European landscape-level assessment and modelling of forest plantations’ growth dynamics and ecosystem services
Application period: 11 June – 10 August, 2026
Research project description
European forests are increasingly expected to provide timber, biomass, carbon storage, biodiversity support and climate-resilience functions under changing environmental, economic and policy conditions. At the same time, large volumes of forestry data have been collected across Europe through national forest inventories, plantation registers, remote sensing products, experimental plots, management databases and disturbance monitoring systems. However, these datasets remain fragmented across countries, species, measurement protocols and management contexts. This limits their potential for comparative modelling, plantation assessment and evidence-based forest planning.
This doctoral project will develop biometric modelling and data-mining approaches to integrate existing European forestry datasets, with particular attention to plantation forests and intensively managed stands. The research will focus on identifying tree species, stand structure, growth and yield patterns, and management regimes across different European regions. Existing datasets from national forest inventories, plantation mapping products, forest management records and remote sensing layers will be harmonised and analysed to evaluate where plantation forests occur, how they grow, how they are managed, and how they are exposed to disturbances such as drought, wind, fire, pests and diseases.
Objectives:
i) Generating maps of production and ecosystem services (ES): building of the available dataset by the research group from selected European countries (including information on species composition, stand age, diameter, height, volume, productivity, management intensity and spatial location), spatialize and interpolate to produce consistent estimates of biomass production and different ES.
ii) Apply data-mining and statistical modelling methods to classify forest types and identify plantation areas, with emphasis on species such as poplar, willow, eucalyptus, conifers and other fast-growing or intensively managed forest systems, and assess their landscape level interactions with existing lad uses.
iii) Integrate these models to generate management scenarios, including rotation length, thinning regimes, biomass production and expected yield under alternative silvicultural assumptions at landscape level.
The expected outcome will be a set of harmonised datasets, growth and yield modelling workflows, spatial analyses and management-planning tools that can support plantation forestry, biomass production, climate adaptation and risk-informed forest management in Europe. Scientifically, the thesis will contribute to forest biometrics, plantation forestry, forest data integration and spatial decision support. Practically, it will provide methods that can help researchers, forest managers and policy actors compare plantation systems across countries and evaluate their role in future European forest-based bioeconomy strategies.
Academic background and skills of the applicant
An ideal candidate holds a master’s degree in forest sciences, environmental sciences, applied ecology, geoinformatics and modelling, or a closely related field. Previous experience with forest inventory data, growth and yield modelling, plantation forestry, remote sensing, or spatial analysis is considered highly valuable. The position requires strong quantitative skills and a willingness to work with large, heterogeneous datasets from different European countries.
Proficiency in R, GIS software, and statistical modelling is required. Experience with spatial databases, Python, or Google Earth Engine is considered an advantage. Knowledge of mixed models, machine learning, forest inventory methods, forest management planning, or disturbance ecology is also regarded as beneficial.
The candidate is expected to work independently, document analytical workflows clearly, and collaborate effectively with international partners. Excellent written and oral communication skills in English are required, as the doctoral thesis will be developed in an international research environment and is expected to result in peer-reviewed scientific publications. The selected candidate must fulfil the language skills requirements of the Doctoral Programme in Science, Forestry and Technology at UEF (see https://www.uef.fi/en/degree-programme/doctoral-programme-in-science-forestry-and-technology (Eligibility and admission criteria)). The candidate should also have an interest in applied forestry questions, including plantation management, biomass production, climate adaptation, and the use of existing data for decision support.
Doctoral programme and research group
Doctoral education in the University of Eastern Finland is arranged in seven discipline specific or thematic doctoral programmes. This research project will be located in the Doctoral Programme in Science, Forestry and Technology, and the submitting department is the School of Forest Sciences.
The doctoral candidate will join the research group working at the interface of forest management, biomass production, plantation forestry, spatial analysis, ecosystem services and climate-resilient forestry. The group combines quantitative forest science, applied silviculture, forest biometrics, geospatial modelling and policy-relevant research on the role of managed forests in the European bioeconomy. The research environment will provide expertise in forest inventory analysis, growth and yield modelling, GIS, data harmonisation, climate adaptation and disturbance-related forest management.
The supervision team has experience in analysing forestry datasets across countries, evaluating biomass production systems, studying plantation forestry and developing spatial approaches for forest management and land-use planning. The research environment will provide expertise in forest inventory analysis, growth and yield modelling, GIS, data harmonisation, climate adaptation and disturbance-related forest management. The doctoral researcher will also benefit from links to European research networks, international datasets and ongoing projects related to forest resilience, biomass production and strategic forest planning.
Partners / Secondments
Forest Science and Technology Centre of Catalonia (CTFC), Spain, hosted by José Ramón González Olabarria
Other interdisciplinary, international and/or intersectoral collaboration
The project will be interdisciplinary by combining forest biometrics, silviculture, plantation forestry, spatial data science, remote sensing, disturbance ecology and management planning. It will also have an international dimension, as it will compare datasets and forest systems across several European countries. The candidate will be integrated into the international networks of the research group.
Intersectoral collaboration may involve scientists from other synergic projects, stakeholders, national inventory organisations, bioeconomy actors and policy-oriented institutions interested in plantation forestry, biomass supply, climate adaptation and risk-informed forest management. The project may also interact with ongoing European and Nordic research initiatives related to forest resilience, forest-based bioeconomy, ecosystem services and climate-smart forestry.
The results will be relevant not only for academic forest science, but also for practical forest planning, policy development and strategic discussions on where and how plantation forestry can contribute to wood supply, biomass production and climate adaptation in Europe.
Intersectoral and interdisciplinary collaboration is strengthened through DP-FOBI’s three summer schools involving academic supervisors, non-academic partners, and other stakeholders, enabling hands-on interaction and knowledge exchange.