Literature DB >> 24249057

Monitoring the health of a forest: A Canadian approach.

P A Addison1.   

Abstract

In Canada, acid rain is the generic term encompassing all forms of air pollution - wet and dry deposition, gaseous pollutant concentrations, and airborne particulates. It was because these pollutants, alone or in combination, may directly or indirectly affect the heath of Canada's forests, that in 1984, the Canadian Forestry Service initiated a national forest monitoring program (Acid Rain National Early Warning System or ARNEWS).Research studies on pollutant effects of the past 15-20 years have demonstrated that it is not possible to define specific symptoms of acid rain or mixtures of pollutants on native tree species or specific responses of the forest ecosystem. Consequently, ARNEWS monitored incipient acid rain effects by determining the forest's state of health rather than by concentrating on specific pollutant responses.The detection system entails experienced insect and disease survey forest rangers assessing both specific plots and the forest as a whole for extraordinary forest damage. The techniques used include mensurational and symptomatological measurements as well as evaluation of stands for damage from natural and anthropogenic causes. Critical also to the system was the capability of the Canadian Forestry Service to support the detection system with research staff who could carry out studies to explain any abnormalities in forest condition detected during the annual surveys. The ultimate outcome of the monitoring system if unexplained forest damage is detected is a research project on possible causes.

Year:  1989        PMID: 24249057     DOI: 10.1007/BF00396727

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  1 in total

1.  A selection of forest condition indicators for monitoring.

Authors:  K H Rutters; B E Law; R C Kucera; A L Gallant; R L Develice; C J Palmer
Journal:  Environ Monit Assess       Date:  1992-01       Impact factor: 2.513

  1 in total

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