Site sensitive maximum stand density index models for mixed conifer stands across the Inland Northwest, USA

Site sensitive maximum stand density index models for mixed conifer stands across the Inland Northwest, USA

https://ift.tt/2KrQ8Mg

Publication date: 15 February 2019

Source: Forest Ecology and Management, Volume 433

Author(s): Mark J. Kimsey, Terry M. Shaw, Mark D. Coleman

Abstract

Density management is a key silvicultural tool for developing management prescriptions that maintain and enhance forest health and productivity, particularly in droughty, fire-prone ecosystems of the Inland Northwest, USA. Within this context, understanding the role of species mixing, climate, topography, and soil properties on maximum stand density is critical for predicting forest stand response to management given a suite of site characteristics and species composition. We assembled a dataset from public and private land management organizations that allowed us to test the role of ecological variables on modifying maximum stand density frontiers. Maximum stand density frontier models were built for selected conifer species using stochastic frontier regression. The influence of species mixing was assessed by including as a covariate basal area proportion of the three conifer species of interest in this study: Pinus ponderosa var. ponderosa, Pseudotsuga menziesii var. glauca, and Abies grandis var. idahoensis. A single, parsimonious model was found to fit each species, with variable coefficients reflecting species adaptation to varying abiotic site factors across the region. Site factors that increased maximum density included cool, moist conditions, soils containing volcanic ash over coarse-textured bedrock, and high tree-species diversity. These observations correspond to regional silvicultural guidance, thereby providing both a site-sensitive, quantitative maximum density measure for mixed species stands, and a tool for evaluating the effect of climate scenarios on future stand carrying capacity.

Superforest

via ScienceDirect Publication: Forest Ecology and Management https://ift.tt/2zaqiu8

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