@article {7089,
	title = {How to model social-ecological systems? {\textendash} A case study on the effects of a future offshore wind farm on the local society and ecosystem, and whether social compensation matters},
	journal = {Marine Policy},
	volume = {119},
	year = {2020},
	abstract = {Models of social-ecological systems (SES) are acknowledged as an important tool to understand human-nature relations. However, many SES models fail to integrate adequate information from both the human and ecological subsystems. With an example model of a future Offshore Wind Farm development and its effects on both the ecosystem and local human population, we illustrate a method facilitating a {\textquotedblleft}balanced{\textquotedblright} SES model, in terms of including information from both subsystems. We use qualitative mathematical modeling, which allows to quickly analyze the structure and dynamics of a system without including quantitative data, and therefore to compare alternative system structures based on different understandings of how the system works. By including similar number of system variables in the two subsystems, we balanced the complexity between them. Our analyses show that this complexity is important in order to predict indirect and sometimes counterintuitive effects. We also highlight some conceptually important questions concerning social compensations during developmental projects in general, and wind farms in particular. Our results suggest that the more project holders get involved in various manner in the local socio-ecological system, the more society will benefit as a whole. Increased involvement through e.g. new projects or job-opportunities around the windfarm has the capacity to offset the negative effects of the windfarm on the local community. These benefits are enhanced when there is an overall acceptance and appropriation of the project. We suggest this method as a tool to support the decision-making process and to facilitate discussions between stakeholders, especially among local communities. {\textcopyright} The Authors},
	keywords = {Acceptance, comparative study, Complexity, Decision making, development project, Eastern English channel, environmental impact assessment, future prospect, local participation, Network, numerical model, offshore structure, participatory approach, Perception, Qualitative modeling, quantitative analysis, Renewable energy, social impact assessment, stakeholder, wind farm},
	issn = {0308597X (ISSN)},
	doi = {10.1016/j.marpol.2020.104031},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085318224\&doi=10.1016\%2fj.marpol.2020.104031\&partnerID=40\&md5=9e69340af6d591878af0f943cd4bc347},
	author = {Haraldsson, M. and Raoux, A. and Riera, F. and Hay, J. and Dambacher, J.M. and Nathalie Niquil}
}
@article {7092,
	title = {An open-source framework to model present and future marine species distributions at local scale},
	journal = {Ecological Informatics},
	volume = {59},
	year = {2020},
	abstract = {Species Distribution Models (SDMs) are useful tools to project potential future species distributions under climate change scenarios. Despite the ability to run SDMs in recent and reliable tools, there are some misuses and proxies that are widely practiced and rarely addressed together, particularly when dealing with marine species. In this paper, we propose an open-source framework that includes (i) a procedure for homogenizing occurrence data to reduce the influence of sampling bias, (ii) a procedure for generating pseudo-absences, (iii) a hierarchical-filter approach, (iv) full incorporation of the third dimension by considering climatic variables at multiple depths and (v) building of maps that predict current and potential future ranges of marine species. This framework is available for non-modeller ecologists interested in investigating future species ranges with a user-friendly script. We investigated the robustness of the framework by applying it to marine species of the Eastern English Channel. Projections were built for the middle and the end of this century under RCP2.6 and RCP8.5 scenarios. {\textcopyright} 2020 Elsevier B.V.},
	keywords = {Climate Change, ecological modeling, English Channel, filter, future prospect, hierarchical system, marine ecosystem, sampling, scenario analysis, species diversity},
	issn = {15749541},
	doi = {10.1016/j.ecoinf.2020.101130},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086876945\&doi=10.1016\%2fj.ecoinf.2020.101130\&partnerID=40\&md5=0a5c308eac10a69880027d5de2e6fe98},
	author = {Ben Rais Lasram, F. and Hattab, T. and Nogues, Quentin and Beaugrand, G. and Dauvin, J.C. and Halouani, G. and Le Loc{\textquoteright}h, F. and Nathalie Niquil and Leroy, B.}
}
