Abstract:The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) have gained considerable attention in ecological research and management as proxies for landscape-scale vegetation quantity and quality. In the Greater Yellowstone Ecosystem (GYE), these indices are especially important for mapping spatiotemporal variation in the forage available to migratory elk (Cervus elaphus). Here, we examined how the accuracy of using MODIS-derived NDVI and EVI as proxies for forage biomass and quality differed across elevation-related phenology and land use gradients, determined if polynomial NDVI/EVI, site, and season effects improved these models, and then mapped spatiotemporal variation in the abundance of high quality forage available to elk across the Upper Yellowstone River Basin (UYRB) of the GYE. Models with a polynomial NDVI effect explained 19%-55% more variation in biomass than the linear NDVI and EVI models. Models with linear season effect explained 14%-20% more variation in chlorophyll, 37%-69% more variation in crude protein, and 26%-50% more variation in in vitro dry matter digestibility (IVDMD) than the linear NDVI and EVI models. Linear NDVI models explained more variation in biomass and quality across the UYRB than the linear EVI models. The accuracy of these models was lowest in grasslands with late onset of growth, in irrigated agriculture, and after the peak in biomass. Forage biomass and quality varied across the elevation-related phenology and land use gradients in the UYRB throughout the season. At their seasonal peak, the abundance of high quality forage for elk was 50% greater in grasslands with late onset of growth and 200% greater in irrigated agriculture than in all other grasslands, suggesting that these grasslands play an especially important role in the movement and fitness of migratory elk. These results provide novel information on the utility of NDVI and EVI for mapping spatiotemporal patterns of forage biomass and quality.
As wildlife becomes more isolated in human-dominated and rapidly changing environments, species conservation requires investment in landscape connectivity. Identifying stepping stones (discrete areas of suitable habitat that facilitate the movement of dispersing individuals) can help meet connectivity goals. We report the occurrence of the snow leopard Panthera uncia in Ikh Nart Nature Reserve, Mongolia, over 250 km from the nearest known population, one of the easternmost records for the species. Ikh Nart Nature Reserve lies within a region considered highly resistant to movement but harbours high densities of argali sheep Ovis ammon and Siberian ibexes Capra sibirica, both important prey items for snow leopards. This occurrence reveals a new distribution record for the species, the capacity of the species to move across low-quality environments, the value of investment in community conservation and collaborative park management, and the role of remote protected areas such as Ikh Nart Nature Reserve as stepping stones for facilitating population expansion and broader connectivity to other potentially suitable but unoccupied areas.
Spatial and temporal variations in grassland phenology are thought to play a critical role in migration patterns of large herbivores in the Greater Yellowstone Ecosystem. Phenology, referring to the timing of green-up in this study, is directly related to biomass and forage quality. Migratory elk (Cervus elaphus), therefore, are believed to follow phenology across an elevation gradient during the growing season to maximize their access to high quality and quantity of forage. Concern that climate change and human land use alterations of phenology may impact the benefits of elk migration highlights the need for landscape-scale vegetation phenology monitoring. Satellite-derived Normalized Difference Vegetation Index (NDVI) shows potential as a remote sensing tool to predict landscape-level shifts in grassland phenology, but is limited by a lack of validation at varying scales, seasons, and in human land use areas. This study is focused on validating the accuracy of satellite-derived NDVI in estimating grassland phenology, biomass, and forage quality throughout the summer growing season within elk migratory ranges in the Upper Yellowstone River Basin. Results from this study will provide managers and researchers with information on the accuracy of NDVI as a tool for monitoring the effects of climate change and human land use on grassland dynamics relevant to migratory elk.
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