Spatially dynamic forest management to sustain biodiversity and economic returns.
Production of marketed commodities and protection of biodiversity in natural systems often conflict and thus the continuously expanding human needs for more goods and benefits from global ecosystems urgently calls for strategies to resolve this conflict. In this paper, we addressed what is the potential of a forest landscape to simultaneously produce habitats for species and economic returns, and how the conflict between habitat availability and timber production varies among taxa. Secondly, we aimed at revealing an optimal combination of management regimes that maximizes habitat availability for given levels of economic returns. We used multi-objective optimization tools to analyze data from a boreal forest landscape consisting of about 30,000 forest stands simulated 50 years into future. We included seven alternative management regimes, spanning from the recommended intensive forest management regime to complete set-aside of stands (protection), and ten different taxa representing a wide variety of habitat associations and social values. Our results demonstrate it is possible to achieve large improvements in habitat availability with little loss in economic returns. In general, providing dead-wood associated species with more habitats tended to be more expensive than providing requirements for other species. No management regime alone maximized habitat availability for the species, and systematic use of any single management regime resulted in considerable reductions in economic returns. Compared with an optimal combination of management regimes, a consistent application of the recommended management regime would result in 5% reduction in economic returns and up to 270% reduction in habitat availability. Thus, for all taxa a combination of management regimes was required to achieve the optimum. Refraining from silvicultural thinnings on a proportion of stands should be considered as a cost-effective management in commercial forests to reconcile the conflict between economic returns and habitat required by species associated with dead-wood. In general, a viable strategy to maintain biodiversity in production landscapes would be to diversify management regimes. Our results emphasize the importance of careful landscape level forest management planning because optimal combinations of management regimes were taxon-specific. For cost-efficiency, the results call for balanced and correctly targeted strategies among habitat types.
Department of Biological and Environmental Sciences, P.O. Box 35, FI-40014 Jyväskylä, University of Jyväskylä, Finland. Electronic address: mikko.monkkonen@jyu.fi.
Mikko
M
Mönkkönen
Department of Economics, P.O. Box 4600, 90014, University of Oulu, Finland; Thule Institute, University of Oulu, Finland; Finnish Forest Research Institute, Northern Unit, Eteläranta 55, P.O. Box 16, FI-96301 Rovaniemi, Finland.
Artti
A
Juutinen
Department of Biological and Environmental Sciences, P.O. Box 35, FI-40014 Jyväskylä, University of Jyväskylä, Finland.
Adriano
A
Mazziotta
Department of Mathematical Information Technology, P.O. Box 35 (Agora), FI-40014, University of Jyväskylä, Finland.
Kaisa
K
Miettinen
Department of Biological and Environmental Sciences, P.O. Box 35, FI-40014 Jyväskylä, University of Jyväskylä, Finland; Department of Mathematical Information Technology, P.O. Box 35 (Agora), FI-40014, University of Jyväskylä, Finland.
Dmitry
D
Podkopaev
Department of Biological and Environmental Sciences, P.O. Box 35, FI-40014 Jyväskylä, University of Jyväskylä, Finland.
Pasi
P
Reunanen
Finnish Forest Research Institute, Northern Unit, Eteläranta 55, P.O. Box 16, FI-96301 Rovaniemi, Finland.
Hannu
H
Salminen
Department of Biology, P.O. Box 111, University of Eastern Finland, Joensuu 80101, Finland.
Olli-Pekka
OP
Tikkanen
D044822:Biodiversity; D003247:Conservation of Natural Resources / Q000379:methods*; D016468:Forestry / Q000379:methods*; D006801:Humans; D014197:Trees; D014934:Wood
Biodiversity; Cost-effectiveness; Forest management; Land use planning; Multi-objective optimization