Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas)

A novel seaweed detection image processing and validation framework: A pragmatic study on natural seaweed beds along North-West Coast of India

Seaweeds play a pivotal role in global ecology contributing significantly to biodiversity conservation and coastal habitat of marine ecosystems. In particular, natural seaweed beds are increasingly vulnerable to climate change and commercial exploitation, necessitate the effective monitoring, especially given the extensive coastlines. Thus, this study presents a novel framework that integrates remote sensing, image processing techniques, and on-site validation methods to standardize indices for seaweed cover changes and abundance detection across three selected natural coastal seaweed beds along the biodiversity-rich North-West Coast of India. We introduce a novel in-situ validation method to assess seaweed abundance while standardizing three remote sensing indices i.e. the Normalized Difference Vegetation Index (NDVI), the Floating Algae Index (FAI), and the Seaweed Enhancing Index (SEI). By correlating ground-truth measurements of seaweed biomass with values derived from remote sensing indices, we enable detailed estimations of both presence and abundance. Our findings reveal that the natural seaweed beds along the Veraval coast exhibit the highest levels of vegetation cover, followed by other selected sites at Kelwa and Porbandar, with robust correlations observed across all indices. Notably, the SEI demonstrated superior accuracy in identifying seaweed habitats compared to NDVI and FAI. Ground-truth validation substantiates the reliability of our results, signifying positive correlations between the index outputs and actual seaweed abundance. Also, this study establishes a robust framework for future research by introducing indices standardization methodologies for remote sensing and image processing of seaweed habitats. By demonstrating the efficacy of in-situ validation and grid-based assessments, we have effectively quantified seaweed density and distribution. Furthermore, the integration of advanced remote sensing data from Landsat-8 not only facilitates long-term monitoring but also provides a valuable baseline for spatio-temporal analyses of seaweed habitat dynamics.

Global floating kelp forests have limited protection despite intensifying marine heatwave threats

Kelp forests are one of the earth's most productive ecosystems and are at great risk from climate change, yet little is known regarding their current conservation status and global future threats. Here, by combining a global remote sensing dataset of floating kelp forests with climate data and projections, we find that exposure to projected marine heatwaves will increase ~6 to ~16 times in the long term (2081-2100) compared to contemporary (2001-2020) exposure. While exposure will intensify across all regions, some southern hemisphere areas which have lower exposure to contemporary and projected marine heatwaves may provide climate refugia for floating kelp forests. Under these escalating threats, less than 3% of global floating kelp forests are currently within highly restrictive marine protected areas (MPAs), the most effective MPAs for protecting biodiversity. Our findings emphasize the urgent need to increase the global protection of floating kelp forests and set bolder climate adaptation goals.

Improving Ocean Management Using Insights from Space

Advancements in space-based ocean observation and computational data processing techniques have demonstrated transformative value for managing living resources, biodiversity, and ecosystems of the ocean. We synthesize advancements in leveraging satellite-derived insights to better understand and manage fishing, an emerging revolution of marine industrialization, ocean hazards, sea surface dynamics, benthic ecosystems, wildlife via electronic tracking, and direct observations of ocean megafauna. We consider how diverse space-based data sources can be better coupled to modernize and improve ocean management. We also highlight examples of how data from space can be developed into tools that can aid marine decision-makers managing subjects from whales to algae. Thoughtful and prospective engagement with such technologies from those inside and outside the marine remote sensing community is, however, essential to ensure that these tools meet their full potential to strengthen the effectiveness of ocean management.

A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific

Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae-kelps-form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of -17.08° S of latitude for 2090-2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to -27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio-ecological systems of the Southeast Pacific.

Kelpwatch: A new visualization and analysis tool to explore kelp canopy dynamics reveals variable response to and recovery from marine heatwaves

Giant kelp and bull kelp forests are increasingly at risk from marine heatwave events, herbivore outbreaks, and the loss or alterations in the behavior of key herbivore predators. The dynamic floating canopy of these kelps is well-suited to study via satellite imagery, which provides high temporal and spatial resolution data of floating kelp canopy across the western United States and Mexico. However, the size and complexity of the satellite image dataset has made ecological analysis difficult for scientists and managers. To increase accessibility of this rich dataset, we created Kelpwatch, a web-based visualization and analysis tool. This tool allows researchers and managers to quantify kelp forest change in response to disturbances, assess historical trends, and allow for effective and actionable kelp forest management. Here, we demonstrate how Kelpwatch can be used to analyze long-term trends in kelp canopy across regions, quantify spatial variability in the response to and recovery from the 2014 to 2016 marine heatwave events, and provide a local analysis of kelp canopy status around the Monterey Peninsula, California. We found that 18.6% of regional sites displayed a significant trend in kelp canopy area over the past 38 years and that there was a latitudinal response to heatwave events for each kelp species. The recovery from heatwave events was more variable across space, with some local areas like Bahía Tortugas in Baja California Sur showing high recovery while kelp canopies around the Monterey Peninsula continued a slow decline and patchy recovery compared to the rest of the Central California region. Kelpwatch provides near real time spatial data and analysis support and makes complex earth observation data actionable for scientists and managers, which can help identify areas for research, monitoring, and management efforts.

The Falkland Islands marine ecosystem: A review of the seasonal dynamics and trophic interactions across the food web

The Falkland Islands marine environment host a mix of temperate and subantarctic species. This review synthesizes baseline information regarding ontogenetic migration patterns and trophic interactions in relation to oceanographic dynamics of the Falkland Shelf, which is useful to inform ecosystem modelling. Many species are strongly influenced by regional oceanographic dynamics that bring together different water masses, resulting in high primary production which supports high biomass in the rest of the food web. Further, many species, including those of commercial interest, show complex ontogenetic migrations that separate spawning, nursing, and feeding grounds spatially and temporally, producing food web connections across space and time. The oceanographic and biological dynamics may make the ecosystem vulnerable to climatic changes in temperature and shifts in the surrounding area. The Falkland marine ecosystem has been understudied and various functional groups, deep-sea habitats and inshore-offshore connections are poorly understood and should be priorities for further research.

Artificial intelligence convolutional neural networks map giant kelp forests from satellite imagery

Climate change is producing shifts in the distribution and abundance of marine species. Such is the case of kelp forests, important marine ecosystem-structuring species whose distributional range limits have been shifting worldwide. Synthesizing long-term time series of kelp forest observations is therefore vital for understanding the drivers shaping ecosystem dynamics and for predicting responses to ongoing and future climate changes. Traditional methods of mapping kelp from satellite imagery are time-consuming and expensive, as they require high amount of human effort for image processing and algorithm optimization. Here we propose the use of mask region-based convolutional neural networks (Mask R-CNN) to automatically assimilate data from open-source satellite imagery (Landsat Thematic Mapper) and detect kelp forest canopy cover. The analyses focused on the giant kelp Macrocystis pyrifera along the shorelines of southern California and Baja California in the northeastern Pacific. Model hyper-parameterization was tuned through cross-validation procedures testing the effect of data augmentation, and different learning rates and anchor sizes. The optimal model detected kelp forests with high performance and low levels of overprediction (Jaccard's index: 0.87 ± 0.07; Dice index: 0.93 ± 0.04; over prediction: 0.06) and allowed reconstructing a time series of 32 years in Baja California (Mexico), a region known for its high variability in kelp owing to El Niño events. The proposed framework based on Mask R-CNN now joins the list of cost-efficient tools for long-term marine ecological monitoring, facilitating well-informed biodiversity conservation, management and decision making.