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Keywords:

  • Brucella abortus;
  • brucellosis;
  • Cervus elaphus;
  • Greater Yellowstone Ecosystem;
  • Montana;
  • resource selection;
  • wildlife disease

Summary

1. The presence of Brucella abortus within free-ranging wildlife populations is an important conservation and management issue because of the risk of brucellosis transmission between wildlife and livestock. Predicting wildlife distributions is necessary to forecast wildlife and livestock spatial overlap and the potential for brucellosis transmission.

2. We used Global Positioning System data collected from telemetry-collared female elk Cervus elaphus to develop resource selection function (RSF) models during the brucellosis transmission risk period (the abortion and calving periods). We validated extrapolation of predictive models at two nearby elk ranges within the Greater Yellowstone Ecosystem. Additionally, we integrated extrapolated RSF maps and domestic livestock distributions to estimate the relative probability of elk and livestock commingling during the brucellosis transmission risk period.

3. The top-ranked model predicted that areas selected by elk had a lower probability of wolf Canis lupus occupancy, were privately owned and south facing, and had steeper slopes, lower road densities and higher Normalized Difference Vegetation Index (NDVI). Elk selected forests and shrublands over grasslands; however, the strength of selection decreased as snowpack increased. Elk selection for privately owned lands may lead to spatial overlap with livestock and increase the risk of elk and livestock intermingling. Furthermore, if both elk and livestock concentrate in areas of higher NDVI, increased spatial overlap may occur in these areas.

4. Predictive accuracy was highest in the study area where the model was developed. When compared to the model development area, predictive accuracy of extrapolated RSF maps was similar or better in one of the elk ranges and lower in the other elk range.

5.Synthesis and applications. Extrapolated RSF and spatial overlap maps can provide a foundation for identifying the highest risk areas of elk and livestock spatial overlap during the brucellosis transmission risk period. However, the predictive accuracy of the models is limited when applied to different areas. Site-specific models of spatial overlap would therefore be needed to provide the most accurate estimates of elk and livestock spatial overlap during the transmission risk period. The degree to which spatial overlap may lead to actual transmission risk needs to be investigated as this is not yet known and could have important implications for managing transmission risk.