PhD project offered by the IMPRS-gBGC in

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Project description

In the context of future climate variability, the feedbacks between the terrestrial biosphere and the climate system still represent one of the highest uncertainties in prognostic simulations. These uncertainties are strongly linked with our current ability in appropriately describing the co-variability between climate and the turnover times of carbon in terrestrial ecosystems. Further, current global estimates show that the spatial co-variation between climate variables and whole ecosystem carbon turnover times (τ) vary strongly in space, and may even show opposite patterns between regions. Theoretically, these regional differences not only depend on climate variability and climate space characteristics, but also on local vegetation properties and other environmental conditions (e.g. soil water holding capacity, plant mortality and disturbance regimes, nutrient availability, among others). Exploring the potential of different co-variates in explaining the spatial variability of τ may shed light on the relevant dynamics that Earth System Models need to narrow down the between model divergence of biosphere-atmosphere feedbacks in prognostic simulations. Furthermore, the search for a breakdown of whole ecosystem turnover times into plant and soil carbon turnover times is key for understanding mechanisms driving whole ecosystem responses.
The current PhD project focuses on exploring the spatial controls of state of the art and improvements on estimates of τ based on novel flux and stock products, towards attaining an overall consistent reasoning behind the spatial variability of carbon turnover times in terrestrial ecosystems. Such an approach necessarily requires a strong focus in exploring spatial and temporal links using different statistical methods. Ultimately, exploring the ability to disentangle between vegetation and soil dynamics (“green-τ” and “brown-τ”) embeds the potential to achieve a mechanistic reasoning with relevance in informing different modeling frameworks. 

Requirements

Applications to the IMPRS-gBGC are open to well-motivated and highly-qualified students from all countries. Prerequisites for this PhD project are:
  • a MSc degree with a background in a quantitative science (e.g. geo-ecology, environmental sciences, biology, applied mathematics, physics, or computer science),
  • interest in terrestrial ecosystems and biogeochemical cycles,
  • experience in advanced statistical methods
  • very good oral and written communication skills in English

After you have been selected

The IMPRS-gBGC office will happily assist you with your transition to Jena.
The conditions of employment, including upgrades and duration follow the rules of the Max Planck Society for the Advancement of Science and those of the German civil service. The gross monthly income amounts about 2000 EUR, which will cover all your expenses in Germany.
The Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. The Max Planck society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.

Global distribution of τ [Carvalhais, et al., Nature, 2014].
Global distribution of τ [Carvalhais, et al., Nature, 2014].


>> more information about the IMPRS-gBGC + application