Quantifying the density of live trees in forest stands and partitioning it between species or other stand components is critical for predicting forest dynamics and responses to management, as well as understanding the impacts of stand composition and structure on productivity. As plant traits such as shade tolerance have been proven to refine understanding of plant community dynamics, we extended a previous model relating maximum stand density to wood specific gravity to incorporate shade tolerance as an additional functional trait. Additionally, we included climatic variables that might influence ecological
dynamics and modulate species-specific traits, across a region and also potentially over time under climate change scenarios. We used data from the USDA Forest Service, Forest Inventory and Analysis program for three states in the northern United States (Minnesota, Wisconsin, and Michigan) that reflect strong gradients in climate and species composition, to fit a maximum density model by quantile regression. The resulting strictly additive density measure conforms well to both existing silvicultural guidance and to observed densities of monocultures that lack such guidance. Wood specific gravity appears to interact with precipitation, while shade tolerance interacts with temperature, in driving maximum density relationships. Our proposed maximum stand density model is not only parsimonious for field application
in management situations, but also empowers the evaluation of the effects of future climate and tree range scenarios on forest management guidelines.
ETS Ingenierías Agrarias Universidad de Valladolid - Avd. Madrid s/n
34004 - PALENCIA - Localización
INIA-CIFOR - Ctra. A Coruña km 7,5
28040 - MADRID - Localización
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