Land use change ranges in each panel are in acres per thousand county acres. The white colored counties represent missing yields for at least one crop in all years.
2006 Land Use in the Dakotas (Cropland Data Layer, USDA NASS). The color legend represents various land use types in the region.
Historical (1981-2005) vs. Projected (2031-’55) Yields. Each year’s crop yields are calculated as an average of all counties in North and South Dakota. Hashed representations of projected yields are from RCP 4.5 emissions scenario from seven GCMs, namely CESM (Community Earth System Model), CNRM (Center National de Recherches Météorologiques (France)), GFDL (Geophysical Fluid Dynamics Laboratory), GISS (Goddard Institute of Space Studies), HADGEM (Hadley Global Environment Model), IPSL (Institut Pierre-Simon Laplace (France)) and MIROC (Model for Interdisciplinary Research on Climate). Median projection in a given year is calculated by taking the median yield value of the yield projections from each of seven climate model outputs in each county and then taking the average across counties. We restrict spring wheat and alfalfa yield forecasts to zero for years in which these are projected to be negative values.
Abstract (from IOP Science): Global agriculture is challenged to increase soil carbon sequestration and reduce greenhouse gas emissions while providing products for an increasing population. Growing crop production could be achieved through higher yield per hectare (i.e. intensive farming) or more hectares (extensive farming), which however, have different ecological and environmental consequences. Multiple lines of evidence indicate that expanding cropland for additional production may lead to loss of vegetation and soil carbon, and threaten the survival of wildlife. New concerns about the impacts of extensive farming have been raised for the US Corn Belt, one of the world's most productive regions, as cropland has rapidly expanded northwestward unto grasslands and wetlands in recent years. Here we used a process-based ecosystem model to distinguish and quantify how natural drivers as well as intensive and extensive farming practices have altered grain production, soil carbon storage, and agricultural carbon footprint in the US Western Corn Belt since 1980. Compared to the period 1980–2005, we found that cropland expansion more than tripled in the most recent decade (2006–2016), becoming a significant factor contributing to growing grain production. Land use change in this period led to a soil carbon loss of 90.8 ± 14.7 Tg (1 Tg = 1012 g). As a result, grain production in this region shifted from carbon neutral to a carbon loss of 2.3 kg C kg−1 grain produced. The enlarging negative carbon footprint (ΔC/ΔP) indicates the major role that cropland expansion has had on the carbon cost of grain production in this region. Therefore, we should be more cautious to pursue high crop production through agricultural cropland conversion, particularly in those carbon-rich soils.
Drought is a complex environmental hazard that impacts both ecological and social systems. Accounting for the role of human attitudes, institutions, and societal values in drought planning is important to help identify how various drought durations and severity may differentially affect social resilience to adequately respond to and manage drought impacts. While there have been successful past efforts to understand how individuals, communities, institutions, and agencies plan for and respond to drought, these studies have relied on extensive multi-year case studies in specific locations. In contrast, this project seeks to determine how social science insights and methods can best contribute to ecological drought preparedness and resilience in situations where extensive field study is not feasible. Specifically, the project team will investigate what a rapid social assessment method might look like in the context of ecological drought, how it may be applied, and what benefits it may contribute to drought preparedness and resilience. This method would allow researchers to expeditiously identify and analyze relevant characteristics of the social system that have bearing on the problem of ecological drought and allow water and resource managers, community leaders, and others involved with drought preparedness and response to quickly identify, assess, and measure important social factors that influence the effects of drought to ecosystems. This project will include analyzing currently available rapid assessment methods from other topical areas (including ecological, rural, hazards, etc.) to inform the method to be developed by providing relevant design criteria. A prototype version of the method will be developed and pilot tested with the identified audience to determine effectiveness and strengths and weaknesses. Finally, the method will be refined and made available more widely to Department of Interior resource managers.
Historical and projected suitable habitat of 14 tree and shrub species a under CCSM4 GCMs from 2000 to 2099 was predicted to assess projected climate change impacts in forest communities of North Central U.S. We obtained presence/absence record of each species from Forest Inventory and Analysis (FIA) data. required ata. Historical tme period ranges from 1971 to 2000, and projected time period ranges from 2071 to 2100. Random Forest was used to project historical and future suitable habitat of all species across West U.S. using the Biomod2 software programmed in R environment. We adopted a climate change scenarios generated from the experiments conducted under fifth assessment of Coupled Model Intercomparison Project (CMIP5) for the Intergovernmental Panel on Climate Change. Selected climate change scenarios include high representative concentrative pathway (RCP8.5).
Landscape Evaporative Response Index (LERI) is remotely-sensed high-resolution information of the evaporative response from the land in near real time. LERI assesses anomalies in actual evapotranspiration (ETa), as percentiles, across the Contiguous US and northern Mexico at a 1-km spatial resolution. LERI is based on the ETa data produced by the U. S. Geological Survey using the operational Simplified Surface Energy Balance (SSEBop) model. SSEBop combines evapotranspiration fraction generated from remotely sensed MODIS thermal imagery, acquired every 8 days, with climatological atmospheric evaporative demand. To quantify LERI, a rank-based, non-parametric method is used to estimate percentiles of the SSEBop ETa, over a period of ETa accumulation, compared to the available period of record (January 2000 to present). LERI percentiles are also binned into four drought categories (LD0 - LD3) analogous to the US Drought Monitor (USDM) categories (i.e. D0-D3) and using the same percentile breaks that USDM considers for soil moisture. By its numerical design, LERI essentially represents the evaporative response of the landscape driven primarily by the anomalous state of soil moisture to meet the climatological atmospheric demand through a combination of evaporation (from soil and leaf surfaces) and transpiration (root-stomata-air) processes. Real-time and high-resolution assessment of this soil moisture state is extremely salient to understanding and forecasting ecological responses. LERI serves as an experimental drought-monitoring and early warning guidance tool and has the potential to inform research into understanding characteristics of Ecological Drought. Preliminary work finds LERI to closely track modeled moisture conditions in the upper soil layers (~10 cm). LERI can complement other drought-monitoring indices and modeled soil moisture products. Work is ongoing to assess LERI’s ability to capture signals of drought early warning, and its unique ability to assess land-surface moisture state. LERI maps, and spatial and historical time series data could be accessed at https://www.esrl.noaa.gov/psd/leri/.
Southwestern Colorado is already experiencing the effects of climate change in the form of larger and more severe wildfires, prolonged severe droughts, tree mortality from insect outbreaks, and earlier snowmelt. Climate scientists expect the region to experience more frequent summer heat waves, longer-lasting and more frequent droughts, and decreased river flow in the future (Lukas et al. 2014). These changes will ultimately impact local communities and challenge natural resource managers in allocating water and range for livestock grazing under unpredictable drought conditions, managing forests in the face of changing fire regimes, and managing threatened species under shifting ecological conditions. Considering the wide-ranging potential impacts of climate change in the region, the goal of this project was to collaborate with decision-makers to develop strategies to reduce those impacts on people and nature. Scientists, land managers, and local communities worked together to identify actions to reduce the negative effects of climate change. Known as “adaptation strategies,” these actions are expected to facilitate effective planning and management under shifting climate conditions. To inform strategy development, researchers and planners provided information on the vulnerability of ecosystems, modeled plausible future climate conditions, and identified the social contexts in which adaptation decisions are made. The project focused on the San Juan River Basin and Upper Gunnison River Basin of southwestern Colorado, though one of the objectives of the project was to develop an adaptation toolkit that can be applied to other landscapes. By identifying appropriate adaptation strategies and actions, this project will help improve the resilience of local communities and ecosystems elsewhere in the face of an uncertain future.
USGS researchers from the North Central CASC and the Northern Prairie Wildlife Research Center recently collaborated with the National Park Service Climate Change Response Program to develop a new product that communicates the results from a collaborative effort—involving resource managers, subject-matter experts, and a larger climate change adaptation team—to identify potential climate impacts and management responses in Badlands National Park. The researchers used scenario planning and ecological simulation modeling to anticipate management challenges and identify options for Badlands National Park and adjacent federal and tribal lands in the coming decades (through 2050). The ecological simulation models help track complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond under different scenarios. Insights from this collaborative effort will help inform resource managers who are tasked with prioritizing investments that better position the park to meet the challenges posed by climate change.