25 resultados para spatial stock assessment


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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The data have been extracted and compiled from various sources but mainly from the ICES data base. The ICES data are from catch databases downloaded from the ICES website on 2014-01-14. These data are resolved by ICES area, country and year. During inspection of these data, it was noted that Norwegian data for years before 1950 had not been entered into the catch database on the ICES website. ICES has been notified of this omission by B. R. MacKenzie. The Norwegian data from ICES Bulletins. Statistiques has been added. Additional historical bluefin tuna catch data from other fishery reports and sources have been included in the data file for years preceding those when countries started reported their landings officially to ICES. These additional data have been reported in the literature previously (MacKenzie and Myers 2007, Fisheries Research).

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To address growing concern over the effects of fisheries non-target catch on elasmobranchs worldwide, the accurate reporting of elasmobranch catch is essential. This requires data on a combination of measures, including reported landings, retained and discarded non-target catch, and post-discard survival. Identification of the factors influencing discard vs. retention is needed to improve catch estimates and to determine wasteful fishing practices. To do this we compared retention rates of elasmobranch non-target catch in a broad subset of fisheries throughout the world by taxon, fishing country, and gear. A regression tree and random forest analysis indicated that taxon was the most important determinant of retention in this dataset, but all three factors together explained 59% of the variance. Estimates of total elasmobranch removals were calculated by dividing the FAO global elasmobranch landings by average retention rates and suggest that total elasmobranch removals may exceed FAO reported landings by as much as 400%. This analysis is the first effort to directly characterize global drivers of discards for elasmobranch non-target catch. Our results highlight the importance of accurate quantification of retention and discard rates to improve assessments of the potential impacts of fisheries on these species.

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Acoustic and pelagic trawl data were collected during various pelagic surveys carried out by IFREMER in May between 2000 and 2012 (except 2001), on the eastern continental shelf of the Bay of Biscay (Pelgas series). The acoustic data were collected with a Simrad EK60 echosounder operating at 38 kHz (beam angle at -3 dB: 7°, pulse length set to 1.024 ms). The echosounder transducer was mounted on the vessel keel, at 6 m below the sea surface. The sampling design were parallel transects spaced 12 nm apart which were orientated perpendicular to the coast line from 20 m to about 200 m bottom depth. The nominal sailing speed was 10 knots and 3 knots on average during fishing operations. The scrutinising (species identification) of acoustic data was done by first characterising acoustic schools by type and then linking these types with the species composition of specific trawl hauls. The data set contains nautical area backscattering values, biomass and abundance estimates for blue whiting for one nautical mile long transect lines. Further information on the survey design, scrutinising and biomass estimation can be found in Doray et al. 2012.

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The copepod Calanus finmarchicus is the dominant species of the meso-zooplankton in the Norwegian Sea, and constitutes an important link between the phytoplankton and the higher trophic levels in the Norwegian Sea food chain. An individualbased model for C. finmarchicus, based on super-individuals and evolving traits for behaviour, stages, etc., is two-way coupled to the NORWegian ECOlogical Model system (NORWECOM). One year of modelled C. finmarchicus spatial distribution, production and biomass are found to represent observations reasonably well. High C. finmarchicus abundance is found along the Norwegian shelf-break in the early summer, while the overwintering population is found along the slope and in the deeper Norwegian Sea basins. The timing of the spring bloom is generally later than in the observations. Annual Norwegian Sea production is found to be 29 million tonnes of carbon and a production to biomass (P/B) ratio of 4.3 emerges. Sensitivity tests show that the modelling system is robust to initial values of behavioural traits and with regards to the number of super-individuals simulated given that this is above about 50,000 individuals. Experiments with the model system indicate that it provides a valuable tool for studies of ecosystem responses to causative forces such as prey density or overwintering population size. For example, introducing C. finmarchicus food limitations reduces the stock dramatically, but on the other hand, a reduced stock may rebuild in one year under normal conditions. The NetCDF file contains model grid coordinates and bottom topography.

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Probabilistic climate data have become available for the first time through the UK Climate Projections 2009, so that the risk of tree growth change can be quantified. We assess the drought risk spatially and temporally using drought probabilities and tree species vulnerabilities across Britain. We assessed the drought impact on the potential yield class of three major tree species (Picea sitchensis, Pinus sylvestris, and Quercus robur) which presently cover around 59% (400,700 ha) of state-managed forests, across lowland and upland sites. Here we show that drought impacts result mostly in reduced tree growth over the next 80 years when using b1, a1b and a1fi IPCC emissions scenarios. We found a maximum reduction of 94% but also a maximum increase of 56% in potential stand yield class in the 2080s from the baseline climate (1961-1990). Furthermore, potential production over the national forest estate for all three species in the 2080s may decrease due to drought by 42% in the lowlands and 32% in the uplands in comparison to the baseline climate. Our results reveal that potential tree growth and forest production on the national forest estate in Britain is likely to reduce, and indicate where and when adaptation measures are required. Moreover, this paper demonstrates the value of probabilistic climate projections for an important economic and environmental sector.

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The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.

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The continuous plankton recorder (CPR) survey is an upper layer plankton monitoring program that has regularly collected samples, at monthly intervals, in the North Atlantic and adjacent seas since 1946. Water from approximately 6 m depth enters the CPR through a small aperture at the front of the sampler and travels down a tunnel where it passes through a silk filtering mesh of 270 µm before exiting at the back of the CPR. The plankton filtered on the silk is analyzed in sections corresponding to 10 nautical miles (approx. 3 m**3 of seawater filtered) and the plankton microscopically identified (Richardson et al., 2006 and reference therein). In the present study we used the CPR data to investigate the current basin scale distribution of C. finmarchicus (C5-C6), C. helgolandicus (C5-C6), C. hyperboreus (C5-C6), Pseudocalanus spp. (C6), Oithona spp. (C1-C6), total Euphausiida, total Thecosomata and the presence/absence of Cnidaria and the Phytoplankton Colour Index (PCI). The PCI, which is a visual assessment of the greenness of the silk, is used as an indicator of the distribution of total phytoplankton biomass across the Atlantic basin (Batten et al., 2003). Monthly data collected between 2000 and 2009 were gridded using the inverse-distance interpolation method, in which the interpolated values were the nodes of a 2 degree by 2 degree grid. The resulting twelve monthly matrices were then averaged within the year and in the case of the zooplankton the data were log-transformed (i.e. log10 (x+1).