Christopher K. Wright

Recent land use change in the Western Corn Belt threatens grasslands and wetlands

In the US Corn Belt, a recent doubling in commodity prices has created incentives for landowners to convert grassland to corn and soybean cropping. Here, we use land cover data from the National Agricultural Statistics Service Cropland Data Layer to assess grassland conversion from 2006 to 2011 in the Western Corn Belt (WCB): five states including North Dakota, South Dakota, Nebraska, Minnesota, and Iowa. Our analysis identifies areas with elevated rates of grass-to-corn/soy conversion (1.0–5.4% annually). Across the WCB, we found a net decline in grass-dominated land cover totaling nearly 530,000 ha. With respect to agronomic attributes of lands undergoing grassland conversion, corn/soy production is expanding onto marginal lands characterized by high erosion risk and vulnerability to drought. Grassland conversion is also concentrated in close proximity to wetlands, posing a threat to waterfowl breeding in the Prairie Pothole Region. Longer-term land cover trends from North Dakota and Iowa indicate that recent grassland conversion represents a persistent shift in land use rather than short-term variability in crop rotation patterns. Our results show that the WCB is rapidly moving down a pathway of increased corn and soybean cultivation. As a result, the window of opportunity for realizing the benefits of a biofuel industry based on perennial bioenergy crops, rather than corn ethanol and soy biodiesel, may be closing in the WCB.

Climate forcing of wetland landscape connectivity in the Great Plains

Habitat connectivity is a landscape attribute critical to the long-term viability of many wildlife species, including migratory birds. Climate change has the potential to affect habitat connectivity within and across the three main wetland complexes in the Great Plains of North America: the prairie potholes of the northern plains, the Rainwater Basin of Nebraska, and the playas of the southern plains. Here, we use these wetlands as model systems in a graph-theory-based approach to establish links between climatic drivers and habitat connectivity for wildlife in current and projected wetland landscapes and to discern how that capacity can vary as a function of climatic forcing. We also provide a case study of macrosystems ecology to examine how the patterns and processes that determine habitat connectivity fluctuate across landscapes, regions, and continents.

Combined analysis of land cover change and NDVI trends in the Northern Eurasian grain belt

We present an approach to regional environmental monitoring in the Northern Eurasian grain belt combining time series analysis of MODIS normalized difference vegetation index (NDVI) data over the period 2001-2008 and land cover change (LCC) analysis of the 2001 and 2008 MODIS Global Land Cover product (MCD12Q1). NDVI trends were overwhelmingly negative across the grain belt with statistically significant (p⩽0.05) positive trends covering only 1% of the land surface. LCC was dominated by transitions between three classes; cropland, grassland, and a mixed cropland/natural vegetation mosaic. Combining our analyses of NDVI trends and LCC, we found a pattern of agricultural abandonment (cropland to grassland) in the southern range of the grain belt coinciding with statistically significant (p⩽0.05) negative NDVI trends and likely driven by regional drought. In the northern range of the grain belt we found an opposite tendency toward agricultural intensification; in this case, represented by LCC from cropland mosaic to pure cropland, and also associated with statistically significant (p⩽0.05) negative NDVI trends. Relatively small clusters of statistically significant (p⩽0.05) positive NDVI trends corresponding with both localized land abandonment and localized agricultural intensification show that land use decision making is not uniform across the region. Land surface change in the Northern Eurasian grain belt is part of a larger pattern of land cover land use change (LCLUC) in Eastern Europe, Russia, and former territories of the Soviet Union following realignment of socialist land tenure and agricultural markets. Here, we show that a combined analysis of LCC and NDVI trends provides a more complete picture of the complexities of LCLUC in the Northern Eurasian grain belt, involving both broader climatic forcing, and narrower anthropogenic impacts, than might be obtained from either analysis alone.

Classifying the Hydrologic Function of Prairie Potholes with Remote Sensing and GIS

A sequence of Landsat TM/ETM+ scenes capturing the substantial surface water variations exhibited by prairie pothole wetlands over a drought to deluge period were analyzed in an attempt to determine the general hydrologic function of individual wetlands (recharge, flow-through, and discharge). Multipixel objects (water bodies) were clustered according to their temporal changes in water extents. We found that wetlands receiving groundwater discharge responded differently over the time period than wetlands that did not. Also, wetlands located within topographically closed discharge basins could be distinguished from discharge basins with overland outlets. Field verification data showed that discharge wetlands with closed basins were most distinct and identifiable with reasonable accuracies (user’s accuracy = 97%, producer’s accuracy = 71%). The classification of other hydrologic function types had lower accuracies reducing the overall accuracy for the four hydrologic function classes to 51%. A simplified classification approach identifying only two hydrologic function classes was 82%. Although this technique has limited success for detecting small wetlands, Landsat-derived multipixel-object clustering can reliably differentiate wetlands receiving groundwater discharge and provides a new approach to quantify wetland dynamics in landscape scale investigations and models.

Land surface anomalies preceding the 2010 Russian heat wave and a link to the North Atlantic oscillation

The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April–May–June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to a warmer-than-normal early growing season was consistent with a persistently negative phase of the North Atlantic oscillation (NAO). Regression analyses showed that early season vegetation productivity in the EWB is a function of both the winter (December–January–February; DJF) and AMJ phases of the NAO. Land surface anomalies preceding the heat wave were thus consistent with highly negative values of both the DJF NAO and AMJ NAO in 2010.

Reanalysis data underestimate significant changes in growing season weather in Kazakhstan

We present time series analyses of recently compiled climate station data which allowed us to assess contemporary trends in growing season weather across Kazakhstan as drivers of a significant decline in growing season normalized difference vegetation index (NDVI) recently observed by satellite remote sensing across much of Central Asia. We used a robust nonparametric time series analysis method, the seasonal Kendall trend test to analyze georeferenced time series of accumulated growing season precipitation (APPT) and accumulated growing degree-days (AGDD). Over the period 2000–2006 we found geographically extensive, statistically significant (p<0.05) decreasing trends in APPT and increasing trends in AGDD. The temperature trends were especially apparent during the warm season and coincided with precipitation decreases in northwest Kazakhstan, indicating that pervasive drought conditions and higher temperature excursions were the likely drivers of NDVI declines observed in Kazakhstan over the same period. We also compared the APPT and AGDD trends at individual stations with results from trend analysis of gridded monthly precipitation data from the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis v4 and gridded daily near surface air temperature from the National Centers for Climate Prediction Reanalysis v2 (NCEP R2). We found substantial deviation between the station and the reanalysis trends, suggesting that GPCC and NCEP data substantially underestimate the geographic extent of recent drought in Kazakhstan. Although gridded climate products offer many advantages in ease of use and complete coverage, our findings for Kazakhstan should serve as a caveat against uncritical use of GPCC and NCEP reanalysis data and demonstrate the importance of compiling and standardizing daily climate data from data-sparse regions like Central Asia.

Reply to Kline et al.: Cropland data layer provides a valid assessment of recent grassland conversion in the Western Corn Belt

Kline et al. (1) pose a series of “what-if” scenarios intended to cast doubt on our (2) findings. These scenarios arise from a critical misreading of our paper and misinterpretation of the US Department of Agriculture’s Cropland Data Layer (CDL).

Characterizing the Climate-Driven Collapses and Expansions of Wetland Habitats with a Fully Integrated Surface–Subsurface Hydrologic Model

Links between climatic forcing and wetland habitats can be conceptualized using a graph-theoretical approach, which treats wetlands as nodes to map habitat connectivity and to define habitat networks for ecological analysis. The first and most crucial step in creating a network model, however, is to characterize the dynamic behaviors of the nodes, i.e., the occurrence of wetlands with ponded water, or water bodies. For the first time, this study applies a 3-D, fully integrated surface and subsurface flow model, HydroGeoSphere (HGS), to simulate the hydrologic dynamics of wetlands in the Prairie Pothole Region (PPR) and to characterize the resulting habitat networks as a function of climate variability. Results show HGS is able to simulate water movement in both surface and subsurface domains and capture “fill-spill” and coalescence/disaggregation behaviors of wetlands as they respond to wet and dry climatic conditions. Our simulations for a small representative subarea of the PPR show wetland networks in the PPR could easily shrink, degrade, or even collapse when the climate becomes drier. This study demonstrates the potential in applying sophisticated hydrologic models to solve critical ecological problems and the practical implications for water-resources management, conservation planning and decision-making in the PPR.

US agricultural policy, land use change, and biofuels: are we driving our way to the next dust bowl?

Lark et al (2015 Environ. Res. Lett. 10 044003), analyze recent shifts in US agricultural land use (2008–2012) using newly-available, high-resolution geospatial information, the Cropland Data Layer. Cropland expansion documented by Lark et al suggests the need to reform national agricultural policies in the wake of an emerging, new era of US agriculture characterized by rapid land cover/land use change.

Reply to Patla et al.: Amphibian habitat and populations in Yellowstone damaged by drought and global warming

Patla et al. (1) suggest that loss of amphibian habitat is distinct from amphibian status, and they claim that we (2) wrongly define populations. Ours is a functional definition of population that serves as a biologically relevant metric of species presence. We demonstrate that this amphibian metapopulation is being destabilized as habitat is lost.