Monitoring dugongs within the Reef 2050 Integrated Monitoring and Reporting Program: final report of the dugong team in the megafauna expert group

The objectives of this report are to determine for the dugong: An assessment of the current status of the relevant elements of the Great Barrier Reef (the Reef), including an evaluation of primary drivers, pressures and responses using the Driving Forces, Pressures, States, Impacts, Responses (DPSIR) Framework; Identification of priority indicators for monitoring the key values associated with these elements; Summary of potential sources of data; Evaluation of adequacy of existing monitoring activities within each theme to achieve the objectives and requirements of RIMReP; Recommendations for the design of an integrated monitoring program as a component of RIMReP, specifically considering: The information requirements for each key element of the Reef to ensure that appropriate data and information are being collected to meet the fundamental objectives of RIMReP; The spatial and temporal sampling design to ensure that greatest value can be extracted from the data collected; The logistics of the design to ensure that it can be implemented efficiently; Likely funding required to implement the recommended monitoring design.An accessible copy of this report is not yet available from this repository, please contact [email protected] for more information

Detectability of dolphins and turtles from Unoccupied Aerial Vehicle (UAV) survey imagery

For many decades occupied aircraft with trained observers have conducted aerial surveys of marine megafauna to estimate population size and dynamics. Recent technological advances mean that unoccupied aerial vehicles (UAVs) now provide a potential alternative to occupied surveys, eliminating some of the disadvantages of occupied surveys such as risk to human life, weather constraints and cost. In this study, data collected from an occupied aircraft (at 500 ft) and a UAV (at 1400 ft) flown at the same time, deployed for counting dugongs, were compared for detecting dolphins and turtles within Shark Bay, Western Australia. The UAV images were manually reviewed post hoc to count the animals sighted and the environmental conditions (visibility, sea state, cloud cover and glare) had been classified by the occupied teams’ data for each image. The UAV captured more sightings (174 dolphins and 368 turtles) than were recorded by the flight team (93 dolphins and 312 turtles). Larger aggregations (>10 animals) were also found in the UAV images (5 aggregations of dolphins and turtles) compared to the occupied teams sightings (0 dolphins and 3 aggregations of turtles). A generalised linear mixed model determined that turtle detection was significantly affected by visibility, while cloud cover, sea state and visibility significantly affected dolphin detection in both platforms. An expert survey of 120 images was also conducted to determine the image ground sampling distance (GSD; four levels from 1.7 to 3.5 cm/pixel) needed to identify dolphin and turtles to species. At 3 cm/pixel only 40% of the dolphins and turtles were identified to species with a reasonable level of certainty (>75% certainty). This study demonstrated that UAVs can be successfully deployed for detecting dolphins and turtles and that a GSD of 1.7 – 3cm/pixel is too low resolution to effectively identify dolphin and turtle species. Overcoming the limitations imposed on UAVs such as aviator regulatory bodies and payload capabilities will make UAVs a pivotal tool for future research, conservation, and management

A Novel Method for Using Small Unoccupied Aerial Vehicles to Survey Wildlife Species and Model Their Density Distribution

There is growing interest from research and conservation groups in the potential for using small unoccupied aerial vehicles (UAVs; <2 kg) to conduct wildlife surveys because they are affordable, easy to use, readily available and reliable. However, limitations such as short flight endurance, and in many situations, aviation regulations, have constrained the use of small UAVs in survey applications. Thus, there is a need to refine survey methods adapted to small UAVs that conform to standard operations within aviation law. We developed a novel survey approach based on a grid sampling design using two multirotor UAVs (Phantom 4 Pros) flying simultaneously, within visual line of sight, from our vessel base-station. We used this approach to assess the fine-scale distribution and abundance of dugongs (Dugong dugon) in the remote waters of the Pilbara, Western Australia during three field seasons across 2 years. We surveyed 64 non-overlapping survey cells in random order one or more times and obtained complete image coverage of each surveyed cell of our 31 km2 survey area. Our sampling design maximizes sampling effort while limiting survey time by surveying four cells, two at a time, from one location. Overall, we conducted 240 flights with up to 17 flights per day (mean = 14 flights per day) and could obtain complete coverage of up to 11.36 km2per day. A total of 149 dugongs were sighted within the 50,482 images which we manually reviewed. Spatially-explicit models of dugong density distribution (corrected for availability and perception bias) were produced using general additive models to identify areas more or less used by dugongs (range of corrected dugong densities across all field season = 0.002–1.79 dugongs per 0.04 km2). Dugong abundance estimates ranged from 47 individuals in June 2019 (CV = 0.17) to 103 individuals in May 2018 (CV = 0.36). Our method, which proved convincing in a real-word application by its feasibility, ease of implementation, and achievable surface coverage has the potential to be used in a wide range of applications from community-based local-scale surveys, to long-term repeated/intensive surveys, and impact assessments and environmental monitoring studies

Operational protocols for the use of drones in marine animal research

The use of drones to study marine animals shows promise for the examination of numerous aspects of their ecology, behaviour, health and movement patterns. However, the responses of some marine phyla to the presence of drones varies broadly, as do the general operational protocols used to study them. Inconsistent methodological approaches could lead to difficulties comparing studies and can call into question the repeatability of research. This review draws on current literature and researchers with a wealth of practical experience to outline the idiosyncrasies of studying various marine taxa with drones. We also outline current best practice for drone operation in marine environments based on the literature and our practical experience in the field. The protocols outlined herein will be of use to researchers interested in incorporating drones as a tool into their research on marine animals and will help form consistent approaches for drone-based studies in the future

An assessment of the distribution and abundance of dugongs and in-water, large marine turtles along the Queensland coast from Cape York to Hinchinbrook Island

This report includes recommendations based on key findings. The objective of this project was to assist the Reef Authority and Queensland Government address requirements of the Reef 2050 Long-Term Sustainability Plan

Extending aerial surveys beyond target marine mammal species: An application of strip transect methodology to humpback whale and dugong abundance estimation in Exmouth Gulf, Western Australia

Aerial surveys are commonly used to estimate abundance of marine mammal populations, to detect trends over time and inform conservation management. Estimating abundance in areas critical to a species’ survival and reproduction is important to assess that population’s status and its vulnerability. Aerial surveys allow relatively large areas to be covered over short periods of time which can be important for highly mobile species with wide-ranging movement patterns such as marine mammals. While aerial surveys are often designed for specific target species, information on additional non-target species is often recorded, as surveys are generally infrequent due to expense and logistical constraints. However, estimating absolute abundance of non-target species can have limitations. For example, in areas that have dense populations of target species, observers’ time may be limited, and information recorded for non-target species may be constrained or incomplete. This study aimed to evaluate the potential for extending aerial surveys designed for target species to estimate absolute (‘true’) abundance of non-target species, accounting for biases including those that were not available to be seen by observers (availability bias) and those that were present but missed (perception bias). A strip transect sampling approach was taken as distances to nontarget species were not measured (i.e., distance sampling could not be undertaken). This project aimed to validate these estimates by comparing observer derived estimates from a range of plausible strip-widths through simulation (as exact strip widths were not recorded for non-target species) with estimates from simultaneously collected aerial images with a known strip width, to identify the ‘best’ strip widths for which to estimate abundance. In addition, the percentage of groups containing calves was evaluated to further inform the importance of the study area. This study used existing data from aerial surveys conducted in Exmouth Gulf, Western Australia (by WA Dept. of Biodiversity, Conservation and Attractions) designed for dolphins (the target species) to produce estimates of non-target humpback whales (Megaptera novaeangliae) and dugongs (Dugong dugon). The resulting ‘best’ strip widths varied depending on the correction factor applied to account for availability bias of the informing abundance estimates, and the number of detections captured in the images across days, consequently leading to variable absolute abundance estimates where these were applied. For humpback whales, estimates were 2960.95 (CV = 44.0%) and 3915.38 (CV = 51.2%), using a ‘best’ half strip width of 637.05m with an availability correction derived from drone data and a half strip width of 833.62m with an availability correction calculated from boat-based data, respectively. For dugongs, absolute abundance was estimated as 838.42 (CVport = 114.59%, CVstarboard = 114.72%) and 1013.36 (CV = 40.46%), using a ‘best’ half strip width of 281.12m and corrected for availability as per Marsh & Sinclair (1989a) and a strip width of 259.92 with a Pollock et al. (2006) availability correction applied, respectively. This study highlighted the need for an adequate survey intensity to improve the reliability of images as a validation tool as well as access to site-specific data on species availability to produce robust abundance estimates. Despite limitations in the extension and validation of these non-target data, the estimates produced here provide the first absolute abundance estimate of humpback whales in Exmouth Gulf and contribute to informing ongoing monitoring and management needs for the proportion of humpback whale and dugong populations that use Exmouth Gulf as critical habitat. Furthermore, the results from this work highlight the opportunities and limitations and provide recommendations for extending aerial survey effort beyond target species. This is particularly important for maximising the potential knowledge gained where funding or logistics may be limiting

New Tools to Identify the Location of Seagrass Meadows: Marine Grazers as Habitat Indicators

Seagrasses are hugely valuable to human life, but the global extent of seagrass meadows remains unclear. As evidence of their value, a United Nations program exists (http://data.unep-wcmc.org/datasets/7) to try and assess their distribution and there has been a call from 122 scientists across 28 countries for more work to manage, protect and monitor seagrass meadows (http://www.bbc.com/news/science-environment-37606827). Emerging from the 12th International Seagrass Biology Workshop, held in October2016, has been the view that grazing marine megafauna may play a useful role in helping to identify previously unknown seagrass habitats. Here we describe this concept,showing how detailed information on the distribution of both dugongs (Dugong dugon) and green sea turtles (Chelonia mydas) obtained, for example, by aerial surveys and satellite tracking, can reveal new information on the location of seagrass meadows. We show examples of how marine megaherbivores have been effective habitat indicators,revealing major, new, deep-water seagrass meadows and offering the potential for more informed estimates of seagrass extent in tropical and sub-tropical regions where currentinformation is often lacking

An inventory of dugong aerial surveys in Australia

• In Australia, the dugong (Dugong dugon) has significant cultural, ecological and conservation value. The species is a Matter of National Environmental Significance and is protected under the EPBC Act as a listed migratory and marine species. • Since the early 1970s various aerial survey methodologies have been used to provide data on the distribution and abundance of the dugong across northern Australia. The survey designs and platforms have evolved through time, and so have the methods to estimate dugong population distribution, sizes and trends. • An inventory of all dugong aerial surveys across the dugong range in Australia has not previously been compiled making it difficult to obtain a clear understanding of the efforts that have been put to date on surveying dugongs across their Australian range. The existence, locality and accessibility of the data generated from those surveys and their associated reports and/or scientifically peer-reviewed publications are not readily located or available for many surveys. • This inventory compiles information from all dugong aerial surveys undertaken since the first use of this methodology for dugongs in Australia, including date of survey, approach undertaken to survey, latest abundance estimate, relevant reference and link to publication, data availability and location etc. It also provides spatially-explicit maps to represent survey effort to date across the entire known dugong range in Australia. The development of this inventory has also helped identify similarities and discrepancies in the way dugong population estimates, trends and spatial distribution models have been generated. • Dugong aerial surveys in Australia date back from the early 1970s with shoreline reconnaissance surveys to assess the presence, distribution and relative numbers of dugongs in the inshore areas around the mainland and islands

Inferences about the conservation utility of using unmanned aerial vehicles to conduct rapid assessments for basking freshwater turtles

Unmanned aerial vehicles (UAVs), an emerging technology, show promise in ecological research. In this comparative study, I compare UAVs to a traditional sampling method, observations using spotting scopes. UAVs have yet to be used successfully for sampling freshwater turtles; however, they have been used with mixed success for monitoring mammals and birds. Herein, I propose that the conservation utility of UAVs be formally assessed in the field prior to them being used to make adaptive conservation and management decisions. I quantitatively and qualitatively evaluate the use of UAVs using a mixed methods approach in contrast to a proven field method as a means to elucidate our basic understanding of presence-absence. Being able to successfully use UAVs for ecological surveying would provide an easy, efficient, and less invasive way to study basking turtles

Detecting animals in African Savanna with UAVs and the crowds

Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different environments, tasks which are routinely performed through manual counting in large collections of images. In this paper, we propose a semi-automatic system able to detect large mammals in semi-arid Savanna. It relies on an animal-detection system based on machine learning, trained with crowd-sourced annotations provided by volunteers who manually interpreted sub-decimeter resolution color images. The system achieves a high recall rate and a human operator can then eliminate false detections with limited effort. Our system provides good perspectives for the development of data-driven management practices in wildlife conservation. It shows that the detection of large mammals in semi-arid Savanna can be approached by processing data provided by standard RGB cameras mounted on affordable fixed wings UAVs