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Cited by 476

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Adapting to climate change: is there scope for ecological management in the face of a global threat?

Open access
HULME, PHILIP E.·2005·Journal of Applied Ecology

Abstract

Summary: Climate change is recognized as a major threat to the survival of species and integrity of ecosystems world‐wide. Although considerable research has focused on climate impacts, relatively little work to date has been conducted on the practical application of strategies for adapting to climate change. Adaptation strategies should aim to increase the flexibility in management of vulnerable ecosystems, enhance the inherent adaptability of species and ecosystem processes, and reduce trends in environmental and social pressures that increase vulnerability to climate variability. Knowledge of the specific attributes of climate change likely to impact on species or habitats is central to any adaptive management strategy. Temperature is not the only climate variable likely to change as a result of anthropogenic increases in greenhouse gases. In some regions changes in precipitation, relative humidity, radiation, wind speed and/or potential evapotranspiration may be more marked than for temperature. Uncertainty exists in the response of species and ecosystems to a given climate scenario. While climate will have a direct impact on the performance of many species, for others impacts will be indirect and result from changes in the spatiotemporal availability of natural resources. In addition, mutualistic and antagonistic interactions among species will mediate both the indirect and direct effects of climate change. Approaches to predict species’ responses to climate change have tended to address either changes in abundance with time or in spatial distribution. While correlative models may provide a good indication of climate change impacts on abundance, greater understanding is generated by models incorporating aspects of life history, intra‐ and interspecific competition and predation. Models are especially sensitive to the uncertainty inherent in future climate predictions, the complexity of species’ interactions and the difficulties in parameterizing dispersal functions. Model outputs that have not been appropriately validated with real data should be treated with caution. Synthesis and applications. While climate impacts may be severe, they are often exacerbated by current management practices, such as the construction of sea defences, flood management and fire exclusion. In many cases adaptation approaches geared to safeguard economic interests run contrary to options for biodiversity conservation. Increased environmental variability implies lower sustainable harvest rates and increased risks of population collapse. Climate change may significantly reduce habitat suitability and may threaten species with limited dispersal ability. In these cases, well‐planned species translocations may prove a better option than management attempts to increase landscape connectivity. Mathematical models, long‐term population studies, natural experiments and the exploitation of natural environmental gradients provide a sound basis for further understanding the consequences of climate change.

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Crossref · 10.1111/j.1365-2664.2005.01082.x

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Metadata

Authors
HULME, P. E.
Venue
Journal of Applied Ecology
Publisher
Wiley
Published
2005-09-28
Volume
42
Issue
5
Pages
784-794
ISSN
  • 0021-8901 (ISSN-L)
  • 1365-2664
OpenAlex
W2104652168
Cited by
476
References
1
FWCI
13.74
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Adapting to climate change: is there scope for ecological management in the face of a global threat? https://app.cochat.ai/papers/10.1111/j.1365-2664.2005.01082.x
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HULME, P. E. (2005). Adapting to climate change: is there scope for ecological management in the face of a global threat? Journal of Applied Ecology. https://doi.org/10.1111/j.1365-2664.2005.01082.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.