Earth Systems and Environment最新文献

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Characterising Heatwave Responses and Climate Driver Impacts Using Multicollinearity-Controlled Generalised Linear Mixed Models in Urban and Forest Trees (2018-2023). 基于多重共线性控制广义线性混合模型的城市和森林树木热浪响应和气候驱动因素影响特征（2018-2023）

IF 4.7 Q1 ENVIRONMENTAL SCIENCES

Earth Systems and Environment

Pub Date : 2026-01-01 Epub Date: 2025-05-15 DOI: 10.1007/s41748-025-00648-5

Ramla Khan, Philip Wheeler, David Gowing

Climate change is intensifying stressors on tree ecosystems, creating an urgent need to understand how climate variables influence vegetation health. This study investigated the influence of leaf temperature, wind speed, surface pressure, and moisture levels on tree health in a deciduous forest at Aspley Heath and an urban area in Milton Keynes, UK, using the normalised difference vegetation index (NDVI) as a vegetation health indicator. Satellite data from 2018 to 2023 revealed multiple heatwave events, with leaf temperatures surpassing the critical thresholds of 38 °C and 42 °C, as determined through controlled experiments. Generalised linear mixed models (GLMMs) demonstrated strong interactions between climate variables and vegetation health. Increased leaf temperature was positively associated with NDVI in both ecosystems, though urban trees showed a weaker response (β = 0.32, 95% CI: 0.16-0.48, p < 0.001) compared to forest trees (β = 0.45, 95% CI: 0.35-0.55, p < 0.001), suggesting urban heat island effects limit thermal benefits. Since all predictors were standardised, these coefficients indicate that a 3.82 °C increase in leaf temperature corresponds to a 0.32 NDVI increase in urban areas and a 0.45 increase in forests, reflecting meaningful ecological responses to moderate warming. Wind speed had a consistently negative impact on NDVI, with stronger effects in urban areas (β = - 0.21, 95% CI: - 0.41 to - 0.02, p = 0.035) than in forests (β = - 0.17, 95% CI: - 0.29 to - 0.05, p = 0.004). Surface pressure showed positive associations with vegetation health (urban: β = 0.17, 95% CI: 0.03-0.31, p = 0.02; forest: β = 0.14, 95% CI: 0.04-0.24 p = 0.005), while moisture availability emerged as a critical factor, with forest trees displaying a stronger response (β = 0.39, 95% CI: 0.29-0.49, p < 0.001) compared to urban trees (β = 0.30, 95% CI: 0.20-0.40, p < 0.001). Additionally, time-lag analysis revealed that leaf temperature had both an immediate effect on NDVI (lag 0: β = 0.64, p < 0.001) and a smaller delayed influence the following day (lag + 1: β = 0.18, p < 0.001) on NDVI, highlighting short-term vegetation sensitivity to thermal stress. These findings highlight how urban and forest trees differ in their resilience to climate variables, emphasising the need for targeted environmental management strategies to mitigate climate-induced stressors and protect tree ecosystems.Graphical abstract: The graphical abstract provides a concise visual summary of the study, illustrating how climate variables impact tree health in contrasting urban and forest environments. Using satellite-derived NDVI data and Generalised Linear Mixed Models (GLMMs), the abstract displays the standardised effect sizes (β-values) for key leaf temperature, wind speed, surface pressure, and moisture availability predictors. Each climate variable is clearly labelled alongside its corresponding β coefficient to improve interpretabili

气候变化正在加剧对树木生态系统的压力，迫切需要了解气候变量如何影响植被健康。本研究使用归一化植被指数（NDVI）作为植被健康指标，调查了叶片温度、风速、地表压力和湿度水平对英国米尔顿凯恩斯市区阿斯普利希思（Aspley Heath）落叶林中树木健康的影响。2018年至2023年的卫星数据显示了多次热浪事件，通过对照实验确定的叶片温度超过了38°C和42°C的临界阈值。广义线性混合模型（glmm）表明气候变量与植被健康之间存在很强的相互作用。在两个生态系统中，叶温升高与NDVI呈正相关，但城市树木对NDVI的响应弱于森林（β = - 0.17, 95% CI: - 0.29 ~ - 0.05, p = 0.004）（β = - 0.32, 95% CI: 0.16 ~ 0.48, p = 0.41 ~ - 0.02, p = 0.035）。地表压力与植被健康呈正相关（城市：β = 0.17, 95% CI: 0.03-0.31, p = 0.02；森林：β = 0.14, 95% CI: 0.04-0.24 p = 0.005），而水分有效性则是一个关键因素，森林树木表现出更强的响应（β = 0.39, 95% CI: 0.29-0.49, p）。图摘要：图摘要提供了研究的简明视觉总结，说明了气候变量如何影响城市和森林环境下的树木健康。摘要利用卫星衍生的NDVI数据和广义线性混合模型（glmm），展示了关键叶温、风速、地表压力和水分有效性预测因子的标准化效应大小（β值）。为了提高可解释性，每个气候变量都与其相应的β系数一起被清楚地标记。叶温对两种生态系统的植被健康均有正向影响，其中森林（β = 0.45）的影响强于城市（β = 0.32）。同样，与城市地区（β = 0.30）相比，森林（β = 0.39）对水分有效性的影响更为显著。风速对树木健康产生负面影响，在城市环境中的影响（β = - 0.21）比在森林环境中的影响（β = - 0.17）更为明显。地表压力在两种环境中都表现出较小但积极的影响（城市：β = 0.17；森林：β = 0.14）。从森林一侧的冷蓝绿色到城市一侧的暖橙红色的渐变背景，以及蓝色和红色的温度计，分别代表了与温暖的城市地区相比，森林中更冷的环境。在热浪图和空间地图旁边，有一个温度计图标，上面显示着正在变暖的地球，从视觉上突出了极端高温事件。

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引用次数: 0

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Q1 ENVIRONMENTAL SCIENCES

Earth Systems and Environment

Pub Date : 2025-09-09 DOI: 10.1007/s41748-025-00789-7

Israr Masood ul Hasan, Bo Li, Niu Zhengrong, Dandan Gao, Yaoling Zhang, Xinqian Li, Muhammad Zubair Nawaz, Muhammad Ikram, Muhammad Irfan, Khalid Hussain, Hai‐Tao Feng