Abstract
Species mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Essential Fish Habitats of three elasmobranch species (S. canicula, G. melastomus, and E. spinax). Similarity and prediction statistics are used to compare the two different spatial patterns obtained by applying the same Bayesian spatio-temporal modelling approach in the two sources. Results showed that the spatial patterns obtained are similar, although differences are present. In particular, models based on fishery-dependent data are better able to identify temporal relationships between the probability of presence of the species and seasonal environmental variables. In contrast, fishery-independent data better discriminate spatial locations where a species is present or absent. Besides the spatial and temporal differences of the two datasets, the consistency of habitat results highlights the inclusion in each dataset of most of the environmental envelope of each species, both in time and space. Consequently, sampling data should be adapted to each species to reasonably cover their environmental envelope, and a combination of datasets will likely provide a better habitat estimation than using each dataset independently. These findings can be useful in helping fishery managers improve definition of survey design and analyses.
Static Representation Exposing Spatial Changes in Spatio-Temporal Dependent Data