Between 1984 and 2004, the non-native Manila clam (Ruditapes philippinarum) was introduced with government support into 18 British estuaries. Following a 1988 introduction to aquaculture on the south coast in Poole Harbour, the species quickly naturalized, becoming a British wild capture fishery. We analyze the emergence of this new non-native fishery in Poole Harbour through six successive phases, from pre-introduction and fishery closure, through establishment, boom, and widespread illegal exploitation, to a reformed management regime characterized by species-specific regulation, enhanced enforcement, and independent sustainability accreditation. We address the wider significance of the species across southern England and explain changing patterns of ports of landing. Quantitative assessments of total aggregate tonnage and value at first sale reveal the high relative significance that this species has established by comparisons with other bivalve wild capture fisheries. With the exception of cockles, the Manila clam now greatly outperforms all other bivalves as a wild fishery in the sheltered estuaries and bays of England. The species' expanding distribution is considered in the context of the opportunities this creates, particularly in light of a general decline in the English inshore fishing fleet. We consider how the Manila clam can transform the economic prospects of individual small-scale fisheries where abundant stocks become established, and note that studies to date have found no evidence of significant displacement of native species or direct harm to the diversity or function of indigenous ecosystems in British waters. The emergence of the Manila clam in England is a case study of how management must adapt to novel fishing opportunities in a changing climate. As such, the Manila clam lies at the forefront of the call for “full-spectrum sustainability”, which includes ecological, economic, social, cultural, institutional and governance criteria.
In the Bay of Biscay, sardine has long been central to the resilience of the pelagic fishing industry. However, its sustainability is of increasing concern due to a steady decrease in body size. This led scientists and sector representatives to engage in participatory scenario planning. The narratives produced describe possible futures over the next decade for the small pelagic socio-ecological system (SES) in the Bay of Biscay. Assessing these narratives intuitively with regard to their capability to maintain healthy stocks as well as profitable exploitation and processing is challenging as they involve a complex network of interacting conditions, including future environmental conditions, changes in practices, and management actions. Yet no single model can capture such a wide range of processes across the different dimensions of the SES. We therefore combined narratives and simulations to integrate the complexity of the SES with the tractability required to assess management measures. A six-step method was tested to translate narrative assertions into quantitative model parameters and assess their values using questionnaires, based on extrapolation of past time series and one-way coupling with complementary models. Causal chain diagrams and sensitivity analysis of implementation choices improved the transparency and reproducibility of this conversion process. To assess scenario performance, the results of thirty-three simulations were evaluated against expert-defined objectives. Consistency with the expected outcomes described in the narratives was assessed, revealing some limitations to the model, narratives and conversion process. Quantitative results were translated back into words and reintegrated into the scenario texts to provide ‘model-pumped narratives’. This work provides tools to overcome the methodological difficulties of the conversion process and improve the robustness and transparency of ‘Story and Simulation’ approaches. The hybrid approach demonstrated the complementarity of the qualitative and quantitative projections and their value for informing management decisions in uncertain multi-sectoral contexts.
Mountain freshwater ecosystems are valuable social–ecological systems that support specialised and, in many cases, endemic fish populations, in turn supporting capture fisheries and new aquaculture systems. Aquaculture is a food security strategy and a rural livelihood diversification solution increasingly promoted in the North-Western Indian Himalaya, though its expansion poses serious trade-offs with freshwater biodiversity conservation. This review synthesises existing knowledge of aquaculture–biodiversity interactions, using the North-Western Indian Himalaya as a focal case study to examine ecosystem-based management of aquatic living resources and develop context-specific insights for mountain freshwater systems. Regional data and the literature show that native cold-water fishes—namely, mahseer ( Tor spp.) and snow trout ( Schizothorax spp.)—occupy narrow ecological niches and have limited adaptive capacity. These species are vulnerable to habitat fragmentation, hydrological alteration, and warming temperatures. Conversely, exotic species, especially rainbow trout ( Oncorhynchus mykiss ) and common carp (Cyprinus carpio ), dominate aquaculture development in the region, exacerbating trade-offs between aquaculture and biodiversity across species, habitats, genetic, and temporal scales. The synthesis indicates that climate change and geomorphological instability may amplify these trade-offs by increasing environmental uncertainty for both wild stocks and culture systems. Aquaculture may provide an alternative source of fish production where capture fisheries decline, but poorly managed intensification could increase pressure on freshwater biodiversity and ecosystem functions. We propose management pathways to align production and conservation, centred on ecosystem-based basin planning, prioritising indigenous species, developing climate-resilient, low-input systems, and implementing inclusive governance frameworks. This synthesis shows that in mountain freshwater ecosystems, sustaining aquatic living resources amid accelerating environmental change requires deliberately managing trade-offs rather than maximising short-term production.
In the context of climate change, sustainable fisheries management needs to be adaptive. This is particularly challenging for small pelagic fisheries, caught between fish stocks influenced by strong environmental fluctuations and globalized markets with many ramifications. Understanding how the impacts of different drivers propagate throughout the social-ecological system and anticipating future disruptions is key to adaptive management. To support such management, we have developed a dashboard of indicators informing about the different components of the system over time. With the support of a panel of experts comprising scientists and stakeholders, we collected over 300 time series on the pelagic habitat and small pelagic fish (SPF) in the Bay of Biscay, their fisheries, as well as their fish markets and the canning industry. Selection of the most informative time series was performed in successive steps, relying on a multivariate statistical method and expert knowledge to select the most appropriate variables among redundant ones and to retain preferred indicators. By fitting different regression models, trends, changepoints, and recent changes in the dynamics of the 105 final indicators were identified over 2000–2021. By considering together indicators ranging from the abiotic environment to the national imports/exports of fish, the dashboard ( https://defipel-tdb.ifremer.fr/ ) allowed us to track the cascading effects of the mid-2000s anchovy crisis across the social-ecological system. A detected decrease in zooplankton size may be used as an alert in support of adaptive management, especially as concomitant changes with decreasing size and fat content of SPF were evidenced. While several methodologies, including multivariate analysis, have been proposed to select indicators to be included in a dashboard, consulting with stakeholders is key to including their in-depth knowledge and ensuring appropriation of the tool.
Monitoring species abundance requires sampling strategies that are both statistically robust and operationally feasible. This study presents a practical method and an accompanying R workflow that help practitioners identify the most efficient probabilistic sampling design and determine the minimum sample size needed for abundance estimation in finite populations. The method relies on reconstructing abundance on the statistical population through spatial modelling, then simulating alternative sampling designs—spatially balanced or not—to quantify the precision of abundance estimates across increasing sample sizes. Precision is expressed using the margin of error, an intuitive metric directly linked to confidence intervals and decision-making needs. The main novelty of this work lies in three contributions: (i) generalizing the optimization framework to any finite population and to a wide range of probabilistic sampling designs, (ii) providing an automated and reproducible three-step workflow that identifies the smallest sample size achieving a predefined precision threshold through a simulation procedure, and (iii) demonstrating its operational relevance through a real-world implementation. The method was applied to a burrowing invertebrate, the Manila clam Ruditapes philippinarum in Arcachon Bay (France), where historical monitoring relied on stratified simple random sampling (StRS). Using kriging-based spatial interpolation to reconstruct abundance, simulations showed that achieving a 10% margin of error required approximately 290 sites under a spatially balanced design, compared with about 480 under simple random sampling. Field implementation confirmed that the optimized spatially balanced design maintained or improved precision relative to the historical protocol. Nevertheless, comparisons with the historical protocol should be interpreted cautiously because surveys were conducted in different years under potentially different ecological conditions. Overall, the framework provides a transparent, adaptable, and cost-effective tool for optimizing abundance monitoring programs.
