Dynamics of a migratory population under different fishing effort allocation schemes in time and space

1996 ◽  
Vol 53 (5) ◽  
pp. 1186-1199 ◽  
Author(s):  
D Pelletier ◽  
P Magal
Keyword(s):  
Fishing Effort ◽  
Time And Space ◽  
Effort Allocation ◽  
Migratory Population

Spatial and Temporal Overlap of the American Lobster (Homarus americanus) and Sea Scallop (Placopecten magellanicus) as Related to the impact of Inshore Scallop Dragging

1992 ◽  
Vol 49 (7) ◽  
pp. 1486-1492 ◽  
Author(s):  
D. L. Roddick ◽  
R. J. Miller
Keyword(s):  
Nova Scotia ◽  
Homarus Americanus ◽  
Fishing Effort ◽  
The Other ◽  
American Lobster ◽  
Placopecten Magellanicus ◽  
Time And Space ◽  
Sea Scallop ◽  
The Impact ◽  
Temporal Overlap

Assessment of the damage of one fishery by another requires knowledge of the overlap, in time and space, of the damaging fishing effort and the abundance of the damaged species, as well as a measure of the rate of damage. This approach was used to measure the impact of inshore scallop dragging on lobsters in Nova Scotia. Areas of reported co-occurrence of lobster and scallop grounds were surveyed by divers to determine the extent of overlap. Only 2 of 52 sites surveyed had lobsters on scallop grounds that could be dragged. Divers surveyed one site six times during 1987 and 1988 and found lobsters most abundant during August and September. Only 2% of the lobsters in the path of scallop drags were either captured or injured. The estimated value of lobsters destroyed by dragging for scallops during periods of peak lobster abundance was minor: $757 at one site and $176 at the other. Restricting dragging to periods of low lobster abundance significantly reduces this cost.

Persistence in the fine-scale distribution and spatial aggregation of fishing

2018 ◽  
Vol 76 (4) ◽  
pp. 1072-1082 ◽  
Author(s):  
Niels T Hintzen ◽  
Geert Aarts ◽  
Adriaan D Rijnsdorp
Keyword(s):  
High Stability ◽  
Large Scale ◽  
Spatial Scales ◽  
Negative Relationship ◽  
Fishing Effort ◽  
Local Scale ◽  
Fine Scale ◽  
Effort Allocation ◽  
The Stability ◽  
First Time

Abstract High-resolution vessel monitoring (VMS) data have led to detailed estimates of the distribution of fishing in both time and space. While several studies have documented large-scale changes in fishing distribution, fine-scale patterns are still poorly documented, despite VMS data allowing for such analyses. We apply a methodology that can explain and predict effort allocation at fine spatial scales; a scale relevant to assess impact on the benthic ecosystem. This study uses VMS data to quantify the stability of fishing grounds (i.e. aggregated fishing effort) at a microscale (tens of meters). The model links effort registered at a large scale (ICES rectangle; 1° longitude × 0.5° latitude, ˜3600 km2) to fine spatial trawling intensities at a local scale (i.e. scale matching gear width, here 24 m). For the first time in the literature, the method estimates the part of an ICES rectangle that is unfavourable or inaccessible for fisheries, which is shown to be highly stable over time and suggests higher proportions of inaccessible grounds for either extremely muddy or courser substrates. The study furthermore shows high stability in aggregation of fishing, where aggregation shows a positive relationship with depth heterogeneity and a negative relationship with year-on-year variability in fishing intensity.

scholarly journals What is the added value of including fleet dynamics processes in fisheries models?

2013 ◽  
Vol 70 (7) ◽  
pp. 992-1010 ◽  
Author(s):  
Paul Marchal ◽  
José A.A. De Oliveira ◽  
Pascal Lorance ◽  
Loïc Baulier ◽  
Lionel Pawlowski
Keyword(s):  
Time Series ◽  
North Sea ◽  
Fishing Effort ◽  
Added Value ◽  
Bioeconomic Model ◽  
Effort Allocation ◽  
Time Period ◽  
Harvest Efficiency ◽  
Annual Trends ◽  
Fleet Dynamics

We develop a spatially and seasonally explicit bioeconomic model with three fleet dynamics processes built in endogenously. The model has been applied to the large French trawlers harvesting a medium-depth demersal stock, North Sea saithe (i.e., pollock, Pollachius virens), and a mix of deepwater species over a 10-year period (1999–2008), and the predictions have been contrasted with observations. The best overall fit was achieved where effort allocation was determined to be 80% by traditions and 20% by economic opportunism and where harvest efficiency increased by 8% a year. With this fleet dynamics parameterization, annual trends in fishing effort and profit were well reproduced by the model over the whole time period. Time series of the observed fishing effort by métier were generally well fitted by the model over the period 1999–2003, but less so over 2004–2008. The model also reasonably reproduced the catches by species over most of the time series, except for black scabbardfish (Aphanopus carbo).

Optimizing effort allocation in data poor mixed fisheries

2019 ◽  
Vol 76 (6) ◽  
pp. 1505-1514 ◽  
Author(s):  
Vasiliki Sgardeli ◽  
George Tserpes ◽  
Christos D Maravelias
Keyword(s):  
Profit Maximization ◽  
Aegean Sea ◽  
Single Species ◽  
Fishing Effort ◽  
Biological Targets ◽  
Catch Shares ◽  
Effort Allocation ◽  
Complex Information ◽  
Conflicting Objectives ◽  
R Programming

Abstract Management of mixed fisheries requires reconciling many different and often conflicting objectives (achieving MSY targets and ensuring economic viability among others). In multi-gear mixed fisheries, where many fleets exploit the same species, reallocation of fishing effort can optimize the biological and socioeconomic output of the fishery. Most existing effort allocation tools require extensive data for their parameterization (i.e. detailed effort data and/or analytical assessment of stock status). We present a low-data demanding effort allocation framework for fisheries managed through effort control, with minimum data requirements the surplus production assessment of key stock, catch shares and basic economic fleet data. Profit maximization is considered the overall management goal, which is constrained by single-species biological targets. The method is tested on the Aegean Sea demersal fishery, where two fleet segments exploit numerous species. To achieve sustainable exploitation for the main Aegean stocks, the total effort should be reduced by ∼30%. The framework allows integrating various biological, economic, or other objectives and provides a simple graphical illustration of the allocation result, which can provide a useful tool to convey complex information to managers. To facilitate its application, the source code developed in R programming environment is provided as a supplement.

scholarly journals Individual quotas, fishing effort allocation, and over-quota discarding in mixed fisheries

2009 ◽  
Vol 67 (2) ◽  
pp. 323-333 ◽  
Author(s):  
J. J. Poos ◽  
J. A. Bogaards ◽  
F. J. Quirijns ◽  
D. M. Gillis ◽  
A. D. Rijnsdorp
Keyword(s):  
Fishing Effort ◽  
Dynamic State ◽  
Substantial Part ◽  
Variable Model ◽  
Effort Allocation ◽  
State Variable ◽  
Catch Rates ◽  
The Cost ◽  
Explicit Dynamic ◽  
Dynamic State Variable Model

Abstract Poos, J. J., Bogaards, J. A., Quirijns, F. J., Gillis, D. M., and Rijnsdorp, A. D. 2010. Individual quotas, fishing effort allocation, and over-quota discarding in mixed fisheries. – ICES Journal of Marine Science, 67: 323–333. Many fisheries are managed by total allowable catches (TACs) and a substantial part by individual quotas. Such output management has not been successful in mixed fisheries when fishers continue to fish while discarding marketable fish. We analyse the effects of individual quotas on spatial and temporal effort allocation and over-quota discarding in a multispecies fishery. Using a spatially explicit dynamic-state variable model, the optimal fishing strategy of fishers constrained by annual individual quotas, facing uncertainty in catch rates, is studied. Individual fishers will move away from areas with high catches of the restricted quota species and, depending on the cost of fishing, will stop fishing in certain periods of the year. Individual vessels will discard marketable fish, but only after their individual quota for the species under consideration has been reached. These results are in line with observations on effort allocation and discarding of marketable fish, both over-quota discarding and highgrading, by the Dutch beam-trawl fleet. The models we present can be used to predict the outcomes of management and are therefore a useful tool for fisheries scientists and managers.

Optimal Effort Allocation Among Competing Mixed-Species Fisheries, Subject to Fishing Mortality Constraints

1986 ◽  
Vol 43 (1) ◽  
pp. 90-100 ◽  
Author(s):  
S. A. Murawski ◽  
J. T. Finn
Keyword(s):  
Optimal Allocation ◽  
Mortality Rates ◽  
Fishing Effort ◽  
Discrete Distributions ◽  
Sensitivity Analyses ◽  
Otter Trawl ◽  
Individual Species ◽  
Fishing Mortality ◽  
Effort Allocation ◽  
By Catch

A linear programming (LP) approach to effort allocation among two or more fisheries (fleets) exploiting several common species/stocks is described and applied to otter trawl fisheries exploiting demersal fish stocks on Georges Bank (northeastern United States). Total instantaneous fishing mortality on a particular species (i) is computed as the linear summation of fishing mortalities generated by each fishery (j):[Formula: see text]where fj is the amount of standardized fishing effort exerted in fishery j and qij is the catchability coefficient for species i taken in fishery j. Mortality on species i due to both directed fishing and by-catch can thus be accounted for in the qij's. Optimal allocation of effort among the j fisheries may be considered a minimization problem (minimize Σfj), subject to the constraints that fishing mortality rates on particular species are maintained at, above, or below certain predefined levels. Fishing mortality goals for individual species can be based on various biological and/or economic criteria: fishing mortality rates that prevent growth or recruitment overfishing, or that optimize productivity from predator–prey systems. Other constraints in the LP model may be included to modify optimal solutions based on various economic and social considerations (e.g. protection of certain fisheries). Sensitivity analyses indicate the general infeasibility of maintaining relatively high or low fishing mortality rates on ubiquitously distributed species, while moderately fishing species with more discrete distributions, due to by-catch considerations.

Effects of fishing effort allocation scenarios on energy efficiency and profitability: An individual-based model applied to Danish fisheries

2010 ◽  
Vol 106 (3) ◽  
pp. 501-516 ◽  
Author(s):  
Francois Bastardie ◽  
J. Rasmus Nielsen ◽  
Bo Sølgaard Andersen ◽  
Ole Ritzau Eigaard
Keyword(s):  
Energy Efficiency ◽  
Fishing Effort ◽  
Individual Based Model ◽  
Effort Allocation

Risk aversion in allocating fishing effort in a highly uncertain coastal fishery for pelagic fish, Moluccas, Indonesia

2001 ◽  
Vol 58 (8) ◽  
pp. 1683-1691 ◽  
Author(s):  
JAE van Oostenbrugge ◽  
WLT van Densen ◽  
M A.M Machiels
Keyword(s):  
Fold Increase ◽  
Fishing Effort ◽  
Pelagic Fish ◽  
Small Scale ◽  
Catch Per Unit Effort ◽  
Effort Allocation ◽  
Operation Costs ◽  
By Catch ◽  
Local Use ◽  
Very High

The Ambonese small-scale purse-seine fishery for small pelagic fish, such as scads and mackerels, is characterised by highly variable daily catches. Fishermen involved in this fishery are therefore seriously constrained in optimising the outcome of their fishery through spatial allocation of effort. Spatial patterns in effort allocation were compared with those in catch per unit effort (CPUE), indexed by both catch weight and profit. Average CPUE indexed by catch weight differed between fishing locations by up to 14 times. However, individual fishermen could only detect such large differences after 14 days of exploratory fishing because of the high variability in daily catches. Daily decisions on effort allocation are therefore not based on maximising CPUE but on minimising operational costs and risk. A very high proportion (88%) of the fishing trips were made within 8 km of the home port, although the capacity of the purse seiners allowed for fishing in more productive areas much farther away. A 10- to 20-fold increase in operation costs (travelling and local use rights) when fishing in other areas reinforced this behaviour.

Sign in / Sign up

Export Citation Format

Share Document