U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2012–3134

November 2012

Net Ecosystem Production (NEP) of the Great Plains, 

United States

Daniel Howard, Tagir Gilmanov, Yingxin Gu, Bruce Wylie, Li Zhang

Printed on recycled paper

Introduction

Gross primary production (GPP) and ecosystem 

respiration (Re) are the fundamental environmental 

characteristics that promote carbon exchanges with the 

atmosphere (Chapin and others, 2009), although other 

exchanges of carbon, such as direct oxidation (Lovett 

and others, 2006), can modify net ecosystem production 

(NEP). The accumulation of carbon in terrestrial ecosystems results in systems in which soil organic matter (SOM) carbon often exceeds biomass carbon (Post 

and Kwon, 2000). This SOM pool exists at a steady 

state between GPP and Re in ecosystems unless drivers change or the ecosystem endures environmental 

perturbations (for example, climatic). As indicated by 

Wilhelm and others (2011), conversion of grasslands 

to agriculture and cultivation can result in reduced soil 

carbon, with the release of carbon dioxide (CO2

) to the 

atmosphere by stimulated oxidation and higher Re; 

therefore, land-use and land management practices have 

clear effects on NEP, with potential repercussions on 

ecosystems. The recent demand for biofuels has changed 

land-use and cropping patterns, especially in Midwestern 

United States (Wilhelm and others, 2011). It is important 

to ensure the sustainability of these and other land uses 

and to assess the effects on NEP.

Flux tower networks, such as AmeriFlux and 

FLUXNET, consist of a growing number of eddy covariance flux tower sites that provide a synoptic record of 

the exchange of carbon, water, and energy between the 

ecosystem and atmosphere at various temporal frequencies. These towers also detect and measure certain site 

characteristics, such as wind, temperature, precipitation, 

humidity, atmospheric pressure, soil features, and phenological progressions. Efforts are continuous to combine flux tower network data with remote sensing data 

to upscale the conditions observed at specific sites to a 

regional and, ultimately, worldwide scale. Data-driven 

regression tree models have the ability to incorporate 

flux tower records and remote sensing data to quantify 

exchanges of carbon with the atmosphere (Wylie and 

others, 2007; Xiao and others, 2010; Zhang and others, 

2010; Zhang and others, 2011). Previous study results 

demonstrated the dramatic effect weather has on NEP 

and revealed specific ecoregions and times acting as 

carbon sinks or sources. As of 2012, more than 100 siteyears of flux tower measurements, represented by more 

than 50 individual cropland or grassland sites throughout the Great Plains and surrounding area, have been 

acquired, quality controlled, and partitioned into gross 

photosynthesis (Pg) and ecosystem Re using detailed 

light-response, soil temperature, and vapor pressure deficit (VPD) based analysis.

Study Area

As shown in figure 1, the Great Plains is a vast 

expanse located in the central United States where 73 

percent of the total surface area is grassland (36 percent) 

or cropland (37 percent). The Great Plains is an agriculturally intensive region where sustainable land management is necessary to promote soil conservation. Major 

environmental and climatic conditions in the Great Plains 

have clear spatially relative patterns that can be observed 

throughout historical data (Gu and others, 2012). For example, the average annual temperature generally increases 

from the northern Great Plains [4 degrees Celsius (°C)] 

to the south (22°C) and precipitation increases from the 

western Great Plains [200 millimeters (mm)] to the east 

(1,500 mm).

Grassland NEP in the Great Plains

Zhang and others (2011) applied regression tree modeling to incorporate grassland-specific flux tower recordings of NEP in conjunction with remote sensing, climate, 

phenology, and other biogeophysical data to map annual 

NEP of grasslands in the Great Plains at 250-meter (m) 

resolution for 2000–2008 (figure 2). In their results, the 

grasslands of the Great Plains were determined to be a net 

sink with an average annual NEP of 24 grams of carbon 

per square meter per year (g C/m2

/yr) and a standard 

deviation of 14 g C/m2

/yr. Throughout the 9-year period, 

the annual NEP was determined to be extremely variable, 
130° 120° 110° 100° 90° 80° 70°

40°

30°

0 250 500 MILES

0 250 500 KILOMETERS

EXPLANATION

Non cropland/grassland

Cropland

Grassland

U.S. Great Plains boundary

Omernik ecoregion (level 3)

Cropland flux tower

Grassland flux tower

Figure 1. Flux towers, land cover, and ecoregions in the Great Plains.

ranging from a low average annual NEP of 0.3 g C/m2/yr 

in 2002 to a high value of 47.7 g C/m2

/yr in 2005. The 

results provided an account of NEP for 36 percent of the 

total land cover in the Great Plains.

NEP Uncertainty Assessment and Site Selection 

and Development of Future Flux Towers

Although there has been substantial growth in flux 

tower networks, the extensive cost, maintenance, and 

management requirements associated with keeping each 

individual flux tower operational has limited network 

development. Proper placement of new flux towers is 

critical for maximizing adequate representation of certain 

vegetation cover types, climate conditions, or biogeophysical conditions. Working directly with the model 

and results from Zhang and others (2011), Gu and others 

(2012) developed an innovative method to identify and 

map areas that are underrepresented by the flux tower network. The NEP model from Zhang and others (2011) was 

regenerated using two different limits on extrapolation 

(10 percent and 50 percent). The absolute difference of 

weekly output from the two model versions was calculated, annually averaged, and mapped with a 250-m 

resolution to assess and identify instances where the NEP 

model relied on heavy extrapolation (figure 3). In theory, a 

pixel that incorporated ancillary environmental input data 

[for example, Normalized Difference Vegetation Index 

(NDVI), weather, soils, and phenology] that conformed 

to characteristics observed at a particular flux tower and, 

therefore, is well represented, would be assigned a similar 

NEP value in the 10 percent and 50 percent extrapolation models; however, pixels that characterized a range of 

environmental variables that were not well represented by 

any flux tower in the network would have a higher likelihood to be assigned NEP values that exhibited significant 

differences between the 10 percent and 50 percent extrapolation models. The resulting maps from this study could 

provide useful information for optimizing the site selection and development of future flux towers in the Great 

Plains and could serve as a proxy for NEP uncertainty 

maps.
120° 110° 100° 90°

40°

30°

U.S. Great Plains boundary

Omernik ecoregion (level 3)

Non cropland/grassland

Cropland

Grassland average annual net ecosystem production (NEP), 

in grams of carbon per square meter per year (g C/m2/yr)

>300

201 to 300

101 to 200

51 to 100

26 to 50

-24 to 25

-49 to -25

-99 to -50

-199 to -100

-299 to -200

<-299

EXPLANATION

0 250 500 MILES

0 250 500 KILOMETERS

Zhang and others, 2011

Figure 2. Average annual net ecosystem production (NEP) (2000–2008) for the grasslands of the Great Plains.
120° 110° 100° 90°

40°

30°

U.S. Great Plains boundary

Omernik ecoregion (level 3)

Incorporated flux tower

Non cropland/grassland

Cropland

High coefficient of variation (CV)

Mean absolute difference, in grams of carbon 

per square meter per year (g C/m2/yr)

0 to 25

26 to 50

51 to 75

76 to 100

>100

Gu and others, 2012

0 250 500 MILES

0 250 500 KILOMETERS

EXPLANATION

Figure 3. Average annual mean absolute difference between the two estimated NEP values (10 percent and 50 percent extrapolation). Areas 

with highest differences (yellow, orange, and red on the map) are interpreted as having low model confidence, being poorly represented by the 

current flux tower network, or both [excluding areas where the interannual coefficient of variation (CV) is greater than 20 percent (black area)].
MINNESOTA

SOUTH

DAKOTA

WYOMING

IOWA

NEBRASKA

UTAH

COLORADO

MISSOURI

KANSAS

108° 105° 102° 99° 96°

42°

39°

0 100 200 MILES

0 100 200 KILOMETERS

EXPLANATION

2009 crop type 

U.S. Greater Platte River Basin

Corn

Wheat

Soybeans

Other crops

Howard and others, 2011

Figure 4. Spatial distribution of corn, soybeans, wheat, and other crops of the Greater Platte River Basin for 2009. 

Crop Type Mapping and Cropland NEP in the 

Great Plains

Although grasslands account for a substantial part 

of the total land cover in the Great Plains, the ultimate 

objective is to model and quantify NEP for all major land 

cover types existing in the Great Plains. Croplands are the 

future of comprehensive NEP quantification in the region. 

The primary requirements for implementing NEP quantification of croplands are to develop spatially-accurate 

crop type classification data and a NEP algorithm for 

specific crop types. Howard and others (2012) developed 

a regression tree model based on weekly 250-m expedited 

Moderate Resolution Imaging Spectroradiometer (eMODIS) NDVI composites (Jenkerson and others, 2010), in 

conjunction with several other environmental variables, to 

identify and map distinct annual crop types (for example, 

corn, soybeans, and wheat) of the Greater Platte River 

Basin during 2000–2009 (figure 4). This approach is being 

expanded to include additional crop types (corn, soybeans, 

winter wheat, spring wheat, cotton, sorghum, and alfalfa) 

for the entire U. S. Great Plains. Additionally, with the use 

of crop-sited flux towers, progress is being made towards 

the development of crop-specific NEP models. With the 

addition of cropland, 73 percent of the total land cover 

will be accounted for in the overall NEP quantification of 

the Great Plains. This quantification of carbon fluxes in 

cropland and grassland will provide a better understanding of the effects various vegetation types and agricultural 

management practices have on the net carbon balance. 

Acknowledgments

This study was funded by the U.S. Geological Survey 

(USGS) Geographic Analysis and Monitoring Program 

and performed under USGS contracts G10PC00044 and 

G08PC91508. Any use of trade, product or firm names is 

for descriptive purposes only and does not imply endorsement by the U.S. Government.
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