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考虑景观异质性可提高树木对干旱脆弱性的空间预测精度。

Accounting for landscape heterogeneity improves spatial predictions of tree vulnerability to drought.

机构信息

Nicholas School of the Environment, Duke University, Box 90328, Durham, NC, 27708, USA.

Department of Civil and Environmental Engineering, Duke University, Box 90287, Durham, NC, 27708, USA.

出版信息

New Phytol. 2018 Oct;220(1):132-146. doi: 10.1111/nph.15274. Epub 2018 Jul 5.

Abstract

As climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability varies regionally and locally through landscape position. Also, most models used in forecasting forest responses to heat and drought do not incorporate relevant spatial processes. In order to improve spatial predictions of tree vulnerability, we employed a nonlinear stochastic model of soil moisture dynamics accounting for landscape differences in aspect, topography and soils. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei, and projected future dynamic water stress through the 21 century. Modeled dynamic water stress tracked spatial patterns of remotely sensed drought-induced canopy loss. Accuracy in predicting drought-impacted stands increased from 60%, accounting for spatially variable soil conditions, to 72% when also including lateral redistribution of water and radiation/temperature effects attributable to aspect. Our analysis also suggests that dynamic water stress will increase through the 21 century, with trees persisting at only selected microsites. Favorable microsites/refugia may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of an heterogeneous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.

摘要

随着气候变化的持续,森林对干旱和热浪的脆弱性正在增加,但脆弱性因景观位置的不同而在区域和局部有所差异。此外,预测森林对高温和干旱的响应的大多数模型都没有纳入相关的空间过程。为了提高树木脆弱性的空间预测,我们采用了一种土壤湿度动态的非线性随机模型,该模型考虑了地形、地貌和土壤方面的景观差异。在德克萨斯州中部的一个流域,我们对一种主要树种——蓝杉(Juniperus ashei)的动态水分胁迫进行了建模,并通过 21 世纪预测了未来的动态水分胁迫。模型化的动态水分胁迫追踪了遥感干旱导致树冠损失的空间模式。在考虑了空间变化的土壤条件后,预测干旱影响林分的准确率从 60%提高到 72%,而当包括归因于方位的水分侧向再分配以及辐射/温度效应时,准确率提高到 72%。我们的分析还表明,动态水分胁迫将在 21 世纪增加,只有在选定的微生境中树木才能存活。在树木能够存活的景观中可能存在有利的微生境/避难所;然而,如果未来的干旱太严重,异质景观的缓冲能力可能会被淹没。纳入空间数据将提高对未来树木水分胁迫的预测,并确定潜在的有弹性的避难所。

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