The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientificand societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS.
Maritime economy, ecosystem-based management and climate change adaptation and mitigation raise emerging needs on coastal ocean and biological observations. Integrated ocean observing aims at optimizing sampling strategies and cost-efficiency, sharing data and best practices, and maximizing the value of the observations for multiple purposes. Recently developed cost-effective, near real time technology such as gliders, radars, ferrybox, and shallow water Argo floats, should be used operationally to generate operational coastal sea observations and analysis. Furthermore, value of disparate coastal ocean observations can be unlocked with multi-dimensional integration on fitness-for-the-purpose, parameter and instrumental. Integration of operational monitoring with offline monitoring programs, such as those for research, ecosystem-based management and commercial purposes, is necessary to fill the gaps. Such integration should lead to a system of networks which can deliver data for all kinds of purposes. Detailed integration activities are identified which should enhance the coastal ocean and biological observing capacity. Ultimately a program is required which integrates physical, biogeochemical and biological observation of the ocean, from coastal to deep-sea environments, bringing together global, regional, and local observation efforts.
Çandarlı Bay is a marine environment at risk of heavy pollution because of industrial facilities including the only ship recycling zone of Turkey, and intense marine traffic related to the raw materials needs of a dense industrial zone. These risk factors make the development of practical environmental management strategies increasingly necessary. Oil spills from the heavy ship traffic, one of the major risks, can be detected by satellite remote sensing technologies. In this study, it is aimed to show spatial characteristics of oil spills as well as its dynamics in the time domain of the bay. Results from a three year period of the study show that as a main environmental problem, oil pollution has a relatively high percentage of spatial distribution in the bay. It is therefore concluded that regular monitoring of the intense oil pollution in the bay is required with an agile and low-cost method of satellite monitoring to intervene in good time and to minimize its impacts. The study provided an extensive understanding of spatio-temporal dynamics of oil pollution in the bay. The approach used will also provide a baseline for decision-makers to develop environmental management plans for other coastal zones with similar sensitivities.
Ocean acidification is mainly being monitored using data loggers which currently offer limited coverage of marine ecosystems. Here, we trial the use of gastropod shells to monitor acidification on rocky shores. Animals living in areas with highly variable pH (8.6–5.9) were compared with those from sites with more stable pH (8.6–7.9). Differences in site pH were reflected in size, shape and erosion patterns in Nerita chamaeleon and Planaxis sulcatus. Shells from acidified sites were shorter, more globular and more eroded, with both of these species proving to be good biomonitors. After an assessment of baseline weathering, shell erosion can be used to indicate the level of exposure of organisms to corrosive water, providing a tool for biomonitoring acidification in heterogeneous intertidal systems. A shell erosion ranking system was found to clearly discriminate between acidified and reference sites. Being spatially-extensive, this approach can identify coastal areas of greater or lesser acidification. Cost-effective and simple shell erosion ranking is amenable to citizen science projects and could serve as an early-warning-signal for natural or anthropogenic acidification of coastal waters.
In coastal waters around the world, the dominant primary producers are benthic macrophytes, including seagrasses and macroalgae, that provide habitat structure and food for diverse and abundant biological communities and drive ecosystem processes. Seagrass meadows and macroalgal forests play key roles for coastal societies, contributing to fishery yields, storm protection, biogeochemical cycling and storage, and important cultural values. These socio-economically valuable services are threatened worldwide by human activities, with substantial areas of seagrass and macroalgal forests lost over the last half-century. Tracking the status and trends in marine macrophyte cover and quality is an emerging priority for ocean and coastal management, but doing so has been challenged by limited coordination across the numerous efforts to monitor macrophytes, which vary widely in goals, methodologies, scales, capacity, governance approaches, and data availability. Here, we present a consensus assessment and recommendations on the current state of and opportunities for advancing global marine macrophyte observations, integrating contributions from a community of researchers with broad geographic and disciplinary expertise. With the increasing scale of human impacts, the time is ripe to harmonize marine macrophyte observations by building on existing networks and identifying a core set of common metrics and approaches in sampling design, field measurements, governance, capacity building, and data management. We recommend a tiered observation system, with improvement of remote sensing and remote underwater imaging to expand capacity to capture broad-scale extent at intervals of several years, coordinated with stratified in situ sampling annually to characterize the key variables of cover and taxonomic or functional group composition, and to provide ground-truth. A robust networked system of macrophyte observations will be facilitated by establishing best practices, including standard protocols, documentation, and sharing of resources at all stages of workflow, and secure archiving of open-access data. Because such a network is necessarily distributed, sustaining it depends on close engagement of local stakeholders and focusing on building and long-term maintenance of local capacity, particularly in the developing world. Realizing these recommendations will produce more effective, efficient, and responsive observing, a more accurate global picture of change in vegetated coastal systems, and stronger international capacity for sustaining observations.
Ocean monitoring will improve outcomes if ways of knowing and priorities from a range of interest groups are successfully integrated. Coastal Indigenous communities hold unique knowledge of the ocean gathered through many generations of inter-dependent living with marine ecosystems. Experiences and observations from living within that system have generated ongoing local and traditional ecological knowledge (LEK and TEK) and Indigenous knowledge (IK) upon which localized sustainable management strategies have been based. Consequently, a comprehensive approach to ocean monitoring should connect academic practices (“science”) and local community and Indigenous practices, encompassing “TEK, LEK, and IK.” This paper recommends research approaches and methods for connecting scientists, local communities, and IK holders and their respective knowledge systems, and priorities, to help improve marine ecosystem management. Case studies from Canada and New Zealand (NZ) highlight the emerging recognition of IK systems in natural resource management, policy and economic development. The in-depth case studies from Ocean Networks Canada (ONC) and the new Moana Project, NZ highlight real-world experiences connecting IK with scientific monitoring programs. Trial-tested recommendations for successful collaboration include practices for two-way knowledge sharing between scientists and communities, co-development of funding proposals, project plans and educational resources, mutually agreed installation of monitoring equipment, and ongoing sharing of data and research results. We recommend that future ocean monitoring research be conducted using cross-cultural and/or transdisciplinary approaches. Vast oceans and relatively limited monitoring data coupled with the urgency of a changing climate emphasize the need for all eyes possible providing new data and insights. Community members and ocean monitoring scientists in joint research teams are essential for increasing ocean information using diverse methods compared with previous scientific research. Research partnerships can also ensure impactful outcomes through improved understanding of community needs and priorities.
Plankton are the base of marine food webs, essential to sustaining fisheries and other marine life. Continuous Plankton Recorders (CPRs) have sampled plankton for decades in both hemispheres and several regional seas. CPR research has been integral to advancing understanding of plankton dynamics and informing policy and management decisions. We describe how the CPR can contribute to global plankton diversity monitoring, being cost-effective over large scales and providing taxonomically resolved data. At OceanObs09 an integrated network of regional CPR surveys was envisaged and in 2011 the existing surveys formed the Global Alliance of CPR Surveys (GACS). GACS first focused on strengthening the dataset by identifying and documenting CPR best practices, delivering training workshops, and developing an integrated database. This resulted in the initiation of new surveys and manuals that enable regional surveys to be standardized and integrated. GACS is not yet global, but it could be expanded into the remaining oceans; tropical and Arctic regions are a priority for survey expansion. The capacity building groundwork is done, but funding is required to implement the GACS vision of a global plankton sampling program that supports decision-making for the scientific and policy communities. A key step is an analysis to optimize the global sampling design. Further developments include expanding the CPR for multidisciplinary measurements via additional sensors, thus maximizing the ship-of-opportunity platform. For example, defining pelagic ecoregions based on plankton and ancillary data could support high seas Marine Protected Area design. Fulfillment of Aichi Target 15, the United Nation’s Sustainable Development Goals, and delivering the Essential Ocean Variables and Essential Biodiversity Variables that the Global Ocean Observing System and Group on Earth Observation’s Biodiversity Observation Network have, respectively, defined requires the taxonomic resolution, spatial scale and time-series data that the CPR approach provides. Synergies with global networks exploiting satellite data and other plankton sensors could be explored, realizing the Survey’s capacity to validate earth observation data and to ground-truth emerging plankton observing platforms. This is required for a fully integrated ocean observing system that can understand global ocean dynamics to inform sustainable marine decision-making.
The fin whale is a globally endangered species and is listed as threatened in Australia, however no peer-reviewed studies are available to indicate the migratory movements of the species in Australian waters. This study uses passive acoustic monitoring as a tool to identify the migratory movements of fin whales in Australian waters. Sampling was conducted from eight locations around Australia between 2009 and 2017, providing a total of 37 annual migratory records. Taken together, our observations provide evidence of fin whale migration through Australian waters, with earliest arrival of the animals recorded on the Western Australian coast, at Cape Leeuwin in April. The whales travel through Cape Leeuwin, migrating northward along the Western Australian coast to the Perth Canyon (May to October), which likely acts as a way-station for feeding. Some whales continue migrating as far north as Dampier (19°S). On Australia’s east coast, at Tuncurry, fin whale seasonal presence each year occurred later, from June to late September/October. A total of only 8,024 fin whale pulses were recorded on the east coast, compared to 177,328 pulses recorded at the Perth Canyon. We suggest these differences, as well as the spatial separation between coasts, provide preliminary evidence that the fin whales present on the east and west coasts constitute separate sub-populations.
Small-scale marine fisheries in Tanzania provide the main source of subsistence for coastal communities, yet due to poor management, they have been overexploited for decades. These coastal fisheries have historically been described as homogeneous in gear-use and fish community makeup. Yet, regional and local variability in the characteristics of these fishing communities was recently identified with community-based fisheries-dependent data. We proposed a flexible modeling approach that incorporated local monitoring data with spatial data to predict the spatial characteristics of the marine fisheries in Tanzania. The spatial models identified relationships between fishery landings and coral reef, seagrass, and mangrove habitat patch attributes, along with fisher density and a hydrologic index. Furthermore, the predicted spatial characteristics matched previously reported fishery characteristics in both districts. The maps developed by our modeling process provide a means for stakeholders and managers to understand the spatial distribution of their fisheries and in turn, focus on explicitly managing what, how, and where fishers operate. Overall, the flexible modeling approach developed here may act as a first step in incorporating local monitoring data into co-management frameworks, which may promote more sustainable fisheries management strategies in data-poor regions.
Analysis of data from vessel monitoring systems and automated identification systems in large-scale fisheries is used to describe the spatial distribution of effort, impact on habitats, and location of fishing grounds. To identify when and where fishing activities occur, analysis needs to take account of different fishing practices in different fleets. Small-scale fisheries (SSFs) vessels have generally been exempted from positional reporting requirements, but recent developments of compact low-cost systems offer the potential to monitor them effectively. To characterize the spatial distribution of fishing activities in SSFs, positions should be collected with sufficient frequency to allow detection of different fishing behaviours, while minimizing demands for data transmission, storage, and analysis. This study sought to suggest optimal rates of data collection to characterize fishing activities at appropriate spatial resolution. In a SSF case study, on-board observers collected Global Navigation Satellite System (GNSS) position and fishing activity every second during each trip. In analysis, data were re-sampled to lower temporal resolutions to evaluate the effect on the identification of number of hauls and area fished. The effect of estimation at different spatial resolutions was also explored. Consistent results were found for polling intervals <60 s in small vessels and <120 in medium and large vessels. Grid cell size of 100 × 100 m resulted in best estimations of area fished. Remote collection and analysis of GNSS or equivalent data at low cost and sufficient resolution to infer small-scale fisheries activities. This has significant implications globally for sustainable management of these fisheries, many of which are currently unregulated.