Abstract
ABSTRACTStatistical methods that quantify individual movements have limited applicability within dendritic ecological networks (DENs), to include riverscapes. We promote an approach herein by deriving an analytical framework (=DistNet and ResistNet) that more appropriately quantifies differentiation by meshing individual DEN segments with fitted distances and annotated environmental features. We first explored the spatial arrangement of diversity in a river network by fitting pairwise distances against graph edges. We then derived effective resistance models (e.g., as a composite of an array of possible environmental covariates) by using a genetic algorithm for heuristic model selection, invoking circuit theory (CircuitScape) to form a graph-based complement to ResistanceGA (a landscape ecology package). Although numerous pairwise distance metrics can be employed, we utilized genetic distances encompassing 13,218 ddRAD loci from N=762 Speckled Dace (Cyprinidae: Rhinichthys osculus) sampled at 78 Colorado River localities (µ=9.77/site). When distances for each locus were fitted into the network, we found intraspecific divergences due to stream reaches were greater than expected when distances alone. In fitting model-averaged ‘effective resistance’ models to the same network, we showed the manner by which a host of anthropogenic and environmental variables contribute to patterns of connectivity underlying riverscape genetic differentiation. Our framework represents a contemporary approach to deriving metapopulation/ metacommunity structure within DENs, in that it allows: (a) The extension of projections into unsampled temporal/spatial components; (b) Comparisons to be made among species and/or drainages, both of which benefit multi-species management; and (c) the quantification of locus-specific patterns, from which adaptive hypotheses could then be derived.
“The intimate relation of hydrological conditions to fish life is proverbial; to be hopelessly or dangerously maladjusted to one’s environment is to be a ‘fish out of water’” (Hubbs 1941).
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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