4.5 Article

HISTORICAL ECOLOGY: USING UNCONVENTIONAL DATA SOURCES TO TEST FOR EFFECTS OF GLOBAL ENVIRONMENTAL CHANGE

Journal

AMERICAN JOURNAL OF BOTANY
Volume 100, Issue 7, Pages 1294-1305

Publisher

BOTANICAL SOC AMER INC
DOI: 10.3732/ajb.1200503

Keywords

climate change; colonization; extinction debt; habitat fragmentation; herbarium specimens; historical ecology; land surveys; maps; repeat photography; time lags

Categories

Funding

  1. Natural Sciences and Engineering Research Council, Canada

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Predicting the future ecological impact of global change drivers requires understanding how these same drivers have acted in the past to produce the plant populations and communities we see today. Historical ecological data sources have made contributions of central importance to global change biology, but remain outside the toolkit of most ecologists. Here we review the strengths and weaknesses of four unconventional sources of historical ecological data: land survey records, legacy vegetation data, historical maps and photographs, and herbarium specimens. We discuss recent contributions made using these data sources to understanding the impacts of habitat disturbance and climate change on plant populations and communities, and the duration of extinction-colonization time lags in response to landscape change. Historical data frequently support inferences made using conventional ecological studies (e. g., increases in warm-adapted species as temperature rises), but there are cases when the addition of different data sources leads to different conclusions (e. g., temporal vegetation change not as predicted by chronosequence studies). The explicit combination of historical and contemporary data sources is an especially powerful approach for unraveling long-term consequences of multiple drivers of global change. Despite the limitations of historical data, which include spotty and potentially biased spatial and temporal coverage, they often represent the only means of characterizing ecological phenomena in the past and have proven indispensable for characterizing the nature, magnitude, and generality of global change impacts on plant populations and communities.

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