National Projects
Project duration: 
Sep 2021 to Aug 2023

The aim of the project is to analyse the past and current impacts of interacting drivers of global change and the risk that they pose to Ecosylstem Services (ES) and biodiversity in Mediterranean forests


Understanding the impacts of drivers of change on biodiversity and ecosystem service provision has been a key goal of environmental research in the last decades. However, there is still little understanding of the interactions and feedbacks between the drivers of ecosystem and biodiversity change and multiple aspects of human well-being with most studies concentrating in partial assessments on the impact of mainly climate change. This lack of integration limits our knowledge about ecosystems responses to multiple drivers of change (e.g. climate change, land use change) and their interaction (e.g. fires), as well as our capacity to intervene to mitigate impacts consequently through restoration measures.

Project actions

  1. To identify patterns of change in biodiversity and ES in forest landscapes, focusing on dynamics of forests and bird communities and on changes in ES provided by forests, both within and beyond protected areas.
  2. To determine the underlying responses of these changes to local and global drivers impacting Mediterranean systems disentangling the relative role of climate, land use and species traits in determining species responses and changes in ES provision at the regional scaleand the role of protected areas at buffering potential impacts.
  3. To develop and apply the novel and internationally accepted risk assessment framework of losing ES and biodiversity by the impact of disturbances, and to consolidate an integrative landscape dynamic modelling approach, allowing to predict observed responses of chosen indicators by accounting for the joint impact of different global change drivers.
  4. To identify priority areas for restoration, and management actions needed, that help minimise the impact of different drivers of global change on biodiversity and ES, by learning from the empirical responses of these assets to past impacts and using novel spatial optimisation algorithms to identify cost-effective restoration recommendations.

Proyecto PID2020-119933RB-C21 financiado por MCIN/ AEI /10.13039/501100011033