@article{gunner_high_2026,

title = {High resolution data reveal fundamental steps and turns in animal movements},

author = {Richard M. Gunner and Rory P. Wilson and Miguel Lurgi and Luca B\"{o}rger and James Redcliffe and Emily L. C. Shepard and Mark D. Holton and Margaret C. Crofoot and Abdulaziz Alagaili and Samantha Andrzejaczek and Daniel Ariano‐S\'{a}nchez and Thomas Barbedette‐Gerard and Nigel C. Bennett and Alice Bernard and Rowan Brown and Nik Cole and Scott Creel and Ariovaldo P. Cruz‐Neto and Agustina Di Virgilio and Carlos M. Duarte and Christophe Eizaguirre and Kyle H. Elliott and Monika Faltusova and Mathieu Garel and Natasha Gillies and Adrian C. Gleiss and Aoife G\"{o}ppert and David Gr\'{e}millet and Sophie De Grissac and Tim Guilford and Maxime Hoareau and Mark Jessopp and Agustina G\'{o}mez‐Laich and Milos Jezek and Sergio A. Lambertucci and Pascal Marchand and Nikki Marks and Andr\'{e}ia Martins and Mark Meekan and Yuichi Mizutani and Rasmus M. Mortensen and Bradley M. Norman and Josue Ortega and Oliver Padget and Michael Painter and Aurore Ponchon and Pascal Provost and Aur\'{e}lien Prudor and Flavio Quintana and Stefanie Reinhardt and Samantha D. Reynolds and Frank Rosell and Carlos R. Ruiz‐Miranda and Peter G. Ryan and David M. Scantlebury and Stefan Schoombie and Rebecca Scott and Vaclav Silovsky and Jeroen Steenbeek and Vikash Tatayah and Carole To\"{i}go and Lucia Torrez and Fred Tremblay and Joshua P. Twining and Ken Yoda and Henri Weimerskirch and Shannon Whelan and Juan M. Morales and Jonathan R. Potts},

url = {https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecm.70069},

doi = {10.1002/ecm.70069},

issn = {0012-9615, 1557-7015},

year  = {2026},

date = {2026-05-01},

urldate = {2026-05-01},

journal = {Ecological Monographs},

volume = {96},

number = {2},

pages = {e70069},

abstract = {Abstract 

 Animal movement paths display substantial complexity and variability, promoting efforts to identify universal rules and models that best describe them. Using high‐resolution (≥10 Hz) movement from 43 vertebrate species spanning diverse taxa, body sizes, and lifestyles, we show that paths are universally composed of straight‐line steps interspersed with sharp turns, echoing patterns documented in lower taxa such as bacteria. We report how vertebrate “fundamental steps”\textemdashstraight travel segments between successive detected turns (with 

 F 

 stepduration 

 as the turn‐to‐turn interval and 

 F 

 steplength 

 as the corresponding distance when displacement is available)\textemdashand “fundamental turn angles” ( 

 F 

 turnangles 

 ; net changes in travel heading between successive steps) vary with species\' mass, locomotor mode, behavior, and environment. Here, “fundamental” denotes the finest scale step/turn events resolvable under our sampling rate and turn‐detection criteria; these event‐scale steps/turns are intrinsically different from the straight‐line segments inferred from low‐resolution position data. To explain these relationships, we posit that animals inherently move in a straight line until sensory information signals a better heading, triggering a turn. Across all species examined, animals spent the vast majority of their travel time moving in straight lines (species‐level means \>90%), with turns representing discrete decision points influenced by body size, locomotor mode, and ecological context. Larger animals turned less frequently, consistent with biomechanical constraints of mass and rotational inertia, while aerial species often exhibited higher turning rates driven by soaring flight demands. We further show that turns can be linked to diverse behavioral drivers, including prey pursuit, obstacle avoidance, predator evasion, and exploitation of environmental energy. By explicitly quantifying turns, we clarify how distributions of step durations and turn angles interact to shape movement patterns and why different statistical models (e.g., correlated random walks, L\'{e}vy flights) emerge when lower resolution data are analyzed. Finally, we demonstrate how fundamental steps and turns can be incorporated into an agent‐based modeling framework using penguins as a case study, enabling reconstruction of realistic tracks and prediction of movement responses to environmental change. Straight‐line travel punctuated by decision‐driven turns thus emerges as a fundamental principle of vertebrate movement, linking fine‐scale movement structure, ecological context, and emergent patterns of space use.},

keywords = {behaviour, Ecospace, IBM, niche modelling},

pubstate = {published},

tppubtype = {article}

}

@article{coll_retrospective_2024,

title = {Retrospective analysis of the pelagic ecosystem of the Western Mediterranean Sea: drivers, changes and effects},

author = {Marta Coll and Jos\'{e} Mar\'{i}a Bellido and Maria Grazia Pennino and Marta Albo-Puigserver and Jos\'{e} Carlos B\'{a}ez and Villy Christensen and Xavier Corrales and Elena Fern\'{a}ndez-Corredor and Joan Gim\'{e}nez and Laura Juli\`{a} and Elena Lloret-Lloret and Diego Macias and Jazel Ouled-Cheikh and F Ramirez and Valerio Sbragaglia and Jeroen Steenbeek},

url = {https://www.sciencedirect.com/science/article/pii/S0048969723064173?casa_token=NLXcFSCgZLEAAAAA:1mB2JzHY1-MT6gNLHKYCyRGOGiaBBAiNMoJW3r3cFjQskSyueeXcQOyeUwsKNSTiHFLfSos0V5k},

doi = {10.1016/j.scitotenv.2023.167790},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-31},

journal = {Science of The Total Environment},

volume = {907},

pages = {167790},

publisher = {Elsevier},

note = {Publisher: Elsevier},

keywords = {Ecospace, Mediterranean Sea},

pubstate = {published},

tppubtype = {article}

}

@article{eddy_global_2024,

title = {Global and regional marine ecosystem model climate change projections reveal key uncertainties},

author = {Tyler D. Eddy and Ryan F. Heneghan and Andrea Bryndum-Buchholz and Beth Fulton and Cheryl Shannon Harrison and Derek P. Tittensor and Heike K. Lotze and Kelly Ortega-Cisneros and Camilla Novaglio and Daniele Bianchi},

url = {https://hal.science/hal-04811335/},

year  = {2024},

date = {2024-01-01},

urldate = {2025-01-08},

keywords = {EcoOcean, Ecospace, FishMIP},

pubstate = {published},

tppubtype = {article}

}

@article{angelini_projected_2024,

title = {The projected impacts of climate change and fishing pressure on a tropical marine food web},

author = {Ronaldo Angelini and Maria Alice Leite Lima and Alex Souza Lira and Fl\'{a}via Lucena-Fr\'{e}dou and Thierry Fr\'{e}dou and Arnaud Bertrand and Tommaso Giarrizzo and Jeroen Steenbeek and Marta Coll and Friedrich Wolfgang Keppeler},

url = {https://www.sciencedirect.com/science/article/pii/S0141113624005701},

year  = {2024},

date = {2024-01-01},

urldate = {2025-01-08},

journal = {Marine Environmental Research},

pages = {106909},

publisher = {Elsevier},

note = {Publisher: Elsevier},

keywords = {Brazil, Ecospace, fisheries},

pubstate = {published},

tppubtype = {article}

}

@article{mutsert_advances_2024,

title = {Advances in spatial-temporal coastal and marine ecosystem modeling using Ecospace},

author = {Kim de Mutsert and Marta Coll and Jeroen Steenbeek and Cameron Ainsworth and Joe Buszowski and David Chagaris and Villy Christensen and Sheila JJ Heymans and Kristy A. Lewis and Simone Libralato},

url = {https://digital.csic.es/handle/10261/329496},

year  = {2024},

date = {2024-01-01},

urldate = {2025-01-08},

publisher = {Elsevier},

note = {Publisher: Elsevier},

keywords = {Ecospace},

pubstate = {published},

tppubtype = {article}

}

@article{stock_exploring_2023,

title = {Exploring multiple stressor effects with Ecopath, Ecosim, and Ecospace: Research designs, modeling techniques, and future directions},

author = {Andy Stock and Cathryn C. Murray and Edward J Gregr and Jeroen Steenbeek and Emie Woodburn and Fiorenza Micheli and Villy Christensen and Kai M. A. Chan},

url = {https://osf.io/rfghy},

doi = {10.1016/j.scitotenv.2023.161719},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-17},

abstract = {Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change \textendash except for fisheries \textendash were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors’ direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics.},

keywords = {Cumulative effects assessment, Cumulative impact assessment, Ecospace},

pubstate = {published},

tppubtype = {article}

}

@article{sadchatheeswaranNovelApproachExplicitly2021,

title = {A Novel Approach to Explicitly Model the Spatiotemporal Impacts of Structural Complexity Created by Alien Ecosystem Engineers in a Marine Benthic Environment},

author = {Saachi Sadchatheeswaran and George M. Branch and Lynne J. Shannon and Marta Coll and Jeroen Steenbeek},

doi = {10.1016/j.ecolmodel.2021.109731},

issn = {0304-3800},

year  = {2021},

date = {2021-11-01},

urldate = {2021-09-22},

journal = {Ecological Modelling},

volume = {459},

pages = {109731},

abstract = {In a prequel to this paper, we used non-spatial temporal modelling to investigate the impact of non-native ecosystem engineers on a small-scale, intertidal rocky shore in Saldanha Bay, on the west coast of South Africa, where invasive species have changed the physical environment between 1980 and 2015. However, we considered this approach incomplete without the direct inclusion of spatial modelling and zonation. To address this, we compared multiple, layered simulations employing the food-web approach of Ecospace, the spatial-temporal module of Ecopath with Ecosim (EwE). Our simulations included a control; a simulation that restricted drivers to depth and habitat preferences; two simulations to account for structural complexity as a function of the biomass of alien ecosystem engineers \textendash the first indirectly via mediation, and the second via a novel plug-in `Ecoengineer' \textendash and lastly the inclusion of wave action to replicate its effects. Only the simulation that included the Ecoengineer routine matched empirical observations of species diversity indices and the exclusion of the native mussel~Choromytilus meridionalis~by the arriving alien~Mytilus galloprovincialis. Inclusion of mediation did not differ from the model simulation that used only habitat preference and depth to drive the model, and the addition of wave action did not improve model fits.~Our results emphasise that when analysing intertidal ecosystems, they should be modelled with an explicit representation of structural~habitat~complexity over time and space, and we consider that~the~application of our Ecoengineer plug-in is~an~effective~and novel~way of accomplishing this.},

keywords = {Ecoengineer, Ecopath with Ecosim, Ecospace, Ecosystem engineer, Intertidal, Invasive},

pubstate = {published},

tppubtype = {article}

}

@article{sadchatheeswaran_novel_2021,

title = {A novel approach to explicitly model the spatiotemporal impacts of structural complexity created by alien ecosystem engineers in a marine benthic environment},

author = {Saachi Sadchatheeswaran and George M. Branch and Lynne J. Shannon and Marta Coll and Jeroen Steenbeek},

url = {https://www.sciencedirect.com/science/article/pii/S0304380021002830},

doi = {10.1016/j.ecolmodel.2021.109731},

issn = {0304-3800},

year  = {2021},

date = {2021-11-01},

urldate = {2021-09-22},

journal = {Ecological Modelling},

volume = {459},

pages = {109731},

abstract = {In a prequel to this paper, we used non-spatial temporal modelling to investigate the impact of non-native ecosystem engineers on a small-scale, intertidal rocky shore in Saldanha Bay, on the west coast of South Africa, where invasive species have changed the physical environment between 1980 and 2015. However, we considered this approach incomplete without the direct inclusion of spatial modelling and zonation. To address this, we compared multiple, layered simulations employing the food-web approach of Ecospace, the spatial-temporal module of Ecopath with Ecosim (EwE). Our simulations included a control; a simulation that restricted drivers to depth and habitat preferences; two simulations to account for structural complexity as a function of the biomass of alien ecosystem engineers \textendash the first indirectly via mediation, and the second via a novel plug-in ‘Ecoengineer’ \textendash and lastly the inclusion of wave action to replicate its effects. Only the simulation that included the Ecoengineer routine matched empirical observations of species diversity indices and the exclusion of the native mussel Choromytilus meridionalis by the arriving alien Mytilus galloprovincialis. Inclusion of mediation did not differ from the model simulation that used only habitat preference and depth to drive the model, and the addition of wave action did not improve model fits. Our results emphasise that when analysing intertidal ecosystems, they should be modelled with an explicit representation of structural habitat complexity over time and space, and we consider that the application of our Ecoengineer plug-in is an effective and novel way of accomplishing this.},

keywords = {Ecoengineer, Ecopath with Ecosim, Ecospace, Ecosystem engineer, Intertidal, Invasive},

pubstate = {published},

tppubtype = {article}

}

@article{serpettiModelingSmallScale2021,

title = {Modeling Small Scale Impacts of Multi-Purpose Platforms: An Ecosystem Approach},

author = {Natalia Serpetti and Steven Benjamins and Stevie Brain and Maurizio Collu and Bethany J. Harvey and Johanna J. Heymans and Adam D. Hughes and Denise Risch and Sophia Rosinski and James J. Waggitt and Ben Wilson},

doi = {10.3389/fmars.2021.694013},

issn = {2296-7745},

year  = {2021},

date = {2021-01-01},

urldate = {2021-07-25},

journal = {Frontiers in Marine Science},

volume = {0},

publisher = {Frontiers},

abstract = {Aquaculture and marine renewable energy are two expanding sectors of the Blue Economy in Europe. Assessing the long-term environmental impacts in terms of eutrophication and noise is a priority for both the EU Water Framework Directive and the Marine Strategy Framework Directive, and cumulative impacts will be important for the Maritime Spatial Planning under the Integrated Maritime Policy. With the constant expansion of aquaculture production, it is expected that farms might be established further offshore in more remote areas, as high-energy conditions offer an opportunity to generate more power locally using Marine Renewable Energy (MRE) devices. A proposed solution is the co-location of MRE devices and aquaculture systems using Multi-Purpose Platforms (MPPs) comprising offshore wind turbines (OWTs) that will provide energy for farm operations as well as potentially shelter the farm. Disentangling the impacts, conflicts and synergies of MPP elements on the surrounding marine ecosystem is challenging. Here we created a high-resolution spatiotemporal Ecospace model of the West of Scotland, in order to assess impacts of a simple MPP configuration on the surrounding ecosystem and how these impacts can cascade through the food web. The model evaluated the following specific ecosystem responses: i) top-down control pathways due to distribution changes among top-predators (harbour porpoise, gadoids and seabirds) driven by attraction to the farming sites and/or repulsion/killing due to OWT operations; ii) bottom-up control pathways due to salmon farm activity providing increasing benthic enrichment predicated by a fish farm particle dispersal model, and sediment nutrient fluxes to the water column by early diagenesis of organic matter (recycled production). Weak responses of the food-web were found for top-down changes, whilst the results showed high sensitivity to increasing changes of bottom-up drivers that cascaded through the food-web from primary producers and detritus to pelagic and benthic consumers respectively. We assessed the sensitivity of the model to each of these impacts and the cumulative effects on the ecosystem, discuss the capabilities and limitations of the Ecospace modelling approach as a potential tool for marine spatial planning and the impact that these results could have for the Blue Economy and the EU's New Green Deal.},

keywords = {aquaculture, Ecopath with Ecosim, Ecospace, Marine renewable energy, Marine Strategy Framework Directive, Maritime spatial planning, Multi purpose platform, Offshore wind, West coast of Scotland},

pubstate = {published},

tppubtype = {article}

}

@article{serpetti_modeling_2021,

title = {Modeling Small Scale Impacts of Multi-Purpose Platforms: An Ecosystem Approach},

author = {Natalia Serpetti and Steven Benjamins and Stevie Brain and Maurizio Collu and Bethany J. Harvey and Johanna J. Heymans and Adam D. Hughes and Denise Risch and Sophia Rosinski and James J. Waggitt and Ben Wilson},

url = {https://www.frontiersin.org/articles/10.3389/fmars.2021.694013/full},

doi = {10.3389/fmars.2021.694013},

issn = {2296-7745},

year  = {2021},

date = {2021-01-01},

urldate = {2021-07-25},

journal = {Frontiers in Marine Science},

volume = {0},

publisher = {Frontiers},

abstract = {Aquaculture and marine renewable energy are two expanding sectors of the Blue Economy in Europe. Assessing the long-term environmental impacts in terms of eutrophication and noise is a priority for both the EU Water Framework Directive and the Marine Strategy Framework Directive, and cumulative impacts will be important for the Maritime Spatial Planning under the Integrated Maritime Policy. With the constant expansion of aquaculture production, it is expected that farms might be established further offshore in more remote areas, as high-energy conditions offer an opportunity to generate more power locally using Marine Renewable Energy (MRE) devices. A proposed solution is the co-location of MRE devices and aquaculture systems using Multi-Purpose Platforms (MPPs) comprising offshore wind turbines (OWTs) that will provide energy for farm operations as well as potentially shelter the farm. Disentangling the impacts, conflicts and synergies of MPP elements on the surrounding marine ecosystem is challenging. Here we created a high-resolution spatiotemporal Ecospace model of the West of Scotland, in order to assess impacts of a simple MPP configuration on the surrounding ecosystem and how these impacts can cascade through the food web. The model evaluated the following specific ecosystem responses: i) top-down control pathways due to distribution changes among top-predators (harbour porpoise, gadoids and seabirds) driven by attraction to the farming sites and/or repulsion/killing due to OWT operations; ii) bottom-up control pathways due to salmon farm activity providing increasing benthic enrichment predicated by a fish farm particle dispersal model, and sediment nutrient fluxes to the water column by early diagenesis of organic matter (recycled production). Weak responses of the food-web were found for top-down changes, whilst the results showed high sensitivity to increasing changes of bottom-up drivers that cascaded through the food-web from primary producers and detritus to pelagic and benthic consumers respectively. We assessed the sensitivity of the model to each of these impacts and the cumulative effects on the ecosystem, discuss the capabilities and limitations of the Ecospace modelling approach as a potential tool for marine spatial planning and the impact that these results could have for the Blue Economy and the EU’s New Green Deal.},

keywords = {aquaculture, Ecopath with Ecosim, Ecospace, Marine renewable energy, Marine Strategy Framework Directive, Maritime spatial planning, Multi purpose platform, Offshore wind, West coast of Scotland},

pubstate = {published},

tppubtype = {article}

}

@article{puts_insights_2020b,

title = {Insights on integrating habitat preferences in process-oriented ecological models \textendash a case study of the southern North Sea},

author = {M. P\"{u}ts and M. Taylor and I. N\'{u}\~{n}ez-Riboni and J. Steenbeek and M. St\"{a}bler and C. M\"{o}llmann and A. Kempf},

url = {http://www.sciencedirect.com/science/article/pii/S030438002030260X},

doi = {10.1016/j.ecolmodel.2020.109189},

issn = {0304-3800},

year  = {2020},

date = {2020-09-01},

urldate = {2020-09-01},

journal = {Ecological Modelling},

volume = {431},

pages = {109189},

keywords = {Ecopath with Ecosim, Ecospace, Food web model, Habitat capacity, Spatial-temporal framework, species distribution model},

pubstate = {published},

tppubtype = {article}

}

@article{putsInsightsIntegratingHabitat2020,

title = {Insights on Integrating Habitat Preferences in Process-Oriented Ecological Models \textendash a Case Study of the Southern North Sea},

author = {Miriam P\"{u}ts and Marc Taylor and Ismael N\'{u}\~{n}ez-Riboni and Jeroen Steenbeek and Moritz St\"{a}bler and Christian M\"{o}llmann and Alexander Kempf},

doi = {10.1016/j.ecolmodel.2020.109189},

issn = {0304-3800},

year  = {2020},

date = {2020-09-01},

urldate = {2020-06-30},

journal = {Ecological Modelling},

volume = {431},

pages = {109189},

abstract = {One of the most applied tools to create ecosystem models to support management decisions in the light of ecosystem-based fisheries management is Ecopath with Ecosim (EwE). Recently, its spatial routine Ecospace has evolved due to the addition of the Habitat Foraging Capacity Model (HFCM), a spatial-temporal dynamic niche model to drive the foraging capacity to distribute biomass over model grid cells. The HFCM allows for continuous implementation of externally derived habitat preference maps based on single species distribution models. So far, guidelines are lacking on how to best define habitat preferences for inclusion in process-oriented trophic modeling studies. As one of the first studies, we applied the newest Ecospace development to an existing EwE model of the southern North Sea with the aim to identify which definition of habitat preference leads to the best model fit. Another key aim of our study was to test for the sensitivity of implementing externally derived habitat preference maps within Ecospace to different time-scales (seasonal, yearly, multi-year, and static). For this purpose, generalized additive models (GAM) were fit to scientific survey data using either presence/absence or abundance as differing criteria of habitat preference. Our results show that Ecospace runs using habitat preference maps based on presence/absence data compared best to empirical data. The optimal time-scale for habitat updating differed for biomass and catch, but implementing variable habitats was generally superior to a static habitat representation. Our study hence highlights the importance of a sigmoidal representation of habitat (e.g. presence/absence) and variable habitat preferences (e.g. multi-year) when combining species distribution models with an ecosystem model. It demonstrates that the interpretation of habitat preference can have a major influence on the model fit and outcome.},

keywords = {Ecopath with Ecosim, Ecospace, Food web model, Habitat capacity, Spatial-temporal framework, species distribution model},

pubstate = {published},

tppubtype = {article}

}

@article{puts_insights_2020,

title = {Insights on integrating habitat preferences in process-oriented ecological models \textendash a case study of the southern North Sea},

author = {Miriam P\"{u}ts and Marc Taylor and Ismael N\'{u}\~{n}ez-Riboni and Jeroen Steenbeek and Moritz St\"{a}bler and Christian M\"{o}llmann and Alexander Kempf},

url = {http://www.sciencedirect.com/science/article/pii/S030438002030260X},

doi = {10.1016/j.ecolmodel.2020.109189},

issn = {0304-3800},

year  = {2020},

date = {2020-09-01},

urldate = {2020-06-30},

journal = {Ecological Modelling},

volume = {431},

pages = {109189},

abstract = {One of the most applied tools to create ecosystem models to support management decisions in the light of ecosystem-based fisheries management is Ecopath with Ecosim (EwE). Recently, its spatial routine Ecospace has evolved due to the addition of the Habitat Foraging Capacity Model (HFCM), a spatial-temporal dynamic niche model to drive the foraging capacity to distribute biomass over model grid cells. The HFCM allows for continuous implementation of externally derived habitat preference maps based on single species distribution models. So far, guidelines are lacking on how to best define habitat preferences for inclusion in process-oriented trophic modeling studies. As one of the first studies, we applied the newest Ecospace development to an existing EwE model of the southern North Sea with the aim to identify which definition of habitat preference leads to the best model fit. Another key aim of our study was to test for the sensitivity of implementing externally derived habitat preference maps within Ecospace to different time-scales (seasonal, yearly, multi-year, and static). For this purpose, generalized additive models (GAM) were fit to scientific survey data using either presence/absence or abundance as differing criteria of habitat preference. Our results show that Ecospace runs using habitat preference maps based on presence/absence data compared best to empirical data. The optimal time-scale for habitat updating differed for biomass and catch, but implementing variable habitats was generally superior to a static habitat representation. Our study hence highlights the importance of a sigmoidal representation of habitat (e.g. presence/absence) and variable habitat preferences (e.g. multi-year) when combining species distribution models with an ecosystem model. It demonstrates that the interpretation of habitat preference can have a major influence on the model fit and outcome.},

keywords = {Ecopath with Ecosim, Ecospace, Food web model, Habitat capacity, Spatial-temporal framework, species distribution model},

pubstate = {published},

tppubtype = {article}

}

@article{steenbeek_combining_2020b,

title = {Combining ecosystem modeling with serious gaming in support of transboundary maritime spatial planning},

author = {J. Steenbeek and G. Romagnoni and J. W. Bentley and J. J. Heymans and N. Serpetti and M. Gon\c{c}alves and C. Santos and H. Warmelink and I. Mayer and X. Keijser and R. Fairgrieve and L. Abspoel},

url = {https://www.ecologyandsociety.org/vol25/iss2/art21/},

doi = {10.5751/ES-11580-250221},

issn = {1708-3087},

year  = {2020},

date = {2020-06-01},

urldate = {2020-06-01},

journal = {Ecology and Society},

volume = {25},

number = {2},

note = {Publisher: The Resilience Alliance},

keywords = {Ecospace, Ocean Decade, science-policy interface, serious gaming, stakeholder involvement},

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{pennino_discard_2020,

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},

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 = {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{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}

}

@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 = {2019-11-25},

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}

}

@article{coll_standardized_2017b,

title = {Standardized ecological indicators to assess aquatic food webs: The ECOIND software plug-in for Ecopath with Ecosim models},

author = {M. Coll and J. Steenbeek},

url = {http://www.sciencedirect.com/science/article/pii/S1364815216311173},

doi = {10.1016/j.envsoft.2016.12.004},

issn = {1364-8152},

year  = {2017},

date = {2017-03-01},

urldate = {2017-01-03},

journal = {Environmental Modelling \& Software},

volume = {89},

pages = {120--130},

keywords = {Ecological standardized indicators, Ecopath with Ecosim, Ecospace, Environmental status, Food web models, Software plug-in},

pubstate = {published},

tppubtype = {article}

}

@article{collStandardizedEcologicalIndicators2017,

title = {Standardized Ecological Indicators to Assess Aquatic Food Webs: The ECOIND Software Plug-in for Ecopath with Ecosim Models},

author = {M Coll and J Steenbeek},

year  = {2017},

date = {2017-01-01},

journal = {Environmental Modelling and Software},

volume = {89},

pages = {120\textendash130},

keywords = {Ecological standardized indicators, Ecopath with Ecosim, Ecospace, Environmental status, Food web models, Software plug-in},

pubstate = {published},

tppubtype = {article}

}

@article{coll_standardized_2017,

title = {Standardized ecological indicators to assess aquatic food webs: the ECOIND software plug-in for Ecopath with Ecosim models},

author = {M Coll and J Steenbeek},

url = {http://www.sciencedirect.com/science/article/pii/S1364815216311173},

doi = {10.1016/j.envsoft.2016.12.004},

year  = {2017},

date = {2017-01-01},

urldate = {2017-01-03},

journal = {Environmental Modelling and Software},

volume = {89},

pages = {120\textendash130},

abstract = {Ecological indicators are useful tools to analyse and communicate historical changes in ecosystems and plausible future scenarios while evaluating environmental status. Here we introduce a new plug-in to the Ecopath with Ecosim (EwE) food web modelling approach, which is widely used to quantitatively describe aquatic ecosystems. The plug-in (ECOIND) calculates standardized ecological indicators. We describe the primary functionality of ECOIND and provide an example of its application in both static and temporal-spatial dynamic modelling, while we highlight several related features including a new taxonomy input database (species traits) and the ability to analyse input uncertainty on output results. ECOIND adds new capabilities to the widely used EwE food web modelling approach and enables broadening its applications into biodiversity and conservation-based frameworks to contribute to integrated ecosystem analyses.},

keywords = {Ecological standardized indicators, Ecopath with Ecosim, Ecospace, Environmental status, Food web models, Software plug-in},

pubstate = {published},

tppubtype = {article}

}

@article{christensen_representing_2014b,

title = {Representing Variable Habitat Quality in a Spatial Food Web Model},

author = {V. Christensen and M. Coll and J. Steenbeek and J. Buszowski and D. Chagaris and C. J. Walters},

url = {http://link.springer.com/article/10.1007/s10021-014-9803-3},

doi = {10.1007/s10021-014-9803-3},

issn = {1432-9840, 1435-0629},

year  = {2014},

date = {2014-08-01},

urldate = {2014-08-01},

journal = {Ecosystems},

volume = {17},

number = {8},

pages = {1397--1412},

note = {00000},

keywords = {Ecology, Ecopath, Ecospace, Environmental Management, Food web model, foraging capacity model, Geoecology/Natural Processes, habitat modeling, Hydrology/Water Resources, Plant Sciences, sampling, simulation model, species distribution model, Zoology},

pubstate = {published},

tppubtype = {article}

}

@article{christensenRepresentingVariableHabitat2014,

title = {Representing Variable Habitat Quality in a Spatial Food Web Model},

author = {Villy Christensen and Marta Coll and Jeroen Steenbeek and Joe Buszowski and Dave Chagaris and Carl J. Walters},

doi = {10.1007/s10021-014-9803-3},

issn = {1432-9840, 1435-0629},

year  = {2014},

date = {2014-08-01},

urldate = {2014-09-19},

journal = {Ecosystems},

pages = {1\textendash16},

abstract = {Why are marine species where they are? The scientific community is faced with an urgent need to understand aquatic ecosystem dynamics in the context of global change. This requires development of scientific tools with the capability to predict how biodiversity, natural resources, and ecosystem services will change in response to stressors such as climate change and further expansion of fishing. Species distribution models and ecosystem models are two methodologies that are being developed to further this understanding. To date, these methodologies offer limited capabilities to work jointly to produce integrated assessments that take both food web dynamics and spatial-temporal environmental variability into account. We here present a new habitat capacity model as an implementation of the spatial-temporal model Ecospace of the Ecopath with Ecosim approach. The new model offers the ability to drive foraging capacity of species from the cumulative impacts of multiple physical, oceanographic, and environmental factors such as depth, bottom type, temperature, salinity, oxygen concentrations, and so on. We use a simulation modeling procedure to evaluate sampling characteristics of the new habitat capacity model. This development bridges the gap between envelope environmental models and classic ecosystem food web models, progressing toward the ability to predict changes in marine ecosystems under scenarios of global change and explicitly taking food web direct and indirect interactions into account.},

keywords = {Ecology, Ecopath, Ecospace, Environmental Management, Food web model, foraging capacity model, Geoecology/Natural Processes, habitat modeling, Hydrology/Water Resources, Plant Sciences, sampling, simulation model, species distribution model, Zoology},

pubstate = {published},

tppubtype = {article}

}

@article{christensen_representing_2014,

title = {Representing Variable Habitat Quality in a Spatial Food Web Model},

author = {Villy Christensen and Marta Coll and Jeroen Steenbeek and Joe Buszowski and Dave Chagaris and Carl J. Walters},

url = {http://link.springer.com/article/10.1007/s10021-014-9803-3},

doi = {10.1007/s10021-014-9803-3},

issn = {1432-9840, 1435-0629},

year  = {2014},

date = {2014-08-01},

urldate = {2014-09-19},

journal = {Ecosystems},

volume = {17},

number = {8},

pages = {1\textendash16},

abstract = {Why are marine species where they are? The scientific community is faced with an urgent need to understand aquatic ecosystem dynamics in the context of global change. This requires development of scientific tools with the capability to predict how biodiversity, natural resources, and ecosystem services will change in response to stressors such as climate change and further expansion of fishing. Species distribution models and ecosystem models are two methodologies that are being developed to further this understanding. To date, these methodologies offer limited capabilities to work jointly to produce integrated assessments that take both food web dynamics and spatial-temporal environmental variability into account. We here present a new habitat capacity model as an implementation of the spatial-temporal model Ecospace of the Ecopath with Ecosim approach. The new model offers the ability to drive foraging capacity of species from the cumulative impacts of multiple physical, oceanographic, and environmental factors such as depth, bottom type, temperature, salinity, oxygen concentrations, and so on. We use a simulation modeling procedure to evaluate sampling characteristics of the new habitat capacity model. This development bridges the gap between envelope environmental models and classic ecosystem food web models, progressing toward the ability to predict changes in marine ecosystems under scenarios of global change and explicitly taking food web direct and indirect interactions into account.},

note = {00000},

keywords = {Ecology, Ecopath, Ecospace, Environmental Management, Food web model, foraging capacity model, Geoecology/Natural Processes, habitat modeling, Hydrology/Water Resources, Plant Sciences, sampling, simulation model, species distribution model, Zoology},

pubstate = {published},

tppubtype = {article}

}

@article{fouzaiFishingManagementScenarios2012,

title = {Fishing Management Scenarios to Rebuild Exploited Resources and Ecosystems of the Northern-Central Adriatic (Mediterranean Sea)},

author = {N. Fouzai and M. Coll and I. Palomera and A. Santojanni and E. Arneri and V. Christensen},

doi = {10.1016/j.jmarsys.2012.05.003},

issn = {0924-7963},

year  = {2012},

date = {2012-01-01},

urldate = {2012-06-03},

journal = {Journal of Marine Systems},

volume = {102\textendash104},

pages = {39\textendash51},

abstract = {We examined various fishing management options to recover exploited marine resources and ecosystems of the Northern-Central Adriatic Sea. Dynamic simulations were based on a spatial ecological model previously calibrated with time series of data. Scenarios regarding spatial management were evaluated with the establishment of two marine protected areas, respectively, in the Pomo pit and the northern region. In addition, three temporal simulations of temporary closures and overall reduction of fishing effort of demersal and pelagic fleets (bottom, mid-water trawls and purse seines) were also considered. Simulations were run for 45\ years (1975\textendash2020), including the calibration period (1975\textendash2002), and changes in biomass and catch of marine resources were analyzed. Our results confirm that current fishing management in the Adriatic Sea does not have clear beneficial impacts for the recovery of exploited resources, which will remain depleted in 2020 if ``business as usual'' continues. Simulations of alternative management suggest that both protected areas could be beneficial for fish population recovery predicting an increase in the biomass of commercial fish and predatory organisms. Simulations of temporary closures and overall reduction of fishing effort also show significant benefits for several commercial resources. We argue that both management measures may be effective tools to recover exploited ecosystems of the Northern-Central Adriatic Sea and halt the decline of marine resources.},

keywords = {Ecopath with Ecosim, Ecospace, fisheries management, Marine protected areas (MPA), Northern-Central Adriatic Sea, Trophic models},

pubstate = {published},

tppubtype = {article}

}

@article{fouzai_fishing_2012,

title = {Fishing management scenarios to rebuild exploited resources and ecosystems of the Northern-Central Adriatic (Mediterranean Sea)},

author = {N. Fouzai and M. Coll and I. Palomera and A. Santojanni and E. Arneri and V. Christensen},

url = {http://www.sciencedirect.com/science/article/pii/S0924796312001169},

doi = {10.1016/j.jmarsys.2012.05.003},

issn = {0924-7963},

year  = {2012},

date = {2012-01-01},

urldate = {2012-06-03},

journal = {Journal of Marine Systems},

volume = {102-104},

pages = {39\textendash51},

abstract = {We examined various fishing management options to recover exploited marine resources and ecosystems of the Northern-Central Adriatic Sea. Dynamic simulations were based on a spatial ecological model previously calibrated with time series of data. Scenarios regarding spatial management were evaluated with the establishment of two marine protected areas, respectively, in the Pomo pit and the northern region. In addition, three temporal simulations of temporary closures and overall reduction of fishing effort of demersal and pelagic fleets (bottom, mid-water trawls and purse seines) were also considered. Simulations were run for 45\ years (1975\textendash2020), including the calibration period (1975\textendash2002), and changes in biomass and catch of marine resources were analyzed. Our results confirm that current fishing management in the Adriatic Sea does not have clear beneficial impacts for the recovery of exploited resources, which will remain depleted in 2020 if “business as usual” continues. Simulations of alternative management suggest that both protected areas could be beneficial for fish population recovery predicting an increase in the biomass of commercial fish and predatory organisms. Simulations of temporary closures and overall reduction of fishing effort also show significant benefits for several commercial resources. We argue that both management measures may be effective tools to recover exploited ecosystems of the Northern-Central Adriatic Sea and halt the decline of marine resources.},

keywords = {Ecopath with Ecosim, Ecospace, fisheries management, Marine protected areas (MPA), Northern-Central Adriatic Sea, Trophic models},

pubstate = {published},

tppubtype = {article}

}