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Predicting species and community responses to global change using structured expert judgement: An Australian mountain ecosystems case study

AbstractConservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which have already undergone recent changes in climate and experienced more frequent large‐scale bushfires. In lieu of empirical data, we use a structured expert elicitation method (the IDEA protocol) to estimate the change in abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species‐level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water‐centric life‐cycles are expected to decline in abundance than other species. While long‐term ecological data will always be the gold standard for informing the future of biodiversity, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and a paucity of data.
- University of Melbourne Australia
- Australian National University Australia
- Centre of Excellence for Biosecurity Risk Analysis Australia
- La Trobe University Australia
- Centre of Excellence for Biosecurity Risk Analysis Australia
570, VEGETATION DYNAMICS, exposure risk, RANGE SHIFTS, Climate Change, Biodiversity & Conservation, CONSERVATION, Environmental Sciences & Ecology, 333, ELICITATION, XXXXXX - Unknown, Animals, PLANTS, KNOWLEDGE, Ecosystem, Uncategorized, 580, Science & Technology, CLIMATE-CHANGE, CONTRACTIONS, Ecology, alpine, Australia, Biodiversity, Plants, Primary Research Articles, EXTINCTION RISK, adaptive capacity, expert elicitation, Environmental sciences, Biological sciences, Earth sciences, climate change, Climate change impacts and adaptation, FOS: Biological sciences, Biodiversity Conservation, BIODIVERSITY, Life Sciences & Biomedicine, Environmental Sciences
570, VEGETATION DYNAMICS, exposure risk, RANGE SHIFTS, Climate Change, Biodiversity & Conservation, CONSERVATION, Environmental Sciences & Ecology, 333, ELICITATION, XXXXXX - Unknown, Animals, PLANTS, KNOWLEDGE, Ecosystem, Uncategorized, 580, Science & Technology, CLIMATE-CHANGE, CONTRACTIONS, Ecology, alpine, Australia, Biodiversity, Plants, Primary Research Articles, EXTINCTION RISK, adaptive capacity, expert elicitation, Environmental sciences, Biological sciences, Earth sciences, climate change, Climate change impacts and adaptation, FOS: Biological sciences, Biodiversity Conservation, BIODIVERSITY, Life Sciences & Biomedicine, Environmental Sciences
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).17 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
