Predicted Suitable Habitat Declines for Midwestern United States Amphibians Under Future Climate and Land-Use Change Scenarios

With current declines of vertebrate taxa meeting or exceeding those of historic mass extinction events, there is a growing need to investigate the main drivers of losses. Two of the main drivers of declines are global climate and land-use changes, both affecting multiple groups of taxa. Amphibians are at great risk from these two drivers of change and investigations into the impact of future change could assist with the formation of conservation plans to mitigate losses. Forecasting changes in suitable habitat with ecological niche modeling serves as a useful tool to begin to understand how species may respond to anthropogenic change. We used Maxent to model suitable habitat space of 33 amphibian species within the Midwestern U.S. under multiple future climate change scenarios and used current and predicted changes in land-use to examine the predicted impact of global climate and land-use change. We predicted reductions in suitable habitat for a high proportion of species in all model scenarios, while few species were predicted to gain suitable habitat. No significant differences in percentage change in habitat space were determined between models predicting suitable habitat solely using climate change scenarios or model output that incorporated the impact of land-use change. Species richness of amphibians is predicted to decrease based on future climate and climate + land-use scenarios. In the future, we encourage continuation of the examination of land-use and other global stressors, and further investigations into physiological tolerances of amphibian species to create more robust predictions

Using Remote Sensing and Biogeographic Modeling to Understand the Oak Savannas of the Sheyenne National Grassland, North Dakota, USA

Oak savannas are valuable and complex ecosystems that provide multiple ecosystem goods and services, including grazing for livestock, watershed regulation, and recreation. These ecosystems of the woodland-prairie ecoregion of the Midwestern United States are, however, in danger of disappearing. The Sheyenne National Grassland, North Dakota, a protected Prairie grassland-savanna, is a representative of such rare habitats, where oak savanna is found at the landscape scale. In this research, I map the distribution patterns of oak savanna in the Sheyenne using a combination of remote sensing and geospatial datasets, including landscape topography, soils, and fire disturbance. Further, I interpret the performance of a suite of advanced Species Distribution Modeling approaches including Maximum Entropy, Random Forest, Generalized Boosted Model, and Classification Tree to analyze the primary environmental and management factors influencing oak distributions at landscape scales. Woody canopy cover was estimated with high classification accuracy (80-95%) for two study areas of the Sheyenne National Grassland. Among the four species distribution modeling approaches tested, the Random Forest (RF) approach provided the best predictive model. RF model parameters indicate that oak trees favor gently sloping locations, on well-drained upland and sandy soils, with north-facing aspect. While no direct data on water relationships were possible in this research, the importance of the topographic and soil variables in the SDM presumably reflect oak preference for locations and soils that are not prone to water saturation, with milder summer temperatures (i.e. northern aspects), providing conditions suitable for seedling establishment and growth. This research increases our understanding of the biogeography of Midwestern tall-grass oak savannas and provides a decision-support tool for oak savanna management

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model

Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and Grasslands (NFs) in the United States. However, few reliable continental-scale modeling tools are available to account for both water and carbon dynamics. The objective of this study was to test a monthly water and carbon balance model, the Water Supply Stress Index (WaSSI) model, for potential application in addressing the influences of drought on NFs ecosystem services across the conterminous United States (CONUS). The performance of the WaSSI model was comprehensively assessed with measured streamflow (Q) at 72 U.S. Geological Survey (USGS) gauging stations, and satellite-based estimates of watershed evapotranspiration (ET) and gross primary productivity (GPP) for 170 National Forest and Grassland (NFs). Across the 72 USGS watersheds, the WaSSI model generally captured the spatial variability of multi-year mean annual and monthly Q and annual ET as evaluated by Correlation Coefficient (R = 0.71–1.0), Nash–Sutcliffe Efficiency (NS = 0.31–1.00), and normalized Root Mean Squared Error (0.06–0.48). The modeled ET and GPP by WaSSI agreed well with the remote sensing-based estimates for multi-year annual and monthly means for all the NFs. However, there were systemic discrepancies in GPP between our simulations and the satellite-based estimates on a yearly and monthly scale, suggesting uncertainties in GPP estimates in all methods (i.e., remote sensing and modeling). Overall, our assessments suggested that the WaSSI model had the capability to reconstruct the long-term forest watershed water and carbon balances at a broad scale. This model evaluation study provides a foundation for model applications in understanding the impacts of climate change and variability (e.g., droughts) on NFs ecosystem service functions

Impacts of Land Use and Climate Changes on Hydrological Processes in South Dakota Watersheds

This study aims to evaluate the impacts of climate and land use change on the hydrology of South Dakota’s watersheds using the Soil and Water Assessment Tool (SWAT). The study analyzed the hydrologic impacts of climate and land use changes in two ways. The first aspect consists of characterizing hydrological changes between two recent decades in three representative watersheds – Bad River watershed, Skunk Creek watershed and Upper Big Sioux River watershed. Two historical land use maps (NLCD 1992 and 2011) were used to represent land use change on these watersheds, and two historical climate datasets (1981-1990 and 2005-2014) were used to create SWAT models for each watershed. Results showed that due to historical land use and climate variations the annual water balance components mostly increased in the 2000s compared to 1980s. Between the 1980s and 2000s, seasonal variation in hydrology mostly increased during the wet season (i.e., May to October) in all three watersheds. Spatial analysis revealed that the hydrological components increased with a decrease in grassland in the watersheds, except in Skunk Creek watershed. The second aspect was to quantify the influence of future climate and land use changes on hydrological processes in the James River Watershed located in South and North Dakotas. A set of 42 scenarios of future projected land use and climate changes were developed under three emission scenarios (A1B, A2 and B1) to represent mid (2046-2065) and end (2080-2099) of the 21st century. Corresponding land use maps (2055 and 2090) were derived from the FOREcasting SCEnarios (FORE-SCE) model to represent land use conditions for mid and end of the century. Projected climate data were used from three general circulation models (CGCM3.1, GFDL-CM2.1, and HADCM3) for the mid-century (2046-2065) and end of the century (2080-2099). The scenarios were designed in a way that (1) land use was changed while climate conditions remained constant, (2) land use remained constant under a changing climate, and (3) both land use and climate were changed simultaneously. Results showed that future climate change will likely have more influence on hydrology compared to future land use change. The combined effects of land use and climate changes would intensify changes in hydrological processes of the region in the near future

Investigation of climate variability and climate change impacts on corn yield in the Eastern Corn Belt, USA

The increasing demand for both food and biofuels requires more corn production at global scale. However, current corn yield is not able to meet bio-ethanol demand without jeopardizing food security or intensifying and expanding corn cultivation. An alternative solution is to utilize cellulose and hemi-cellulose from perennial grasses to fulfill the increasing demand for biofuel energy. A watershed level scenario analysis is often applied to figure out a sustainable way to strike the balance between food and fuel demands, and maintain environment integrity. However, a solid modeling application requires a clear understanding of crop responses under various climate stresses. This is especially important for evaluating future climate impacts. Therefore, correct representation of corn growth and yield projection under various climate conditions (limited or oversupplied water) is essential for quantifying the relative benefits of alternative biofuel crops. The main objective of this study is to improve the evaluation of climate variability and climate change effects on corn growth based on plant-water interaction in the Midwestern US via a modeling approach. Traditional crop modeling methods with the Soil and Water Assessment Tool (SWAT) are improved from many points, including introducing stress parameters under limited or oversupplied water conditions, improving seasonal crop growth simulation from imagery-based LAI information, and integrating CO2 effects on crop growth and crop-water relations. The SWAT model’s ability to represent crop responses under various climate conditions are evaluated at both plot scale, where observed soil moisture data is available and watershed scale, where direct soil moisture evaluation is not feasible. My results indicate that soil moisture evaluation is important in constraining crop water availability and thus better simulates crop responses to climate variability. Over a long term period, drought stress (limited moisture) explains the majority of yield reduction across all return periods at regional scale. Aeration stress (oversupplied water) results in higher yield decline over smaller spatial areas. Future climate change introduces more variability in drought and aeration stress, resulting in yield reduction, which cannot be compensated by positive effects brought by CO2 enhancement on crop growth. Information conveyed from this study can also provide valuable suggestions to local stakeholders for developing better watershed management plans. It helps to accurately identify climate sensitive cropland inside a watershed, which could be potential places for more climate resilient plants, like biofuel crops. This is a sustainable strategy to maintain both food/fuel provision, and mitigate the negative impact of future climate change on cash crops

Predicting Chronic Fine and Coarse Particulate Exposures Using Spatiotemporal Models for the Northeastern and Midwestern United States

Background: Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 μm; PM2.5) and coarse particles (PM with aerodynamic diameter 2.5–10 μm; PM10–2.5), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM2.5 and PM10–2.5 concentrations for the northeastern and midwestern United States. Methods: For PM2.5, we developed models for two periods: 1988–1998 and 1999–2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM10 (PM with aerodynamic diameter < 10 μm) and extinction coefficients (km−1). PM10–2.5 levels were estimated as the difference in monthly predicted PM10 and PM2.5, with predicted PM10 from our previously developed PM10 model. Results: Predictive performance for PM2.5 was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM2.5 models, respectively) with high precision (2.2 and 2.7 μg/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM10–2.5 was weaker (cross-validation R2 = 0.39) with lower precision (5.5 μg/m3). PM10–2.5 levels exhibited greater local spatial variability than PM10 or PM2.5, suggesting that PM2.5 measurements at ambient monitoring sites are more representative for surrounding populations than for PM10 and especially PM10–2.5. Conclusions: We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM2.5 and PM10–2.5 for estimating exposures of populations living in the northeastern and midwestern United States

Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin

Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, for large-scale river basins, determination of the relative importance of sediment sources is complicated by spatiotemporal variability in erosional processes and sediment sources, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sampling, analytical, and interpretive methods for sediment fingerprinting has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of sediment source fingerprinting as an aid to large-scale landscape conservation and restoration under current management frameworks. Most MRB studies reported credible fingerprinting results and found near-channel sources to be the dominant sediment sources in most cases, and yet a lack of standardization in procedural steps makes results difficult to compare. Findings from MRB studies demonstrated that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are needed to make this technique applicable in large-scale landscape conservation and restoration efforts. We summarize research needs and discuss sediment fingerprinting use for basin-scale management efforts with the aim of encouraging that this technique is robust and reliable as it moves forward

Quantifying the Impacts of Land Use, Management and Climate Change on Water Resources in Missouri River Basin

A location-specific evaluation of hydrological landscape responses concerning past and projected climate and land use land cover (LULC) changes can provide a powerful intellectual basis for developing efficient and profitable agroecosystems, and overcoming uncertain and detrimental consequences of LULC and climate shifts. This dissertation assessed the impacts of land use, management, and climate change on water resources in the Missouri River Basin (MRB) through four specific studies that included: (i) to study the responses of leached nutrient concentrations and soil health to winter rye cover crop (CC) under no-till corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation, (ii) to simulate hydrological responses of integrated crop-livestock (ICL) system under projected climate changes in an agricultural watershed, (iii) to evaluate the hydrological landscape responses in relation to past (1986-2018) LULC and climate shifts across South Dakota (SD), and (iv) to evaluate the hydrological landscape responses in relation to past (1986-2018) LULC and climate shifts across MRB. Cover cropping has been promoted for the ecological agricultural intensification, however, the vulnerability of CC establishment and expected soil health and water quality benefits under short and cold growing periods for CC are of concerns among producers in the northern Great Plains (NGP) region. Thus, a field experiment from 2017 to 2020 was conducted to assess the impacts of winter rye (Secale cereale L.) CC on soil health and water quality parameters under a no-till corn-soybean rotation at Southeast Research Farm (SERF), Beresford, SD. Interestingly, the study site faced one dry (2020) and two abnormally wet (2018 and 2019) years which received 31% lower (2020), and 31% (2018) and 23% (2019) higher precipitation, respectively, than the annual average (1953-2019). Data showed that biomass of the rye CC was 251 kg ha-1 in 2018, 1213 kg ha-1 in 2019, and 147 kg ha-1 in 2020, coinciding with contrasting growing degree days i.e., 1458, 2042, 794, respectively, as a consequence of variable weather conditions. Cover cropping did not impact water quality for the majority of the study period. However, a significant reduction in leached nitrate (~19-20%) and total nitrogen (TN) (~8.5-16%) concentrations were found only in 2019, pertaining to sequestered 18.8 kg N ha-1. Rye CC showed 13 and 11% significantly higher microbially active carbon and water-extractable organic nitrogen, respectively, than the control (No CC) treatment. The non-significant impacts on soil health indicators due to winter rye showed that study duration (3 years) may not be sufficient to see the beneficial impacts of cover crop on soils. However, significant reductions in leached nitrate and TN concentrations for one (2019) out of three study years suggest that well-established rye CC (biomass = 1213 kg ha-1; which was 4.8 and 8.3 times higher than that in 2018 and 2020) has the potential of reducing nutrient leaching and enhancing soil health for the study region. The ICL systems, when well managed properly, have beneficial impacts on soils and water yield, however, very limited studies are available due to the complexity of these integrated systems. Thus, a simulation study was conducted to assess the hydrological impacts of long-term implementation of ICL systems at watershed scale with the projected climate scenarios on water yield using the Soil and Water Assessment Tool (SWAT) model over two time periods [i.e. Near Future (2021-2050) and Far Future (2070-2099)]. This study was conducted in three phases over Skunk Creek Watershed (SCW), SD, USA. In phase I, the impact of long-term ICL system implementation (1976- 2005; 30 years) on soil hydrology was evaluated. Phase II and phase III evaluated the impacts of projected climate changes under existing land cover and ICL system, respectively. Outcomes of phase I showed a significant decrease in water yield and surface runoff. Phase II showed the susceptibility of SCW to extreme events such as floods and waterlogging during spring, and droughts during summers under the projected climate changes. Phase III showed the reduction in water yield and surface runoff due to the ICL system and minimizing the induced detrimental impacts only due to climate change. Evapotranspiration (ET) plays a significant role in crop growth and development, therefore, an accurate estimation of ET is very important for water use and availability. The past hydrological landscape responses were studied using well-validated (r2 = 0.91, PBIAS= -4%, and %RMSE = 11.8%) actual evapotranspiration (ETa) time-series (1986- 2018) estimations. The developed ETa products were further used to understand the crop water-use (CWU) characteristics and existing historic mono-directional (increasing or decreasing) trends across the SD and MRB regions. Spatial variability of the Operational Simplified Surface Energy Balance (SSEBop) model- and Landsat-based ETa estimations showed strong correspondence with land cover and climate across the basin. The drier foothills in northwestern MRB, dominated by grassland/shrubland, showed lower ETa (\u3c 400 mm/year), whereas, cropland dominated regions in lower semi-humid MRB and forested headwater exhibited higher ETa (\u3e 500 mm/year). For the SD region, Mann Kendall trend analysis revealed an absence of a significant trend in annual CWU at a regional scale due to the combined impact of varying weather conditions, and the presence of both increasing (12%) and decreasing (9%) CWU trends over a substantial portion at the pixel-scale. Whereas, for the MRB, summer season CWU trend analysis revealed a significant increasing trend at the regional-scale with 30% MRB cropland pixels under a significant increasing trend at pixel-scale. The existing increasing trends can be explained by the shift in agricultural practices, increased irrigated cropland area, higher productions, moisture regime shifts, and decreased risk of farming in the dry areas. Moreover, the decreasing trend pixels could be the result of the dynamic conversion of wetlands to croplands, decreased and improved irrigation and water management practices in the region. Overall, both studies highlight the potential of Landsat imagery and remote sensing-based ETa modeling approaches in generating historical time-series ETa maps over a wide range of elevation, vegetation, and climate

A Case-Study Application of the Experimental Watershed Study Design to Advance Adaptive Management of Contemporary Watersheds

settings Open AccessFeature PaperArticle A Case-Study Application of the Experimental Watershed Study Design to Advance Adaptive Management of Contemporary Watersheds by Jason A. Hubbart 1,*,Elliott Kellner 2 andSean J. Zeiger 3 1 West Virginia University, Institute of Water Security and Science, Davis College of Agriculture, Natural Resources and Design, Schools of Agriculture and Food, and Natural Resources, 3109 Agricultural Sciences Building, Morgantown, WV 26506, USA 2 West Virginia University, Institute of Water Security and Science, Davis College of Agriculture Natural Resources and Design, Division of Plant and Soil Sciences, 3011 Agricultural Sciences Building, Morgantown, WV 26506, USA 3 School of Natural Resources, University of Missouri, 203-T ABNR Building, Columbia, MO 65211, USA * Author to whom correspondence should be addressed. Water 2019, 11(11), 2355; https://doi.org/10.3390/w11112355 Received: 14 September 2019 / Revised: 30 October 2019 / Accepted: 6 November 2019 / Published: 9 November 2019 (This article belongs to the Special Issue Integrated Water Resources Research: Advancements in Understanding to Improve Future Sustainability) Download PDF Browse Figure Review Reports Cite This Paper Abstract Land managers are often inadequately informed to make management decisions in contemporary watersheds, in which sources of impairment are simultaneously shifting due to the combined influences of land use change, rapid ongoing human population growth, and changing environmental conditions. There is, thus, a great need for effective collaborative adaptive management (CAM; or derivatives) efforts utilizing an accepted methodological approach that provides data needed to properly identify and address past, present, and future sources of impairment. The experimental watershed study design holds great promise for meeting such needs and facilitating an effective collaborative and adaptive management process. To advance understanding of natural and anthropogenic influences on sources of impairment, and to demonstrate the approach in a contemporary watershed, a nested-scale experimental watershed study design was implemented in a representative, contemporary, mixed-use watershed located in Midwestern USA. Results identify challenges associated with CAM, and how the experimental watershed approach can help to objectively elucidate causal factors, target critical source areas, and provide the science-based information needed to make informed management decisions. Results show urban/suburban development and agriculture are primary drivers of alterations to watershed hydrology, streamflow regimes, transport of multiple water quality constituents, and stream physical habitat. However, several natural processes and watershed characteristics, such as surficial geology and stream system evolution, are likely compounding observed water quality impairment and aquatic habitat degradation. Given the varied and complicated set of factors contributing to such issues in the study watershed and other contemporary watersheds, watershed restoration is likely subject to physical limitations and should be conceptualized in the context of achievable goals/objectives. Overall, results demonstrate the immense, globally transferrable value of the experimental watershed approach and coupled CAM process to address contemporary water resource management challenges

Predicting Suitable Habitat Decline of Midwestern United States Amphibians and Quantifying the Consequence of Declines Using Pond-Breeding Salamanders

With current declines of vertebrate taxa meeting or exceeding those of historic mass extinction events, there is a growing need to investigate the main drivers of declines. Amphibians are perhaps at greatest risk of global climate change and land-use changes than most other vertebrate classes and also have significant roles in ecosystem processes – combined, this creates a cause for concern. I designed a study that would investigate the effects of current and predicted climate change and land-use changes on amphibians using species distribution models and a field study to identify the potential consequences of amphibian species declines by investigating the role of larval pond-breeding salamanders in wetlands in the Midwestern U.S. My objectives were to: (1) quantify changes in suitable habitat space and species richness for amphibians from current to future predictions, (2) compare predictions based exclusively on climate with predictions based on both climate and land-use, (3) identify what factors influence density of biota in ephemeral wetlands in the Midwest and (4) determine if larval pond-breeding salamanders have a measurable role in shaping wetland biotic communities. Model results indicate climate, not land-use, is a primary factor driving predicted changes in suitable habitat for amphibians in the Midwest and the changing climate is predicted to result in an overall decline of amphibian species richness based on future predictions. Wetland investigations showed local level factors influence aquatic invertebrate density while landscape level factors influence larval pond-breeding salamanders. I did not find any significant effects of larval pond-breeding salamander densities on the density of aquatic invertebrates. However, larval salamanders showed a predation bias for certain taxa as well as for taxa within the predator functional group. Future research should center on the role larval ambystomatid salamanders have on whole-ecosystem processes within wetlands and further interpolate the relationships between current and predicted global climate change on the potential decline of ecosystem processes