GUARDEN
GUARDEN

GUARDEN
GUARDEN
 : 
safeGUARDing biodivErsity aNd critical ecosystem services across sectors and scales
safeGUARDing biodivErsity aNd critical ecosystem services across sectors and scales

A Project coordinated by IIIA.

Web page:

Principal investigator: 

Collaborating organisations:

CIRAD    CENTRE DE COOPERATION INTERNATIONALE EN RECHERCHE AGRONOMIQUE POUR LEDEVELOPPEMENT - C.I.R.A.D. EPIC    FR
INRIA    INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE  ...

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CIRAD    CENTRE DE COOPERATION INTERNATIONALE EN RECHERCHE AGRONOMIQUE POUR LEDEVELOPPEMENT - C.I.R.A.D. EPIC    FR
INRIA    INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE    FR
CSIC    AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS    ES
HUA    CHAROKOPEIO PANEPISTIMIO    EL
NBC    STICHTING NATURALIS BIODIVERSITY CENTER    NL
MBG    AGENTSCHAP PLANTENTUIN MEISE    BE
ICCS    EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLGISTON-EMP    EL
FREDU    FREDERICK UNIVERSITY FU    CY
CBNM    PARC NATIONAL DE PORT-CROS    FR
UNTNR    UNIVERSITY OF ANTANANARIVO    MG
DRAXIS    DRAXIS ENVIRONMENTAL SA    EL
EBOS    EBOS TECHNOLOGIES LIMITED    CY
ENV    ENVECO ANONYMI ETAIRIA PROSTASIAS KAI DIAHIRISIS PERIVALLONTOS A.E.    EL
MOA    MINISTRY OF AGRICULTURE, RURAL DEVELOPMENT AND ENVIRONMENT OF CYPRUS    CY
AMB    AREA METROPOLITANA DE BARCELONA    ES
 

Funding entity:

European Commission
European Commission

Funding call:

HORIZON-CL6-2021-GOVERNANCE-01 submitted for HORIZON-CL6-2021-GOVERNANCE-01 / 06 Oct 2021
HORIZON-CL6-2021-GOVERNANCE-01 submitted for HORIZON-CL6-2021-GOVERNANCE-01 / 06 Oct 2021

Funding call URL:

Project #:

101060693
101060693

Total funding amount:

4.556.888,75€
4.556.888,75€

IIIA funding amount:

100.000,00€
100.000,00€

Duration:

01/Nov/2022
01/Nov/2022
31/Oct/2025
31/Oct/2025

Extension date:

GUARDEN’s main mission is to safeguard biodiversity and its contributions to people by bringing them at the forefront of policy and decision-making. This will be achieved through the development of user-oriented Decision Support Applications (DSAs), and leveraging on Multi-Stakeholder Partnerships (MSPs). They will take into account policy and management objectives and priorities across sectors and scales, build consensus to tackle data gaps, analytical uncertainties or conflicting objectives, and assess options to implement adaptive transformative change. To do so, GUARDEN will make use of a suite of methods and tools using Deep Learning, Earth Observation, and hybrid modelling to augment the amount of standardized and geo-localized biodiversity data, build-up a new generation of predictive models of biodiversity and ecosystem status indicators under multiple pressures (human and climate), and propose a set of complementary ecological indicators likely to be incorporated into local management and policy. The GUARDEN approach will be applied at sectoral case studies involving end users and stakeholders through Multi-Stakeholder Partnerships, and addressing critical cross-sectoral challenges (at the nexus of biodiversity and deployment of energy/transport infrastructure, agriculture, and coastal urban development). Thus, the GUARDEN DSAs shall help stakeholders engaged in the challenge to improve their holistic understanding of ecosystem functioning, biodiversity loss and its drivers and explore the potential ecological and societal impacts of alternative decisions. Upon the acquisition of this new knowledge and evidence, the DSAs will help end-users not only navigate but also (re-)shape the policy landscape to make informed all-encompassing decisions through cross-sectoral integration.

GUARDEN’s main mission is to safeguard biodiversity and its contributions to people by bringing them at the forefront of policy and decision-making. This will be achieved through the development of user-oriented Decision Support Applications (DSAs), and leveraging on Multi-Stakeholder Partnerships (MSPs). They will take into account policy and management objectives and priorities across sectors and scales, build consensus to tackle data gaps, analytical uncertainties or conflicting objectives, and assess options to implement adaptive transformative change. To do so, GUARDEN will make use of a suite of methods and tools using Deep Learning, Earth Observation, and hybrid modelling to augment the amount of standardized and geo-localized biodiversity data, build-up a new generation of predictive models of biodiversity and ecosystem status indicators under multiple pressures (human and climate), and propose a set of complementary ecological indicators likely to be incorporated into local management and policy. The GUARDEN approach will be applied at sectoral case studies involving end users and stakeholders through Multi-Stakeholder Partnerships, and addressing critical cross-sectoral challenges (at the nexus of biodiversity and deployment of energy/transport infrastructure, agriculture, and coastal urban development). Thus, the GUARDEN DSAs shall help stakeholders engaged in the challenge to improve their holistic understanding of ecosystem functioning, biodiversity loss and its drivers and explore the potential ecological and societal impacts of alternative decisions. Upon the acquisition of this new knowledge and evidence, the DSAs will help end-users not only navigate but also (re-)shape the policy landscape to make informed all-encompassing decisions through cross-sectoral integration.

2024
Manel Rodríguez Soto,  Juan A. Rodríguez-Aguilar,  & Maite López-Sánchez (2024). An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning. The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) . [BibTeX]  [PDF]
2023
Bjoern Komander,  Jesus Cerquides,  & Jaume Piera (2023). Developing and Validating Tools for the Automated Analysis and Enhancement of Online Discussions. HHAI 2023: Augmenting Human Intellect (pp 433--435). IOS Press. [BibTeX]  [PDF]
Bjoern Komander,  Jesus Cerquides,  Jaume Piera,  Jeffrey Chan,  & Azadeh Alavi (2023). Expert Finding for Citizen Science. Artificial Intelligence Research and Development (pp 59--69). IOS Press. https://doi.org/10.3233/FAIA230659. [BibTeX]  [PDF]
Jesus Cerquides
Scientific Researcher
Phone Ext. 431859