Shifting cultivation geographies in the Central and Eastern US

Climate change is projected to transform U.S. agriculture through changes in yield [1–6] and shifts in the cultivation geographies of many crops [7–10]. Though climate strongly influences where and how humans cultivate [5, 11, 12], millennia of human activity have pushed cultivation geographies far beyond what sun, soil, and water alone can support. Modern agricultural systems emerge from the interactions of biophysical conditions with the cultivation decisions of millions of farmers—themselves shaped by the interactions technological norms, political-economic incentives, and on-farm realities.

The agricultural landscapes that emerge from these complex interactions in the United States (U.S.) are some of the most productive agricultural systems on the planet. Over the last century, these systems have seen a tripling of soy and wheat yields and a five-fold increase in corn yields [13]. Today, over of two-thirds of land in the coterminous U.S. is devoted to the production of food, fuel, and fiber [14]. Six crops—corn, cotton, soy, wheat, hay, and alfalfa—cover nearly 80% of cultivated acreage [15, 16]. The dominance of these crops reflects less biophysical conditions and more political-economic and technological norms that incentivize simplified commodity production [14, 17]. Innovations in input use [18, 19], crop genetics [20–22], irrigation technologies [23, 24], and precision agriculture [25, 26] have strongly contributed to the dominance of these five crops. Federal policies—including the introduction of price floors for major grains and acreage-based production controls [27, 28]—have also contributed, driving a drop in the average number of crops produced per farm from roughly 4.5 to 1 over the last 60 years [29]. Federal crop and income insurance programs further incentivize commodity cultivation by providing a financial buffer against their under-performance [30], slowing adaptation to future climate change [31]. These federal policies are themselves the outcomes of political processes that reflect efforts by private agricultural, food, energy, and environmental organizations to lobby for particular programs [32, 33].

There is strong consensus that significant shifts in the agricultural technologies and political-economic incentives that currently shape U.S. agricultural systems are needed to meet future demand for food, fuel, and fiber in a much warmer climate. For example, Liang et al [5] project that by 2040, climate change will reduce the total factor productivity (TFP)—a measure of agricultural output per unit input—of U.S. agriculture by 4.34% annually (RCP8.5). They conclude that in the next 30 years, climate change will cause the loss of all national TFP gains achieved from 1981 to 2010 and that technological advances would have to double by 2040 to sustain current levels of agricultural output. Burchfield et al [15] find that without maintaining historical rates of innovation, the negative impacts of climate change on U.S. yields corn, soy, and wheat will be increasingly severe; however, if technological innovation grows at even the lowest rates seen in recent decades, yields may actually increase [34]. Other work highlights the adaptive potential of climate-smart agricultural practices [35, 36], on-farm emission reduction efforts [26, 37, 38], cultivar shifts [39–41], infrastructural expansion, and shifting U.S. Farm Bill priorities [17, 42]. Taken together, this research highlights how even small differences in our assumptions about the pace and direction of future technological and political-economic change can significantly alter projected agricultural futures.

Despite the importance of agricultural technology and political-economic incentives in shaping agricultural land use, most contemporary efforts to understand and project cultivation geographies have focused exclusively on the role of biophysical conditions [7, 8, 10, 43–45]. Understanding how biophysical conditions interact with agricultural technologies, political-economic incentives, and on-farm realities to shape cultivation possibilities for farmers (and the socio-environmental consequences of these cultivation outcomes) is paramount to identifying adaptive pathways towards resilient and sustainable agricultural futures. In this paper, I explore how climate has historically interacted with agricultural activity to shape the cultivation geographies of six crops that constitute ∼80% of cultivated land in the Central and Eastern U.S.: alfalfa, corn, cotton, hay, soy, and wheat. For each crop, I first model the probability of a crop's occurrence based solely on biophysical conditions (which I refer to as 'biophysical suitability') and again based on the historical interactions between biophysical conditions and the capacity of various human interventions—such as input use and crop insurance—to alter biophysical realities ('agricultural suitability'). One goal of these modeling efforts is to determine whether we can predict historical cultivation geographies using only biophysical predictors for which reasonable projections into the future exist. Another is to assess the extent to which human interventions have already expanded, amplified, and altered the cultivation geographies defined by biophysical conditions alone. The results indicate that we can, in fact, predict historical cultivation geographies well using only biophysical predictors; however, they also suggest that accounting for endogenous human responses to biophysical realities expands and amplifies cultivation geographies. Using these historical models, I project future shifts in cultivation geographies to 2100 under low, moderate, and high emissions scenarios using only biophysical predictors. While these preliminary projections suggest that biophysical shifts alone are likely to drive the northern shift of current cultivation geographies—with much of the Midwestern US becoming unsuitable to the cultivation of corn by 2100—the projections also likely overestimate these shifts by ignoring the potential impact of technological innovation and adoption, varietal shifts, and a shift towards more adaptive political-economic incentives. I conclude by discussing the importance of supporting efforts across the Central and Eastern U.S. to mitigate these probable geographic shifts through intentional human intervention, while also warning of biophysical limits to these efforts.

2.1. Data

2.2. Historical suitability models and validation

2.3. Future suitability projections

3.1. Historical suitability models

The results suggest that climate, soil, and topography drive cultivation geographies (table 2(A)), with climatic predictors—particularly average temperature, temperature variability, and temperature extremes—dominating variable importance (figure 2, SI figure 1; SI table 1). This finding corroborates previous research indicating that cultivation geographies are strongly driven by biophysical parameters alone [8–10, 60] and confirms my hypothesis that we can predict cultivation geographies reasonably well using only biophysical factors. In particular, indicators of mean, maximum, and minimum seasonal temperature show the highest variable importance across crops (figure 2) and appear to interact with crop suitability in highly nonlinear ways (SI figure 14).

The inclusion of indicators of human intervention—agricultural input use, farm resources, and farm(er) characteristics—increases predictive performance, with the percent of correctly classified crop occurrences rising to 93% for corn and soy, 97% for cotton, and nearly 95% for wheat (table 2(B): Sensitivity). In addition to increasing predictive performance of the models, the inclusion of agricultural predictors alters predicted cultivation geographies in two important ways. First, agricultural activity amplifies biophysical geographies, with regions showing high biophysical suitability to a particular crop increasing in suitability and, conversely, regions less biophysically suited to a crop's cultivation showing declines in suitability (figure 1(C)). Second, agricultural activity expands biophysical suitability, with areas on the periphery of biophysically suited regions increasing in suitability—particularly for alfalfa, corn, and soy (figure 1(C)).

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What are the agricultural factors driving the amplification and expansion of biophysical suitability? When averaged across crops, crop insurance coverage—or the total acres enrolled in any federal, private, or other crop insurance program standardized by the total number of agricultural acres in a county—is the most important predictor of crop suitability (figure 2). This is seen most strongly for corn and soy cultivation, which are among the most heavily insured commodity crops in the U.S. [61]. Government receipts—which include payments for participation in conservation programs, loan deficiency payments, disaster payments, and all other federal farm programs under which payments were made directly to farm operators (with the exception of federal crop insurance)—as well as chemical and fertilizer use are also strongly predictive of crop suitability. Despite the relative importance of crop insurance and federal support, climate indicators dominate variable importance across crops, particularly indicators of seasonal temperature (e.g. temperature seasonality, minimum cold temperature, maximum warm temperature) (figure 2; SI figure 2).

Across crops, indicators of agricultural activity are associated with lower levels of crop suitability. Figure 3 shows partial dependence plots for the most important agricultural predictors. These plots visualize the effect of each predictor on the probability of crop presence while holding other predictors constant. For most crops, an increase in the use of inputs (chemicals and fertilizer) and an increase in government support (insurance and government receipts) is associated with a decrease in the predicted suitability of a region to a crop. This suggests that areas of relatively low suitability require higher levels of input use and external resources to support the crop's cultivation. This is further supported by the finding that the regions in which crops move from 'absent' to 'present' with the addition of agricultural predictors (figures 1(B) and (C)) are those with relatively high levels of input use, insurance coverage, and federal support; conversely, regions that move from 'present' to 'absent' are those with relatively low levels of these factors (figure 1; SI figure 18).

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3.2. Future suitability projections

The high accuracy of the historical biophysical models (table 2(A)) suggests that we can, in fact, predict major shifts in crop suitability reasonably well using only biophysical predictors; however, our preliminary results also highlight the important ways in which agricultural technology, political-economic incentives, and farm circumstances have already amplified, expanded, and contracted biophysical suitability in many regions. Given the importance of these biophysical predictors in shaping crop suitability, I project suitability to 2100 using only biophysical indicators. These projections, of course, miss important human dynamics driving cultivation geographies, particularly adaptive technological and management efforts to mitigate biophysical changes; however, given the strong performance of historical biophysical suitability models, they also likely capture the major regional shifts in suitability we can anticipate over the next century for these important crops.

With moderate emissions (SSP3-7.0), the Central and Eastern U.S. is projected to see daily mean temperature increases of up to 6 °C by 2100 (figure 4(A)). The maximum temperature in the warmest month of the year is projected to increase by up to 10 °C, with some of the highest increases in agriculturally important regions (figure 4(B)). This corroborates existing studies projecting an increase of at least 2 °C in mean U.S. temperatures by 2050 and of up to 8 °C by the end of the century under severe warming [62, 63]. Though precipitation is generally less predictive of suitability than temperature, the region is also expected to see significant shifts in precipitation (figures 4(C) and (D)), which intensify under more severe emissions scenarios (SI figure 5).

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The future climate conditions depicted in figure 4 will significantly reshape biophysical suitability across the Central and Eastern U.S. (figure 5; SI figures 6 and 7), causing a near collapse of corn cultivation in the Midwestern U.S. by 2100. Soy, alfalfa, and wheat cultivation shift strongly northward by the end of the century. The area across the southern U.S. cultivated with cotton strongly contracts, and hay cultivation expands into the Central U.S. These shifts are similar, though less severe under SSP2-4.5, which assumes moderate population growth, slow progress towards sustainable development, and moderate declines in environmental system quality (SI figure 12). These shifts are strongly exacerbated under more severe emissions SSP5-8.5 which assumes continued fossil-fueled development, strong market integration, and rapid economic growth (SI figure 13). Under this more severe scenario, suitability loss is widespread for all crops, with a complete collapse of suitability (as defined by a suitability threshold of 0.4) by 2100 for corn, hay, and cotton. Importantly, in figure 5 I classify crop 'presence' using a suitability threshold of 0.4 rather than higher sensitivity-maximizing thresholds used for historical suitability maps, as these higher thresholds render most crops completely unsuitable to the Central and Eastern U.S. in the future (SI figure 13). Though this lower threshold may not reflect the suitability levels required to meet modern production objectives, it provides a sense of when and where a crop's cultivation may cease to be a viable option for farmers in a region.

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Although agricultural activity—specifically input use, crop insurance, and government support—plays an important role in amplifying and expanding current cultivation geographies, I find that climate drives suitability, accurately predicting as much as 93% of cotton and wheat occurrences and ∼87 and ∼90% of corn and soy occurrences (table 2(A); SI table 1). This corresponds with existing research highlighting the significant contribution of climate variability to agricultural yields [5, 12, 64] and the nonlinear manner in which climate—particularly temperature—interacts with yields [3, 34] (SI figure 14). This research holds dire warnings for the future of global agricultural systems, suggesting that each 1 °C of warming is projected to decrease global yields of wheat by 6%, maize by 7.4% and soybeans by 3.1% [4]. The research presented in this paper looks beyond production to identify the regions biophysically capable of supporting these crops in the future. The findings suggest massive shifts in suitability for the six crops that currently dominate agricultural landscapes in the U.S. This means that significant agricultural adaptation will be necessary and inevitable in the Central and Eastern U.S.

Understanding the factors that have historically altered otherwise unsuitable landscapes for agricultural production is key to supporting future adaptation. Though indicators of seasonal weather dominate variable importance, the results also indicate that access to crop insurance coverage and agricultural inputs strongly contribute to crop suitability, which has extremely important implications for the future. According to the USDA's Risk Management Agency (RMA), the agency responsible for administering federal crop insurance programs, over 85% of planted acreage for major crops is currently covered by crop insurance, with over 90% of corn and soy cultivation covered by some form of insurance [65]. Though these programs are an important source of income stabilization for U.S. farmers, they are also associated with lower rates of adoption of adaptive, climate-smart management practices that help to mitigate climate change impacts. For example, insured corn and soy have climate sensitivities that are, respectively, 67% and 43% larger than uninsured areas [31]. Similarly, I find that areas with higher rates of insured acreage are strongly associated with decreased crop suitability (figure 3; SI figure 18). Participation in these programs is also associated with other maladaptive practices such as reduced on-farm diversification [66, 67], the cultivation of more water-intensive crops [68, 69], and the expansion of corn and soy production beyond the periphery of the Corn Belt, displacing other crops better suited to the biophysical realities of the region [11, 70–73]. Given the overwhelming importance of federal crop insurance to countless U.S. farmers [31, 61, 74], it is imperative to critically examine whether these insurance programs are decoupling farmers from environmental risk in a manner that disincentivizes agricultural adaptation to changing climate.

Fertilizer and chemical use also contribute to the expansion and amplification of biophysical suitability. Fertilizer and chemical application rates in the Central and Eastern U.S. are some of the highest on the planet [18] and overuse in the region has already affected ecosystem quality [75] and farmers' bottom lines [11], with average per farm expenditures—of which labor, machinery, fertilizer, and chemicals comprise over 30%—reaching over $176 000 in 2017 [13]. Given the importance of input use in supporting crop suitability, three important points must be made. First, considering that an estimated 65% of farming operations currently do not follow best management practices for fertilizer and chemical application [76–78], the adoption and efficient application of existing technologies should be a top priority moving forward [24]. This said, there is emergent research indicating that maximum yields will soon plateau unless more radical changes such as change in crop carbon use efficiency are made [35, 79, 80]. Second, even in areas biophysically suited to the cultivation of a crop, the challenges of modern farming may render cultivation unsuitable for many farmers [81–83]. Increased input expenditures are strongly associated with unprecedented levels of famer debt [84] and a nearly 40% drop in net farm income since 2013 [85–87]. These socioeconomic challenges are deeply exacerbated for Black farmers [42, 88–91] and other underserved groups [92–94]. Additional research is needed to identify how political-economic, technological, sociocultural, and individual factors interact with biophysical suitability to define what is actually attainable for farmers. In addition to these important social thresholds, it is equally important to identify the environmental thresholds that may significantly reshape future suitability. Input-intensive agricultural systems exert a number of negative environmental externalities that erode ecosystem services essential to crop production, including pollination [95, 96], pest management [97], water retention [98], climate regulation [99, 100], and nutrient supply [101, 102]. These externalities can undermine the ecosystem services essential to agricultural production, reducing yields [15] and resilience to changing climate [103].

Despite these climatic, social, and ecological challenges, there is room for optimism. First, the projections presented in this study assume that the fundamental relationships between biophysical conditions, agricultural activity, and suitability do not change in the future. The technological innovations of the last century have drastically increased agricultural productivity, bringing tremendous changes to agricultural systems worldwide. It is highly likely that the next century will bring similarly transformative innovations; however, for these innovations to be effective they must mitigate, rather than accelerate, the socio-environmental externalities associated with current production practices. This is possible through sustainable intensification that leverages information-intensive—rather than input intensive—innovations such as genome editing and precision agriculture as well as ecosystem-based interventions boost ecosystem services to support agricultural productivity [24, 34, 104]. Given that even small shifts in our assumptions about technological innovation significantly alter projected agricultural futures [34], understanding when and how technological change might mitigate suitability shifts as well as how access to these technologies might vary across agricultural communities is a crucial area for continued research. The projections presented in this paper miss important, emergent innovations such as climate-smart agricultural initiatives that reduce greenhouse gas emissions and sequester carbon [36, 105] or the increase of conservation agricultural practices across the region [73, 106, 107]. By missing the potential role of these important future innovations, the tentative projections presented in this paper likely overestimate shifts in cultivation geographies. Understanding how increased participation in these initiatives might mitigate the cultivation shifts suggested by these analyses is a crucial avenue for future research.

Second, these projections assume the political-economic forces manifest in historical cultivation geographies will persist into the future. Since the 1960s, harvested soy and corn acreage has increased by 76%, while acreage for other feed crops such as oats, barley, sorghum, and hay has declined by a combined 50 million acres [17, 108]. Corn and soy alone now comprise nearly 56% of harvested cropland in the U.S. [13], with cultivation expanding well beyond the periphery of the Corn Belt into regions less biophysically suited to these crops [70, 109]. The strong market and policy signals driving the expansion of corn and soy into poorly suited regions limits farmer capacity to explore more sustainable alternatives [110], or worse, locks farmers into maladaptive systems that buffers them economically from environmental change [31]. Rather than incentivizing systems lock-in with a few crops that will require higher rates of agricultural intervention in the future, we must incentivize and support experimentation with alternative crops [111] and management paradigms. These adaptive transitions will not be without significant economic costs, so federal agricultural policy must shift from incentivizing maladaptive lock-in towards incentivizing experimentation to create new cultivation regimes suited to future biophysical realities [112]. This experimentation will be expensive, time-consuming, and difficult for U.S. farmers who are already reporting, on average, negative net incomes [91]. Therefore, it is imperative federal farm policy devote significant funds to compensating farmers for engaging in the hard work of agricultural transition [112]. The research community must support this shift by examining and elevating barriers and bridges to transition—from reliable access to childcare [113] to psycho-social decision-making processes [114, 115] to racial discrimination [42]; by working to design and promote new climate-smart agricultural practices and technologies; and crucially, by pushing for more adaptive federal policies that support resilience over monoculture [116].

This research highlights the ways in which human activity has altered otherwise unsuitable landscapes for agricultural production. Over the last 20 years, agricultural activity—specifically access to crop insurance and the use of agricultural inputs—has expanded and amplified biophysical suitability. Though climate change will challenge many agricultural communities in the Central and Eastern U.S. by altering the biophysical factors that drive suitability, sustaining historical rates of agricultural activity could help to mitigate projected shifts in biophysical suitability in some regions. For these agricultural interventions to be effective, however, they must mitigate, rather than accelerate, the socio-environmental externalities associated with current production practices. In addition to incentivizing experimentation and supporting sustainable intensification, stakeholder-engaged work is needed to increase our fundamental understanding of how agricultural landscapes emerge and to use this understanding to prepare for the major agricultural transitions anticipated over the next century. Agricultural adaptation to climate change in the Central and Eastern U.S. will be necessary and inevitable. The time to start the transition is now.

I thank Dr Chris Lant for the conversations that inspired this paper, Dr Tom Edwards for sharing his modeling insights, and to Drs Matt Yost, Jeremy Cowan, and Debjani Sihi for their soil expertise. Special thanks to Drs Andrea Rissing, Doug Jackson-Smith, and Andrea Basche for crucial conversations about future cropscapes and to Britta Schumacher for her invaluable help constructing the USDA Census data. Finally, many thanks to the teams who built and shared the open-source data used throughout the paper.

No new data were created or analysed in this study.