Project: AdaptAlentejo – Predicting ecosystem-level responses to climate change (POCI-01-0145-FEDER-030793)
Scientific Area: Aquatic Ecology, Biodiversity, Ecological Networks, Ecosystem Services, Biogeography
Context: Climate change is causing biodiversity loss at unprecedented rates threatening ecological stability and human welfare. Freshwater ecosystems (e.g. ponds, lakes, rivers) are particularly vulnerable since species’ potential responses to climate change (e.g. warming, drought) are constrained by the relatively discrete boundaries of these ecosystems. Predicting such responses remains a challenge because most research is still focused on individual species and rarely generalized across different scales and climatic conditions. To advance our understanding on how natural systems respond to climate change it is crucial to find ways to reconcile research at individual, community and ecosystem-level. Eco-physiological studies measuring how organisms adapt to environmental conditions have demonstrated the crucial role of temperature in constraining species distributions. Ecological networks, such as aquatic food webs, are reorganizing as a result of such distributional shifts. In particular, increased temperatures have negative impacts on higher trophic levels (e.g. predatory fish) with cascading effects on food-web structure (e.g. “what-eats-what”) and vital ecosystem services (e.g. detrital decomposition, carbon sequestration). The potential loss of higher trophic levels is particularly crucial in freshwater systems since it can enhance greenhouse gas (GHG) emissions (e.g. CO2, CH4), leading to further global warming (>20% of global CH4 emissions originate in freshwater systems). However, the relationship between food-web structure and GHG emissions is not well understood, particularly in the context of climate change. Unravelling the links between changes in food web structure and GHG emissions is critical to be able to predict how aquatic ecosystems respond to change, but also how much they are contributing to such change. AdaptAlentejo – Predicting ecosystem-level responses to climate change – will address this gap in knowledge by combining multiple disciplines (physiology, biogeochemistry, geophysics) and state-of-art tools (metagenomics, ecological networks, carbon flux measurements). Some of the project’s activities include: (1) Quantify species’ physiological responses to increasing temperatures; (2) Quantify energy flows within aquatic food webs; (3) Test ecosystem-level responses using biodiversity surveys; experimental mesocosms and whole-ecosystem (i.e. reservoirs) manipulations. AdaptAlentejo will use the Iberian Ponds Network and one the Europe’s largest artificial water reservoir network – Alqueva – as case studies. AdaptAlentejo brings together an international interdisciplinary team coordinated by an early-career ecologist, Miguel Matias, with experience in theoretical, empirical and experimental approaches in aquatic biodiversity research and, Miguel B. Araújo a leading expert in biodiversity modelling and climate change.
Profile and qualifications:Any national, foreign and stateless candidate(s) who hold a doctorate degree in Biology, Environmental Sciences, Biochemistry, Computational Biology, Mathematics or Physics and have a scientific and professional curriculum that fits one of the suitable profiles required to achieve the proposed objectives, namely:
-Aquatic ecologist profile: Experience with biodiversity surveys of aquatic food webs (fish, zooplankton or macroinvertebrates) and measurement of carbon emissions (CO2, CH4). Additional experience on electrofishing and/or gut content analysis also welcomed;
-Molecular Ecologist profile: Experience with molecular approaches (i.e. Environmental DNA to conduct and analyze data from biodiversity surveys and/or gut content analysis;
-Theoretical / Computational ecologist profile: Experience with theoretical/computational approaches to model changes in aquatic food-webs. Background in Physics/Mathematics would be considered if candidate has previous experience with modelling food webs;
Stipend: Monthly remuneration to be paid is the remuneration corresponding to level 33 of the Single Salary Table, approved by Order no. 1553-C/2008 of December 31st, i.e. 2128,34 Euros.
How to apply: Candidates have to submit their application files and supporting documentation, preferably in a digital form, in PDF format, via email to email@example.com before the 5/03/2019. For further details on the application procedure please check the official announcement on the EraCareers website: http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=109793
Application reference: CatBio-01