Search Results (198)

Carbon sinks are of great significance for mitigating the greenhouse effect and climate change. However, only a few carbon sink measurement methods are suitable for small-scale research, such as at the city-region scale. Methods that can accurately distinguish the high–low gradients of forest carbon sinks within small-scale areas have not yet been established. To fill this gap, we used a tree allometric growth model—the i-Tree Eco model—and applied it to Tai’an, which is a National Forest City in China. By using indicator conversion methods, we innovatively combined the China Forest Resources Inventory Geographic Information Database with i-Tree Eco. The results showed that i-Tree Eco successfully estimated the carbon sinks provided by urban–rural forests (in 2019)—the total carbon storage in Tai’an forest was 5,828,165.90 t; the average carbon storage per hectare was 37.19 tC·ha⁻¹; the total carbon sequestration was 936,789.03 tC·yr⁻¹; and the annual carbon sequestration was, on average, 5.97 tC·ha⁻¹·yr⁻¹. Our method improved the spatial resolution of carbon sequestration and storage compared to the commonly used InVEST model, from about 350 m × 350 m to 195 m × 195 m. Compared to the traditional IPCC method, the i-Tree Eco model provided greater accuracy and timeliness in small-scale carbon sequestration measurements, eliminating the need to wait for the next forest inventory to be published. Our method yielded results that covered the entire city region and better reflected the spatial heterogeneity of carbon sinks. We conclude that the innovative application of the i-Tree Eco model to urban–rural-scale carbon sink measurements provides stronger technical support for urban green space planning, as well as data guidance, in relation to local carbon mitigation strategies. Full article

Although the allocation of biomass among floral organs reflects critical trade-offs in plant reproductive strategies, the scaling relationships governing biomass allocations remain poorly resolved, particularly in flowers. Here, we report the fresh mass scaling allocation patterns among four floral organs (i.e., sepals, petals, stamens, and carpels), and the two subtending structural components (i.e., the pedicel and receptacle) of 497 flowers of the hypogynous Rosa chinensis var. minima (miniature rose) using reduced major axis protocols. The two-parameter Weibull probability density function was also applied to characterize the distributions of floral organ mass, and revealed skewed tendencies in all six measured traits. The results show that the numerical values of the scaling exponents (α) for all pairwise power-law relationships significantly exceeded unity (α > 1), indicating disproportionate investments in larger floral structures with increasing overall flower size. Specifically, the scaling exponent of corolla fresh mass vs. calyx fresh mass was α = 1.131 (95% confidence interval [CI]: 1.086, 1.175), indicating that petal investment outpaces sepal investment as flower size increases. Reproductive organs also exhibited significant disproportionate investments (i.e., allometry): the collective carpel (gynoecium) fresh mass scaled allometrically with respect to the collective stamen (androecium) mass (α = 1.062, CI: 1.028, 1.098). Subtending axial structures (pedicel and receptacle) also had hyperallometric patterns, with pedicel mass scaling at α = 1.167 (CI: 1.106, 1.235) with respect to receptacle mass. Likewise, the combined fresh mass of all four foliar homologues (sepals, petals, androecium, and gynoecium) scaled disproportionately with respect to the biomass of the two subtending axial structures (α = 1.169, CI: 1.126, 1.214), indicating a prioritized resource allocation to reproductive and display organs. These findings are in accord with hypotheses positing that floral display traits, such as corolla size, primarily enhance pollen export by attracting pollinators, while maintaining fruit setting success through coordinated investment in gynoecium development. The consistent hyperallometry across all organ pairwise comparisons underscores the role of developmental integration in shaping floral architecture in Rosaceae, as predicted by scaling theory. By integrating morphometric and scaling analyses, this study proposes a tractable methodology for investigating floral resource allocation in monomorphic-flowering species and provides empirical evidence consistent with the adaptive patterns of floral traits within this ecologically and horticulturally significant lineage. Full article

We adapt previously developed conceptual and numerical models of ciguateric food chains on the Great Barrier Reef, Australia, to model the bioaccumulation of ciguatoxins (CTXs) in parrotfish, the simplest food chain with only two trophic levels. Our model indicates that relatively low (1 cell/cm²) densities of Gambierdiscus/Fukuyoa species (hereafter collectively referred to as Gambierdiscus) producing known concentrations of CTX are unlikely to be a risk of producing ciguateric fishes on the Great Barrier Reef unless CTX can accumulate and be retained in parrotfish over many months. Cell densities on turf algae equivalent to 10 Gambierdiscus/cm² producing known maximum concentrations of Pacific-CTX-4 (0.6 pg P-CTX-4/cell) are more difficult to assess but could be a risk. This cell density may be a higher risk for parrotfish than we previously suggested for production of ciguateric groupers (third-trophic-level predators) since second-trophic-level fishes can accumulate CTX loads without the subsequent losses that occur between trophic levels. Our analysis suggests that the ratios of parrotfish length-to-area grazed and weight-to-area grazed scale differently (allometrically), where the area grazed is a proxy for the number of Gambierdiscus consumed and hence proportional to toxin accumulation. Such scaling can help explain fish size–toxicity relationships within and between trophic levels for ciguateric fishes. Our modelling reveals that CTX bioaccumulates but does not necessarily biomagnify in food chains, with the relative enrichment and depletion rates of CTX varying with fish size and/or trophic level through an interplay of local and regional food chain influences. Our numerical model for the bioaccumulation and transfer of CTX across food chains helps conceptualize the development of ciguateric fishes by comparing scenarios that reveal limiting steps in producing ciguateric fish and focuses attention on the relative contributions from each part of the food chain rather than only on single components, such as CTX production. 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

This study addresses the challenges of manual measurement bias and low robustness in detecting small, occluded targets in complex marine environments during real-time onboard sorting of Portunus trituberculatus. We propose YOLO-DFAM, an enhanced YOLOv11n-based model that replaces the global average pooling in the Focal Modulation module with a spatial–channel dual-attention mechanism and incorporates the ASF-YOLO cross-scale fusion strategy to improve feature representation across varying target sizes. These enhancements significantly boost detection, achieving an mAP@50 of 98.0% and precision of 94.6%, outperforming RetinaNet-CSL and Rotated Faster R-CNN by up to 6.3% while maintaining real-time inference at 180.3 FPS with only 7.2 GFLOPs. Unlike prior static-scene approaches, our unified framework integrates attention-guided detection, scale-adaptive tracking, and lightweight weight estimation for dynamic marine conditions. A ByteTrack-based tracking module with dynamic scale calibration, EMA filtering, and optical flow compensation ensures stable multi-frame tracking. Additionally, a region-specific allometric weight estimation model (R² = 0.9856) reduces dimensional errors by 85.7% and maintains prediction errors below 4.7% using only 12 spline-interpolated calibration sets. YOLO-DFAM provides an accurate, efficient solution for intelligent onboard fishery monitoring. Full article

Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates resolving two biological constraints: phylogenetic conservation of allometric coefficients and ontogenetic regulation of scaling relationships. This study establishes an integrated framework combining the following: (1) phylogenetic signal detection (Blomberg’s K/Pagel’s λ) across 157 species’ allometric equations, revealing weak but significant evolutionary constraints (λ = 0.1249, p = 0.0027; K ≈ 0, p = 0.621); (2) hierarchical error decomposition of 9105 stems in a Mt. Wuyishan forest dynamics plot (15 species), identifying family-level error stratification (e.g., Theaceae vs. Myrtaceae, Δerror > 25%); (3) ontogenetic trajectory analysis of Castanopsis eyrei between Mt. Wuyishan and Mt. Huangshan, demonstrating significant biomass deviations in small trees (5–15 cm DBH, p < 0.05). Key findings resolve the following hypotheses: (1) absence of strong phylogenetic signals validates generalized models for phylogenetically diverse communities; (2) ontogenetic regulation dominates error magnitude, particularly in early developmental stages; (3) differential modeling is recommended: species-specific equations for pure forests/seedlings vs. generalized equations for mixed mature forests. This work establishes an error hierarchy: ontogeny > taxonomy > phylogeny, providing a mechanistic basis for optimizing forest carbon stock assessments. Full article

As China shifts from rapid to high-quality development, urban growth has exhibited allometric patterns. This study evaluated land use efficiency from the perspective of architectural space, focusing on 41 cities in the Yangtze River Delta urban agglomeration from 2010 to 2020. A land development intensity index was constructed at both the provincial and municipal levels using the entropy weight method, integrating floor area ratio, building density, and functional mix. The spatiotemporal characteristics of land development intensity and population density were analyzed, and a coordination coupling model was applied to identify mismatches between land and population. The results reveal: (1) Temporally, the imbalance of “more people, less land” in the Yangtze River Delta diminished. Spatially, leading regions exhibit a diffusion effect. Shanghai showed a decline in both population density and development intensity; Zhejiang maintained balanced development; Jiangsu experienced accelerated growth; and Anhui showed signs of catching up. (2) Although the two indicators showed a high coupling degree and strong correlation, the coordination degree remained low, indicating poor quality of correlation. The land-population relationship demonstrated a fluctuating pattern of “strengthening–weakening” over time. Shanghai exhibited the highest coordination, while more than half of the cities in Jiangsu, Zhejiang, and Anhui still needed optimization. (3) Unlike previous findings that linked such patterns to shrinking cities, in this transformation stage, the number of cities where land development intensity exceeded population density continued to grow in advanced regions. This study first applied 3D building data at the macro scale to support differentiated spatial policies. Full article

The use of cellular energy allocation (CEA) as a physiological energetic biomarker is useful for detecting the sublethal effects of environmental contaminants. The CEA assesses the health and energy status of organisms, serving as a reliable indicator for monitoring the health of aquatic ecosystems. This study aimed to evaluate the impact of emerging contaminants already listed as a priority for monitoring in freshwater ecosystems, namely sulfamethoxazole (0.156–2.50 mg/L), trimethoprim (25.0–400 mg/L), 4-chloroaniline (5.21–20.0 mg/L), and 3,4-dichloroaniline (0.38–4.00 mg/L), on the CEA of D. rerio embryos. A standard fish embryo toxicity test was conducted, and an adaptation of the allometric scaling approach was developed through the relationship between the size and the fresh weight of the embryos. All the compounds affected the fractions of the energy reserves (total carbohydrate, lipid, and protein contents) differently, with carbohydrates being the predominant energy fraction and the most responsive indicator. Although the energy consumed showed no significant changes, the CEA was notably altered after exposure to all the contaminants, indicating a direct connection to shifts in the available energy. The CEA alterations may indicate a reallocation of energy toward detoxification, combating the stress of contaminant exposure. Energy allocation biomarkers provide a comprehensive assessment of an organism’s physiological state, which is essential for evaluating emerging contaminants’ impacts, safeguarding aquatic ecosystems, and shaping effective environmental policies. Full article

China has implemented large-scale mangrove restoration and afforestation initiatives in recent years. However, there has been a paucity of research on the growth of mangrove seedlings in a composite stress environment and the allometric growth equation of mangrove seedlings. To enhance juvenile mangrove survival rates and develop precise carbon sequestration models, this study examines biomass accumulation patterns and allometric equation development under diverse environmental and biological conditions. A manipulative field experiment employed a three-factor full factorial design using seedlings from eight mangrove species. The experimental design incorporated three variables: salinity, flooding (environmental stressors), and aboveground interspecific competition (a biological factor). Following a two-year growth period, measurements of surviving seedlings’ basal diameter, plant height, and above- and belowground biomass were collected to assess growth responses and construct allometric models. Results indicated that high salinity reduced total mangrove biomass, whereas prolonged flooding increased tree height. Interspecific competition favored fast-growing species (e.g., Sonneratia caseolaris) while suppressing slow-growing counterparts (e.g., Avicennia marina). Synergistic effects between salinity and flooding influenced biomass and basal diameter, whereas salinity–flooding and salinity–competition interactions demonstrated antagonistic effects on tree height. High salinity, prolonged flooding, and competition elevated the proportion of aboveground biomass allocation. The results suggest that salinity stress and flooding stress were major growth-limiting factors for juvenile mangroves. Slow-growing species are not suitable to be mixed with fast-growing species in mangrove afforestation projects. Allometric models fitting for juvenile mangroves growing under different environmental factors were also developed. This study deepens our understanding of the growth of mangrove seedlings under composite stress conditions, provides effective tools for assessing the carbon sink potential of mangrove seedlings, and provides scientific guidance for future mangrove restoration projects. Full article

Forests play a pivotal role in the global carbon cycle, making accurate estimation of forest carbon stocks essential for climate change mitigation efforts. However, the diverse methods available for assessing forest carbon yield varying results and have different limitations. This study provides a comprehensive review of current methods for estimating forest carbon stocks, including field-based measurements, remote sensing techniques, and integrated approaches. We systematically collected and analyzed recent studies (2010–2025) on forest carbon estimation across various ecosystems. Our review indicates that field-based methods, such as forest inventories and allometric equations, offer high accuracy at local scales but are labor-intensive. Remote sensing methods (e.g., LiDAR and satellite imagery) enable large-scale carbon assessment with moderate accuracy and efficiency. Integrated approaches that combine ground measurements with remote sensing data can improve accuracy while expanding spatial coverage. We discuss the strengths and weaknesses of each method category in terms of accuracy, cost, and scalability. Based on the synthesis of findings, we recommend a balanced approach that leverages both ground and remote sensing techniques for reliable forest carbon monitoring. This review also identifies knowledge gaps and suggests directions for future research to enhance the precision and applicability of forest carbon estimation methods. Full article

Background/Objectives: As a monocyclic β-lactam antibiotic, aztreonam has regained attention recently because combining it with β-lactamase inhibitors helps fight drug-resistant bacteria. This study aimed to systematically characterize the plasma and tissue concentration-time profiles of aztreonam in rats, mice, dogs, monkeys, and humans by developing a multi-species, physiologically based pharmacokinetic (PBPK) model. Methods: A rat PBPK model was optimized and validated using plasma concentration-time curves determined by liquid chromatography–tandem mass spectrometry (LC-MS/MS) following intravenous administration, with reliability confirmed through another dose experiment. The rat model characteristics, modeling experience, ADMET Predictor (11.0) software prediction results, and allometric scaling were used to extrapolate to mouse, human, dog, and monkey models. The tissue-to-plasma partition coefficients (K_p values) were predicted using GastroPlus (9.0) software, and the sensitivity analyses of key parameters were evaluated. Finally, the cross-species validation was performed using the average fold error (AFE) and absolute relative error (ARE). Results: The cross-species validation showed that the model predictions were highly consistent with the experimental data (AFE < 2, ARE < 30%), but the deviation of the volume of distribution (V_ss) in dogs and monkeys suggested the need to supplement the species-specific parameters to optimize the prediction accuracy. The K_p values revealed a high distribution of aztreonam in the kidneys (K_p = 2.0–3.0), which was consistent with its clearance mechanism dominated by renal excretion. Conclusions: The PBPK model developed in this study can be used to predict aztreonam pharmacokinetics across species, elucidating its renal-targeted distribution and providing key theoretical support for the clinical dose optimization of aztreonam, the assessment of target tissue exposure in drug-resistant bacterial infections, and the development of combination therapy strategies. Full article

Background/Objectives: The pharmacokinetics of vancomycin (VCM) in patients with febrile neutropenia (FN) are highly variable due to coexisting conditions such as systemic inflammatory response syndrome and augmented renal clearance. Upon hematopoietic recovery, VCM clearance (CLvcm) is expected to normalize, which contributes to intra-individual variability. This study aimed to investigate the factors contributing to intra-individual variability in CLvcm among pediatric patients with FN. Methods: This retrospective, single-center study analyzed 33 pediatric patients (48 FN episodes) who met the inclusion criteria. CLvcm was estimated using Bayesian estimation based on the pediatric population pharmacokinetic model developed by Le et al., and standardized with allometrically scaled body weight. The change (Δ) in each clinical laboratory parameter or CLvcm was calculated as the difference between the values at the current and previous TDM within the same episode. Results: A total of 155 VCM TDM data points were analyzed. Intra-individual comparisons revealed that CLvcm decreased significantly in patients recovering from FN to a non-FN state (n = 18, p = 0.0285). Further analysis of intra-individual variability revealed that Δ CLvcm correlated significantly with Δ hemoglobin, Δ C-reactive protein, and Δ maximum daily body temperature, with the strongest correlation observed for Δ maximum daily body temperature (rs = 0.325, p = 0.001). Multivariate analysis confirmed Δ maximum daily body temperature as a significant factor influencing Δ CLvcm (B = 0.376, 95% CI: 0.074 to 0.678, p = 0.015). Conclusions: Maximum daily body temperature was identified as a factor influencing intra-individual variability in CLvcm in pediatric FN patients, particularly during the recovery process from FN to a non-FN state. The finding suggests that dose adjustment based on maximum daily body temperature may allow safe and effective VCM therapy in FN patients. Full article

Background: Clarithromycin is a commonly used macrolide antibiotic. Infection is a major source of mortality and morbidity in critical care units. Pharmacokinetics may vary during critical illness and suboptimal antimicrobial exposure has been shown to be associated with treatment failure. The pharmacokinetics of intravenous clarithromycin in critical illness have not previously been described. Methods: Pharmacokinetic, clinical and demographic data were collected from critically ill adults receiving intravenous clarithromycin. Drug concentrations were measured using high-performance liquid chromatography/mass spectrometry. Population pharmacokinetic analysis was performed using NONMEM version 7.5.1. Allometric weight scaling was added, and periods of renal replacement therapy were excluded a priori. Simulations of 10,000 patients were performed to assess pharmacokinetic–pharmacodynamic (PKPD) target attainment. Results: The analysis included 121 samples taken from 19 participants. A two-compartment model was found to provide the best fit. The addition of covariates did not improve model fit. There was no evidence of auto-inhibition in this population. Population parameter estimates of clearance and volume of distribution were lower than previously reported, with high interindividual variability. Simulations suggested reasonable pharmacokinetic–pharmacodynamic (PKPD) target attainment with current dosing regimens for most organisms that clarithromycin is used to treat with known clinical breakpoints. Conclusions: To our knowledge, this is the first study to describe the pharmacokinetics of intravenous clarithromycin in humans. Although our simulations suggest reasonable target attainment, further investigation into appropriate PKPD targets and clinical breakpoints for clarithromycin may enable dosing optimisation in this population. Full article

Forest growing stock volume (GSV) is a fundamental indicator for assessing the status of forest resources. It reflects forest carbon storage levels and serves as a key metric for evaluating the carbon sequestration capacity of forest ecosystems, thereby playing a crucial role in supporting national “dual-carbon” objectives. Traditional allometric models typically estimate GSV using tree species, diameter at breast height (DBH), and canopy height. However, at larger spatial scales, these models often neglect stand density, resulting in substantial estimation errors in regions characterized by significant density variability. To enhance the accuracy of large-scale GSV estimation, this study incorporates high-resolution, spatially continuous forest structural parameters—including dominant tree species, stand density, canopy height, and DBH—extracted through the synergistic utilization of active (e.g., Sentinel-1 SAR, ICESat-2 photon data) and passive (e.g., Landsat-8 OLI, Sentinel-2 MSI) multi-source remote sensing data. Within an allometric modeling framework, stand density is introduced as an additional explanatory variable. Subsequently, GSV is modeled in a stratified manner according to tree species across distinct ecological zones within Kunming City. The results indicate that: (1) the total estimated GSV of Kunming City in 2020, based on remote sensing imagery and second-class forest inventory data collected in the same year, was 1.01 × 10⁸ m³, which closely aligns with contemporaneous statistical records. The model yielded an R² of 0.727, an RMSE of 537.566 m³, and a MAE of 239.767 m³, indicating a high level of overall accuracy when validated against official ground-based inventory plots organized by provincial and municipal forestry authorities; (2) the incorporation of the dynamic stand density parameter significantly improved model performance, which elevated R² from 0.565 to 0.727 and significantly reduced RMSE. This result confirms that stand density is a critical explanatory factor; and (3) GSV exhibited pronounced spatial heterogeneity across both tree species and administrative regions, underscoring the spatial structural variability of forests within the study area. Full article

Background/Objectives: Physiologically based pharmacokinetic (PBPK) modeling is an important tool in biologic drug development. However, a standardized modeling strategy is currently missing. A cross-industry collaboration developed PBPK models for seven case studies, including monoclonal antibodies, antibody–drug conjugates, and bispecific T-cell engagers, to identify key parameters and establish a workflow to simulate biologic drugs in monkeys and in humans. Methods: PBPK models were developed in the monkey with limited data, including the molecular weight, the binding affinity to FcRn, and the additional systemic clearance of IgG, which is 20% of the total clearance. The binding affinity was only available for human FcRn and corrected for the known species-dependent differences in IgG binding. The strategy of monkey simulations was evaluated with an additional 14 studies published in the literature. Three different scenarios were simulated in humans afterwards: without, with allometrically scaled, and with optimized additional systemic clearance. Results: The plasma peak concentration and the area under the curve were predicted within 50% of the observed data for all studied case examples in the monkey, which demonstrates that sparse input parameters are sufficient for successful predictions in the monkey. Simulations in humans demonstrated the need for additional systemic clearance, because drug exposure was highly overpredicted without an additional systemic clearance term. Allometric scaling improved the predictions, but optimization led to the best fit, which is currently a limitation in the translation from animals to humans. Conclusions: This work highlights the importance of understanding the general mechanisms of drug uptake in different tissue types and cells in both target-dependent and -independent processes. Full article