Long-term adaptation potential of Central European mountain forests to climate change: a GIS-assisted sensitivity assessment

Long-term adaptation potential of Central European mountain forests to climate change: a... An ecological risk assessment is described for determining the adaptation potential of the approximately 11 000 Swiss Forest Inventory points (FIP) to a hypothetically changing climate. The core of the study is a spatially explicit forest community model that generates estimates of the potential natural vegetation for the entire potential forest area of Switzerland under today's as well as under altered climate regimes. The model is based on the Bayes formula. The probabilities of the communities occurring along ecological gradients are derived from empirical data featuring the relationships between quasi-natural vegetation types and measured site variables. Bioclimatological input variables are the quotient between July temperature and annual precipitation (model version A) or mean annual temperature (model version B). Other site variables include aspect, acidity of top soil and, to account for continentality, geographical region. Climate change scenarios are defined as follows: ‘Moderate climate change’ implies an increase of the mean annual temperature of 4°C to 1.4°C depending on the region (model version B) or an increase of the July temperature of 1.5°C (model version A). ‘Strong climate change’ implies an increase of the mean annual temperature of 2°C to 2.8°C (model version B) or an increase of the July temperature of 3.0°C (model version A). The simulation experiment showed that the geographical distribution of 15 potential natural forest types (distinguished on the basis of floristic affinities) varies considerably with changing temperature. Under moderate warming 30–55% of the FIP change their potential natural vegetation type, whereas under strong climate change the values increase to 55–89% depending on the model version used. In the ecological risk assessment the existing tree species composition on any FIP was compared with the expected tree species composition under today's as well as under altered climate regimes. A major finding indicated that, under the current climate conditions, approximately 25–30% (depending on the model version used) of all FIP must be considered as poorly adapted, i.e. less than 20% of the actual basal area consists of tree species that are expected as dominating taxa. This definition applies for trees with a diameter at breast height (DBH) ≥ 12 cm. Moderate warming increases the percentage of poorly adapted FIP by 5–10% (relative to all FIP considered), strong warming leads to a 10–30% increase of poorly adapted FIP (relative to all FIP considered). If trees with a DBH < 12cm are considered, the percentage of FIP that have to be classified as poorly adapted is reduced significantly. There are strong regional differences as exhibited in risk maps of 10 km × 10 km resolution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Forest Ecology and Management Elsevier

Long-term adaptation potential of Central European mountain forests to climate change: a GIS-assisted sensitivity assessment

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Publisher
Elsevier
Copyright
Copyright © 1996 Elsevier Ltd
ISSN
0378-1127
eISSN
1872-7042
DOI
10.1016/0378-1127(95)03633-4
Publisher site
See Article on Publisher Site

Abstract

An ecological risk assessment is described for determining the adaptation potential of the approximately 11 000 Swiss Forest Inventory points (FIP) to a hypothetically changing climate. The core of the study is a spatially explicit forest community model that generates estimates of the potential natural vegetation for the entire potential forest area of Switzerland under today's as well as under altered climate regimes. The model is based on the Bayes formula. The probabilities of the communities occurring along ecological gradients are derived from empirical data featuring the relationships between quasi-natural vegetation types and measured site variables. Bioclimatological input variables are the quotient between July temperature and annual precipitation (model version A) or mean annual temperature (model version B). Other site variables include aspect, acidity of top soil and, to account for continentality, geographical region. Climate change scenarios are defined as follows: ‘Moderate climate change’ implies an increase of the mean annual temperature of 4°C to 1.4°C depending on the region (model version B) or an increase of the July temperature of 1.5°C (model version A). ‘Strong climate change’ implies an increase of the mean annual temperature of 2°C to 2.8°C (model version B) or an increase of the July temperature of 3.0°C (model version A). The simulation experiment showed that the geographical distribution of 15 potential natural forest types (distinguished on the basis of floristic affinities) varies considerably with changing temperature. Under moderate warming 30–55% of the FIP change their potential natural vegetation type, whereas under strong climate change the values increase to 55–89% depending on the model version used. In the ecological risk assessment the existing tree species composition on any FIP was compared with the expected tree species composition under today's as well as under altered climate regimes. A major finding indicated that, under the current climate conditions, approximately 25–30% (depending on the model version used) of all FIP must be considered as poorly adapted, i.e. less than 20% of the actual basal area consists of tree species that are expected as dominating taxa. This definition applies for trees with a diameter at breast height (DBH) ≥ 12 cm. Moderate warming increases the percentage of poorly adapted FIP by 5–10% (relative to all FIP considered), strong warming leads to a 10–30% increase of poorly adapted FIP (relative to all FIP considered). If trees with a DBH < 12cm are considered, the percentage of FIP that have to be classified as poorly adapted is reduced significantly. There are strong regional differences as exhibited in risk maps of 10 km × 10 km resolution.

Journal

Forest Ecology and ManagementElsevier

Published: Jan 1, 1996

References

  • The role of models in ecological risk assessment: a 1990's perspective
    Barnthouse, L.W.
  • A simulated map of the potential natural forest vegetation of Switzerland
    Brzeziecki, B.; Kienast, F.; Wildi, O.
  • Sensitivity of a forest ecosystem model to climate parametrization schemes
    Fischlin, A.; Bugmann, H.; Gyalistras, D.
  • Ecological response surfaces for North American boreal tree species and their use in forest classification
    Lenihan, J.M.
  • Predicting the distribution of plant communities using annual rainfall and elevation: an example from southern Africa
    Palmer, A.R.; van Staden, J.M.

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