Dominique Gravel

This study identifies crown structure and growth characteristics as key predictors of maple syrup yield, explaining up to 47% of inter-individual variability in syrup production.

This study investigates how climate and competition affect population growth rates of 31 tree species across eastern North America, finding climate has a stronger impact than competition.

The paper investigates how network architectures influence coevolutionary dynamics and adaptation in ecological communities through simulations across empirical and artificial networks.

The paper integrates predator energetics and behavior into a functional response model to explain indirect interactions in a vertebrate community, finding that predator energetic balance drives changes in prey interactions.

The paper introduces the Ecological Coherence framework to analyze co-variation in community abundance dynamics across terrestrial and marine assemblages, finding weak correlations and key taxa influencing community responses.

This paper introduces Ecological Coherence (EC) and Ecological Network Coherence (ENC) to analyze how species co-responses to environmental changes are structured and how they predict ecological instability.

The paper simulates food web evolution to study how phylogenetic signal in trophic structure changes over time and examines its relationship with species network positions and diversification dynamics.

The paper examines nematode encapsulations in Galapagos snails to explore host-parasite interactions and their ecological and evolutionary implications.

The paper examines how snowmelt timing and predation influence species occurrence and community structure in Arctic ecosystems over 10 years.

The paper develops a framework to quantify uncertainty in ecological network construction due to stochasticity and sampling limitations.

The paper shows that species interactions vary more with climate than individual species do, highlighting the importance of considering interactions in community studies.

The paper develops a quantitative framework to model the biogeography of ecological interaction networks, finding that environmental factors influence species co-occurrence but not interactions, which are stochastic.

The paper argues that current species interaction network models are inadequate and proposes considering intra-specific variability to improve predictive understanding of ecological interactions.