Suchergebnisse

This study investigated the interplay between the class climate, learning motivation, and learning effectiveness among college students in Xi'an, China. The participants of this study were college students in Xi'an, and the data were collected through the convenience sampling method. Out of the 560 distributed questionnaires, 541 valid responses were collected. The collected data were analyzed through item analysis, confirmatory factor analysis, and reliability analysis. The results revealed that there was no significant difference in class climate, learning motivation, and learning effectiveness regarding gender, while grade level demonstrated significant differences in these dimensions. In addition, in the linear regression analysis, class climate, learning motivation, and learning effectiveness all showed significant positive correlations in that class climate and learning motivation had a significant positive impact on learning effectiveness. Within the mediator model including class climate, learning motivation, and learning effectiveness, it was observed that learning motivation exerted a partial mediating effect on the relationship between class climate and learning effectiveness.

Abstract. In steep wildfire-burned terrains, intense rainfall can produce large runoff that can trigger highly destructive debris flows. However, the ability
to accurately characterize and forecast debris flow susceptibility in burned terrains using physics-based tools remains limited. Here, we augment
the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) to simulate both overland and channelized flows and assess postfire
debris flow susceptibility over a regional domain. We perform hindcast simulations using high-resolution weather-radar-derived precipitation and
reanalysis data to drive non-burned baseline and burn scar sensitivity experiments. Our simulations focus on January 2021 when an atmospheric river
triggered numerous debris flows within a wildfire burn scar in Big Sur – one of which destroyed California's famous Highway 1. Compared to the
baseline, our burn scar simulation yields dramatic increases in total and peak discharge and shorter lags between rainfall onset and peak
discharge, consistent with streamflow observations at nearby US Geological Survey (USGS) streamflow gage sites. For the 404 catchments located in
the simulated burn scar area, median catchment-area-normalized peak discharge increases by ∼ 450 % compared to the baseline. Catchments
with anomalously high catchment-area-normalized peak discharge correspond well with post-event field-based and remotely sensed debris flow
observations. We suggest that our regional postfire debris flow susceptibility analysis demonstrates WRF-Hydro as a compelling new physics-based
tool whose utility could be further extended via coupling to sediment erosion and transport models and/or ensemble-based operational weather
forecasts. Given the high-fidelity performance of our augmented version of WRF-Hydro, as well as its potential usage in probabilistic hazard
forecasts, we argue for its continued development and application in postfire hydrologic and natural hazard assessments.

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback. ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31430015, 31830012]; US NSFNational Science Foundation (NSF) [DEB-0955771]; ClimMani COST actionEuropean Cooperation in Science and Technology (COST) [ES1308] ; We thank J. Wang (Hebei University), S. Yang (Institute of Botany, Chinese Academy of Sciences), L. Zhou (East China Normal University), C. Qiao (Xinyang Normal University) and H. Li (Henan University) for their help in meta-analyses and interaction analyses, and H. Li, Y. Liu (Institute of Tibetan Plateau Research, Chinese Academy of Sciences) and Y. He (Peking University) for their help in plotting figures. This work was financially supported by the National Natural Science Foundation of China (grant nos. 31430015 and 31830012). This study emerged from the INTERFACE Workshop in Beijing, China (https://www.bio.purdue.edu/INTERFACE/) supported by the US NSF DEB-0955771. We also acknowledge support from the ClimMani COST action (ES1308). ; Public domain authored by a U.S. government employee