Evaluating spatio-temporal dynamics of multiple fisheries-targeted populations simultaneously: A case study of the Bohai Sea ecosystem in China

Guan, Lisha; Shan, Xiujuan; Jin, Xianshi; Gorfine, Harry; Yang, Tao; Li, Zhongyi

doi:10.1016/j.ecolmodel.2020.108987

Cited by 6 publications

(6 citation statements)

References 28 publications

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“…Besides, the method's R scripts can be run with minimal skills and require only minor changes from the users, who would adjust the factors to compute the vulnerability indices so as to better reflect the changes over time of the exploitation status of tuna species and the apparent abundance of associated species. Moreover, transferring the analysis workflow to a different dataset or ecosystem necessitates few simple adjustments, which in our opinion constitutes the main appeal of this approach in comparison to the ones mentioned in the introduction section (Grüss et al, 2019; Guan et al, 2020; Kai et al, 2017; Paradinas et al, 2015; Quiroz & Prates, 2018; Sibert et al, 2012). A further strength is undoubtedly the flexibility in data input, even if it implies cautious interpretation from the users.…”

Section: Discussionmentioning

confidence: 99%

“…in the introduction section (Grüss et al, 2019;Guan et al, 2020;Kai et al, 2017;Paradinas et al, 2015;Quiroz & Prates, 2018;Sibert et al, 2012). A further strength is undoubtedly the flexibility in data input, even if it implies cautious interpretation from the users.…”

Section: Potential For Fisheries Managementmentioning

confidence: 99%

“…To overcome the difficulties posed by the spatiotemporal dimension and the multi-specific characteristic of many fisheries, scientists have used different methods, including generalized linear mixed models (Kai et al, 2017), Bayesian modelling (Paradinas et al, 2015;Quiroz & Prates, 2018), joint dynamic species distribution models implemented in the vector autoregressive spatiotemporal package (Guan et al, 2020),…”

Section: Introductionmentioning

confidence: 99%

“…In multi‐specific large‐scale fisheries, species' distributions and their associative behaviours may change in space and time; hence disentangling seasonal or yearly dynamics and, in case of communities, isolating the key life stages of the target species and vulnerable species poses a great challenge to managers (Hilborn et al, 2021). To overcome the difficulties posed by the spatiotemporal dimension and the multi‐specific characteristic of many fisheries, scientists have used different methods, including generalized linear mixed models (Kai et al, 2017), Bayesian modelling (Paradinas et al, 2015; Quiroz & Prates, 2018), joint dynamic species distribution models implemented in the vector autoregressive spatiotemporal package (Guan et al, 2020), Poisson‐link delta models (Grüss et al, 2019) or spatially explicit age‐structured ecosystem models (Sibert et al, 2012). Such models are highly complex and require technical skills and consequential decisions from the users.…”

Section: Introductionmentioning

confidence: 99%

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Multi‐species hotspots detection using self‐organizing maps: Simulation and application to purse seine tuna fisheries management

et al. 2022

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1. To fulfil fisheries management objectives that often include implementing the precautionary and ecosystem-based approaches, multispecies fisheries data need to be analysed. Amongst the different methods dealing with these multidimensional data, self-organizing maps (SOMs) remain rarely used, although they are highly flexible in data input and offer visualization possibilities particularly suited to summarize complex datasets.2. Here, we propose to combine SOMs with a clustering approach to break down data complexity and produce simple geographic maps showing catch hotspots, which can indicate sensitive zones in terms of fishery management. To promote this approach, we tested it first on simulated datasets and then on the openaccess ICCAT commercial catch database of the tropical tuna fisheries of the Atlantic Ocean. We aimed to detect drifting fish aggregating devices (dFADs) catch hotspots of juveniles of two tuna species, bigeye and yellowfin tunas and of the silky shark, a commonly bycaught vulnerable shark species, in tropical tuna purse seine fisheries. Simulations on datasets increasing in complexity (in number, geographic and duration extent of the hotspots and number of species in the analysis) informed us about the method's sensitivity and limits.3. Our findings showed that, in the context of multi-specific fisheries, the detection of the hotspot is dependent on a certain level of catch within the hotspot and that adding species to the analysis tended to mask small and short-duration hotspots. Applied to tropical tuna fisheries' data, the method confirmed the empirical knowledge on which first time-area closures were based and provided scientifical support. 4. All in all, the visual support provided by the method, its interpretability and its potential transferability to other fisheries' systems constitute its main strengths and imply a possible implementation in management decisions; specifically, as a tool to reach agreement between stakeholders in the definition of regulated areas for protecting juveniles of tunas and vulnerable associated species to dFAD practices.

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Section: Discussionmentioning

confidence: 99%

Section: Potential For Fisheries Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi‐species hotspots detection using self‐organizing maps: Simulation and application to purse seine tuna fisheries management

et al. 2022

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“…The Bohai Strait and associated Bohai and Yellow seas constitute an important marine ecosystem that has relatively high flow exchange and supports feeding grounds and a passage corridor for fish migration (Guan et al 2020). Recent investigations have reported a declining trend in multiple fishery stocks (Barman et al 2020).…”

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confidence: 99%

Examining Epibenthic Assemblages Associated with Artificial Reefs Using a Species Archetype Approach

Fang

Rose

et al. 2022

Mar Coast Fish

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The placement of artificial reefs (ARs) influences, to various degrees, a wide range of epibenthic species, whereas most assessments focus on target or focal species. Methods of capturing the responses of many species can inform management about the full range of likely responses of species to the location and arrangement of ARs. Performing many single‐species analyses presents difficulties in interpretation. We used monitoring data from 14 surveys from June 2017 to August 2020 in an area with ARs deployed in the Bohai Sea, China. Both trap and visual census data were collected, and a suite of environmental variables was also collected or estimated for sampled sites and for spatial cells throughout the study area. The data were used to fit a species archetype model (SAM) that relies on the shared responses of species to environmental variables. The many species were grouped into six distinct archetypes. Species membership in the archetypes was confirmed by comparing results to the isometric feature mapping and partitioning around medoids (ISOPAM) approach, which relied on species co‐occurrence applied to the same data. The SAM results were also validated by comparing archetypes determined with fitting to predictions from a single survey that was not used in fitting. The six archetypes identified by the SAM had member species that differed in dependence on substrate types, distance to the nearest AR, distance to the nearest gravel, temperature, dissolved oxygen, time since AR deployment, and sampling method. The importance of the environmental variables was assessed by computing the changes in predicted occurrence probabilities of the archetypes when environmental variables were varied with the other environmental variables set at their minimum, mean, maximum, or optimal values. Species archetype modeling provides a valuable approach for predicting occurrence probabilities of epibenthic species assemblages in response to the locations and arrangement of ARs, and results can inform management related to fishing enhancement and conservation.

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Ensemble projections of fish distribution in response to climate changes in the Yellow and Bohai Seas, China

Chen

Shan

Gorfine

et al. 2023

Ecological Indicators

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Evaluating spatio-temporal dynamics of multiple fisheries-targeted populations simultaneously: A case study of the Bohai Sea ecosystem in China

Cited by 6 publications

References 28 publications

Multi‐species hotspots detection using self‐organizing maps: Simulation and application to purse seine tuna fisheries management

Multi‐species hotspots detection using self‐organizing maps: Simulation and application to purse seine tuna fisheries management

Examining Epibenthic Assemblages Associated with Artificial Reefs Using a Species Archetype Approach

Ensemble projections of fish distribution in response to climate changes in the Yellow and Bohai Seas, China

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