Planning for dynamic process: An assemblage-level surrogate strategy for species seasonal movement pathways

Seasonally mobile species are globally prevalent and often provide vital ecosystem functions and services along their seasonal movement pathways. However, owing to the challenges of planning for features that are spatially and temporally variable, mobile species are rarely accounted for in conservation planning. To protect this dynamic process, planners need a temporally explicit surrogate for species seasonal movement pathways. Because reserve networks typically aim to represent the full spectrum of biodiversity, these surrogates also need to capture the assemblage-level organization of species in order to preserve the full range of seasonal movement pathways that occur within a given planning region. 0002">To this end, this study introduces a new assemblage-level surrogate strategy for species seasonal movements that preserves variation in biodiversity across the 12months. Two monthly, assemblage-level attributes were integrated: discrete species assemblages and continuous assemblage suitability, thereby allowing planners to select complementary combinations of sites that achieve comprehensive assemblage coverage in each month. 0003">As a marine case-study, this strategy was applied to the US Mid-Atlantic, and a gap analysis was used to evaluate the ability of the Mid-Atlantic's current spatial management scheme to accommodate species' seasonal movements. 0004">The results indicate that current protected areas in the Mid-Atlantic will be unable to meet even modest quantitative objectives for protecting seasonal movements, and priority conservation areas are identified for designing a reserve network that offers year-round protection. 0005">Planning for processes remains a significant gap in conservation planning, and this study seeks to address this gap by proposing a surrogate strategy that will aid the incorporation of a widespread dynamic process into reserve design. This strategy uses public, predominantly global datasets that have terrestrial and marine counterparts, making it applicable to planning for species seasonal movements both on land and at sea.