Determination of the probability of the occurrence of Iran life zones (an integration of binary logistic regression and geostatistics)
Paper Details
Determination of the probability of the occurrence of Iran life zones (an integration of binary logistic regression and geostatistics)
Abstract
The occurrence probability of the life zones of Iran including Hyrcanian humid forests, Zagros semiarid and humid forests, humid grasslands, semiarid scrub-grasslands, arid desert scrubs and arid deserts was determined using binary logistic regression. The environmental predictors in this study were elevation, mean annual precipitation, temperature, maximum and minimum temperature, relative humidity, and reference evapotranspiration. The occurrence of the life zones with the probability of 0-1, 0.2-1, 0.4-1, 0.6-1 and 0.8-1 was compared to the reference data using kappa coefficient and Z-statistic. Mean annual precipitation was the significant variable in determination of the presence probability of 5 out of 6 life zones followed by elevation and mean annual maximum temperature which were significant for predicting the occurrence probability of 4 life zones. The highest agreement between the predicted map and the reference map was related to the Hyrcanian humid forests and arid deserts. Continuously distributed life zones with no gap had the most accurate predicted presence, while the life zones which were discontinuously and sparsely distributed, had the lowest accurate predicted presence. The best agreement between the predicted data and the reference data for all the life zones was found for the occurrence probability of 0.2-1, and this range can be used as an efficient range of probability for comparing the predicted data and the reference data in vegetation and life zone modeling based on logistic regression.
Allen RG, Pereira LS, Raes D, Smith M. 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300, 6541.
Aspinall RJ. 2002. Use of logistic regression for validation of maps of the spatial distribution of vegetation species derived from high spatial resolution hyperspectral remotely sensed data. Ecological Modelling 157(2), 301-312.
Box EO. 1981. Predicting physiognomic vegetation types with climate variables. Vegetatio 45(2), 127-139.
Calef MP, David McGuire A, Epstein HE, Scott Rupp T, Shugart HH. 2005. Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach. Journal of Biogeography 32(5), 863-878.
Chakraborty A, Joshi PK, Ghosh A, Areendran G. 2013. Assessing biome boundary shifts under climate change scenarios in India. Ecological Indicators 34, 536-547.
Congalton RG, Green K. 2008. Assessing the accuracy of remotely sensed data: principles and practices. CRC press.
Diaz HF, Villalba R, Greenwood G, Bradley RS. 2006. The impact of climate change in the American Cordillera. Eos, Transactions American Geophysical Union 87(32), 315-315.
Franklin J. 1998. Predicting the distribution of shrub species in southern California from climate and terrain-derived variables. Journal of Vegetation Science 9, 733–748.
Guisan A, Weiss SB, Weiss AD. 1999. GLM versus CCA spatial modeling of plant species distribution. Plant Ecology 143, 107–122.
Holdridge LR. 1967. Life zone ecology. Life zone ecology., (rev. ed.)).
Javanshir K. 1976. Atlas of Woody Plants of Iran. National Society of Natural Resources and Human Environment Conservation, Tehran, Iran, 163 pp.
Landis JR, Koch GG. 1977. The measurement of observer agreement for categorical data. Biometrics 33, 159-174.
Lugo AE, Brown SL, Dodson R, Smith TS, Shugart HH. 1999. The Holdridge life zones of the conterminous United States in relation to ecosystem mapping. Journal of Biogeography 26(5), 1025-1038.
Rijt CWCJ, Hazelhoff L, Blom CWPM. 1996. Vegetation zonation in a former tidal area: A vegetation‐type response model based on DCA and logistic regression using GIS. Journal of Vegetation Science 7(4), 505-518.
Wohlgemuth T. 1998. Modeling floristic species richness on a regional scale: a case study in Switzerland. Biodiversity Conservation 7, 159–177.
Zimmermann NE, Kienast F. 1999. Predictive mapping of alpine grasslands in Switzerland: species versus community approach. Journal of vegetation Science 10, 469–482.
Mohammad Mousaei Sanjerehei (2014), Determination of the probability of the occurrence of Iran life zones (an integration of binary logistic regression and geostatistics); JBES, V4, N6, June, P408-417
https://innspub.net/determination-of-the-probability-of-the-occurrence-of-iran-life-zones-an-integration-of-binary-logistic-regression-and-geostatistics/
Copyright © 2014
By Authors and International
Network for Natural Sciences
(INNSPUB) https://innspub.net
This article is published under the terms of the
Creative Commons Attribution License 4.0