The effect of climate change on rural land cover patterns in the Central United States

Lant, Christopher L.; Stoebner, Timothy J.; Schoof, J. T.; Crabb, Benjamin A.

doi:10.1007/s10584-016-1738-6

Cited by 21 publications

(13 citation statements)

References 44 publications

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“…This finding should come as no surprise because soybean has already been called Africa's Cinderella crop (Kolapo, ). Moreover, a meta‐analysis of projected changes in the production areas depicts a promising future for soybean (Lant et al, ). Based on this knowledge, we undertook a systematic modelling analysis of future trends based on all the available data for soybean and other major legume crops in Africa.…”

Section: Resultsmentioning

confidence: 99%

“…Africa is one of the few continents where substantial arable land is available for crop production; and with mechanization, the land area under cultivation could grow significantly. Globally, land that is suitable for soybean production has shown a northward shift in recent years (Lant, Stoebner, Schoof, & Crabb, 2016). The projected yield and sowing area gains suggest a large expansion in global soybean production, even though such shifts in production areas will depend (2017), driven by climate projections from a global climate model for two future scenarios following the Representative Concentration Pathways (RCP4.5 and RCP8.5) largely upon GHG emissions and the success of mitigation strategies (Tai et al, 2014;Tai & Martin 2017).…”

Section: Climate Change Is Unlikely To Have Negative Impacts On Futmentioning

confidence: 99%

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Modelling predicts that soybean is poised to dominate crop production across Africa

Foyer

Siddique

Tai

et al. 2018

Plant Cell & Environment

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The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume‐based farming is particularly important in Africa, where small‐scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land‐use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.

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Section: Resultsmentioning

confidence: 99%

Section: Climate Change Is Unlikely To Have Negative Impacts On Futmentioning

confidence: 99%

Modelling predicts that soybean is poised to dominate crop production across Africa

Foyer

Siddique

Tai

et al. 2018

Plant Cell & Environment

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“…However, there was more agreement between the trends predicted by the BRT PDM and BRT SDM than between other combinations of PDM and SDM algorithms. Predictions from the BRT SDM were also similar to geographic responses predicted for crops in the region (some of which fall in the same subtribe as A. gerardii ) that have current distributions similar to the distribution of A. gerardii (Lant, Stoebner, Schoof & Crabb, ). For these reasons, we have more confidence in predictions from the BRT SDM.…”

Section: Resultsmentioning

confidence: 99%

Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change

Smith

Alsdurf

Knapp

et al. 2017

Global Change Biology

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Phenotypic distribution within species can vary widely across environmental gradients but forecasts of species' responses to environmental change often assume species respond homogenously across their ranges. We compared predictions from species and phenotype distribution models under future climate scenarios for Andropogon gerardii, a widely distributed, dominant grass found throughout the central United States. Phenotype data on aboveground biomass, height, leaf width, and chlorophyll content were obtained from 33 populations spanning a ~1000 km gradient that encompassed the majority of the species' environmental range. Species and phenotype distribution models were trained using current climate conditions and projected to future climate scenarios. We used permutation procedures to infer the most important variable for each model. The species-level response to climate was most sensitive to maximum temperature of the hottest month, but phenotypic variables were most sensitive to mean annual precipitation. The phenotype distribution models predict that A. gerardii could be largely functionally eliminated from where this species currently dominates, with biomass and height declining by up to ~60% and leaf width by ~20%. By the 2070s, the core area of highest suitability for A. gerardii is projected to shift up to ~700 km northeastward. Further, short-statured phenotypes found in the present-day short grass prairies on the western periphery of the species' range will become favored in the current core ~800 km eastward of their current location. Combined, species and phenotype models predict this currently dominant prairie grass will decline in prevalence and stature. Thus, sourcing plant material for grassland restoration and forage should consider changes in the phenotype that will be favored under future climate conditions. Phenotype distribution models account for the role of intraspecific variation in determining responses to anticipated climate change and thereby complement predictions from species distributions models in guiding climate adaptation strategies.

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“…D r a f t 6 Land cover variables for current conditions included rowcrops (corn, soybean, and cotton), wheat, forest, and developed land and derived from the National Agricultural Statistics Service's Cropland Data Layer (http://nassgeodata.gmu.edu/CropSpace/). For the identified climate change scenarios, multivariable fractional polynomials were applied in a logistic regression context to model land cover variables as a response to climatic, edaphic, and topographic determinants (Stoebner and Lant 2014;Lant et al 2016). Developed land and water classifications were not modeled and therefore assumed to not change under any scenario.…”

Section: Climate and Land Cover Scenariosmentioning

confidence: 99%

Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change

Bouska

Whitledge

Lant

et al. 2019

Can. J. Fish. Aquat. Sci.

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Land cover is an important determinant of aquatic habitat and is projected to shift with climate changes, yet climate-driven land cover changes are rarely factored into climate assessments. To quantify impacts and uncertainty of coupled climate and land cover change on warm-water fish species’ distributions, we used an ensemble model approach to project distributions of 14 species. For each species, current range projections were compared to 27 scenario-based projections and aggregated to visualize uncertainty. Multiple regression and model selection techniques were used to identify drivers of range change. Novel, or no-analogue, climates were assessed to evaluate transferability of models. Changes in total probability of occurrence ranged widely across species, from a 63% increase to a 65% decrease. Distributional gains and losses were largely driven by temperature and flow variables and underscore the importance of habitat heterogeneity and connectivity to facilitate adaptation to changing conditions. Finally, novel climate conditions were driven by mean annual maximum temperature, which stresses the importance of understanding the role of temperature on fish physiology and the role of temperature-mitigating management practices.

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The effect of climate change on rural land cover patterns in the Central United States

Cited by 21 publications

References 44 publications

Modelling predicts that soybean is poised to dominate crop production across Africa

Modelling predicts that soybean is poised to dominate crop production across Africa

Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change

Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change

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