The European Union has set ambitious targets to reduce greenhouse gas emissions by at least 55% in 2030 and to become climate neutral by 2050. TheEuropean Forest Institute organised a ThinkForest event to explore what forests can contribute to achieving these climate goals.
Forests and forestry play three important roles in climate change mitigation. First, reducing deforestation and forest degradation lowers GHG emissions. Second, forest management and restoration can maintain or enhance forest carbon stocks and sinks. Third, improving the use of wood products can store carbon over the long-term, and avoid emissions by substituting emissions-intensive materials.
Our ThinkForest event will ask:
How much can forest-based activities contribute to climate change mitigation?
What role do policies play?
How can we maximise forest-based climate change mitigation nationally/locally?
In this occasion, the coordinator of the ForestPaths-project, Hans Verkerk, will present a new study titled “Forest-based climate change mitigation and adaptation in Europe”.
PhD candidate Elisa Bruni from the Climate and Environmental Sciences Laboratory (LSCE) in France is pleased to invite you to her doctoral thesis defence entitled “Soil organic carbon modelling: estimating carbon input changes required to reach policy objectives aimed at increasing soil organic carbon stocks”.
The defence will take place on Monday 28 March 2022 at 2:00 p.m. in Amphi 7 of AgroParisTech (Paris-Maine), located at 19 Avenue du Maine, 75015 Paris. For those who prefer to attend remotely, you can join the videoconference through the following link (Meeting ID: 930 0252 2076 / Password: 954715). The presentation will be held in English.
The thesis jury board is composed of the following experts:
Axel DON, Senior Lecturer, Thünen Institute (Germany) – Rapporteur & Examiner
Isabelle BASILE, Research Director, INRAE Centre PACA (France) – Rapporteur & Examiner
Sébastien Barot, Director of Research, IRD (France) – Examiner
Patricia Garnier, Director of Research, INRAE (France) – Examiner
Emanuele Lugato, Project manager, Joint Research Centre (Europe) – Examiner
Stefano Manzoni, Senior Lecturer, Stockholm University (Sweden) – Examiner
Claire Chenu, Director of Research, INRAE (France) – Thesis director
Bertrand Guenet, Research Fellow, INRAE (France) – Examiner
Denis Angers, Honorary Director of Research, Université de Laval (Canada) – Invited
Gaby Deckmyn, Senior Scientist, University of Antwerp (Belgium) – Invited
Thesis abstract
To partially compensate for CO2 emissions, the 4 per 1000 initiative proposed an annual 4‰ soil organic carbon (SOC) stock increase. Yet, the feasibility of such an ambitious target is still under debate. The most efficient way to increase the SOC stocks is to increase the C input to the soil. The objective of this thesis was to estimate the C input required to yearly increase the SOC stocks by 4‰ in European croplands.
To solve this problem, we built an inverse modelling approach and tested it on a SOC model, by estimating the C input required to reach the 4‰ objective at multiple long-term agricultural experiments in Europe. Then, we applied this approach to a multimodel ensemble, to assess the uncertainties of the estimations according to different representations of the SOC dynamics. As a first attempt to provide insights for policymakers on the feasibility of a 4‰ target in Europe, we applied a multi-model ensemble over the whole European cropland area, and we generated maps of the required C input under two scenarios of climate change. To improve the simulation of SOC stocks at the European scale, we tested a new, statistically derived, parametrization technique.
Our study demonstrates that there are substantial uncertainties around the C input required to reach a 4‰ target. However, a general pattern emerges at the European cropland scale, where the 4‰ target seems feasible under future scenarios of climate change, only assuming drastic increases of C input to the soil.
In recent years, significant model developments have been made in modelling peatland ecosystems. These developments have been motivated by the importance of these ecosystems to green-house gas emissions and to forestry. Therefore, it is also central to understand how they respond to changing conditions and management.
In this seminar organized by Luke Finland, we will take a look at processes driving peatland ghg emissions and growth, as well as novel modelling approaches to quantify their ghg impacts at larger scales.
Forestry Speed Dating puts innovators in contact with potential partners and end-users, to speed up innovation and create new partnerships. Through a series of speed dating workshops, and facilitation of meeting with innovators, you can find inspiration and explore new solutions towards a sustainable forest circular bioeconomy for your area.
Get in touch with the innovators behind digital solutions for soil monitoring and hear about how they can help you in monitoring your forest soil.
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
Cookie
Duration
Description
_GRECAPTCHA
5 months 27 days
This cookie is set by the Google recaptcha service to identify bots to protect the website against malicious spam attacks.
cookielawinfo-checkbox-advertisement
1 year
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .
cookielawinfo-checkbox-analytics
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional
11 months
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
CookieLawInfoConsent
1 year
Records the default button state of the corresponding category & the status of CCPA. It works only in coordination with the primary cookie.
viewed_cookie_policy
11 months
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Cookie
Duration
Description
_ga
2 years
The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.