Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Bedriñana‐Romano, Luis; Hucke‐Gaete, Rodrigo; Viddi, Francisco A.; Johnson, Devin S.; Zerbini, Alexandre N.; Morales, Juan Manuel; Mate, Bruce R.; Palacios, Daniel M.

doi:10.1038/s41598-021-82220-5

Cited by 28 publications

(37 citation statements)

References 100 publications

(118 reference statements)

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“…Marine mammal foraging areas often overlap with fisheries 22 , 23 resulting in accidental entanglement, injuries or mortalities 24 , 25 . Shipping lanes intersect with movement corridors leading to collisions 26 – 28 and noise pollution can cause ‘auditory masking’ and permanent or temporary acoustic injuries 29 , 30 . Physical factors such as coastal topography (e.g.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline

Dudhat

Pande

Nair

et al. 2022

Sci Rep

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Marine mammal strandings provide vital information on species’ life histories, population health and status of marine ecosystems. Opportunistic reporting of strandings also serve as a powerful low-cost tool for monitoring these elusive mammals. We collated data over ~ 270 years available through various open access databases, reports and publications. Annual strandings along the Indian coast (mean = 11.25 ± SE 9.1) increased in the last two years of the study (2015–2017, mean = 27.66 ± SE 8.5 strandings /year). We found that stranding events spike during June—September along the west coast and during December–January along the east coast. We identified several sections of the coastline, such as Mumbai (0.38 strandings/km), Kozhikode (0.28 strandings/km), Tuticorin (0.4 strandings/km), Rameswaram (1.82 strandings/km), Chennai (0.32 strandings/km) and Bhubaneshwar (0.26 strandings/km) with a higher number of stranded animals reported. Emerging Hotspot Analysis located new and consecutive hotspots along the north-west coast, and sporadic hotspots along the south-east coast. We recommend establishing regional stranding response centres at the identified hotspots coordinated by a National Stranding Centre with adequately trained personnel and central funding support. Regular stranding response training programs for field veterinarians, and frontline personnel of State Forest Departments near stranding hotspots would provide an improved understanding of marine mammal health and threats in Indian waters. Further, the suggested National Stranding Centre needs to maintain a ‘National Stranding Database’ for long-term marine mammal conservation planning in India.

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Section: Introductionmentioning

confidence: 99%

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline

Dudhat

Pande

Nair

et al. 2022

Sci Rep

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“…We fitted a continuous-time correlated-random-walk model (CTCRW) which estimates two state variables, velocity and true locations from error-prone observed locations, and two parameters, β controlling directional persistence and σ controlling the overall variability in velocity 54 . We used a modified CTCRW that considers β t and σ t to be random variables that vary among continuous time intervals t (expressed in hours) as a function of environmental covariates 55 . A0 and B0 are intercepts, A and B are vectors of slopes, X t is the corresponding design matrix holding covariate data, and ε 1 and ε 2 correspond to standard deviations.…”

Section: Methodsmentioning

confidence: 99%

Individual and joint estimation of humpback whale migratory patterns and their environmental drivers in the Southwest Atlantic Ocean

Bedriñana‐Romano

Zerbini

Andriolo

et al. 2022

Sci Rep

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Humpback whales (Megaptera novaeangliae) perform seasonal migrations from high latitude feeding grounds to low latitude breeding and calving grounds. Feeding grounds at polar regions are currently experiencing major ecosystem modifications, therefore, quantitatively assessing species responses to habitat characteristics is crucial for understanding how whales might respond to such modifications. We analyzed satellite telemetry data from 22 individual humpback whales in the Southwest Atlantic Ocean (SWA). Tagging effort was divided in two periods, 2003–2012 and 2016–2019. Correlations between whale’s movement parameters and environmental variables were used as proxy for inferring behavioral responses to environmental variation. Two versions of a covariate-driven continuous-time correlated random-walk state-space model, were fitted to the data: i) Population-level models (P-models), which assess correlation parameters pooling data across all individuals or groups, and ii) individual-level models (I-models), fitted independently for each tagged whale. Area of Restricted Search behavior (slower and less directionally persistent movement, ARS) was concentrated at cold waters south of the Polar Front (~ 50°S). The best model showed that ARS was expected to occur in coastal areas and over ridges and seamounts. Ice coverage during August of each year was a consistent predictor of ARS across models. Wind stress curl and sea surface temperature anomalies were also correlated with movement parameters but elicited larger inter-individual variation. I-models were consistent with P-models’ predictions for the case of females accompanied by calves (mothers), while males and those of undetermined sex (males +) presented more variability as a group. Spatial predictions of humpback whale behavioral responses showed that feeding grounds for this population are concentrated in the complex system of islands, ridges, and rises of the Scotia Sea and the northern Weddell Ridge. More southernly incursions were observed in recent years, suggesting a potential response to increased temperature and large ice coverage reduction observed in the late 2010s. Although, small sample size and differences in tracking duration precluded appropriately testing predictions for such a distributional shift, our modelling framework showed the efficiency of borrowing statistical strength during data pooling, while pinpointing where more complexity should be added in the future as additional data become available.

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“…Threats that cetacean populations face are multiple, but well-documented ( Bedriñana-Romano et al 2021 , Campana et al 2015 , David et al 2011 , de Stephanis et al 2013 , Garcia-Cegarra et al 2021 , Gero and Whitehead 2016 , Huntington 2009 , Jepson et al 2016 , Jung and Madon In press , Lusseau et al 2009 , Sèbe et al 2019 , Van Waerebeek and Leaper 2008 ). Citizen science can play an important role in the acquisition of ecological data (e.g.…”

Section: Additional Informationmentioning

confidence: 99%

Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe Archipelago, based on citizen science

Coché¹,

Arnaud²,

Bouveret³

et al. 2021

BDJ

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In the French West Indies, more than 20 species of cetaceans have been observed over the last decades. The recognition of this hotspot of biodiversity of marine mammals, observed in the French Exclusive Economic Zone of the West Indies, motivated the French government to create in 2010 a marine protected area (MPA) dedicated to the conservation of marine mammals: the Agoa Sanctuary. Threats that cetacean populations face are multiple, but well-documented. Cetacean conservation can only be achieved if relevant and reliable data are available, starting by occurrence data. In the Guadeloupe Archipelago and in addition to some data collected by the Agoa Sanctuary, occurrence data are mainly available through the contribution of citizen science and of local stakeholders (i.e. non-profit organisations (NPO) and whale-watchers). However, no observation network has been coordinated and no standards exist for cetacean presence data collection and management. In recent years, several whale watchers and NPOs regularly collected cetacean observation data around the Guadeloupe Archipelago. Our objective was to gather datasets from three Guadeloupean whale watchers, two NPOs and the Agoa Sanctuary, that agreed to share their data. These heterogeneous data went through a careful process of curation and standardisation in order to create a new extended database, using a newly-designed metadata set. This aggregated dataset contains a total of 4,704 records of 21 species collected in the Guadeloupe Archipelago from 2000 to 2019. The database was called Kakila ("who is there?" in Guadeloupean Creole). The Kakila database was developed following the FAIR principles with the ultimate objective of ensuring sustainability. All these data were transferred into the PNDB repository (Pöle National de Données de Biodiversité, Biodiversity French Data Hub, https://www.pndb.fr). In the Agoa Sanctuary and surrounding waters, marine mammals have to interact with increasing anthropogenic pressure from growing human activities. In this context, the Kakila database fulfils the need for an organised system to structure marine mammal occurrences collected by multiple local stakeholders with a common objective: contribute to the knowledge and conservation of cetaceans living in the French Antilles waters. Much needed data analysis will enable us to identify high cetacean presence areas, to document the presence of rarer species and to determine areas of possible negative interactions with anthropogenic activities.

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Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Cited by 28 publications

References 100 publications

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline

Individual and joint estimation of humpback whale migratory patterns and their environmental drivers in the Southwest Atlantic Ocean

Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe Archipelago, based on citizen science

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