Thesis title:	Dynamic Ecosystem Models (DEM) as tools for tracing the effects of environmental and biotic factors on vegetation in shifting climates
PhD Programme:	Physical Sciences
Supervisor:	Anneli Poska, Senior Research Scientist
Co-supervisor:	Siim Veski, Professor
Offered by:	School of Science, Department of Geology

Description
The subject of the PhD project „ Dynamic Ecosystem Models (DEM) as tools for tracing the effects of major environmental and biotic factors on vegetation in shifting climates.” is closely connected to the personal research funding team grant (PRG323) led by Siim Veski „Tracking the time-lags of species response to environmental change using palaeo-proxy data and modelling (TrackLag)”. The PhD project is planned to start in 2019.
Current Earth System Model (ESM) or Dynamic Ecosystem Model (DEM) based assessments of climate-induced shifts in species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. As a consequence, most simulations of vegetation change at high northern latitudes project an immediate response of vegetation to climate change, with turnover rates at decadal rather than centennial scales. Howevere, the palaeoecological data suggests that non-climatic factors (migration and competitive capacity, nutrient availability etc.) can create substantial time-lags between the creation of favorable climatic conditions and range shifts.
The PhD project will focus on developing, evaluating, and employing a state-of-the-art version of an individual-based DEM LPJ-GUESS (Lund-Potsdam-Jena –General Ecosystem Simulator) in order to improve the predictions of the climate driven temperate forest composition change using a combination of palaeoecological, ecological and remote sensing datasets. The selected model is uniquely suitable for planned investigation as it combines individual and patch (neighbourhood) based representation of vegetation dynamics, incorporates the N-cycle and employs a representation of vegetation dynamics (successional processes: establishment, growth, mortality) similar to a forest gap model, allowing explicit representation of competition for resources (light, water, nutrients etc.).

This PhD project will:

• Compile an overview of model based assessments of vegetation responses to current climate change in a temperate zone and compare that with known palaeoecological evidence
• Prepare necessary inputs (e.g. climate, land use) for past, present, and future scenario runs of the DEM LPJ-Guess using the palaeoecological evidence and model based predictions
• Conduct a series of scenario runs and model sensitivity tests, and use the gained information to improve the ability of LPJ-Guess to predict climate driven vegetation changes in temperate zones.

Job description
The position is available for a 4-year period and your key tasks as a PhD student at TalTech are to:

• Manage and carry through your research project
• Attend PhD courses
• Write 3 scientific articles and your PhD thesis
• Teach and disseminate your research
• Stay at an external research institution for a few months, preferably abroad
• Work for the department

The student will be expected to conduct a series of DEM simulations, write and modify code written in C++, and to systematize and apply a number of different environmental and ecological datasets (climate, land use, etc.).

Qualifications
General admissions criteria:

• A good BSc and MSc degree from an internationally recognised university in a relevant Earth or Environmental science discipline (e.g. Physical Geography, Ecology (Paleoecology), Forestry etc. ). Applicants with a strong Physics, Chemistry, or Mathematics background with an interest in modelling and ecosystem sciences are also welcome.
• English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0, or equivalent level.

Specific candidate requirements:

• Highly motivated graduate, keen to work on a multidisciplinary project, good communicative skills, proactive and independent work
• Certified knowledge of at least one programming language and a willingness to learn C++
• An ability to work with GIS software  An emphasis will also be laid on previous publications (if any) and relevant work experience
• Previous experience or proven interest in the research field of earth sciences