BioConsult SH (Germany)

There is an ambitious global goal to protect 30% of the ocean by 2030. However, currently, only 8.1% of the ocean is protected and over 80% of the ocean is still unexplored. We thus urgently need to collect data for evidence-based decision-making to help tackle the global climate and biodiversity crises and to support coastal communities. But mapping these areas and key indicator species like whales using ship-based and aerial surveys tend to be limited in scale/scope, time-consuming, expensive and pose safety risks to surveyors, while acoustic monitoring is difficult to convert into counts of individuals for most species. To overcome these challenges, BioConsult SH and HiDef Aerial Surveying Ltd developed the service, SPACEWHALE. Bridging technological innovation with marine conservation, SPACEWHALE monitors whales and other wildlife species from space using satellite imagery and AI. We determine where whales are, provide a minimum count and investigate when they are in certain areas—quickly and over wide cross-border areas—yet at comparable costs to traditional survey methods. The “SPACEWHALE” service uses very high-resolution satellite imagery (e.g., resolution of 0.3 m per pixel). At this resolution, we can distinguish between several large whale species as well as between juveniles and adults. In addition, we can detect a diverse range of large cetaceans down to a body length of 9 meters and smaller. By taking a snapshot of the ocean area of interest, we can capture very large and remote areas almost instantaneously. Due to licensing restrictions, we are not permitted to share satellite imagery itself, but we summarise our findings in a report that contains easily processable data, such as the locations of the whales, for further analysis. We developed a semi-automatic process to evaluate satellite images combining state-of-the-art artificial intelligence with marine mammal expertise. Artificial intelligence as applied in SPACEWHALE means that data are collected and processed in a standardized way: satellite imagery is first analysed by a convolutional neural network-based object detection algorithm. Our algorithm is highly effective: a study in collaboration with Stony Brook University in New York and HiDef Aerial Surveying Ltd from the UK showed that the algorithm correctly classified 100% of images containing whales and 94% of images containing only water (Borowicz et al. 2019). Once the automated process is complete, a large team of expert reviewers validates the outputs to ensure that misclassifications such as boats, rocks, waves or sea foam are minimized, implementing a human-in-the-loop framework for comparable and quality-checked data. Applying this semi-automatic approach in diverse ecosystems, we have already successfully monitored fin whales and other species in the Bay of Biscay and in the Pelagos Sanctuary, blue whales and other marine megafauna off Mexico, humpback whales in Hawaiian waters, and southern right whales off Argentina and New Zealand. The methodology has been validated through comparison with conventional aerial and ship-based surveys demonstrating a strong agreement (Höschle et al. 2022). Satellite snapshots can be taken over previously unexplored areas, providing baseline data for environmental impact assessments for offshore wind farm operators and contributing to the identification of Important Marine Mammal Areas and Marine Protected Areas. The service can be applied at different spatial and temporal scales, from local and regional to ocean basins and over time with repeated surveys, enabling long-term monitoring, generating robust, standardized data for marine spatial planning and complementing international efforts (e. g. Marine Strategy Framework Directive, Convention on Biological Diversity targets, United Nations Ocean Decade). We are at a step where satellite-based data informs applied conservation by providing useful guidance to find solutions that balance species conservation with human use of the seas. It has the potential to elevate conservation efforts to appropriate spatial scales for wide ranging species.

In the Wadden Sea, intertidal mussel beds of the blue mussel (Mytilus edulis) and the Pacific oyster (Magallana gigas) form distinct epibenthic communities and local hotspots of high biomass and biodiversity. To detect and evaluate natural and anthropogenic processes, a ground-based monitoring program started over 25 years ago in the German Wadden Sea. In this study, we describe the potential of drones and machine learning approaches for a remote sensing-based integration into an existing monitoring program of intertidal mussel beds. A fixed wing drone was used to cover an area of up to 39ha in a single flight, with an overall time saving potential of 50%. Applying machine learning approaches, a detailed extraction of the intertidal blue mussel bed coverage with an overall accuracy (OA) up to 95.6% was reached, applying a Support Vector Machine (SVM). The application of a multispectral sensor improved the classification performance. Compared to ground-based monitoring, the drone-based method provided significantly more information on the area extension, coverage, and associated algae of the mussel beds. The results show that drones can provide a non-invasive way to survey large and difficult to access areas providing detailed maps of mussel beds and their internal structures.

Best environmental practice (BEP) is a key component of an ecosystem approach to management and is typically a product of practical experience in established industries. For an emerging activity such as deep seabed mining, no such experience will exist at the time of deciding on the permissibility of the first industrial mines. Therefore, experience from deep ocean scientific experiments and research are important to develop a preliminary understanding of BEP for deep seabed mining. This paper offers a detailed review of the scientific literature from which it identifies elements of preliminary BEP for nodule mining. The paper describes the currently envisaged mining process for manganese nodules and its expected effects on the environment and extracts specific recommendations on how to minimise environmental impacts from mining in different layers of the ocean (benthic, benthopelagic, pelagic, and surface waters) as well as from noise and light impacts. In doing so, the paper aims to inform the Mining Code being developed by the International Seabed Authority (ISA). The ISA is the intergovernmental institution mandated to organise and control seabed mining on the international seabed. The ISA is obligated to ensure effective protection of the marine environment from harm likely to arise from mining, with BEP being a core tool to achieve that. This paper provides suggestions for a future ISA Standard on BEP.

Before piling of offshore wind farm foundations, acoustic harassment devices (AHDs) are used to drive harbor porpoises out of the area where they could suffer injuries. Until 2017, a combination of pingers and seal scarer devices (usually SPL = 174-193 dB re 1 μPa (rms) @ 1m at 1 to 20 kHz depending on the device) was prescribed for mitigation purposes in Germany. However, seal scarers led to decreased porpoise detection rates in much larger distances than intended, when 750 m is usually rendered sufficient to avoid injuries. Therefore, devices specifically designed for mitigation purposes were developed and are prescribed since then. These acoustic porpoise deterrents (APDs; e.g. FaunaGuard Porpoise Module; SPL = 172 dB re 1 μPa (rms) @ 1m at 60 to 150 kHz) aim to keep the animals away from offshore construction sites but should not lead to large-scale disturbance as caused by a seal scarer. Although project-specific evaluations indicated that APDs are effective, a cross-project analysis and a comparison with data from previous piling procedures employing seal scarers were still pending. The present study aimed to fill this gap. Between March 2018 and April 2019, harbor porpoise detection rates were monitored acoustically in four offshore wind farm projects using CPODs before, during and after piling at different distances up to 10 km from piling. APD operation led to a significant decrease in detection rates in the vicinity of the device, indicating the displacement of the animals from a small-scale area. Depending on the wind farm, detection rates during APD operation decreased by 30 to 100% at 750 m distance compared to 6 hours before APD operation. Furthermore, reduced detection rates during APD operation were only observed up to about 2.5 km distance even when the APD was switched on for over 40 minutes. Given that the extent of disturbance to harbor porpoises is lower when using an acoustic porpoise deterrent compared to the seal scarer, we consider that preferential use of an acoustic porpoise deterrent is an improvement to mitigation strategies and an important step forward to a less harmful piling procedure.

Regime shifts are likely to have strong impacts on all trophic levels and their interactions. In addition, weather conditions and sea level rise together with tidal currents may change sediment morphology in coastal areas and estuaries. Here, we studied the effects of these drivers of ecosystems on abundance of seven wader species feeding on macrozoobenthos in the German sector of the Wadden Sea. We hypothesized that regime shift caused decreases in wader abundance and that changes in sediment morphology driven by sea level rise and tidal amplitude affected these changes. We analyzed numbers of waders on a short term, 1998–2016, that matched a large-scale geographical study of sediment morphology in the German sector, and at a long term, 1987–2019. Changes in numbers of waders were estimated as slope of coefficients of the trends of wader species numbers in the two periods. The average (se) year of decreases in numbers of waders was initiated for most species and tidal basins in the year 1992 (± 0.4) that followed a regime shift in the Southern North Sea and in the Wadden Sea in 1988–1989. There were no statistical differences between the years when numbers of waders started to decrease between the northern and the southwestern tidal basins of the German sector, indicating that the drives affected both coastal sections simultaneously. Significant relationships were found between slopes of coefficients of wader species and sediment morphology and physical features as sea level rise and tidal amplitude. Relationships were most pronounced for the long term, 1987–2019 compared to the short term, 1998–2016. We conclude that regime shift and changes in sediment morphology driven by sea level rise and sediment change can affect abundance of migratory wader species in large estuaries and shallow coastal waters.

ZusammenfassungIm Folgenden werden die Hinweise im Umgang mit Schimmel zusammengefasst:

<strong>Abstract</strong> Large parts of the continents are continuously scanned by terrestrial weather radars to monitor precipitation and wind conditions. These systems also monitor the mass movements of bird, bat, and insect migration, but it is still unknown how many of these systems perform with regard to detection and quantification of migration intensities of the different groups. In this study that was undertaken within five regions across Europe and the Middle East we examined to what extent bird migration intensities derived from different weather radars are comparable between each other and relate to intensities measured by local small‐scaled radars, some of them specifically developed to monitor birds. Good correspondence was found for the relative day‐to‐day pattern in migration intensities among most radar systems that were compared. Absolute intensities varied between different systems and regions. The findings of this study can be used to infer about absolute bird migration intensities measured by different radar systems and consequently help resolving methodological issues regarding the estimation of migrant numbers in the Western‐Palearctic region. It further depicts a scientific basis for the future monitoring of migratory bird populations across a large spatio‐temporal scale, predicting their movements and studying its consequences on ecological systems and human lives.