Partial Least Squares Path Modeling Research Articles

Aboveground carbon sequestration of Cunninghamia lanceolata forests: Magnitude and drivers

Understanding the spatial variation, temporal changes, and their underlying driving forces of carbon sequestration in various forests is of great importance for understanding the carbon cycle and carbon management options. How carbon density and sequestration in various Cunninghamia lanceolata forests, extensively cultivated for timber production in subtropical China, vary with biodiversity, forest structure, environment, and cultural factors remain poorly explored, presenting a critical knowledge gap for realizing carbon sequestration supply potential through management. Based on a large-scale database of 449 permanent forest inventory plots, we quantified the spatial-temporal heterogeneity of aboveground carbon densities and carbon accumulation rates in Cunninghamia lanceolate forests in Hunan Province, China, and attributed the contributions of stand structure, environmental, and management factors to the heterogeneity using quantile age-sequence analysis, partial least squares path modeling (PLS-PM), and hot-spot analysis. The results showed lower values of carbon density and sequestration on average, in comparison with other forests in the same climate zone (i.e., subtropics), with pronounced spatial and temporal variability. Specifically, quantile regression analysis using carbon accumulation rates along an age sequence showed large differences in carbon sequestration rates among underperformed and outperformed forests (0.50 and 1.80 ​Mg⋅​ha−1·yr−1). PLS-PM demonstrated that maximum DBH and stand density were the main crucial drivers of aboveground carbon density from young to mature forests. Furthermore, species diversity and geo-topographic factors were the significant factors causing the large discrepancy in aboveground carbon density change between low- and high-carbon-bearing forests. Hotspot analysis revealed the importance of culture attributes in shaping the geospatial patterns of carbon sequestration. Our work highlighted that retaining large-sized DBH trees and increasing shade-tolerant tree species were important to enhance carbon sequestration in C. lanceolate forests.

THE INFLUENCE OF ENTREPRENEURIAL INTERNAL AND EXTERNAL FACTORS ON THE SUSTAINABILITY OF THE ORGANIC VEGETABLE BUSINESS DURING THE COVID-19 PANDEMIC

The organic vegetable business is a business that has high opportunities. The real conditions experienced during the Covid-19 pandemic harmed farmers who were also in the organic vegetable business, namely a 50 percent decrease in sales. A sustainable agricultural business depends on the entrepreneurial spirit possessed by agribusiness actors. This study aims to analyze the influence of entrepreneurial internal and external factors on the sustainability of the organic vegetable business with business performance as an intervening variable. This research was carried out from October to December 2022 in Batur Village, Getasan District. The type of research used in this research is descriptive quantitative, with primary and secondary data types. The sample used is 100 respondents, taken by nonprobability sampling with the purposive method. Data analysis techniques used by researchers are structural equation modeling (SEM) and partial least squares path modeling (PLS-SEM). The results of this research are entrepreneurial internal factors (X1) with p-value 0,003 and entrepreneurial external factors (X2) with p-value 0,000 have a significant and significant positive effect on the sustainability of the organic vegetable business (Y2). But entrepreneurial internal factors (X1) with p-value 0,117 and entrepreneurial external factors (X2) with p-value 0,122 have no significant effect on business sustainability (Y2) through business performance (Y1) as intervening variables. Therefore, if everyone improves business performance personally it will distrupt business performance in the group.

Ofloxacin weakened treatment performance of rural domestic sewage in an aerobic biofilm system by affecting biofilm resistance, bacterial community, and functional genes

Ofloxacin (OFL) is a typical fluoroquinolone antibiotic widely detected in rural domestic sewage, however, its effects on the performance of aerobic biofilm systems during sewage treatment process remain poorly understood. We carried out an aerobic biofilm experiment to explore how the OFL with different concentrations affects the pollutant removal efficiency of rural domestic sewage. Results demonstrated that the OFL negatively affected pollutant removal in aerobic biofilm systems. High OFL levels resulted in a decrease in removal efficiency: 9.33% for chemical oxygen demand (COD), 18.57% for ammonium (NH4+-N), and 8.49% for total phosphorus (TP) after 35 days. The findings related to the chemical and biological properties of the biofilm revealed that the OFL exposure triggered oxidative stress and SOS responses, decreased the live cell number and extracellular polymeric substance content of biofilm, and altered bacterial community composition. More specifically, the relative abundance of key genera linked to COD (e.g., Rhodobacter), NH4+-N (e.g., Nitrosomonas), and TP (e.g., Dechlorimonas) removal was decreased. Such the OFL-induced decrease of these genera might result in the down-regulation of carbon degradation (amyA), ammonia oxidation (hao), and phosphorus adsorption (ppx) functional genes. The conventional pollutants (COD, NH4+-N, and TP) removal was directly affected by biofilm resistance, functional genes, and bacterial community under OFL exposure, and the bacterial community played a more dominant role based on partial least-squares path model analysis. These findings will provide valuable insights into understanding how antibiotics impact the performance of aerobic biofilm systems during rural domestic sewage treatment.

The Influence of Leadership Development on Civil Servants Performance through Work Motivation

The aim of the research is to find out how the performance of civil servants of the Directorate General of Agrarian Affairs is through work motivation and the impact of visionary leadership, work culture and career development. Analysis The PLS-SEM (Partial least square path modeling) approach was used in this study as part of the quantitative research methodology. Use the questionnaire as the main tool for collecting data. The research sample consisted of 103 answers from a saturated sample. Discussion of the results of the research resulted in the conclusion that visionary leadership, work culture, and career development have a direct, positive, and large effect on work motivation at the Directorate General of Agrarian Management. The direct impact of civil servants performance at the Directorate General of Agrarian Management is visionary leadership, work culture, career development, and work motivation. Through work motivation, visionary leadership, work culture, and career development have an indirect and quite large impact on civil servants.

Specifying and validating overconfidence bias among retail investors: a formative index

PurposeThe study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.Design/methodology/approachThe study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.FindingsThe major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.Practical implicationsThe formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.Originality/valueThis research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.Highlights Overconfidence bias is an important predictor of retail investors' behaviorFormative dimensions of the overconfidence bias index.Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.Modern portfolio theory and illusion of control theory support this study.

Impact of information usefulness and adoption in social media on purchase intention :Evidence of Indonesia

The Product reviews on YouTube Channel offer information for consumers to evaluate products before making a decision. Understanding how consumers adopt the information and its impact on purchase intention becomes crucial. This study aims to determine the influence of information usefulness and information adoption on purchase intention on YouTube channels. The study developed a research model based on the Information Adoption Model (IAM) and Theory of Reasoned Action (TRA). A survey design was employed to test the proposed linkages among variables with a sample size of 447 respondents by the purposive sampling method. The study deploys the partial least squares path modeling (PLS-SEM) to analyze the data. The results confirmed that relevance, comprehensiveness, source expertise, attitude toward information, and information usefulness positively affect information adoption and purchase intention. Additionally, attitude toward information has a positive influence on behavioral intentions. However, timeliness, accuracy, and source expertise do not have any significant relationship with the information usefulness

Microbial Necromass, Lignin, and Glycoproteins for Determining and Optimizing Blue Carbon Formation.

Coastal wetlands contribute to the mitigation of climate change through the sequestration of "blue carbon". Microbial necromass, lignin, and glycoproteins (i.e., glomalin-related soil proteins (GRSP)), as important components of soil organic carbon (SOC), are sensitive to environmental change. However, their contributions to blue carbon formation and the underlying factors remain largely unresolved. To address this paucity of knowledge, we investigated their contributions to blue carbon formation along a salinity gradient in coastal marshes. Our results revealed decreasing contributions of microbial necromass and lignin to blue carbon as the salinity increased, while GRSP showed an opposite trend. Using random forest models, we showed that their contributions to SOC were dependent on microbial biomass and resource stoichiometry. In N-limited saline soils, contributions of microbial necromass to SOC decreased due to increased N-acquisition enzyme activity. Decreases in lignin contributions were linked to reduced mineral protection offered by short-range-ordered Fe (FeSRO). Partial least-squares path modeling (PLS-PM) further indicated that GRSP could increase microbial necromass and lignin formation by enhancing mineral protection. Our findings have implications for improving the accumulation of refractory and mineral-bound organic matter in coastal wetlands, considering the current scenario of heightened nutrient discharge and sea-level rise.

Short-term continuous monocropping reduces peanut yield mainly via altering soil enzyme activity and fungal community

Continuous monocropping can lead to soil sickness and increase of soil-borne disease, which finally reduces crop yield. Microorganisms benefit plants by increasing nutrient availability, participating in auxin synthesis, and defending against pathogens. However, little is known about the influence of short-term successive peanuts cropping on soil properties, enzyme activities, its yield, plant-associated microbes, and their potential correlations in peanut production. Here, we examined the community structure, composition, network structure and function of microbes in the rhizosphere and bulk soils under different monocropping years. Moreover, we assessed the impact of changes in the soil micro-environment and associated soil microbes on peanut yield. Our results showed that increase of monocropping year significantly decreased most soil properties, enzyme activities and peanut yield (p < 0.05). Principal co-ordinates analysis (PCoA) and analysis of similarities (ANOSIM) indicated that monocropping year significantly influenced the fungal community structure in the rhizosphere and bulk soils (p < 0.01), while had no effect on the bacterial community. With the increase of continuous monocropping year, peanut selectively decreased (e.g., Candidatus_Entotheonella, Bacillus and Bryobacter) or increased (e.g., Nitrospira, Nocardioides, Ensifer, Gaiella, and Novosphingobium) the abundance of some beneficial bacterial genera in the rhizosphere. Continuous monocropping significantly increased the abundance of plant pathogens (e.g., Plectosphaerella, Colletotrichum, Lectera, Gibberella, Metarhizium, and Microdochium) in the rhizosphere and negatively affected the balance of fungal community. Besides, these species were correlated negatively with L-leucine aminopeptidase (LAP) activity. Network co-occurrence analysis showed that continuous monocropping simplified the interaction network of bacteria and fungi. Random forest and partial least squares path modeling (PLS-PM) analysis further showed that fungal community, pathogen abundance, soil pH, and LAP activity negatively affected peanut yield. In conclusion, short-term continuous monocropping decreased LAP activity and increased potential fungal pathogens abundance, leading to reduction of peanut yield.

Dual Regulatory Role of Penicillium oxalicum SL2 in Soil: Phosphorus Solubilization and Pb Stabilization.

The mechanisms of the P. oxalicum SL2-mediated microbial community on phosphorus solubilization and Pb stabilization were investigated through a 90-day soil experiment. In the treatments inoculated with P. oxalicum SL2, the amount of P. oxalicum SL2-GFP remained at 77.8%-138.6% of the initial inoculation amount after 90 days, and the available phosphorus (AP) content increased 21.7%-40.8% while EDTA-Pb decreased 29.9%-43.2% compared with CK treatment. SEM-EDS results showed that P. oxalicum SL2 changed the agglomeration degree of microaggregates and promoted the combination of Pb with C and O elements. These phenomena were enhanced when applied with Ca3(PO4)2. Microbial community analysis showed that P. oxalicum SL2 improved soil microbial activity, in which the fungi absolute abundance increased about 15 times within 90 days. Correlation analyses and a partial least-squares path model showed that the activation of Penicillium, Ascobolus, Humicola, and Spizellomyces in a fungal community increased the content of oxalate and AP, which directly decreased EDTA-Pb content, while the change of Bacillus, Ramlibacter, Gemmatimonas, and Candidatus Solibacter in the bacterial community regulated Fe/Mn/S/N cycle-related functions, thus promoting the conversion of Pb to oxidizable state. Our findings highlight that P. oxalicum SL2 enhanced the microbial-induced phosphate precipitation process by activating soil microbial communities and regulating their ecological functions.

Interactions between water quality and microbes in epiphytic biofilm and superficial sediment of lake in trophic agriculture area

Epiphytic and superficial sediment biofilm-dwelling microbial communities play a pivotal role in water quality regulation and biogeochemical cycling in shallow lakes. However, the interactions are far from clear between water physicochemical parameters and microbial community on aquatic plants and in surface sediments of lake in trophic agriculture area. This study employed Illumina sequencing, Partial Least Squares Path Modeling (PLS-PM), and physico-chemical analytical methods to explore the interactions between water quality and microbes (bacteria and eukaryotes) in three substrates of trophic shallow Lake Cyohoha North, Rwanda. The Lake Cyohoha was significantly polluted with total phosphorus (TP), total nitrogen (TN), nitrate nitrogen (NO3-N), and ammonia nitrogen (NH3−N) in the wet season compared to the dry season. PLS-PM revealed a strong positive correlation (+0.9301) between land use types and physico-chemical variables in the rainy season. In three substrates of the trophic lake, Proteobacteria, Cyanobacteria, Firmicutes, and Actinobacteria were dominant phyla in the bacterial communities, and Rotifers, Platyhelminthes, Gastrotricha, and Ascomycota dominated in microeukaryotic communities. As revealed by null and neutral models, stochastic processes predominantly governed the assembly of bacterial and microeukaryotic communities in biofilms and surface sediments. Network analysis revealed that the microbial interconnections in Ceratophyllum demersum were more stable and complex compared to those in Eichhornia crassipes and sediments. Co-occurrence network analysis (|r| > 0.7, p < 0.05) revealed that there were complex interactions among physicochemical parameters and microbes in epiphytic and sediment biofilms, and many keystone microbes on three substrates played important role in nutrients removal, food web and microbial community stable. These findings emphasize that eutrophic water influence the structure, composition, and interactions of microbes in epiphytic and surface sediment biofilms, and provided new insights into the interconnections between water quality and microbial community in presentative substrates in tropical lacustrine ecosystems in agriculturally polluted areas. The study provides useful information for water quality protection and aquatic plants restoration for policy making and catchment management.

The impact of rainfall events on dissolved oxygen concentrations in a subtropical urban reservoir

Understanding controls of dissolved oxygen (DO) concentrations in reservoirs is important as they are important for fisheries and a significant driver of greenhouse gas emissions. The latter is of global significance as IPCC inventories now require greenhouse gas emissions from artificial reservoirs to be included. Declines in dissolved oxygen (DO) concentrations in lakes and reservoirs have been linked to climate change and human activity. However, these effects can vary widely in any given region under various meteorological conditions. There is a clear need to know how changes in weather patterns affect DO in reservoirs by changing internal processes. Based on a six-year (2016–2021) high-frequency (twice a week) dataset from a shallow urban reservoir (Xinglinwan Reservoir) in subtropical China, the long-term (six years) and short-term (8–72-h) drivers of DO concentrations in surface waters were evaluated. Over the past six years, the concentration of DO has gradually decreased in the reservoir from 2016 to 2021. Multivariate adaptive regression spline (MARS) models were developed to identify the key factors explaining variability in DO and partial least squares path models (PLS-PM) were used to explore the short-term relationships between DO and environmental variables in rainy and dry (non-rain) periods, separately. We identified three key drivers operating on different time scales. First, the long-term decline of DO in Xinglinwan Reservoir from 2016 to 2021 was best explained by anthropogenic nutrient inputs. Second, rainy periods prior to sampling reduced DO concentrations indirectly by affecting the algal biomass and nutrient concentrations. This effect varied in complexity with the duration of the rainfall period. Third, water temperature best explained DO concentrations during dry periods, while wind reduced DO by reducing algal biomass. We conclude that anthropogenic nutrient and organic matter inputs drive long-term oxygen declines in urban subtropical reservoirs, while meteorological factors determine short-term variability in DO concentrations.

Higher Order Partial Least Squares Path Modeling Using Binary Data: An Application on Multidimensional Poverty and Social Protection in East Java Province

The standard partial least squares path modeling (PLS-PM) estimation process assumes the observed data as continuous variables. With slight modifications, this estimation algorithm can be used for data on a binary scale and even for more complex models such as higher order constructs. This study aims to determine by simulation and application of real data the performance of the higher-order construct modeling approach, which of the repeated indicator and two-stage approaches provides better results. From simulation study it was found that the repeated indicator approach with binary data (BinPLS) was better than the two-stage approach. Empirical results also show that the BinPLS measurement model with the repeated indicator approach is better than standard PLS. Evaluation of the structural model also shows that BinPLS with a repeated indicator approach is the best because it produces path coefficients and the power to explain multidimensional poverty and social protection models that are better than BinPLS with a two-stage approach and standard PLS.

Brain‐age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum

AbstractBackgroundNeuroimaging‐derived brain‐age is a useful biomarker to study the brain’s biological aging process. Brain‐age has shown cross‐sectional associations with cognitive function and modifiable risk factors for dementia. We aimed to study, in cognitively unimpaired (CU) individuals, the mediating role of brain‐age in the association between modifiable risk factors and cognitive changes, and the impact of AD pathology on this role.MethodWe included 416 CU individuals from the ALFA+ study with available structural MRI, measurements of the global cognitive Preclinical Alzheimer’s Cognitive Composite (PACC) (370 individuals had a follow‐up PACC assessment 3.28±0.27 years later), and lifestyle and cardiovascular risk factors assessments. We computed brain‐age delta as the difference between chronological and predicted brain‐age using a previously pre‐trained machine learning algorithm on structural MRI data. Partial Least Squares Path Modeling (PLS‐PM) was employed to investigate the mediation effect of brain‐age delta between a computed latent variable from modifiable risk factors (cardiovascular, mental health and mood, metabolic/endocrine disease history, and alcohol consumption factors; Table 1) and a latent variable from longitudinal PACC. Statistical bias adjustment was performed to control for the confounding effects of age and sex by using multiple linear regression. The analysis was performed on the whole sample (ALL) and after stratification by amyloid‐ß (Aß) status. Participants were classified as amyloid‐ß positive (Aß+) if CSF Aß42/40&lt;0.071 (Milà‐Alomà et al, 2020). Significance of mediation was examined by 95% confidence interval bootstrap.ResultThe effect of risk factors (latent risk) on longitudinal cognition (latent cognition) was partially mediated by brain‐age delta only in Aß+ individuals (57.286%) (Figure 1C). Higher latent risk was associated with older brain‐age delta (p = 0.003) and older brain‐age delta was associated with worse latent cognition (p = 0.007). Conversely, the indirect effect was not significant in ALL nor in Aß‐ individuals, where brain‐age delta was not significantly associated with latent cognition (Figure 1A‐B). Still, higher latent risk was associated with older brain‐age delta (ALL: p&lt;0.001; Aß‐: p = 0.004) and associated with worse latent cognition (ALL: p = 0.012, Aß‐: p = 0.001).ConclusionIn CU individuals in the AD continuum, biological brain aging mediates the association between modifiable risk factors and cognitive decline.

Brain‐age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum

AbstractBackgroundNeuroimaging‐derived brain‐age is a useful biomarker to study the brain’s biological aging process. Brain‐age has shown cross‐sectional associations with cognitive function and modifiable risk factors for dementia. We aimed to study, in cognitively unimpaired (CU) individuals, the mediating role of brain‐age in the association between modifiable risk factors and cognitive changes, and the impact of AD pathology on this role.MethodWe included 416 CU individuals from the ALFA+ study with available structural MRI, measurements of the global cognitive Preclinical Alzheimer’s Cognitive Composite (PACC) (370 individuals had a follow‐up PACC assessment 3.28±0.27 years later), and lifestyle and cardiovascular risk factors assessments. We computed brain‐age delta as the difference between chronological and predicted brain‐age using a previously pre‐trained machine learning algorithm on structural MRI data. Partial Least Squares Path Modeling (PLS‐PM) was employed to investigate the mediation effect of brain‐age delta between a computed latent variable from modifiable risk factors (cardiovascular, mental health and mood, metabolic/endocrine disease history, and alcohol consumption factors; Table 1) and a latent variable from longitudinal PACC. Statistical bias adjustment was performed to control for the confounding effects of age and sex by using multiple linear regression. The analysis was performed on the whole sample (ALL) and after stratification by amyloid‐β (Aβ) status. Participants were classified as amyloid‐β positive (Aβ+) if CSF Aβ42/40&lt;0.071 (Milà‐Alomà et al, 2020). Significance of mediation was examined by 95% confidence interval bootstrap.ResultThe effect of risk factors (latent risk) on longitudinal cognition (latent cognition) was partially mediated by brain‐age delta only in Aβ+ individuals (57.286%) (Figure 1C). Higher latent risk was associated with older brain‐age delta (p = 0.003) and older brain‐age delta was associated with worse latent cognition (p = 0.007). Conversely, the indirect effect was not significant in ALL nor in Aβ‐ individuals, where brain‐age delta was not significantly associated with latent cognition (Figure 1A‐B). Still, higher latent risk was associated with older brain‐age delta (ALL: p&lt;0.001; Aβ‐: p = 0.004) and associated with worse latent cognition (ALL: p = 0.012, Aβ‐: p = 0.001).ConclusionIn CU individuals in the AD continuum, biological brain aging mediates the association between modifiable risk factors and cognitive decline.

Impact of typical land use type on the stability and content of carbon and nitrogen of soil aggregates in western Hubei

AbstractIn order to investigate the characteristics of soil structural stability and the factors influencing it under typical land use types in the karst region of western Hubei, soil samples were collected from five land use types (natural mixed forest [NF], cypress forest [CF], stone dike terrace [ST], stone dike forest [SF], and abandoned land [AL]) in Xialaoxi to analyze the particle size distribution of aggregates, structural stability, and the distribution characteristics of carbon, nitrogen, and extracellular enzyme contents. The results showed that the aggregates of NF, CF, SF, and AL were dominated by &gt;2‐mm aggregates, while ST showed mostly 2–0.25‐mm aggregates. The mean weight diameter (EMWD) and the geometric mean diameter (EGMD) of mechanical aggregates showed a trend of CF &gt; NF &gt; SF &gt; AL &gt; ST, whereas the erodibility factor K showed an opposite trend. The total organic carbon (TOC), labile organic carbon (LOC), and total nitrogen (TN) contents of aggregates of each particle size were significantly higher in NF and CF than in ST and AL under the five land types. The content of available nitrogen (AN) was highest in NF and ST. The content of carbon and nitrogen and extracellular hydrolases (β‐glucosidase [BG], cellulose disaccharide hydrolase [CBH], β‐N‐acetyl‐aminoglucosidase [NAG], and leucine aminopeptidase [LAP]) in soil aggregates were mainly concentrated in &lt;0.25–0.053‐mm aggregates. The variation in carbon and nitrogen abundance of each particle size agglomerate mainly originated from the LAP content of that particle size agglomerate and showed significant correlation. The partial least squares path models (PLS‐PM) showed that the main influences on the stability of soil aggregates in small watersheds were land use types, soil physical properties, carbon and nitrogen abundance, and extracellular enzyme activity. In conclusion, the structural stability of soil aggregates in Xialaoxi watershed is the result of the interaction between human disturbance and soil nutrient self‐cycling. In general, NF and CF have better soil aggregate stability and are conducive to soil carbon and nitrogen accumulation, whereas for later development and management of SF, ST, and AL sample plots, scientific cultivation means should be adopted, and attention should be paid to long‐term carbon and nitrogen accumulation and conservation.

Maize-soybean intercropping improved maize growth traits by increasing soil nutrients and reducing plant pathogen abundance

IntroductionMaize (Zea mays L.)–soybean (Glycine max L.) intercropping has been widely utilized in agricultural production due to its effectiveness in improving crop yield and nutrient use efficiency. However, the responses of maize rhizosphere microbial communities and the plant pathogen relative abundance to maize growth traits in maize-soybean intercropping systems with different chemical nitrogen fertilizer application rates remain unclear.MethodsIn this study, a field experiment was conducted, and the bacterial and fungal communities of maize rhizosphere soils in maize-soybean intercropping systems treated with different N fertilization rates were investigated using Illumina NovaSeq sequencing. Maize growth traits, soil physicochemical properties and soil enzyme activities were also examined.Results and discussion:We found that intercropping and N fertilizer treatments strongly influenced soil microbial diversity, structure and function. The PLSPM (partial least squares path modeling) confirmed that soil nutrients directly positively affected maize biomass and that intercropping practices indirectly positively affected maize biomass via soil nutrients, especially NH4+-N. Intercropping agronomic approaches also improved maize growth traits by reducing the plant pathogen abundance, and the relative abundance of the plant pathogen Trichothecium roseum significantly decreased with intercropping treatments compared to monocropping treatments. These results confirmed the benefits of maize-soybean intercropping treatments for agricultural production.

The Influence of Product Quality, Brand Image, and Brand Trust on Avoskin Serum Purchasing Decisions in National University Students

This study aims to determine the effect of Product Quality, Brand Image, and Brand Trust on the Purchase Decision of Avoskin Serum among female students at the National University. The sample in this study were 100 female students at the National University who had purchased avoskin serum products. This study uses primary data by collecting data through questionnaires distributed to 100 respondents, using a purposive sampling method. The data analysis technique uses the Partial Least Squares Path Modeling (PLS-SEM) 3.3.2 program. This shows that Product Quality (X1) has a positive and significant effect on Purchasing Decisions (Y), Brand Image (X2) has a positive and significant effect on Purchase Decisions (Y), Brand Trust (X3) has a positive and significant effect on Purchase Decisions (Y ). So it can be concluded that product quality, brand image, and brand trust have a positive and significant effect on purchasing decisions.

Factors controlling the heavy metal ion activity in soil contaminated by microplastics with different mulch durations: Partial least squares path model

Film covers have been widely applied worldwide. However, the effects of long-term plastic film mulching use on heavy metal (HM) activity in soil remain unclear. This study focused on farmland in the upstream part of the Pearl River in China and collected 103 soil samples after 2, 5, and 15 years of plastic film mulching. The main environmental factors controlling microplastics (MPs), plasticizer phthalic acid esters (PAEs), HM pollution characteristics, and HM activity were analyzed. The results showed that Polyethylene (PE) and di(2-ethylhexyl) dicyclohexyl phthalate (DCHP) were the main MPs and PAEs, respectively. The abundance of MPs and the concentrations of free HM ions (Cd, Cu, and Ni) in the soil solution increased with increasing plastic film mulching duration. The Partial Least Squares Path Model (PLS-PM) indicated that after plastic film mulching, soil chemical properties (pH/amorphous Fe) and biological properties (Dissolved organic carbon/ Easily oxidizable carbon/Microbial biomass carbon) were the main controlling factors for free and complexed HM ions (Cd, Pb, Cu, and Ni). These results suggest that, after plastic film mulching, MPs indirectly regulate HM activity by altering soil properties. This study provides a new perspective for the management of MPs and HM activities in agricultural ecosystems.

The Assembly Process of Free-Living and Particle-Attached Bacterial Communities in Shrimp-Rearing Waters: The Overwhelming Influence of Nutrient Factors Relative to Microalgal Inoculation.

The ecological functions of bacterial communities vary between particle-attached (PA) lifestyles and free-living (FL) lifestyles, and separately exploring their community assembly helps to elucidate the microecological mechanisms of shrimp rearing. Microalgal inoculation and nutrient enrichment during shrimp rearing are two important driving factors that affect rearing-water bacterial communities, but their relative contributions to the bacterial community assembly have not been evaluated. Here, we inoculated two microalgae, Nannochloropsis oculata and Thalassiosira weissflogii, into shrimp-rearing waters to investigate the distinct effects of various environmental factors on PA and FL bacterial communities. Our study showed that the composition and representative bacteria of different microalgal treatments were significantly different between the PA and FL bacterial communities. Regression analyses and Mantel tests revealed that nutrients were vital factors that constrained the diversity, structure, and co-occurrence patterns of both the PA and FL bacterial communities. Partial least squares path modeling (PLS-PM) analysis indicated that microalgae could directly or indirectly affect the PA bacterial community through nutrient interactions. Moreover, a significant interaction was detected between PA and FL bacterial communities. Our study reveals the unequal effects of microalgae and nutrients on bacterial community assembly and helps explore microbial community assembly in shrimp-rearing ecosystems.

Root carbon and soil temperature may be key drivers of below-ground biomass in grassland following prescribed fires in autumn and spring

Under global warming, fire and the season in which the fire occurs both have important impacts on grassland plant biomass. Still, the effect of fire on below-ground biomass (BB) along a natural aridity gradient and the main impact factors remain unclear. Here, we conducted a fire manipulation experiment (including un-fired, autumn fire and spring fire treatments) to investigate the effects of prescribed fire on BB and its critical determinants along a transect of grassland in northern China. BB had different response strategies in different aridity regions and fire seasons, despite above-ground biomass (AB) and root-shoot ratio were not significantly affected by fire. General linear regression models revealed that the fire changed the trend of increasing BB to decreasing along increasing aridity (p ＜ 0.05). Random forest model (RFM) and partial correlations revealed that the BB was primarily influenced by aridity, followed by the nitrogen (N) and phosphorus (P) concentration ratio of AB under un-fired disturbance. For autumn fire, the BB was primarily influenced by below-ground biomass carbon concentration (BB c), followed by the C and N concentration ratio of BB. For spring fire, the BB was primarily influenced by soil temperature (ST), followed by aridity and soil total phosphorus concentration (Soil p). Furthermore, partial least squares path model (PLS-PM) revealed that autumn fires weakened the effects of environmental factors on BB, while spring fires enhanced the effects of soil nutrients on BB. These suggested that fire disrupted the original stable nutrient dynamics of BB. Our results suggested that fire promoted the growth of BB in relatively humid areas (aridity = 0.51–0.53) while inhibited the growth of BB in relatively arid areas (aridity = 0.68–0.74). BB c and ST may be key drivers of BB after prescribed fire in autumn and spring.