Predicting the distribution of a portunid crab in Patagonian coastal waters

Ovalipes trimaculatus is a commercially important, cosmopolitan portunid crab. However, environmental conditions that drive its distribution have never been studied. Thus, we aimed to assess the habitat preferences of this species in northern Patagonia by developing a species distribution model. We...

Full description

Saved in:
Bibliographic Details
Published in:Marine ecology. Progress series (Halstenbek) 2020-03, Vol.638, p.95-105
Main Authors: de la Barra, Paula, Svendsen, Guillermo, Romero, M. Alejandra, Avaca, M. Soledad, Narvarte, Maite
Format: Article
Language:English
Subjects:
Benthos
Biomass
Coastal waters
Commercial fishing
Density
Depth
Ecological distribution
Environmental conditions
Fishers
Fishing grounds
Fishing zones
Geographical distribution
Granulometry
Habitat preferences
Habitat selection
Marine crustaceans
Prey
Species
Substrates
Surveying
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Ovalipes trimaculatus is a commercially important, cosmopolitan portunid crab. However, environmental conditions that drive its distribution have never been studied. Thus, we aimed to assess the habitat preferences of this species in northern Patagonia by developing a species distribution model. We obtained spatial quantitative data of the crab and its prey species from a benthic survey performed prior to commercial fishing in the area. We used measurements of environmental condition, biomass, richness and evenness of its prey as predictors, and modeled the density of O. trimaculatus through a delta-gamma model, and produced a map of its predicted biomass. Prey biomass, depth and substrate type were the most important variables for predicting the distribution of O. trimaculatus. The model predicts a restricted depth range, with maximum crab density at 10 m (the shallowest depth sampled) in bottom substrates of relatively fine granulometry, such as silty sand and silt. Prey biomass does not determine crab presence, but, where the crab is present, higher prey biomass correlates with higher crab abundance. Our results accurately predicted 1 of the 2 actual fishing grounds; hence, the model may be a useful tool for local fishers and managers.
ISSN:0171-8630
1616-1599
DOI:10.3354/meps13249