Artificial intelligence and automated monitoring for assisting conservation of marine ecosystems: A perspective

Conservation of marine ecosystems has been highlighted as a priority to ensure a sustainable future. Effective management requires data collection over large spatio-temporal scales, readily accessible and integrated information from monitoring, and tools to support decision-making. However, there are many roadblocks to achieving adequate and timely information on both the effectiveness, and long-term success of conservation efforts, including limited funding, inadequate sampling, and data processing bottlenecks. These factors can result in ineffective, or even detrimental, management decisions in already impacted ecosystems. An automated approach facilitated by artificial intelligence (AI) provides conservation managers with a toolkit that can help alleviate a number of these issues by reducing the monitoring bottlenecks and long-term costs of monitoring. Automating the collection, transfer, and processing of data provides managers access to greater information, thereby facilitating timely and effective management. Incorporating automation and big data availability into a decision support system with a user-friendly interface also enables effective adaptive management. We summarise the current state of artificial intelligence and automation techniques used in marine science and use examples in other disciplines to identify existing and potentially transferable methods that can enable automated monitoring and improve predictive modelling capabilities to support decision making. We also discuss emerging technologies that are likely to be useful as research in computer science and associated technologies continues to develop and become more accessible. Our perspective highlights the potential of AI and big data analytics for supporting decision-making, but also points to important knowledge gaps in multiple areas of the automation processes. These current challenges should be prioritised in conservation research to move toward implementing AI and automation in conservation management for a more informed understanding of impacted ecosystems to result in successful outcomes for conservation managers. We conclude that the current research and emphasis on automated and AI assisted tools in several scientific disciplines may mean the future of monitoring and management in marine science is facilitated and improved by the implementation of automation

Anthropogenic pressures and life history predict trajectories of seagrass meadow extent at a global scale

Seagrass meadows are threatened by multiple pressures, jeopardizing the many benefits they provide to humanity and biodiversity, including climate regulation and food provision through fisheries production. Conservation of seagrass requires identification of the main pressures contributing to loss and the regions most at risk of ongoing loss. Here, we model trajectories of seagrass change at the global scale and show they are related to multiple anthropogenic pressures but that trajectories vary widely with seagrass life-history strategies. Rapidly declining trajectories of seagrass meadow extent (>25% loss from 2000 to 2010) were most strongly associated with high pressures from destructive demersal fishing and poor water quality. Conversely, seagrass meadow extent was more likely to be increasing when these two pressures were low. Meadows dominated by seagrasses with persistent life-history strategies tended to have slowly changing or stable trajectories, while those with opportunistic species were more variable, with a higher probability of either rapidly declining or rapidly increasing. Global predictions of regions most at risk for decline show high-risk areas in Europe, North America, Japan, and southeast Asia, including places where comprehensive long-term monitoring data are lacking. Our results highlight where seagrass loss may be occurring unnoticed and where urgent conservation interventions are required to reverse loss and sustain their essential services

Opportunities for improving recognition of coastal wetlands in global ecosystem assessment frameworks

Vegetated coastal wetlands, including seagrass, saltmarsh and mangroves, are threatened globally, yet the need to avert these losses is poorly recognized in international policy, such as in the Convention on Biological Diversity and the United Nations (UN) Sustainable Development Goals. Identifying the impact of overlooking coastal wetlands in ecosystem assessment frameworks could help prioritize research efforts to fill these gaps. Here, we examine gaps in the recognition of coastal wetlands in globally applicable ecosystem assessments. We address both shortfalls in assessment frameworks when it comes to assessing wetlands, and gaps in data that limit widespread application of assessments. We examine five assessment frameworks that track fisheries, greenhouse gas emissions, ecosystem threats, and ecosystem services. We found that these assessments inform management decisions, but that the functions provided by coastal wetlands are incompletely represented. Most frameworks had sufficient complexity to measure wetland status, but limitations in data meant they were incompletely informed about wetland functions and services. Incomplete representation of coastal wetlands may lead to them being overlooked by research and management. Improving the coverage of coastal wetlands in ecosystem assessments requires improving global scale mapping of wetland trends, developing global-scale indicators of wetland function and synthesis to quantitatively link animal population dynamics to wetland trends. Filling these gaps will help ensure coastal wetland conservation is properly informed to manage them for the outstanding benefits they bring humanity

A High-Throughput Screen Indicates Gemcitabine and JAK Inhibitors May be Useful for Treating Pediatric AML

Improvement in survival has been achieved for children and adolescents with AML but is largely attributed to enhanced supportive care as opposed to the development of better treatment regimens. High risk subtypes continue to have poor outcomes with event free survival rates \u3c 40% despite the use of high intensity chemotherapy in combination with hematopoietic stem cell transplant. Here we combine high-throughput screening, intracellular accumulation assays, and in vivo efficacy studies to identify therapeutic strategies for pediatric AML. We report therapeutics not currently used to treat AML, gemcitabine and cabazitaxel, have broad anti-leukemic activity across subtypes and are more effective relative to the AML standard of care, cytarabine, both in vitro and in vivo. JAK inhibitors are selective for acute megakaryoblastic leukemia and significantly prolong survival in multiple preclinical models. Our approach provides advances in the development of treatment strategies for pediatric AML

Harnessing big data to support the conservation and rehabilitation of mangrove forests globally

Mangrove forests are found on sheltered coastlines in tropical, subtropical, and some warm temperate regions. These forests support unique biodiversity and provide a range of benefits to coastal communities, but as a result of large-scale conversion for aquaculture, agriculture, and urbanization, mangroves are considered increasingly threatened ecosystems. Scientific advances have led to accurate and comprehensive global datasets on mangrove extent, structure, and condition, and these can support evaluation of ecosystem services and stimulate greater conservation and rehabilitation efforts. To increase the utility and uptake of these products, in this Perspective we provide an overview of these recent and forthcoming global datasets and explore the challenges of translating these new analyses into policy action and on-the-ground conservation. We describe a new platform for visualizing and disseminating these datasets to the global science community, non-governmental organizations, government officials, and rehabilitation practitioners and highlight future directions and collaborations to increase the uptake and impact of large-scale mangrove research. This Perspective reviews the role of global-scale research in stimulating policy action and on-the-ground conservation for mangrove ecosystems. We outline the current state of knowledge in terms of global analyses and examine the challenge of translating this research in action

Global typologies of coastal wetland status to inform conservation and management

Global-scale conservation initiatives and policy instruments rely on ecosystem indicators to track progress towards targets and objectives. A deeper understanding of indicator interrelationships would benefit these efforts and help characterize ecosystem status. We study interrelationships among 34 indicators for mangroves, saltmarsh, and seagrass ecosystems, and develop data-driven, spatially explicit typologies of coastal wetland status at a global scale. After accounting for environmental covariates and gap-filling missing data, we obtained two levels of clustering at 5 and 18 typologies, providing outputs at different scales for different end users. We generated 2,845 cells (1° (lat) × 1° (long)) globally, of which 29.7% were characterized by high land- and marine-based impacts and a high proportion of threatened species, 13.5% by high climate-based impacts, and 9.6% were refuges with lower impacts, high fish density and a low proportion of threatened species. We identify instances where specific actions could have positive outcomes for coastal wetlands across regions facing similar issues. For example, land- and marine-based threats to coastal wetlands were associated with ecological structure and function indicators, suggesting that reducing these threats may reduce habitat degradation and threats to species persistence. However, several interdimensional relationships might be affected by temporal or spatial mismatches in data. Weak relationships mean that global biodiversity maps that categorize areas by single indicators (such as threats or trends in habitat size) may not be representative of changes in other indicators (e.g., ecosystem function). By simplifying the complex global mosaic of coastal wetland status and identifying regions with similar issues that could benefit from knowledge exchange across national boundaries, we help set the scene for globally and regionally coordinated conservation

Restoring tropical coastal wetland water quality: ecosystem service provisioning by a native freshwater bivalve

Freshwater bivalves can influence water quality by reducing phytoplankton levels through filter-feeding and altering nutrient levels through excretion and biodeposition. In northeast Australia, native freshwater bivalves (Corbicula australis) may help restore the water quality of coastal wetlands that receive high nutrient loads in runoff from nearby agricultural activity. We investigated the biofiltration and biodeposition capacity of C. australis and discuss their potential to provide an ecosystem service benefit of improved water quality to the Great Barrier Reef (GBR). The filtration and biodeposition rates of C. australis were measured in natural and artificial wetlands across: (1) the population's size range; and (2) the temperature range of the wetlands they inhabit. High frequency water temperature loggers were deployed in wetlands throughout the year to determine water column temperature seasonality, population densities were measured to scale from individuals to ecosystem service provisioning potential. Bivalve filtration and biodeposition were quantified by measuring the rates of chlorophyll a removal and nutrient biodeposition, respectively. Biofiltration rates did not increase with size or differ between natural and artificial wetlands. In contrast, size was positively related to phosphorus (P) and nitrogen (N) biodepsoition rates, and N biodeposition rates differed between natural and artificial wetlands. Our results also suggest that biofiltration and biodeposition capacity of C. australis may be limited in high water temperatures only experienced in summer months. Overall, we demonstrate the importance of size, population density, and environmental context (i.e. wetland type and season) for the filtering capacity and biodeposition rate of C. australis. Larger individuals and denser populations mean that filtration and biodeposition rates are likely to be higher in artificial wetlands and may lead to greater processing of nutrient rich water

Nutrient subsidy indicators predict the presence of an avian mobile-link species

Island ecosystems can be inordinately dependent on avian nutrient subsidies because of their isolation from external nutrient pools. We investigated relationships between several nutrient subsidy indicators and the presence of Torresian Imperial-Pigeon (TIP, Ducula spilorrhoa) breeding colonies in island forests of northeast Australia. The following nutrient subsidy indicators were measured in island forest soil and leaf samples: nutrient origin (δN and δC ); total carbon (C), nitrogen (N), and phosphorus (P) levels; and nutrient quality (C:N:P ratios). Random Forest models were used to determine the relative importance of nutrient subsidy indicators for classifying island forests as ‘TIP colony present’ or ‘TIP colony absent’. Total P was the most important soil nutrient subsidy indicator, while δN was the most important leaf nutrient subsidy indicator. Furthermore, in both soil and leaves, δN enrichment and N and P levels increased as the probability of TIP colony presence increased. Measures of nutrient quality also implied plant growth rates were higher in island forests with increased likelihood of TIP colony presence. Torresian Imperial-Pigeons should be classified as an avian mobile-link species with an important role in island ecosystem functioning, encouraging further investigation of the direct and indirect effects associated with TIP nutrient subsidies. This research highlights the importance of understanding the local-scale connectivity processes that underpin the longer distance movements of inter-continental migrants for effective ecosystem management

Spatial dynamics of coastal forest bird assemblages: the influence of landscape context, forest type, and structural connectivity

Context: Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation. Objectives: This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales. Methods: Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12\ua0km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis. Results: Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale. Conclusions: Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales