Mejora la biodiversidad en ecosistemas nuevos restaurando la complejidad ecológica ~ Bioblogia.net

4 de marzo de 2023

Mejora la biodiversidad en ecosistemas nuevos restaurando la complejidad ecológica

Oferta compartida por Cristina


Biodiversity Dynamics in Novel Ecosystems


Applications are invited for a PhD fellowship/scholarship at Graduate School of Natural Sciences, Aarhus University, Denmark, within the Biology programme. The position is available from August 2023 or later.


Title:
Biodiversity Dynamics in Novel Ecosystems


Research area and project description:
This PhD project is part of the newly established Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), funded by the Danish National Research Foundation. ECONOVO aims to provide new perspectives on widely emerging ecological novelty and seek out strategies for how to steer towards the most positive outcomes for the biosphere. Novel ecosystems (NEs) have species compositions and/or abiotic conditions without historical precedent and are assembling rapidly around the world. By the late 21st century most of Earths ecosystems are expected to be NEs. Key drivers are climate and atmospheric change, globalization and transportation of organisms, and extirpation of large-sized organisms. The spread of NEs is likely to profoundly affect biosphere functioning, but how so is poorly understood. To address this complex theme, ECONOVO will take an unparalleled, interdisciplinary approach, integrating Big Data and field-based ecology, satellite-based remote sensing, archaeology, paleoecology, and population genomics.

This PhD project will be part of ECONOVO research theme 2: Complexity restoration. We will test if restoring ecological complexity can enhance species diversity in NEs, with specific focus on trophic complexity linked to megafauna. In this project we will employ a combination of large-scale macroecological approaches combined with detailed field studies in South Africa. We will use study areas in South Africa to populate a gradient of ecological novelty, quantified using non-native plant species composition and dynamics, and intersect this with a gradient of trophic complexity, quantified using megafauna community composition and dynamics. The analysis will be repeated in two regions with contrasting ecosystem productivity and biogeographic setting. The large-scale approaches will rely on existing large data bases and state-of-the-art remote sensing data and techniques. The field component will include detailed measurements on vegetation structure using terrestrial LiDAR and overall biodiversity measurements focused on plants and potentially other taxa.

The project is embedded within ECONOVO and will require a high degree of collaboration with ECONOVO staff and external collaborators. The project is twinned with a parallel PhD project based in South Africa, and strong collaboration notably during fieldwork, is required.


Please upload a project description (½-4 pages). This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found.

Qualifications and specific competences:
While the overall aims of the PhD project are outlined, the candidate is expected and encouraged to contribute ideas and together with the supervisors and collaborators develop the research based on previous work and initial findings.

Applicants must have a relevant MSc degree in ecology, biology or equivalent and have graduated before the application deadline.

Applicants must have experience with quantitative ecological analyses and a strong willingness to further develop skills in spatial analyses and working with big data, including remote sensing data. Coding and data handling in R and Google Earth Engine will be essential to the project, and experience with these is an advantage.

Experience with field-based ecology is highly desirable and a willingness to perform fieldwork in beautiful but sometimes harsh environments is essential. Specific knowledge of plants or other taxonomic groups is an advantage. Experience with (terrestrial) laser scanning is an advantage.

The successful candidate is expected to have strong collaborative skills, strong potential to publish at a high international level, and have excellent command of English. International applicants who do not have English as their first language must prove excellent English language writing skills and fluency.


Place of employment and place of work:
The place of employment and work is Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) and Section for Ecoinformatics & Biodiversity (ECOINF), Department of Biology, Aarhus University, Ny Munkegade 116, DK-8000 Aarhus C, Denmark.


Contacts:
Applicants seeking further information for this project are invited to contact: Professor Jens-Christian Svenning, email: svenning@bio.au.dk, Assistant Professor Robert Buitenwerf, email: buitenwerf@bio.au.dk or Assistant Professor Elizabeth Le Roux, email: eleroux@bio.au.dk



How to apply:

For information about application requirements and mandatory attachments, please see the Application guide. Please read the Application guide thoroughly before applying.

When ready to apply, go to https://phd.nat.au.dk/for-applicants/apply-here/ (Note, the online application system opens 1 March 2023)Choose February 2023 Call with deadline 1 May 2023 at 23:59 CET.
You will be directed to the call and must choose the programme “Biology”.
In the boxed named “Study”: In the dropdown menu, please choose: “Biodiversity Dynamics in Novel Ecosystems (BiDNoE)”

Please note:The programme committee may request further information or invite the applicant to attend an interview.
The project will only be initiated if the graduate school/the faculty grants funding.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background.

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