High seas marine protected areas: Benthic environmental conservation priorities from a GIS analysis of global ocean biophysical data

Harris, Peter T.; Whiteway, Tanya

doi:10.1016/j.ocecoaman.2008.09.009

Cited by 75 publications

(52 citation statements)

References 20 publications

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“…Water depth is either directly or indirectly related to several variables such as temperature, pressure, light availability, presence and abundance of predator or prey species and food supply, and therefore exerts a first order control over the occurrence of species in the oceans. However, some authors have discussed whether water depth is in fact the most important factor or whether it is an indirect surrogate for the distribution of benthic species (ENTRAMBASAGUAS et al, 2008;HARRIS;WHITEWAY, 2009). Furthermore, there was a strong correlation between many of the environmental variables used in the analyses, and although the model is robust in this regard, the jackknife results from the Maxent may only be taken as a guide.…”

Section: Discussionmentioning

confidence: 99%

“…According to Harris and Whiteway (2009), to be ''representative'' the MPA should contain areas that reasonably reflect the biotic diversity of the marine ecosystems from which they derive. In addition, Edgar et al (2008) highlighted the need to maximize representation and persistence of biodiversity in comprehensive protected areas, focusing especially on threatened and under-protected ecosystems and species threatened with extinction.…”

Section: Introductionmentioning

confidence: 99%

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Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil

Magris

Déstro

2010

Braz. j. oceanogr.

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A B S T R A C TSpatial analysis and modeling tools were employed to predict suitable habitat distribution for threatened marine invertebrates and estimate the overlap between highly suitable areas for these species and the Brazilian marine protected areas (MPAs). Records of the occurrence of species were obtained from the collections included in the Ocean Biogeographic Information System (OBISBrazil), with additional records culled from the literature. The distribution data of 16 out of 33 threatened species, with at least ten occurrences in the available records, were selected for modeling by Maxent algorithm (Maximum Entropy Modeling) based on environmental variables (temperature, salinity, bathymetry and their derivatives). The resulting maps were filtered with a fixed threshold of 0.5 (to distinguish only the highly suitable areas) and superimposed on MPA digital maps. The algorithm produced reasonable predictions of the species' potential distributions, showing that the patterns predicted by the model are largely consistent with current knowledge of the species. The distribution of the highly suitable areas showed little overlapping with Brazilian MPAs. This study showed how the habitat suitability for threatened species can be assessed using GIS applications and modeling tools. R E S U M ONeste estudo foram utilizadas análises espaciais e ferramentas de modelagem para predizer a distribuição dos hábitats adequados aos invertebrados marinhos ameaçados e estimar a sobreposição destas áreas em relação às áreas marinhas protegidas existentes. Registros de ocorrência das espécies foram obtidos das coleções incluídas no Ocean Biogeographic Information System (OBIS-Brasil) e de dados provenientes da literatura. Dados de distribuição de 16 das 33 espécies ameaçadas, com pelo menos 10 registros de ocorrência, foram selecionados para modelagem utilizando o algoritmo Maxent (Maximum Entropy Modeling) e variáveis ambientais (temperatura, salinidade, batimetria e derivados). Os mapas resultantes foram filtrados para obtenção de áreas altamente adequadas, através de um limiar de corte de 0.5, e sobrepostos com o mapa digital de áreas protegidas. O algoritmo apresentou modelos de predição satisfatórios, mostrando que os padrões previstos no modelo são coerentes com o conhecimento atual sobre as espécies. A distribuição das áreas altamente adequadas mostrou baixa sobreposição com as áreas protegidas brasileiras. Este estudo indicou como a adequabilidade de hábitats para espécies ameaçadas pode ser realizada, utilizando aplicações em SIG e ferramentas de modelagem.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil

Magris

Déstro

2010

Braz. j. oceanogr.

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“…In accordance with the aforementioned UNGA resolutions [24][25][26][27][28] The use of spatial management tools to preserve the marine biodiversity of species inhabiting the HS has been broadly discussed in recent years [55]. To make such spatial management possible, our immediate objectives are: assessing specific biodiversity (mainly describing new species to science); describing the different habitats, ecosystems and deep-sea geomorphological features identified; and analysing their interactions and relationships to protect the full range of potentially different habitats.…”

Section: Methodsmentioning

confidence: 99%

A First Approach to Assess the Impact of Bottom Trawling Over Vulnerable Marine Ecosystems on the High Seas of the Southwest Atlantic

Portela¹,

Cristobo²,

Ríos³

et al. 2015

Biodiversity in Ecosystems - Linking Structure and Function

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“…This has been well established for the genus Sterechinus, which includes 2 species with different depth range distribution (Brey & Gutt 1991, Jacob et al 2003, David et al 2005a. In marine habitats, depth is correlated to many environmental factors such as light intensity, temperature, salinity, predator or competitor occurrence and food supplies (Harris & Whiteway 2009 neumayeri generated by (A, B) GARP, using the median commission value (area under the receiver operating curve, AUC = 0.85 for S. antarcticus and 0.91 for S. neumayeri), (C, D) GARP, using the Maxent 'best fit' commission value (AUC = 0.89 for S. ant arcticus and 0.87 for S. neumayeri) and (E, F) Maxent (AUC = 0.97 for S. antarcticus and 0.98 for S. neumayeri). Maps were generated using 8 continuous environmental variables.…”

Section: Ecological Relevance Of Modelsmentioning

confidence: 97%

Large-scale distribution analysis of Antarctic echinoids using ecological niche modelling

Pierrat¹,

Saucède²,

Laffont³

et al. 2012

Mar. Ecol. Prog. Ser.

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Understanding the factors that determine the distribution of taxa at various spatial scales is a crucial challenge in the context of global climate change. This holds particularly true for polar marine biota that are composed of both highly adapted and vulnerable faunas. We analysed the distribution of 2 Antarctic echinoid species, Sterechinus antarcticus and S. neumayeri, at the scale of the entire Southern Ocean using 2 niche modelling procedures. The performance of distribution models was tested with regard to the known ecology of the species. The respective contributions of environmental parameters are discussed along with the putative roles played by biotic interactions and biogeographic processes. Depth was the parameter that contributed most to both distribution models, whereas sea ice coverage and sea surface temperature had significant contributions for S. neumayeri only. Suitability maps of the 2 species were mostly similar, with a few notable differences. The Campbell Plateau and Tasmania were predicted as suitable areas for S. antarcticus only, while S. neumayeri was restricted to the south of the Ant arctic Polar Front. However, numerous sampling data attest that S. antarcticus is absent from the Campbell Plateau and from Tasmania. Different hypotheses are formulated to explain the mismatch between observed and modelled distribution data. They stress the putative roles played by both oceanographic barriers to dispersal (Antarctic Polar Front), biotic factors (species exclusion patterns) and biogeographic processes (ongoing dispersal).KEY WORDS: Habitat suitability map · Sterechinus · Echinoidea · GARP · Maxent · Southern OceanResale or republication not permitted without written consent of the publisher

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High seas marine protected areas: Benthic environmental conservation priorities from a GIS analysis of global ocean biophysical data

Cited by 75 publications

References 20 publications

Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil

Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil

A First Approach to Assess the Impact of Bottom Trawling Over Vulnerable Marine Ecosystems on the High Seas of the Southwest Atlantic

Large-scale distribution analysis of Antarctic echinoids using ecological niche modelling

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