Large-scale prediction of seagrass distribution: the case of Cymodocea nodosa (Mediterranean-Atlantic)

Understanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. We model the environmental niche of Cymodocea nodosa using a combination of environmental variables and landscape metrics to examine factors defining its distribution and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 ºC to 26.4 ºC and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 m and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems.

Can we use niche models of indicator species to predict the distribution of endangered communities?

European-wide conservation policies are based on the identification of priority habitats. However, research on conservation biogeography often relies on the results and projections of species distribution models to assess species' vulnerability to global change. We assess whether the distribution and structure of threatened communities can be predicted by the suitability of the environmental conditions for their indicator species. We present some preliminary results elucidating if using species distribution models of indicator species at a regional scale is a valid approach to predict these endangered communities. Dune plant assemblages, affected by severe conditions, are excellent models for studying possible interactions among their integrating species and the environment. We use data from an extensive survey of xerophytic inland sand dune scrub communities from Portugal, one of the most threatened habitat types of Europe. We identify indicator shrub species of different types of communities, model their geographical response to the environment, and evaluate whether the output of these niche models are able to predict the distribution of each type of community in a different region.

Size selectivity of trammel nets in southern European small-scale fisheries

Trammel net size selectivity was studied for the most important metiers in four southern European areas: the Cantabrian Sea (Atlantic, Basque Country, Spain), the Algarve (Atlantic, southern Portugal), the Gulf of Cadiz (Atlantic, Spain) and the Cyclades Islands (Mediterranean, Aegean Sea, Greece). These metiers were: cuttlefish (Sepia officinalis) and soles (Solea senegalensis, Microchirus azevia, Synaptura lusitanica) in the Algarve and the Gulf of Cadiz, sole (Solea solea) in the Cantabrian Sea and mixed fin-fish in the Cyclades. In each area, experimental trammel nets of six different types (combinations of two large outer panel mesh sizes and three small inner panel meshes) were constructed. Fishing trials were carried out on a seasonal basis (four seasons in the Cantabrian Sea, Algarve and Cyclades and two seasons in the Gulf of Cadiz) with chartered commercial fishing vessels. Overall, size selectivity was estimated for 17 out of 28 species for which sufficient data were available. Trammel nets generally caught a wide size range of the most important species, with length frequency distributions that were skewed to the right and/or bi-modal. In many cases the length frequency distributions of the different nets were highly overlapped. The Kolmogorov-Smirnov test also showed that the large outer panel meshes generally had no effect in terms of size selectivity, while the opposite was true for the small inner panel ones. Six different selectivity models (normal scale, normal location, gamma, log-normal, bi-modal and gamma semi-Wileman) were fitted to data for the most abundant species in the four areas. For fish, the bi-modal model provided the best fits for the majority of the data sets, with the uni-modal models giving poor fits in most cases. For Sepia officinalis, where trammelling or pocketing was the method of capture in 100% of the cases, the logistic model fitted by maximum likelihood was judged to be more appropriate for describing the size selective properties of the trammel nets. Our results, which are among the first ones on trammel net selectivity in European waters, will be useful for evaluating the impacts of competing gear for the socio-economically important small-scale static gear fisheries. (c) 2006 Elsevier B.V All rights reserved.