Jennifer Santoro, 2013 Duke Stanback Intern and graduate student at Duke University's Nicholas School of the Environment, created this 3D flyover model of habitat suitability in Shenandoah National Park.
See Jen's award-winning video of her experiences as a summer intern with the Virginia Chapter of The American Chestnut Foundation:
http://www.youtube.com/watch?v=ktfsebZPyIY
3D Mapping Description
3D Flyover Model of SNP - Click here for the video flyover
These 3D maps describe good (red) chestnut habitat and fair (orange) chestnut habitat predictions for the year 2070 using a radiative forcing scenario of 8.5 W/m2 under the Community Climate System Model (CCSM4) developed by the National Center for Atmospheric Research in the US (http://www.cesm.ucar.edu/models/ccsm4.0/). As can be seen in the maps, much of the habitat is focused on ridge tops and higher elevations. Sand content, elevation, and slope were the most important predictor variables of chestnut habitat in the model.
In this model, I used maximum monthly temperature for the warmest month of the year (for 2013, this was July in Shenandoah) and extrapolated maximum monthly temperatures for July 2070 using the Community Climate System Model (CCSM4) developed by the National Center for Atmospheric Research in the US. This scenario is part of the coupled model intercomparison project, phase five (CMIP5). Data are available in four representative concentration pathways (RCPs) developed by the IPCC, which describe the radiative forcing of greenhouse gas concentration trajectories to the year 2100 (Hijams et al 2005). The four RCPs are 2.6 W/m2, 4.5 W/m2, 6.0 W/m2, and 8.5 W/m2. Here, Maxent was used to model future chestnut habitat predictions using maximum temperature of the warmest month for RCP 8.5 in both 2050 and 2070.
Maxent models predicted that 13.5% (10,722 hectares) of the terrain was good habitat today and 11.56% (9,191 hectares) would be good habitat in 2070 due to climate warming. Since temperature was ranked ninth out of eleven environmental variables in importance to the model, these Maxent models predict that climate warming will not have a large impact on chestnut habitat suitability in the future.
References
Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
NCAR Community Climate System Model 4.0 (CCSM4.0). 2012. National Center for Atmospheric Research, USA. Available online at http://www.cesm.ucar.edu/models/ccsm4.0/
Maxent citations:
Phillips, S. J., M. Dudik, and R.E. Schapire. 2004. A maximum entropy approach to species distribution modeling. Pages 655-662 in Proceedings of the 21st International Conference on Machine Learning. ACM Press, New York
Phillips, S. J., R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modeling 190: 231-259.
AVI video, 67.2 MB
