Daniel B. Stouffer

This paper shows that coupling species' demography and interactions changes the structural stability of ecological communities in non-linear ways.

The paper shows that sublinear density dependence can arise from sequential shifts in resource limitation, without needing other factors like predation, and predicts superlinear dependence at high and low densities.

The paper evaluates grouping strategies in species-interaction models using Drosophila data, finding that optimal groupings vary between effects and responses and cannot be reliably predicted from species attributes.

The paper investigates how plant fidelity to root symbionts affects performance under changing community contexts, finding that fidelity to antagonists is stronger and mutualist fidelity impacts performance differently based on plant traits and herbivore presence.

The paper integrates intraspecific variation into population dynamics to show how mutualistic species persist, finding that specialized individuals promote persistence without competitors, but heterogeneous mixtures are better with competitors.

This paper adapts joint species distribution models to ecological networks to model Eltonian niches, revealing trait and phylogeny relationships and enabling interaction predictions without empirical data.

This study examines how introduced trout affect the recovery of native galaxiid fish populations after extreme flooding, finding that trout reduce growth rates and impact smaller fish more severely.

The paper examines how alpine-plant communities respond to warming and loss of dominant species, finding varied and often combined responses across different sites.

pymfinder analyzes network motifs in directed, undirected, unipartite, or bipartite networks, enabling node- and link-specific motif profile computation and weighted motif analysis.

The paper shows that ecological interactions share common evolutionary mechanisms, with differences only in parameter positions, not interaction types.

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.