Chris McGonigle | USGS Science

USGS2020

Combining fisheries surveys to inform marine species distribution modelling

Ecosystem-scale examination of fish communities typically involves creating spatio-temporally explicit relative abundance distribution maps using data from multiple fishery-independent surveys. However, sampling performance varies by vessel and sampling gear, which may influence estimated species distribution patterns. Using GAMMs, the effect of different gear–vessel combinations on relative abundance estimates at length was investigated using European fisheries-independent groundfish survey data. We constructed a modelling framework for evaluating relative efficiency of multiple gear–vessel combinations. 19 northeast Atlantic surveys for 254 species-length combinations were examined. Space-time variables explained most of the variation in catches for 181/254 species-length cases, indicating that for many species, models successfully characterized distribution patterns when combining data from disparate surveys. Variables controlling for gear efficiency explained substantial variation in catches for 127/254 species-length data sets. Models that fail to control for gear efficiencies across surveys can mask changes in the spatial distribution of species. Estimated relative differences in catch efficiencies grouped strongly by gear type, but did not exhibit a clear pattern across species’ functional forms, suggesting difficulty in predicting the potential impact of gear efficiency differences when combining survey data to assess species’ distributions and highlighting the importance of modelling approaches that can control for gear differences.

ICES Journal of Marine Science↗

USGS2018

Dynamic occupancy modeling of temperate marine fish in area-based closures

Species distribution models (SDMs) are commonly used to model the spatial structure of species in the marine environment, however, most fail to account for detectability of the target species. This can result in underestimates of occupancy, where nondetection is conflated with absence. The site occupancy model (SOM) overcomes this failure by treating occupancy as a latent variable of the model and incorporates a detection submodel to account for variability in detection rates. These have rarely been applied in the context of marine fish and never for the multiseason dynamic occupancy model (DOM). In this study, a DOM is developed for a designated species of concern, cusk ( Brosme brosme ), over a four-season period. Making novel use of a high-resolution 3-dimensional hydrodynamic model, detectability of cusk is considered as a function of current speed and algae cover. Algal cover on the seabed is measured from video surveys to divide the study area into two distinct regions: those with canopy forming species of algae and those without (henceforth bottom types). Modeled estimates of the proportion of sites occupied in each season are 0.88, 0.45, 0.74, and 0.83. These are significantly greater than the proportion of occupied sites measured from underwater video observations which are 0.57, 0.28, 0.43, and 0.57. Individual fish are detected more frequently with increasing current speed in areas lacking canopy and less frequently with increasing current speed in areas with canopy. The results indicate that, where possible, SDM studies for all marine species should take account of detectability to avoid underestimating the proportion of sites occupied at a given study area. Sampling closed areas or areas of conservation often requires the use of nonphysical, low impact sampling methods like camera surveys. These methods inherently result in detection probabilities less than one, an issue compounded by time-varying features of the environment that are rarely accounted for marine studies. This work highlights the use of modeled hydrodynamics as a tool to correct some of this imbalance.

Gulf of Maine↗