Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.

Abstract from Ecosphere: The Prairie Pothole Region, situated in the northern Great Plains, provides important stopover habitat for migratory shorebirds. During spring migration in the U.S. Prairie Potholes, 7.3 million shorebirds refuel in the region's myriad small, freshwater wetlands. Shorebirds use mudflats, shorelines, and ephemeral wetlands that are far more abundant in wet years than dry years. Generally, climate change is expected to bring warmer temperatures, seasonality shifts, more extreme events, and changes to precipitation. The impacts to wetland habitats are uncertain. In the Prairie Potholes, earlier spring onset and warmer temperatures may advance drying of wetlands or, alternately, increased spring precipitation may produce abundant shallow‐water habitats. To look at the availability of habitats for migratory shorebirds under different climate regimes, we compared habitat selection between a historic wet year and a dry year using binomial random‐effects models to describe local and landscape patterns. We found that in the dry year shorebirds were distributed more northerly and among more permanent wetlands, whereas in the wet year shorebirds were distributed more southerly and among more temporary wetlands. However, landscape‐scale variation played a larger role in the dry year. At the local wetland scale, shorebirds selected similarly between years—for shallower wetlands and wetlands in croplands. Overall, while shorebirds were sensitive to local habitat conditions, they exhibited a degree of adaptive capacity to climate change impacts by their ability to shift on the landscape. This indicates an avenue through which management decisions can enhance climate change resilience for these species given an uncertain future—by preserving shallow‐water wetlands in croplands throughout the landscape.

The North American Prairie Pothole Region (PPR) is an expansive region that covers parts of five Midwestern states and three Canadian provinces. This region contains millions of wetlands in which waterfowl breed and from which 50-80% of the continent's migratory ducks originate each year. Previous modeling efforts indicated that climate change would result in a shift of suitable waterfowl breeding habitat from the central PPR to the southeastern portion of the region, an area where the majority of wetlands have been drained. If this future scenario were to materialize, a significant restoration effort would be needed in the southeastern PPR to support waterfowl production. However, more recent research has revealed that changes in climate are influencing these critical wetland habitats in novel ways, and previous modeling results may no longer be valid. Land and natural resource managers are in need of more accurate, up-to-date scientific information in order to make fully informed planning decisions about these important wetlands and waterfowl habitat. This project aimed to improve our understanding of how future climate changes might impact wetland ecosystems and waterfowl habitats of the PPR. Project researchers used a newly developed wetland simulation model to simulate hydrologic and chemical conditions of prairie pothole wetlands under various climate change scenarios. Results were compared to results from previous modeling and analysis efforts to gain a better understanding of future impacts to wetlands and the ability of prairie pothole wetlands to continue meeting the habitat needs of breeding waterfowl. Throughout this effort, the project team worked directly with land managers from the U.S. Fish and Wildlife Service’s Habitat and Population Evaluation Team and Chase Lake Wetland Management District in North Dakota to ensure that study results and science products can directly inform climate adaptation plans for waterfowl habitat.    

The Missouri River system is the life-blood of the American Midwest, providing critical water resources that drive the region’s agriculture, industry, hydroelectric power generation, and ecosystems. The basin has a long history of development and diversion of water resources, meaning that streamflow records that reflect natural, unmanaged flows over the past century have been rare. As a result, research on the complex interactions between temperature and precipitation in driving droughts and surface water variability in the Missouri River Basin has lagged behind similar work done in other major basins in the country, and has hindered drought planning efforts.  To address this need, researchers will use tree-rings to develop reconstructions of historic, natural streamflow in the Upper Missouri River Basin. This will be the first such network of hydrologic reconstructions for the basin. Specifically, the tree-ring analysis will provide information on precipitation, temperature, and streamflow for the basin going back 800 years. This historical information will then be used to explore the drivers of drought and periods of high flow in the basin, beyond just precipitation. For example, evidence suggests that temperature is an increasingly important driver of drought, and an analysis of the impacts of warming temperatures on streamflow can be used to help managers anticipate future impacts on water supplies in the basin. Lastly, researchers will work closely with engineers and water managers with the U.S. Bureau of Reclamation and the Montana Department of Natural Resources and Conservation to integrate information on droughts and natural variability in streamflow into their water operations and drought planning efforts. Through this effort, researchers will seek to address questions such as “what are the impacts to current water operations under severe droughts, like the 1930s Dust Bowl or 1500s megadrought?” and “how could operations be changed to improve water management for droughts like these, given projected future warming?”. This information will help water managers in the Missouri River Basin develop adaptation strategies to manage the future range of potential drought and flood events in the basin, ultimately helping to reduce the billions of dollars that these events cost today in infrastructure and economic impact.

Lakes, reservoirs, and ponds are central and integral features of the North Central U.S. These water bodies provide aesthetic, cultural, and ecosystem services to surrounding wildlife and human communities. External impacts – such as climate change – can have significant impacts to these important parts of the region’s landscape. Understanding the responses of lakes to these drivers is critical for species conservation and management decisions.   Water temperature data are foundational to providing this understanding and are currently the most widely measured of all aquatic parameters with over 400 unique groups monitoring water temperature in U.S. lakes and rivers. However, lake temperature data are lacking at the relevant spatial and temporal scales needed for decision-making, and there has been a lack of national coordination and synthesis of these data collection efforts. Assembling and harmonizing this wealth of data would provide a valuable resource for modeling, analyzing, and predicting water temperature.   This project will build upon previous work funded by the Northeast CASC that provided a foundation for modeling and predicting water temperature of approximately 11,000 lakes in Minnesota, Wisconsin, and Michigan. Project researchers are expanding those efforts by using the modeling techniques from the previous project, along with existing temperature data, to reconstruct a historical record of water temperatures from 1979 to 2018 and generate predictions for tens of thousands of lakes in the prairie pothole region of North and South Dakota. With this information, the team will also analyze the habitat suitability of these lakes to several fish species.   Data from this project will help water and natural resource managers clarify and quantify risks to fish populations, for example by identifying where the preferred thermal habitat of a species is projected to disappear and put the fish at risk of local extirpation. Results will be directly relevant to understanding the health of water resources in the North Central U.S. and can inform specific conservation actions.

The purpose of this project was to estimate and map the probability that grassland converts to cropland in the northern plains and prairie region given potential climate change. This region provides critical breeding and migratory habitat for waterfowl and other wetland-dependent species, and is also a highly productive agricultural region. Generally, the regional effects projected by climate models are increasing temperatures and more variable precipitation, which could provide incentives for private landowners to convert native and managed grassland to intensive cropland. Conversion of grassland to cropland can result in habitat loss for dependent species and the degradation of a range of ecosystem services. If climate change alters the spatial distribution of both agricultural land use and suitable habitat, land managers and conservationists may need to alter efforts to offset the negative consequences of combined climate and land-use change on habitats and dependent species. The land-use change projections associated with this report provide information for such management efforts.

Abstract (from Diversity and Distributions):  Aim Surrogate species can provide an efficient mechanism for biodiversity conservation if they encompass the needs or indicate the status of a broader set of species. When species that are the focus of ongoing management efforts act as effective surrogates for other species, these incidental surrogacy benefits lead to additional efficiency. Assessing surrogate relationships often relies on grouping species by distributional patterns or by species traits, but there are few approaches for integrating outputs from multiple methods into summaries of surrogate relationships that can inform decision‐making. Location Prairie Pothole Region of the United States. Methods We evaluated how well five upland‐nesting waterfowl species that are a focus of management may act as surrogates for other wetland‐dependent birds. We grouped species by their patterns of relative abundance at multiple scales and by different sets of traits, and evaluated whether empirical validation could effectively select among the resulting species groupings. We used an ensemble approach to integrate the different estimated relationships among species and visualized the ensemble as a network diagram. Results Estimated relationships among species were sensitive to methodological decisions, with qualitatively different relationships arising from different approaches. An ensemble provided an effective tool for integrating across different estimates and highlighted the Sora (Porzana carolina), American Avocet (Recurvirostra Americana) and Black Tern (Chlidonias niger) as the non‐waterfowl species expected to show the strongest incidental surrogacy relationships with the waterfowl that are the focus of ongoing management. Main conclusions An ensemble approach integrated multiple estimates of surrogate relationship strength among species and allowed for intuitive visualizations within a network. By accounting for methodological uncertainty while providing a simple continuous metric of surrogacy, our approach is amenable to both further validation and integration into decision‐making.

Globally, spring phenology and abiotic processes are shifting earlier with warming. Differences in the magnitudes of these shifts may decouple the timing of plant resource requirements from resource availability. In riparian forests across the northern hemisphere, warming could decouple seed release from snowmelt peak streamflow, thus reducing moisture and safe sites for dominant tree recruitment. We combined field observations with climate, hydrology, and phenology models to simulate future change in synchrony of seed release and snowmelt peaks in the South Platte River Basin, Colorado, for three Salicaceae species that dominate western USA riparian forests. Chilling requirements for overcoming winter endodormancy were strongest in Salix exigua, moderately supported for Populus deltoides, and indiscernible in Salix amygdaloides. Ensemble mean projected warming of 3.5°C shifted snowmelt peaks 10–19 d earlier relative to S. exigua and P. deltoides seed release, because decreased winter chilling combined with increased spring forcing limited change in their phenology. By contrast, warming shifted both snowmelt peaks and S. amygdaloides seed release 21 d earlier, maintaining their synchrony. Decoupling of snowmelt from seed release for Salicaceae with strong chilling requirements is likely to reduce resources critical for recruitment of these foundational riparian forests, although the magnitude of future decoupling remains uncertain.