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Understanding the effects of climate change on global ecology is a required to predict the effects of climate change on the distribution and abundance of species, and to be able to identify ecosystems and landscapes most at risk to climate change in the future. To date, most approaches to understanding ecological effects of climate change on species have used individual or limited numbers of populations of a species, for example, using Niche modeling, or time-series analysis of individual populations. While useful, we argue these approaches are fundamentally limited because they do not address species responses at the most appropriate scale for global climate analyses that of the global distribution of a species. Niche models generally predict uniform distributional shifts, but such predictions do not match observations of historic (i.e., Pleistocene) or current species range shifts. This is because they ignore several key components of species responses to climate change; 1) species interactions, 2) spatial/temporal variation in climatic downscaling to local population dynamics, and 3) climate driven synchrony and asynchrony in population dynamics. Therefore, the goal of our proposal is to use extensive datasets for two contrasting large mammalian species over the entire range of their global and North American distribution to understand the effects of climate change on global scale population dynamics. We call our approach the Global Population Dynamics approach. The main components of the Global Population Dynamics approach are to 1) construct historic and project future environmental niche models based on NASA remotely sensed datasets to evaluate the effect of potential climate change on Elk (Cervus) and Caribou and Reindeer (Rangifer) throughout their circumpolar distribution; 2) evaluate the effects of biotic (i.e., vegetation biomass, predation) and abiotic (i.e, climate) on ungulate population dynamics using time-series of population counts, and 3) understand the degree of spatial synchrony between populations of elk and caribou across global scales and how changes in climate/vegetation synchrony drives population synchrony. To answer these questions we will use global-scale datasets on the distribution of elk and caribou (broad scale telemetry location datasets), combined with one of the most extensive sets of abundance datasets including >100 time series of these species. We will then address our research objectives by developing niche and time-series population- models using matching spatial-temporal time series of remotely sensed vegetation indices from combined AVHRR-MODIS and MODIS NPP time series ( from 1981-the present), MODIS snowcover and landcover, as well as global time series of climate data. Using the MODIS NPP 17A2/A3 dataset will allow us to address the effects of climate itself on ungulates as well as the effects of climate on terrestrial vegetation for the first time. Addressing questions 2 and 3 will then feed back to objective 1 to relax the assumptions of uniform climatic response of species given spatial drivers of asynchrony, and extend the naïve predictions of niche models for these two well studied, but contrasting, species. Finally, we will be able to extend our adjusted Niche model projections to potential future effects of climate change using the most recent CMIP-5 climate model outputs developed for the 5th IPCC assessment. While data-hungry, our Global Population Dynamics approach will set the stage for understanding the challenges of interpreting local-scale climatic analyses for these and other species, and establish a firm understanding of climate change on the distribution and abundance of these two ecologically and economically important species.

Project PI: Mark Hebblewhite/University of Montana, College of Forestry and Conservation

Department of Ecosystem and Conservation Sciences College of Forestry and Conservation University of Montana Missoula, MT 59812

Phone: (406) 243-6675

Email: mark.hebblewhite@umontana.edu

http://www.cfc.umt.edu/PersonnelDetail.aspx?id=1133

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Started: Mar 31, 2011

Last Activity: Mar 31, 2011

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