At COSSEE, we combine open science, evidence synthesis, meta-science, and methodological development to answer important questions in ecology and evolution while improving how research itself is done.
Led by Dr. Shinichi Nakagawa and supported by the Canada Excellence Research Chair program, the group works across life-history evolution, trans-generational effects, environmental change, evolutionary medicine, eco-toxicology, and research reliability.
Explore COSSEE Research
Use the switches below to navigate the page by objective: start with the overall logic of the program, move into the three research hubs, inspect core methods, or scan the current and historical project portfolio.
The core objective
COSSEE integrates cutting-edge ecological and evolutionary research with open science practices to produce evidence that is more rigorous, transparent, collaborative, and reusable. The goal is not only to answer scientific questions, but also to improve the systems, tools, and standards that shape research quality.
That means building a research program where synthesis, computation, statistics, and open workflows are not separate pieces, but part of the same engine.
Work starts from fundamental and applied questions in ecology, evolution, environmental change, and evidence quality.
Step 2Build better evidence
We combine experiments, big data, literature synthesis, and meta-analytic workflows to map what is known and what is missing.
Step 3Improve the methods
Statistical development, reproducible pipelines, and AI-supported infrastructure make the research process itself stronger.
Step 4Share reusable outputs
Open tools, transparent reporting, and collaborative synthesis communities help others reuse, update, and extend the work.
3linked hubs structure the overall research program.
4+major workflow stages connect questions, synthesis, methods, and reusable outputs.
2main lenses guide the work: answering ecological questions and improving research practice.
Manyprojects span fundamental biology, applied environmental issues, and meta-scientific innovation.
Research Synthesis Hub
This hub aggregates and synthesizes global evidence to map knowledge, identify gaps, and build stronger comparative understanding across ecology and evolution.
Typical outputs: meta-analyses, systematic reviews, evidence maps, research weaving.
Main value: turning scattered studies into coherent evidence.
Example themes: PFAS, disease prevalence, thermal plasticity, parental environments.
Meta-Research Hub
This hub studies research quality itself, including rigor, bias, replicability, and how scientific systems can become more reliable and more equitable.
Main value: improving how evidence is produced and interpreted.
Example themes: publication bias, taxonomic bias, geographic bias, replicability.
Open Science Infrastructure
This hub builds the workflows, tools, and community systems that make transparency and reproducibility easier to practice at scale.
Typical outputs: AI-assisted pipelines, open platforms, reusable code, reporting guidance.
Main value: lowering the practical barriers to better science.
Example themes: screening automation, data extraction, collaborative infrastructure.
Why these hubs work together
COSSEE's structure is intentionally connected: synthesis reveals what the evidence says, meta-research tests how trustworthy that evidence is, and infrastructure makes it easier to do the next round of work better. That loop is a defining part of the program.
COSSEE uses interdisciplinary approaches that range from behavioural experiments and molecular tools to computational models, big-data analyses, and research synthesis. Different projects combine these elements in different ways, but the general philosophy stays the same: build evidence carefully, document it openly, and make methods reusable.
What makes the methodology distinctive
Variance-aware thinking: not just whether means differ, but how distributions, variability, and structure change.
Cross-scale synthesis: combining individual studies, large datasets, and higher-order syntheses.
Method development alongside application: statistical and computational tools are part of the research program, not just support work.
Open-by-design practice: registrations, reproducible workflows, transparent reporting, and reusable outputs are built into the pipeline.
Current projects
Evidence synthesis for PFAS effects on biota
Meta-analysis on trans-generational effects of parental environments
Sex differences in thermal plasticity
Taxonomic and geographic biases in academic literature
Development of effect sizes for covariance, skewness, and kurtosis comparisons
Phylogenetic multilevel meta-analyses
Interactive effects of stress and environmental enrichment on animal behaviour
Global synthesis of disease prevalence in corals
Robust inference and reproducibility in ecology and evolution
Key research topics
Fundamental: sexual selection, mating systems, parental care, animal personality, ageing, phenotypic plasticity.
