The Zoning of Lorestan Province’s forests decline risk using logistic regression model

Document Type : Animal environment

Authors

Department of Environment, Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran

Abstract

Habitat destruction is the most important threat to species. Forests are one of the most important habitats for wildlife. According to the latest official statistics of Forests, Range and Watershed Management Organization, approximately 25% of Zagros forests declined between 2001 and 2014. Identifying and zoning forest areas susceptible to decline to take preventative measures can help protect these important habitats. Hence, we used logistic regression model along with forest areas with over 50% decline as dependent variable and 12 environmental factors including annual mean rainfall, annual mean temperature, annual mean relative humidity, annual mean evapotranspiration, aridity index, drought index, dust storm index, NDVI, percentage of slope, geographic aspect, distance to agricultural lands and distance to surface waters as independent variables to identify forest areas susceptible to decline. The performance of the model was satisfactory with ROC of 0.93 and Pseudo-R2 equal to 0.33. Results indicated that about 51.3% of Lorestan province’s forests are faced with the risk of decline, of which about 25.3% have low risk, 8.7% have medium risk, 8.8% have high risk and 8.5% have very high risk of decline. Climatic factors including aridity index, evapotranspiration, annual mean rainfall, drought index, relative humidity and annual mean temperature were respectively recognized as the most important factors affecting Lorestan province’s forests decline.

Keywords


  1. Beier, CM.; Sink, S.E.; Hennon, P.E.; D’Amore, D.V. and Juday, G.P., 2008. Twentieth century warming and the dendroclimatology of declining yellow cedar forests in southeastern Alaska. Canadian Journal of Forest Research. Vol. 38, pp: 1319-1334.
  2. Bigler, C.; Barker, O.U.; Bugmann, H.; Dobbertin, M. and Rigling, A., 2006. Drought as an inciting mortality factor in Scots pine stands of the Valais, Switzerland. Ecosystems. Vol. 9, pp: 330-343.
  3. Das, A.J.; Battles, J.; Van Mantgemd, P.J. and Stephenson, N.L., 2008. Spatial elements of mortality risk in old-growth forests. Ecology. Vol. 89, pp: 1744-1756.
  4. Espadafor, M.; Lorite, I.J.; Gavilan, P. and Berengena, J., 2011. An analysis of the tendency of reference evapotranspiration estimates and other climate variables during last 45 years in Southern Spain. Agricultural Water Management. Vol. 98, pp: 1045-1061.
  5. Farmer, A., 1993. The effects of dust on vegetation-a review. Environmental Pollution. Vol. 79, pp: 63-75.
  6. Franklin, J.F.; Shugart, H.H. and Harmon, M.E., 1987. Tree death as an ecological process. Bioscience. Vol. 37, pp: 550-556.
  7. Guarin, A. and Taylor, A.H., 2005. Drought triggered tree mortality in mixed conifer forests in Yosemite National Park, California, USA. Forest ecology and management. Vol. 218, pp: 229-244.
  8. Harrison, P.A.; Berry, P.M.; Butt, N. and New, M., 2006. Modeling climate change impacts on species’ distributions at the European scale: implications for conservation policy. Environmental Science and Policy. Vol. 9, pp: 116-128.
  9. He, Z. and Lo, C., 2007. Modeling urban growth in Atlanta using logistic regression. Computers, Environment and Urban Systems. Vol. 31, No. 6, pp: 667-688.
  10. Keenan, J.R.; Reams, G.R.; Achard, F.; de Freitas, V.J.; Grainger, A. and Lindquist, E., 2015. Dynamics of global forest area: Results from the FAO Global Forest Resources Assessment 2015. Forest Ecology and Management. Vol. 352, pp: 9-20.
  11. Koprowski, L.J.; Gavish, L. and Doumas, S.L., 2016. Sciurus anomalus. Mammalian Species. Vol. 48, No. 934,
    pp: 48-58.
  12. Mackee, B.; Nolan, T.; Dooesken, J. and Kleist, J., 1995. Drought monitoring with multiple timescale. Conference on Applied Climatology. Bostun.
  13. Newbery, D.M. and Lingenfelder, M., 2009. Plurality of tree species responses to drought perturbation in Bornean tropical rain forest. Plant Ecology. Vol. 201, pp: 147-167.
  14. O’Loingsigh, T.; McTainsh, G.H.; Tews, E.K.; Strong, C.L.; Leys, J.F.; Shinkfield, P. and Tapper, N.J., 2014. The Dust Storm Index (DSI): A method for monitoring broadscale wind erosion using meteorological records. Aeolian Research. Vol. 12, pp: 29-40.
  15. Segan, D.B.; Murray, K.A. and Watson, J.E, 2016. A global assessment of current and future biodiversity vulnerability to habitat loss-climate change interactions. Global Ecology and Conservation. Vol. 5, pp: 12-21.
  16. UNEP (United Nations Environment Programme). 1997. World atlas of desertification 2ED. UNEP, London.
  17. Walther, G.R.; Post, E.; Convey, P.; Menzel,A.; Parmesan, C.; Beebee, T.J.C.; Fromentin, J.M.; Hoeghguldberg, O. and Bairlein, F., 2002. Ecological responses to recent climate change. Nature. Vol. 416, pp: 389-395.