Temporal and spatial variability in availability bias has consequences for marine bird abundance estimates during the non‐breeding season DOI Creative Commons
Ruth E. Dunn, James Duckworth, Susan O’Brien

et al.

Ecological Solutions and Evidence, Journal Year: 2024, Volume and Issue: 5(4)

Published: Oct. 1, 2024

Abstract To effectively monitor how marine ecosystems are being reshaped by anthropogenic pressures, we require understanding of species abundances and distributions. Due to their socio‐economic ecological value, predatory often at the forefront survey efforts. However, data only valuable if they can reliably be converted into estimates underlying We consider at‐sea surveys predators that inform impact assessments offshore windfarms. These subject a form detection bias called ‘availability bias’ whereby individuals which submerged below surface consequently ‘unavailable’ for detection. Although correction factors commonly used in these surveys, currently based on limited may not species‐, time‐, or area‐specific. Here, use time‐depth‐recorder investigate variation bird availability bias. found proportion diving birds sea during daylight hours, therefore unavailable counted varied species, month, area. For three our focal wintering around northwest Europe (Atlantic puffin, common guillemot, razorbill), results were different comparable values previously correct bias, whereas no regularly fourth (red‐throated diver). now present species‐ month‐specific areas study populations non‐breeding seasons: North Sea, north west coasts UK, Baltic Icelandic coastal waters. Practical implication : Variation hours spent lead differences factors, thereby impacting estimations abundances. encourage from area, month conducted provide more accurate abundance estimates. Using relevant will result increasingly distribution birds, with relevance range applications including planning windfarm developments, designation monitoring protected areas, environmental change.

Language: Английский

On the impact of preferential sampling on ecological status and trend assessment DOI
Philippe Aubry, Charlotte Francesiaz, Matthieu Guillemain

et al.

Ecological Modelling, Journal Year: 2024, Volume and Issue: 492, P. 110707 - 110707

Published: April 9, 2024

Language: Английский

Citations

8
Global impact of the COVID-19 lockdown on biodiversity data collection DOI Creative Commons
Stephanie Roilo, Jan O. Engler, Anna F. Cord

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 13, 2025

Abstract The COVID-19 pandemic triggered different governmental responses across borders, with cascading effects on people’s movements and biodiversity data collection. We quantified changes in the number of species occurrence records collected during first global lockdown (March 15th to May 1st 2020) relative pre-pandemic levels using from Global Biodiversity Information Facility (GBIF). modelled how such relate stringency policy responses, human mobility, countries’ population size economic class 129 countries. further focused community science project eBird, which constitutes largest dataset GBIF, investigate participation activity patterns individual observers (eBirders) lockdown. found that decreases GBIF correlated declines numbers visitors parks outdoor areas, were significantly larger developing countries compared developed ones. While ranges eBirders shrunk all analysed, least declined more than countries, as disrupted influx international visitors. Our results suggest community-based, local monitoring programmes are essential reduce biases monitoring.

Language: Английский

Citations

0
Defining model complexity: An ecological perspective DOI Creative Commons
Charlotte Malmborg, Alyssa Willson, L. M. Bradley

et al.

Meteorological Applications, Journal Year: 2024, Volume and Issue: 31(3)

Published: May 1, 2024

Abstract Models have become a key component of scientific hypothesis testing and climate sustainability planning, as enabled by increased data availability computing power. As result, understanding how the perceived ‘complexity’ model corresponds to its accuracy predictive power has prevalent research topic. However, wide variety definitions complexity been proposed used, leading an imprecise what is consequences across studies, study systems, disciplines. Here, we propose more explicit definition complexity, incorporating four facets—model class, inputs, parameters, computational complexity—which are modulated real‐world process being modelled. We illustrate these facets with several examples drawn from ecological literature. Overall, argue that precise terminology metrics (e.g., number inputs) may be necessary characterize emergent outcomes including comparison, performance, transferability decision support.

Language: Английский

Citations

2
Temporal and spatial variability in availability bias has consequences for marine bird abundance estimates during the non-breeding season DOI Creative Commons
Ruth E. Dunn, James Duckworth, Susan O’Brien

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 14, 2024

Abstract To effectively monitor how marine ecosystems are being reshaped by anthropogenic pressures, we require understanding of species abundances and distributions. Due to their socio-economic ecological value, predatory often at the forefront survey efforts. However, data only valuable if they can reliably be converted into estimates underlying We consider at-sea surveys predators that inform impact assessments offshore windfarms. These subject a form detection bias called ‘availability bias’ whereby individuals which submerged below surface consequently ‘unavailable’ for detection. Although correction factors commonly used in these surveys, currently based on limited may not species-, time-, or area-specific. Here, use time-depth-recorder investigate variation bird availability bias. found proportion diving birds sea during daylight hours, therefore unavailable counted varied species, month, area. For three our focal wintering around northwest Europe (Atlantic puffin, common guillemot, razorbill) results were different comparable values previously correct bias, whereas no regularly fourth (red-throated diver). now present species- month-specific areas study populations non-breeding seasons: North Sea, north west coasts UK, Baltic Icelandic coastal waters. Synthesis applications: Variation hours spent lead differences factors, thereby impacting estimations abundances. encourage from area, month conducted provide more accurate abundance estimates. Using relevant will result increasingly distribution birds, with relevance range applications including planning windfarm developments, designation monitoring protected areas, environmental change.

Language: Английский

Citations

1
Temporal and spatial variability in availability bias has consequences for marine bird abundance estimates during the non‐breeding season DOI Creative Commons
Ruth E. Dunn, James Duckworth, Susan O’Brien

et al.

Ecological Solutions and Evidence, Journal Year: 2024, Volume and Issue: 5(4)

Published: Oct. 1, 2024

Abstract To effectively monitor how marine ecosystems are being reshaped by anthropogenic pressures, we require understanding of species abundances and distributions. Due to their socio‐economic ecological value, predatory often at the forefront survey efforts. However, data only valuable if they can reliably be converted into estimates underlying We consider at‐sea surveys predators that inform impact assessments offshore windfarms. These subject a form detection bias called ‘availability bias’ whereby individuals which submerged below surface consequently ‘unavailable’ for detection. Although correction factors commonly used in these surveys, currently based on limited may not species‐, time‐, or area‐specific. Here, use time‐depth‐recorder investigate variation bird availability bias. found proportion diving birds sea during daylight hours, therefore unavailable counted varied species, month, area. For three our focal wintering around northwest Europe (Atlantic puffin, common guillemot, razorbill), results were different comparable values previously correct bias, whereas no regularly fourth (red‐throated diver). now present species‐ month‐specific areas study populations non‐breeding seasons: North Sea, north west coasts UK, Baltic Icelandic coastal waters. Practical implication : Variation hours spent lead differences factors, thereby impacting estimations abundances. encourage from area, month conducted provide more accurate abundance estimates. Using relevant will result increasingly distribution birds, with relevance range applications including planning windfarm developments, designation monitoring protected areas, environmental change.

Language: Английский

Citations

0