direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Inhalt des Dokuments

Julie Louvrier

Lupe

"It is my deepest wish to provide science-based solutions for society, especially in the field of applied ecology and nature conservation research. I am particularly touched by the issues of recolonizing carnivore species and the problematics that come with it. My aim is to provide cutting-edge tools to wildlife managers to help anticipating possible conflicts with human activities while reaching the goals of stable and sustainable carnivore populations in Europe."

 

Biographical sketch

I received my engineering degree at the Montpellier engineering school for agricultural sciences, Montpellier SupAgro. There, I developed a strong interest in ecology and more particularly, conservation biology. As part of an exchange program with the University of Madison, Wisconsin, I studied animal ecology and ecological modelling. For my bachelor thesis, I investigated the differences in the choice of litter vegetation from white-tailed deer fawns, in different parts of the state of Wisconsin, under the supervision of Prof. Dr. Timothy Van Deelen at the University of Wisconsin.

A supervised gap year allowed me to realize two internships in order to develop my knowledge in ecology and expand my experience in different research facilities. The first internship consisted of studying ants’ communities as bioindicators of ecosystems, under the supervision of Dr. Alan Andersen, at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), in Darwin, Australia. During the second internship I established sampling protocols to assess the conservation status of two rare plants in the Parc National des Écrins in France. This internship was based in the Centre d’Ecologie Fonctionnelle et Evolutive in Montpellier (CEFE) and was supervised by Prof. Dr. Aurélien Besnard.

During my master thesis, I developed a first statistical model to assess wolves’ distribution in France, based on citizen-science data, under the supervision of Dr. Olivier Gimenez, in the department Conservation Biology in the CEFE. The general goal of my PhD was to develop robust statistical methods, based on presence-only datasets of wolves and lynx in Europe, to assess and predict their distribution. I received the award Prix la Recherche in the category Environment for the first paper I published on wolf distribution in France. (Louvrier, Julie, et al. "Mapping and explaining wolf recolonization in France using dynamic occupancy models and opportunistic data." Ecography 41.4 (2018): 647-660).

Following my PhD, I received a postdoctoral fellowship from the Deutscher Akademischer Austauschdienst (DAAD) to develop a project consisting of studying urban meso-carnivores communities based on camera trap surveys from citizen sciences at the Leibniz Institute for Zoo and Wildlife Research (Leibniz-IZW) in Berlin, under the supervision of Prof. Dr. Stephanie Kramer-Schadt. Recently, I received an IPODI fellowship for the project entitled “Developing a spatially explicit individual-based population model to assess and predict wolf (Canis lupus) recolonization in Germany” under the supervision of Prof. Dr. Stephanie Kramer-Schadt.

 

Research interests

Ecology, large carnivores, conservation biology, ecological statistics, spatial ecology, statistical modelling.

Contact

E-Mail: julie.louvrier at tu-berlin.de

 

 

Research Project

Developing a spatially explicit individual-based population model to assess and predict wolf (Canis lupus) recolonization in Germany

Duration: May 2020 - May 2022

Mentor: Prof. Dr. Stephanie Kramer-Schadt, Faculty VI, Animal Ecology

Abstract: The recovery of wolves and other large carnivores in human-dominated areas in Europe comes with challenges. The first question arising is about knowing where there are sufficiently large and functional areas left for populations to settle. In addition, due to the wolves’ predation on game and livestock, their recolonization comes with potential human-wildlife conflicts. Predictive models are therefore very important to guide conservation and management decisions and help to anticipate possible future conflicts. Until now, little research has been done into the dynamic prediction of wolves’ distribution in Germany.

In this project, we will develop a spatially-explicit individual-based model (IBM) to predict the future expansion of the population of wolves in Germany with a parametrization based on the available past and present data. Our main goal is to gain insight into the processes underlying the population expansion by making optimal use of all the available information about wolves’ biology, behaviour, and movements. The innovation will rely on the fact that no IBM accounting for population demography processes, dispersal processes and settlement processes has been done for a social species such as the wolf. Our approach will provide a cutting-edge tool in the context of the management of a species with possible conflictual interactions with human activities. With such an original model, it will also be possible to assess the effects of landscape on mechanisms underlying juvenile dispersal and settlement.

The main improvements of developing cutting-edge IBMs in this project, compared to previous habitat suitability analyses for wolves, are that the methodology applied considers the mechanism on the individual level, leading to outputs on the population level. On a methodological aspect, this study will constitute a timely step into the improvement and innovation of the current IBMs that have been done on large carnivores by including environmental covariates to explain the dispersal process of wolves. Additionally, including the pedigree at the first stages of the recolonization process, using presence-data combined with telemetry data, has not yet been done to our knowledge. The novelty will also rely in the use of a varied panel of data types. Furthermore, as wolves are currently recolonizing Germany, this project will bring urgently needed predictions about where wolves will occur, depending on different scenarios.

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

This site uses Matomo for anonymized webanalysis. Visit Data Privacy for more information and opt-out options.