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Seal S, Bayyana S, Pande A, Ghanekar C, Hatkar PS, Pathan S, Patel S, Rajpurkar S, Prajapati S, Gole S, Iyer S, Nair A, Prabakaran N, Sivakumar K, Johnson JA. Spatial prioritization of dugong habitats in India can contribute towards achieving the 30 × 30 global biodiversity target. Sci Rep 2024; 14:13984. [PMID: 38886526 PMCID: PMC11183059 DOI: 10.1038/s41598-024-64760-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 06/12/2024] [Indexed: 06/20/2024] Open
Abstract
Indian coastal waters are critical for dugong populations in the western Indian Ocean. Systematic spatial planning of dugong habitats can help to achieve biodiversity conservation and area-based protection targets in the region. In this study, we employed environmental niche modelling to predict suitable dugong habitats and identify influencing factors along its entire distribution range in Indian waters. We examined data on fishing pressures collected through systematic interview surveys, citizen-science data, and field surveys to demarcate dugong habitats with varying risks. Seagrass presence was the primary factor in determining dugong habitat suitability across the study sites. Other variables such as depth, bathymetric slope, and Euclidean distance from the shore were significant factors, particularly in predicting seasonal suitability. Predicted suitable habitats showed a remarkable shift from pre-monsoon in Palk Bay to post-monsoon in the Gulf of Mannar, indicating the potential of seasonal dugong movement. The entire coastline along the Palk Bay-Gulf of Mannar region was observed to be at high to moderate risk, including the Gulf of Mannar Marine National Park, a high-risk area. The Andaman Islands exhibited high suitability during pre- and post-monsoon season, whereas the Nicobar Islands were highly suitable for monsoon season. Risk assessment of modelled suitable areas revealed that < 15% of high-risk areas across Andaman and Nicobar Islands and Palk Bay and Gulf of Mannar, Tamil Nadu, fall within the existing protected areas. A few offshore reef islands are identified under high-risk zones in the Gulf of Kutch, Gujarat. We highlight the utility of citizen science and secondary data in performing large-scale spatial ecological analysis. Overall, identifying synoptic scale 'Critical Dugong Habitats' has positive implications for the country's progress towards achieving the global 30 × 30 target through systematic conservation planning.
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Affiliation(s)
- Sohom Seal
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Sharad Bayyana
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
- Centre for Biodiversity and Conservation Science, School of Environment, University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Anant Pande
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
- Marine Program, Wildlife Conservation Society - India, Bengaluru, Karnataka, 560 097, India
| | - Chinmaya Ghanekar
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Prachi Sachchidanand Hatkar
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Sameeha Pathan
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Shivani Patel
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Sagar Rajpurkar
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Sumit Prajapati
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Swapnali Gole
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Sweta Iyer
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Aditi Nair
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Nehru Prabakaran
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
| | - Kuppusamy Sivakumar
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India
- Department of Ecology and Environment, Pondicherry University, Puducherry, India
| | - Jeyaraj Antony Johnson
- Department of Habitat Ecology, Wildlife Institute of India, P.O. Chandrabani, Dehradun, Uttarakhand, 248 001, India.
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Mikkelsen D, McGowan AM, Gibson JS, Lanyon JM, Horsman S, Seddon JM. Faecal bacterial communities differ amongst discrete foraging populations of dugongs along the east Australian coast. FEMS Microbiol Ecol 2024; 100:fiae051. [PMID: 38658192 PMCID: PMC11141782 DOI: 10.1093/femsec/fiae051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 03/01/2024] [Accepted: 04/23/2024] [Indexed: 04/26/2024] Open
Abstract
Gut bacterial communities play a vital role in a host's digestion and fermentation of complex carbohydrates, absorption of nutrients, and energy harvest/storage. Dugongs are obligate seagrass grazers with an expanded hindgut and associated microbiome. Here, we characterised and compared the faecal bacterial communities of dugongs from genetically distinct populations along the east coast of Australia, between subtropical Moreton Bay and tropical Cleveland Bay. Amplicon sequencing of fresh dugong faecal samples (n=47) revealed Firmicutes (62%) dominating the faecal bacterial communities across all populations. Several bacterial genera (Bacteroides, Clostridium sensu stricto 1, Blautia and Polaribacter) were detected in samples from all locations, suggesting their importance in seagrass digestion. Principal coordinate analysis showed the three southern-most dugong populations having different faecal bacterial community compositions from northern populations. The relative abundances of the genera Clostridium sensu stricto 13 and dgA-11 gut group were higher, but Bacteroides was lower, in the southern dugong populations, compared to the northern populations, suggesting potential adaptive changes associated with location. This study contributes to our knowledge of the faecal bacterial communities of dugongs inhabiting Australian coastal waters. Future studies of diet selection in relation to seagrass availability throughout the dugong's range will help to advance our understanding of the roles that seagrass species may play in affecting the dugong's faecal bacterial community composition.
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Affiliation(s)
- Deirdre Mikkelsen
- School of Agriculture and Food Sustainability, The University of Queensland, St. Lucia, Queensland 4072, Australia
| | - Alexandra M McGowan
- School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343, Australia
| | - Justine S Gibson
- School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343, Australia
| | - Janet M Lanyon
- School of the Environment, The University of Queensland, St Lucia, Queensland 4072, Australia
| | - Sara Horsman
- School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343, Australia
| | - Jennifer M Seddon
- School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343, Australia
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3
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Skerratt J, Baird ME, Mongin M, Ellis R, Smith RA, Shaw M, Steven ADL. Dispersal of the pesticide diuron in the Great Barrier Reef. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 879:163041. [PMID: 36965738 DOI: 10.1016/j.scitotenv.2023.163041] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 05/17/2023]
Abstract
Pesticides from urban and agricultural runoff have been detected at concentrations above current water quality guidelines in the Great Barrier Reef (GBR) marine environment. We quantify the load of the pesticide diuron entering GBR waters using the GBR-Dynamic SedNet catchment model. After comparison of simulated distributions with observations at 11 monitoring sites we determined a half-life of diuron in GBR marine waters of 40 days. We followed diuron dispersal in the GBR (2016-2018) using the 1 km resolution eReefs marine model. The highest diuron concentrations in GBR waters occurred in the Mackay-Whitsunday region with a spike in January and March 2017, associated with 126 and 118 kg d-1 diuron loads from Plane Creek and the O'Connell River respectively. We quantify areas of GBR waters exposed to potentially ecotoxic concentrations of diuron. Between 2016 and 2018, 400 km2 and 1400 km2 of the GBR were exposed to concentrations exceeding ecosystem threshold values of 0.43 and 0.075 μg L-1 respectively. Using observed mapped coral and seagrass habitat, 175 km2 of seagrass beds and 50 km2 of coral habitats had peak diuron concentrations above 0.075 μg L-1 during this period. While the highest concentrations are localised to river plumes and inshore environments, non-zero diuron concentrations extend along the Queensland coast. These simulations provide new knowledge for the understanding of pesticide dispersal and management-use in GBR catchments and the design of in-water monitoring systems.
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Affiliation(s)
| | | | | | - Robin Ellis
- Science Division, Department of Environment and Science, Queensland Government, Brisbane, Australia
| | - Rachael A Smith
- Office of the Great Barrier Reef, Department of Environment and Science, Brisbane 4102, QLD, Australia
| | - Melanie Shaw
- Science Division, Department of Environment and Science, Queensland Government, Brisbane, Australia
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Duarte de Paula Costa M, Adame MF, Bryant CV, Hill J, Kelleway JJ, Lovelock CE, Ola A, Rasheed MA, Salinas C, Serrano O, Waltham N, York PH, Young M, Macreadie P. Quantifying blue carbon stocks and the role of protected areas to conserve coastal wetlands. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162518. [PMID: 36870497 DOI: 10.1016/j.scitotenv.2023.162518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 02/24/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
Vegetated coastal ecosystems, in particular mangroves, tidal marshes and seagrasses are highly efficient at sequestering and storing carbon, making them valuable assets for climate change mitigation and adaptation. The state of Queensland, in northeastern Australia, contains almost half of the total area of these blue carbon ecosystems in the country, yet there are few detailed regional or state-wide assessments of their total sedimentary organic carbon (SOC) stocks. We compiled existing SOC data and used boosted regression tree models to evaluate the influence of environmental variables in explaining the variability in SOC stocks, and to produce spatially explicit blue carbon estimates. The final models explained 75 % (for mangroves and tidal marshes) and 65 % (for seagrasses) of the variability in SOC stocks. Total SOC stocks in the state of Queensland were estimated at 569 ± 98 Tg C (173 ± 32 Tg C, 232 ± 50 Tg C, and 164 ± 16 Tg C from mangroves, tidal marshes and seagrasses, respectively). Regional predictions for each of Queensland's eleven Natural Resource Management regions revealed that 60 % of the state's SOC stocks occurred within three regions (Cape York, Torres Strait and Southern Gulf Natural Resource Management regions) due to a combination of high values of SOC stocks and large areas of coastal wetlands. Protected areas in Queensland play an important role in conserving SOC assets in Queensland's coastal wetlands. For example, ~19 Tg C within terrestrial protected areas, ~27 Tg C within marine protected areas and ~ 40 Tg C within areas of matters of State Environmental Significance. Using multi-decadal (1987-2020) mapped distributions of mangroves in Queensland; we found that mangrove area increased by approximately 30,000 ha from 1987 to 2020, which led to temporal fluctuations in mangrove plant and SOC stocks. We estimated that plant stocks decreased from ~45 Tg C in 1987 to ~34.2 Tg C in 2020, while SOC stocks remained relatively constant from ~107.9 Tg C in 1987 to 108.0 Tg C in 2020. Considering the level of current protection, emissions from mangrove deforestation are potentially very low; therefore, representing minor opportunities for mangrove blue carbon projects in the region. Our study provides much needed information on current trends in carbon stocks and their conservation in Queensland's coastal wetlands, while also contributing to guide future management actions, including blue carbon restoration projects.
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Affiliation(s)
- Micheli Duarte de Paula Costa
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood Campus, Burwood, VIC 3125, Australia.
| | - Maria Fernanda Adame
- Australian Rivers Institute, Coastal & Marine Research Centre, Griffith University, Nathan, QLD 4111, Australia
| | - Catherine V Bryant
- Centre for Tropical Water and Aquatic Ecosystem Research, James Cook University, Cairns, QLD 4870, Australia
| | - Jack Hill
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia
| | - Jeffrey J Kelleway
- School of Earth, Atmospheric and Life Sciences and GeoQuEST Research Centre, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Catherine E Lovelock
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia
| | - Anne Ola
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia
| | - Michael A Rasheed
- Centre for Tropical Water and Aquatic Ecosystem Research, James Cook University, Cairns, QLD 4870, Australia
| | - Cristian Salinas
- School of Science & Centre for Marine Ecosystems Research, Edith Cowan University, Joondalup Drive, Joondalup, WA 6027, Australia
| | - Oscar Serrano
- School of Science & Centre for Marine Ecosystems Research, Edith Cowan University, Joondalup Drive, Joondalup, WA 6027, Australia; Centro de Estudios Avanzados de Blanes, Consejo Superior de Investigaciones Científicas, Blanes, Spain
| | - Nathan Waltham
- Centre for Tropical Water and Aquatic Ecosystem Research, James Cook University, Townsville, QLD, Australia
| | - Paul H York
- Centre for Tropical Water and Aquatic Ecosystem Research, James Cook University, Cairns, QLD 4870, Australia
| | - Mary Young
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Warrnambool Campus, Geelong, VIC 3125, Australia
| | - Peter Macreadie
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood Campus, Burwood, VIC 3125, Australia
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A report card approach to describe temporal and spatial trends in parameters for coastal seagrass habitats. Sci Rep 2023; 13:2295. [PMID: 36759649 PMCID: PMC9911721 DOI: 10.1038/s41598-023-29147-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/31/2023] [Indexed: 02/11/2023] Open
Abstract
Report cards that are designed to monitor environmental trends have the potential to provide a powerful communication tool because they are easy to understand and accessible to the general public, scientists, managers and policy makers. Given this functionality, they are increasingly popular in marine ecosystem reporting. We describe a report card method for seagrass that incorporates spatial and temporal variability in three metrics-meadow area, species and biomass-developed using long-term (greater than 10 years) monitoring data. This framework summarises large amounts of spatially and temporally complex data to give a numeric score that provides reliable comparisons of seagrass condition in both persistent and naturally variable meadows. We provide an example of how this is applied to seagrass meadows in an industrial port in the Great Barrier Reef World Heritage Area of north-eastern Australia.
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Carter AB, Collier C, Coles R, Lawrence E, Rasheed MA. Community-specific "desired" states for seagrasses through cycles of loss and recovery. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 314:115059. [PMID: 35462253 DOI: 10.1016/j.jenvman.2022.115059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 04/05/2022] [Accepted: 04/08/2022] [Indexed: 06/14/2023]
Abstract
Seagrass habitats provide critical ecosystem services, yet there is ongoing concern over mounting pressures and continuing degradation. Defining a desired state for these habitats is a key step in implementing appropriate management but is often difficult given the challenges of available data and an evaluation of where to set benchmarks. We use more than 20 years of historical seagrass biomass data (1995-2018) for the diverse seagrass communities of Australia's Great Barrier Reef World Heritage Area (GBRWHA) to develop desired state benchmarks. Desired state for seagrass biomass was estimated for 25 of 36 previously defined seagrass communities with the remainder having insufficient data. Desired state varied by more than one order of magnitude between community types and was influenced by the mix of species in the communities and the range of environmental conditions. We identify a historical, decadal-scale cycle of decline with recovery to desired state in coastal intertidal communities. In contrast a number of the estuary and coastal subtidal communities have not recovered to desired state biomass. Understanding a historical context is critically important for setting benchmarks and making informed management decisions on the present state of seagrass in the GBRWHA. The approach we have developed is scalable for monitoring, management and assessment of pressures for other management areas and for other jurisdictions. Our results guide conservation planning through prioritization of the at-risk seagrass communities that are continuing to fall below their desired state.
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Affiliation(s)
- Alex B Carter
- Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER), James Cook University, Cairns, Australia.
| | - Catherine Collier
- Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER), James Cook University, Cairns, Australia
| | - Rob Coles
- Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER), James Cook University, Cairns, Australia
| | | | - Michael A Rasheed
- Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER), James Cook University, Cairns, Australia
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Improving Approaches to Mapping Seagrass within the Great Barrier Reef: From Field to Spaceborne Earth Observation. REMOTE SENSING 2022. [DOI: 10.3390/rs14112604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Seagrass meadows are a key ecosystem of the Great Barrier Reef World Heritage Area, providing one of the natural heritage attributes underpinning the reef’s outstanding universal value. We reviewed approaches employed to date to create maps of seagrass meadows in the optically complex waters of the Great Barrier Reef and explored enhanced mapping approaches with a focus on emerging technologies, and key considerations for future mapping. Our review showed that field-based mapping of seagrass has traditionally been the most common approach in the GBRWHA, with few attempts to adopt remote sensing approaches and emerging technologies. Using a series of case studies to harness the power of machine- and deep-learning, we mapped seagrass cover with PlanetScope and UAV-captured imagery in a variety of settings. Using a machine-learning pixel-based classification coupled with a bootstrapping process, we were able to significantly improve maps of seagrass, particularly in low cover, fragmented and complex habitats. We also used deep-learning models to derive enhanced maps from UAV imagery. Combined, these lessons and emerging technologies show that more accurate and efficient seagrass mapping approaches are possible, producing maps of higher confidence for users and enabling the upscaling of seagrass mapping into the future.
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