Amplified plant turnover in response to climate change forecast by Late Quaternary records

Research output: Contribution to journalLetterResearchpeer-review

David Bravo Nogues, S. Veloz, Benjamin George Holt, J. Singarayer, P. Valdes, B. Davis, S. C. Brewer, J. W. Williams, Carsten Rahbek

Conservation decisions are informed by twenty-first-century climate impact projections that typically predict high extinction risk. Conversely, the palaeorecord shows strong sensitivity of species abundances and distributions to past climate changes, but few clear instances of extinctions attributable to rising temperatures. However, few studies have incorporated palaeoecological data into projections of future distributions. Here we project changes in abundance and conservation status under a climate warming scenario for 187 European and North American plant taxa using niche-based models calibrated against taxa-climate relationships for the past 21,000 years. We find that incorporating long-term data into niche-based models increases the magnitude of projected future changes for plant abundances and community turnover. The larger projected changes in abundances and community turnover translate into different, and often more threatened, projected IUCN conservation status for declining tree taxa, compared with traditional approaches. An average of 18.4% (North America) and 15.5% (Europe) of taxa switch IUCN categories when compared with single-time model results. When taxa categorized as ' Least Concern' are excluded, the palaeo-calibrated models increase, on average, the conservation threat status of 33.2% and 56.8% of taxa. Notably, however, few models predict total disappearance of taxa, suggesting resilience for these taxa, if climate were the only extinction driver. Long-term studies linking palaeorecords and forecasting techniques have the potential to improve conservation assessments.

Original languageEnglish
JournalNature climate change
Volume6
Issue number12
Pages (from-to)1115-1119
Number of pages5
ISSN1758-678X
DOIs
Publication statusPublished - 2016

ID: 173502774