Document Type

Article

Department/Program

Virginia Institute of Marine Science

Publication Date

9-14-2017

Journal

Marine Ecology Progress Series

Volume

579

First Page

81

Last Page

96

Abstract

Studies aiming to assess intra- and interspecies community relationships in marine habitats are typically limited to accessible, nearshore areas of restricted temporal and spatial scale, within which only segments of the populations of interest are available. Using multivariate first-order auto regressive state-space (MARSS-1) models, we estimated measures of interspecies interactions and density dependence of 7 Atlantic coastal shark species (4 large and 3 small coastal sharks) at 2 spatial scales. Localized analyses were based on data from 4 relatively spatially limited, fishery-independent surveys conducted along the southeast US Atlantic coast and within the Gulf of Mexico. We then compared these localized results to those generated using broad-scale indices of relative abundance estimated as common trends across the collection of 6 spatially restricted surveys. The MARSS-1 framework was also used to estimate relative community stability. Localized MARSS-1 analyses identified density-dependent compensation in all populations in addition to 9 interspecies interactions, while results of broad-scale MARSS-1 analyses revealed density dependence in 5 species and 9 interspecies interactions. More specifically, our results support the manifestation of density-dependent compensation of neonate and juvenile shark life stages within nursery areas. Overall, interactions within smaller spatial areas differed from those identified using the broad-scale relative abundance trends, indicating that small-scale interactions cannot be extrapolated to shark population growth rates of an entire stock.

DOI

doi: 10.3354/meps12288

Keywords

Atlantic coastal sharks; Early life history; Generalized linear models; GLMs; MARSS-1; Multivariate first-order autoregressive state-space model

Available for download on Sunday, October 30, 2022

Share

COinS