Species-level networks emerge as the combination of interactions spanning multiple individuals, and their study has received considerable attention over the past 30 y. However, less is known about the structure of interaction configurations within …
Inferring the structure of bipartite (e.g. pollination, frugivory, or herbivory) networks from field (observational) data is a challenging task. Interaction data are hard to collect and require typically large sampling efforts, particularly to characterize infrequent interactions.
The consequences of plant–animal interactions often transcend the mere encounter stage, as those encounters are followed by a chain of subsequent stages on the plant’s reproductive cycle that ultimately determine fitness. Yet, the dissemination and …
Mutualistic interactions among free-living species generally involve weak links and highly asymmetric dependence among partners, yet our understanding of factors beyond their emergence is still limited. Using individual-based interactions of a …
The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 …
Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data …
UPDATE 26 October 2022: There is now a DHARMa.helpers package that facilitates checking Bayesian brms models with DHARMa. Check it out!
The R package DHARMa is incredibly useful to check many different kinds of statistical models.
Hurricane winds can have large impacts on forest structure and dynamics. To date, most evaluations of hurricane impacts have focused on short-term responses after a hurricane, often lacked pre-hurricane measurements, and missed responses occurring …
Slides discussing variable selection, information criteria (AIC, BIC, DIC), and other statistical modelling issues, with a focus on modelling ecological data.