In recent years, global climate change has had significant biological, temporal, and spatial effects on many terrestrial habitats. The objective of this study was to evaluate the effect of climate change on the geographic distribution of Juniperus excelsa and prioritize its habitats for protection against these effects until 2070. The study was conducted using the MaxEnt species distribution model and two data series GFDL-CM3 and MRI-CGCM3 under scenarios RCP2.6 and RCP4.5 of the 5th IPCC report. Our results revealed that elevation, minimum temperature of coldest month, precipitation of coldest quarter, annual mean temperature, and slope aspect, in that order, have the greatest effects on the species’ distribution in the study area. Under optimistic scenario RCP2.6, both models predicted that the species’ presence area will grow, but under RCP4.5, models predicted that by 2070, some parts of its habitat in western and central heights will be lost because of change in climate parameters like minimum temperature of coldest month and precipitation of coldest quarter. Under the latter scenario, the northeastern parts of the study area showed no changes in terms of climatic parameters and climatic niche. The results of both climate data series indicated that the Juniperus excelsa will slowly migrate to higher elevations to cope with the changing climate. Assessment of the results through field studies showed that outputs of GFDL-CM3 are closer to the reality.
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Citation
Fatemi SS, Rahimi M, Tarkesh M, Ravanbakhsh H (2018). Predicting the impacts of climate change on the distribution of Juniperus excelsa M. Bieb. in the central and eastern Alborz Mountains, Iran. iForest 11: 643-650. - doi: 10.3832/ifor2559-011
Academic Editor
Paolo Cherubini
Paper history
Received: Jul 19, 2017
Accepted: Jul 22, 2018
First online: Oct 04, 2018
Publication Date: Oct 31, 2018
Publication Time: 2.47 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2018
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This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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