Predicted probability of marten year-round occurrence
derived from future (2076-2095) climate projections and vegetation simulations.
Projected marten distribution was created with Maxent (Phillips et al. 2006)
using marten detections (N = 102, spanning 1993 – 2011) and eight predictor
variables: mean potential evapotranspiration, mean annual precipitation, mean
fraction of vegetation carbon burned, mean forest carbon (g C m2),
mean fraction of vegetation carbon in forest, understory index (fraction of
grass vegetation carbon in forest), average maximum tree LAI, and modal
vegetation class.
Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case CSIRO Mk3 (Gordon 2002) under the A2 emission scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures and ratios for precipitation) were used to modify PRISM 800m historical baseline (Daly et al. 2008).
Vegetation variables were simulated with the MC1 dynamic global vegetation model (Bachelet et al. 2001). This marten distribution projection was generated as part of a pilot project to apply and evaluate the Yale Framework (Yale Science Panel for Integrating Climate Adaptation and Landscape Conservation Planning).
Grid Value Predicted Probability of Occurrence
1 0 – 0.2
2 0.2 – 0.4
3 0.4 – 0.6
4 0.6 – 0.8
5 0.8 – 1.0
Bachelet D., R.P. Neilson, J.M. Lenihan, and R.J. Drapek. 2001. Climate change effects on vegetation distribution and carbon budget in the U.S. Ecosystems 4:164-185.
Daly, C., M. Halbleib, J.I. Smith, W.P. Gibson, M.K. Doggett, G.H. Taylor, J. Curtis, and P.A. Pasteris. 2008. Physiographically-sensitive mapping of temperature and precipitation across the conterminous United States. International Journal of Climatology 28: 2031-2064.
Gordon, H.B., L.D. Rotstayn, J.L. McGregor, M.R. Dix, E.A. Kowalczyk, S.P. O’Farrell, L.J. Waterman, A.C. Hirst, S.G. Wilson, M.A. Collier, I.G. Watterson, and T.I. Elliott. 2002. The CSIRO Mk3 climate system model. CSIRO Atmos. Res. Tech. Pap., 60, 130 pp., Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia.
Naki?enovi?, N. and R. Swart, Eds. 2000. Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge Univ. Press, Cambridge, U. K.
Phillips, S.J., R.P. Anderson, and R.E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231-259.
Note: The MC1 model is described in data basin (http://databasin.org/climate-center/features/mc1-dynamic-global-vegetation-model).
my_csia2_f2The Conservation Biology Institute (CBI) provides scientific expertise to support the conservation and recovery of biological diversity in its natural state through applied research, education, planning, and community service.