Department of Botany, University of Kashmir, Srinagar, Jammu and Kashmir, India.
Central Himalayan Environment Association, Dehradun, India.
Environ Monit Assess. 2022 Jul 21;194(9):596. doi: 10.1007/s10661-022-10245-y.
Reliable predictions of future distribution ranges of ecologically important species in response to climate change are required for developing effective management strategies. Here we used an ensemble modelling approach to predict the distribution of three important species of Abies namely, Abies pindrow, Abies spectabilis and Abies densa in the Hindu Kush Himalayan region under the current and two shared socioeconomic pathways (SSP245 and SSP585) and time periods of 2050 and 2090s. A correlative ensemble model using presence/absence data of the three Abies species and 22 environmental variables, including 19 bioclimatic variables and 3 topographic variables, from known distributions was built to predict the potential current and future distribution of these species. The individual models used to build the final ensemble performed well and provided reliable results for both the current and future distribution of all three species. For A. pindrow, precipitation of the driest month (Bio14) was the most important environmental variable with 83.3% contribution to model output while temperature seasonality (Bio4) and annual mean diurnal range (Bio2) were the most important variables for A. spectabilis and A. densa with 48.4% and 46.1% contribution to final model output, respectively. Under current climatic conditions, the ensemble models projected a total suitable habitat of about 433,003 km, 790,837 km and 676,918 km for A. pindrow, A. spectabilis and A. densa, respectively, which is approximately 10.36%, 18.91% and 16.91% of the total area of Hindu Kush Himalayan region. Projections of habitat suitability under future climate scenarios for all the shared socioeconomic pathways showed a reduction in potentially suitable habitats with a maximum overall loss of approximately 14% of the total suitable area of A. pindrow under SSP 8.5 by 2090. A decline in total suitable habitat is predicted to be 9.6% in A. spectabilis by 2090 under the SSP585 scenario while in A. densa 6.67% loss in the suitable area is expected by 2050 under the SSP585 scenario. Furthermore, there is no elevational change predicted in the case of A. pindrow while A. spectabilis is expected to show an upward shift by about 29 m per decade and A. densa is showing a downward shift at a rate of 11 m per decade. The results are interesting, and intriguing given the occurrence of these species across the Hindu Kush Himalayan region. Thus, our study underscores the need for consideration of unexpected responses of species to climate change and formulation of strategies for better forest management and conservation of important conifer species, such as A. pindrow, A. spectabilis and A. densa.
为了制定有效的管理策略,需要对生态重要物种未来的分布范围进行可靠的预测,以应对气候变化。在这里,我们使用集合建模方法来预测喜玛拉雅山脉地区三种重要的冷杉物种,即白皮松、川西云杉和苍山冷杉,在当前和两种共享社会经济路径(SSP245 和 SSP585)以及 2050 年和 2090 年两个时期的分布情况。使用三种冷杉物种的存在/缺失数据和 22 个环境变量(包括 19 个生物气候变量和 3 个地形变量)构建了一个相关的集合模型,用于预测这些物种的潜在当前和未来分布。用于构建最终集合的单个模型表现良好,为所有三种物种的当前和未来分布提供了可靠的结果。对于白皮松,最干燥月份的降水量(Bio14)是对模型输出贡献最大的环境变量,占 83.3%;而对于川西云杉和苍山冷杉,温度季节性(Bio4)和年平均日较差(Bio2)是最重要的变量,分别占最终模型输出的 48.4%和 46.1%。在当前气候条件下,集合模型预测白皮松、川西云杉和苍山冷杉的总适宜栖息地分别约为 433003、790837 和 676918 平方公里,分别约占喜玛拉雅山脉地区总面积的 10.36%、18.91%和 16.91%。所有共享社会经济路径的未来气候情景下的栖息地适宜性预测显示,潜在适宜栖息地减少,到 2090 年,白皮松在 SSP8.5 下总适宜面积最大损失约 14%。到 2090 年,在 SSP585 情景下,川西云杉的总适宜栖息地预计将减少 9.6%,而在 SSP585 情景下,苍山冷杉的适宜面积预计将减少 6.67%。此外,白皮松的海拔没有变化预测,而川西云杉预计每十年上升约 29 米,苍山冷杉则以每年 11 米的速度下降。考虑到这些物种在喜玛拉雅山脉地区的存在,这些结果是有趣和引人关注的。因此,我们的研究强调了需要考虑物种对气候变化的意外反应,并制定更好的森林管理和保护重要针叶树种(如白皮松、川西云杉和苍山冷杉)的战略。