A GIS environmental modelling approach to essential fish habitat designation

Valavanis, Vasilis D.; Georgakarakos, S.; Kapantagakis, Argyris; Palialexis, Andreas; Katara, Isidora

doi:10.1016/j.ecolmodel.2004.02.015

Cited by 84 publications

(30 citation statements)

References 21 publications

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“…Surface temperature measurements were used in order to replace missing SST values, in satellite imageries, frequently observed in overcast or coastal areas. Satellite images, provided by the German Aerospace Agency's (DLR) and the Distributed Active Archive Center (NASA), were transformed into Sea Surface Temperature (SST) in Celsius and Sea Surface Chlorophyll-a concentration (SSC) using GIS tools (Valavanis et al, 2004). Salinity data have not been used, since the analysis is restricted to the two provided satellite imageries and the acoustically measured bottom depth.…”

Section: Data Collectionmentioning

confidence: 99%

Mapping abundance distribution of small pelagic species applying hydroacoustics and Co-Kriging techniques

Georgakarakos

Kitsiou

2008

Hydrobiologia

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Hydroacoustic technology provides ground tools for the estimation of abundance and spatial distribution of pelagic species. The final products of such surveys, the interpolated choropleth maps, are based on a Geostatistical analysis of the acoustic measurements to minimise, as much as possible, the interpolation error, and to quantify uncertainty. The current study is based on fisheries acoustic measurements and satellite images covering the sea area of Thermaikos Gulf over the years 1996, 1997 and 1998. Spatial interpolations describing the abundance and distribution of small pelagic species in the research area, as well as sea surface temperature (SST), Chlorophyll-a content (SSC) and average depth, were produced, based on Ordinary and Universal Kriging and Co-Kriging Geostatistical methods. The results of the Geostatistical analysis showed that the Co-Kriging spatial interpolation method produced the best results regarding fish abundance when SST and average depth variables were included in the model. The latter indicates that there is an existing spatial cross-correlation between fish abundance and the environmental variables. Consequently, the potential reduction of the overall error in the estimation process, as presented in this study, is very significant, particularly with regard to error reduction in stock assessment and management.

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Section: Data Collectionmentioning

confidence: 99%

Mapping abundance distribution of small pelagic species applying hydroacoustics and Co-Kriging techniques

Georgakarakos

Kitsiou

2008

Hydrobiologia

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“…These include readily available remotely sensed data on a variety of surface oceanographic parameters, Geographic Information Systems (GIS) and powerful statistical modelling tools such as generalised additive models (GAM), which allow modelling of non-linear relationships, and generalised additive mixed models (GAMM), the latter allowing explicit consideration of spatial autocorrelation, particularly through the development of the ''R'' programming language (see Pierce et al, 2001Pierce et al, , 2002Valavanis et al, 2008Valavanis et al, , 2004Zuur et al, 2007). Valavanis et al (2004) adopted a GIS-environmental modelling approach to identify EFH for short-finned squid (Illex coindetti) in the eastern Mediterranean Sea. Koubbi et al (2006) reported an application on habitat modelling for flatfish larvae in the eastern English Channel.…”

Section: Introductionmentioning

confidence: 99%

Identifying essential fish habitat for small pelagic species in Spanish Mediterranean waters

et al. 2008

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Populations of small pelagic fish support important fisheries in Spanish Mediterranean waters, particularly sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus), and are distributed along the entire length of the Spanish continental shelf. Using annual acoustic survey data for the years 2003-2005, a GIS-based environmental modelling approach was used to investigate the distribution and abundance of small pelagic fish in relation to environmental variables. Multivariate analysis was applied to provide a preliminary picture of relationships between fish and environmental conditions, followed by application of Generalised Additive Models (GAMs). GAMs showed the presence/absence of fish to be related to bathymetry, sea surface chlorophyll-a concentration and sea surface temperature (SST). The strength and significance of these relationships varied spatially and temporally. High resolution Essential Fish Habitat (EFH) maps were generated for sardine and anchovy, based on the predicted probability of presence of each species. Substantial inter-annual variability in the distribution and quality of EFH was observed, particularly for anchovy. Identification of EFH is of great importance to assess and manage sardine and anchovy resources as it provides a natural link between population dynamics features and geographical scenarios.

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“…Further, geostatistical tools can be used to assess the effects of trends on catch data (Rufino et al, 2006), such as the importance of factors including habitat association of species and spatial survey scales (Stelzenmüller et al, 2005) or type of fishing gears (Stelzenmüller et al, 2006) on spatial estimations of the distribution patterns of marine resources. Data on species-environment associations have been used to provide such spatially explicit models of habitat suitability by using Geographic Information System (GIS) (Guisan & Zimmermann, 2000;Stoner et al, 2001;Le Pape et al, 2003;Valavanis et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Spatial patterns and GIS habitat modelling of fish in two French Mediterranean coastal areas

et al. 2008

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A GIS environmental modelling approach to essential fish habitat designation

Cited by 84 publications

References 21 publications

Mapping abundance distribution of small pelagic species applying hydroacoustics and Co-Kriging techniques

Mapping abundance distribution of small pelagic species applying hydroacoustics and Co-Kriging techniques

Identifying essential fish habitat for small pelagic species in Spanish Mediterranean waters

Spatial patterns and GIS habitat modelling of fish in two French Mediterranean coastal areas

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