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气候与生态恢复力
发表日期: 2015-07-13 作者: Adam M. Wilson 文章来源:《PNAS 》
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科研人员报告了一种为气候对生态系统恢复力的影响建模的方法。一个生态系统在诸如火灾等扰动之后回到它之前的状态的能力与这个系统从这类扰动中恢复的速度密切相关。Adam Wilson及其同事使用过去15年的卫星照片,追踪了南非弗洛勒尔角灌木林地在火灾之后的恢复。恢复的速率和重新获得的生物质数量都随着夏季降水、冬季温度以及土壤肥力的增加而增加。这组作者使用这些结果估计了各种气候模型下的未来恢复率。这些模型都预测了冬季温度将会变得更暖,这很可能倾向于增加恢复率。然而,某些模型还预测了降水下降,特别是在该地区的西部,这很可能倾向于减缓恢复率和抵消变暖的效应。低恢复率可能通过燃料的缺乏以及把这个生态系统从灌木林地转向半沙漠植被而减少火灾频率。这组作者说,这种方法可能用于为全球尺度上的气候对生态系统恢复力的影响进行建模。(来源:生物360))

 

Climatic controls on ecosystem resilience: postfire regeneration in the Cape Floristic Region of South Africa

 

Abstract  Conservation of biodiversity and natural resources in a changing climate requires understanding what controls ecosystem resilience to disturbance. This understanding is especially important in the fire-prone Mediterranean systems of the world. The fire frequency in these systems is sensitive to climate, and recent climate change has resulted in more frequent fires over the last few decades. However, the sensitivity of postfire recovery and biomass/fuel load accumulation to climate is less well understood than fire frequency despite its importance in driving the fire regime. In this study, we develop a hierarchical statistical framework to model postfire ecosystem recovery using satellite-derived observations of vegetation as a function of stand age, topography, and climate. In the Cape Floristic Region (CFR) of South Africa, a fire-prone biodiversity hotspot, we found strong postfire recovery gradients associated with climate resulting in faster recovery in regions with higher soil fertility, minimum July (winter) temperature, and mean January (summer) precipitation. Projections using an ensemble of 11 downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) suggest that warmer winter temperatures in 2080–2100 will encourage faster postfire recovery across the region, which could further increase fire frequency due to faster fuel accumulation. However, some models project decreasing precipitation in the western CFR, which would slow recovery rates there, likely reducing fire frequency through lack of fuel and potentially driving local biome shifts from fynbos shrubland to nonburning semidesert vegetation. This simple yet powerful approach to making inferences from large, remotely sensed datasets has potential for wide application to modeling ecosystem resilience in disturbance-prone ecosystems globally.

 

原文链接:http://www.pnas.org/content/early/2015/07/01/1416710112.full.pdf

 


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