Identifying hotspots for spatial management of the Indonesian deep-slope demersal fishery

The Indonesian deep-slope demersal fishery targets mostly snappers and groupers and is vital for the wellbeing of millions of people. More than 100 species are captured at depths of 50–500 m along shelves and seamounts using mostly droplines and bottom longlines. The main target species are Pristipomoides multidens, Pristipomoides filamentosus, Pristipomoides typus, Atrobucca brevis, Epinephelus areolatus, and Lutjanus malabaricus. The fleet in this fishery is predominantly unlicensed small-scale (1–10 gross ton) vessels. The fishery is unmanaged and lacks data that would allow policymakers to formulate sustainable management strategies. Here, we use fisheries-dependent data on catch composition, as well as fishing location and gear type, to determine factors that dictate catch composition and catches containing high proportions of immature fishes. Results indicate that immature fish assemblages are caught in particular locations, or “hotspots,” through a combination of fishing gear and habitat characteristics. The important “hotspots” occurred in the Java Sea-Makassar Strait area. Only 2.4% of marine protected areas (MPAs) were located within “hotspots.” Our findings highlight places of high conservation priority, such as the Java Sea, where expansion of current MPAs would greatly benefit the deep-slope demersal fishery in Indonesia by reducing immature catches, thus identifying a preexisting management that is appropriate for the sustainability of this fishery. The modeling methods we developed are transferable to other fisheries that lack data on fish abundance in order to prioritize management and conservation

A crew-operated data recording system for length-based stock assessment of Indonesia’s deep demersal fisheries

Deep demersal fisheries in Indonesia yielded close to 90,000 metric tons of snapper and grouper in 2019, landed by a fleet of approximately 10,000 fishing boats. Prior to the present study, information on these multi-species, dispersed, small- to medium-scale fisheries was scarce, while reliable species-specific data on catch and effort were non-existent. This data-deficiency made stock assessments and design of harvest control rules impossible. We developed a new data collection method, the Crew Operated Data Recording System (CODRS), to collect verifiable species- and length-composition data from catches across all segments of the fleet. CODRS engaged crews of 579 fishing vessels to take pictures of each fish in their catch, in combination with the deployment of a tracking device on their boats. Furthermore, we also conducted a frame survey to map the fleet across the entire Indonesian archipelago. Using more than 2 million CODRS images, we aimed to understand the basic characteristics and challenges within the fishery. We updated life-history parameters for the top 50 species in the fishery based on the maximum observed length-frequency distribution of the catch (i.e., asymptotic length, size at maturity, optimum fishing length, total mortality, and spawning potential ratio). Length-based stock assessments using the updated life-history parameters showed high risks of overfishing for most of the major target species, especially for snapper species with large maximum sizes. Our results indicated that effective management and harvest strategies are urgently needed across Indonesia’s eleven Fishery Management Areas to prevent the collapse of these important fisheries

Exploring the status of the Indonesian deep demersal fishery using length-based stock assessments

The deep demersal snapper-grouper fishery in Indonesia is a data-poor fisheries resource that provides food security and a source of income to millions globally. Owing to an ongoing crew-operated data recording system implemented in Indonesia since 2015, the stocks of this fishery can now be assessed using length-frequency data and updated life-history parameters. Here, we use two length-based methods, one that is fishery-specific and another that is more generalized, to assess the status of Indonesian stocks. Specifically, we develop a literature-based assessment method based on a patchwork of conventional approaches but tailored to the studied stocks, and compare it with a newly established and broadly applicable length-based Bayesian biomass estimation method (LBB). The methods were applied to 16 stocks from 4 Indonesian Fisheries Management Areas and were compared based on simulations, as well as the convergence of the resulting stock status classification and uncertainty of the results. Analyzing the effect of using the literature-based species/family-specific life-history parameter values for asymptotic length (Linf) and relative natural mortality (M/K) in LBB showed that different values do affect the estimated biomass indicator. Nevertheless, in more than half the cases, the stock status classification did not differ between the two methods, while LBB results became more reliable with narrower confidence limits. Simulations, as well as similar status indicators between the two models support the value of the literature-based approach as an assessment methodology for the Indonesian deep demersal fisheries. Narrower confidence ranges highlight the importance of using fishery-specific information when applying generalized stock assessment methods. While most catches had few immature fish, half of the assessed stocks were consistently shown to have low biomass, indicating that important Indonesian stocks are at high risk of overfishing