A mixed modeling approach to predict the effect of environmental modification on species distributions

A mixed modeling approach to predict the effect of environmental modification on species distributions

Cozzoli, F.
Eelkema, M.
Bouma, T.J.
Ysebaert, T.
Escaravage, V.
Herman, P.M.J.

Civil Engineering and Geosciences

Hydraulic Engineering

2014-02-26

Human infrastructures can modify ecosystems, thereby affecting the occurrence and spatial distribution of organisms, as well as ecosystem functionality. Sustainable development requires the ability to predict responses of species to anthropogenic pressures. We investigated the large scale, long term effect of important human alterations of benthic habitats with an integrated approach combining engineering and ecological modelling. We focused our analysis on the Oosterschelde basin (The Netherlands), which was partially embanked by a storm surge barrier (Oosterscheldekering, 1986). We made use of 1) a prognostic (numerical) environmental (hydrodynamic) model and 2) a novel application of quantile regression to Species Distribution Modeling (SDM) to simulate both the realized and potential (habitat suitability) abundance of four macrozoobenthic species: Scoloplos armiger, Peringia ulvae, Cerastoderma edule and Lanice conchilega. The analysis shows that part of the fluctuations in macrozoobenthic biomass stocks during the last decades is related to the effect of the coastal defense infrastructures on the basin morphology and hydrodynamics. The methodological framework we propose is particularly suitable for the analysis of large abundance datasets combined with high-resolution environmental data. Our analysis provides useful information on future changes in ecosystem functionality induced by human activities.

http://resolver.tudelft.nl/uuid:68eec820-2ed0-4a55-b98d-f13f79572c38

https://doi.org/10.1371/journal.pone.0089131

Public Library of Science PLOS

1932-6203

Plos One, 9 (2), e89131, 2014

Institutional Repository

journal article

(c) 2014 Cozzoli et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.