Overlay of projected marten distributions, 2046-2065, 800 m resolution

Jun 18, 2012
Agreement in predicted marten year-round distribution derived from future (2046-2065) climate projections and vegetation simulations using 3 GCMs (Hadley CM3 (Johns et al. 2003), MIROC (Hasumi and Emori 2004), and CSIRO Mk3 (Gordon 2002)) under the A2 emissions scenario (Naki?enovi? et al. 2000).

Projected marten distribution was created with Maxent (Phillips et al. 2006) using marten detections (N = 302, spanning 1990 – 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.

Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, under the A2 emission scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures and ratios for precipitation) were used to modify PRISM 800m historical baseline (Daly et al. 2008). Vegetation variables were simulated with MC1 dynamic global vegetation model (Bachelet et al. 2001).  This data layer 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 indicates number of projections with predicted probability of marten occurrence >= 0.5.

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.

Gordon, H.B., L.D. Rotstayn, J.L. McGregor, M.R. Dix, E.A. Kowalczyk, S.P. O’Farrell, L.J. Waterman, A.C. Hirst, S.G. Wilson, M.A. Collier, I.G. Watterson, and T.I. Elliott.  2002. The CSIRO Mk3 climate system model. CSIRO Atmos. Res. Tech. Pap., 60, 130 pp., Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia.

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

Johns, T.C., J.M. Gregory, W.J. Ingram, C.E. Johnson, A. Jones, J.A. Lowe, J.F.B. Mitchell, D.L. Roberts, D.M.H. Sexton, D.S. Stevenson, S.F.B. Tett, and M.J. Woodage. 2003. Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios. ClimDyn 20: 583-612.

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.
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Spencer, W. and H. Rustigian-Romsos. 2012. Unpublished.
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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.