Long-term regional vegetation dynamics is essential for the understanding of past land cover changes. High-resolution pollen analysis of a 1020 cm core from a large lake, Lake Yangzonghai (YZH), in central Yunnan, SW China, was conducted to reveal regional vegetation dynamics in the lake catchment over the past 13,400 years. Pollen record, principal component analysis (PCA) of pollen percentages of major arboreal taxa, and plant abundances estimated from the “Regional Estimates of VEgetation Abundance from Large Sites” (REVEALS) model show five successional stages of vegetation dynamics since 13,400 cal. a BP: regional vegetation with high coverages in the lateglacial (13,400–11,400 cal. a BP) was dominated by evergreen broadleaved forest (EBF) and deciduous broadleaved forest (DBF), together with some grass meadows and marshes; pine forest and alder forest expanded in the early Holocene (11,400–9000 cal. a BP) when vegetation coverages were still high; regional vegetation with low coverages was dominated by sweetgum forest, together with some pine forest during the mid-Holocene (9000–4200 cal. a BP); more pine forest, grass meadows and marshes occupied the lake catchment during the late Holocene (4200–800 cal. a BP), when vegetation coverages were higher than the average of the past 13,400 years; regional vegetation with low coverage was dominated by grass meadows and marshes, great deforestation happened in the last 800 years. Regional vegetation dynamics over the past 13,400 years in the Lake YZH catchment was the result of regional vegetation response to climate changes during the lateglacial and early–mid Holocene, and to human activities mainly during the late Holocene. Full article

Studies on obligate halophytes combining eco-physiological techniques and proteomic analysis are crucial for understanding salinity tolerance mechanisms but are limited. We thus examined growth, water relations, ion homeostasis, photosynthesis, oxidative stress mitigation and proteomic responses of an obligate halophyte Suaeda fruticosa to increasing salinity under semi-hydroponic culture. Most biomass parameters increased under moderate (300 mmol L⁻¹ of NaCl) salinity, while high (900 mmol L⁻¹ of NaCl) salinity caused some reduction in biomass parameters. Under moderate salinity, plants showed effective osmotic adjustment with concomitant accumulation of Na⁺ in both roots and leaves. Accumulation of Na⁺ did not accompany nutrient deficiency, damage to photosynthetic machinery and oxidative damage in plants treated with 300 mmol L⁻¹ of NaCl. Under high salinity, plants showed further decline in sap osmotic potential with higher Na⁺ accumulation that did not coincide with a decline in relative water content, Fv/Fm, and oxidative damage markers (H₂O₂ and MDA). There were 22, 54 and 7 proteins in optimal salinity and 29, 46 and 8 proteins in high salinity treatment that were up-regulated, down-regulated or exhibited no change, respectively, as compared to control plants. These data indicate that biomass reduction in S. fruticosa at high salinity might result primarily from increased energetic cost rather than ionic toxicity. Full article

Industrialization and increased energy use are leading to a greater influence of environmental and climate challenges on human existence and progress. China’s emissions in 2023 totaled 12.6 gigatons, representing 35% of global emissions, establishing it as the top carbon emitter globally. Combined with China’s industrial structure, it is essential to investigate carbon reduction in the building sector due to its significant contribution to carbon emissions. This study introduces a third-party organization into the relationship between stakeholders, based on traditional government regulation. It constructs a three-party dynamic evolution model involving the government, environmental protection organization, and construction enterprise. The study analyzes the evolution process of the three-party strategy selection using evolutionary game theory. We analyze the elements influencing decision-making for the three parties through simulation analysis and provide appropriate recommendations. The study’s findings indicate that low-carbon construction in China’s construction sector is an intricate system involving several stakeholders, each guided by their own interests when determining their behavioral methods. Government penalties and financial subsidies can influence construction enterprises to adopt low-carbon production practices to some degree, but excessive rewards and punishments may not support system stability. Full article

Natural plants contain numerous chemical compounds that are beneficial to human health. The berries from the Lycium genus are widely consumed and are highly nutritious. Moreover, their chemical constituents have attracted attention for their health-promoting properties. In East Asia, there are three varieties of the Lycium genus (Lycium barbarum L., Lycium chinense Miller, and L. ruthenicum Murray) that possess medicinal value and are commonly used for treating chronic diseases and improving metabolic disorders. These varieties are locally referred to as “red Goji berries” or “black Goji berries” due to their distinct colors, and they differ in their chemical compositions, primarily in terms of carotenoid and anthocyanin content. The pharmacological functions of these berries include anti-aging, antioxidant, anti-inflammatory, and anti-exercise fatigue effects. This review aims to analyze previous and recent studies on the active ingredients and pharmacological activities of these Lycium varieties, elucidating their signaling pathways and assessing their impact on the gut microbiota. Furthermore, the potential prospects for using these active ingredients in the treatment of COVID-19 are evaluated. This review explores the potential targets of these Lycium varieties in the treatment of relevant diseases, highlighting their potential value in drug development. Full article

Polymer microspheres with temperature and salt resistance were synthesized using the anti-suspension polymerization method, incorporating the functional monomers AMPS, AM, and AA. To enhance their self-gelling properties, the microspheres were designed with a core–shell structure. The shell is composed of a polymeric surfactant, fatty alcohol polyoxyethylene ether methacrylate (AEOMA), which serves as a thermosensitive crosslinking agent, enabling self-crosslinking upon shell decomposition, addressing compatibility with reservoir pore throat dimensions. Comprehensive characterizations including infrared spectroscopy, scanning electron microscopy, optical microscopy, and laser particle size analysis were conducted. The microspheres exhibited successful synthesis, a nanoscale size, and regular spherical morphology. They demonstrated excellent temperature and salt resistance, making them suitable for high-temperature, high-salinity reservoir profile control. With a stable three-dimensional network structure, the microspheres displayed good expansion behavior due to hydrophilic groups along the polymer chains, resulting in favorable water affinity. Even after aging, the microspheres maintained their gelling state with a distinct and stable microscopic network skeleton. They exhibited superior plugging performance in low-permeability reservoirs, while effectively improving water absorption profiles in reservoirs with permeability contrasts of 10 to 80, thereby enhancing oil recovery. Full article

Improving the spot brightness and uniformity of arrangement of the array laser is conducive to ensuring the beam quality of the fiber laser. Based on the light tracing principle, the optical model performance of two common fiber lasers was first analyzed. Then, a novel rotationally polarized optical model with high power and spot uniformity was designed and optimized on the basis of the aforementioned analysis. The results of the evaluation metrics of the multi-indicator optical model show that the spot uniformity of our proposed model improved by 24.03%, the power improved by 0.55%, and the maximum light distance was shortened from 120 mm to 82.58 mm. Further, the results of the coupling tolerance analysis of the optical elements show that the total coupling efficiency was 89.04%. The coupling power and tolerance relationships did not produce degradation compared with the traditional model. Extensive comparative results show that the designed rotationally polarized optical path model can effectively improve the optical coupling efficiency and spot uniformity of arrayed semiconductor lasers. Full article

Stern flaps and interceptors are prevalent stern appendages on medium- to high-speed ships, designed to modify the sailing posture of ships and diminish resistance. Using the Reynolds-averaged Navier–Stokes (RANS) method combined with overset mesh technology, this study evaluates the performance of a ship in regular waves before and after interceptor and stern flap installation. The findings indicate that the interceptor and stern flap resistance reduction rates initially declined and then rose with wavelength, typically 1–3% higher than in calm water. For a constant wavelength of 1.5 L_PP and when wave steepness ak ≥ 0.05, the interceptor and stern flap resistance reduction rates in regular waves decline as wave steepness increases. The stern appendages have a more prominent impact on ship posture owing to heightened ship motion amplitude in wave conditions compared to calm water. Moreover, after fitting the interceptor and stern flap, the heave and pitch transfer functions of the ship lessen after fitting the interceptor and stern flap, particularly when λ/L_PP = 1–2; average reduction rates for TF₃ and TF₅ are 7.2% and 3.9%, respectively, with a stern flap, and 4.4% and 2.1% after fitting the interceptor. This study offers invaluable insights and practical guidance for designing and applying stern appendages. Full article

Cancer has been one of the most problematic health issues globally. Typically, all cancers share a common characteristic or cancer hallmark, such as sustaining cell proliferation, evading growth suppressors, and enabling replicative immortality. Indeed, cell cycle regulation in cancer is often found to be dysregulated, leading to an increase in aggressiveness. These dysregulations are partly due to the aberrant cellular signaling pathway. In recent years, circular RNAs (circRNAs) have been widely studied and classified as one of the regulators in various cancers. Numerous studies have reported that circRNAs antagonize or promote cancer progression through the modulation of cell cycle regulators or their associated signaling pathways, directly or indirectly. Mostly, circRNAs are known to act as microRNA (miRNA) sponges. However, they also hold additional mechanisms for regulating cellular activity, including protein binding, RNA-binding protein (RBP) recruitment, and protein translation. This review will discuss the current knowledge of how circRNAs regulate cell cycle-related proteins through the abovementioned mechanisms in different cancers. Full article

Unraveling the multisymptomatic Gulf War Illness (GWI) pathology and finding an effective cure have eluded researchers for decades. The chronic symptom persistence and limitations for studying the etiologies in mouse models that differ significantly from those in humans pose challenges for drug discovery and finding effective therapeutic regimens. The GWI exposome differs significantly in the study cohorts, and the above makes it difficult to recreate a model closely resembling the GWI symptom pathology. We have used a double engraftment strategy for reconstituting a human immune system coupled with human microbiome transfer to create a humanized-mouse model for GWI. Using whole-genome shotgun sequencing and blood immune cytokine enzyme linked immunosorbent assay (ELISA), we show that our double humanized mice treated with Gulf War (GW) chemicals show significantly altered gut microbiomes, similar to those reported in a Veteran cohort of GWI. The results also showed similar cytokine profiles, such as increased levels of IL-1β, IL-6, and TNF R-1, in the double humanized model, as found previously in a human cohort. Further, a novel GWI Veteran fecal microbiota transfer was used to create a second alternative model that closely resembled the microbiome and immune-system-associated pathology of a GWI Veteran. A GWI Veteran microbiota transplant in humanized mice showed a human microbiome reconstitution and a systemic inflammatory pathology, as reflected by increases in interleukins 1β, 6, 8 (IL-1β, IL-6, IL-8), tumor necrosis factor receptor 1 (TNF R-1), and endotoxemia. In conclusion, though preliminary, we report a novel in vivo model with a human microbiome reconstitution and an engrafted human immune phenotype that may help to better understand gut–immune interactions in GWI. Full article

Cetaceans, which are crucial in marine ecosystems, act as sentinels for ecosystem and human–environmental health. However, emerging fungal infections, particularly by Candida spp., pose a growing concern in these marine mammals. This review consolidates current knowledge on the prevalence, clinical manifestations, species distribution, and antifungal resistance of Candida infections in cetaceans. We detail the diverse pathogenic impacts of Candida, including respiratory, dermal, and systemic afflictions, underscoring diagnostic and treatment challenges amid rising antifungal resistance. Our analysis extends beyond health concerns in captive cetaceans, where confinement stress heightens vulnerability, to encompass substantial ecological risks in wild populations. The review emphasizes the One Health perspective, linking cetacean health with broader environmental and human public health issues. We particularly focus on the potential zoonotic transmission of emerging fungal pathogens such as Candida auris and the role of environmental changes in fostering antifungal resistance. The study underscores the need for concerted, interdisciplinary efforts in veterinary, medical, and environmental sciences to enhance understanding and management of Candida infections in cetaceans. We advocate for comprehensive monitoring and collaborative research initiatives to mitigate the rising challenge of these infections. Addressing Candida spp. in cetaceans is not just a conservation priority but a critical step in safeguarding overall marine health and, by extension, human health in the context of evolving infectious diseases. Full article

Current point cloud registration methods predominantly focus on extracting geometric information from point clouds. In certain scenarios, i.e., when the target objects to be registered contain a large number of repetitive planar structures, the point-only based methods struggle to extract distinctive features from the similar structures, which greatly limits the accuracy of registration. Moreover, the deep learning-based approaches achieve commendable results on public datasets, but they face challenges in generalizing to unseen few-shot datasets with significant domain differences from the training data, and that is especially common in industrial applications where samples are generally scarce. Moreover, existing registration methods can achieve high accuracy on complete point clouds. However, for partial point cloud registration, many methods are incapable of accurately identifying correspondences, making it challenging to estimate precise rigid transformations. This paper introduces a domain-adaptive multimodal feature fusion method for partial point cloud registration in an unsupervised manner, named DAMF-Net, that significantly addresses registration challenges in scenes dominated by repetitive planar structures, and it can generalize well-trained networks on public datasets to unseen few-shot datasets. Specifically, we first introduce a point-guided two-stage multimodal feature fusion module that utilizes the geometric information contained in point clouds to guide the texture information in images for preliminary and supplementary feature fusion. Secondly, we incorporate a gradient-inverse domain-aware module to construct a domain classifier in a generative adversarial manner, weakening the feature extractor’s ability to distinguish between source and target domain samples, thereby achieving generalization across different domains. Experiments on a public dataset and our industrial components dataset demonstrate that our method improves the registration accuracy in specific scenarios with numerous repetitive planar structures and achieves high accuracy on unseen few-shot datasets, compared with the results of state-of-the-art traditional and deep learning-based point cloud registration methods. Full article

In the process of completing large-scale and fine-grained sensing tasks for the new generation of crowd-sensing systems, the role of analysis, reasoning, and decision making based on artificial intelligence has become indispensable. Mobile crowd sensing, which is an open system reliant on the broad participation of mobile intelligent terminal devices in data sensing and computation, poses a significant risk of user privacy data leakage. To mitigate the data security threats that arise from malicious users in federated learning and the constraints of end devices in crowd-sensing applications, which are unsuitable for high computational overheads associated with traditional cryptographic security mechanisms, we propose FedCrow, which is a federated-learning-based approach for protecting crowd-sensing data that integrates federated learning with crowd sensing. FedCrow enables the training of artificial intelligence models on multiple user devices without the need to upload user data to a central server, thus mitigating the risk of crowd-sensing user data leakage. To address security vulnerabilities in the model data during the interaction process in federated learning, the system employs encryption methods suitable for crowd-sensing applications to ensure secure data transmission during the training process, thereby establishing a secure federated-learning framework for protecting crowd-sensing data. To combat potential malicious users in federated learning, a legitimate user identification method based on the user contribution level was designed using the gradient similarity principle. By filtering out malicious users, the system reduces the threat of attacks, thereby enhancing the system accuracy and security. Through various attack experiments, the system’s ability to defend against malicious user attacks was validated. The experimental results demonstrate the method’s effectiveness in countering common attacks in federated learning. Additionally, through comparative experiments, suitable encryption methods based on the size of the data in crowd-sensing applications were identified to effectively protect the data security during transmission. Full article

In this research, the properties and cementitious performance of thermally activated cement pastes (referred to as DCPs) are investigated. Hydrated pastes prepared from Portland cement and slag blended cement were subjected to different thermal treatments: 350 °C for 2 h, 550 °C for 2 h, 550 °C for 24 h and 750 °C for 2 h. The properties and the reactivity as SCM of the DCPs were characterised as well as their effect on the mechanical performance and hydration of new blended cements incorporating the DCPs as supplementary cementitious materials (SCMs). It was observed that the temperature and duration of the thermal treatment increased the grindability and BET specific surface area of the DCP, as well as the formation of C₂S phases and the reactivity as SCM. In contrast, the mechanical strength results for the blended cements indicated that thermal treatment at 350 °C for 2 h provided better performance. The hydration study results showed that highly reactive DCP interfered with the early hydration of the main clinker phases in Portland cement, leading to early setting and slow strength gain. The effect on blended cement hydration was most marked for binary Portland cement–DCP blends. In contrast, in the case of ternary slag cement–DCP blends the use of reactive DCP as SCM enabled to significantly increase early age strength. Full article

Background: The variation in body mass index (BMI) of inpatients with anorexia nervosa has not been analyzed across the age span. A positive correlation between BMI and age has been reported in adolescent inpatients aged 15 years and younger that levels off at 15 to 18 years. BMIs standardized for age and sex (standard deviation scores, SDSs) were negatively correlated with age in these inpatients aged 8 to 18 years. Methods: The aims of the current retrospective study were threefold: first, to confirm the relationships of BMI, BMI-SDS and age in adolescent inpatients in a larger sample; second, to systematically assess the relationship of BMI, BMI-SDS, body height-SDS and age in adult inpatients at the time of referral; and third, to assess body height-SDSs and age to evaluate stunting. Results: We included 1001 girls (aged 12–17.9 years) and 1371 women (aged 18–73 years) admitted to inpatient treatment between 2014 and 2021. Mean BMI at admission was 14.95 kg/m² (SD = 1.43; range 10.67–18.47) in adolescents and 14.63 kg/m² (SD = 2.02; range 8.28–18.47) in adults. None of the adolescent patients but 20 adults had very low BMI values below 10 kg/m². Adolescents showed a small but significant positive correlation between age and BMI (r = 0.12; p = 2.4 × 10⁻⁴). In adults, BMI was not correlated with age (r = −0.03; p = 0.3). BMI-SDSs was negatively correlated with age in adolescents and less so in adults (r = −0.35; p < 0.001 and r = −0.09; p = 0.001). Curve fit analyses for all patients indicated that there was a quadratic (age × age) relationship between age and BMI-SDS. Height correlated positively with BMI in adult (r = 0.1; p < 0.001) and adolescent (r = 0.09 p = 0.005) patients and we detected no evidence for stunting. Conclusions: In conclusion, the BMI of inpatients seems to be relatively stable across the age span with mean values between 14 and 15 kg/m². BMI values initially increase with age in younger patients, drop between ages 18 and 23 and then slowly decline with age. Full article

The Xinjiang Uygur Autonomous Region (Xinjiang), being a rapidly developing region and a comprehensive energy base, plays an important role in China’s low-carbon energy transition. This paper attempts to develop a hybrid approach integrating energy allocation analysis, Logarithmic Mean Divisia Index (LMDI) decomposition, and a system dynamics (SD) model to identify the driving factors of the energy system’s changes during 2005–2020, and to analyze future scenarios of the energy system from 2020 to 2060. The results indicate that in 2005–2020, coal and electricity consumption increased sharply, due to the expansion of the chemical and non-ferrous metal industries. Meanwhile, the natural gas flow also expanded greatly because of the construction of the Central Asia pipeline and the increase in local production. In the baseline scenario, energy-related carbon emissions (ERCE) will peak in 2046 at 628 Mt and decrease to 552 Mt in 2060. With a controlled GDP growth rate and an adjusted industrial structure, ERCE will peak in 2041 at 565 Mt and decrease to 438 Mt in 2060. With a controlled energy intensity and an adjusted energy structure, ERCE will peak in 2039 at 526 Mt and decrease to 364 Mt in 2060. If all policy measures are adopted, ERCE will peak in 2035 at 491 Mt and decrease to 298 Mt in 2060. Full article

Background/Objectives: The inhibitory effects of tyrosine kinase inhibitors (TKIs) on glucose uptake through their binding to human glucose transporter-1 (GLUT-1) have been well documented. Thus, our research aimed to explore the potential impact of various TKIs of GLUT-1 on the standard [¹⁸F]FDG-PET monitoring of tumor response in patients. Methods: To achieve this, we conducted an analysis on three patients who were undergoing treatment with different TKIs and harbored actionable alterations. Alongside the assessment of FDG data (including SUVmax, total lesion glycolysis (TLG), and metabolic tumor volume (MTV)), we also examined the changes in tumor sizes through follow-up [¹⁸F]FDG-PET/CT imaging. Notably, our patients harbored alterations in BRAFV600, RET, and c-KIT and exhibited positive responses to the targeted treatment. Results: Our analysis revealed that FDG data derived from SUVmax, TLG, and MTV offered quantifiable outcomes that were consistent with the measurements of tumor size. Conclusions: These findings lend support to the notion that the inhibition of GLUT-1, as a consequence of treatment efficacy, could be indirectly gauged through [¹⁸F] FDG-PET/CT imaging in cancer patients undergoing TKI therapy. Full article

Hepatocellular carcinoma (HCC) results in the abnormal regulation of cellular metabolic pathways. Constraint-based modeling approaches can be utilized to dissect metabolic reprogramming, enabling the identification of biomarkers and anticancer targets for diagnosis and treatment. In this study, two genome-scale metabolic models (GSMMs) were reconstructed by employing RNA sequencing expression patterns of hepatocellular carcinoma (HCC) and their healthy counterparts. An anticancer target discovery (ACTD) framework was integrated with the two models to identify HCC targets for anticancer treatment. The ACTD framework encompassed four fuzzy objectives to assess both the suppression of cancer cell growth and the minimization of side effects during treatment. The composition of a nutrient may significantly affect target identification. Within the ACTD framework, ten distinct nutrient media were utilized to assess nutrient uptake for identifying potential anticancer enzymes. The findings revealed the successful identification of target enzymes within the cholesterol biosynthetic pathway using a cholesterol-free cell culture medium. Conversely, target enzymes in the cholesterol biosynthetic pathway were not identified when the nutrient uptake included a cholesterol component. Moreover, the enzymes PGS1 and CRL1 were detected in all ten nutrient media. Additionally, the ACTD framework comprises dual-group representations of target combinations, pairing a single-target enzyme with an additional nutrient uptake reaction. Additionally, the enzymes PGS1 and CRL1 were identified across the ten-nutrient media. Furthermore, the ACTD framework encompasses two-group representations of target combinations involving the pairing of a single-target enzyme with an additional nutrient uptake reaction. Computational analysis unveiled that cell viability for all dual-target combinations exceeded that of their respective single-target enzymes. Consequently, integrating a target enzyme while adjusting an additional exchange reaction could efficiently mitigate cell proliferation rates and ATP production in the treated cancer cells. Nevertheless, most dual-target combinations led to lower side effects in contrast to their single-target counterparts. Additionally, differential expression of metabolites between cancer cells and their healthy counterparts were assessed via parsimonious flux variability analysis employing the GSMMs to pinpoint potential biomarkers. The variabilities of the fluxes and metabolite flow rates in cancer and healthy cells were classified into seven categories. Accordingly, two secretions and thirteen uptakes (including eight essential amino acids and two conditionally essential amino acids) were identified as potential biomarkers. The findings of this study indicated that cancer cells exhibit a higher uptake of amino acids compared with their healthy counterparts. Full article

With the high proportion of renewable energy sources and power electronic devices accessed in the distribution network, the harmonic pollution problem has become increasingly serious. The traditional centralized harmonic mitigation strategy has difficulty in effectively dealing with these scattered and random harmonics. Therefore, a distributed harmonic mitigation strategy based on the dynamic points incentive of blockchain communities is proposed in this paper. Firstly, a comprehensive voltage sensitivity partitioning method with harmonic weight differentiation is proposed to realize the reasonable partitioning of each control node and controlled node in the distribution network concerning variability in harmonic components and their distribution. Then, a harmonic mitigation strategy based on the dynamic integral excitation of self-learning algorithms is constructed to promote self-organized optimization and active distributed coordinated control of mitigation devices. The strategy ensures that the total harmonic voltage distortion rate of each node meets the requirements by adjusting the partitioned collaboration to realize optimal harmonic mitigation. By setting optimized partitions in different scenarios and conducting simulation verification, the results demonstrate the effectiveness of the strategy in this paper. It stimulates synergy between devices through a dynamic incentive mechanism and significantly reduces the total harmonic voltage distortion rate across various test scenarios, reflecting the adaptability of the harmonic mitigation method presented. Full article

Recent advancements in vaccine delivery systems have seen the utilization of various materials, including lipids, polymers, peptides, metals, and inorganic substances, for constructing non-viral vectors. Among these, lipid-based nanoparticles, composed of natural, synthetic, or physiological lipid/phospholipid materials, offer significant advantages such as biocompatibility, biodegradability, and safety, making them ideal for vaccine delivery. These lipid-based vectors can protect encapsulated antigens and/or mRNA from degradation, precisely tune chemical and physical properties to mimic viruses, facilitate targeted delivery to specific immune cells, and enable efficient endosomal escape for robust immune activation. Notably, lipid-based vaccines, exemplified by those developed by BioNTech/Pfizer and Moderna against COVID-19, have gained approval for human use. This review highlights rational design strategies for vaccine delivery, emphasizing lymphoid organ targeting and effective endosomal escape. It also discusses the importance of rational formulation design and structure–activity relationships, along with reviewing components and potential applications of lipid-based vectors. Additionally, it addresses current challenges and future prospects in translating lipid-based vaccine therapies for cancer and infectious diseases into clinical practice. Full article

Moso bamboo (Phyllostachys heterocycla cv. Pubescens) is known for its high capacity to sequester atmospheric carbon (C), which has a unique role to play in the fight against global warming. However, due to rising labor costs and falling bamboo prices, many Moso bamboo forests are shifting to an extensive management model without fertilization, resulting in gradual degradation of Moso bamboo forests. However, many Moso bamboo forests are being degraded due to rising labor costs and declining bamboo timber prices. To delineate the effect of degradation on soil microbial carbon sequestration, we instituted a rigorous analysis of Moso bamboo forests subjected to different degradation durations, namely: continuous management (CK), 5 years of degradation (D-5), and 10 years of degradation (D-10). Our inquiry encompassed soil strata at 0–20 cm and 20–40 cm, scrutinizing alterations in soil organic carbon (SOC), water-soluble carbon (WSOC), microbial carbon (MBC) and microbial residues. We discerned a positive correlation between degradation and augmented levels of SOC, WSOC, and MBC across both strata. Furthermore, degradation escalated concentrations of specific soil amino sugars and microbial residues. Intriguingly, extended degradation diminished the proportional contribution of microbial residuals to SOC, implying a possible decline in microbial activity longitudinally. These findings offer a detailed insight into microbial C processes within degraded bamboo ecosystems. Full article

There has been a limited number of studies on the effects of harmful algal blooms (HABs) on natural rocky intertidal ecosystems. From mid-September to early November 2021, an unprecedented HAB caused by Karenia selliformis hit the Pacific coast of southeast Hokkaido, Japan, for the first time, causing massive mortalities among marine organisms. To clarify the immediate impacts of the HAB on the abundance of 10 rocky intertidal species in four functional groups (macroalgae, sessile invertebrates, molluscan grazers, and molluscan carnivores), we focused on two questions: (1) How did the HAB affect the abundance of each species differently at the regional scale? and (2) How did the impacts of the HAB on the abundance of each functional groups vary spatially, and was the spatial variation of the HAB impacts related to the spatial distribution of the cell density of HAB species? To study these issues, we compared census data for 17 years before the HAB and within one month after it for five shores on the southeast coast of Hokkaido. The results showed that two macroalgae species and all three molluscan grazer species declined significantly after the HAB. Moreover, the decrease in molluscan grazers was significantly correlated with cell density. These results suggest that the impacts of the HAB in southeast Hokkaido on the abundance of rocky intertidal organisms are highly variable depending on species and locality, presumably because of differences in species-specific tolerances to HAB toxins and the spatial variation in the density of the HAB organisms. Full article

With rapid economic development and urban expansion, China faces a serious imbalance between production, living, and ecological land use, in which the erosion of water ecological space by urban expansion is especially notable. In order to alleviate or solve this imbalance, this study constructs the water ecological space in the Mulan River Basin based on national land spatial planning using remote sensing statistics and the 2000–2020 statistical yearbooks for the Mulan River Basin. A landscape index is applied to explore this landscape in terms of its production–living–ecological space (PLES) patterns and evolutionary characteristics. Factors affecting the drivers of PLES changes are analyzed through Geo-Detector, and predictions are made using the cellular automata Markov (CA-Markov) model. It was found that (1) PLES distribution patterns in the Mulan River Basin from 2000 to 2020 are dominated by non-watershed ecological spaces, with a significant expansion of living space. Its ecological space is shrinking, and there is significant spatial variation between its near-river and fringe areas. (2) Of the PLES conversions, the most dramatic conversions are those of production space and living space, with 81.14 km² of production space being transferred into living space. Non-water ecological space and water ecological space are also mainly transferred into production space. (3) As shown by the results of the landscape index calculation, non-water ecological space in the Mulan River Basin is the dominant landscape, the values of the Shannon diversity index (SHDI) and Shannon homogeneity index (SHEI) are small, the overall level of landscape diversity is low, the aggregation index (AI) is high, and the degree of aggregation is obvious. (4) The progressive PLES changes in the Mulan River Basin are influenced by a combination of natural geographic and socioeconomic factors, with the mean population density and mean elevation being the most important factors affecting PLES changes among social and natural factors, respectively. (5) The Kappa coefficient of the CA-Markov model simulation is 0.8187, showing a good simulation accuracy, and it is predicted that the area of water ecological space in the Mulan River Basin will increase by 3.66 km² by 2030, the area of production space and non-water ecological space will further decrease, and the area of construction land will increase by 260.67 km². Overall, the aquatic ecological space in the Mulan River Basin has made progress in terms of landscape ecological protection, though it still faces serious erosion. Therefore, attaching importance to the restoration of the water ecological space in the Mulan River Basin, integrating multiple elements of mountains, water, forests, fields, and lakes, optimizing the spatial structure of its PLES dynamics, and formulating a reasonable spatial planning policy are effective means of guaranteeing its ecological and economic sustainable development. This study offers recommendations for and scientific defenses of the logical design of PLES spatial functions in the Mulan River Basin. Full article