The global need to transition to renewable and decentralized systems entails agricultural systems as producers of residual biomass. Avocado trees (Persea americana Mill.) are one of the main woody crops cultivated in Mexico, with over 150,000 hectares grown in the country. The aim of the present study is to evaluate the use of avocado pruning residues as an energy input, focusing on the revalorization of biomass and the generation of economic benefits for small producers in the region. For that purpose, we developed allometric equations to calculate biomass availability from pruning residues, evaluated their thermochemical properties, and proposed technological alternatives for their energy use. Two allometric equations for pruning residues as a function of tree height and crown diameter were obtained: one for light and minor maintenance pruning (R² = 0.63) and one for rejuvenation pruning (R² = 0.86). From these equations, we estimate the mean amount of biomass generated from light and rejuvenation pruning to be 42.7 and 25.1 kg per tree and year, respectively, which amounts to 1324 and 780 kg ha⁻¹ DM (dry matter), with an energy potential of 26.2 and 15.4 GJ ha⁻¹. The thermochemical analysis shows that a higher proportion of leaves generates a higher ash content, which reduces the quality of the residues as a fuel. Avocado pruning residues have high potential for energy use and could be implemented in the industrial and residential sectors, generating a complementary source of income for producers.

It is argued that counting the total number of times a scientific article is cited by others, does neither result in a proxy for its cognitive impact nor for its quality. One would have to distinguish at least substitutable and fundamental references. A supposed correlation between peer review assessments and citation counts is conceptually problematic, because peer review includes objective as well as subjective considerations (convictions). With refined methods, however, a differential citation analysis might be able in the future to answer if a given article did or did not have positive cognitive impact on subsequent research.

Dendrochronology, the study of annual rings formed by trees and woody plants, has important applications in research of climate and environmental phenomena of the past. Since its inception in the late 19^th century, dendrochronology has not had a way to quantify uncertainty about the years assigned to each ring (dating). There are, however, many woody species and sites where it is difficult or impossible to delimit annual ring boundaries and verify them with crossdating, especially in the lowland tropics. Rather than ignoring dating uncertainty or discarding such samples as useless, we present for the first time a probabilistic approach to assign expected ages with a confidence interval. It is proven that the cumulative age in a tree-ring time series advances by an amount equal to the probability that a putative growth boundary is truly annual. Confidence curves for the tree stem radius as a function of uncertain ages are determined. A sensitivity analysis shows the effect of uncertainty of the probability that a recognizable boundary is annual, as well as of the number of expected missing boundaries. Furthermore, we derive a probabilistic version of the mean sensitivity of a dendrochronological time series, which quantifies a tree’s sensitivity to environmental variation over time, as well as probabilistic versions of the autocorrelation and process standard deviation. A computer code in Mathematica is provided, with sample input files, as supporting information. Further research is necessary to analyze frequency patterns of false and missing boundaries for different species and sites.

Growth curves are monotonically increasing functions that measure repeatedly the same subjects over time. The classical growth curve model in the statistical literature is the Generalized Multivariate Analysis of Variance (GMANOVA) model. In order to model the tree trunk radius (r) over time (t) of trees on different sites, GMANOVA is combined here with the adapted PL regression model Q = A·T+E, where for and for , A = initial relative growth to be estimated, , and E is an error term for each tree and time point. Furthermore, Ei[–b·r] = , , with TPR being the turning point radius in a sigmoid curve, and at is an estimated calibrating time-radius point. Advantages of the approach are that growth rates can be compared among growth curves with different turning point radiuses and different starting points, hidden outliers are easily detectable, the method is statistically robust, and heteroscedasticity of the residuals among time points is allowed. The model was implemented with dendrochronological data of 235 Pinus montezumae trees on ten Mexican volcano sites to calculate comparison intervals for the estimated initial relative growth . One site (at the Popocatépetl volcano) stood out, with being 3.9 times the value of the site with the slowest-growing trees. Calculating variance components for the initial relative growth, 34% of the growth variation was found among sites, 31% among trees, and 35% over time. Without the Popocatépetl site, the numbers changed to 7%, 42%, and 51%. Further explanation of differences in growth would need to focus on factors that vary within sites and over time.