@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 = {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 = {2020-01-01},

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, GIS, local study, niches, North Sea, species distributions},

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{christensen_representing_2014,

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 = {https://doi.org/10.1007/s10021-014-9803-3},

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

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

journal = {Ecosystems},

volume = {17},

number = {8},

pages = {1397--1412},

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 = {Ecospace, food web, habitat modeling, species distributions},

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--51},

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 = {Adriatic Sea, Ecopath with Ecosim, Ecospace, fisheries management, Marine protected areas (MPA), trophic ecology},

pubstate = {published},

tppubtype = {article}

}