This study examines whether a fish stock can be managed using cumulative sum (CUSUM) control charts if limited historical information is available for the fish stock. We use the term ‘limited’ in the sense of having a minimal number of... more
This study examines whether a fish stock can be managed using cumulative sum (CUSUM) control charts if limited historical information is available for the fish stock. We use the term ‘limited’ in the sense of having a minimal number of historical observations of relevant stock indicators and their respective control means (or reference points) that are aligned with the objectives of fisheries management. In the present study, a Decision Interval Cumulative Sum (DI-CUSUM) control chart was used to monitor two indices from a simulated fishery; the recruitment indicator and the large fish indicator (LFI). The fishery was subsequently managed using a harvest control rule (HCR) that triggered only when a significant deviation in the indicator trend was detected by the DI-CUSUM. The HCR was constructed using methods adopted from engineering process control theory where the adjustment in total allowable catch was determined by estimating the size of the shift in the indicator time series. We found that monitoring a combined indicator of both recruitment and LFI was more successful in controlling the fishery irrespective of the initial state of the fish stock. We discuss how DI-CUSUM could be incorporated into the management process for data poor fisheries.
Harpadon nehereus, commonly known as ‘Bombay duck’, is a fish with a discontinuous distribution along the Indian peninsula. The fisheries are dominant on the north-east and north-west coast but are absent in commercial landings below 15°... more
Harpadon nehereus, commonly known as ‘Bombay duck’, is a fish with a discontinuous distribution along the Indian peninsula. The fisheries are dominant on the north-east and north-west coast but are absent in commercial landings below 15° north latitude. Heretofore stock assessment studies had not considered the various spawning stock components that replenish this fishery, therefore the present study. Fish samples were collected from four locations: two each from the northeast and the northwest coasts. Twenty-four morphometric variables were measured using a box-truss network method. Factor analysis of these variables differentiated the east and the west coast fish populations. Multiple comparisons on the factor scores indicated two independent stocks on the east coast, whereas the fishery on the west coast is replenished by a single stock. The important morphometric traits that accounted for most of the stock variations were related to swimming adaptations of the fish. Future stock assessments can consider the population on the west coast as a single stock when formulating management plans. To harvest the resource in a sustainable manner, the maritime states on the west coast should adopt collaborative efforts towards managing this fishery.
We demonstrate a harvest control rule based on the self-starting cumulative sum (SS-CUSUM) control chart that can maintain a fish stock at its starting (status-quo) level. The SS-CUSUM is an indicator monitoring tool commonly used in... more
We demonstrate a harvest control rule based on the self-starting cumulative sum (SS-CUSUM) control chart that can maintain a fish stock at its starting (status-quo) level. The SS-CUSUM is an indicator monitoring tool commonly used in quality control engineering and does not require a long time series or pre-defined reference point for detecting temporal trends. The reference points in SS-CUSUM are calibrated in the form of running means that are updated on an ongoing basis when new observations become available. The SS-CUSUM can be initiated with as few as two observations in the time series, and can be applied long before many other methods, soon after initial data become available. A wide range of stock indicators can be monitored but in this study, we demonstrate the method using an equally weighted sum of two indicators: a recruitment indicator and a large fish indicator from a simulated fishery. We assume that no life history data are available other than two years of both indicator data and current harvest levels when the SS-CUSUM initiates. The signals generated from SS-CUSUM trigger a harvest control rule (SS-CUSUM-HCR), where the shift that occurs in the indicator time series is computed and is used as an adjustment factor for updating the Total Allowable Catch (TAC). Our study shows that the SS-CUSUM-HCR can maintain the fish stock at its starting status-quo level (even for overfished initial states) but has limited scope if the fishery is already in an undesirable state such as a stock collapse. We discuss how the SS-CUSUM approach could be adapted to move beyond a status-quo management strategy, if additional information on the desirable state of the fishery is available.
