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Bengtson Nash SM, Groβ J, Castrillon J, Casa MV, Luche GD, Meager J, Ghosh R, Eggebo J, Nizzetto PB. Antarctic sea-ice low resonates in the ecophysiology of humpback whales. Sci Total Environ 2023; 887:164053. [PMID: 37178847 DOI: 10.1016/j.scitotenv.2023.164053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/05/2023] [Accepted: 05/06/2023] [Indexed: 05/15/2023]
Abstract
The past six years have been marked by some of the most dramatic climatic events observed in the Antarctic region in recent history, commencing with the 2017 sea-ice extreme low. The Humpback Whale Sentinel Programme is a circum-polar biomonitoring program for long term surveillance of the Antarctic sea-ice ecosystem. It has previously signalled the extreme La Niña event of 2010/11, and it was therefore of interest to assess the capacity of existing biomonitoring measures under the program to detect the impacts of 2017 anomalous climatic events. Six ecophysiological markers of population adiposity, diet, and fecundity were targeted, as well as calf and juvenile mortality via stranding records. All indicators, with the exception of bulk stable isotope dietary tracers, indicated a negative trend in 2017, whilst C and N bulk stable isotopes appeared to indicate a lag phase resulting from the anomalous year. The collation of multiple biochemical, chemical, and observational lines of evidence via a single biomonitoring platform provides comprehensive information for evidence-led policy in the Antarctic and Southern Ocean region.
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Affiliation(s)
- Susan M Bengtson Nash
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia.
| | - Jasmin Groβ
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
| | - Juliana Castrillon
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
| | - Maria Valeria Casa
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
| | - Greta Dalle Luche
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
| | - Justin Meager
- Queensland Department of Environment and Science, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Ruma Ghosh
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
| | - June Eggebo
- Griffith University, Centre for Planetary Health and Food Security, Southern Ocean Persistent Organic Pollutants Program, Kessels Road, Nathan, QLD 4111, Australia
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Dunstan A, Robertson K, Fitzpatrick R, Pickford J, Meager J. Use of unmanned aerial vehicles (UAVs) for mark-resight nesting population estimation of adult female green sea turtles at Raine Island. PLoS One 2020; 15:e0228524. [PMID: 32497041 PMCID: PMC7272060 DOI: 10.1371/journal.pone.0228524] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 05/06/2020] [Indexed: 11/19/2022] Open
Abstract
Nester abundance is a key measure of the performance of the world’s largest green turtle rookery at Raine Island, Australia, and has been estimated by mark-resight counts since 1984. Nesters are first marked by painting their carapace with a longitudinal white stripe. Painted and unpainted turtles are then counted by a surface observer on a small boat in waters adjacent to the reef. Unmanned aerial vehicles (UAV) and underwater video may provide more cost-effective and less biased alternatives to this approach, but estimates must be comparable with historical estimates. Here we compare and evaluate the three methods. We found comparatively little variation in resighting probabilities between consecutive days of sampling or time of day, which supports an underlying assumption of the method (i.e. demographic closure during sampling). This lack of bias in the location availability for detection of painted versus unpainted turtles and further supported by a parallel satellite tracking study of 40 turtles at Raine Island. Our results demonstrated that surface observers consistently reported higher proportions of marked turtles than either the UAV or underwater video method. This in turn yielded higher population estimates with UAV or underwater video compared to the historical surface observer method, which suggested correction factors of 1.53 and 1.73 respectively. We attributed this to observer search error because a white marked turtle is easier to spot than the non-marked turtle. In contrast, the UAV and underwater video methods allowed subsequent frame-by-frame review, thus reducing observer search error. UAVs were the most efficient in terms of survey time, personnel commitment and weather tolerance compared to the other methods. However, underwater video may also be a useful alternative for in-water mark-resight surveys of turtles.
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Affiliation(s)
- Andrew Dunstan
- Queensland Department of Environment and Science, Brisbane, Queensland, Australia
- * E-mail:
| | - Katharine Robertson
- Queensland Department of Environment and Science, Brisbane, Queensland, Australia
| | - Richard Fitzpatrick
- Biopixel Oceans Foundation, James Cook University, Smithfield, Queensland, Australia
| | - Jeffrey Pickford
- Queensland Department of Natural Resources Mines and Energy, Brisbane, Queensland, Australia
| | - Justin Meager
- Queensland Department of Environment and Science, Brisbane, Queensland, Australia
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Bell IP, Meager J, van de Merwe JP, Madden Hof CA. Green turtle (Chelonia mydas) population demographics at three chemically distinct foraging areas in the northern Great Barrier Reef. Sci Total Environ 2019; 652:1040-1050. [PMID: 30586791 DOI: 10.1016/j.scitotenv.2018.10.150] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 10/10/2018] [Accepted: 10/10/2018] [Indexed: 06/09/2023]
Abstract
The catchments of the Great Barrier Reef (GBR) have experienced significant modifications in recent decades, leading to increases in sources of pollutants and declines in coastal water quality. As coastal waters of the GBR support some of the highest density green turtle (Chelonia mydas) foraging populations in the western Pacific Ocean, understanding the effects of contaminants on GBR green turtle populations is a priority. In 2012, elevated strandings of green turtles in the Upstart Bay region instigated the WWF's collaborative Rivers to Reef to Turtles (RRT) project to investigate if coastal pollutants are compromising green turtle health. Important to interpreting these investigations into toxicology and health is understanding the demographics of the green turtle populations being investigated. In three green turtle foraging grounds, Cleveland Bay (CLV), Upstart Bay (UPB) and the Howick Group of Reefs (HWK), this study explored population size, age class structure, sex ratio, growth rates, body condition and diet, as well as indices of turtle health, such as plastron barnacle loads and eye lesions. The three foraging populations had similar age class structure and adult sex ratios to other green turtle foraging populations in the GBR. Somatic growth rate was nonlinear, peaking in immature turtles, and was much slower in turtles foraging at HWK compared to the other two sites. This may have been due to differences in food source, which was supported by the observed dietary shifts between seagrass and algae in HWK turtles, compared to a consistently seagrass diet in CLV and UPB turtles. There were also small differences in body condition between sites, as well as differences in barnacle loads, eye lesions and occurrence of fibropapilloma tumors. This study provides important information on green turtle foraging ground population dynamics in the northern GBR, and context for the other papers in this special issue.
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Affiliation(s)
- Ian P Bell
- Aquatic Species Program, Queensland Department of Environment and Science, Townsville, Queensland 4810, Australia.
| | - Justin Meager
- Aquatic Species Program, Queensland Department of Environment and Science, Brisbane, Queensland 4810, Australia
| | - Jason P van de Merwe
- Griffith Sciences and Australian Rivers Institute, Griffith University, Gold Coast, Queensland 4222, Australia
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