Predicted probability of marten year-round occurrence
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.
Predictor variables had a grid cell size of 800 m by 800 m, 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. 2008). This marten distribution model has a 10-fold cross-validated AUC
of 0.848 +/- 0.014 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
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.
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).