Mapping Evidence to Theory in Ecology
Mapping Evidence to Theory in Ecology
Addressing the Challenges of Generalization and Causality
September 2024 - February 2025
Ecology as a scientific discipline is expected to provide the knowledge needed for solving the biodiversity crisis. Accordingly, ecological research generates a steeply increasing amount of data and empirical findings, aimed at increasing knowledge about ecological systems. In principle, this rise in information should lead to a steady improvement of understanding of these systems, and thus also to a steady increase in information that can directly be used for improving biodiversity protection and management.
However, the translation of knowledge gained in single empirical studies into more general knowledge about ecological systems and into practically useful knowledge is not straightforward. Ecological systems are highly complex, and ecological processes are strongly context dependent. This leads to the fact that empirical results from single case studies are hard to extrapolate to other systems, and hard to translate into meaningful instructions for management. The core problem is how to synthesize the results of large amounts of case studies that are highly diverse with respect to research approach (e.g. field surveys or controlled lab experiments) as well as study systems (e.g. plants or insects, dry grasslands or oceans).
Meaningful synthesis needs to take ecological complexity into account and needs to assure that important information on the respective context of the study is not lost. What is needed, thus, are tools and workflows that allow developing 'case-specific generalizations'. Recent advances in data science and AI technology may offer novel ways of dealing with complexity in ecology and may allow the development of knowledge synthesis tools that can manage context
dependence. Especially promising seems the idea to bring together advanced AI based technologies with conceptual causal models, because this may allow moving beyond pure pattern recognition towards causal inference. The vision is that complex, multifactorial hypotheses about ecological mechanisms would become the basis of a digital atlas of knowledge, and in this atlas the available empirical evidence would be mapped on these hypotheses to allow for case-specific explanations and predictions.
Members
- Convenor
PD Dr. Tina Heger
Leibniz Institute of Freshwater Ecology
and Inland Fisheries (IGB)Freie Universität Berlin
Institute of Biology- Fellows
Dr. Alejandra Parreno
Technical University of Munich
TUM School of Life SciencesDr. Aline Potiron
Utrecht University /
Freudenthal Institute
Postdoctoral Researcher in the philosophy of the life sciencesJ.-Prof. Dr. Alkistis Elliott-Graves
Bielefeld University
Faculty of History, Philosophy and Theology / Department of PhilosophyProf. Dr. Alsayed Algergawy
University of Passau
Faculty of Computer Science and MathematicsProf. Dr. Anika Groß
Anhalt University
Computer Science and LanguagesProf. Dr. Birgitta König-Ries
Friedrich Schiller University Jena
Faculty of Mathematics und Computer ScienceDr. Bruno Travassos-Britto
University of Toronto Mississauga
Biology FacultyDr. Carlos Arnillas Merino
University of Toronto ScarboroughDr. Daniel Mietchen
FIZ Karlsruhe (Location Berlin)
Leibniz Institute for Information InfrastructureDaphne Auer
Friedrich Schiller University Jena
Computer ScientistDr. Eleonora Louise Slabbert
Anhalt University
Agriculture, Ecotrophology, and Landscape DevelopmentProf. Dr. Eric Higgs
University of Victoria
School of Environmental StudiesProf. Dr. Federica Russo
Utrecht University
Freudenthal InstituteDr. Florencia Yannelli
Instituto Argentino de Investigaciones de las Zonas Áridas (IADIZA)
Mendoza, ArgentinaHrishikesh Jadhav
Junior Data Scientist
Universität Passau
Master degree Artificial Intelligence EngineeringDr. Jennifer D'Souza
TIB, Hannover
Junior AI Research Group LeadDr. Jonas Wahl
TU Berlin
Postdoctoral ResearcherProf. Dr. Jonathan Jeschke
Freie Universität Berlin
Institute of BiologyLeibniz Institute of Freshwater Ecology
and Inland Fisheries (IGB)Dr. Josh Brian
Kings College, London
Department of Geography
Faculty of Social Science & Public PolicyDr. Lars Vogt
TIB, Hannover
Comm. Head of ORKG Curation & Community BuildingLéna Bureau
McGill UniversityDr. Lena Neuenkamp
Institute of Landscape Ecology
Münster UniversityDr. Lotte Korell
Helmholtz Centre for Environmental Research
Department of Species Interaction Ecology (SIE)Dr. Manuel Pacheco-Romero
Leuphana University Lüneburg
Social Ecological Systems InstituteMarc Brinner
Bielefeld University
Faculty of Linguistics and Literary StudiesProf. Dr. Marie I. Kaiser
Bielefeld University
Faculty of History, Philosophy and Theology / Department of PhilosophyMoritz Plenz
Heidelberg University
Department of Computational Linguistics
Doctoral StudentAss. Prof. Nancy Shackelford
University of Victoria
School of Environmental StudiesProf. Dr. Phyllis Kristin Illari
University College London
Department of Science And Technology StudiesDr. Robert Frühstückl
Faculty of History, Philosophy and Theology / Department of Philosophy
Bielefeld UniversityProf. Dr. Sina Zarrieß
Bielefeld University
Faculty of Linguistics and Literary StudiesTarek Al Mustafa
Friedrich-Schiller Universität Jena
Faculty of Mathematics and Computer ScienceDr. Timothy James Alamenciak
University of WaterlooProf. Dr. Vicky Temperton
Leuphana University Lüneburg
Institute of Ecology