Microplastics on the menu: Plastics pollute Indonesian Manta Ray and Whale Shark feeding grounds

The implications of plastic pollution, including microplastics, on marine ecosystems and species are increasingly seen as an environmental disaster. Yet few reports focus on filter-feeding megafauna in regions heavily impacted by plastic pollution, such as Indonesia in the Coral Triangle, a global marine biodiversity hotspot. Here, we evaluate plastic abundance and characterize debris from feeding grounds for manta rays Mobula alfredi and whale sharks Rhincodon typus in three coastal locations in Indonesia: Nusa Penida Marine Protected Area, Komodo National Park, and Pantai Bentar, East Java. A 200 μm plankton net was used to sample the top 0.5 m of the water column (‘trawl survey’) and floating plastics were assessed along ∼440 m long transects (‘visual survey’) during the Indonesian north-west (wet) and south-east (dry) monsoon seasons during 2016–2018. Microplastics were identified visually, measured and categorized from trawl samples, and larger floating plastics were counted and categorized visually from boats. Plastic abundance ranged widely from 0.04 to 0.90 pieces m–3 (trawl survey) and 210 to 40,844 pieces km–2 (visual survey). Results from linear models showed significant seasonal and location differences in estimated plastic abundance for trawl and visual surveys in Nusa Penida and Komodo. Plastic abundance was up to ∼ 44 times higher in the wet than the dry season, with the largest seasonal effect observed in Nusa Penida. Overall, small pieces  50% combined) were the most prevalent plastics. Theoretical plastic ingestion rates were calculated using estimated filtration volumes of manta rays and whale sharks and the mean plastic abundance in their feeding grounds. Upper plastic ingestion estimates for manta rays were ∼63 and 25 pieces h–1 for Nusa Penida and Komodo locations, respectively, and ∼137 pieces h–1 for whale sharks in Java. Analysis of manta ray egested material confirmed plastic ingestion, the consequences of which might include exposure to toxic plastic additives and adhered persistent organic pollutants. Communicating this information to communities who stand to benefit from healthy megafauna populations might help local governments as they work toward reducing plastics in the marine environment

Improving sightings-derived residency estimation for whale shark aggregations: A novel metric applied to a global data set

The world’s largest extant fish, the whale shark Rhincodon typus, is one of the most-studied species of sharks globally. The discovery of predictable aggregation sites where these animals gather seasonally or are sighted year-round – most of which are coastal and juvenile-dominated – has allowed for a rapid expansion of research on this species. The most common method for studying whale sharks at these sites is photographic identification (photo-ID). This technique allows for long-term individual-based data to be collected which can, in turn, be used to evaluate population structure, build population models, identify long-distance movements, and assess philopatry and other population dynamics. Lagged identification rate (LIR) models have fewer underlying assumptions than more traditional capture mark recapture approaches, making them more broadly applicable to marine taxa, especially far-ranging megafauna species like whale sharks. However, the increased flexibility comes at a cost. Parameter estimations based on LIR can be difficult to interpret and may not be comparable between areas with different sampling regimes. Using a unique data-set from the Philippines with ~8 years of nearly continuous survey effort, we were able to derive a metric for converting LIR residency estimates into more intuitive days-per-year units. We applied this metric to 25 different sites allowing for the first quantitatively-meaningful comparison of sightings-derived residence among the world’s whale shark aggregations. We validated these results against the only three published acoustic residence metrics (falling within the ranges established by these earlier works in all cases). The results were then used to understand residency behaviours exhibited by the sharks at each site. The adjusted residency metric is an improvement to LIR-based population modelling, already one of the most widely used tools for describing whale shark aggregations. The standardised methods presented here can serve as a valuable tool for assessing residency patterns of whale sharks, which is crucial for tailored conservation action, and can cautiously be tested in other taxa