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Testing alternative indicators for biodiversity conservation in old-growth boreal forests: ecology and economics. Artti Juutinen 1 & Mikko Mönkkönen 2 1 University of Oulu/Faculty of Economics and Industrial Management, Finland 2 University of Oulu/Department of Biology, Finland. Background.
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Testing alternative indicators for biodiversity conservation in old-growth boreal forests: ecology and economics Artti Juutinen1 & Mikko Mönkkönen2 1University of Oulu/Faculty of Economics and Industrial Management, Finland 2 University of Oulu/Department of Biology, Finland
Background • Habitat loss • Setting aside areas that are particularly biodiverse: site selection problem • The contribution, which the area can make to represent the overall biodiversity • It is costly to measure the overall biodiversity • Surrogate measures of biodiversity
Background • How is one to choose a good indicator? • Indicators should reflect the overall biodiversity (the chosen ecological features that are regarded important) • Indicators should not be expensive to monitor • Formal tests are required
Method • Site selection models • Clear-cutting or protection • We compare the benchmark models and indicator models • In the benchmark the focus is on species diversity, best available data • The benchmark selection represents the maximum level of biodiversity in the area at given resources devoted to conservation
Funds available for conservation (A) Benchmark selection a B The goal level of representation (B) b Indicator selection Representation of species A Conservation costs (excluding inventory costs) Method
Method • IDIV-model • Maximize species richness in the selected stands subject to the given budget constraint (species are counted once, if they are present in the selected stands) • The IDIV model, which incorporates information on all species, is the benchmark model with which all the other models are compared. • Budget constraint: • INUM-model • Maximize count of species in the selected stands subject to the given budget constraint (species are counted as many times as they are present in the selected stands)
Data • 32 SEMI-NATURAL OLD GROWTH FORESTS STANDS FROM FINLAND • IN THE OPTIMIZATIONS THE STANDS WERE TREATED AS HAVING EQUAL SIZE • FOUR FOREST TYPES, EIGHT REPLICATES OF EACH XERIC CONIFEROUS FORESTS, MESIC SPRUCE FORESTS, SPRUCE MIRES, HERB RICH SPRUCE DOMINATED HEATH FORESTS • SPECIES, 632 (PRESENCE/ABSENCE) • VASCULAR PLANTS (103), BIRDS (30), WOOD-INHABITING FUNGI (64), BEETLES (435) • DECAYING WOOD • COMMERCIAL VALUES OF THE STANDS • THE OPPORTUNITY COSTS OF CONSERVATION • MAXIMUM NPV FOR EACH STAND, MELA-MODEL • FAUSTMANN ROTATION MODEL • INVENTORY COSTS OF THE SPECIES GROUPS AND DECAYING WOOD
Data • INDICATORS • TAXONOMIC GROUPS • A SUBGROUP OF OLD-GROWTH FOREST INDICATOR SPECIES BASED ON THEIR KNOWN STATUS AS OLD-GROWTH FOREST SPECIALISTS (42 species including species of birds, beetles and wood-inhabiting fungi) • THE AMOUNT AND QUALITY OF DECAYING WOOD
Conclusions • The use of indicators seems to result in a loss of overall diversity. • It is important to consider trade-offs between conservation costs and diversity loss when assessing the goodness of an indicator. • Biodiversity indicators can be tested in economic context by using integrated site selection model. • Species richness based model may not be appropriate for indicator groups having small number of species. • It seems to be more efficient to use indicators than execute large biodiversity survey. • how to reduce inventory costs of biodiversity surveys? • Birds and vascular plants should be used as indicators in protecting boreal old-growth forests in the study area.
