Search Results (44)

Monitoring and assessing the spatial heterogeneity of soil elements within cultivated land presents core challenges in precision agriculture. Uncertainty analysis methods and optimal sampling densities for arsenic (As) pollution risk assessments in typical high-altitude regions of the southeastern Qinghai–Tibet Plateau remain insufficiently studied. This study investigates arsenic contamination in cultivated soils of a representative high-altitude region. By combining multi-level grid deployment with random sampling, seven datasets with varying sampling densities (62, 98, 139, 221, 289, 394, and 570 samples) were collected from 612 monitoring sites. The results indicate significant arsenic enrichment in the study area, with concentrations reaching 3.6 times the national soil background value and 2.4 times the plateau soil background value. Compared to arithmetic mean and median analyses, the geometric mean evaluation demonstrates lower uncertainty across different sampling densities in ecological environment assessments, averaging 4.3%, thereby providing more accurate results. Significant directional anisotropy exhibits a pronounced quadratic trend. The strongest spatial correlation occurs along the northwest–southeast direction, with the spatial autocorrelation distance in the vertical direction being 2.39 times greater than in other directions. Increasing sampling density is a macro-level requirement for accurately assessing the environmental risk characteristics of arsenic in plateau ecosystems; however, it is not the only factor influencing the spatial variability of arsenic concentrations. By comprehensively considering model fitting parameters, spatial distribution patterns, and cost–benefit analysis, a moderate sampling density of 20 points per square kilometer was determined to be optimal. This density provides a basis for exploring the distribution patterns and dynamic monitoring of arsenic as a risk element in plateau environments, while also provide monitoring guidance for developing countries with limited and fragmented agricultural land areas. Full article

This study investigates the spatial heterogeneity and species diversity of grassland vegetation in the agro-pastoral ecotone of China’s Loess Plateau, integrating Taylor’s power law model with the minimum area concept to address scale-dependent ecological patterns. Field surveys were conducted across four vegetation types: small-leaf poplar forest (SP), pine–caragana mixed forest (PC), caragana shrubland (RC), and saline grassland (SG). Nested quadrats (0.25–8 m²) were used to establish species–area relationships (SARs), while binary occurrence frequency data fitted to Taylor’s power law quantified spatial heterogeneity parameters (δ_i, δ_c, CACD) and derived diversity indices (H′, J′, D). the results showed that species composition differed significantly among vegetation types, with RC exhibiting the highest richness (25 species) and SG the lowest (12 species). SAR analysis showed distinct z-values: SP had the lowest z (0.14), indicating minimal area effects and high homogeneity, while SG had the highest area sensitivity. Spatial heterogeneity (δ_c) was highest in RC and lowest in SP. Over 82.5% of herb-layer species exhibited aggregated distributions (δ_i > 0). The dominant species Leymus secalinus (Georgi) Tzvelev shifted from regular (δ_i < 0) under SP/SG to aggregated (δ_i > 0) under PC/RC. Diversity metrics peaked in PC plots (highest H′ and richness, lowest dominance), whereas SP showed high dominance but low diversity. CACD values (critical aggregation diversity) were maximized under SG. The integration of power law modeling and minimum area analysis effectively captures scale-dependent vegetation patterns. Pine–caragana mixed forests (PC) optimize biodiversity and spatial heterogeneity, suggesting moderated canopy structures enhance ecological stability. These findings provide a theoretical basis for sustainable grassland management in ecologically sensitive agro-pastoral zones. Full article

Background and Objectives: Surgical treatment is central to breast cancer management; however, its long-term impact on QoL varies substantially among patients. This study sought to model the dynamic trajectories of postoperative QoL following breast-conserving surgery (BCS), mastectomy with immediate reconstruction (Mx+IR), and mastectomy alone (MA). It also examined how these trajectories varied across different age groups and over time. Materials and Methods: The review and meta-analysis identified 150 peer-reviewed studies reporting QoL outcomes using validated instruments (EORTC QLQ-C30 or BREAST-Q). A total of 123 observations from 45 studies were included for analysis of global QoL. We standardized QoL scores to a 0–100 scale and harmonized postoperative assessments across six time intervals, extending to more than 73 months. Multilevel random-effects models evaluated linear, quadratic, and logarithmic functions. Subgroup analyses and meta-regressions assessed the moderating effects of surgical type and age. Results: BCS showed the steepest QoL gains, followed by Mx+IR, while MA had the lowest scores and slowest recovery. Compared to BCS, MA showed significantly poorer and delayed recovery, and Mx+IR showed a smaller, borderline decrease. All groups displayed modest long-term QoL plateauing. Conclusions: Global QoL after breast cancer surgery follows distinct, time-dependent patterns shaped by surgical approach and age. These findings emphasize the importance of discussing patients’ quality-of-life expectations with them so that survivorship care can be personalized to their needs. Full article

Evolutionary processes involving sustainability are here expressed in units of classical mechanics, where newly evolved traits are distance, segments of evolutionary trees are time, and species as entire character sets are mass. Data arranged on a morphological evolutionary tree (caulogram) allow precise calculations of evolutionary velocity, acceleration, momentum and force, with force interpretable as resistance to environmental change. Stem-taxon trees of species of the moss family Streptotrichaceae and Pottiaceae tribe Pleuroweisieae were developed as sets of minimally monophyletic genera, and annotated with numbers of newly evolved traits per species. Calculations provided evidence that precise and comparative measures of the results of sustainable evolutionary processes may be calculated, and, as directly derived from expressed traits, are also accurate and informative about processes leading to resilience across multiple extinction events. The two groups evidenced similar, gradual evolutionary rates, implying that similar evolutionary processes occur across 110 my for Streptotrichaceae and 66 my for Pleuroweisieae, although habitats differ. Extension of sets of new traits per species into the past imply origination of the oldest extinct recognizable progenitors near the Permian–Triassic extinction event, when a cut-off in all data imply a complete over-haul of the character set for both groups, i.e., a major change in evolutionary mass. Speciation occurs in bursts. Extinction is gradual, the negative of acceleration. The rates of origination of genera over time for both groups are nearly the same as those previously proposed for genera of extinct horses. Plateaus in graphs of species per genus imply ancient quadratic patterns of speciation. The combination of process-governed stability through stasis of morphological traits, and of resilience as the ability to survive multiple extinction events has apparently little changed, and both contribute to sustainability over geologic time. Full article

Bare land exposed by glacier retreat provides new opportunities for ecosystem development. Investigating primary vegetation succession in deglaciated regions can provide significant insights for ecological restoration, particularly for future climate change scenarios. Nonetheless, research on this topic in the Qinghai–Tibet Plateau has been exceedingly limited. This study aimed to investigate vegetation succession in the deglaciated area of the Zepu glacier during the Little Ice Age in southeastern Tibet. Quadrat surveys were performed on arboreal communities, and trends in vegetation change were assessed utilizing multi-year (1986–2024) remote sensing data. The findings indicate that vegetation succession in the Zepu glacier deglaciated area typically adheres to a sequence of bare land–shrub–tree, divided into four stages: (1) shrub (species include Larix griffithii Mast., Hippophae rhamnoides subsp. yunnanensis Rousi, Betula utilis D. Don, and Populus pseudoglauca C. Wang & P. Y. Fu); (2) broadleaf forest primarily dominated by Hippophae rhamnoides subsp. yunnanensis Rousi; (3) mixed coniferous–broadleaf forest with Hippophae rhamnoides subsp. yunnanensis Rousi and Populus pseudoglauca C. Wang & P. Y. Fu as the dominant species; and (4) mixed coniferous–broadleaf forest dominated by Picea likiangensis (Franch.) E. Pritz. Soil depth and NDVI both increase with succession. Species diversity is significantly higher in the third stage compared to other successional stages. In addition, soil moisture content is significantly greater in the broadleaf-dominated communities than in the conifer-dominated communities. An analysis of NDVI from 1986 to 2024 reveals an overall positive trend in vegetation recovery in the area, with 93% of the area showing significant vegetation increase. Temperature is the primary controlling factor for this recovery, showing a positive correlation with vegetation cover. The results indicate that Key ecological indicators—including species composition, diversity, NDVI, soil depth, and soil moisture content—exhibit stage-specific patterns, reflecting distinct phases of primary succession. These findings enhance our comprehension of vegetation succession in deglaciated areas and their influencing factors in deglaciated areas, providing theoretical support for vegetation restoration in climate change. Full article

Climate change alters plant biomass allocation and aboveground–belowground trade-offs in grassland ecosystems, potentially affecting critical functions such as carbon sequestration. However, uncertainties persist regarding how precipitation gradients regulate (1) responses of aboveground biomass (AGB), belowground biomass (BGB), and total biomass in alpine grasslands, and (2) precipitation-mediated AGB-BGB allocation strategies. To address this, we conducted a large-scale field survey across precipitation gradients (400–700 mm/y) in the Sanjiangyuan alpine grasslands, Qinghai–Tibet Plateau. During the 2024 growing season, a total of 63 sites (including 189 plots and 945 quadrats) were sampled along five aridity classes: <400, 400–500, 500–600, 600–700, and >700 mm/y. Our findings revealed precipitation as the dominant driver of biomass dynamics: AGB exhibited equal growth rates relative to BGB within the 600–700 mm/y range, but accelerated under drier/wetter conditions. This suggests preferential allocation to aboveground parts under most precipitation regimes. Precipitation explained 31.71% of AGB–BGB trade-off variance (random forest IncMSE), surpassing contributions from AGB (17.61%), specific leaf area (SLA, 13.87%), and BGB (12.91%). Structural equation modeling confirmed precipitation’s positive effects on SLA (β = 0.28, p < 0.05), AGB (β = 0.53, p < 0.05), and BGB (β = 0.60, p < 0.05), with AGB-mediated cascades (β = 0.33, p < 0.05) dominating trade-off regulation. These results advance our understanding of mechanistic drivers governing allometric AGB–BGB relationships across climatic gradients in alpine ecosystems of the Sanjiangyuan Region on the Qinghai–Tibet Plateau. Full article

Noxious weeds (NWs) are increasingly recognized as a significant threat to the native alpine grassland ecosystems of the Qinghai–Tibetan Plateau (QTP). However, large-scale quantification of their continuous fractional cover remains challenging. This study proposes a pixel-level estimation framework utilizing time-series Sentinel-2 imagery. A Dynamic Mask Non-Stationary Transformer (DMNST) model was developed and trained using multi-temporal multispectral data to map the spatial distribution of NWs in the Three-River Headwaters Region. The model was calibrated and validated using field data collected from 170 plots (1530 quadrats). The results demonstrated that both the dynamic masking module and the non-stationary normalization significantly enhanced the prediction accuracy and robustness, particularly when applied jointly. The model performance varied across different combinations of spectral bands and temporal inputs, with the optimal configurations achieving a test R² of 0.770, MSE of 0.009, and RMSE of 0.096. These findings underscore the critical role of the input configuration and architectural enhancements in accurately modeling the fractional cover of NWs. This study confirms the applicability of Sentinel-2 time-series imagery for modeling the continuous fractional cover of NWs and provides a scalable tool for invasive species monitoring and ecological risk assessment in alpine ecosystems. Full article

In this study, we present a methodology for predicting timber board foot volume using a forest landscape model, incorporating allometric equations and forest inventory data. The research focuses on the Ozark Plateau, a 48,000-square-mile region characterized by productive soils and varied precipitation. To simulate timber volume, we used the LANDIS PRO forest landscape model, initialized with forest composition data derived from the USDA Forest Service’s Forest Inventory and Analysis (FIA) plots. The model accounted for species-specific growth rates and was run from the year 2000 to 2100 at five-year intervals. Timber volume estimates were calculated using both quadratic mean diameter (QMD) and tree diameter in the Hahn and Hansen board foot volume equation. These estimates were compared across different forest types—deciduous, coniferous, and mixed stands—and verified against FIA plot data using a paired permutation test. Results showed high correlations between QMD and tree diameter methods, with a slightly lower volume estimate from the QMD approach. Projections indicate significant increases in board foot volume for key species groups such as red oak and white oak while showing declines toward the end of the model period in groups like shortleaf pine due to age-related mortality and regeneration challenges. The model’s estimates closely align with state-level FIA data, underscoring the effectiveness of the integrated approach. The study highlights the utility of integrating landscape models and forest inventory data to predict timber volume over time, offering valuable insights for forest management and policy planning. Full article

As the contradiction between vegetation growth and soil moisture (SM) demand in arid zones gradually expands, accurately obtaining SM data is crucial for ecological construction. Remote sensing products limit small-scale studies due to the low resolution, and the emergence of downscaling solves this problem. This study proposes an improved semi-physical SM downscaling method. The effects of environmental factors on SM in different geographical zones (Windy Sand Hills, Flood Plains, Loess Yuan, Hilly Loess, Earth-rock Hills and Rocky Mountain) were analyzed using Random Forests. Vegetation and topographic factors were incorporated into the traditional downscaling algorithm based on the Mualem–van Genuchten model by setting weights, yielding 250 m resolution SM data for the Loess Plateau. This study found the following: (1) The Normalized Difference Vegetation Index (NDVI) was the most important environmental factor in all divisions except the Flood Plain, and the Digital Elevation Model (DEM) was second only to the NDVI in the overall importance evaluation, both of which positively influenced SM. (2) SM variability increased and then decreased when SM was below 0.4 cm³/cm³, but showed a quadratic growth trend when exceeding this threshold. The Rocky Mountain division exhibited the highest variability under the same SM. (3) Validation showed that the improved algorithm, based on geographic divisions to analyze factors importance and interpolation of coarse-scale SM and variability, had the highest accuracy, with an average R of 0.753 and an average ubRMSE of 0.042 cm³/cm³. The improved algorithm produced higher resolution, more accurate SM data, and offered insights for downscaling studies in arid regions, meeting the region’s high-resolution SM needs. Full article

In grassland ecosystems, aboveground biomass (AGB) is critical for energy flow, biodiversity maintenance, carbon storage, climate regulation, and livestock husbandry. Particularly on the climate-sensitive Tibetan Plateau, accurate AGB monitoring is crucial for assessing large-scale grassland livestock capacity. Previous studies focused on predicting AGB mainly at the plant community level and from the perspective of dry weight (AGB_d). This study aims to predict grassland AGB in Xizang at both the plant taxonomic group (sedge, graminoid, forb) and community levels, from both an AGB_d and a fresh weight (AGB_f) perspective. Three to four independent variables (growing mean temperature, total precipitation, total radiation and NDVI_max, maximum normalized difference vegetation index) were used for AGB prediction using nine models in Xizang grasslands. The random forest model (RFM) showed the greatest potential in simulating AGB (training R² ≥ 0.62, validation R² ≥ 0.87). This could be due to the nonlinear relationships between AGB, meteorological factors, and NDVI_max. The RFM exhibited robustness against outliers and zero values resulting from taxonomic groups that were absent from the quadrats. The accuracies of the RFM were different between fresh and dry weight, and among the three taxonomic groups. The RFM’s use of fewer variables can reduce complexity and costs compared to previous studies. Therefore, the RFM emerged as the optimal model among the nine models, offering potential for large-scale investigations into grassland AGB, especially for analyzing spatiotemporal patterns of plant taxonomic groups. Full article

As one of the dominant species of the alpine grassland on the Qinghai–Tibet Plateau, the activities (e.g., gnawing, burrowing, and grass storage) of plateau pikas (Ochotona curzoniae) directly alter the plant community structure of the grassland ecosystem and affect livestock production and greenhouse gas emission. In order to investigate the effects of rodent isolation (RI) on plant community structure and greenhouse gas emission in the alpine grassland of the Qinghai–Tibet Plateau, we established plots of rodent isolation and rodent activity (i.e., the control sample (CK)) in the 14th village, Seni District, Nagqu City in May 2018. From July 2019 to September, the numbers, sizes, and total damaged area of effective holes; the height, coverage, and aboveground plant biomass; and the methane (CH₄) and nitrous oxide (N₂O) emissions of the alpine grassland were monitored by the quadrat survey method and static closed-chamber method. The results show that the invasion and tunneling of Ochotona curzoniae resulted in the destruction of alpine grassland measuring 0.064 m² per square meter, while the rodent isolation plots showed that 97.9% of the alpine grassland remained unaltered; such unaffected land implies that the economic income of herdsmen could increase by 140 CNY hm⁻². The rodent isolation plots also show that the height and proportion of grasses and sedges in the alpine grassland increased, while the proportion of poisonous weeds decreased. Moreover, the rodent isolation plots also showed a significantly increased coverage of aboveground biomass (p < 0.05), although species richness showed no significant effect based on the Shannon–Weiner, Simpson, and Pielou indices (p > 0.05). The soil uptake of CH₄ and N₂O was 204.99 ± 50.23 μg m⁻² h⁻¹ and 4.48 ± 1.02 μg m⁻² h⁻¹ in the rodent isolation plots, significantly higher by 465.75% and 3001.4% relative to the rodent activity plots, respectively (p < 0.05). Therefore, the establishment of rodent isolation areas can effectively alleviate the degree of damage to alpine grasslands in the short run and slow down the greenhouse gas emission rate to some extent. However, excessive rodent control may also have negative effects on grassland ecosystems, so more attention should be paid in future studies to determining the disturbance threshold of plateau pika in this area. These results provide theoretical guidance for rodent control, grassland protection, and ecological environment management on the Qinghai–Tibet Plateau. Full article

The objective of this study was to evaluate the effects of the inclusion of dried Salvia officinalis (SO) shrub leaves on nutrient degradability, ruminal in vitro fermentation, gas production (GP), methane (CH₄), and carbon dioxide (CO₂) productions. Dried and ground SO shrub leaves were included at 0% (control), 0.5%, 1%, 1.5%, and 2% DM of a diet consisting of (per kg DM) 500 g concentrate feed mixture, 400 g berseem hay, and 100 g rice straw. The diet was incubated for 48 h. The asymptotic GP and the rate of GP changed linearly and quadratically (p < 0.01), with the highest GP observed at 1% inclusion of SO and then decreasing thereafter with greater inclusion (i.e., 1.5% and 2%), while CH₄ production and its rate decreased linearly (p < 0.01) with all levels of SO inclusion. A linear increase in CO₂ production and its rate was also found with an increasing level of SO inclusion in the diet (p < 0.05). Furthermore, the degradability of DM, NDF, and the concentration of total short-chain fatty acids and acetate changed linearly and quadratically, with the greatest being found at 1% SO inclusion and then steadily declining after (p < 0.01) with the 1.5% and 2% inclusion levels. Meanwhile, the propionate, NH₃-N, and microbial crude protein levels showed similar trends, with the plateau found at 1% inclusion of SO, where there was no change in butyrate concentration. Moreover, the pH, metabolizable energy, and partitioning factor (PF₂₄) also changed linearly and quadratically (p < 0.05), where the pH and PF₂₄ were considerably reduced and ME increased with a 1% inclusion of SO (p < 0.05). In summary, SO at 1% inclusion in the diet showed the potential to improve gas production kinetics, nutrient degradability, and the ruminal fermentation profile, with a more significant reduction in ruminal CH₄ production suggesting that SO at 1% could be included in the ruminant diet to reduce their carbon footprint and increase the production performance. Full article

The study’s aim was to examine alcohol consumption patterns and predictors of consumption across time among Hispanics with traumatic brain injury (TBI) in the U.S. within ten years post-injury. This longitudinal cohort study included 1342 Hispanic individuals (77.6% males) from the multi-site, longitudinal TBI Model Systems (TBIMS) database. The main outcome measures were consumption information, demographic, and injury characteristics. Across the full sample, alcohol consumption variables generally demonstrated quadratic movement characterized by an initial increase followed by a plateau or slight decrease over the ten years post-injury. The predictors of higher consumption were being men, single, with a history of excessive alcohol use, with a nonviolent mechanism of injury, shorter duration of PTA, and higher levels of education. Participants had a greater number of 5+ drinks/episode occurrences in the past month if they were men and had had a greater number of 5+ drinks/episode occurrences in the month before injury. There was no differential change in alcohol consumption over time as a function of these predictors. This study identified a profile of at-risk Hispanics with TBI for increased alcohol consumption. These individuals should be identified and targeted for early evidence-based alcohol intervention after TBI when results might be most favorable. Full article

The high altitude in mountainous regions results in lower atmospheric pressure, oxygen concentration and temperature, leading to lower combustion efficiency in motor vehicles. Therefore, there may be differences in carbon dioxide (CO₂), carbon monoxide (CO), and nitrogen oxides (NO_x) emissions characteristics at different altitudes. In this study, a portable emission measurement system was used to investigate the effects of varying elevations on the emission factors of CO₂, CO, and NO_x on diesel and gasoline-powered vehicles at altitudes ranging from 2270 to 4540 m in the Qinghai–Tibet Plateau of China. Additionally, the influencing factors of CO₂, CO, and NO_x emissions were studied. Results showed that the CO₂, CO, and NO_x emission factors for diesel vehicles varied in the range of 161.83–195.54, 0.59–0.77, and 4.61–6.58 g/km; the population means with 90% confidence intervals were 178.54, 0.68, and 5.60 g/km, respectively. For gasoline vehicles, the CO₂, CO, and NO_x emission factors varied in the range of 161.66–181.98, 0.95–1.06, and 0.12–0.25 g/km; the population means with 90% confidence intervals were 171.82, 1.01, and 0.19 g/km, respectively. Overall, the emission factors of diesel vehicles were higher than those of gasoline vehicles, and the emissions increased with increasing altitude. Atmospheric pressure was identified as the primary environmental factor affecting CO₂, CO, and NO_x emissions. As the speed of motor vehicles increased, the emission of CO₂ also increased, while there was a quadratic relationship with acceleration. This study provides a reference and guidance for vehicle pollution control in high-altitude regions. Full article

The increasing popularity of Greek yogurt generates large amounts of acid whey worldwide. The use of yogurt acid whey in animal nutrition is limited. The aim of this study was to determine the effect of a yogurt acid whey powder (YAWP) addition to maize forage prior to ensiling on the nutritional, microbial and fermentation quality of maize silage. Depending on the addition level of the YAWP to maize forage, there were the following four experimental treatments: YAWP 0, 2.5, 5 and 10% w/w. An increasing YAWP inclusion level linearly increased the maize silage dry matter, crude protein and ash concentrations, whereas it reduced the crude fiber, neutral-detergent fiber and acid-detergent fiber concentrations. The silage pH decreased quadratically with the increasing YAWP level, with the lower plateau noted for the YAWP 5% addition. Concentrations of total bacteria in the silage and Lactobacillus spp. decreased linearly with the YAWP increase. The silage acetic acid content decreased linearly, whereas propionic acid, lactic acid and the ratio of lactic to acetic acid increased linearly with the increasing YAWP level. The ammonia-N content decreased linearly with the increasing YAWP level. In conclusion, the incorporation of the 5 and 10% YAWP addition in silage preparation improved the nutritional and fermentative quality of the produced silage. Full article