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Predicting cetacean habitats from their energetic needs and the distribution of their prey in two contrasted tropical regions

PloS one, 2014-08, Vol.9 (8), p.e105958-e105958

2014

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Predicting top predator habitats in the Southwest Indian Ocean

Ecography (Copenhagen), 2014-03, Vol.37 (3), p.261-278

2014

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Assessing the impact of bycatch on dolphin populations: the case of the common dolphin in the eastern North Atlantic

PloS one, 2012-02, Vol.7 (2), p.e32615-e32615

2012

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FISHGLOB_data: an integrated dataset of fish biodiversity sampled with scientific bottom-trawl surveys

Scientific data, 2024-01, Vol.11 (1), p.24-24, Article 24

2024

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Predicting bycatch hotspots in tropical tuna purse seine fisheries at the basin scale

Global ecology and conservation, 2020-12, Vol.24, p.e01393, Article e01393

2020

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Corrigendum to “Predicting bycatch hotspots in tropical tuna purse seine fisheries at the basin scale” [Global Ecol. Conserv. 24 (2020) e01393]

Global ecology and conservation, 2021-01, Vol.25, p.e01427, Article e01427

2021

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Assessing the effects of coral reef habitat and marine protected areas on threatened megafauna using aerial surveys

Aquatic conservation, 2023-03, Vol.33 (3), p.286-297

2023

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Putting eagle rays on the map by coupling aerial video-surveys and deep learning

Biological conservation, 2022-03, Vol.267, p.109494, Article 109494

2022

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Extrapolating cetacean densities beyond surveyed regions: habitat-based predictions in the circumtropical belt

Journal of biogeography, 2015-07, Vol.42 (7), p.1267-1280

2015

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Leveraging social media and deep learning to detect rare megafauna in video surveys

Conservation biology, 2022-02, Vol.36 (1), p.e13798-n/a

2022

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Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

Conservation biology, 2017-06, Vol.31 (3), p.601-614

2017

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dsmextra: Extrapolation assessment tools for density surface models

Methods in ecology and evolution, 2020-11, Vol.11 (11), p.1464-1469

2020

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Geographical differences in habitat relationships of cetaceans across an ocean basin

Ecography (Copenhagen), 2020-08, Vol.43 (8), p.1250-1259

2020

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Reviewing the science on 50 years of conservation: Knowledge production biases and lessons for practice

Ambio, 2024-07

2024

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Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

Scientific reports, 2016-03, Vol.6 (1), p.22615-22615, Article 22615

2016

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Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

Diversity & distributions, 2017-10, Vol.23 (9/10), p.1098-1109

2017

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Contrasting ecological information content in whaling archives with modern cetacean surveys for conservation planning and identification of historical distribution changes

Conservation biology, 2023-06, Vol.37 (3), p.e14043-n/a

2023

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Predicting cetacean and seabird habitats across a productivity gradient in the South Pacific gyre

Progress in oceanography, 2014-01, Vol.120, p.383-398

2014

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Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

Conservation biology, 2017-06, Vol.31 (3), p.601

2017

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Divergent responses of pelagic and benthic fish body-size structure to remoteness and protection from humans

Science (American Association for the Advancement of Science), 2024-03, Vol.383 (6686), p.976-982

2024

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Assessing cetacean surveys throughout the Mediterranean Sea: a gap analysis in environmental space

Scientific reports, 2018-02, Vol.8 (1), p.3126-14, Article 3126

2018

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Artificial Intelligence and Social Networks Can Help to Protect the Famous Dugong

Frontiers for young minds, 2022-10, Vol.10

2022

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Predicting cetacean habitats from their energetic needs and the distribution of their prey in two contrasted tropical regions

Predicting top predator habitats in the Southwest Indian Ocean

Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?

Assessing the impact of bycatch on dolphin populations: the case of the common dolphin in the eastern North Atlantic

FISHGLOB_data: an integrated dataset of fish biodiversity sampled with scientific bottom-trawl surveys

Predicting bycatch hotspots in tropical tuna purse seine fisheries at the basin scale

Corrigendum to “Predicting bycatch hotspots in tropical tuna purse seine fisheries at the basin scale” [Global Ecol. Conserv. 24 (2020) e01393]

Assessing the effects of coral reef habitat and marine protected areas on threatened megafauna using aerial surveys

Putting eagle rays on the map by coupling aerial video-surveys and deep learning

Extrapolating cetacean densities beyond surveyed regions: habitat-based predictions in the circumtropical belt

Leveraging social media and deep learning to detect rare megafauna in video surveys

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

dsmextra: Extrapolation assessment tools for density surface models

Geographical differences in habitat relationships of cetaceans across an ocean basin

Reviewing the science on 50 years of conservation: Knowledge production biases and lessons for practice

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

Contrasting ecological information content in whaling archives with modern cetacean surveys for conservation planning and identification of historical distribution changes

Predicting cetacean and seabird habitats across a productivity gradient in the South Pacific gyre

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

Divergent responses of pelagic and benthic fish body-size structure to remoteness and protection from humans

Assessing cetacean surveys throughout the Mediterranean Sea: a gap analysis in environmental space

Combining multiple visual surveys to model the habitat of deep‐diving cetaceans at the basin scale: Large‐scale modelling of deep‐diving cetacean habitats

Artificial Intelligence and Social Networks Can Help to Protect the Famous Dugong

Combining multiple visual surveys to model the habitat of deep‐diving cetaceans at the basin scale

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