Dataset Information

Human and climatic drivers affect spatial fishing patterns in a multiple-use marine protected area: The Galapagos Marine Reserve.

ABSTRACT: Assessments of the effectiveness of marine protected areas (MPAs) usually assume that fishing patterns change exclusively due to the implementation of an MPA. This assumption increases the risk of erroneous conclusions in assessing marine zoning, and consequently counter-productive management actions. Accordingly, it is important to understand how fishers respond to a combination of the implementation of no-take zones, and various climatic and human drivers of change. Those adaptive responses could influence the interpretation of assessment of no-take zone effectiveness, yet few studies have examined these aspects. Indeed, such analysis is often unfeasible in developing countries, due to the dominance of data-poor fisheries, which precludes full examination of the social-ecological outcomes of MPAs. In the Galapagos Marine Reserve (Ecuador), however, the availability of long-term spatially explicit fishery monitoring data (1997-2011) for the spiny lobster fishery allows such an analysis. Accordingly, we evaluated how the spatiotemporal allocation of fishing effort in this multiple-use MPA was affected by the interaction of diverse climatic and human drivers, before and after implementation of no-take zones. Geographic information system modelling techniques were used in combination with boosted regression models to identify how these drivers influenced fishers' behavior. Our results show that the boom-and-bust exploitation of the sea cucumber fishery and the global financial crisis 2007-09, rather than no-take zone implementation, were the most important drivers affecting the distribution of fishing effort across the archipelago. Both drivers triggered substantial macro-scale changes in fishing effort dynamics, which in turn altered the micro-scale dynamics of fishing patterns. Fishers' adaptive responses were identified, and their management implications analyzed. This leads to recommendations for more effective marine and fishery management in the Galapagos, based on improved assessment of the effectiveness of no-take zones.

SUBMITTER: Castrejon M

PROVIDER: S-EPMC6977758 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Human and climatic drivers affect spatial fishing patterns in a multiple-use marine protected area: The Galapagos Marine Reserve.

Castrejón Mauricio M Charles Anthony A

PloS one 20200123 1

Assessments of the effectiveness of marine protected areas (MPAs) usually assume that fishing patterns change exclusively due to the implementation of an MPA. This assumption increases the risk of erroneous conclusions in assessing marine zoning, and consequently counter-productive management actions. Accordingly, it is important to understand how fishers respond to a combination of the implementation of no-take zones, and various climatic and human drivers of change. Those adaptive responses co ...[more]

PMID: 31971982

Similar Datasets

Project description:The Galápagos Archipelago is home to a diverse range of marine bioregions due to the confluence of several cold and warm water currents, resulting in some of the most productive tropical marine ecosystems in the world. These ecosystems are strongly influenced by El Niño events which can reduce primary production by an order of magnitude, dramatically reducing energy available throughout the food web. Fisheries are an important component of the local economy, although artisanal and illegal overfishing have dramatically reduced the productivity of invertebrate and finfish resources in recent decades, resulting in reductions in catches for local fishers. The regionally-endemic sailfin grouper (Myctereoperca olfax), locally known as bacalao, was once the most important fished species in the Galápagos, but is now listed as vulnerable by the IUCN due to its limited range and dramatic declines in catch over time. It is unknown how reduction of this predatory species has affected ecosystem structure and function. In the absence of stock assessments, we used an estimate of unfished bacalao biomass from fishers' ecological knowledge along with unfished biomass estimates of other heavily exploited stocks-lobster (Panulirus penicillatus and P. gracilis) and sea cucumber (Isostichopus fuscus)-to create historical, unfished versions of existing modern day ecosystem models. We used the unfished and modern versions of the ecosystem models to test the ecosystem effects of bacalao exploitation at the Bolivar Channel, located in the cold, west upwelling bioregion of the archipelago during both El Niño and non El Niño years, and at Floreana Island, in the warmer, central bioregion. Fishers' ecological knowledge indicates that at present, the biomass of bacalao is at least seven times lower than when unfished. This reduced bacalao biomass is linked with a greatly reduced ecosystem role compared to when unfished, and ecosystem role is further reduced in El Niño years. Allowing bacalao populations to rebuild to at least half of unfished biomass would partially restore their role within these ecosystems, while also resulting in greater fisheries catches. Comparing ecosystem impacts caused by fishing and El Niño, fishing has had a greater negative impact on bacalao ecosystem role than regular El Niño events.

Project description:The waters around the Galápagos Marine Reserve (GMR) are important fishing grounds for authorized artisanal vessels fishing within the reserve as well as for national and foreign industrial fleets operating in the wider Ecuadorian Insular Exclusive Economic Zone (IEEZ). Although it was not originally designed for fisheries management, Automatic Identification System (AIS) data provides useful, open access, near real-time and high-resolution information that allows for increased monitoring, particularly around Marine Protected Areas (MPAs) and in Areas Beyond National Jurisdiction. This study uses AIS data provided by Global Fishing Watch to assess the spatial distribution and seasonal dynamics of fishing effort by vessel flag within the GMR and the IEEZ from 2012 to 2021. Based on kernel density estimation analysis, we determinate the core-use areas (50%) and spatial extent (95%) of fishing activities by fleets (Ecuadorian and foreign), gear types and seasons (warm, from December to May; and cold, from June to November). Our results show that the Ecuadorian fleet recorded the most observed fishing hours in the study area, with 32,829 hours in the IEEZ and 20,816 hours within the GMR. The foreign flags with the most observed fishing hours in the IEEZ were Panama (3,245 hours) and Nicaragua (2,468.5 hours), while in the GMR were the 'Unknown flag' (4,991.4 hours) and Panama (133.7 hours). Vessels fished employing different fishing gears, but the waters of the GMR and IEEZ were mostly targeted by tuna purse-seiners and drifting longlines. The spatial distribution of the fishing effort exhibits marked seasonal variability, likely influenced by seasonal migrations of target species such as tunas (e.g., Thunnus albacares, T. obesus and Katsuwonus pelamis), marlins (e.g., Makaira nigricans) and sharks (e.g., Alopias pelagicus). The collection and use of this type of spatial and seasonal information is an essential step to understand the dynamics of fishing activities in national waters and improve fisheries management, particularly in less studied areas and fisheries.

Project description:Boosted regression trees. excellent for data-poor spatial management but hard to useMarine resource managers and scientists often advocate spatial approaches to manage data-poor species. Existing spatial prediction and management techniques are either insufficiently robust, struggle with sparse input data, or make suboptimal use of multiple explanatory variables. Boosted Regression Trees feature excellent performance and are well suited to modelling the distribution of data-limited species, but are extremely complicated and time-consuming to learn and use, hindering access for a wide potential user base and therefore limiting uptake and usage.Brts automated and simplified for accessible general use with rich feature setWe have built a software suite in R which integrates pre-existing functions with new tailor-made functions to automate the processing and predictive mapping of species abundance data: by automating and greatly simplifying Boosted Regression Tree spatial modelling, the gbm.auto R package suite makes this powerful statistical modelling technique more accessible to potential users in the ecological and modelling communities. The package and its documentation allow the user to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables. Databases of the processed model objects and a report explaining all the steps taken within the model are also generated. The package includes a previously unavailable Decision Support Tool which combines estimated escapement biomass (the percentage of an exploited population which must be retained each year to conserve it) with the predicted abundance maps to generate maps showing the location and size of habitat that should be protected to conserve the target stocks (candidate MPAs), based on stakeholder priorities, such as the minimisation of fishing effort displacement.Gbm.auto for management in various settingsBy bridging the gap between advanced statistical methods for species distribution modelling and conservation science, management and policy, these tools can allow improved spatial abundance predictions, and therefore better management, decision-making, and conservation. Although this package was built to support spatial management of a data-limited marine elasmobranch fishery, it should be equally applicable to spatial abundance modelling, area protection, and stakeholder engagement in various scenarios.

Dataset Information

Human and climatic drivers affect spatial fishing patterns in a multiple-use marine protected area: The Galapagos Marine Reserve.

Publications

Human and climatic drivers affect spatial fishing patterns in a multiple-use marine protected area: The Galapagos Marine Reserve.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets