IRCEB: Spatial dynamics are crucial for understanding population, community, and ecosystem processes. Two general problems in landscape ecology do not yet have adequate solutions: (1) translating observations taken at small spatial (and temporal) scales into expected patterns at landscape and geographic scales, and (2) understanding the influences of spatial heterogeneity on individual movements/demography, and on population distribution and dynamics. We propose to address these issues using a multi-faceted research program that integrates empirical data collection with spatial modeling and GIS analyses. The proposed experimental organism is the American elk. This species is of high conservation/natural management interest, and several elk reintroduction efforts in North America are currently in progress. However, little is known about how fast reintroduced elk populations may spread. Thus, by successfully completing the research goals outlined in this proposal we will not only be able to address questions of central importance to theoretical ecology, but will also obtain insights for improved management decisions. Our specific approach to the two issues above will be based on developing a series of spatial models addressing a range of scales, from a microscale (tens of m and hours) through a mesoscale (km and weeks) to a macroscale (tens to hundreds of km and years). At each scale we will parameterize the model using small-scale data on individual movements and demography, and test the model by predicting independent data on spatial redistribution of populations at broader (landscape and, ultimately, geographic) spatial scales. Data on individual movements will be obtained by following elk equipped with radiocollars at four different sites, varying in landscape heterogeneity and elk population density (two sites where elk have been long established, and two where they were recently introduced). Landscape heterogeneity will be quantified using a combination of remote sensing methods and detailed on-the-ground analyses of such variables as the distribution of winter and summer forage biomass and quality, land and habitat classification, and landscape structure. We will determine how accurately microscale model can predict mesoscale data, and mesoscale model can predict macroscale data. Furthermore, the macroscale predictions of the detailed, mechanism-based mesoscale model will be contrasted to the predictions from a more phenomenological (but much less data-demanding) macroscale model. This comparison will allow us to determine whether it is essential to understand processes governing movement at multiple spatial scales in order to make meaningful predictions of population redistribution at larger (geographic) scales.
