@article{pennino_discard_2020,

title = {Discard ban: A simulation-based approach combining hierarchical Bayesian and food web spatial models},

author = {M. Grazia Pennino and A. H. Bevilacqua and M. Angeles Torres and J. M. Bellido and J. Sole and J. Steenbeek and M. Coll},

url = {https://www.sciencedirect.com/science/article/pii/S0308597X18307954},

doi = {10.1016/j.marpol.2019.103703},

issn = {0308-597X},

year  = {2020},

date = {2020-06-01},

urldate = {2020-06-01},

journal = {Marine Policy},

volume = {116},

pages = {103703},

keywords = {Bayesian model, Discards, Ecospace, Food web model, Landing obligation, Mediterranean Sea, spatial ecology},

pubstate = {published},

tppubtype = {article}

}

@article{penninoDiscardBanSimulationbased2020,

title = {Discard Ban: A Simulation-Based Approach Combining Hierarchical Bayesian and Food Web Spatial Models},

author = {Maria Grazia Pennino and Ana Helena Bevilacqua and M. Angeles Torres and Jose M. Bellido and Jordi Sole and Jeroen Steenbeek and Marta Coll},

doi = {10.1016/j.marpol.2019.103703},

issn = {0308-597X},

year  = {2020},

date = {2020-06-01},

urldate = {2021-02-10},

journal = {Marine Policy},

volume = {116},

pages = {103703},

abstract = {Discarding is one of the most important topics in fisheries management, both for economic and ecological reasons. The European Union has included, through the current EU Common Fisheries Policy (CFP) Regulation, a discard ban with a quite controversial instrument: to enforce the landing of unwanted catch as a measure to promote their reduction. This management decision may condition the future of the fishing exploitation in European Sea. Within this context, both stakeholders and policy makers are now claiming for more effective tools that can be used to support the decision-making framework. In this study, we propose a simulation-based approach combining hierarchical Bayesian Spatial Models (H-BSMs) with the spatial-temporal module of Ecopath with Ecosim (EwE) approach, Ecospace, in the North Western Mediterranean Sea. In particular, we firstly assessed high-density discard areas using H-BSMs with fisheries and environmental data, and secondly, we simulated potential management options to identify the trade-offs of the discard ban application within these areas using EwE. We argue that coupling novel methods, as the ones used in this study, could be a decisive step to identify the best management action among a set of different scenarios within the context of the discard ban application in European Seas.},

keywords = {Bayesian model, Discards, Ecospace, Food web model, Landing obligation, Mediterranean Sea, spatial ecology},

pubstate = {published},

tppubtype = {article}

}

@article{coll_predicting_2019,

title = {Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches},

author = {M. Coll and M. Grazia-Pennino and J. Steenbeek and J. Sole and J. M. Bellido},

url = {http://www.sciencedirect.com/science/article/pii/S030438001930170X},

doi = {10.1016/j.ecolmodel.2019.05.005},

issn = {0304-3800},

year  = {2019},

date = {2019-08-01},

urldate = {2019-08-01},

journal = {Ecological Modelling},

volume = {405},

pages = {86--101},

abstract = {The spatial prediction of species distributions from survey data is a significant component of spatial planning and the ecosystem-based management approach to marine resources. Statistical analysis of species occurrences and their relationships with associated environmental factors is used to predict how likely a species is to occur in unsampled locations as well as future conditions. However, it is known that environmental factors alone may not be sufficient to account for species distribution. Other ecological processes including species interactions (such as competition and predation), and the impact of human activities, may affect the spatial arrangement of a species. Novel techniques have been developed to take a more holistic approach to estimating species distributions, such as Bayesian Hierarchical Species Distribution model (B-HSD model) and mechanistic food-web models using the new Ecospace Habitat Foraging Capacity model (E-HFC model). Here we used both species distribution and spatial food-web models to predict the distribution of European hake (Merluccius merluccius), anglerfishes (Lophius piscatorius and L. budegassa) and red mullets (Mullus barbatus and M. surmuletus) in an exploited marine ecosystem of the Northwestern Mediterranean Sea. We explored the complementarity of both approaches, comparing results of food-web models previously informed with species distribution modelling results, aside from their applicability as independent techniques. The study shows that both modelling results are positively and significantly correlated with observational data. Predicted spatial patterns of biomasses show positive and significant correlations between modelling approaches and are more similar when using both methodologies in a complementary way: when using the E-HFC model previously informed with the environmental envelopes obtained from the B-HSD model outputs, or directly using niche calculations from B-HSD models to drive the niche priors of E-HFC. We discuss advantages, limitations and future developments of both modelling techniques.},

keywords = {Bayesian model, Ecospace, fisheries, food web, Mediterranean Sea, model interoperability, regional study, spatial ecology, species distributions},

pubstate = {published},

tppubtype = {article}

}

@article{collPredictingMarineSpecies2019,

title = {Predicting Marine Species Distributions: Complementarity of Food-Web and Bayesian Hierarchical Modelling Approaches},

author = {M. Coll and M. Grazia Pennino and J. Steenbeek and J. Sole and J. M. Bellido},

doi = {10.1016/j.ecolmodel.2019.05.005},

issn = {0304-3800},

year  = {2019},

date = {2019-08-01},

urldate = {2019-11-25},

journal = {Ecological Modelling},

volume = {405},

pages = {86\textendash101},

abstract = {The spatial prediction of species distributions from survey data is a significant component of spatial planning and the ecosystem-based management approach to marine resources. Statistical analysis of species occurrences and their relationships with associated environmental factors is used to predict how likely a species is to occur in unsampled locations as well as future conditions. However, it is known that environmental factors alone may not be sufficient to account for species distribution. Other ecological processes including species interactions (such as competition and predation), and the impact of human activities, may affect the spatial arrangement of a species. Novel techniques have been developed to take a more holistic approach to estimating species distributions, such as Bayesian Hierarchical Species Distribution model (B-HSD model) and mechanistic food-web models using the new Ecospace Habitat Foraging Capacity model (E-HFC model). Here we used both species distribution and spatial food-web models to predict the distribution of European hake (Merluccius merluccius), anglerfishes (Lophius piscatorius and L. budegassa) and red mullets (Mullus barbatus and M. surmuletus) in an exploited marine ecosystem of the Northwestern Mediterranean Sea. We explored the complementarity of both approaches, comparing results of food-web models previously informed with species distribution modelling results, aside from their applicability as independent techniques. The study shows that both modelling results are positively and significantly correlated with observational data. Predicted spatial patterns of biomasses show positive and significant correlations between modelling approaches and are more similar when using both methodologies in a complementary way: when using the E-HFC model previously informed with the environmental envelopes obtained from the B-HSD model outputs, or directly using niche calculations from B-HSD models to drive the niche priors of E-HFC. We discuss advantages, limitations and future developments of both modelling techniques.},

keywords = {Bayesian model, Commercial species, Ecospace, Food-web model, Mediterranean Sea, spatial ecology, Species distribution models},

pubstate = {published},

tppubtype = {article}

}