Sensitivity of tropical forests to climate change in the humid tropics of north Queensland

Hilbert, David W., Ostendorf, Bertram, and Hopkins, Mike S. (2001) Sensitivity of tropical forests to climate change in the humid tropics of north Queensland. Austral Ecology, 26 (6). pp. 590-603.

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An analysis using an artificial neural network model suggests that the tropical forests of north Queensland are highly sensitive to climate change within the range that is likely to occur in the next 50–100 years. The distribution and extent of environments suitable for 15 structural forest types were estimated, using the model, in 10 climate scenarios that include warming up to 1°C and altered precipitation from –10% to +20%. Large changes in the distribution of forest environments are predicted with even minor climate change. Increased precipitation favours some rainforest types, whereas decreased rainfall increases the area suitable for forests dominated by sclerophyllous genera such as Eucalyptus and Allocasuarina. Rainforest environments respond differentially to increased temperature. The area of lowland mesophyll vine forest environments increases with warming, whereas upland complex notophyll vine forest environments respond either positively or negatively to temperature, depending on precipitation. Highland rainforest environments (simple notophyll and simple microphyll vine fern forests and thickets), the habitat for many of the region’s endemic vertebrates, decrease by 50% with only a 1°C warming. Estimates of the stress to present forests resulting from spatial shifts of forest environments (assuming no change in the present forest distributions) indicate that several forest types would be highly stressed by a 1°C warming and most are sensitive to any change in rainfall. Most forests will experience climates in the near future that are more appropriate to some other structural forest type. Thus, the propensity for ecological change in the region is high and, in the long term, significant shifts in the extent and spatial distribution of forests are likely. A detailed spatial analysis of the sensitivity to climate change indicates that the strongest effects of climate change will be experienced at boundaries between forest classes and in ecotonal communities between rainforest and open woodland.

Item ID: 13086
Item Type: Article (Research - C1)
ISSN: 1442-9993
Keywords: artificial neural network; Australia; global change; landscape ecology; modelling; rainforest; wet tropics
Date Deposited: 16 Dec 2010 02:39
FoR Codes: 07 AGRICULTURAL AND VETERINARY SCIENCES > 0705 Forestry Sciences > 070599 Forestry Sciences not elsewhere classified @ 100%
SEO Codes: 96 ENVIRONMENT > 9699 Other Environment > 969999 Environment not elsewhere classified @ 100%
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