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30 results for “fisheries catch”
Social-Ecological Dynamics of Recreational Fishery Landscapes: Recreational angler catch and satisfaction in the Midwest, 2018 to 2024
The goal of this dataset is to understand angler information gathering and sharing, technology use, expectation-setting, site choice, and the factors influencing angler satisfaction in rural and urban environments. These data were collected through on-site creel surveys and instantaneous counts of fishing effort and associated angler vehicles. Traditional creel surveys are completed only at the end of an angler's fishing trip. These dual-intercept creel survey data are novel because anglers were intercepted both before and after their fishing trip. This survey design allowed us to collect unbiased estimates of anglers' expected catch. These data can be used to understand the role of angler expectations in angler satisfaction and behavior. Data collection were conducted in two counties in Wisconsin, USA. Vilas County is a primarily rural, forested, and glaciated region with many relatively small lakes. Dane County has a larger urban center (Madison, WI) that is surrounded by agricultural areas. Most of the Dane County lakes surveyed were part of the Yahara chain of lakes: Lakes Mendota, Monona, Wingra, Waubesa, and Kegonsa. Dane county has fewer, larger lakes with greater connectivity to each other. Vilas County was sampled in the summer of 2018, the summer of 2019, and the summer and winter of 2022. Dane County was sampled in the winter and summer of 2022.
Global monthly catches from tuna surface fisheries by 1° grid (1958-2023) (FIRMS level 0)
<p>We compiled a comprehensive dataset of geo-referenced catches from global tuna fisheries that use fishing gears set at the water's surface. This dataset was created by harmonizing public domain data from the five tuna Regional Fisheries Management Organizations (t-RFMOs) for the period 1958-2023. Under the auspices of the Fisheries and Resources Monitoring System (FIRMS) of the United Nations Food and Agriculture Organization (FAO), we developed a systematic data flow process in collaboration with the t-RFMO Secretariats. This process involved the implementation of a data exchange format adhering to the standards of the FAO Coordinating Working Party on Fishery Statistics (CWP), facilitating the seamless integration of data into the dataset.</p> <p>Geo-referenced catch data from tuna surface fisheries are reported in either the number of fish or live-weight equivalent (metric tonnes), with some strata providing catches in both units. The catches primarily represent the quantities of retained fish either landed or transhipped at sea and in ports. The data are stratified by year, month, fishing fleet, fishing gear, fishing mode, 1° grid area of longitude and latitude, and taxon.</p> <p>The dataset encompasses 42 medium- and large-sized pelagic species found in both neritic and oceanic habitats of the world's oceans. This includes 14 species of tunas, 9 species of billfish, 4 species of Spanish mackerels, 2 species of bonitos, and wahoo. Despite uncertainties and incomplete data due to under-reporting, the dataset also includes reported catches for 12 species of pelagic sharks and rays that may be either targeted or incidentally caught in tuna and tuna-like fisheries.</p> <p>The dataset serves as a benchmark for the monitoring and assessment of both artisanal and industrial fisheries using surrounding nets, gillnets, entangling nets, and pole-and-lines from over 70 fishing fleets across 69 countries that have exploited tuna and tuna-like species for subsistence and commercial purposes over more than six decades.</p>
Global annual catches from tuna fisheries (1918-2023) (FIRMS level 0)
<p>We constructed the most comprehensive dataset of nominal catches from global tuna fisheries by compiling and harmonizing public domain data from the five tuna Regional Fisheries Management Organizations (t-RFMOs) for the period 1918-2023. Under the auspices of the Fisheries and Resources Monitoring System (FIRMS) of the United Nations Food and Agriculture Organization (FAO),we developed a systematic data flow process in collaboration with the t-RFMO Secretariats. This process involved the implementation of a data exchange format adhering to the standards of the FAO Coordinating Working Party on Fishery Statistics (CWP),facilitating the seamless integration of data into the dataset.<br><br>Nominal catch data are expressed in live-weight equivalent (metric tonnes) and primarily represent the quantities of retained fish either landed or transhipped at sea and in ports. In recent years,data from fisheries in the Atlantic and Western-Central Pacific Oceans have partially included amounts of fish discarded dead. The data are stratified by year,fishing fleet,fishing gear,large spatial area,and taxon.<br><br>The dataset encompasses 50 medium- and large-sized pelagic species found in both neritic and oceanic habitats of the world's oceans. This includes 15 species of tunas,10 species of billfish,8 species of Spanish mackerels,2 species of bonitos,and wahoo. In 2023,the global catch for these species was estimated to exceed 6.4 million metric tonnes. Despite uncertainties and incomplete data due to under-reporting,the dataset also includes reported catches for 14 species of pelagic sharks and rays that may be either targeted or incidentally caught in tuna and tuna-like fisheries. The total reported catch of these elasmobranch species was approximately 154,000 metric tonnes in 2023.<br><br>The dataset serves as a benchmark for the monitoring and assessment of both artisanal and industrial fisheries from over 161 fishing fleets across 159 countries that have exploited tuna and tuna-like species for subsistence and commercial purposes over more than seven decades.</p>
Fishery impacts - CA commercial lobster catch and effort, and trap distribution around marine reserves
These data describe landings and fishing effort for the CA commercial spiny lobster fishery. Data are contained in two tables: 1) a time series collected by the California Fish and Wildlife (CDFW) of lobster catch (kg) and effort (lobster trap pulls) by year (1998-2020) and location (geographic fishery blocks). Catch is recorded and reported to CDFW by fish processors (buyers) with “fish tickets”. Trap pulls are recorded and reported by fishermen with logbooks. 2) The number of traps counted in the water at increasing distances from the boundary of marine reserves, three reserves located in the northern region of the fishery and three from the southern region of the fishery, in November 2022.
Global monthly catches from tuna fisheries by 1° and 5° grids (1950-2023) (FIRMS level 0)
<p>We compiled a comprehensive dataset of geo-referenced catches from global tuna fisheries available at a spatial resolution of 1° and 5° grid areas. This dataset was created by harmonizing public domain data from the five tuna Regional Fisheries Management Organizations (t-RFMOs) for the period 1950-2023. Under the auspices of the Fisheries and Resources Monitoring System (FIRMS) of the United Nations Food and Agriculture Organization (FAO), we developed a systematic data flow process in collaboration with the t-RFMO Secretariats. This process involved the implementation of a data exchange format adhering to the standards of the FAO Coordinating Working Party on Fishery Statistics (CWP), facilitating the seamless integration of data into the dataset.<br><br>Geo-referenced catch data from tuna fisheries are reported in either the number of fish or live-weight equivalent (metric tonnes), with some strata providing catches in both units. The catches primarily represent the quantities of retained fish either landed or transhipped at sea and in ports. The data are stratified by year, month, fishing fleet, fishing gear, fishing mode, 1° or 5° grid area of longitude and latitude, and taxon.<br><br>The dataset encompasses 49 medium- and large-sized pelagic species found in both neritic and oceanic habitats of the world's oceans. This includes 15 species of tunas, 10 species of billfish, 7 species of Spanish mackerels, 2 species of bonitos, and wahoo. Despite uncertainties and incomplete data due to under-reporting, the dataset also includes reported catches for 14 species of pelagic sharks and rays that may be either targeted or incidentally caught in tuna and tuna-like fisheries.<br><br>The dataset serves as a benchmark for the monitoring and assessment of both artisanal and industrial fisheries from over 115 fishing fleets across 114 countries that have exploited tuna and tuna-like species for subsistence and commercial purposes over more than seven decades.</p>
Global monthly catches from tuna fisheries by 5° grid (1950-2023) (FIRMS level 0)
We compiled a comprehensive dataset of geo-referenced catches from global tuna fisheries available on a spatial resolution of 5° grid areas. This dataset was created by harmonizing public domain data from the five tuna Regional Fisheries Management Organizations (t-RFMOs) for the period 1950-2023. Under the auspices of the Fisheries and Resources Monitoring System (FIRMS) of the United Nations Food and Agriculture Organization (FAO), we developed a systematic data flow process in collaboration with the t-RFMO Secretariats. This process involved the implementation of a data exchange format adhering to the standards of the FAO Coordinating Working Party on Fishery Statistics (CWP), facilitating the seamless integration of data into the dataset.<br><br>Geo-referenced catch data from tuna fisheries are reported in either the number of fish or live-weight equivalent (metric tonnes), with some strata providing catches in both units. The catches primarily represent the quantities of retained fish either landed or transhipped at sea and in ports. The data are stratified by year, month, fishing fleet, fishing gear, fishing mode, 5° grid area of longitude and latitude, and taxon.<br><br>The dataset encompasses 49 medium- and large-sized pelagic species found in both neritic and oceanic habitats of the world's oceans. This includes 15 species of tunas, 10 species of billfish, 7 species of Spanish mackerels, 2 species of bonitos, and wahoo. Despite uncertainties and incomplete data due to under-reporting, the dataset also includes reported catches for 14 species of pelagic sharks and rays that may be either targeted or incidentally caught in tuna and tuna-like fisheries.<br><br>The dataset serves as a benchmark for the monitoring and assessment of both artisanal and industrial fisheries from over 115 fishing fleets across 114 countries that have exploited tuna and tuna-like species for subsistence and commercial purposes over more than seven decades.
FIG. 3 in Catching tuna in the Aegean: biological background of tuna fisheries and the archaeological implications
FIG. 3. — Beach seine fishing scene on a Mycenean hydria (12th c. BC) from Naxos. The large fish in the net are probably tuna (reproduced from Hadjianastasiou 1991).
FIG. 2 in Catching tuna in the Aegean: biological background of tuna fisheries and the archaeological implications
FIG. 2. — Thynnus sp. bones from Late Classical strata (400-300 BC) at Kalaureia, Poros island. Scale bar: 4 cm. Credits: D. Mylona, Kalaureia excavations photographic archive.
FIG. 5 in Catching tuna in the Aegean: biological background of tuna fisheries and the archaeological implications
FIG. 5. — Sketch of a thynneion (stationary tuna trap) at Kandylio a few short distance north of Halieis (reproduced from Panagiotopoulos 1914).
FIG. 4 in Catching tuna in the Aegean: biological background of tuna fisheries and the archaeological implications
FIG. 4. — Wall painting of one of the two Little Fishermen from the so called West House at Akrotiri,Thera. The fish he holds are little tunny (Euthynnus allet- teratus Rafinesque, 1810) or bullet tunny (Auxis rochei Risso, 1810) (reproduced from Doumas 1992).
Figure 6 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 6. Cluster analysis based on CPUE (kg/h) and the distance (Bray–Curtis, UPGMA) of the catch during the fishing months.
Figure 2 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 2. Monthly changes in catch per unit effort (CPUE), index of relative importance (IRI), and biodiversity indices (S, species richness; H', Shannon–Wiener diversity; and J´, Pielou's evenness).
Figure 8 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 8. Cluster analysis based on CPUE (N/h) and the distance (Bray–Curtis, UPGMA) of the catch during the fishing months.
AQUAVITAE_Fish key performance indicators for diets from fisheries by-catch valorisation
<p><span lang="EN-GB">This dataset contains the key performance indicators associated with a nutritional trial performed at the Centro de Ciências do Mar do Algarve (CCMAR, Faro, Portugal) within the framework of the Cross-cutting Case Study on by-products of the AquaVitae project (</span><span lang="EN-US">New species, processes and products contributing to increased production and improved sustainability in emerging low trophic, and existing low and high trophic aquaculture value chains in the Atlantic) funded by the European Union’s Horizon 2020 Research and Innovation Programme (GA 818173</span><span lang="EN-GB">). This study aimed to assess the effects of no-fishmeal (FM) diets and </span><span lang="EN-US">fish protein hydrolysates (FPHs) produced from fisheries discards on the growth performance of gilthead seabream (<em>Sparus aurata</em>). T</span><span lang="EN-GB">wo FPHs were prepared from the enzymatic hydrolysis of discards from whole-body blue whiting (<em>Micromesistius poutassou</em>) and gurnard heads (<em>Trigla</em> spp.); the former contained a higher proportion of large peptides (LP), while the latter had more small peptides (SP). Gilthead seabream juveniles <span>(initial weight ± 8.0 g) were reared on f</span><span>our isoproteic (48%) and isolipic (16%) diets for eight weeks. Basal diets were a commercial-like diet (COM) and a diet based on ingredients not used directly for human consumption (FUTURE diet - FUT), without FM or soy protein concentrate. The FUT diet was further supplemented with one of the FPHs (<span>FUTLP and </span></span><span>FUTSP </span><span>diets). For further information on experimental conditions, please refer to the publication: “Aragão C., Colen R., Teodósio R., Cabano M., Antelo L.T., Vázquez J.A. and Engrola S., 2025. Fish protein hydrolysates under a circular economy approach: an effective tool to mitigate adverse effects of no-fishmeal diets. Aquaculture Nutrition 2025: 1352251. doi: 10.1155/anu/1352251”. In addition to properly citing this dataset, it would be appreciated that when using this dataset in a publication, the original publication is cited.</span></span></p>
FIG. 1 in Catching tuna in the Aegean: biological background of tuna fisheries and the archaeological implications
FIG. 1. — Map of the Aegean Sea with sites mentioned in the text noted on it. Credits: V. Triggas.
Figure 3 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 3. Monthly distribution of the catch.
Figure 4 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 4. Rank–abundance curves by month in terms of CPUE% (kg/h).
Figure 5 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 5. Rank–abundance curves by month in terms of CPUE% (N/h).
Figure 1 in Catch composition of trawl fisheries in Mersin Bay with emphasis on catch biodiversity
Figure 1. Study area.
Data from: Human-wildlife coexistence needs more evidence-based interventions to reduce the losses of crops, livestock, and fishery catches
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