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Predicting mixed forests responses to climate change and drought stress with a plant hydraulics model

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.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

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(opens in new window) H2020-MSCA-IF-2019

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Coordinator

UNIVERSIDAD POLITECNICA DE MADRID
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 172 932,48
Address
CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO
28040 MADRID
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 172 932,48
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