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Durophagous predators consume hard‐shelled prey such as bivalves, gastropods, and large crustaceans, typically by crushing the mineralized exoskeleton. This is costly from the point of view of the bite forces involved, handling times, and the stresses inflicted on the predator's skeleton. It is not uncommon for durophagous taxa to display an ontogenetic shift from softer to harder prey items, implying that it is relatively difficult for smaller animals to consume shelled prey. Batoid fishes (rays, skates, sawfishes, and guitarfishes) have independently evolved durophagy multiple times, despite the challenges associated with crushing prey harder than their own cartilaginous skeleton.Potamotrygon leopoldiis a durophagous freshwater ray endemic to the Xingu River in Brazil, with a jaw morphology superficially similar to its distant durophagous marine relatives, eagle rays (e.g.,Aetomylaeus, Aetobatus). We used second moment of area as a proxy for the ability to resist bending and analyzed the arrangement of the mineralized skeleton of the jaw ofP. leopoldiover ontogeny using data from computed tomography (CT) scans. The jaws ofP. leopoldido not resist bending nearly as well as other durophagous elasmobranchs, and the jaws are stiffest nearest the joints rather than beneath the dentition. While second moment has similar material distribution over ontogeny, mineralization of the jaws under the teeth increases with age. Neonate rays have low jaw stiffness and poor mineralization, suggesting thatP. leopoldimay not feed on hard‐shelled prey early in life. These differences in the shape, stiffness and mineralization of the jaws ofP. leopoldicompared to its durophagous relatives show there are several solutions to the problem of crushing shelled prey with a compliant skeleton.

Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system‐level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi‐scalar community‐level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel‐2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.