Pulque is one of the oldest fermented beverages, with its origins dating back to pre-Hispanic Mexico. Recently, public consumption has increased. However, the majority of Agave plantations for pulque production have disappeared or been abandoned in recent decades. To create strategies for the conservation and production of pulque agaves, it is necessary to first determine their taxonomic identities and to better understand their genetic and morphological diversity. Despite the historical importance of pulque in Mexico, little attention has been placed on the study of Agave plants used for its production. Therefore, we analyzed the morphological diversity of vegetative characters of nine landraces of two Agave species (A. salmiana and A. mapisaga) which are widely cultivated for pulque production in Tlaxcala, Mexico. The analysis of morphological characters showed that the landraces largely clustered based on classic taxonomic relationships. One cluster of landraces associated with Agave mapisaga var. mapisaga and another with A. salmiana subsp. salmiana, but with the exception of A. salmiana subsp. salmiana "Ayoteco", which is more closely related with A. mapisaga var. mapisaga. Additionally, we analyzed the genetic relationships between 14 landraces and wild individuals using molecular markers (trnL and ITS). The identified genetic variants or haplotypes and genetic pools mainly corresponded with the species. In the case of "Ayoteco", incongruence between markers was observed. Low selection intensity, genetic flow events, and the plasticity of morphological traits may explain the high number of landraces without clear differences in their morphological diversity (vegetative characters) or genetic pools. The use of reproductive traits and massive sequencing might be useful for identifying possible morphological and genetic changes in the Agave landraces used for pulque production.

Summary Parametric nonlinear regression (PNR) models are used widely to fit weed seedling emergence patterns to soil microclimatic indices. However, such approximation has been questioned, mainly due to several statistical limitations. Alternatively, nonparametric approaches can be used to overcome the problems presented by PNR models. Here, we used an emergence data set of Phalaris paradoxa to compare both approaches. Mean squared error and correlation results indicated higher accuracy for the descriptive ability but similar poor performance for predictive ability of the nonparametric approach in comparison with the PNR approach. These results suggest that our nonparametric cumulative distribution function approach is a valuable alternative to the classical parametric nonlinear regression models to describe complex emergence patterns for P. paradoxa, but not to predict them.

Background Ant-plant mutualistic networks tend to have a nested structure that contributes to their stability, but the ecological factors that give rise to this structure are not fully understood. Here, we evaluate whether ant abundance and dominance hierarchy determine the structure of the ant-plant networks in two types of vegetation: oak and grassland, in two temperate environments of Mexico: Flor del Bosque State Park (FBSP) and La Malinche National Park (MNP). We predicted that dominant and abundant ant species make up the core, and submissives, the periphery of the network. We also expected a higher specialization level in the ant trophic level than in plant trophic level due to competition among the ant species for the plant-derived resources. Methods The ant-plant interaction network was obtained from the frequency of ant-plant interactions. We calculated a dominance hierarchy index for the ants using sampling with baits and evaluated their abundance using pitfall traps. Results In MNP, the Formica spp. species complex formed the core of the network (in both the oak forest and the grassland), while in FBSP, the core species were Prenolepis imparis (oak forest) and Camponotus rubrithorax (grassland). Although these core species were dominant in their respective sites, they were not necessarily the most dominant ant species. Three of the four networks (oak forest and grassland in FBSP, and oak forest in MNP) were nested and had a higher number of plant species than ant species. Although greater specialization was observed in the ant trophic level in the two sites and vegetations, possibly due to competition with the more dominant ant species, this was not statistically significant. In three of these networks (grassland and oak forest of MNP and oak forest of FBSP), we found no correlation between the dominance hierarchy and abundance of the ant species and their position within the network. However, a positive correlation was found between the nestedness contribution value and ant dominance hierarchy in the grassland of the site FBSP, which could be due to the richer ant-plant network and higher dominance index of this community. Conclusions Our evidence suggests that ant abundance and dominance hierarchy have little influence on network structure in temperate ecosystems, probably due to the species-poor ant-plant network and a dominance hierarchy formed only by the presence of dominant and submissive species with no intermediate dominant species between them (absence of gradient in hierarchy) in these ecosystems.

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Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). However, in many situations, experimental data are presented in a grouped way and, therefore, the standard nonparametric kernel estimators cannot be computed. Kernel estimators for the density and distribution functions for interval‐grouped data, as well as bootstrap confidence bands for these functions, have been proposed and implemented in the binnednp package. Analysis with different treatments can also be performed using a bootstrap approach and a Cramér‐von Mises type distance. Several bandwidth selection procedures were also implemented. This package also allows to estimate different emergence indices that measure the shape of the data distribution. The values of these indices are useful for the selection of the soil depth at which HTT should be measured which, in turn, would maximize the predictive power of the proposed methods. This paper presents the functions of the package and provides an example using an emergence data set of Avena sterilis (wild oat). The binnednp package provides investigators with a unique set of tools allowing the weed science research community to analyze interval‐grouped data.