Small-scale non-linear geostatistical analysis of Liocarcinus depurator (Crustacea: Brachyura) abundance and size structure in a western Mediterranean population

Abstract

The small-scale spatial distribution of density and biomass of the crab Liocarcinus depurator off the Ebro delta was analysed using universal kriging (non-linear geostatistics), considering depth as an external trend. In order to understand the spatial distribution of crab size, a third variable was created from the residuals of the non-linear regression between biomass and density. Variogram analysis of crab density and residuals of the biomass/density relationship presented a quadratic relationship with depth, while biomass showed a linear relationship with depth. All experimental variograms were fitted to spherical models. The patch size (range) found was 10.64 km for density, 14.53 km for biomass and 20.49 km for the residual variables. The spatial distribution of 8 sediment variables (temperature, redox potential at 1 and 6 cm depth [R1 and R6], carbonate content [CO 3 ], median grain size [ϕ], sediment sorting [IGSD: inclusive graphic standard deviation] and organic matter content [OM]) was studied. The maps obtained were compared with those calculated for the biological variables of L. depurator using Mantel and partial Mantel tests. Distribution characteristics of this species were significantly affected by most sediment variables considered, particularly by temperature, organic matter content and redox potential, although overall the correlation level was low, coinciding with the generalist ecological role and opportunistic behaviour of the species. Density and biomass, as well as residuals, presented a negative correlation with the sorting coefficient (IGSD) and with carbonates. In relation to IGSD, high densities of L. depurator were found in homogeneous sediments. Residuals (size structure of the population) were significantly correlated with grain size (ϕ), with larger individuals occurring in finer sediments, while juveniles were preferably found in areas with very fine sand sediments. Both density and biomass presented significant positive correlations with the redox potential, indicating that the species favoured well-oxygenated sediments with a low organic content.

Decapod crustacean assemblages off the West coast of central Italy (western Mediterranean)

“…These species are linked more to sediment type and to the amount of suspended organic matter (Vernberg and Vernberg 1983;Rufino et al, 2004). Sediment characteristics have been found to strongly influence occurrence and distribution of many benthic decapod crustaceans, especially those with burrowing and burying habits (Atkinson and Taylor, 1988;Pinheiro et al, 1996;Comeau et al, 1998).…”

Geographic, bathymetric and inter-annual variability in the distribution of <i>Liocarcinus depurator</i> (Brachyura: Portunidae) along the Mediterranean coast of the Iberian peninsula

“…In deeper waters along the upper and middle continental slope, muddy sediments again constitute the most widespread type of sediment (Blake and Doyle, 1983). In this context, L. depurator appears to clearly favour muddy sediments over sandy or coarser sediments normally associated with higher water current velocities (Minervini et al, 1982;Rufino et al, 2004). Similar patterns of bimodal depth distribution associated with sediments with different proportions of coarse particles are found in the study areas for the distributions of burying and burrowing decapod crustaceans, such as the crabs Goneplax rhomboides, Medorippe lanata, Calappa granulata and Monodaeus couchi, the Norway lobster Nephrops norvegicus and the hermit crabs Dardanus arrosor and Pagurus prideaux (Abelló et al, 1988;Abelló et al, 2002).…”

Spatial designs and properties of spatial correlation: Effects on covariance estimation

“…Numerous authors interpret the effective range in the exponential covariance function as a measure to describe the spatial heterogeneity or "patchiness" in a landscape (e.g., Saetre and Baath 2000;Franklin et al 2002;Schwarz et al 2003;Rufino et al 2004;Kennard and Outcalt 2006). Dalthorp et al (2000) demonstrated with discrete data that the range and nugget parameters influence the patch configuration on a simulated landscape, although Schabenberger and Gotway (2005, p. 140) questioned the use of the range parameter as an estimate of patch size.…”

“…Indeed, spatial covariance parameter estimates in ecological settings have been interpreted to describe the spatial heterogeneity or "patchiness" in a landscape that cannot be explained by measured covariates (e.g., Rossi et al 1992;Bellehumeur and Legendre 1998;Dalthorp et al 2000;Augustine and Frank 2001;Schwarz et al 2003;Rufino et al 2004;Kennard and Outcalt 2006).…”