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基于最大熵模型预测青藏高原紫芒的分布。

Predicting the distribution of Stipa purpurea across the Tibetan Plateau via the MaxEnt model.

机构信息

Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Roadm, Chaoyang District, Beijing, 100101, China.

School of Earth Science and Resource, Chang'an University, Xi'an, 710000, China.

出版信息

BMC Ecol. 2018 Feb 21;18(1):10. doi: 10.1186/s12898-018-0165-0.

Abstract

BACKGROUND

The ecosystems across Tibetan Plateau are changing rapidly under the influence of climate warming, which has caused substantial changes in spatial and temporal environmental patterns. Stipa purpurea, as a dominant herbsage resource in alpine steppe, has a great influence on animal husbandry in the Tibetan Plateau. Global warming has been forecasted to continue in the future (2050s, 2070s), questioning the future distribution of S. purpurea and its response to climate change. The maximum entropy (MaxEnt) modeling, due to its multiple advantages (e.g. uses presence-only data, performs well with incomplete data, and requires small sample sizes and gaps), has been used to understand species environment relationships and predict species distributions across locations that have not been sampled.

RESULTS

Annual mean temperature, annual precipitation, temperature seasonality, altitude, and precipitation during the driest month, significantly affected the distribution of S. purpurea. Only 0.70% of the Tibetan Plateau area included a very highly suitable habitat (habitat suitability [HS] = 0.8-1.0). Highly suitable habitat (HS = 0.6-0.8), moderately suitable habitat (HS = 0.4-0.6), and unsuitable habitat (HS = 0.2-0.4) occupied 6.20, 14.30 and 22.40% of the Tibetan Plateau area, respectively, and the majority (56.40%) of the Tibetan Plateau area constituted a highly unsuitable habitat (HS = 0-0.2). In addition, the response curves of species ecological suitability simulated by generalized additive model nearly corresponded with the response curves generated by the MaxEnt model.

CONCLUSIONS

At a temporal scale, the habitat suitability of S. purpurea tends to increase from the 1990s to 2050s, but decline from the 2050s to 2070s. At a spatial scale, the future distribution of S. purpurea will not exhibit sweeping changes and will remain in the central and southeastern regions of the Tibetan Plateau. These results benefit the local animal husbandry and provide evidence for establishing reasonable management practices.

摘要

背景

受气候变暖影响,青藏高原生态系统变化迅速,导致时空环境格局发生了重大变化。作为高寒草原的主要草本资源,紫花针茅对青藏高原畜牧业有很大影响。据预测,未来(2050 年代、2070 年代)全球气温将继续上升,这对紫花针茅的未来分布及其对气候变化的响应提出了质疑。最大熵(MaxEnt)模型由于具有多种优势(例如,仅使用存在数据,在数据不完全的情况下表现良好,并且需要较小的样本量和差距),已被用于了解物种与环境的关系,并预测未采样地点的物种分布。

结果

年平均气温、年降水量、温度季节性、海拔和最干旱月降水量显著影响了紫花针茅的分布。仅有 0.70%的青藏高原地区属于极适宜生境(生境适宜度[HS] = 0.8-1.0)。高度适宜生境(HS = 0.6-0.8)、中度适宜生境(HS = 0.4-0.6)和不适宜生境(HS = 0.2-0.4)分别占青藏高原地区的 6.20%、14.30%和 22.40%,而大部分(56.40%)青藏高原地区属于极不适宜生境(HS = 0-0.2)。此外,广义加性模型模拟的物种生态适宜性响应曲线与 MaxEnt 模型生成的响应曲线几乎一致。

结论

在时间尺度上,紫花针茅的生境适宜度从 1990 年代到 2050 年代趋于增加,但从 2050 年代到 2070 年代则下降。在空间尺度上,紫花针茅的未来分布不会发生巨大变化,仍将集中在青藏高原的中南部地区。这些结果有利于当地畜牧业的发展,并为制定合理的管理措施提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6451/5822641/d9df141c3fa2/12898_2018_165_Fig1_HTML.jpg

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