A spatial method to calculate small-scale fisheries effort in data poor scenarios

Johnson, Andrew F.; Moreno-Báez, Marcia; Girón‐Nava, Alfredo; Corominas, Julia; Erisman, Brad; Ezcurra, Exequiel; Aburto‐Oropeza, Octavio

doi:10.1371/journal.pone.0174064

Cited by 39 publications

(36 citation statements)

References 22 publications

(27 reference statements)

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“…For example, it is estimated that 85% of GOC fisheries are either at their maximum sustainable yield or overexploited (Cisneros-Mata 2010), and there are twice as many pangas than needed to land the theoretical maximum fish biomass (Johnson et al 2017). Currently, only * 7% of the GOC is under some form of protection in Marine Protected Areas (MPAs, clearly defined geographical spaces, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature and associated ecosystem services and cultural values: Dudley 2008).…”

Section: Study Areamentioning

confidence: 99%

“…Given that fishing pressure is high (Cisneros-Mata 2010; Johnson et al 2017) and current fisheries management tools have not been sufficient (Rife et al 2013), marine reserves in the GOC should include 30% of each major habitat type within each The effects of changes in climate and ocean chemistry (increased sea temperature, ocean acidification and sea level), and the resilience of marine habitats and species to these changes will vary regionally within the GOC Fisheries production will likely decrease, due to similar effects observed during ENSO events Climate change will likely reduce the biomass of some trophic or taxonomic groups and restructure food webs Climate change will likely affect biological interactions between species through changes in their distribution, life history and connectivity Some species ranges may contract or shift to the Northern GOC and the Pacific coast of Baja California…”

Section: Representationmentioning

confidence: 99%

“…7c). A recent publication provided a similar spatial distribution of fishing pressure calculated as a function of the spatial pattern of human population density and boat density (Johnson et al 2017). To maximise the benefits for biodiversity conservation and fisheries management in the GOC, we recommend protecting areas in marine reserves where habitats and populations are likely to be in the best condition both now and in the future (reviewed in Green et al 2014) by: avoiding establishing reserves in areas with local anthropogenic threats that cannot be controlled within the reserve (e.g.…”

Section: Considering Threats and Opportunitiesmentioning

confidence: 99%

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Ecological guidelines for designing networks of marine reserves in the unique biophysical environment of the Gulf of California

Munguía‐Vega

Green

Suárez-Castillo³

et al. 2018

Rev Fish Biol Fisheries

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No-take marine reserves can be powerful management tools, but only if they are well designed and effectively managed. We review how ecological guidelines for improving marine reserve design can be adapted based on an area's unique evolutionary, oceanic, and ecological characteristics in the Gulf of California, Mexico. We provide ecological guidelines to maximize benefits for fisheries management, biodiversity conservation and climate change adaptation. These guidelines include: representing 30% of each major habitat (and multiple examples of each) in marine reserves within each of three biogeographic subregions; protecting critical areas in the life cycle of focal species (spawning and nursery areas) and sites with unique biodiversity; and establishing reserves in areas where local threats can be managed effectively. Given that strong, asymmetric oceanic currents reverse direction twice a year, to maximize 123Rev Fish Biol Fisheries (2018) 28:749-776 https://doi.org/10.1007/s11160-018-9529-y( 0123456789().,-volV) (0123456789().,-volV)

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Section: Study Areamentioning

confidence: 99%

Section: Representationmentioning

confidence: 99%

Section: Considering Threats and Opportunitiesmentioning

confidence: 99%

See 1 more Smart Citation

Ecological guidelines for designing networks of marine reserves in the unique biophysical environment of the Gulf of California

Munguía‐Vega

Green

Suárez-Castillo³

et al. 2018

Rev Fish Biol Fisheries

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“…While there is no denial that human population growth can exert pressure on natural resources around the world (Johnson et al, 2017;McKee, Sciulli, David Fooce, & Waite, 2004;Vitousek, Mooney, Lubchenco, & Melillo, 2008), attributing all the blame to global or local population growth is simply inaccurate (Allison, 2001;Robbins, 2011). The oversimplified linear population-environment relationship is problematic (Durham, 1995;Gray & Moseley, 2005;Oldham, 2006), ignoring many other rigorously studied and well-supported factors (i.e.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing overfishing: Moving beyond Malthus for effective and equitable solutions

et al. 2017

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Inaccurate or incomplete diagnosis of the root causes of overfishing can lead to misguided and ineffective fisheries policies and programmes. The “Malthusian overfishing narrative” suggests that overfishing is driven by too many fishers chasing too few fish and that fishing effort grows proportionately to human population growth, requiring policy interventions that reduce fisher access, the number of fishers, or the human population. By neglecting other drivers of overfishing that may be more directly related to fishing pressure and provide more tangible policy levers for achieving fisheries sustainability, Malthusian overfishing relegates blame to regions of the world with high population growth rates, while consumers, corporations and political systems responsible for these other mediating drivers remain unexamined. While social–ecological systems literature has provided alternatives to the Malthusian paradigm, its focus on institutions and organized social units often fails to address fundamental issues of power and politics that have inhibited the design and implementation of effective fisheries policy. Here, we apply a political ecology lens to unpack Malthusian overfishing and, relying upon insights derived from the social sciences, reconstruct the narrative incorporating four exemplar mediating drivers: technology and innovation, resource demand and distribution, marginalization and equity, and governance and management. We argue that a more nuanced understanding of such factors will lead to effective and equitable fisheries policies and programmes, by identifying a suite of policy levers designed to address the root causes of overfishing in diverse contexts.

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“…Although great efforts have been conducted on global fisheries, data-poor situations are still prevalent, especially in developing countries (Costello et al 2012). Particularly, due to the lack of economic importance and social attention, data-poor situations are prevalent for small-scale fisheries, which often serve as forage and play a critical role in marine ecosystems (Johnson et al 2017). With the advance of ecosystem-based fisheries management, the population status of such species should be paid more attention, which calls for feasible approaches to the challenge of assessment and management for datapoor stocks.…”

mentioning

confidence: 99%

Evaluating the Performances of Size‐Frequency‐Based Methods for Estimating Fishing Mortality of Pholis fangi

et al. 2019

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Age‐structured data are commonly needed in stock assessments but are unavailable for the majority of existing fisheries, while fish size (length or weight) data are most readily accessible and carry critical information of population status. However, the performances of assessment methods based on size‐frequency data have been less well understood. This study evaluated the reliability of two size‐frequency‐based assessment methods in R package, s6model and TropFishR, for estimating the exploitation status of one data‐poor stock, Pholis fangi in Haizhou Bay, China. We used both simulation and empirical approaches to compare the performances of the two assessment methods in estimating F and Fmsy and examined their robustness to the stochasticity and amount of sampling data. In the simulation test, s6model and TropFishR yielded satisfactorily accurate and consistent estimates of F and Fmsy. In the empirical test, the estimated stock exploitation status varied substantially among seasons. TropfishR and s6model estimated the F/Fmsy to be 2.40 and 2.05 in spring, respectively, indicating remarkable overfishing, and 0.43 and 0.41 in fall, respectively, indicating an optimistic exploitation level. The reflected pattern was consistent with the fishery characteristics of this species. The s6model method was substantially influenced by sample size and might lead to unreasonable estimations in small samples, whereas TropFishR was relatively robust on the changes of sample size. This study highlighted the usefulness of size‐frequency methods in guiding fisheries management and provided references for their applications in data‐limited situations.

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A spatial method to calculate small-scale fisheries effort in data poor scenarios

Cited by 39 publications

References 22 publications

Ecological guidelines for designing networks of marine reserves in the unique biophysical environment of the Gulf of California

Ecological guidelines for designing networks of marine reserves in the unique biophysical environment of the Gulf of California

Reconstructing overfishing: Moving beyond Malthus for effective and equitable solutions

Evaluating the Performances of Size‐Frequency‐Based Methods for Estimating Fishing Mortality of Pholis fangi

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