ESRs individual project

ESR01 – Integrating LIDAR information into operational mixed forests growth and yield models

Recruiting Institution: UNIVERSIDAD DE VALLADOLID, Valladolid, Spain

Enrolling PhD school: Escuela de Doctorado de la Universidad de Valladolid-ESDUVA, Valladolid, Spain

Project description

Forest inventory is moving from ground sampling to remote sensing measurements. Growth and yield models need to be improved through higher resolution of forest information especially in mixed species stands as well as natural stands. Implementation of standardized protocol on the use of the new technologies are needed. ESR will use Unmanned Aerial Vehicle (UAV) and terrestrial mobile application of LiDAR (Light Detection and Ranging) and photogrammetric techniques such as Structure for Motion (SfM) for estimating 3-D structures from 2-D dimensional image sequences. The tests are applied on experimental plots on monospecific and mixed species stands. Outcomes expected included information about LiDAR and SfM implementation in growth, yield and above-ground carbon models and related Decision Support Systems for optimizing carbon balance. Standardized protocols on field measurements will be developed. The position will have a strong link with regards to content to ESR02, ESR09 and ESR12.

Supervisor: Felipe Bravo (email: fbravo@pvs.uva.es)

Early Stage Researcher: Frederico Simôes (email: frederico.tupinamba@uva.es)

ESR02 – Drought resistance and growth stability of trees and stand in dependence of species identity, stand density, and structure

Recruiting Institution: Technische Universitaet Muenchen – TUM, Freising, Germany

Enrolling PhD school: TUM Graduated School, Freising, Germany

Project description

Scientifically, the position focusses on thinning and mixing effect on drought resistance and growth stability of tree and stand growth. In particular, the memory effect of the past growing and competition situations on current structure and resilience will be emphasized. Analyses will employ stands along an ecological, transnational transect. The project requires dendrometric fieldwork at an international level, measurement in the tree ring lab, and biostatistical and programming skills for data analyses. It is envisaged to apply an innovative combination of terrestrial laser scanning (TLidar) and mobile computer tomography scanning of stems (mCT) for deeper insights into the dependency of current growth on antecedent drivers of tree and stand dynamics. The position will have a strong link with regards to content to ESR03, ESR04, ESR05, ESR06 and ESR12.

Supervisor Hans Pretzsch (email: hans.pretzsch@tum.de)

Early Stage Researcher Shamin Ahmed (email: shamim.ahmed@tum.de)

ESR03 – Growth resistance and resilience of tree species to drought stress in even- versus uneven-aged forest

Recruiting Institution: Warsaw University of Life Sciences – SGGW, Institute of Forest Sciences, Warsaw, Poland

Enrolling PhD school: SGGW graduated program, Warsaw, Poland

Project description

The main goal of the position is to study temporal growth stability, as well as the resistance of selected tree species under extreme drought stress in even- versus uneven-aged  stands. Analyses will employ stands along an ecological, transnational transect. The project requires dendrometric fieldwork at an international level, measurement in the tree ring lab, and statistical and programming skills for data analyses.  The position will have a strong link with regards to content to ESR02, ESR04, ESR05, ESR06 and ESR12.

Supervisor Kamil Bielak (email: kamil_bielak@sggw.edu.pl)

Early Stage Researcher Bodhan Kolinsky (email: bohdan_kolisnyk@sggw.edu.pl)

ESR04 – Species-specific functional response to drought stress and the relevance for intra- and interspecific interaction

Recruiting Institution: Institution Nacional de Investigacion Y Tecnologia Agraria y Alimentaria – INIA, Madrid, Spain

Enrolling PhD school: Escuela de Doctorado de la Universidad de Valladolid-ESDUVA, Valladolid, Spain

Project description

The position focuses in species-specific functional response to drought stress and the relevance for intra- and interspecific interaction. For this purpose, the mechanisms of temporal complementarity in different types of mixtures will be analyzed through a triplet approach. The approach includes the ecophysiological assessment of tree species, their functional response and temporal complementarity in within and between-year growth in pure and mixed stands. Analyses will combine national triplets  and transnational stands. The project includes field work (dendrometric measurements, gas exchange, dendrometers), measurements in the lab (tree ring data, carbohydrates content, isotopes), and biostatistical and programming skills for data analysis. The position will have a strong link with regards to content to ESR01, ESR02, ESR03, ESR05, ESR06 and ESR12.

Supervisor Marta Pardos (email: pardos@inia.es)

Early Stage Researcher Przemyslaw Jankowski (email: przemyslawjankow@gmail.com)

ESR05 – Relationship between stand density, nutrition, productivity and water use efficiency in pure pine stand

Recruiting Institution:  Stellenbosch University – SU, Stellenbosch, South Africa

Enrolling PhD school: PhD programme in Forestry and Natural Resource Sciences of the University of Stellenbosch, South Africa

Project description

Afforestation of shrublands or grasslands with industrial plantations (mono-specific stands) results in stream flow reduction. In dry climates only a limited amount of water can be sacrificed for the ecosystem services provided by trees. As a consequence, the relationship between thinning type (thinning from above or from below) and the Water Use Efficiency (WUE) of pure stands is essential to quantify. Two existing field experiments on mono-specific stands with three treatments: un-thinned, thinned from above and thinned from below will be used. Measurements include (a) growth data:  height, diameter, basal area and volume growth plus leaf area index fluctuations (b) Evapotranspiration estimates using the heat pulse techniques (c) Isotopic signatures in the annual rings will be determined to correlate this with WUE.  The experimental plots are located in the summer rainfall zone of South Africa.  Understanding how WUE is affected by the type of thinning treatment (from above or from below) will support management strategies in industrial plantations located in areas where there is a high risk of seasonal drought. Information will be use also to optimize wood production, carbon sequestration, above-ground carbon stock model and WUE.

Supervisor Ben du Toit (email: ben@sun.ac.za)

Early Stage Researcher Faqrul Chowdhury (email: faqrul@cu.ac.bd)

ESR06 – Effect of Nitrogen deposition on C sink potential of temperate forests

Recruiting Institution:  Libera Università di Bolzano –  UNIBZ, Bolzano, Italy

Enrolling PhD school:  PhD program in Mountain Environment and Agriculture, Bolzano, Italy

Project description

Scientifically, the position focusses on the effect of Nitrogen deposition on C cycle of temperate forests. In particular, the role of N deposition on C-sink potential of forests will be assessed in a couple of field-scale N-manipulation experiments in beech and sessile oak forests where increased atmospheric N deposition is simulated by applying mineral N using either canopy-level fertilization (NAB) or traditional ground-level fertilization (NBL). In all sites, N fertilization treatments are replicated and compared against current N deposition. The project requires knowledge of ecophysiology and biogeochemistry with particular emphasis to the relationship between nitrogen and carbon cycles at ecosystem scale. The position will have a strong link with regards to content to ESR02, ESR03, ESR04, ESR05 and ESR06.

Supervisor Camilla Wellstein (email: camilla.wellstein@unibz.it)

Early Stage Researcher Daniel Minklaev (email: daminikaev@unibz.it)

ESR07 – CO2 emission control in forest operations

Recruiting Institution:  Università degli Studi di Padova – UNIPD, Padova, Italy

Enrolling PhD school:  PhD Program Land, Environment, Resources and Health, Legnaro PD, Italy

Project description

The activity aims to provide robust data on fuel consumption along a 3D gradient (e.g. surface/terrain, mechanization level, forest composition). The first part of the activity will provide the necessary data for setting up and testing of a robust standardized protocol in nomenclature and data acquisition methodology to create more comparable fuel consumption and CO2 emission datasets in harvesting operations. The ESR activity will be discussed with the participation of ESR08, ESR10 and ESR11. Expected Results: 1) robust protocol to support managers to collect standardized data on fuel consumption; 2) update inventory on fuel consumption for some of  the most common forest machines by considering terrain and forest composition variables; 3) CO2 emission model for some of the most common forest machines.

Supervisor Stefano Grigolato (email: stefano.grigolato@unipd.it)

Early Stage Researcher Mihail Bacescu (email: mihail.bacescu@phd.unipd.it)

ESR08 – Soil wheel CO2 interaction

Recruiting Institution:  Ministerium für Klimaschutz, Umwelt, Landwirtschaft, Natur- und Verbraucherschutz des Landes Nordrhein-Westfalen – FBZ, Germany

Enrolling PhD school:  PhD Program Land, Environment, Resources and Health, Legnaro PD, Italy

Project description

The candidate will be in charge of managing the project contribution of FBZ.  Mainly he will contribute to the research activities in WP4 “Understanding carbon emission in forest operation”. In real field operations, fuel consumption will be determined according to surface and terrain and mechanization level. It will also be related to soil machine interaction considering rolling distance in machine movement. Based on these information, tools for optimization for efficient forest operations and simulation models for machine performance in forest environments under the aspect of CO2 emission will be developed.  The candidate will be a part of the project research and training network, he will share information with project partners and will take part and support the manifold international training events.

Supervisor: Thilo Wagner (email: thilo.wagner@wald-und-holz.nrw.de)

Early Stage Researcher Filippo Guerra (email: filippo.guerra@wald-und-holz.nrw.de)

ESR09 – Intelligent combination of airborne data and terrestrial LiDAR for obtaining micro surface, tree and assortment data for an improved timber harvesting planning

Recruiting Institution:  Stellenbosch University – SU, Stellenbosch, South Africa

Enrolling PhD school:  PhD programme in Forestry and Natural Resource Sciences of the University of Stellenbosch, South Africa

Project description

The application of 3D point clouds in forest operations’ planning is still in its infancy. One of the most promising field of using 3D point clouds concerns the evaluation of the effects of terrain characteristics on the efficiency of machinery used in harvesting operations. Fusion of 3D point clouds derived from Structure for Motion (SfM) from a series of camera images mounted on a UAV (Unmanned Aerial Vehicle) and from TLS (Terrestrial Laser Scanner) data seems to be more promising because of the possibility to derive a precise model of soil surface and tree size and distribution.  Work will include the identification of appropriate case studies for a rapid and precise analysis of terrain morphology. Testing different Terrestrial Laser Scanner (TLS), Simultaneous Localization and Mapping (SLAM) and Unmanned Aerial Vehicle (UAV) systems to identify the most appropriate combination. Developing the protocol to fuse the 3D data from the two different systems. Develop the scripts and implement them into a tool. Test the system and validate the data collected together with ESR11 and ESR12. Expected results include tools to retrieve precise soil surface information from combined TLS and UAV data and predict obstacles and slope for machine use. These data are fundamental to retrieving information for optimizing harvesting planning in order to increase the efficiency of the harvesting operations and to minimize fuel consumption and CO2 emission per production unit. According to the harvesting technology and micro- relief and tree characteristics, it would be possible to support accurate information for optimizing carbon balance.

Supervisor: Bruce Talbot (email: bruce@sun.ac.za)

Early Stage Researcher Giuseppe Capizzi (email: giuseppe.capizzi@studenti.unipd.it)

ESR10 – Forest machine simulation for resource efficient production

Recruiting Institution:   RWTH Aachen University – RWTH, Aachen, Germany

Enrolling PhD school:  PhD program of the Electrical Engineering and Information Technology Faculty, RWTH Aachen University, Aachen, Germany

Project description

Scientifically, the position focuses on the development of experimental models allowing for a highly detailed simulation of forest machine operations with respect to different forest machines, operation plans, forest types, tree species and wood products in different regions and countries. The result is the simulative basis for the forest machines’ Digital Twin, which allows to predict emission as well as consumption key figures for concrete forest machines operating in a specific wood harvesting scenario following a certain operation plan. An important aspect will be to create accurate models of the drivers’ behaviour replicating the real drivers’ control activities and providing the necessary control input for the Digital Twin. They will be used in repeatable simulation runs, which serve as the basis for optimization problems to optimize the harvesting plan with respect to the carbon footprint of the harvesting operations. The project requires fieldwork at an international level. The position will have a strong link with regards to content to ESR07, ESR08, ESR09, ESR11 and ESR12.

Supervisor: Jurgen Rossmann (email: rossmann@mmi.rwth-aachen.de)

Early Stage Researcher Abhay Bharadwaj (email: bharadwaj@mmi.rwth-aachen.de)

ESR11 – Optimisation analysis for harvesting strategies (at the stand level)

Recruiting Institution:   Berner Fachhochschule – BFH, Switzerland

Enrolling PhD school:  PhD programme in Forestry and Natural Resource Sciences of the University of Stellenbosch, South Africa

Project description

Scientifically, the position focuses on optimization such as of partial costs per individual assortment in harvesting operations. A wider focus is given by including other aspects such as carbon impact (CO2 emissions) in these considerations. The position will have a strong link with regards to content to ESR07, ESR08 and ESR09.

Supervisor Martin Ziesak (email: martin.ziesak@bfh.ch)

Early Stage Researcher Francesco Sforza (email: francesco.sforza@bfh.ch)

ESR12 – Opportunities and limitations of robust optimization in forest management on enterprise level

Recruiting Institution:    Technische Universitaet Muenchen – TUM, Freising, Germany

Enrolling PhD school:  TUM Graduated School, Germany

Project description

Scientifically, the position focuses on robust optimization approaches. Various methods can include uncertainty spaces. The approach could move from the presently mainly static methodology into a dynamic formulation to optimize tree species composition and harvest scheduling simultaneously on stand and enterprise level. Multiple objective optimization will complement the basic analyses by using appropriate indicators to express carbon relationships appropriately. Interesting questions such as how forest structures, harvesting criteria/methods and geographic attributes will influence a carbon sensitive forest management are central for this project. Relations to ESR02, ESR04, ESR07, ESR08 and ESR11 exist.

Supervisor: Thomas Knoke (email: knoke@tum.de)

Early Stage Researcher Logan Bingham (email: logan.bingham@tum.de)

Who we are

A group of 10 academic partners and 12 non-academic partners working together for a contamination of “ideas” between the domains of forest growth and forest operating efficiency

Contacts

Project coordinator: TESAF Department, Università degli Studi di Padova ITALY

E-mail: skillforaction.tesaf@unipd.it

EU – Horizon 2020

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie

Grant Agreement 936355