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Proc Natl Acad Sci U S A. 2015 Jul 21;112(29):9058-63. doi: 10.1073/pnas.1416710112. Epub 2015 Jul 6.

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

Author information

1
Department of Geography, University at Buffalo, Buffalo, NY 14261; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520-8106; Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06269; adamw@buffalo.edu.
2
Department of Plant Sciences, University of California, Davis, CA 95616.
3
Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06269;

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.

KEYWORDS:

climate; ecology; fire; hierarchical Bayesian; remote sensing

PMID:
26150521
PMCID:
PMC4517208
DOI:
10.1073/pnas.1416710112
[Indexed for MEDLINE]
Free PMC Article

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