A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

Distribution and species richness of seagrass meadows in the Sea of Marmara

Comprehensive data on seagrass distribution and species richness in the Sea of Marmara (SoM) are absent from global seagrass mapping, hindering long-term monitoring and practical protection efforts for these vital meadows. This study aims to assess the species richness, spatial distribution patterns, and fundamental ecological aspects of seagrass meadows in the SoM, which serves as a crucial transition zone between the Black Sea and the Mediterranean Sea. The data set was obtained through a series of underwater surveys conducted between June and September 2024 at 140 surveyed stations, covering a total area of about 0.534 km2. Spatial and species-specific surface area (m2), cover percentage (%), and depth limits (m) of seagrass meadows were estimated from underwater records collected along line transects. Seagrass meadows constituted 51.9 % of the area surveyed in the SoM, covering an area of 0.277 km2. Results revealed a rich diversity of seagrass species within the SoM, identifying four species: Cymodocea nodosa, Posidonia oceanica, Zostera marina, and Z. noltei. C. nodosa was the most common species, occupying 82.8 % (0.230 km2) of the total surface area. The lower depth limits of seagrasses in the SoM were shallower than in other Mediterranean regions, with P. oceanica at 15.7 m and C. nodosa at 11.1 m. This limitation attributed to reductions in light penetration caused by high primary production and excessive pollution loads in the SoM. In conclusion, this dataset includes the first underwater observation-based mapping and identification of new areas for seagrass species in the SoM, contributing to distribution maps for the Mediterranean basin.

First Observations of a Deep-Water Seagrass Meadow (Thalassodendron ciliatum) on an Oceanic Reef in the Southern Coral Sea Marine Park, Australia

Tropical seagrass meadows are important global marine ecosystems that provide critical ecosystem goods and services. The extent of global seagrass meadows is mostly mapped from shallow coastal regions and not well known or sampled from deeper offshore locations. Seagrasses can, however, form deep-water meadows, which likely significantly increase the total area of global seagrass ecosystems and may contribute important ecological functions to offshore tropical seascapes. Here we report the first observation of a dense meadow of Thalassodendron ciliatum at a depth of 25 m using remotely operated vehicles (ROVs) from the Coral Sea Marine Park (CSMP). Despite significant survey effort in the region, to date there have only been three other observations of seagrass in the CSMP, all sparse and small patches of Halophila ovalis and Halophila decipiens. We discuss the significance of this newly discovered meadow within the context of current reef health monitoring of the CSMP, reef fish biodiversity and the ecological value of deep-water seagrass habitats for offshore coral reef systems like the Coral Sea.

Status and habitat suitability evaluation: A case study of the typical temperate seagrass beds in the Bohai Sea, China

Seagrass beds serve crucial ecological functions, yet they are facing a severe decline necessitating immediate conservation and restoration efforts. Current assessments of seagrass habitat suitability are insufficient, thus hindering the restoration effects. This study used a combination of field surveys and satellite remote sensing to conduct a three-year monitoring of typical temperate seagrass beds in the Caofeidian and Xingcheng areas of the Bohai Sea. The relationships between seagrass community factors and environmental factors were investigated using Spearman correlation analysis, BIOENV analysis, and redundancy analysis (RDA). Subsequently, the weights of each environmental factor were determined using the Analytic Hierarchy Process (AHP), leading to the development of the Habitat Suitability Index (HSI). Seagrass habitat suitability maps for Caofeidian and Xingcheng areas were then generated using Geographic Information System (GIS). The results indicate that both seagrass ecosystems degraded during the study period, which coincided with a decreasing trend in habitat suitability shown by the suitability maps. This study provides a methodology for seagrass bed habitat suitability assessment, thereby contributing to the conservation and restoration of these vital ecosystems.

Stressor fluctuations alter mechanisms underpinning seagrass responses to multiple stressors

Multiple anthropogenic stressors degrade ecosystems globally. A key knowledge gap in multiple stressor research is how variability in stressor intensity (i.e., fluctuations) and synchronicity (i.e., timing of fluctuations) affect biological responses, and the mechanisms underpinning responses. We evaluated the mechanistic effects of reduced light and herbicide contamination on seagrass, and determined how variations in stressor intensity and synchronicity influence the underlying mechanisms of responses. We used structural causal modelling and structural equation modelling to elucidate direct and mediating effects. Out-of-phase introduction (i.e., asynchronous fluctuations) altered the mechanistic pathways of how stressors affect seagrass relative to static stressors, and resulted in the greatest biomass loss (under the most intense stressor combination, ∼50 % reduction). Therefore, previous experiments that predominantly test only static stressor intensities might underestimate detrimental impacts in nature. Future experiments should explore mechanistic effects across realistic stressor intensities and synchronicities to improve our understanding and management of multiple stressors.

Prediction of potential occurrence of historical objects with defensive function in Slovakia using machine learning approach

In this article, we aim at the prediction of possible locations of already defunct historical objects with a defensive function (HODFs) in Slovakia, which have not been found and documented so far, using three machine learning methods. Specifically, we used the support vector machine, k-nearest neighbors, and random forest algorithms, which were trained based on the following five factors influencing the possible occurrence of HODFs: elevation, distance from a river, distance from a settlement, lithological rock type, and type of representative geoecosystems. Training and testing datasets were based on a database of already documented 605 HODFs, which were divided into 70% of training samples and 30% of testing samples. All of the three models reached the AUC-ROC value over 0.74 based on the testing dataset. The best performance was recorded by the random forest predictive model with the AUC-ROC value equal to 0.79. The results of the random forest model were also validated with the recently documented HODFs via the archeological research.

Sirenian genomes illuminate the evolution of fully aquatic species within the mammalian superorder afrotheria

Sirenians of the superorder Afrotheria were the first mammals to transition from land to water and are the only herbivorous marine mammals. Here, we generated a chromosome-level dugong (Dugong dugon) genome. A comparison of our assembly with other afrotherian genomes reveals possible molecular adaptations to aquatic life by sirenians, including a shift in daily activity patterns (circadian clock) and tolerance to a high-iodine plant diet mediated through changes in the iodide transporter NIS (SLC5A5) and its co-transporters. Functional in vitro assays confirm that sirenian amino acid substitutions alter the properties of the circadian clock protein PER2 and NIS. Sirenians show evidence of convergent regression of integumentary system (skin and its appendages) genes with cetaceans. Our analysis also uncovers gene losses that may be maladaptive in a modern environment, including a candidate gene (KCNK18) for sirenian cold stress syndrome likely lost during their evolutionary shift in daily activity patterns. Genomes from nine Australian locations and the functionally extinct Okinawan population confirm and date a genetic break ~10.7 thousand years ago on the Australian east coast and provide evidence of an associated ecotype, and highlight the need for whole-genome resequencing data from dugong populations worldwide for conservation and genetic management.

Spatial prioritization of dugong habitats in India can contribute towards achieving the 30 × 30 global biodiversity target

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.

Faecal bacterial communities differ amongst discrete foraging populations of dugongs along the east Australian coast

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.

Dispersal of the pesticide diuron in the Great Barrier Reef

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.

Quantifying blue carbon stocks and the role of protected areas to conserve coastal wetlands

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.

A report card approach to describe temporal and spatial trends in parameters for coastal seagrass habitats

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.

Community-specific "desired" states for seagrasses through cycles of loss and recovery

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.

Improving Approaches to Mapping Seagrass within the Great Barrier Reef: From Field to Spaceborne Earth Observation

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.