Project description
Understanding mixed forests' response to drought can help predict impacts of climate change
Droughts are expected to become more frequent and intense in many parts of the world. When trees die during droughts, less carbon is stored in forests, thus worsening climate change. Therefore, for scientists to be able to predict the socioeconomic and ecological impacts of climate change and inform conservation strategies, forest responses need to be modelled to droughts. However, current models are ineffective for mixed forests due to their diverse species and functional traits. To address this problem, the EU-funded FORECAST project aims to develop a model for mixed forests based on known biophysical constraints, plant functional traits and optimisation theory. The model will also be used to guide the conservation of the mixed Mediterranean forest Hayedo de Montejo, a World Heritage Site.
Objective
The frequency and intensity of droughts are expected to increase in many regions of the world due to global climate change. Droughts can lead to widespread tree mortality, leading to a loss of carbon stored in forests that will feedback to exacerbate climate change. Thus, modelling forest responses to drought is critical for predicting climate change socio-economic and ecological impacts and informing conservation strategies. However, current models are not capable of adequately representing forest responses to drought, especially for mixed forests due to their diversity in species and functional traits. The proposed research intends to solve this problem by developing a model for mixed forests based on known biophysical constraints, plant functional traits and optimization theory. The model’s performance will be evaluated with (1) detailed measurements at Hayedo de Montejo (HM), a mixed Mediterranean forest with diverse functional traits, (2) data from a network of eddy-covariance towers that measure ecosystem fluxes, and (3) mortality data from two national forest inventories that span a wide range of forest types. Next, the model will be used for forecasting the vulnerability of HM to different climate change scenarios for guiding the conservation of this World Heritage Site.
I will develop this project at Universidad Politécnica de Madrid, one of Europe’s leading academic institutions. A secondment at Centro de Investigación Ecológica y Aplicaciones Forestales (Barcelona) will allow me to learn new modelling approaches, gain access to global plant databases, and establish new collaborations. A secondment at Dirección General de Medio Ambiente y Sostenibilidad de la Comunidad de Madrid, a non-academic institution in charge of HM’s management, will ensure intersectoral transfer of knowledge among scientists, educators, managers and policy makers. This MSCA will facilitate my return to Europe and enhance my chances of obtaining a permanent position in Europe.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social scienceseducational sciencesdidactics
- social sciencessociologydemographymortality
- natural sciencescomputer and information sciencesdatabases
- natural sciencesbiological sciencesecologyecosystems
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
28040 Madrid
Spain