An approach to assess data-less small-scale fisheries: examples from Congo rivers

Abstract

Small-scale fisheries (SSF) account for much of the global fish catch, but data to assess them often do not exist, impeding assessments of their historical dynamics and status. Here, we propose an approach to assess 'data-less' SSF using local knowledge to produce data, life history theory to describe their historical multispecies dynamics, and length-based reference points to evaluate stock status. We demonstrate use of this approach in three data-less SSFs of the Congo Basin. Fishers' recalls of past fishing events indicated fish catch declined by 65–80% over the last half-century. Declines in and depletion of many historically important species reduced the diversity of exploited species, making the species composition of the catch more homogenous in recent years. Length-at-catch of 11 of the 12 most important species were below their respective lengths-at-maturity and optimal lengths (obtained from Fishbase) in recent years, indicating overfishing. The most overfished species were large-bodied and found in the Congo mainstem. These results show the approach can suitably assess data-less SSF. Fishers' knowledge produced data at a fraction of the cost and effort of collecting fisheries landings data. Historical and current data on fish catch, length-at-catch, and species diversity can inform management and restoration efforts to curb shifting baselines of these fisheries. Classification of stock status allows prioritizing management efforts. The approach is easy to apply and generates intuitive results, having potential to complement the toolkits of researchers and managers working in SSF and engage stakeholders in decision-making processes.

Local knowledge reconstructs historical resource use

“…In the Congo Basin study, regression models that were fitted to unfiltered recalls of typical harvests revealed declines in catch on the order of 65-80% during the past halfcentury. Findings from Castello et al (2023) in the Congo Basin demonstrate that, despite variability, samples of recalls can effectively produce historical resource-level information, and the results of the present study indicate that such information is almost as reliable as data collected from conventional fisheries monitoring.…”

“…This was the case regardless of whether recalls were filtered to minimize age and time effects, most likely because such effects were generally small. The validity of these results is demonstrated by application of recalls of typical harvests to reconstruct catches in three "data-less" fisheries in the Congo Basin (Castello et al 2023), based on surveys of ~100 fishers per fishery. In the Congo Basin study, regression models that were fitted to unfiltered recalls of typical harvests revealed declines in catch on the order of 65-80% during the past halfcentury.…”

Filling global gaps in monitoring data with local knowledge

“…One small vein of this fastgrowing literature is of interest here, because it focuses on measuring spatial or temporal changes in the abundance or biomass of taxa or resources of conservation concern. Recent studies have surveyed local people asking them to estimate (qualitatively or quantitatively) the (relative or absolute) abundance or biomass of taxa or resources in different places or points in time (Van Holt, Townsend & Cronkleton, 2010;Gandiwa, 2012;Danielsen et al, 2014a;Danielsen et al, 2014b;Tomaselli et al, 2018;Naah & Braun, 2019;Henri et al, 2020;Afriyie & Asare, 2020;Benner, Nielsen & Lertzman, 2021;Djagoun et al, 2022;Castello et al, 2023). Some studies have analysed the raw data for trends (Tesfamichael, Pitcher & Pauly, 2014), while others have used advanced methods (Ainsworth, Pitcher & Rotinsulu, 2008;Early-Capistrán et al, 2020) to infer changes to the taxa or resources.…”

“…Relative to scientific approaches, Anad on et al ( 2009) estimated that sightings of tortoises were 100 times cheaper, and Castello (2004) estimated that counts of an endangered air-breathing fish, Arapaima gigas, were 200 times cheaper and faster. Castello et al (2023) reconstructed time series of fish catch for up to 60 years in the past in three fisheries of the Congo Basin using 329 fisher interviews done by five people during 1 month of fieldwork; the research cost a tiny fraction of that for collecting conventional data on fisheries landings.…”

Fishers' ecological knowledge points to fishing‐induced changes in the Peruvian Amazon

“…Conducting stock assessments that rely on dataintensive methods is often impracticable in floodplaindominated tropical regions such as Amazonia (Castello et al, 2023;Shephard et al, 2020). There, fish size and abundance are heavily influenced by interannual variability in flooding as the flood pulse controls the availability of spawning, nursing, and feeding habitat, and species respond differently to hydrological stimuli and environmental pressure (Castello, Isaac, & Thapa, 2015;Welcomme, 1999).…”