首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents
Authors:ANNI ARPONEN  JOONA LEHTOMÄKI  JARNO LEPPÄNEN  ERKKI TOMPPO  ATTE MOILANEN
Institution:Metapopulation Research Group, Department of Biosciences, P.O. Box 65, FI-00014, University of Helsinki, Finland. anni.arponen@helsinki.fi
Abstract:The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.
Keywords:fine resolution  grain  high resolution  reserve selection  scale  spatial optimization  uncertainty  Zonation software  escala  grano  incertidumbre  optimización espacial  resolución alta  resolución fina  selección de reservas  software Zonation
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号