil production ( USDA

- FAS, 2013a ) . The U.S., Brazil, and Argentina are expected to continue to account for 88 percent of global exports of soybeans and soybean products ( Figure 20 ). Underlying these projections is an assumption that China would continue to be heavily reliant on soybean imports ( Figure 21 ), which are projected to rise 59 percent to 90 million tons in 2021/22 ( USDA

- OCE, 2013 )

.

106Figure 18

. Projections of G lobal C otton I mports to 2023. Source: ( USDA

- OCE, 2014b )

Figure 19

. Project ed U.S. G lobal E xports of S oyb eans, S oybean M eal, and S oybean O il. Source: ( USDA

- OCE, 2014b )

107Figure 20

. Projections of G lobal S oybean E xports to 2023. Source: ( USDA

- OCE, 2014b )

Figure 21

. Projections of G lobal S oybean I mports to 2023. Source: ( USDA

- OCE, 2014b )
China is the largest importer of U.S. soybeans and soybean products at 50 percent of the total value of U.S. soybean and soybean product exports, followed b y Mexico (8.9 percent) and Japan (4.2 percent) ( USDA

- FAS, 2013a ) . Over the next decade, global trade in soybeans is expected to increase by 31 percent, soybean meal by 17 percent, and soybean oil by 12 percent.

108Under the No Action Alternative, the U.S. is expected to continue to be a leading producer and exporter of cotton and soybean products.

4.1.3 Agronomic Practices in Cotton and Soybean Production

Under the No Action Alternative, MON 88701 cotton and MON 87708 soybean w ould continue to be regulated by APHIS

. Current availability and usage of commercially

- available (both GE and non

- GE) cotton and soybean varieties are expected to remain the same under the No Action Alternative.

General agronomic practices such as plantin g and harvesting times, crop nutrition, use of plant growth regulators, and pre

- harvest and harvest practices are expected to remain the same Specialized agronomic practices such as row spacing, the use of cover crop s and crop rotation practices, as well as adoption of precision agriculture may change over time.

Tillage

Under the N o A ction A lternative, if hard

- to

- control and/or GR weeds continue to be problematic

or to become a problem where they were not previously found, cotton and soybean growers may need to increase or revert to conventional tillage or hand

- weeding. This may be a greater problem in soybean growing states because of the high prevalence of no

- tillage used for soybean production.

Most growers are n ot expected to increase tillage in the short

- term due to the economic (reduced fuel use, less time in the field) and environmental benefits (reduced soil erosion and better moisture retention) associated with these practices. The increase of GR weeds makes glyphosate use less attractive, although, glyphosate still controls large numbers of weeds ( Monsanto, 2013a )

. Mid

- South and possibly Southeastern states soybean growers who previously adopted no

- till production are now replacing that with increasingly aggressive tillage in their management
pr ograms (see Cumulative Impacts: Cotton and Soybean Agronomic Practices and Costs of Production

, Changes in Tillage). In parts of the Heartland, GR waterhemp and marestail are widespread ( Bowman, 2013 ) . No

- till practices are being maintained in many areas , but the presence of HR weeds and rapidly increasing presence of GR weeds in particular, sometimes necessitate the i nclusion of tillage in weed control strategies ( Arbuckle and Lasley, 2013 )

. An Iowa poll disclosed that farmers ther e used mechanical weed control (i.e., cultivation) 25 percent of the time, and 55 percent found it to be effective or very effective for weed control ( Arbuckle and Lasley, 2013 ) . Farmers apparently value soil cultivation for weed control, but practice it only to a limited extent (25 percent ) at present.

The fact that tillage is increasing in soybean productio n suggests that this trend may continue under the No Action Alternative as herbicide

- resistant weeds become more difficult to control with available herbicide chemistries. In an attempt to offset the increase in tillage that might otherwise result in the effort to ma nage herbicide resistant weeds, the Natural Resources Conservation Service (NRCS) is offering farmers technical and financial assistance to manage herbicide resistant weeds while maintaining conservation stewardship through two programs: the Conservation Security Program and the Environme ntal Quality Incentives Program.

109In the majority of the states that produce cotton, conventional tillage is used ( USDA

- NRCS, 2013d ) , suggesting that the existing practice of conservation agriculture before the era of HR crops provide erosion control, but that no additional erosion loss improvements derive from use of HR crops

. Other benefits of conservation tillage can be measured in improvements to soil organic matter, stability, infiltration, nutrients, and water management ( USDA

- NRCS, 2006b )

. However, Alabama, North Carolina, South Carolina, and Tennessee are cotton

- producing states where no

- till exceeds conventional tillage (Table 13)

. (In the era beginning with the first herbicide resistant crops (1996/1997) and through 2010, the rate of this erosion stabilized at around 1 billion tons per year (USDA

- NRCS, 2013d) suggesting that the existing practices of conservation agriculture before the era of herbicide resistant crops provide erosion control, but that no additional erosion loss improvements derive from use of HR crops. Other benefits of conservation tillage can be measured in improvements to soil organic matter, stability, infiltration, nut rients, and water management (USDA

- NRCS, 2006c)

I n these states, shifts toward conventional tillage may be more dramatic as GR weeds increase. Overall, conservation tillage is likely to decrease over time as GR weed populations continue to develop and spre ad. Under the N o A ction A lternative, an increase in the use of traditional tillage methods in states where GR weeds may be found could result in the potential loss of many of the benefits of conservation tillage. In areas where the NRCS had agreements with growers that restrict cultivation, an increasing number of variances are likely to be needed to accommodate grower needs.

Conservation tillage provides growers with benefits that include reduced soil erosion. The period before HR crops began to be commerc ialized and for which NRCS has records, shows that for U

. S

. cropland from 1982

- 1997, rill erosion (i.e., small channel) and surface erosion was declining ( USDA

- NRCS, 2013d )

. The reduction in erosion was accompanied by an increasing trend towards various types of conservation tillage (about 11% between 1990 and 1998 ); by the period 1998

- 2004, use of conservation tillage showed an increase of less than 3 percent ( Conservation

- Technology

- Information

- Center, 2006 ) . In the era beginning with the first herbicide resistant crops (1996/1997) and through 2010, the rate of this erosion stabilized at around 1 billion tons per year ( USDA

- NRCS, 2013d ) suggesting that the existing practices of conservation agriculture before the era of herbicide resistant crops provide erosion control, but that n o additional erosion loss improvements derive from use of HR crops. Other benefits of conservation tillage can be measured in improvements to soil organic matter, stability, infiltration, nutrients, and water management ( USDA

- NRCS, 2006c )

Table 13 . Tillage P ractices by C rop, 2007. Tillage M ethod Soybean Cotton
Acres in No

- Till Exceeds Conventional Tillage Illinois Indiana Kansas Kentucky Maryland Michigan Missouri Alabama North Carolina South Carolina Tennessee

110Tillage M ethod Soybean Cotton
North Carolina Ohio Pennsylvania South Dakota Virginia Wisconsin Acres in Conventional Tillage Exceeds Other Types of Tillage Arkansas Louisiana Arkansas California Georgia Louisiana Mississippi Missouri Texas Mulch Till Exceeds Other Types of Tillage Iowa Minnesota Nebraska North Dakota New York
Data derived from ( USDA

- ERS, 2014b )

. Crop Rotation Crop rotations are unlikely to change u nder the N o A ction A lternative, because existing varieties can be profitably produced by continuing to use current methods

. T his likely means continued reliance on producing cotton in a monoculture unless a cover or rotational crop can either reduce pests or soil compaction, or is needed to increase soil fertility. For soybeans, increased rotations are likely to continue as long as the crops ca n be profitably produced.

C otton should be rotated with other crops on a regular basis to maintain soil productivity and reduce the incidence of various weeds, insect pests, or diseases ( Hake et al. , 1996 ) . However, because of economic factors including production cost s, relative rate of return, and current market conditions, continuous cotton production has been and is likely t o remain unchanged on the majority of U.S. cotton acres ( Sandretto and Payne, 2006 ; USDA

- ERS, 2006 ) . By region, however, different patterns of rotation exist. Based on interviews conducted by Monsanto in 2010, approximately 54 percent of U.S. cotton acres are followed by cotton in the crop rotation sequence. By region, this percent is highest in the Southwest (61 percent ) and lowest in the West (30 percent ). Only in the West region is cotton rotated to another crop, wheat, on the majority of cotton acres. Corn (16 percent ), wheat (9 percent ), soybean (8 percent ), sorghum (8 percent ), and peanuts (4 percent ) are the other crops most frequently rotated with
cotton ( Monsanto, 2013a ) . Based on recent state

- specific information from interviews with university exte nsion crop production specialists and extension weed control specialists, regional changes in crop rotation patterns on cotton fields may be occurring due to economic factors, including production costs related to GR weeds.

Crop rotation is a common practice on U.S. soybean fields. Soybeans are often rotated with corn, winter wheat, spring cereals, and dry beans ( OECD, 2000 ) , the selection of which varies 111regionally. Corn is the most commonly rotate d crop with soybeans. USDA ARMS results for corn and soybean indicate a small increase in corn in rotation and continuous corn over the past decad e ( US

- FDA, 2011b ; Ebel, 2012 )

. Returns for producers from a corn

- soybean rotation are variable and depend on the price and projected yield of both corn and soybean for an individual operator ( Stockton, 2007 ) . Studies have found the soybean yield tends to increase under this rotation sequence and is attributed to an effec tive break in the soybean disease and pest cycle ( Nafziger, 2007 ; Al

- Kaisi, 2011 ) . Soybean itself may be a cover crop in short rotations because it contributes nitrogen to the soil ( Hoorman et al. , 2009 ) . Continuous soybean production is sometimes practiced , but yield can be reduced the second or later years as pest and disease incidence tend s to increase ( Pedersen et al. , 2001 ; Monsanto, 2010 )

. As described in the No Action Alternative analysis of tillage, tillage may increase as part of the effort to manage herbicide

- resistant wee ds. In an attempt to offset the increase in tillage that might otherwise result in the effort to manage herbicide resistant weeds, the Natural Resources Conservation Service ( NRCS ) is offering farmers technical and financial assistance to manage herbicide resistant weeds while maintaining conservation stewardship through two programs: the Conservation Security Program and the Environme ntal Quality Incentives Program . Among the practices that qualify for financial and technical incentives are the use of c over crop ping and crop rotation

. As a result, cover cropping and crop rotation, both of which have been shown to reduc e weed pressure , are practices that are expected to increase under the No Action Alternative.

Agronomic Inputs

Nutrients/Fertilizer

Under the N o A ction A lternative, cotton and soybean fertilizer requirements for macronutrients (including nitrogen, phosphorus, and potassium) and micronutrients ( such as zinc, iron, and magnesium ) are not likely to change because fertilizer formulations will continue to be applied to existing varieties of cotton and soybeans.

With respect specifically to soybean, some growers will add microbial inoculants to the soil to facilitate the symbiotic relationship between nitrogen

- fixing bacteria and soybean ( Conley and Christmas, 2005 ) . Industry has approximated that about one

- third of U.S. soybean acreage was inoculated in 2009 ( Seed Today, 2009 ) . Under the No Action Altern ative, the use of inoculates is unlikely to change from current use because of its benefits to soybean yield

.
Insecticides

The use of insecticides on cotton and soybean crops is likely to continue so long as insecticide

resistant pest populations do not de velop under the No Action Alternative.

In the U.S., the cotton industry has consistently relied heavily on insecticide use strategies to manage arthropod pests ( Gianesi and Carp enter, 1999 ) . Insecticides were applied to 66 percent of the cotton acreage in 2007 ( USDA

- NASS, 2008b ) . Of 30 listed insecticides, a cephate was the most utilized insecticide, with 26 percent of the pla nted acreage being treated at an average rate of 0.900 pounds per acre per crop year ( USDA

- NASS, 2008b ) . Dicrotophos was the second most

112commonly utilized insecticide, applied to 21 percent of the acreage at an average rate of 0.565 pounds per year ( USDA

- NASS, 2008b ) . Other insecticides applied in the 2007 growing year included a cetamiprid (6 percent of acreage), c yfluthrin (8 percent of acreage), c ypermethrin (7 percent of acreage), i m i dacloprid (6 percent of acreage), l ambda

- cyhalothrin (5 percent of acreage), m alathion (5 percent of acreage), and t hiamethoxam (11 percent of acreage) ( USDA

NASS, 2008 b ) . Overall, insecticide use in cotton has decreased while the adoption of GE Bt cotton varieties has increased ( Fernandez

- Cornejo et al. , 2014b )

. While insect management is important in soybean production

, the crop is able to sustain a substantial amount of insect damage without loss of yield. This resiliency of soybean aga inst insect damage is best represented by a 2006 survey ( USDA

- NASS, 2009e ) that found that insec ticides were applied to only 16 percent of the 72.9 million soybean acres planted in surveyed states in 2006. Of the 12 reported insecticides, the three most common

- lambda

cyhaloth rin, chlorpyrifos, and esfenvalerate

- were applied to 6, 5, and 3 percent of the planted acres, respectively ( USDA

- NASS, 2009e )

.
If insecticide

- resistant insect populations are selected for and reproduce unhindered, the use of a particular insecticide formulation is likely to diminish unless another MOA /chemistry becomes available. If new insecticidal chemistries become available, g rowers are likely to change to the novel insecticide until a resistant population arises. This pattern of insecticide use, followed by resistant pest populations developing and concomitant decease in use in the product is likely unless growers strategicall y deploy the use of existing insecticides. Integrated pest management (IPM) strategies currently in use seek to strategically use existing pesticides to ensure pesticide

resistant populations are less likely to develop and spread. Under the No Action Alter native, it is likely that the cost of insect control and the time spent managing insect pests in soybean will be similar to the current use levels . Under the No Action Alternative, insecticide use in cotton may increase if Bt

- resistant insect pests continu e to develop.

Herbicides

EPA

- registered herbicides will continue to be used for weed management on GE cotton a nd soybean varieties no longer regulated by APHIS

. The increase of GR weeds makes glyphosate use less attractive, although, glyphosate still cont rols large numbers of weeds ( Monsanto, 2013a )

. From 2008 to 2011, acres to which glyphosate was applied were either stable or declined, but other herbicides (residuals applied to soil that persist for extended periods) applied increased by 177 percent ( Monsanto, 2013a ) . To manage glyphosate resistance, growers are not using more glyphosate, but are using more sites of action in addition to glyphosate.

Dicamba is currently labeled for use in cotton only in pre

- plant applications because cotton plants can be damaged by t his herbicide ( US

- EPA, 2006b ; 2009c ) . Dicamba is limited to early
pre

- plant and late post

- emergence (pre

- harves t) applications in soybean. Under the No Action Alternative, the u se of GR cotton and soybean is expected to continue , accompanied by an increasing use of additional herbicides to control other HR weeds. The use of pre

- plant (less selective) residual herbi cides is also increasing and is likely to continue to increase.

The following section provides a brief background of herbicide use in cotton and soybeans in the U.S. It is provided to give the context for the analyses related to HR we ed selection (more

113information on these subjects is provided in Appendix 3 : Weed Management and Herbicide Use; Appendix 4 : Herbicide Use Trends in Cotton and Soybean; Appendix 5: Common Weeds in Cotton and Soybean; and Appendix 6 : Herbicide Resistance )

. Herbicide use in cotton differs substantially from that in soybean both in the types of herbicides used and the variety of herbicide sites of action (see Appendix 3 and 4 ). Cotton requires more time to develop a close d canopy than soybeans, so cotton becom es more susceptible to competition by early season weed s ( Frans and Chandler, 1989 )

. Cotton may be planted in wider

rows than soybeans, and the resulting light penetration into an unclosed canopy allows weed germination and growth over a longer period of time than in soybeans ( Frans and Chandler, 1989 )

. For these reasons, post

- emergent applications o f herbicides are more common in cotton crops than in soybeans , but there may be fewer herbicide options

. In contrast, soybean growers have come to rely almost exclusively on glyphosate for weed control. Prior to the adoption of GR soybean, growers relied h eavily on ALS and microtubule inhibitors. With the adoption of GR soybean, glyphosate was used on more than 95 percent of soybean acreage and by three quarters of soybean growers. Glyphosate represented the only herbicide site of action used. As GR weeds h ave become more prevalent, the trend among soybean growers is to use more sites of action including 2,4

- D, chloroacetamides, PPO and ALS inhibitors ( USDA

- NASS, 2013a ; Hartzler, 2014a ; VanGessel, 2014b )

.
As described in more detail in Appendix 4 , the trend to use more herbicides with different modes of action is observed for both cotton and soybean. Between 2009 and 2011, there was a 113 percent and 220 percent increase in pre

- and post

- application, respectively, of non

- glyphosate
treatments on GR cotton. F rom 2008 to 2011, there was also a 177 percent and 345 percent increase in the use of pre

- and post

- emergence herbicide application, respective ly, of non

glyphosate herbicides on GR soybeans ( Monsanto, 2013 a ) . With respect to dicamba, however,

a fter 1994, the use of dicamba steadily declined through 2006 to 17.4 million treated acres with 2.7 million pounds used because of competitive market introductions of sulfonylurea herbicides (chlorsulfuron, metsulf uron

- methyl, and thifensulfuron

- methyl) in wheat, new broadleaf herbicide active ingredients in corn, and GR corn. However, dicamba

- treated acres have increased by as much as 4.0 million acres since 2006. Most of the increase in dicamba

- treated acres has o ccurred in fallow, pastureland, sorghum, and cotton ( Monsanto, 2013a ) . Dicamba

treated acres have increased in cotton, in particular, because it is a common pre

- plant herbicide recommendation for GR marestail (horseweed) and Palmer amaranth in the Midsouth region ( McClelland et al. , 2006 )

. Approximately 25.3 million acres of crops were treated with dic amba in 2011 (see Table 8

- 1 in Appendix 8) . Based on USDA

- NASS ( USDA

- NASS, 2005b ; 2007a ; 2010b ; 2011c ; 2012d ) statistics, dicamba application rates ranged from 0.07 to 0.24 pounds per acre with the average number of applications ranging from 1 to 1.9 applications per cropping season. Dicamb a rates are lowest in barley, wheat and oats, where typically more than one application is made on these crops per cropping season.

Growers are also applying herbicides with different modes of action, and adopting other stewardship practices that reflect the recommendations for BMPs as outlined by the Weed Science Society of America and the National Science Foundation ( WSSA, 2010 ; Ferrell, 2013 )

. Heavily infested fields are being hand

- weeded at a cost of up to $100 per acre ( Ferrell, 2013 )

.

114While these changes are positive in that they diversify weed control, the cost of these treatments poses a substantive threat to soybean production in this region.

In additi on to increased tillage, growers are also using pre

- plant burndown treatments with multiple herbicides on their minimum

- till acres and are using residual herbicides more frequently ( Prince et al. , 2012b ) . They also are moving to multiple herbicide applications, and are applying herbicides with several different sites of action at different times over the course of the season to eliminate weeds (including some HR biotypes) . In an Iowa poll, farmers reported that 60 percent of the time, they used multiple herbicide modes of action ( Arbuckle and Lasley, 2013 )

. Increasingly, herbicide suppliers offer multiple herbicides as pre

- mixes ( Owen, 2014a ) . These might include both 2,4

- D and glyphosate as recommended in these regions by extension herbicide specialists ( Hartzler, 2014b )

.
Extension weed scientists estimated the increased cost of the additional herbicides needed to control glyphosate

- r esistant weeds in soybean to be as much as $42/acre (for Palmer amaranth in Tennessee), with most estimates of the increased costs falling in the range of $20 to $30/acre ( Carpenter et al. , 2002 ) . These costs will vary depending on the specific weed species present in any particular field. However, as resistance to glyphosate and other herbicides has developed and spread in weed populations, these costs ma y have increased since these estimates were made. For example, there are waterhemp populations in Iowa corn and soybean production fields with resistance to five herbicide sites of action (see ( Owen, 2012 ) ).

The continued selection of weeds resistant to glyphosate and other her bicides used will continue under the No Action Alternative. As such

, crop management practices will require modifications to address these weeds. These include management practices including the use of alternative herbicides for weed c ontrol, as well as mechanical cultivation practice s, and crop rotation ( Benbrook, 2009 ; Norsworthy et al. , 201 2 ) . Under the No Action Alternative, it is likely that the cost of weed management and the time spent managing weeds will continue to increase.

Organic Production Systems Under the No Action Alternative, the current availability of GE, non

- GE, and organ ic cotton and soybean would remain unchanged from what it is currently in the U.S. Organic seed producers would continue to utilize the same methods as applied in certified seed production systems designed to maintain soybean and cotton seed identity and meet National Organic Standards as established by the NOP

. P roduction costs associated with organic systems will also generally be higher than conventional systems, resulting i n higher pricing for organic cotton compared to conventional cotton.

The USDA census of organic agriculture reported organic cotton farming on 30 farms in the U.S. in 2008, two in Arizona, three in New Mexico, four in California, an d 21 in Texas ( USDA

NASS, 2008a ) . Texas (66 percent ) and New Mexico (20 percent ) together accounted for approximately 86 percent of the production. Based on USDA Economic Research Service ( ERS ) data, between 1997 and 2008, organic cotton acreage ranged from 9,213 acres in 2004 to 15,377 acres in 2008 ( USDA

- ERS, 2008 ) . In 2008 about 0.16 percent of the total 9.41 million acres of cotton was produced organically ( USDA

- ERS, 20 08 ) . In recent years, small and sporadic acreages of organic cotton production have been cultivated in other states, including Missouri,

115Illinois, Kansas, Tennessee, and Colorado ( USDA

- ERS, 2010 )

. As of 2012, the U.S. was the sixth

- ranking producer of organic cotton in the world, behind India, Syria, Turkey, China, and Tanz ania ( Memon, 2012 )

. Based upon recent trend information, the presence of GE cotton varieties on the market has not affected the ability of organic production systems to maintain their market share. Between 2000 and 2008, although 11 GE cotton events were no longer subject to regulation under the P PA and 7 CFR p art 340, the acreage of organic cotton
p roduction remained at approximately 15,000 acres ( USDA

- ERS, 2008 ; USDA

- APHIS, 2014c )

. Organic soybean production practice s include crop rotation , use of cover crop s, gre en and animal manures, application of rock minerals such as lime, other soil additives, mechanical weed control, biological control of pests, and disease control primarily through management practices ( Kuepper, 2003 ; (CAST), 2009 ; USDA

- AMS, 2011b )

. Organic soybean was produced on 96,080 acres in 2011 and yielded 2.9 million bushels, equal to approximately 0.09 percent of U.S. soybean production ( USDA

- NASS, 2013d ) . The average yield was 30 bushels per acre

. Major production states are Iowa, Minnesota, Michigan, New York, Illinois, Ne braska, and Wisconsin ( USDA

- NASS, 2012a )

. Based upon recent trend information, the presence of GE soybean varieties on the market has not affected the ability of organic production systems to maintain their marke t share.

All producers of organic or specialty crops must address the potential for cross

- pollination with undesired varieties, which may include GE varieties. Methods such as isolation distance s, use o f border or barrier rows, and differing planting schedules are used by producers of specialty crops to prevent unwanted material from entering their fields ( Wozniak, 2002 ; NCAT, 2003 ; Bradford, 2006 ; T homison, 2009 ; Roth, 2011 ) . Several categories of specialty soybeans are currently grown in the U.S. and marketed both domestically and internati onally. Producers of organic and other specialty soybeans currently have production and handling procedures in place to ensure that their product meets standards specified either in the USDA NOP regulations or through contr acts, as relevant.

Organic and other non

- GE specialty soybeans offer consumers the option of choosing non

- GE products if that is their preference. The consumer reaction to GE crops since their commercialization has been well researched, particularly as to whether consumers would prefer

non

- GE and whether they support labeling of foods containing GE ingredients. The hundreds of surveys that have been done over the years present contradictory evidence, likely due to differences in sampling techniques, the sur vey instruments used, and the way questions are framed ( Kalaitzandonakes et al. , 2005 ) . Further, preferences expressed in surveys may not be consistent with actual purch asing behavior ( Fernandez

- Cornejo and Caswell, 2006 ) . For example, a study of consumers in the Netherlands from 1997 to 2000, a period of time during which GE ingredients were required to be labeled and similar products were available to consumers with and without GE ingredients, showed no major changes in purchasing behavior with respect to the GE

- labeled products ( Kalaitzandonakes et al. , 2005 )

.

1164.1.4 Health and Safety for Livestock and Humans

Humans Health
Under the No Action Alternative, MON 88701 cotton and MON 87708 soybean would continue as a regulated article under APHIS

. Grower exposure to th ese product s would be limited to individuals involved in the cultivation under regulated conditions . Cotton and s oybean growers and farm workers will continue to be exposed to existing traditional and GE cotton and soybean varieties and their respective cultivation practice s

. Under the No Action Alternative, human exposure to existing conventional non

- GE and GE cotton and soybean varieties and their products is not expected to change. Ninety percent of
cotton and 93 percent of soybean grown in the U.S. in 201 3 was GE ( USDA

- ERS, 2014a )

. Human healt h concerns associated with GE crops include the potential toxicity of the introduced genes and their products, the expression of new antigenic proteins, and/or altered levels of existing allergens ( Malarkey, 2003 ; Dona and Arvanitoyann is, 2009 )

. GE crops are subjected to far greater levels of scrutiny than foods produced by traditional plant breeding techniques. They are assessed for the potential toxicity of the introduced genes and their products, and for altered levels of existing allergens, to assure that a GE food is as safe and nutritious as its conventional counterpart (Malarkey, 2003). FDA has no further questions that MON 87708 soybean and MON 88701 cotton are as safe as conventional soybean and cott on for consumption by humans and animals. Furthermore, there is a broad consensus among scientific professionals with expertise in assessing risks associated with the safety of food, feed and fiber derived from GE crops that they are no different from thos e derived from non

- GE crop varieties.

U nder the FFDCA , it is the responsibility of food and feed manufacturers to ensure that the products they market are safe and labeled properly. Food and feed derived from GE organism must be in compliance with all applicable legal and regulatory requirements. GE organisms for food and feed may undergo a voluntary consultation process with the FDA prior to release onto the market. As described in Section 1 .4.2, MON 88701 cotton contains t he phosphinothricin N

acetyltransferase ( PAT ) protein

, confer ring resistance to glufosinate

. FDA has previously reviewed submissions regarding the safety of food and feed derived from crops containing the pat gene (BNFs 000 055 (soybean), 000073 (corn), 000081 (corn), 000085 (cotton), and 000092 (cotton)). The PAT protein is considered to be safe for consumption by humans and animals. Both cotton and soy bean (and other crops) containing the pat gene are already in commerce and this exposure is expected to continue under the No Action Alternative.

The greatest risk to human (worker) safety in agriculture is associated with physical injuries usually occurring during the maintenance and use of farm machinery. Cuts, bruises, loss of fingers and limbs are examples of injuries resulting from mechanical hazards. Physical injuries resulting from maintenance and use of farm machinery are unlikely to change in frequency or severity if the No Action Alternative is adopted.

Cotton and s oybean growers and farmworkers may be exposed to a variety of EPA

- registered pesticide s in both GE and non

- GE p roduction systems

. Herbicide use may increase to meet the need for additional integrated weed management tactics t o mitigate herbicide

- resistant weeds in different cropping systems ( Owen and Zelaya, 2005 ; Culpepper, 2008 ; Owen, 2008 ; Heap,

1172014d ) . However, w orker safety is taken into consideration when a pesticide label is developed during the EPA registration pro cess. When use is consistent with the label, pesticides present minimal risk to the worker. No changes to current worker safety are anticipated under the No Action Alternative.

Animal Feed
Under the No Action Alternative, MON 8 8 701 cotton and MON 87708 soybean would continue as regulated article s under APHIS . Under the No Action Alternative, livestock exposure to cotton and soybean would continue to be limited to currently

- available varieties, including non

GE and GE varieties

. Processing of cotton gene rally provides cottonseed meal, cottonseed hulls, and whole cottonseed to be utilized in the animal feed industry as sources of protein, fiber and energy ( NCPA, 2002 ; OECD, 2009a ) . The value of cottonseed as animal feed represents a substantial portion of the
gro wer’s income from cotton ( Blasi and Drouillard, 2002 )

. Cottonseed meal, which makes up over a third of the value of cottonseed, is an excellent source of protein for ruminant animals and is widely used in animal feed ( Blasi and Dr ouillard, 2002 ; Calhoun, 2011 ) . Cottonseed contains the anti

- nutrients gossypol and cyclopropenoid fatty acids. Gossypol helps protect the cotton plant from pathogens, but is an anti

- nutrient for whic h sensitivity is species

- dependent. Gossypol is also toxic to some species ( Gadberry, 2011 )

. The cottonseed hull is the tough, protective covering of the cottonseed that is re moved prior to processing the seed for oil and meal. It is used as feed for livestock and can be an economical roughage that provides fiber, as well as serving as a good carrier for cottonseed meal and grain ( NCPA, 2002 ) . Gin by

- products, the dried plant material cleaned from the fiber during ginning, is also used as a source of roughage for livestock feeds.

Cottonseed is typically fed to ruminants (i.e., cattle), because they have a relatively low sensitivity to gossy pol and can tolerate moderate gossypol inclusion in their diets. Highly processed cottonseed meal is also fed to non

- ruminant farm animals in limited quantities ( OECD, 2009b ) . Cyclopropenoid fatty acids interfere with the metabolism of saturated fats ( Rolph et al.

, 1990 ; Cao et al. , 1993 ) and reportedly have adverse effects on egg yolk discoloration and reduced hatchability in chickens ( OECD, 2004 ; Lordelo et al. , 2007 ; OECD, 2008b )

. Soybeans yield both solid (meal) and liquid (oil) pr oducts. Soybean meal is high in protein and is used for products such as tofu, soymilk, meat replacements, and protein powder; it also provides a natural source of dietary fiber ( USB, 2009 )

. However, a nti

- nutrients commonly found in raw soybean also include trypsin inhibitors and lectins ( US

- FDA, 2011a ) . Routine processing in moist heat inactivates these anti

- nutrients ( US

- FDA, 2011a )

. Nearly 98 percent of soybean meal produced in the U.S. is used as animal feed ( Soyatech, 2011 )

. Poultry consume more than 45 percent of domestic soybean m eal or 590 million bushels of the U.S. soybean crop, with soy oil increasingly replacing animal fats and oils in broiler diets ( USB, 2011 ) . Soybean can be the dominant component of livestock diets, such as in poultry, where upwards of 66 percen t of their protein intake is derived from soy ( Waldroup and Smith, 2008 )

. Other animals fed domestic soybean (by crop volumes consumed) include swine (26 percent ), 118beef cattl e (12 percent ), dairy cattle (9 percent ), other (e.g., poultry, farm

- raised fish ) ( 3 percent ), and household pets (2 percent ) ( Soy Stats, 2010 ; USB, 2011 )

. Although the soybean market is dominated by seed production , soybean has a long history in the U.S. as a nutritious grazing f orage , hay , and silage crop for livestock ( Blount et al. , 2009 )

. Varieties of soybean have been developed specifically for grazing and hay, but use of the standard grain varieties is recommended by some because of the whole plant feed ing value ( Weiderholt and Albrecht, 2003 )

.

Non

- GE cotton and soybean varieties, both those developed for conventional use and for use in organic production systems, are not routinely required to be evaluated by any regulatory agency in the U.S. for animal feed safety prior to release in the market. Under the FFDCA , it is the responsibility of food and feed manufacturers to ensure that the products they market are safe and properly labeled. F ood and feed derived from any GE crop event must be in compliance with all applicable legal and regulatory requirements.

Animal feed safety reviews frequently compare the compositional characteristics of the GE crop with non

- transgenic, conventional varieties of that crop ( Aumaitre et al. , 2002 ; FAO, 2009 )

. T his comparison also evaluates the composition of the modified crop under actual agronomic conditions, including various agronomic inputs ( Herman et al. , 2010 ) . Composit ion characteristics evaluated in these comparative tests include moisture, protein, fat, carbohydrates, ash, minerals, dietary fiber, essential and non

- essential amino acids, fatty acids, vitamins, and anti

- nutrients ( Herman et al. , 2010 )

. GE organisms for food and feed typically undergo a voluntary consultation process with the FDA prior to release onto the market. Although a voluntary process, to date , all applicants proposing to commercialize a GE variety that would be included in the food supply have completed a consultation with the FDA. In a consultation, a developer who intends to commercialize a bioengineered food meets with the FDA to identify and discuss relevant safety

, nutritional, or other regulatory issues regarding the bioengineered food and then submits to the FDA a summary of its scientific and regulatory assessment of the food. This process includes: 1) an evaluation of the amino acid sequence introduced into the food crop to confirm whether the protein is related to known toxins and allergens; 2) an assessment of the protein’s potential for digestion; 3) an evaluation of the history of safe use in food ( Hammond and Jez, 2011 )

. The FDA evaluates the submission and responds to the developer by letter with any concerns it may have or additional information it may require.

Most of the cotton and soybean currently grown in the U

. S

. is GE ( USDA

- NASS, 2006 )

, and this market share is expected to continue under the No Action Alternative

. Livestock are routinely exposed to GE cotton and soybean in animal feed

. All currently

- available GE cotton and soybean varieties used in animal feed are considered safe for a nimal consumption and this is unlikely to change under the No Action Alternative

.

4.1.5 Animal Communities

Under the No Action Alternative, MON 88701 c otton and MON 87708 soybean would con tinue to be regulated by APHIS. The current availability and us e of commercially cultivated soybean

119and cotton , including conventional and GE varieties, would be unaffected under this alternative

. Herbicide use may increase to meet the need for additional integrated weed management tactics
to mitig ate HR weeds in different cropping systems ( Owen and Zelaya, 2005 ; Culpepper, 2008 ; Heap, 2014d ) , which may adversely impact w ildlife and habitats. Most growers strive to cultivate a single plant species in a field while excluding all other plant species to maximize yield and increase ease in cultivation and harvesting. As a result, using herbicides in agricultural fields directly decreases plant biodiversity , and indirectly reduces the resources available to animals for habitat and food. H erbicides are used on 98 percent of soybean acreage ( USDA

- NASS, 2013a ) and on greater than 99 percent of cotton acres ( USDA

- NASS, 2011b )

.
Growers choose pesticides based on weed, insect and disease pressures, cost of seed and other inputs, technology fees, human safety

, potential for crop injury, and ease and flexibility of the production system ( Heiniger, 2000 ; Farnham, 2001 )

. Agricultural production of cotton and soybean uses EPA

- registered pesticide s, including dicamba and glufosinate, for weed management. The environmental risks of pesticide use on wildlife and wildlife habitat are assessed by the EPA during the pesticide registration process , and are regularly reevaluated by the EPA for each pesticide to maintain its registered status under FIFRA

. Additional integrated weed management tactics may impact the adoption of conservation tillage practice s. Under the No Action Alternative, if tillage rates increase as a means of weed suppression, then increases in soil erosion are expected, and this could adversely impact wildlife habitat. In contrast, increased use of cover crop s may create beneficial impacts on wildlife by providing habitat and food.

The widespread use of conservation tillage and no

- till practices , especially in association with the planting of GE HR soybean varieties , benefitted wildlife through improved water quality, availability of waste grain, retention of cover in fields, and increased populations of invertebrates ( Brady, 2007 ; Sharpe, 2010a )

. Conservation tillage practice s that leav e crop residue serve to increase the diversity and density of birds and mammals in agricultural fields ( USDA

- NRCS, 1999a )

. Increased residue also provides habitat for insects and other arthropods . This increas es food source s for insect predators

. Insects are importan t for many upland game birds and other birds during the spring and summer brood

- rearing season because they provide a protein

- rich diet for their fast

- growing young A nutrient

- rich diet also benefits migratory birds ( USDA

- NRCS, 2003 )

. If growers abandon conservation tillage practices, then these benefits to wildlife may be lost.

Changes to crop m anagement practices may create both beneficial and adverse effects on biological resources , but their net impact on biological resources under the No Action Alter native is unknown.

4.1.6 Plant Communities

Weeds are commonly found in cotton and soybean fields and if not controlled can substantially decrease yields. The most problematic weeds of each crop are shown in Appendix 5. Appendix 3 lists three categories of weeds: annual broadleaf weeds, annual grass weeds, and perennial weeds. In summary, common weeds in cotton fields include b arnyardgrass, crabgrass, pigweed species (including Palmer amaranth), morning glory spp., common cocklebur, and common

120lambsquarters . These are common annual weed species in almost all cotton

- growing regions. Johnsongrass, bermudagrass, and nutsedge are common perennial weed species.

Weeds in soybean include : f oxtail

, pigweed, velvetleaf, lambsquarters, and cocklebur , which are common weeds in Midwest ern soybean fields. Certain growers in Indiana have reported giant ragweed, lambsquarters, Canada thistle, cocklebur, and velvetleaf to be difficult

- to

- control weeds in soybean ( Nice and Johnson, 2005 ) . Giant and/or common ragweed are also common and problematic in Minnesota, Missouri, Arkansas, Wisconsin and Illinois ( Iow a

- State

- University, 2003 ; Andersen et al. , 2004 ; Boerboom, 2006 ) . In a 2005

- 2006 survey of 1,200 growers of GR crops ( e.g., soybean, corn and cott on) in six Midwestern and S outhern states, growers classified these as most difficult to control ( Kruger et al. , 2009 ) . Waterhemp is also reported to be problematic in Minnesota, Indiana, Nebraska, Wisconsin and Missouri ( Iowa

- State

- University, 2003 ; Andersen et al. , 2004 ; Boerboom, 2006 ; Kruger et al. , 2009 ; Legleiter et al. , 2009 )

. Horseweed has been reported to be problematic in Ohio, Arkansas, Tennessee, Kansas, Wisconsin and Illinois ( Mueller et al. , 2005 ; Boerboom, 2006 ; Peterson and D., 2012 )

. Among these three categories, annual broadleaf weeds include the species that have become most difficult to control due to the selection of HR biotypes 10 . Fo r example, velvetleaf and lambsquarters are both somewhat tolerant of glyphosate and also for some species such as pigweed, waterhemp, ragweed, and kochia, GR biotypes have been selected ( Heap, 2014d )

. Species such as waterhemp have develop ed resistance to as many as five different herbicide sites of action ( Owen, 2012 ) . Annual grass weeds that inhabit soybean fields are still largely controlled by glyphosate. Foxtail is an importan t weed actively managed on almost all acreage used for soy beans . Perennial weeds a re particularly difficult to control because they can survive for more than two years and can regrow every year from rhizomes . Among the perennial weeds, biotypes of Johnsongrass have been selected for glyphosate resistance.

In 2012, the area of U.S. crop land infested with GR weeds expanded to 61 million acres, according to a survey conducted by Stratus Agri

- Marketing ( Farm Industry News, 2013 )

. At present, d icamba

- resistant and glufosinate

- resistant weeds account for <1 percent and 0.5 percent of resistant biotypes

, respectively ( Heap, 2014a )

. No dicamba

- resistant populations have been reported in the main soybean production areas, including the Midwest, the South and the East C oast of the U.S. Additional discussion of HR weeds can be found in Appendix 6.

Soybean is not listed as a weed in major weed references, nor is it present on the lists of noxious weed species distributed by the federal govern ment (7 CFR p art 360)

. M odern soybean harvesting equipment is efficient, so few seeds remain in soybean fields following harv est

. Therefore, volunteer soybean s are typically not a problem in subsequent crops rotated with
soy beans

. Even when volunteer soybean s occur they do not compete well with other crops and

10 Plants of a given species are not identical, but are made up of “biotypes ” with various genetic traits. Within a weed species, individuals may possess an inherent ability to withstand the eff e cts of a particular herbicide. Repeated use of that herbicide in the absence of other weed control herbicides or practices has the potential to expose the weed population to a “selection pressure,” which may potentially lead to an increase in the number o f surviving resistant biotypes in the population ( Herbicide

- Resistance

- Action

- Committee, 2013 )

. Herbicide resistance is discussed in more detail in Appendix 6 of the EIS

.

121are easily controlled with common agronomic practices. Volunteer soybeans are limited by the geography in which soybean is planted. Soybean requires specific environmental conditions to grow as a volunteer ( OECD, 2000 )

. Mature soybean seeds are sensitive to cold and rarely survive in freezing winter conditions ( Raper and Kramer, 1987 )

. Volunteer soybeans can occur in regions with warmer climates where temperature and moisture conditions are suitable for viability and germination can occur year

- round, such as the Mississippi Delta and the southeast U.S. ( Zapiola et al. , 2008 )

. For volunteer soybean emerg ing after planting, shallow cultivation or use of another herbicide will control volunteers and effectively red uce competition with the crop. Several post

- emergence herbicides are also available to control volunteer soybean ( either conventional or herbicide

- tolerant soybean) in each of the major soybean rotational crops ( Monsanto, 2013a )

. With regard to volunteer cotton

, volunteer cotton populations can be managed ( Fromme et al.

, 2010 ; Morgan et al. , 2011 ) and feral populations occur rarely in the U.S. Cotton Belt ( Wozniak, 2002 )

. Cotton is not listed as a weed in major weed references, nor is it present on the lists of noxious weed species distributed by the federal government (7 CFR p art 360)

. Cotton does not possess any of the attributes commonly associated with weeds, such as long persistence of the seed in the soil, ability to disperse, invade, or become a dominant species in new or diverse landscapes, or the ability to compete well with native vege tation

. It is recognized that in some agricultural systems, cotton can volunteer in a subsequent rotational crop

. However, volunteers are easily controlled through tillage or the use of appropriate herbicides with diverse modes

- of

action ( e.g. , ALS inhibit or, chloroacetamide, 5

- enolpyruvylshikimate

- 3

- phosphate synthase ( EPSPS ) , PPO inhibitor, Photosystem I ( PSI ) disruption, Photosystem II ( PSII ) inhibitor, synthetic auxin, and tubulin inhibitor classes) ( Monsanto, 2013a )

.
Volunteer cotton is an issue for growers when much seed may germinate in a spring crop after a dry fall ( Fromme et al. , 2010 )

. Following harvest, cotton volunteers are an important issue, because m ost cotton

- producing states have an active Boll Weevil Eradication Program , one of whose goals is to destroy cotton so that it cannot persist after harvest and support weevil growth

. These programs are directed by various state and regional organizations . D ire ctives from the Program authorities for support of weevil control measures are enforced by state laws and authorities

. Cotton producers must destroy cotton stalks after cotton harvest for successful boll weevil eradication , which focuses on remov al of over

- wintering habitat and breeding sites for boll weevils. Growers must destroy cotton stalks by a published date each year. Growers remove these cotton stalks by applying the herbicide 2

- 4,D and additionally may shred cotton stalks ( Robertson et al. , 2002 )

.

4.1.7 Soil Microorganisms

Under the No Action Alternative, MON 87708 s oybean and MON 88701 c otton would continue to be regulated by APHIS

. Agricultural practices such as pesticide applications an d tillage are known to impact soil microbial populations, species composition, colonization, and associated biochemical processes. The use of these practices from what is currently practiced today is unlikely to change under the No Action Alternative.

Grow ers inoculating soy bean fields with Bradyrhizobium japonicum bacteria experience increased yield s ( Conley and Christmas, 2005 )

. In 2009, the industry estimated that one

- third of
122U.S. soybean acreage was inoculated ( Seed Today, 2009 ) . Under the N o A ction A lternative, the use of inoculates is unlikely to change from t he current use , unless new or improved strains become available.

4.1.8 Water

If drought conditions west of the Mississippi continue, then abandonment rates for cotton appear likely to increase. Cotton prices are expected to fall less than competing crops which makes planting cotton relatively more attractive to growers. Stronger soybean prices relative to corn should also favor soybean plantings in 2014 ( USDA

- OCE, 2014a )

. Corn and soybean s generally require less water than cotton (see Table 14 o n comparative water needs ) ( Brouwer and Heibloem, 1986 )

Table 14

. Comparison o f Water Needs a nd Drought Sensitivity f or Some Globally Important Crops.

Crop Minimum

- maxim um water (mm needed over total growing period) Sensitivity to drought

Alfalfa 800

- 1600 low

- medium Citrus 900

- 1200 low

- medium Cotton 700

- 1300 low Corn (Maize) 500

- 800 medium

- high Soybean 450

- 700 low

- medium Sugarbeet 550

- 750 low

- medium Sugarcane 1500

- 2500 high Sunflower 600

- 1000 low

- medium Tomato 400

- 800 medium

- high
Source: ( Brouwer and Heibloem, 1986 )
USDA projections indicate that demands on agricultural water supplies are likely to increase over time as alternative nonfarm uses of water continue to grow. Potential Native American
water

- right claims were estimated at nearly 46 million acre

- feet annually and could impact the distribution and cost of irrigation water in the West. For many s tates, the scope of water demands for the environment have expanded from a minimum in

- stream flow to an “environmental

- flows” standard (i.e., a concept requiring water to meet the needs for water quality, but to also rehabilitate ecosystem habitats). Energy

- sector g rowth is expected to substantially increase water demands for an expanding biofuels sector, utility

- scale development of solar power, innovation in thermoelectric generating capacity, and commercial oil

- shale and deep shale natural gas development ( Schaible and Aillery, 2012a )

.

P rojected climate change

— through warming temperatures, shifting precipitation patterns, and reduced snowpack

— is expected to reduce water supplies and increase water demand across much of the West. These trends are placing greater pressure on existing water allo cations, heightening the importance of U.S. water management and conservation for the sustainability of irrigated agriculture ( Schaible and Aillery, 2012a ) . Expansion in competing areas of national water demand may present U.S. cotton and soybean producers with more difficult farming

123decisions and fewer so cioeconomic options ( e.g., whether to purchase enough water for a crop, or to clear or even sell land )

. Under the No Action Alternative, water allotment for agricultural use is expected to be restricted as demand for water increases globally. Pressure for the conservation of existing surface water and groundwater resources is expected to increase

. In areas where increased tillage is used to control weeds and soil erosion, water may be more l i kely to be impacted by sediments in agricultur al runoff ( Fawcett and Towery )

.

4.1.9 Air Quality

Agricultural activities such as the use of tillage, pesticide s , prescribed burning, and farm equipment can all effect air quality . Growers choose those activities that are most suited for their operations. To manage weeds growers may use a combination of activities including pesticide use. In some areas, tillage is increasing as growers use till age to manage herbicide

- resistant weeds. This activity affects air as particulate matter can increase w ith increasing tillage. Also conventional tillage can use more fossil fuels than conservation tillage methods , resulting in emission of air pollutants fr om fossil fuel combustion. U nder the No Action A lternative, these potential emissions may cause some transient impacts to local air quality. These impacts are unlikely to affect areas with impaired air quality because of the potential for chemical dispersi on in air currents and the relatively large distances from agricultural production areas to areas under air quality management plans

, which generally encompass urban areas

.

4.1.10 Climate Change

Under the No Action Alternative, cropping practices to manage weeds will likely increase in intensity. Increase s in herbicide applications or the use of tillage w ould increase the contribution of cotton and soybean cultivation to GHG emissions. This increase would occur from the combustion of fossi l fuels for equipment used to apply herbicides and to till fields. The manufacture of herbicides may also contribute to the release of greenhouse gases, but t he overall contribution is likely to be minor

. The magnitude of the effect will depend on the HR weed management practices that growers choose to use

.
4.2 Preferred Alternative

Under the Preferred Alternative, MON 88701 cotton and MON 87708 soybean would not be regulated by APHIS. MON 88701 cotton has increased resistance to the herbicides dicamba and
g lufosinate. MON 87708 soybean has increased resistance to the herbicide dicamba. As with other deregulated GE crop varieties, i f these dicam b a

- resistant varieties are no longer regulated they would also be available for cross

- breeding with all other GE var ieties that are no longer regulated by APHIS and non

- GE cultivars

. Monsanto intends to cross MON 87708 soybean with MON 89788 (Roundup Ready 2 Yield soybean) utilizing traditional breeding techniques

, producing a soybean variety with resistance to both dic amba and glyphosate ( Monsanto, 2012a ) (see Section 1.4.1)

. Monsanto has indicated MON 88701 cotton will be st acked wit h Roundup Ready Flex Cotton and Bollgard II (MON 88913 and MON 15985) , resulting in a cotton variety with resistance to dicamba, glufosinate, and glyphosate, as well as protection against feeding by a range of Lepidopteran species (see Section 1.4 .2 for more details) ( Monsanto, 2013a )

. More
124commercially av ailable GE cotton and soybean varieties provide growers with more choices and additional tools for weed management. Growers may adopt these new varieties where HR weeds already are present. Continued use of commercially available GE cotton and soybean varieties is expected if the varieties meet grower needs.

4.2.1 Land Use

Under the Preferred Alternative there would be no direct or indirect effects on land use resulting from the decision to approve the petitions. The drivers of land used for cotton and soybean production include the price of cotton and soybean and the suitability of the land for this production. The decision to approve the se petitions will not affect these factors.

In 201 4 , GE cotton and soybean, including stacked and herbicide

- resistant varieties, covered approximately 96 and 94 percent , respectively, of the total acreage planted to cotton and soybean in the U.S. ( USDA

- ERS, 2014d ) . Under the Preferred Alternative, it is not anticipated that the availability of MON 88701 cotton and MON 87708 soybean will chance th e acreage of GE cotton or GE soybean as compared to the No Action Alternative.

4.2.2 Socioeconomics

Domestic Cotton and Soybean Production According to the petitions submitted by Monsanto

, MON 88701 cotton and MON 87708 soybean

are compositionally similar to currently available varieties of cotton and soybean , respectively

. These events would be suitable for use in food, feed, and industrial applications of cotton and soybean products. Therefore, the use of these events in cotton or soybean processes would not ch ange when compared to the No Action Alternative.

Foreign Trade A determination of nonregulated status of MON 88701 cotton and MON 87708 soybean is not expected to adversely impact trade under the Preferred Alternative. Although the primary U.S. cotton and soybean export destinations do not present major barriers to trade in GE products, Monsanto would need to obtain approval of MON 88701 cotton and MON 87708 soybean in destination countries before commercializati on to avoid adversely affecting current trade flows. As a result, Monsanto has requested import approval of MON 88701 cotton and MON 87708 soybean in key export markets of the U.S. that have functioning regulatory systems. These include, but are not limited to: Canada, Mexico, Japan, the EU, South Korea, and China ( Monsanto, 2013a ) . The regulatory status of these events is summarized in Table 15 and Table 16

.

125Table 15 . Status of Import Approvals of MON 88701 Cotton in Key U.S. Cotton Export Markets

.
MON 88701 Cotton MON 88701 Cotton Stacks 1,2
Country Submission Approval Submission Approval

Canada June 2012 June 2014 June 2014 September 2014 Mexico May 2013 In review June 2013

- Japan Nov ember 2012 In review June 2013 In review
Korea Oct ober 2012 In review Not yet submitted

- Australia Jan uary 2013 January 2014 NA

- EU Feb ruary 2013 In review Not yet submitted

- China Not yet submitted

- NA Philippines Not yet submitted

- Not yet submitted

- Source: ( Monsanto, 2013a ) Definitions: EU = European Union; NA = Not Applicable
1 MON 88701 cotton will be stacked with Roundup Ready Flex Cotton and Bollgard II (MON 88913 and MON 15985).
2 Progeny (breeding stacks) of GE crops are not regulated by APHIS.

Table 16

. Status of Import Approvals of MON 87708 Soybean in Key U.S. Soybean Export Markets

.
MON 87708 Soybean MON 87708 Soybean Stack 1,2

Country Submission Approval Submission Approval Canada November 2010 Oct ober 2012 Nov ember 2012 January 2013 Mexico November 2011 July 2012 June 2012 February 2013 Japan March 2011 Oct ober 2013 Sept ember 2012 February 2014 Korea February 2011 Oct ober 2013 Jan uary 2013 June 2014 Australia May 2011 May 2012 NA
EU January 2011 In review March 2012 In review
China October 2012 In review NA
Taiwan March 2011 April 2013 April 2013 In review
India April 2013 April 2013 April 2013 September 2014
Source: ( Monsanto, 2013a ) Definitions: EU = European Union; NA = Not Applicable
1 MON 87708 soybean will be stacked with Roundup Ready 2 Yield (MON 89788).
2 Progeny (breeding stacks) of GE crops are not regulated by APHIS.

4.2.3 Agronomic Practices in Cotton and Soybean Production

Under the Preferred Alternative

, there would be no direct or indirect effect on cotton or soybean agronomic practices or the cost of production as a result of deregulation of MON 88701 cotton
126and MON 87708 soybean . Under this alternative , growers would be able to plant MON 88701 cotton and MON 87708 soyb ean, but would not be able to make applications of dicamba other than currently approved by the EPA. The new post

- emergent use of dicamba on these cotton or soybean events is not permitted until the EPA approves the new uses. Glufosinate use is allowed

on GE cotton and soybean containing the LibertyLink ® glufosinate

- resistance traits. I t is assumed that glufosinate will be able to be used on deregulated MON 88701 cotton varieties

. Therefore, the types of agronomic practices used to cultivate these cotton and soybean varieties

, such as tillage, crop rotation , fertilization, and pesticide use

, would be similar to those currently used . Growers would continue to manage weeds using a combination of chemical and cultural methods described i n the No Action Alternative and Appendix 3

. Under the Preferred Alternative, similar to the No Action Alternative, growers may continue to rely on glyphosate and glufosinate to manage weeds in cotton and soy bean . Weed scientists will continue to
encourage growers to use best management practices

.
O rganic Production Systems
Under the Preferred Alternative, there are no major impacts anticipated to organic cotton or soybean production systems beyond what may be already occurring under the No Action Alternative. As stated above in Section 3.5.4, USDA recognizes the importance for coexistence for all agricultural production systems, and has several initiatives in place focused on unintended
presence.

Under the Preferred Alternative, MON 8 8701 cotton and MON 87708 soybean would not be regulated by APHIS and would be available for growers to adopt. Both MON 88701 cotton and MON 87708 soybean are not anticipated to increase acreage of GE cotton or GE soybean, as growers already cultivating GE cotton or soybean are the g rowers most likely to adopt MON 88701 cotton and MON 87708 soybean , respectively. Therefore

, isolation practices of organic growers that are already in place in their production systems would not need to change due to the introd uction of these cotton and soybean varieties

. GE GR soybean and cotton varieties are already extensively grown (93 percent of all soybean acres and 90 percent of all cotton acres ( USDA

- NASS, 2013c ) ), while organic soybean and cotton production represents a small percentage of the total U.S. soybean and cotton acreage. Similar to the No Action Alternative, combined organic soybean and cotton acreage is likely to remain small, regardless of whether new varieties o f GE or non

- GE cotton and soybean, including MON 88701 cotton and MON 87708 soybean, become available for commercial production.

When compared to other GE varieties of soybean and cotton, MON 88701 cotton and MON 87708 soybean should not present any new or different issues and impacts for organic and other specialty producers and consumers. Organic producers manage identity and preserve the integrity of organic production systems utilizing vari ous measures ( Guerena and Sullivan, 2003 )

. Agronomic tests conducted by Monsanto found MON 88701 cotton and MON 87708 soybean to be substantially equivalent to the non

- GE control variety . Therefore, pollination characteristics would be similar to other soybean varieties currently available to growers ( USDA

- APHIS, 2014a ; 2014b )

. As stated above, isolation practices that organic producers are currently using whether spatial or temporal would not be affected by the nonregulated status of these products. Because cotton and soybean are largely self

- pollinating , there is limited pollen movement , so

127organic farmers are not expected to be affected by a determination of nonregulated status of M ON 88701 cotton and MON 87708 soybean

. Agronomic practices used in organic cotton and soybean production would remain unaffected by selection of the Preferred Alternative.

4.2.4 Health and Safety for Livestock and Human s
Worker Safety

APH IS has not identified any direct or indirect ad verse effects on worker safety associated with the selection of the Preferred Alternative. Existing hazards to workers occurring through the various management practices that are used to grow cotton and soybean are expected to continue

. Workers will continue to use farm equipment and agricultural chemicals. The decision to approve the two petitions does not authorize a change in herbicide use on these cotton or soybea n varieties. The EPA regulates the use of herbicides under FIFRA and considers the effects on human health when approving the use of herbicides (See Appendix 8 for a summary of the EPA’s human health assessment of the proposed new uses of dicamba on these GE crop varie t i es).

Food and Feed

The direct and indirect effects on food and feed will not be different under the Preferred Alternative when compared to the No Action Alternative. People and livestock will continue to

consume GE cotton and soy based

- products

, as well as animal products from livestock fed cotton and soy products. As des cribed in the petition, MON 88701 cotton and MON 87708 soybean are compositionally similar to currently available varieties of cotton and soy bean . Therefore

, they are not expected to have different nutritional qualities than other available cotton or soy be an varieties.

Monsanto provided the FDA with information on the identity, function, and characterization of the genes in MON 88701 cotton and MON 87708 soybean. The FDA evaluated the information in Monsanto’s submissions to ensure that regulatory and safet y issues regarding the human food and animal feed from the new plant varieties have been resolved prior to commercial distribution. C onsultations with the FDA for MON 88701 cotton ( US

- FDA, 2013 ) and MON 87708 soybean ( US

- FDA, 2011b ) have been completed and the FDA has no further questions about food and feed derived from these cotton and soybean varieties

.

N o potential impacts to the safety of people and livestock are expected to result from exp osure to the introduced dicamba mono

- oxygenase ( DMO ) and PAT proteins in food and feed derived from MON 88701 cotton

. Cottonseed, which is a by

- product of fiber production, is used in human food, animal feed, and a range of industrial products. Food uses of cottonseed include cottonseed oil and, to a lesser degree, cotton linters ( US

- FDA, 2013 ) . Cottonseed oil or refined, bleached, and deodorized (RBD) oil is highly refined to remove naturally occurring toxicants, gossypol, and cyclopropenoid fatty acids ( Reeves and Weihrauch, 1979 ; US

- FDA , 2013 )

. Cottonseed oil is primarily consumed as a salad or cooking oil, for frying, in mayonnaise, and shortening. Cotton linters are short fibers that remain on cotton seeds after the long fibers have been removed at the ginning process for textile ma nufacturing ( US

- FDA, 2013 ) . They are removed from the seeds and processed into pure cellulose, which is used in casings for bologna,

sausa ges, and frankfurters and in ice cream and salad dressings ( US

- FDA, 2013 )

. 128Whole cottonseed, cottonseed meal, hulls, and cotton gin trash are used in animal feeds for cattle, sheep, goats, horses, poultry, swine, fish, and shrimp. Cottonseed meal is the product obtained after removal of oil from whole cottonseed flakes or cake and is used as a protein supplement in animal feed. Cottonseed h ulls are used as a source of fiber in feeds ( US

- FDA, 2013 )

.
RBD oil and linters are processed fractions that contain negligible amounts o f total protein ( Reeves and Weihrauch, 1979 ) . The DMO and PAT proteins represents a very small portion of the total protein in the cottonseed of MON 88701 cotton; therefore

, no exposure to MON 88701 DMO or PAT proteins is anticipated for food uses of MON 88701 cotton

. During the consultation process, the FDA reviewed information on the id entity, function, and characterization of the inserted gens and a safety and nutritional assessment of the food and feed derived from MON 88701 cotton ( US

- FDA, 2013 ) . Neither the DMO n or PAT protein s ha ve relevant amino acid sequence s similar to known allergens, toxins or other proteins that may have adverse effects on mammals. Furthermore, the DMO and PAT proteins in MON 88701 cotton are rapidly digested in simulated gastric and intestinal fluids, and these studies did not show any observable adverse effects in mouse acute oral toxicity analyses ( Monsanto, 2013a ) . A compositional analysis of MON 88701 cotton demonstrate s that it is comparable with currently

ava ilable cotton varieties, further indicating that there would be no negative impact on human or livestock health from consumption of MON 88701 cotton in food or feed ( Monsanto, 2013a )

. The PAT enzyme present in MON 88701 cotton is identical to the wild

- type protein produced in S. hygroscopicus and is analogous to th e PAT proteins in commercially available glufosinate

resistant products in several crops including cotton, corn, soybean, and canola ( USDA

- APHIS, 2014c )

. The Organi z ation for Economic Co

- operation and Development ( OECD ) recognizes PAT proteins produced from different genes to be equivalent with regard to function and safety ( OECD, 1999 ) . PAT proteins are structurally similar only to other acetyltransferases known to
not cause adverse effects after consumption ( Herouet et al. , 2005 ) . In 1997, a tolerance exemption was issued for PAT proteins by the EPA ( 40 CFR part 180, 1997 ; CFR Part 180.1151, 2005 ) . Additionally, the FDA has previously reviewed submissions regarding the safety of food and feed derived from crops containing the pat gene (BNFs 000055 (soybean) , 000073 (corn)

, 000081 (corn) , 000085 (cotton) , and 000092 (cotton) ). Because the PAT protein

, expressed in MON 88701 cotton and in the crops noted above

, has already been reviewed by the FDA and has been in commercially produced c r ops, there are not expected to be any effects on food and feed from MON 88701 cotton

, when compared to the No Action Alternative.

With respect to MON 87708 soybean, no potential impacts to the safety of people and livestock are expected to resul t from exposure to the introduced DMO protein. Upon deregulation and commercialization, s oybean and forage produced from MON 87708 soybean would enter the food and feed chain and would be consumed by humans and animals. During the consultation process on MON 87708 soybean, the FDA reviewed information submitted by Monsanto on the safety of the DMO protein, including a dietary risk assessment ( US

- FDA, 2011b )

. T he DMO protein is rapidly digested in simulated gastric and intestinal fluids, and did not show any observable adve rse effects in mouse acute oral toxicity analyses ( Monsanto, 20 13a ) . A compositional analysis of MON 87708 soybean demonstrate d that it is comparable with currently

- available soybean varieties, further indicating that there would be no negative impact
129on human or livestock health from consumption of MON 87708 soybean in food or feed ( Monsanto, 2013a )

.

4.2.5 Biological Resources

Animal Communities
Under the Preferred Alternative, the direct and indirect effects on wildlife from approving these petitions for deregulation would be similar to the effects under the No Action Alternative. Wildlife would continue to visit cotton fields on a limited basis with preferences for other agricultural fields, including soybean fields. As described in the No Action Alternative, animal population s could be indirectly impacted by changes in agricultural practices, such as tillage. Increases in tillage to control weeds can increase soil erosion and cause indirect impacts on wildlife.

Under the Preferred Alternative , cultivation of MON 88701 cotton o r MON 87708 soybean will not result in any changes in current agricultural practices. Growers will con tinue to use cultural practices and herbicides to manage weeds, and biodiversity within a field is expected to remain unchanged . Agricultural production o f cotton and soybean is expected to continue rely ing upon EPA

- registered pesticide s, including dicamba and glufosinate, for weed management.

Feed derived from GE soybean and cotton must comply with all applicable legal and regu latory requirements, which are designed to protect human health

. Monsanto completed the biotechnology consultation process with the FDA for the safety and nutritional assessment of food and feed derived from MON 88708 soybean on October 11, 2011 (BNF No. 00125) and for MON 88701 cotton on April 24, 2013

. MON 88701 cotton ( US

- FDA, 2013 ) and MON 8770 8 soybean ( US

- FDA, 2011b ) are compositionally similar to other commercially a vailable upland cotton and soybean varieties, and there are no known toxic properties associated with them.

Data submitted by Monsanto indicate that these proteins are unlikely to be a toxin or allergen in animal diets ( Monsanto, 2013a )

. As a result, animals that may consume these cotton or soybean varieties are no t expected to be affected from deregulation of MON 88701 cotton and MON 87708 soybean under the Preferred Alternative.

Plant C ommunities
Under the Preferred Alternative, the direct and indirect effects of approving these petitions on plant communities, in cluding weed complexes, is expected to be the same as those under the No Action Alternative. Agronomic practices and inputs associated with MON 88701 cotton and MON 87708 soybean would not be different than what is utilized on current commercially available GE cotton and soybean varieties

. As a result, c hoosing the Preferred Alternative would
not result in change s to the plant communities in or around cotton and soybean fields.

We ed communities within agricultural fields, including cotton and soybeans are impacted primarily by tillage practice s and herbicide treatments ( Owen and Zelaya, 2005 )

. Non

- target plant communities in areas surrounding production fiel ds would be exposed to the effects associated with agricultural production, including exposure to various inputs

, such as herbicides.

130Management practices such as herbicide use and mechanical cultivation can select for weeds that

are adapted to these management practices

. MON 88701 cotton contains the PAT protein conferring resistant to the herbicide glufosinate

. Both MON 88701 cotton and MON 87708 soybean will be combined with glyphosate

- resistance traits using traditional breeding t echniques ( Monsanto, 2013a ) . Other deregulated GE cotton and soybean varieties are available with resistance to each of these herbicides. Additionally, GE cotton varieties with resistance to both glufosinate and glyphosate are already available (e.g., Gly TolTM LibertyLink ® and WidestrikeTM Roundup Ready FlexTM). Therefore, a determination of non

- regulated status for MON 88701 cotton and MON 87708 soybean by APHIS under the Preferred Alternative is not expected to change current agronomic practices. Additional ly, MON 88701 cotton a nd MON 87708 s oybean have been shown to be phenotypically and agronomically similar to other commercially grown cotton and soybean varieties; therefore, agronomic practices associated with cotton and soybean cultivation, such as tilla ge, are not different than currently used

. Therefore, there are no changes in effects to plant communities under the Preferred Alternative when compared to the No Action Alternative.

While MON 88701 cotton and MON 87708 soybean can resist application s of dicamba, non

regulated statues of A PHIS under the P referred A lternative would not allow for the new (i.e., post

- emergence) use s on these varieties. Pre

- plant dicamba use on these and other cotton and soybean varieties could continue as permitted by the EPA

. The EPA regulates the use of herbicides under FIFRA and is making a separate decision on the proposed new uses of dicamba; the p otential cumulative impact s of the EPA’s decision are reviewed in Chapter 5.

Soil Microorganisms

The potential effects on soil quality of choosing the Preferred Alternative are no different than the effects under the No Action Alternative. Soil microorganisms are affected by agricultural management practices, as described in the No Action analysis on soil microorganisms (Section 4.1.8) . One factor that driv es a grower’s selection of agricultural practices is weed management. Another is the trend toward increased h erbicide u se to control HR weeds in different cropping systems ( Owen and Zelaya, 2005 ; Culpepper, 2008 ; Owen, 2008 ; Heap, 2014d ) and they will be similar under the No Action and the Preferred Alternative

. The decision to approve these petitions will not directly or indirectly effect these grower decisions to use tillage to manage weeds. Approving the petitions would allow these varieties to be planted, but it does not allow for the use of dicamba on the plants. The use of dicamba is regulated by the EPA. The EPA regulates the use of herbicides under FIFRA and is making a separate decision which may or may not allow its use on these plants. APHIS considers the potential cumulative impact s on soil microorganisms of its decision combined with the EPA’s decision in the Cumulative Impacts analysis in C hapter 5

. Growers inoculating soybean fields with Bradyrhizobium japonicum bacteria are likely to continue using this organism when addi tional plant varieties become available. This is because seed breeders have an ongoing interest in making their varieties compatible with existing cropping materials and practices. Under the preferred alternative , use s of inoculates is unlikely to change from current use s

.

1314.2.6 Physical Environment

Water Agricultural practices can affect water quality. Under the Preferred Alternative, the overall agricultural impacts on water quantity are likely to be the same as those described under the N o Action Alternative. Choosing the Preferred Alternative does not change grower choices on how to grow cotton and soybeans or manage weeds in their fields. Any reduction in tillage compared to the amount of tillage occurring under the No Action Alternative w ould be associated with relatively less agricultural runoff and sedimentation

. T his w ould result in less water quality impacts. The converse is also true

. I n areas where tillage is used or increased to control weeds in cott on and soybean, water may be affected by sedimentation from surface runoff ( Robertson et al. , 2009 )

. Use of pesticides for field crop production may introduce resi due s into water from spray drift

, runoff from cleaning pesticide application equipment, soil erosion, and filtration through soil into groundwater

. As part of assessing the risk of the exposure of aquatic organisms and the environment to a pesticide, the EPA estimates concentrations of pesticides in natural water bodies, such as lakes or p onds. As part of the Food Quality Protection Act (FQPA ) of 1996, the EPA estimates pesticide concentrations in drinking water when it establishes maximum pesticide residues in and on food (tolerances). For both drinking water and aquatic exposure assessments and for water quality assessments, the EPA typically relies on field monitoring data

as well as mathematical models to generate exposure estimates ( US

- EPA, 2012c )

. Approving the petitions would allow these varieties to be planted, but it does not allow for the

n ew post

- emergence use o f dicamba on the plants. The EPA regulates the use of herbicides under FIFRA and is making a separate decision which may or may not allow its use on these plants. APHIS consi ders the potential cumulative impact s on water quality of its decision combined with the EPA’s decision in Chapter 5.

Air Quality Agricultural activities

, such as the use of tillage, pesticide s , pres cribed burning, and farm equip ment, can all effect air quality

. Growers choose those activities that are most suited for their operations. To manage weeds, growers may use a combination of activities

, including pesticide use. In areas where HR weeds are increasing in prevalence, increased tillage is occurring in cotton and soybeans to combat the se weeds. I ncreasing the frequency of tillage increases the release of air pollutant s by releasing particulate matter and exhaust from the burning fossi l fuels used to run tillage equipment

.
MON 88701 cotton a nd MON 87708 s oybean have been shown to be phenotypically and agronomically similar to other commercially grown cotton and soybean varieties; therefore, agronomic practices associated with cotton and soybean cultivation are not expected to change. Under the P referred A lternative, any effects to air quality associated with deregulation of MON 88701 cotton and MON87708 soybean are likely to be similar to the No Action A lternative bec ause agronomic practices are not expected to change

.

132Approving the petitions would allow MON 88701 cotton and MON 87708 soybean to be planted, but it does not allow for the additional new use s of dicamba

. The use of herbicides is regulated by the EPA under FIFRA

, and the EPA is making a separate decision on the proposed new uses of dicamba on these plants. APHIS considers the potential impacts on air quality of its decision combined with the EPA’s decision in Chapter 5 (Cumulative Impacts ).

Climate Change Various environmental parameters are anticipated to be altered under the influenc e of continued climate change

. Droughts, floods, and temperature changes are predicted to become more prevalent and more severe as climate change occurs

. This requires faster crop improvement programs to develop climate

- adapted varieties ( James, 2013 ) . The ongoing trend of a general increase in the current range o f weeds and pests reflects one impact of climate change on agriculture

. In general, North American production is expected to adapt to climate change impacts with improved cultivars and responsive farm management ( Field et al. , 2007 ; IPCC, 2007 )

. The same types of agricultural activities t hat a ffect soil, water and air quality can contribute to climate change

. C hoosing the Preferred Alternative does not change these production practice s. Therefore

, the potential impacts on climate change are the same under the Preferred and the No Action Alternative.

4.3 Potential Environmental Consequences

- Alternative 3

Under Alternative 3

, P etition 12

- 185

- 01p for deregulation of MON 88701 cotton would be
app roved , but not P etition 10

- 18 8

- 01p ( MON 87708 soybean )

. Approving the petition would allow MON 8870 1 cotton to be planted without a n APHIS permit or acknowledged notification

. MON 87708 soybean would continue to be regulated by APHIS . This decision does not allow for additional uses of herbicides on cotton or soybeans

. The EPA regulates the use of herbicides under FIFRA and is making a separate decision which may or may not allow the new use s of dicamba on these plants. APHIS considers the potential cumulative impact s associated with its decision combined with the EPA’s decision in Chapter 5

. Under the Preferred Alternative, neither of these two events (MON 88701 cotton and MON 87 708 soybean), either individually or together, would have different effects on natural or biological resources than the No Action Alternative N o direct or indirect effects associated with of growing MON 8870 1 cotton were identified in the Preferred Alternative (Alternative 2) when compared to the No Action Alternative. Therefore, approving P etition 12

- 185

- 01 p for deregulation of M ON 8870 1 cotton under Alternative 3 is also not expected to have different direct and indirect effects on those resource areas. In addition, APHIS does not expect Alternative 3 to have different socioeconomic or human health

- related effects than the No Action Alternative

.
4.4 Potential Environmental Consequences

- Alt ernative 4

Under Altern ative 4

, P etition 10

- 188

- 01p for deregulation of MON 87708 soybean would be approved

, but not P etition 12

- 185

- 01p ( MON 8870 1 cotton )

. By a pproving P etition 10

- 188

- 01p

133for deregulation

, MON 87708 soybean could be planted without a n AP HIS permit or acknowledged notification . MON 8870 1 cotton would continue to be regulated by APHIS

. APHIS’ decision does not allow for additional uses of herbicides on cotton or soybeans

. The EPA regulates the use of herbicides under FIFRA and is making a separate decision on the proposed new use s of dicamba on these plants

. APHIS considers the potential cumulative impact s associated with its decision combined with the EPA’s decision in Chapter 5

. Under the Preferred Alternative, neither of these two events (MON 88701 cotton and MON 87708 soybean), either individually or together, would have different effects on natural or biological resources th an the No Action Alternative

. No direct or indirect effects associated with of growing MON 87708 soybean were identified in the Preferred Alternative (Alternative 2) when compared to the No Action Alternative. Therefore, a pproving just P etition 10

- 188

- 01p for MON 87708 soybean is also not expected to have any different direct and indirect effects on those resource areas than the No Action Alternative . In addition, APHIS does not expect Alternative 4 to have different socioeconomic or human health

- related effects than the No Action Alternative.

134

### 5 CUMULATIVE IMPACTS

Cumulative impacts are defined as the “impact on the environment, which results from the incremental impact of the action when added to other past, present, and reasonably forese eable future actions regardless of what agency (federal or non

- federal) or person undertakes such other actions” (40 CFR 1508.7). This section assesses current and reasonably foreseeable future impacts associated with the three Action Alternatives (see Section 2) . APHIS considers the impacts of Action Alternative s combined with its past, present, and reasonably foreseeable future actions

, as well as the actions of others

, in this section.

Considered in this section are the potential cumulative impact s related to changes in management practices that are likely to be associated with the adoption of MON 88701 cotton or MON 87708 soybean in the context of the impacts that agriculture has on biological, physical, human health and socioeconomic (including production) resources in the areas where cotton and soybeans are grown. Impacts on natural and biological resources are also considered in the cumulative impacts analyses. Possible implications of how these impac ts might affect the availability of those resources for human use and consumption are also analyzed. The initial step in this process was an analysis of the potential changes in management practices likely to occur if APHIS approves one or more of the Mons anto petitions and the EPA approves the new uses of dicamba on MON 88701 cotton and MON 87708 soybean. In the second phase of analysis, APHIS analyzed how changes in management practices might impact natural and biological resources. Possible impacts of an interaction with other APHIS actions (past and those currently pending) were also considered.

The first reasonably foreseeable future action considered is that EPA will approve the registration of the proposed new uses of the dicamba on MON 88701 cotton and MON 87708 soybean

. A second reasonably foreseeable action is the expected determinations of nonregulated status for other HR crops, whose implications are noted later in this section. APHIS assumes that the EPA will approve the proposed new uses of the dicamba formulation M1691 (U.S. EPA Reg. No. 524

- 582) on MON 88701 cotton and MON 87708 soybean following the determination s of nonregulated status for MON 88701 cotton and MON 87708 soybean . This herbicide product contains the dicamba diglycolamine (DGA) salt which has a lower volatility profile than the dimethylamine (DMA) salt or other acid

- based formulations of dicamba currently in use.

APHIS also assumes that the EPA will approve these proposed new uses on two new products containing the BAPMA salt of dicamba (Engenia, Reg No 7969

- GUL and MON 100111, Reg. No. 524

- ANO), which are pending at EPA, as well as two Monsanto formulations (Reg No 524

- 616 and 524

- 617). Mon santo has indicated the use of the higher volatility DMA salt and dicamba acid formulations on MON 87708 so y bean and MON88701 cotton will not be allowed ( Monsanto, 2013a )

.
Because th ese types of potential impact s would occur only if both APHIS and the EPA take the actions previously described, APHIS has analyzed i n more detail th ese types of potential cumulative impact s in this section.

1355.1 Cumulative Impacts Methodology

For this analysis of cumulative impact s, Alternative 1, the No Action Alternative, was the baseline for comparisons. Under Alternative 1, MON 88701 cotton and MON 87708 soybean would not be determined as non regulated and could only be grown under APHIS notifications or permits. Under this scen ario, APHIS assumes that the EPA would not approve Monsanto’s application for the new dicamba uses on the GE varieties that are the subject of this EIS. Existing EPA

- approved uses of dicamba would continue to be available and currently available varieties of cotton and soybean would continue to be grown.

5.2 Geographic Boundaries for the Analysis of Cumulative Effects

APHIS evaluated impacts at the regional and national levels for this analysis. Regional levels included the ecoregions defined in Section 3 (Affe cted Environment). The national level is the conterminous U.S. states, as little cotton and soybeans are grown elsewhere in the U.S.

5.3 Proposed New Dicamba Uses and EPA Risk Assessments

The EPA uses risk assess m ent s for registration decisions. It evaluates risk based on exposure and hazard to b oth hu m ans and other organis m s. A pesticide cannot be registered, nor can an existing registration be amended, unless the registered u s e conforms to the EPA standard of “ n o unreasonable adverse effect s on the environment” as described in FIFRA . In the general sense, there are four aspects of the risk assessment process: hazard identification, exposure assessment, dose/response assessment, and risk estimation. Once the EPA determines that this standard can be met, it issues a registration or modifies an existing one. The registration label includes strict limits on the quantities and methods allowed for the use of a pesticide to ensure that the standard is met.

The EPA uses environmental fate data to pre d ict pote n tial concentration of the pesticide and its degradation products in air, soil, and s urface and groundwater . These data are also used to estimate residue levels in the drinking water co mponent of human dietary risk assess m ent s.

Results of envir o n m ental fate studies ena b le the EPA to deter m ine where a pestici d e and its degradates (byproducts) go in the en vir o n m ent (i.e., air, water, and soil), how long they persist, and in what quantities (i.e., concentrations) they would be found in environmental media

. This infor m ation is used by the EPA to develop esti m ated environ m ental concentrations (EECs) that can be compared to toxicity and ecotoxicology data as part of the risk ass e ss m ent process. EEC values are based on the m ax i m u m allowable application rate for a pe sticid e, althoug h typica l application rates are usually lower th an the m axi m u m allowed. This approach, along with other factors such as the conditions on the farm field, result in “high

- end” to “bounding” estimates of exposure. When these are compared to the most sensitive toxicological endpoints in human and ecological effects stu dies, the results are conservative risk estimates. If these estimates exceed concern levels, the EPA will refine the exposure estimates using additional information or may perform a probabilistic assessment of risks.

The EPA is conducting an independent assessment of direct and indirect effects associated with the use of dicamba on MON 88701 cotton and MON 87708 soybean concurrently with the

136development of this EIS. The EPA Health Effects Division (HED) of the Office of Pe sticide Programs (OPP) is charged with estimating the risk to human health from exposure to pesticides. HED evaluated hazard and exposure data and conducted dietary, residential (non

- occupational), aggregate, and occupational exposure assessments to estimate the risk to human health that will result from the proposed new use of the DGA salt formulation of dicamba on dicamba

- resistant soybean and cotton

. Additionally, the Environmental Fate and Effects Division (EFED) completed a review of the new use request for the herbicide dicamba.

The primary difference between the proposed new use of dicamba on soybeans and cotton and the previous soybean and cotton use assessed is the timing of the applications. For conventional cotton, the maximu m seasonal application rate of dicamba is the same as that proposed for use

on MON 88701 cotton. However, for dicamba

- resistant cotton, if the EPA approves Monsanto’s application a s APHIS assumes , cotton may be treated with dicamba at later plant growth st ages during the growing season compared to its current uses. Consequently, Monsanto estimates that at peak MON 88701 cotton adoption at of about 50% of U.S. cotton acre age more frequent applications of dicamba will be made to cotton, since the trait allows new post

- emergent exposure (Appendix Table A

- 40) ( Monsanto, 20 13a )

.
For MON 87708 soybean, the new label would similarly allow for applications at later stages of plant growth than currently approved for dicamba use on soybean. Monsanto estimates that about 40% of U.S. soybean acre age will be planted with the technology

. Again, more frequent application s can be expected on MON 87708 soybean since post

- emergent exposure is tolerated (Table A

- 2, A

- 3, A

- 5) ( Monsanto, 2013a ) . Thus, more soybean acre age is likely to be treated with dicamba on MON 87708 soybean than on present varieties, where it is used only as a burndown herbicide.

A summary of the EPA’s human health and ecological risk assessment s for the proposed new uses of dicamba on MON 88701 cotton and MON 87708 soybean is provided in Appendix 8 of this EIS. These assessments provide the EPA with information needed to develop label use restrictions for the pesticide. Growers are required to use pesticides, such as dicamba, glyphosate, and glufosinate, consistent ly with the application instructions p rovided on EPA

approved pesticide label and any other applicable federal or state laws and regulations. Labels include restrictions on pesticide use/application, such as required personal protective equipment for applicators and requirements related to min imizing drift or exclusion distances from bodies of water when necessary. These label restrictions carry the weight of law and are enforced by the EPA and states (FIFRA 7 USC 136j (a)(2)(G) Unlawfu l Acts).

These direct effects of dicamba use are outside the scope of this EIS. APHIS decisions regarding the regulat ed status of the petitions for these new GE varieties will be made independently of the results of the EPA assessments. One assumption of the APHIS analysis is that EPA will establish label restrictions associated with the use s of dicamba on these varieties that will ensure the safety standards for hu m an health and the environ m ent.

Because of concern s about weed resistance the EPA is proposing new management requirements when appropriate for specific herbicides. These requirements include robust resistant weed monitoring and reporting to EPA, grower education and remediation, and w ill allow the EPA to take sw ift action to impose additional restrictions on the manufacturer and the use of the

137herb icide if resistance develops ( US

- EPA, 2014a )

. One example of the EPA’s new requirements related to weed resistance management for registration of another herbicide formulation with an active ingredient (2,4

- D) that has the same mode of action as dicamba is detailed in Appendix 10 of the EIS. These provisions would require D ow to conduct an active stewardship prog ram including monitoring and swift steps as needed to remediate weed resistance to 2,4

- D . It would allow the EPA to modify the registration quickly and easily to impose additional measures to manage resistance when appropriate . The label would also contain information on resistance management consistent with the Weed Science Society of America’s BMPs for comprehensive resistance management approaches ( US

- EPA, 2014a )

. Practices such as the use of an herbicide with a trait for a third mode of action in glyphosate resistant crops, and recommendations regarding the most effective rates and timing of applications for dicamba and glufosinate treatments will reduce the potent ial for weed communities in cotton and soybean fields to shift to more resistant weed species. EPA has specified such requirements be included on the label for the Enlist Duo herbicide as part of that proposed registration ( US

- EPA, 2014a )

. In the future, the agency intends to apply this approach to weed resistance management for all existing and new herbicides used on herbicide tolerant crops

. 11 APHIS expects that the EPA will implement similar re sistance management re quirements for the registration of M1691 dicamba formulation ( US

- EPA, 2014a )

. APHIS sees as reasonably foreseeable that these provisions will be generally useful for preventing or remediating the development of weed r esistance. Nevertheless, APHIS’ analysis in this section focuses on the cumulative impact s associated with these varieties, including possible development of HR weeds associated with application of EPA

- approved herbicides , as wel l as changes in management pra ctices resulting from their use.

5.4 No Action Alternative

. Current Management Practices Considered in the Analysis of Cumulative Impacts

This analysis addresses the potential impacts of the Alternatives on natural and biological resources and their interrelated socioeconomic impact s within the U.S. on APHIS’ determination of nonregulated status for MON 88701 cotton and MON 87708 soybean

. First, the overall background in which US cotton and soybean are produced, and herbicides are used is a dynamic one, in that various agronomic factors are changing such as an increase in glyphosate resistant weeds and other herbicide resistant weeds

. Superimposed on this is the price of commodities, which determines wh at economic practices can be used for cotton and soybean production and which are not economically justifiable. Rotation crops and their economies and needs also are part of this complex interation, as are the production practice s that take place on these. Cultural and physical methods to control weeds are also a large and important part of the Agroecosystem and grower production processes for these crops

. In this miliueu, dicamba use is already a part of the agronomic input pra ctices, along with other herbicides

. In the Environmenal Consequences section (Section 4), APHIS has presented these issues and facts, and in this section of Cumulative impacts focuses on changing patterns of dicamba use, and of tillage, both important

11 h ttp://yo semite.epa.gov/opa/admpress.nsf/bd4379a92ceceeac8525735900400c27/72fde554930f3f6985257d720059 1180!OpenDocument

138con siderations in the potential for environmental impacts that might derive from planting of MON 88701 cotton and MON 87708 soybean

.
Current Dicamba Use The agronomic practices that are expected to be affected by nonregulated status for MON 88701 cotton and MON 87708 soybean are those that relate to the application of dicamba. The factors that would contribute to increased dicamba use on cotton and soybean include the application rate and the number of acres to which dicamba would be applied on these new GE p lant varieties.

In 2012, the highest use of dicamba was on corn crops, with almost 12 million acres of corn treated. About 12% of corn acres received a dicamba application either alone or with another herbicide. The second crop most frequently treated wit h dicamba was fallow or idled cropland, with approximately 6.7 million acres treated. On spring and winter wheat, 1.8 and 3.6 million acres received dicamba applications or 14.6% and 8.4% of acres, respectively. Dicamba was used on 1.5 million cotton acres which represents 11.5% of the total U.S. cotton crop acreage ( Monsanto, 2014a ) . Dicamba usage on additional crops is summarized in Table 17 and Appendix 8.

Table 17 . Summary of Dicamba Use on U.S. Agricultural Crops

.

U.S. Total 2012 Treated Acres % Dicamba Only Treated as % of

Total U.S. Crop Total Dicamba Usage (Mixtures + Alone) Dicamba Only Dicamba Mixtures

Corn 11,919,841 441,945 11,477,896 4% 12.4% Fallow 1 6,665,137 17,757 6,647,380 0.3% 17.9% Winter Wheat 3,622,105 135,020 3,487,085 4% 8.4% Pastureland 3,221,382 492,671 2,728,711 15% 8.9% Spring Wheat 1,804,741 79,148 1,725,593 4% 14.6% Sorghum 1,683,586 49,491 1,634,095 3% 14.6% Cotton 1,455,312 79,093 1,376,219 5% 11.5% Soybeans 1,055,926 3,215 1,052,711 0.3% 1.4% Sugarcane 190,317

- - 0% 26.9% Source: BASF Corporation market research ( Monsanto, 2014a )
1 Total acreage is from cropland idled ( USDA

- ERS, 2011d )

. For 2011, Monsanto proprietary and U SDA

- NASS data indicate that 10% of cotton crops received a single pre

- plant application of dicamba (Tables A

- 2 and A

- 3 of the Monsanto ER) ( Monsanto, 2013a )

. Monsanto proprietary data show that dicamba use on cotton has increased 2.4 times between 2006 and 2012 ( Table 23 )

. For 2011, 1.2% of soybean crops received a single application of dicamba, likely for burndown before planting. Because of the sensitivity of soybean to dicamba, application has been infrequent and accompanied by lengthy plant

- back restrictions

.
Current Tillage Patterns

139The relationship of weed control to changes in tillage practice s may be evident in different regions of soybean and cotton production

. S urveys and studies of cotton and soybean management practices reveal some trends in a four

- region tillage report , comprising West, Midwest, Mid

- South and Southeast regions ( Monsanto, 2013d )

. Conservation t illage practices increased

, especially no till acres, at the expense of conv entional tillage for cotton, corn and soybean in the 10 year period 1998 to 2007 but subsequently began to change (Appendix 9) ( Monsanto, 2013d )

.

Recent tillage trends in cotton

. Conventional tillage of cotton fields in the M id

- South increased from 2007 to 2012/2013, while conser vation tillage substantially declined

. In the Midwest and Southeast, no till declined, but appears to be replaced by reduced

- till methods, since conventional tillage is flat but only trending toward an increase in both areas

. The survey of experts from bot h Southern regions together showed that the first factor identified that led to the change in tillage practice s was economics, the second reason was to manage existing weeds ( Monsanto, 2013d ) ; the first factor was likely a part of the second factor, whic h would be to solve important evolving weed problems using economically justifiable practices.

Recent tillage trends in soybean

. During the five year period 2007

- 2012, soybean growers in the Mid

- South (includes MS, LA, AR, and TN) increased conventional ti llage and practiced less no

till, but did not change reduced

- till efforts in the most recent period ( Monsanto, 2013d ) . The first and second drivers behind the observed trend were stated as the same as those for cotton (economics and weed management), while the third driver was see d bed preparation , the fourth, managing soil moisture and the fifth as preventing weed resistance

. . Some locations such as Tennessee, receive action recommendations from extension weed specialists to respond to severe Palmer amaranth with discing out the c rop and replanting, unless they can find a chopping crew to selectively remove this weed ( Steckel, 2013 )

. Soybean production in Midwestern states 12 also showed a two year trend towards increasing conventional tillage, with a substantive decrease in

no

- till, but instead with an increase in red uced

- till. Other regions such as the Southeast and East showed a two year trend toward increased conventional tillage, or no change, but no corresponding increase in reduced

- till practices. Experts considered that economics and managing existing weeds were the third and fourth proximate reason for the changes in these
states ( Monsanto, 2013d ) , although the second reason , a need for better seed bed preparation, could also be related to weed management issues, since seed bed preparation controls early weed competitors of the crop ( Gunsolus et al. , 2010 ) . A first reason for this grower response was a need to manage increased crop residue, which may be a consequence of newer varieties leaving increased stalk and crop detritus ( Monsanto, 2013d ) . While all reasons for the tillage changes are

n ot clear, and require further assessment, at least some of the changes were responses to weeds and weed resistance.

Magnitude of Potential Impacts on Resources APHIS identified changes in management practices that could cause impacts on natural and biologi cal resources. If approved for general use, the degree to which the GE crop varieties that

12 Ohio, Michigan, Indiana, Illinois, Wisconsin, Missouri, Minnesota, Iowa, Kentucky, Kansas, Nebraska, North Dakkota, and South Dakota.

140are the subject of this EIS are adopted will determine the magnitude of the impacts of the associated new management practices. Therefore, APHIS reviewed and analyze d here the range of possible management practices and their impacts

. Because APHIS does not regulate production or management practices, the agency cannot control the choices growers make.

5.5 Assumptions

A summary of the assumptions made for the analyses incl uded in this section follow:

• The APHIS PPRA s did not identify any changes in MON 88701 cotton or MON 87708 soybean that would directly or indirectly affect natural or biological resources. These plants are compositionally similar to other cotton and soybean plants. The growth habits of these plants are also similar to other cotton and soybean plants. APHIS assumes that growers will choose management practices appropriate for the crops planted.

• APHIS used information available from extension services, trade journals, scientific journals, and public comments for petitions to identify common practices.

• Most of the U.S. cotton and soybean acreage is currently planted in HR varieties. APHIS assumes that HR cotton and soybean varieties will continue to be planted under all of the Alternatives.

• Under Alternatives 2, 3, and 4, when MON 88701 cotton and MON 87708 soybean, and the crops are determined as nonregulated

, these could be crossed with any currentl y available varieties of these crops, including GE varieties no longer regulated by APHIS.

• APHIS considers that h erbicide applications will conform to the EPA

- registered uses for cotton and soybean.

• In addition to cotton and soybean, APHIS assumes that ot her approved dicamba uses (e.g. on pastures, wheat, oats, barley, millet, turf, sorghum, corn, sugarcane, asparagus) will conform to EPA

- approved label requirements.

• APHIS assumes that the impacts associated with drift from dicamba and other pesticide
app lications will be mitigated to an acceptable level by the registration requirements established by EPA.

• APHIS assumes that dicamba treatments may or may not include glyphosate, although many treatments may be made with the dicamba (M1691) formulation to co tton and soybean which could possibly include both as a premix. Stewardship agreements and registration requirements for new dicamba herbicide use with respect to MON 87708 soybean and MON 88701 cotton will include a requirement to us e both dicamba and glyphosate and another herbicide in certain circumstances . Monsanto states : “ In fields where glyphosate

- resistant broadleaf weeds are present or suspected glyphosate plus dicamba will be recommended. In addition, Monsanto will recommend an additional herbicide with a third mode

- of

- action that also has activity on the glyphosate

- resistant broadleaf weed, thereby providing two effective modes

- of

- action to control glyphosate

resistant weeds ” ( Monsanto, 2013d )

.

• APHIS accepts as likely the Monsanto estimate of herbicide use for dicamba, glyphosate, and glufosinate for the four Alternatives, assuming approval of the new dicamba uses by EPA. The herbicide volume estimates are discussed in detail in Appendix 4. These estimates were based on th e assumption that dicamba use on MON 88701 cotton and MON 87708 soybean will increase, while dicamba uses on turf, range, pasture, and

141industrial manag ement will not change. In brief, dicamba use is expected to increase under the No Action and Action Alter natives (analysis by Monsanto of trends between 2011 and 2015 shows an expected 100% increase in use of non

- glyphosate herbicides ( Monsanto, 2013a ) ). Under the Action Alternatives, the increase in dicamba use is expected to be greater when compared to the No Action Alternative. Glyphosate use on cotton and soybean is not expected to increase under the No Action and Preferred Alternatives because of market saturation; between 2011 and 2013, HR soybean was planted on 93

- 94% of total acres and HR cotton was planted on 73%

- 82% of total acres ( USDA

- NASS, 2012c ; 2013c ) . As of 2010, 98% of the corn acres, 99% of the cotton acres and 98% of the soybean acres are treated with herbicides (with glyphosate being the most commonly used) ( USDA

- NASS, 2011b ; 2013a )

. APHIS understands that growers will be required to participate in Monsanto Technology Stewardship Agreements (MTSA) and Technology Use Guides (TUGs). The Technology Use Guides contain best

man agement practices and requirements for growers who use MON 88701 cotton and MON 87708 soybean varieties, including weed resistance management practices ( Monsanto, 2013a ) . Practices such as the use of an herbicide with a trait for a third mode of action in glyphosate resistant crops, and recommendations regarding th e most effective rates and timing of applications for dicamba and glufosinate treatments will reduce the potential for weed communities in cotton and soybean fields to shift to more resistant weed species. EPA has specified such requirements be included on the label for the Enlist Duo herbicide as part of that proposed registration ( US

- EPA, 2014a )

. In the future, the agency intends to apply this approach to weed resistance management for all existing and new herbicides used on herbicide tolerant crops

. 13 APHIS expects the EPA to implement similar appropriate label requirements on the registration of M1691 herbici de regarding

re sistance management

.
5.6 Preferred Alternative : Cumulative Impac t

Production of MON 87708 soybean and MON 88701 cotton would not affect natural or biological resources directly, but rather the agricultural management practices (e.g., pesticide applications) associated with cultivation of these crops and its potential impact on natural and biolo gical resources. The interaction of cultural and mechanical practices affect agricultural and natural resources, and these include crop rotation s, and sequences of crops, selections of varieties and traits and tillage practice s. Pest control practices are also relevant and include patterns, numbers and specific choices of applied herbicides or other pesticidal chemicals as well as mechanical and cultural controls. These management practices all accumulate spec ific outcomes for crop yield, and soil, water, or air impacts. Other consequences may include development of problem or herbicide resistant weeds, or adverse effects on successive crops planted on the same land. APHIS will discuss those selected issues whi ch will or may potentially impact these agricultural and natural resources in the context of the Cumulative Impacts section, since as noted, the EPA approval of new dicamba uses was a foreseeable event, rather than an already existing status.

13 h ttp://y osemite.epa.gov/opa/admpress.nsf/bd4379a92ceceeac8525735900400c27/72fde554930f3f6985257d720059 1180!OpenDocument

1425.6.1 Land Use and Acreage

Summary: MON 87708 soybean and MON 88701 cotton commercialization and the EPA approval of the new uses of dicamba on these crops are not likely to change overall agricultural acreage in the United States. If weed control costs become lower as a re sult of the availability of these crops with the proposed new EPA

- registered dicamba uses, and net returns on either soybean or cotton are also higher, APHIS concludes that under the Preferred Alternative

, there may be economic incentives for growers to in cre ase soybean and cotton acreage in two of the 13 regions of soybean and cotton production.

U.S. soybean acreage increased over the past two decades. The greatest increase occurred in the northern and western parts of the Region G and the Region H ( USDA

- NASS, 2013d ) . During the same period, wheat and small grain acreage decreased in these ar eas ( USDA

- NASS, 2013d )

. U.S. planted cotton acreage declined somewhat, and between1996 and 2004, averaged 14.4 million acres, while between 2005 and 2013, averaged 11.9 million acres ( USDA

- NASS, 2014c )

. Cotton acreage is expected to increase about 1 million acres in 2014, with subsequent moderate growth, reflecting falling values for other crops; soybean acreage will remain around 78 million acres until 2023, but both soybean and corn will compete for land use with other crops ( USDA

OCE, 2014b )

. An APHIS determination of nonregulated status of the two varieties and the EPA registration of new formulations of dicamba is not anticipated to change cotton and soybean acreage in Reg ions A

- M because other factors such as cotton and soybean prices have a greater influence on planting decisions. Cotton and soybean acreage in Regions G and I is not likely to change unless the MON 87708 soybean and MON 88701 cotton crop strategy for weed control reduces costs compared to the No Action Alternative. If the cost of production is sufficiently reduced to allow the net returns from growing dicamba

- resistant soybeans to exceed that of other crops, growers may choose to plant more soybeans in thes e areas under this Alter native. Other factors su ch as changes in price of commodities and input costs are also variable and affect planting decisions. One of these is the pricing of these products, and the utility to growers of purchasing MON 87708 soybean and MON 88701 cotton seeds

. The potential contribution of MON 88701 cotton to expanding cotton acreage in Region D and J (70% of U.S. cotton acreage) and MON 87708 soybean in Region C and G (57% of U.S. soybean acreage) is not known

. APHIS does not interp ret the dicamba

- resistance trait as having any potential for changing the economics of soybean and cotton production in the United States , and so these crops (MON 87708 soybean and MON 88701 cotton) are not likely to increase production acreage of either o f these crops

.

5.6.2 Agronomic Practices

Summary: Currently, dicamba is used on only about 1% of soybean acres, and on average, once a season as a burndown or pre

- plant herbicide. On dicamba

- resistant soybean, Monsanto projects dicamba is likely to be used twice a year on no

- till and GR weed infested fields, or once on conventional fields

. While dicamba use is expected to increase if dicamba

- resistant soybean is determined as nonregulated, APHIS agrees with analyses indicating that substantive PRE non

- glyphosate herbicide applications will likely be eliminated, as may more than half of POST non

- glyphosate applications.

143Currently, dicamba is used on about 12% of cotton acres, mainly as a pre

- plant application once per season

. Monsanto asserts that the rate and number of applications made on MON 88701 cotton will depend on two primary factors: 1) the tillage practice s and 2) the weed spectrum

. Monsanto projects that 39% of MON 88701 cotton acreage will receive one application, about one half will receive two applications of dicamba per season and the remaining 11% , three. Overall, the projected adoption of MON 88701 cotton will be about 50% of all cotton acres

. The amount of dicamba that would be used on cotton may increase 14

- fold, but A PHIS agrees with estimates that the application of other herbicides would likely decrease on 2.6 million acres of cotton , which would be 26% of harvested cotton acres from 2014

. Glufosinate use on soybean and cotton has been increasing in recent years as a result of growers choosing to plant glufosinate

- resistant varieties because of the increased prevalence of glyphosate

- resistant weeds

. APHIS concludes that total U.S. glufosinate use on soybean and cotton is expected to decrease because dicamba is a more versatile and efficacious herbicide, and use of dicamba as a POST application will likely be preferred on MON 87708 soybean and MON 88701 cotton

. Glyphosate use is not expected to increase, since it is used on most soybean acreage already and on at least 83% of cotton, but will continue to be used because of its efficacy in controlling many weed species

. APHIS concludes that pressure to increase

con ventional tillage rates because of increasing weed resistance of some species to glyphosate can be alleviated with use of a new herbicide chemistry in addition to use of the existing effectiveness of glyphosate herbicide.

Non

- glyphosate herbicide use in cotton and soybean during the period from 2008 to present has been steadily increasing in response to a need to control glyphosate

- resistant weeds that are increasingly present. Some of the increases may also have come in response to ad vice from weed scientists for averting the development of herbicide

resistant we eds. It is likely that because PRE and POST application s of dicamba ( including those with glyphosate) will control certain HR weeds, use of MON 87708 soybean and MON 88701 cott on will allow for replacement of other herbicides. Similar results are likely in cotton as well. Under the Preferred Alternative the addition of POST

applied dicamba and residual herbicides will be parts of a coordinated herbicide use strategy on MON 87708 soybean and MON 88701 cotton crops.
Changes in Dicamba Use Dicamba is currently registered for use on soybeans at application rates similar to those proposed for MON 87708 soybean. However, the proposed EPA

- approved label would allow for dicamba applicat ions at later stages of plant growth than currently approved for soybean. At peak MON 87708 soybean use, Monsanto estimates that the technology will be adopted on about 4 0 percent of all soybean acres, compared to 2011 when only 1.2 percent of soybean grow ers used dicamba once per year for burndown or pre

- plant weed control (Tables A

- 2, A

- 3, and A

- 5 of the Monsanto ER) ( Monsanto, 2013a ) . Dicamba will likely be used on average twice per season on Xtend soybean, on no

- till and GR Ameranthus

- infested fields, and twice for conventional tillage fields (Table A

- 5 of the M onsanto ER) ( Monsanto, 2013b ; 2013a ) . Thus, more dicamba herbicide will be sprayed on Xtend soybean acre age than are likely to be sprayed with dicamba

144on p resent varieties. Increased use of dicamba would however, result in a decrease of up to 21 percent of projected total acreage treated with PRE 14 non

- glyphosate herbicide, and 56 percent of projected total area treated with POST 15 non

- glyphosate herbicide , wh en peak use of Xtend soybean attains 40 percent of all soybean crops (Section A.3.6 of the Monsanto ER) Monsanto ( Monsanto, 2013b )

. At peak extent of Xtend cotton adoption, 50% of US acres will be planted to the variety, and no

till cotton acres would be sprayed three times in W.TX, AZ, OK, NM, and KS and conventional till acres two times

. In all other cotton growing regions , Xtend no

- till cotton will be sprayed twice and conventional till but once ( Monsanto, 2013b )

. One commenter on the DEIS suggested that because GR Palmer ameranth was common i n the Delta and Southeast regions that an additional application of dicamba would be needed in these states ( Merchant et al. , 2013 )

. However
, this study actually showed that a second herbicide chemistry was needed for Palmer control, b ut not a second application of dicamba (CFS Science Comment I, 2014)

. Replacement of non

- glyphosate PRE herbicides by Xtend dicamba will likely occur on 34% of cot ton acres, and replacement of POST herbicides on 37% of cotton acres ( Monsanto, 2013b ) . APHIS concludes that these values of herbicide reductions presented by Monsanto are reasonable estimates of future herbicide use

.
If the Preferred Alternative is chose n, and the EPA approves new use s of dicamba for MON 87708 soybean and MON 88701 cotton the increase in dicamba use on cotton acres with respect to the present use of dicamba on cotton would be an increase of 14.3 times more than that estimated under the No Action Alternative (Appendix 4, Table 4

- 9). The increased use of dicamba on soybean would be 88 times more than present, since it is so sparingly used in current practice. The use of dicamba on soybean with respect to dicamba use on all other crops would present an increase of 5.4 times , and the increased use of dicamba in both crops compared to all dicamba uses would be 6.8 times . Dicamba at present can mainly be used as a pre

- plant on cotton (if the maximum application rate is used ) , and the planting can come only 21 days after application (Clarity dicamba label). No dicamba application is permitted west of the Rocky Mountains. If dicamba is used on soybean in pre

- plant applications under present label directions (at maximum applica tion rate: pla nting not earlier than 28 days after application

, ( see Clarity dicamba label ( BASF, 2010 ) ) relatively little is used because allow able exposure to the crop is limited.

One additi onal source for a possible increase in crop use of dicamba is on corn fields that are adjacent to MON 87708 soybean

. G rowers who might have used a non

- dicamba herbicide on corn, possibly to protect adjacent and sensitive soybean might instead apply dicamba herbicide to corn because this sensitivity issue would be no longer relevant

. APHIS has considered this concern (CFS Science Comment I), but concludes that corn growers have many choices of herbicides, many newer than dicamba, and would not necessarily be any more likely to choose dicamba for weeds on the corn adjacent to MON 87708 soybean

. P revious dicamba use on corn from 1993

- 1997 attained to 21

- 29% of corn acreage, but later declined in 2010 and 2011 to 7

-

14 PRE = pre

- plant/pre

- emergence application to the crop
15 POST = post

- emergence in

- crop use

14510% of acres (see CFS Science Comments I)

. Again, APHIS considers that th is older

, three fold higher use of dicamba reflect s needs for the herbicide at that time, and that newer herbicides may be better , more numerous and more economical . S o, additional dicamba use on adjacent corn production near soybean is not likely to be observed

. Changes in Glufosinate Use Glufosinate use is expected to increase under the No Action Alternative as growers continue to increase their adoption of glufosinate

- resistant crops

. U nder the Preferred Alternative , APHIS agrees that glufosinate use may decline, based on comparative efficacy data and the observation that dicamba is considered a more effective option for GR weed control compared to glufosinate ( Monsanto, 2013a )

. As one commenter noted (CFS Science Comments I), efficacy in control of some GR weeds such as Palmer ameranth is enhanced by using both glufosinate and dicamba ( Merchant et al. , 2013 )

. Monsanto does recommend for the Mid South and in Southeast states that when GR weeds are present, growers should apply glufosinate

. Since use of glufosinate resistant cotton and soybean is already high in these stat es (USDA

- AMS in ( York, 2012 )

, 39

- 67% Glufosinate tolerant varieties planted in NC, VA, SC, GA, TN). Glufosinate (Liberty) can be used on Bayer varieties, and is commonly used off

- label on Phytogen Widestrike lines

. If glufosinate with dicamba were in new cotton usages, APHIS concludes that the dicamba

- and glufosinate

- resistant varieties would replace these glufosinate

- resistant

- only varieties and would not result in additional glufosinate applications.

Changes in Glyphosate Use

Glyphosate use on cotton and soybean is not expected to increase under the No Action or Preferred Alternatives because of market saturation; between 2011 and 2013, HR soybean was planted on 93

- 94% of total acres and HR cotton was planted on 73%

- 82% of total acres ( USDA

NASS, 2012c ; 2013c ) . As of 2010, 98% of the co rn acres, 99% of the cotton acres and 98% of the soybean acres are treated with herbicides (with glyphosate being the most commonly used) ( USDA

- NASS, 2011b ; 2013a )

. Changes in Use of Non

- G lyphosate Herbicides APHIS considered the question of whether some e xisting agronomic practices may facilitate new resistant weeds and more herbicide use . Mortensen et al. ( 2012 ) assert that the use of additional herbicide resistant crops will only increase the frequency of herbicide applications. T he appearance of new herbicide resistant weeds then becomes an unavoidable consequence of more herbicide applications

. Under that assertion, the availability of MON 87708 soybean and MON 88701 cotton could be accompanied first by first enhanced control, but followed by increasing weed resistance that required higher rates of herbicide applications to meet the increasing weed resistan ce

. Using glyphosate, growers discovered that they could simplify weed control often with use of only glyphosate

. In the absence of two

- factor herbicide control, resistance to glyphosate easily developed and following that, non

- glyphosate herbicide
treatme nts expanded

. While dicamba use will increase following determination of nonregulated status of MON 87708 soybean and MON 88701 cotton , the likelihood that use of other herbicides will decrease should also to be assessed

. The larger tapestry of how existin g herbicides will be used together is also a key part of the success of herbicides in directing sustainable weed control measures.

146APHIS concludes that h erbicides alone do not cause resistance, nor do HR crops, rather, the absence of diversity in herbicide use and in tactics for weed management is more relevant ( Norsworthy et al.

, 2012 ; Shaner, 2014 ) . While managing existing and future problem weeds with herbicides is a focus at present, APHIS agrees that th is focus is not likely to provide for agronomic sustainability. New r esearch into weed science and broader weed management practices might take new directions to improve the prognosis, but limited options may be available at present to deal sustainably with weeds ( Shaner, 2014 )

. Soybean herbicide trends and replacement by MON 87708 soybean and MON 88701 cotton

. Some assert th at new herbicide use on synthetic auxin

- type resistant soybean will simply add to existing herbicide use. It is informative to measure how herbicide usage changed from the first availability of glyphosate resistant crops to the presen t. Mortensen et al. ( 2012 ) used data from 2007 and earlier from an 2010 NRC publication showing a decrease in use of the non

- glyphosate herbicides

. Using this, they postulated constant levels of non

- glyphosate herbicide use until additional herbicide resi stant crops were available. After these crops were adopted, t he se authors assumed highly increased herbicide usage rates. Using extensive market research data, Monsanto ( Monsanto, 2013a ) showed that total area treated PRE with non

- glyphosate herbicides for 2002

- 2007 on soybean increased only 11% and treated POST de creased 7% ( ( Monsanto, 2013a )

, Appendix A, Herbicide use trends: Impact of DR soybean on future herbicide use; Table A

- 10 and A

- 11). In the more recent period 2008

- 2011, PRE applications increased 177% and POST 345% (Tables A

- 10 and A

- 11). From these it is clear that the present pattern of non

- glyphosate herbic ide applications is steadily increasing, even without any additional herbicide resistant crops. The factors which drive this increase are the development of glyphosate resistant weeds, and the advice of weed experts and extension personnel which advocate i ncreased use of best management practices, often including multiple herbicides ( Marshall, 2012 ; Norsworthy et al.

, 2012 )

Data derived from market researc h on herbicide use by grower s ( Monsanto, 2013a ) was subjected to regression analysis procedures, and assessment made of existing trends. From this, forecasts of how much herbicide would be used in future PRE and POST applications to soybean crops were made, based on weed management needs, acce ptable weed control, and on costs of herbicide and mechanical tillage (ER, Herbicide use trends: Impact of DR soybean on future herbicide use ( Monsanto, 2013a ) ). As noted in Figures A

- 1 and A

- 2 ( ( Monsanto, 2013a )

, Appendix A), beginning in about 2015, the increase in non

- glyphosate herbicide use levels off because of the restraints of economics and efficiency of weed contr ol

. As can be shown later in this section, the use of the dicamba and glyphosate tolerant crops will have advantages over many of the non

- glyphosate herbicides presently being used on soybean ( ( Monsanto, 2013a ) , Appendix A, S ection A

- 4.2.2 and following). Under the Preferred Alternative, APHIS agrees that d icamba may dis place substantial quantities of these herbicides, and potentially stabilize increases in the total herbicides that are applied to soybean. For example, dicamba and glyphosate resistant Xtend plants may lead to dis place ment of 60% of some of the PRE herbicides used in soybean production

. These include synthetic auxins like 2,4

- D, the PSI inhibitor paraquat or the glutamine synthase inhibitors, like glufosinate, because of improved efficacy, lack of a carryover effect, and for reasons of crop safety ( ( Monsanto, 2013a )

, Appendix A, Herbicide use trends: Impact of DT soybean on future herbicide use ; Table A

- 15). For POST herbicides, various PPO herbicides such as fomesafen and chloransulam

- methyl,

147various ALS inhibitors such as chlorimuron and imazamox, and a PSII inhibitor bentazone, are
pr ojected to be 80% dis placed by dicamba/glyphosate used on herbicide

- resistant soybean

. I ssues related to efficacy, carryover, crop safety and existing weed resistance to these herbicides will drive this displacement ( ( Monsanto, 2013a ) , Appendix A, Herbicide use trends: Impact of DT soybean on future herbicide use; Table A

- 16).

The PPOs are one of the few classes of effective POST herbicides for soybean , given that widespread weeds have both resistance to glyphosate and resistance to several classes of herbicide ( Hager, 2013 ) . Dicamba can replace the PPOs (some PPOs have less eff icacy on GR waterhemp compared to other PPOs (fluthiacet) ( Hager, 2013 ) while others are effective as residuals on GR and ALS resistant weeds (such as flumioxazin ( VanGessel, 2014a ) ) but should be used cautiously to avoid new resistance ( University of Illinois , 2013 ) . In both situations, availability of MON 87708 soybean would be a useful tool to deal with GR weeds and to spare the use of effective PPOs

. As a professor and extension agronomist notes with respect to cotton (S. Culpepper, University of Georgia . Public Comment APHIS

- 2013

- 0043

- 3209 ), “ The greatest risk for developing herbicide resistance is actually occurring at this moment with the PPO herbicides and glufosinate. These products are being over used as growers have no other effective herbicidal op tions. New technologies such as dicamba could be used to delay resistance development to the PPO herbicides and glufosinate and, in turn, systems could be developed using the PPO herbicides, glufosinate and dicamba extending the life of each of these chemi stries. ” APHIS concludes that the usefulness of the PPO herbicide class and glufosinate could be prolonged by reducing overexposure of weeds to these effective soybean herbicides by the availability of dicamba

- and glufosinate

- resistant crops

. Effects o f MON 87708 soybean and MON 88701 cotton on herbicide use trends

. A pattern of increasing use of non

- glyphosate herbicides (see Table A

- 37 to A

- 39) on cotton can be discerned from grower surveys conducted by a contracting company for Monsanto in 2012 ( Monsanto, 2013a ) . PRE herbicide use over t he period 2002 to 2009 increased about 15%, with growers notably using 2,4

- D and paraquat for burndown, fomesafen, trifluralin and fumioxazin as preplants with activity extending into post emergent growth, and pendimethalin as a preemergent ( ( Monsanto, 2013a ) , Appendix A, A.4.1.3. Analysis of Cotton Herbicide Use From 2002

- 2011). PRE non

- glyphosate herbicide use in cotton increased more sharply between 2009 and 2011, rising 113% ( ( Monsanto, 2013a ) , Appendix A, Table A

- 37). To some extent, the totals reflect a decline in total cotton acres from 2002 and 2003 compared to 2009, and an increase in cotton acreage again by 2011 ( ( Monsanto, 2013a ) , Table A

- 39).

A 250% increase in non

- glyph osate herbicide applications occurred between 2003 (30.2%) and 2011 (75.8%) when expressed as ratios of the acreage of non

- glyphosate herbicides to total planted cotton acres ( Table 18 ) . Applications of non

- glyphosate herbicide treatments increased in 2008 from 1.5 and in 2011 to almost 2.2 ( ( Monsanto, 2013a ) , Table A

- 38). Glyphosate

- resistant cotton plantings declined 24% during the first period, then increased 68% from 2009 to 2011. The much larger increase in non

- glyphosate herbicides applied was not correlated with GR cotton plantings, but with a rise in GR weed development, and the recommendations by weed scientists and extension personnel that growers should employ diversity in weed management practices to counteract the p attern of resistant weed development.

148Table 18

. Acres and Percentage s of Cotton Acres Treated with Non

- Glyphosate Herbicides

. Acreage (X1000) Year

2003 2005 2007 2009 2011

Total Area Treated

- Non

Glyphosate Herbicides 4,119 4,625 2,941 3,734 11,018

Total Planted Cotton Acres 13,626 14,024 10,732 9,042 14,533

Ratio of Treated Acres to Total Acres 30.2% 33.0% 27.4% 41.3% 75.8%

Data from ER, Appendix Table A

- 39 ( Monsanto, 2013a )
For POST emergent non

- glyphosate herbicide usage on GR cotton, a pattern of stasis and slight decline was s een between 2002 and 2009 based on grower survey data assembled by Monsanto ( ( Monsanto, 2013a ) , Appendix A, A. 4.1.4., Table A

- 39). For 2009 to 2011, the total acreage treated with non

- glyphosate herbicides increased 220%. Just as was observed in the case of PRE herbicides, the amount of increased herbicide applica tion was far greater than that caused by the large increase in planted GR cotton acres. Again, management of weed resistance, both that already present, and avoidance of future weed resistance was the likely cause of the observed increases ( ( Monsanto, 2013a ) , Appendix A, A.4.1.4., Analysis of Cotton Herbicide Use From 2002

- 2011). For both PRE and POST glyphosate applications, the average numbers per year remained relatively stable, about 1.2 for PRE and about 1.7 for POST applications ( ( Monsanto, 2013a ) , Table A

- 38). Just as observed for PRE applications of non

- glyphosate herbicide to cotton, POST applications began rising from about 1.5 per season to around 2.2 ( ( Monsanto, 2013a )

, Tables A

- 38 and A

- 40).

APHIS concludes that under the Preferred Alternative the determination of nonregulated status for MON 87708 soybean and MON 88701 cotton will likely have considerable impacts on herbicide use patterns. Monsanto predicts that at peak adoption, 10.8 million acres will be planted with the MON 88701 cotton ( ( Monsanto, 2013a ) , Appendix A, A.4.1.5, Table A

- 40). The prediction is based on regional

- specific patterns of treatments per acre, the differences between no

- till (21%) and conventional tillage in herbicide treatments and with the assumption that 50% of growers will plant MON 87708 soybean and MON 88701 cotton . The consequences of this level of dicamba use for application of other herbicides on cotton were then assessed

. For PRE cotton herbicides, 100% displacement of diflufenzopyr was likely because of crop safety issues, 75% displacement of nine herbicides including paraquat, thifensulfuron, and carfentrazone because of crop safety issues, carryover, efficacy or grower p references, and 50% displacement of seven herbicides including 2,4

- D, fomesafen, and metolachlor for reasons of efficacy, crop safety, weed resistance and convenience ( ( Monsanto, 2013a ) , Table A

- 42). At

149peak adoption of MON 88701 cotton , 2.6 million acres will not receive these displaced herbicides with which these acres otherwise would have been treated. Among the likely displaced herbicides, the agronomic risk issues of these in comparison with dicamba shows that the displaced have between 2 and 5 issues in which they scored lower than dicamba in efficacy of the h erbicide, Palmer amaranth resistance in the class, number of resistant weeds to the class, long rotational restrictions, or serious crop injury potential ( ( Monsanto, 2013a ) , Appendix, Table A

- 55). Among the herbicides that may be replaced, several can be used as both PRE residuals, and POST directed

- spray herbicides, such as fluometuron, prometryn, and diuron ( Steckel, 2014 )

. Under the Preferred Alternative, MON 87708 soybean and MON 88701 cotton will be available, and dicamba can be used to prolong the useful activities of these herbicides by providing a means for overlapping herbicidal control of problem and resistant weeds

. It is more likely t hat weed resistance will not develop as quickly as under the No Action alternative

. Under the Preferred Alternative

, with this HR crop available, growers will be offered an opportunity to alternat e herbicide resistance systems (such as glufosinate and HPPD inhibitor resistant cotton) in successive seasons.

Dicamba Volatilization and Drift Summary: APHIS anticipates that the EPA will approve the registration of the proposed new uses of dicamba formulation M1691 (U.S. EPA Reg. No. 524

- 582) on MON 88701 cotton and MON 87708 soybean. This herbicide product contains the dicamba diglycolamine (DGA) salt which has a lower volatilit y profile than the dimethylamine (DMA) salt or other acid

- based formulations of dicamba currently in use. APHIS also anticipates that the EPA will approve these proposed new uses on two new products containing the BAPMA salt of dicamba (Engenia, Reg

. No

. 7969

- GUL and MON 100111, Reg. No. 524

- ANO), which are pending at EPA, as well as two Monsanto formulations (Reg

. No

. 524

- 616 and 524

- 617). Monsanto will not allow the use of the higher volatility DMA salt and dicamba acid formulations on MON 87708 so y bean and MON 88701 cotton (Monsanto 2013a). Consequently, if the EPA registers new herbicide use s for MON 87708 soybean and MON 88701 cotton , volatilization and drift issues will not likely be substantially different from those for other h erbicides on conventional crops following a determination of nonregulated status for these crops . The EPA retains oversight and regulatory authority for all environmental impacts caused by herbicide drift or volatility. APHIS accepts that there are also nu merous practical measures that good growers will adopt to reduce off

- target movement of applied herbicides.

A n assumption in the No Action Alternative is that dicamba will be applied increasingly to cotton and soybean, because dicamba can be used to contro l GR weeds. As a result, the acreage to which dicamba will be applied may likely increase from 1.4 to 4 0% of soybean cropland and from11.5% of cotton cropland to 50% ( Monsanto, 2013b )

. Dicamba burndown applications on cotton and soybean ha ve been steadily increasing sinc e 2006 ( see Table 23 ) since it has activity against several GR weeds, often when applied with 2,4

- D ( Monsanto, 2013a ) . Current use of dicamba for burndown applications in cotton and soybean are 10% and 12%, respectively ( Monsanto, 2013a ) . The formulations used under the No Action Alter native are those dicamba formulation currently registered by EPA, including both the dimethylamine (DMA) formulation and the DGA. The D G A formulation is about 10 times less volatile than for D M A.

150If MON 87708 soybean and MON 88701 cotton are nonregulated and EPA approves the
propose d new uses of dicamba on these crops

, Monsanto estimates that dicamba would replace about one

- third of other non

- glyphosate herbicides at maximum adoption rates

. However , the relative use of dicamba on cotton would increase 14.5

- fold (Appendix 4, Table 4

- 12) and on soybean 88

- fold (Appendix 4, Table 4

- 9). Potential for off

- target impacts would decline because growers would be applying the lower volatility dicamba formulation in place of these oth er higher volatility herbicides

.

U nlike the No Action Alternative, for the Action Alternatives, APHIS expects that the EPA will approve the registration of the proposed new uses of dicamba formulation M1691 (U.S. EPA Reg. No. 524

- 582) on MON 88701 cotton and MON 87708 soybean. This herbici de product contains the dicamba diglycolamine (DGA) salt which has a lower volatility profile than the dimethylamine (DMA) salt or other acid

- based formulations of dicamba currently in use. APHIS also expects that the EPA will approve these proposed new u ses on two new products containing the BAPMA salt of dicamba (Engenia, Reg

. No

. 7969

- GUL and MON 100111, Reg. No. 524

- ANO), which are pending at EPA, as well as two Monsanto formulations (Reg

. No

. 524

- 616 and 524

- 617). Monsanto will not allow the use of th e higher volatility DMA salt and dicamba acid formulations on MON 87708 soybean and MON 88701 cotton

. Consequently, APHIS deems it likely that o verall use of more volatile formulations of dicamba may decline if MON 87708 soybean and MON 88701 cotton are determined as nonregulated

. Though off

- target dicamba effects may be lower for the Preferred Alternative than for the No Action Alternative, the use of dicamba may occur over a longer season under the Preferred Alternative. This could increase exposure of dicamba

- sensitive plants at growth stages later in the season than under the No Action Alternative . These offsetting impacts (less volatile formulations but potentially greater exposure) make it difficult to predict which Alternative is likely to result i n more drift and possible plant injury.

Recently, EPA approved the registration of Enlist Duo herbicide (a premix of 2,4

- D and glyphosate) for use on 2,4

- D

- resistant corn and soybean

. Measures to limit off

- site transport of 2,4

- D choline salt in spray dri ft have been included as part of the label requirements specified by EPA for the registration of Enlist Duo. To mitigate against potential risks to non

- target organisms or crops , the herbicide label will require specific techniques, suc h as a 30

- foot on

- fi el d buffer zone and use of a specific nozzle/formulation combination ( US

- EPA, 2014a )

. APHIS expects the EPA to implement similar appropriate label requirements on the registrat ion of M1691 herbicide regarding res istance management

. APHIS recognizes that there are many practical methods available to growers to reduce off

target herbicide effects

. The sources of the movement is either spra y particle drift, volatility of the herbicide or tank contamination ( Boerboom, 2004 )

. York ( 2014 ) notes that for 2,4

- D, growers should always use the the 2,4

- D amine, and avoid the 2,4

- D ester or acid formulati ons within a mile of cotton production because of large potential for volatile damage; similarly for dicamba, the diglycolamine salt is much less volatile than is the dicamba dimethy lamine or acid formulation ( Monsanto, 2013c ) . Spray drift with auxinics can also be handled adequate ly with 200 foot buffers, avoiding nozzles with fine spray output , and not applying these herbicides on windy days (which would also be counter to label directions for crop applications) ( York, 2014 )

. Contamination of tanks can be avoided either by not using previously deployed tanks that

151contain ed auxinic herbicides or by thorough tank cleaning. While inadvertent off

- target dicamb a always provides a potential for injury to cotton or soybean, APHIS emphasizes that grower attentiveness to commonsense rules for choosing formul ations and practices can substantially eliminate such incidents of crop injury.

Tillage Practice Summary: Conventional tillage is increasing in some soybean and cotton growing areas, most likely because of increased problems with glyphosate

- resistant weeds

. This conclusion applies especially to Mid

- South states, which includes declines in both conventional and reduced tillage practice s

. Production of MON 88701 cotton and MON 87708 soybean and other newer herbicide

- resistant crops may be able to reverse some of those trends, especially in the near term, because new HR crops will be avai lable for commodity growers experiencing problem weeds

. Under the Preferred Alternative, adoption of MON 88701 cotton and MON 87708 soybean may help reverse these recent trends, allowing some growers to return to using conservation tillage.

No

- till farmin g practices are centered on effective herbicide

- based weed control

. Un der the No Action Alternative increased or more extensive t illage is occurring in certain areas where HR weeds are no longer effectively controlled by currently

- registered herbicides . Mo re aggressive tillage is one effective weed control option

. APHIS suggests that a doption of MON 88701 cotton and MON 87708 soybean may reverse this trend of increasing tillage that is occurring under the No Action Alternative. Reports of increased tillage as a result of GR weeds have already been made for cotton and soybean ( Shaw et al. , 2012 ; Riar et al. , 2013 ) . In some Tennessee counties (included in the region “Mid

- South”) , the area devoted to conservation tillage decreased by as much as 25% in soybean fields infested with GR horseweed ( Shaw et al. , 2012 )

. As noted earlier, survey of regional tillage patterns and expert assessments suggest that problem weeds were at least partially responsible for increases in conventional tillage and dec lines in conservation tillage; these conclusions were especially applicable in the Mid

- South states ( see Current Management Practices, Section 5.4). To some extent these were similar to other regions that showed declines in no

- till practices, although thes e were accompanied with increases in reduced till practices.

Under the Preferred Alternative, a doption of MON 88701 cotton and MON 87708 soybean and the EPA registration of new dicamba uses on these crops is expected to improve the control of GR weeds, dec reasing tillage intensity when compared to the No Action Alternative. This potential reduction in tillage is most likely to occur with the use of MON 88701 cotton because the increase in the use of tillage for weed management has occurred particularly in t he management of Palmer amaranth in cotton where “researchers recognize that integrated weed management (IWM) strategies that include tillage may be necessary” ( Shaw et al. , 2012 )

. Soybean

- planted acres that are in direct rotation with corn acres that also have the same weed complex will also benefit from the adoption of MON 87708 soybean and facilitation of reduced tillage. Midwestern states are beginning to identify GR Palmer amaranth just as in locations in the Southern States ( Brooks, 2013 ) and indic ations are that tillage practice s have begun to change similar to th ose observed in the Mid

- South states . Under the Preferred Alternative, APHIS concludes that c ontrol of these GR wee ds c ould improve in both regions , since a dica mba

- based herbicide strategy using MON 87708 soybean and MON 88701 cotton should

152provide herbicide diversity and effective use of dicamba . If dicamba resistant weeds develop, growers might consider increased tillage as a remedy. APHIS anticipates that grow ers who practice good stewardship of this technology will attain extended usefulness of MON 87708 soybean and MON 88701 cotton. However, alternatives will eventually be needed, and thus additional effective herbicide strategies may need to be developed, as will new or classic cultural or mechanical practices may need to be adopted.

Crop Rotation
Under the Preferred Alternative, a doption of MON 88701 cotton and MON 87708 soybean and EPA registration for new dicamba formulations for these crops is not expected to change cotton and soybean crop rotation al practices. However, if dicamba

- resistant weeds reduce the cost effectivenes s of growing certain crops, rotation practices may need to change. For example (see Table 19 and Table 20 ), wheat and small grain crops are sometimes rotated with soybeans (wheat 22%, barley 1.9%, oats 4.9%) and with cotton (wheat 9.3%, barley, 0.4%). Usage of dicamba on wheat crops was either 0.5% (following cotton rotation) or 5% (following soybean rotation ( see Table 19 an d Table 20 )

. Some growers of small grain cereals rely on dicamba for inexpensive

wee d control. If dicamba was to become ineffective and the cost of alternative herbicides was too expensive, these growers may choose not to grow small grains. Input costs are just one factor that determines whether a given rotation crop is grown. However, o ther considerations include benefits to the soil, disease management considerations, and economic returns from gr owing the rotation crop. Under the Preferred Alternative, APHIS concludes that minor changes to crop rotations are possible, but not likely to be substantial.

153154 Table 19

. Rotational Practices Following Soybean Production in the United S tates

.

This U.S. summary was developed by compiling the data from all three regional summaries. All acreage is expressed as 1000s of acres. 1 Acreage planted of the specific crops is based on 2008 planting data ( USDA

- ERS, 2012b ) “other” crop and newly seeded alfalfa acreages are based on 2008 planting data from the Individual States data which was obtained from Quick Stat searches on http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp

. Originally provided in Petition for the Determination of Nonregulated Status for Dicamba

- Tolerant Soybean MON 87708 ( Monsanto, 2012a ) Table VIII

- 24
2 Column E is obtained by compiling the data from all three regional summaries.
3 Column F is obtained by dividing Column E by Column D.
4 Column G is obtained by dividing Column E by Column B.
5 Column H is obtained by compiling the data from all three regional summaries.
6 Column I is obtained by dividing Column H by Column E.
7 Column J is obtained by dividing Column B by Column D Total.
8 Column K is obtained by dividing Column H Total by Column D Total.
9 Various vegetables. A B C D E F G H I J K Major Total % % Acreage of % Dicamba % Soybean Estimated Crops Acreage of Rotational Rotational Rotational Dicamba in Usage in Acres % Dicamba Total Following Rotational Crop Acres Crop Crop of Rotational Rotational Preceding Usage in Soybean Soybean in Crop in the Following Following Total Crop Crop Major Major State Acres 1 Rotation U.S. 1 Soybean 2 Soybean 3 Soybean 4 Option 5 Option 6 Rotations 7 Rotations 8
United 75,037 Corn 80,130 51,500 64.3 68.6 5,053 9.8% States Soybean 75,037 10,866 14.5 14.5 4,350 40.0% Sorghum 4,020 841 20.9 1.1 Cotton 3,767 1,570 41.7 2.1 153 9.7% Wheat 37,414 8,396 22.4 11.2 448 5.3% Barley 2,159 41 1.9 0.05 Oats 1,995 98 4.9 0.1 Rice 2,301 1,042 45.3 1.4 Alfalfa 1,864 162 8.7 0.2 Sugar Beets 830 144 17.3 0.19 Potatoes 334 32 9.6 0.04 Dry Beans 1,183 35 3.0 0.05 Dry Peas 520 38 7.3 0.05 Millet 250 41 16.4 0.05 Flax 345 76 22.0 0.10 Other 9 452 155 31.3 0.20
Total 212,601 75,037 10,004 35.3 4.7155 Table 20

. Rotational Practices Following Cotton Production in the U nited S tates

. A B C D E F G H G I J K L M

Total Acres Cotton Acres 1 Rotational Crops Following

Cotton Rotational Crop Acres 2 % Rotational

Crop of

Total Cotton 3 Dicamba Usage in Rotational

Crop 4 Glufosinate Usage in Rotation Crop 5 Glyphosate Usage in Rotation Crop 6 % Usage in Total Rotational Crop Acres 7

% Acres % Acres % Acres Dicamba G lufosinate Glyphosate

United Cotton 5,858 53.4 50 2,930 21. 1,264 90.2 5,284 26.7 11.5 48.2 States Corn 1,736 15.8 8.1 141 6 37 88.0 1,527 1.3 0.3 13.9 10,974 Soybean 861 7.8 50 431 2.1 8 95.9 826 3.9 0.1 7.5 Sorghum 836 7.6 8.3 69 1.0 34.7 290 0.6 2.6 Wheat 1,025 9.3 5.6 57 NL 14.1 145 0.5 1.3 Barley 40 0.4 5.0 NL 27.5 11 0.02 0.1 Peanut 432 3.9 NL NL 21.1 91 0.8 Sunflower 22 0.2 NL NL 72.7 16 0.1 Alfalfa 8 47 0.4 NL NL 50 24 0.2 Vegetables 9 50 0.5 NL NL 2 1 0.01 Dry Beans 0.5 0.005 NL NL 40.0 0.2 0.002 Peppers 8 0.1 NL NL 37.5 3 0.03 Tomatoes 24 0.2 NL NL 45.8 11 0.1 Onions 6 0.06 NL NL 33.3 2 0.02 Tobacco 0.3 NL NL NL Total: Total: Total: Total: 10,974 3,630 1,309 8,231 33.1 11.9 75.0
This table was developed by compiling the data from all four regional summaries (Tables VIII

- 21 through VIII

- 24 of Monsanto Petition for Dicamba Cotton). All acreages are expressed as 1000s of acres. NL indicates not labeled for use. 1 Cotton acreage based on 2010 planting data ( USDA

- ERS, 2012b ; USDA

- NASS, 2014c )

. 2 Column C is obtained by compiling the data from the four regional summaries. 3 Column D is obtained by dividing Column C by Column A. 4 Column E is obtained by dividing Column F by Column C; Column F is ob tained by compiling the data from all four regional summaries. 5 Column G is obtained by dividing Column H by Column C; Column H is obtained by compiling the data from all four regional summ aries. 6 Column I is obtained by dividing Column J by Column C; Co lumn J is obtained by compiling the data from all four regional summaries 7 Column K is obtained by dividing Column F Total by Column C Total; Column L is obtained by dividing Column H Total by Column C Total; Column M is obtained by dividing Column J Total by Column C Total. 8 Newly seeded alfalfa. 9 Vegetables: Cauliflower (37 ,000 acres), lettuce (271 ,000 acres), and broccoli (124 ,000 acres) ( USDA

- ERS, 2012b )

. 10 Totals m ay not be exact due to roundin gGeneral Agronomic Inputs Adoption of MON 88701 cotton and MON 87708 soybean is not expected to change the general agronomic inputs associated with cotton and soybean production except to increase dicamba usage. Fertilizer, insecticide, fungicide, and water use are expected to remain unchanged from the No Action Alternative.

5.6.3 Socioeconomics

Potential Impacts of Dicamba

- Resistant Weeds on Production Practices for Other Crops and Grower Economics

To a nalyze the potential impacts from increased selection for dicamba

- resistant weeds under the Preferred Alternative, APHIS assumed that the greatest potential for impacts would be in regions where appreciable acres of cotton or soybean were grown in proximit y to appreciable acres of crops that already use dicamba for weed management.

This impact is likely to be highest in crops grown in rotation with MON 87708 soybean and MON 88701 cotton . Corn is the largest crop grown after soybean, followed in frequency by soybean again , then wheat, cotton and rice ( Table 19 ). When moisture is adequate, growers in southern Indiana, Illinois, Missouri and Arkansas may double

- crop winter wheat and soybeans in the same year. This leads to rotation of much of the winter wheat in this area with soybeans. However, there are no accurate ways of determining exactly what land is rotated from corn or soybean to other crops reliant on dicamba for w eed control. The rotation varies by region, such that for the eight state Southeast region, where soybean most frequently follows soybean, then corn, cotton, wheat and rice (ER Table VIII

- 26, ( Monsanto, 2012a ) ). Cotton again is the largest crop grown following cotton (i.e., continuous cotton) , followed by corn, wheat, soybean and then sorghum ( Table 20 ).

S election of dicamba

- resistant weeds in cotton or soybean may cause some types of cumulative impact s on other regional crops

. AP HIS conservatively assumed that proximity of other dicamba

- treated crops to dicamba

- treated MON 87708 soybean and MON 88701 cotton c ould facilitate th e potential impacts . The APHIS analysis is based on percentage of cropland devoted to cotton and soybean an d the percent of cropland devoted to crops to which dicamba is applied in each region. Table 17 identifies the major crops onto which dicamba is applied. Crops include: small grains (e.g., barley , oats) , corn, cotton , sorghum, soybeans, sugarcane, and wheat. APHIS also obtained the percent of regional cropland devoted to other major rotational crops of each region. These data are summarized in Table 21

. Regions D, E
, F, and J are areas where cotton and soybean production are predominant (at least >45% of crop a cres) and could potentially be at greater risk for development of dicamba resistant weeds

. C rops which receive applications of dicamba are components of th is landscape ( see Table 17

. In Regions L and M, cotton (no soybean) is of modest acreage and not expected to contribute to the cumulative impact s because there are few crops grown in these regions on which dicamba are applied. Region K has sorghum associated with a modest cotton crop, and selection of dicamba

- resistant weeds may have possible impact on sorghum production. In contrast, Regions D, F , and I, represent areas where cotton and soybean, and other crops onto which dicamba is

156applied are grown frequently in rotation and in proximity of one an other (shaded in gray in Table 21 ).

Region J has frequent co

- planting of cotton and wheat, which may be supportive for generating dicamba

- resistant weeds and be difficult to suppress if dicamba were used frequently in wheat. However, use of dicamba on wheat amounts t o only 8% [winter wheat] on these crops (see Table 17 ) and so alternatives to dicamba are being used and loss of dicamba usage because of dicamba resistant weeds would not be an insurmountable problem to control of weeds in wheat

. Region D includes the coastal Southeast and the Northeast to P ennsylvania . Principal crops to which dicamba is applied in this region are corn and wheat which together make up 43% of the crops grown. Soybean and cotton account for 53% of the crop acreage. With a large percentage of the acreage potentially planted to MON 87708 soybean and MON 88701 cotton , and another two crops to which dicamba would be applied ( cotton other than MON 88701) as a pre

- plant and wheat as a post

- emergent ), this region may have an increased potential to generate dicamba

resistant weeds

. If dicamba

- resistant weeds become widely prevalent in these regions, growers of dicamba appropriate rotation cr ops would be affected, although those who are affected could change their management practices.

Region F includes southern states bordering the Mississippi River (L ouisiana , M ississippi

, A rkansas , T ennessee , and M issouri ). Soybean is a principal crop for 51% of acres, and other crops that have dicamba applied in this region are wheat, cotton, and sugarcane (although sugarcane has limited rotation potential) . This region has a high incidence of GR weeds

. Therefore , the potential for selecting weeds with multiple resistance to bot h glyphosate and dicamba is high er relative to other regions. However, because dicamba only controls broadleaf weeds, herbicides with different modes of action will have to be used to control grasses. Th is will reduce the likelihood of multiple resistance because growers will not be able to depend exclusively on herbicide formulations labeled for MON 87708 soybean and MON 88701 cotton

, and b ecause of losses recently experienced with GR weeds, they will have another incentive to

use best management practices

. By employing a range of other management techniques they can reduce the risk of multiple resistance in weeds

. In addition, the EPA has the authority to address weed resistance by modifying the labeled uses of dicamba to mitigate risks of developing multi ply resistant weeds.

Region H includes parts of western North and South Dakota. The major crop in this region is wheat on which dicamba may be applied. Acreage for wheat in this region (34% of acres) is somewhat lower than that for corn and soybean togeth er (46% of acres) . A large percentage of the crops could have dicamba applied, and these may enhance the potential for development of weed resistance.

Region I consists of central K ansas , N ebraska , and part of O klahoma . Major crops in the region that may r eceive dicamba treatment are wheat, cotton, sorghum, and small grains. Soybean is about one fifth of the crop acreage and potentially could be replaced with MON 87708 soybean

, while 43% of the other crops would use a modest amount of dicamba. This region c ould potentially see an increased development of weed resistance to dicamba.

Region J consists of a part of north

- central Texas. This region most frequently grows cotton. Crops that receive applications of dicamba include small grains, cotton, and sorghum. In both

157Regions I and J, other crops receiving applications of dicamba excee d the amount of cotton and soybean that is grown. Determinations of nonregulated status for MON 87708 and 88701 could increase the potential for development of weed resistance to dicamba in several crops. Cumulative impacts are not expected in Region J und er Alternative 4 (nonregulated status of MON 87708 soybean

, only) or in the case that MON 88701 cotton is not widely adopted in this region.

Table 21

. Percent of Regional Cropland Devoted to Crops on which Dicamba is Used in Each E coRegion.

Percent of Regional Cropland

Ecoregion Crops on which dicamba is used (table also includes other important crops) Total Total

Corn Soy Wheat Oat, Barley, Millet Cotton Rice 2 Sorghum Alfalfa 1 Nut and Fruit Trees 1 % of Cropland in Cotton + Soy % of Cropland in O ther

Crops Using D icamba

A 48 18 6 2 18 18 56
B 53 26 3 15 26 56
C 53 40 3 3 40 56
D 28 32 15 21 <1 53 43
E 52 46 7 1 <1 47 59
F 51 20 10 12 11 1 32 72
G 45 40 8 40 53
H 26 20 34 3 20 60
I 34 23 33 1 12 9 35 76
J 2 0 39 54 6 54 47
K 13 0 26 6 48 6 26 67
L 12 0 12 6 25 40 25 30
M 9 0 14 10 13 28 10 23 Multiple crops may be grown the same year: double cropping of wheat for example, is common. Regions shaded in gray indicate areas where cotton and soybean are major crops (>40%) and other dicamba using crops are also widely prevalent (>40%). 1. No dicamba use 2. Little or no dicamba use

Possible Economic Impacts of MON 87708 S oybean and MON 88701 C otton on Rotation Crops on Which Growers Use Dicamba Summary: Production of minor crops in ecoregions where soybean, cotton and corn are major parts of the landscape (i.e., those crops that represent a small proportion of total crop acreage), are not likely to be impacted by the potential development of new dicamba

- resistant weeds

. APHIS considered whether the possibility of dicamba

- resistant weed developing in cotton or soybean would lead to new problem weeds in typical rotation crops. APHIS concludes that in the use of dicamba for fallow and burndown, there are several other herbicides that may be used in the same price range, in the event

158that dicamba resis tant weeds were to develop

. Although use of any herbicide requires consideration of cost, efficaciousness, plant

- back considerations and problem weeds, and the possibility of new dicamba resistant weeds appearing, then any increases in costs for weed contr ol in some crops may be acceptable. In the case of sorghum, it appears that dicamba resistant weeds would be controllable by availability of at least some of the alternative herbicides. An APHIS determination of nonregulated status wou ld not cause large impacts to pasture and rangeland by diminished effectiveness of dicamba because use of dicamba is relatively small, mechanical and cultural techniques are relatively important and numerous other herbicide choices are available

. For small grains, cost comparative alternatives exist, including those effective on broadleaf weeds, but some alternatives require more restrictions and may be more costly

. O ther tillage and cultivation possibilities that are practical present themselves in the eve nt of developing dicamba resistant weeds , however

. Should dicamba resistant weeds develop in conventional corn (that is, not dicamba resistant) no appreciable impacts on corn are expected, since only 12% of the corn producers are using dicamba, and there a re a number of alternative choices available for burndown use, both for PRE and POST applications. APHIS concludes that additional choices for control of multiply resistant weeds in soybean (such choices are increased with dicamba resistant varieties) may also be helpful for corn production, which is a frequent rotation crop, and this benefit may outweigh possible impacts of the loss of dicamba usefulness in corn production.

To evaluate how crops on which dicamba is currently used for weed control might be impacted if dicamba

- resistant weeds become more prevalent, APHIS examined the management options and costs for weed control in these crops. Weed control programs vary by crop, weed problem, geography, and cropping system (e.g., no

- till, conventional

- till, etc.). In those crops where it is labeled for use, dicamba is usually just one part of a much broader weed management strategy. Many growers use a combination of weed control techniques including cultural, mechanical, and chemical. APHIS is aware that the weeds of importance in one crop (e.g., soybean) are not necessarily the same ones that are problem weeds in a rotation crop (e.g., wheat)

. Thus, the potential impacts from a dicamba resistant weed species arising in soybean may not have a similar impact on wheat crops

. From a 2012 BASF market estimate of agricultural uses of dicamba ( Monsanto, 2014a ) , APHIS identified eight crops (or fallow cropland) where as much as 8% of the crop is treated with dicamba ( Table 17 ). Many of these, (e.g., small grains) are managed similarly and are considered together. For each c rop, or group of similar crops, APHIS considered the types and cost of herbicides that are used for broadleaf weed control. APHIS focused on post

- emergent, broadleaf weed control, as this is the primary use of dicamba in these crops.

Pasture One important agricultural use of dicamba is for broadleaf weed control on pastures, as noted in Table 17

. Alternative Herbicides and Management Options Effective management of weeds in pasture and rangeland usually involves a combination of cultural, mechanical, and chemical methods. The primary means of controlling weeds is proper management of desirable forage grasses and legumes. Overgra zing is a major cause contributing 159to the establishment and proliferation of weeds. Low soil fertility in pastures also contributes to weed problems. Some degraded pastures can be revitalized by reseeding or inter

- seeding to improve forage growth and compe tition. For some situations, burning or mowing can stimulate forage grass growth and suppress weeds. Combined with well

- timed herbicide applications, these methods can effectively manage weeds ( Martinson and Peterson, 2013 )

. Other methods that have a definite place in range management are: chemical, roto

- beating, plowing, disking, railing, chaining, burning, reseeding, and changes in grazing schedules. There

are s pecific sites and reasons for use of the controls listed. Each is effective if used properly ( Prather, 2014 )

.
Table 22 s hows a range of herbicide products that are currently registered for pastures and rangeland and t heir estimated costs. Herbicide alternatives to dicamba that provide reasonable low

- cost herbicide control are shaded in gray. Most pasture is not treated with herbicide. Mowing is a non

- chemical control method that is often used and is estimated to cost $ 13.95/acre in N ebraska ( University of Nebraska, 2012 )

.
Table 22

. Post

- emergence Broadleaf Herbicides Commonly Used in Pastures and Rangeland

. Herbicide (common name) MOA 1 Rate (lb ae or ai/A) Cost $/Acre

2,4

- D 4 1

- 2 5.00

- 10.00 Aminopyralid 4 0.06

- 0.11 16.12

- 32.11 Metsulfuron 2 0.06

- 0.6 1.35

- 13.53 Carfentrazone 14 0.015

- 0.031 1.70

- 3.40 Chlorsulfuron 2 0.19

- 1.0 5.00

- 25.08

Clopyralid 4 0.14

- 0.375 13.33

- 35.70 Dicamba 4 0.5

- 1.5 9.99

- 29.97 Fluroxypyr 4 0.6

- 0.72 20.63

- 24.76

Picloram 4 0.25 7.50 Triclopyr 4 0.25 3.75 Hexazinone 5 0.67

- 1.12 25.54

- 42.69

Paraquat 22 0.25

- 0.5 3.98

- 7.96 Tebuthiuron 7 0.4 16.00

Source: ( Texas Cooperative Extension )

1 Weed Science Society of America mode of action category Note: Alternative low cost herbicide options to dicamba are shaded. lb ae /A = pounds acid equivalent per acre lb ai/A = pounds active ingredient per acre
Potential Impacts to Pasture and Rangeland from Increased Weed Resistance Although, according to BASF market estimates, pasture and rangeland represents the fourth largest agricultural use of dicamba, most pasture and rangeland is not treated with herbicid es. Non

- chemical options are most often used, and there are similarly priced chemical alternatives to dicamba ( Table 22 ). Healthy stands of forage pastures tend to exclude weeds, and good 160management includes mechanical, cultural, biological as well as chemical controls, so a variety of weed control methods are typically used, that may or may not use herbicides ( Green et al.

, 2006 )

. The cumulative impact s on pasture and rangeland would be the dimi nished utility of dicamba if used, because of selection for dicamba

- resistant weeds in crops rotated with MON 87708 soybean and MON 88701 cotton

. APHIS concludes that even if dicamba

- resistant weeds became more prevalent, the cumulative impacts to pasture and rangeland weed management are expected to be small under all the Alternatives.

Small Grains (Wheat, Barley, Oats)

Spring wheat applications of dicamba have declined from 12% to 5% of acres from 2006 to 2012, respectively ( USDA

- NASS, 2014d ) , in NASS’s seven program states 16 ( USDA

- NASS, 2005a ) . Applications to winter wheat 17 increased from 8% to 15% in that same period in USDA

NASS’ 15 program states. Conditions are usually very f avorable to winter wheat growth in the fall, and the crop out

- competes many weeds. About 96% of spring wheat was treated with herbicide, while about 57% of winter wheat was treated. Wheat may be rotated with corn or soybeans. In some areas such as Indiana, Illinois, Kentucky, Missouri, and Arkansas, winter wheat is often planted with the intent to double crop with soybeans the same season. Winter wheat is harvested (usually in June) and soybeans are planted in no

- till wheat stubble when there are favorable moisture conditions ( North Dakota State University ; Moechnig and Wrage, 2012 )

. In 2003 and 2011, 5% of barley acres received applications of dicamba ( USD A

- NASS, 2014d ) and 88% of barley acres were treated with herbicides in NASS’s program states

. 18 Market reports indicate that the use of dicamba in barley has been declining since 2008 ( Table 23 ) ( Monsanto, 2014a )

.
Table 23

. Changes in Dicamba Applicati on to Crops 2006

- 2012. Year 2006 2008 2010 2012 Crop Dicamba

- Treated Acres Corn 8,080,614 8,113,801 6,459,632 11,919,844 Fallow 2,144,260 3,017,717 4,274,678 6,665,140 Wheat, Winter 2,348,897 3,742,572 2,577,953 3,622,102 Pastureland 1,454,649 1,218,179 2,604,944 3,221,382 Wheat, Spring 1,569,079 1,351,665 1,512,894 1,804,742 Sorghum (Milo) 550,795 1,114,162 955,997 1,683,584 Cotton 590,953 589,919 854,649 1,455,309 Soybeans 279,275 529,638 648,509 1,055,926 Sugarcane 198,042 177,089 225,295 190,317 Barley 108,393 211,067 101,158 47,144 Source: BASF market data. In Monsanto NOI supplement ( Monsanto, 2014a )

Alternative Herbicides and Management Options

16 A rkansas , M innesota , M ontana , N orth D akota , O regon , S outh D akota , W ashington. 17 Program States 2012 : C O, ID, IL, KS, MI, MO, MT, NE, OH, OK, OR, SD, TX and WA ( USDA

- NASS, 2013b ) 18 Program States 2011: AZ, CA, CO, ID, MN, MT, ND, OR, PA, V A , WA, WI, and WY ( USDA

- NASS, 2012 )

.

161A wide range of herbicide products are currently registered for small grains that could replace dicamba . Use of pre

- plant or pre

- emergence herbicides occurs on a small portion of grain acreage usually with 1

- 2 post

- emergence applications. Post

- emergence graminicides are often used to control grass weeds such as wild oats and foxtail. Many different herbicid es are available for post

- emergence broadleaf weed control. Dominant modes of action in small grains are auxins (WSSA Group 4) and ALS inhibitors (WSSA Group 2). While one auxinic class herbicide, 2,4

- D is a widely used herbicide for these crops, it does n ot provide acceptable control of some key broadleaf weeds such as kochia and wild buckwheat ( Zollinger et al. , 2006 ) . Glyphosate and 2,4

- D treatments are often combined with one of the herbicides listed in Table 24 ( Zollinger et al.

, 2006 )

.
A number of alternative herbicides and estimated costs are listed in Table 24 . Chlorsulfuron, an ALS inhibitor for example, can provide control similar to dicamba at low cos t ( Zollinger et al.

, 2006 ; Zollinger, 2014 ) . However, resistance to ALS inhibitors is widespread. The cost of some other products is similar, such as pyrosulfotole and bromoxynil or premixes of both, which provide high levels of control of some key broadleaf we eds, such as kochia and also wild buckwheat ( Zollinger et al.

, 2006 )

.
Some non

- chemical control methods can also substitute for dicamba or enhance other control measures. Weeds such as common lambsquarters and common ragweed often germinate early in the spring. Tillage just before spring planting can eliminate the major flush of these early emerging weeds. A 2009 USDA report on custom tillage rates estimated the cost of harrowing at $7.30

- 8.40 per acre in Kansas ( USDA

- NASS, 2009f ) . Crop rotation is a recommended weed management practice, providing a tangible, recognized level of control where practiced, and this cultural means of control is often an important part of an integrated weed control plan.

Table 24 . Post

- emergence Broadleaf Herbicides Currently Approved for Use in Wheat, Barley, Oats, and Rye.

Herbicide (common name) MOA 1 Crops 2 Rate (lb. acid equivalent or active ingredient /A) Cost $/

Acre Comments

2,4

- D amine 4 WW, SW, B, O, R 0.25

- 0.5 1.15

- 2.30

MCPA 4 WW, SW, B, O, R 0.25

- 0.5 1.30

- 3.20 Similar in spectrum to 2,4

- D

Bromoxynil 6 WW, SW, B, O, R 0.25

- 0.5 8.80

- 19.05

Carfentrazone 14 WW, SW, B, O, R 0.008

- 0.031 4.00

- 15.10

Chlorsulfuron 2 WW, SW, B, O 0.008

- 0.015 3.60

- 7.05

Clopyralid 4 WW, SW, B, O 0.09

- 0.12 16.80

- 22.15

Dicamba 4 WW, SW, B, O, R 0.06

- 0.12 2.30

- 5.25

162Herbicide (common name) MOA 1 Crops 2 Rate (lb. acid equivalent or active ingredient /A) Cost $/

Acre Comments

Pyrasulfotole 27 WW, SW, B, O 0.028

- 0.038 8.50

- 11.55 Available only in premix w/ bromoxynil

Florasulam 2 WW, SW, B, O 0.004 7.20 Available only in premix w/ MCPA

Fluroxypyr 4 WW, SW, B, O 0.11

- 0.14 10.60

- 14.15

Thifensulfuron 2 WW, SW, B, O 0.014

- 0.019 15.95

- 31.85

Tribenuron 2 WW, SW, B 0.008

- 0.16 4.70

- 9.35

Metsulfuron 2 WW, SW, B 0.004 1.50

Prosulfuron 2 WW, SW, B, O 0.009

- 0.018 3.65

- 7.25

Pyraflufen 14 WW, SW, B, O, R 0.0008

- 0.0016 1.65

- 3.30 Primarily pre

- plant but can be applied POST

Triasulfuron 2 WW, SW 0.013

- 0.026 3.00

- 6.05

Imazamox 2 WW, SW 0.031

- 0.047 16.25

- 24.40 Clearfield varieties only

Alternative low cost herbicide options to dicamba are shaded. 1. WSSA Mode of Action 2. Crops labelled for use Abbreviations: B=barley; O=oats; SW=spring wheat; R=rye; WW=winter wheat Source : ( DAS, 2013b )

A final note o n potential future impact of dicamba resistant crops is that Monsanto has been field testing dicamba

- and glufosinate

- resistant wheat, and dicamba

- resistant canola as well

. These products are not likely to have any near term availability, and any predictions about their status would be highly speculative at the present time.

Potential Impacts of Dicamba

- Resistance on Small Grains Winter wheat, spring wheat, barley, and oat growers often do not use herbicides. When needed

, dicamba provides an inexpensive and effective weed management tool especially for some weeds not controlled by some other herbicides, such as wild buckwheat. As noted in the discussion that follows, there are several areas where these crops are rotated w ith either cotton or soybean or grown in proximity. If dicamba

- resistant weeds were to develop in cotton and soybean fields, it is likely that they could eventually be found in wheat and small grain crops on rotated with MON 87708 soybean and MON 88701 cotton acreage or on neighboring farms. MCPA and 2,4

- D are low priced, common alternatives, but if applied to emerged wheat can cause damage, and as noted, may not control key weeds ( Johnson and Nice, 2009 ) . Other low cost herbicides, such as the ALS inhi bitor chlorsulfuron, may not be as effective because of
163widespread resistance to ALS inhibitors. Pyraflufen is a low

- cost PPO inhibitor that is usually used pre

- plant. It cannot be used post

- emergent (unlike dicamba) on small grains except wheat, and it ha s more restrictions than dicamba when used on wheat. Most likely, APHIS concludes that alternative chemical control options would be more expensive and that some chemical alternatives are less flex ible

. APHIS concludes some potential c umulative impact s to wheat and small grain growers if dicamba

- resistant weeds become more prevalent , but alternatives to control weeds in small grains may still be effective for many growers

.
Fallow and Burndown Uses

For many c rops, including soybean, dicamba has been used in mixes with other herbicides such as glyphosate, 2,4

- D, glufosinate, or paraquat in the spring or fall as a “burndown” herbicide prior to planting, especially in connection with a glyphosate

- or glufosinate

- resistant crop ( PennState

- Extension, 2013a ) . This timing may extend anywhere from 0

- 30 days prior to planting, depending on the crop, geography, and product used. It is used to improve control of winter annuals, perennials, and early

- emerging, summer annual weeds. Examples of weeds controlled include shepard’s purse, marestail, dandelion, common lambsquarters, and giant ragweed. When use d as a burndown, its control of broad leaf weeds is excellent, but control of Palmer amaranth may not be as effective as that achieved by flumioxazin ( Edwards et al. , 2012 )

. More recent recommendations include mixtures of flumioxazin (residual) with diuron or with paraquat (foliar active herbicides) ( University of Georgia CAES Extension, 2014 )

. Often burndown herbicides are a critical part of an overall weed control program since these remove weeds that will be competing with the crop as it emerges. Burndown herb icide applications are almost obligatory for no

- till crop production systems where tillage is not desired. Use of no

- till crop culture is common in corn, soybeans, cotton, and wheat. Both soybeans and cotton are largely planted as GR varieties and glyphosa te is an important herbicide use d in post

emergent weed control. For wheat managed with herbicides, burndown applications are popular but there are post

- emergent options including bromoxynil and pyrasulfotole, provided these are appli ed in early stages of wheat growth ( Johnson and Nice, 2009 ; Zollinger, 2014 )

. Fallowing (land left plowed or disced lightly but not sown to crops) is used in arid areas of the plains and the West as a means to store soil moisture for a following crop. Fallow may encompass the summer season but is usually applied to a longer period of time (often 4

- 12 months). Weed control on fallowed acres is critical for reducing moisture loss. While tillage is an alt ernative to herbicidal control, it is usually less desirable because it increases erosion, adds costs of fuel and labor, and enhances soil moisture loss ( Simmons and Nafziger, 2012 ; Fernandez

- Cornejo et al. , 2013 )

.
Alternatives to Dicamba

Herbicides effective for burndown and foliar activity on broadleaf weeds are listed in Table 25

. Depending on the crop to be planted and the target wee d species, these products can offer an alternative to dicamba, with some at greater cost. In several cases, these herbicides offer some advantages over dicamba such as longer residual control.

164Some non

- chemical control methods can also substitute for dicamba or enhance other control measures. Tillage can substitute for herbicide applications to remove weeds before planting except where no

- till conditions are desired ( Croissant et al. , 2008 ) . Using a price for diesel of $3.50 per gallon, the fuel cost for tillage ranges from $19

- 25/acre using the USDA energy estimator for tillage in Iowa, North Carolina, and Arkansas ( USDA

- NRCS, 20 13b )

.
Table 25 . Herbicides Available for Use on Fallow and for Burndown

.

Herbicide (common

name) MOA 1 Crops 2 Rate (lb acid equivalent or active ingredient/A) Cost $/

Acre Comments

2,4

- D amine 4 C, SB, CT, SG 0.25

- 0.5 1.15

- 2.30

Atrazine 5 C 1.0 3.20

Isoxaflutole 6 C 0.05

- 0.09 14.90

- 29.80

Chlorimuron 14 SB 0.033 8.10 Usually in combination with metribuzin ($18/ Acre )

Metribuzin 5 C, SB 0.5

- 0.75 5.60

- 8.50 Often at lower rates in combination w/ other herbicides

Dicamba 4 C, SB, CT,SG 0.25 5.25

Mesotrione 28 C 0.18

- 0.24 32.00

- 41.00

Glyphosate 9 C, SB, CT, SG 1.0

- 1.5 4.00

- 6.00

Flumioxazin 14 CT, SB 0.05

- 0.1 9.00

- 18.00

Sulfentrazone 14 SB 0.14

- 0.375 23.60

- 63.00 Obtained at lower cost in premixes

Saflufenacil 14 C, SB, SG 0 .02 5.45

Paraquat 22 C, SB, CT, SG 0.5

- 1.0 9.00

- 18.00

Glufosinate 10 C, CT, SB 0.53

- 0.66 13.60

- 16.85

Iodosulfuron 2 C, SB 0.0019 7.20 Fall only for soybeans, up to 30 days before corn

1 WSSA mode of action category
2 C=corn, SB=soybean, CT=cotton, SG=small grain Alternative low cost herbicide options to dicamba are shaded. Source: ( DAS, 2013b )

165Potential Impacts of Dicamba Resistance on Fallow and Burndown Applications

Under the Preferred Alternativ e, d evelopment of weed resistance to dicamba would have limited impact on fallow and burndown applications because numerous herbicides are available, and mixes of glyphosate with 2,4

- D or atrazine complements glyphosate effectiveness ( University of Nebraska Extension, 2014 ) . Important or resistant weeds may be controlled by various herbicides or combinations, and as the University of Nebraska Extension presents for corn, 31 combinations or single herbicides are recommended as broadleaf burndowns for corn alone; soil

- active

r esiduals (such as flumioxazin) also may be mixed into the burndown application ( University of Nebraska Extension, 2014 ) . Soybean burndown in Nebraska has about 20 choices, of w hich five are glyphosate or a tank mixture with glyphosate. Certain weeds (e.g., lambsquarters) have always been tolerant of glyphosate and are more effectively controlled by other herbicides. Several herbicides priced similar to dicamba are available for general weed management. For specific weed applications, many recommended herbicides are more costly. However, when weed pressure of certain species has become high, growers will necessarily choose these to provide efficacious control. Each grower selectio n takes into account crop selectivity (plant back limits), problem weeds, application requirements and cost. APHIS concludes that l oss of dicamba as an effective herbicide may increase management costs in some cases. Crops that may be adversely impacted in clude cotton, soybean, corn, and possibly wheat.

Corn

Dicamba is used on about 12% of U

. S

. corn and unavailability of dicamba treatment options because of dicamba resistant weeds in corn could require that growers choose other herbicides, if available. Si nce soybean is followed by corn 64% of the time, the possibility of dicamba

resistant weeds arising in corn may be a relevant issue

. A large number of herbicide alternatives are available for weed control in corn. Iowa State ( 2014b ) for a herbicide effective ness rating chart lists 10 PRE herbicides and 23 POST choices

. For burndown options in no

- till corn, Penn State Extension ( PennState

- Extension, 2013b ) lists14 herbicides u sed alone or in combinations with other herbicides

. Various Amaranthus species can be problem weeds because of multiple herbicide resistance, and PPO

- , HPPD

- , ALS

- and glyphosate

- resistant weeds are known in Iowa. ( Owen, 2014b ) For preplant use, if these resistant wee ds are not present, seven of ten of the Iowa

- listed herbicides give good to excellent control

. For POST use, 17 of the 23 herbicides have good to excellent effectiveness.

Potential Impacts of Dicamba

- resistant Weeds on Corn

While the potential for dicamba

- resistant weeds arising in soybean and then found in corn following typical rotations is a possible consequence of MON 87708 soybean production, sufficiently broad numbers of choices of alternative corn herbicides are available

. Some of the Ameranthus with resistance to various herbicide classes may be more likely controllable with a new option for POST dicamba treatment in soybean

. APHIS concludes t hat dicamba may not be usable in field corn, in which at present it is only modestly de ployed, but that the loss of dicamba utility may be outweighed by the benefits of having new control measures for resistant weeds in soybean.

166Sorghum

Sorghum is most commonly rotated with wheat, corn, and soybean ( Bean and Trostle, 2013 ) . In Texas, sorghum is also rotated with cotton, and sometimes peanuts.

A number of herbicide products are currently labeled for sorghum. Herbicide management for sorghum can include burndown, pre

- emergence, and post

- emergence herbicide applications. Pre

emergence applications typically use atrazine in combination with an acetamide such as metolachlor. Post

- emergence herbicides such as 2,4

- D, atrazine, dicamba, bentazon, and bromoxyni l are used to control broadleaf weeds that escape the pre

- emergence treatment. These herbicides may be combined in premixes or tank mixes to broaden the weed control spectrum. Common combinations include 2,4

- D with atrazine, dicamba with atrazine, and brom oxynil with atrazine ( Kansas State University Agricultural Experiment Station and Cooperative Extension Service, 2014 ) . In

- season row cultivation has been used in the past to control weeds, but it is less

c ommonly used today because it requires costly fuel and labor expenses ( Kansas State University Cooperative Extension, 1998 )

. Alternative Herbicides and Management Options Several possible alternative herbicides for weed control in sorghum and their estimated costs are summarized in Table 26 . Atrazine, pendimethalin, saflufenacil and 2,4

- D/atrazine mixtures are effective on a variety of broadleaf weeds and are similar in cost ( Moechnig et al. , 2010 )

.
Some non

- chemical control methods can also substitute for dicamba or enhance other control measures. Weeds such as common lambsqu arters and common ragweed often germinate early in the spring. Tillage just before planting can eliminate these early emerging weeds. A 2009 USDA report on custom tillage rates estimated the cost of harrowing at $7.30

- 8.40 per acre in Kansas ( USDA

- NASS, 2009f ) . In season row cultivation provides another, non

- chemical alternative and costs between $7.00 and $8.00 per acre ( University of Nebraska, 2012 )

.
Table 26 . Post

- emergence Broadleaf Herbicides Currently Available for Use on Sorghum.

H erbicide (common

name) MOA 1 Rate (lb acid equivalent or active ingredient/A) Cost $/

Acre Comments

2,4

- D amine 4 0.25

- 0.5 1.15

- 2.30

Atrazine 5 1.0 3.20
Bromoxynil 6 0.25

- 0.5 8.80

- 19.05

Carfentrazone 14 0.008 4.00

Bentazon 6 0.5

- 1.0 12.60

- 25.20 Not a recommended tank mix on label but not prohibited

. Dicamba 4 0.25 5.25

167H erbicide (common

name) MOA 1 Rate (lb acid equivalent or active ingredient/A) Cost $/

Acre Comments

Prosulfuron 2 0.009

- 0.018 3.30

- 6.60

Halosulfuron 2 0.03 12.50

*Alternative low cost herbicides to dicamba are shaded.
1 WSSA mode of action category

. Source: ( DAS, 2013b )
Potential Impacts of Dicamba

- Resistant Weeds on Sorghum

If dicamba

- resistant weeds were to become a problem, sorghum growers would likely have additional choices of herbicides. 2,4

- D may be applied with oth er herbicides such as carfentrazone (a PPO inhibitor) for more rapid activity to improve control. Weeds effectively controlled with 2,4

- D, include ragweed, pigweed, and lambsquarters, but atrazine

- and ALS

resistant biotypes may exist for these weeds. The refore, APHIS concludes that if dicamba

resistant weeds become a problem, weed management costs for sorghum would not likely increase, since alternatives exist, but alternatives may be somewhat limited.

Rice

Rotating rice with corn or soybean is limited to the Mississippi River Valley and Texas ( Louisiana State University Research and Extension, 2013 ; University of Arkansas, 2013 ) . In 2008, rice followed soybean in 1.4% of overall planted soybean acreage ( Table 19 ). As indicated in Table 21 , for Region F, ri ce production rises to 11% of acres of the region. Although rice is not a registered usage of dicamba, another auxinic herbicide, 2,4

- D, was used on 13% of planted fields ( USDA

- NASS, 2014d ) . However, there is no information about cros s

- resistance of weeds to dicamba in rice; therefore, this is not further discuss ed within Cumulative Impacts.

Non

- MON 88701 Cotton

Cotton is rotated with other crops less than one

- half the time ( Table 20 ). In Texas and the High Plains, for example, few other crops are productive in the conditions of low rainfall and high heat favorable for cotton cultivation. In drought years, dryland cotton may be abandoned on a large percentage of these acres ( Smith, 2013 ) . Mostly in the mid

- South, rotations are more common. There, cotton may be rotated with soybeans or corn ( University of Georgia CAES Extension, 2014 ) . Most dicamba applications are made prior to planting, with some made in the late fall ( Monsanto, 2014a )

. If growers were to plant cotton varieties other than MON 88701 and use di camba as an herbicide after having produc ed a MON 88701 cotton crop in the previous season, they would not be making an appropriate choice, since rotation of herbicides is an important principle of weed management. Grower decisions to repeatedly use dicamb a

- based weed control will determine whether dicamba

- resistant weeds become an issue or not.

168Weed Management Programs and Options

Cotton is an annual crop that is usually planted in wide rows (38

- 40 inches apart). Use of no

- till is common in cotton and herbicides are an important means of weed control. Currently, most cotton varieties in the U.S. are glyphosate

- resistant, so glyphosate is the primary herbicide use d. A common cotton production practice is application of a pre

- plant or pre

- emergence, soil

residual herbicide followed by 1

- 2 post

- emergence treatments usually with glyphosate. The soil

residual herbicides include a range of modes of action. Although a large portion of cotton acreage was once tr eated only with post

- emergence applications of glyphosate or with a glyphosate burndown ( Givens et al. , 2009 ) , this practice is decl ining because GR weeds are now widely prevalent in cotton fields. Glufosinate

- resistant cotton varieties are increasingly being used (e.g., in a five state region of the mid

- South , these crops accounted for 33% of all professionally surveyed cotton acres), so post

- emergent glufosinate applications are replacing glyphosate for some growers ( Riar et al. , 2013 )

.
Recent recommendations for cotton production in those areas experiencing GR weeds in glyphosate

- resistant crops would include a burndown with multiple herbicides, a pre

- emergent treatment with residual herbicides, post

- emergent herbicide treatments of glyphosate and a residual broadleaf herbicide or graminicide, and perhaps layby application to keep weeds
cont rolled until canopy closure ( Marshall, 2012 ; Bond et al. , 2014 ) . Because cotton is naturally sensitive to dicamba, 2,4

- D and other auxinic herbicides, the current use of dicamba for this crop is limited to pre

- plant burndown or fall application. 2,4

- D is sometimes added to burndown applications to improve control of w inter annuals, perennials, and early emerging summer annual weeds and was used on about 7% of cotton acres in a 2010 survey ( USDA

- NASS, 2014d ) and dicamba at 8 percent during that same season. Estimates for 2011 suggest that on cotton , 2,4

- D was used on 17 percent of acres and dicamba on 10 percent ( Monsanto, 2013a ) . Burndown occurs 0 to 30 days prior to planting depending on crop, geography, and product used. Burndown herbicide applications are almost obligatory for no

- till crop production systems ( Hartzler, 2013 )

. Dicamba and 2,4

- D are typically used in combination with other broad

- spectrum herbicides, such as glyphosa te, glufosinate or paraquat

. Herbicides with utility in burndown and major foliar activity on broadleaf weeds are listed in Table 25

. These herbicides are alternative s to dicamba.

Some non

- chemical control methods can also substitute for dicamba or enhance other control measures. Tillage can be a substitute for herbicide applications to remove weeds before planting except where no

- till conditions are desired. USDA rep orts on custom tillage rates estimated the cost of most pre

- plant tillage at $13

- 15 per acre ( University of Nebraska, 2012 )

.

P otential Impacts to Cotton Growers from Dicamba

- Resistant Weeds

According to BASF proprietary grower surveys, dicamba use in cotton is limited to pre

- plant burndown since cotton is sensitive to the herbicide. However, because of the widespread adoption of no

- till in cotton production combined with the prevalence of GR weeds in cotton fields, dicamba is one of several herbicides for burndown applications in cotton and these could include 2,4

- D, paraquat, and flumioxazin. Consequently, if dicamba

- resistant w eeds become more prevalent in cotton varieties other than MON 88701

, PRE weed management costs will likely be similar or possibly slightly increase d for some cotton producers. As noted earlier, a variety of post

- emergent or lay

- by herbicides can be used fo r cotton weed control, and dicamba

169is not used for such post emergent uses

. Under the Preferred Alternative, the nonregulated status of MON 87708 soybean and MON 88701 cotton would have inconsequential effects on the cultivation of other varieties of soybe ans and cotton if dicamba resistant weeds were to increase.

Sugarcane

While a large proportion of sugarcane is treated annually with dicamba, the crop may be harvested in three seasons including the one following planting, and then receive a fallow year,

s o in the four year cycle, rotated crops are not an issue in typical sugarcane production ( LSU

Extension, 2014 )

. Weed Management Choices and Development of Resistant Weeds

MON 87708 soybean and MON 88701 cotton are expected to be attractive to those cotton and soybean growers who have or will have difficulty with weed control caused by GR weeds. In the event that MON 87708 soybean and MON 88701 cotton become widely used, and dicamba

resistant weeds become more w idespread, there are three types of growers that are most likely to be impacted.

1) The first type is the soybean and cotton growers who almost exclusively have adopted GR crops and are already confronted with weed control problems related to GR weeds. Until now, these growers have relied more on glyphosate than dicamba, but it can be assumed they will adopt MON 87708 soybean and MON 88701 cotton and develop a reliance on dicamba as a solution to the GR weed problem. The ease and effectiveness of dicamba will tend to encourage growers to use a less diversified approach to weed control, but because dicamba only controls broadleaf weeds, this will require growers to pursue a more diversified weed management strategy. Therefore, they will have an incentive to dive rsify before they are forced to do so when dicamba

- resistant weeds
emerge.
2) A second type of grower includes those that have responded to the recommendations of : state extension experts (e.g., following advice received during seminars attended by growers [e .g., B. Young, Purdue University, 2014 Commodity Classic ( Young, 2014 ) ]; state agronomy publications ( Iowa State Extension, 2014 ) ; national grower associations such as the American Soybean Association ( ASA, 2011 ) , and representatives of seed technology companies ) . T hese specialists continue to alert growers to the need for new models for weed control that will require integrated weed resistance management and an understanding of target weeds sensitivity to herbicide sites of action.

Reliance on a single herbicide, s uch as glyphosate for weed control, is no longer a realistic option. Since dicamba is only effective on broadleaf weeds, it does not provide the single herbicide option to achieve effective weed control.

Failure to consider and vigorously respond to the ex istence of resistant weed populations will result in a loss of yield and sometimes loss of an entire crop. Consequently, these growers will use best management practices to both avoid weed resistance and control resistant weeds already present or that are believed to be present. The potential for enhanced weed control offered by this and other new HR crops will be fully embraced. 170Growers who do will be actively delaying the onset of weed resistance within their own fields. Because these growers will be foll owing best management practices, their response to weed control will be more integrated with greater precautions taken to avert new weed resistance.

These growers will be likely to deter new weed development using MON 87708 soybean and MON 88701 cotton , an d use other HR crops such as 2,4

- D

- resistant crops or MGI

resistant (mesotrione, glufosinate, isoxaflutole) soybean. Because new herbicide b est

m anagement practices exemplify initiatives of grower s , the y will likely find that availability of MON 87708 soyb ean and MON 88701 cotton will provide weed management benefits for multiple years.

3) The third type of growers is those who already rely on dicamba for weed control in non

GR crops; growers of sorghum, corn or certain small grains are examples. These grower s are more reliant on dicamba than glyphosate for weed control and may not currently be faced with the same degree of weed control problems as the first group. The development of dicamba

- resistant weeds resulting from reliance on either dicamba in current or new herbicide formulations for MON 87708 soybean and MON 88701 cotton may render dicamba less effective to those who were already using it on these other crops. This could necessitate adopting more costly and less environmentally beneficial weed managem ent practices than are currently in use

. No cumulative impact s are expected on organic growers because these growers do not use synthetic herbicides, such as dicamba, for weed control, therefore weed resistance to dicamba would not impact the practices they employ for weed control (including tillage, cultivation, hand

- weeding, cover crop s). USDA acknowledges that the overall increase in herbicide resistant weeds negatively impacts our agricultural system as a whole, given the overall number of weeds, weed pollen, and weed seed may be increased and this may have an impact on weed control for all production systems

. The potential for undesired volatilization or drift of applied dicamba onto organic crops is as o f high possibility, but no less than those onto conventional soybean or
cotton

. APHIS concludes that because EPA will mandate use of the low

- volatility formulations of dicamba, and that organic crops likewise are not at any higher risk than conventional cr ops, impacts on organic crops may occur, but at reduced incidence because the formulation of dicamba being delivered onto the MON 87708 soybean and MON 88701 cotton crop is less volatile than dicamba being used on other crops; the low volatility formulatio n may also be more frequently used in place of higher volatility and older dicamba formulations.

5.6.4 Health and Safety for Livestock and Humans

No cumulative impact s were identified on human health or livestock f or any of the Alternatives. The EPA considers the direct and indirect impacts from herbicide use on human health and non

target organisms as part of their regulatory decision. T hose impacts are outside the scope of this EIS.

1715.6.5 Biological Resources

Animal Communities As described in the No Action Alternative, agricultural practices can affect wildlife in and around agricultural fields. Wildlife commonly found in each region is described in the Affected Environment, Chapter 3. As discussed in Chapter 4, MON 88701 cotton and MON 87708 soybean are not expected to directly or indirectly impact wildlife differently from the cotton and soybean varieties that are currently available under the No Action Alternative. While direct impacts f rom the changes in herbicide use associated with MON 87708 soybean and MON 88701 cotton could potentially affect certain wildlife, those impacts are outside the scope of this EIS.

The EPA considers impacts on wildlife as part of its e valuation of the new label. Dicamba has an extensive history of safe use. It has been thoroughly reviewed and reregistered by all major regulatory agencies in the world within the last ten years. The EPA affirmed that dicamba posed no unreasonable adverse effect s on the environment when used as directed. Therefore, cumulative impact s on animal resources are not expected to differ from the No Action and Action Alternatives. Impacts of herbicides on nontarget organisms are assessed by the EPA. T hose impacts are outside the scope of this EIS.

Plant Communities Summary: Populations of waterhemp with multiple herbicide resistance have been detected in some states in the Midwest. While not widespread, they are a concern because they are only susceptible to some PPO inhibitors, PSII inhibitors and dicamba. In some southern states, pigweeds in soybean are only susceptible to PPO inhibitors and to dicamba. When dicamba can be applied coordinately with one of the few herbicides to which these weeds are susceptible, it reduces the chance that resistance to these herbicides will develop, since the use of overlapping sites of action is an important strategy advanced by weed scientists for suppressing weed resi stance. APHIS concurs that dicamba use in MON 87708 soybean and MON 88701 cotton can potentially extend the longevity of unique herbicides that are needed for the control of specific highly resistant weeds.

An important consideration for the potential of weeds to develop resistance is knowing whether growers will select appropriate strategies for management practices

. These practices must be actively selected to avert future weed resistance. Best management practices include employing a di versity of herbicides, rotation of herbicide choices, crop rotation , and others. APHIS anticipates that the EPA will implement appropriate measures with respect to weed resistance management associated with the registration of dicamba on MON 87708 soybean and MON 88701 cotton . State extension agents, seed providers, herbicide suppliers and other professionals, will also provide advice and training to growers, who are becoming more likely to perceive the needs for sustainable weed manag ement and execute best management practices

. APHIS concludes that the overall success in averting weed resistance will depend on these management practice choices made by individual growers.

172Clearly the grower’s responses to recommended management practice s prescribed by extension personnel and weed scientists will determine the potential impacts and benefits of associated with adoption of MON 87708 soybean and MON 88701 cotton

. Reduced usefulness of herbicides for cotton and soybean crops must be balanced with the potential benefits deriving from applying intensive risk

- averting practices . Because growers have become more receptive to understanding the causes of herbicide resistance in weeds

, they have also become more responsive to these issues. Under the Preferred Alternative, as under the No Action Alternative, APHIS concludes that more growers are likely to take actions (e.g., best management practices to reduce development of resistance) that reduce the chances for weed resistance, especially as more recent studies have shown that there is only modest additional short

- term cost for applying these actions, with no change in profitability

. Large long

- term costs for not applying these actions are also a likely consequence, which weed experts will continue to emphasize to growers.

Monsanto estimates of herbicide use under the likeliest adoption scenario are listed in Table 4

- 9 of Appendix 4 for soybean at 40% and 100% adop tion, and 4

- 12 for cotton at 50% adoption. An increase in herbicide use is expected under all four Alternatives. Dicamba use on crops may increase from 3.8 million pounds in 2011 under the No Action Alternative to 29.5 million pounds at full adoption (Tabl e 8

- 1 in Appendix 8 and Appendix 4) ( Monsanto, 2013a ) . Under Alternative 2, the increase may reach 25.7 million pounds at the height of adoption, assumed to be 50% of cotton acres and 35% of soybean acres, but these rates are difficult to predict.

T he presently increasing use of dicamba under the No Action Alternative ( see Table 23 and Appendix A in the Monsanto ER ( Mo nsanto, 2013a ) ) and the potential for increasing use following the EPA approval of new uses of dicamba, may be expected to increase the selection pressure for dicamba

- resistant weeds. However, selection pressure is influenced by factors other than the volume of herbicide applied. The selection pressure is strongly related to the long

- term repeated use of one or a limited number of herbicides or modes of action ( Durgan and Gunsolus, 2003 ; Duke, 2005 ) . It is also a function of the diversity of management practices employed. The greater the diversity of management practices, the smaller the selection pressure for resistant weeds.

Without diversified weed control practices, a ll management techniques, including the use of herbicides, hand weeding, mowing, et c., exert pressure to select weeds with resistance to that management practice . For hand weeding, weed forms are selected that resemble the crop. For example, spurred anoda and nightshade resemble young cotton, so these weeds are often overlooked during hand

- weeding ( University of California Davis , 1996 ; Coble, 2012 ) . Mowing selects plants that flower rapidly and grow low to the ground ( Radosevich et al. , 2007 ) . Mowing alters the stature of some weeds. Repeated mowing can change the appearance of a weed from a single

- stemmed, tall, upright form to a plant with multiple shoots that are relatively prostrate ( Radosevich et al. , 2007 )

. Repeated use of h erbicides with diversification select s for resistant plants that are no longer sensitive to its mode of action ( Owen, 2008 )

. The increased selection pressure res ulting from the wide

- spread use of glyphosate on GR crops, the subsequent reductions in the use of other herbicides, and changes in weed management practices (such as the reduction in tillage and decreased use of crop rotation ), has r esulted in both weed population shifts and increasing glyphosate resistance among some weed populations

173( Owen, 2008 ; Duke and Powles, 2009 ) . GR crops themselves do not influence weeds any more than non

- transgenic crops. It is the weed control tactics chosen by growers that create selection pressure that gradually shifts these weed communities and may result in the evoluti on of HR weeds ( Owen, 2008 ) . Impacts of herbicide treatment on nontarget organisms are assessed by the EPA. T hose impacts are outside the scope of this EIS.

Control of volun teers arising after harvest and of persisting cotton plants is often accomplished by use of 2,4

- D applications, which growers may combine with mechanical destruction ( Robertson et al. , 2002 )

. As noted earlier, the cotton destruction for overwintering plants is mandated by Boll Weevil Control programs. Assuming 2,4

- D resistant cotton is available to growers, other herbicide regimes will need to be selected, and DowAgrosciences has indicated th at it is currently accomplishing trials to find suitable herbicide replacement for control of this cotton variety (DowAgrosciences, personal communication, 2014)

. A similar experimental approach to manage post

- harvest cotton may be needed for MON 88701 cot ton

. Although the Dow Agrosciences patent for 2,4

- D resistant crops does not indicate that Enlist corn has tolerance to dicamba, a non

- commercial level of 2,4

- D resistance could potentially be displayed by dicamba resistant cotton, since cross resistance i n weeds to both herbicides has been noted ( Monsanto, 2012a ; 2012b )

. Dicamba soybean appears to have only slight resistance to 2,4

- D compared to a nontransgenic control soybean ( Feng and Brinker, 2010 ) , with no infor mation available about 2,4

- D resistance in dicamba

- resistant cotton ( Brinker et al. , 2012 ) . APHIS concludes that potential for cross resistance of HR cotton has not been shown, and doubtless new herbicide procedures for eliminating overwintering potential in these cotton varieties will need to be established.

Overal l USDA Responsibility for Averting Resistant Weed Development When assessing issues of herbicide

- resistan t weeds , especially those with existing resistance

, but also th ose that may develop resistance to dicamba from commercialization of MON 87708 soybean and MON 88701 cotton , there are at least two perspectives that these assessments must take in to account. The first is that growers are presently in need of short

- term solutions for GR weeds, which are certainly extensive and probably increasing. The second is that growers need to embrace the complexity of weed control with not just herbicides and HR crops, but with all the possible cultural, mechanical, chemical and preventative management practices . The first perspective is intimately tied to short

- term ap proaches to resistant weed control and weed control in general, but the second is one that is longer term, requiring more experimental effort, and experience with control of problem weeds. This EIS deals necessarily with the first perspective, since that c an be addressed with herbicide resistan t crop technology provided by seed companies and pesti cide providers, including making MON 87708 soybean and MON 88701 cotton commercially available . Unquestionably, there is a grower

- and professionally

- expressed nee d for additional herbicide technologies for responding to widespread issues of existing herbicide resistance

. From the second perspective, weed control should optimally be done using integrated weed management practices, without over

- reliance on herbicide s. Many growers are already using multiple technologies ( Prince et al. , 2012b ; Sosnoskie and Culpepper, 2014 )

, and as noted by a Georgia agronomist and profes so r (Public Comment APHIS

- 2013

- 0043

- 3209 )

,

174“It is also critical to highlight, at least in Georgia, no weed management program relies exclusively on herbicides. The University of Georgia Weed Science Extensio n Team stresses to growers at more than 50 meetings each year that herbicides are only one part of the weed management program. Sustainability is only possible with the adoption and implementation of diverse management programs and Georgia growers have acc epted this message as fact (Sosnoskie and Culpepper 2014). Growers are using programs that are complex and diverse integrating herbicides, hand weeding, and tillage or cover
crop s. Dicamba will not change this approach but would simply be an additional tool to add into these management systems.”

A s more challenging problem weeds arise (with resistance to both herbicides and other techniques) there is need to further develop these practices. Agencies within USDA deal with developing agro nomic production practice s , such as the NRCS with improving tillage practice s, and with planting cover crop s that may outcompete weeds. Other parts of USDA, such as ARS

, take into account the physiology of crops and weeds, and the interactions between them

, and are providing practical research in understanding the biology and ecology of agricultural weeds in farm ecosystems.

USDA

- APHIS has responsibility for assuring tha t new GE crops are not plant pest s, which is a limited category of agricultural concern. Necessar ily, APHIS must focus primarily on that issue, making brief notes of possible impacts on the agroecosystem by the plant . At its discretion, APHIS may secondarily note possible changes in herbicide usage on the crop. T he Coordinated Framework and U.S. statutes clearly relegate the authority to regulate all other pesticide

- related issues including environmental impacts

, and stewardship issues to EPA.

The EPA has noted the increasing problems and also the economic issues growers are facing from the emergence of HR weeds. When evaluating the proposed new uses of 2,4

- D on 2,4

- D

resistant corn and soybean, EPA recognized that using herbicide formulations consisting of a premix of two different active ingredients (e.g., 2,4

- D and glyphosate) could increase the number of species and the distribution of weeds resistant to 2,4

- D

. As a result

, the EPA is proposing to impose require ments on DowAgrosciences to ensure better management practices . These proposed requirements include robust monitoring and reporting to the EPA, grower education and remediation, and would allow the EPA to take swift action to impose additional restrictions on the manufacturer and the use of the pesticide if resistance develops ( US

- EPA, 2014a ) . It would allow the EPA to modify the registration quickly and easily to impose additional measures
on growers to manage resista nce if needed. Because EPA has signaled a new direction in stewardship

, APHIS anticipates that the EPA may implement similar label requirements relevant
to re sistance management for the registration of the M1691 dicamba formulation for MON 88701 cotton and 87708 soybean ( US

- EPA, 2014a )

.
The label for dicamba resistant crops would most likely also contain information on resistance management consistent with the Weed Science Society of America’s BMPs for comprehensive resistance management approaches ( US

- EPA, 2014a ) . The details of the EPA’s new proposed requirements related to weed resistance management for the recent registration of a new herbicide product is provided in Appendix 10 of the EIS. APHIS anticipates that the EPA will implement similar appropriate label requirements relevant to resistance management on the registration of M1691 herbicide ( US

- EPA, 2014a )

. 175A large complex of state extension agents, herbicide producer representatives, seed company staff, are all involved in bringing science and technology to farms, showing growers how to efficiently deal with weeds, and weed resistance issues, and these certain ly include appeals to consider all the possible non

- chemical means of improving weed control. The advice of state extension experts, as well as input from USDA studies, will continue to provide growers with expert support as they design ever more complex m anagement systems to preserve profitability and sustainability of their production systems. Financial reward for growers will ultimately be the mechanism by which increased integrated weed management is practically advanced in U.S. farming.

Herbicide

- Resis tant Weeds In this section, the likelihood that problem weeds in cotton and soybean (i.e., those weeds that are actively managed in these crops) will become more resistant to dicamba is reviewed. Appendix 5 includes an analysis of the problem weeds of cotton and soyb ean. Those that have HR biotypes are described in Appendix 6.

As of April 12, 2014, worldwide, there were 429 instances of HR weeds in 234 species ( Heap, 2014d ) . The first HR biotypes were described in the 1950s. The number of weeds resist ant to herbicides increased dramatically in the 1980s and 1990s. Today, resistance to 22 of the 25 known herbicide sites of action has been identified ( Heap, 2014c ) . Of the 25 known herbicide sites of action, 11 are com monly used on cotton and soybean (Appendix 4). Furthermore, while there are hundreds of cases of HR weeds, most of these weeds are not actively managed or directly targeted in cotton and soybean. The analysis below focuses on weeds that are actively
manage d in cotton and soybean fields and addresses which of these have developed herbicide resistance to the major herbicides used in cotton and soybean.

There are 69 broadleaf and 11 grass weed species that require control measures in the major growing regions of soybean and cotton (Appendix 5). There are 25 broadleaf and six grass weeds, respectively, that are a problem in both cotton and soybean, 23 broadleaf and three grass weeds that are mostly problematic in cotton (Table 5

- 1 in Appendix 5), and 21 broadlea f and two grass weeds that are mostly problematic in soybean (Table 5

- 1 in Appendix 5).

The most common types of weed resistance in the U.S. are to ALS and PSII herbicides. There are 15 problem weed biotypes resistant to each mode of action. The problem w eed resistant to the most sites of action is waterhemp ( Table 27 ). Multiple resistance involving biotypes with 13 combinations of sites of action have been reported, including one biotype that is resistant to five sites of action ( Owen, 2012 ) . Common ragweed, and pigweed, waterhemp, and kochia are each reported to have biotypes resistant to four or more sites of action including biotypes that are multiply resistant to two herbicides ( Table 27

, Table 28 ). Multiple HR biotypes have also been selected in redroot pigweed and giant ragweed. None of the problem grasses have multiple resistances.

Resistance of kochia to dicamba arising in wheat and c orn in two states (Colo rado and Nebraska) has been described ( Heap, 2014d )

. Other observations suggest possible tolerance or variability of susceptibility in some Kansas populations ( Crespo et al. , 2014 ) but also one resistant accession was detected in 67 that were screened. The authors caution that dicamba should not be the only effective herbicide applied to Kochia in this region, and that higher rates of dicamba were needed
176to control Kochia if the plants had r eached 8

- 12 c enti m eters in height

. Resistant k ochia appears to occupy an enlarging area of the western and northern Great Plains states, and control efforts in these areas

. As is true of all soybean and cotton growing areas, agronomists and growers in this area need to be especially vigilant and selective of best weed management practices for potentially problematic weeds.

To respond to th e trend of increasing weed resistance to herbicides and to avoid decreased crop yields resulting from weed competition, growers must continually employ and adapt management strategies. Appropriate weed management requires much more than the application of herbicides , including diversified methods and cultural practices ( Norsworthy et al. , 2012 )

. Use of herbicides with alternati ng sites of action is one method ( Norsworthy et al. , 2012 ) , as is using multiple herbicides effective on specific problem weeds . Alternative sites of action refer to using herbicides that have different physiological modes of action. Some common sites of her bicide action include auxin growth regulators, amino acid inhibitors, chlorophyll pigment inhibitors, and lipid biosynthesis inhibitors ( Ross and Childs, 2011 ) ( see Appendix 3).

Dicamba Resistance in Cotton and Interference with Boll Weevil Eradication

As noted earlier in the Environmental Consequences Section, Plant Communities, the auxinic herbicide 2,4

- D is used extensively to eliminate post season persistence of cotton

. These cotton removals are mandated, in many cases

, by law, as part of Boll Weevil Eradication programs, W hen the cotton plant removals are not be accomplished by shredding, herbicides must be used

. T he most effective stalk herbicide is 2,4

- D and MON 88701 cotton already has some minor level resistance to 2,4

- D

. Consequently

, Monsanto’s dicamba

- resistant cotton may not be destroyed by 2,4

- D application and may not necessarily be usable if either Dow’s 2,4

- D

- resistant cotton i s grown, or this second auxinic resistant variety

, MON 88701 cotton

. A dditional herbicide protocols may be needed to chemically destroy the se late season post

- harvest herbicide

- resistant
cotton va rie ties

. Several herbicide choices have been shown to contro l cotton volunteers when these are treated in spring before planting (Morgan et al., 2011)

, and effective herbicide protocol s for immediate post

- season stalk devitalization of 2,4

- D resistant cotton using dicamba, 2,4

- D P or dicamba + diflufenzopyr herbicides ha ve recently been documented ( Lassiter et al.

, 2014 )

. Dicamba Resistance Trait Sustaining Other Effective Herbicides Use of overlapping sites of action, in which problem weeds are targeted with more than one effective herbicide is a key weed management strategy ( Herbicide

- Resistance

- Action

Committee, 2014 ) . The practice of using herbicides with overlapping and alterna tive sites of action could potentially diminish the populations of GR weeds and reduce the likelihood of the development of new HR weed populations ( Dill et al. , 2008 ; Duke and Powles, 2008 ; Owen, 2008 ; Duke and Powles, 2009 ; DAS, 2010 ; Norswo rthy et al. , 2012 )

. In the Midwest, some populations of waterhemp currently have susceptibility only to N

phenylthalamides of the PPO group (saflu fenacil, flumioxin, sulfentrazone used on soybean) ( Legleiter and Johnson, 2013 )

, the PS II groups (metribuzin) , and dicamba ( Table 28 ). In southern states, some populations of pigweed species (see Table 27 ) have resistance to all herbicide groups commonly used on soybean except for PPOs and dicamba. Because resistant weed s should be treated with overlapping

, effective herbicides ( Herbicide

- Resistance

- Action

177Committee, 2014 ) , dicamba

- resistant soybean and cotton treated concurrently with dicamba and

a PPO herbicide is the only herbicide weed control strategy likely to be successful (Culpepper, Public Comment APHIS

- 2013

- 0043

- 3209 )

. Further more , prevention of resistance to both would more likely be achieved if they were used in accordance with a best management plan that specifi ed treatments within the same season, rather than individually in alternate seasons. Th erefore , the availability of MON 87708 soybean and MON 88701 cotton used with suitable choices of herbicides could promote sustainable use of herbicides, such as PPOs in the case of these two major resistant weeds.

178T able 27 . Known Weed Resistance in the Southern U nited S tates

. 1
Most Common Broadleaf Weeds (# states where listed as a top weed) Resistance Group 2 ALS (Group 2) PPO (Group 14) PS II (Group 5) Glycine (Group 9) Phenoxy (Group 4) Chemistry Class 2 Sulfonyl u rea Imidazolinones Triazoles Diphenyl ether N

- phenyl thalimide Triazinones

- Phenoxy Benzoic acid Example chlorimuron imazethapyr chloransulam lactofen fomesafen flumioxazin metribuzin glyphosate 2,4

- D dicamba

Pigweed spp. 3 (12) X X X X X Velvetleaf (11) Lambsquarters (10) X X X Cocklebur (9) X X X Common ragweed (7) X X X X X X Smartweed spp. (6) Morning glory (5) Waterhemp (5) X X X X X X Hor s e weed (marestail) (3) X X X

Giant ragweed (3) X X X X Kochia (2) X X X X
1 Source: ( Heap, 2014d )
2 Cross resistance is possible within a resistance group and/or chemistry class 3 Includes redroot pigweed and smooth pigweed

179Tabl e 28 . Known Weed Resistance in the Midwestern U nited S tates

. Most Common Broadleaf Weeds (# states where listed as a top weed) Resistance Group 1 ALS (Group 2) PPO (Group 14) PS II (Group 5) Glycine (Group 9) Phenoxy (Group 4)

Chemistry
Class 1 Sulfon u rea Imidazolinones Triazoles Diphenyl ether N

- phenyl thalimide Triazinones

- Phenoxy Benzoic acid
Example chlorimuron imazethapyr chloransulam lactofen fomesafen flumioxazin metribuzin glyphosate 2,4 D dicamba

Pigweed spp. 2 (12) X X X X X Velvetleaf (11) Lambsquarters (10) X X X Cocklebur (9) X X X Common ragweed (7) X X X X X X Smartweed spp. (6) Morning glory (5) Waterhemp (5) X X X X X X Horesweed (marestail) (3) X X X

Giant ragweed (3) X X X X Kochia (2) X X X X
Source: www.weedscience.org

1 Cross resistance is possible within a resistance group and/or chemistry class

2 Includes redroot pigweed and smooth pigweed

180Managing Glyphosate

- Resistant Weeds APHIS, recognizing that the need for additional weed management tools is the reason why MON 88701 cotton and MON 87708 soybean have been developed, has considered whether the current impacts of the management practices for resistant weeds may also potentially contribute to the cumulative impact s of MON 87708 soybean and MON 88701 cotton

. In 2012, the area of U.S. cropland infested with GR weeds expanded to 61 million acres, according to a survey conducted by Stratus Agri

- Marketing ( Farm Industry News, 2013 )

. Table 27 and Table 28 lists horse weed species that have been identified as HR in ( Farm Industry News, 2013 ) at least some part of their range in the U.S. The use of glyphosate on cotton and soybean is not expected to increase under any of the Alternatives because most cotton and soybean in the U.S. alread y has the GR trait and so glyphosate use is saturated on these crops. Between 2011 and 201 4 , HR soybean was planted on 93 to 94 percent of total soybean acres and HR cotton planted on 73 to 96 percent of total
cotton acres The increase of GR weeds only makes glyphosate use less attractive, although as noted, glyphosate still controls large numbers of weeds ( Monsanto, 2013a ) . From 2008 to 2011, acres to which glyphosate was applied were either stable or declined, but other herbicides (residuals applied to soil that persist for extende d periods) applied increased by 177 percent ( Monsanto, 2013a ) . To manage glyphosate resistance, growers are not using more glyphosate, but are using more sites of action in addition to glyphosate.

Mid

- South and possibly the Southeastern s tate soybean growers who previously adopted no

- till production are now replaci ng that with increasingly aggressive tillage in their management programs (see Cumulative Impacts: Cotton and Soybean Agronomic Practices and Costs of Production. Changes in Tillage). In parts of the Heartland, GR waterhemp and marestail are widespread ( Bowman, 2013 ) . No

- till practices are being maintained in many areas , but the presence of HR weeds and rapidly increas ing presence of GR weeds in particular, sometimes necessitate the inclusion of tillage in weed control strategies ( Arbu ckle and Lasley, 2013 )

. An Iowa poll disclosed that farmers there used mechanical weed control (i.e., cultivation) 25 percent of the time, and 55 percent found it to be effective or very effective for weed control ( Arbuckle and Lasley, 2013 ) . Farmers apparently value soil cultivation for weed control, but practice it only to a limited extent (25 percent ) at present.

Under the No Action Alternative, GR weeds are likely to be an increasingly serious concern in the Mid

- South, and Southeast ( Prince et al. , 2012a ) and Great Plains regions ( Spaunhorst et al.

, 2014 ) . Multiply

- resistant weeds have also begun to be discovered, and in Iowa, 88% of 2011 waterhemp populations may be multiply resistant; i midazolinone herbicide weed resistance was the highest, with up to 92% of waterhemp in soybean having cross resistance, even though pressure on weeds with this herbicide was not maintained in r ecent years ( Owen, 2014c ) . The availability of MON 87708 soybean and MON 88701 cotton under the Preferred Alternative (along with an EPA decision to register new herbicide formulations for these crop s) would increase the herbicide s available for postemergent weed control, allowing more selective control of weeds whose resistances are known.

Under the No Action Alternative, growers wou ld likely use increased conventional tillage or additional herbicides to control weeds. The further adoption of conservation tillage practice s could be impeded as growers who have already adopted conservation tillage are forced to return

181to more aggressive tillage systems to maintain soybean yields ( Conley, 2013 ) . This practice is likely in a limited number of locations where alternative herbicides are not effective.

Under the Preferred Alternative, dicamba use is expected to increase relative to the No Action Alternative. However, increases in use of other herbicides such as chloroacetam ides, glufosinate, ALS inhibitors, PPO inhibitors, and HPPD inhibitors are expected to be less than under the No Action Alternative because MON 87708 soybean and MON 88701 cotton will be adopted. The availability of inexpensive and effective herbicides (including new use of dicamba) combined with MON 87708 soybean and MON 88701 cotton may delay the adoption of non

- chemical management strategies under the Preferred Alternative. Fewer growers would be expected to adopt aggressive tillage when herbicides re main effective for weed control. Selection of weeds resistant to glyphosate, auxins, chloroacetamides, ALS inhibitors, and glufosinate will still occur under the Preferred Alternative. The selection pressure for HR weeds under the Preferred Alternative rel ative to the No Action Alternative will depend on the management practices employed under each Alternative and cannot be predicted

. APHIS concludes that m ore diversified herbicide choices, and other weed management practices will result in less selective
p ressure for resistance to any given herbicide or management technique.

Potential for Weed Resistance to M1691 or Other Dicamba Formulations Summary: Weed resistance is not a consequence of the use of herbicide resistant crops. APHIS under the Preferred A lternative concludes that the extent and types of resistant weeds depend on how growers either employ the techniques of weed management or ignore them. Growers are expected to rotate by using different herbicides and different rotation crops to deter devel opment of new herbicide resistant weeds.

There is a consensus among weed scientists that the best way to delay the development of weed resistance is to use multiple herbicides with different modes of action that are effective against a single weed species

. Dicamba used post

- emergent will provide another herbicide treatment option that is consistent with this strategy. However, for areas where glyphosate resistance is prevalent, the use of MON 87708 soybean and MON 88701
cotton crops which will allow trea tments with both glyphosate and dicamba, will not effectively delay the onset of resistance to these herbicides . If growers plant MON 87708 soybean and MON 88701 cotton in areas with GR weeds without including multiply effective additional herbicides (in addition to dicamba and glufosinate) and diversified weed management methods as part of their practices , APHIS concludes that this may accelerate the development of weed resistance to dicamba . Therefore, best management practices that combine both herbici des and other weed control methods are essential components of a strategy to prevent the development of HR weeds and manage existing HR weed populations. Since dicamba only controls broadleaf weeds, this further emphasizes the need for a broad

- based weed m anagement system

. Under the Preferred Alternative, APHIS notes that the EPA will have new regulatory mechanisms in place to oversee HR crops and to deter resistant weed development. APHIS expects the EPA to implement appropriate label requirements for registration of the M1691 herbici de relevant to weed re sistance management , as it has recently done for Dow Agrosciences’ Enlist Duo (glyphosate and 2,4

- D premix) to be used on 2,4

- D

182resistant soybean and corn. The EPA is also expected to require crop ove rsight by manufacturers for reporting and responding to new incidences of weed resistance. Monsanto will be required to take action to deal with such weed resistance in MON 87708 soybean and MON 88701 cotton , following the pattern being established by the EPA for Dow Agrosciences for the continuing oversight of 2,4

- D and Enlist crops.

The relative risk that a resistant weed biotype will be selected following herbicide exposure is highly correlated to the herbicide mechanism of action ( Sammons et al. , 2007 ) . Herbicide families have been classified according to their risk of resistant weed development. Beckie (2006) lists ALS

- and ACCase

- inhibiting herbicides as high risk for selection of resistant biotypes, while glyp hosate and auxin type herbicides are considered low risk. Weeds resistant to auxin herbicides have been slowly accumulating over the past seventy years, but none have become particularly problematic. As of 2013, there are 31 species listed that include bio types that are resistant to auxin herbicides, eight of which are located in the U nited S tates ( Table 28

, prepared from data in ( Heap, 2014b ) ). Of the 31 species found world

- wide, seven are resistant to dicamba. Of these, two are found within the U nited S tates ( Table 28

, highlighted in gray) and five are found outside the U nited S tates (yellow starthistle, lambsquarters, common hempnettle, wild mustard, indian hedge mustard, kochia, and prickly lettuce). Of these, GR biotypes are found only for kochia and lambsquarters. Thus, the combination of glyphosate and dicamba

cu rrently controls a wide range of problem weeds.

Despite the fact that glyphosate and auxin herbicides are considered low risk, resistant biotypes are being selected from the use of these herbicides. GR weeds in a few species such as Palmer amaranth, water hemp, horseweed, ragweed, and giant ragweed, have become widely prevalent in certain areas and cropping systems, such as cotton and soybean, where glyphosate was the only herbicide use d for weed control and sometimes continuous croppi ng and no

- till farming was also practiced. The lack of diversity of weed management practices in such situations is believed to have contributed substantially to the selection of resistant biotypes.

Though auxin HR weeds (e.g., 2,4

- D and dicamba) have bee n relatively slow to develop and are not particularly widespread, some will note that the same was true for GR weeds prior to the widespread use of glyphosate on GR crops. The selection of GR weeds purportedly came about through the almost exclusive use of glyphosate for weed control in some crops such as cotton, corn and soybean without the adoption of best management practices, including employing a diversity of weed management practices. Therefore, selection of dicamba resistant weeds may be preventable depending on how glyphosate, dicamba, and other herbi cides are used on MON 88708 soybean, MON 88701 cotton and other crops. The likelihood of selection of dicamba

resistant weeds is greater as the selection pressure for resistance increases. When considerin g cumulative impact s under the Preferred Alternative, selection pressure is expected to be greater than under the No Action Alternative because dicamba use is expected to be considerably higher (Appendix 4, Table 4

- 9 and 4

- 12) if the EPA registers the new use of dicamba on MON 88701 cotton and MON 87708 soybean. To mitigate the increased selection pressure associated with the

183increased use of dicamba, Monsanto recommends 19 the following practices for weed management and for herbici de selection:

• Actively growing weeds in fields compete with the crop, so should be eliminated prior to planting.

• Maintain good weed control until crop canopy can be an indicator of good weed control throughout the remainder of the season.

• Include two or more crops in a crop rotation and ideally rotate to a different crop each
year.

• Use a broad spectrum soil active residual herbicide in the corn season of a crop rotation and in soybeans when hard

- to

- control w eeds are present.

• The addition of a non

- glyphosate herbicide reduces the sole use of glyphosate which can decrease the risk of developing of weed resistance.

• Use the full, labeled rate of glyphosate based on the most difficult

- to

- control weed in the field.

• Control weeds before they reach four inches tall (in soybeans before eight inches tall).

• Reduce weed populations from year to year, allowing for more efficient use of herbicides and other cultural practices to control weeds.

• Tillage should be considered a s an alternate weed control practice where appropriate.

The selection and distribution of dicamba

- resistant weeds is impossible to predict because the extent to which growers will use best practices with these HR crops is uncertain

. A 2010 grower
survey ( Prince et al. , 2012b ) observed that many growers were using practices targeted specifically at preventing o r managing GR weeds, but that these practices were not new introductions to their weed management plans. Growers recognized that rotating herbicides, using tank mixes, and increasing tillage would be effective strategies to manage GR weeds but did not seem to recognize that HR weeds were the result of repeated use of a herbicide or herbicides with the same mode of action if additional weed management practices were not implemented ( Prince et al. , 2012b ) . Education efforts to increase grower awareness are ongoing and there appears to be an increase in grower perception of the effectiveness of practices

recomme nded by the weed science community ( Prince et al. , 2012b )

. Modeling studies suggest that exclusive use o f an herbicide can select for HR weeds in as little as five years ( Neve et al. , 2011 ) . Because growers who adopt MON 87708 soybean or MON 88701 cotton are expected to be those who have had the most difficulty with ( Neve et al.

, 2011 ) GR weeds, the selection of biotypes exhibiting multiple resistance to both glyphosate and dicamba is expected to be related to the probability of selecting resistance to just dicamba and not the product of selecting resistance to both sites of action. Thus, multiple resistance could be expected to appear in as little as fiv e years if glyphosate and dicamba are used exclusively in

some areas . The southernmost part of the Southeast (Region D) is expected to be a problem region because GR weeds are already reported to be present in greater than 90% of cropland ( Farm Industry News, 2013 ) . In this region, Palmer amaranth can no longer be controlled with

19 Website, April 15, 2014: http://www.monsanto.com/weedmanagement/pages/field

- management

- guidelines.aspx

184glyphosate and would be a particular risk for the selection of multiple resistant biotypes. In the Heartland (Regions C and G) and prairie states (Region I), HR waterhemp has been selected to several herbicides and a biotype resistant to four herbicides ha s been detected ( Bell et al. , 2013 )

. Furthermore, biotypes with resistance to either dicamba or glyphosate have already appeared in Nebraska ( Table 29 )

. A multiply

- resistant biotype could form by hybridization and dissemination. APHIS concludes that i f MON 87708 soybean and MON 88701 cotton are exclusively used by growers for weed management, without appropriate use and coordination with use of other herbicide sites of action, independently ari sing weed biotypes that are multiply resistant to dicamba and other herbicides are likely to be selected.

Table 29 . Auxin

- Resistant Weeds

. Species Year/Location Auxin Situation GR/GT 1 Amaranthus tuberculatus Ameranthsyn. rudis) 2009

- USA (Nebraska) 2,4

- D Pasture +

Common Waterhemp 2 Carduus nutans 1981

- New Zealand 2,4

- D Pasture Musk Thistle 3 Carduus pycnocephalus 1997

- New Zealand 2,4

- D, MCPA, MCPB Pasture

Italian Thistle 4 Centaurea cyanus 2012

– Poland Dicamba Winter wheat

5 Centaurea solstitialis 1988

- USA (Washington) Picloram Roadsides

Yellow Starthistle 5 Chenopodium album 2005

- New Zealand Dicamba Corn Lambsquarters 6 Cirsium arvense 1979

- Sweden MCPA Cropland Canada thistle 1985

- Hungary 2,4

- D and MCPA Pasture 8 Commelina diffusa 1957

- USA (Hawaii) 2,4

- D Sugarcane Spreading Dayflower 9 Daucus carota 1957

- Canada (Ontario) 2,4

- D Roadsides Wild Carrot 1993

- USA (Michigan) 2,4

- D roadsides and cropland 1994

- USA (Ohio) 2,4

- D soybean 10 Descurainia sophia 2011

- China MCPA winter wheat

Flixweed 11 Digitaria ischaemum 2002

- USA (California) quinclorac rice Smooth Crabgrass 12 Echinochloa colona 2000

- Colombia quinclorac rice + Junglerice 13 Echinochloa crus

- galli

var crus - galli 1998

- USA (Louisiana) quinclorac rice

Barnyardgrass 1999

- Brazil quinclorac rice 1999

- USA (Arkansas) *Multiple

- 2 MOA's propanil and quinclorac rice

2000

- China quinclorac rice 2009

- Brazil *Multiple

- 2 MOA's bispyribac

- sodium, imazethapyr, rice

185Species Year/Location Auxin Situation GR/GT penoxsulam, and quinclorac 2013

- Uruguay quinclorac rice

14 Echinochloa crus

- galli var. zelayensis 2013

- China quinclorac rice

15 Echinochloa crus

pavonis 1999

- Brazil quinclorac rice

Gulf Cockspur

16 Fimbristylis miliacea 1989

- Malaysia 2,4

- D rice Globe Fringerush 17 Galeopsis tetrahit 1998

- Canada (Alberta) dicamba, fluroxypyr, and MCPA barley, cereals, cropland, wheat Common Hempnettle 18 Galium spurium 1996

- Canada (Alberta) *Multiple

- 2 MOA's imazethapyr, metsulfuron

- methyl, quinclorac, sulfometuron

methyl, thifensulfuron

methyl, triasulfuron, and tribenuron

methyl cereals and wheat

False Cleavers 19 Kochia scoparia 1995

- USA (Montana) dicamba and fluroxypyr cropland and wheat +

Kochia 1995

- USA (ND) dicamba wheat 1997

- USA (Idaho) dicamba roadsides
1999

- USA (Colorado) dicamba corn 2010

- USA (Nebraska) dicamba corn 20 Lactuca serriola 2007

- USA (Washington) 2,4

- D, dicamba, MCPA cereals

Prickly Lettuce 21 Limnocharis flava 1995

- Indonesia 2,4

- D rice Yellow bur

- head 1998

- Malaysia *Multiple

- 2 MOA's 2,4

- D and bensulfuron

- methyl rice

22 Limnophila erecta 2002

- Malaysia *Multiple

- 2 MOA's 2,4

- D, cinosulfuron, mesosulfuron

methyl, and pyrazosulfuron

- ethyl rice

Marshweed

23 Papaver rhoeas 1993

- Spain *Multiple

- 2 MOA's 2,4

- D and tribenuron

- methyl cereals and wheat Corn Poppy 1998

- Italy *Multiple

- 2 MOA's 2,4

- D, iodosulfuron

methyl

- sodium, and wheat

186Species Year/Location Auxin Situation GR/GT tribenuron

- methyl 1998

- Italy 2,4

- D wheat

24 Ranunculus acris 1988

- New Zealand MCPA Pastures

Tall Buttercup 25 Raphanus raphanistrum 1999

- Australia (Western Australia) 2,4

- D cereals +

Wild Radish 2006

- Australia (South Australia) *Multiple

- 3 MOA's 2,4

- D, diflufenican, MCPA, and triasulfuron cereals

2009

- Australia (Victoria) *Multiple

- 2 MOA's 2,4

- D, chlorsulfuron, and metosulam barley and wheat

2010

- Australia (Western Australia) *Multiple

- 4 MOA's 2,4

- D, chlorsulfuron, diflufenican, glyphosate, imazethapyr, MCPA, metosulam, and sulfometuron

methyl Fallow

2011

- Australia (Victoria) 2,4

- D Barley and Wheat 2013

- Australia (New South Wales) 2,4

- D Barley, Oats, and Wheat 26 Sinapis arvensis 1990

- Canada (Manitoba) 2,4

- D, dicamba, dichlorprop, MCPA, mecoprop, and picloram barley, cropland, and wheat

Wild Mustard 2008

- Turkey *Multiple

- 2 MOA's dicamba, propoxycarbazone

sodium, thifensulfuron

methyl, triasulfuron, and tribenuron

methyl not specified

27 Sisymbrium orientale 2005

- Australia (South Australia) *Multiple

- 2 MOA's 2,4

- D, imazethapyr, MCPA, metosulam, and metsulfuron

methyl cereals

Indian Hedge Mustard dicamba, propoxycarbazone

sodium, thifensulfuron

methyl, triasulfuron, and tribenuron

methyl 28 Soliva sessilis 1999

- New Zealand clopyralid, picloram, and triclopyr Golf courses

Carpet Burweed 29 Sphenoclea zeylanica 1983

- Philippines 2,4

- D rice

Gooseweed 1995

- Malaysia 2,4

- D rice
187Species Year/Location Auxin Situation GR/GT 2000

- Thailand 2,4

- D rice 30 Stellaria media 1985

- United Kingdom mecoprop cereals and wheat Common Chickweed 2010

- China fluroxypyr and MCPA winter wheat

31 Tripleurospermum perforatum (=T. inodorum) 1975

– France 2,4

- D cereals

Scentless Chamomile 1975

– United Kingdom 2,4

- D cereals

Source: ( Heap, 2014b ) U.S. dicamba resistance highlighted in gray.

M any types of resistance could potentially arise in weed populations ; no predictions could be made for cross resistance by unknown new weed biotypes. As indicated in Table 29 , weed resistance to both herbicides is rare, with only two known occurrences.

Cumulative Impacts of Other HR Crops on MON 87708 S oybean and MON 88701 C otton and on Weed Resistance

Summary: Other crops are current ly being evaluated for nonregulated status by USDA

APHIS which, if determined as nonregulated, may have impacts with MON 87708 soybean and MON 88701 cotton on the development of herbicide

- resistant weeds

. These crops include GE soybean, corn and cotton with resistance to the auxinic class herbicide 2,4

- D, and two GE soybean varieties with resistance to HPPD inhibitors

. Weed resistance to auxin class herbicides is relatively limited compared to other herbicide classes

. Nevertheless, there has been some detec tion of cross resistance in weed populations to more than one class of auxinic herbicide, including a few with 2,4

- D and dicamba resistance

. The extent and mode of such cross resistance has not been well

investigated

. However, because of the potential for cross

- resistance, growers will likely be cautioned not to plant 2,4

- D

- resistant and dicamba

- resistant crops in successive years on the same fields. Under the Preferred Alternative, APHIS concludes that weed cross

resistance should and will be monitored car efully

. The EPA will likely mandate remediation, should such resistance develop.

Newly available HR crops will facilitate recommendations from weed scientists that include rotation of herbicide chemistries to help reduce resistance development. HPPD inhib itor

- resistant soybeans include one nonregulated soybean (isoxaflutole) cultivar and another in process of attaining non

- regulated status (mesotrione and isoxaflutole)

. APHIS concludes that rotation of MON 87708 soybean and MON 88701 cotton with these HR cr ops with auxinic activity would then add additional flexibility when these crops are also available to cotton and soybean growers

. MON 887 7 0 1 cotton also has resistance to glufosinate, which will offer breadth in mode of action chemistry. Other existing

188h erbicide resistant crops include those with glufosinate resistance alone, and these also may enhance flexibility for sustainable weed management decisions.

Other crops with auxin class herbicide activity

. In addition to glyphosate

- and glufosinate

resistan t crops planted by growers, other HR crops have recently been determined as nonregulated and will become available. Along with dicamba

- resistant MON 87708 soybean and MON 88701 cotton , growers will likely select from those with two new herbicide classes of activity. GE crops newly determined as nonregulated for 2,4

- D

- resistant corn and soybean. 2,4

- D, along with dicamba, are both synthetic auxins (auxinic class). If the petitions for d eterminations for nonregulated status are made by APHIS for dicamba resistant crops, use of both dicamba and 2,4

- D is expected to increase above current usage .Still other crops now in development and field testing may culminate in requests for nonregulated status

. These include a Monsanto corn variety that has resistance to dicamba , glyphosate and to glufosinate ( Monsanto, 2014a ; 2014b ) but this product is distant from even production of a petition and is only in Phase 3 of four phases

. APHIS is uncertain whether this corn variety will eventually be available to growers or not

. An additional 2,4

- D resistant cotton crop has been submitted by Dow Agrosciences as a petition for nonregulated status

. Also, a cross

- licensing agree ment for Monsanto to use 2,4

- D traits in corn has been negotiated ( Farm

- Industry

- News, 2013 ) and if activated by new hybrids, could also provide additional crops with resistance to auxinic type herbicides.

While it is clear that growers will be offered two auxinic class herbicides in several crops, and that both 2,4

- D and dicamba will be used wi th greater frequency, weed scientists are generally appreciative of an additional herbicide resistance chemistry being available to growers (see comments by Norsworthy and Culpepper on this docket)

. Being highly aware of the need to avert development of ne w herbicide resistance engendered by HR crops

, scientists state that these product s can help minimize selection pressure on weeds by providing a second effective mode of action (J. Norsworthy, public comment, this docket)

. In cotton, only highly limited mo des of action are available to growers; dicamba resistant cotton could prolong the usefulness of these few remaining chemistries (S. Culpepper, public comment this docket)

. Speaking from close interactions with growers, Culpepper (public comment) declares that growers will not follow practices of over

- dependence on dicamba when they know it will lead to “poor weed control and eventual crop failure.” APHIS agrees that the potential for weed resistance to dicamba is clear to growers and that with the continu ed advice and counsel of weed scientists and others, they will choose to make dicamba and 2,4

- D sustaining tool s for management of cotton and soybean weeds, and not create additional liabilities to crop production.

Weed resistance to auxinic class herbicid es. Depending on how widely these crops are adopted and what weed control management practices are followed by growers, weed resistance to each herbicide could potentially increase, and weeds arise with resistance to both herbicides. A comparison of the hi story of resistance development by weeds to 2,4

- D and to dicamba may provide some evidence for the likelihood of rapid development of such resistance ( Feng and Brinker )

. Although both dicamba and 2,4

- D have been used widely in agriculture for about five decades, only a limited number of resistant weeds have arisen compared to the number that have arisen to other herbicide modes of action ( Mithila et al. , 2011 ) . Detected weed resistance to dicamba occurred in two species, although Kochia resistance arose in five locations ( Table 29 )

189( Heap, 2014d ) . Kochia resistant to dicamba in Montana may also have low

- level resistance to 2,4

- D. Weed resistance to 2,4

- D occurred in four US species, only two of which occ ur in soybean and cotton production areas ( Heap, 2014d ) . Two 2,4

- D resistant weeds, wild mustard, Sinapis arvensis , and prickly lettuce, Lactuca serriola also have dicamba resistance, the first in Canada, the second in Washington ( Heap, 2014d ) . Thus, only three weed species have arisen with resistance to both dicamba and 2,4

- D in the United States and Canada. With 23 herbicides in the auxinic group ( Heap, 2014d ) , the world list of resistant weeds in the group was either only 29 populations ( Mithila et al. , 2011 ) or 31 populations ( Heap, 2014d )

. That relatively few 2,4

- D resistant weeds have developed over a long period in U.S. corn, soybean or cotton production indicates that high levels of new weed resistance can be avoided following determination of nonregulated status for MON 87708 soybean and MON 88701
cotton , particularly if diversified weed management practices are implemented

. . Agricultural usage of dicamba on all U.S. crops was increasing between 1990 and 1994, when it reached 9.4 million pounds applied annually (Petit ion VIII

- 11) ( Monsanto, 2012b ) . The frequency of annual use of dicamba was 1.00 for soybean (20 06) 1.00 for cotton ( 200 7 ) and 1.02 for corn ( 200 5 ) (Table VIII

- 13 ( Monsanto, 2012b ) ). Agricult ural usage of 2,4

- D averaged 30 million pounds in the period 1992

- 2000 in an earlier era when fewer herbicide choices were available ( US

- EPA, 2005 ) 20 , and would have been expected to result in high levels of resistant weed populations because of frequent use. Although usage of 2,4

- D has declined considerably, as recently as 2004, according to USDA

- NASS, usage was still between 21 to 33% for wheat, corn, cotton, and soybean crops ( Mithila et al. , 2011 )

. Additional considerations may influence the low incidence of weed resi stance to 2,4

- D and dicamba. One of these is a relatively low frequency of repeated exposures both historically and in current usage. Practical crop production issues limit the usefulness of 2,4

- D treatments, and may have led to its replacement by other he rbicides. For example, 2,4

- D in soybean may be used in burndown treatments no less than15 to 30 days in advance of planting depending on rate of application ( Nufarm, Undated ) , and this is a lengthy wait for a preplant herbicide. 2,4

- D may be used once, pre

- emergence, and then most likely, less frequently on emerged corn that is 8 inches or taller because it requires application by directed nozzles only ( Nufarm, Undated ) . 2,4

- D may not be used on cotton at all. Dicamba presently is used infrequently; in 2012, the herbicide was used on only 4% of corn, 5% of cotton a nd 0.3% of soybean in the United States (see Table 17 )

. Dicamba on soybean may be applied 14 to 28 days before planting (dependent on rate) and then once on mature soy beans at pre

- harvest. Cotton may receive a dicamba treatment as a pre

- plant application, and later only as a pre

- harvest treatment ( BASF, 2010 ) . On corn, dicamba may be used as a pre

- plant (but not around the time of germination) or after the corn is more than 8 inches tall (but with restrictions if soybean is planted nearby) ( BASF, 2010 )

. Potential for development of weed herbicide re sistance to dicamba. Resistance to one of the auxinic herbicides does not necessarily predispose resistance to another auxinic herbicide; for

20 Current use on cotton, soybean and corn (2010

- 2012, most recent data ( USDA

- NASS, 2014d ) ) is 9.3 million pounds. Next most recent report of usage for these crops (2005

- 2007 most recent data, ( USDA

- NASS, 2014d ) ) is 6 million pounds.

190example, yellow star thistle with 3

- fold resistance to picloram has 4.4

- fold resistance to dicamba, but no resista nce to 2,4

- D ( Fuerst et al. , 1996 ) . Another recent report of 2,4

- D r esistance in waterhemp shows that for visual injury levels, field resistant water hemp had 19.2

- fold resistance to 2,4

- D, but had only 4.5

- fold resistance to dicamba ( Bernards et al. , 2012 ) . While there are three groups of auxinic herbicides, Beckie and Tardiff ( 2012 ) note, “the extent and level of cross resistance among classes varies widely by auxinic

- resistant weed species and is currently unpredictable.” Some mechanisms may restrict the potential for res istance to these auxinic herbicides, including dicamba. Possibilities that may diminish resistance potential of weeds to 2,4

- D include fitness penalties for plants carrying resistance traits, complexities of the mode of action of auxin, or the rare occurre nces of resistance alleles in the target weed populations ( Mithila et al. , 2011 ) . Presumabl y, mechanisms of potential dicamba resistance are similar to 2,4

- D mechanisms and will also engender limited herbicide resistance development in weeds.

Other crops with new herbicide resistance. Other HR crops that exhibit resistance to different herbicide modes of action would provide rotational choices consistent with best management practices. Enlist 2,4

- D

- resistant crops may be of limited usefulness to growers that plant MON 87708 soybean and MON 88701 cotton because both dicamba and 2,4

- D have the same mode of action. Those other HR crops include one with nonregulated status and the other is a petition requesting nonregulated status, both of which are resistant to HPPD inhibitors: these are isoxaflutole

- resistant and mesotrione

- resistant soybean ( USDA

- APHIS, 2014f ) . With these alternative HR soybe an varieties, the availability of MON 87708 soybean and MON 88701
cotton will accommodate rotations of auxinic and HPPD inhibitor herbicide chemistries from one season to another. Thus, sequential multi

- season use of the HPPD inhibitors will help growers

av oid the continued applications to field s of WSSA Class 4 herbicides (2,4

- D and dicamba) which would be a risk factor s for development of resistant weeds. It is difficult to decide whether the grower benefits of an additional mode of action in an herbicide resistant rotation crop will outweigh the concerns of having two simultaneous auxinic class herbicides that may addit ively increase the risk of HR weed development. Aside from glufosinate resistant cotton, no other HR cotton is available. However, since soybean is a rotation crop for cotton in about 8% of cotton acres, the soybean resistant to HPPD inhibitors may be of v alue in providing a diversity of herbicides that may reduce resistant weed development

. APHIS concludes that MON 88701 cotton and MON 87708 soybean will encourage the use of diverse herbicides for improved problem weed control, as long as other auxin class herbicides are not also used in successive crop rotation s with these varieties.

Volunteer MON 87708 soybean and control options

Concerns were raised by one commenter that options for control of glyphosate resistant soybean volunteers were presently limited, and then with availability of dicamba resistant soybean, control options for these volunteers may further be reduced (CFS, Science Comments I). According to Georgia cotton extension specialists, volunteer soybean is uncommon, but can sometimes be observed following hurricane damage to soybean fields ( York et al. , 2005 )

. If these volunteers are present, these weed scientists have shown that use of trifloxysulfuron provides control when applied post

- emergence, and that control can be accomplished at presently allowable rates.

191Biodiversity Summary : While in general , herbicides do not promote biodiversity, the potential for biodiversity may be enhanced by availability of an additional herbicide chemistry in a resistant crop

. The use of the new herbicide chemistry may lead to increased productivity and consequently , increased yield on existing agricultural land

. APHIS concludes that the consequences of such yield increase could include a somewhat diminished demand for new conversio n of CRP lands or other as yet unconverted nonagricultural lands, and thus to increased potential for maintaining animal and plant biodiversity

. As described in the No Action Alternative, agricultural practices can affect biodiversity in and around agricul tural fields. Growers have the opportunity to choose many different practices to manage their operations.

Agricultural practices have the potential to impact diversity at the farm level by affecting farm biota, including birds, wildlife, invertebrates, so il microorganisms, and weed populations. Conservation tillage leaves a higher rate of plant residue and increases soil organic matter ( Hussain et al. , 1999 )

. This benefits soil biota by providing additional food sources (energy) ( USDA

- NRCS, 1996b ) and increasing the diversity of soil microorganisms. It also benefits invertebrate detritivores, their p redators, and ultimately, birds and other wildlife higher in the food chain ( Towery and Werblow, 2010 ; Carpenter, 2011a ) . Ground

- nesting and seed

- eating birds, in particular, have been found to benefit from greater food and cover assoc iated with conservation tillage ( SOWAP, 2007 )

. Herbicide use in agricultural fields can impact biodiversity by decreasing weed quantities or causing a shift in weed species. This can affect insects, birds, and mammals t hat use these weeds. The quantity and type of herbicide use associated with conventional and GE crops depends on many variables, including cropping systems, type and abundance of weeds, production practice s, and individual grower decisions.

As described in the No Action Alternative, agricultural practices can affect biodiversity in and around agricultural fields. Growers have the opportunity to choose many different practices to manage their operations. Bot h tillage and herbicide use patterns influence biodiversity. If MON 88701 cotton and MON 87708 soybean are approved, it is likely that use of no

- till management will remain the same or increase. Therefore, use of these products is lik ely to provide stability to biodiversity , especially in fields where tillage is used currently to control GR weeds. In many regions tillage is used for purposes other than weed control, so in these areas only the changes in herbicide use patterns may influ ence biodiversity. Because many management choices affect farm level biodiversity, the magnitude of this impact on biodiversity is uncertain.

Habitat loss is the greatest direct impact that agriculture has on biodiversity ( Ammann, 2005 )

. Therefore, methods that increase crop yields have the potential to reduce impacts to bio diversity by reducing the amount of land converted to agriculture ( Carpenter, 2011a ) . Gains in yields have generally not been obtained by HR cultivars unless higher yielding ones are modified to incorporate an HR trait ( NRC, 2010b )

. APHIS concludes that nonregulated status for MON 88701 cotton and MON 87708 soybean will have no effect on existent biodiversity.

192( USDA

- NRCS, 1996b ; Hussain et al. , 1999 ; Ammann, 2005 ; SOWAP, 2007 ; NRC, 2010b ; Towery and Werblow, 2010 ; Carpenter, 2011a ; Carpenter, 2011b )

5.6.6 Physical Environment

Summary: Potential cumulative impact s on the Physical Environment can mostly be ascribed to the use of dicamba on MON 87708 soybean and MON 88701 cotton

. Dicamba

- resistant crops may deter growers from returning to conventional tillage that may otherwise become necessary for controlling glyph osate

- resistant weeds

. Under the No Action Alternative, development of additional glyphosate

- resistant and other herbicide

- resistant weeds will likely continue; one response that growers may take wou ld be to increase such tillage. The potential impacts on Soil, Water, Air Quality and Climate Change, which are directly affected by the increased use of tillage, would be diminished under the Preferred Alternative. Any direct and indirect impacts of dicamba use are being assessed by the EPA, and are outside the scope of this EIS

.
After the EPA approves the proposed uses of dicamba and the Preferred Alternative is chosen by APHIS, there is an expectation that the use of dicamba will increase. This increase in dicamba use has the potential to impact natural resour ces. APHIS does not regulate the use of dicamba. The direct and indirect impacts which arise from this increased use are the result of the action that the EPA is taking with respect to labeling dicamba (M1691) for use on MON 87708 soybean and MON 88701 cot ton that are the subject of the two petitions being considered in this EIS. APHIS ex pects the EPA to implement appropriate label requirements for registration of the M1691 , and has considered the cumulative impact s from changes in production practice s that may arise from HR weeds.

Soil Quality The major cotton and soybean regions in the U.S. also are areas where soil erosion exceeds replacement. Many of these intensively farmed areas are also on highl y erodible lands. In some of these areas conservation tillage has been adopted as part of the management plan for controlling erosion.

If conventional tillage increases to control glyphosate

- and other herbicide

- resistant weeds, there may be an impact on soil quality . Residue management that employs intensive tillage and leaves low amounts of crop residue on the surface results in greater losses of soil organic matter (SOM) ( USDA

- NRCS, 1996b ) . The total acreage that may be impacted by such an increase in tillage would be based on the extent of resistant weeds present in a field and the weed management
str ategy chosen by a grower. Adoption of MON 88701 cotton and MON 87708 soybean can provide growers with an alternative herbicide to glyphosate and glufosinate. Intensive use of glyphosate on GR crops has been associated with increased se lection for GR weeds. Many growers have expressed a need for these crop events during the scoping comment period associated with this EIS because of their weed problems.

Based on individual grower needs, these two events and the EPA approv al of dicamba use on them could provide growers with an alternative to intensive tillage practice s that may be used to address herbicide resistance issues. This could reduce the potential loss of SOM and soil erosion

193that may result when more aggressive tillage practices are used to combat HR weeds under the No Action Alternative. However, the selection of weeds resistant to glyphosate, dicamba, and glufosinate will limit the use of this product and any benefit to soil that may arise. The magnitude of the benefit or the loss of the benefit is uncertain because growers individually make decisions on soil management practices. Therefore, each action could contribute incrementally to the problem of soil erosion.

Wa ter Quality Under the No Action Alternative, increased tillage to manage GR weeds may occur and lead to increased soil erosion and decreases in water quality from sedimentation and transport of nutrients and other chemicals to surface water. When consideri ng the cumulative impact s of the Preferred Alternative, MON 87708 soybean and MON 88701 cotton cropping systems may help to preserve gains in conservation tillage in the short term. In the long term, selection of dicamba

resista nt weeds may result in similar aggressive tillage practice s that are expected to occur under the No Action Alternative and negate the benefits mentioned above.

Air Quality Under the No Action Alternative, increased tillage to mana ge GR weeds may occur and lead to decreased air quality from increased air particulates and exhaust from farm equipment. When considering the cumulative impact s of the Preferred Alternative, MON 87708 soybean and MON 88701 cotton cropping systems for cotton and soybean may help to preserve gains in conservation tillage and benefit air quality in the short term. In the long term, selection of dicamba resistant weeds may result in similar aggressive tillage pract ice s that are expected to occur under the No Action Alternative and negate the benefits mentioned above.

Climate Change Under the No Action Alternative, there is a potential impact on climate change from inc reased herbicide use and more aggressive tillage regimes to control HR weeds, causing increased release of GHG from burning additional fossil fuels and soil disruption that releases sequestered carbon as GHGs. When considering the cumulative impact s of the Preferred Alternative, MON 87708 soybean and MON 88701 cotton cropping systems for cotton and soybean may help to preserve gains in conservation tillage and reduce GHG contributions to climate change in the short term. In the long term, selection of dicamba resistant weeds may result in similar aggressive tillage practice s that are expected to occur under the No Action and negate the benefits mentioned above

.
5.7 Cumulative Impacts

- Alternative 3

5.7.1 Agronomic Practices

Under Alternative 3, only MON 88701 cotton would no longer be subject to regulation by APHIS. MON 87708 soybean would continue to be regulated. Under this Alternative, supplementation of EPA’s regist ration for dicamba use on MON 88701 cotton , dicamba use is predicted to increase relative to the No Action Alternative (Appendix 4, Table 4

- 12), but is less than the increase expected under the Preferred Alternative.
194The increased use of dicamba may incre ase the selection of dicamba

- resistant weeds, which might increase the costs for weed control in cotton, sorghum, soybean, and fallow applications. The pressure for selecting dicamba

- resistant weeds is expected to be lower in Alternative 3 than Alternative 2 because dicamba

- resistant soybeans could not be commercially grown. Those regions where there is a higher percentage of cotton acre age and less of soybean will show less usage of dicamba and thus less likelihood of dicamba

- resistant weeds, especially un der Alternative 3 (Regions J, K, L). There would be one less tool for GR weeds in soybean if new formulations for MON 87708 soybean were not available for soybean applications, and under present management conditions, these GR weeds would potentially by m ore difficult to control.

5.7.2 Health and Safety Aspects for Livestock and Humans

No cumulative impact s from the changes in production practice s were identified on human health for any of the Alternatives. APHIS expects the EPA to implement appropriate label requiremen ts for registration of the M1691. The EPA considers the direct and indirect impacts from herbicide use on human health as part of their regul atory decision. Therefore, those impacts are outside the scope of this EIS.

5.7.3 Biological Resources

Depending on the adoption rate of MON 88701 cotton as well as the management practices employed by growers, there may be an increase in the selection of dicamba

- resistant weeds under Alternative 3 relative to the No Action Alternative. However, the selecti on of dicamba

resistant weeds is expected to be less than under the Preferred Alternative. An increased level of resistant weeds would result in need for additional herbicide applications for their control, which could have impacts by drift to vegetation i n the vicinity. Impacts on beneficial insects that typically may improve insect control on crops may be incurred because of the additional chemicals inadvertently applied to adjacent natural plants ( Egan et al. , 2014 )

. The EPA considers the direct and indirect impacts from herbicide use on non

- target organisms as part of their regulatory decisions. Therefore, those impacts are outside the scope of th is EIS. The EPA is analyzing the potential impacts of the proposed new uses of dicamba on the environment, including non

- target organisms. It is probable that the EPA will include label restrictions and requirements to limit off

- site transport of dicamba as has been done with the proposed registration of Enlist Duo ( US

- EPA, 2014a )

. APHIS expects the EPA to implement biologicall y and environmentally protective label requirements for registration of the M1691

.

5.7.4 Physical Environment

If conservation tillage practice s were to decrease, natural resources could be impacted. However, cotton growers still have se veral effective herbicide chemistries to control GR weeds, including atrazine and chloroacetamides. Consequently, under Alternative 3, tillage practices for cotton growers are not expected to differ compared to the No Action Alternative.

1955.8 Cumulative Impact s

- Alternative 4

5.8.1 Agronomic Practices

Under Alternative 4, MON 87708 soybean would be granted nonregulated status but MON 88701 cotton would continue to be regulated. If APHIS selects this Alternative and EPA approves the new use of dicamba on MON 87708 so ybean, Monsanto estimates an increase in dicamba use associated with adoption of MON 87708 soybean (at peak adoption of 40%) to 20.5 million (Table 4

- 9) or 5.4 times the dicamba use on all crops under the No Action Alternative (Appendix 4, Table 4

- 9). T he increased use of dicamba may increase the selection of dicamba

- resistant weeds which may eventually increase costs for weed control in cotton, sorghum, soybean, and fallow applications. APHIS expects the EPA to implement appropriate label requirements f or registration of the M1691 regarding weed resistance management. The pressure for selecting dicamba

- resistant weeds is expected to be lower in Alternative 4 than the Preferred Alternative. Those regions where soybean acres are high with respect to cotton (Regions E, F, G, I, see Table 21 ) would show less overall dicamba use (since dicamba would be used at minimal levels in cotton), and less likelihood for development of dicamba

- resistant weeds than in areas with high acreage of both cotton and soybean. Control of GR weeds in cotton would include herbicides other than dicamba, so less control over these weeds is a consequence of not having dicamba available for pre and post

- emergent treatment of these weeds.

Those regions where there is a higher percentage of cotton acres and less of soybean will show less usage of dicamba and thus less likelihood of dicamba

- resistant weeds, especially under Alternative 4 (Regions J, K, and L). No cumulative impact s we re identified on Human Health for any of the Alternatives.

5.8.2 Health and Safety Aspects for Livestock and Humans

No cumulative impact s were identified on human health or livestock for any of the Alternatives. EP A considers the direct and indirect impacts from herbicide use on human health and non

- target organisms as part of their regulatory decisions. Therefore, those impacts are outside the scope of this EIS.

5.8.3 Biological Resources

Depending on the adoption rate of MON 87708 soybean and the management practices used by growers, there may be an increase in the selection of dicamba

- resistant weeds under Alternative 4 relative to the No Action Alternative. The selection of dicamba

- resistant weeds is expected to be less than under the Preferred Alternative. An increased level of resistant weeds would result in the need for additional herbicide applications for their control, which could impact non

- target organisms in the vicinity. Impacts on benefi cial insects that typical may improve insect control on crops may be incurred because of the additional chemicals inadvertently applied to adjacent natural plants ( Egan et al. , 2014 )

. The EPA considers the direct and indirect impacts from herbicide use on non

- target organisms as part of their regulatory decisions. Therefore, those impacts are outside the scope of this EIS

. The EPA is analyzing the potential impacts of the

196proposed new uses of dicamba on the environment, including non

- target organisms. It is probabl e that the EPA will include label restrictions and requirements to limit off

- site transport of dicamba as has been done with the proposed registration of Enlist Duo ( US

- EPA, 2014a )

.

5.8.4 Physical Environment

If conservation tillage practice s were to decrease, natural resources could be impacted. Under the No Action Alternative, soy bean growers are expected to use less conservation tillage in areas where GR weeds are poorly controlled by herbicides. Under Alternative 4, weed control by dicamba is expected to be more effective in soybean than under the No Action Alternative. Therefore , conservation tillage practices are expected to be more widely practiced under Alternative 4 than under the No Action Alternative and natural resources are less likely to be adversely impacted.

197

### 6 OTHER IMPACTS AND M ITIGATION MEASURES

This section describes other potential impacts associated with the implementation of the Action Alternatives, including unavoidable impacts; short

- term versus long

- term productivity of the environment; and irreversible/irretrievable comm itment of resources. This section also describes potential impact mitigation measures, as applicable, beyond what is already built into the Alternatives.

6.1 Unavoidable Impacts

Unavoidable impacts are any adverse environmental effects which cannot be avoided should the proposal be implemented ( 40 CFR § 1502.16 ) . Herbicides represent a tool that allows for the economical production of cotton and soybeans. As long as herbicides are used to produce cotton and so ybean, weeds will develop resistance to the herbicides used. Under all four Alternatives, the selection of HR weeds is an unavoidable impact. Growers may mitigate the rate at which weeds develop resistance by adopting best management practices. APHIS does not have the authority to regulate grower management practices nor does APHIS have the authority to regulate herbicide use

.
6.2 Short Term Versus Long Term Effects

In the short term, growers who adopt MON 87708 soybean or MON 88701 cotton are likely to experience more efficient and less costly control of GR weeds. Adopters may be better able to maintain conservation tillage programs on their farms. Growers of non

- GE crops and other GE crops may experience a decline in the weed seed bank as overall weed control improves on neighboring farms.

Over the long term, as weeds develop resistance to dicamba or glufosinate, multiple resistance to these compounds and glyphosate, will likely reduce the efficiency of weed control. This will tend
to increase weed management costs. Some growers may need to use more aggressive tillage to control resistant weeds. Adoption of conventional tillage would be expected to result in greater soil erosion, loss of organic matter, soil compaction, and reduced mois ture holding capacity, as compared to conservation or reduced tillage methods. This would lead to an increase in potential sedimentation and turbidity in nearby surface waters during rain and irrigation events and adverse impacts to biol ogical resources. Non

- adopters and growers of non

- GE crops will again be impacted by weeds from neighboring farms. Growers of small cereal crops will experience greater weed control costs as alternatives to these herbicides are likely to be more costly.

6.3 Ir reversible Resource Commitments

Irreversible resource commitments represent a loss of future options. This applies primarily to the use of nonrenewable resources and to factors that are renewable only over long time spans, or to adverse impacts that cannot be reversed. An irretrievable commitment of resources represents opportunities that are lost for the period of the proposed action. It also includes the use of renewable resources, such as timber or human effort, as well as other utilization opportunities that are foregone in favor of the proposed action.

198No irreversible or irretrievable commitments of resources were identified with the Action Alternatives.

6.4 Mitigation Measures

As defined in the CEQ regulations for implementing NEPA ( 40 CFR § 1508.20 ) mitigation includes:

• avoiding the impact altogether by not taking a certain action or parts of an action;

• minimizing impacts by limiting the degree or magnitude of the action and its implementation;

• rectifying the impact by repairing, rehabili tating, or restoring the affected environment;

• reducing or eliminating the impact over time by preservation and maintenance operations during the life of the action; and

• compensating for the impact by replacing or providing substitute resources or environm ents.
APHIS does not have the authority to regulate types of management practices or use of herbicides. Nevertheless, mitigation can occur by a number of means. First growers may voluntarily adopt best practices recommended by weed experts. Second, any gro wer who uses either MON 87708 soybean or MON 88701 cotton will be expected to follow a stewardship agreement. APHIS assumes that there would be no binding enforcement mechanism to ensure that farmers follow the stewardship agreement but failure to do so could jeopardize a grower’s access to the technology.

Mitigation measures to oversee the proper use of herbicides are determined by the EPA and are disseminated to the herbicide use rs through EPA

- approved labels. Ad herence to herbicide label requirements, including application rates and techniques and following industry herbicide stewardship programs, will largely minimize improper herbicide usage. The extent of herbicide drift will be mitigated by the requirement to use dicamba and glufosinate by conditions on the label that will require nozzles that limit drift and restrictions on when and how the herbicide can be applied. State and local governments may also impose restrictions on when and how herbicides can be applied (see Appendix 7).

199

### 7 THREATENED AND ENDAN GERED SPECIES

The Endangered Species Act (ESA) of 1973, as amended, is one of the most far

- reaching wildlife conservation laws ever enacted by any nation. Congress passed the ESA to prevent extinctions facing many species of fish, wildlife and plants. The purpose of the ESA is to conserve endangered and threatened species (TES) and the ecosystems on which they depend as key components of America’s heritage. To implement the ESA, the U.S. Fish & Wildlife Service (USFWS) works in cooperation with the National Marine Fisheries Service (NMFS), other Federal, State, and local agencies, T ribes, non

- governmental organizations, and private citizens. Before a plant or animal species can receive the protection provided by the ESA, it must first be added to the Federal list of threatened and endangered wildlife and plants.

A species is added to the list when it is determined by the USFWS/NMFS to be endangered or threatened because of any of the following factors:

• The present or threatened destruction, modification, or curtailment of its habitat or range;

• Overutilization for commercial, recreatio nal, scientific, or educational purposes;

• Disease or predation ;

• The inadequacy of existing regulatory mechanisms; and

• The natural or manmade factors affecting its survival.

Once an animal or plant is added to the list, protective measures apply to the spec ies and its habitat. These measures include protection from adverse effects of federal activities.

7.1 Requirements for Federal Agencies

Federal Section 7 (a)(2) of the ESA requires that federal agencies, in consultation with USFWS and/or the NMFS, ensure that any action they authorize, fund, or carry out is “not likely to jeopardize the continued existence of a listed species or result in the destruction or adverse modification of designated critical habitat .” It is the responsibil ity of the federal agency taking the action to assess the effects of their action and to consult with the USFWS and NMFS if it is determined that the action “may affect” listed species or designated critical habitat. To facilitate their ESA consultation re quirements, APHIS met with the USFWS from 1999 to 2003 to discuss factors relevant to APHIS’ regulatory authority and effects analysis for petitions for nonregulated status and developed a process for conducting an effects determination consistent with the Plant Protection Act (PPA) of 2000 (Title IV of Public Law 106

- 224). APHIS uses this process to help fulfill its obligations and responsibilities under Section 7 of the ESA for biotechnology regulatory actions.

APHIS met with USFWS officials on June 15, 2 011, to discuss whether APHIS has any obligations under the ESA regarding analyzing the effects of pesticide use assoc iated with all GE crops on TES. As a result of these joint discussions, USFWS and APHIS have agreed that it is not necessary for APHIS to perform an ESA effects analysis on pesticide use associated with GE crops currently planted because the EPA has both regulatory authority over the labeling of pesticides and the necessary technical expertise to assess pesticide effects on the environment

u nder FIFRA

. APHIS has no statutory authority to authorize or regulate the use of dicamba,

200glufosinate, or any other herbicide, by cotton and soybean growers. Under APHIS’ current Part 340 regulatio ns, APHIS only has the authority to regulate MON 87708 soybean and MON 88701 cotton or any GE organism as long as APHIS believes they may pose a p lant pest risk (7 CFR § 340.1). APHIS has no regulatory jurisdiction over any other risks associated with GE organisms including risks resulting from the use of herbicides or other pesticides on those organisms.

After completing a plant pest risk analysis, if APHIS determines that MON 87708 soybean and MON 88701 cotton seeds , plants, or parts thereof is not likely to pose a plant pest risk, then these articles would no longer be subject to the plant pest provisions of the PPA or to the regulatory requirements of 7 CFR Part 340, and therefore, APHIS must reach a determination that these

ar ticles are no longer regulated. As part of its analysis, APHIS considered the potential effects of MON 87708 soybean and MON 88701 cotton on the environment including, as required by the ESA, any potential effects to threatened and endangered species and critical habitat . As part of this process, APHIS thoroughly reviews the GE product information and data related to the organism (generally a plant species, but m ay also be other GE organisms). For each transgene/transgenic plant, APHIS considers the following:

• A review of the biology and taxonomy of the crop plant and its sexually compatible relatives;

• Characterization of each transgene with respect to its structure and function and the
nature of the organism from which it was obtained;

• A determination of where the new transgene and its products (if any) are produced in the plant and their quantity;

• A review of the agronomic performance of the plant, including disease and pest susceptibilities, weediness potential, and agronomic and environmental impacts;

• Determination of the concentrations of known plant toxicants (if any are known in the plant);

• Analysis to determine if the transgenic plant is sexually compatible with any TES of plants or a host of any TES; and

• Any other information that may inform the potential for an organism to pose a plant pest risk.

7.2 Potential Effects of MON 88701 Cotton and MON 87708 Soybean on TES

In following this review process, APH IS, as described below, has evaluated the potential effects that a determination of nonregulated status of MON 87708 soybean and MON 88701 cotton may have, if any, on federally

- listed TES species and species proposed for listing, as well as designated crit ical habitat and ha bitat proposed for designation. Based upon the scope of the EIS and production areas identified in the Affected Environment section of the EIS, APHIS reviewed the USFWS list of TES species (listed and proposed) f or each state where soybean and cotton are commercially produced ( USFW S, 2014a ; 2014b )

. Prior to this review, APHIS considered the potential for MON 87708 soybean and MON 88 701 cotton to extend the range of soybean production and also the potential to extend agricultural
pro duction into new natural areas. APHIS has determined that agronomic characteristics and cultivation practice s required for M ON 87708 soybean and MON 88701 cotton are essentially 201indistinguishable from practices used to grow other cotton and soybean varieties, including other herbicide

- resistant varieties ( Monsanto, 2012a ; 2012b ; 2013a ; USDA

- APHIS, 2014d ; 2014e )

. Although MON 87708 soybean and MON 88701cotton may be expected to replace other varieties of cotton and soybean curre ntly cultivated, APHIS does not expect the cultivation of these to result in new cotton or soybean acres to be planted in areas that are not already devoted to agriculture. Accordingly, the issues discussed herein focus on the potential environmental

conse quences of the determination of nonregulated status of MON 87708 soybean and MON 88701 cotton on TES species in the areas where cotton and soybean are currently grown.

For its analysis on TES plants and critical habitat , APHIS focused on the agronomic differences between the regulated articles and cotton and soybean varieties currently grown; the potential for increased weediness ; and the potential for gene movement to native plan ts, listed species, and species proposed for listing.

For its analysis of effects on TES animals, APHIS focused on the implications of exposure to the novel proteins expressed in the plants ( Table 30 ) as a result of the transformation, and the ability of the plants to serve as a host for a TES.

Table 30

. Novel P roteins A ssociated with M ON 87708 S oybean and MON 88701 Cotton

. Regulated Article Protein Phenotypic Effects

MON 87708 soybean dicamba mono

- oxygenase (DMO) Resistance to the h e rbi c ide d icamba (3,6

- dichloro

- 2

- methoxybenzoic acid)

.

MON 88701 cotton dicamba mono

- oxygenase (DMO) Resistance to the h e rbi c ide d icamba (3,6

- dichloro

- 2

- methoxybenzoic acid)

. phosphinothricin acetyltransferase (PAT) Resistance to glufosinate

Source: ( Monsanto, 2012a ; 2012b )

7.2.1 Potential Effects of MON 88701 Cotton on TES Plant Species

Upland cotton ( G. hirsutum ) possesses few of the characteristics common to plants that are successful weeds ( Baker, 1965 ; Keeler, 1989 ) and is not considered to be a serious or common weed in the U.S . It is not listed as a weed in the major weed references ( Muenscher, 1939 ; Crockett, 1977 ; Holm et al. , 1979 ) , nor is it present on Federal or State lists of noxious weed species ( USDA

- APHIS, 2012 ; USDA

- NRCS, 2012a ) . Modern Upland cotton is a domest icated perennial grown as an annual crop that is not generally persistent in unmanaged or undisturbed environments without human intervention. Modern cultivars are not frost tolerant and do not survive freezing winter conditions, do not produce abundant or long

- lived seeds that can persist or lie dormant in soil, do not exhibit vegetative propagation or rapid vegetative growth, and do not compete effectively with other cultivated plants ( OECD, 2008a ) . In areas where winter temperatures are mild and freezing does not occur, cotton plants can occur as vo lunteers in the

202following growing season. These volunteers can be easily controlled by herbicides or mechanical means. Excepting dicamba and glufosinate, MON 88701 is expected to be sensitive to the same herbicides as other cotton varieties ( USDA

- APHIS, 2014d ) . Cotton can become locally feral or naturalized in suitable areas, such as southern Florida, Hawaii, and Pu erto Rico ( Fryxell 1984 ; Coile and Garland, 2003 ; Wunderlin and Hansen, 2008 ; USDA

- NRCS, 2012c )

. The agronomic and morphologic characteristics data provided by Monsanto were used in the APHIS analysis of the weediness potential for MON 88701 cotton, and evaluated for the potential to i mpact TES and critical habitat

. Agronomic studies conducted by Monsanto tested the hypothesis that the weediness potential of MON 88701 cotton is unchanged with respect to conventional cotton ( Monsanto, 2012b ; 2013a ) . Monsanto collected agronomic data relevant to weedy traits such as plant vigor and height and seed yield from field experiments conducted in two studies at a total of 15 (Study 1) and 11 (Study 2) locations across the U.S. during the 2010 growing season ( Monsanto, 2012b ) . All locations in Study 2 were also included in Study 1. Data were collected for control Coker 130 cotton and MON 88701 cotton, as well as for MON 88701 cotton treated with the herbicides glufosinate (0.5 lb a.i./acre at the 3

– 5 leaf stage) and dicamba (0.5 lb a.e./acre at the 6

- 10 leaf stage) to allow for assessment of MON 88701 under the agronomic system that it is expected to be used ( Monsanto, 2012b ) . Data were also co llected for 11 (Study 1) and eight (Study 2) commercial reference varieties (four varieties grown per site) to establish statistical tolerance intervals for the various traits assessed ( Monsanto, 2012b )

. Plant vigor was assessed qualitatively. No differences in vigor were observed between MON 88701 cotton and the Coker 130 control at 14 and 30 days after planting for 73 out of 74 comparisons across all sites and treatments. At one site, MON 88701 cotton plants were slightly less vigorous than Coker 130 at 30 days after planting, but were within the range of vigor ratings of the commercial reference v arieties ( Monsanto, 2012b ) . Other agronomic dat a were assessed quantitatively. In the combined

- site analysis, no statistically significant (p < 0.05) differences were observed between MON 88701 cotton and the Coker 130 control for stand count at 14 and 30 days after planting, final stand count, seed cotton yield, number of immature seeds per boll, b oll weight, or a variety of fiber characteristics ( Monsanto, 2012b ) . In both studies, whether

u ntreated or herbicide treated, MON 88701 cotton plants were shorter than Coker 130 control plants, took slightly longer to mature, produced more but smaller seed, and had a slightly increased fiber strength ( Monsanto, 2012b ) . These differences were all small and in all cases the mean values for these characteristics were within the range observed fo r the commercial reference varieties ( Monsanto, 2012b ) . Changes in disease or insect pest susceptibility or in response to abiotic stress were not observed in MON 88701 cotton relative to the control ( Monsanto, 2012b )

. In summary, no differences were detected between MON 88701 cotton and non

- transgenic cotton in growth, reproduction, or interactions with pests and diseases, other than the intended effect of resistance to the two herbicid es ( Monsanto, 2012b ; USDA

- APHIS, 2014d )

. As part of its analysis of effects on species and habitat, APHIS evaluated the potential of MON 88701 cotto n to cross with wild relatives. C ultivated G. barbadense (Pima or Egyptian cotton), is grown in Arizona, California, New Me xico, and Texas ( Pleasants and We ndell, 2005b ; USDA

NASS, 2012e )

. Naturalized populations of G. barbadense grow in Puerto Rico, the Virgin

203Islands and most of the major Hawaiian Islands ( Fryxell 1984 ; Bates, 1990 ; USDA

- NRCS, 2012b ) . Two wild species of cotton are native to the U.S.

, G. thurberi and G. tomentosum , and grow in Arizona and Hawaii respectively ( Fryxell 1984 ; USDA

- NRCS, 2012b )

. G. hirsutum is tetraploid and thus effect ively incompatible with diploid species such as G. thurberi. Plants from these two groups do not normally hybridize spontaneously and produce fertile offspring, and experimental crosses are difficult ( OECD, 2008a )

. In contrast, G. hirsutum is sexually compatible with the tetraploids G. barbadense (cultivated Pima or Egyptian cotton) and G.
tomentosum and can form viable and fertile progeny with both species ( Brubaker CL et al. , 1993 ; Saha et al. , 2006 ; OECD, 2008a ) . Thus, unassisted outcrossing and gene introgression could potentially occur in areas where these species are co

- located ( USDA

- APHIS, 2014d )

. For transgene introgression from MON 88701 cotton to occur there would have to be spatial proximity between MON 88701 cotton and the recipient variety or species; overlap in their flowering period; and because cotton is insect pollinated, they must share s imilar pollinators ( Pleasants and Wendell, 2005b ) . Published studies report that there has been relatively little gene introgression from G. hirsutum into native or naturalized G. barb adense in Mesoamerica and the Caribbean, despite the fact that G. barbadense has been grown in the presence of the predominant G. hirsutum since prehistoric times ( Wendel et al. , 1992 ; Brubaker CL et al. , 1993 )

. In contrast, introgression from G. barbadense to native or naturalized G . hirsutum in these areas has been relatively common ( Wendel et al. , 1992 ; Brubaker CL et al. , 1993 ) . Various mechanisms have been suggested to account for this difference ( Percy and Wendel, 1990 ; Brubaker CL et al. , 1993 ; Jiang et al. , 2000 ; OGTR, 2008 ) . While none of these mechanisms leads to complete isolation between the two species, the reported asymmetry in gene flow suggests that gene introgression from cultivated G. hirsutum varieties such as MON 88701 to native or naturalized G. barbadense should be rare ( USDA

- APHIS, 2014d )

. Natural populations of G. tomentosum are found on all Hawaiian I slands except Kauai and Hawaii. Populations are located on the drier, leeward coastal plains of the islands at low elevations, which are also the areas t hat are primarily used for agriculture ( Pleasants and Wendell, 2005b ) . As discussed further in the PPRA , there is overlap in the timing of flowering (both seasonally and time of day), and potential pollinators with G. hirsutum ( USDA

- APHIS, 2014d ) . However, G. hirsutum has not been grown as an agricultural commodity in Hawaii for decades, and, seed companies no longer use the Hawaiian Islands as a winter nursery for cotton ( Grace, 2012 ; USDA

- APHIS, 2014d ) . Even if gene introgression into wild relatives were to
occur, e xpression of the DMO and PAT proteins does not cause any major changes in the phenotype of cotton plants other than to confer resistance to the herbicides di camba and glufosinate ( Monsanto, 2012b ; USDA

- APHIS, 2014d ) . In the absence of treatment with these herbicides, the transgenic material in MON 88701 is unlikely to confer a selective advantage on any hybrid progeny that may result from outcrossing ( USDA

- APHIS, 2014d )

. None of the relatives of cotton are Federally listed (or proposed) as endangered or threatened species ( USFWS, 2014c ) . In Florida wild populations of upland cotton, G. hirsutum have been listed as endangered by the state ( Coile and Garland, 2003 ) . However, wild G. hirsutum is not
pr esent in the northwestern panhandle where cotton cultivation occurs, and cultivation of cotton is prohibited by the EPA in those areas of southern Florida where it is found ( US

- EPA, 2001 ; Coile and Garland, 2003 ; Wunderlin and Hansen, 2008 ) . Thus, outcrossing from MON 88701

204cotton to naturalized G. hirsutum in Florida is highly unlikely. Accordingly, a determination of nonregulated status of MON 88701 cotton is not expected to impa ct state endangered feral cotton populations.

Based on agronomic field data, literature surveyed on cotton weediness potential, the bi ology of cotton, and no sexual compatibility of TES with cotton in areas where cotton is commercially
gr own, APHIS has concluded that MON 88701 cotton will have no effect on threatened or endangered plant species or on critical habitat

7.2.2 Potential Effects of MON 88701 Cotton on TES Animal Species

Threatened and endangered animal species that may be exposed to the gene products in MON 88701 cotton would be those TES that inhabit cotton fields and feed on MON 88701 cotton. To identify potential effects on threatened and endangered animal species, APHIS evaluated the risks to threate ned and endangered animals from consuming MON 88701 cotton.
Cotton plants contain the anti

- nutrient g ossypol that plays a role in defense of cotton against insect pests ( Chan et al. , 1978 ; Kong et al. , 2010 )

. Gossypol is a yellow polyp henolic pigment found in the cotton plant and in the small pigment glands in the seed ( Ely and Guthrie, 2012 )

. Studies indicate that on cotton bollworm ( Helicoverpa armige ra ) higher levels of gossypol were fatal although lower levels were found to be beneficial to growth ( Paz Celorio

- Mancera et al.

, 2011 )

. G ossypol is harmful to monogastrics such as chickens, swine, and young ruminants ( Ely and Guthrie, 2012 )

. This defense seems to have little effect in reducing feeding by adult ruminants. In the North Carolina, 92 % of cotton growers surveyed reported damage from white

tailed deer ( North Carolina Department of Agriculture and Consumer Services, 2010 )

. Whole cottonseed is often used by deer managers as a supplemental feed because it is cheaper than
pro tein pellets and feral hogs and raccoons will not consume it ( DeYou ng, 2005 ; Taylor et al.

, 2013 ) . When doing so, managers generally stop feeding in June to allow time for plasma gossypol levels to reduce prior to entering the breeding season. Although feeding studie s of whole cottonseed to whitetails is lacking, there is a general belief that feeding high concentrations, especially during breeding season, may reduce breeding success ( Bullock et al.

, 2010 ) . Studies on European red deer indicate that bucks fed whole cottonseed had negative response in regard to body weight and antler growth ( Brown et al. , 2002 ) . In studies of fallow deer, feeding whole cottonseed to bucks resulted in decreased body weight, body condition score, antler growth, and plasma testosterone conce ntration ( Mapel, 2004 )

. Whole cottonseed is commonly used as a supplemental protein f eed for cattle ( Ely and Guthrie, 2012 )

. However, care must be taken to not overfeed because of the possib ility of gossypol toxicity. If fed too much whole cottonseed, even mature dairy cows have been known to become ill and fatalities have occurred when it was the sole diet ( Ely and Guthrie, 2012 )

. Other domestic ruminants such as goats have also shown negative effects from consumption of whole cottonseed feed. However, some of the detrimental effects were attributed to the increased dietary intake of ether extract and neutral detergent fiber rather than gossypol ( Luginbuhl et al. , 2000 ) . One study indicated that whole cottonseed introduced as 15 % of the diet to Nubian buck kids had positive results in growth, but at 30 %

205had increased r ed blood cell fragility and reduced reproductive pe rformance ( Solaiman, 2007 )

. Perhaps partly because of the toxic effects of gossypol in cotton plants, especially in non

ruminants, information on wildlife depredation of cotton other than whitetail deer is lacking. However, wildlife may use cotton fields as a food source, consuming the insects that live on and among the plants. Quall and some other birds are known to nest i n grassy strips on the edge of cotton fields and will enter the fields to obtain food or grit ( Palmer and Bromley, NoDate )

. However, TES generally are found outside of agricultu ral fields in natural settings. Few if any TES are likely to use cotton fields because they d o not provide suitable habitat. Only whooping crane ( Grus americana ), sandhill crane ( Grus canadensis pulla ), piping plover ( Charadrius melodus ), interior least tern ( Sterna antillarum ), and Sprague’s pipit ( Anthus spragueii; a candidate species ) occasionally feed in farmed sites ( USFWS, 2011 )

. T hese bird species may visit cotton fields during migratory periods, but would not be present during normal farming operations ( Krapu et al. , 2004 ; USFWS, 2011 )

. Monsanto has presented information comparing the compositional elements of MON 88701 cotton variety with conventional varieties and evaluating the differences between varieties with and without herbicide applications ( Monsanto, 2012b ) . The samples for compositional

asses sment were collected from eight locations in 2010, chosen to represent typical cotton growing regions of the U.S. , and compared to a control variety, Coker 130 ( Monsanto, 2012b )

. Analytes were assessed quantitatively and included 47 nutrients (proximates, fiber, amino acids, fatty acids, minerals, and vitamin E) and five anti

- nut rients (fatty acids, gossypol). Statistically significant (p <0.05) differences in the combined

- site nutrient levels were observed for 16 nutrients in both herbicide treated and untreated MON 88701 cotton compared to the Coker 130 control: the proximates ash, calories, carboh ydrates, moisture, and total fat; acid detergent fiber, neutral detergent fiber, total dietary fiber; the amino acid arginine; the fatty acid 14:0 myristic acid; the minerals calcium, magnesium, manganese, pota ssium, and zinc; and vitamin E. Three addition al nutrients were statistically significantly different in herbicide treated MON 88701 cotton only (the amino acids methionine and proline, and the fatty acid 18:2 linoleic acid), while one additional nutrient was statistically significantly different in u ntreated MON 88701 cotton only (crude fiber) ( Monsanto, 2012b )

. With the exception of calcium (increased 14 % and 15 % relative to control in treated and untreated MON 88701 cotton respectively), all differences in

nu trient levels were 10 % or less. In addition, most of the statistically significant differences in nutrie nt levels were not consistently observed across locations, with the exception of calcium (statistically significant differences observed in seven of eight locations), ash (statistically significant differences observed at six (treated) and four (untreated) locations), 18:0 stearic acid (statistically significant differences observed at five locations), and manganese (statistically significant differences observed at five locations for untreated MON 88701 cotton only) ( Monsanto, 2012b ) . However, in all of these cases, the mean levels of all nutrients in MON 88701 cotton were within the 99 % tolerance i nterval established from the conventional commercial reference varieties ( International

- Life

- Sciences

- Institute, 2010 )

. While the mean level of methionine in herbicide treated (but not untreated) MON 88701 were slightly outside of the 99 % tolerance interval, the mean increase in methionine was less than 5 % . The increase was not consistently observed across locations (a statistically significant difference was observed at

2 06only one of the eight locations), and the mean level of methionine was within the natural variation observed for commercial cotton varieties ( International

- Life

- Sciences

- Institute, 2010 )

.
Stati stically significant (p <0.05) increases in combined

- site anti

- nutrient levels were observed for two anti

- nutrients in both herbicide treated and untreated MON 88701 cotton: the cyclopropenoid dihydrosterculic acid and total gossypol. In addition, a statis tically significant increase in free gossypol was observed in treated MON 88701 cotton. The increase was less than 10 % in all cases except dihydrosterculic acid in untreated MON 88701 cotton, which increased 12.6 % ( Monsanto, 2012b ) . The increases were not consistently observed across locations and the anti

- nutrient levels were all within the 99 % tol erance interval established from the conventional commercial reference varieties ( International

- Life

- Sciences

- Institute, 2010 )

.
The statistically significant changes observed for th e above

- mentioned nutrients and anti

nutrients are unlikely to make MON 88701 cotton more susceptible to pests and diseases, or to cause MON 88701 cotton to have a greater impact on non

- target organisms, than existing cotton varieties ( USDA

- APHIS, 2014e ) . The disease, insect pest, arthropod abundance, and agronomic data presented for MON 88701 cotton did not indicate any statistically significant difference from the control variety ( Monsanto, 2012b )

.
Monsanto used a multistep approach to characterize the novel DMO protein in MON 88701 cotton to determine if DMO is safe for human and animal consumption. It was found that MON 88701 cotton DMO has no relevant amino acid sequence similarities with known allergens, gliad ins, glutenins, toxins, and other biologically active proteins that may have adverse effects on mammals ( Monsanto, 2013a )

. The DMO protein was rapidly degraded in simulated gastric and intestinal fluids and a high dose of this protein in a mouse acute oral toxicity evaluation demonstrated it is not acutely toxic, a nd does not cause any adverse effect ( Monsanto, 2013a )

. The DMO enzyme present in MON 88701 cotton has sequence similarity and many catalytic and domain structural similarities with a wide variety of oxygenases found in numerous species of microorganisms widely distributed and prevalent in the environment ( Chakraborty J et al. , 2012 )

. It also has similarity with oxygenases such as pheophorbide A oxygenase which are found in plants such as rice, maize, canola and pea ( Rodoni et al. , 1997 ; Yang M et al. , 2004 ) that are consumed in a variety of food and feed sources which have a history of safe human consumption. Plants, animals and humans are extensively exposed to these types of enzymes ( Monsanto, 2012b )

. The PPRA , Petition, and the petitioner’s Environmental Report all support the conclusion that exposure to MON 88701 cotton DMO poses no meaningful risk to the environment, or human and animal health ( Monsanto, 2012b ; 2013a ; USDA

- APHIS, 2014e )

. The PAT enzyme present in MON 88701 cotton is identical to the wild

- type protein produced in S. hygroscopicus and is analogous to the PAT proteins in commercially available glufosinate

resistant products in several crops including cotton, corn, soybean, and canola ( USDA

- APHIS, 2014f )

. OECD recognizes PAT proteins produced from different genes to be equivalent with regard to function and safety ( OECD, 1999 ) . PAT proteins are structurally similar only to other acetyltransferases known to not cause adverse effects after consumption ( Herouet et al. , 2005 )

. In 1997, a tolerance exemption was issued for PAT proteins by the EPA ( 40 CFR part 180, 1997 ; CFR Part 18 0.1151, 2005 )

.

207On April 6, 2012, Monsanto submitted a safety and nutritional assessment summary document to the FDA to initiate a consultation on the food and feed safety and compositional assessment of MON 88701 cotton. Monsanto r eceived a completed consultation letter from the FDA on April 24, 2013 ( US

- FDA, 2013 )

. FDA concluded: “food and feed derived from MON 8870 1 cotton are not materially different in composition, safety, and other relevant parameters from cottonseed

derived food and feed currently on the market, and that GE MON 88701 cotton does not raise issues that would require premarket review or ap proval by FDA ( US

- FDA, 2013 ) .” All indications are that the ingestion of the plant or plant parts is unlikely to affect thr eatened and endangered species

. T here is no allergenicity potential with MON 88701 cotton , and the slight increase in levels of gossypol in MON 88701 cotton is statistically insignificant. Therefore, there is no increased risk of direct or indirect tox icity or allergenicity impacts on animal species that feed on cotton or the associated biological food chain of organisms. B ased on these analyses, APHIS concludes that, although unlikely, consumption of MON 88701 cotton would have no effect on any listed threatened or endangered animal species or animal species proposed for listing.

APHIS considered the possibility that MON 88701 cotton could serve a host plant for a threatened or endangered species (i.e.

, a listed insect or othe r organism that may use the cotton plant to complete its lifecycle) . A review of the species list reveals that there are none that would use cotton as a host plant ( USFWS, 2014b )

.

7.2.3 Summary of Potential Effects of MON 88701 Cotton on TES Sp ecies

After reviewing the possible effects of allowing the environmental release of MON 88701
cotton , APHIS has not identified any stressor that could affect the reproduction, numbers, or distribution of a listed TES or species proposed for listing. As a r esult, a detailed exposure analysis for individual species is not necessary. APHIS also considered the potential effect of a determination of nonregulated status of MON 88701 cotton on designated critical habitat or habitat propose d for designation, and could identify no differences from effects that would occur from the production of other cotton varieties. Cotton is not considered a particularly competitive plant species and has been selected for domestication and cultivation unde r conditions not normally found in natural settings. Cotton is not sexually compatible with, nor does it serve as a host plant for any listed species or species proposed for listing. Consumption of MON 88701 cotton by any listed species or species proposed for listing will not result in an allergic reaction or increase the risk of a toxic reaction. Based on these factors, APHIS ha s concluded that a determination of nonregulated status of MON 88701 cotton, and the corresponding environmental release of this cotton variety will have no effect on listed species or species proposed for listing, and would not affect designated habitat o r habitat proposed for designation. Because of this no

- effect determination, consultation under Section 7(a)(2) of the Act or the concurrence of the USFWS or NMFS is not required.

7.2.4 Potential Effects of MON 87708 Soybean on TES Plant Species

Soybean has been cultivated around the globe without any report that it is a serious weed or that it forms persistent feral pop ulations ( OECD, 2000 )

. Soybean does not possess any of the attributes commonly associated with weeds ( Baker, 1965 ) , such as long pers istence of seed in the

208soil ; the ability to disperse, invade, and become a dominant speci es in new or diverse landscapes; or the ability to compete well with native vegetation. Furthermore, mature soybean seeds have no innate dormancy; germinating seedlin gs and plants are sensitive to cold, are not expected to survive in freezing winter conditions and do not vegetatively reproduce ( Raper and Kramer, 1987 ; OECD, 2000 ) . Soyb eans that volunteer from the previous year’s crop are rarely a management issue, as crop losses attributable to interference from soybean volunteers are minimal ( Owen and Zelaya, 2005 ) . However, volunteers can be a problem particularly in the South where win ters are milder, and particularly if weather events lead to soybean seed loss prior to harvest ( York et al. , 2005 )

. The agronomic and morphologic characteristics data provided by Monsanto were used in the APHIS analysis of the weediness p otential for MON 87708 soybean. Agronomic studies conducted by Monsanto tested the hypothesis that the weediness potential of MON 87708 soybean is unchanged with respect to conventional soybean ( Monsanto, 2013a ) . No differences were detected between MON 87708 soybean and nontransgenic soybean in growth, reproduction, or interactions with pests a nd diseases, other than the intended effect of herbicide resistance to dicamba ( Monsanto, 2013a ) . MON 87708 also has slightly increased resistance/reduced sensitivity to three other phenoxy synthetic herbicides compared to the conventional control soybean A3525 ( USDA

- APHIS, 2014d ) . This increased resistance is not expected to substantially affect control of MON 8770 8 soybean volunteers. Excellent ratings are obtained for pos t

- emergence control of volunteer soybean s in the rotational crops corn, sorghum, wheat, barley, oats, cotton and rice for one or more labeled herbicides with different modes of action than the synthetic auxins to which MON 87708 has acquired complete or partial resistance ( Monsanto, 2012a )

. Based on analysis of the information provided by Monsanto, along with knowledge of soybean biology, APHIS has concluded that the expression of the DMO protein providing the herbicide resistance traits in MON 8770 8 soybean is unlikely to appreciably improve seedling establishment or increase weediness potential ( Monsanto, 2012 a ; 2013a )

. APHIS has concluded that the approval of a petition of nonregulated status for MON 8770 8 soybean does not present a risk of weediness when compared to other currently cultivated soybean varieties ( USDA

- A PHIS, 2014d )

. APHIS evaluated the potential of MON 87708 soybean to cross with listed species. APHIS has determined that there is no risk to unrelated plant species from the cu ltivation of MON 87708 soybean. Soybean is highly self

- pollinating and can on ly cross with other members of Glycine subgenus Soja ( OECD, 2000 )

. Wild soybean species are e ndemic in China, Korea, Japan, Taiwan and the former Union of Soviet Socialist Republics ; in the U.S. there are no Glycine species found outside of cultivation and there is no potential for outcrossing ( OECD, 2000 )

. After reviewing the list of threatened and endangered plant species in the U.S. where soybean is grown, APHIS determined that MON 877 08 soybean would not be sexually compatible with any listed threatened or endangered plant species proposed for listing, as none of these listed plants are in the same genus nor are known to cross pollinate with species of the genus Glycine ( USFWS, 2014c )

.

209Based on agronomic field data, literature surveyed on soybean weediness potential, lack of ability to disperse outside of agricultural fields, and no sexually compatibility with wild relatives or listed plants with soybean, APHIS has co ncluded that MON 87708 soybean will have no effect on threatened or endangered plant species or critical habitat

.

7.2.5 Potential Effects of MON 87708 Soybean on TES Animal Species

Threatened and endangered animal species that may be exp osed to the gene products in MON 87708 soybean would be those TES that inhabit soybean fields and feed on MON 87708 soybean. To identify potential effects on threatened and endangered animal species, APHIS evaluated the risks from consuming MON 87708 soybe an.
Soybean is commonly used as a feed for livestock. Additionally, wildlife may use soybean fields as a food source, consuming the plant or insects that live on the plants, although, TES generally are found outside of agricultural fields. Few if any TES a re likely to use soybean fields because they do not provide suitable habitat. Only whooping crane ( Grus americana ), sandhill crane ( Grus canadensis pulla ), piping plover ( Charadrius melodus ), interior least tern ( Sterna antillarum ), and Sprague’s pipit ( An thus spragueii; a candidate species ) occasionally feed in farmed sites ( USFWS, 2011 )

. These bird species may visit soybean fields during migratory periods, but would not be present during normal farming operations ( Krapu et al. , 2004 ; USFWS, 2011 ) . In a study of soybean consumption by wildlife in Nebraska, results indicated that soybeans do not provide the high energy food source needed by cranes and waterfowl ( Krapu et al. , 2004 )

. The Delmarva fox squirrel ( Sciurus niger cinereus ), which inhabits mature forests of mixed hardwoods an d pines, may be found adjacent to agricultural ar eas of the Delmarva Peninsula ( USFWS, 2008 ) . The squirrel forages for food in woodlots and openings, such as farm fields, with a diet that mainly includes acorns, nuts/seeds of hickory, beech, wa lnut, and loblolly pine. They also feed on tree buds and flowers, fungi, insects, fruit, and seeds in the spring and mature, green pine cones in the summer and early fall ( USFWS, 2008 ) . The Louis iana black bear (Ursus americanus luteolus), occurring in Louisiana, Mississippi, and Texas, may occasionally forage on soybean; however, other crops such as corn, sugarcane, and winter wheat are preferred by the species ( Mississippi State University Extension Service, 1996 )

.
APHIS has examined data on the food and feed safety of MON 87708 soybean, evaluating the agronomic and morphological characteristics, including compositional and nutritional characteristics, safety evaluations and toxicity tests, as compared to a conventional hybrid soybean variety grown at multiple sites ( Monsanto, 2012a ; 2013a )

. Nutrients assessed in this analysis included proximates (ash, carbohydrates by calculation, moisture, protein, and fat), fiber, amino acids (18 components), fatty acids (FA, C8

- C22), and vitamin E (α

- tochopherol) in seed, and proximates (a sh, carbohydrates by calculation, moisture, protein , and fat) and fiber in forage

. The anti

- nutrients assessed in seed included raffinose, stachyose, lectin, phytic acid, trypsin inhibitors, and isoflavones (daidzein, genistein, and glycitei n) ( Monsanto, 2013a )

. The results confirmed that the differe nces observed in the analysis were not meaningful to food and feed safety or the nutritional quality of MON 877 08 soybean ( Monsanto, 2013a )

. In addition, the levels of assessed components in MON 87708 soybean were compositionally equivalent to the

210conventional control and within the range of variability of the comm ercial reference varieties that were grown concurrently in the same f ield trial ( Monsanto, 2013a )

. This indicates that the only statistically significant compositional difference between MON 87708 soybean and conventional hybrid soybean is the expression of the DMO proteins.

Monsanto used a multistep approach to characterize the novel DMO proteins in MON 87708 soybean to determine if DMO is safe for human and animal consumption. It was found that MON 87708 soybean DMO has no relevant amino acid sequence similarities with known allergens, gliadins, glutenins, toxin s, and other biologically active proteins that may have adverse effects o n mammals ( Monsanto, 2013a )

. MON 87708 soybean DMO was rapidly degraded in simulated gastric and intestinal fluids and a high dose of this protein in a mouse acute oral toxicity evaluation demonstrated that it is not acutely toxic, and does no t cause any adv erse effect ( Monsanto, 2013a )

. The safety ass essment supports the conclusion that exposure to MON 87708 soybean DMO poses no meaningful risk to the environment, or human and animal health.

On November 9, 2010 Monsanto submitted a safety and nutritional assessment summary document to the FDA to initia te a consultation on the food and feed safety and compositional assessment of MON 87708 soybean ( Monsanto, 2012a ) . Monsanto received a completed consultation letter from the FDA on October 11, 2011 ( US

- FDA, 2011b )

. FDA concluded: “food and feed derived from MON 87708 soybean are not materially different in composition, safety, and other relevant parameters from soybean

- derived food and feed currently on the market, a nd that the GE MON 87708 soybean do not raise issues that would require premarket review or approval by FDA ” ( US

- FDA, 2011b ) . Therefore, the ingestion of the plant or plant parts is unlikely to affect thr eatened and endangered species

. Because there is no toxicity or allergenicity potential with MON 87708 soybean , there would be no direct or indirect toxicity or allergenicity impacts on animal species that feed on soybean or the associated biological food chain of organisms. Therefore, based on these analyses, APHIS concludes that, although unlikely,

consu mption of MON 87708 soybean would have no effect on any listed threatened or endangered animal species or animal species proposed for listing.

APHIS considered the possibility that MON 87708 soybean could serve as a host plant for a threatened or endangere d species (i.e., a listed insect or other organism that may use the soybean plant to complete its lifecycle) . A review of the species list reveals that there are no members of the genus Glycine that serve as a host plant for any threatened or endangered species ( USFWS, 2014c )

. Combining the above information, cultivation of MON 87708 soybean and their progeny are expected to have no effect on threatened or endangered animals or those proposed for listing.

7.2.6 Summary of Potential Eff ects of MON 87708 Soybean on TES

After reviewing the possible effects of allowing the environmental release of MON 87708 soybean, APHIS has not identified any stressor that could affect the reproduction, numbers, or distribution of a listed TES o r sp ecies proposed for listing. APHIS also considered the potential effect of a determination of nonregulated status of MON 87708 soybean on designated critical habitat or habitat proposed for designation, and could identify no differe nces from effects that

211would occur from the product ion of other soybean varieties. Soybean is not considered a particularly competitive plant species and has been selected for domestication and cultivation under conditions not normally found in natural set tings. Soybean is not sexually compatible with, or serves as a host species for, any listed species or species proposed for listing. Consumption of MON 87708 soybean by any listed species or species proposed for listing will not result i n a toxic or allerg ic reaction. Based on these factors, APHIS has concluded that a determination of nonregulated status of MON 8770 8 soybean, and the corresponding environmental release of this soybean variety will have no effect on listed species or species proposed for lis ting, and would not affect designated habitat or ha bitat proposed for designation. Because of this no

- effect determination, consultation under Section 7(a)(2) of the Act or the concurrences of the USFWS or NMFS is not required

212

### 8 CONSIDERATION OF EXE CUTIVE OR DERS, STANDARDS, AND TREATIES RELATING TO ENVIRONMENTAL IMPACT S

8.1 Executive Orders with Domestic Implications

The following executive orders require consideration of the potential impacts of the Federal action to various segments of the population.

• Executive Order (EO) 12898 ( US

- NARA, 2013 ) , "Federal Actions to Address Environmental Justice in Minority Populations and Low

- Income Pop ulations," requires Federal agencies to conduct their programs, policies, and activities that substantially affect human health or the environment in a manner so as not to exclude persons and populations from participation in or benefi ting from such programs. It also enforces existing statutes to prevent minority and low

- income communities from being subjected to disproportionately high and adverse human health or environmental effects.

• EO 13045 ( US

- NARA, 2013 ), “Protection of Children from Environmental Health Risks and Safety Risks,” acknowledges that children may suffer disproportionately from environmental health and safety risks because of their developmental stage, greater metabolic activity levels, and behavior pa tterns, as compared to adults. The EO (to the extent permitted by law and consistent with the Agency’s mission) requires each Federal agency to identif y, assess, and address environmental health risks and safety risks that may disproportionately affect children.

The No Action and Preferred Alternatives were analyzed with respect to EO 12898 and EO 13045. None of the Alternatives are expected to have a di sproportionate adverse effect on minorities, low

- income populations, or children.

FDA completed new protein and biotechnology consultations with Monsanto on MON 87708 soybean and MON 88701 cotton ( US

- FDA, 2011b ; 2013 )

. As part of the evaluations for these events, FDA reviewed the safety and nutritional assessments submitted by Monsanto concluding that food and feed derived from MON 87708 soybean and MON 88701 cotton are not materially different in composition, safety, and other relevant parameters from soybean

- and cotton

- derived food an d feed currently on the market.

Monsanto conducted compositional analyses to establish the nutritional adequacy of forage

- and grain

- derived products from MON 87708 soybean and MON 88701 cotton in comparison to conventi onal counterparts. The studies compared data on key nutrients, secondary metabolites, and anti

- nutrients for MON 87708 soybean and MON 88701 cotton forage and grain samples and the conventional variety controls. According to Monsanto, the measured parameters were within the combined literature range for soybean and cotton and the comparisons indicated no biologically meaningful differences for food and feed safety and nutrition ( US

- FDA, 2011b ; 2013 )

. The DMO protein in MON 87708 soybean and MON 88701 cotton was investigated for its potential to be a toxin or allergen. Bioinformatics studies confirmed the absence of any

213biologically statistically significant amino acid sequence similarity to kno wn protein toxins or allergens. Digestibility studies demonstrated that this protein would be rapidly degraded following ingestion, similar to other dietary proteins. Enzymatic activity of the DMO protein was shown to be eliminated under all heating conditions ( US

- FDA, 2011b ; 2013 )

. Acute oral mouse toxicity studies were performed for the DMO protein, as ingestion represents the most likely route of human exposure to these proteins. No clinical signs of toxicity were observed in any of the test animals.

Monsanto indicated in their submission to FDA that the PAT protein in MON 88701 cotton was shown to be equivalent to that produced in other transgenic crops and previous assessments have shown it is non

- toxic to mammals and does not exhibit any potenti al to be allergenic to humans. A biotechnology consultation on cotton lines containing the PAT protein was completed on June 5, 2003 ( US

- FDA, 2003 ) and also was evaluated as part of the consultatio n on MON 88701 cotton completed in 2013 ( US

- FDA, 2013 )

. As with the DMO protein, Monsanto evaluated the allergenicity of the PAT protein i nserted in MON 88701 cotton th rough bioinformatics analyses. No meaningful homologies to known or reputed allergens or toxins were identified.

Taken together, the evidence indicates that the DMO and PAT proteins are not toxic or not likely to be allergenic to humans.

Additionally, both Food Standards Australia New Zealand ( FSANZ ) and Health Canada have evaluated the food safety of MON 87708 soybean ( FSANZ, 2012 ; Health

- Canada, 20 14 ) and FSANZ has evaluated the food safety of MON 88701 cotton ( FSANZ, 2013 ) . FSANZ did not identify any potential public health and safety concerns and conclud ed that food derived from MON 87708 soybean and MON 88701 cotton “is considered to be as safe for human consumption as food derived from conventional soybean or cotton cultivars” ( FSANZ, 2012 ; 2013 )

. Health Canada has granted food safety approval for MON 87708 soybean in 2012 ( Health

- Canada, 2014 )

.
Based on th e information submitted by the applicant and reviewed by APHIS, MON 87708 soybean and MON 88701 cotton are agronomically, phenotypically, and biochemically comparable to conventional soybean and cotton grown, marketed, and consumed except for the inserted proteins DMO and PAT proteins

. The results of available mammalian toxicity studies associated with the DMO and PAT proteins establish the safety of MON 8770 8 soybean and MON 88701 cotton and associated products to humans, including minorities, low

- income populations, and children who might be exposed to them through agricultural production and/or processing. No additional safety precautions would need to be taken with nonregulated MON 8770 8 soybean and MON 88701 cotton. Based on these factors, a determinat ion of nonregulated status to MON 8770 8 soybean and MON 88701 cotton is not expected to have a disproportionate adverse effect on minorities, low

- income populations, or children.

Agricultural workers, which may include children, minorities, and low

- income populations, could come into contact with the deregulated Xtend crops being grown. Common agricultural practices that would be used with the MON 87708 soybean MON 88701 cotton are no different than those utilized on current conventional and GE crops. If EP A approves the additional new

214uses of dicamba on MON 87708 soybean MON 88701 cotton , dicamba use patterns on these cotton and soybean varieties would be different than is currently allowed

. As a result, the use of dicamba is expected to increase.

EPA regulates the use of herbicides under FIFRA and is making a separate decision which may or may not allow the additional use of dicamba on these plants. EPA considers the toxicity of pesticides to h umans, including sensitive population, such as children, in its pesticide registration and registration reviews.

Currently, t he EPA is proposing to revise the existing Worker Protection Standard (WPS) at 40 CFR part 170 to r educe the incidence of occupational pesticide exposure and related illness among agricultural workers (workers) and pesticide handlers (handlers) covered by the rule. EPA is proposing to strengthen the protections provided to agricultural workers and handl ers under the WPS by improving elements of the existing regulation, such as training, notification

, communication materials, use of personal protective equipment, and decontamination supplies. The EPA expects the revisions, once final , to prevent unreasonable adverse effect s from exposure to pesticides among agricultural workers and pesticide handlers; vulnerable groups, such as minority and low

- income populations, child farmworkers, and farmworker families; and the general public. This regulation, in combination with other components of EPA’s pesticide regulatory program, is intended to prevent unreasonable adverse effects of pesticides among pesticide applicators, workers, handlers, the general pub lic, and vulnerable groups, such as minority and low

‐ income populations.

Further, the increased cost of seed for HR crops such as MON 87708 soybean MON 88701
cotton relative to conventional seeds is not a barrier to low income producers, since net returns for HR soybean and corn were in the aggregate no different ( Fernandez

- Cornejo et al. , 2014a )

. Regardless of seed premiums charged for GE seeds

, such as MON 87708 soybean MON 88701
cotton , growers select GE herbicide resistant seeds because they are associated with certain conveniences in the production of the crop, such simplifying herbicide practices and gaining ability to spray herbicides at different times in the developmental stages of the crop.

The following executive order addresses Federal responsibilities re garding the introduction and effects of invasive species:

EO 13112 ( US

- NARA, 2013 ), “Invasive Species,” states that Federal agencies tak e action to prevent the introduction of invasive species, to provide for their control, and to minimize the economic, ecological, and human health impacts that invasive species

cause.
Neither soybean nor cotton is listed in the U.S. as a noxious weed species by the Federal government ( USDA

- NRCS, 2013c ) , nor are these crops listed as invasive species by major invasive plant data bases ( University of Georgia and USDOI

- NPS, 2012 ; Global

- Restoration

Netwo rk, 2014 )

. While pollen

- mediated gene transfer can occur, there are no differences in the potential for gene flow and weediness from conventional or other GE varieties

. Outcrossing and weediness are

215addressed in the P PRAs ( USDA

- APHIS, 2014d ; 2014e ) and MON 8770 8 soybea n and MON 88701 cotton are similar to other HR

- soybean or HR

- cotton varieties. The risk of gene flow and weediness of MON 8770 8 soybean and MON 88701 cotton is no greater than that of other nonregulated, HR soybean or cotton varieties.

The following executive order requires the protection of migratory bird populations:

EO 13186 ( US

- NARA, 2013 ), “Responsibilities of Federal Agencies t o Protect Migratory Birds,” states that federal agencies taking actions that have, or are likely to have, a measurable negative effect on migratory bird populations are directed to develop and implement, within two years, a Memorandum of Understanding (MOU ) with the Fish and Wildlife Service that shall promote the conservation o f migratory bird populations.

Data submitted by the applicant has shown no substantial difference in compositional and nutritional quality of MON 87708 soybean compared with other GE soybean or non

- GE soybean , apart from the presence of the DMO protein. Similarly, except for the presence of the inserted proteins, MON 88701 cotton has been found to be compositionally and nutritionally comparable to other G E cotton or non

- GE cotton varieties. Additionally, the PAT protein has been cultivated in commercial cotton strains since 2003. The migratory birds that forage in soybean and cotton fields are unlikely to be affe cted adversely by ingesting MON 87708 soybean or MON 88701 cotton and their associated products.

EPA considers the toxicity of pesticides to birds in its pesticide registration and registration reviews.

8.2 International Implications

EO 12114 ( US

- NARA, 2013 ) , “Environmental Effects Abroad of Major Federal Actions” requires federal officials to take into c onsideration any potential environmental effects outside the U.S., its territories, and possessions that result from actions being taken.

APHIS has given this EO careful consideration and does not expect a ny major environmental impact outside the U nited S t ates in the event of a determination of nonregulated status of MON 8770 8 soybean and MON 88701 cotton

. All existing national and international regulatory authorities and phytosanitary regimes that currently apply to introductions of new soybean and
cotton cultivars internationally apply equally to those covered by an APHIS determination of nonregulate d status under 7 CFR part 340.

Any international trade of MON 8770 8 soybean and MON 88701 cotton subsequent to a determination of nonregulated status of the product would be fully subject to national phytosanitary requirements and be in accordance with phytosanitary standards developed under the International Plant Protection Convention (IPPC) ( International

- Plant

- Protection

- Convention, 2011 )

. The purpose of the IPPC “is to secure a common and effective action to prevent the spread and introduction of pests of plants and plant products and to promote appropriate measures for thei r control” ( International

- Plant

- Protection

- Convention, 2011 )

. The protection it

216affords extends to natural flora and plant products and includes both direct and indirect dam age by pests, including wee ds.

The IPPC establishes a standard for the reciprocal acceptance of phytosanitary certification among the nations that have signed or acceded to the Convention (17 2 countries as of March 2010). In April 2004, a standard for PRA of living modified organism s (LMOs) was adopted at a meeting of the governing body of the IPPC as a supplement to an existing standard, International Standard for Phytosanitary Measures No. 11 (ISPM

- 11, Pest Risk Analysis for Q uarantine Pests). The standard acknowledges that all LMO s will not present a pest risk and that a determination needs to be made early in the PRA for importation as to whether the LMO poses a potential pest risk resulting from the genetic modification. APHIS pest risk assessment procedur es for GE organisms are consistent with the gui dance developed under the IPPC. In addition, issues that may relate to commercialization and transboundary movement of particular agricultural commodities produced through biotechnology are being addressed in other international forums and through national regulations.

The Cartagena Protocol on Biosafety is a treaty under the United Nations Convention on Biological Diversity (CBD) that established a framework for the safe transboundary movement, with respect to the environment and biodiversity, of LMOs, which include those m odified through biotechnology. The Protocol came into force on September 11, 2003, and 160 countries are Parties to it as of December 2010 ( CBD, 2012 )

. Although the U.S. is not a party to the CBD, and thus not a party to the Cartagena Protocol on Biosafety, U.S. exporters will still need to comply with those regulations that importing countries which are Parties to the Protocol have promulgated to comply with their obligations. The first intentional transboundary movement of LMOs intended for environmental release (field trials or commercial planting) will require consent from the importing country under an advanced informed agreement (AIA) provision, which includes a requirement for a risk assessment c onsistent with Annex III of the Protocol and the required documentation.

LMOs imported for food, feed, or processing (FFP) are exempt from the AIA procedure and are covered under Article 1 1 and Annex II of the Protocol. Under Article 11, Parties must post decisions to the Biosafety Clearinghouse database on domestic use of LMOs for FFP that may be sub ject to transboundary movement. To facilitate compliance with obligations to this protocol, the U.S. Government has developed a website that provides the statu s of all regulatory reviews completed for different uses of bioengineered products ( NBII, 2010 )

. These data will be available t o the Biosafety Clearinghouse.

APHIS continues to work toward harmonization of biosafety and biotechnology consensus documents, guidelines, and regulations, including within the North American Plant Protection Organization (NAPPO), which includes Mexico, Canada, and the U.S., and within the Organi s ation for Economic Coope ration and Development (OECD). NAPPO has completed three modules of the Regional Standards for Phy tosanitary Measures (RSPM) No. 14, Importation and Release into the Environment of Transgenic Pla nts in NAPPO Member Countries ( North Amer ican Plant Protection Organization, 2003 )

.

217APHIS also participates in the North American Biotechnology Initiative (NABI) , a forum for information exchange and cooperation on agricultural biotechnology issues fo r the U.S., Mexico, and Canada. In addition , bilateral discussions on biotechnology regulatory issues are held regularly with other countries including Argentina, Brazil, Japan, China, and Korea.

8.3 Compliance with Clean Water Act and Clean Air Act

This EIS evaluated the potential changes in soybean a nd cotton production associated with approving the petition for a determination of nonregulated status to MON 8770 8 soybean and MON 88701 cotton (see, 4.2.1) and determined that the cultivation of MON 8770 8 soybean and MON 88701 cotton would not lead to th e increase in or expand the area of soybean and cotton production that could impact water resources or air quality any differently than currently cultivated soybean and cotton varieties. The herbicide resistance conferred by the genetic modification of MON 8770 8 soybean and MON 88701 cotton is not expected to result in any changes in water usage for cultivation compared to current soybean and cotton production. Based on these analyses, AP HIS concludes that an extension of a determination of nonregulated status
to MON 8770 8 soybean and MON 88701 cotton would comply with the CWA and the CAA.

8.4 Impacts on Unique Characteristics of Geographic Areas

Approving the petition for a determination of n onregulated status to MON 8770 8 soybean and MON 88701 cotton is not expected to impact unique characteristics of geographic areas such as parklands, prime farmlands, wetlands, wild and scenic areas, or ecologically critical areas.

Monsanto has presented re sults of agronomic field trials for MON 8770 8 soybean and MON 88701 cotton that demonstrate there are no differences in agronomic practices, between MON 8770 8 soybean and currently available HR

- soybean varieties or between MON 88701 cotton and currently av ailable HR

- cotton varieties. The common agricultural practices that would be carried out in the cultivation of MON 8770 8 soybean and MON 88701 cotton are not expected to deviate from current practices

. The product is expected to be cultivated by growers on agricultural land currently suitable for production of soybean or cotton, and is not anticipated to expand the cultivation of soybean or cotton to new, natural areas.

The Preferred Alternative for MON 8770 8 soybean and MON 88701 cotton does not propose major ground disturbances or new physical destruction or damage to property, or any alterations of property, wildlife habitat, or land scapes. Likewise, no prescribed sale, lease, or transfer of ownership of any property is expected as a d irect result of a determination of nonregulated status for MON 8770 8 soybean and MON 88701 cotton. This action would not convert land use to nonagricultural use and, therefore, would have no ad verse impact on prime farmland

. Standard agricultural practices for land preparation, planting, irrigation , and harvesting of plants would be used on agricultural lands planted to MON 8770 8 soybean and MON 88701 cotton, including the use of EPA

- registered pesticide s.
Based on these findings, including the assumption that pesticide label use restrictions are in place to protect unique geographic areas and that those label use restrictions are adhered to, approving the petition for a determ ination of nonregulated status to MON 8770 8 soybean and MON 88701

218cotton is not expected to impact unique characteristics of geographic areas such as park lands, prime farm lands, wetlands, wild and scenic areas, or ecologically critical areas any differen tly than soybean and cotton varieties already in commercial agriculture

.
8.5 National Historic Preservation Act (NHPA) of 1966 as Amended

The NHPA of 1966 and its implementing regulations (36 CFR 800) require Federal agencies to: 1) determine whether activ ities they propose constitute "undertakings" that have the potential to cause effects on historic properties; 2) if so, to evaluate the effects of such undertakings on such historic resources and consult with the Advisory Council on Historic Preservation ( i.e., State Historic Preservation Office, Tribal Historic Preservation Officers), as appropriate.

The APHIS proposed action, a determination of nonregulated status of MON 8770 8 soybean and MON 88701 cotton is not expected to adversely impact cultural resou rces on tribal properties. Any farming activity that may be taken by farmers on tribal lands would only be con ducted at the tribe’s request. Thus, the tribes would have control over any potential conflict with cultural resources on tribal properties.

The A PHIS Preferred Alternative would neither impact districts, sites, highways, structures, or objects listed in or eligible for listing in the National Register of Historic Places, nor would it likely cause any loss or destruction of important scientific, cul tural, or historical resources. This action is limited to a determination of nonregulated status of MON 8770 8 soybean and MON 88701 cotton.

The APHIS proposed action is not an undertaking that may directly or indirectly cause alteration in the character or use of historic prope rties protected under the NHPA. In general, common agricultural activities conducted under this action do not have the potential to introduce visual, atmospheric, or noise elements to areas in which they are used that could result in effects on the character or use of historic properties. For example, there is potential for increased noise on the use and enjoyment of a historic property during the operation of tractors and other mechanical equipment close to such sites. A built

- in miti gating factor for this issue is that virtually all of the methods involved would only have temporary effects on the audible nature of a site and can be ended at any time to restore the audible qualities of such sites to their original condition wit h no fur ther adverse effects. These cultivation practice s are already being conducted throughout the soybean and cotton production regions. The cultivation of MON 8770 8 soybean and MON 88701 cotton is not expected to change any of the se agronomic practices that would result in an adverse impact under the NHPA.

219

### 9 LIST OF PREPARERS

Name, Title, Project Function Education and Experience

APHIS Sidney W. Abel III

Assistant Deputy Administrator

Reviewer  M.S., Environmental Sciences

– Chemistry, The George Washington University

 B.S., Special Studies

– Environmental Chemistry, University of Maryland

 25 years of professional experience in developing and conducting environmental risk assessments specializing in th e fate, transport, and effects of physical, chemical, and biological substances.

Michael P. Blanchette

Senior Environmental Protection Specialist

Threatened and Endangered Species Analysis  B.S., Entomology, University of New Hampshire

 2 4 years of professional experience as an Environmental Protection Specialist

 10 years evaluating plant pest and environmental impacts of genetically engineered crops, including effects to threatened and endangered species and critical habitat.

Omar Gardner

Environmental Protection Specialist

Environmental Consequences  M.S., Environmental Science & Policy, Johns Hopkins Univ ersity

.

 B.S., Environmental Science, CUNY Medgar Evers College

 1 year of professional experience in environmental risk
assessment of genetically engineered organisms.

220Name, Title, Project Function Education and Experience

Ron Hardman  Ph.D., Inegrated Toxicology and Environmental Health, Duke University

 M.S., Marine Science/Oceans and Human Health, Universit y of North Carolina at Wilmington

 B.S., Biology, Adelphi Universtiy

 18 years of experience in molecular and cellular biology.

 14 years of experience in environmental and human health risk assessment

.

 12 years experience in environmental regulatory anaylsis and compliance

Neil E. Hoffman

Science Advisor  Ph.D., Plant Physiology, University of California, Davis

 B.S., Plant Biology, Cornell University

 30 years of professional experience in plant biochemistry and molecular biology.

 10 years of professional experience in environmental risk assessment of genetically engineered organisms.

Andrea Lemay

Biological Scientist  M.S., Plant Pathology, North Carolina State University

 B.S., Plant and Soil Science , University of Massachusetts

 12 years of professional experience in risk analysis

 12 years of professional experience conducting NEPA analysis.

Elizabeth Nelson

Acting Branch Chief

– Senior Environmental Protection Specialist  MBA, University of Maryland University College

 M.S., Health Care Administration, University of Maryland University College

 B.S., Biology, Bowie State University

 14 years of professional experience in environmental compliance, policy, and management, including preparation of NEPA documentation.

221Name, Title, Project Function Education and Experience

LaKisha J. Odom

AAAS Fellow  Ph.D., Integrative Biosciences, Tuskegee University

 M.A., Environmental and Natural Resource Policy The George Washington University

 B.S., Environmental Science, Tuskegee University

 5 years of professional experience as an Environmental Protection Specialist

.

 4 years evaluating plant pest and environmental impacts of genetically engineere d cotton

.
Alan Pearson

Biotechnologist  Ph.D., Biology, Massachusetts Institute of Technology

 B.A., Biochemistry, Brandeis University

 5 years of professional experience in environmental risk
assessment of genetically engineered organisms.

 15 years of professional experience in molecular and cellular biology.

Kari Perez

Environmental Protection Specialist  Ph.D., Plant Breeding and Genetics, Cornell University

 9 years experience agricultural biology research

 2 year experience in environmental risk assessment of genetically engineered organisms

Craig Roseland

Senior Environmental Protection Specialist  Ph.D., Developmental and Cell Biology, University of California, Irvine

 B.S., Biological Sciences, University of California, Irvine

 11 years of experience in environmental risk assessment and regulatory analysis.

222Name, Title, Project Function Education and Experience

Joanne Serrels

Environmental Protection Speciali st  M.S., Environmental Science & Policy, Johns Hopkins Univ ersity

.

 B.S., Wildlife Biology and Management , University of Rhode Island

 7 years of professional experience conducting NEPA analyses.

 2 years of professional experience in environmental risk
assessment of genetically engineered organisms.

Diane Sinkowski

Environmental Protection Specialist  M.E., Environmental Engineering Sciences, University of Florida

 B.S., Nuclear Engineering Sciences (Health Physics), Minor in Environmental Studies, University of Florida

 20 years of professional experience assessing environmental impacts, evaluating human and environmental exposures, and conducting risk
assessment s.

 10 years of professional experience conducting NEPA analyses.

 4 years of professional experience in environmental risk
assessment of genetically engineered organisms.

Eilee n Sutker

Environmental Protection Specialist  Ph.D. Plant Pathology, North Carolina State University

 M.S. Plant Pathology University of Georgia

 B.S. Botany , The Ohio State University

 J.D., Cleveland

- Marshall College of Law

 12 years of professional experience in Pest Permitting, NEPA analysis, pest and environmental risk assessment.

223Name, Title, Project Function Education and Experience

Kham Vongpaseuth

Environmental Protection Specialist  Ph.D. Plant Biology , Un iversity of Massachusetts Amherst

 M.Sc. Botany, University College Dublin, Ireland

 B.S. Biology, The College of New Jersey

 4 years of professional experience in environmental risk
assessment of genetically engineered organisms.

Joseph Vorgetts

Senior Environmental Protection Specialist  Ph.D., Entomology, Clemson University

 M.S., Entomology, Rutgers University

 B.S., Environmental Science, Rutgers University

 13 years of experience in environmental risk assessment and regulatory development and analysis.

 25 years of experience in insect survey, suppression and management with pesticides and biological control organisms.

 2 years of professional experience in environmental risk
assessment of genetically engineered organisms.

Karen Walker

Environmental Protection Specialist  Ph.D., Entomology, Virginia Tech

 M.S., Biology, George Mason University

 B.S., Biology, George Mason University

 13 years of experience in environmental risk assessment and regulatory development and analysis.

 8 years of experience in insect survey and suppression management.

 1 year of professional experience in environmental risk
assessment of genetically enginee red organisms.

224

### 10 DISTRIBUTION LIST FO R THIS F EIS

Distribution of This Final EIS to Contacts in EPA Regions:

Robert Koethe US EPA Region 1 Mail Code OES05

- 4 5 Post Office Square, Suite 100 Boston, MA 02109

- 3912

Grace Musumeci US EPA, Region 2 290 Broadway New York, NY 10007

- 1866

Barbara Rudnick US EPA, Region 3 1650 Arch Street Philadelphia, PA 19103

- 2029

Ntale Kajumba US EPA, Region 4 Federal Center 61 Forsyth Street, SW Atlanta, GA 30303

- 3104

Ken Westlake US EPA, Region 5 77 West Jackson Boule vard Chicago, IL 60604

- 3507 Michael Jansky US EPA, Region 6 Fountain Place 12th Floor, Suite 1200 1445 Ross Avenue Dallas, TX 75202

- 2733

US EPA, Region 7 NEP A Program 11201 Renner Blvd. Lenexa, KS 66219

Philip Strobel US EPA, Region 8 1595 Wynkoop St. Denver, CO 80202

- 1129

James Munson US EPA, Region 9 75 Hawthorne Street San Francisco, CA 94105

Christine Reichgott US EPA Region 10 1200 Sixth Avenue, Suite 900 Mail Code: ETTA

- 088 Seattle, WA 98101

Distribution to Contacts Requesting a Copy of This Final EIS

David Ortman 7043 22 nd Avenue N.W. Seattle, WA 98117

Marcia Ishii

- Eiteman Senior Scientist, Pesticide Action Network 1611 Telegraph Ave. Suite 1200 Oakland, CA 94612

Food & Water Watch 1616 P Street NW, Suite 300 Washington, DC 20036

National Cotton Council of America
2251521 New Hampshire Ave NW Washington DC 20036

- 1205

Steve Smith Save Our Crops Coalition ssmith@redgold.com Sharon Pratt Center for Food Safety 660 Pennsylvania Ave. Suite 302 Washington, DC 20003

General Distribution of This Final EIS

In addition to th e contacts in the above distribution list s, APHIS notified all of its stakeholders of the availability of th is final EIS

.

226

### 11 BIBL I OGRAPHY

"USDA regulations implementing NEPA ." 7 CFR part 1 b. http://www.law.cornell.edu/cfr/text/7/part

- 1b

. "Groups of organisms which are or contain plant pest s and exemptions." 7 CFR part 340.2. http://www.ecfr.gov/cgi

- bin/text

idx?SID =002a21a619b924956d7d6fb4453f0786&node=7:5.1.1.1.10&rgn=div5

. "National Environmental Policy Act Implementing Procedures." 7 CFR part 372. http://www.ecfr.gov/cgi

- bin/text

idx?SID=002a21a619b924956d7d6fb4453f0786&node=7:5.1.1.1.22&rgn=div5

. "Insecticides and Environmental Pesticide Control Subchapter II

- Environmental Pesticide Control." 7 U.S.C. 136 et
seq. http://www.law.cornell.edu/uscode/pdf/uscode07/lii_usc_TI_07_CH_6_SC_II_SE_1 36.pdf

. "US CODE TITLE 7

- AGRICULTURE CHAPTER 104

— PLANT PROTECTION." 7 U.S.C. §§ 7 701

– 7772. http://www.law.cornell.edu/uscode/text/7/chapter

- 104

. "Toxic Substances Control." 15 U.S.C. 53 et
seq. http: //www.law.cornell.edu/uscode/text/15/chapter

- 53

. "Federal Food, Drug, and Cosmetic Act." 21 U.S.C. 301 et
seq. http://www.law.cornell.edu/uscode/text/21/chapter

- 9

. "Environmental consequen ces." 40 CFR § 1502.16. http://www.gpo.gov/fdsys/granule/CFR

2012

- title40

- vol34/CFR

- 2012

- title40

- vol34

- sec1502

- 16

. "Mitigation." 40 CFR § 1508.20. http://www.gpo.gov/fdsys/granule/CFR

- 2012

- title40

- vol34/CFR

- 2012

- title40

- vol34

- sec1508

- 20/content

- detail.html

. "Phosphinothricin Acet yltransferase and the Genetic Material Necessary for Its Production in All Plants; Exemption From the Requirement of a Tolerance On All Raw Agricultural Commodities." 40 CFR part 180. 1997. "CEQ

- Regulations for Implementing NEPA " 40 CFR parts 1500

- 1508. http://energy.gov/sites/prod/files/NEPA

- 40CFR1500_1508.pdf

. "National Environmental Policy Act as amended." 42 U.S.C. 4321 et seq. https: // www.fsa.usda.gov/Internet/FSA_File/nepa_statute.pdf

. "Coordinated Framework for Regulation of Biotechnology." 51 FR 23302. http://www.aphis.usda.gov/brs/fedregister/coordinated_framework.pdf

. "FDA Statement of Policy: Foods Derived From New Plant Varieties." 57 FR 22984. http://www.farmtoconsumer.org/news/57

- fr

- 22984

- wl

- new

- plant

- varieties.pdf

. (CAST), CfASaT (2009) "Sustainability of U.S. soybean production: Conventional, transgenic, and organic production systems." Submitted by Registration Manager. http://www.cast

science.org/publications/index.cfm?sustainability_of_us_soybean_production&show=pro duct&productID=2947

.

227Adams, G; Boyd, S; and Huffman, M (2014) "The Economic Outlook for U.S. Cotton 2014. National Cotton Council of America (NCC)." National Cotton Council of America. https:// www.cotton.org/econ/repo rts/annual

- outlook.cfm

. AgriMoney "Cotton gains, as China data counters bearish talk." AgriMoney . Last Accessed: Feb 19, 2014 http://www.agrimoney.com/news/cotton

- gains

- as

- china

- data

- counters

- bearish

talk

-- 6767.html

. AirNow (2013) "Air Quality Index (AQI)

- A Guide to Air Quality and Your Health." Last Accessed: March 11, 2014 http://airnow.gov/index.cfm?action=aqibasics.aqi

. Akin, S (2009a) "Arkansas Insect Pest Photo Gallery." University of Arkansas. http://insectphotos.uark.edu/index.html

. Akin, S (2009b) "So ybean Pests." University of Arkansas Division of Agriculture. http://insectphotos.uark.edu/soybean/index.html

. Al

- Kaisi, M (2011) "How Does Soybean Yield Fare Following Corn. Iowa State Univer sity Integrated Crop Management News February 25, 2011." Iowa State University. http://www.extension.iastate.edu/CropNews/2011/0225alkaisi.htm

. Al

- Kaisi, M; Hanna, M; and Tidman , M (2003) "Crop rotation considerations for 2004 management season rotation." Iowa State University. http://www.ipm.iastate.edu/ipm/icm/2003/12

- 15

- 2003/croprotation.html

. Albers, DW and Reinbott, DL (1994) "Cotton tillage and planting guidelines." University of Missouri Extension. Last Accessed: March 11, 2014 http://extension.missouri.edu/p/G4270

. Alberton, O; Kaschuk, G; and Hungria, M (2006) "Sampling effects on the assessment of genetic diversity of rhizobia associated with soybean and common bean." Soil Biology and Biochemistry. 38 (6): p 1298

- 307. http://www.sciencedirect.com/science/article/pii/S0038071705003445

. Ammann, K (2005) "Effects of biotechnology on biodiversity: herbicide

- tolerant and insect

resistant GM crops." TRENDS in Biotechnology. 23 (8): p 388

- 94. http://www.sciencedirect.com/science/article/pii/S0167779905001691

. Andersen, SM; Clay, SA; Wrage, LJ; and Matthees, D (2004) "Soybean foliage residues of dicamba and 2,4

- D and correlation to application rates and yield." Agronomy Journal. 96 (3): p 750

- 60. https:// www.agronomy.org/publications/aj/pdfs/96/3/0750

. Aneja, VP; Schlesinger, WH; and Erisman, JW (2009) "Effects of agriculture upon the air quality and climate: Research, policy, and regulations." Environmental Science and Technology. 43 p 4234

- 40. http://pubs.acs.org/doi/abs/10.1021/es8 024403

. Anonymous (2007) "More D&PL cotton varieties available in San Joaquin than ever before." Western Farm Press. Last Accessed: Feb. 21, 2014 http://west ernfarmpress.com/more

dpl

- cotton

- varieties

- available

- san

- joaquin

- ever

- 0

. AOSCA (2010) "General IP Protocols Standards." The Association of Official Seed Certifying Agencies. http:/ /www.identitypreserved.com/handbook/aosca

- general.htm

.

228Arbuckle, J, J.G. and Lasley, P "Iowa Farm and Rural Life Poll. 2013 Summary Report." https://store.extension.iastate.edu/Product/Iowa

- Farm

- and

- Rural

- Life

- Poll

- 2013

- Summary

- Report. Aref, S and Pike, D (1998) "Midwest farmers’ perceptions of crop pest infestation." Agronomy Journal. 90 p 819

- 25. https://dl.sciencesocieties.org/publications/aj/abstracts/90/6/AJ0900060819.

ASA. "Herbicide Best Weed

- Resistance Practices." PodCasts 2011. http://soygrowers.com/podcasts/herbicide

- best

- weed

- resistance

practices/

. ATTRA (2003) "Organic Cotton Production." https://attra.ncat.org/attra

pub/summaries/summary.ph p?pub=89. AUDAS (2004) "Old Rotation." Auburn University Department of Agronomy and Soils. http://www.ag.auburn.edu/agrn/longterm/oldrotation.php

. Aumaitre, A; Aulrich, K; Chesson, A; Flachowsky, G; and Piva, G (2002) "New feeds from genetically modified plants: substantial equivalence, nutritional equivalence, digestibility, and safety for animals and the food chain." Livestock Production Science. 74 p 223

- 38. http://www.sciencedirect.com/science/article/pii/S0301622602000167#

. Babu, K; Selvadass, M; and Somaskekar, R (2013) "Characterization of the Conventional and O rganic Cotton Fibres." The Journal of the Textile Institute. 104 p 1101

- 12. http://www.tandfonline.com/doi/abs/10.1080/00405000.2013.774948

. Backlund, P (2008) "Effects of Clim ate Change on Agriculture, Land Resources, Water Resources, and Biodiversity in the United States." U.S. Climate Change Science Program and the Subcommittee on Global Change Research. http://www.usda.gov/oce/climate_change/SAP4_3/CCSPFinalReport.pdf

. Baker, H (1965) "Characteristics and modes of origins of weeds " The Genetics of Colonizing Species . London: Acedemic Press. p 147

- 68. http://www.cabdirect.org/abstracts/19661605504.html?freeview=true

. Baker, JB; Southard, RJ; and Mitchell, JP (2005) "Agricultural dust production in standard and conservation tillage systems in the San Joaquin Valley." Journal of Environment Quality. 34 (4): p 1260

- 69. http://www.ncbi.nlm.nih.gov/pubmed/15998847

. Baker, JM; Ochsner, TE; Venterea, RT; and Griffis, TJ (2007) "Tillage and soil carbon sequestration

- What do we really know?" Agriculture, Ecosystems and Environment. 118 (1

- 4): p 1

- 5. http://www.sciencedirect.com/science/article/pii/S0167880906001617

. Baldock, J; Posner, J; Hedtcke, J; and Hall, J (2012) "Organic and Conventional PRoduction Systems: Corn and Soybein Yeild Trends 1990

- 2010." University of Wisonsin. BASF (2010) "Clarity Herbicide Label." Last Accessed: 3/17/14 http://agproducts.basf.us/products/clarity

- herbicide.html

. Bates, DM (1990) "Malvaceae: Mallow family: Manual of the flowering plants of Hawaii." Manual of the Flowering Plants of Hawai'i . Honolulu, Hawai'i: University of Hawai'i Press. p 868

- 903.

229Bayer (2006) "Petition for Determination of Nonregulated Status for Glyphosate

- Tolerant cotton: GlyTolTM cotton Event GHB614." Submitted by Scott, Alejandra, Registration Manager. Bayer CropScience. Research Triangle Park, NC. http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

. Bean, B and Trostle, C (2013) "Quick Guide for Weed Control in Texas Grain Sorghum

2013." http://lubbock.tamu.edu/files/2013/03/sorghumweedcontrolguide13.pdf

. Beckie, HJ and Tardif, FJ (2012) "Herbicide cross resistance in weeds." Crop Protection. 35 (0): p 15

- 28. http://www.sciencedirect.com/science/article/pii/S0261219411004091

. Bell, MS; Hager, AG; and Tranel, PJ (2013) "Multiple Resistance to Herbicides from Four Site

of

- Action Groups in Waterh emp (Amaranthus tuberculatus)." Weed Science. 61 (3): p 460

- 68. Last Accessed: 2014/04/10 http://dx.doi.org/10.1614/WS

- D

- 12

- 00166.1

. Benbrook, C (2009) "Impacts of Genetically Engineered Crops on Pe sticide Use in the United States: The First Thirteen Years. Critical Issue Report Number 3." The Organic Center.
Benedict, JH; El

- Zik, KM; Oliver, LR; Roberts, PA; and Wilson, LT (1989) "Economic injury levels and thresholds for pests of cotton." Integrat ed pest management systems and cotton production . Ed. Frisbie, R.E., K.M. El

- Zik and L.T. Wilson. John Wiley and Sons, Inc. New York. p 437. Berglund, DR and Helms, TC (2003) "Soybean Production." North Dakota Extension Service. http://www.ag.ndsu.edu/pubs/plantsci/rowcrops/a250.pdf

. Berk A. (2008). "Do deer love soybeans?" http://w ww.articlesbase.com/sports

- and

- fitness

articles/do

- deer

- love

- soybeans

- 700903.html

. Bernards, ML; Crespo, RJ; Kruger, GR; Gaussoin, R; and Tranel, PJ (2012) "A Waterhemp (Amaranthus tuberculatus) Population Resistant to 2,4

- D." Weed Science. 60 (3): p 379

- 8 4. Last Accessed: 2014/05/21 http://dx.doi.org/10.1614/WS

- D

- 11

- 00170.1

. Blasi, DA and Drouillard, J. "Composition and feeding value of cottonseed feed products for beef cattle." Manhattan, Kansas: Kansas State University Agricultural Experiment Station and Cooperative Extension Service, 2002. http://www.ksre.ksu.edu/bookstore/pubs/MF2538.pdf

. Blount, A; Wr ight, D; Sprenkel, R; Hewitt, T; and Myer, R (2009) "Forage Soybeans for Grazing, Hay and Silage." Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. htt p://edis.ifas.ufl.edu/ag184

. Boerboom, C (2000) "Timing Postemergence Herbicides in Corn and Soybeans." http://www.soils.wisc.edu/extension/wcmc/proceedings/3B.boerboom.pd f

. Boerboom, C (2004) "Field case studies of dicamba movement to soybeans." Boerboom, C (2006) "Glyphosate resistance strategies and management recommendations for problem weeds." Madison, Wisconsin. htt p://www.jstor.org/stable/3989060

. Boerboom, CM (1999) "Nonchemical options for delaying weed resistance to herbicides in Midwest cropping system." Weed Technology. 13 p 636

- 42.

230Bohmfalk, G; Frisbie, R; Sterling, W; Metzger, R; and Knutson, A (2011a) "Texa s Cotton Insects: Identification, Biology and Sampling of Cotton Insects." http://www.soilcropandmore.info/crops/CottonInformation/insect/B

- 933/b

933.htm

. Bohmfalk, G; Frisbie, R; Sterling, W; Metzger, R; and Knutson, A (2011b) "Texas Cotton Insects: Identification, Biology and Sampling of Cotton Insects." Texas AgriLife Extension Service. http://www.soilcropandmore.info/crops/CottonInformation/insect/B

933/b

- 933.htm

. Bond, JA; Dodds, DM; Eubank, TW; and Reynolds, DB (2014) "Herbicide Programs for Managing Glyphosate

- and ALS Resistant Palmer Amaranth in Mississippi Cotton." http://msucares.com/pubs/infosheets_research/i1362.pdf

. Bowman, ND to: Weissinger, Arthur K. (2013). Management of Weeds in Soybeans

- Heartland Region Boyd, M; Phipps, B; an d Wrather, J (2004a) "Cotton Pests Scouting and Management." MU Extension, University of Missouri. http://ipm.missouri.edu/ipm_pubs/ipm1025.pdf

. Boyd, ML; Phipps, BJ; and Wrather, JA (2004b) "Cot ton Integrated Pest Management." Missouri University Extension. Last Accessed: February 24, 2014 http://ipm.missouri.edu/ipm_pubs/ipm1025.pdf

. Bradford, K. "Methods to Maintain Genetic Purity of Seed Stocks." San Pablo: University of California

- Division of Agriculture and Natural Resources, 2006. 1

- 5. Vol. 8189 of Agricultural Biotechnology in California Series

. http://ucanr.org/freepubs/docs /8189.pdf

. Brady, N and Weil, R (1996) The Nature and Properties of Soils, 11th Edition . Upper Saddle River, NJ: Prentice

- Hall, INc. Brady, SJ (2007) "Effects of Cropland Conservation Practices on Fish and Wildlife Habitat." The Wildlife Society. http://www.fsa.usda.gov/Internet/FSA_File/chap_1.pdf

. Brinker, R; Burns, W; Feng, P; Kendig, J; LeClere, S; Lutke, J; and Malven, M (May 27, 2014

2012) "Cotton Transgenic event MON 88701 and met hods of use thereof." US Patent: 8735661. Brookes, G and Barfoot, P (2004) Co

- existence case study of North America: Widespread GM cropping with non GM and organic crops? Dorchester, England: PG Economics Ltd. Brooks, R (2013) "Palmer Amaranth Pigweed Cr eeps Farther Into the Midwest." http://www.agweb.com/article/palmer_amaranth_pigweed_creeps_farther_int o_the_midwest_NAA_Rhonda_Brooks/

. Brouwer, C and Heibloem, M (1986) "Irrigation Water Management: Irrigation Water Needs." FAO. http://www.fao.org/docrep/S2022E/S2022E00.htm

. Brown, C; D.A. Neuendorff; T.A. Strauch; A.W. Lewis; M.L. Wade; R.D. Randel; B.C. Baldwin; and Calhoun., MC (2002) "Consumption of Whole Cottonseed and EasifloTM Cottonseed Affect Growth in Red Deer Stags." Texas A&M University. Last Accessed: March 27, 2014 https://articlesearchdatabase.tamu.edu/article.cfm ?WhichArticle=171.

231Brubaker CL; JA Koontz; and Wendell, J (1993) "Bidirectional Cytoplasmic and Nuclear Introgression in the New World Cottons, Gossypium barbadense and G. hirsutum (Malvaceae)." American Journal of Botany. 80 (10): p 1203

- 08. http://www.jstor.org/stable/2445549

. Bullock, S; D.G. Hewitt; R.L. Stanko; M.K. Dowd; J. Rutledge; and Draeger., DA (2010) "Plasma gossypol dynamics in white

- tailed deer: Implications for whole cottonseed as a supplemental feed." Small Ruminant Research. 93 (2010): p 165

- 70. Last Accessed: Ma rch 26, 2014 http://www.cottonseed.com/publications/Bullock%20et%20al%202010.pdf

. Butcher, GS; Niven, DK; and Present, T (2007) "Status and Trends of Waterbirds in High

Int ensity Agricultural Areas of the United States." Technical Report of the National Audubon Society. p 52. http://web4.audubon.org/bird/waterbirds/pdf/Status_and_Trends_of_Waterbirds_in_ High

- Intensity_Agricultural_Areas_of_the_United_States.pdf

. Calhoun, MC (2011) "Cottonseed meal and whole cottonseed: Optimizing their use in dairy

c attle rations." Texas Agricultural Experiment Station, Texas A&M University System. http://www.cottonseed.com/publications/Cottonseed%20Meal%20and%20Who l e%20Cottonseed.pdf

. Cambra

- Lopez, M; Aarmoml, AJA; Zhao, Y; and Calvert, S (2010) "Airborne particulate matter from livestock production systems: A review of an air pollution problem. ." Environmental Pollution. 158 (1): p 1

- 17. http://www.sciencedirect.com/science/article/pii/S0269749109003509

. Cantrell, RG (2006) "Agricultural Research Division, Cotton Incorporated. Research on Sustainability." 19TH Annual EFS® System Conf erence: Greenville, SC. http://www.cottoninc.com/fiber/quality/Fiber

- Management/Conferences/2006

- Conference/AFocusonCottonS ustainability.pdf

. Cao, J; Blond, J

- P; and Bézard, J (1993) "Inhibition of fatty acid Δ 6

- and Δ 5

- desaturation by cyclopropene fatty acids in rat liver microsomes." Biochimica et Biophysica Acta. 1210 (1): p 27

- 34. http://www.sciencedirect.com/science/article/pii/000527609390045B

. Carlson, E and LaForest, J (2010) "Cotton Insect Identification." University of Georgia Center for Invasive Species and Ecosystem Healh. http://wiki.bugwood.org/Cotton_insect_identification

. Carpenter, J (2011a) "Impact of GM Crops on Biodiversity " http://www .landesbioscience.com/journals/36/article/15086/

. Carpenter, J and Gianessi, L "Herbicide tolerant soybeans: Why growers are adopting Roundup Ready varieties." http://www.agbioforum.org/v 2n2/v2n2a02

- carpenter.htm

. Carpenter, JE (2011b) "Impact of GM Crops on Biodiversity " GM Crops. 2 (1): p 7

- 23. http://www.landesbioscience.com/journals/36/article/15086/

. Carpente r, JE; Felsot, A; Goode, T; Hammig, M; Onstad, D; and Sankula, S (2002) "Comparative Environmental Impacts of Biotechnology

- Derived and Traditional Soybean, Corn, and Cotton Crops." http://www.cast

232science.org/download.cfm?PublicationID=2895&File=1e307d08220dda0fbe464878597f 6421515eTR

. CBD (2012) "The Cartegena Protocol on Biosafety : About the Protocol." Convention on Biological Diversity. http://bch.cbd.int/protocol/background/

. CEC. "Ecological Regions of North America." Commission on Environmental Cooperation, 2006. http://www3.cec.org/islandora/en/item/2560

- ecological

- regions

- north

- america

level

- i

- iii

- en.pdf

. CEC (2009) "Terrestrial Ecoregions, 2009." Commission for Environmental Cooperation. Last Accessed: Sepember 13, 2013 http://www.cec.org/Page.as p?PageID=122&ContentID=1329

. CEC (2011) "North American Terrestrial Ecoregions

- Level III." Commission for Environmental Cooperation. Last Accessed: June 18, 2013 http://www3.cec.org/islandora/en/item/10415

- north

- american

- terrestrial

ecoregionslevel

- iii

- en.pdf

. "180.1151

- Phosphinothricin Acetyltransferase (PAT) and the genetic material necessary for its production all plants; exemption from t he requirement of a tolerance." CFR Part 180.1151. 2005. Last Accessed: March 18, 2014 http://www.gpo.gov/fdsys/pkg/CFR

2005

- title40

- vol23/xml/CF R

- 2005

- title40

- vol23

- sec180

- 1151.xml

. Chakraborty J; D Ghosal; A Dutta; and Dutta., T (2012) " An insight into the origin and functional evolution of bacterial aromatic ring

- hydroxylating oxygenases." Journal of Biomolecular Structure and Dynamics. 30 (1): p 1

- 19. http://www.tandfonline.com/doi/abs/10.1080/07391102.2012.682208?url_ver=Z39.8 8

- 2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed#.VHTzYYvF9KI

. Chan, B; AC Waiss Jr.; RG Binder; and Elliger., C (1978) "Inhibition of lepidopterous larval growth by cotton constituents." Entomologia Experimentalis et Applicata 24 (3): p 294

- 300. http://onlinelibrary.wiley.com/doi/10.1111/j.1570

- 7458.1978.tb02785.x/abstract

. Chaudhry, MR; ICAC; and Truscott, L (2012) "Organic Cotton: A Production System. " https:// www.icac.org/wp

- content/uploads/2012/08/e_review_june_20121.pdf

. Clark, S and Alexander, C (2010) "The Profitability of Transitioning to Organic Grain Crops in Indiana." Purdue University. http://www.agecon.purdue.edu/extension/pubs/paer/2010/february/alexander.
asp Coble, H to: Hoffman, Neil. (2012). Weeds selected by h oe labor. Coile, N and Garland (2003) "Notes on Florida's Endangered and Threatened Plants." Florida Department of Agriculture and Consumer Services. Last Accessed: November 5, 2012 http:/ /www.virtualherbarium.org/EPAC/Notes2003.pdf

. Commission, E (2010) "A Decade of EU

- Funded GMO Research (2001

- 2010)." Publications of the European Union. http ://ec.europa.eu/research/biosociety/pdf/a_decade_of_eu

funded_gmo_research.pdf

.

233Committee on Identifying and Assessing Unintended Effects of Genetically Engineered Foods on Human Health, NRC (2004) "New approaches for identifying unintended changes in food composition." Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects . Washington, D.C.: Institute of Medicine and National Research Council, National Academies Press. p 73

- 102. http://www.ncbi.nlm.nih.gov/books/NBK215761/

. Committee on the Impact of Biotechnology on Farm

- Level Economics and Sustainability; National Research Council (2010) The Impact of Genetically Engineered Crops on Farm Sustainability in the U nited States . National Academies Press

- The National Academies Press. http://www.nap.edu/catalog.php?record_id=12804

. Conley, S to: Weissinger, Arthur K., PhD. (2013). Management of Weeds in So ybeans

- Heartland Region. Conley, S and Christmas, E. "Utilizing Inoculates in a Corn

- Soybean Rotation

- SPS

- 100

- W." Purdue Extension, 2005. Vol. 2011. https:// www.extension.purdue.ed u/extmedia/sps/sps

100

- w.pdf

. Conservation

- Technology

- Information

- Center (2006) "The National Crop Residue Management (CRM) Survey." http://www.conservationinformation .org/pdf/2006CRMSurveySummaryLoRes. pdf

. Convention on Biological Diversity (2014) "Modified Organism

- MON

- 15985

- 7

- Bollgard IITM cotton." Submitted by Registration Manager. http:// bch.cbd.int/database/record.shtml?documentid=14774

. Cook, E; Bartlein, P; Diffenbaugh, N; Seager, R; Shuman, B; Webb, R; Williams, J; and Woodhouse, C. "Hydrological Variability and Change." The U.S. Climate Change Science Program, 2008. Cordain, L (1999) "Cereal grains: Humanity's double

- edged sword." Evolutionary Aspects of Nutrition and Health: Diet, Exercise, Genetics and Chronic Disease . World Rev Nutr Diet. p 19

- 73. http://www.direct

- ms.org/pdf/EvolutionPaleolithic/Cereal%20Sword.pdf

. Corn and Soybean Digest (2014) "Looming price risk ahead for corn, soybeans." http://cornands oybeandigest.com/blog/looming

- price

- risk

- ahead

- corn

soybeans

. Crespo, RJ (2011) "Herbicide

- Resistant Risk Assessment: Response of Common Nebraska Weeds to Dicamba Dose." Theses, Dissertations, and Student Research in Agronomy and Horticulture. Paper 31. Di ssertations and Theses

. http://digitalcommons.unl.edu/agronhortdiss/31/?utm_source=digitalcommo ns.un l.edu%2Fagronhortdiss%2F31&utm_medium=PDF&utm_campaign=PDFCoverPages

. Crespo, RJ; Bernards, ML; Sbatella, GM; Kruger, GR; Lee, DJ; and Wilson, RG (2014) "Response of Nebraska Kochia (Kochia scoparia) Accessions to Dicamba." Weed Technology. 28 (1): p 151

- 62. Last Accessed: 2014/11/07 http://dx.doi.org/10.1614/WT

D

- 13

- 00109.1

.

234Crockett, LJ (1977) Wildly Successful Plants: A Handbook of North American Weeds. Honolulu: University of Hawaii Press. http://books.google.com/books/about/Wildly_successful_plants.html?id=Xg4pAQ AAMAAJ

. Croissant, RL; Peterson, GA; and Westfall, DG (2008) "Dryland Cropping Syste ms." Colorado State University Extension http://www.ext.colostate.edu/pubs/crops/00516.html

. CTIC (2011) "Top 10 conservation tillage benefits." Conservation Technology Information Center. Last Accessed: February 22, 2001 http://www.ctic.purdue.edu/resourcedisplay/293/

. Culpepper, A, Whitaker, JR, MacRae, A, and York, AC. (2008) "Distribution of glyphosate

resistant Palmer Amara nth (Amaranthus palmeri) in Georgia and North Carolina during 2005 and 2006." Journal of Cotton Science. 12 p 306

- 10. https:// www.cotton.org/journal/2008

- 12/3/upload/JCS12

- 306.pdf

. DAS (2010) "Petition for Determination of Nonregulated Status for Herbicide Tolerant DAS

40278

- 9 Corn. Submitted by L. Tagliani, Regulatory Leader, Regulatory Sciences & Government Affairs." Dow AgroSciences, LLC. http://www.aphis.usda.gov/brs/aphisdocs/09_23301p.pdf

. "DAS

- 686

- 416

- 4 Soybean Dow AgroSciences Petition Number 09

- 349

- 01p for a Determination of Non

- regulated Status for Herbicide Tolerant DAS

- 68416

- 4 Soybean Supplementary Documentation in Support of Draft Environmental Assessment." DAS. 2013a.

DAS to: Hoffma n, Neil. (2013b). Supplemental Documentation in Support of Environmental Assessments in Response to Questions 4, 6

- 7 Received December 12, 2012 regarding DAS

- 40278

- 9 corn and DAS

- 68416

- 4 soybean. 2

- 4,D use

Delate, K (2003) "Growing Organic Soybeans on Con servation Program Land." Iowa State Univeristy Extension. https://store.extension.iastate.edu/Product/Growing

- Organic

Soybeans

- on

- Conservation

- Reserve

- Program

- Land. DeYoung, C (2005) "Feeding Cottonseed to Deer." Inside Deer Research. 2 (2): p 4. http://ckwri.tamuk.edu/fileadmin/user_upload/docs/Inside_Deer_Research/2005_Fall_ Newsletter_reduced.pdf

. Dill, GM; CaJacob, C; and Padgette, S (2 008) "Glyphosate

- resistant crops: Adoption, use and future considerations." Pest Management Science. 64 p 326

- 31. http://onlinelibrary.wiley.com/doi/10.1002/ps.1501/full

. Dona, A and A rvanitoyannis, IS (2009) "Health risks of genetically modified foods." Critical Reviews in Food Science and Nutrition. 49 p 164

- 75. http://www.unio nccs.net/images/library/file/Agricultura_y_alimentacion/Health_Risk s_GMOs.pdf

. Doran, J; Sarrantonio, M; and Liebig, M (1996) "Soil health and sustainability." Advances in Agronomy. 56 p 1

- 54. http://www.sciencedirect.com/science/article/pii/S0065211308601789

. 235Duffy, M (2011) "Estimated Cost of Crop Production in Iowa

- 2011." Iowa State University http:/ /www.extension.iastate.edu/agdm/crops/pdf/a1

- 20.pdf

. Duke, S (2005) "Taking stock of herbicide

- resistant crops ten years after introduction." Pest Management Science. 61 p 211

- 18. http://www.ncbi.nlm.nih.gov/pubmed/15660452

. Duke, SO and Powles, SB (2008) "Glyphosate: A once

- in

- a

- century herbicide." Pest Management Science. 64 (4): p 319

- 25. http://onlineli brary.wiley.com/doi/10.1002/ps.1518/abstract

. Duke, SO and Powles, SB (2009) "Glyphosate

- resistant crops and weeds: Now and in the future." http://www.agbioforum.org/v12n34/v12n34a10

- duke. htm

. Durgan, BR and Gunsolus, JL (2003) "Developing Weed Management Strategies that Address Weed Species Shifts and Herbicide Resistant Weeds." http://appliedweeds.cfans.umn.edu/pubs/03pub0 1.pdf

. Ebel, R (2012) "Agricultural Resources and Environmental Indicators, 2012." USDA

ERS. http://www.ers.usda.gov/media/874175/eib98.pdf

. Edwards, CB; Eubank, TW; Shaw, DR; and Steckel, LE ( 2012) "Preemergence and Postemergence Efficacy of Dicamba on Glyphosate Resistant Palmer Amaranth (Amaranthus palmeri S. Wats.) and Optimum Rate for Control " http://ms soy.org/wp

content/uploads/2013/08/20

- 2012

- FINAL

- REP

- MSSOY.pdf

. Egan, JF; Bohnenblust, E; Goslee, S, Mortensen, D., ; and Tooker, J (2014) "Herbicide drift can affect plant and arthropod communities " Agriculture, Ecosystems & Environment. 185 p 77

- 87. Las t Accessed: 4

- 23

- 14 http://www.sciencedirect.com/science/article/pii/S0167880913004398

. El

- Zik, KM; Grimes, DW; and Thaxton, PM (1989) Cultural Management and Pest Suppressi on

. Eds. Frisbie, R.E., K.M. El

- Zik and L.T. Wilson. New York: John Wiley and Sons, Inc. http://www.cabdirect.org/abstracts/19911154901.html?freeview=true

. Ellington, JJ; Car rillo, T; McCauley, J; McWilliams, D; Lillywhite, J; Pierce, J; and Drake, J. "Precision Cotton Production." New Mexico State University Cooperative Extension, 2007. 1

- 11. http://aces.nmsu.edu /pubs/_circulars/CR

- 629.pdf

. Ely, LO and Guthrie, LD (2012) "Feeding Whole Cottonseed to Dairy Cows and Replacements." http://www.caes.uga.edu/publications/pubDetail.cfm?pk_id=77 52

. Entomology, KSUDo "Facts and Information on Cotton Pests." Kansas State University. http://entomology.k

- state.edu/extension/insect

- information/crop

- pests/cott on/

. EPA (2014) "Ag 101: demographics." Last Accessed: 13Mar14 http://www.epa.gov/oecaagct/ag101/demographics.html

. Extension, UoM (2013) "Soybean Production." http://www.extension.umn.edu/agriculture/soybean/

. FAO (1997) "Land Cover and Land Use. From "AFRICOVER Land Cover Classification"." Food and Agriculture Organization of the United Nations. Last Accessed: September 16, 2013 http://www.fao.org/sd/EIdirect/EIre0044.htm

.

236FAO (2009) "Codex Alimentarius, Foods Derived from Modern Biotechnology, 2nd Edition." World Health Organization, Food and Agriculture Organizati on of the United Nations. ftp://ftp.fao.org/docrep/fao/011/a1554e/a1554e00.pdf

. Farm

- Industry

- News (2013) "Monsanto, Dow Agrosciences cross

- license next generation of weed, insect control technology in corn." http://farmindustrynews.com/corn

- rootworm

traits/monsanto

- dow

- agrosciences

- cross

- license

- next

- generation

- weed

- insect

- control

- tec

. Farm Industry News (2013) "Glyphosate

- resistant weed problem extends to more species, more farms." http://farmindustrynews.com/ag

- technology

- solution

- center/glyphosate

- resistant

weed

- problem

- extends

- more

- species

- more

- farms

. Farnham, D (2001) "Corn Planting." Cooperative Extension Service, Iowa State University of Science and Technology. Last Accessed: April 6, 2011 file:///C:/Users/apkwperez.USDA/Downloads/PM1885.pdf. Faust, MA (2002) "New feeds from genetically modifi ed plants: The US approach to safety for animals and the food chain." Livestock Production Science. 74 (3): p 239

- 54. http://www.sciencedirect.com/science/article/pii/S0301622602000179

. Fawcett, R and Towery, D "Conservation Tillage and Plant Biotechnology: How New Technologies Can Improve the Environment By Reducing the Need to Plow." The Conservation Technology Informat ion Center. http://www.ctic.org/media/pdf/Biotech2003.pdf

. Felsot, AS (2005) "Evaluation and mitigation of spray drift ." International Workshop on Crop Protection Chemistry i n Latin America; Harmonized Approaches for Environmental Assessment and Regulation: San Jose, Coasta Rica. Last Accessed: March 11, 2014 http://feql.wsu.edu/esrp531/fall05/felsotco staricadrift.pdf

. Feng, P and Brinker, R "Methods for weed control using plants having dicamba

- degrading enzymatic activity US RE45048 E1." US Patent: https:// www.google.com/patents/USRE45048?dq=Methods+for+weed+control+using+pl ants+having+dicamba

degradation+enzymatic+activity&hl=en&sa=X&ei=MiZ2VMDtBsSBsQTq2oCoDQ& ve d=0CB0Q6AEwAA

. Feng, PCC and Brinker, RJ 2010) "Methods for weed control using plants having dicamba

degrading enzymatic activity." US Patent: US 7,855,326 B2. http://www.google.com/patents/US785532 6

. Fernandez

- Cornejo, J (2007) "Off

- Farm Income, Technology Adoption, and Farm Economic Performance." http://www.ers.usda.gov/media/200316/err36_1_.pdf

. Fernandez

- Cornejo, J and Caswell, M ( 2006) "The First Decade of Genetically Engineered Crops in the United States. Economic Information Bulletin Number 11." http://www.ers.usda.gov/media/255908/eib11_1_.pdf

. Fernandez

- Cornejo, J; Hallahan, C; Nehring, R; Wechsler, S; and Grube, A (2013) "Conservation Tillage, Herbicide Use, and Genetically Engineered Soybeans in the U.S.A." ISB News Report, April 2013 h ttp://www.isb.vt.edu/news/2013/Apr/Conservation

- Tillage.pdf

. 237Fernandez

- Cornejo, J and McBride, W (2002) "Adoption of bioengineered crops." U.S. Department of Agriculture. http://www.foodsafety.k

state.edu/articles/17/adopt_biocrops_USag.pdf

. Fernandez

- Cornejo, J; Wechsler, S; Livingston, M; and Mitchell, L (2014a) "Genetically Engineered Crops in the United States." http://www.ers.usda.gov/publications/err

economic

- research

- report/err162.aspx

. Fernandez

- Cornejo, J; Wechsler, SJ; Livingston, M; and Mitchell, L (2014b) "Genetically Engineered Crops in the United States." USDA

- Econom ic Research Service. http://www.ers.usda.gov/publications/err

- economic

- research

- report/err162.aspx

. Ferrell, J to: Weissinger, Arthur K. (2013). Management of Wee ds in Soybeans; concerns about use of 2,4

- D

- Florida Region

Field

- to

- Market (2012) "Environmental and Socioeconomic Indicators for Measuring Outcomes of On

- Farm Agricultural Production in the United States: Second Report." http://www.usarice.com/doclib/188/6132.pdf

. Field, CB; Mortsch, LD; Brklacich, M; Forbes, DL; Kovacs, P; Patz, JA; Running, SW; and Scott, MJ (2007) "North America. Climate Change 2007: Impacts, Adaptation and Vulnerability." Clim ate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change . Cambridge, UK: Cambridge University Press. p 617

- 52. Last Accessed: December 3, 2010 http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch14s14

- 4

- 4.html

. Fleskes, J; Jarvis, R; and Gilmer, D (2003) "Selection of flooded agricultural fields and other land scapes by female northern pintails wintering in Tulare Basin, California." Wildlife Society Bulletin. 31 (3): p 793

- 803. http://www.jstor.org/stable/3784602

. Foreman, L and Livezey, J (2002) "Characterist ics and Production Costs of U.S. Soybean Farms." USDA Economic Research Service. http://www.ers.usda.gov/publications/sb

statistical

- bulletin/sb974

- 4.aspx

. Franke, T; Kelsey, K; and Royer, T "Pest Management Needs Assessment for Oklahoma Cotton Producers." http://pods.dasnr.okstate.edu/docushare/dsweb/Get/Document

- 6227/EPP

7081web.pdf

. Frans, RE and Chandler, JM (1989) "Strategies and Tactics for Weed Management." Integrated Pest Management Systems and Cotton Production . New York: John Wiley and Sons, Inc. http://books.google.com/books/about/Integrated_Pest_Management_Systems_and_C .html?id=2EqtzV2

- B4QC

. Freeman, B (2012) "Cotton Insect Pests." Alabama Cooperative Extension System, Alabama A&M and Auburn U niversities. http://www.aces.edu/pubs/docs/A/ANR

- 0409/ANR

0409

- low.pdf

. Fromme, D; Grichar, J; Morgan, G; and Bean, B (2010) "Control of Volunteer Cotton in Corn." http://www.txbollweevil.org/downloads/10finalcornboardreport.pdf

.

238Fryxell , PA (1984) "Taxonomy and Germplasm Resources." Cotton, Agronomy Monograph 24, 1984 . Madison, WI: ASA

- CSSA

- SSA. p 27

- 57

. https://dl.sciencesocieties.org/publications/books/tocs/agronomymonogra/cotton. FSANZ (2012) "Approval Report

- Food derived from Herbicide

- tolerant Soybean Line MON87708." Food Standards Australia New Zeland. Last Accessed: January 29, 2014 http://www.foodstandards.gov.au/code/applications/documents/A1063%20GM%20 Soybean%20MON87708%20AppR%20FINAL.pdf

. FSANZ (2013) "Approval Report

- Food derived from Herbicide

- tolerant Cotton Lone MON88701." Food Standards Australia New Zeland. Last Accessed: January 29, 2014 http://www.foodstandards.gov.a u/code/applications/Documents/A1080

- GM

AppR.pdf

. Fuerst, EP; Sterling, TM; Norman, MA; Prather, TS; Irzyk, GP; Wu, Y; Lownds, NK; and Callihan, RH (1996) "Physiological characterization of picloram resistance in yellow starthistle." Pesticide Biochemistry and Physiology. 56 (2): p 149

- 61. http://www.sciencedirect.com/science/article/pii/S0048357596900693

. Funtanilla, M; Lyford, C; and Wang, C (2009) "An Evaluation of the Orga nic Cotton Marketing Opportunity." Agricultural and Applied Economics Association's 2009 AAEA and ACCI Joint Annual Meeting

. http://ageconsearch.umn.edu/bitstr eam/49359/2/2009%20aaea%20paper%2004

- 30

- 09.pdf

. Gadberry, S. "Alternative feeds for beef cattle." Little Rock, Arkansas: University of Arkansas Research and Extension, 2011. 1

- 6. Vol. FSA3047. http://www.uaex.edu/publications/pdf/fsa

- 3047.pdf

. Galle, AM; Linz, GM; Homan, JH; and Bleier, WJ (2009) "Avian Use of Harvested Crop Fields in North Dakota During Spring Migration." Western North American Naturalist. 69 (4). http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1909&context=icwdm_us danwrc

. Garbeva, P; van Veen, JA; and van Elsas, JD (2004) "Microbial diversi ty in soil: Selection of microbial populations by plant and soil type and implications for disease suppressiveness." Annual Review of Phytopathology. 42. http://www.ncbi.nlm.nih.gov/pubmed/1528366 7

. Gardner, JG; Nehring, R; and Nelson, CH (2009) "Genetically Modified Crops and Household Labor Savings in US Crop Production." http://www.agbioforum.org/v12n34/v12n34a06

- gardner.pdf

. Garrison, RL and Lewis, JC (1987) "Effects of Browsing by White

- Tailed Deer on Yields of Soybeans." Wildlife Society Bulletin. 15 (4): p 555

- 59. http://www.jstor.org/stable/3782582

. Genito, D; Gburek, WJ ; and Sharpley, AN (2002) "Response of stream macrionvertebrates to agricultural land cover in a small watershed." Freshwater Ecology. 17 p 109

- 19. http://www.tandfonline.com/doi/pdf/10.1080/02705060.2002.9663874

.

239Gesell, S and Calvin, D (2000) "Insect Pests of Soybean in Pennsylvania." Penn State Department of Entomology. http://ento.psu.edu/extension/factsheets/insect

- pests

- of

soybeans

. Gianesi, LP and Carpenter, JE (1999) "Agricultural Biotechnology: Insect Control Benefits." National Center for Food and Agricultural Policy. http://www.iatp.org/files/Agricultural_Biotechnology_Insect_Control_Bene.htm

. Gianessi, L and Reigner, N (2007) "The value of herbicides in U.S. crop production." Weed Technology. 21 (2): p 559

- 66. http://www.bioone.org/doi/abs/10.1614/wt

- 06

- 130.1

. Gibbs, M; Dufour, R; and Guerena, M (2005) "BASIC Cotton Manual. Practical Lessons Learned from the Sustainable Cotton Project’s Biological Agricul ture Systems in Cotton (BASIC) Program." Sustainable Cotton Project. http://caff.org/wp

content/uploads/2010/07/Cotton

- Manual.pdf

. Givens, WA; Shaw, DR; Johnson, WG; Weller, SC; Young, BG; Wilson, RG; Owen, MDK; and Jordan, D (2009) "A Grower Survey of Herbicide Use Patterns in Glyphosate

- Resistant Cropping Systems." Weed Technology. 23 (1): p 156

- 61. Last Accessed: 2014/04/14 http://dx.doi.org/10.1614/WT

- 08

- 039.1

. Global

- Restoration

- Network (2014) "Center for Invasive Plant Management (CIPM) Restoration Database." Global Restoration Network

- Society for Ecological Restoration. Last Accessed: January 30, 2014 http://www.globalrestorationnetwork.org/database/cipm

database/

. Gouge, DH; Way, MO; Knutson, A; Cronholm, G; and Patrick, C (No Date) "Managing Soybean Insects." Texas Agricultural Extension Se rvice, Texas A&M University. http://varietytesting.tamu.edu/soybeans/otherpublications/19994382727

- B1501.pdf

. Grace, J to: Pearson, Alan. (2012). Re: Inquiry on Cotton Cultivation in Hawaii. Graneto, MJ; Malven, M; Mannion, RM; Soteres, JK; Bollman, SL; Hood, BS; Honegger, JL; Wideman, MA; and Dobert, RC (2013) "Petitioner's Environmental Report for Dicamba and Glufosinate

- Tolerant Cotton MON 88701 (USDA Petitio n #12

- 185

- 01p_a1)." Green, JD; Witt, WW; and Martin, JR (2006) "Weed Management in Grass Pastures, Hayfields, and Other Farmstead Sites." Cooperative Extension Service, University of Kentucky Extension. http://www2.ca.uky.edu/agc/pubs/agr/agr172/agr172.pdf

. Greene, JK (2012) "Cotton Insect Management." South Carolina Pest Management Handbook for Field Crops 2012. http://www.clemson.edu/extension/rowcrops/pest/files/2012%20PMH%20Web%2 0Page%20Version/2012%20PMH_COTTONIC.pdf

. Greene, JK (2014a) "Cotton Insect Management " Clemson University. http://www.clemson.edu/extension/rowcrops/pest/files/2014%20Pest%20man agement%20files.pdf/cottoninsectmanagementPMH2014.pdf

. Greene, JK (2014 b) "Soybean Insect Control." South Carolina Pest Management Handbook for Field

240Crops. http://www.clemson.edu/ext ension/rowcrops/pest/files/2014%20Pest%20manage ment%20files.pdf/managementofsoybeaninsectsPMH2014.pdf

. Guerena, M and Sullivan, P (2003) "Organic cotton production." Appropriate Technology Transfer for Rural Areas, National Center for Appropriate Technolog y. https://attra.ncat.org/attra

- pub/viewhtml.php?id=89. Gunsolus, J; Wyse, D; Mondaca, K; and Fernholz, C (2010) "Weed Management, Chapter 6." Risk Management Guide for Organic Producers, ed. , Kristine M. Moncada and Craig C. Sheaffer . St. Paul: Universit y Minnesota, College of FANRS. http://www.organicriskmanagement.umn.edu/weed_mgmt6.html

. Hager, A (2013) "Controlling large horseweed and waterhemp in soybean." http://bulletin.ipm.illinois.edu/?p=1336

. Hager, AG; Young, BG; and Bernards, ML (2011) "Revisiting the realm of residuals: A few suggestions for improving the effectiveness of soil residual herbicides." The Bulletin, Pes t Management and Crop Development University of Illinois Extension. http://bulletin.ipm.illinois.edu/pdf/revisiting_residuals.pdf

. Hake, KD; Blasingame, D; Burmester, C; Goodell, PB; and Stichler, C. "Crop Rotation." Newsletter of the Cotton Physiology Education Program : National Cotton Council, 1991. 1

- 4. Vol. 3. https:// www.cotton.org/te ch/physiology/cpt/soilmgt/upload/CPT

- Oct91

- REPOP.pdf

. Hake, SJ; Kerby, TA; and Hake, KD (1996) "Preparation for the new crop season

- Fall/winter." Cotton Production Manual . University of California Division of Agriculture and Natural Resources. p 228

- 47. Hammond, BG and Jez, JM (2011) "Impact of food processing on the safety assessment for proteins introduced into biotechnology

- derived soybean and corn crops." Food Chem Toxicol. 49 (4): p 711

- 21. http://www.ncbi.nlm.nih.gov/pubmed/21167896

. Hammond, R; Michel, A; and Eisley, J. "Defoliators on Soybean." Ohio State University, 2009. Vol. 2014. http://ohioline.osu.edu/ent

- fact/pdf/0039.pd f

. Hartzler, B (2013) "Don’t Delay the Burndown Application." http://www.extension.iastate.edu/CropNews/2013/0426hartzler.htm

. Hartzler, B (2014a) "Can you afford to skip the

r esidual?" http://www.weeds.iastate.edu/mgmt/2014/skipresidual.pdf

. Hartzler, B. "Palmer amaranth: ID, biology and management." Department of Agronomy, Iowa State University, 2014b. http://www.weeds.iastate.edu/mgmt/2014/Palmer%20amaranthICMv2.0.pdf

. Health

- Canada (2014) "Table of Novel Food Decisions." Health Canada. Last Accessed: January 29, 2014 http://www.hc

- sc.gc.ca/fn

- an/gmf

- agm/appro/index

- eng.php

. Heap, I (2014a) "Herbicide

- Resistant Weeds by Site of Action " International Survey of Herbicide Resistant Weeds. http://www.weedscience.com/summary/SOASummary.aspx

.

241Heap, I (2014b) "Herbicide resistant weeds

- Synthetic auxins (O/4) resistant weeds." International Survey of Herbicide Resistant Weeds. http://www.weedscience.org/Summary/MOA.aspx?MOAID=24

. Heap, I (2014c) "International Survey of Herbicide Resistant Weeds." Weed Science Society of America. www .weedscience.org

. Heap, I "The International Survey of Herbicide Resistant Weeds." http://www.weedscience.org/summary/home.aspx

. Heatherly, L; Dorrance, A; Hoeft, R; Onstad, D; Orf, J; Porter, P; Spurlock, S; and Young, B (2009) "Sustainability of U.S. Soybean Production: Conventional, Transgenic, and Organic Production Systems." Council for Agricultural Science and Technology. http://www.cast

science.org/publications/?sustainability_of_us_soybean_production&show=product&pro ductID=2947

. Heiniger, RW (2000) "Irrigation and drought management." North Carolina State University. http://www.ces.ncsu.edu/plymouth/cropsci/cornguide/Chapter4.html

. Herbert, A; Malone, S; Dively, G; Greene, J; Tooker, J; Whalen, J; and Youngman, R (2011) "Mid

- Atlantic Guid e to the Insect Pests and Beneficials of Corn, Soybean, and Small Grains." Virginia

- Tech. http://pubs.ext.vt.edu/444/444

- 360/444

- 360_pdf.pdf

. Herbert, A; Malone, S; Dively, G; Greene, JK; T ooker, J; Whalen, J; and Youngman, R (No Date) "Mid

- Atlantic Guide to the Insect Pests and Beneficials of Corn, Soybean, and Small Grains." Virginia Tech. http://pubs.ext.vt.edu/444/444

- 360 /444

- 360_pdf.pdf

. Herbicide

- Resistance

- Action

- Committee (2013) "Guideline to the management of herbicide resistance." http://www.hracglobal.com/Education/ManagementofH erbicideResistance.as
px

. Herbicide

- Resistance

- Action

- Committee (2014) "Resistance management strategies." Last Accessed: 4

- 24

- 14 http://www.hracglobal.com/

. Herman, RA; Phillips, AM; Lepping, MD; Fast, BJ; and Sab batini, J (2010) "Compositional safety of event DAS

- 40278

- 9 (AAD

- 1) herbicide

- tolerant maize." GM Crops. 1 (5): p 294

- 311. http://www.ncbi.nlm.nih.gov/pubmed/21844687

. Hernandez

- Soriano, MC; Mingorance, MD; and Pena, A (2007) "Interaction of pesticides with a surfactant

- modified soil interface: Effect of soil properties." Physicochem. Eng. Aspects. 306 p 49

- 55. http://www.sciencedirect.com/science/article/pii/S092777570600879X#

. Herouet, C; Esdale, DJ; Maillyon, BA; Debruyene, E; Schulz, A; Currier, T; Hendrickx, K; van der Klis, RJ; and Rouan, D (2005) "Safety Evaluation of the phosphinoth rin acetyltransferase proteins encoded by the pat and bar sequences that confer tolerance to glufosinate

- ammonium herbicide in transgenic plants." Regulatory Toxicology and Pharmacology. 41 p 134

- 49. http://www.ncbi.nlm.nih.gov/pubmed/15698537

. Higgins, R (1997) "Soybean Insects

- Soybean Production Handbook." http://www.ksre.ksu.edu/mil/Resources/Crop%20 Production%20Handbooks /Soybeans.pdf

.

242Higley, LG and Boethel, DJ (1994) "Handbook of Soybean Insect Pests." Entomological Society of America. http://www.ent.iastate.edu/soybeaninsects/node/54

. Hoeft, RG; Nafziger, ED; Johnson, RR; and Aldrich, SR (2000) Modern Corn and Soybean Production . MCSP Publications. Holm, L; Pancho, JV; Herberger, JP; and Plucknett, DL (1979) A Geographical Atlas of World Weeds . John Wiley and Sons.
Hoorman, J; Islam , R; and Sundermeier, A (2009) "Sustainable Crop Rotations with Cover Crops." Ohio State University. http://ohioline.osu.edu/sag

- fact/pdf/0009.pdf

. Hurley, TM; Mitchell, PD; and Frisvold, GB (20 09) "Characteristics of Herbicides and Weed

Management Programs Most Important to Corn, Cotton, and Soybean Growers." http://www.aae.wisc.edu/pdmitchell/Working/Herbicide.pdf

. Hussain , I; Olson, KR; and Ebelhar, SA (1999) "Impacts of tillage and no

- till on production of maize and soybean on an eroded Illinois silt loam soil." Soil and Tillage. 52 (1

- 2): p 37

- 49. http://www.sciencedirect.com/science/article/pii/S0167198799000549#

. Hutmacher, RB; Vargas, RN; and Wright, SD (2006) "Methods to enable the coexistence of diverse cotton production systems

. "

International

- Life

- Sciences

- Institute "Crop Compositi on Database." Last Accessed: November 5, 2012 https:// www.cropcomposition.org/query/index.html

. International

- Plant

- Protection

- Convention (2011) "International Standards for Phytosanitary Meas ures (ISPMs)." https:// www.ippc.int/standards

. Iowa

- State

- University (2003) "Weeds to watch: New weed threats for corn and soybean fields." Iowa State University Extension. file:///C:/Users/apkwperez.USDA/Downl oads/IPM0072A.pdf. Iowa State Extension (2014) "2014 Herbicide Guide for Iowa Corn and Soybean Production." Iowa State University. https://store.extension.iastate.edu/Product/2014

- Herbicide

- Guide

for

- Iowa

- Corn

- and

- Soybean

- Production. IPCC (2007) "Climate C hange 2007: The Physical Science Basis." Cambridge University Press. http://www.ipcc.ch/publications_and_data/publ ications_ipcc_fourth_assessment_r eport_wg1_report_the_physical_science_basis.htm

. James, C (2013) "Global Status of Commercialized Biotech/GM Crops: 2013. ISAAA Brief No. 46." ISAAA. http://www.isaaa.org/resources/publications/briefs/46/default.asp

. Jasinski, JR; Eisley, JB; Young, CE; Kovach, J; and Willson, H (2003) "Select Nontarget Arthropod Abundance i n Transgenic and Nontransgenic Field Crops in Ohio." Environmental Entomology. 32 (2): p 407

- 13. http://www.bioone.org/doi/abs/10.1603/0046

- 225X

- 32.2.407

. Jawson, MD; Franzluebbers; a nd Berg, RK (1989) "Bradyrhizobium japonicum survival in and soybean inoculation with Fluid Gels." Applied and Environmental Microbiology. 55 (3): p 617

- 22. http://www .ncbi.nlm.nih.gov/pmc/articles/PMC184169/pdf/aem00096

- 0083.pdf

.

243Jia, F; Ramaswamy, S; Sloderbeck, PE; Whitworth, J; and Thiessen, EJ (2007) "Crop Profile for Corn in the Northern and Central Plains (KS, NE, ND, and SD) " http://www.ipmcenters.org/cropprofiles/docs/NorthCentralCorn.pdf

. Jiang, CX; Chee, PW; Draye, X; Morrell, PL; Smith, CW; and Paterson, AH (2000) "Multilocus Interactions Restrict Gene Introgression in Interspec ific Populations of Polyploid Gossypium (Cotton)." Evolution. 54 (3): p 798

- 814. http://onlinelibrary.wiley.com/doi/10.1111/j.0014

- 3820.2000.tb00081.x/abstract

. Johnson, B and Nice, G (2009) "Weed Control in Wheat." Purdue University. https://ag.purdue.edu/btny/weedscience/documents/wheatweedcontrol09.pdf. Johnson, J; MacDonald, S; Meyer, L; Norrington, B; and Skelly, C (2014) "The World and United States Cotton O utlook." U.S. Department of Agriculture. http://www.usda.gov/oce/forum/2014_Speeches/Cotton.pdf

. Jones, C and Jacobsen, J (2003) "Micronutrients: Cycling, Testing and Fertilizer Recomme ndations." Montana State University Extension. http://msuextension.org/publications/AgandNaturalResources/4449/4449_7.pd f

. Kalaitzandonakes, N; Marks, LA; and Vickne r, SS (2005) "Sentiments and Acts Towards Genetically Modified Foods." International Journal of Biotechnology. 7 (1/2/3): p 161

- 77. http://www.ask

- force.org/w eb/Regulation/Kalaitzandonakes

- Sentiments

- Acts

2005.pdf

. Kammermeyer, K; Bowers, J; Cooper, B; Forster, D; Grahl, K; Holbrook, T; Martin, C; McDonald, S; Nicholson, N; VanBrackle, M; and Waters, G (2003) "Feral Hogs In Georgia: Disease, Damage and Control ." Georgia Department of Natural Resources. http://feralhogs.tamu.edu/files/2010/05/Feral

- Hogs

- in

- Georgia.pdf

. Kansas State University Agricultural Experiment Station and Coo perative Extension Service (2014) "2014 Chemical Weed Control for Field Crops, Pastures, Rangeland, and Noncropland." http://www.ksre.ksu.edu/bookstore/pubs/SRP1099.pdf

. Kansas State Univer sity Cooperative Extension (1998) "Grain Sorghum Production Handbook." Kansas State University Agricultural Experiment Station and Cooperative Extension Service. http://www.ksre.ksu.edu/bookst ore/pubs/c687.pdf

. Keeler, KH (1989) "Can Genetically Engineered Crops Become Weeds? ." Bio/Technology. 7 (11): p 1134

- 39. http://www.nature.com/nbt/journal/v7/n11/abs/nbt1189

- 1134.html

. Kiely, T; Donaldson, D; and Grube, A (2004) "Pesticides Industry Sales and Usage

- 2000 and 2001 Market Estimates." Biological and Economic Analysis Division, Office of Pesticide Programs, Office of Prevention, Pesticides, and Toxic Substances, US

EPA. http://www.epa.gov/pesticides/pestsales/01pestsales/market_estimates2001.pdf

. Kirkpatrick, TL and Thomas, AC "Crop Rotation for Management of Nematodes in Cotton and Soybean." http://www.uaex.edu/publications/pdf/FSA

- 7550.pdf

.

244Knodel, JJ; Beauzay, P; and Boetel, M (2013) "2013 Field Crop Insect Management Guide." North Dakota State University Extension Service Entomology. http://www.ag.ndsu.edu/pubs/plantsci/rowcrops/e1143.pdf

. Kok, H; Fjell, D; and Kilgore, G (1997) "Seedbed Preparation and Planting Practices

- Soybean Produ ction Handbook." Kansas State University. http://www.ksre.ksu.edu/mil/Resources/Crop%20Production%20Handbooks/ Soybeans.pdf

. Kong, G; Daud, MK; and Zhu, S (2010 ) "Effects of pigment glands and gossypol on growth, development and insecticide

- resistance of cotton bollworm (Heliothis armigera (Hübner))." Crop Protection 29 p 813

- 19. h ttp://www.sciencedirect.com/science/article/pii/S0261219410000839

. Konikow, LF (2013) "Groundwater Depletion in the United States (1900

- 2008)." United States Geological Survey. http://pubs.usgs.gov/sir/20 13/5079/

. Krapu, GL; Brandt, DA; and Cox, RR (2004) "Less Waste Corn, More Land in Soybeans, and the Switch to Genetically Modified Crops: Trends with Important Implications for Wildlife Management." Wildlife Society Bulletin, 2004. 32 (1): p 127

- 36. http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1065&context=usgsnpwrc

. Krausz, RF; Young, BG; Kapusta, G; and Matthews, JL (2001) "Influence of weed comp etition and herbicides on glyphosate

- resistant soybean ( Glycine max )." Weed Technology. 15 (3): p 530

- 34. http://www.bioone.org/doi/abs/10.1614/0890

- 037X%282001%29015%5B0530%3AIOWCAH%5D2.0.CO%3B2

. Kruger, GR; Johnson, WG; Weller, SC; Owen, MDK; Shaw, DR; WIlson, RG; Bernards, ML; and Young, BG (2009) "Weed pressure and problem weeds have changed with the adopt ion of Roundup Ready  crops." http://www.monsanto.com/weedmanagement/documents/benchmark

weedssummaryrept3.pdf

. Kuepper, G (2003) "Organic soybean production." Appropriate Technology Transfer for Rural Areas. http://www.coolbean.info/pdf/soybean_research/library/forage _an d_food_producti on/Organic_Soybean_Production.pdf

. Kuepper, G (2006) "Organic system plans: Field and row crops and pasture and range systems." Appropriate Technology Transfer for Rural Areas, National Sustainable Agriculture Information Service. https://at tra.ncat.org/attra

- pub/summaries/summary.php?pub=167. Landis, DA; Menalled, FD; Costamagna, AC; and Wilkinson, TK (2005) "Manipulating plant resources to enhance beneficial arthropods in agricultural landscapes." Weed Science. 53 (6): p 902

- 08. http://dx.doi.org/10.1614/WS

- 04

- 050R1.1

. Langemeier, LN (1997) "Soybean Production Handbook." http://www.ksre.ksu. edu/mil/Resources/Crop%20Production%20Handbooks /Soybeans.pdf

. Lassiter, RB; Lee, JA; Braxton, BB; and Peterson, MA (2014) "Investigation Into Post

- Harvest Control of 2,4

- D Tolerant Cotton." Procedings Beltwide Cotton Conference 2014 . Ed.
245National Cotton CO uncil. Dow AgroSciences LLC. https://ncc.confex.com/.../FINAL%20

- %20Abstract%20

- %20Post

- harvest%... Legleiter, T and Johnson, B (2013) "Stunted, Burned, and Crinkled Soybean Plants." Purdue University. https://ag.purdue.edu/btny/weedscience/Documents/PPO_ soybean.pdf. Legleiter, TR; Bradley, KW; and Massey, RE (2009) "Glyphosate

- resistant waterhemp ( Amaranthus rudis ) control and economic returns with herbicide programs in soybean." Weed Technology. 23 (1): p 54

- 61. http://www.bioone.org/doi/abs/10.1614/WT

- 08

- 069.1

. Lemieux, PM; Lutes, CC; and Santoianni, DA (2004) "Emissions of organic air toxics from open burning: a comprehensive review." Progress in En ergy and Combustion Science. 30 (1): p 1

- 32. http://www.sciencedirect.com/science/article/pii/S0360128503000613

. Lenat, DR and Crawford, JK (1994) "Effects of land use on water quality and aquatic biota of three North Carolina piedmont streams." Hydrobiologia. 294 (3): p 185

- 99. http://link.springer.com/article/10.1007%2FBF0 0021291

. Lendman, S (2014) "Potential Health Hazards of Genetically Engineered Foods." http://www.globalresearch.ca/potential

- health

- hazards

- of

- genet ically

engineered

- foods/8148

. Leonard, BR (2007) "Cotton Aphid Population Dynamics and Control Strategies in Conservation Tillage Cotton Fields." http://www.cottoninc.com/fiber/Agricultural

Research/Agricultural

- Meetings

- Conferences/Conservation

- Tillage

- Conferences/2007

- Presentations/ Cotton%20Aphid%20Population%20Dynamics%20And%20Control%20St rategies.pdf Lordelo, MM; Calhoun, MC; Dale, NM; Dowd, MK; and Davis, AJ (2007) "Relative toxicity of gossypol enantiomers in laying and broiler breeder hens." Poultry Science. 86 (3): p 582

- 90. http://www.ncbi.nlm.nih.gov/pubmed/17297172

. Lorenz, G; Johnson, DR; Studebaker, G; Allen, C; and Young, S (2006) "Insect Pest Management in Soybeans " University of Arkansas Division of Agricultur e Cooperative Extension Service. http://www.uaex.edu/publications/pdf/MP197/chapter12.pdf

. Louisiana State University Research and Extension (2013) "Louisiana Suggested Chemical Weed Management Guide." http://www.lsuagcenter.com/en/communicati ons/publications/Publications+Catal og/Crops+and+Livestock/Weed+Control/Louisiana+Suggested+Chemical+Weed+Manag ement+Guide_seriespage

- 2.htm

. Loux, MM; Stachler, JM; Johnson, WG; Nice, G; and Bauman, TT (2008) "Weed Control Guide for Ohio Field Crops " Ohio State University Extension. http://ohioline.osu.edu/b789/index.html

. LSU

- Extension (2014) "Sugarcane Yearly Rotation Poster." http://www.lsuagcenter.com/en/communications/publications/Publications+Catal og/Crops+and+Livestock/Sugarcane/Sugarcane

- Yearly

- Crop

- Rotation

- Poster.htm

.

246Luginbuhl, J; Poore, M; and Conrad, A (2000) "Effect of Level of Whole Cottonseed on Intake, Digestibility, and Performance of Growing Male Goats Fed Hay

- based Diets." 78 p 1677

- 83. http://www.ncbi.nlm.nih.g ov/pubmed/10875652

. Lyles, L and Woodruff, NP (1962) "How Moisture and Tillage Affect Soil Cloddiness for Wind Erosion Control." Agricultural Engineering. 43 (3): p 150

- 53. http: //weru.ksu.edu/new_weru/publications/Andrew_pdf/646.pdf

. MacGowan, B; Humberg, L; Beasley, J; DeVault, T; Retamosa, M; and Rhodes, O (2006) "Corn and Soybean Crop Depredation by Wildlife." Purdue Extension, Department of Forestry and Natural Resources. http://www.ces.purdue.edu/extmedia/FNR/FNR

- 265

- W.pdf

. Madden, NM; Southard, RJ; and Mitchell, JP (2009) "Soil Water Content and Soil Disaggregation by Disking Affects PM10 Emissions." Journa l of Environmental Quality. 38 p 36

- 43. http://www.pubfacts.com/fulltext_frame.p hp?PMID=19141793&title=Soil%20water %20content%20and%20soil%20disaggregation%20by%20disking%20affects%20PM10 %20emissions

. Malarkey, T (2003) "Human health concerns with GM crops." Mutation Research. 544 (2

- 3): p 217

– 21. http://www.ncbi.nlm.nih.gov/pubmed/14644323

. Mapel, SL (2004) "Effect of Cottonseed Meal Consumption on Performance of Female Fallow Deer " Texas A&M University. Dissertations and Theses

. http://repository.tamu.edu/bitstream/handle/1969.1/325/etd

- tamu

- 2004A

- ANSC

Mapel

- 1.pdf?sequence=1

. Maraseni, TN and Cockfield, G (2011) "Does the adoption of zero tillage reduce greenhous e gas emissions? An assessment for the grains industry in Australia." Agricultural Systems. 104 (6): p 451

- 58. http://www.sciencedirect.com/science/article/pii/S0308521X1100 031X

. Marra, MC and Piggott, NE (2006) "The Value of Non

- Pecuniary Characteristics of Crop Biotechnologies: A New Look at the Evidence." Natural Resource Management and Policy. 30 p 145

- 77. http://link.springer.com/chapter/10.1007%2F978

- 0

- 387

- 36953

- 2_8

. Marshall, M (2012) "2012 Herbicide Programs For Weed Control in Cotton " http://www.clemson.edu/extension/county/hampton/programs/row_crops/Cotton/mikem arshall.pdf

. Martinson, K and Peterson, P (2013) "Managing established horse pastures." http://www.extension.umn.edu/agriculture/horse/pasture/managing

established

- horse

- pastures/

. McBride, WD and Green, C (2008) "The Profitability of Organic Soybean Production." http://ageconsearch.umn.edu/bitstream/6449/2/465035.pdf

. McCauley, A; Jones, C; and Jacobsen, J (2005) "Basic Soil Properties." Montana State University Extension Services. http://landresources.montana.edu/swm/documents/Final_proof_SW1.pdf

.

247McClelland, MR; Smith, KL; and Norsworthy, JK (2006) "Managing Glyphosate

- Resistant Horseweed in Conservati on

- Tillage Cotton Production: Final Summary and Recommendations." http://arkansasagnews.uark.edu/552

- 22.pdf

. McCray, K. "Ground water: Out of sight, but not out of mind." Focus on Agriculture 2012. http://www.fb.org/newsroom/focus/fo2012/fo0312.html

. McGuire, A (2006) "The Effects of Reducing Tillage on Pest Management." Washington State University. http://www.tfrec.wsu.edu/pdfs/P1701.pdf McMahon, K (2011) "Commodity prices right to double

- crop soybeans in wheat stubble." http://farmindustrynews.com/soybean

- varieties/commodity

- prices

- right

- double

crop

- soybeans

- wheat

- stubble

. Memon, N (2012) "Organic Cotton: Biggest Markets Are Europe and the United States." Pakistan Textile Journal. PTJ March 2012 p 42

- 43. http://ptj.com.pk/Web

- 2012/03

- 2012/March

- 2012

- PDF/Organic

- Cotton

- Dr

- Noor.pdf Mensah, EC (2007) "Factors That Affect the Adoption of Roundup Ready Soybean Technology in the U.S. ." Journal of Economic Development and Business Policy. Volume 1. http://www.jepson.gonzaga.edu/JEDBP/Volumes/V1papers/Mensah.pdf

. Merchant, RM; Sosnoskie, LM; Culpepper, SA; Steckel, LE; York, A; Braxton, LB; and Ford, J (2013) "Weed Response to 2,4

- D, 2,4

- DB, and Dicamba Applied Alone or with Glufosinate." The Journal of Cotton Science. 17 p 212

- 18. http://www.cotton.org/journal/2013

- 17/3/212.cfm

. Meyer, L; MacDonald, S; and Foreman, L (2007) "Cotton backgrounder

. " http://www .ers.usda.gov/publications/cws

- cotton

- and

- wool

- outlook/cws

07b01.aspx

. Mississippi State University (2013) "United States Cotton Losses, 2012." http://www.entomology.msstat e.edu/resources/croplosses/2012loss.asp

. Mississippi State University (2014) "2014 Insect Control Guide for Agronomic Crops." Extension Service of Mississippi State University. http://msucares .com/pubs/publications/p2471.pdf

. Mississippi State University Extension Service (1996) "Ecology and Management of the Louisiana Black Bear." http://icwdm.org/Publications/pdf/Bears/bears MSU.pdf

. Mitchell, JP; Carter, L; Munk, DS; Klonsky, KM; Hutmacher, RB; Shrestha, A; DeMoura, R; and Wroble, JF (2012) "Conservation tillage systems for cotton advance in the San Joaquin Valley." California Agriculture. 66 (3): p 108

- 15. http://ucce.ucdavis.edu/files/repositoryfiles/ca6603p108

- 95385.pdf

. Mithila, J; Hall, C; Johnson, WG; Kelley, KB; and Riechers, DE (2011) "Evolution of Resistance to Auxinic Herbicides: Histo rical Perspectives, Mechanisms of Resistance, and Implications for Broadleaf Weed Management in Agronomic Crops." Weed Science. 59 (4): p 445

- 57. http://dx.doi.org/10.1614/WS

- D

- 11

- 00062.1

.

248Moechnig, M; Deneke, D; and Wrage, L (2010) "Weed Control in Sorghum 2010." South Dakota State University Extension. http://www.sdstate.edu/ps/extension/weed

mgmt/upload/FS525D.pdf

. Moechnig, M; Deneke, D; Wrage, L; Alms, J; Vos, D; Rosenberg, M; Szczepaniec, A; Hadi, B; and Ruden, K (2013) "2013 South Dakota Crop Protection Guide: Soybeans: Common Insect and Mite Pests." South Dakota State University. http://igrow.org/up/resources/03

- 3000

- 2013_3.pdf

. Moechnig, M and Wrage, LJ (2012) "Weed Control in Small Grains: 2012." http://www .sdstate.edu/ps/extension/weed

- mgmt/upload/Small

- grains

- final.pdf

. Monsanto (2004) "Petition for the Determination of Nonregulated Status for MON 88017 Corn." Submitted by Sinhu, Ravinder, Registration Manager. Monsanto Company. St. Louis, MO. http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

. Monsanto (2010) "Planting Soybean After Soybean." Monsanto (2012a) "Petition for the Determination of Nonregu lated Status for Dicamba

- Tolerant Soybean MON 87708." Submitted by Mannion, Rhonda M., Registration Manager. Monsanto Company. St. Louis, MO. http://www.aphis.usda.gov/brs/aphisdocs/10_ 18801p.pdf

. Monsanto (2012b) "Petition for the Determination of Nonregulated Status for Dicamba and Glufosinate

- Tolerant Cotton MON 88701." Submitted by Marianne Malven, Registration Manager. Monsanto Company. St. Louis, MO. http://www.aphis.usda.gov/brs/aphisdocs/12_18501p.pdf

. Monsanto (2013a) "Petitioner's Environmental Report for Dicamba

- Tolerant Soybean MON 87708 and Dicamba and Glufosinate Tolerant Cotton MON 88701." Monsanto (201 3b) "Petitioner’s Environmental Report for Dicamba

- Tolerant Soybean MON 87708 and Dicamba

- and Glufosinate

- Tolerant Cotton MON 88701." Monsanto Company. Monsanto (2013c) "RoundupReady Extend. Dicamba Basics." http://www.roundupreadyplus.com/Content/assets/docs/forum/NeedToKnow_Di cambaBasics.pdf

. Monsanto (2013d) "Supplemental Information to Support the NEPA Analy sis for the Determination of Nonregulated Status of Dicamba

- Tolerant Soybean MON 87708 and Dicamba

- and Glufosinate

- Tolerant Cotton MON 88701." Monsanto Company. For OECD Unique Identifiers: MON

- 87708

- 9 (soybean) and MON

- 88701

- 3 (cotton). http://www.aphis.usda.gov/brs/aphisdocs/monsanto_submitted_eis_supp.pdf

. Monsanto (2014a) "Supplemental Information to Support the NEPA Analys is for the Determination of Nonregulated Status of Dicamba

- Tolerant Soybean MON 87708 and Dicamba

- and Glufosinate

- Tolerant Cotton MON 88701." Submitted by Mannion, Rhonda, Registration Manager. Monsanto Company. Monsanto (2014b) "Supplemental Informatio n to Support the NEPA Analysis for the Determination of Nonregulated Status of Dicamba

- Tolerant Soybean MON 87708 and

249Dicamba

- and Glufosinate

- Tolerant Cotton MON 88701. Impact and Benefits of Dicamba

- Tolerant Soyb ean and Dicamba and Glufosinate

- Tolerant Cotton on Weed Resistance Management

. " Mora, MA (1997) "Feeding flights of cattle egrets nesting in an agricultural ecosystem." Southwestern Naturalist. 42 (1): p 52

- 58. http://www.jstor.org/stable/30054060

. Morgan, GD; Fromme, DA; Baumann, PA; Grichar, J; Bean, B; Matocha, ME; and Mott, DA (2011) "Managing Volunteer Cotton in Grain Crops (Corn, Sorghum, Soybean, and Wheat)

. "
Mortensen, DA; J.F., E; Maxwell, BD ; Ryan, MR; and Smith, RG "Navigating a Critical Juncture for Sustainable Weed Management." American Institute of Biological Sciences. http://bioscience.oxfordjournals.org/content/6 2/1/75.short

. Mossler, MA (2013) "Florida Crop/Pest Management Profile: Cotton " University of Florida IFS Extension. http://edis.ifas.ufl.edu/pi220

. Mueller, TC; Mitchell, PD; Young, BG; and Culpepper, AS (20 05) "Proactive versus reactive management of glyphosate

- resistant or

- tolerant weeds." Weed Technology. 19 (4): p 924

- 33. http://wssajournals.org/doi/abs/10.1614/WT

- 04

- 297R.1?=

. Muensch er, W (1939) Weeds . New York and London: Cornell University Press.

Muñoz

- Carpena, R; Shukla, S; and Morgan, K (2006) "Field Devices for Monitoring Soil Water Content." Southern Regional Water Program Publication. http://www.bae.ncsu.edu/topic/go_irrigation /docs/Field

- devices

- monitoring

- .pdf

. Musser, F; Catchot, A; Davis, J; Herbert, D; Lorenz, G; Reed, T; Reisig, D; and Stewart, S (2013) "2012 Soybean Insect Losses in the Southern US." http://www.cals.ncsu.edu/entomology/sites/default/files/2013%20Musser%20et%20 al.%20Soybean%20insect_0.pdf

. Nafziger, E (2007) "What Will Replace the Corn

- Soybean Rotation? ." http://www.agry.purdue.edu/CCA/2007/2007/Proceedings/Emerson%20Nafziger

CCA%20proceedings_KLS.pdf

. National Center for Appropriate Technology (2 003) "NCAT’s Organic Crops Workbook A: Guide to Sustainable and Allowed Practices." National Center for Appropriate Technology. http://www.agrisk.umn.edu/cache/arl04288.pdf

. National Corn Growers Association (2007) "Sustainability

- Conserving and Preserving: Soil Management and Tillage." http://www.ncga.com/uploads/useruploads/conservingpreservingsoilma nageme nt.pdf National Cotton Council of America (2014) "The Economic Outlook for U.S. Cotton 2014." National Cotton Council of America. https:// www.cotton.org/econ/reports/annual

outloo k.cfm

. National Cottonseed Products Association (2002) "Cottonseed feed products guide." http://www.cottonseed.com/publications/feedproductsguide.asp

. 250National Land Cover Database (2014) "National Land Cover Database 2006 (NLCD2006)." U.S. Geological Survey. http://www.mrlc.gov/nlcd06_leg.php

. National Soybean Research Laboratory "Soybean Production Basics." http://www.nsrl.illinois.edu/general/soyprod.html

. NBII (2010) "United States Regulatory Agencies Unified Biotechnology Website " NCAT (2003) "NCAT’s Organic Crops Workbook A: Guide to Sustainable and Allowed Pr actices. National Center for Appropriate Technology (NCAT)." National Center for Appropriate Technology. http://www.agrisk.umn.edu/cache/arl04288.pdf

. NCGA (2007) "Sustainability

- Conserving and Preserving: Soil Management and Tillage. National Corn Growers Association (NCGA)." http://www.ncga.com/uploads/useruploads/conservingpreservingsoilmanagem ent.p df NCPA (2002) "Cottonseed Feed Products Guide. National Cottonseed Products Association (NCPA)." http://www.cottonseed.com/publications/feedproductsguide.asp

. Nelson, RG; Hellwi nckel, CM; Brandt, CC; West, TO; De La Torre Ugarte, DG; and Marland, G (2009) "Energy use and carbon dioxide emissions from cropland production in the United States, 1990

- 2004." Journal of Environment Quality. 38 (2): p 418

- 25. http://www.ncbi.nlm.nih.gov/pubmed/19202012

. Neve, P; Norsworthy, JK; Smith, KL; and Zelaya, IA (2011) "Modelling evolution and management of glyphosate resistance in Amaranthus palmeri." Weed Research. 51 (2): p 99

- 112. http://onlinelibrary.wiley.com/doi/10.1111/j.1365

- 3180.2010.00838.x/full

. New, L and Fipps, G (2000) "Center Pivot Irrigation." Texas Water Resources Institute. http://irrigationtraining.tamu.edu/south

- texas/technologies

- bmps/center

- pivot

irrigation /

. Nice, G and Johnson, B (2005) "Indiana's top ten most problematic weeds." Purdue Extension. http://www.btny.purdue.edu/WeedScience/2005/topten05.pdf

. Norsworthy, JK; Ward, SM; Shaw, D R; Llewellyn, RS; Nichols, RL; Webster, TM; Bradley, KW; Frisvold, G; Powles, SB; Burgos, NR; Witt, WW; and Barrett, M (2012) "Reducing the Risks of Herbicide Resistance: Best Management Practices and Recommendations." Weed Science. 12 (31

- 62): p 32. http://www.wssajournals.org/doi/pdf/10.1614/WS

- D

- 11

- 00155.1

. North

- Carolina

- Cooperative

- Extension (1994) "Pests of Cotton." http://ipm.ncsu.edu/AG271/cotton/cotton.html

. North American Plant Protection Organization (2003) "NAPPO Regional Standards for Phytosanitary Measures (RSPM)." North American Plant Protection Organization. http://www.nappo.org/en/data/files/download/ArchivedStandars/RSPMNo. 14

- Oct03

- e.pdf

. North Carolina Department of Agriculture and Consumer Services (2010) "Wildlife damage to N.C. field crops totals $29.4 mi llion." http://www.ncagr.gov/paffairs/release/2010/3

- 10wildlifedamage.htm

. 251North Dakota State University "Chemical Weed Control for Field Crops: Hard Red Spring and Durum Whe at, Winter Wheat and Barley." http://www.ag.ndsu.edu/weeds/weed

- control

guides/nd

- weed

- control

- guide

- 1/wcg

- files/3.1

- Wheat.pdf

. NRC (2004) "New Approaches for Identifying Unintended Changes in Food Composition. Committee on Identifying and Assessing Unintended Effects of Genetically Engineered Foods on Human Health, National Research Council (NRC)." Safety of Genetically Engineered Foods: Approac hes to Assessing Unintended Health Effects . Washington, D.C.: Institute of Medicine and National Research Council, National Academies Press. p 73

- 102. http://www.ncbi.nlm.nih.gov/books/NBK215761/

. NRC (2010a) The Impact of Genetically Engineered Crops on Farm Sustainability in the United States . Washington, D.C.: National Academies Press

- The National Academies Press. http://www.nap.ed u/catalog.php?record_id=12804

. NRC (2010b) The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Committee on the Impact of Biotechnology on Farm

- Level Economics and Sustainability; National Research Council (NRC) . Nationa l Academies Press

- The National Academies Press. http://www.nap.edu/catalog.php?record_id=12804

. NSRL (No Date) "Soybean Production Basics." National Soybean Research Laboratory. http://www.nsrl.illinois.edu/general/soyprod.html

. Nufarm. "Weedar 64. 2,4

- D Amine Weed Killer Label." Undated. OECD (1999) "Consensus Document on General Information Concerning the Genes and Their Enzym es that Confer Tolerance to Glyphosate Herbicide." Environment Directorate, Organisation for Economic Co

- operation and Development. Last Accessed: November 2, 2012 http://www.oecd. org/science/biosafety

- biotrack/46815618.pdf

. OECD (2000) "Consensus Document on the Biology of Glycine max (L.). Merr. (Soybean)." http://www.oecd.org/dataoecd/16/56/46815668.pdf

. OECD (2004) "Consensus document on the compositional considerations for new varities of cotton ( Gossypium hirsutum and Gossypium barbadense ): Key food and feed nutrients and anti

- nutrients

. " OECD (2008a) "Consensus Document on the Biology of Cotton (Gossypium spp.)." Environment Directorate, Organization for Economic Co

- operation and Development. Last Accessed: November 2, 2012 http://www.oecd.org/science/biosafety

biotrack/46815918.pdf

. OECD (2008b) "Consensus document on the biology of cotton (Gossypium spp.). ." Organization for Economic Co

- operation and Development. Last Accessed: November 2, 2012 http://www.oecd.org/science/biosafety

- biotrack/46815918.pdf

. OECD (2009a) "Consensus document on the compositional considerations for new varieties of cotton ( Gossypium hirsutum and Gossypium barbadense ): Key food and feed nutrients and anti

- nutrients [ENV/JM/MONO(2004)16]

. " http://www.oecd.org/science/biotrack/46815236.pdf

.

252OECD (2009b) "Consensu s document on the compositional considerations for new varities of cotton ( Gossypium hirsutum and Gossypium barbadense ): Key food and feed nutrients and anti

- nutrients

. " OGTR (2008) "The Biology of Gossypium hirsutum L. and Gossypiu m barbadense L. (cotton), version 2.

. " http://www.ogtr.gov.au/internet/ogtr/publishing.nsf/content/cotton

3/$FILE/biologycotton08.pdf

. OTA (2010 ) "Organic Cotton Facts." Organic Trade Association. https://ota.com/sites/default/files/indexed_files/Organic

- Cotton

- Facts.pdf. OTA. "2010 and Preliminary 2011 U.S. Organic Cotton Production & Marketing Trends." Organic Trade Association, 2012. http://www.organicnewsroom.com/2012/01/us_organic_cotton_acreage_cont.html

. OTA (2014) "2012 and Preliminary 2013 U.S. Organic Cotton Production & Marketing Trends." Organic T rade Association. https://ota.com/sites/default/files/indexed_files/2012%20and%202013%20Organic%20C otton%20Report.pdf. Owen, M (2014a) "Pest resistance: Overall principles and implications on evolved herbicide resistance in Iowa

. " https://store.extension. iastate.edu/Product/2014

- Herbicide

- Guide

for

- Iowa

- Corn

- and

- Soybean

- Production. Owen, MD; Young, BG; Shaw, DR; Wilson, RG; Jordan, DL; Dixon, PM; and Weller, SC (2011) "Benchmark study on glyphosate

- resistant crop systems in the United States. Part 2: Persp ectives." Pest Management Science. 67 (7): p 747

- 57. http://www.ncbi.nlm.nih.gov/pubmed/21452168

. Owen, MD and Zelaya, I (2005) "Herbicide

- resistant crops and weed resistance to herbicides " Pest Management Science. 61 p 301

- 11. http://www.weeds.iastate.edu/weednews/2005/Herbicide

resistant%20crops%20and%20weed%20r esistance%20to%20herbicides.pdf

. Owen, MDK (2008) "Weed species shifts in glyphosate

- resistant crops." Pest Management Science. 64 p 377

- 87. Owen, MDK (2012) "Assessment of herbicide resistance in Iowa." http://www.weeds.iastate.edu/mgmt/2012/resistancereport.html

. Owen, MDK (2014b) "2014 Herbicide Guide for Iowa Corn and Soybean Production." Iowa State University. http://www.w eeds.iastate.edu/WC94.pdf

. Owen, MDK (2014c) "2014 Herbicide Guide for Iowa Corn and Soybean Production: Weed management update for 2014." Iowa State University Extension and Outreach. https://store.extension.iastate.edu/Product/2014

- Herbicide

- Guide

- for

- Io wa

- Corn

- and

Soybean

- Production. Palmer, W and Bromley, P (NoDate) "Pesticides and Wildlife

- Cotton." North Carolina Cooperative Extension Service. Last Accessed: March 26, 2014 http://ipm.n csu.edu/wildlife/cotton_wildlife.html

.

253Papendick, RI and Moldenhauer, WC (1995a) "Crop Residue Management To Reduce Erosion and Improve Soil Quality: Northwest." USDA

- Agricultural Research Service. http://eprints.nwisrl.ars.usda.gov/1205/1/878.pdf

. Papendick, RI and Moldenhauer, WC (1995b) "Crop Residue Management To Reduce Erosion and Improve Soil Quality: Northwest." USDA Agricultural Research Service. http://eprints.nwisrl.ars.usda.gov/1205/1/878.pdf

. Paz Celorio

- Mancera, Mdl; Seung

- Joon Ahn; Heiko Vogel; and Heckel., DG (2011) "Transcriptional responses underlying the hormetic and detrimental effects of the plant secondary m etabolite gossypol on the generalist herbivore Helicoverpa armigera." BMC Genomics. 12 p 575. Last Accessed: March 27, 2014 http://www.biomedcentral.com/1471

- 2164/12/575

. Pedersen, P; Lauer, J; Grau, C; and Gaska, J (2001) "Raising Non

- Rotation Soybean." University of Wisconsin

Madison. http://www.soils.wisc.edu/extension/wcmc/proceedin gs01/Pedersen

- etal.PDF

. Peet, M (2001) "Conservation Tillage." North Carolina State University. Last Accessed: December 5, 2010 http://www.ncsu.edu/sustainable/tillage/tillage.html

. PennS tate

- Extension (2013a) "Agronomy Guide: Crop and Soil Management,Table 2.2

- 7, Characteristics of "burndown" herbicides for no

- till corn " http://extension.psu.edu/agronomy

- guide/ pm/tables/table

- 2

- 2

- 7

. PennState

- Extension (2013b) "Table 2.2

- 7. Characteristics of "burndown" herbicides for no

- till corn " http://extension.psu.edu/agronomy

- guide/pm/tables/tab le

- 2

- 2

- 7

. Percy, R and Wendel, J (1990) "Allozyme evidence for the origin and diversification of Gossypium barbadense L " Theoritical and Applied Genetics. 79 p 529

- 42. http://www.ncbi.nlm.nih.go v/pubmed/24226459

. Peterson, D and D., S (2012) "Plan now for good marestail control in soybeans." http://www.agprofe ssional.com/resource

- centers/soybean/news/Plan

- now

- for

good

- marestail

- control

- in

- soybeans

- 143657086.html

. Place, G; Smith, A; Dunphy, J; and Reberg

- Horton, C (2009) "Planting Rate Recommendations for Organic Soybean Producers." North Carolina State Univers ity, Department of Crop Science. http://content.ces.ncsu.edu/planting

- rate

- recommendations

- for

- organic

- soybean

producers.pdf

. Pleasants, J and Wende ll, J (2005a) "Assessment of potential for gene flow between transgenic cotton and the endemic Hawaiian cotton

- Final Report. ." Pleasants, J and Wendell, J (2005b) "Assessment of potential for gene flow between transg enic cotton and the endemic Hawaiian cotton

- Final Report: Report to the EPA." http://www.ncwss.org/proceed/2005/proc05/abstracts/129.pdf

. Prather, T (2014) "Weed Control in Pasture and Rangeland." Peachey, Ed. Last Accessed: 4

- 10

- 14 http://pnwhandbooks.org/weed/

. Price, GK; W. Lin; J.B. Falck

- Zepeda; and Fernandez

- Cornejo, J. "The Size and Distri bution of Market Benefits from Adopting Agricultural Biotechnology, Technical Bulletin No. (TB

2541906)." Washington: USDA Economic Research Service, 2003. 44. http://www.e rs.usda.gov/publications/tb

- technical

- bulletin/tb1906.aspx

. Prince, JM; Shaw, DR; Givens, WA; Newman, ME; Owen, MDK; Weller, SC; Young, BG; Wilson, RG; and Jordan, DL (2012a) "Benchmark Study: II. A 2010 Survey to Assess Grower Awareness of and Attitudes t oward Glyphosate Resistance." Weed Technology. 26 (3): p 531

- 35. Last Accessed: 2014/04/11 http://dx.doi.org/10.1614/WT

- D

- 11

- 00091.1

. Prince, JM; Shaw, DR; Givens, WA; Owen, MDK; Weller, SC; Young, BG; Wilson, RG; and Jordan, DL (2012b) "Benchmark Study: IV. Survey of Grower Practices for Managing Glyphosate

- Resistant Weed Populations." Weed Technology. 26 (3): p 543

- 48. Last Accessed: 2014/04/13 http://dx.doi.org/10.1614/WT

- D

- 11

- 00094.1

. "Food Quality Protection Act." Pub. L. No. 104

– 170, S. http://www.gpo.gov/fdsys/pkg/PLAW

104publ170/html/PLAW

- 104publ170. htm

. Radosevich, SR; Holt, JS; and Ghersa, CM (2007) Ecology of Weeds and Invasive Plants: Relationship to Agriculture and Natural Resource Management . John Wiley & Sons, Inc., Hoboken, New Jersey. http://www.wiley.com/WileyCDA/WileyTitle/productCd

0471767794.html

. Randall, GW; Evans, SD; Lueschen, WE; and Moncrief, JF (2002a) "Tillage Best Management Practices for Corn

- Soybean Rotations in the Minnesota River Basin

- Soils, Landscape, Climate, Crops, and Economics WW

- 06676." University of Minnesota Extensions. Last Accessed: May 18, 2011 http://www.extension.umn.edu/distribution/naturalresources/DD6676.html

. Randall, GW; Evans, SD; Lueschen, WE; and Moncrief, JF (2002b) "Tillage Best Management Practices for Corn

- Soybean Rotations in the Minnesota River Basin Based On Soils, Landscape, Climate, Crops, and Economics (FO

- 6676)." University of Minnesota Extensions. Last Accessed: May 18, 2011 http:// www.extension.umn.edu/agriculture/tillage/tillage

- systems/tillage

- best

management

- practices

- for

- corn

- soybean

- rotations/

. Raper, CD, Jr. and Kramer, PJ (1987) "Stress Physiology." Soybeans: Improvement, Production and Uses . Madison, WI: American Society of Agronomy. p 589

- 641. https://dl.sciencesocieties.org/publications/books/tocs/agronomymonogra/soybeansimpro

ve. Reeves, JB and Weihrauch, JL (1979) "Composition of Foods: Fats and Oils

- Raw, Processed, Prepared

. " http://naldc.nal.usda.gov/naldc/download.xhtml?id=CAT87209368&content= PDF

. Riar, DS; Norsworthy, JK; Bararpour, MT; Bell, HD; and Schrage, BW (2012) "Activation and length of residual hervicides under furrow and sprinkler irrigation ." Summaries of Arkansas Cotton Research 2012. AAES Research Series p 107

- 12. http://arkansasagnews.uark.edu/610

- 19.pdf

. Riar, DS; Norsworthy, JK; Steckel , LE; Stephenson, DO; and Bond, JA (2013) "Consultant Perspectives on Weed Management Needs in Midsouthern United States Cotton: A

255Follow

- Up Survey." Weed Technology. 27 (4): p 778

- 87. Last Accessed: 2014/04/14 http://dx.doi.org/10.1614/WT

- D

- 13

- 00070.1

. Riar, DS; Norsworthy, JK; Steckel, LE; Stephenson, I, D. O.; Eubank, TW; and Scott, C (2013 ) "Assessment of Weed Management Practices and Problem Weeds in the Midsouth United States

- Soybean: A Consul tant's Perspective." Weed Technology. 27 (3): p 612

- 22. http://www.bioone.org/doi/pdf/10.1614/WT

- D

- 12

- 00167.1

. Rippey, B (2004) "U.S. Drought Monitor CONUS." USDA. http://droughtmonitor.unl.edu

. Ritchie, SW; Hanway, JJ; and Benson, GO (2008) "How a Corn Plant Develops: Special Report No. 48." Iowa State University of Science and Technology, Cooperative Extension Service. http://www.virtual.chapingo.mx/dona/paginaCBasicos/howgrowcorn.pdf

. Robertson, A; Nyvall, RF; and Martinson, CA (2009) "Controlling Corn Diseases in Conservation Tillage." Iowa State University, University Extension. https://store.extension.iastate.edu/Product/Controlling

- Corn

- Diseases

- in

- Conservation

Tillage. Robertson, B; Smith, K; Scott, B; and Studebaker, G (2002) "Options For Chemical Stalk Termination." https:// www.uaex.edu/farm

- ranch/crops

- commercial

horticulture/cotton/Chemical%20Stalk%20Destruction.pdf

. Rodoni, S; Mühlecker, W; Anderl, M; Kräutler, B; Moser, D; Thomas, H; Matile, P; and Hörtensteiner, S (1997) "Chlorophyll breakdown in senescent chloroplasts: Cleavage of pheophorbide α in two enzymic steps." Plant Physiology. 115 p 669

- 76. http://www.ncbi.n lm.nih.gov/pmc/articles/PMC158527/

. Rolph, CE; Moreton, RS; and Harwood, JL (1990) "Control of acyl lipid desaturation in the yeast Rhodotorula gracilis via the use of the cyclopropenoid fatty acid, sterculate." Applied Microbiology and Biotechnology. 34 ( 1): p 91

- 96. http://link.springer.com/article/10.1007%2FBF00170930

. Rosenzweig, C; Iglesius, A; Yang, XB; Epstein, PR; and Chivian, E (2001) "Climate change and extreme weather events

- I mplications for food production, plant disease s, and pests." Ross, MA and Childs, DJ (2011) "Herbicide Mode

- of

- Action Summary." Cooperative Extension Service, Perdue University. http://www.extension.purdue.edu/extmedia/WS/WS

- 23

- W.html

. Roth, G (2011) "Between the Rows: Organic Corn Production " Penn State. http://extension.psu.edu/plants/crops/grains/corn/production/between

- the

- rows

organic

- corn

- production

. Rude, PA (1984) Integrated Pest Manag ement for Cotton in the Western Region of the United States . University of California. http://anrcatalog.ucanr.edu/Details.aspx?itemNo=3305

. Rude, PA (1996) Integrated Pest Management for Cotton in the Western Region of the United States . Ed. Group, IPM Manual. Davis, CA: University of California. http://anrcatalog.ucanr.edu/Details.aspx?itemNo=3305

. Saha, S; Raska DA; an d DM., S (2006) "Upland Cotton (Gossypium hirsutum L.) x Hawaiian Cotton (G. tomentosum Nutt. ex Seem.) F1 Hybrid Hypoaneuploid Chromosome

256Substitution Series. ." Journal of Cotton Science 10 p 263

- 72. http://www.cotton.org/journal/2006

- 10/4/upload/jcs10

- 263.pdf

. Sammons, RD; Heering, DC; Dinicola, N; Glick, H; and Elmore, GA (2007) "Sustainability and stewardship of glyphosate and glyphosate

- resistant crops." W eed Technology. 21 (2): p 347

- 54. http://www.bioone.org/doi/pdf/10.1614/WT

- 04

- 150.1

. Sandretto, C and Payne, J (2006) "Soil Management and Conservation." U.S. Department of Agriculture, Econ omic Research Service. http://www.ers.usda.gov/publications/eib

economic

- information

- bulletin/eib16.aspx

. Schaible, GD and Aillery, MP (2012a) "Water Conserva tion in Irrigated Agriculture: Trends and Challenges in the Face of Emerging Demands." USDA

ERS. http://www.ers.usda.gov/publications/eib

- economic

- information

bulletin/eib99.aspx

. Schaible, GD and Aillery, MP (2012b) "Water Conservation in Irrigated Agriculture: Trends and Challenges in the Face of Emerging Demands." USDA

- ERS. Schmidhuber, J and Tubiello, FN (2007) "Global food security under climate change ." PNAS. 104 (50): p 19703

- 08. http://www.pnas.org/content/104/50/19703.full?sid

. Schneider, RW and Strittmatter, G (2003) "Petition for Determination of Nonregulated Status for Roundup Ready ® Sugar beet H7

- 1

. " http://www.aphis.usda.gov/brs/aphisdocs/03_32301p.pdf

. Schowalter, T (2014) "2014 Louisiana Insect Pest Management Guide." Louisiana State U niversity. http://www.lsuagcenter.com/en/communications/publications/management_g uides/Louisiana+Insect+Pest+Management+G uide.htm

. Seed Today (2009) "OSU Specialist Finds Yields Increase with Rhizobial Inoculants." Country Journal Plublishing Co. http:// www.seedtoday.com/articles/OSU_Specialist_Finds_Yield_Increase_with_Rhi zobial_Inoculants

- 72101.html

. Service, NCCE (No Date) "Soybean Insect Pests." North Carolina Cooperative Extension Service. http://ipm.ncsu.edu/soybeans/insects/insects_soybeans.html

. Service, PUCE (1999) "Common Soybean Insects." Purdue University. http://extension.entm.purdue.edu/publications /E

- 85.pdf

. Shaner, DL (2014 ) "Lessons Learned From the History of Herbicide Resistance." Weed Science. 62 (2): p 427

- 31. http://www.bioone.org/doi/abs/10.1614/WS

- D

- 13

- 00109.1

. Sharpe, T (2010a) "Cropland Management." Tarheel Wildlife: A Guide for Managing Wildlife on Private Lands in North Carolina . Raleigh: North Carolina Wildlife Resources Commission. p 80. http://www.ncwildlife.org/portals/0/Conserving/documents/TarheelWildlife/Tarheel_ Wildlife.pdf

. Sharpe, T. "Tarheel wildlife

- A guide for managing wildlife on private lands in North Carolilna." Raleigh, North Carolin a: North Carolina Wildlife Resources Commission, 2010b.

257Shaw, DR; Culpepper, S; Owen, M; Price, A; and Wilson, R (2012) "Herbicide

- resistant weeds threaten soil conservation gains: finding a balance for soil and farm sustainability."
Simmons, FW and Nafzi ger, ED (2012) "Chapter 10: Soil Management and Tillage." Illinois Agronomy Handbook . University of Illinois, Crop Science Extension & Outreach. http://extension.cropsci.illinois.edu/handbook ;https://extension.cropsci.illinois.edu/handbook/pdfs/chapter10.pdf. Smith, CW and Cothren, JT (1999) Cotton: Origin, history, technology, and production . New York, NY: John Wiley and Sons, Inc. http://www.wiley.com/WileyCDA/WileyTitle/productCd

- 0471180459.html

. Smith, R. "50 percent cotton abandonment rate no surprise to PCG [Plains Cotton Growers]." SouthWest Farm Press, Aug 21, 2013 2013. Print. Solaiman, S (2007) "Feeding Value of Whole Cottonseed for Goats." Tuskeegee University. Last Accessed: March 27, 2014 http://www.boergoats.com/clean/articles/feeding/wholecottonseed.pdf

. Sosnoskie, L M and Culpepper, AS (2014) "Glyphosate

- Resistant Palmer Amaranth (Amaranthus palmeri) Increases Herbicide Use, Tillage, and Hand

- Weeding in Georgia Cotton." Weed Science. 62 (2): p 393

- 402. Last Accessed: 2014/12/02 http://dx.doi.org/10.1614/WS

- D

13

- 00077.1

. SOWAP (2007) "Impact of Conservation Tillage on Terrestrial Biodiversity." Soil and Water Protection Project. http://www.sowap.org/re sults/biodiversity.htm

. Soy Stats (2010) "Soy Stats 2010, Domestic Utilization, U.S. Soybean Oil Consumption 2010." http://www.soystats.com/

. Soyatech (2011) "Soy Facts." Soyatech, LLC. http://www.soyatech.com/soy_facts.htm

. Spaunhorst, DJ; Siefert

- Higgins, S; and Bradley, KW (2014) "Glyphosate

- Resistant Giant Ragweed (Ambrosia trifida) and Waterhemp (Amaranthus rudis) Management in Dicamba

- Resistant Soybean (Glyc ine max)." Weed Technology. 28 (1): p 131

- 41. Last Accessed: 2014/04/11 http://dx.doi.org/10.1614/WT

- D

- 13

- 00091.1

. Station, NYSAE. "Soybean Pests: Insect Management Guide." Ed. University, CornellNo Date. http://www.nysipm.cornell.edu/publications/soy_ins_mgmt/files/soy_ins_pests.pdf

. Steckel, L (2013) " Palmer Amaranth Regrowing From PPO Herbicide Applica tion

– Now What?

- See more
at: http://news.utcrops.com/category/soybean/page/7/#sthash.diXp39b1.dpuf. " UT Crops Blog. http://news.utcrops.com/2013/07/palmer

- amaranth

- regrowing

- from

- ppo

- herbicide

application

- now

- what/#more

- 8288

. Steckel, L (2014) "2014 Weed Control Manual for Tennessee (PB 1580)." University of Tennessee Extension. https://utextension.tennessee.edu/publications/Documents/PB1580.pdf. Stepenuck, KF; Crunkilton, RL; and Wang, L (2002) "Impacts of urban land use on macroinvertebrate communities in southeastern Wisconsin streams." Journal of the

258American Water Resources Association. 38 (4): p 1041

- 51. http://onlinelibrary.wil ey.com/doi/10.1111/j.1752

- 1688.2002.tb05544.x/pdf

. Stevenson, K; Anderson, RV; and Vigue, G (2002) "The density and diversity of soil invertebrates in conventional and pesticide free corn." Transactions of the Illinois State Academy of Science. 95 (1): p 1

- 9. http://www.wiu.edu/cbt/agriculture/farms/organic/pdfs/invertebrates.pdf

. Steward, DR; Bruss, PJ; Yang, X; Staggenborg, SA; Welch, SM; and Apley, MD (2013) "Tapping unsustainable groundwater stores for agricultural production in the High Plains Aquifer of Kansas, projections to 2110." Proceedings of the National Academy of Sciences. 110 (37): p E3477

- E86. http://www.pnas.org/content/110/37/E3477.abstract

. Stockton, M (2007) "Continuous Corn or a Corn/Soybean Rotation?" University of Nebraska

Lincoln, Crop Watch, Nebraska Crop Production & Pest Management Information. http://cropwatch.unl.edu/archive/

- /asset_publisher/VHeSpfv0Agju/content/892035

. TAMU (2014) "Texas Water Resources Institute Irrigation Training Program. Crop

- Specific guidelines : Cotton Production." Texas A&M University. Last Accessed: March 6, 2014 http://irrigationtraining.tamu.edu/

. Tarter, S (2011) "Roundup Ready Beans Still on Top." http://www.pjstar.com/news/x1923551347/Roundup

- Ready

- beans

- still

- on

- top Taylor, B; Lyons, E; Rollins, D; Scott, C; Huston, J; and Taylor, C (2013) "Consumption of Whole Cottonseed by White Tailed Deer and Nontarget Species." Human

- Wildlife Interactions. 7 (1): p 99

- 106. Last Accessed: March 26, 2014 http://www. berrymaninstitute.org/files/uploads/pdf/journal/spring2013/HWI_7.1_p p99

- 106_small.pdf

. Tennessee, Uo (2014) "2014 Soybean Insect Control Recommendations." University of Tennessee. http://www.utcrops.com/cotton/cotton_insects/pubs/PB1768

- Soybean.pdf

. Texas Cooperative Extension (2004) "Suggestions for Weed Control in Pastures and Forages. Document No. B

- 5038 3

- 04." http: //forages.tamu.edu/PDF/B

- 5038.pdf

. Thomas, G. "Common Soybean Insects." Ed. Extension, University of Missouri1993. http://extension.missouri.edu/p/PS6

. Thomison, P (2009) "Managing "Pollen Drift" to Minim ize Contamination of Non

- GMO Corn, AGF

- 153." Horticulture and Crop Sciences, Ohio State University. http://ohioline.osu.edu/agf

- fact/0153.html

. TOCMC (2011) "From field to finished product: Texas O rganic Cotton Marketing Cooperative." http://www.texasorganic.com/organicinfo/fieldtoproduct2.htm

. TOCMC (2014) "Texas Organic Cotton Marketing Cooperative." http://www.texasorganic.com/

. Towery, D and Werblow, S (2010) "Facilitating Conservation Farming Practices and Enhancing Environmental Sustainability with Agricultural Biotechnology." Conservation Technology Information Center. http://www.ctic.purdue.edu/media/pdf/Biotech_Executive_Summary.pdf

. 259Tyler, DD; Wagger, MG; McCraken, DV; and Hargrove, W (1994a) "Role of Conservation Tillage in Sustainable Agri culture in the Southern United States." Conservation Tillage in Temperate Agroecosystems . CRC Press. p 209

- 29. http://www.cabdirect.org/abstracts/19951904041.html?freeview=true

. Tyler, DD; Wagger, MG; McCraken, DV; and Hargrove, W (1994b) "Role of Conservation Tillage in Sustainable Agriculture in the Southern United States." Conservation Tillage in Temperate Agroe cosystems . Ed. Carter, M.R. CRC Press. p 209

- 29. U.S. EPA Reg. No. 524

- 537. "

Monsanto Company Roundup WeatherMax®, EPA Reg No. 524

- 537." http://www.cdms.net/labelsmsds/lmdefault.aspx?p d=6026

. University

- of

- Arizona

- Cooperative

- Extension (2001) "Cotton Insect Publications." University of Arizona. http://ag.arizona.edu/crop/cotton/insects/ctninspub.html

. University

- of

- Illinois

- Extension "Soybeans: Insects." http://ipm.illinois.edu/fieldcrops/soybeans/insects.html

. University

- of

- Minnesota

- Extension "Soybean Production." University of Minnesota Exte nsion. http://www.extension.umn.edu/agriculture/soybean/

. University

- of

- Minnesota

- Extension (2011) "Soybean Cyst Nematode Management Guide." http://www.extension.umn.edu/agriculture/soybean/soybean

- cyst

nematode/EFANS

- Soybean

- SoybeanCystNematode

- WebQuality.pdf

. University of Arkansas (2006) "Soil and Water Ma nagement Soybeans

– Crop Irrigation." University of Arkansas Division of Agriculture Cooperative Extension Service. http://www.uaex.edu/farm

- ranch/crops

- commercial

- hortic ulture/soybean/

. University of Arkansas (2013) "Recommended Chemicals for Weed and Bush Control." Last Accessed: August 6, 2013 http://www.uaex.edu/Other_Areas/publications/pdf/ MP44/MP44.pdf

. University of California (2008a) "UC pest management guidelines: Cotton

- Crop Rotation." University of California Statewide Integrated Pest Management Program. http://www.ipm.uc davis.edu/PMG/r114900611.html

. University of California (2008b) "UC pest management guidelines: Cotton, crop rotation ." University of California Statewide Integrated Pest Management Program. http://www.ipm.ucdavis.edu/PMG/r114900611.html

. University of California Davis (1996) Cotton Production Manual

. University of Georgia and USDOI

- NPS (2012) "Invasive Plant Atlas of the United States, Plant Species Reported to be Invasiv e in Natural Areas." The University of Georgia

- Center for Invasive Species and Ecosystem Health and the National Park Service. Last Accessed: January 30, 2014 http://www.invasiveplantatl as.org/distribution.html

. University of Georgia CAES Extension (2014) "2014 Georgia Cotton Production Guide." The University of Georgia Cooperative Extension http://www.ugacotton.com/production

gui de/

. 260University of Illinois (2013) "Recommendations for Management of Glyphosate

- Resistant Waterhemp in Illinois Soybean." Last Accessed: 5

- 14

- 14 http://weeds.cropsci.illin ois.edu/extension/factsheets/whempsoy.pdf

. University of Kentucky "Soybeans." http://www.uky.edu/Ag/GrainCrops/soybean.htm

. University of Minnesota "Soybean Production. University of Minnesota Extension." University of Minnesota Extension. http://www.extension.umn.edu/agriculture/soybean/

. University of Nebraska (2012) "Nebraska Farm Custom Rates." http://cropwatch.unl.edu/web/economics/customrates

. University of Nebraska (2013) "Soybean Insects." http://entomology.unl.edu/extension/crops/soybean.shtml

. University of Nebraska Extension (2014) "2014 Guide for Weed Management in Nebraska." University of Nebraska. http://www.ianrpubs.unl.edu/epublic/live/ec130/build/ec130.pdf

. US

- CDC (2013) "Agricultural Water." Centers for Disease Control and Prevention. http://www.cdc.gov/healthywater/other/agricultural/

. US

- EPA (2001) "Bt Plant

- Incorporated Protectants October 15, 2001 Biopesticides Registration Action Document." h ttp://www.epa.gov/oppbppd1/biopesticides/pips/bt_brad.htm

. US

- EPA (2003) "Memorandum: Glufosinate ammonium (PC code 128850). Section 3 registrations for transgenic cotton (ID#

- 0F06140), transgenic rice (ID#

- 0F06210), and bushberry (ID#

- 2E06404). Huma n health risk assessment . DP barcode: D290086. Case number: 293386. Submission: S635308. 40 CFR 180.473." USEPA Office of Prevention, Pesticides, and Toxic Substances.

US

- EPA (2005) "Protecting Water Quality from Agricultural Runof f (EPA 841

- F

- 05

- 001)." U.S. Environmental Protection Agency. Last Accessed: September 13, 2013 http://water.epa.gov/polwaste/nps/upload/2005_4_29_nps_Ag_Runoff_ Fact_Sheet. pdf

. US

- EPA (2006a) "Reregistration Eligibility Decision (RED) Document for Dicamba and Associated Salts, Case No. 0065." Environmental Protection Agency. http://www.epa.gov/oppsrr d1/REDs/dicamba_red.pdf

. US

- EPA (2006b) "Reregistration Eligibility Decision for Dicamba and Associated Salts." Environmental Protection Agency. http://www.epa.gov/oppsrrd1/REDs/dicamba_red.p df

. US

- EPA (2008) "Glufosinate Summary Document, Registration Review: Initial Docket, March 2008, Case #7224." Division, Special Review and Reregistration. http://www.epa .gov/oppsrrd1/registration_review/glufosinate_ammonium /

. US

- EPA (2009a) "Memorandum: Correction to the amendments to the dicamba RED." US Environmental Protection Agency, Office of Prevention, Pesticides, and Toxic Substances. http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OPP

- 2005

- 0479

- 0026;oldLink=false

. US

- EPA (2009b) "Reregistration Eligibility Decision (RED) for Dicamba and Associated Salts: Memorandum (June 17)

- Correction to the Amendments to the Dicamba 261RED

. " http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OPP

- 2005

- 0479

- 0026;ol dLink=false

. US

- EPA (2009c) "Reregistration Eligibility Decision for Dicamba and Associated Salts

. "

US

- EPA (2010a) "Primary Distinguishing Characteristics of Level III Ecoregions of the Continental United States." United States Environmental Protection A gency. Last Accessed: June 26, 2013 http://www.epa.gov/wed/pages/ecoregions/level_iii_iv.htm

. US

- EPA (2010b) "A Set of Scientific Issues Being Considered by the Environmental Protecti on Agency Regarding: Field Volatilization of Conventional Pesticides." U.S. Environmental Protection Agency. http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- O PP

2009

- 0687

- 0037

. US

- EPA (2011a) "Agricultural Burning." U.S. Environmental Protection Agency. http://www.epa.gov/agriculture/tburn.html#Air

. US

- EPA (2011b) "Chapter 6: Agriculture." Inve ntory of U.S. Greenhouse Gas Emissions and Sinks: 1990

- 2009 . Washington, DC: U.S. Environmental Protection Agency. p 6

- 1 through 6

- 40. h ttp://www.epa.gov/climatechange/emissions/downloads11/US

- GHG

Inventory

- 2011

- Chapter

- 6

- Agriculture.pdf

. US

- EPA (2011c) "Inventory of U.S. Greenhouse Gas Emissions And Sinks: 1990

– 2009." U.S. Environmental Protection Agency. http://www.epa.gov/climatechange/Downloads/ghgemissions/US

- GHG

Inventory

- 2011

- Complete_Report.pdf

. US

- EPA (2011d) "Pest icides: Registration Review." U.S. Environmental Protection Agency. http://www.epa.gov/oppsrrd1/registration_review/index.htm

. US

- EPA (2012a) "Crop Production." United States Environ mental Protection Agency. Last Accessed: September 16, 2013 http://www.epa.gov/oecaagct/ag101/printcrop.html

. US

- EPA (2012b) "Glufosinate Ammonium. Updated Human Health Risk Assessment for th e Proposed New Use of Glufosinate Ammonium in/on Citrus Fruit (Crop Group 10), Pome Fruit (Crop Group 11), Stone Fruit (Crop Group 12), Olives and Sweet Corn." US Environmental Protection Agency. http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OPP

- 2009

- 0813

- 0005

. US

- EPA (2012c) "Water Exposure Models Used by the Office of Pesticide Programss." http://www.epa.gov/oppefed1/models/water/models4.htm

. US

- EPA (2013a) "Environmental Fate and Ecological Risk Assessment for the Registration Review of Glufosinate. CAS 77182

- 82

- 2 PC Code 128850." US Environmental Protection Agency, Office of Pesticide Pro gram. http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OPP

- 2008

- 0190

- 0023

. US

- EPA (2013b) "Memorandum: Glufosinate Ammonium. Human Health Risk Assessment for R egistration Review. Decision No.: 471210. DP barcode: 0406360. CAS No.: 77182

- 82

- 2. 40 CFR: 180.437. ." USEPA Office of Chemical Safety and Pollution

262Prevention. h ttp://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OPP

- 2008

- 0190

- 0026

. US

- EPA (2013c) "Particulate Matter Air and Radiation. ." United States Environmental Protection Agency. Last Accessed: March 11, 2014 http://www. epa.gov/pm/

US

- EPA (2014a) "Proposed Registration of Enlist Duo TM Herbicide

. " Last Accessed: November 5, 2013 http://www.regulations.gov/#!documentDetail;D=EPA

- H Q

- OPP

- 2014

- 0195

- 0010

. US

- EPA (2014b) "Worker Protection Standard for Agricultural Pesticides." US Environmental Protection Agency, Office of Pesticide Program. Last Accessed: Feb. 28, 2014 http://www .epa.gov/agriculture/twor.html

. "Premarket Notice Concerning Bioengineered Foods." US

- FDA. 2001. Last Accessed: Feb. 28, 2014 (https:// www.federalregister.gov/articles/2001/01/18/01

- 1046/premarket

- notice

concerning

- bioengineered

- foods

. US

- FDA (2003) "Completed Consultat ions on Bioengineered Foods BNF No. 86." US Food and Drug Administration. Last Accessed: January 29, 2014 http://www.fda.gov/Food/Biotechnology/Submissions/ucm155787.htm

. US

- FD A (2011a) "Completed Consultations on Bioengineered Foods: BNF 125." Food and Drug Administration, Office of Food Additive Safety, Center for Food Safety and Applied Nutrition. Last Accessed: March 4, 2014 http://www.accessdata.fda.gov/scripts/fdcc/?set=Biocon&id=MON%2D87708%2D 9

. US

- FDA (2011b) "Completed Consultations on Bioengineered Foods: BNF No. 125." Food and Drug Administration, Office of Food Additive Safety, C enter for Food Safety and Applied Nutrition. Last Accessed: March 4, 2014 http://www.accessdata.fda.gov/scripts/fdcc/?set=Biocon&id=MON%2D87708%2D 9

. US

- FDA (2013) "Completed Consultations on Bioengineered Foods BFN No. 135." US Food and Drug Administration. Last Accessed: January 29, 2014 http://www.a ccessdata.fda.gov/scripts/fcn/fcnDetailNavigation.cfm?rpt=bioListing &id=97

. US

- FDA (2014) "Biotechnology Consultations on Food from GE Plant Varieties." US Food and Drug Administration. Last Accessed: Feb. 25, 2014 http://www.accessdata.fda.gov/scripts/fdcc/?set=Biocon

. US

- FDA (2014 (updated)) "Guidance for Industry: Recommendations for the Early Food Safety Evaluation of New Non

- Pesticidal Proteins Produced by New Plant Varieties Intend ed for Food Use." U.S. Food and Drug Administration. http://www.fda.gov/Food/GuidanceRegulation/GuidanceDocumentsRegu latoryInformation/ucm096126 .htm

. US

- NARA (2013) "National Archives and Records Administration: Executive Orders Disposition Tables Index." United States National Archives and Records

263Administration. http://www.archives.gov/federal

- register/executive

orders/disposition.html

. "Coordinated Framework for Regulation of Biotechnology." US

- OSTP. 1986. http://www.aphis. usda.gov/brs/fedregister/coordinated_framework.pdf

. USB (2009) "Food and Feed." United Soybean Board. http://www.soyconnection.com/soybean_oil/pdf/foodvsfuel_soy_biofu els.pdf

. USB (2011) "U.S. Soy Growers Poised for Growth in Global Animal

- Feed Industry." United Soybean Board. http://unitedsoybean.org/topics/animal

- ag

. USDA

- AMS (2010) "National Organic Program

. " Last Accessed: May 14, 2010 http://www.ams.usda.gov/AMSv1.0/nop

. USDA

- AMS (2011a) "Pesticide Data Program, Annual Summary, Calendar Year 2009." US Department of Agriculture, Agricultural Marketing Servic e, Science and Technology Programs.

USDA

- AMS. "Policy memorandum: Genetically modified organisms." US Department of Agriculture, Agricultural Marketing Service, 2011b.

USDA

- AMS (2012) "2010

– 2011 Pilot Study: Pesticide Residue Testing of Organic Produce. USDA National Organic Program, USDA Science and Technology Programs, November 2012." USDA Agricultural Marketing Service. http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STE LPRDC5101234

. USDA

- AMS (2013) "Annual Organic Cotton Market Summary." USDA Agricultural Marketing Service, Cotton and Tobacco Programs. Last Accessed: May 14, 2010 http://www.ams.usda.gov/mnrepo rts/cnaocms.pdf

. USDA

- AMS (2014) "Cotton varieties planted 2014

. " http://www.ams.usda.gov/mnreports/cnavar.pdf

. USDA

- APHIS (2010) "Pioneer Hi

- Bred International High Oleic Soybean DP

- 305432

- 1, F inal Environmental Assessment." USDA Animal and Plant Health Inspection Service, Biotechnology Regulatory Services. http://www.aphis.usda.gov/biotechnology/petitions_tabl e_pending.shtml

. USDA

- APHIS "United States Department of Agriculture, Animal Plant Health Inspection Service, Federal Noxious Weeds List. Available online
at http://plants.usda.gov/java/noxious. " Last Ac cessed: March 19, 2014 http://plants.usda.gov/java/noxious

. USDA

- APHIS (2014a) "DRAFT Plant Pest Risk Assessment for Dicamba

- Resistant Soybean (Glycine max) MON 87708."

USDA

- APHIS (2014b) "DRAFT Plant Pe st Risk Assessment for Dicamba and Glufosinate Resistant Cotton (Gossypium hirsutum) MON 88701."

USDA

- APHIS "Petitions for Non

- regulated Status." USDA

- APHIS. Last Accessed: April 1, 2014 http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

.

264USDA

- APHIS (2014d) "Plant Pest Risk Assessment: Monsanto Petition (10

- 188

- 01p) for Determination of Nonregulated Status of Dicamba Herbicide

- resistant Soybean (Glycine max) MON 87708." USDA Animal and Plant Health Inspection Service. http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

. USDA

- APHIS (2014e) "Plant Pest R isk Assessment: Monsanto Petition (12

- 185

- 01p) for Determination of Non

- regulated Status of Dicamba and Glufosinate Resistant MON 88701 Cotton." USDA Animal and Plant Health Inspection Service. http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

. USDA

- APHIS "USDA Online Database: Biotechnology Petitions for Determination of Nonregulated Status [ http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml ] " USDA Animal and Plant Health Inspection Service. Last Accessed: April 1, 2014 http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

. USDA

- ARS (1995) "Crop Residue To Reduce Erosion and Improve Soil Quality

- Northwest. Conservation Research Report Numb er 40." USDA Agricultural Research Service. http://eprints.nwisrl.ars.usda.gov/1205/1/878.pdf

. USDA

- ARS (2011) "At ARS, the Atmosphere Is Right for Air Emissions Studies." USDA Agricultural Research Service. Last Accessed: November 19, 2013 http://www.ars.usda.gov/is/AR/archive/jul11/emissions0711.htm?pf=1

. USDA

- ERS (1997) "Crop Residue Management." Agricultura l Resources and Environmental Indicators 1996

- 1997 . USDA Economic Research Service. http://www.ers.usda.gov/publications/arei/ah712/AH7124

- 2.PDF

. USDA

- ERS (2006) "Chapter 4.2: Soil Management and Conservation." Agricultural Resources and Environmental Indicators, 2006 Edition / EIB

- 16 . USDA Economic Research Service. http://webarchives.cdlib.org/sw15d8pg7m/http://ers.usda.gov/publications/arei/ei b16/eib16_4

- 2.pdf

. USDA

- ERS (2008) "Certified Organic Acreage of other Crops, by State, 2008." U.S. Department of Agriculture Economic Research S ervice. www.ers.usda.gov/datafiles/Organic_Production/StateLevel_Tables_/Othercrops .xls

. USDA

- ERS (2009) "Conservation Policy: Compliance Provisions for Soil and Wetland Conservation." U.S. Department of Agriculture Economic Research Service. http://www.ers.usda.gov/Briefing/ConservationPolicy/compliance.htm

. USDA

- ERS (2010) "Data sets: Organic production." http://www.ers.usda.gov/data

products/organic

- production.aspx

. USDA

- ERS (2011a) "Agricultural Resource Management Survey. Farm Financial and Cro p Production Practices." http://www.ers.usda.gov/data

- products/arms

- farm

- financial

- and

crop

- production

- practices.aspx

. USDA

- ERS (2011b) "Certified Organic and Total Acreage of Selected Crops, 1995

- 2011." USDA Economic Research Service. http://www.ers.usda.gov/data

- products/organic

production.aspx

. 265USDA

- ERS (2011c) "Corn: Ba ckground." http://www.ers.usda.gov/Briefing/Corn/background.htm

. USDA

- ERS (2011d) "Major Land Uses

. " Agriculture. http://www.ers.usda.gov/data

products/major

- land

- uses.aspx

. USDA

- ERS (2011e) "Major Uses of Land in the United States, 2007." USDA

- ERS.

USDA

- ERS (2012a) "Cotton: Background." United States Department of Agriculture

- Economic Research Service. http://www.ers.usda.gov/topics/crops/cotton

wool/background.aspx

. USDA

- ERS (2012b) "Crops

. " Agriculture. Last Accessed: 4

- 23

- 14 http://webarchives.cdlib.org/sw10z7207q/http://www.ers.usda.gov/Browse/view.aspx? subject=Crops

. USDA

- ERS (2012c) "Recent Conservation Reserve Program Enrollments Signal Changing Priorities

. "

USDA

- ERS (2012d) "Water Conservation in Irrigated Agriculture: Trends and Challenges in the Face of Emerging Demands." U.S. Department of Agriculture, Economic Research Service. http://www.ers.usda.gov/publications/eib

- economic

- information

bulletin/eib99.aspx

. USDA

- ERS. "Organic Production

- Table 3: Certified organic and total U.S. acr eage, selected crops and livestock, 1995

- 2011." USDA

- Economic Research Service, 2013a. Vol. 2014. http://www.ers.usda.gov/data

- products/organic

- production.aspx

. USDA

- ERS. "Soybea ns Cost and Returns." Ed. USDA

- ERS. USDA: ERS, 2013b.

USDA

- ERS "Soybeans Cost and Returns 2010

- 2011." USDA's Economic Research Service. http://www.ers.usda.gov/data

- products.aspx

. USDA

- ERS (2014a ) "Adoption of Genetically Engineered Crops in the U.S. Recent Trends in GE Adoption." http://www.ers.usda.gov/data

- p roducts/adoption

- of

- genetically

engineered

- crops

- in

- the

- us/recent

- trends

- in

- ge

- adoption.aspx

. USDA

- ERS (2014b) "ARMS Farm Financial and Crop Production Practices." USDA

- Economic Research Service.

USDA

- ERS (2014c) "Outlook for U.S. Agricultural Trade

. " Ser vice, Economic Research. http://usda.mannlib.cornell.edu/usda/current/AES/AES

- 08

- 28

- 2014.pdf

. USDA

- ERS (2014d) "Recent trends in GE adoption." United States Department of A griculture Economic Research Service. Last Accessed: April 2014 http://www.ers.usda.gov/data

products/adoption

- of

- gen etically

- engineered

- crops

- in

- the

- us/recent

- trends

- in

- ge

adoption.aspx

. USDA

- ERS (2014e) "Soybeans & Oil Crops Overview " USDA

- Economic Research Service. Last Accessed: Feb. 27, 2014 http://www.ers.usda.gov/topics/crops/soybeans

- oil

crops.aspx

. USDA

- FAS "Global Agricultural Trade System Online." USDA.

266USDA

- FAS (2013b) "Oilseeds: World Market and Trade." U.S. Department of Agriculture

– Foreign Agricultural Service. http://www.fas.usda.gov/oilseeds_arc.asp

. USDA

- FAS (2014) "Cotton: World Markets and Trade." USDA

- Foreign Agricultural Service. Last Accessed: Feb. 6, 2014 http://apps.fas.usda.gov/psdonline/circulars/cotton.pdf

. USDA

- FSA (2010) "Biomass Crop Assistance Program: Final Programmatic Environmental Impact Statement." United States Department of Agriculture, Farm Service Agency. http://www.fsa.usda.gov/Internet/FSA_File/bcapfinalpeis062510.pdf

. USDA

- NASS (2005a) "Agricultural Chemical Usage 2004 Field Crops Summary." USDA National Agricultural Statistics Service. http://usda01.library.cornell.edu/usda/nass/AgriChemUsFC//2000s/2005/AgriCh emUsFC

- 05

- 18

- 2005.pdf

. USDA

- NASS (2005b) "Agricultural Statistics 2005." USDA

- National agricultural Statistics Service.

USDA

- NASS (2006) "Agricultural Chemical Usage 2005 Field Crops Summary." USDA National Agricultural Statistics Service. http://usda.mannlib.cornell.edu/usda/nass/AgriChemUsFC//2000s/2006/AgriChe mUsFC

- 05

- 17

- 2006.pdf

. USDA

- NASS (2007a) "Census of Agriculture: Summary and State Data Volume 1 • Geographic Area Series • Part 51." USDA

- National Agricultural Statistics Service.

USDA

- NASS (2007b) "Irrigated All Cotton, Harvested Acres: 2007

. " http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_ Maps/Crops_and_Plants/Field_Crops_Harvested/07

- M1 86

- RGBDot1

- largetext.pdf

. USDA

- NASS (2007c) "Irrigated All Soybean, Harvested Acres: 2007

. " http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_ Maps/Crops_and_Plants/Field_Crops_Harvested/07

- M194

- RGBDot1

- largetext.pdf

. USDA

- NASS (2008a) "2007 census of agriculture: Organic production survey (2008)." http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Organics/O RGANICS.pdf

. USDA

- NASS (2008b) "Agricultural Chemical Usage 2007 Field Crops Summary." USDA National A gricultural Statistics Service. http://usda.mannlib.cornell.edu/usda/nass/AgriChemUsFC/2000s/2008/AgriChe mUsFC

- 05

- 21

- 2008.pdf

. USDA

- NASS (2009a) " 2007 Census Ag Atlas Map: Acres of Irrigated Land." United States Department of Agriculture, National Agricultural Statistics Service. Last Accessed: September 8, 2013 http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_Ma ps/Farms/Land_in_Farms_and_Land_Use/07

- M080

- RGBDot1

- largetext.pdf

. USDA

- NASS (2009b) "2007 Census Ag Atlas Map: Irrigated Cotton for Grain, Harvested Acres: 2007." United States Department of Agriculture, National Agricultural Statistics Service. Last Accessed: September 16,

2672013 http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_Ma ps/Crops_and_Plants/Field_Crops_Harvested/07

- M186

- RGBDot1

- largetext.pdf

. USDA

- NASS (2009c) "2007 Census Ag Atlas Map: Irrigated Soybeans for Beans, Harvested Acres: 2007." United States Department of Agriculture, National Agricultural Statistics Service. Last Accessed: September 16, 2013 http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Ag_Atlas_Ma ps/Crops_and_Plants/Field_Crops_Harvested /07

- M194

- RGBDot1

- largetext.pdf

. USDA

- NASS (2009d) "2007 census of agriculture: United States summary and state data

. "

USDA

- NASS (2009e) "Census of Agriculture: Summary and State Data Volume 1 • Geographic Area Series • Part 51." USDA

- National Agricultura l Statistics Service.

USDA

- NASS (2009f) "Rates Paid by Kansas Farmers for Custom Work." Kansas Department of Agriculture, Division of Statistics, in Cooperation With USDA National Agricultural Statistics Service. Last Accessed: 4

- 15

- 14 http://www.nass.usda.gov/Statistics_by_State/Kansas/Publications/Custom_Rates/cust om09.pdf

. USDA

- NASS (2010a) "2008 Farm and Ranch Irrigation Survey." USDA National Agr icultural Statistics Service. http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Farm_and_ Ranch_Irrigation_Survey/inde x.asp

. USDA

- NASS (2010b) "Agricultural Statistics 2010." USDA

- National Agricultural Statistics Service.

USDA

- NASS (2011a) "Acreage." U.S. Department of Agriculture

- National Agricultural Statistics Service. http://usda01.library.cornell.edu/usda/current/Acre/Acre

- 06

- 30

- 2011.pdf

. USDA

- NASS (2011b) "Agricultural Chemical Use: Corn, Upland Cotton and Fall Potatoes 2010." USDA National Agricultural Statistics Service. http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/Fie ldCropChemicalUseFactSheet06.09.11.pdf

. USDA

- NASS (2011c) "Agricu ltural Statistics 2011." UDSA

- National Agricultural Statistics Service.

USDA

- NASS "U.S. & All States Data

- Crops Planted, Harvested, Yield, Production, Price (MYA), Value of Production 1991

- 2011." USDA National Agricultural Statistics Service. http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats_1.0/index.asp

. USDA

- NASS (2012a) "2011 Certified Organic Production Survey." USDA National Agricultural Statistics Service

. http://usda01.library.cornell.edu/usda/current/OrganicProduction/OrganicProduc tion

- 10

- 04

- 2012.pdf

. USDA

- NASS (2012b) "2012 Agricultural Chem ical Use Survey

- Soybean." The Agricultural Chemical Use Program of the National Agricultural Statistics

268Service. http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/20 12_Soybeans_Highlights/ChemUseHighlights

- Soybeans

- 2012.pdf

. USDA

- NASS (2012c) "Acreage

. " Agriculture. http://usda01.library.cornell.edu/usda/nass/Acre/2010s/2012/Acre

- 06

- 29

- 2012.pdf

. USDA

- NASS (2012d) "Census of Agricultrue

- Preliminary Report." USDA

- National Agricultural Statistics Service.

USDA

- NASS (2012e) "Crop Production 2012." USDA Na tional Agricultural Statistics Service. Last Accessed: November 5, 2012 http://executiveagnetwork.com/crop

- production

- 9

. USDA

- NASS (2012 ) "Agricultural Chemical Usage

- Field Crop Methodology and Quality Measures

. " http://www.nass.usda.gov/Publications/Methodology_and_Data_Quality/Agr icultural_Chemi cal_Usage_

- _Field_Crops/05_2012/chfcqm12.pdf

. USDA

- NASS (2013a) "2012 Agricultural Chemical Use Survey: Soybean " USDA

- National Agricultural Statistics Service. http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/20 12_Soybeans_Highlights/ChemUseHighlights

- Soybeans

- 2012.pdf

. USDA

- NASS (2013b) "2012 Agricultural Chemical Use Survey: Wheat

. " Last Acce ssed: 4

- 23

- 14 http://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Chemical_Use/2012_W heat_Highlights/ChemUseHighlights

- Wheat.pdf

. USDA

- NASS (2013c) "Acreage

. " USDA. http://usda.mannlib.cornell.edu/usda/current/Acre/Acre

- 06

- 28

- 2013.pdf

. USDA

- NASS (2013d) "Crop Production 2012 Summary." USD A

- National Agricultural Statistics Service.

USDA

- NASS (2013e) "National Agricultural Statistics Service Cropland Data." USDA, National Agricultural Statistics Service. Last Accessed: 7September 13, 2013 http://nassgeodata.gmu.edu/CropScape/ and http://www.nass.usda.gov/research/Cropland/sarsfaqs2.html

. National Statistics for Soybeans . USDA

- NASS: USDA

- NASS, 2013f http://www.nass.usda.gov/Statistics_by_Subject/result.php?4378EB63

- 5283

- 3A7B

89EF

63C62203D62B§o r=CROPS&group=FIELD%20CROPS&comm=SOYBEANS

. USDA

- NASS (2013g) "Quick Stats 2.0

. " http://www.nass.usda.gov/Quick_Stats/

USDA

- NASS (2013h) "Soybeans 2012 Yield per Harvested Acre by County for Selected S tates

. "

USDA

- NASS (2013i) "Upland Cotton 2012 Yield Per Harvested Acre by County for Selected States

. " http://www.nass.usda.gov/Charts_and_Maps/Crops_County/p df/CTU

- YI12

- RGBChor.pdf

. USDA

- NASS (2013j) "USDA National Agricultural Statistics Service Cropland Data Layer

. " Last Accessed: 7September 13, 2013 http://nassgeodata.gmu.edu/CropScape/ and http://www.nass.usda.gov/research/Cropland/sarsfaqs2.html

. 269USDA

- NASS (2014a) "Crop production: 2013 summary, January 2014

. " Last Accessed: Feb 19, 2014 http://usda01.library.cornell.edu/usda/current/CropProdSu/CropProdSu

- 01

- 10

- 2014.pdf

. USDA

- NASS (2014b) "Prospective Plantings." USDA National Agricultural Statistics Service (NASS). http://usda.mannlib.cornell.edu/usda/current/ProsPlan/ProsPlan

- 03

- 31

- 2014.pdf

. USDA

- NASS "Quick Stats." USDA. Last Accessed: 4

- 8

- 2014 http://www.nass.usda.gov/Quick_Stats/

. USDA

- NASS "Quick Stats 2.0." USDA National Agricultural Statistics Service. http://quickstats.nass.usda.gov/

. USDA

- NASS. "U.S. All Cotton Acres." Washington, D.C.: U.S. Department of Agriculture, National Agricultural Statistics Service, 2014e. http://www.nass.usda.gov/Charts_and_Maps/graphics/cotnac.pdf

. USDA

- NRCS (1996a) "Effects of Residue Management and No

- Till on Soil Quality." Natural Resources Conservation Service. http://soils.usda.gov/sqi/management/files/sq_atn_3.pdf

. USDA

- NRCS (1996b) "Effects of Residue Management and No

- Till on Soil Quality. Soil Quality

- Agronomy: Technical Note No. 3." USDA Natural Resources Conservation Service. http://soils.usda.gov/sqi/management/files/sq_atn_ 3.pdf

. USDA

- NRCS (1999a) "Conservation Tillage Systems and Wildlife." U.S. Department of Agriculture

– Natural Resources Conservation Service. http://www.nrcs.usda.gov/Interne t/FSE_DOCUMENTS/nrcs143_022212.pdf

. USDA

- NRCS (1999b) "Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys." U.S. Department of Agriculture

– Natural Resources Conservation Service. http://soils.usda.gov/technical/classification/taxonomy/

. USDA

- NRCS (2003) "Wildlife Plan for CRP, Iowa Job Sheet." U.S. Department of Agriculture

– Natural Resources Conservation Service. ftp://ftp

fc.sc.egov.usda.gov/IA/news/wildlifeplan.pdf

. USDA

- NRCS (2004) "Soil Biology and Land Management. Soil Quality

– Soil Biology Technical Note No. 4." USDA Natural Resources Conservation Service. http://soils.usda.gov/sqi/publications/publications.html#atn

. USDA

- NRCS (2005) "Residue and Tillage Management, No Till/Strip Till/Direct Seed. Conservation Practice Job Sheet 329

. " http://www.nrcs.usda.gov/wps/portal/nrcs/detail//?cid=nrcs144p2_027119

. USDA

- NRCS (2006a) "Conservation Resource Brief: Air Quality, Number 0605." National Resour ces Conservation Service. http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs143_023301.pdf

. USDA

- NRCS (2006b) "Conservation Resource Brief: Soil Quality." USDA Natural Res ources Conservation Service. https://prod.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs143_023219.pdf.

270USDA

- NRCS (2006c) "Conservation Resource Brief: Soil Quality

. " NRCS, USDA. https://prod.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs143_023219.pdf.

USDA

- NRCS (2 006d) "USDA Handbook 296: Land Resource Regions and Major Land Resource Areas of the United States, the Caribbean, and the Pacific Basin." United States Department of Agriculture, National Resources Conservation Service. Last Accessed: August 21, 2013 ftp://ftp

fc.sc.egov.usda.gov/NSSC/Ag_Handbook_296/Handbook_296_low.pdf

. USDA

- NRCS (2010a) "2007 National Resources Inventory: Soil Erosion on Cropland

. " http://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/technical/nra/nri/?ci d=stelprdb1041887

. USDA

- NRCS (2010b) "Conservation Practice Standard, Conservation Crop Rotation (Ac.) Code 328." U.S. Department of Agriculture

– Natural Resources Conservation Service. http://efotg.sc.egov.usda.gov/references/public/CO/CO328.pdf

. USDA

- NRCS (2011 ) "RCA Appraisal: Soil and Water Resources Conservation Act." USDA Natural Resources Conservation Service. Last Accessed: September 10, 2013 http://www.nrcs.usda.gov/Intern et/FSE_DOCUMENTS/stelprdb1044939.pdf

. USDA

- NRCS "Introduced, Invasive, and Noxious Plants: U.S. Weeds." USDA Natural Resource Conservation Service. Last Accessed: March 19, 2014 http://pla nts.usda.gov/java/invasiveOne?startChar=G

. USDA

- NRCS "Plant profile for Gossypium barbadense. The PLANTS Database." National Plant Data Team, Greensboro, NC. Last Accessed: November 26, 2012 http://plants.usda.gov

. US DA

- NRCS (2012c) "PLANTS Profile Gossypium hirsutum L. upland cotton." USDA

- Natural Resources Conservation Service. http://plants.usda.gov/core/profile?symbol=GOHI

. USDA

- NRCS (2013a) "Energy Es timator: Tillage." Last Accessed: Dce. 10, 2013 http://ecat.sc.egov.usda.gov/Default.aspx

. USDA

- NRCS (2013b) "Energy Estimator: Tillage." Last Accessed: Dce. 10, 2013 http://ecat.sc.egov.usda.gov/Default.aspx

. USDA

- NRCS "Introduced, Invasive, and Noxious Plants: Federal Noxious Weeds." USDA Natural Resource Conservation Service. Last Accessed: December 3, 2013 http://plants.usda.gov/java/noxious?rptType=Federal

. USDA

- NRCS (2013d) "Summary Report: 2010 National Resources Inventory

. " USDA. http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1167354.pdf

. USDA

- OCE (2013) "USDA Agricultural Projections to 2022

. " USDA. htt p://www.ers.usda.gov/publications/oce

- usda

- agricultural

projections/oce131.aspx

. USDA

- OCE "The Outlook for U.S. Agriculture. Speech and PowerPoint slides presented by USDA Chief Economist Joseph Glauber at the 2014 Agricultural Outlook Forum." USDA Office of the Chief Economist. http://www.usda.gov/oce/forum/

.

271USDA

- OCE (2014b) "USDA Agricultural Projections to 2023

. " USDA. http://www.ers.usda.gov/publications/oce

- usda

- agricultural

projections/oce141.aspx

. USDA (2014) "USDA Livestock, Poultry & Grain Market News: National Organic Grain and Feedstuffs

- Bi

- weekly, Nov. 14

- 22." USDA. http://www.ams.usda.gov/mnreports/lsbnof.pdf

. USFWS (2008) "Delmarva Peninsula Fox Squirrel Sciurus niger cinereus ." www.fws.gov/endangered/esa

- library/pdf/squirrel.pdf

. USFWS (2011) "Environmental Assessment: Use of Genetically Modified, Glyphosate

- Tolerant Soybeans and Corn on National Wildlife Refuge Lands in the Mount ain

- Prairie Region (Region 6)." USFWS Division of Refuge Planning. http://www.fws.gov/mountain

prairie/planning/resources/documents/resources_gmo_ea.pdf

. USFWS "Endangered Species List for Soybean Growing States [ http://www.fws.gov/endangered/]. " USFWS. Last Accessed: March 12, 2014 http://www.fws.gov/endange red/

. USFWS "Endangered Species Listings for Cotton Producing States [ http://www.fws.gov/endangered/]. " USFWS. Last Accessed: April 1, 2014 http://www.fws.gov /endangered/

. USFWS "Listed and Proposed Endangered Species [ http://www.fws.gov/endangered/]. " USFWS. Last Accessed: April 1, 2014 http://www.fws.gov/endanger ed/

. USGCRP (2009) "Agriculture." Global Climate Change Impacts in the United States . U.S. Global Change Research Program. p 71

- 78. http://nca2009.globalchange.gov/agriculture

. USGS

- NLCD "National Land Cover Database [ http://www.mrlc.gov/nlcd2006.php]. " United States Geological Survey. Last Accessed: September 6, 2013 http://www.mrlc.gov/nlcd2006.p hp

. USGS (2013) "Mine and MIneral Processing Plant Locations

- Supplemental Information for USGS Map I

- 2654." United States Geological Survey. Last Accessed: September 16, 2013 http://minerals .usgs.gov/minerals/pubs/mapdata/

. UW

- NPMP (No Date) "Corn and Soybean Herbicide Chart." University of Wisconsin

- Nutrient and Pest Management (NPM) Program. http://www.glyphosateweeds crops.org/Info/MOA_060807.pdf

. Van Deynze, AE; Sundstrom, FJ; and Bradford, KJ (2005) "Pollen

- mediated gene flow in California cotton depends on pollinator activity." Crop Science. 45 (4): p 1565

- 70. https:// www.crops.org/publications/cs/abstracts/45/4/1565

. VanGessel (2014a) "Sorting out PPO Herbicides." University of Delaware Cooperative Extension. https://extension.udel.edu/weeklycropupd ate/?tag=soybean

- weed

- control. VanGessel, M (2014b) "No

- Till Soybean Burndown Considerations." https://extension.udel.edu/weeklycropupdate/?tag=soybean

- weed

- control.

272Vitosh, ML (1996) "N

- P

- K Fertilizers." Michigan State University Extension. Extension Bull etin E

- 896. Reprint July 1996. Last Accessed: March 7, 2014 http://fieldcrop.msu.edu/uploads/documents/e0896.pdf

. Waldroup, P and Smith, K (2008) "Soybean Meal Information Center Fact She et: Soybean Use

- Poultry." United Soybean Board. http://www.soymeal.org/FactSheets/PoultrySoybeanUse.pdf

. Wang, L; Lyons, J; Kanehl, P; Bannerman, R; and Emmons, E (2000) "Watershed u rbanization and changes in fish communities in southeastern Wisconsin streams." J. American Water Resources Association. 36 p 1173

- 89. http://onlinelibrary.wiley .com/doi/10.1111/j.1752

- 1688.2000.tb05719.x/abstract

. Weersink, A; Walker, M; Swanton, C; and Shaw, JE (1992) "Costs of conventional and conservation tillage systems." Soil and Water Conservation. 47 (4): p 328

- 34. http://www.jswconline.org/content/47/4/328.abstract

. Weiderholt, R and Albrecht, K (2003) "Using Soybean as Forage." University of Wisconsin Cooperative Extension. http://www.uwex.edu/ces/crops/uwforage/SoybeanForage.htm

. Weil, A (2008) "Is Cottonseed Oil Okay?" Weil Lifestyle, LLC. Last Accessed: Feb. 25, 2014 http://www.drweil .com/drw/u/QAA400361/Is

- Cottonseed

- Oil

- Okay.html

. Welbaum, GE; Sturz, AV; Dong, Z; and Nowak, J (2004) "Managing Soil Microorganisms to Improve Productivity of Agro

- Ecosystems." Critical Reviews in Plant Sciences. 23 (2): p 175

- 93. http://www.tandfonline.com/doi/abs/10.1080/07352680490433295

. Wendel, J; Brubaker CL; and Percival AE (1992) "Genetic Diversity in Gossypium hirsutum and the Origin of Upland Cotton." American Journal of Botany 79 (11): p 1291

- 310. http://www.jstor.org/stable/2445058

. West, TO and Marland, G (2002) "A synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: Comparing tilla ge practice s in the United States." Agriculture, Ecosystems & Environment. 91 p 217

- 32. http://www.sciencedirect.com/science/article/pii/S016788090 100233X

. Whitney, D (1997) "Fertilization

- Soybean Production Handbook." Kansas State University. http://www.ksre.ksu.edu/library/crpsl2/c449.pdf

. Whitworth, R; Michaud, J; and Davis, H (2014) "Soybean Insect Management." Kansas State University. http://www.ksre.ksu.edu/bookstore/pubs/mf743.pdf

. Whitworth, RJ; Michaud, JP; and Davis, HN (2011) "Soybean Insect Management 2011." Kansas State University Agricultural Experiment Station and Cooperative Extension. http://www.ksre.ksu.edu/bookstore/

. WHO (2014) "World Health Organization (WHO): Frequently asked questions on genetically modified foods. ." Last Accessed: Feb. 19, 2014 http://www.who.int/foodsafety/publications/biotech/20questions/en/

. Williams, M (2013a) "Cotton Insect Eradiation/Cotton Insect Losses

- 2013." Mississippi State University.

273Williams, MR. "Cotton Insect Losses

- 2012." Ed. University, Mississippi State2013b. http://www.entomology.msstate.edu/resources/croplosses/2012loss.asp

. Wozniak, CA (2002) "Gene Flow Assessment for Plant

- Incorporated Protectants by the Biopesticide and Pollution Prevention Division, U.S. EPA." p 162

- 77. Columbus, Ohio. La st Accessed: December 3, 2010 http://www.biosci.ohio

state.edu/~asnowlab/Proceedings.pdf

. WSSA (2010) "WSSA Supports NRC Findings on Weed Control. Weed Science Society of America." http://invasivespecies.org.au/traction/permalink/WeedsNews483

. Wunderlin, R and Hansen, B (2008) Atlas of Florida Vascular Plants Tampa, FL: University of South Florida. http://florida.plantatlas.usf.edu/

. Yang M; E Wardzala; GS Johal; and Gray., J (2004) "The wound

- inducible Lls1 gene from maize is an orthologue of the Arabidopsis Acd1 gene, and the LLS1 protein is present in

no n

- photosynthetic tissues." Plant Molecular Biology. 54 p 175

- 91. http://www.ncbi.nlm.nih.gov/pubmed/15159621

. Yang, Y and Sheng, G (2003) "Enhanced pesticide sorption by soils containing particula te matter from crop residue burns." Environ. Sci. Technol. 37 p 3636

- 39. http://pubs.acs.org/doi/pdf/10.1021/es034006a

. York, A. (2012). "Weed Control Options in N.C." Last Accessed: 12

- 3

- 14 http://wayne.ces.ncsu.edu/files/library/96/wayne%20co.%20york%20cotton%20grow er%20meetings%202012.pdf

. York, AC (2014) "Section 14. Avoiding 2,4

- D injury to cotton., p. 164." http://cotton.ces.ncsu.edu/wp

- content/uploads/2014/02/2014

- Cotton

Information.pdf

. York, AC; Beam, JB; and Culpepper, AS (20 05) "Control of volunteer glyphosate

- resistant soybean in cotton." Journal of Cotton Science. 9 p 102

- 09. http://www.cotton.org/journal/2005

- 09/2/upload/jcs09

- 102.pdf

. Young, B to : Roseland, C. (2014). Living Without Regrets: Managing Weed Resistance. http://agwired.com/2014/03/03/living

- without

- regrets

- managing

- weed

resistance/

. Young, I M and Ritz, K (2000) "Tillage, habitat space and function of soil microbes." Soil and Tillage Research. 53 (3

– 4): p 201

- 13. http://www.sciencedirect.com/science/article/pii/ S0167198799001063

. Zapiola, ML; Campbell, CK; Butler, MD; and Mallory

- Smith, CA (2008) "Escape and establishment of transgenic glyphosateresistant creeping bentgrass Agrostis stolonifera in Oregon, USA: A 4

- year study." Journal of Applied Ecology. 45 p 486

– 94. http://onlinelibrary.wiley.com/doi/10.1111/j.1365

- 2664.2007.01430.x/full

. Zhao, L (2007a) "Understanding Air Emissions from Animal Feeding Operations." Ohio State University Extension. Last Accessed: March 11, 2014 http://ohioline.osu.edu/aex

fact/0721.html

.

274Zhao, L (2007b) "Understanding Air Emissions from Animal Feeding Operations." Ohio State University Extension. Last Accessed: March 11, 2014 http://ohioline.osu.edu/aex

fact/0721.html

. Zollinger, R (2014) "2014 North Dakota Weed Control Guide (W

- 253)." North Dakota State University. http://www.ag.ndsu.edu/weeds/weed

- control

- guides/nd

- weed

- control

- guide

1

. Zollinger, R; Peterson, D; and Moechnig, M (2006) "The Glyphosate, Weeds, and Crops Series: Biology and Management of Wild Buckwheat (GWC

- 10)." Purdue University Extension. Last Accessed: 4

- 15

- 14 https:// www.extension.purdue.edu/extmedia/GWC/GWC

- 10

- W.pdf

.

275

### 12 INDEX

acreage, 25, 32, 53, 56, 57, 61, 84, 100, 103, 127, 146, 222, 251, 263 air quality, vii, x, 23, 25, 33, 47, 48, 49, 50, 126, 136, 198, 222, 233 alternatives, 1, v, vi, vii, x, 12, 17, 19, 26, 102, 117, 122, 125, 130, 135, 154, 157, 163, 166, 168, 169, 170, 171, 181, 186, 195, 197, 198 beef production, 29, 94, 121, 235, 244 buffer zones, 88, 155 climate change, 25, 50, 51, 52, 53, 126, 136, 198, 262 cotton, conventional, 105, 130, 220 cotton, organic, 19, 89, 90, 117, 130, 131 cotton, volu nteer, 86, 124 cover crops, viii, 50, 74, 76, 77, 89, 111, 114, 118, 122, 175, 179 critical habitat, 204, 205, 206, 207, 209, 212, 214, 216, 224 crop rotation, ix, 29, 61, 70, 71, 73, 74, 75, 76, 77, 80, 89, 92, 111, 113, 114, 117, 118, 130, 145, 157, 176, 177, 188, 195, 265

cross

- pollination, 90, 92, 118 cultivation practices, 51, 117, 119, 206, 223 cumulative impacts, vii, ix, 10, 11, 12, 17, 134, 135, 137, 138, 139, 141, 160, 165, 168, 175, 176, 185, 187, 197, 198, 199, 200 dairy production, 29, 56, 58, 94, 121, 210, 237 economic environment, 1, 18, 107, 110, 127, 144, 220 endangered species, xxiii, 97, 205, 212, 215, 224 environmental consequences, 14, 17, 102, 206 exports, 18, 25, 91, 103, 106, 107, 127 Federal Food, Drug and Cosmetic Act, ii, xxi, 8, 9 5, 96, 99, 119, 121 Federal Insecticide, Fungicide and Rodenticide Act, ii, vii, xxi, 7, 8, 11, 97, 122, 131, 134, 135, 136, 137, 139, 140, 204, 219 food and feed, ii, 18, 25, 95, 96, 99, 100, 119, 121, 131, 132, 133, 211, 212, 214, 215, 217, 257 Food Qual ity Protection Act, xxi, 8, 99, 135 forage, 4, 29, 51, 56, 57, 63, 75, 94, 121, 133, 164, 165, 214, 215, 217, 220, 250 gene flow, 90, 208, 220, 259, 277 grazing, 29, 51, 57, 58, 94, 121, 164 greenhouse gases, xxii, 50, 51, 52, 100, 101, 126, 198, 267
groun dwater, x, 41, 42, 44, 45, 46, 47, 87, 126, 135, 139, 264 hay production, 4, 29, 54, 55, 56, 57, 61, 94, 121 herbicide use, ii, vii, 10, 11, 20, 80, 81, 82, 102, 105, 116, 131, 134, 144, 145, 147, 148, 149, 150, 151, 153, 154, 168, 173, 175, 176, 177, 187, 196, 198, 199, 200, 201, 202, 203 human health, 8, 10, 20, 25, 95, 98, 99, 102, 131, 133, 137, 138, 140, 175, 199, 200, 217, 219, 225 human safety, 82, 84, 98, 122 irrigation, 22, 26, 41, 42, 44, 45, 46, 47, 49, 50, 70, 73, 75, 84, 85, 86, 87, 100, 125, 2 02, 222, 255, 256, 260 isolation distances, 16, 17, 118 land use, 25, 32, 53, 56, 57, 61, 84, 100, 103, 127, 146, 222, 251, 263 National Environmental Policy Act, iv, xxii, 1, 2, 9, 10, 203, 225, 226, 227, 228, 230, 232, 254 National Organic Program, xxii, 87, 88, 91, 117, 118 notifications, xxi, 97, 136, 137, 219 organic farming, 87 pesticide registration, 96, 98, 122, 219, 220 pesticide tolerance, 8, 99 physical environment, 25, 33 plant diseases, i, 70, 82, 261 plant pest risk analysis, i, iii, vi, xxii, 2, 17, 208, 211

276plant pests, i, iii, iv, v, vi, vii, xxii, 1, 2, 3, 5, 6, 7, 9, 11, 14, 15, 16, 17, 21, 25, 68, 179, 205, 224, 226, 232 pollination, 90, 92, 130 polymerase chain reaction, 89 production costs, 26, 90, 105, 113 production practices, 25, 51, 91, 118, 136, 141, 173, 179, 196, 197, 199 registered pesticide, 7, 119, 122, 133, 223 risk assessment, xxii, 2, 11, 15, 64, 97, 98, 99, 133, 139, 140, 221, 224, 225, 226, 227, 228, 229, 266 scoping, iv, 10, 197 seed production, 28, 94, 117, 121 silage, 2 9, 94, 103, 121 socioeconomic impacts, 9, 12, 141 soil quality, x, 22, 71, 72, 73, 134, 197 soybean, conventional, vii, 16, 17, 220 soybean, organic, 19, 90, 91, 92, 130 soybean, volunteers, 124, 195, 213 spray drift, 47, 92, 135, 155, 242 stewardship, 71, 111, 114, 116, 141, 157, 179, 203, 261 tillage practices, vii, ix, x, 19, 22, 51, 62, 70, 72, 73, 74, 122, 134, 143, 145, 147, 156, 157, 179, 185, 198, 200, 201, 278 unreasonable adverse effects, 7, 8, 11, 97, 139, 176, 219 water resources, 22, 33, 44, 46 , 47, 52, 53, 222 weediness, 74, 205, 206, 207, 209, 213, 214, 220 worker health, 96, 98 worker safety, 25, 93, 94, 97, 120, 131

277