Las mezclas de gramíneas y leguminosas muestran el potencial de aumentar la producción de biomasa aérea y subterránea en los barbechos andinos basados en el forraje

Descargue el texto completo en el portal de la revista Agronomy: https://doi.org/10.3390/agronomy12010142Los suelos altoandinos están amenazados por la intensificación de los sistemas de cultivo. Los barbechos mejorados basados en el forraje ofrecen una gran promesa para abordar este problema, pero es necesario investigar para entender mejor el potencial de las mezclas de especies frente a los monocultivos para apoyar múltiples objetivos de los agricultores, especialmente la producción de forraje y la conservación del suelo. Hemos utilizado un estudio en maceta para cuantificar la producción de biomasa aérea y subterránea, así como la absorción total de N de las mezclas de gramíneas y leguminosas entre cinco gramíneas: (1) avena (Avena sativa), (2) ryegrass (Lolium multiflorum), (3) festulolium (Lolium × Festuca genera), (4) bromo (Bromus catharticus), y (5) hierba de la huerta (Dactylis glomerata), y cuatro leguminosas: (1) veza (Vicia dasycarpa), (2) trébol rojo (Trifolium pratense), (3) medicago negro (Medicago lupulina), y (4) alfalfa (Medicago sativa) en relación al rendimiento de cada especie en monocultivo dentro de dos suelos de los Andes centrales peruanos. Los bicultivos de gramíneas y leguminosas demostraron un rendimiento superior, produciendo un 65% y un 28% más de biomasa seca total y de absorción total de N en promedio que los monocultivos. La biomasa aérea de los bicultivos estuvo significativamente influenciada por la especie de leguminosa presente, mientras que la biomasa subterránea estuvo más afectada por la especie de hierba en la mezcla. Al evaluar el crecimiento de cada especie por separado, nuestros resultados indican que el exceso de rendimiento fue impulsado más por el mayor crecimiento de las gramíneas en relación con las leguminosas. Nuestros resultados indican que la combinación de grupos funcionales clave (p. ej., gramíneas y leguminosas, anuales y perennes) es muy prometedora para el desarrollo de barbechos mejorados que apoyen la salud del suelo y la productividad en los agroecosistemas andinos.Soils of the Andean highlands are under threat from cropping system intensification. Improved forage-based fallows offer great promise to address this issue, but research is needed to better understand the potential of species mixtures vs. monocultures to support multiple farmer objectives, especially forage production and soil conservation. We used a pot study to quantify above- and belowground biomass production as well as the total N uptake of grass–legume pairs between five grasses: (1) oat (Avena sativa), (2) ryegrass (Lolium multiflorum), (3) festulolium (Lolium × Festuca genera), (4) brome grass (Bromus catharticus), and (5) orchard grass (Dactylis glomerata), and four legumes: (1) vetch (Vicia dasycarpa), (2) red clover (Trifolium pratense), (3) black medic (Medicago lupulina), and (4) alfalfa (Medicago sativa) relative to the performance of each species in monoculture within two soils from the central Peruvian Andes. Grass–legume bicultures demonstrated significant overyielding, producing 65% and 28% more total dry biomass and total N uptake on average than monocultures. Aboveground biomass of bicultures was significantly influenced by the species of legume present, while belowground biomass was more affected by the grass species in the mixture. When evaluating the growth of each species separately, our findings indicate that overyielding was driven more by the enhanced growth of grasses relative to legumes. Our findings indicate that combining key functional groups (e.g., grass and legume, annual and perennial) offers great promise for developing improved fallows for supporting soil health and productivity in Andean agroecosystems

Explaining Andean Potato Weevils in Relation to Local and Landscape Features: A Facilitated Ecoinformatics Approach

BACKGROUND: Pest impact on an agricultural field is jointly influenced by local and landscape features. Rarely, however, are these features studied together. The present study applies a "facilitated ecoinformatics" approach to jointly screen many local and landscape features of suspected importance to Andean potato weevils (Premnotrypes spp.), the most serious pests of potatoes in the high Andes. METHODOLOGY/PRINCIPAL FINDINGS: We generated a comprehensive list of predictors of weevil damage, including both local and landscape features deemed important by farmers and researchers. To test their importance, we assembled an observational dataset measuring these features across 138 randomly-selected potato fields in Huancavelica, Peru. Data for local features were generated primarily by participating farmers who were trained to maintain records of their management operations. An information theoretic approach to modeling the data resulted in 131,071 models, the best of which explained 40.2-46.4% of the observed variance in infestations. The best model considering both local and landscape features strongly outperformed the best models considering them in isolation. Multi-model inferences confirmed many, but not all of the expected patterns, and suggested gaps in local knowledge for Andean potato weevils. The most important predictors were the field's perimeter-to-area ratio, the number of nearby potato storage units, the amount of potatoes planted in close proximity to the field, and the number of insecticide treatments made early in the season. CONCLUSIONS/SIGNIFICANCE: Results underscored the need to refine the timing of insecticide applications and to explore adjustments in potato hilling as potential control tactics for Andean weevils. We believe our study illustrates the potential of ecoinformatics research to help streamline IPM learning in agricultural learning collaboratives

Standardized predicted impacts of explanatory variables on Andean potato infestations.

<p>The model is initially set to predict infestations for a field with no pesticide applications and with mean (for continuous variables) or most common (for ordinal and categorical variables) values for all other explanatory variables. For continuous explanatory variables, bars reflect predicted changes in infestations in response to a one standard deviation increase in the explanatory variable. For ordinal explanatory variables, the bars reflect predicted changes in infestations in response to a single unit increase in the explanatory variable; except for the number of hillings, for which only a decrease could maintain predictions within observed bounds.To obtain multi-model predictions, parameter estimates were multiplied by their corresponding parameter weights. Hence, predicted effects are “attenuated” for explanatory variables with parameter weights smaller than 1.</p