During the conservation movement of the United States of America, the prairie ecosystems prairies were largely ignored, and instead converted for food production (Samson et al. 2004). Indeed, prairie landscapes are the least protected biome world-wide as a result of human alteration and disturbance (Hoekstra et al. 2004; White et al. 2000). This has resulted in the large-scale loss and desertification of important prairie habitats and the species that rely on them (Pennisi 2019; Rosenberg et. el. 2019; White et al. 2000).
The prairie habitats of the Great Plains represent a critical ecosystem for both humans and wildlife. Landscape change and other human activities have affected the distribution and abundance of a number of obligate prairie vertebrate species. On average, temperate grassland biomes have suffered greater species “loss” (more species are no longer found within the full range of their former habitats) than any other North American biome (Forrest et al. 2004; Laliberte & Ripple 2004). The limited extent of large connected areas where biodiversity is a primary management objective may explain why 74% of 39 species classified as grassland obligates with distributions centered in the northern Great Plains are identified as imperiled by federal, state, and provincial governments.
We seek to provide the necessary scientific understanding for sustainable wildlife and land management that will attempt to maximize the available wildlife habitat and travel corridors. Our interdisciplinary team consists of experts in the fields of ecology, genetics, disease, remote sensing, and technology, allowing us to approach this issue from multiple perspectives and more fully address each aspect of the entire socio-ecological system.
Our objectives are to use these technologies to assess the impacts of habitat loss, habitat change, and fragmentation on wildlife movement and habitat selection. Prairie habitat are a matrix of a complex set of micro habitat types that vary both spatially and temporally. This causes certain animals to move and select resources differently than similar grassland species. This will affect home range sizes as well as resource selection. Understanding how species movement and use habitat different in low disturbance habitat, medium disturbance habitat, as well as a high disturbance prairie habitat will allow for a greater understanding of the impacts of habitat loss and fragmentation on wildlife, in addition to identifying possible human-wildlife conflict ‘hot spots’ that can be targeted with conflict management efforts. Conflict ‘hot spot’ characteristics can also be identified and used to identify potential conflict areas in other regions where agricultural expansion into natural habitats is occurring. This will allow for informed management of fragmented habitats and directed wildlife corridor design to meet the needs of multiple wildlife species, with the goal of decreased human-wildlife conflict. Given the recent intensification of many agricultural practices worldwide, the proposed research provides a timely and valuable contribution to the fields of spatial ecology, landscape ecology, and human-wildlife conflict management.
This work is assessing the impacts of habitat loss and fragmentation on wildlife movements and habitat selection. Through the use of remotely sensed imagery and Global Positioning System (GPS) technologies we are starting to understand the impact of human activities and land use changes on animal movements and habitat selection. This is an emerging area of ecology, as the use of remotely sensed imagery and GPS technologies allow for fine scale data to be collected on both habitat features and animal space use. This has allowed for increased understanding of the impacts of land use change and other human activities on a variety of wildlife behaviors, movements, and habitat selection. It is also a useful tool for understanding human-wildlife conflict, as the space use and requirements of each can be accurately measured and projected across much larger areas than was previously possible.