Predicting Whole Forest Structure, Primary Productivity, and Biomass Density From Maximum Tree Size and Resource Limitations
Christopher P. Kempes, Sungho Choi, William Dooris, Geoffrey B. West

TL;DR
This paper presents a mechanistic framework that predicts forest structure, primary productivity, and biomass density using only maximum tree size and resource limitations, linking local meteorology to global ecological processes.
Contribution
It introduces a predictive model that relates maximum tree size to forest structure and productivity, reducing parameter complexity and enabling environmental predictions from local data.
Findings
Forests converge to model predictions as they mature.
Maximum tree size can be derived from local meteorology.
The framework links local environmental factors to global ecological metrics.
Abstract
In the face of uncertain biological response to climate change and the many critiques concerning model complexity it is increasingly important to develop predictive mechanistic frameworks that capture the dominant features of ecological communities and their dependencies on environmental factors. This is particularly important for critical global processes such as biomass changes, carbon export, and biogenic climate feedback. Past efforts have successfully understood a broad spectrum of plant and community traits across a range of biological diversity and body size, including tree size distributions and maximum tree height, from mechanical, hydrodynamic, and resource constraints. Recently it was shown that global scaling relationships for net primary productivity are correlated with local meteorology and the overall biomass density within a forest. Along with previous efforts, this…
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Taxonomy
TopicsPlant Water Relations and Carbon Dynamics · Ecology and Vegetation Dynamics Studies · Fire effects on ecosystems
