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 = 302, spanning 1990 – 2011) and nine predictor variables: mean
winter (January – March) precipitation, mean amount of snow on the ground in
March, mean understory index (fraction of grass vegetation carbon in forest), mean fraction of total forest carbon in coarse
wood carbon, average maximum tree LAI, mean fraction of vegetation carbon
burned, mean forest carbon (g C m2), mean fraction of vegetation
carbon in forest, and modal vegetation class.
Future climate drivers were generated using statistical
downscaling (simple delta method) of general circulation model projections, in
this case MIROC 3.2 medres (Hasumi and Emori 2004) under the A2 emission
scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures
and ratios for precipitation) were used to modify PRISM 4km historical baseline
(Daly et al. 1994). Vegetation variables were simulated with 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
References:
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., R.P. Neilson, and D.L.
Phillips. 1994. A statistical topographic model for mapping climatological
precipitation over mountainous terrain. Journal of Applied Meteorology
33:140–158.
Hasumi, H., and S. Emori, Eds.
2004. K?1 Coupled GCM (MIROC) Description, K?1 Tech. Rep. 1, 34 pp., Cent. for
Clim. Syst. Res., Tokyo, Japan. Available online at http://www.ccsr.u?tokyo.ac.jp/kyosei/hasumi/MIROC/tech?repo.pdf
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).