Atlas of cetacean distribution in North-West European waters, compiled and edited by James B. Reid, Peter G. H. Evans and Simon P. Northridge. Joint Nature Conservation Committee, Peterborough, 2003, 76 pp. Price £17.00.

Distribution maps of cetaceans and seabirds at basin and monthly scales are needed for conservation and marine management. These are usually created from standardised and systematic aerial and vessel surveys, with recorded animal densities interpolated across study areas. However, distribution maps at basin and monthly scales have previously not been possible because individual surveys have restricted spatial and temporal coverage. This study develops an alternative approach consisting of: (1) collating diverse survey data to maximise spatial and temporal coverage, (2) using detection functions to estimate variation in the surface area covered (km2) among these surveys, standardising measurements of effort and animal densities, and (3) developing species distribution models (SDM) that overcome issues with heterogeneous and uneven coverage. 2.68 million km of survey data in the North‐East Atlantic between 1980 and 2018 were collated and standardised. SDM using Generalized Linear Models and General Estimating Equations in a hurdle approach were developed. Distribution maps were then created for 12 cetacean and 12 seabird species at 10 km and monthly resolution. Qualitative and quantitative assessment indicated good model performance. Synthesis and applications. This study provides the largest ever collation and standardisation of diverse survey data for cetaceans and seabirds, and the most comprehensive distribution maps of these taxa in the North‐East Atlantic. These distribution maps have numerous applications including the identification of important areas needing protection, and the quantification of overlap between vulnerable species and anthropogenic activities. This study demonstrates how the analysis of existing and diverse survey data can meet conservation and marine management needs.

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Distribution maps of cetacean and seabird populations in the North‐East Atlantic

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Seabirds: A Natural History

The North Sea basin is one of the busiest maritime areas globally with a considerable number of anthropogenic pressures impacting the functioning of the marine ecosystem. Due to growing EU ambitions for the deployment of large offshore wind farm projects (OWF), as part of the 2050 renewable energy roadmap, there is a key need for a holistic understanding of OWF potential impacts on the marine ecosystem. We propose a holistic Cumulative Effect Assessment methodology, applied using a geo-spatial open-source software, to assess impacts of OWF related pressures on selected seabed habitats, fish, seabird and mammal species. We take into account pressures specific to the three OWF development phases, spanning 1999–2050, for the entire North Sea basin. Our results underline 2022 as the peak year of cumulative impacts for the approved OWFs, followed by a considerable increase in potential impacts of the planned 212GWs, by 2050. The spatio-temporal analysis of the OWF environmental impacts presents the shift between highly impacted areas over the studied timeline and distinguishes between concentrated areas of high impacts (S–E of UK) and dispersed areas of high impacts (Germany). Our results can inform decision-makers and the OWF industry in a joint effort to mitigate the environmental impacts of future large OWF developments.

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Spatial and temporal analysis of cumulative environmental effects of offshore wind farms in the North Sea basin

Methodological analysis of bioclimatic variable selection in species distribution modeling with application to agricultural pests (Metcalfa pruinosa and Spodoptera litura)

Species distribution modelling is needed to support ecological impact assessments

Aim Spatial sampling biases in biodiversity data arise because of complex interactions between geography, species characteristics and human behaviour, including preferences for or against particular species or habitats; biases are therefore not necessarily independent of the environmental niches of species. We evaluate when correlations between spatial sampling biases and environmental niches are likely to affect species distribution models (SDMs) developed both with and without attempts to correct these biases. Innovation A virtual species and virtual ecologist framework was used to simulate biodiversity data with either no spatial sampling bias or biases that were correlated (positively or negatively) with one of the environmental variables used to define the environmental niches of the species. The environmental variables used to define the species niche were simulated with spatial autocorrelation operating at multiple spatial scales. Virtual samples were then used to model species distributions, with models evaluated based on their ability to rank the suitability of sites correctly. Main conclusions Correlations between spatial sampling bias and environmental niches frequently reduced the rank correlation of model predictions, but the relative importance of these effects varied with species type (greater decline in rank correlation as the environmental niche broadens) and data type (models built using detection/non-detection data were less affected than those using detection-only data). Bias-correction effectiveness varied depending on the structure of the spatial bias but was also highly variable across methods and dependent on data type. The implications of these results are that spatial sampling bias is a greater concern for SDMs where: (1) the distribution of effort is non-random with respect to an environmental gradient thought to be correlated with a species’ distribution; (2) the species being modelled has a broad environmental niche; and (3) the data for modelling contain only information on detections (i.e., presence only). 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/geb.13491

Martin Goodall

Papers

Distribution maps of cetacean and seabird populations in the North‐East Atlantic

Species distribution modelling is needed to support ecological impact assessments

Correlations between spatial sampling biases and environmental niches affect species distribution models

Data from: Distribution maps of cetacean and seabird populations in the North-East Atlantic