DOI: 10.25338/b8061x
title: Multiple Benefits from Agricultural and Natural Land Covers in the Central Valley, CA

description: The data and code provided in this repository are associated with the
 technical report on the "Multiple Benefits from Agricultural and
 Natural Land Covers" project and were prepared by the authors for the
 Migratory Bird Conservation Partnership. MBCP partner organizations
 include The Nature Conservancy, California Audubon, and Point Blue
 Conservation Science. Executive Summary The Central Valley of California
 is one of the most heavily modified landscapes in the world, with millions
 of acres of semi-arid grassland and desert transformed into an irrigated
 crop production powerhouse through large-scale infrastructure and
 irrigation projects. Despite its reputation as an agricultural “sacrifice
 zone”, it remains an area of conservation focus for its varied, unique,
 and vibrant ecosystems, from rare vernal pools and serpentine grasslands
 to the extensive networks of riverine systems, riparian forests, and
 wetlands that converge at the Sacramento-San Joaquin Delta. While the
 importance of these natural areas for human-valued functions such as water
 supply and quality regulation, biodiversity, culture, and recreation is
 well established, the dominance of agricultural land covers in the Central
 Valley underscores the need to understand to what extent they contribute
 to or detract from similar valued ecosystem functions beyond crop
 production. Much of the information that is available on the potential
 benefits from agricultural and natural land covers is not centralized.
 Instead, disparate reports from research activities that vary in
 geographic location, scope, and timeframe constitute the bulk of the
 literature. Furthermore, most studies implement a particular suite of
 metrics to characterize benefits or tradeoffs provided by a land cover
 depending on the objectives of the study. Therefore, a synthesis of
 information on multiple benefits that aggregates metrics into a single
 database with comparable units of measure is an important step towards
 incorporating multiple benefits research into concerted planning and
 policy making efforts for a multifunctional Central Valley landscape. We
 performed a rapid evidence assessment following a consistent search
 strategy and pre-determined inclusion/exclusion criteria. We limited the
 results of the literature search to peer-reviewed publications from
 2010-2020 with a geographic focus on the Central Valley, including the
 Sacramento-San Joaquin Delta. We extracted published, quantitative
 estimates of land cover associated benefits and/or tradeoffs and compiled
 a database consisting of metrics on: 1) climate regulation (e.g.,
 greenhouse gas emissions, carbon storage/sequestration), 2) economy (e.g.,
 livelihoods, production value), 3) environmental quality (e.g., pollution,
 pesticide load), 4) water (e.g., water quality, water use), and 5)
 wildlife, specifically value for avian conservation. We also consulted a
 panel of experts in the fields of agricultural ecology and conservation to
 assess: 1) avian conservation value, and 2) vulnerability to the impacts
 of climate change of each of the land covers. Finally, we produced a
 spatially-explicit model using publicly-available datasets to visualize
 the distribution of ecosystem benefits and tradeoffs, including carbon
 storage potential, air and water quality, groundwater recharge, and
 socio-cultural benefits. We found that the agricultural land covers most
 likely to be associated with multiple benefits were alfalfa, rice, and
 rangelands/pastures. Alfalfa was associated with benefits such as carbon
 sequestration and managed aquifer recharge potential, along with minor
 support for biodiversity, although tradeoffs such as nitrous oxide
 emissions from mature stands and high consumptive water use were also
 noted. Flooded rice systems were notable for their high value for
 wildlife, particularly migrating and wintering bird species, along with
 their economic value in the form of relatively high wages for agricultural
 labor, although methane emissions and consumptive water use were also a
 concern. Rangelands and pastures (i.e., grasslands managed for livestock
 production) had high potential benefits for climate regulation via carbon
 storage and sequestration in soils and belowground biomass, along with
 high value for biodiversity and support of valuable agricultural
 pollination services. In contrast, annual field crops such as tomatoes,
 corn, and cotton were the most likely to be associated with tradeoffs such
 as greenhouse gas emissions, nitrate leaching hazard, and heavy pesticide
 use. Natural land covers such as wetlands and riparian areas were mostly
 associated with benefits such as carbon storage (particularly in riparian
 areas) and pollutant mitigation (in the case of wetlands), while some
 tradeoffs in greenhouse gas emissions were noted. The spatial distribution
 of benefits and tradeoffs was highly heterogeneous, although in many cases
 a north-south trend was evident with areas in the northern Central
 Valley/Sacramento Valley exhibiting more relative benefits than areas in
 the southern Central Valley/San Joaquin Valley. The former is noted for
 the concentrated production of rice, along with a mixture of tomatoes,
 alfalfa, and orchard crops such as almonds and walnuts. The latter, on the
 other hand, is associated with most of the Central Valley’s annual
 production of annual row crops (e.g., cotton), oranges and lemons, table
 grapes, and deciduous perennial tree crops such as pistachios, almonds,
 peaches, and prunes. Carbon storage patterns were particularly
 distinctive, with hotspots in the highly organic soils of the
 Sacramento-San Joaquin Delta and the former Tulare lakebed. Our ability to
 draw general conclusions on the relative benefits or tradeoffs associated
 with Central Valley land covers was limited by the single-intervention
 nature of most of the quantitative research available on benefit/tradeoff
 related metrics. Experimental designs often must restrict activities to a
 single or few related land covers and investigate the impacts of an
 intervention on the metric of interest. For the purposes of cross-system
 comparisons, there were very few studies that addressed variability in
 benefit/tradeoff metrics across multiple land covers from a multiple
 benefits or multi-functional landscapes perspective. Studies reviewed for
 many land covers were focused on a few key metrics of known importance for
 that land cover, e.g., methane emissions in rice, rather than a broader
 survey of potential benefits and tradeoffs. Furthermore, most experimental
 analyses are spatially biased and not representative of the entire Central
 Valley landscape. These challenges highlight the need for more research on
 human-valued benefits across land covers from a multiple benefits
 perspective, preferably with a common set of metrics and indicators
 relevant to most or all of the land covers under consideration.
 This report synthesizes the most recent, Central-Valley-specific
 literature available on multiple benefit and tradeoff metrics. Section I
 presents individual land cover profiles, with details on both the
 quantitative estimates for benefit metrics available in the literature as
 well as other land-cover-relevant metrics not included in benefit/tradeoff
 analysis. Section II presents results for spatial models of benefits and
 tradeoff metrics, including carbon storage, air, water, and habitat
 quality, groundwater recharge potential, and socio-cultural benefits,
 across the Central Valley. Finally, Section III provides further details
 on a cross-land cover benefit/tradeoff analysis using data extracted from
 the published literature, along with the results of expert panel scoring
 on relative avian conservation value and climate change vulnerability
 among land covers. Appendices are included for detailed coverage of
 methods for the rapid evidence assessment, benefit/tradeoff analyses, and
 index development.
description: Methods for Rapid Evidence
 Assessment and Benefit/Tradeoff analysis We performed a rapid review of
 the literature from the last 10 years focusing on benefits from
 agricultural and natural land covers in the Central Valley. We focused our
 search on 10 priority agricultural land covers, selected according to
 harvested acreage as reported by the California County Agricultural
 Commissioners’ 2018 Crop Report [30], and 3 priority natural (i.e., not
 for production purposes) land covers based on land area in the Central
 Valley [98]. See Appendix II for a detailed overview of the search
 strategy employed, the inclusion criteria, and the data collected from
 each study in the review. The resulting library of research included
 reports from peer-review studies as well as publicly available federal or
 state surveys/censuses and expert source surveys. In
 total, we reviewed 107 studies that included approximately 10 agricultural
 land covers and 3 natural land covers, recording over 77 different metrics
 for benefits and tradeoffs provisioned by those land covers. From the 107
 studies we obtained 512 unique observations across land covers and benefit
 metrics.  To
 complement the metrics reported in the peer-reviewed literature, we
 included metrics with quality data available in public repositories such
 as federal and state censuses, technical reports, and databases. These
 metrics were chosen because they provided information to supplement a
 benefit category with few examples in recent published literature or
 because they described metrics that are more suitable for survey formats
 than for the experimental interventions in the studies reviewed above.
 These additional datasets included: Crop
 production value ($USD
 ha<sup>-1</sup>)<sup> </sup> 
 Pesticide use by land cover type (kg applied
 ha<sup>-1</sup>)  Consumptive water use
 (m<sup>3</sup> ha<sup>-1</sup>) 
 Employment (workers ha<sup>-1</sup>) and average
 weekly wages earned ($USD worker<sup>-1</sup>
 ha<sup>-1</sup>) in the agricultural sector  Avian conservation
 score The Avian Conservation Score was
 developed through a survey of domain experts. In an iterative process, the
 expert sources reached a consensus on scores for each landcover type
 according to their relative value for nesting, foraging, or roosting
 different avian taxa during the breeding and non-breeding seasons. Avian
 taxa considered were those for which the Central Valley Joint Venture has
 established conservation objectives, including grassland, oak savannah,
 and riparian landbirds, waterfowl, shorebirds, and other waterbirds
 (Central Valley Joint Venture 2020). Each land cover type was given a
 final score on a 0-1 scale representing its relative total value across
 taxa and seasons.  Although our search strategy
 reflected <i>a priori </i>selection of focal benefit
 categories and metrics, benefit categories were subsequently adjusted to
 reflect the actual availability of information on each benefit category
 and associated metrics. Of the metrics described in the gap analysis
 above, we chose a subset of metrics with the best representation across
 land cover types and recategorized them into a suite of benefit
 categories: 1) Environmental health or quality, which included air
 pollution and pesticide use metrics; 2) Economy, which included
 agricultural (crop and forage) production value and livelihood value
 metrics; 3) Climate, which included greenhouse gas emission and carbon
 storage/sequestration metrics; 4) Water, which included water
 quality/pollution and water use metrics, and 5) Wildlife, which included
 the Avian Conservation Score. These categories were subsequently used to
 calculate a Multiple Benefits Index across land covers (within metrics)
 and within specific land covers (across metrics). The Multiple Benefits Index was
 calculated by normalizing all of the above metrics to a similar scale to
 enable comparison of multiple benefits and tradeoffs across land cover
 types. To compare benefit metrics within each landcover, reported values
 were converted to the same unit of measure and then transformed to a 0-1
 scale by setting the highest reported value across all land covers to 1
 and then calculating the remaining values according to the following
 formula: where MBI represents the Multiple Benefits Index, or normalized value of X, and X<sub>i</sub> represents a single value in the vector of values for X. Metrics were then categorized <i>post hoc </i>as either “benefits” or “tradeoffs” depending on their perceived value to the above sectors or interests. Benefits were those metrics that related to provisioning of a desirable service such as pollutant removal, while tradeoffs were metrics that related to provisioning of an undesirable service such as greenhouse gas emissions. Metrics considered tradeoffs were assigned a negative value by multiplying the Multiple Benefits Index by -1. The results of within-land cover benefit/tradeoff analyses were presented in the individual land cover profiles in Section III, while the results of cross-land cover benefit/tradeoff analysis are presented below. To compare land covers across all metrics, we calculated the mean Multiple Benefits Index score for all metrics within a land cover type and then ranked landcovers from highest to lowest mean score. See Appendix III for the rationale behind the selected metrics, along with unit conversions and assumptions made for each metric included in the benefit-tradeoff analysis. Finally, the benefit/tradeoff analysis was placed into the context of a changing environment through the development of a Climate Change Vulnerability Index, similarly to the climate change vulnerability index developed for birds in the Central Valley. As with the avian conservation score, we developed a survey for a panel of expert sources. The expert panel scored landcovers according to their estimated vulnerability to climate change based on a combination of sensitivity (intrinsic, physiological factors that contribute to climate change vulnerability) and exposure (extrinsic, environmental factors that contribute to climate change vulnerability) factors. Sensitivity scores and exposure scores were summed separately within each land cover and then multiplied together to derive the overall vulnerability index (sum of sensitivity*sum of exposure).  Because it does not represent a specific benefit or tradeoff, but rather a property of individual land covers, the CCVI was not included in the benefit/tradeoff analysis. Instead, it was used as a standalone metric to contextualize benefits and tradeoffs expected from land covers under climate change and the resulting uncertainty surrounding management scenarios. Methods for spatial hotspot/coldspot analysis of ecosystem benefits/tradeoffs <b>Ecosystem Service Metrics and Source Data</b> Land cover data were obtained from the USDA NASS Cropscape Data Layer (CDL2019), and recategorized according to the specifications of this project (Table 1). Riparian zones were determined as a 25 meter buffer around National Hydrological Dataset (NHD) flowlines for natural rivers and bodies of water, limited to non-developed and non-agricultural land cover categories. Air and Water Quality metric obtained from the California Healthy Places Index (HPI) geospatial dataset, Pollution and H<sub>2</sub>O Contamination indices respectively. Habitat quality metric obtained from Department of Fish and Wildlife (CDFW) Areas of Conservation Emphasis (ACE) dataset. Soil organic carbon content and percent clay particles were aggregated from the NRCS SSURGO soil data viewer. Parameter values were aggregated from individual soil horizon by volume up to soil map unit component, and aggregated from map unit component by percent total extent to map units. Theoretical maximum carbon storage was calculated based on percent clay as per Hoyle et al (2011) by the following equation:<br> <b><i>SOC%=0.5482× </i></b><b>ln</b><b><i>(clay%)</i></b><b><i>+1.3073</i></b> Soil potential carbon accumulation was calculated by subtracting existing soil carbon stock (SSURGO) from the theoretical maximum calculated as above, and applying a weighting factor based on land cover expected biomass productivity and soil disturbance frequency (Table 1). Rangeland and forest biomass productivity metrics were obtained from SSURGO soil data viewer by map unit component, and aggregated to map unit by percent total extent. Perennial crop biomass productivity data, previously used in orchard life cycle assessment modeling (Marvinney et al 2015, Kendall et al 2015) was obtained from a cooperating agri-services firm operating out of the San Joaquin Valley region, for 14 different tree crops. These data were joined to the CDL2019 perennial crops with average value assigned to any tree crop for which no biomass data was available. Groundwater recharge potential data was obtained from the UC Davis SAGBI dataset. Groundwater depth data was obtained from the Department of Water Resources (DWR) open test well data as the average of measurements from 2015-201 Crop productivity data (5-year mean yield in tons per acre) was obtained from the County Crop Commission (CCC) reports via USDA NASS, and joined to CDL2019 land cover units as well as recategorized land cover units as the mean yield value of any constituent crop types. The CDL 2019 original unit-based productivity analysis is thus the more accurate representation, as less aggregation of yield values was required.<br>   <b>Transformation and Aggregation of Ecosystem Service Metrics</b> Linear transformation was used to convert the range of values in each metric dataset to a scale of 0-1, with 0 being ‘worst’ and 1 ‘best’ in terms of ecosystem services provided. Combined metrics were generated by averaging the transformed values in the relevant metrics, and applying a linear transformation to re-scale the values to 0-1. Metrics were aggregated to a 5km hex grid covering the Central Valley by area-weighted averaging. Ecosystem service ‘hot’ and ‘cold’ spots were generated by extracting hexes with values below 0.2 and above 0.8 for the combination of all examined metrics.<br> <br>   Hoyle F.C., Baldock J.A., Murphy D.V. (2011) Soil Organic Carbon – Role in Rainfed Farming Systems. In: Tow P., Cooper I., Partridge I., Birch C. (eds) Rainfed Farming Systems. Springer, Dordrecht<br> <br> Marvinney EM, Kendall AM, Brodt SB (2015) Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production, Part II: Scenario and Sensitivity Analysis. J Ind Ecol 19(6)<br> <br> Kendall AM, Marvinney EM, Zhu W, Brodt SB (2015) Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production, Part I: Analytical Framework and Baseline Results. J Ind Ecol (19) 6<br>  
description: The database compiled from the Rapid Evidence Assessment, and
 data files for crop production values, pesticide use, water use, wages and
 employment (public databases), and the Avian Conservation Score are in
 separate .csv files that must be loaded individually. All data files
 needed to run in the R script are included in this repository.