Responses of bryosphere fauna to drought across a boreal forest chronosequence

Projected changes in precipitation regimes can greatly impact soil biota, which in turn alters key ecosystem functions. In moss-dominated ecosystems, the bryosphere (i.e., the ground moss layer including live and senesced moss) plays a key role in carbon and nutrient cycling, and it hosts high abundances of microfauna (i.e., nematodes and tardigrades) and mesofauna (i.e., mites and springtails). However, we know very little about how bryosphere fauna responds to precipitation, and whether this response changes across environmental gradients. Here, we used a mesocosm experiment to study the effect of volume and frequency of precipitation on the abundance and community composition of functional groups of bryosphere fauna. Hylocomium splendens bryospheres were sampled from a long-term post-fire boreal forest chronosequence in northern Sweden which varies greatly in environmental conditions. We found that reduced precipitation promoted the abundance of total microfauna and of total mesofauna, but impaired predaceous/omnivorous nematodes, and springtails. Generally, bryosphere fauna responded more strongly to precipitation volume than to precipitation frequency. For some faunal functional groups, the effects of precipitation frequency were stronger at reduced precipitation volumes. Context-dependency effects were found for microfauna only: microfauna was more sensitive to precipitation in late-successional forests (i.e., those with lower productivity and soil nutrient availability) than in earlier-successional forests. Our results also suggest that drought-induced changes in trophic interactions and food resources in the bryosphere may increase faunal abundance. Consequently, drier bryospheres that may result from climate change could promote carbon and nutrient turnover from fauna activity, especially in older, less productive forests

An Interpretable Moderated Mediation Model: How does Punctum Image Influence Tourists’ Behavioral Intention?

This study aims to investigate the influence of punctum image in destinations on tourists’ behavioral intentions. The study proposes the concepts of punctum and studium image based on semiology and uses an interpretable moderated mediation model to examine the effects of punctum image, studium image, flow experience, and human interaction on behavioral intention. The proposed research collected data from 440 tourists who visited a destination and used a structural equation model to analyze the relationships among the variables. The study employed bootstrapping to test the significance of the mediating effects and conducted a moderated mediation analysis to examine the moderating role of human interaction. The findings of the study indicate that punctum image has a positive effect on studium image and behavioral intention. Studium image is found to mediate the relationship between punctum image and behavioral intention. Additionally, the study shows that there are multiple mediations of studium image and flow experience between punctum image and behavioral intention. Finally, the study finds that human interaction plays a moderating role in two of the mediating effects. The results of this research have important theoretical and managerial implications. The study highlights the importance of punctum image in destination branding and suggests that destinations should focus on creating memorable and distinctive images to attract tourists. The study also emphasizes the role of studium image and flow experience in shaping tourists’ behavioral intentions, which could help destinations to design more effective marketing strategies. Finally, the study underscores the importance of human interaction in shaping tourists’ experiences and suggests that destinations should focus on providing high-quality human interactions to enhance tourists’ experiences and satisfaction. The use of an interpretable moderated mediation model in this study enhances the interpretability and practical applicability of the results for decision-makers.</p

Assessing the Alteration of Soil Quality under Long-Term Fertilization Management in Farmland Soil: Integrating a Minimum Data Set and Developing New Biological Indicators

The key role of soil quality improvement in achieving sustainable agricultural development based on highly intensive use of farmland is increasingly being recognized, as is the ponderance of suitable evaluation of the soil quality. The overarching goal of this study was to determine an accurate assessment framework by the comparison of the scoring function (linear and non-linear) and integration method (area and weighted additive), which integrally evaluates the soil quality of an eleven-year field fertilization experiment (including CK, no fertilizer; CF, conventional fertilization; SF, formulated fertilization; SFO, SF with organic fertilizer). Thirty-three properties, including eighteen physiochemical-related and fifteen biological-related properties, associated with soil functions were measured as potential soil quality indicators, and the soil multifunctionality (SMF) was applied to validate the soil quality indices (SQIs). Principal component analysis and relationship analysis were used with indicators sensitive to management to determine a minimum data set (MDS). The results showed that the electrical conductivity, large macroaggregate-associated total nitrogen, small macroaggregate-associated organic carbon, carbon fixation, and enzyme activities of phenol oxidase and cellulase were chosen as the MDS. All the SQIs were significantly correlated with the SMF (p p < 0.05), and the treatment of the organic fertilizer had the highest SQI value (0.66). Soil quality evaluation in long-term fertilized farmland suggested that the soil quality constraints between treatments of synthetic and organic fertilizer are related to the soil functions of nutrient cycling and sustain biological activity due to their higher contribution rates to the SQI in the organic fertilizer treatment, which provides insights into ways to reduce the gap in soil quality. The framework method can provide an accurate quantitative tool for the evaluation of soil quality from the target indicators by bridging management objectives and field-level actions