Keywords
acidification, eutrophication, indicators, open modelling, niche
Start Date
1-7-2008 12:00 AM
Abstract
Damage to semi-natural habitats due to air pollution has hitherto been quantified using biogeochemical indicators, but predictions of species change are necessary to relate impacts on ecosystems to the habitat quality metrics used in conservation and policy communities. Ongoing pollution by reactive nitrogen (N) is delaying the recovery of acidsensitive ecosystems from sulphur (S) pollution, and causing additional damage through eutrophication. Dynamic soil chemistry models are currently used to set national emissions thresholds for acid pollutants in a UNECE process, using simple targets based on soil pH or acid-base balance. These indicators are however poorly related to conservation targets based on habitat quality, which are defined in terms of the presence and abundance of indicator species. We demonstrate an approach to predicting habitat quality change under different N and S pollution scenarios, which brings together biogeochemists, biodiversity specialists and policymakers in an open modelling framework.
Predicting Winners and Losers: Translating Air Pollution Policy Initiatives into Indicators of Habitat Quality Change
Damage to semi-natural habitats due to air pollution has hitherto been quantified using biogeochemical indicators, but predictions of species change are necessary to relate impacts on ecosystems to the habitat quality metrics used in conservation and policy communities. Ongoing pollution by reactive nitrogen (N) is delaying the recovery of acidsensitive ecosystems from sulphur (S) pollution, and causing additional damage through eutrophication. Dynamic soil chemistry models are currently used to set national emissions thresholds for acid pollutants in a UNECE process, using simple targets based on soil pH or acid-base balance. These indicators are however poorly related to conservation targets based on habitat quality, which are defined in terms of the presence and abundance of indicator species. We demonstrate an approach to predicting habitat quality change under different N and S pollution scenarios, which brings together biogeochemists, biodiversity specialists and policymakers in an open modelling framework.
