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Filters: Tags: hierarchical sampling units (X) > partyWithName: Cameron L Aldridge (X)

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Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species’ conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., fine-scale) with low genetic diversity relative...
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We produced 13 hierarchically nested cluster levels that reflect the results from developing a hierarchical monitoring framework for greater sage-grouse across the western United States. Polygons (clusters) within each cluster level group a population of sage-grouse leks (sage-grouse breeding grounds) and each level increasingly groups lek clusters from previous levels. We developed the hierarchical clustering approach by identifying biologically relevant population units aimed to use a statistical and repeatable approach and include biologically relevant landscape and habitat characteristics. We desired a framework that was spatially hierarchical, discretized the landscape while capturing connectivity (habitat...


    map background search result map search result map Hierarchically nested and biologically relevant range-wide monitoring frameworks for greater sage-grouse, western United States Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023) Hierarchically nested and biologically relevant range-wide monitoring frameworks for greater sage-grouse, western United States Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)