Applying spatial conservation prioritization software and high-resolution GIS data to a national-scale study in forest conservation

Applying spatial conservation prioritization software and high-resolution GIS data to a... We apply a recently developed conservation prioritization method (Zonation algorithm) to a national-scale conservation planning task. The Finnish Forest and Park Service (Metsähallitus) was given the mandate to expand the current protected areas in southern Finland by 10 000 ha. The question is which areas should be selected out of the total area of 1 760 000 ha. The data available include a nation-wide GIS data set describing general features of forests at the resolution of 25 m × 25 m for entire Finland and another data set about biodiversity features within the current state-managed conservation areas. Ecologically, the key information includes forest age and the volume of growing stock for 20 forest types representing different productivity classes and dominant tree species. Our analysis employs four different connectivity components to identify forest areas that are (i) locally of high quality and internally well connected, (ii) well connected to surrounding high-quality forests, (iii) well connected to existing conservation areas, and (iv) large enough to allow efficient implementation. Expert evaluation of the results suggested that the present quantitative analysis was helpful in identifying areas with high conservation value systematically across southern Finland. Our analysis also showed that the highest forest conservation potential in Finland is located on privately owned land. The present techniques can be applied to many large-scale planning and management projects. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Forest Ecology and Management Elsevier

Applying spatial conservation prioritization software and high-resolution GIS data to a national-scale study in forest conservation

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Abstract

We apply a recently developed conservation prioritization method (Zonation algorithm) to a national-scale conservation planning task. The Finnish Forest and Park Service (Metsähallitus) was given the mandate to expand the current protected areas in southern Finland by 10 000 ha. The question is which areas should be selected out of the total area of 1 760 000 ha. The data available include a nation-wide GIS data set describing general features of forests at the resolution of 25 m × 25 m for entire Finland and another data set about biodiversity features within the current state-managed conservation areas. Ecologically, the key information includes forest age and the volume of growing stock for 20 forest types representing different productivity classes and dominant tree species. Our analysis employs four different connectivity components to identify forest areas that are (i) locally of high quality and internally well connected, (ii) well connected to surrounding high-quality forests, (iii) well connected to existing conservation areas, and (iv) large enough to allow efficient implementation. Expert evaluation of the results suggested that the present quantitative analysis was helpful in identifying areas with high conservation value systematically across southern Finland. Our analysis also showed that the highest forest conservation potential in Finland is located on privately owned land. The present techniques can be applied to many large-scale planning and management projects.

Journal

Forest Ecology and ManagementElsevier

Published: Nov 10, 2009

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