The Mexican Sierra Madre Occidental (SMO) represents a region where hundreds of plant species reach the limits of their northern or southern range. The SMO also features a unique cultural diversity, and many communities living within the forest or in its close vicinity depend on the products and services that these forests provide. Our study was based on a large set of remeasured field plots placed in the forests of Durango which are part of the SMO. Using hierarchical clustering, three distinctly different forest types were identified based on structural differences and the relation between stem density and basal area. Maximum forest densities were estimated using a 0.975th quantile regression. Forest production (expressed as current periodic volume increment per unit of area and time) was estimated based on number of stems, forest density, mean height, and forest diversity. Forest density is the principal factors affecting periodic volume production. The discussion presented recommendations for the sustainable use of this unique natural resource. Maintaining minimum levels of residual density is key to ensuring the continued viability of the forests of the Mexican SMO. Future research is needed to identify optimum residual structures, productive residual densities, and desirable levels of biodiversity.
Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystems.
Research Highlights: Analyzing the contrasting ecological gradients makes it easier to understand the influence of climate on carbon accumulation. Background and Objectives: The increasing climatic variability has implications for vegetation, impacting on its ecological functions, among which carbon accumulation stands out. In the present study, we used climate-dendrochronology relationships to evaluate carbon accumulation in two conifer species that grow in contrasting humidity sites: Pinus strobiformis Engelm (mesic sites) and Pinus leiophylla var. chihuahuana (Engelm.) Shaw (arid sites). Materials and Methods: Using a dendrochronological approach, we estimated the correlation of biomass and carbon accumulation of each species with some climatic variables (temperature, precipitation, and a drought index) and generated a linear mixed model. Results: The response in carbon accumulation between species with respect to climate was significantly different. P. strobiformis showed a positive correlation with the climatic variables analyzed, while in P. leiophylla the correlation was negative, except with precipitation. Conclusions: These results show that forests in both mesic and arid sites are prone to climate changes, although their responses are different, impacting the productivity and carbon cycles of forest ecosystems.
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