Wetlands in the Minnesota Prairie Pothole Region are critical landscape elements because of their unmatched importance to breeding waterfowl, and other wildlife. They provide vast benefits to store runoff or act as nutrient sinks and offer other environmental and socio-economic returns. Data on location, extent and types of wetlands collected by the U.S. Fish and Wildlife Service National Wetlands Inventory is used for developing conservation strategies and evaluating net landscape changes affecting fish and wildlife populations. Minnesota wetlands were mapped 27 y ago by the National Wetlands Inventory. We examined 176 10.2-km2 (4-mi2) sample plots in the Minnesota Prairie Pothole Region, using aerial photo interpretation techniques, to determine the current accuracy of the National Wetlands Inventory data used in the eastern Prairie Pothole Region for conservation planning and evaluation. We stratified our analysis by Bailey's (1995) Ecological Subsections. We estimated that across the entire Minnesota Prairie Pothole Region 4.3% of wetland area has been lost since 1980 with losses varying from 0 to 15% among Ecological Subsections. Implications of these findings suggest that National Wetlands Inventory data should be regularly updated in areas subject to rapid wetland change.
There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively‐farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land‐cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management‐related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row‐crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land‐cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land‐cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land‐cover. Further, our results indicated that track‐survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.