Massey Research Online - Browsing by Author "Wang Z"

Browsing by Author "Wang Z"

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Assessing the win-win situation of forage production and soil organic carbon through a short-term active restoration strategy in alpine grasslands
(Frontiers Media S.A., 2024-01-11) Wang Y; Wang Z; Kang Y; Zhang Z; Bao D; Sun X; Su J
INTRODUCTION: Grassland degradation has seriously affected the ecological environment and human livelihood. To abate these, implementing effective management strategies to restore and improve the service functions and productivity of degraded grasslands is crucial. METHODS: To evaluate the influences of restoration measures combined with different grazing intensities on short-term (1 year) grassland restoration, the changes in soil physicochemical properties, as well as plant traits under restoration measures of different grazing intensities, reseeding, and fertilization, were analyzed. RESULTS: Soil organic carbon (SOC) increased to varying degrees, whereas available nutrients decreased under all combined restoration measures. Reseeding, alone and in combination with fertilization, substantially increased SOC, improved grassland vegetation status, and enhanced grassland productivity. The aboveground biomass of Gramineae and the total aboveground biomass increased under the combined restoration measures of transferring livestock out of the pasture 45 days in advance, reseeding, and fertilization (T4). Redundancy analysis revealed a strong correlation between grassland vegetation characteristics, SOC, and available potassium. Considering soil and vegetation factors, the short-term results suggested that the combination measures in T4had the most marked positive impact on grassland restoration. DISCUSSION: These findings offer valuable theoretical insights for the ecological restoration of degraded grasslands in alpine regions.
Author Correction: Dense sampling of bird diversity increases power of comparative genomics.
(2021-04) Feng S; Stiller J; Deng Y; Armstrong J; Fang Q; Reeve AH; Xie D; Chen G; Guo C; Faircloth BC; Petersen B; Wang Z; Zhou Q; Diekhans M; Chen W; Andreu-Sánchez S; Margaryan A; Howard JT; Parent C; Pacheco G; Sinding M-HS; Puetz L; Cavill E; Ribeiro ÂM; Eckhart L; Fjeldså J; Hosner PA; Brumfield RT; Christidis L; Bertelsen MF; Sicheritz-Ponten T; Tietze DT; Robertson BC; Song G; Borgia G; Claramunt S; Lovette IJ; Cowen SJ; Njoroge P; Dumbacher JP; Ryder OA; Fuchs J; Bunce M; Burt DW; Cracraft J; Meng G; Hackett SJ; Ryan PG; Jønsson KA; Jamieson IG; da Fonseca RR; Braun EL; Houde P; Mirarab S; Suh A; Hansson B; Ponnikas S; Sigeman H; Stervander M; Frandsen PB; van der Zwan H; van der Sluis R; Visser C; Balakrishnan CN; Clark AG; Fitzpatrick JW; Bowman R; Chen N; Cloutier A; Sackton TB; Edwards SV; Foote DJ; Shakya SB; Sheldon FH; Vignal A; Soares AER; Shapiro B; González-Solís J; Ferrer-Obiol J; Rozas J; Riutort M; Tigano A; Friesen V; Dalén L; Urrutia AO; Székely T; Liu Y; Campana MG; Corvelo A; Fleischer RC; Rutherford KM; Gemmell NJ; Dussex N; Mouritsen H; Thiele N; Delmore K; Liedvogel M; Franke A; Hoeppner MP; Krone O; Fudickar AM; Milá B; Ketterson ED; Fidler AE; Friis G; Parody-Merino ÁM; Battley PF; Cox MP; Lima NCB; Prosdocimi F; Parchman TL; Schlinger BA; Loiselle BA; Blake JG; Lim HC; Day LB; Fuxjager MJ; Baldwin MW; Braun MJ; Wirthlin M; Dikow RB; Ryder TB; Camenisch G; Keller LF; DaCosta JM; Hauber ME; Louder MIM; Witt CC; McGuire JA; Mudge J; Megna LC; Carling MD; Wang B; Taylor SA; Del-Rio G; Aleixo A; Vasconcelos ATR; Mello CV; Weir JT; Haussler D; Li Q; Yang H; Wang J; Lei F; Rahbek C; Gilbert MTP; Graves GR; Jarvis ED; Paten B; Zhang G
In Supplementary Table 1 of this Article, 23 samples (B10K-DU-029-32, B10K-DU-029-33, B10K-DU-029-36 to B10K-DU-029-44, B10K-DU- 029-46, B10K-DU-029-47, B10K-DU-029-49 to B10K-DU-029-53, B10K-DU- 029-75 to B10K-DU-029-77, B10K-DU-029-80, and B10K-DU-030-03; styled in boldface in the revised table) were assigned to the incorrect institution. Supplementary Table 1 has been amended to reflect the correct source institution for these samples, and associated data (tissue, museum ID/source specimen ID, site, state/province, latitude, longitude, date collected and sex) have been updated accordingly. The original table is provided as Supplementary Information to this Amendment, and the original Article has been corrected online.
Comparative transcriptomes reveal geographic differences in the ability of the liver of plateau zokors (Eospalax baileyi) to respond and adapt to toxic plants
(BioMed Central Ltd, 2023-12) Tan Y; Wang Y; Liu Q; Wang Z; Shi S; Su J
BACKGROUND: Environmental changes are expected to intensify in the future. The invasion of toxic plants under environmental changes may change herbivore feeding environments. Herbivores living long-term in toxic plant-feeding environments will inevitably ingest plant secondary metabolites (PSMs), and under different feeding environments are likely to have unique protection mechanisms that support improved adaptation to PSMs in their habitat. We aimed to compare different subterranean herbivore population responses and adaptations to toxic plants to unveil their feeding challenges. RESULTS: Here, we investigated the adaptive capacity of the liver in two geographically separated populations of plateau zokors (Eospalax baileyi) before and after exposure to the toxic plant Stellera chamaejasme (SC), at the organ, biochemical, and transcriptomic levels. The results showed no significant liver granules or inflammatory reactions in the Tianzhu (TZ) population after the SC treatment. The transaminase level in the TZ population was significantly lower than that in the Luqu population. Transcriptome analysis revealed that the TZ population exhibited interactions with other detoxification metabolic pathways by oxytocin pathway-associated genes, including diacylglycerol lipase alpha (Dagla), calcium/calmodulin dependent protein kinase II Alpha (Camk2a), and CD38 molecule (Cd38). The phase II process of liver drug metabolism increased to promote the rate of metabolism. We found that alternative splicing (AS) and the expression of the cyclin D (Ccnd1) gene interact-a TZ population hallmark-reduced liver inflammatory responses. CONCLUSION: Our study supports the detoxification limitation hypothesis that differences in liver detoxification metabolism gene expression and AS are potential factors in herbivore adaptation to PSMs and may be a strategy of different herbivore populations to improve toxic plant adaptability.
DeepCAC: a deep learning approach on DNA transcription factors classification based on multi-head self-attention and concatenate convolutional neural network
(BioMed Central Ltd, 2023-09-18) Zhang J; Liu B; Wu J; Wang Z; Li J
Understanding gene expression processes necessitates the accurate classification and identification of transcription factors, which is supported by high-throughput sequencing technologies. However, these techniques suffer from inherent limitations such as time consumption and high costs. To address these challenges, the field of bioinformatics has increasingly turned to deep learning technologies for analyzing gene sequences. Nevertheless, the pursuit of improved experimental results has led to the inclusion of numerous complex analysis function modules, resulting in models with a growing number of parameters. To overcome these limitations, it is proposed a novel approach for analyzing DNA transcription factor sequences, which is named as DeepCAC. This method leverages deep convolutional neural networks with a multi-head self-attention mechanism. By employing convolutional neural networks, it can effectively capture local hidden features in the sequences. Simultaneously, the multi-head self-attention mechanism enhances the identification of hidden features with long-distant dependencies. This approach reduces the overall number of parameters in the model while harnessing the computational power of sequence data from multi-head self-attention. Through training with labeled data, experiments demonstrate that this approach significantly improves performance while requiring fewer parameters compared to existing methods. Additionally, the effectiveness of our approach is validated in accurately predicting DNA transcription factor sequences.
DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites.
(29/06/2022) Zhang J; Liu B; Wang Z; Lehnert K; Gahegan M
BACKGROUND: Addressing the laborious nature of traditional biological experiments by using an efficient computational approach to analyze RNA-binding proteins (RBPs) binding sites has always been a challenging task. RBPs play a vital role in post-transcriptional control. Identification of RBPs binding sites is a key step for the anatomy of the essential mechanism of gene regulation by controlling splicing, stability, localization and translation. Traditional methods for detecting RBPs binding sites are time-consuming and computationally-intensive. Recently, the computational method has been incorporated in researches of RBPs. Nevertheless, lots of them not only rely on the sequence data of RNA but also need additional data, for example the secondary structural data of RNA, to improve the performance of prediction, which needs the pre-work to prepare the learnable representation of structural data. RESULTS: To reduce the dependency of those pre-work, in this paper, we introduce DeepPN, a deep parallel neural network that is constructed with a convolutional neural network (CNN) and graph convolutional network (GCN) for detecting RBPs binding sites. It includes a two-layer CNN and GCN in parallel to extract the hidden features, followed by a fully connected layer to make the prediction. DeepPN discriminates the RBP binding sites on learnable representation of RNA sequences, which only uses the sequence data without using other data, for example the secondary or tertiary structure data of RNA. DeepPN is evaluated on 24 datasets of RBPs binding sites with other state-of-the-art methods. The results show that the performance of DeepPN is comparable to the published methods. CONCLUSION: The experimental results show that DeepPN can effectively capture potential hidden features in RBPs and use these features for effective prediction of binding sites.
DeepSIM: a novel deep learning method for graph similarity computation
(Springer-Verlag GmbH, 2024-01) Liu B; Wang Z; Zhang J; Wu J; Qu G
Abstract: Graphs are widely used to model real-life information, where graph similarity computation is one of the most significant applications, such as inferring the properties of a compound based on similarity to a known group. Definition methods (e.g., graph edit distance and maximum common subgraph) have extremely high computational cost, and the existing efficient deep learning methods suffer from the problem of inadequate feature extraction which would have a bad effect on similarity computation. In this paper, a double-branch model called DeepSIM was raised to deeply mine graph-level and node-level features to address the above problems. On the graph-level branch, a novel embedding relational reasoning network was presented to obtain interaction between pairwise inputs. Meanwhile, a new local-to-global attention mechanism is designed to improve the capability of CNN-based node-level feature extraction module on another path. In DeepSIM, double-branch outputs will be concatenated as the final feature. The experimental results demonstrate that our methods perform well on several datasets compared to the state-of-the-art deep learning models in related fields.
Different effects of grazing and nitrogen addition on ecosystem multifunctionality are driven by changes in plant resource stoichiometry in a typical steppe
(5/08/2022) Li L; He XZ; Zhang X; Hu J; Wang M; Wang Z; Hou F
Purpose: Herbivore grazing and nitrogen (N) input may alter the multiple ecosystem functions (i.e., multifunctionality, hereafter) associated with carbon (C), N, and phosphorus (P) cycling. Most studies on variations in plant diversity, soil biotic or abiotic factors, and linkages to ecosystem functions have focused on grazing or N enrichment alone. Few studies have combined these two factors to explore the role of plant resource stoichiometry (C:N:P ratios) in ecosystem multifunctionality (EMF) control. Here, we evaluated the direct and indirect effects of stocking rate (0, 2.7, 5.3, and 8.7 sheep ha− 1) and N addition rate (0, 5, 10, and 20 g N m− 2 yr− 1) on a range of ecosystem functions and EMF via changing plant diversity, soil pH and plant resource stoichiometry in a typical steppe on the Loess Plateau. Results: We found that increasing stocking rate and interaction between grazing and N addition significantly decreased EMF, while increasing N addition rate significantly promoted EMF. Grazing decreased soil NH4+-N, soil NO3−-N, aboveground biomass, and plant C, N, and P pools, but increased soil total N and P at 8.7 and 5.3 sheep ha− 1, respectively. N addition increased soil NH4+-N, NO3−-N, and total P. Plant aboveground biomass, and plant C, N, and P pools increased at the lower N addition rate (≤ 5 g N m− 2 yr− 1) under grazing. The structural equation models indicated that (1) EMF was driven by the direct effects of grazing and the indirect effects of grazing on plant resource stoichiometry and soil pH; (2) EMF increased with increasing N addition rates, but such positive response of EMF to increasing N addition rates was alleviated at high levels of plant resource stoichiometry and diversity; and (3) the indirect effects of plant diversity induced by grazing and N addition had moderate effects on EMF via the variations of plant resource stoichiometry. Conclusions: This study demonstrated grazing and N addition had contrasting effects on ecosystem multifunctionality in a typical steppe, and highlighted the capacity of plant diversity in balancing plant elements that serve as a key mechanism in the maintenance of EMF in response to intensive grazing and N enrichment.
DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning
(BioMed Central Ltd, 2023-12) Wu J; Liu B; Zhang J; Wang Z; Li J
PURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets. RESULTS: In this study, the paper introduces a novel deep learning framework, termed DL-PPI, for predicting PPIs based on sequence data. The proposed framework comprises two key components aimed at improving the accuracy of feature extraction from individual protein sequences and capturing relationships between proteins in unfamiliar datasets. 1. Protein Node Feature Extraction Module: To enhance the accuracy of feature extraction from individual protein sequences and facilitate the understanding of relationships between proteins in unknown datasets, the paper devised a novel protein node feature extraction module utilizing the Inception method. This module efficiently captures relevant patterns and representations within protein sequences, enabling more informative feature extraction. 2. Feature-Relational Reasoning Network (FRN): In the Global Feature Extraction module of our model, the paper developed a novel FRN that leveraged Graph Neural Networks to determine interactions between pairs of input proteins. The FRN effectively captures the underlying relational information between proteins, contributing to improved PPI predictions. DL-PPI framework demonstrates state-of-the-art performance in the realm of sequence-based PPI prediction.
Does Parental Mind-Mindedness Account for Cross-Cultural Differences in Preschoolers' Theory of Mind?
(John Wiley and Sons, Inc., 2018-07-01) Hughes C; Devine RT; Wang Z
This study of 241 parent-child dyads from the United Kingdom (N = 120, Mage = 3.92, SD = 0.53) and Hong Kong (N = 121, Mage = 3.99, SD = 0.50) breaks new ground by adopting a cross-cultural approach to investigate children's theory of mind and parental mind-mindedness. Relative to the Hong Kong sample, U.K. children showed superior theory-of-mind performance and U.K. parents showed greater levels of mind-mindedness. Within both cultures parental mind-mindedness was correlated with theory of mind. Mind-mindedness also accounted for cultural differences in preschoolers' theory of mind. We argue that children's family environments might shed light on how culture shapes children's theory of mind.
Grazing activity increases decomposition of yak dung and litter in an alpine meadow on the Qinghai-Tibet plateau
(Springer Nature Switzerland AG on behalf of the Royal Netherlands Society of Agricultural Science, 2019-11) Yang C; Zhang Y; Hou F; Millner JP; Wang Z; Chang S; Shang Z
Aims: This study investigated the influences of herbivore grazing intensity and grazing season on decomposition and nutrient release of dung and litter, which aimed to improve our understandings of grazing affecting nutrient cycling in alpine meadows on the Qinghai-Tibetan Platean. Methods: A factorial design experiment comprising 3 grazing intensities (non-grazing, moderate grazing, and heavy grazing) and 2 grazing seasons (summer and winter), was applied to quantify the decomposition and chemistry of dung and litter in an alpine pasture using the litterbag technique. Litterbags were retrieved for analysis of mass loss and nutrient release with 180, 360, 540, and 720 days after placement. Results: Grazing activity accelerated the decomposition of dung and litter and increased nutrient release from dung and litter by increasing soil temperature compared with non-grazing pastures, whereas grazing season had no effect on decomposition. The decomposition time was shorter for dung than that for litter. Conclusions: Herbivores grazing benefited dung and litter decomposition and nutrient cycling directly by increasing soil temperature, which is likely to promote soil microbial activity due to low temperatures in alpine meadows, and indirectly through herbage ingestion and dung deposition which increase the organic debris concentration used for microorganisms growth and reproduction. This study provides insights into the mechanisms of grazing regulating nutrient cycling in alpine ecosystems.
Himalayan Marmot (Marmota himalayana) Redistribution to High Latitudes under Climate Change
(MDPI (Basel, Switzerland), 2023-08-28) Wang Z; Kang Y; Wang Y; Tan Y; Yao B; An K; Su J; Crowther M
Climate warming and human activities impact the expansion and contraction of species distribution. The Himalayan marmot (Marmota himalayana) is a unique mammal and an ecosystem engineer in the Qinghai-Tibet Plateau (QTP). This pest aggravates grassland degradation and is a carrier and transmitter of plagues. Therefore, exploring the future distribution of Himalayan marmots based on climate change and human activities is crucial for ecosystem management, biodiversity conservation, and public health safety. Here, a maximum entropy model was explored to forecast changes in the distribution and centroid migration of the Himalayan marmot in the 2050s and 2070s. The results implied that the human footprint index (72.80%) and altitude (16.40%) were the crucial environmental factors affecting the potential distribution of Himalayan marmots, with moderately covered grassland being the preferred habitat of the Himalayan marmot. Over the next 30-50 years, the area of suitable habitat for the Himalayan marmot will increase slightly and the distribution center will shift towards higher latitudes in the northeastern part of the plateau. These results demonstrate the influence of climate change on Himalayan marmots and provide a theoretical reference for ecological management and plague monitoring.
Learning and integration of adaptive hybrid graph structures for multivariate time series forecasting
(Elsevier Inc., 2023-11-01) Guo T; Hou F; Pang Y; Jia X; Wang Z; Wang R
Recent status-of-the-art methods for multivariate time series forecasting can be categorized into graph-based approach and global-local approach. The former approach uses graphs to represent the dependencies among variables and apply graph neural networks to the forecasting problem. The latter approach decomposes the matrix of multivariate time series into global components and local components to capture the shared information across variables. However, both approaches cannot capture the propagation delay of the dependencies among individual variables of a multivariate time series, for example, the congestion at intersection A has delayed effects on the neighboring intersection B. In addition, graph-based forecasting methods cannot capture the shared global tendency across the variables of a multivariate time series; and global-local forecasting methods cannot reflect the nonlinear inter-dependencies among variables of a multivariate time series. In this paper, we propose to combine the advantages of both approaches by integrating Adaptive Global-Local Graph Structure Learning with Gated Recurrent Units (AGLG-GRU). We learn a global graph to represent the shared information across variables. And we learn dynamic local graphs to capture the local randomness and nonlinear dependencies among variables. We apply diffusion convolution and graph convolution operations to global and dynamic local graphs to integrate the information of graphs and update gated recurrent unit for multivariate time series forecasting. The experimental results on seven representative real-world datasets demonstrate that our approach outperforms various existing methods.
Molecular Detection of Zoonotic and Veterinary Pathogenic Bacteria in Pet Dogs and Their Parasitizing Ticks in Junggar Basin, North-Western China
(Frontiers Media S.A., 2022-07) Guo J; Song S; Cao S; Sun Z; Zhou Q; Deng X; Zhao T; Chai Y; Zhu D; Chen C; Baryshnikov PI; Blair HT; Wang Z; Wang Y; Zhang H
Despite the recognized epidemiological importance of ticks as vectors for pathogens that cause numerous zoonotic and veterinary diseases, data regarding the pathogens of pet dogs and their parasitic ticks in the Junggar Basin are scarce. In this study, a total of 178 blood samples and 436 parasitic ticks were collected from pet dogs in Junggar Basin, Xinjiang Uygur Autonomous Region (XUAR), north-western China. All ticks were identified as Rhipicephalus turanicus sensu stricto (s.s.) according to morphological and molecular characteristics. Rh. turanicus s.s. ticks were collected from pet dogs in China for the first time. Seven tick-borne pathogens, such as Ehrlichia chaffeensis, Anaplasma phagocytophilum, Rickettsia massiliae, Candidatus R. barbariae, Brucella spp., Rickettsia sibirica, and Anaplasma ovis, were detected from ticks, whereas the first five bacteria were detected from blood samples of dogs. Brucella spp. was the most predominant pathogen in both blood samples and ticks of pet dogs, with the detection rates of 16.29 and 16.74%, respectively. Moreover, 17 ticks and 1 blood sample were co-infected with two pathogens, and 1 tick was co-infected with three pathogens. This study provided molecular evidence for the occurrence of Anaplasma spp., Ehrlichia spp., Rickettsia spp., and Brucella spp. circulating in pet dogs and their parasitic ticks in Junggar Basin, north-western China. These findings extend our knowledge of the tick-borne pathogens in pet dogs and their parasitic ticks in Central Asia; therefore, further research on these pathogens and their role in human and animal diseases is required.
Net-Zero Energy Campuses in India: Blending Education and Governance for Sustainable and Just Transition
(MDPI (Basel, Switzerland), 2023-12-21) Kalluri B; Vishnupriya V; Arjunan P; Dhariwal J; Wang Z; Zhang W; Wu W
This study addresses the urgent need for comprehensive climate education amid a climate emergency. Human (energy) behaviors are developed from childhood and early adulthood. This study hypothesizes that transcending a nation’s net-zero energy ambition can be accomplished through experiential education. An Urban Governance Lab plus nEt-Zero Energy league model is introduced. Various behavioral interventions are designed based on the principles of serious games. Discussions provide rich narratives on how a nation with so many diverse communities can forge a rapid net-zero transition. The blended multi-disciplinary STEM education can drive energy citizenship in campus-like communities. A scenarios-based analysis demonstrating the potential of the proposed model in shaping energy behavior in young citizens leading to net zero is presented. The results from the scenario analysis present optimistic evidence underlining how campus-like communities driven by bottom-up initiatives can realize net-zero ambition beyond hope.
Obligate mutualism within a host drives the extreme specialization of a fig wasp genome
(BioMed Central Ltd, 20/12/2013) Xiao J-H; Yue Z; Jia L-Y; Yang X-H; Niu L-H; Wang Z; Zhang P; Sun B-F; He S-M; Li Z; Xiong T-L; Xin W; Gu H-F; Wang B; Werren JH; Murphy RW; Wheeler D; Niu L-M; Ma G-C; Tang T; Bian S-N; Wang N-X; Yang C-Y; Wang N; Fu Y-G; Li W-Z; Yi SV; Yang X-Y; Zhou Q; Lu C-X; Xu C-Y; He L-J; Yu L-L; Chen M; Zheng Y; Wang S-W; Zhao S; Li Y-H; Yu Y-Y; Qian X-J; Cai Y; Bian L-L; Zhang S; Wang J-Y; Yin Y; Xiao H; Wang G-H; Yu H; Wu W-S; Cook JM; Wang J; Huang D-W
Background: Fig pollinating wasps form obligate symbioses with their fig hosts. This mutualism arose approximately 75 million years ago. Unlike many other intimate symbioses, which involve vertical transmission of symbionts to host offspring, female fig wasps fly great distances to transfer horizontally between hosts. In contrast, male wasps are wingless and cannot disperse. Symbionts that keep intimate contact with their hosts often show genome reduction, but it is not clear if the wide dispersal of female fig wasps will counteract this general tendency. We sequenced the genome of the fig wasp Ceratosolen solmsi to address this question. Results: The genome size of the fig wasp C. solmsi is typical of insects, but has undergone dramatic reductions of gene families involved in environmental sensing and detoxification. The streamlined chemosensory ability reflects the overwhelming importance of females finding trees of their only host species, Ficus hispida, during their fleeting adult lives. Despite long-distance dispersal, little need exists for detoxification or environmental protection because fig wasps spend nearly all of their lives inside a largely benign host. Analyses of transcriptomes in females and males at four key life stages reveal that the extreme anatomical sexual dimorphism of fig wasps may result from a strong bias in sex-differential gene expression. Conclusions: Our comparison of the C. solmsi genome with other insects provides new insights into the evolution of obligate mutualism. The draft genome of the fig wasp, and transcriptomic comparisons between both sexes at four different life stages, provide insights into the molecular basis for the extreme anatomical sexual dimorphism of this species. © 2013 Xiao et al.; licensee BioMed Central Ltd.
Picture book reading improves children's learning understanding.
(John Wiley and Sons Limited, 2024-02-28) Wang Z; Shao Y
Mental state reasoning is an integral part of children's teaching and learning understanding. This study investigated whether a picture book reading approach focusing on mental state discourse and contrasting perspectives in a preschool classroom setting would improve children's teaching and learning understanding and school readiness. In total, 104 children from four classrooms aged between 46 and 64 months (53 girls, M = 54.03 months, SD = 3.68) participated in the study. Half of the classrooms were randomly assigned to an experimental group where teachers read picture books rich in mental state discourse and engaged in intensive discussions with children for eight weeks. Children's false belief understanding and teaching and learning understanding were measured before and after the eight-week period. The result revealed that picture book reading improved children's learning understanding with a medium effect size, controlling for demographic variables, children's verbal ability, inhibition, and initial false belief understanding. The experimental group children further demonstrated more advanced school readiness 18 months after the intervention ended in a follow-up study using a teacher questionnaire.
Possibility of Wild Boar Harm Occurring in Five Provinces of Northwest China
(MDPI (Basel, Switzerland), 2023-12-08) Liu P; Wang Z; An K; Tan Y; Ji W; Su J; Phillips CJC
With the implementation of ecological engineering projects and related policies in China, wild boar (Sus scrofa) populations have surged, leading to increasingly serious conflicts with humans. We evaluated their potential habitat changes from the perspective of environmental suitability. To elucidate the suitable habitat characteristics for wild boars, we obtained data from 79 sites in five provinces in northwest China using database retrieval, human-wildlife conflict (HWC) incident questionnaires, and document retrieval. Thus, 10 environmental variables with lower correlation were selected, and potentially suitable distribution areas for wild boars under the current climate scenario were predicted based on the maximum entropy model. These areas were superimposed with different land use types in different periods to explore habitat selection. Precipitation seasonality (26.40%), human footprint index (16.50%), and elevation (11.90%) were the main environmental factors affecting wild boar distribution. The areas with high potential suitability for wild boars were mainly in the southeast and northwest of the region (total area of 2.63 × 105 km2). The land use types in the high-suitability zones are mainly woodland and grassland with high coverage, canopy density, and cultivated land borders. This study provides a reference for the effective prevention of HWC and management of wild boars.
Psychometric validation of the sibling inventory of behavior in three- to six-year-old Chinese children.
(Frontiers Media S.A., 2023-03-06) Xu H; Wang Z; Gao X; Wang X; Wu Q; Osman A
With increasing attention on sibling relationship studies in China, one problem that has been neglected is the limited validation of instruments used to assess these relationships. The present study evaluated the psychometric properties of the Sibling Inventory of Behavior to measure Chinese children’s sibling relationships using a stratified random sample of 590 parents of three- to six-year-olds in three economic regions. The confirmatory factor analysis obtained an adequate fit, suggesting that the Chinese version of the instrument had a six-factor structure (i.e., Companionship, Empathy, Teaching, Rivalry, Aggression, and Avoidance). It demonstrated satisfactory internal consistency as well as test–retest reliability. Results of discriminant, convergent, and criterion-related validity test also fulfilled psychometric requirements. Furthermore, the residual measurement invariance across regions was discovered. Given the importance, emergence, and tendency of sibling studies in China, having a reliable and valid instrument with robust psychometric properties is essential and impactful.
Secret of the Masters: Young Chess Players Show Advanced Visual Perspective Taking.
(Frontiers Media S.A., 2019-10-24) Gao Q; Chen W; Wang Z; Lin D; Moeller K
Playing chess requires perspective taking in order to consistently infer the opponent's next moves. The present study examined whether long-term chess players are more advanced in visual perspective taking tasks than their counterparts without chess training during laboratory visual perspective taking tasks. Visual perspective taking performance was assessed among 11- to 12-year-old experienced chess players (n = 15) and their counterparts without chess training (n = 15) using a dot perspective task. Participants judged their own and the avatar's visual perspective that were either consistent with each other or not. The results indicated that the chess players out-performed the non-chess players (Experiment 1), yet this advantage disappeared when the task required less executive functioning (Experiment 2). Additionally, unlike the non-chess players whose performance improved in Experiment 2 when the executive function (EF) demand was reduced, the chess players did not show better perspective taking under such condition. These findings suggested that long-term chess experience might be associated with children's more efficient perspective taking of other people's viewpoints without exhausting their cognitive resources.
Soil Microbial Community Composition and Diversity Are Insusceptible to Nitrogen Addition in a Semi-Arid Grassland in Northwestern China
(MDPI (Basel, Switzerland), 2023-10-11) Tuo H; Li M; Ghanizadeh H; Huang J; Yang M; Wang Z; Wang Y; Tian H; Ye F; Li W; Monokrousos N
Human-caused nitrogen (N) deposition is a global environmental issue that can change community composition, functions, and ecosystem services. N deposition affects plants, soil, and microorganisms regionally and is linked to ecosystem, soil, and climate factors. We examined the effects of six N addition levels (0, 2.34 g, 4.67, 9.34,18.68, and 37.35 g N m−2 yr−1) on aboveground vegetation, surface soil properties, and microbial community. Alterations in microbial communities in response to N addition were monitored using 16S rRNA (16S ribosomal ribonucleic acid, where S donates a sedimentation coefficient) and ITS (internal transcribed spacer) regions for bacterial and fungal communities, respectively. N addition positively affected aboveground vegetation traits, such as biomass and community weighted mean of leaf nitrogen. N addition also limited phosphorus (P) availability and altered the microbial community assembly process from random processes to deterministic processes. The microbial community diversity and composition, however, were not sensitive to N addition. Partial least squares structural equation models showed that the composition of bacterial communities was mainly driven by the composition of plant communities and total nitrogen, while the composition of fungal communities was driven by soil pH and community weighted mean of leaf nitrogen. Taken together, the results of this research improved our understanding of the response of grassland ecosystems to N deposition and provided a theoretical basis for grassland utilization and management under N deposition.

Browsing by Author "Wang Z"

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