Distribution Of Fishing Effort Research Articles

Novel computer vision tools applied to marine recreational fisheries spatial planning

Successful marine spatial planning relies on understanding patterns of human use, with accurate, detailed, and up-to-date information about the spatial distribution of fishing effort. In commercial vessels, tracking systems like the vessel monitoring system (VMS) or the automatic identification system (AIS) have helped to maintain and enhance the biodiversity of areas by generating large sources of positional data that served for commercial marine spatial planning. However, there is no regulation regarding location systems such as VMS or AIS for marine recreational fishing boats. Obtaining spatial data on marine recreational fishing can be difficult and time-intensive given the widespread and variable nature of the fleet. Remote cameras and computer vision systems are increasingly used to overcome the cost limitations of these conventional methods. Here we show a novel high-resolution and low-cost tracking system based on photo time-lapses and state-of-the-art computer vision algorithms, including deep learning, to automatically classify and obtain precise trajectories of fishing and cruising boats in coastal areas. Our method contributes to the automatic surveillance of marine protected areas by providing an image-based tool for automatic, real-time monitoring. Our method also allows for determining the intensity and spatial-temporal distribution of recreational fishing effort, important to defining the sustainability of the activity and coastal areas. We finally discuss the opportunities and limitations of computer vision tools applied to marine recreational fisheries spatial planning.

HyFish: hydrological factor fusion for prediction of fishing effort distribution with VMS dataset

Predicting fishing effort distribution is crucial for guiding fisheries management in developing effective strategies and protecting marine ecosystems. This task requires a deep understanding of how various hydrological factors, such as water temperature, surface height, salinity, and currents influence fishing activities. However, there are significant challenges in designing the prediction model. Firstly, how hydrological factors affect fishing effort distributions remains unquantified. Secondly, the prediction model must effectively integrate the spatial and temporal dynamics of fishing behaviors, a task that shows analytical difficulties. In this study, we first quantify the correlation between hydrological factor fields and fishing effort distributions through spatiotemporal analysis. Building on the insights from this analysis, we develop a deep-learning model designed to forecast the daily distribution of fishing effort for the upcoming week. The proposed model incorporates residual networks to extract features from both the fishing effort distribution and the hydrological factor fields, thus addressing the spatial limits of fishing activity. It also employs Long Short-Term Memory (LSTM) networks to manage the temporal dynamics of fishing activity. Furthermore, an attention mechanism is included to capture the importance of various hydrological factors. We apply the approach to the VMS dataset from 1,899 trawling fishing vessels in the East China Sea from September 2015 to May 2017. The dataset from September 2015 to May 2016 is used for correlation analysis and training the prediction model, while the dataset from September 2016 to May 2017 is employed to evaluate the prediction accuracy. The prediction error ratio for each day of the upcoming week range is only 5.6% across all weeks from September 2016 to May 2017. HyFish, notable for its low prediction error ratio, will serve as a versatile tool in fisheries management for developing sustainable practices and in fisheries research for providing quantitative insights into fishing resource dynamics and assessing ecological risks related to fishing activities.

Marine protected areas can benefit biodiversity even when bycatch species only partially overlap fisheries

Abstract Marine protected areas (MPAs) are increasingly relied upon to preserve biodiversity and ensure fisheries sustainability. Although recent analyses have shown that MPAs can provide overall biodiversity benefits even when they only redistribute fishing effort, these did not account for refuges outside of fishing grounds for non‐target species. It has been argued that such refuges could render MPAs obsolete where their chief benefit is to ensure species persistence. Here, we modelled the outcomes associated with placing MPAs within a seascape where non‐target species' ranges can extend beyond fishing grounds. In scenarios with no explicit fishing‐induced habitat damage, we found that MPAs provided a net biodiversity benefit so long as there was at least an approximately 60% overlap between fishing grounds and non‐target species' ranges. In scenarios with explicit fishing‐induced habitat damage for non‐target species, we found that MPAs instead benefitted biodiversity at all overlaps, but that this was reduced if target species' abundances also declined with damage. Additionally, we identified counterintuitive mechanisms by which MPAs could either help or harm the same species depending on their location by changing fishing effort distribution patterns. However, MPAs did always increase the total fishing effort required to reach a catch target. Policy implications: Our results showed that MPAs could still deliver biodiversity benefits in otherwise well‐regulated fisheries when species' ranges and fishing grounds did not fully overlap, and particularly when sensitive species and habitats were present. Well‐placed MPAs should thus be considered in such settings. However, MPAs were also less likely to be useful when range overlaps were low and always resulted in higher fishing effort to maintain the same catches.

HiTrip: Historical trajectory interpolation for trawlers via deep learning on multi-source data

The Vessel Monitoring System (VMS) on trawlers has revolutionized our understanding of spatiotemporal fishing activities. However, the low temporal resolution of historical VMS datasets complicates a precise analysis of fishing effort distribution. One inherent challenge for precise interpolation is the stark contrast between trawler movement patterns during steaming, characterized by straight lines, and fishing, which often involves consecutive turns. In this study, we introduce HiTrip, a deep learning approach that interpolates historical VMS data from two-hour intervals down to three minutes by harnessing both VMS and marine hydrological datasets. The proposed deep learning model, integrating ResNet, LSTM, and MLP, seamlessly synthesizes spatial features from coarse fishing effort distributions, sea surface factor fields, and current fields, while accounting for the temporal relationships within trajectory segments. Evaluated on 1855 East China Sea trawler VMS records and Copernicus Climate Data Store hydrological factor data, HiTrip achieves a 0.20 km interpolation error, meeting a finery 0.005° × 0.005°spatial resolution demand for fishing effort distribution analysis. Ablation study validates the efficacy of our deep learning model integrating multi-source datasets. Moreover, when evaluated on a diverse Global Fishing Watch dataset, which includes 45 trawlers spanning various global maritime regions, HiTrip maintains a 0.40 km error, emphasizing its broad generalization ability.

Modeling the spatiotemporal patterns and drivers of Dungeness crab fishing effort to inform whale entanglement risk mitigation on the U.S. West Coast

Understanding and characterizing the spatiotemporal dynamics of fishing fleets is crucial for ecosystem-based fisheries management (EBFM). EBFM must not only account for the sustainability of target species catches, but also for the collateral impacts of fishing operations on habitats and non-target species. Increased rates of large whale entanglements in commercial Dungeness crab fishing gear have made reducing whale-fishery interactions a current and pressing challenge on the U.S. West Coast. While several habitat models exist for different large whale species along the West Coast, less is known about the crab fishery and the degree to which different factors influence the intensity and distribution of aggregate fishing effort. Here, we modeled the spatiotemporal patterns of Dungeness crab fishing effort in Oregon and Washington as a function of environmental, economic, temporal, social, and management related predictor variables using generalized linear mixed effects models. We then assessed the predictive performance of such models and discussed their usefulness in informing fishery management. Our models revealed low between-year variability and consistent spatial and temporal patterns in commercial Dungeness crab fishing effort. However, fishing effort was also responsive to multiple environmental, economic and management cues, which influenced the baseline effort distribution pattern. The best predictive model, chosen through out-of-sample cross-validation, showed moderate predictive performance and relied upon environmental, economic, and social covariates. Our results help fill the current knowledge gap around Dungeness crab fleet dynamics, and support growing calls to integrate fisheries behavioral data into fisheries management and marine spatial planning.

The environmental niche of the squid-jigging fleet in the North Pacific Ocean based on automatic identification system data

The vast number of fishing fleets and limited regulatory capacity pose challenges to the effective monitoring and management of marine fishery resources. To understand the fishing characteristics of spatial distribution for squid-jigging fleets in the North Pacific Ocean (NPO), satellite-based automatic identification system (AIS) data during 2016 ∼ 2020 and marine environmental data were applied to explore the drivers of fishing activities based on the boosted regression tree (BRT) and generalized additive model (GAM). The results showed that the BRT model has better performance than the GAM. The spatial distribution of squid-jigging fleets has a significant seasonality. Specifically, the spatial distribution of Fishing effort (FE) gradually shifted to the northwest from May to September, while gradually shifted to the southwest from October to November. The favourable area for focusing FE was the 150°E ∼ 165°E, 40°N ∼ 44°N. The latitudinal distribution of FE was not wide and the longitudinal distribution was long. Variations in the marine environment constantly influenced the FE of the squid-jigging fleets. Overall, the influence of sea surface temperature (T0) on FE was most significant. The favourable range of T0 for FE was 12 ∼ 20°C. Water temperature at the 300 m depth (T300) was also an important factor through the fishing season. The favourable range of T300 for FE was 3 ∼ 6°C. There were obvious differences in the influence of other environmental factors on FE in different months. Different environmental variables drive the spatial distribution of fishing effort in different months. This study may help to scientifically and effectively guide fishery management and sustainable development by evaluating the spatial variations in fishing activity.

Evaluating simple measures of spatial-temporal overlap as a proxy for encounter risk between a protected species and commercial fishery

Spatial and temporal assessments of overlap are becoming increasingly popular as indicators of encounter risk. The overlap in distributions between protected species and commercial fishing effort is of interest for reducing bycatch. We explored overlap between the U.S. Atlantic sea scallop fishery and loggerhead turtles (Caretta caretta) using 2 metrics, and we assessed the ability of one of those metrics to track estimated fishery interactions over time. Moderate overlap occurred between June - September; mild overlap in the spring (May) and fall (October - November); and relatively little overlap from December to April. Qualitatively, there appeared to be some correspondence between the overlap values averaged across months for each calendar year and published annual loggerhead interaction estimates with fisheries, but the predictive performance of the overlap metric was low. When data on the relative distributions of commercial fishing effort and protected species are available, simple measures of spatial and temporal overlap can provide a quick and cost-effective way to identify when and where bycatch is likely to occur. In this case study, however, overlap was limited in helping to understand the relative susceptibility of protected species to commercial fishing (i.e., magnitude of interactions). We therefore caution against using overlap as a meaningful predictor of absolute risk unless there is direct evidence to suggest a relationship.

Closed Season and the Distribution of Small-Scale Fisheries Fishing Effort in Davao Gulf, Philippines

The Davao Gulf supports various livelihoods and activities for small-scale and commercial fisheries. However, facing a declining catch, a closed season was implemented to arrest the decline. This study aimed to describe the Davao Gulf fisheries, determine the movement patterns of fishing boats during closed and open seasons, and quantify and compare their catch and their fishing distances. Boat tracking was combined with catch logbook monitoring of fishers and supplemented with interview surveys (N = 35) and mapping surveys (N = 167), including the use of secondary catch data. Results from the interviews showed that the average age of the fishers was 45 years old, with 27 years of fishing experience using motorized boats with 8 HP engines. Their average catch was 7 kg per trip dominated by big-eyed scad (Selar crumenophthalmus), frigate tuna (Auxis thazard), roundscad (Decapterus spp.), skipjack tuna (Katsuwonus pelamis), and yellowfin tuna (Thunnus albacares). There were highly significant differences between the volume of catch of small-scale fishers and commercial fishers after the closure in 2014 (278 t vs. 80 t; p < 0.001) and between the species caught (p < 0.001). Fishing activities were associated with a speed class of 0–1 km/h, while the average moving speed was 5.28 km/h. Fishing ground overlap was common among fishers from the same port of origin but not fishers of different ports. Some fishers move farther away from their port during the closure period. Our study provided a better understanding of fishing effort distribution in the Davao Gulf.

Social Fish‐Tancing in Wisconsin: The Effects of the COVID‐19 Pandemic on Statewide License Sales and Fishing Effort in Northern Inland Lakes

AbstractThe first year of the COVID‐19 pandemic in 2020 was associated with an “anthropause” in many industries, initially reducing greenhouse gas emissions and other negative anthropogenic influences. However, outdoor recreation has exploded in popularity in response to closures of indoor recreation options, increased free time, and/or increased levels of stress. We tested for the effects of the COVID‐19 pandemic on the sale of fishing licenses in Wisconsin and on vehicle counts that were observed at public lake access points in Vilas County, Wisconsin, in 2020. In the summer of 2020, fishing license sales in Wisconsin, USA, increased, particularly among first‐time license purchasers for whom cumulative sales in 2020 increased by 71% and 35% compared with the previous 5‐year average for Wisconsin residents and nonresidents, respectively. Changes in the vehicle counts at lake access points in the summer of 2020 varied considerably by lake. However, lakes with greater proportions of public shoreline experienced pandemic‐associated increases in lake visitors. Our results suggest that the distribution of recreational fishing effort in Wisconsin changed during the pandemic, potentially placing additional harvest pressures on hot spot inland lakes.

Ecosystem modeling to evaluate the ecological sustainability of small-scale fisheries: A case study from El Hierro, Canary Islands

This paper examines various fishery management scenarios based on the recovery of small-scale fisheries (SSF) following a submarine volcanic eruption in 2011 in El Hierro Island (Canary Islands, Spain). After this catastrophic event, the SSF composition of La Restinga fishing community was affected by socio-economic and demographic changes. The uncertainty derived from this situation provides an opportunity to evaluate the fisheries’ sustainability and advice on different management options under an ecosystem-based approach. The Ecopath with Ecosim modeling framework was used to build a model of El Hierro Island, where the versatile and traditional multispecies small-scale fleet of La Restinga operates. Our main goal is to improve traditional fisheries, based on the relevance of key local fisheries and multi-specific fishery strategies in the light of scientific knowledge. Temporal simulations for the next decade were analyzed by creating scenarios of alternative fishing effort distributions based on the fishing trends observed in El Hierro small-scale community of La Restinga after a natural hazard. The outcomes of this modeling prototype show the vulnerability of some littoral and demersal species, the resilience of migratory species, and the sustainability of SSF diversification practices. These results could develop an adaptive and co-management strategy with the local fishing community to preserve the small-scale fishing system and marine resources.

Recovery Signals of Rhodoliths Beds since Bottom Trawling Ban in the SCI Menorca Channel (Western Mediterranean)

One of the objectives of the LIFE IP INTEMARES project is to assess the impact of bottom trawling on the vulnerable benthic habitats of the circalittoral bottoms of the Menorca Channel (western Mediterranean), designated a Site of Community Importance (SCI) within the Natura 2000 network. The present study compares the epibenthic communities of four areas, subjected to different bottom trawl fishing intensity levels. The assignment of fishing effort levels was based on the fishing effort distribution in the area calculated from Vessel Monitoring System (VMS) data and the existence of two Fishing Protected Zones in the Menorca Channel. Biological samples were collected from 39 beam trawl stations, sampled during a scientific survey on April 2019. We compare the diversity, composition, and density of the epibenthic flora and fauna, together with the rhodoliths coverage and the morphology of the main species of rhodoliths of four areas subjected to different levels of bottom trawl fishing effort, including one that has never been impacted by trawling. Our results have shown negative impacts of bottom trawling on rhodoliths beds and the first signals of their recovery in areas recently closed to this fishery, which indicate that this is an effective measure for the conservation of this habitat of special interest and must be included in the management plan required to declare the Menorca Channel as a Special Area of Conservation.

Short-term prediction of fishing effort distributions by discovering fishing chronology among trawlers based on VMS dataset

Short-term prediction of fishing effort distributions will guide fishery management in a dynamic way. However, it meets two unique challenges: the randomness of fishers’ behaviors and the diversity of marine meteorology such as sea storms in the short period. This study proposes short-term prediction system of fishing effort distribution by mining a new kind of knowledge: fishing chronology among trawlers. We first define, quantify, and dig out chronological fishing relations among trawlers based on the VMS dataset. Then the system extracts the optimal early bird set from chronological fishing relations, whose current fishing behaviors can serve as indicators of future fishing effort distributions. Based on the knowledge of fishing chronology, we further design a Convolution Neural Network (CNN) to predict the short-term fishing effort distribution, only taking the current fishing behaviors of early birds as input. We evaluate the system performance on the VMS dataset of 1589 trawlers in the East China Sea from October 2015 to April 2017. The system uses the VMS traces in the first half period to calculate fishing chronology among trawlers, to extract early birds, and to train the CNN model. The traces in the last half period is used to evaluate the prediction accuracy. The results confirm a low prediction error ratio of 6.95% across all the weeks only by tracking 19 early birds. More importantly, our prediction system keeps its accuracy during the week of a sea storm in Feb. 8th to 10th, 2017. The application of our system for fishery management is encouraging: tracking only 1% trawlers suffices to predict short-term fishing effort distributions in the near future.

Fishery spatial plans and effort displacement in the eastern Ionian Sea: A bioeconomic modelling

The management of fisheries requires well-planned approaches that consider the socio-ecological costs and benefits of management options while minimising conflicts among fishing practices. We developed a framework to anticipate the cost-effectiveness of several fisheries management options, including space-time closures, gear selectivity improvements, and fishing effort reduction of eastern Ionian Sea fisheries. We also examined to what extent these fisheries could be influenced by placing new aquaculture sites into specific areas. We used a dynamic space-time model considering the effect of possible fishing effort displacement on alternative marine areas. A fine-scale distribution of 6 species of high commercial importance, for the eastern Ionian fisheries (central Mediterranean), was used together with the fishing effort distribution of trawlers, purse-seines, and small-scale fisheries to track the implications on several bio-economic indicators. The study revealed that the stocks and the fisheries economics benefited from a 10% reduction in fishing effort for all fishery sectors, while the unwanted fish catch was slightly higher. Thus, although there are notable advantages, this management option is not sufficient to support an EU regulatory framework aiming to promote more selective fishing practices and mitigate unwanted catches. However, we showed that the protection of juveniles, by imposing selectivity improvements or space-time closures on trawlers, slightly reduced the unwanted catch. Nevertheless, the benefit for the majority of stocks and fisheries economics, during the five-year simulation period, was limited. In the case of space-time closures, this is attributed to the offset due to the fishing effort displacement towards other areas. While the benefit on fish populations by improving trawl selectivity, it depends on the species. Finally, the establishment of new aquaculture units could lead to a slight re-allocation of fishing effort along the border of the new sites without substantially affecting the profit of small-scale fisheries. Such findings are useful for fisheries management and broader spatial planning in the Ionian Sea. They will provide insight to policymakers and different fishing sectors, thus enabling a more transparent and participatory decision–making process.

Trends in shore-based angling effort determined from aerial surveys: a case study from KwaZulu-Natal, South Africa

Understanding the spatiotemporal characteristics of effort is a critical component of managing fisheries. Recreational shore-angling is the largest sector of the linefishery and one of the primary recreational activities undertaken along the coast of KwaZulu-Natal (KZN), South Africa. The aim of this study was to make a reliable estimate of current total shore-based angling effort in KZN and to examine the spatial and temporal distribution of the effort. To do this, randomised monthly flights to count shore-anglers in an ‘instantaneous’ manner were conducted along the entire KZN coastline between January and December 2018, and then compared with similar aerial surveys conducted in 1994/95 and 2007/08. A total of 44 flights were undertaken, with 21 and 23 flights conducted along the north and south coasts, respectively. Ground-truthing revealed that the aerial counts of shore-anglers were 89% accurate. Angler effort was significantly higher over weekends and during good-weather days. Seasonality of shore-based angling effort showed that greatest effort occurred during the winter months (June to September), coinciding with the seasonal availability of popular angling species. More-developed stretches of the KZN coast with higher population densities and easier beach-access had the highest angling effort. Total annual angler effort was calculated to be 785 538 angler-days y–1, which represents a 22.9% decline from the estimate made in 1994/95 and a 6.9% decline from the estimate made in 2007/08. Spatial distribution of shore-based fishing effort was very similar in 2007/08 and 2018, with the major differences being a decrease in fishing effort at St Lucia and Maphelane, and a slight increase in effort on the ‘upper’ (northern) south coast during 2018. Based on the results of this study, recommendations for improved management of the KZN shore fishery include: (i) follow-up using an independent roving-creel survey; (ii) improvement of coastal law enforcement; (iii) implementation of a linefish observer programme; and (iv) a repeat of the aerial survey every 10 years.

Spatial patterns and environmental risks of ringnet fishing along the Kenyan coast

Ringnet fishing began in the early 20th century and is practised worldwide, mainly to target nearshore pelagic species. The method was introduced to Kenya’s coastal waters by migrant fishers from Tanzania. However, the impacts of this fishing gear remain poorly assessed. We assessed the spatial distribution of ringnet fishing effort and its possible effects on ecosystem components, such as coral reefs, marine megafauna and marine protected areas, on the south coast of Kenya. We tracked 89 ringnet fishing trips made from December 2015 to January 2016 and used spatial multicriteria analysis to determine hotspots of possible environmental risks. The results showed that habitat type and bathymetric profile influenced the spatial distribution of ringnet fishing effort. Mixed seagrass and coral habitats had the highest concentration of the effort. Most of the habitats in the study area were moderately exposed to the impacts of the ringnet fishery. The study identifies high-risk areas that require spatial measures to minimise possible environmental risks of the gear both to habitats and to endangered sea turtles.

Can modelling the drift of bycaught dolphin stranded carcasses help identify involved fisheries? An exploratory study

Between the 1st of February and the March 31, 2017, 793 stranded cetaceans were found along the French Atlantic coasts. Common dolphins made up 84% of these strandings, and most of these presented evidence of death in fishing gear. The aim of this work is to test an approach that could help identify the fisheries potentially involved in a given stranding event. To do this we examined how the distributions of likely areas of mortality of bycaught dolphins, inferred from carcass drift modelling, coincide with fishing effort statistics of various fleets, generated from the Vessel Monitoring System, in the area over the same dates. Using reverse drift modelling, two main mortality areas were identified. A total of 3690 common dolphins (IC95% [2230; 6900]) were estimated to have died in fishing gear within the Bay of Biscay during this unusual stranding event. There was a positive correlation between the origin of stranded bycaught dolphins and the fishing effort distribution of French midwater pair trawlers, Spanish otter bottom trawlers and French Danish seiners. This co-occurrence highlights a risk and identifies fisheries that require further investigation (through observers or e-monitoring). These fisheries differed in their fishing gear, but two characteristics appear to be shared: they targeted predatory fishes (sea bass and hake) in winter and used high vertical opening gear.

Improving the interpretation of fishing effort and pressures in mixed fisheries using spatial overlap metrics

Managing mixed fisheries requires understanding fishers’ behaviour to allow predicting future fisheries distribution and impact on marine ecosystems. A new approach was developed to compare fine-scale fishing effort distribution of Eastern English Channel (EEC) bottom trawlers to the monthly and spatially resolved abundance distributions of commercial species. First, the added value of using species-specific spatial overlap metric to quantify effective fishing effort and improve the relationship between fishing effort and fishing mortality was assessed. Second, based on the Ideal Free Distribution (IFD) theory, the species-specific weights given by fishers to different species were estimated by maximizing the overlap between target species assemblage and effort distributions in October. At a seasonal scale, our results emphasized the importance of cuttlefish (Sepia officinalis) and red mullet (Mullus surmuletus) for the global distribution of EEC bottom trawlers. In October, cuttlefish and red mullet were clearly more determining fishers’ location choice than historically harvested species and also than the overall expected revenue. This is likely due to external constraints such as low cod (Gadus morhua) quota, causing IFD assumptions violated. This study evidenced the importance of getting good insights into spatiotemporal distributions of stocks and fleets to understand fishers’ behaviour and improve mixed fisheries management advice.

Distribution of deep-water corals, sponges, and demersal fisheries landings in Southern California, USA: implications for conservation priorities.

Deep-sea corals in Southern California are diverse and abundant but subject to multiple stressors, including bottom-contact fisheries using mobile and fixed gear. There is a need for more information on the distribution of these taxa in relation to the distribution of demersal fishing effort, and the distribution of marine protected areas, in order to improve spatial planning. There are many marine managed areas in Southern California, including essential fish habitat (EFH) areas, conservation areas, and a national marine sanctuary, but specific areas of overlap between bottom fishing and benthic epifauna are poorly known. Groundfish surveys were conducted by the National Marine Fisheries Service using a remotely operated vehicle throughout Southern California between 2003 and 2011 to document abundance and distribution of deep-water rockfish and flatfish to a depth of 500 m. Corals and sponges were also common in these images, providing an opportunity to examine these communities. Analyses of 34,792 still images revealed abundance and diversity of coral and sponge taxa, as well as frequency of fishing debris. The occurrence data were overlaid in a geographic information system with landings data for deep-water (>50 m) demersal fisheries to identify areas of spatial overlap. Corals or sponges were observed in 23% of images. A total of 15 coral genera and six sponge morphotypes were identified. A total of 70 species codes were targeted by deep-water demersal fisheries operating below 50 m for years 2007–2011. A novel priority-setting algorithm was developed to identify areas of high richness, abundance, and fishing intensity (RAFi). Several highly-ranked areas were already protected as EFH (Footprint, Piggy Bank). Other highly-ranked sites (West Catalina Island, San Clemente Island, 9-Mile Bank, Santa Rosa Flats) were encompassed by transient gear restrictions, such as Rockfish conservation areas, but are now recommended for permanent protection by the Pacific Fishery Management Council.

Assessment of the stock status of small-scale and multi-gear fisheries resources in the tropical Eastern Pacific region

Small-scale multi-gear fisheries contribute half of global fisheries landings but are generally data-poor, hindering their assessment and management. Aiming to overcome various existing challenges, we used two complementary length-based approaches to assess the status of three main target species in the small-scale fisheries of Eastern Pacific countries: Spotted rose snapper Lutjanus guttatus, Pacific sierra Scomberomorus sierra, and Pacific bearded Brotula clarkae, using length-frequency catch data (LFCD) from the Colombian Pacific coast. Two data sources – official governmental data and community-based monitoring from a non-government organization – were used to estimate two sets of stock indicators: one based on the derivation of growth and mortality parameters from modal progression, catch curve analysis and a yield-per-recruit model using TropFishR; and the second based on the relative contribution of fish sizes with regard to proposed reference values for healthy stocks. Growth estimates differed between data sources and exhibited large confidence intervals, indicating an overall high uncertainty underlying the LFCD revealed through a novel bootstrapped approach. Estimated values of stock indicators, exploitation rate, fishing mortality and size-proportions converged in suggesting a state of heavy to over-exploitation for the three assessed species, although differences were observed among data sources that we attribute mainly to fisheries selectivity and sampling design. In order to improve future assessments of stocks in multi-gear and data-poor contexts, estimations of fleet-specific selectivity should be used to reconstruct LFCD prior to analyses. Additionally, sampling design should be based on fishing effort distribution among gears and areas and, when feasible, fishery-independent data on stock conditions should be included.

Modelling the spatiotemporal distribution of fisheries discards: A case study on eastern Ionian Sea trawl fishery

The mitigation and incorporation of fisheries discards into the spatial management perspective call for a well-planned approach considering their high spatiotemporal variability. This study describes an approach to map the spatiotemporal distribution of bottom trawl discards taking into account on-board observer data, environmental information and high-resolution estimates of fishing effort derived from Vessel Monitoring System data. Two were the main objectives: i) mapping the Discards Per Unit Effort (DPUE: kg/h) and ii) mapping the total discards quantities (in kg) in a predefined spatial unit (grid cell of 5 × 5 km). For this purpose, discards data from commercial bottom trawlers (seasonal basis, period 2003–2006, 2008) operating on the continental shelf of the eastern Ionian Sea were analyzed. The DPUE for a) all species with Minimum Landing Size (MLS), b) all species without MLS and c) all fish species, were modeled by means of Generalized Additive Models (GAMs) using satellite environmental parameters, bathymetry and season as independent covariates. Mapping discards quantities in a predefined spatial unit was based on the spatial overlapping between GAM estimates for the year 2010 and fishing effort distribution for the same year. Spatial clusters of high discard quantities (hot spots) and their spatiotemporal persistence were also investigated. Results revealed how the environmental and temporal factors influence the DPUE distribution of each discard group and indicated increased discards quantities in areas of high fishing effort. The potential implications of the resulting DPUE maps for advancing discards spatial mitigation are further discussed. Mapping discards quantities using both the DPUE and the fishing effort distribution provide valuable insights that can be useful to investigate the broader ecosystem consequences of the EU landing obligation and other potential fishery management policies.