Description: Predicted probability of fisher year-round
occurrence created with Maxent (Phillips et al. 2006) using fisher detections
(N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter
(January – March) precipitation, mean summer (July – September) precipitation,
mean summer temperature amplitude, mean daily low temperature for the month of
the year with the warmest mean daily low temperature, mean fraction of
vegetation carbon burned, mean vegetation carbon (g C m2), and modal
vegetation class. Predictor variables had a grid cell size of 10 km, vegetation
variables were simulated with MC1 (Hayhoe et al. 2004)
and climate variables were provided by the PRISM GROUP (Daly et al. 1994). This
fisher distribution model has a 10-fold cross-validated AUC of 0.819 +/- 0.041
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:
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.
Hayhoe,
K., D. Cayan, C.B. Field, P.C. Frumhoff , E.P. Maurer, N. L. Miller, S.C.
Moser, S.H. Schneider, K.N. Cahill, E.E. Cleland, L. Dale, R. Drapek, R.M.
Hanemann, L.S. Kalkstein, J. Lenihan, C.K. Lunch, R.P. Neilson, S.C. Sheridan
and J.H. Verville. 2004.
Emissions pathways, climate change, and impacts on
California, Proc. Natl. Acad. Sci. 101: 12422-12427.
Phillips,
S.J., R.P. Anderson,
and R.E. Schapire. 2006. Maximum
entropy modeling of species geographic distributions.
Ecological
Modelling 190: 231-259.