Nuevos escenarios para la docencia universitaria : entornos híbridos y pedagogías emergentes.

Memorias del IX Simposio Internacional de Docencia Universitaria (SIDU)Los trabajos reunidos en esta Memoria representan una contribución importante al campo de la educación y de la docencia universitaria, en tanto muestran distintas maneras de responder a las problemáticas educativas cotidianas y presentan propuestas para afrontar los retos emergentes en el campo de la educación superior. Invitamos a los lectores a realizar una lectura atenta y crítica de los trabajos compilados en esta publicación. Estamos seguros de que este acercamiento propiciará la reflexión y el análisis riguroso de los objetos de estudio abordados por los autores, y estimulará la generación de nuevos proyectos de investigación, intervención e innovación educativa que incidan en el desarrollo de mejores prácticas de docencia en educación media superior y superior.Pimera edición digitaldoi.org/10.56019/EDU-CETYS.2024.182

Global urban environmental change drives adaptation in white clover

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

Comparison of relatedness estimators based on empirical genetic data of humpback whales (<i>Megaptera novaeangliae</i>) in the Gulf of Maine

Relatedness is a measure used in population biology to gain insight into heritability, kin selection, social systems, captive breeding, mating strategies as well as population structure. Several relatedness estimators have been developed to infer pairwise relatedness between individuals from genotype data, and there is considerable interest in their reliability. Relatedness estimators appear to be highly dependent on specific population characteristics (e.g. mating system), and data quality. Therefore, a prior assessment of estimator performance is essential before deciding on which to apply to a specific population and objective. However, the majority of studies aimed at assessing the performance of relatedness estimators have used simulated genotype data, and only rarely empirical genotypes from known pedigrees. The aim of this study was to conduct an evaluation of the performance of the available relatedness estimators using known relationships and empirical genotype data from an outbred population of humpback whales in the Gulf of Maine. Consequently, the most reliable measures can be applied to species with similar characteristics where the relatedness is unknown. We employed data from 20 polymorphic microsatellite markers in 425 individuals and two popular software packages (ML-RELATE, COANCESTRY) to evaluate a suite of common relatedness estimators, categorized as maximum likelihood and method of moments estimators. The results of our study showed that the performance of relatedness estimators was affected by the relationship category targeted in the assessment. The maximum likelihood methods overall performed better, but ambiguities and higher misclassification was detected with relationship categories allowing inherent variance among loci. The necessity of merging the two estimator categories for evaluation is arguable, as method of moments estimators often have values outside the true relatedness range (0,1). Overall, our results indicate that estimates of pairwise relatedness must be conducted with care to avoid incorrect inferences which potentially could have conservation ramifications