PhD Candidate (100%) - Analysis of tree regeneration with empirical data and modeling

     
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WorkplaceZurich, Zurich region, Switzerland
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Description

The Forest Ecology Group at the Institute of Terrestrial Ecosystems of ETH Zurich, seeks a

PhD candidate (100%) - Analysis of tree regeneration with empirical data and modeling

The Forest Ecology Group at ETH Zurich seeks to appoint a PhD candidate to analyze and assess tree regeneration data with three main objectives: (1) to quantify recruitment rates of a wide range of European tree species by fusing heterogeneous data sets; (2) to evaluate the nature and extent of species-specific recruitment limitation along an extended environmental gradient in Europe using a model of long-term forest dynamics; and (3) to explore the implications of shifting recruitment patterns for forest dynamics under global climate change. A wide array of data is available for this project, including National Forest Inventories, Forest Reserves, Growth-and-Yield plots, and other sources. Forests will be affected strongly by human-induced climate change, mediated by changes of growth, mortality, and regeneration of trees. However, knowledge on the nature and extent of recruitment limitation for long-term forest dynamics is patchy and scarce. This project will provide a substantial contribution to elucidating the role of regeneration processes for forest dynamics.
The Forest Ecology Group at ETH is a dynamic interdisciplinary research team that examines both theoretical and applied questions in forest ecology using a combination of empirical and modeling techniques. The overarching aim of the group is to further our understanding of the structure and function of forest ecosystems, with a particular focus on mountain areas such as the European Alps. We offer world-class facilities in a relaxing work atmosphere with lots of opportunities for collaboration both within and beyond our group.

Required qualifications comprise an MSc degree in forest sciences, environmental sciences, ecology, forestry, geography, biology, landscape ecology, or a related field, and good knowledge of forest ecology. Knowledge of European forest ecosystems is an asset. Candidates should have good basic skills in statistics. Knowledge of the R software and experience with dynamic modeling techniques and computer programming are an asset. The contract is for one year; an extension by two to three years is foreseen, starting date is January 1, 2019 (negotiable within limits).

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