Bio‐ORACLE: a global environmental dataset for marine species distribution modelling

Tyberghein, L.; Verbruggen, Heroen; Pauly, Klaas; Troupin, Charles; Mineur, Frédéric; Clerck, Olivier De

doi:10.1111/j.1466-8238.2011.00656.x

Cited by 713 publications

(553 citation statements)

References 54 publications

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“…water temperature, salinity, depth, nutrient concentrations, seabed types, etc), which are typically easier to record and map across vast expanses (i.e. regional, global scale) in contrast to species and habitat data [42][43][44] . Despite inherent limitations and associated uncertainties, predictive modelling is a cost-effective alternative to field surveys as it can help identifying and mapping where sensitive marine ecosystems may occur.…”

mentioning

confidence: 99%

Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea

Martin

Giannoulaki

Leo

et al. 2014

Sci Rep

131

109

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Bioconstructions such as coralligenous outcrops and maërl beds are typical Mediterranean underwater seascapes. Fine-scale knowledge on the distribution of these sensitive habitats is crucial for their effective management and conservation. In the present study, a thorough review of existing spatial datasets showing the distribution of coralligenous and maërl habitats across the Mediterranean Sea was undertaken, highlighting current gaps in knowledge. Predictive modelling was then carried out, based on environmental predictors, to produce the first continuous maps of these two habitats across the entire basin. These predicted occurrence maps for coralligenous outcrops and maërl beds provide critical information about where the two habitats are most likely to occur. The collated occurrence data and derived distribution model outputs can help addressing the challenge of developing basin-wide spatial plans and to guide cost-effective future surveys and monitoring efforts towards areas that are presently poorly-sampled

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mentioning

confidence: 99%

Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea

Martin

Giannoulaki

Leo

et al. 2014

Sci Rep

131

109

View full text Add to dashboard Cite

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“…Using variables that are at a global scale and averaged across years can be used to describe global patterns, but may not provide information regarding conditions present at small scales and extreme events that could restrict species' distributions. While the decision to not incorporate latitudes above and below 70°north and south (Tyberghein et al, 2012) did not meaningfully restrict occurrence data (only three records for C. maenas in Norway were outside the modeling window), it has implications for invasion risk as increases in access to shipping and future climate modification to the high arctic could alter susceptibility to invasion in this region (Ware et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…Environmental layers were accessed from Bio-ORA-CLE as outlined in Tyberghein et al (2012). The data package 70°N-70°S Real Values was utilized, which included 23 raster layers with 5 arcmin resolution.…”

Section: Environmental Layersmentioning

confidence: 99%

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Modeling invasion risk for coastal marine species utilizing environmental and transport vector data

Crafton

2014

Hydrobiologia

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Invasive species can cause ecological and economic damage and can be transported by several vectors, many of which are connected to socioeconomic activities. This research presents a model that combines introduction likelihood and environmental suitability to characterize global patterns of invasion risk in coastal marine areas by identifying where a species is both likely to arrive and able to survive. The model projects environmental suitability using MaxEnt and considers commercial port locations, as a proxy for commercial shipping, to map patterns of relative invasion risk on a near global scale. A case study of five coastal marine crab species is presented. These models identify several regions that are at risk of new invasion where modeled environmental suitability and introduction likelihood overlap. The distribution of large commercial ports is near global but not evenly distributed; northern hemisphere temperate locations have a higher density of ports and tend to have more opportunities for invasion according to these models. This approach can be adapted to other marine and non-marine species and to current and future environmental and socioeconomic conditions, but it works best when occurrence data are representative of the complete range of conditions under which a species can survive.

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“…The bioclimatic envelope model approach has also been used to quantify potential changes in the global distribution of 115 marine mammals (Kaschner et al, 2011). Predictions for marine mammals are currently more uncertain than for cold-blooded organisms (Kaschner et al, 2011), in part, due to restricted data availability on species occurrence and habitat usage (Kaschner et al, 2011;Tyberghein et al, 2012). Additionally, marine mammals are less constrained by physical environmental conditions than cold-blooded species: the distribution and density of food supply is an important factor in defining their distribution.…”

Section: Quantitative Approaches and Lca Perspectivementioning

confidence: 99%

Towards a meaningful assessment of marine ecological impacts in life cycle assessment (LCA)

Woods

Veltman

Huijbregts

et al. 2016

Environment International

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Human demands on marine resources and space are currently unprecedented and concerns are rising over observed declines in marine biodiversity. A quantitative understanding of the impact of industrial activities on the marine environment is thus essential. Life cycle assessment (LCA) is a widely applied method for quantifying the environmental impact of products and processes. LCA was originally developed to assess the impacts of landbased industries on mainly terrestrial and freshwater ecosystems. As such, impact indicators for major drivers of marine biodiversity loss are currently lacking. We review quantitative approaches for cause-effect assessment of seven major drivers of marine biodiversity loss: climate change, ocean acidification, eutrophication-induced hypoxia, seabed damage, overexploitation of biotic resources, invasive species and marine plastic debris. Our review shows that impact indicators can be developed for all identified drivers, albeit at different levels of coverage of cause-effect pathways and variable levels of uncertainty and spatial coverage. Modeling approaches to predict the spatial distribution and intensity of human-driven interventions in the marine environment are relatively well-established and can be employed to develop spatially-explicit LCA fate factors. Modeling approaches to quantify the effects of these interventions on marine biodiversity are less well-developed. We highlight specific research challenges to facilitate a coherent incorporation of marine biodiversity loss in LCA, thereby making LCA a more comprehensive and robust environmental impact assessment tool. Research challenges of particular importance include i) incorporation of the non-linear behavior of global circulation models (GCMs) within an LCA framework and ii) improving spatial differentiation, especially the representation of coastal regions in GCMs and ocean-carbon cycle models.

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Bio‐ORACLE: a global environmental dataset for marine species distribution modelling

Cited by 713 publications

References 54 publications

Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea

Coralligenous and maërl habitats: predictive modelling to identify their spatial distributions across the Mediterranean Sea

Modeling invasion risk for coastal marine species utilizing environmental and transport vector data

Towards a meaningful assessment of marine ecological impacts in life cycle assessment (LCA)

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