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USGS2018

Southeast

The Southeast includes vast expanses of coastal and inland low-lying areas, the southern portion of the Appalachian Mountains, numerous high-growth metropolitan areas, and large rural expanses. These beaches and bayous, fields and forests, and cities and small towns are all at risk from a changing climate. While some climate change impacts, such as sea level rise and extreme downpours, are being acutely felt now, others, like increasing exposure to dangerous high temperatures, humidity, and new local diseases, are expected to become more significant in the coming decades. While all regional residents and communities are potentially at risk for some impacts, some communities or populations are at greater risk due to their locations, services available to them, and economic situations. Observed warming since the mid-20th century has been uneven in the Southeast region, with average daily minimum temperatures increasing three times faster than average daily maximum temperatures. The number of extreme rainfall events is increasing. Climate model simulations of future conditions project increases in both temperature and extreme precipitation. Trends towards a more urbanized and denser Southeast are expected to continue, creating new climate vulnerabilities. Cities across the Southeast are experiencing more and longer summer heat waves. Vector-borne diseases pose a greater risk in cities than in rural areas because of higher population densities and other human factors, and the major urban centers in the Southeast are already impacted by poor air quality during warmer months. Increasing precipitation and extreme weather events will likely impact roads, freight rail, and passenger rail, which will likely have cascading effects across the region. Infrastructure related to drinking water and wastewater treatment also has the potential to be compromised by climate-related events. Increases in extreme rainfall events and high tide coastal floods due to future climate change will impact the quality of life of permanent residents as well as tourists visiting the low-lying and coastal regions of the Southeast. Sea level rise is contributing to increased coastal flooding in the Southeast, and high tide flooding already poses daily risks to businesses, neighborhoods, infrastructure, transportation, and ecosystems in the region. There have been numerous instances of intense rainfall events that have had devastating impacts on inland communities in recent years. The ecological resources that people depend on for livelihoods, protection, and well-being are increasingly at risk from the impacts of climate change. Sea level rise will result in the rapid conversion of coastal, terrestrial, and freshwater ecosystems to tidal saline habitats. Reductions in the frequency and intensity of cold winter temperature extremes are already allowing tropical and subtropical species to move northward and replace more temperate species. Warmer winter temperatures are also expected to facilitate the northward movement of problematic invasive species, which could transform natural systems north of their current distribution. In the future, rising temperatures and increases in the duration and intensity of drought are expected to increase wildfire occurrence and also reduce the effectiveness of prescribed fire practices. Many in rural communities are maintaining connections to traditional livelihoods and relying on natural resources that are inherently vulnerable to climate changes. Climate trends and possible climate futures show patterns that are already impacting—and are projected to further impact—rural sectors, from agriculture and forestry to human health and labor productivity. Future temperature increases are projected to pose challenges to human health. Increases in temperatures, water stress , freeze-free days, drought, and wildfire risks, together with changing conditions for invasive species and the movement of diseases, create a number of potential risks for existing agricultural systems. Rural communities tend to be more vulnerable to these changes due to factors such as demography, occupations, earnings, literacy, and poverty incidence. In fact, a recent economic study using a higher scenario (RCP8.5) suggests that the southern and midwestern populations are likely to suffer the largest losses from future climate changes in the United States. Climate change tends to compound existing vulnerabilities and exacerbate existing inequities. Already poor regions, including those found in the Southeast, are expected to continue incurring greater losses than elsewhere in the United States.

Report↗

USGS2018

The Pothole Hydrology-Linked Systems Simulator (PHyLiSS)—Development and application of a systems model for prairie-pothole wetlands

The North American Prairie Pothole Region covers about 770,000 square kilometers of the United States and Canada (including parts of 5 States and 3 provinces: North Dakota, South Dakota, Montana, Minnesota, Iowa, Saskatchewan, Manitoba, and Alberta). The Laurentide Ice Sheet shaped the landscape of the region about 12,000 to 14,000 years ago. The retreat of the ice sheet left behind low-permeability glacial till and a landscape dotted with millions of depressions known today as prairie potholes. The wetlands that subsequently formed in these depressions, prairie-pothole wetlands, provide critical migratory-bird habitat and support dynamic aquatic communities. Extensive grasslands and productive agricultural systems surround these wetland ecosystems. In prairie-pothole wetlands, the compositions of plant, invertebrate, and vertebrate communities are highly dependent on hydrogeochemical conditions. Regional climate shifts between wet and dry periods affect the length of time that wetlands contain ponded surface water and the chemistry of that ponded water. Land-use change can exacerbate or reduce the effects of climate on wetland hydrology and water chemistry. A mechanistic understanding of the relation among climate, land use, hydrology, chemistry, and biota in prairie-pothole wetlands is needed to better understand the complex, and often interacting, effects of climate and land use on prairie-pothole wetland systems and to facilitate climate and land-use change adaptation efforts. The Pothole Hydrology-Linked Systems Simulator (PHyLiSS) model was developed to address this need. The model simulates water-surface elevation dynamics in prairie-pothole wetlands and quantifies changes in salinity. The PHyLiSS model is unique among other wetland models because it accommodates differing sizes and morphometries of wetland basins, is not dependent on a priori designations of wetland class, and allows for functional changes associated with dynamic shifts in ecohydrological states. The PHyLiSS model also has the capability to simulate wetland salinity, and potential future iterations will also simulate the effects of changing hydrology and geochemical conditions on biota. This report documents the development of the hydrological and geochemical components of the PHyLiSS model and provides example applications.

Open-File Report↗

USGS2022

Exploring the role of cryptic nitrogen fixers in terrestrial ecosystems: A frontier in nitrogen cycling research

Biological nitrogen fixation represents the largest natural flux of new nitrogen (N) into terrestrial ecosystems, providing a critical N source to support net primary productivity of both natural and agricultural systems. When they are common, symbiotic associations between plants and bacteria can add more than 100 kg N ha −1 y −1 to ecosystems. Yet, these associations are uncommon in many terrestrial ecosystems. In most cases, N inputs derive from more cryptic sources, including mutualistic and/or free-living microorganisms in soil, plant litter, decomposing roots and wood, lichens, insects, and mosses, among others. Unfortunately, large gaps remain in the understanding of cryptic N fixation. We conducted a literature review to explore rates, patterns, and controls of cryptic N fixation in both unmanaged and agricultural ecosystems. Our analysis indicates that, as is common with N fixation, rates are highly variable across most cryptic niches, with N inputs in any particular cryptic niche ranging from near zero to more than 20 kg ha −1 y −1 . Such large variation underscores the need for more comprehensive measurements of N fixation by organisms not in symbiotic relationships with vascular plants in terrestrial ecosystems, as well as identifying the factors that govern cryptic N fixation rates. We highlight several challenges, opportunities, and priorities in this important research area, and we propose a conceptual model that posits an interacting hierarchy of biophysical and biogeochemical controls over N fixation that should generate valuable new hypotheses and research.

Ecosystems↗

USGS2021

Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area

Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVI MccL and EVI2 MccL ) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.

Remote Sensing↗

USGS2018

Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA

Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential ( ψ T ) time series) and chemical tracer and dating ( 3 H, Cl − , Br − , CFCs, SF 6 , and 3 H/ 3 He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.

Northern High Plains Aquifer↗

USGS2025

Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops

Winter cover crops reduce erosion and nutrient runoff from agricultural systems. Although cereal cover crops can decrease field nitrate leaching by 50%–95%, the magnitude of this reduction varies within and between fields, making it challenging to monitor the impact of cover crops on nitrate leaching at large spatial extents. Satellite remote sensing using red-edge bands has been shown to effectively estimate crop nitrogen (N) content (kg ha −1 ) in later growth-stage crops with a closed canopy. In this study, we evaluated 15 spectral indices derived from Sentinel-2 imagery to estimate N concentration (%) and content (kg ha −1 ) of cereal cover crops, using 1627 destructive samples collected from 2018 to 2023 in Maryland. Observed N content ranged from 0.1 to 214.7 kg ha −1 , while N concentration ranged from 0.6% to 5.5%. The 15 indices considered were poor predictors of N concentration (adj. R 2 = 0.089, root mean squared error [RMSE] = 0.802%), but were more successful at measuring N content (biomass × N concentration). Delta red-edge (ΔRE) was the best predictor of N content (adj. R 2 = 0.748, RMSE = 13.10 kg ha −1 from cross-validation with 80% train and 20% test splits iterated 100 times) using samples with imagery collected within ±4 days of destructive sampling ( n = 1110). Our findings indicate that longer red-edge wavelengths (783 and 740 nm) are more suited for estimating N content in cereal cover crops compared to shorter red-edge wavelengths, which have been shown to be more sensitive to biomass. Leave-one-year-out cross-validation demonstrated that the relationship between ΔRE and N content was robust across all four cover crop sampling years included in the study (adj. R 2 = 0.700–0.769, RMSE = 10.70–15.40 kg ha −1 ). Regression model performance improved with the addition of multiple predictors, including biomass (estimated from Normalized Difference Vegetation Index), weather variables (adj. R 2 = 0.765, RMSE = 12.37 kg ha −1 ), management variables (species, season, adj. R 2 = 0.772, and RMSE = 12.13 kg ha −1 ), and biophysical variables (height, fractional ground cover, adj. R 2 = 0.818, and RMSE = 10.29 kg ha −1 ). These findings demonstrate the feasibility of quantifying N content in cereal cover crops using a red-edge-based spectral index across large geographic extents and indicate the inclusion of additional predictors, such as weather and management data, improves model accuracy. This work has implications for quantifying reductions in N leaching associated with cover crops, aiding in policymaking and evaluation of conservation programs that impact water bodies such as Chesapeake Bay.

Maryland↗

USGS2014

Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States

BACKGROUND Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty. RESULTS The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55–90% at NE and by 28–96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty. RESULTS: The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55–90% at NE and by 28–96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration. CONCLUSIONS: Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.

Maryl;Nebraska↗

USGS2014

Avian response to conservation buffers in agricultural landscapes during winter

Native herbaceous vegetation cover along row‐crop field edges (i.e., field buffers) increases breeding densities of many bird species. However, the effect of field buffers on bird species during the non‐breeding season is less understood. We compared density, avian richness, and avian conservation value on row‐crop fields containing buffers strategically designed for wildlife versus fields without buffers in 3 southeastern U.S. states during winter 2007 and 2008. Fields with buffers were enrolled in U.S. Department of Agriculture, Conservation Reserve Program practice Habitat Buffers for Upland Birds (CP33), which targets restoration of northern bobwhite ( Colinus virginianus ) and other upland bird species. Overall species richness did not differ on fields with buffers versus fields without buffers in 2007, but was 29% greater on fields with buffers in 2008. Swamp sparrows ( Melospiza georgiana ), song sparrows ( M. melodia ), field sparrows ( Spizella pusilla ), and red‐bellied woodpeckers ( Melanerpes carolinus ) had greater densities on fields with buffers compared with fields without buffers. Increasing field‐buffer width did not result in greater bird densities. Our results suggest a small change in primary land use (≈7%) produced a disproportionate population response by some grassland‐dependent and woodland bird species during winter. Because field buffers provide a direct source of winter food and cover resources, they may be a pragmatic means to provide critical non‐breeding habitat with little alteration of existing agricultural systems.

Arkansas, Kentucky, Mississippi↗

USGS2019

Typha (cattail) invasion in North American wetlands: Biology, regional problems, impacts, ecosystem services, and management

Typha is an iconic wetland plant found worldwide. Hybridization and anthropogenic disturbances have resulted in large increases in Typha abundance in wetland ecosystems throughout North America at a cost to native floral and faunal biodiversity. As demonstrated by three regional case studies, Typha is capable of rapidly colonizing habitats and forming monodominant vegetation stands due to traits such as robust size, rapid growth rate, and rhizomatic expansion. Increased nutrient inputs into wetlands and altered hydrologic regimes are among the principal anthropogenic drivers of Typha invasion. Typha is associated with a wide range of negative ecological impacts to wetland and agricultural systems, but also is linked with a variety of ecosystem services such as bioremediation and provisioning of biomass, as well as an assortment of traditional cultural uses. Numerous physical, chemical, and hydrologic control methods are used to manage invasive Typha, but results are inconsistent and multiple methods and repeated treatments often are required. While this review focuses on invasive Typha in North America, the literature cited comes from research on Typha and other invasive species from around the world. As such, many of the underlying concepts in this review are relevant to invasive species in other wetland ecosystems worldwide.

Wetlands↗

USGS2022

Estimating bee abundance: Can mark-recapture methods validate common sampling protocols?

Wild bees are essential pollinators in natural and agricultural systems, but populations of some species have declined. Efforts to assess the status of wild bees are hindered by uncertainty in common sampling methods, such as pan traps and aerial netting, which may or may not provide a valid index of abundance across species and habitats. Mark-recapture methods are a common and effective means of estimating population size, widely used in vertebrates but rarely applied to bees. Here we review existing mark-recapture studies of wild bees and present a new case study comparing mark-recapture population estimates to pan trap and net capture for four taxa in a wild bee community. Net, but not trap, capture was correlated with abundance estimates across sites and taxa. Logistical limitations ensure that mark-recapture studies will not fully replace other bee sampling methods, but they do provide a feasible way to monitor selected species and measure the performance of other sampling methods.

Apidologie↗

USGS2016

Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds

Precipitation patterns and nutrient inputs affect transport of nitrate (NO 3 -N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996–2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO 3 -N than the LCR watershed (31.2 versus 21.3 kg NO 3 -N ha − 1 y − 1 ). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51 kg TP ha − 1 yr − 1 ), despite greater TP concentrations in the LCR. About 65% of NO 3 -N and 50% of TP loads were transported during April–June, and < 20% of the annual loads were transported later in the growing season from July–September. Monthly NO 3 -N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO 3 -N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO 3 -N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.

Science of the Total Environment↗

USGS2025

Multiyear crop residue cover mapping using narrow-band vs. broad-band shortwave infrared satellite imagery

Crop residue serves an important role in agricultural systems as high levels of fractional crop residue cover ( f R ) can reduce erosion, preserve soil moisture, and build soil organic carbon. However, the ability to accurately quantify f R at scale has been limited. In this study we produced annual maps of f R for farmland in Maryland, USA using WorldView-3 (WV3) imagery paired with on-farm photographs ( n = 895) classified to f R using SamplePoint software. Univariate linear regressions were used to compare photograph f R to WV3 crop residue indices including: 1) Shortwave Infrared Normalized Difference Residue Index (SINDRI), 2) Shortwave Infrared Difference Residue Index (SIDRI), 3) Normalized Difference Tillage Index (NDTI), and 4) Shortwave Infrared Angle Index (SWIRA). SINDRI and SIDRI are based on narrow bands capable of measuring lignocellulose absorption features. NDTI and SWIRA are based on Landsat-comparable broad bands. Our findings demonstrated that SINDRI outperformed other indices in f R estimation in terms of coefficient of determination ( R 2 = 0.869) and root mean square error (RMSE = 0.111), when R 2 and RMSE were averaged across six individual years. For a univariate analysis combining five years of high-quality WV3 imagery, SINDRI again exhibited the highest f R estimation performance ( R 2 = 0.795; RMSE = 0.141), suggesting that SINDRI can map f R accurately with a singular relationship, potentially reducing the need for labor-intensive ground data collection. For broad-band indices, a multiple linear regression analysis that included a Water Index (WI) and Normalized Difference Vegetation Index (NDVI) as additional predictors increased the accuracy of f R estimation significantly, particularly for SWIRA ( R 2 = 0.767; RMSE = 0.144), but also NDTI ( R 2 = 0.654; RMSE = 0.174). Our findings suggest that while indices computed from narrow-band imagery are most accurate for f R estimation, SWIRA has the potential to improve f R estimation compared to NDTI, especially when used in conjunction with WI and NDVI. An index suite of SWIRA, WI, and NDVI can be computed with Landsat 4–9 imagery, providing a more accurate record of global f R dating back to 1982.

Soil and Tillage Research↗

USGS2001

Processes controlling the episodic streamwater transport of atrazine and other agrichemicals in an agricultural watershed

Episodic streamwater transport of atrazine (a common agricultural herbicide) and nutrients has been observed throughout agricultural watersheds in the United States and poses a serious threat to the quality of its water resources. Catchment-scale atrazine and nutrient transport processes after agricultural application are still poorly understood, and predicting episodic streamwater composition remains an elusive goal. We instrumented a 1.2-km 2 agricultural catchment near Harrisonburg, Virginia, and examined streamwater, overland flow, soil water, groundwater, and rainfall during the summer of 1998. Storm chemographs demonstrated different patterns for constituents derived primarily from weathering (silica and calcium), compared to constituents derived primarily from early spring land applications (nitrate, atrazine, DOC, potassium, chloride, and sulfate). During storms, the concentrations of silica and calcium decreased, the atrazine response was variable, and the concentrations of nitrate, DOC, potassium, chloride, and sulfate increased; the elevated nitrate signal lagged several hours behind the other elevated constituents. Graphical and statistical analyses indicated a relatively stable spring-fed baseflow was modified by a mixture of overland flow and soil water. A rapid, short-duration overland-flow pulse dominated the streamflow early in the event and contributed most of the potassium, DOC, chloride, suspended sediment, and atrazine. A longer-duration soil–water pulse dominated the streamflow later in the event and contributed the nitrate as well as additional potassium, DOC, sulfate, and atrazine. The contributions to the episodic streamflow were quantified using a flushing model in which overland-flow and soil–water concentrations decreased exponentially with time during an episode. Flushing time constants for the overland-flow and soil–water reservoirs were calculated on a storm-by-storm basis using separate tracers for each time-variable reservoir. Initial component concentrations were estimated through regression analyses. Mass-balance calculations were used for flow separations and to predict the observed streamwater composition. Model forecasts indicated that reduced fertilizer and pesticide application (rather than elimination of overland-flow or soil–water contributions) was necessary to improve the episodic streamwater composition. This study provides important additional understanding of the catchment-scale processes by which land-applied pesticides and nutrients can move through agricultural systems.

Virginia↗

USGS2021

A comprehensive statewide spatiotemporal stream assessment of per- and polyfluoroalkyl substances (PFAS) in an agricultural region of the United States

Public concern regarding per- and polyfluoroalkyl substances (PFAS) has grown substantially in recent years. In addition, research has documented multiple potential agriculture-related release pathways for PFAS (e.g., biosolids and livestock manure). Nevertheless, little research on the environmental prevalence of PFAS has been conducted in agricultural regions of the United States. To fill this gap, we conducted the first statewide spatiotemporal assessment of PFAS in Iowa streams across a region of intense agricultural activity. At least one PFAS was detected at 19 of the 60 stream sites sampled (32%) with 10 different PFAS detected statewide. The number of PFAS detected in the stream samples ranged from one to nine. While PFAS were detected in agricultural streams, sites with the most PFAS detected and in the highest concentration were small, effluent-affected streams where wastewater treatment plant discharge is driving stream PFAS concentrations. No individual PFAS had an exposure:activity ratio (EAR) of >1.0 (exposure concentration shown to trigger observed adverse biological activity). Five stream locations, however, had at least one EAR of >0.001, a precautionary effect screening threshold. Additional targeted temporal sampling would be beneficial to specifically capture potential agricultural source applications and corresponding runoff conditions to fully characterize the prevalence of PFAS in such agricultural systems.

Iowa↗

USGS2021

Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff

Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern Nevada/northern California, United States to evaluate the impacts of climate change on snow-fed agricultural systems that use surface water and groundwater conjunctively. We explicitly represent individual surface water rights within the hydrologic model and allow the integrated code to change river diversions in response to earlier snowmelt runoff and water availability. Historically under-used supplemental groundwater rights are dynamically activated within the model to offset diminished surface water deliveries. The model accounts for feedbacks between the natural hydrology and anthropogenic stresses, which is a first-of-its-kind assessment of the impacts of climate change on individual water rights, and more broadly on river basin operations. Earlier snowmelt decreases annual surface water deliveries to all water rights, not just the junior water rights, owing to a lack of surface water storage in the upper river basin capable of capturing earlier runoff. Conversely, downstream irrigators with access to reservoir storage benefit from earlier runoff flowing past upstream points of diversion prior to the start of the irrigation season. Despite regional shifts toward greater reliance on groundwater for irrigation, crop consumption (a common surrogate for crop yield) decreases due to spatiotemporal changes in water supply that preferentially impact a subset of growers in the region.

California↗

USGS2009

Seasonal movements and home ranges of white-tailed deer in north-central South Dakota

Knowledge of movement patterns of white-tailed deer ( Odocoileus virginianus (Zimmermann, 1780)) inhabiting landscapes intensively modified by agricultural systems is important to the present and future understanding of deer ecology. Little information exists regarding daily and seasonal movements of white-tailed deer in north-central South Dakota. Therefore, our goal was to determine movement patterns and home-range use of female white-tailed deer in north-central South Dakota. From January 2005 to January 2007, 29 adult (>18 months) and 13 yearling (8–18 months) white-tailed deer were monitored for movement using radiotelemetry. We collected 2822 locations, calculated 76 home ranges, and documented 50 seasonal movements. Mean migration distance between summer and winter home ranges was 19.4 km (SE = 2.0 km). Mean 95% home-range size was 10.2 km 2 (SE = 1.2 km 2 , n = 27) during winter and 9.2 km 2 (SE = 1.0 km 2 , n = 49) during summer. Ambient temperature appeared to be a primary cause of seasonal migration. Additionally, movements exhibited by white-tailed deer in north-central South Dakota were influenced by a highly fragmented landscape dominated by row crops and pasture or grassland.

South Dakota↗

USGS2014

Assessing landscape constraints on species abundance: Does the neighborhood limit species response to local habitat conservation programs?

Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants.

Nebraska↗

USGS2000

An assessment of irrigation needs and crop yield for the United States under potential climate changes

Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.

Open-File Report↗