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Ferreira LC, Jenner C, Jenner M, Udyawer V, Radford B, Davenport A, Moller L, Andrews-Goff V, Double M, Thums M. Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data. MOVEMENT ECOLOGY 2024; 12:42. [PMID: 38845039 PMCID: PMC11157879 DOI: 10.1186/s40462-024-00481-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 05/21/2024] [Indexed: 06/09/2024]
Abstract
BACKGROUND Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species. METHODS We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia. RESULTS Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence. CONCLUSIONS Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.
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Affiliation(s)
- Luciana C Ferreira
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia.
| | - Curt Jenner
- Centre for Whale Research (WA) Inc., Fremantle, WA, Australia
| | | | - Vinay Udyawer
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
| | - Ben Radford
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
| | - Andrew Davenport
- Centre for Whale Research (WA) Inc., Fremantle, WA, Australia
- Centre for Marine Science and Technology, Curtin University, Bentley, WA, Australia
| | - Luciana Moller
- Cetacean Ecology, Behaviour and Evolution Lab, College of Science and Engineering, Flinders University, Bedford Park, SA, Australia
| | - Virginia Andrews-Goff
- Australian Antarctic Division, Department of Climate Change, Energy, the Environment and Water, Kingston, TAS, Australia
| | - Mike Double
- Australian Antarctic Division, Department of Climate Change, Energy, the Environment and Water, Kingston, TAS, Australia
| | - Michele Thums
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
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Hardin EE, Cullen JA, Fuentes MMPB. Comparing acoustic and satellite telemetry: an analysis quantifying the space use of Chelonia mydas in Bimini, Bahamas. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231152. [PMID: 38204794 PMCID: PMC10776224 DOI: 10.1098/rsos.231152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024]
Abstract
Passive acoustic and Argos satellite telemetry are common methods for tracking marine species and are often used similarly to quantify space use. However, data-driven comparisons of these methods and their associated ecological inferences are limited. To address this, we compared temporal durations, spatial resolutions, financial costs and estimates of occurrence and range distributions for each tracking approach using nine juvenile green turtles (Chelonia mydas) in Bimini, Bahamas. Tracking durations were similar, although acoustic tracking provided higher spatiotemporal resolution than satellite tracking. Occurrence distributions (95%) estimated from satellite telemetry were 12 times larger than those from acoustic telemetry, while satellite range distributions (95%) were 89 times larger. While individuals generally remained within the extent of the acoustic receiver array, gaps in coverage were identified. These gaps, combined with the lower accuracy of satellite telemetry, were likely drivers for the larger satellite distributions. Costs differed between telemetry methods, with acoustic telemetry being less expensive at larger sample sizes with a previously established array. Our results suggest that acoustic and satellite telemetry may not provide similar inferences of individual space use. As such, we provide recommendations to identify telemetry methods appropriate for specific study objectives and provide discussion on the biases of each.
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Affiliation(s)
- Emily E. Hardin
- Marine Turtle Research, Ecology and Conservation Group, Department of Earth, Ocean & Atmospheric Science, Florida State University, Tallahassee, FL 32304, USA
| | - Joshua A. Cullen
- Marine Turtle Research, Ecology and Conservation Group, Department of Earth, Ocean & Atmospheric Science, Florida State University, Tallahassee, FL 32304, USA
| | - Mariana M. P. B. Fuentes
- Marine Turtle Research, Ecology and Conservation Group, Department of Earth, Ocean & Atmospheric Science, Florida State University, Tallahassee, FL 32304, USA
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3
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Łoś M, Smolak K, Mitrus C, Rohm W, Van de Weghe N, Sila-Nowicka K. The applicability of human mobility scaling laws on animals-A Herring Gull case study. PLoS One 2023; 18:e0286239. [PMID: 37531341 PMCID: PMC10395819 DOI: 10.1371/journal.pone.0286239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 05/11/2023] [Indexed: 08/04/2023] Open
Abstract
With the development of sensors, recording and availability of high-resolution movement data from animals and humans, two disciplines have rapidly developed: human mobility and movement ecology. Addressing methodological gaps between these two mobility fields could improve the understanding of movement processes and has been defined as the Integrated Science of Movement. We apply well-known human mobility metrics and data processing methods to Global Positioning System (GPS) tracking data of European Herring Gulls (Larus argentatus) to test the usefulness of these methods for explaining animal mobility behavior. We use stop detection, spatial aggregation, and for the first time on animal movement data, two approaches to temporal aggregation (Next Time-Bin and Next Place). We also calculate from this data a set of movement statistics (visitation frequency, distinct locations over time, and radius of gyration). Furthermore, we analyze and compare the gull and human data from the perspective of scaling laws commonly used for human mobility. The results confirm those of previous studies and indicate differences in movement parameters between the breeding season and other parts of the year. This paper also shows that methods used in human mobility analysis have the potential to improve our understanding of animal behavior.
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Affiliation(s)
- Marcelina Łoś
- Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | - Kamil Smolak
- Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | - Cezary Mitrus
- Department of Vertebrate Ecology and Palaeontology, Institute of Environmental Biology, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | - Witold Rohm
- Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | | | - Katarzyna Sila-Nowicka
- School of Environment, The University of Auckland, Auckland, New Zealand
- Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
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4
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Tanabe LK, Cochran JEM, Berumen ML. Inter-nesting, migration, and foraging behaviors of green turtles (Chelonia mydas) in the central-southern Red Sea. Sci Rep 2023; 13:11222. [PMID: 37433818 DOI: 10.1038/s41598-023-37942-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/30/2023] [Indexed: 07/13/2023] Open
Abstract
Sea turtles are migratory with nesting and foraging areas in distinct and often widely separated habitats. Telemetry has been a vital tool for tracking sea turtle migrations between these areas, but tagging efforts are often focused on only a few large rookeries in a given region. For instance, turtle tagging in the Red Sea has been focused in the north of the basin. We tagged five green turtles (Chelonia mydas) at a nesting site in the central-southern Red Sea and tracked them for 72-243 days. During the inter-nesting period, the turtles showed high site-fidelity, with a maximum home range of 161 km2. After the nesting season, the turtles migrated up to 1100 km to five distinct foraging locations in three countries (Saudi Arabia, Sudan, and Eritrea). Movements within foraging habitats were more wide-ranging compared to inter-nesting movements, with home ranges varying between 1.19 and 931 km2. The tracking data revealed that the creation of a relatively small marine reserve could protect the critical inter-nesting habitat in the Farasan Banks. The results also highlight the need for multinational collaboration to protect migratory corridors and foraging sites of this endangered species.
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Affiliation(s)
- Lyndsey K Tanabe
- Division of Biological and Environmental Science and Engineering, Red Sea Research Center, King Abdullah University of Science and Technology, 23955‑6900, Thuwal, Kingdom of Saudi Arabia.
| | - Jesse E M Cochran
- Division of Biological and Environmental Science and Engineering, Red Sea Research Center, King Abdullah University of Science and Technology, 23955‑6900, Thuwal, Kingdom of Saudi Arabia
| | - Michael L Berumen
- Division of Biological and Environmental Science and Engineering, Red Sea Research Center, King Abdullah University of Science and Technology, 23955‑6900, Thuwal, Kingdom of Saudi Arabia
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Cerini F, Childs DZ, Clements CF. A predictive timeline of wildlife population collapse. Nat Ecol Evol 2023; 7:320-331. [PMID: 36702859 DOI: 10.1038/s41559-023-01985-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 01/06/2023] [Indexed: 01/27/2023]
Abstract
Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals' behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.
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Affiliation(s)
- Francesco Cerini
- School of Biological Sciences, University of Bristol, Bristol, UK.
| | - Dylan Z Childs
- School of Biosciences, University of Sheffield, Sheffield, UK
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6
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Bassing SB, DeVivo M, Ganz TR, Kertson BN, Prugh LR, Roussin T, Satterfield L, Windell RM, Wirsing AJ, Gardner B. Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2023; 33:e2745. [PMID: 36107138 DOI: 10.1002/eap.2745] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 07/05/2022] [Accepted: 07/22/2022] [Indexed: 06/15/2023]
Abstract
Estimating habitat and spatial associations for wildlife is common across ecological studies and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inference to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eulerian) data for seven species collected simultaneously in eastern Washington (2018-2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differed depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, although specific habitat relationships differed. We hypothesize the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.
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Affiliation(s)
- Sarah B Bassing
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Melia DeVivo
- Washington Department of Fish and Wildlife, Spokane Valley, Washington, USA
| | - Taylor R Ganz
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Brian N Kertson
- Washington Department of Fish and Wildlife, Snoqualmie, Washington, USA
| | - Laura R Prugh
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Trent Roussin
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
- Washington Department of Fish and Wildlife, Colville, Washington, USA
| | - Lauren Satterfield
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Rebecca M Windell
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Aaron J Wirsing
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
| | - Beth Gardner
- School of Environmental and Forest Sciences, University of Washington, Seattle, Washington, USA
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The Use of Animal-Borne Biologging and Telemetry Data to Quantify Spatial Overlap of Wildlife with Marine Renewables. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2021. [DOI: 10.3390/jmse9030263] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The growth of the marine renewable energy sector requires the potential effects on marine wildlife to be considered carefully. For this purpose, utilization distributions derived from animal-borne biologging and telemetry data provide accurate information on individual space use. The degree of spatial overlap between potentially vulnerable wildlife such as seabirds and development areas can subsequently be quantified and incorporated into impact assessments and siting decisions. While rich in information, processing and analyses of animal-borne tracking data are often not trivial. There is therefore a need for straightforward and reproducible workflows for this technique to be useful to marine renewables stakeholders. The aim of this study was to develop an analysis workflow to extract utilization distributions from animal-borne biologging and telemetry data explicitly for use in assessment of animal spatial overlap with marine renewable energy development areas. We applied the method to European shags (Phalacrocorax aristotelis) in relation to tidal stream turbines. While shag occurrence in the tidal development area was high (99.4%), there was no overlap (0.14%) with the smaller tidal lease sites within the development area. The method can be applied to any animal-borne bio-tracking datasets and is relevant to stakeholders aiming to quantify environmental effects of marine renewables.
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8
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Ferreira LC, Thums M, Fossette S, Wilson P, Shimada T, Tucker AD, Pendoley K, Waayers D, Guinea ML, Loewenthal G, King J, Speirs M, Rob D, Whiting SD. Multiple satellite tracking datasets inform green turtle conservation at a regional scale. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.13197] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Affiliation(s)
- Luciana C. Ferreira
- Australian Institute of Marine Science Indian Ocean Marine Research Centre University of Western Australia Crawley WA Australia
| | - Michele Thums
- Australian Institute of Marine Science Indian Ocean Marine Research Centre University of Western Australia Crawley WA Australia
| | - Sabrina Fossette
- Marine Science Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | - Phillipa Wilson
- Australian Institute of Marine Science Indian Ocean Marine Research Centre University of Western Australia Crawley WA Australia
| | - Takahiro Shimada
- Australian Institute of Marine Science Indian Ocean Marine Research Centre University of Western Australia Crawley WA Australia
| | - Anton D. Tucker
- Marine Science Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | | | | | | | - Graham Loewenthal
- Remote Sensing and Spatial Analysis Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | - Joanne King
- Department of Biodiversity, Conservation and Attractions Parks and Wildlife Service Karratha WA Australia
| | - Marissa Speirs
- Marine Science Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | - Dani Rob
- Marine Science Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | - Scott D. Whiting
- Marine Science Program, Biodiversity and Conservation Science Department of Biodiversity, Conservation and Attractions Kensington WA Australia
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