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Recurring use of chemical fertilizers (CFs) in agriculture has resulted the remarkable improvement in crop productivity but their ruinous effects on environment have made a serious issue. Biological entities (e.g., several microorganisms) showing fertilizer‐like activities have gained attention in this regard. Several soil resident microorganisms interact strongly with neighboring plants and promote the growth and development of those plants through various means. In exchange of this, microbes utilize different compounds released from plant roots for their own nutrition. This mutualistic mode of interrelation predominantly relies on the transmission of signals from microbes to plants and vice versa. However, climatic factors (e.g., CO2 level, temperature, and water availability) are also important for this association. These bacterial strains are literally known as plant growth promoting rhizobacteria (PGPR) which facilitate plant growth through nitrogen fixation, mineral solubilization, phytostimulation, stress resistance, etc. Responding to the external environmental stimuli, they often modulate the expression of genes responsible for the transport of nutrients. Reduction of the use of CFs through the application of PGPR strains in the cultivation of some economically important plants has been reported by several authors. Significant yield improvement compared to the control groups was found in all experimental studies. Commercial development of the PGPR inoculants with remarkable biostimulating activities and their successive application should be expanded through collaborative association with different sectors after the removal of existing lacunae. Reading more than 100 articles on various aspects of rhizobacteria, the plan of writing this article has been executed. In this review, we have discussed about the colonization and potency of PGPR strains and how their well‐planned application in agriculture could evidently reinforce the global economy. The main structure of this text is designed as an outline from the development of interrelation between plants and PGPR to the commercialization of PGPR based on their potential role in the field of agriculture. [ABSTRACT FROM AUTHOR]

Summary In theory, there is a trade‐off between hydraulic efficiency and safety. However, the strength and direction of this trade‐off at the leaf level are not consistent across studies, and habitat climate may impact this trade‐off. We compiled a leaf hydraulic efficiency and safety dataset for 362 species from 81 sites world‐wide, with 280 paired observations of both traits, and tested whether climate was associated with departure from the proposed trade‐off. The leaf hydraulic efficiency–safety trade‐off was weak (R2 = 0.144) at the global scale. Mean annual precipitation and solar radiation (SR) modified the trade‐off. Species from dry and high SR habitats (e.g. desert and tropical savanna) were generally located above the trade‐off line, indicating that these species tended to have higher leaf hydraulic safety and efficiency than species from wet habitats with low SR (e.g. subtropical monsoon forest and montane rainforest), which were located below the trade‐off line. Leaves with high vein density, dry leaf mass per area, and osmotic regulation enhanced safety without compromising hydraulic efficiency. Variation in the hydraulic efficiency–safety trade‐off at the leaf level likely facilitates plant survival in specific habitats and allows for a more nuanced view of leaf hydraulic adaption strategies at the global scale. [ABSTRACT FROM AUTHOR]

The coupled processes of ecosystem carbon and water cycles are usually evaluated using the water use efficiency (WUE), and improving WUE is crucial for maintaining the sustainability of ecosystems. However, it remains unclear whether the WUE in different ecosystem responds synchronously to the synergistic effect of the same climate factors at daily and monthly scales. Therefore, we employed a machine learning-driven factor analysis method and a geographic detector model, and we quantitatively evaluated the individual effects and the synergistic effect of climate factors on the daily mean water use efficiency (WUED) and monthly mean water use efficiency (WUEM) in different ecosystems in China. Our results showed that (1) among the 10 carbon flux monitoring sites in China, WUED and WUEM exhibited the highest positive correlations with the near-surface air humidity and the highest negative correlation with solar radiation. The correlation between WUEM and climate factors was generally greater than that between WUED and climate factors. (2) There were significant differences in the order of importance and degree of impact of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the near-surface air humidity imposed the greatest influence on the WUED and WUEM changes, followed by the near-surface water vapor pressure. (3) There were significant differences in the synergistic effects of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the WUED variability was most sensitive to the synergistic effect of solar radiation and photosynthetically active radiation, while the WUEM variability was most sensitive to the synergistic effect of the near-surface air humidity and soil moisture. The research results indicated that synchronous responses of the WUE in very few ecosystems to the same climate factors and their synergistic effect occurred at daily and monthly scales. This finding enhances the understanding of sustainable water resource use and the impact of climate change on water use efficiency, providing crucial insights for improving climate-adaptive ecosystem management and sustainable water resource utilization across different ecosystems. [ABSTRACT FROM AUTHOR]

Energy generation and economic development are closely linked, with energy playing a pivotal role in wealth creation. However, the finite nature of fossil fuel resources and associated environmental challenges has emphasized the need for sustainable energy alternatives based on renewable sources. Among these alternatives, photovoltaic (PV) systems hold significant potential for fostering a sustainable energy system. Despite ongoing material research, achieving a major breakthrough in enhancing the conversion efficiency of commercial PV modules remains a challenge. To optimize PV system yield, installation must consider geographic location and design factors. PV modules often yield different results compared to manufacturer specifications due to factors such as high temperatures, dust, and arid to semiarid climates. Therefore, it is crucial to conduct outdoor testing and characterization of PV modules tailored to specific locations, such as Jordan, to maximize system performance. This research aims to examine the impact of ambient temperature, dust accumulation, and solar irradiance intensity on PV system performance in Jordan, providing valuable insights through monitoring power output variations. The findings will contribute to improving PV system efficiency in Jordan's unique climate and aid manufacturers in developing innovative PV applications. The collected data includes solar radiation, temperature, voltage, current, and output power. The results confirm that the Azraq site is a better location when compared to Mafraq based on the possibility of generated more output power using a PV system. [ABSTRACT FROM AUTHOR]

Plant aboveground biomass reflects the resilience of ecosystem productivity to different environmental factors and plays an important role in biodiversity and ecosystem carbon cycles. Although many studies have investigated the relationship between aboveground biomass and species diversity, stand structural diversity is an important factor affecting ecosystem function. The mechanism of how climate and soil factors affect aboveground biomass through species diversity and structural diversity remains unclear. Here, combing data from 8 locations of Abies fargesii var. faxoniana primary forest, a structural equation model was used to study the effects of climate factors, soil factors, species diversity, and structural diversity on aboveground biomass. Our results demonstrated that climate factors affect aboveground biomass mainly through the indirect effect of species diversity. Species diversity indirectly affects aboveground biomass through its effects on structural diversity. Both direct effects of soil factors and indirect effects through structural diversity can significantly affect aboveground biomass. Therefore, maintaining higher diversity of stand structure and soil nutrients can improve aboveground biomass, and thus better improve ecosystem functions such as carbon storage. [ABSTRACT FROM AUTHOR]

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As a vital indicator for measuring the coupled carbon–water cycle of an ecosystem, water use efficiency (WUE) can also reflect the adaptive capacity of plants in different ecosystems. Located in Southwest China, the Li River Basin has a representative karst landform, and the uneven rainfall in the region leads to severe water shortage. In this study, we analyzed the spatial–temporal transformation characteristics of the WUE of the basin and its relationship with different influencing factors from 2001 to 2020 based on a correlation analysis and trend analysis. The main conclusions are as follows: (1) The average value of WUE in the Li River Basin was 1.8251 gC· mm−1·m−2, and it kept decreasing at a rate of 0.0072 gC· mm−1·m−2·a−1 in the past 20 years. With respect to the spatial distribution of the multi-year average of WUE, it exhibits a gradual increasing trend from west to east. (2) Between gross primary productivity (GPP) and evapotranspiration (ET), it was found that ET was the primary influencing factor of WUE. Precipitation was positively correlated with WUE in the Li River Basin, accounting for 67.22% of the total area of the basin. The air temperature was negatively correlated with WUE, and the area was negatively correlated with WUE, accounting for 92.67% of the basin area. (3) The normalized difference vegetation index (NDVI) and leaf area index (LAI) were negatively correlated with WUE, and the proportions of negatively correlated areas to the total area of the basin were similar; both were between 60 and 70%. The growth of vegetation inhibited the increase in WUE in the basin to a certain extent. Regarding Vapor Pressure Deficit (VPD), the proportions of positive and negative correlation areas with WUE were similar, accounting for 49.58% and 50.42%, respectively. (4) The occurrence of drought events and the enhancement in its degree led to a continuous increase in WUE in the basin; for different land cover types, the correlation of the standardized precipitation evapotranspiration index (SPEI) was in the following order from strongest to weakest: grassland > cropland > forest > shrubland. [ABSTRACT FROM AUTHOR]

Specimen data play a crucial role in geographical distribution research. In this study, the collection information of liverwort specimens in China was compiled and analyzed to investigate the history, current status, and limitations of liverwort research in China. By utilizing the latest systematic research findings and corresponding environmental data, a niche model was developed to offer theoretical support for exploring the potential geographical distribution and diversity of liverwort resources. A total of 55,427 liverwort specimens were collected in China, resulting in the recording of 1212 species belonging to 169 genera and 63 families. However, there are imbalances in the distributions of liverwort data among different groups, collection units, and geographical areas, with families such as Lejeuneaceae, Porellaceae, and Plagiochilaceae having the highest number of specimens. Similarly, genera such as Porella, Frullania, and Horikawaella were well represented. Remarkably, 125 species had specimen counts exceeding 100. Unfortunately, approximately 51.77% of the species had fewer than 10 recorded specimens. There were four obvious peaks in the collection years of the bryophyte specimens in China, among which the largest collection occurred from 2010 to 2023. Notably, the number of specimens collected at different stages closely aligned with the history of taxonomic research on liverworts in China. The results of the integrity of the liverwort collection indicate that there is insufficient representation of some families and genera, with a concentration of common and widely distributed large families and genera. Tropical and subtropical humid areas are key regions for liverwort diversity, with water and temperature being the primary environmental factors influencing their geographical distribution. The specific temporal and spatial data of species recorded from plant specimens will enhance the study of species diversity, comprehensive protection, and sustainable utilization. Additionally, these data will contribute to the investigation of large-scale biodiversity distribution patterns and the impact of global change on diversity. [ABSTRACT FROM AUTHOR]

Background: Malaria remains an important public health problem, particularly in sub-Saharan Africa. In Rwanda, where malaria ranks among the leading causes of mortality and morbidity, disease transmission is influenced by climatic factors. However, there is a paucity of studies investigating the link between climate change and malaria dynamics, which hinders the development of effective national malaria response strategies. Addressing this critical gap, this study analyses how climatic factors influence malaria transmission across Rwanda, thereby informing tailored interventions and enhancing disease management frameworks. Methods: The study analysed the potential impact of temperature and cumulative rainfall on malaria incidence in Rwanda from 2012 to 2021 using meteorological data from the Rwanda Meteorological Agency and malaria case records from the Rwanda Health Management and Information System. The analysis was performed in two stages. First, district-specific generalized linear models with a quasi-Poisson distribution were applied, which were enhanced by distributed lag non-linear models to explore non-linear and lagged effects. Second, random effects multivariate meta-analysis was employed to pool the estimates and to refine them through best linear unbiased predictions. Results: A 1-month lag with specific temperature and rainfall thresholds influenced malaria incidence across Rwanda. Average temperature of 18.5 °C was associated with higher malaria risk, while temperature above 23.9 °C reduced the risk. Rainfall demonstrated a dual effect on malaria risk: conditions of low (below 73 mm per month) and high (above 223 mm per month) precipitation correlated with lower risk, while moderate rainfall (87 to 223 mm per month) correlated with higher risk. Seasonal patterns showed increased malaria risk during the major rainy season, while the short dry season presented lower risk. Conclusion: The study underscores the influence of temperature and rainfall on malaria transmission in Rwanda and calls for tailored interventions that are specific to location and season. The findings are crucial for informing policy that enhance preparedness and contribute to malaria elimination efforts. Future research should explore additional ecological and socioeconomic factors and their differential contribution to malaria transmission. [ABSTRACT FROM AUTHOR]

As a key component of the ecosystem, soil seed banks (SSBs) play a vital role in the evolution and renewal of plant communities. Although the pattern and mechanisms of influence of SSBs along the altitudinal gradient have been reported, most studies have focused on forest, grassland and alpine meadow ecosystems. The pattern and factors of SSBs across the altitudinal gradient in sedge peatlands remain largely unknown. Through vegetation surveys and seed germination experiments, we studied the changes in aboveground vegetation and SSBs in sedge peatlands at altitudes ranging from 300 m to 1300 m in the Changbai Mountains, China, and discussed the direct and indirect effects of climatic factors, soil properties and aboveground vegetation on SSBs. The results showed that the richness and density of the SSBs of sedge peatlands decreased with the altitude. Similarly, aboveground vegetation richness and density declined with altitude. A Spearman correlation analysis showed that SSB richness and density were mainly correlated with mean annual temperature, soil total phosphorus and ammonia nitrogen and the plant composition and richness of aboveground vegetation. A structural equation model analysis showed that climatic factors and aboveground vegetation directly affected seed bank richness, while soil properties indirectly affected it by directly affecting aboveground vegetation. Climatic factors, soil properties and aboveground vegetation directly affected SSB density, and soil properties indirectly affected it by directly affecting aboveground vegetation. This finding enhances our understanding of the altitude patterns of the SSBs in sedge peatlands and the response to future climate and environmental changes. [ABSTRACT FROM AUTHOR]

Stingless bees are essential for the pollination of cultivated and native plant species. Anthropogenic activities in natural ecosystems trigger changes in the microclimate, impacting the flight activity of bees. Here, we examine the effects of some abiotic factors on the flight activity of some stingless bees. We installed four colonies of each species (Plebeia droryana, Scaptotrigona bipunctata and Melipona quadrisfasciata) in three distinct areas (predominantly urbanized area, mosaic of pastures with agricultural cultivation and mosaic of natural vegetation with fragmented landscapes) represented by different uses and land cover (L.U.L.C.). All observations were in the morning during three time slots. For each area, we recorded daily abiotic factors and measured the flight activity of bees entering and leaving the colony. P. droryana and S. bipunctata had similar flight activities, with less activity in anthropized areas. M. quadrifasciata showed the lowest activity among species in the three areas. The flight activity of S. bipunctata showed significant differences. Abiotic factors had significant differences between areas, light intensity had the greatest influence on flight activity among the three species. Our study indicates that stingless bees exhibit a pattern of behavior. However, the abiotic characteristics of a given ecosystem can affect the flight activity of each species based on its normative behavior. This is the first study to evaluate abiotic effects on the flight activity of P. droryana, S. bipunctata and M. quadrifasciata in southern Brazil. The results obtained here can contribute to the establishment of a conservation plan for stingless bee species and prevent future extinctions in a scenario of environmental changes. [ABSTRACT FROM AUTHOR]

The chickpea plays a significant role in global agriculture and occupies an increasing share in the human diet. The main aim of the research was to develop a model for the prediction of two chickpea productivity traits in the available dataset. Genomic data for accessions were encoded in Artificial Image Objects, and a model for the thousand-seed weight (TSW) and number of seeds per plant (SNpP) prediction was constructed using a Convolutional Neural Network, dictionary learning and sparse coding for feature extraction, and extreme gradient boosting for regression. The model was capable of predicting both traits with an acceptable accuracy of 84–85%. The most important factors for model solution were identified using the dense regression attention maps method. The SNPs important for the SNpP and TSW traits were found in 34 and 49 genes, respectively. Genomic prediction with a constructed model can help breeding programs harness genotypic and phenotypic diversity to more effectively produce varieties with a desired phenotype. [ABSTRACT FROM AUTHOR]

Abstract Background Malaria remains an important public health problem, particularly in sub-Saharan Africa. In Rwanda, where malaria ranks among the leading causes of mortality and morbidity, disease transmission is influenced by climatic factors. However, there is a paucity of studies investigating the link between climate change and malaria dynamics, which hinders the development of effective national malaria response strategies. Addressing this critical gap, this study analyses how climatic factors influence malaria transmission across Rwanda, thereby informing tailored interventions and enhancing disease management frameworks. Methods The study analysed the potential impact of temperature and cumulative rainfall on malaria incidence in Rwanda from 2012 to 2021 using meteorological data from the Rwanda Meteorological Agency and malaria case records from the Rwanda Health Management and Information System. The analysis was performed in two stages. First, district-specific generalized linear models with a quasi-Poisson distribution were applied, which were enhanced by distributed lag non-linear models to explore non-linear and lagged effects. Second, random effects multivariate meta-analysis was employed to pool the estimates and to refine them through best linear unbiased predictions. Results A 1-month lag with specific temperature and rainfall thresholds influenced malaria incidence across Rwanda. Average temperature of 18.5 °C was associated with higher malaria risk, while temperature above 23.9 °C reduced the risk. Rainfall demonstrated a dual effect on malaria risk: conditions of low (below 73 mm per month) and high (above 223 mm per month) precipitation correlated with lower risk, while moderate rainfall (87 to 223 mm per month) correlated with higher risk. Seasonal patterns showed increased malaria risk during the major rainy season, while the short dry season presented lower risk. Conclusion The study underscores the influence of temperature and rainfall on malaria transmission in Rwanda and calls for tailored interventions that are specific to location and season. The findings are crucial for informing policy that enhance preparedness and contribute to malaria elimination efforts. Future research should explore additional ecological and socioeconomic factors and their differential contribution to malaria transmission.

Specific leaf area (SLA) and leaf dry matter content (LDMC) are key leaf functional traits often used to reflect plant resource utilization strategies and predict plant responses to environmental changes. In general, grassland plants at different elevations exhibit varying survival strategies. However, it remains unclear how grassland plants adapt to changes in elevation and their driving factors. To address this issue, we utilized SLA and LDMC data of grassland plants from 223 study sites at different elevations in China, along with climate and soil data, to investigate variations in resource utilization strategies of grassland plants along different elevational gradients and their dominant influencing factors employing linear mixed-effects models, variance partitioning method, piecewise Structural Equation Modeling, etc. The results show that with increasing elevation, SLA significantly decreases, and LDMC significantly increases (P < 0.001). This indicates different resource utilization strategies of grassland plants across elevation gradients, transitioning from a "faster investment-return" at lower elevations to a "slower investment-return" at higher elevations. Across different elevation gradients, climatic factors are the main factors affecting grassland plant resource utilization strategies, with soil nutrient factors also playing a nonnegligible coordinating role. Among these, mean annual precipitation and hottest month mean temperature are key climatic factors influencing SLA of grassland plants, explaining 28.94% and 23.88% of SLA variation, respectively. The key factors affecting LDMC of grassland plants are mainly hottest month mean temperature and soil phosphorus content, with relative importance of 24.24% and 20.27%, respectively. Additionally, the direct effect of elevation on grassland plant resource utilization strategies is greater than its indirect effect (through influencing climatic and soil nutrient factors). These findings emphasize the substantive impact of elevation on grassland plant resource utilization strategies and have important ecological value for grassland management and protection under global change. [ABSTRACT FROM AUTHOR]

Rubber plantations are an important component of tropical forest ecosystems and are emerging as crucial contributors to carbon sequestration in the tropics. However, ecosystem respiration (RECO), which constitutes an essential constraint on the carbon fixation capacity of rubber plantations, and its driving mechanisms remains unclear. Therefore, this study developed a data-driven semi-empirical model to simulate rubber plantations RECO utilising eddy covariance flux measurements and was upscaled to Hainan Island using remote sensing images and climatic data. Numerical simulations experiments analysed direct and indirect of climatic factors impacts on rubber plantations RECO. The results showed that the model accurately captured RECO trends and seasonality (R2 = 0.87, RMSE = 1.27 g C m−2 d−1); in the past 19 years, RECO showed a noticeable increase, particularly in the late rainy season and the seasonality of RECO has shown a delayed pattern. The RECO in the central region (52% area) exhibited multimodal enhancement while northern and southern regions (37% area) showed oscillations or decreases. Temporally, RECO is higher in the rainy season compared to the dry season, and spatially, RECO is higher in the southern region than in the northern region. Among the climatic factors, water conditions (rainfall and air humidity) have been emerged as dominant factors (5.38%) influencing RECO, surpassing temperature (3.96%) and radiation (3.81%). In addition, climatic factors make a positive overall contribution during the dry season but perform oppositely in the rainy season. This study offers theoretical and technical insights into high carbon sink management in rubber plantations and carbon sequestration in tropical forests ecosystems. [ABSTRACT FROM AUTHOR]

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne virus recognized by the World Health Organization as an emerging infectious disease of growing concern. Utilizing phylodynamic and phylogeographic methods, we have reconstructed the origin and transmission patterns of SFTSV lineages and the roles demographic, ecological, and climatic factors have played in shaping its emergence and spread throughout Asia. Environmental changes and fluctuations in tick populations, exacerbated by the widespread use of pesticides, have contributed significantly to its geographic expansion. The increased adaptability of Lineage L2 strains to the Haemaphysalis longicornis vector has facilitated the dispersal of SFTSV through Southeast Asia. Increased surveillance and proactive measures are needed to prevent further spread to Australia, Indonesia, and North America. [ABSTRACT FROM AUTHOR]

Introduction: As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the southeastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in longterm historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. Methods: This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Results and discussion: Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation. [ABSTRACT FROM AUTHOR]

In order to investigate the impact of climatic factors on the quality of Siraitia grosvenorii fruits pollinated in different seasons and the underlying molecular mechanism involved, the differences in climate factors, quality traits, and gene expression between fruits of the main cultivar S. grosvenorii “Qingpiguo” pollinated in summer and autumn were statistically analyzed by monitoring climate factors at different developmental stages, measuring morphological changes, detecting mogroside metabolism, and analyzing gene expression using qRT-PCR. The results were as follows: (1)Compared to summer-pollinated fruits, the average temperature and effective accumulated temperature of autumn-pollinated fruits decreased significantly after 35 d. Additionally, the temperature difference between day and night increased significantly before 65 d. However, this difference was still less than that of the average temperature and effective accumulated temperature. The light intensity and air humidity remained similar. (2)The transverse diameters, longitudinal diameters, and single fruit weights of autumn-pollinated fruits increased compared to those of summer-pollinated fruits, however, these differences were not statistically significant. (3)Mogroside V and 11-O-mogroside V in autumn-pollinated fruits accumulated slowly from 55 d with a delay of about 10 d, moreover, the content of both compounds in ripe fruits decreased by 40.66% and 46.07%, respectively. (4)In autumn, the number and extent of up-regulated mogroside V synthetase genes were relatively lower, and their co-expression consistency was poorer than in summer. Furthermore, the glucosyltransferase gene SgUGT94-289-3 which was responsible for the final step in mogroside V biosynthesis, exhibited down-regulation at all time points of 55 d. In summary, the shape and size of S. grosvenorii fruits pollinated in different seasons were not significantly affected by climatic factors; however, the content of mogroside V was significantly influenced by the temperature, which potentially influences these variations in mogroside V by regulating both the co-expression consistency and expression level of mogroside V synthetase genes. The results of this study provide the theoretical reference for high-quality cultivation and genetic breeding of S. grosvenorii. [ABSTRACT FROM AUTHOR]

The stand basal area, closely related to age, site quality, and stand density, is an important factor for predicting forest growth and yield. The accurate estimation of site quality is especially a key component in the stand basal area model. We utilized sample plots with Picea asperata Mast. as the dominant species in the multi-period National Forest Inventory (NFI) dataset to establish a site index (SI) model including climate effects through the difference form of theoretical growth equations and mixed-effects models. We combined the SI calculated from the SI model, stand age, and stand density index to construct a basal area growth model for Picea asperata Mast. stands. The results show that the Korf model is the best SI base model for Picea asperata Mast. The mean temperatures in summer and winter precipitation were used as the fixed parameters to construct a nonlinear model. Ultimately, elevation, origin, and region, as random effects, were incorporated into the mixed-effects model. The coefficients (R2) of determination of the base model, the nonlinear model including climate, and the nonlinear mixed-effects model are 0.869, 0.899, and 0.921, with root-mean-square errors (RMSEs) of 1.320, 1.315, and 1.301, respectively. Among the basal area models, the Richards model has higher precision. And the basal area model including an SI incorporating climatic factors had a higher determination coefficient (R2) of 0.918 than that of the model including an SI without considering climatic effects. The mixed-effects model incorporating climatic and topographic factors shows a better fitting performance of SI, resulting in a higher precision of the basal area model. This indicates that in the development of forest growth models, both biophysical and climatic factors should be comprehensively considered. [ABSTRACT FROM AUTHOR]

In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0-5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture. [ABSTRACT FROM AUTHOR]

In order to understand the effect of shading on the growth and physiological respond of Menyanthes trifoliata L.and to provide suitable habitat in Beijing area for its protection and utilization. Growth and physiological index of M.trifoliata during different periods were studied under four shading treatments, including full sunlight, 50% shading, 75% shading and 90% shading. The microclimatic factors were also monitored under same conditions. The results showed that height growth, rhizome growh and leaf area growth of M.trifoliata under 50%-90% shading treatment for 60 days during summer were significantly higher than those in full sunlight; SPAD and Fv/Fm of M.trifoliata were effectively increased under 50% shading, compared with CK; moderate shading could effectively reduce light intensity, daily maximum temperatures and increase air humidity. In conclusion, 50% shading of M.trifoliata for 60-90 days in summer is the most favorable cultivation method. [ABSTRACT FROM AUTHOR]

Background/Objectives: Recent studies provide the first indications of the impact of climate factors on human health, especially with individuals already grappling with internal and neurological conditions being particularly vulnerable. In the face of escalating climate change, our research delves into the specific influence of a spectrum of climatic factors and seasonal variations on the hospital admissions of patients receiving treatment for epileptic seizures at our clinic in Kaiserslautern. Methods: Our study encompassed data from 9366 epilepsy patients who were admitted to hospital due to epileptic seizures. We considered seven climate parameters that Germany's National Meteorological Service made available. We employed the Kruskal–Wallis test to examine the correlation between the frequency of admittance to our hospital in the mentioned patient group and seasons. Furthermore, we used conditional Poisson regression and distributed lag linear models (DLMs) to scrutinize the coherence of the frequency of patient admittance and the investigated climate parameters. The mentioned parameters were also analyzed in a subgroup analysis regarding the gender and age of patients and the classification of seizures according to ILAE 2017. Results: Our results demonstrate that climatic factors, such as precipitation and air pressure, can increase the frequency of hospital admissions for seizures in patients with general-onset epilepsy. In contrast, patients with focal seizures are less prone to climatic changes. Consequently, admittance to the hospital for seizures is less affected by climatic factors in the latter patient group. Conclusions: The present study demonstrated that climatic factors are possible trigger factors for the provocation of seizures, particularly in patients with generalized seizures. This was determined indirectly by analyzing the frequency of seizure-related emergency admissions and their relation to prevailing climate factors. Our study is consistent with other studies showing that climate factors, such as cerebral infarcts or cerebral hemorrhages, influence patients' health. [ABSTRACT FROM AUTHOR]

Soil fungi play a critical role in the biogeochemical cycles of forest ecosystems. Larix gmelinii is a strong and important timber tree species, which forms close associations with a wide range of soil fungi. However, the temporal-spatial disparity effects on the assembly of soil fungal communities in L. gmelinii forests are poorly understood. To address these questions, a total of 120 samples, including 60 bulk soil and 60 root samples, were collected from Aershan and Genhe in July (summer) and October (autumn)2021. We obtained 7,788 operational taxonomic units (OTUs) after merging, filtering, and rarefying using high-throughput sequencing. The dominant phyla are Basidiomycota, Ascomycota, Mortierellomycota, and Mucoromycota. There were 13 dominant families, among which the families with average relative abundance more than 5% included Thelephoraceae, Mortierellaceae, Archaeorhizomycoaceae, and Inocybaceae. In the functional guilds, symbiotrophic fungi had a relative advantage in the identified functions, and the relative abundances of pathotrophic and saprotrophic fungi varied significantly between sites. There were 12 families differentially expressed across compartments, 10 families differentially expressed between seasons, and 69 families were differentially expressed between sites. The variation in alpha diversity in the bulk soil was greater than that in the rhizosphere soil. Among the three parts (compartment, season, and site), the site had a crucial effect on the beta diversity of the fungal community. Deterministic processes dominated fungal community assembly in Genhe, whereas stochastic processes dominated in Aershan. Soil physicochemical properties and climatic factors significantly affected fungal community structure, among which soil total nitrogen and pH had the greatest effect. This study highlights that spatial variations play a vital role in the structure and assembly of soil fungal communities in L. gmelinii forests, which is of great significance for us in maintaining the health of the forests. [ABSTRACT FROM AUTHOR]

Evaluation of the net ecosystem exchange (NEE) of agroecosystems may help to assess regional carbon cycles and ensure carbon neutrality. However, farmland NEE is influenced by climate change, phenological period, and crop management. Therefore, in this study, we investigated the time-lag effects of climate change on the phenology and NEE of winter wheat, as well as the influence of crop management. We found that the impact of climate change on the phenology of winter wheat exhibits a time lag of 1 to 2 months, with notable spatial and temporal heterogeneity. When accounting for time-lag effects, the correlation between climate change and both phenology and NEE significantly strengthens, with the lagged impact on NEE primarily mediated through changes in phenology. Specifically, climate change accelerates the green-up and heading dates but delays the maturity date, while crop management extends the phenological period. Our findings indicated that during the green-up stage, NEE is mainly influenced by temperature changes resulting from climate change. During the heading stage, it is predominantly affected by crop management, and during the maturity stage, it is impacted by both factors, with crop management having a more significant effect. Overall, the accelerated green-up stage and delayed heading and maturity stages contribute to enhanced carbon sequestration. This research provides new insights into carbon exchanges in agricultural ecosystems. [ABSTRACT FROM AUTHOR]

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded annually were below the previous year. In the literature, it is possible to find studies focused on the spread of dengue only for some specific regions of Mexico. However, given the increase in the number of cases during 2022 in regions not considered by previously published works, this study covers cases reported in all states of the country. On the other hand, determining a relationship between the dynamics of dengue cases and climatic factors through a computational model can provide relevant information on the transmission of the virus. A multiple-learning computational approach was developed to simulate the number of the different risks of dengue cases according to the classification reported per epidemiological week by considering climatic factors in Mexico. For the development of the model, the data were obtained from the reports published in the Epidemiological Panorama of Dengue in Mexico and in the National Meteorological Service. The classification of non-severe dengue, dengue with warning signs, and severe dengue were modeled in parallel through an artificial neural network model. Five variables were considered to train the model: the monthly average of the minimum, mean, and maximum temperatures, the precipitation, and the number of the epidemiological week. The selection of variables in this work is focused on the spread of the different risks of dengue once the mosquito begins transmitting the virus. Therefore, temperature and precipitation were chosen as climatic factors due to the close relationship between the density of adult mosquitoes and the incidence of the disease. The Levenberg–Marquardt algorithm was applied to fit the coefficients during the learning process. In the results, the ANN model simulated the classification of the different risks of dengue with the following precisions (R2): 0.9684, 0.9721, and 0.8001 for non-severe dengue, with alarm signs and severe, respectively. Applying a correlation matrix and a sensitivity analysis of the ANN model coefficients, both the average minimum temperature and precipitation were relevant to predict the number of dengue cases. Finally, the information discovered in this work can support the decision-making of the Ministry of Health to avoid a syndemic between the increase in dengue cases and other seasonal diseases. [ABSTRACT FROM AUTHOR]

Plants synthesize aromatic components during their secondary metabolism, these components are known as volatile oils or essential oils. Oils extracted from medicinal and aromatic plants have been investigated and applied due to their ethnomedicinal properties and the presence of abundant bioactive compounds. Many research studies examined the variations in the yield and composition of essential oil depending on the season and duration of the day-night period. The aim of the present study is twofold, we have performed a bibliometric analysis by using the Scopus database (data collection) and VOSviewer software (analysis) along with a comprehensive review of the literature published to date on the essential oils extracted from aromatic and medicinal plants, with an emphasis on their chemical profiles based on climatic and circadian periods. Extensive research on this relationship between abiotic factors (climatic and circadian) and chemical constituents, has identified significant variability among them. Phyto medicines and preparations with well-defined and verified bioactive volatile components, action mechanisms, and therapeutic potential of essential oils, have been utilized as pharmacological means. During this study, it was observed that this field is under-explored, and only limited data is available so far, therefore it has a lot of scope for future research. [ABSTRACT FROM AUTHOR]

The olive tree is one of the most common type of cultivation in the Mediterranean area, having high economic and social importance. The Alentejo region, Portugal, is an area with a high presence of olive groves, which in 2022 accounted for 201,474 hectares. The aim of this study was to assess the relationship between olive pollen, weather data, and olive tree production, between the years 2002 and 2022. Pollen data were obtained from an urban station located in Évora, in the Alentejo region, and were used to calculate several metrics, such as the Pollen Season Duration (PSD), Seasonal Pollen Index (SPIn), peak value, and weekly pollen accumulation values. Monthly minimum, maximum, and mean temperature and precipitation sums were obtained from the E-OBS observational dataset. Considering the relationship between pollen/weather and olive production, mutual information and correlation analyses were conducted. Subsequently, several machine learning algorithms were trained using pollen and weather datasets, and we obtained suitable forecast models for olive tree production after cross-validation. The results showed high variability in pollen concentrations in Évora over the years. Complex associations were found, with certain weeks of pollen accumulation showing significant mutual information with olive production, particularly during June. The analyzed linear correlation coefficients remained generally low, underscoring the challenge of predicting olive production based on linear relationships. Among the machine learning algorithms employed to predict olive production, Decision Trees, Extreme Gradient Boosting, and Gradient Boosting Regressor were the most robust performers (r2 > 0.70), while linear models displayed a subpar performance (r2 < 0.5), emphasizing the complexity of this approach. These models highlight the roles of maximum and minimum temperatures during March and May and pollen accumulation during the second half of June. The developed models may be used as decision-support tools by growers and stakeholders to further enhance the sustainability of the thriving olive sector in southern Portugal. [ABSTRACT FROM AUTHOR]

Respiratory disorders significantly impact adolescents' health, often resulting in hospital admissions. Meteorological elements such as wind patterns have emerged as potential contributors to respiratory symptoms. However, it remains uncertain whether fluctuations in wind characteristics over extended periods have a tangible impact on respiratory health, particularly in regions characterized by distinct annual wind patterns. Crete is situated in the central-eastern Mediterranean Sea and frequently faces southerly winds carrying Sahara Desert sand from Africa and northerly winds from the Aegean Sea. This retrospective study analyzes long-term wind direction data and their relationship to respiratory symptoms observed in children up to 14 years old admitted at the University Hospital of Heraklion between 2002 and 2010. Symptoms such as headache, dyspnea, dry cough, dizziness, tachypnea, throat ache, and earache were predominantly reported during the presence of southern winds. Fever, productive cough, and chest pain were more frequently reported during northern winds. Cough was the most common symptom regardless of the wind pattern. Southern winds were significantly associated with higher probabilities of productive or non-productive cough, headache, dyspnea, tachypnea, dizziness, earache, and throat ache. Northern winds were related to a higher incidence of productive cough. Rhinitis, asthma, allergies, pharyngitis, and sinusitis were related to southern winds, while bronchiolitis and pneumonia were associated with northern winds. These findings underscore the critical role of local climatic factors, emphasizing their potential impact on exacerbating respiratory conditions in children. Moreover, they point out the need for further research to elucidate the underlying mechanisms and develop targeted interventions for at-risk populations. [ABSTRACT FROM AUTHOR]

It is necessary to understand vegetation evolution and its sensitivity to the global climate, particularly with regard to ecosystems and environmental balance. 25 watersheds were selected in Algeria for this study. Here, the vegetation index (NDVI) and climatic variables (precipitation and temperature) were used to verify the temporal-spatial patterns and impact of the time difference from 1981 to 2021 by applying the correlation coefficient and time delay analysis. The NDVI showed a significant decline, especially in recent years, and spatial differences in NDVI in all areas of study were narrow (slope values from 0.0005 to 0.04), decrease in surface water area from year to year was observed in all regions. The vegetation index was negatively associated with low rainfall and high temperatures. The vegetation's reaction to temperature has been greater than that too rainfall. In general, a time lag in the vegetation response was found over a time period of at least 1 month. This study provided new insights into variations in vegetation change and the importance of vegetation recovery. [ABSTRACT FROM AUTHOR]

Study region: The Amur River Basin (ARB), a transboundary river basin comprising four sub-regions: the Northeast Plain of China, Mongolian Plateau, Siberian Federal region and Far East Federal region. Study focus: This research presents a comprehensive analysis on the lake dynamics in both lake area and number across the entire ARB from 1999 to 2021, using multi-source remote sensing datasets. The driving mechanisms are analyzed, considering the gradients in climatic conditions and varying levels of anthropogenic activities in different sub-regions. New hydrological insights for the region: The study found that both the total area and number of lakes in ARB decreased before 2009, whereafter increased significantly until 2021. Specifically, lakes in the Mongolian Plateau shrank seriously (-46.6 km2 yr−1), while those in the Northeast Plain of China, Siberian Federal region, and Far Eastern Federal region all showed overall expanding trends. Lake changes in the entire ARB were predominantly influenced by precipitation (R2:0.54,) and soil moisture (R2:0.55). Increasing irrigation and grazing were the main forces in the Mongolian Plateau, while hydro-climatic factors played more important roles in Northeast Plain, Siberian Federal region, and Far Eastern Federal region. This study provides a comprehensive cross-regional analysis of lake area changes and driving forces, which is of great value in ensuring lake ecological safety in ARB and other regions with densely distributed lakes.

Leaf anatomical traits are susceptible to environmental changes and can reflect plant adaptation strategies to the environment. Populus euphratica plays a key role in maintaining ecosystem processes and functions in arid zones, but the variations in leaf anatomical traits of Populus euphratica and their drivers at large scales remain unclear. Here, we investigated 10 leaf anatomical traits of Populus euphratica from 12 sampling sites in the arid zone of China, and explored how they were affected by geographic, climatic, and soil factors. Our results showed that these traits differed significantly between sites (P < 0.05), which was mainly determined by climate and soil factors that together explained 41.4 % of the trait variation. The impact of climate factors is the most critical, as they can directly influence the variation in leaf anatomical traits and indirectly affect trait variation by influencing soil factors. Among them, the max temperature of the warmest month (BIO5), soil available phosphorus (SAP) and soil moisture content (SM) had the most critical effect. Besides, temperature was the major influencing factor for the ratio of spongy tissue thickness to leaf thickness (SR), palisade tissue thickness (PT), the ratio of palisade tissue thickness to spongy tissue thickness (PSR), and the ratio of palisade tissue thickness to leaf thickness (CTR), while soil nutrient was the major influencing factor for leaf thickness (LT), lower epidermis thickness (LET), and spongy tissue thickness (ST). Our results provide important insights into the response of dryland forests to climate change, and suggest that climate warming and declining soil quality may have a stronger effect on Populus euphratica.

Climate change represents a considerable threat to aquatic ecosystems, potentially affecting various water quality parameters.The study aims to assess the impacts climatic factors on the water quality parameters in tilapia broodfish pond and forecasting of water temperature in a tilapia broodfish pond using the ARIMAX model. Daily longitudinal time series data on water quality parameters were collected from the pond, while monthly climatic data were obtained from the Bangladesh Meteorological Department. Water temperature exhibited seasonal variation, peaking at 31.23 °C in October and dropping to 20.8 °C in December. pH levels ranged from 7.36 to 10.32, with the lowest recorded in December and the highest in August. Dissolved oxygen levels varied from 7.09 mg/L to 10.65 mg/L, with the lowest in September and the highest in January. Ammonia levels were highest in February at 0.33 mg/L. Water transparency ranged from 15.37 to 28 inches, with the highest in January and the lowest in June. Climatic factors significantly influenced these variations, as specified by Canonical correlation analysis (CCA). The best-fitting model, ARIMAX (1, 0, 1), indicated a fluctuating trend influenced by important exogenous factors like air temperature and solar intensity. By the end January 2025, the water temperature is expected to rise to 27.93 °C. This is a noticeable increase started from November to January. These higher temperatures may improve tilapia broodfish growth and development earlier. But the temperatures are predicted to drop started from February to March, which could negatively affect tilapia growth and development. A clear seasonal fluctuating pattern is exhibited in the future. These findings provide important insights for researchers, policymakers, academics, and those involved in tilapia farming. By considering air temperature and solar intensity in planning, stakeholders can better anticipate future pond conditions. Developing adaptive management strategies to reduce negative impacts and make the most of favorable conditions will be essential for sustainable tilapia production in the context of climate change.

One of the key variables that can affect energy consumption in a building is the shape of the structure. The current study aims to balance the using solar radiation (lighting, heating, and cooling) and energy consumption by analyzing climatic factors’ effect on building formation systems’ standards. The research shows the mechanism of reaching optimal solutions in building performance problems using evolutionary algorithms as a reliable strategy. By examining the formation of compact fabric elements, the mass of the building on the site is compared with the parametric model adapted to the context to find out the negatives and positives according to the heat gain for each. The research relied on analytical and descriptive methods to clarify the determinants. The analysis included three main axes, the urban characteristics, the urban climatic compatibility in the study area, and parametric analysis. According to the results, shaped building blocks can simultaneously enhance indoor daylight levels and energy performance. Using the framework as a reference model can increase the chances of solving complex urban design problems earlier and recommend sustainable building designs.

The Region of Central Macedonia (RCM) in Northern Greece recorded the highest number of human West Nile virus (WNV) infections in Greece, despite considerable local mosquito control actions. We examined spatial patterns and associations of mosquito levels, infected mosquito levels, and WNV human cases (WNVhc) across the municipalities of this region over the period 2010–2023 and linked it with climatic characteristics. We combined novel entomological and available epidemiological and climate data for the RCM, aggregated at the municipality level and used Local and Global Moran's I index to assess spatial associations of mosquito levels, infected mosquito levels, and WNVhc. We identified areas with strong interdependencies between adjacent municipalities in the Western part of the region. Furthermore, we employed a Generalized Linear Mixed Model to first, identify the factors driving the observed levels of mosquitoes, infected mosquitoes and WNVhc and second, estimate the influence of climatic features on the observed levels. This modeling approach indicates a strong dependence of the mosquito levels on the temperatures in winter and spring and the total precipitation in early spring, while virus circulation relies on the temperatures of late spring and summer. Our findings highlight the significant influence of climatic factors on mosquito populations (∼60 % explained variance) and the incidence of WNV human cases (∼40 % explained variance), while the unexplained ∼40 % of the variance suggests that targeted interventions and enhanced surveillance in identified hot-spots can enhance public health response.

The quantity of DNA in angiosperms exhibits variation attributed to many external influences, such as environmental factors, geographical features, or stress factors, which exert constant selection pressure on organisms. Since invasive species possess adaptive capabilities to acclimate to novel environmental conditions, ragweed (Ambrosia artemisiifolia L.) was chosen as a subject for investigating their influence on genome size variation. Slovakia has diverse climatic conditions, suitable for testing the hypothesis that air temperature and precipitation, the main limiting factors of ragweed occurrence, would also have an impact on its genome size. Our results using flow cytometry confirmed this hypothesis and also found a significant association with geographical features such as latitude, altitude, and longitude. We can conclude that plants growing in colder environments farther from oceanic influences exhibit smaller DNA amounts, while optimal growth conditions result in a greater variability in genome size, reflecting the diminished effect of selection pressure. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Entomology is the property of Chinese Journal of Applied Entomology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Botanical Research is the property of Bulletin of Botanical Research Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The shelterbelt is an indispensable barrier to the ecological and economic development of an oasis. Soil moisture, groundwater and irrigation greatly affect the shelterbelt water consumption and development. In this study, the transpiration rate of shelterbelt trees, soil moisture and meteorological data were collected to determine the effects of soil moisture and meteorological factors on the water consumption of different shelterbelt tree species via multivariate statistical methods. The results showed that the water consumption rate was positively correlated with solar radiation, air temperature and precipitation. Moreover, the leaf transpiration rate exhibited the trend of P. Russkii Jabl. P. alba P. simonii Carr.>P. nigracv, while the average daily water consumption decreased in the order of P. alba>P. Russkii Jabl.>P. simonii Carr.>P. nigracv. The average daily water consumption levels of P. alba, P. Russkii Jabl., P. simonii Carr. and P. nigracv were (9.15±0.92) kg/(tree·d), (6.95±1.41) kg/(tree·d), (4.43±1.32) kg/(tree·d), and (1.58±0.18) kg/(tree·d), respectively. Over the growing season, the soil water consumption levels of P. alba, P. Russkii Jabl., P. simonii Carr., and P. nigracv in each shelterbelt tree stand reached 674.8, 336.9, 358.1 and 161.7 kg, respectively. More than 96% of the soil moisture lost was provided by the upper 120-cm soil layer. Understanding the influence and contribution of soil water and meteorological factors to shelterbelt water consumption is beneficial for shelterbelt management and protection. [ABSTRACT FROM AUTHOR]

Copyright of South China Fisheries Science is the property of South China Fisheries Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Specific leaf area (SLA) and leaf dry matter content (LDMC) are key leaf functional traits commonly used to reflect tree resource utilization strategies and predict forest ecosystem responses to environmental changes. Previous research on tree resource utilization strategies (SLA and LDMC) primarily focused on the species level within limited spatial scales, making it crucial to quantify the spatial variability and driving factors of these strategies. Whether there are discrepancies in resource utilization strategies between trees in planted and natural forests, and the dominant factors and mechanisms influencing them, remain unclear. This study, based on field surveys and the literature from 2008 to 2020 covering 263 planted and 434 natural forests in China, using generalized additive models (GAMs) and structural equation models (SEMs), analyzes the spatial differences and dominant factors in tree resource utilization strategies between planted and natural forests. The results show that the SLA of planted forests is significantly higher than that of natural forests (p < 0.01), and LDMC is significantly lower (p < 0.0001), indicating a "faster investment–return" resource utilization strategy. As the mean annual high temperature (MAHT) and mean annual precipitation (MAP) steadily rise, trees have adapted their resource utilization strategies, transitioning from a "conservative" survival tactic to a "rapid investment–return" model. Compared to natural forests, planted forest trees exhibit stronger environmental plasticity and greater variability with forest age in their resource utilization strategies. Overall, forest age is the dominant factor influencing resource utilization strategies in both planted and natural forests, having a far greater direct impact than climatic factors (temperature, precipitation, and sunlight) and soil nutrient factors. Additionally, as forest age increases, both planted and natural forests show an increase in SLA and a decrease in LDMC, indicating a gradual shift towards more efficient resource utilization strategies. [ABSTRACT FROM AUTHOR]

Net ecosystem productivity (NEP) is an important index to estimate ecosystem carbon source / sink. Analyzing the spatial and temporal variation characteristics of NEP and its response to climate factors is of great significance to scientifically evaluate the carbon sequestration capacity of regional ecosystem and deal with climate change. Based on remote sensing data, land use data, meteorological data and DEM data, this paper studied the temporal and spatial distribution characteristics of NEP in Southwest Guangxi by using the methods of trend analysis, correlation analysis and residual analysis, and discussed the impact of different climate factors on NEP. The results showed that: (1)The mean value of NEP in the study area had been increasing from 2000 to 2018, with an annual growth rate of 2.0384 g·m–2·a –1 in southwest Guangxi, 2.7428 g·m–2·a –1 in non-karst areas, and 0.6817 g·m–2·a –1 in karst areas. (2)In the past 19 years, NEP in the study area had a spatial distribution pattern of high in the northwest and low in the southeast. The area with a very significant increase in NEP (15.39%) was greater than the area with a significant decrease (8.13%), indicating that the carbon sink capacity of the ecosystem in the study area as a whole showed an increasing trend. (3)There was a positive correlation between NEP and temperature and precipitation in study area, but the correlation coefficient between NEP and precipitation(0.0904) was stronger than that with temperature (0.0455). (4)The contribution rates of human activities to the positive and negative effects of NEP in the study area were 50.24% and 49.76% respectively. [ABSTRACT FROM AUTHOR]