Predicting Impacts of Climate Change on Teak and Sal Forests in Central India Using Maximum Entropy Modeling: an Approach for Future Conservation and Silvicultural Strategies

IF 1.5 4区 农林科学 Q2 FORESTRY Forest Science Pub Date : 2023-04-15 DOI:10.1093/forsci/fxad014
Maneesh Kumar Patasaraiya, Rinku Moni Devi, Bhaskar Sinha, Jigyasa Bisaria
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引用次数: 2

Abstract

Climate change impacts on tropical forests and tree species have been documented as changes in distribution, growing period, phenology, habitat, productivity, species composition, and migration. This study attempts to assess the current and future habitat suitability distribution of two dominant species of Central India, teak (Tectona grandis Linn. f.) and sal (Shorea robusta Gaertn. f.) using a maximum entropy (MaxEnt) model to predict species occurrences by finding the distribution that has the most spread. The future suitable habitat ranges of the species were modeled for two time periods (2050 and 2070) and two representative concentration pathways (RCP 2.6 and 8.5). Representative concentration pathways are scenarios that describe alternative trajectories for carbon dioxide emissions and the resulting atmospheric concentration from 2000 to 2100. We collected and modeled the spatially well-dispersed species occurrence points of teak and sal. The results suggested an increase in suitable habitat range for teak and a decrease for sal for both time periods and RCPs. Furthermore, the jackknife analysis identified temperature and precipitation seasonality as the major variables that influence the distribution of teak. In the case of sal, minimum temperature makes the maximum contribution to distribution changes. The suitable silvicultural strategies for forest management are proposed based on the future distribution of species in relation to the climate variables responsible for the change in their distribution range. These findings and strategies will help forest departments build future management plans for teak and sal forest with a focus on minimizing the impact of climate change. Study Implications: Our study used maximum entropy (MaxEnt) modeling to understand the impact of changing climate on the distribution of teak and sal forests of central India and to propose future silvicultural strategies. The study used MaxEnt model for two time periods and two climate change scenarios at highest resolution. An increase in future suitable habitat for teak and a decrease for sal is predicted by the model. Temperature for teak and precipitation for sal were identified as the major influencing climatic variables. We recommend forest and other related government departments to commission focused research to understand the changing patterns of species with climate change and design appropriate silviculture strategies for effective management.
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利用最大熵模型预测气候变化对印度中部柚木和萨尔林的影响:一种未来保护和造林策略的方法
气候变化对热带森林和树种的影响主要表现在分布、生长期、物候、生境、生产力、物种组成和迁移等方面。本研究试图评估印度中部两种优势物种柚木(Tectona grandis Linn)的当前和未来生境适宜性分布。f.)和sal (Shorea robusta Gaertn.)f)使用最大熵(MaxEnt)模型,通过找到传播最广的分布来预测物种的出现。在2050年和2070年两个时间段和两个具有代表性的浓度路径(RCP 2.6和8.5)下,模拟了该物种未来的适宜生境范围。代表性浓度路径是描述2000年至2100年二氧化碳排放和由此产生的大气浓度的备选轨迹的情景。我们收集了柚木和咸鱼在空间上分布良好的物种分布点并建立了模型。结果表明,在不同的时间段和不同的rcp下,柚木的适宜生境范围有所增加,而小柚木的适宜生境范围有所减少。此外,叠刀分析还发现温度和降水季节性是影响柚木分布的主要变量。在盐的情况下,最低温度对分布变化的贡献最大。根据造成物种分布范围变化的气候变量对物种未来分布的影响,提出了适合森林管理的造林策略。这些发现和战略将有助于森林部门制定未来的柚木和小森林管理计划,重点是尽量减少气候变化的影响。研究意义:我们的研究使用最大熵(MaxEnt)模型来了解气候变化对印度中部柚木和盐林分布的影响,并提出未来的造林策略。该研究使用MaxEnt模型对两个时间段和两个气候变化情景进行了最高分辨率的模拟。该模型预测未来适宜柚木生长的生境将增加,适宜盐碱生长的生境将减少。对柚木的温度和对盐的降水被确定为主要的影响气候变量。我们建议森林和其他相关政府部门开展重点研究,以了解物种随气候变化的变化模式,并设计适当的造林策略,以实现有效的管理。
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来源期刊
Forest Science
Forest Science 农林科学-林学
CiteScore
2.80
自引率
7.10%
发文量
45
审稿时长
3 months
期刊介绍: Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management. Forest Science is published bimonthly in February, April, June, August, October, and December.
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