Predicted probability of marten year-round occurrence, 1986-2005, 4 km resolution

Predicted probability of marten year-round occurrence 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. Predictor variables had a grid cell size of 4 km by 4 km, vegetation variables were simulated with MC1 dynamic global vegetation model (Bachelet et al. 2001) and historical climate variables were provided by the PRISM GROUP (Daly et al. 1994).  This marten distribution model has a 10-fold cross-validated AUC of 0.863 +/- 0.021 and 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.

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).