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

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

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

Bay watch: using unmanned aerial vehicles (UAV’s) to survey the box jellyfish Chironex fleckeri

Biological investigations on free ranging marine species are regarded as challenging throughout the scientific community. This is particularly true for ‘logistically difficult species’ where their cryptic natures, low abundance, patchy distributions and difficult and/or dangerous sampling environments, make traditional surveys near impossible. What results is a lack of ecological knowledge on such marine species. However, advances in UAV technology holds potential for overcoming these logistical difficulties and filling this knowledge gap. Our research focused on one such logistically difficult species, the Australian box Jellyfish (Chironex fleckeri), and we investigated the capacity of consumer grade UAV technology to detect this, highly venomous, target species in the inshore waters of Northern Queensland Australia. At two sites in the Weipa area, we utilized video analysis, visual count comparisons with a netted animal tally, and evaluated the role of associated environmental conditions, such as wind speed, water visibility and cloud cover on jellyfish detection rates. In total fifteen, 70 meter transects were completed between two sites, with 107 individuals captured. Drone success varied between the two sites with a significant difference between field and post-field (laboratory) counts. Animal size and cloud cover also had significant effects on detection rates with an increase in cloud cover and animal size enhancing detection probability. This study provides evidence to suggest drone surveys overcome obstacles that traditional surveys can’t, with respect to species deemed logistically difficult and open scope for further ecological investigations on such species

Understanding, Quantifying, and Reducing Bias in Fisheries-independent Visual Surveys

Understanding spatiotemporal changes in populations is vital for conservation managers to assess current recovery efforts, determine future conservation priorities, and forms the basis to explore complex ecological questions. In fisheries, these data have traditionally been collected using fisheries-independent surveys that rely on extractive sampling practices (e.g., longlines, gillnets, trawls). However, with the growing availability of low-cost, high-definition cameras, researchers are increasingly using visual surveys as a non-invasive alternative. Camera surveys have a number of advantages including their archivable data, and offer insights into species habitat use and behavior. However, the use of cameras has a number of inherent biases. Understanding, quantifying, and mitigating against these biases is critical if camera systems are to be used to inform management and policy. In this dissertation, potential biases were explored for two commonly used visual survey methods; baited remote underwater videos (BRUV), and unmanned aerial vehicles (UAV). Specifically, our objectives were to answer: (1) Are metrics of relative abundance derived from BRUVs linearly related to true changes in abundance for elasmobranchs, (2) Are these same metrics sensitive to changes in density-independent factors, and (3) Can UAVs be used to replace or supplement traditional diver transects for marine invertebrate species? Using a combination of standard and full-spherical camera BRUV deployments, Chapter One found that tradition BRUVs likely undercount sharks in high density environments, while also having lower probability of detection than full-spherical cameras. Using a spatially-explicit, individual-based-model, Chapter Two revealed that metrics of relative abundance derived BRUVs are also highly sensitive to factors unrelated to changes in abundance (e.g., swimming speed, current strength, and movement patterns). Lastly, using paired snorkeler-UAV transect sampling Chapter Three found counts derived from UAV transects did not significantly differ from divers, and offered a number of advantages over this traditional technique (increased percision, larger surveyed area, and automation). Furthermore, we found that UAVs could be used to improve sampling design used to quantify invertebrates, by estimating their distribution within a study region prior to initiating transect sampling. Collectively, these works improve our understanding and interpretation of video survey results that are used for management across the globe