Data from: Predicting range shifts of the giant pandas under future climate and land use scenarios

Aim: Understanding and predicting how species will respond to
global environmental change (i.e., climate and land use change) is
essential to efficiently inform conservation and management strategies for
authorities and managers. Here, we assessed the combined effect of future
climate and land use change on the potential range shifts of the giant
pandas (Ailuropoda melanoleuca).  Location: Sichuan
Province, China. Methods: We used ensemble species distribution
models (SDMs) to forecast range shifts of the giant pandas by the 2050s
and 2070s under four combined climate and land use change scenarios. We
also compared the differences in distributional changes
of giant pandas among the five mountains in the study area. 
Results: Our ensemble SDMs exhibited good model performance in
terms of both AUC (0.931) and TSS (0.747), and suggested that
precipitation seasonality, annual mean temperature, the proportion of
forest cover and total annual precipitation are the most important factors
in shaping the current distribution patterns for the giant pandas. Our
projections of future species distribution also suggested a range
expansion under an optimistic greenhouse gas emission, while suggesting a
range contraction under a pessimistic greenhouse gas emission. Moreover,
we found that there is considerable variation in the projected range
change patterns among the five mountains in the study area. Especially,
the suitable habitat of the giant panda is predicted to increase under all
scenarios in Minshan mountains, while is predicted to decrease under all
scenarios in Daxiangling and Liangshan mountains, indicating the
vulnerability of the giant pandas at low latitudes.  Main
conclusions: Our findings highlight the importance of an
integrated approach that combines climate and land use change to predict
the future species distribution and the need for a spatial explicit
consideration of the projected range change patterns of target species for
guiding conservation and management strategies.

研究目的：理解并预测物种对全球环境变化（即气候变化与土地利用变化）的响应规律，可为管理当局与决策者制定高效的保护与管理策略提供核心依据。本研究聚焦大熊猫（Ailuropoda melanoleuca），评估未来气候变化与土地利用变化对其潜在分布区迁移的综合影响。
研究区域：中国四川省。
研究方法：本研究采用集成物种分布模型（ensemble species distribution models, SDMs），在四种气候变化与土地利用变化组合情景下，预测21世纪50年代与70年代大熊猫的分布区变化情况。同时对比分析研究区内五大山系间大熊猫分布变化的差异。
研究结果：本研究构建的集成物种分布模型在AUC（曲线下面积，0.931）与TSS（真实技能统计量，0.747）两项指标上均表现出优异的模型性能。结果表明，降水季节性、年平均气温、森林覆盖率与年总降水量是塑造大熊猫当前分布格局的关键环境因子。未来分布预测结果显示，在乐观温室气体排放情景下，大熊猫的适宜分布区将出现扩张；而在悲观温室气体排放情景下，适宜分布区则会发生收缩。此外，研究区内五大山系的预测分布变化模式存在显著差异：岷山（Minshan）山系的大熊猫适宜栖息地在所有情景下均呈扩张趋势，而大相岭（Daxiangling）山系与凉山（Liangshan）山系的适宜栖息地在所有情景下均呈缩减趋势，这表明低纬度分布的大熊猫种群面临更高的生存脆弱性。
主要结论：本研究结果凸显了整合气候变化与土地利用变化因素以预测物种未来分布的重要性，同时强调在制定保护与管理策略时，需充分考量目标物种的空间显性分布变化模式，以提升策略的针对性与实操性。