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Trait-based approaches to global change ecology: moving from description to prediction

Proceedings of the Royal Society. B, Biological sciences, 2022-03, Vol.289 (1971), p.20220071-20220071 [Peer Reviewed Journal]

2022 The Authors. 2022 ;ISSN: 0962-8452 ;EISSN: 1471-2954 ;DOI: 10.1098/rspb.2022.0071 ;PMID: 35291837

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  • Title:
    Trait-based approaches to global change ecology: moving from description to prediction
  • Author: Green, Stephanie J ; Brookson, Cole B ; Hardy, Natasha A ; Crowder, Larry B
  • Subjects: Review
  • Is Part Of: Proceedings of the Royal Society. B, Biological sciences, 2022-03, Vol.289 (1971), p.20220071-20220071
  • Description: Trait-based approaches are increasingly recognized as a tool for understanding ecosystem re-assembly and function under intensifying global change. Here we synthesize trait-based research globally ( = 865 studies) to examine the contexts in which traits may be used for global change prediction. We find that exponential growth in the field over the last decade remains dominated by descriptive studies of terrestrial plant morphology, highlighting significant opportunities to expand trait-based thinking across systems and taxa. Very few studies (less than 3%) focus on predicting ecological effects of global change, mostly in the past 5 years and via singular traits that mediate abiotic limits on species distribution. Beyond organism size (the most examined trait), we identify over 2500 other morphological, physiological, behavioural and life-history traits known to mediate environmental filters of species' range and abundance as candidates for future predictive global change work. Though uncommon, spatially explicit process models-which mechanistically link traits to changes in organism distributions and abundance-are among the most promising frameworks for holistic global change prediction at scales relevant for conservation decision-making. Further progress towards trait-based forecasting requires addressing persistent barriers including (1) matching scales of multivariate trait and environment data to focal processes disrupted by global change, and (2) propagating variation in trait and environmental parameters throughout process model functions using simulation.
  • Publisher: England: The Royal Society
  • Language: English
  • Identifier: ISSN: 0962-8452
    EISSN: 1471-2954
    DOI: 10.1098/rspb.2022.0071
    PMID: 35291837
  • Source: PubMed Central
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