Accurately quantifying individual tree parameters is a critical step for assessing carbon sequestration in forest ecosystems. However, it is challenging to gather comprehensive tree point cloud data when using either unmanned aerial vehicle light detection and ranging (UAV-LiDAR) or terrestrial laser scanning (TLS) alone. Moreover, there is still limited research on the effect of point cloud filtering algorithms on the extraction of individual tree parameters from multiplatform LiDAR data. Here, we employed a multifiltering algorithm to increase the accuracy of individual tree parameter (tree height and diameter at breast height (DBH)) extraction with the fusion of TLS and UAV-LiDAR (TLS-UAV-LiDAR) data. The results showed that compared to a single filtering algorithm (improved progressive triangulated irregular network densification, IPTD, or a cloth simulation filter, CSF), the multifiltering algorithm (IPTD + CSF) improves the accuracy of tree height extraction with TLS, UAV-LiDAR, and TLS-UAV-LiDAR data (with R2 improvements from 1% to 7%). IPTD + CSF also enhances the accuracy of DBH extraction with TLS and TLS-UAV-LiDAR. In comparison to single-platform LiDAR (TLS or UAV-LiDAR), TLS-UAV-LiDAR can compensate for the missing crown and stem information, enabling a more detailed depiction of the tree structure. The highest accuracy of individual tree parameter extraction was achieved using the multifiltering algorithm combined with TLS-UAV-LiDAR data. The multifiltering algorithm can facilitate the application of multiplatform LiDAR data and offers an accurate way to quantify individual tree parameters.

Spectral and texture features play important roles in plantation leaf area index (LAI) estimation, and their combination may enhance LAI inversion accuracy. Furthermore, research on the impact of different machine learning (ML) models on their hyperparameter combinations and splitting ratios remains challenging. In our study, experiments based on spectral and textural features of GF-6 WFV data were conducted on Eucalyptus grandis plantation forests in Huangmian Town, Guangxi, China. ML methods such as multiple stepwise regression (MSR), random forest (RF), back-propagation neural network (BPNN), and support vector regression (SVR) were mainly utilized to perform model hyper-parameter tuning and split-ratio analysis in order to estimate the LAI. The results of the study showed that spectral and gray level co-occurrence matrix (GLCM) texture features were very sensitive to changes in Eucalyptus grandis LAI. The accuracy of combining the two was 10% higher than when they were not combined. Furthermore, it was found that the nonlinear methods (RF, BPNN, and SVR) outperformed the linear method (MSR), with the average Rmax2 of the nonlinear model being 26% higher than that of the linear model, and the RMSE value being 29% lower than that of the linear model. In addition, by analyzing different combinations of features, model hyperparameter fine-tuning, and splitting ratios in the nonlinear model, it was found that the splitting ratios of different combinations of model hyperparameters have a great impact on the accuracy of the model. A total of 12 out of 21 data sets showed high accuracy and stability at a split ratio of 8.5:1.5 (ratio of 0.85), with the best-performing RF model differing from the lowest by 91% for Rmax2 and 39% for Rstd2. Combining spectral and texture features provides highly accurate inversion data. Model hyper-parameter fine-tuning and segmental scale tuning can facilitate the application of inversion data to fully utilize the optimal performance of the ML model.

The photosynthetic capacity is contingent upon the balance between nitrogen (N) and phosphorus (P) concentration, as well as environmental factors. Ensuring a balanced and timely supply of nitrogen and phosphorus facilitated healthy leaf growth and sustained efficient photosynthetic activity during trees active growth phases. However, the effects of the interactions between these factors on photosynthesis, particularly in the unique context of karst ecosystems, remain unclear. To address this, we conducted an assessment of photosynthetic parameters, including the 25 ℃ maximum carboxylation rate (V cmax,25 ) and the 25 ℃ maximum electron transport rate (J max,25 ), and chemical traits of leaves (leaf N, leaf P, and N:P ratio) in nine locally dominant species across both subtropical non-karst and karst areas in southwestern China. Our findings revealed that concentrations of leaf phosphorus and soil phosphorus were significantly higher in karst areas compared to non-karst areas. Additionally, the V cmax,25 of both karst and non-karst species were synergistically affected by leaf N and P concentrations, rather than being constrained by least available nutrient. Specifically, V cmax,25 of karst species was strongly related to leaf P, and increasing leaf N substantially increased the sensitivity of V cmax,25 to leaf P, highlighting the importance of maintaining a balance between N and P concentrations. These insights substantially enhance the understanding of photosynthetic dynamics and resource management in diverse ecosystems, providing a solid foundation for further research and conservation strategies.

The construction of ecological safety network system plays a critical role in ecological protection and restoration for people’s welfare and national security. In order to construct a better ecological security pattern, we took the Lijiang River basin with typical karst landforms as a research example, to extract ecological source sites with landscape ecological risk and connectivity indices, to identify and grade the potential ecological corridors and nodes with the minimum cumulative resistance and gravity models, and finally to construct the regional ecological security pattern in a coordinated way the conservation of Mountains-RiversForests-Farmlands-Lakes-Grasslands-Deserts ecosystem. The results showed that:（1） The ecological risk of the Lijiang River basin was characterized as high in the center and south, and low in the east and north. The high and higher risk areas accounted 43.34% of the total watershed area.（2） There were five ecological source areas, mainly located in forests and nature reserves, accounting for 28.99%（1689.05km2） of the total watershed area.（3） Six potential ecological corridors and 38 potential ecological nodes were identified, which were concentrated in the vicinity of Lingtian town.（4） The Lijiang River basin was constructed as a protective pattern of ecological conservation, restoration, control, and corridor construction. In addition, more ecological compensation funds and techniques should be supported to Lingchuan and Xingan counties in order to ensure the successful construction of the corridor.We hope this study could provide scientific knowledge for improving the ecosystem function of the Lijiang River basin and the successful implementation of national land use plan.

Ecosystem water-use efficiency (WUE) has been central in revealing the variability in terrestrial carbon and water cycles. Short-rotation plantations such as Eucalyptus plantations can simultaneously impact net primary production (NPP) and actual evapotranspiration (ETa), components of WUE, resulting in changes in terrestrial carbon and water cycles. However, there are few detailed studies on the changes in the WUE of Eucalyptus plantations at the catchment scale with high spatial remote sensing imagery. Here, we present the changes in the WUE of Eucalyptus plantations and its driving factors (i.e., NPP and ETa) using satellite-based models combined with 5-m spatial resolution RapidEye imagery in a small county in South China. The increases in ETa of Eucalyptus plantations are primarily the result of climate warming and result in low WUE of Eucalyptus plantations. The management practice used (short rotation in this study) can enhance the effect of climate warming on WUE by varying the NPP of Eucalyptus plantations. A high value of NPP leads to a high WUE of Eucalyptus plantations at the end of a short rotation, while a low value of NPP results in a low WUE at the beginning of another short rotation. Changes in the WUE of Eucalyptus plantations indicated large spatial and temporal variability, associated with climate warming and short-rotation practices.

Mogrosides III (1) and IIIE (2) are two important bioactive cucurbitane-type triterpenoid triglycosides in the edible fruits of Siraitia grosvenorii (Swingle), which are isomers and have only a minor difference in their structures. To clarify the effects of structural difference and drug-metabolizing-enzyme induction on their metabolism in vivo, their metabolites in normal rats and drug-metabolizing-enzyme-induced rats were tentatively identified and semiquantified by using the HPLC-DAD-ESI-IT-TOF-MSn technique. Totally, 76, 78, 96, and 121 metabolites of mogrosides were identified in the NIII (normal rats orally administered with mogroside III), NIIIE (normal rats orally administered with mogroside IIIE), EIII (drug-metabolizing-enzyme-induced rats orally administered with mogroside III), and EIIIE (drug-metabolizing-enzyme-induced rats orally administered with mogroside IIIE) groups, respectively. The metabolite differences among these groups indicated that their minor structural differences are responsible for the significant differences in their metabolites, and the induction of drug-metabolizing enzymes significantly increased the number of their metabolites. These findings would improve our understanding of the in vivo processes of mogrosides III and IIIE as well as their interactions with other food bioactive components or drugs.

Given the high degree of fragmentation and poor resistance to disturbance in karst landscapes, it is important to clarify the spatial and temporal dynamics of landscape patterns in karst areas when designing karst ecological protection strategies. Using the Li River Basin as the study area, the spatial distribution and dynamic evolution of landscape patterns in the basin were analyzed at the levels of landscape utilization, landscape type dynamics and landscape pattern indices based on the Landsat series images for 2000 to 2020 obtained from the GEE platform as the data source. The results show three important aspects of this typical karst watershed. (1) There are large differences in landscape structure and landscape type trends between the karst and non-karst areas in the Li River Basin. (2) The comprehensive landscape type dynamic attitude of the Li River Basin is 0.22%, and the composite index of landscape type use varies from 239.49 to 244.88. The degree of landscape use is higher in karst areas than in non-karst areas, and the rate of landscape change in karst areas is more intense. The integrated index of landscape use in karst areas ranges from 262.32 to 270.50, and in non-karst areas it spans 225.28 to 227.01. The integrated landscape type motility in the karst areas is 0.31%, which is about twice as high as that in non-karst areas. (3) The overall landscape evolution of the Li River Basin shows trends of increasing fragmentation, decreasing connectivity, decreasing dominance and increasing heterogeneity, and these trends are particularly prominent in the karst areas. The results of this study can provide a scientific basis for realizing the construction goals of the National Sustainable Development Innovation Demonstration Zone in Guilin, and a technical reference for the ecological environmental management of the karst watershed.

Rural agricultural activity generates cropland, secondary vegetation and straggling primary forest and can modify the soil seed bank (SSB), potentially impacting the restoration of preferred species. The interaction between vegetation and seed banks during the recovery process is dependent on management practices and recovery pathways. This study was carried out in Guilin of southwest China to assess the variation in plant diversity and species composition of both aboveground and soil seed banks across three typical vegetation types with different human interventions: orchard, bamboo shrub and primary forest. The results show that there were significant differences in the species composition and diversity of aboveground vegetation and SSB, as well as in soil properties among three typical vegetation types. The primary forest had the highest aboveground species diversity, while the orchard had the highest species diversity and seed density of SSB. In addition, principal component analysis (PCA) and canonical correspondence analyses (CCAs) showed that the species composition and plant life forms of the three typical vegetation types were significantly influenced by soil properties. Based on these findings, the characteristics of aboveground vegetation and the soil seed bank and their correlations with soil properties are expected to drastically change with human intervention. These results imply that unsustainable land use has greatly impacted soil properties, and consequently, the aboveground vegetation and SSB. Nevertheless, vegetation will recover quickly after farming is abandoned. The successful restoration of fragmented ecosystems requires the addition of seeds and seedlings of target species, especially perennial woody plants from the relevant natural ecosystems, to accelerate succession from bamboo shrub to forest.

Gas exchange capacity of leaves is mainly restricted by the content of N and P and environmental factors. However, the effects of interaction between N and P and environmental factors on photosynthetic capacity in subtropical tree species remain unclear. We measured the gas exchange parameters (25℃ maximum carboxylation rate [Vcmax,25], and 25℃ maximum electron transport rates [Jmax,25]) and the chemical properties of leaves (leaf N, leaf P and N:P) in 9 local dominant species in the subtropical non-karst and karst regions of southwest China. Environmental factors (temperature [Temp] and soil moisture content [SMC]) of the study site were also monitored at the same time. We found that P restriction is common in different research sites. The results of the mixed linear model show that with the increase of leaf N content of karst species, the sensitivity of Vcmax,25 to leaf P increased significantly, and there was a significant interaction of N×P (P < 0.001). Non-karst species tend to N×SMC interaction (P = 0.04). The difference in N×P interaction on gas exchange parameters between non-karst and karst species might result from the decoupling phenomenon of N and P caused by climate change. Factors such as N sedimentation and soil P loss aggravate the N:P imbalance and lead to the decoupling effect between N and P elements, and continuously weaken the influence of N×P interaction on plant Vcmax and Jmax.

[目的]分析液流密度径向差异及其对整树蒸腾量估算的影响,以期为中大径级桉树人工林蒸腾的准确估算和尺度扩展提供可靠依据.[方法]采用Granier热扩散探针法(TDP)测定了10年生中等径级尾巨桉(Eu-calyptus urophylla×Eucalyptus grandis)3个边材径向深度0～2、2～4、4～6 cm的液流密度.[结果]尾巨桉液流密度径向分布格局为递减型,日变化格局均为单峰型.用单点径向深度0～2、2～4、4～6 cm液流密度代表整个边材液流密度估算的整树日蒸腾量Tr2、Tr4和Tr6较基于多点估算值Tr246分别高估92.9％、低估28.2％和低估74.0％.由于0～2 cm边材深度液流密度对环境变化较为敏感,并且Tr2与Tr246之间的拟合精度较高(R2=0.964),因此,基于Tr2构建的整树日蒸腾量估算校正函数Tr246=0.522Tr2有效的提高了整树蒸腾估算的便捷性和准确度.[结论]中等径级尾巨桉液流密度具有明显的径向变化特征,不考虑这种径向变化将会导致整树蒸腾估算的较大误差.基于边材最外侧(0～2 cm)液流密度估算的整树蒸腾经过校正后可以方便准确地估算中等径级桉树人工林蒸腾耗水.

The ratio between nitrogen and phosphorus (N/P) in plant leaves has been widely used to assess the availability of nutrients. However, it is challenging to rapidly and accurately estimate the leaf N/P ratio, especially for mixed forest. In this study, we collected 301 samples from nine typical karst areas in Guangxi Province during the growing season of 2018 to 2020. We then utilized five models (partial least squares regression (PLSR), backpropagation neural network (BPNN), general regression neural network (GRNN), PLSR+BPNN, and PLSR+GRNN) to estimate the leaf N/P ratio of plants based on these samples. We also applied the fractional differentiation to extract additional information from the original spectra of each sample. The results showed that the average leaf N/P ratio of plants was 17.97. Plant growth was primarily limited by phosphorus in these karst areas. The sensitive spectra to estimate leaf N/P ratio had wavelengths ranging from 400–730 nm. The prediction capabilities of these five models can be ranked in descending order as PLSR+GRNN, PLSR+BPNN, PLSR, GRNN, and BPNN when considering both accuracy and robustness. The PLSR+GRNN model yielded high R2 and performance to deviation (RPD), and low root mean squared error (RMSE) with values of 0.91, 3.15, and 1.98, respectively, for the training test and 0.81, 2.25, and 2.46, respectively, for validation test. Compared with the PLSR model, both PLSR+BPNN and PLSR+GRNN models had higher accuracy and were more stable. Moreover, both PLSR+BPNN and PLSR+GRNN models overcame the issue of overfitting, which occurs when a single model is used to predict leaf N/P ratio. Therefore, both PLSR+BPNN and PLSR+GRNN models can be used to predict the leaf N/P ratio of plants in karst areas. Fractional differentiation is a promising spectral preprocessing technique that can improve the accuracy of models. We conclude that the leaf N/P ratio of mixed forest can be effectively estimated using combined models based on field spectroradiometer data in karst areas.

Leaf stoichiometry and its biogeography play vital roles in nutrient cycling of plant communities. To understand the potential drivers of leaf stoichiometry in karst ecosystems, we measured leaf morphological traits (dry mass content (DM), specific leaf area (SLA)), and biochemical traits (C, N, P, K and Ca stoichiometry) of 53 species of different functional groups, as well as soil properties, across seven karst sites in Southwest China, and explored the relationships between these leaf traits and environmental factors. The results showed that: (1) in karst areas of Southwest China, there were higher leaf C and Ca concentrations as well as higher N/P and K/P ratios compared to other ecosystems, plants were more limited by P rather than by N; (2) mean annual temperature positively influenced leaf N, P, and Ca, while mean annual precipitation exerted more influence on leaf K; (3) a strong phylogeny signal was detected in leaf N (p < 0.05), and significant influence of species composition on the variance of leaf N, K, and Ca was observed (p < 0.05); (4) the influence of soil properties on leaf P and Ca, and the influence of leaf features (SLA and DM) on leaf K were also observed based on a variance partitioning analysis. Abiotic factors such as soil, site, and climate were more important than biotic factors (leaf features and phylogeny) in determining leaf N, P, and Ca. In general, the driving factors exhibited a synergistic effect on leaf stoichiometry across different sites, offering a key mechanism that needs to be integrated into the modeling of biogeochemical nutrients cycling in karst ecosystems.

The regulation on transpiration and water status is critical for tree survival during drought. Eucalyptus is introduced and widely planted in southern China for timber production. Eucalyptus plantations are expanding into rugged terrains with shallow soils and soil water capacitance. With the ongoing decline in precipitation and the typical monsoon climate in this region, the trees suffer regular seasonal drought, yet their response mechanisms to drought remain obscure. We examined leaf water status, stomatal and hydraulic behavior, and wholetree transpiration of a wildly planted eucalyptus cultivar, Eucalyptus urophylla x Eucalyptus grandis, across seasons with different water availability in order to identify its response strategy to drought. During the study period, both predawn (psi(PD)) and midday (psi(MD)) leaf water potential varied considerably, but the water potential gradient between the mots and leaves (Delta psi(S-L)), measured as the difference between psi(PD) and psi(MD) remained constant, indicating an isohydrodynamic regulation on water status under drought. Despite strong stomatal down regulation on transpiration in response to increasing evaporative demand, leaf water potential declined to levels approaching -2 MPa at midday in the driest months, inducing more than 60% loss of xylem hydraulic conductance. Both stomatal and whole-tree hydraulic conductance linearly declined with increasing drought intensity. Whole-tree hydraulic conductance was exponentially correlated with the sensitivity of stomatal conductance to VPD. These results demonstrated that stomatal and hydraulic regulation on transpiration of eucalyptus was coupled through tight correlation between stomatal response to evaporative demand and whole-tree hydraulic conductance. This coordination between liquid and gas phase conductance found in this study was helpful to keep a balance between allowable maximum transpiration and hydraulic safety of eucalyptus under varying soil and atmosphere moisture conditions.

[目的]试验不同长度热消散探针(TDP)测量毛竹液流的可行性,分析年龄对立竹液流的影响,并据此对立竹液流进行尺度扩展,估算桂北毛竹林的蒸腾耗水,为区域毛竹林的生态水文效应研究和指导关键生态功能区植被结构调整提供依据.[方法]显微镜观察毛竹输水结构在竹壁上的径向分布.基于热消散方法,用5 mm和10 mm长度的TDP探针对1～2年生立竹和3龄以上立竹的基部液流进行连续测量,并同步测定环境因子.[结果]维管束在毛竹竹壁上不均匀分布,竹壁外侧维管束小而密,导管分化不完全,竹壁内侧维管束大而疏,导管分化完全,直径较大.10 mm TDP探针测得的液流密度显著高于5 mm探针,其平均液流密度是5 mm探针的4.03倍.在生长旺季的7月,基于10 mm TDP探针测量的1～2年生立竹正午液流密度显著高于3龄以上立竹,而在早上和傍晚二者基本相同.1～2年生立竹液流的平均日通量在测量生长季内均高于3龄以上立竹,二者的平均日液流通量分别为51.15和33.80 g·cm-2d-1.以立竹年龄和基径作为液流尺度扩展依据估测的桂北毛竹林日蒸腾耗水量在观测生长季内为0.01～0.72 mm·d-1,平均日蒸腾耗水量为0.31 mm·d-1.[结论]10 mm长度的TDP探针较5 mm探针更适宜用于毛竹液流的测量.1～2年生立竹比3龄以上立竹具有更高的液流密度和日液流通量,因此年龄是毛竹液流由立竹到林分尺度扩展时除立竹直径外另一个必须要考虑的因素.

We investigated the seasonal water use patterns of five canopy tree species, Schima superba, Liquidambar formosana Hance, Quercus griffithii Hook, Quercus acutissima Carruth, and Pinus massoniana, in a subtropical secondary forest in Guangxi province, which were pervasively planted in South China. The hypothesis is that the trees can make different temporal use of environmental resources that change seasonally and consequently contribute to their coexistence. Sap flow technique was used to measure the daily and seasonal transpiration during the period from June 2016 to May 2017. The sap flow—derived daily transpiration (EL), leaf water potential (ΔΨ), hydraulic conductance (K), as well as the responses of EL to driving factor—water vapour pressure deficit (VPD) was determined in dry and wet seasons. Measured data of stem sap flow showed that L. formosana, Q. griffithii, and P. massoniana transpired more water than S. superba and Q. acutissima during the whole monitoring period, whereas daily EL of P. massoniana rapidly decreased under dry season. We attributed the different water use patterns to the significant difference in ΔΨ, K, and wood density among the five species. Moreover, linear relationships between the daily transpiration and VPD might suggest diverse water use strategies. For the species of S. superba, Q. acutissima, and P. massoniana, less water consumption and relatively flat change of transpiration with VPD were observed, suggesting a relatively tighter stomatal control. The slope values for L. formosana and Q. griffithii, which were much higher even under dry season, might own a weak stomatal control. These different functional and hydraulic traits, together with the associated water use strategies, might facilitate the coexistence of these five canopy tree species, which would assist in predicting the impact of future environmental changes on plant biodiversity and ecosystem services in the investigated region.

Forest transpiration is coupled with environmental variables and has a profound effect on regional water cycle and water balance. Understanding how the biotic and abiotic environments influence transpiration is vital in understanding forest water use strategies, and for evaluating forest feedback to climate change. Moso bamboo (Phyllostachys edulis), a woody bamboo species, is rapidly spreading in the southern parts of China and must have a significant influence on ecosystem processes here. This study examined cuhn sap flow in P. edulis in southern China to identify key factors that determine its transpiration at individual and stand scale. Sap flux density was higher in the 1-2 years old ramets than those > 3 years old, during the entire growing season. Daily accumulated sap flux density and its sensitivity to the physical environment (air vapor pressure deficit-VPD and solar radiation) during the non-shooting period were approximately 2 and 3 times higher than during the shooting-leafing period for 1-2 and > 3 years old culms, respectively. During the non-shooting period, daily maximum and accumulated sap flux density of the 1-2 years old ramets had no correlation with soil water content, while that of > 3 years old ramets declined linearly with decreasing soil water content (SWC). Stand transpiration remained low, and was not affected by changes in SWC during the shooting-leafing period, while that of nonshooting period was linearly correlated with SWC. The results showed that transpiration of Moso bamboo was interactively influenced by culm age, phenological stages and soil drought. We demonstrate the role of ramet age and phenology on bamboo stand transpiration and how it responds to soil drought. Our study reveals the special water use strategies in Moso bamboo forests.

To investigate the effect of reclamation on soil quality in the Huixian Karst Wetland, samples from different soil levels were collected from marsh wetland, reclaimed paddy field, and reclaimed dry farmland, for analyzing soil nutrient (carbon, nitrogen, phosphorous, and potassium) contents, microbial biomass carbon/nitrogen (MBC/MBN), and microbial activity indicators[i.e. basal respiration (BR), potential respiration (PR), microbial quotient (qMB), and metabolic quotient (qCO2)]. The correlations between the soil nutrient contents and soil microbial activity indictors were examined. The results showed that:①Artificial reclamation led to the trend of slight acidity in the soil and a marked loss in soil nutrients, while, the pH value, soil water content (SWC), and the contents of soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), available phosphorus (AP), total potassium (TK), and available potassium (AK) decreased with reclamation. ②Among all the microbes, bacteria were the most numerous, followed by actinomycetes, and fungi were the least numerous. The microbial quantity decreased with the increase in the soil depth on the whole. The proportion of bacteria and actinomycetes were much higher in the paddy field, and that of fungi was the highest in the dry farmland. ③ In total, protease, sucrase, urease, catalase, and polyphenol oxidase activities decreased with the increasing of soil depths. Soil reclamation reduced the soil enzyme activities. ④qCO2 decreased after an initial increase in the marsh wetland, while it rose gradually in the reclaimed paddy field and reclaimed dry farmland. The contents of MBC, MBN, BR, PR, and qMB were the highest in the marsh wetland, followed by those in the reclaimed paddy field, with the lowest contents occurring in the reclaimed dry farmland. The trend of qCO2 contents in the 0-10 cm and 10-20 cm soil layers followed the order of marsh wetland > paddy field > dry farmland, but in the 20-30 cm and 30-40 cm soil layers, it showed the order dry farmland > paddy field > marsh wetland. The continuation of reclamation resulted in the decrease in soil microbial activity, and soil quality as well, especially in the dry farmland. Meanwhile, we should reduce the areas of paddy fields and dry farmlands under reclamation during the process of wetland ecological restoration in future. Conversion of farmlands to wetlands or lakes, to improve and increase the size of wetland ecosystems of nearby lands, should be done gradually.