Estimating fine‐scale movement rates and habitat preferences using multiple data sources

Abstract

Fisheries scientists and managers must track rapid shifts in fish spatial distribution to mitigate stakeholder conflict and optimize survey designs, and these spatial shifts result in part from animal movement. Information regarding animal movement can be obtained from selection experiments, tagging studies, flux through movement gates (e.g. acoustic arrays), fishery catch-per-unit effort (CPUE), resource surveys and genetic/chemical markers. However, there are few accessible approaches to combine these data types while accounting for spatially correlated residual patterns. We therefore discuss a movement model involving diffusion (random movement), taxis (movement towards preferred habitat) and advection (passive drift following ocean currents). We specifically outline how these movement processes can be fitted to data while discretizing space and time and estimating non-linear habitat preferences using environmental layers as well as spatial process errors. Finally, we introduce an R package, ATM, by fitting the model to bottom trawl survey, longline fishery and tagging data for Pacific cod (Gadus macrocephalus, Gadidae) in the Bering Sea during winter/summer seasons from 1982 to 2019. Combining data types predicts an increasing proportion of cod residing in the northern Bering Sea from 2013 to 2019, and estimates are informative in a recent stock assessment model. We fit sensitivity analyses by dropping tag, survey or fishery data, and this analysis shows that tagging data are necessary to identify diffusion rates, while survey data are informative about movement among biogeographic strata. This "hybrid" species distribution model can help explain poleward movement, project distributions under future climate conditions and evaluate alternative tag-deployment scenarios to optimize tagging designs.

Estimating contemporary migration numbers of adults based on kinship relationships in iteroparous species

“…The proposed estimators are limited to detecting parental movements on a period between breeding seasons in the given populations. Thus, the estimation of fine-scale spatiotemporal movements, which is available to integrate data sources (Thorson et al, 2021), is beyond the scope of this paper. Although population dynamics models with coarser spatial resolution than the spatial scale of environmental layers are frequently used in assessment models, i.e., the target application of the proposed method, the proposed estimators require pre-specification of the population structure.…”

“…Essentially, there are two approaches to estimate the contemporary migration rate. The first approach involves using the mark-recapture (MR) method, which estimates the migration rate along with other population parameters (Kéry & Schaub, 2011; Thorson et al, 2021). Here, the rational is that, for example, conventional tags provide release and recovery location information for known release and recovery dates, which generates a movement fraction matrix among strata per given time interval.…”

Oceans of plenty? Challenges, advancements, and future directions for the provision of evidence-based fisheries management advice

“…Population spatial structure is influenced by the marine biophysical environment (e.g., currents, temperature, prey, and predators), fish behavior (e.g., habitat preferences, dispersal, and movement), and fishing patterns, which can manifest in an array of biogeographic patterns (Cadrin 2020 ). Spatiotemporal (including species distribution) models can elucidate local and broad-scale distributions, while linking population dynamics to environment or habitat variables (Thorson 2019b ; Thorson et al 2021 ). On the other hand, spatially-stratified models can account for population structure and broad-scale spatial dynamics (Goethel et al 2011 ; Sippel et al 2015 ).…”

“…Multiscalar, modular, and hybrid (i.e., cross-framework) modeling approaches will continue to gain traction as facets of each framework are borrowed and shared. For example, by using hybrid modeling approaches, the multiscalar nature of common data sources (e.g., fine-scale biologging data and broad-scale historical fishery data) and population processes can be explicitly addressed, while also adjusting to the scale of management (e.g., by embedding spatiotemporal sub-models within coarser resolution spatially stratified assessments; Thorson et al 2021 ). Similarly, wider incorporation of state-space frameworks that utilize spatial and temporal random effects and spatial autocorrelation will aid implementation of spatially explicit assessment approaches by reducing the number of effective parameters (e.g., Cao et al 2020 ).…”

Estimating contemporary migration numbers of adults based on kinship relationships in iteroparous species

“…Essentially, there are two primary approaches to estimating the contemporary migration rate. The first approach involves using the mark–recapture (MR) method, which estimates the migration rate and other population parameters (Kéry & Schaub, 2011; Thorson et al, 2021). Here, the rationale is that, for example, conventional tags provide release and recovery location information for known release and recovery dates, which generates a movement fraction matrix among strata per the given time interval.…”