Predictive models of coral and sponge distribution, abundance and diversity in bottom trawl surveys of the Aleutian Islands, Alaska

Abstract

Ecosystem management requires information to determine and mitigate adverse impacts of fishing on all ecosystem components. Deep-sea coral and sponge ecosystems often co-occur with fishing activities, and there is considerable research documenting the vulnerability and slow recovery of deep-sea coral and sponge communities to damage. The objective of the present analysis was to construct models that could predict the distribution, abundance and diversity of deep sea corals and sponges in the Aleutian Islands. Generalized additive models were constructed based on bottom trawl survey data collected from 1991 to 2011 and tested on data from 2012. The results showed that deep-sea coral and sponge distributions were strongly influenced by the maximum tidal currents at bottom trawl locations, possibly indicative of reduced sedimentation or increased food-delivery processes near the seafloor in areas of moderate to high current. Depth and location were also important factors affecting the distribution of deep-sea sponges and corals. The analysis resulted in acceptable models of presence or absence for all taxonomic groups and similar fits when models were applied to test data. The best-fitting models of abundance explained between 20 and 25% of the deviance in the abundance data. Current management protects ~50% of the coral and sponge habitat in the Aleutian Islands at depths to 500 m. The models constructed here will allow managers to evaluate ecological versus economic benefits between protecting coral and sponge habitat and allowing commercial fishing by examining the effect of spatial closures on the amount of coral and sponge habitat that is protected.

Model of trawlable area using benthic terrain and oceanographic variables—Informing survey design and habitat maps in the Gulf of Alaska

“…To determine discrete towpaths for each bottom trawl, we estimated the actual position of the net using detailed information on vessel position, wire length, tow depth, and timing of initiation and cessation of the tow. As per Rooper, Zimmermann, Prescott, and Hermann (), actual location of the net on the bottom was estimated via triangulation (based on seafloor depth and the wire out), subtracting this distance from the vessel position in the direction of the haul. We assumed the bottom trawl was directly behind the vessel during the tow and that all tows were conducted in a straight line from beginning and end points without deviation.…”

High-Resolution Habitat Suitability Models for the Conservation and Management of Vulnerable Marine Ecosystems on the Louisville Seamount Chain, South Pacific Ocean

“…The distributions of a number of deep-sea species have been successfully modeled using a GAM approach, including corals (Rooper et al, 2014;Murillo et al, 2016), sponges (Rooper et al, 2014;Murillo et al, 2016), and fish (Leathwick et al, 2006). GAMs were developed in R using the "mgcv" package (Wood, 2006).…”

“…The quantity, quality, and distribution of species presence records, the availability of true absence records, and the environmental predictor variables used can all influence the reliability of the models (Araújo and Guisan, 2006;Guisan et al, 2006). Recent efforts to improve the accuracy of habitat suitability models, and thus their usefulness for the management of the impact of fishing on VMEs, have included use of abundance data (as opposed to relying only on presence-absence data), ground-truth model validation, ensemble modeling, and estimates of model uncertainty (Rooper et al, 2014(Rooper et al, , 2016Anderson et al, 2016a,b;Robert et al, 2016).…”

Taxonomic Resolution, Functional Traits, and the Influence of Species Groupings on Mapping Antarctic Seafloor Biodiversity

“…The full biological dataset is published in Robineau et al (2018) and is publically available through the Australian Antarctic Division doi: 10.4225/15/5ae7cf565cebb.…”