Fishers, and the communities they support face a range of challenges brought on by complexity and uncertainty in their social-ecological systems (SESs). This undermines their ability to achieve sustainability whilst hampering proactive planning and decision-making. To capacitate fishers to apply risk aversion strategies at smaller scales of operation and for managers to apply inclusive management approaches such as the ecosystem approach to fisheries management (EAF), a better understanding of the relationships and interactions in marine SESs must be developed. At the same time, the EAF requires the inclusion of multiple stakeholders, disciplines and objectives into decision-making processes. Previous work in the southern Cape with fishers, identified drivers of change. Building on this previous research, and using causal mapping, fishers mapped out drivers of change in an iterative process in a problem framing exercise which also highlighted hidden drivers of change and feedback loops. To explore the relative importance of key drivers of change with participants, weighted hierarchies as well as a Bayesian Belief Network (BBN) were developed. By identifying and highlighting these hidden system interactions a more integrated systems view has been facilitated, adding to the understanding of this fishery system. Drivers identified in the weighted hierarchy were consistent with those identified in the causal maps and previous research, of interest is the relative weighting attributed to these drivers. Whereas the weighted hierarchies emphasised the political dimensions, group work already indicated the range of perceptions, reflecting the considerable uncertainties in this SES. While methodologically challenging at first, the individual approach behind the BBN construction yielded a better reflection of the diversity of views and a better balance of political, economic and climate dimensions of drivers of change. We show how, by using SDMTs, the most disenfranchised community members can engage meaningfully in a structured process. As structure is crucial to management processes, the research shows that where the appropriate groundwork, capacity building and resourcing takes place, disenfranchised stakeholders can be integrated into formal management processes; fulfilling a key requirement of an EAF.
Fisheries and Fisheries Management
Mediterranean red coral Corallium rubrum is considered the most precious coral worldwide. Harvesting activities are performed by licensed scuba divers and managed through the recent pan-Mediterranean management plan issued by General Fisheries Commission for the Mediterranean (GFCM) along with measures locally enacted, imposing limits on licenses, harvesting season, minimum depth of dive, and size. The use of Remotely Operated Vehicles (ROVs) is prohibited, with the only exception being for scientific purposes. Despite measures already in force, the implementation of additional management tools has been recently recommended. This article reports results from the first monitoring campaign on C. rubrum harvesting based on ROVs for seabed exploration and Onboard Scientific Observers (OSOs), carried out from 2012 to 2015 along the coast of Sardinia (Mediterranean Sea—Western basin). More than 450 dives were monitored, confirming how ROV’s support eases the scouting of exploitable banks, leading to increases in catches. OSOs reported the collection of colonies below the minimum reference size and catches/dive above limits. Onboard observers collected data also on colony diameter, which is crucial for the estimation of population size structure and exploitation status. OSOs proved to be valid tools in providing additional and reliable information on red coral harvesting, thus deserving to be included among mandatory measures for the sustainable exploitation of red coral in the Mediterranean Sea.
Distributing fishing mortality across the widest possible range of species, stocks, and sizes in proportion to their natural productivity (i.e., balanced harvest, BH) has been suggested as a new paradigm of fisheries management to minimize the effects of fishing on the ecosystem structure while maximizing overall yield. Models that have been used to test the effects of BH, however, usually concentrate on fish and assume full alignment of fishing mortality with the productivity of each species. Here, we used the trophic-level-based approach EcoTroph to investigate the effects of BH on the biomass and catch trophic spectra of a virtual ecosystem assuming (1) a full implementation, where all trophic levels can be fished according to their productivity and (2) a more realistic implementation, where low and intermediate trophic levels are only partially exploitable by fisheries mimicking current technological and practical limitations. EcoTroph simulations show that a BH fishing pattern does not fully maintain ecosystem structure but results in small structural changes and a large total yield. The resulting catch, however, was dominated by low trophic levels (i.e., 2–2.5). Considering that fishing mortality cannot be fully aligned to all species, we observed an additional adverse impact of BH: the increase in unexploitable biomass. In contrast, protecting lower trophic levels appeared as an efficient way to limit the impact of fisheries on the highest trophic levels, which play a crucial role in ecosystem stability and biodiversity. We conclude that given our inability to align fishing mortality to the productivity of each species, BH could lead to strong adverse impacts on the ecosystem. Instead of expanding fishing pressure toward new species and trophic levels, we first should ensure the sustainable management of those that are currently harvested beyond their capacity to replenish.
The CMSY and Bayesian Schaefer model (BSM) methods were applied to assess data-limited fishery stocks in the Japan Sea and surrounding areas of the Northwest Pacific. Ten stocks including 4 fish species and 5 cephalopod species were assessed; the CMSY method was used in 3 stocks with catch data only, and the BSM method in 7 stocks with both catch time series and catch per unit effort (CPUE) data available. The two methods estimated the maximum intrinsic rate of population increase (r) and carrying capacity of each stock, which allowed the computation of maximum sustainable yield (MSY), and exploited biomass relative to the biomass at maximum sustainable yield (B/BMSY). All 10 stocks were overfished, if to a different extent, and one, the spear squid (Heterololigo bleekeri) has collapsed. The reference points estimated here may be used as indicator for fishery management in this ecoregion.
This contribution presents time series of the ‘fishery biomass’ of fish populations, defined as the weight (whole-body, wet weight) of the in-water part of a fishable population, i.e., that part of a population (also called ‘stock’) that is exposed to a certain fishing gear. Detailed data of this type are only available for a limited number of species that are targets of the fisheries in the waters of economically developed regions, such as Europe, the USA, Canada or Australia. However, similar fishery biomass assessments are generally lacking for developing countries, even for many of their most heavily fished species. Here, an estimation of the long-term fishery biomass trends of 1320 fish and invertebrate populations for 483 species exploited by fisheries in the 232 coastal Marine Ecoregions (MEs) around the world was undertaken. Fishery biomass trends were derived using the Bayesian CMSY stock assessment method applied to the global fisheries catch database for 1950–2014 as reconstructed by the Sea Around Us for every maritime fishing country in the world. Overall, the results suggest a consistent decline in the fishery biomass of exploited populations, in virtually all climatic zones and ocean basins in the world. The only zone with currently higher fishery biomass than in 1950 is the northern Pacific polar-boreal zone, likely due to environmental changes that occurred in the region positively affecting fish populations, combined with prudent management of the fisheries. For populations in MEs that are known to have highly questionable catch statistics, the results suggested smaller declines in fishery biomass than likely occurred in reality, implying that these results do not exaggerate declining trends in fishery biomass. This study used informative Bayesian priors to improve the trend analyses in areas where systematic stock assessments were conducted. The use of these independent assessments reduced the uncertainty associated with the findings of this study.
Dungeness crab (Cancer magister) is one of the most lucrative fisheries on the United States (U.S.) west coast. There have been large spatial and temporal fluctuations in catch, which reflect the interconnected influences of the coupled natural-human fishery system. Changing ocean conditions are likely to further alter the magnitude and distribution of Dungeness crab catch, the impacts of which will propagate ecologically and through the social systems of fishing communities. Therefore, the effect of changing ocean conditions on U.S. west coast Dungeness crab catch per unit effort (CPUE) was used as an interdisciplinary case study to examine the susceptibility, a metric that integrates Dungeness crab reliance and social vulnerability indices, of coastal communities to changes in the fishery. Statistical models indicated that ocean conditions influence commercial CPUE 3–5 years later and that CPUE is likely to decline in the future as ocean conditions change. In particular, sea surface temperature scenarios for 2080 (+1.7 and +2.8°C) reduced Dungeness crab CPUE by 30–100%, depending on fishing port latitude. Declines in Dungeness crab CPUE were greater for southern port communities than for northern port communities under both scenarios – demonstrating greater exposure at the southern end of the species range. We show that U.S. west coast communities are differentially susceptible to a decline in Dungeness crab catch, with Washington communities being at least five times more susceptible than California communities. Our overall assessment showed varying levels of risk (a combination of exposure and susceptibility) for Dungeness crab fishing ports that do not necessarily align with regional or fishery management boundaries.
With the increased uncertainty introduced through climate change and fishing pressure, having accurate estimates of fish biomass is essential for global ecosystem and economic health. Acoustic surveys are an efficient way to determine population size for pelagic species in the Northeast Atlantic (NEA), but acoustic population estimates still contain uncertainty and are difficult for some species. For example, Atlantic mackerel (Scomber scombrus) is one of the most valuable fisheries in the NEA and is not monitored acoustically, as mackerel lack the swim bladder that provides the strongest acoustic echo (target strength) at common assessment frequencies. For all pelagic species, and especially for mackerel, behavior is a source of variation in acoustic measurements and therefore in population estimates. Behavior is mediated by both extrinsic and intrinsic factors, such as the environment and the life history of the fish. In turn, behavior affects the density of the shoal and the tilt angle of the fish relative to the survey vessel, affecting their target strength, which affects the biomass estimate. Some fish may also undergo an anti-predator response to survey vessels, changing their behavior in response to the survey. Understanding these behaviors and incorporating them into acoustic stock assessment methods can improve the accuracy of population estimates. Individual-based models (IBM) of fish shoals provide a pathway for incorporating behavior into acoustic methods. IBMs have been used extensively to build theoretical models of fish shoals, but few have been successfully tested in lab or field conditions. As computational power and monitoring technology improve, modeling the collective behavior of pelagic fishes will be possible. Novel, interdisciplinary approaches to data collection and analysis will help translate theoretical IBMs to the fisheries science domain. Beyond acoustic stock assessments, this approach can be used to investigate knowledge gaps in the effects of fisheries-induced evolution and the potential for range shifts under climate change. Further work to synthesize existing models and incorporate field data will help determine how environmental, ecological, physiological, and anthropogenic factors, often affecting both behavior and acoustic surveying, are interconnected. Moving from theoretical models to practical applications will be a valuable tool in tackling the uncertainty that accompanies further fisheries exploitation and warming oceans.
Aquatic ecologists routinely count animals to provide critical information for conservation and management. Increased accessibility to underwater recording equipment such as action cameras and unmanned underwater devices has allowed footage to be captured efficiently and safely, without the logistical difficulties manual data collection often presents. It has, however, led to immense volumes of data being collected that require manual processing and thus significant time, labor, and money. The use of deep learning to automate image processing has substantial benefits but has rarely been adopted within the field of aquatic ecology. To test its efficacy and utility, we compared the accuracy and speed of deep learning techniques against human counterparts for quantifying fish abundance in underwater images and video footage. We collected footage of fish assemblages in seagrass meadows in Queensland, Australia. We produced three models using an object detection framework to detect the target species, an ecologically important fish, luderick (Girella tricuspidata). Our models were trained on three randomized 80:20 ratios of training:validation datasets from a total of 6,080 annotations. The computer accurately determined abundance from videos with high performance using unseen footage from the same estuary as the training data (F1 = 92.4%, mAP50 = 92.5%) and from novel footage collected from a different estuary (F1 = 92.3%, mAP50 = 93.4%). The computer’s performance in determining abundance was 7.1% better than human marine experts and 13.4% better than citizen scientists in single image test datasets, and 1.5 and 7.8% higher in video datasets, respectively. We show that deep learning can be a more accurate tool than humans at determining abundance and that results are consistent and transferable across survey locations. Deep learning methods provide a faster, cheaper, and more accurate alternative to manual data analysis methods currently used to monitor and assess animal abundance and have much to offer the field of aquatic ecology.
Due to limited data availability, only a small subset of the exploited fish and invertebrate populations have been assessed along Chinese coasts, which precludes comprehensive management of the fisheries. Here, we applied a length-based Bayesian biomass estimator (LBB) to 14 fish and invertebrate stocks in China’s coastal waters to estimate their growth, length at first capture and current relative biomass (B/B0, B/BMSY) from length-frequency (LF) data. Of the 14 populations assessed, one have collapsed, nine are grossly over-exploited, and three are overfished. Moreover, 13 populations have smaller mean lengths at first capture (Lc) than the optimal length at first capture (Lc_opt), indicating that they are suffering from growth overfishing. Thus, larger mesh sizes in commercial fishery would increase both the catch and biomass for these species, given current levels of fishing mortality. Our results confirm that fishery resources in China’s coastal waters are strongly depleted, and that stricter management measures are needed to restore the abundance of China’s marine fisheries resources.
Fishing strategies, effort and harvests of small-scale fishers are important to understand for effective planning of regulatory measures and development programs. Gender differences in fishing can highlight inequities deserving transformative solutions, but might mask other important factors. We examined fishing modes, fishing frequency, catch-per-unit-effort (CPUE), resource preferences and perceptions of fishery stock among artisanal gastropod (trochus) fishers in Samoa using structured questionnaires and mixed effects models. The fishery has an extremely modest carbon footprint of 18–23 tons of CO2 p.a., as few fishers used motorized boats. Trochus (Rochia nilotica), an introduced gastropod, was the second-most harvested resource, after fish, despite populations only being established in the past decade. Daily catch volume varied according to gender and villages (n = 34), and was also affected by fishing effort, experience, assets (boat), and fishing costs of fishers. Boat users had much higher CPUE than fishers without a boat. Fishers who practised both gleaning and diving caught a greater diversity of marine resources; effects that explained otherwise seeming gender disparities. Trochus tended to be ranked more important (by catch volume) by women than men, and rank importance varied greatly among villages. Local ecological knowledge of fishers informed the historical colonization of trochus around Samoa and current trends in population abundance. Fishing efficiency, catch diversity and perspectives about stocks were similar between fishermen and fisherwomen, when accounting for other explanatory variables. Greater importance of these shellfish to women, and gender similarities in many of the fishing responses, underscore the need to ensure equal representation of women in the decision making in small-scale fisheries.