The Horizontal Distribution of Branch Biomass in European Beech: A Model Based on Measurements and TLS Based Proxies

Modeling the horizontal distribution of tree crown biomass from terrestrial laser scanning data

Tree crown biomass is rarely assessed individually in forest monitoring, but when it is to be reported, standard conversion factors are commonly used for predicting crown biomass as a function of stem biomass. Further, in the conventional methods, the predicted total tree biomass is assigned exclusively to the stem position. In reality, however, tree and in particular crown biomass is spatially distributed over the entire crown projection area. In this study, we investigated the "Horizontal Biomass Distribution (HBD)" model, which serves to depict this biomass as a spatial distribution over the crown projection area: here, the individual tree crown biomass is modeled as a continuous distribution within the area defined by the crown projection. We examined two empirical HBD prediction models: (1) Weibull distribution; and (2) Segmented polynomial regression; which describe the biomass contained up to a given crown radius on the horizontal projection of individual trees, i.e., spatial distribution of crown biomass as a function of the horizontal distance from the stem. The approach was demonstrated using terrestrial laser scanning (TLS) on a sample of 33 urban trees from eight species. We found that (1) the segmented polynomial regression model revealed better performance in defining the HBD for various tree species; (2) a certain variability in HBD patterns was observed between the sample trees, with the variability being more pronounced between species groups than within species; and (3) the methodological approaches using TLS proxies are suitable and convenient to non-destructively assess the HBD, which would be otherwise impractical by direct measurements.

Forest Biometric Systems in Mexico: A Systematic Review of Available Models

Biometric systems are the basis of forest management and consist of a set of equations that describe the relationships between forest attributes and dendrometric variables. A systematic review of the state of the art of biometric systems in Mexico was carried out by a Mexican consortium (10 researchers), covering a period of 50 years ca (1970–2019), using the main scientific literature delivered by a systematic search (WoS, Scopus, Scielo, Redalyc) and a targeted search (theses, technical reports, etc.). A single selection criterion was established for the inclusion of information in the analysis: the document had to present at least one of the equations of interest. We found 376 documents containing 2524 equations for volume (69%), diameter (11%), height (9%) and site index (11%). These equations were developed for forest species mainly from temperate regions (88%), such as pine (66%) and oak (9%). Consequently, the Mexican states with the highest number of equations were Durango (28%), Chihuahua (17%), Hidalgo (13%) and Oaxaca (8%). Although large, the number of equations identified concentrated on a relatively small number of models: Schumacher & Hall and Fang et al. for volume; Chapman-Richards and Schumacher for site index and diameter; and Chapman-Richards and the allometric equation for height. An analysis of model fit, measured through R2, showed that, on average, the volume, diameter and site index models show high fit (R2 = 0.96), although this pattern was more consistent in the volume models. Publication bias was evaluated by means of a funnel plot analysis, with no apparent bias identified. A limitation of our study is that the information obtained is not updated to the present year; however, the 50-year trends allow us to assume that no recent significant changes in the patterns exist. Finally, we highlight the need to assess the predictive ability of the models to ensure accurate estimates to support better forest management decisions.