Biodiversity considerations in conservation system planning: map‐based approach for nova scotia, canada

Biodiversity considerations in conservation system planning include three main criteria: representation, special elements, and focal species. A GIS‐based approach utilizing simple models was used to assess existing biophysical data relative to these criteria for conservation system planning in Nova Scotia, Canada, with potential utility in applications elsewhere. Representative samples of natural landscapes were identified on the basis of size (≥10 000 ha) and degree of naturalness (natural cover, uneven‐aged forests, low or zero road density). Special elements were selected, including hotspots of diversity and rarity, critical habitat for species at risk, significant wetlands, old and unique forests, and ecosites. Habitat requirements of viable populations of focal species (American moose, American marten, and Northern Goshawk) were identified using species distribution data, habitat suitability, and population viability analyses. Priority core areas for biodiversity conservation system planning were identified on the basis of these three sets of criteria. Key areas of habitat connectivity were delineated by selecting the least‐cost paths for focal species between relevant core areas through cost–distance analyses based on habitat suitability, road density, and minimum corridor width. Collectively, these biodiversity considerations indicate that ∼60% of Nova Scotia, including 32% in core areas, should be managed for conservation objectives to maintain genes, species, and ecosystems over time. Although data and modeling limitations require that our analysis of richness and diversity, habitat suitability, population viability, and core area selection be verified, the area calculations and other results are consistent with those in similar studies. Consequently, the system design and other information generated are useful for local and regional biodiversity conservation planning and management, and the methodological approach is of potential use in other regions where the necessary field‐based data may be made available.