مروری بر مدل‎سازی زیستگاه به‌عنوان ابزاری برای مدیریت زیستگاه‌های حیات‌وحش

نوع مقاله: مقاله پژوهشی

نویسنده

استادیار، دانشگاه فردوسی

چکیده

چکیده
سیستم اطلاعات مکانی (GIS) که علم و فناوری تجزیه و تحلیل داده­های مکان­مرجع می­باشد، توانایی تلفیق تعداد زیادی پارامتر را به صورت همزمان دارد. و این توانایی در کنار مبانی آماری مدل‎سازی مجموعه­ای مناسب را در اختیار اکولوژیست­ها برای اجرای مدل‎های اکولوژیک قرار می­دهد. یکی از این مدل­های اکولوژیکی که در امر مدیریت و حفاظت گونه­های حیات­وحش بسیار مهم تلقی می­گردد مدل های زیستگاه برای گونه­های حیات‎وحش است. بطور کلی مدل های زیستگاه در دو گروه مدل‎های توزیع گونه و مدل های مطلوبیت زیستگاه جای می گیرند که امروزه بسیار مورد استقبال اکولوژیست­ها و زیست­شناسان واقع شده‎اند. این مدل­ها در واقع باعث معرفی آشیان بوم­شناختی گونه‎ها می­شوند که می‎تواند در حفاظت گونه­های حیات­وحش به عنوان مثال مدیریت توزیع گونه­ها، ارزیابی اثرات فاکتورهای محیطی و انسانی مختلف (از قبیل آلودگی و اقلیم)، ارزیابی ریسک هجوم‎های بیولوژیکی و مدیریت گونه­های در معرض خطر مؤثر واقع شود. بر این اساس در مطالعه حاضر سعی شد به مبانی مدل‎سازی زیستگاه و رویکردهای مختلف آن به عنوان ابزاری برای مدیران حیات­وحش پرداخته شود تا بتواند بستری را برای ارتقاء اقدمات حفاظتی در کشورمان فراهم سازد.
 

کلیدواژه‌ها


Alizadeh, A.; (2006). Identifying bird species as biodiversity indicators for terrestrial ecosystem management, PhD thesis, RMIT University, Melbourne, Australia, pp 173.

Anderson, M.C.; Watts, J.M.; Freilich, J.E.; Yool, S.R.; Wakefield, G.I.; Mccaulery, J.F.; Fahnestock, A.;(1999). Regression-tree modeling of desert tortoise habitat in the centeral Mojave desert. Ecological application; 10: 890-897.

Anderson, R. P.; Lew, D.; Peterson, A.T.; (2003). Evaluating predictive models of species’ distributions criteria for selecting optimal models. Ecological Modelling; 162: 211-232.

Aspinall, R.; (1992). An inductive modeling procedure based on Bayes Theorem for analysis of pattern in spatial data. Geographical Information Systems; 6: 105-121.

Browning, D. M.; Beaupr, S. J.; Duncan, L.; (2005). Using partitioned Mahalanobis D2(K) to formulate a GIS-based model of timber rattlesnake hibernacula. Journal of Wildlife Management; 69: 33-44.

Browning, D.M.; Beaupr, S.J.; Duncan, L.; (2005). Using partitioned Mahalanobis D2(K) to formulate a GIS-based model of timber rattlesnake hibernacula. Journal of Wildlife Management; 69: 33-44.

Busby, J.R.; (1991). BIOCLIM–a bioclimate analysis and prediction system. In: Nature Conservation: Cost Effective Biological Surveys and Data Analysis (eds Margules, C.R. and Austin, M.P.). CSIRO, Melbourne, 64-68 pp.

Busby, J.R.; (1991). BIOCLIM–a bioclimate analysis and prediction system. In: Nature Conservation: Cost Effective Biological Surveys and Data Analysis (eds Margules, C.R. and Austin, M.P.). CSIRO, Melbourne, 64-68 pp.

Carey, P.D.; (1996). DISPERSE: a cellular automaton for predicting the distribution of species in a changed climate. Global Ecology and Biogeography Letter; 5: 217-226.

Carpenter, G.; Gillison, A.N.; Winter, J.; (1993). DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals. Biodivers. Conservation; 2: 667-680.

Clark, J.D.; (1993). A multivariate model of female Black Bear habitat use for a geographic information system. Journal of Wildlife Management; 57(3): 519-526.

Clark, J.S.; (1991) Disturbance and tree life history on the shifting mosaic landscape. Ecology; 72: 1102-1118.

Costa, J.; Peterson, T.; Beard, C.B.; (2002). Ecologic niche modeling and differentiation of populations of Triatoma brasiliensis neiva, 1911, the most important chagas, disease vector in northeastern Brazil (Hemiptra, Reduviidae, Triatominae). Tropical Medicine and Hygiene; 67(5): 516-520.

Decoursey, D.G.; (1992). Developing models with more detail: do more algorithms give more truth? Weed Technology; 6: 709-715.

Dunn, J.E.; Duncan, L.; (2000). Partitioning Mahalanobis D2 to sharpen GIS classificaton. In: Management Information Systems 2000: GIS and Remote Sensing (eds Brebbia CA, Pascolo P), 195-204. WIT Press, Southampton.

Ferrier, S.; Drielsma, M.; Manion, G.; Watson, G.; (2002). Extended statistical approaches to modelling spatial pattern in biodiversity in north-east New South Wales. II. Communitylevel modelling. Biodivers. Conservation; 11: 2309-2338.

Griffin, S.C.; Taper, M.L.; Hoffman, R.; Mills, L.S.; (2010). Ranking Mahalanobis distance models for predictions of occupancy from presence-only data. Journal of Wildlife Management; 74(5): 1112-1121

Grinnell, J.; (1917). The niche-relationships of the California thrasher, Auk. 427-433.

Guisan, A.; Zimmermann, N.E.; (2000). Predictive habitat distribution models in ecology. Ecological Modelling; 135: 147-186.

Harrell, F.E.; Lee, K.L.; Mark, D.B.; (1996). Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat. Med.; 15: 361-387.

Hijmans, R.J.; Guarino, L.; Cruz, M.; Rojas, E.; (2001). Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant Genetic Resources Newsletter; 127: 15-19.

Hirzel, A.H.; Hausser, J.; Chessel, D.; Perrin, N.; (2002). Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology; 83(7): 2027-2036.

Hirzel, A.H.; Helfer, V.; Métral, F.; (2001). Assessing habitat-suitability models with a virtual species. Ecological Modelling; 145(2): 111-121.

Hirzel, A.H.; Le Lay, G.; (2008). Habitat suitability modelling and niche theory. Applied Ecology; 45: 1372-1381.

Hirzel, A.H.; Posse, B.; Oggier, P.A.; Crettenand, Y.; Glenz, C.; Arlettaz, R.; (2004). Ecological requirements of a reintroduced species, with implications for release policy: the bearded vulture recolonizing the Alps. Journal of Applied Ecology; 41: 1103-1116.

Korzukhin, M.D.; Ter-Mikaelian, M.T.; Wagner, R.G.; (1996). Process versus empirical models: which approach for forest ecosystem management? Forest Research; 26: 879-887.

Lehmann, A.; Overton, J.M.; Leathwick, J.R.; (2002). GRASP: generalized regression analysis and spatial prediction. Ecological. Modelling; 157: 189-207.

Levins, R.; (1966). The strategy of model building in population ecology, American Scientist; 421: 421-431.

Nix, H.; McMahon, J.; Mackenzie, D.; (1977). Potential areas of production and the future of pigeon pea and other grain legumes in Australia. In: The potential for pigeon pea in Australia. Proceedings of Pigeon Pea (Cajanus cajan (L.) Millsp.) Field Day. (Eds: Wallis, E.S., Whiteman, P.C.). University of Queensland. Queensland. Australia. 5/1–5/12.

Pearson, R.G.; Dawson, T.P.; Berry, P.M.; Harrison, P.A.; (2002). SPECIES: a spatial evaluation of climate impact on the envelope of species. Ecological Modelling; 154: 289-300.

Peterson, A. T.; Cohoon, K. P.; (1999). Sensitivity of distributional prediction algorithms to geographic data completeness, Ecological Modelling; 117: 159-164.

Peterson, A. T.; Stockwell, D. R. B.; Kluza, D. A.; (2002). Distributional prediction based on ecological niche modeling of primary occurrence data. In: Scott, J. M., P. J. Heglund., M. L. Morrison, J.B. Haufler., M. G. Raphael., W. A. Wall and F. B. Samson, Editors, Predicting Species Occurrences. Issues of Accuracy and Scale, Island Press, Washington, 617-623.

Peterson, A.T.; Lash, R.R.; Carroll, D.S.; Johnson, K.M.; (2006). Geographic potential for outbreaks of Marburg hemorrhagic fever. American Journal of Tropical Medicine and Hygiene; 75(1): 9-15.

Peterson, A.T.; Lash, R.R.; Carroll, D.S.; Johnson, K.M.; (2006). Geographic potential for outbreaks of Marburg hemorrhagic fever. American Journal of Tropical Medicine and Hygiene; 75(1): 9-15.

Phillips, S.J.; Anderson, R.P.; Schapired, R.E.; (2006). Maximum entropy modelling of species geographic distributions. Ecological Modelling; 190: 231-259.

Pickett, S.T.A.; Kolasa, G.; Jones, C.G.;  (1994). Ecological Understanding: the Nature of Theory and the Theory of Nature. Academic Press, New York.

Prentice, I.C.; (1986). Some concepts and objectives of forest dynamics research. In: Fanta, J. (Ed.), Forest Dynamics Research in Western and Central Europe. PUDOC, Wageningen, 32-41.

Rotenberry, J.T.; Knick, S.T.; Dunn, J.E.; (2002). A minimalist approach to mapping species' habitat: Pearson's planes of closest fit. Pages 281-289 in Scott, J. M., Heglund, P. J., Morrison, M. L., Haufler, J. B., Raphael, M. G., Wall, W. A., Samson, F. B. editors. Predicting species occurrences: issues of accuracy and scale. Island Press, Washington, D.C., USA.

Rotenberry, J.T.; Knick, S.T.; Dunn, J.E.; (1999). A minimalist approach to mapping species habitat: Pearson's planes of closest fit. Predicting Species Occurrence: Issues of Scale and Accuracy, conference, Snowbird, Utah.

Rushton, S.P.; Ormerod, S.J.; Kerby, G.; (2004). New paradigms for modeling species distributions? Journal of Applied Ecology; 41(2): 193-200.

Sharpe, P.J.A.; (1990). Forest modeling approaches: compromises between generality and precision. In: Process Modeling of Forest Growth Responses to Environmental Stress. (Eds: Dixon, R.K., Meldahl, R.S., Ruark, G.A., Warren, W.G.). Timber Press, Portland, OR. 180-190.

Sharpe, P.J.A.; Rykiel, E.J.; (1991). Modeling integrated response of plants to multiple stress. In: Response of Plants to Multiple Stress. (Eds: Mooney, H.A., Winner, W.E., Pell, E.J.). Academic Press, San Diego, CA. 205-224.

Stockwell, D.; Noble, I. R.; (1991). Induction of sets of rules from animal distribution data: a robust and informative method of data analysis, Mathematics and Computers in Simulation; 32: 249-254.

Stockwell, D.; Peters, D.; (1999). The GARP modelling system: problems and solutions to automated spatial prediction, Geographic Information Systems; 13: 143-158.

Stockwell, D.; Peterson, A.T.; (2002). Effects of sample size on accuracy of species distribution models, Ecolgical Modelling; 148: 1-13.

Strubbe, D.; Matthysen, E.; (2009). Predicting the potential distribution of invasive ring-necked parakeets Psittacula krameri in northern Belgium using an ecological niche modelling approach. Biological Invasions; 11: 497-513.

Termansen, M.; McClean, C. J.; Preston, C.D.; (2006). The use of genetic algorithms and Bayesian classification to model species distribution, Ecological Modelling; 192: 410-424.

Von Humboldt, A.; Bonpland, A.; (1807). Essai sur la ge´ographie des plantes. Paris.

Zimmermann, N.E.; Kienast, F.; (1999). Predictive mapping of alpine grasslands in Switzerland: species versus community approach. Journal of Vegetation Science; 10: 469-482.