Predicted probability of fisher year-round occurrence, 2046-2065, Hadley CM3 A1fi, 10 km resolution

May 25, 2012
Description:
Future (2046-2065) predicted probability of fisher year-round occurrence projected under the A1fi emissions scenario with the Hadley CM3 GCM model (Gordon et al. 2000, Pope et al. 2000). Projected fisher distribution was 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 projected climate variables were provided by the PRISM GROUP (Daly et al. 1994). This fisher 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:

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.

Gordon C., C. Cooper , C.A. Senior, H. Banks, J.M. Gregory, T.C. Johns , J.F.B. Mitchell, and R.A. Wood.  2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168.

Hayhoe, K., D. Cayan, C.B. Field, P.C. Frumhoff , E.P. Maurer, N.L. Miller, S.C. Moser, S.H. Schneider, K. Nicholas 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.

Pope, V.D., M.L. Gallani, P.R. Rowntree, and R.A. Stratton. 2000. The impact of new physical parameterisations in the Hadley Centre climate model – HadAM3. Clim Dyn 16:123–146.
Data Provided By:
Conservation Biology Institute
Content date:
2046-2065
Citation:
Spencer, W. and H. Rustigian-Romsos. 2012. Unpublished.
Spatial Resolution:
10000.0 (meter)
Contact Organization:
Conservation Biology Institute
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Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 3.0 License.
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Conservation Biology Institute

The 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.