KA, Cabeza M, Klein. However, even when combined the validation data sets cover only a small fraction of the total landscape (2.5, Table 1 ) and the mean decay distance for dispersal we used (2 km) is relatively large compared to the average size of sites in the validation. Chirici G, Winter S, McRoberts. How much of the initial representation levels from the detailed data can be covered by protecting a given fraction of the landscape. A Comparison of Coarse Open and Detailed Proprietary Forest Inventory Data in Finland.
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An overlap.0 indicates complete match, whereas overlap.0 means absence of overlap. We encourage the reader to refer to a large body of existing literature for the conceptual background 88, 90, 91, the exact operational principles 20, 89, and the different applications of Zonation (e.g. Elbakidze M, Angelstam PK, Sobolev N, Degerman E, Andersson K, Axelsson R,. Biodiversity value and the optimal location of forest conservation sites in Southern Finland. We used only areas with permanent conservation contracts for validation, as the conservation effectiveness of temporary or fixed-term contracts is questionable. Note that the input data set Detailed with classes is actually a combination of coarse and detailed as the detailed data only covered 46 of the landscape ( Table 1 ). Connectivity and average size of habitat patches) and relevant at the scale of operative planning. Importantly, however, the high-priorities of any of the analyses do not much overlap with the low priorities in any other run. Wilson KA, Underwood EC, Morrison SA, Klausmeyer KR, Murdoch WW, Reyers B,. Synthesis of pattern and process in biodiversity conservation assessment: a flexible whole-landscape modelling framework. Regions dense with high-priority areas ( Fig 4B, 4D and 4F ) receive higher overall priority because of the connectivity effect, which is evident from the marginal plots in Fig 4B, 4D and.
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