Unmanned aerial vehicles (UAVs) have the potential to be an important tool providing low-cost but sufficiently precise mapping products to support environmental management. In this study, we present possible applications of UAVs to map and monitor three representative coastal tropical habitats: mangroves, rocky shores and coral reefs. We conducted UAVs surveys in a Marine Protected Area (MPA) of the tropical eastern Pacific region to investigate the suitability and usefulness of using this tool in a remote area for a variety of management and monitoring purposes. For mangrove ecosystems, we evaluated the potential of UAV-derived data to estimate canopy cover. On an intertidal rocky shore, we evaluated the potential of UAVs to obtain a detailed relative topographic position index that can be used to correlate the distribution patterns of resident and transient fauna. Finally, we compared the standard diver-based coral reef mapping approach used at the MPA with the use of a map produced with the UAV. Our results suggest that the use of UAVs by conservation practitioners in MPAs with diverse habitats, such as in the tropics, is likely to improve the knowledge of the MPAs environments and provide highly detailed information for monitoring helping to understand the nursery function of these inter-connected tropical habitats, at a reduced cost. This tool, therefore, has the potential to support conservation measures in a more effective way.
Tools and Data
The high degree of marine habitat degradation and the depletion of marine resources has led to numerous calls and initiatives to increase the coverage of marine protected areas (MPAs). Currently, marine reserves (no-take areas) cover approximately 2.2% of the world's oceans whilst most calls and targets suggest protection levels should be between 20% and 30% in order to achieve both conservation and resource management objectives. In this study a systematic conservation planning framework was developed using ecological and socio-economic data. This framework was used to test different protection scenarios in Portugal. The current situation in mainland Portugal is alarming, with 0.2% of the waters under national jurisdiction included in MPAs and only 0.002% being marine reserves. Moreover, ecologically important habitats, such as seagrass beds and mäerl beds, have less than 10% of their area protected. The solutions provided by Marxan, and subsequently improved with MinPatch, revealed that there is a need to considerably increase the area under protection. However, adequate protection could be achieved with a number of MPAs (between 5 and 14) similar to the number of already existing MPAs (n = 8). Different stakeholders (artisanal fisheries, industrial fisheries, and other human uses such as oil and gas, and offshore aquaculture) were considered in different scenarios, with the results of the multivariate analysis indicating that there are several solutions that satisfy all stakeholders. Therefore, the results of this study are a valuable starting point for the ongoing implementation process of an MPA network in Portugal since they integrate the most important stakeholders whilst also taking in consideration the ecological aspects. This framework can be applied elsewhere and can be easily amended whenever new information is available.
Capabilities of remotely operated vehicles (ROVs) have increased substantially in the last decade, and mini-ROV designs are now able to conduct visual research frequently conducted by snorkellers or divers in shallow marine environments. There are logistical, financial and experimental benefits of using mini-ROVs over snorkellers or divers, yet the adoption of mini-ROVs for common shallow underwater research tasks has not been widespread. To assess the capabilities of mini-ROVs to sample fish communities we compared the results produced by a mini-ROV to that of snorkellers for performing two of the most common marine video-based research activities (1) underwater visual fish census and (2) observing and tracking fish behaviour. Results of both activities suggested that the fish community observed by the mini-ROV was not distinguishable to that observed by the snorkellers, however, the mini-ROV detected significantly more fish (39% higher abundance) and greater diversity (24% higher). When tracking butterflyfish behaviour, video obtained from the mini-mini-ROV was as efficient as a snorkeller at finding and tracking individuals. Video from the mini-ROV produced comparable responses to that from snorkellers with hand-held GoPros, although over the course of tracks the response between the two methods differed, with a decrease in refuge time for snorkeller video and an increase in tailbeat rate for the mini-ROV video. Our study shows that video obtained from mini-ROVs can be used for research in shallow marine environments when direct manipulations are not required. We predict the research capabilities of mini-ROVs to increase substantially in the coming years, which should cement the use of this tool for research across all marine environments.
Environmental DNA is increasingly being used in marine invasive species surveillance despite the inability to discriminate between contemporary intracellular (i.e., living) and extracellularly persistent (i.e., legacy) DNA fragments. Environmental RNA is emerging as a powerful alternative when distinguishing the living portion of a community is essential. A positive relationship between DNA and RNA signals may justify the use of DNA only for more rapid and cost-effective detections. In this study environmental DNA and RNA were co-extracted from settlement plates and water samples collected in an Auckland harbor, New Zealand. Samples were analyzed using a specific droplet digital PCR assay for the invasive Mediterranean fanworm (Sabella spallanzanii), combined with metabarcoding of metazoan communities (Cytochrome c oxidase subunit I). The number and magnitude of S. spallanzanii detections was higher in DNA compared to RNA, and in water samples. An assessment of detection sensitivity and specificity using a Receiver Operator Characteristics (ROC) analysis supported a relationship between the magnitude of DNA signal and the likelihood of RNA detection for both sampled matrices. A prediction threshold of 400 COI copies in DNA samples provides an indicator for the detection of eRNA, hence the putative presence of living S. spallanzanii population under the conditions tested in this study. Metabarcoding community analysis revealed the taxonomic composition of the water samples to be more diverse than the plate samples which were largely dominated by mollusks. There was a strong association between mollusks and presumed extracellular droplet digital PCR signals. Nevertheless, droplet digital PCR detection signals based on environmental DNA were negatively correlated with metabarcoding diversity indices on plates. This highlights complex interactions between environmental DNA and RNA detections and environmental matrices that can affect targeted approaches. These interactions need to be considered when designing surveillance programs.
Many coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.
With the ongoing, exponential increase in ocean data from autonomous platforms, satellites, models, and in particular, the growing field of quantitative imaging, there arises a need for scalable and cost-efficient visualization tools to interpret these large volumes of data. With the recent proliferation of consumer grade head-mounted displays, the emerging field of virtual reality (VR) has demonstrated its benefit in numerous disciplines, ranging from medicine to archeology. However, these benefits have not received as much attention in the ocean sciences. Here, we summarize some of the ways that virtual reality has been applied to this field. We highlight a few examples in which we (the authors) demonstrate the utility of VR as a tool for ocean scientists. For oceanic datasets that are well-suited for three-dimensional visualization, virtual reality has the potential to enhance the practice of ocean science.
The prevalence of social media platforms that share photos and videos could prove useful for wildlife research and conservation programs. When social media users post pictures and videos of animals, near real-time data like individual identification, sex, location, or other information are made accessible to scientists. These data can help inform researchers about animal occurrence, behavior, or threats to survival. The endangered Hawaiian monk seal (Neomonachus schauinslandi) population has only 1,400 seals remaining in the wild. A small but growing population of seals has recently reestablished itself in the human-populated main Hawaiian Islands. While this population growth raises concerns about human-seal interactions it also provides the opportunity to capitalize on human observations to enhance research and conservation activities. We measured the potential utility of non-traditional data sources, in this case Instagram, to supplement current population monitoring of monk seals in the main Hawaiian Islands. We tracked all Instagram posts with the identifier #monkseal for a one-year period and assessed the photos for biological and geographical information, behavioral concerns, human disturbance and public perceptions. Social media posts were less likely to provide images suitable for individual seal identification (16.5%) than traditional sighting reports (79.9%). However, social media enhanced the ability to detect human-seal interactions or animal disturbances: 22.1%, of the 2,392 Instagram posts examined showed people within 3 meters of a seal, and 17.8% indicated a disturbance to the animal, meanwhile only 0.64% of traditional reports noted a disturbance to the animal. This project demonstrated that data obtained through social media posts have value to monk seal research and management strategies beyond traditional data collection, and further development of social media platforms as data resources is warranted. Many conservation programs may benefit from similar work using social media to supplement the research and conservation activities they are undertaking.
The declining costs of Unoccupied Aircraft Systems (UAS, aka drones), their ease of use, and their ability to collect high resolution data from a variety of sensors has resulted in an explosion of applications across the globe. Scientists working in the marine environment are increasingly using UAS to study a variety of topics, from counting wildlife populations in remote locations to estimating the effects of storms and sea level rise on shorelines. UAS also provide transformative potential to study the ways in which humans interact with and affect marine and coastal ecosystems, but doing so presents unique ethical and legal challenges. Human subjects have property rights that must be respected and they have rights to privacy, as well as expectations of privacy and security that may extend beyond actual legal rights. Using two case studies to illustrate these challenges, we outline the legal and regulatory landscapes that scientists confront when people are their primary study subjects, and conclude with an initial set of legal best practices to guide researchers in their efforts to study human interactions with natural resources in the marine environment.
Harmful algae blooms (HABs) in coastal marine environments are increasing in number and duration, pressuring local resource managers to implement mitigation solutions to protect human and ecosystem health. However, insufficient spatial and temporal observations create uninformed management decisions. In order to better detect and map blooms, as well as the environmental conditions responsible for their formation, long-term, unattended observation platforms are desired. In this article, we describe a new cost-efficient, autonomous, mobile platform capable of accepting several sensors that can be used to monitor HABs in near real time. The Navocean autonomous sail-powered surface vehicle is deployable by a single person from shore, capable of waypoint navigation in shallow and deep waters, and powered completely by renewable energy. We present results from three surveys of the Florida Red Tide HAB (Karenia brevis) of 2017–2018. The vessel made significant progress toward waypoints regardless of wind conditions while underway measurements revealed patches of elevated chl. a likely attributable to the K. brevis blooms as based on ancillary measurements. Measurements of colored dissolved organic matter (CDOM) and turbidity provided an environmental context for the blooms. While the autonomous sailboat directly adds to our phytoplankton/HAB monitoring capabilities, the package may also help to ground-truth satellite measurements of HABs if careful validation measurements are performed. Finally, several other pending and future use cases for coastal and inland monitoring are discussed. To our knowledge, this is the first demonstration of a sail-driven vessel used for coastal HAB monitoring.
Most cetacean species are wide-ranging and highly mobile, creating significant challenges for researchers by limiting the scope of data that can be collected and leaving large areas un-surveyed. Aerial surveys have proven an effective way to locate and study cetacean movements but are costly and limited in spatial extent. Here we present a semi-automated pipeline for whale detection from very high-resolution (sub-meter) satellite imagery that makes use of a convolutional neural network (CNN). We trained ResNet, and DenseNet CNNs using down-scaled aerial imagery and tested each model on 31 cm-resolution imagery obtained from the WorldView-3 sensor. Satellite imagery was tiled and the trained algorithms were used to classify whether or not a tile was likely to contain a whale. Our best model correctly classified 100% of tiles with whales, and 94% of tiles containing only water. All model architectures performed well, with learning rate controlling performance more than architecture. While the resolution of commercially-available satellite imagery continues to make whale identification a challenging problem, our approach provides the means to efficiently eliminate areas without whales and, in doing so, greatly accelerates ocean surveys for large cetaceans.