Daniel S. Falster

The paper compares climate influences on native and introduced plant species in Australia, finding native annuals are more climate-dependent than introduced ones.

The paper quantifies reproductive allocation in perennial shrubs across their lifetimes using nutrient currencies, finding higher costs than typical estimates and highlighting nutrient resorption's role in amplifying these costs.

This paper presents a general framework explaining variation in plant economics traits across environments and ontogeny through three core assumptions about growth optimization and tradeoffs.

Across 109,626 wood density records from 16,829 plant species (GWDD v.2), intraspecific variation explains 15% of global variance, tracks interspecific environmental gradients at 20-30% magnitude, and limits single-plant predictability.

The paper creates a high-resolution global map of wood density using species and vegetation data, showing improved accuracy and a wider density range than previous estimates.

The paper analyzes global tree crown architecture to identify factors driving diversity in height, crown size, and shape across species.

The paper introduces an R package for hierarchical Bayesian longitudinal modeling of growth data, providing tools for model fitting and case studies.

This paper introduces a hierarchical Bayesian model to improve growth and size estimates from repeat forest surveys by accounting for measurement error and individual variation.

The paper introduces a data model, workflow, and R package for building harmonised ecological trait databases that adhere to FAIR principles.

APCalign aligns and updates scientific names for Australian vascular plants to the most likely currently accepted names using the Australian Plant Census or APNI.

The paper quantifies reproductive effort allocation across 14 plant species, revealing trade-offs and shifts in investment among reproductive tissues.

This paper reviews reproductive allocation schedules in woody plants, finding variation in strategies and suggesting more data is needed to integrate theory with observation.