Variability of fishing effort for the German brown shrimp (Crangon crangon) fishing fleet: influencing factors, and seasonal and spatial patterns
Author(s) -
Georg Respondek,
Joachim Paul Gröger,
Jens Floeter,
A. Temming
Publication year - 2014
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsu016
Subject(s) - shrimp , fishing , crangon crangon , fishery , catch per unit effort , environmental science , autoregressive integrated moving average , geography , biology , decapoda , statistics , time series , crustacean , mathematics
We examined factors affecting the fishing effort in the German brown shrimp (Crangon crangon) fishery, including shrimp and fuel price, catch per unit effort (cpue), number of days with strong wind, fishing port, and season. Time-series analysis (TS) using rational transfer functions (ARIMAX, an extension of autoregressive integrated moving average (ARIMA) modelling) were applied to model mean monthly boat effort (MBE, in hours), aggregated from the logbook data of five German ports for the years 20002008. We addressed two major areas: (i) whether cyclic effort patterns and the effect of external factors such as wind differ regionally, and (ii) whether external factors such as cpue, shrimp and fuel prices have a significant influence on the effort pattern. The estimated ARIMAX models accounted for 5277% of the variance in MBE if analysed separately for each port, indicating a stable seasonal pattern of fishing effort without major interannual variations or significant trends. In spite of considerable variability in the external factors, none of cpue, shrimp or fuel price had a significant effect on the fishing effort. We interpreted this stability as a lack of alternative target species and discuss the theory that a response of a fishery to these external factors might only occur once certain critical threshold values have been exceeded, which was not the case during the investigated period. The models indicated differences in the seasonal patterns of the different harbours, with shorter trips and an earlier start for the main fishing season in the southwest (SW) regions, whereas in the northeast (NE) harbours, trips were longer, peak effort was shifted by 12 months and the spring season was of greater importance. The relationships of these regional patterns to the shrimp life cycle and coast topography, as well as implications for future management, are discussed.
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