Correction of Relative Fish Abundance Estimates from Catch Data for Variable Fishing Intensity during Lake Surveys

1989 ◽  
Vol 46 (6) ◽  
pp. 1022-1025 ◽  
Author(s):  
P. M. Ryan ◽  
J. J. Kerekes
Keyword(s):  
Brook Trout ◽  
Unit Area ◽  
Fishing Effort ◽  
Fish Abundance ◽  
Lake Area ◽  
Catch Per Unit Effort ◽  
Fixed Amount ◽  
Catch Data ◽  
Abundance Estimates ◽  
Lake Size

Six small Newfoundland lakes were fished with gillnets over a 3–6 yr period in a manner typical of standard lake surveys where surveyors have a fixed amount of gear available, but lake size varies. Catch and effort data for brook trout (Salvelinus fontinalis) were examined for the purpose of selecting an appropriate measure of the relative abundance of trout. Fishing effort was not a function of lake area but fishing intensity or fishing effort per unit area varied inversely with lake area. Brook trout yield (kilograms per hectare) was positively related to fishing intensity Catch per unit effort (kilograms) of brook trout was inversely related to fishing intensity. Methods are suggested to correct for the bias in catch data resulting from variable fishing intensity during lake surveys and improve the recognition of differences in relative fish abundance.

scholarly journals Changes in fish stocks in an Estonian estuary: overfishing by cormorants?

2010 ◽  
Vol 67 (9) ◽  
pp. 1972-1979 ◽  
Author(s):  
Markus Vetemaa ◽  
Redik Eschbaum ◽  
Anu Albert ◽  
Lauri Saks ◽  
Aare Verliin ◽  
...  
Keyword(s):  
Fishing Effort ◽  
Fish Abundance ◽  
Commercial Fishing ◽  
Catch Per Unit Effort ◽  
Phalacrocorax Carbo ◽  
Normal Functioning ◽  
Coastal Fish ◽  
Fish Stocks ◽  
Phalacrocorax Carbo Sinensis ◽  
Bird Colonies

Abstract Vetemaa, M., Eschbaum, R., Albert, A., Saks, L., Verliin, A., Jürgens, K., Kesler, M., Hubel, K., Hannesson, R., and Saat, T. 2010. Changes in fish stocks in an Estonian estuary: overfishing by cormorants? – ICES Journal of Marine Science, 67: 1972–1979. In Estonia, the cormorant Phalacrocorax carbo sinensis is a newcomer, and its numbers have increased rapidly since 1985. In the shallow protected (no fishery) Käina Bay in Väinameri (West Estonia), the colony was established in 1995. Gillnet sampling indicated that roach was the most abundant spawning fish species in 1995. Ten years later, when the study was repeated, the catch per unit effort was already more than 100 times lower than in 1995. The number of spawning perch decreased tenfold from 1995 to 2005. During the same period, commercial fishing effort in the entire Väinameri area decreased several times. The change in fish abundance in the Käina Bay and in the coastal fish-monitoring areas in the archipelago sea nearby, together with an analysis of food of cormorants, indicates that the decline in fish abundance might be related to the increased numbers of cormorants. The conclusion is drawn that the establishment of a cormorant colony could have seriously damaged or even prevented normal functioning of historically important spawning grounds and affected fish recruitment to adjacent areas. Therefore, expanding bird colonies might play a role similar to an expanding fishing fleet, by overexploiting the resource.

ICCAT stock assessments of Atlantic billfish

2003 ◽  
Vol 54 (4) ◽  
pp. 361 ◽  
Author(s):  
Victor Restrepo ◽  
Eric D. Prince ◽  
Gerry P. Scott ◽  
Yuji Uozumi
Keyword(s):  
Fishing Effort ◽  
Data Sets ◽  
Historical Overview ◽  
Catch Per Unit Effort ◽  
Historical Trends ◽  
Istiophorus Platypterus ◽  
Catch Data ◽  
Makaira Nigricans ◽  
Stock Assessments ◽  
The Status

This paper presents a historical overview of the assessments of the Atlantic stocks of blue marlin (Makaira nigricans), white marlin (Tetrapturus albidus) and sailfish (Istiophorus platypterus) that have been conducted by the International Commission for the Conservation of Atlantic Tunas between 1977 and 2000. Details are presented on the data sets used and the models applied, noting the strengths and weaknesses of the assessments. The major causes of uncertainty in the current perception of the status of the stocks are related to some of the data used and to their interpretation, especially historical trends in catch per unit effort. In particular, there are uncertainties about historical catch data, including discards, and about the degree to which longline fishing effort overlaps with billfish habitat. The paper concludes with an account of the efforts that should be made to reduce these uncertainties.

scholarly journals Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series

2021 ◽  
Vol 13 (2) ◽  
pp. 205
Author(s):  
Philipp Hochreuther ◽  
Niklas Neckel ◽  
Nathalie Reimann ◽  
Angelika Humbert ◽  
Matthias Braun
Keyword(s):  
Time Series ◽  
Observation Interval ◽  
Lake Area ◽  
Climate Data ◽  
Melt Pond ◽  
Automated Processing ◽  
Average Observation ◽  
Average Size ◽  
Lake Size ◽  
Sentinel 2

The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km2 area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016–2019, with an average size of 64,212 m2. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km2 and a maximum individual lake size of 30 km2. With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks.

Multiple challenges confront a high-effort inland recreational fishery in decline

2018 ◽  
Vol 75 (9) ◽  
pp. 1357-1368 ◽  
Author(s):  
Christopher L. Cahill ◽  
Stephanie Mogensen ◽  
Kyle L. Wilson ◽  
Ariane Cantin ◽  
R. Nilo Sinnatamby ◽  
...  
Keyword(s):  
Multiple Stressors ◽  
Fishing Effort ◽  
Population Declines ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
Abundance Estimates ◽  
Sampling Locations ◽  
Management Perspective ◽  
Capture Recapture ◽  
Multiple Challenges ◽  
High Effort

Catch-and-release regulations designed to protect fisheries may fail to halt population declines, particularly in situations where fishing effort is high and when multiple stressors threaten a population. We demonstrate this claim using Alberta’s Bow River, which supports a high-effort rainbow trout (Oncorhynchus mykiss) fishery where anglers voluntarily release >99% of their catch. We examined the population trend of adult trout, which were tagged and recaptured using electrofishing surveys conducted intermittently during 2003–2013. We constructed Bayesian multisession capture–recapture models in Stan to obtain abundance estimates for trout and regressed trend during two periods to account for variation in sampling locations. General patterns from all models indicated the population declined throughout the study. Potential stressors to this system that may have contributed to the decline include whirling disease (Myxobolus cerebralis), which was detected for the first time in 2016, notable floods, and release mortality. Because disease and floods are largely uncontrollable from a management perspective, we suggest that stringent tactics such as angler effort restrictions may be necessary to maintain similar fisheries.

scholarly journals Factors affecting relative abundance of low-mobility fishing resources: spiny lobster in the Galapagos Marine Reserve

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7278 ◽  
Author(s):  
Juan Carlos Murillo-Posada ◽  
Silvia Salas ◽  
Iván Velázquez-Abunader
Keyword(s):  
Monitoring System ◽  
Relative Abundance ◽  
Spatial Scales ◽  
Marine Reserve ◽  
Spiny Lobster ◽  
Fishing Effort ◽  
Additive Models ◽  
Catch Per Unit Effort ◽  
Monthly Basis ◽  
Galapagos Marine Reserve

Management of low-mobility or benthic fisheries is a difficult task because variation in the spatial distribution and population dynamics of the resources make the monitoring and assessment of these fisheries challenging. We assumed that environmental, spatial, and temporal factors can contribute to the variability of the relative abundance of such species; we used Generalized Additive Models for Location Scale and Shape (GAMLSS) to test this hypothesis using as a case study the lobster fishery (targeting two species) in the Galapagos Marine Reserve, Ecuador. We gathered data on each of the two species of lobster on a monthly basis over seven years, including: (a) onboard observers’ records of catch data, fishing effort, and ground location by trip, and (b) data from interviews undertaken with fishers at their arrival to port, recording the same type of information as obtained from onboard observers. We use this information to analyze the effect of the measured variables and to standardize the Catch per Unit Effort (CPUE) in each case, using the GAMLSS. For both species, the temperature, region, fishing schedule, month, distance, and the monitoring system were significant variables of the selected models associated with the variability of the catch rate. ForPanulirus penicillatus, CPUE was higher at night than during the day, and forPanulirus gracilisit was higher during the day. Increased temperature resulted in a decrease of CPUE values. It was evident that temporal, spatial scales and monitoring system can influence the variability of this indicator. We contend that the identification of drivers of change of relative abundance in low-mobility species can help to support the development of monitoring and assessment programs for this type of fisheries.

Fishing on floating objects (FOBs): how French tropical tuna purse seiners split fishing effort between GPS-monitored and unmonitored FOBs

2018 ◽  
Vol 75 (11) ◽  
pp. 1849-1858 ◽  
Author(s):  
Julia E. Snouck-Hurgronje ◽  
David M. Kaplan ◽  
Emmanuel Chassot ◽  
Alexandra Maufroy ◽  
Daniel Gaertner
Keyword(s):  
Search Time ◽  
Fishing Effort ◽  
Purse Seine ◽  
Trajectory Data ◽  
Catch Per Unit Effort ◽  
Position Information ◽  
Foreign Objects ◽  
Tropical Tuna ◽  
Floating Objects ◽  
Over Time

Fishing on floating objects (FOBs) dominates catch in tropical tuna purse seine fisheries. One frequently cited advantage of deploying GPS-monitored FOBs is that the position information can be used for directed fishing to reduce search time for tuna. However, purse seiners also fish on foreign objects for which position information is not available. It is critical to quantify the prevalence of fishing on GPS-monitored versus unmonitored FOBs to understand how they impact fishing effort and catch per unit effort. We analyzed French commercial, observer, and FOB trajectory data in the Atlantic and Indian oceans to determine how often purse seine vessels fish on GPS-monitored FOBs. Only 2.7%–20.4% of French FOB fishing sets over 2007–2013 in both oceans were made on GPS-monitored FOBs. Though increasing over time, the low percentage suggests that French vessels do not primarily use GPS-monitored FOBs to reduce search time for tuna. We hypothesize that fishery-wide FOB deployments have important collective consequences for overall fishing effort and recommend that future effort metrics should be based on fishery-wide FOB activities.

Population Dynamics of the Arcto-Norwegian Cod

1967 ◽  
Vol 24 (1) ◽  
pp. 145-190 ◽  
Author(s):  
D. J. Garrod
Keyword(s):  
Gadus Morhua ◽  
Barents Sea ◽  
Fishing Effort ◽  
Catch Per Unit Effort ◽  
Group Iii ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Post War ◽  
The One ◽  
Definition Of

By reason of its geographical distribution, the Arcto-Norwegian cod (Gadus morhua) supports three distinct fisheries, two feeding fisheries in the Barents Sea and at Bear Island–Spitsbergen, and a spawning fishery off the Norway coast. In the past this diversity of fishing on the one stock has made it difficult to unify all the data to give an overall description of post-war changes in the stock. In this contribution three modifications of conventional procedures are introduced which enable this to be done. These are: (i) a system of weighting the catch per unit effort data from each fishery to a level of comparability; (ii) a more rigorous definition of the effective fishing effort on each age-group; (iii) a method of estimation of the effective fishing effort on partially recruited age-groups.Using these methods the analysis presents the effects of fishing on each fishery in the context of its effect on the total stock, and at the same time it indicates ways in which factors other than fishing may have influenced the apparent abundance of the stock. The treatment of the data is also used to derive estimates of spawning stock and recruitment of 3-year-old cod for subsequent analysis of stock–recruitment relationships.

scholarly journals Overlooked biological and economic implications of within-season fishery dynamics

2014 ◽  
Vol 71 (2) ◽  
pp. 181-188 ◽  
Author(s):  
Xiaozi Liu ◽  
Mikko Heino
Keyword(s):  
Concentration Profile ◽  
Fishing Effort ◽  
Economic Consequences ◽  
Fish Abundance ◽  
Fishing Pressure ◽  
Fishing Mortality ◽  
Economic Implications ◽  
Special Cases ◽  
Total Stock ◽  
Stock Abundance

Catch equations relate fisheries catch to initial fish abundance and the applied fishing pressure. The Baranov catch equation, often simply referred to as the catch equation, is the commonest one. However, there are exactly three ways of describing seasonal progression of fishing parsimoniously with a single parameter: assume catch rate, fishing effort, or fishing mortality is constant, the last being the assumption underlying the Baranov catch equation. These assumptions imply different dynamics, and only in special cases two of these assumptions can hold true simultaneously. Whether this happens is dictated by the concentration profile (i.e., the dependence of mean fish density where fishing takes place on total stock abundance). We show that the assumed seasonal progression of fishing and the type of the concentration profile have major implications for fishery dynamics as well as biological and economic consequences of fishing, calling for increased awareness of these overlooked assumptions of fishery dynamics. However, in many cases the Baranov catch equation serves as a good approximation, even when its assumption of constant fishing mortality is violated.

It’s complicated…Environmental DNA as a predictor of trout and char abundance in streams

2020 ◽  
Author(s):  
Adam J. Sepulveda ◽  
Robert Al-Chokhachy ◽  
Matthew B Laramie ◽  
Kyle Crapster ◽  
W Ladd Knotek ◽  
...  
Keyword(s):  
Cutthroat Trout ◽  
Environmental Dna ◽  
Fish Abundance ◽  
Bull Trout ◽  
Intermountain West ◽  
Salvelinus Confluentus ◽  
Oncorhynchus Clarkii ◽  
Habitat Monitoring ◽  
Abundance Estimates ◽  
Random Site

The potential to provide inferences about fish abundance from environmental (e)DNA samples has generated great interest. However, the accuracy of these abundance estimates is often low and variable across species and space. A plausible refinement is the use of common aquatic habitat monitoring data to account for attributes that influence eDNA dynamics. We therefore evaluated the relationships between eDNA concentration and abundance of bull trout (Salvelinus confluentus), westslope cutthroat trout (Oncorhynchus clarkii lewisi) and rainbow trout (O. mykiss) at 42 stream sites in the Intermountain West (USA and CAN) and tested if accounting for site-specific habitat attributes improved the accuracy of fish abundance estimates. eDNA concentrations were positively associated with fish abundance but these relationships varied by species and site and there was considerable variation unaccounted for. Random site-level differences explained much of this variation, but specific habitat attributes of those sites explained relatively small amounts of this variation. Our results underscore that either eDNA sampling or environmental characterization will require further refinement before eDNA can be used reliably to estimate fish abundance in streams.

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