Insights on integrating habitat preferences in process-oriented ecological models – a case study of the southern North Sea

Miriam Püts, Marc Taylor, Ismael Núñez-Riboni, Jeroen Steenbeek, Moritz Stäbler, Christian Möllmann and Alexander Kempf

Ecological Modelling, 2020, vol. 431, issue C

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: Ecospace; Spatial-temporal framework; Habitat capacity; Species distribution model; Food web model; Ecopath with Ecosim (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030438002030260X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:431:y:2020:i:c:s030438002030260x

DOI: 10.1016/j.ecolmodel.2020.109189

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().