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Ingram, E. C.

Publications and source records attributed to Ingram, E. C..

2 recordsLinked to original sources

Telemetry-validation of dorsal scute microchemistry: complementary tools reconstruct the migratory life-history of an endangered population of Atlantic Sturgeon

An understanding of age-specific habitat requirements and the timing of critical ontogenetic transitions is essential to inform conservation and recovery efforts for Atlantic Sturgeon (Acipenser oxyrinchus). However, these are often difficult to assess due to the species cryptic nature and the consequent lack of temporal and spatial habitat data across life stages. Sampling and microchemistry analysis of dorsal scute apical spines (i.e., dorsal scutes) represents an innovative methodology to reconstruct past life-history events of endangered populations of Atlantic Sturgeon. Here, we establish the broad potential of dorsal scute sampling for wild-caught Atlantic Sturgeon and compare age-estimates and trace-element ratio patterns from dorsal scute with those from pectoral fin spines. We also evaluate microchemistry signatures from both structures to infer past habitat use and age at initial entry into marine waters and, importantly, validate these interpretations using known locations from acoustic telemetry detections. Major ontogenetic shifts in habitat use detected in the microchemistry signatures suggest our methodology was appropriate to identify the timing of initial juvenile migration into marine habitat, while providing additional information regarding the timing of transitions between freshwater and marine habitats that are essential to the management and conservation of this endangered species. As such, the collection of dorsal scute samples is suggested to complement ongoing research efforts for wild-populations and provides additional data points beyond those available from conventional tag-recapture methods alone, allowing researchers and managers to retrospectively identify environmental transitions and habitat use that occur prior to sampling encounters or outside of monitored areas.

ecology↗

Artificial intelligence and species distribution ensemble models inform resource interactions with offshore wind development

Development of offshore wind energy resources has led to growing concerns for marine wildlife. However, significant uncertainty remains regarding the technologys potential to impact species of interest that may occupy planned development sites. This is further compounded by the difficulty of monitoring highly migratory or data-poor species in marine waters, making practical assessment of site- or species-specific threats that could require additional management intervention particularly problematic. Here, I identify a highly generalizable framework to inform species interactions in marine habitats allocated for offshore resource exploitation, using telemetry-derived artificial intelligence species distribution models. Results from a case study of the federally protected Atlantic Sturgeon (Acipenser oxyrinchus) demonstrate excellent discriminatory capacity (i.e., AUC [≥] 0.9) at a relatively fine scale (raster resolution = 1 km2), while providing critical information on predicted occurrence over a broad swath of unmonitored marine habitats (i.e., the Atlantic OCS region of the US; area > 620,000 km2). Furthermore, ensemble map products developed from these models are readily scalable to ongoing management needs and, when overlaid with offshore wind energy lease areas, can feed directly into management strategies to inform best practices for potential habitat influences on Atlantic Sturgeon, as well as other species of commercial or conservation interest.

ecology↗