A diameter distribution model was constructed to fit the diameter class structure of a mixed forest of spruce and fir trees.

Taking a 1 hm² coniferous and broad-leaved mixed plots in the Jingouling forest farm of Jilin region as the research object, a finite mixed Weibull model was used for fitting the diameter distribution of each plots, and the fitting results were compared with the Gamma model and Weibull model. The results indicated that for most of the mixed forests of spruce and fir in the region, they belong to a unimodal distribution, and from the perspective of shape parameters, they belong to a positively skewed mountainous distribution.

The RMSE (root mean square error) and MAE (mean absolute error) of the finite mixed Weibull model are significantly smaller than those of the Weibull model and Gamma model, indicating a clear advantage; The RMSE error of the finite mixed Weibull distribution decreased by 29.38% and 31.73% respectively compared to the Weibull distribution and Gamma distribution, and the MAE decreased by 28.27% and 36.23% respectively. Regardless of unimodal or multimodal distribution, the finite mixed Weibull model is superior to the Weibull model. From the composition of tree species in various plots, the advantage of the limited mixed Weibull model is greater in plots with a higher proportion of coniferous trees.

It indicates that more finite mixed Weibull models can be used to replace the Weibull model when fitting the diameter distribution of spruce and fir mixed forests.

This study aimed to systematically analyze the phenotypic traits of Xanthoceras sorbifolium seeds from different provenances, to construct a scientific germplasm evaluation system, and to provide a theoretical basis for genetic improvement, germplasm innovation, and industrial development of Xanthoceras sorbifolium.

Seeds from 12 provenances (including Gansu, Shanxi, Shandong, etc.) were used as experimental materials. Ten traits, including longitudinal diameter, transverse diameter, and single seed weight, were measured. Multivariate analyses, including one-way ANOVA, Pearson correlation analysis, cluster analysis, and principal component analysis (PCA), were combined to reveal differences in phenotypic traits, internal correlations, and comprehensive performance among provenances.

Significant differences in seed phenotypic traits were observed among provenances (P<0.05). Single seed weight showed coefficient of variation, while seed shape index exhibited the lowest. 100-seed weight was significantly and positively correlated with transverse diameter, longitudinal diameter, kernel weight, and single seed weight (P<0.05), whereas seed volume was significantly negatively correlated with kernel rate (P<0.05). Cluster analysis divided the provenances into three groups: Group I (provenances 2, 3, 9, 11, 12), termed the “small-seed low-weight type”; Group II (provenances 1, 7, 8, 10), the “medium-seed medium-weight type”; and Group III (provenances 4, 5, 6), the “large-seed high-weight type”. PCA indicated that the first three principal components explained 74.05% of the cumulative variance, with provenance 4 achieving the highest comprehensive score (164.89 points), demonstrating the most superior germplasm characteristics.

The established “morphological trait analysis—statistical model construction—germplasm classification” three-level evaluation system provides a new framework for scientific evaluation and genetic improvement of Xanthoceras sorbifolium germplasm. Due to its outstanding comprehensive performance, Provenance 4 is recommended as an excellent parental material for stress-resistant breeding.

This study focused on the soil nutrient characteristics of the mixed forest of Cunninghamia lanceolata/Sassafras tzumu with Chimonobambusa quadrangularis planted under the canopy in the state-owned forest farm of Junlian County, Sichuan Province. By comparing the soil nutrient features of the mixed forests of Cunninghamia lanceolata + Chimonobambusa quadrangularis and Sassafras tzumu+Chimonobambusa quadrangularis with those of the pure forests of Cunninghamia lanceolata, Sassafras tzumu and Chimonobambusa quadrangularis, the study aimed to explore the effect of forest and bamboo compound management on soil nutrients, and to provide a scientific basis for improving soil quality and efficiency in the hilly areas of southern Sichuan.

By analyzing and determining the soil chemical properties of the compound forest stands of Cunninghamia lanceolata + Chimonobambusa quadrangularis, Sassafras tzumu + Chimonobambusa quadrangularis, the pure forest stands of Cunninghamia lanceolata, Sassafras tzumu and Chimonobambusa quadrangularis, using the Nemerow method for comprehensive evaluation of soil, the influence of mixed management on forest soil was explored.

1) The mixed management significantly increased soil nutrient content. In terms of basic nutrients, the soil organic matter content of the mixed forests of Cunninghamia lanceolata+Chimonobambusa quadrangularis and Sassafras tzumu+Chimonobambusa quadrangularis was 77.20±3.07 g/kg and 82.57±16.43 g/kg, respectively, which was 43.1% and 14.4% higher than that of the pure forests of Cunninghamia lanceolata (53.97±6.08 g/kg) and Sassafras tzumu (72.17±7.40 g/kg); 2) In terms of available nutrients, the contents of water-soluble nitrogen, available phosphorus and available potassium in the mixed forest of Sassafras tzumu+Chimonobambusa quadrangularis were 268.00 ± 43.21 mg/kg, 3.42 ± 1.16 mg/kg and 145.67 ± 20.67 mg/kg, respectively, which were 16.0%, 10.7% and 20.7% higher than those of the pure forest of Sassafras tzumu; 3) The comprehensive evaluation of soil showed that the Nemerow comprehensive index of the mixed forest of Sassafras tzumu+Chimonobambusa quadrangularis was 1.46, and the forest soil nutrient grade was improved from medium to good.

The mixed management of forest and bamboo effectively improved the soil nutrient status through the ecological complementary effect among speciess compared with pure forest management. Among them, the compound forest of Sassafras tzumu+Chimonobambusa quadrangularis performed best in increasing soil organic matter content, promoting the accumulation of nitrogen, phosphorus and potassium nutrients and improving the proportion of available nutrients. The research results not only enriched the soil ecological theory of forest-bamboo mixed management, but also provided practical references for the ecological restoration and sustainable management of degraded forest land in the hilly areas of southern Sichuan.

This study aimed to investigate the differences in growth and physiological characteristics of seedlings from five predominant Camellia oleifera cultivars in Hunan Province under acidic purple soil, alkaline purple soil, and red soil (control) conditions, so as to provide a theoretical basis for ecological adaptability evaluation, cultivar selection, and targeted soil improvement of C. oleifera in purple soil regions of Hunan.

A pot experiment was conducted using red soil as the control. Growth, physiological, and biochemical indices of three-year-old seedlings of five cultivars (‘Huashuo’@@@, ‘Huajin’@@@, ‘Huaxin’@@@, ‘Xianglin 210’@@@, and ‘Hengdong Datao No.2’@@@) were measured across three soil types. The data were comprehensively evaluated using membership function method and principal component analysis.

The acidic purple soil was more favorable for the growth of C. oleifera, with the average membership function values of growth indicators for all cultivars being higher than those in the red soil and alkaline purple soil. Under acidic soil conditions, ‘Huashuo’@@@ and ‘Hengdong Datao No.2’@@@ showed the most comprehensive performance, with generally desirable growth, physiological, and biochemical parameters, although their chlorophyll content was comparatively lower. In alkaline soil, both ‘Huashuo’@@@ and ‘Huaxin’@@@ exhibited elevated antioxidant enzyme activities; however, ‘Huashuo’@@@ displayed the highest malondialdehyde (MDA) content, indicating substantial membrane damage and poor adaptability. In contrast, ‘Huaxin’@@@ maintained lower MDA levels and achieved higher membership function rankings, reflecting superior membrane stability and stress tolerance. Principal component analysis revealed that all cultivars performed better in acidic soil than in the other soil types. ‘Hengdong Datao No. 2’@@@ and ‘Huaxin’@@@ performed well in both red soil and acidic purple soil, whereas ‘Huajin’@@@ and ‘Huaxin’@@@ demonstrated relatively better adaptability in alkaline purple soil.

Comprehensive analysis of all measured indicators revealed that acidic purple soil was the most suitable for C. oleifera growth, with cultivars grown in this soil type occupying the top five positions in the overall ranking. The order of soil adaptability was determined as: acidic purple soil>red soil>alkaline purple soil. ‘Hengdong Datao No. 2’@@@ and ‘Huaxin’@@@ exhibited the best performance in both acidic purple soil and red soil, while ‘Huajin’@@@ and ‘Huaxin’@@@ showed relatively superior adaptation in alkaline purple soil. Considering the overall performance across all three soil types, ‘Huaxin’@@@ demonstrated the strongest comprehensive adaptability.

To clarify the impact of fertilization methods on the nutrients and economic characteristics of Camellia oleifera, explore the relationship between nutrients and fruit economic characteristics, and to identify suitable fertilization methods for Camellia oleifera forests.

Using ‘Ganxing 48’@@@ Camellia oleifera as the material, three fertilization treatments were set up: hole fertilization (D), furrow fertilization (G), and no fertilization (CK). The nutrient content and fruit economic characteristics of Camellia oleifera leaves, fruits, roots, and flower buds were investigated, and a partial least squares path model was constructed to analyze the relationship between tree nutrients and fruit economic characteristics as well as the influence of fertilization methods on tree nutrients and fruit economic characteristics.

Compared with CK, the fruit shape index of the hole application treatment is closer to 1, and the quality of fresh fruits increased by 21.51% and 9.00%, respectively. The oil yield of fresh fruits increased by 22.21% and 24.67% respectively, and the oil production per plant increased by 33.12% and 41.23% respectively; With the extension of growth time, N and K nutrients gradually accumulate as a whole; P nutrients gradually transfer from leaves, fruits, and roots to flower buds. The soluble sugars in roots and flower buds gradually transfer to the fruit; The overall trend of soluble starch content is decreasing and increasing. Fertilization can promote the accumulation of N, K and soluble starch in various organs, increase P content in roots, leaves, and fruits during the growth period of spring shoots, promote the accumulation of soluble sugars in leaves and fruits, and alleviate the consumption of soluble sugars in roots and flower buds. The results of the PLS-PM show that G mainly increases fruit nutrients and reduces leaf nutrients during the oil conversion period, while D mainly reduces leaf nutrients during the rapid growth period of spring shoots and increases root nutrients during the peak fruit growth period, thereby improving fruit economic traits. The results of PCA showed that 5 fruit quality indicators, 2 moisture content indicators, fruit shape index, fresh fruit oil content, dry seed oil content, and oil production were the main indicators for evaluating the fertilization effect, with a cumulative contribution rate of 88.79%. The comprehensive score from high to low was D>G>CK.

Hole fertilization is a more suitable fertilization method for Camellia oleifera forests, as it improves fruit economic characteristics by affecting the nutrients of Camellia oleifera at different stages.

To investigate the effects of two microbial fertilizers on the growth and photosynthetic characteristics of Camellia oleifera seedlings, and to provide some practical references and theoretical support for the nutrient management of Camellia oleifera.

The growth indexes, gas exchange parameters, chlorophyll fluorescence parameters and antioxidant enzyme activities of Camellia oleifera seedlings were measured after applying two kinds of microbial fertilizers, and combined with the principal component and subordinate function analysis to comprehensively evaluate the effects of different treatments and screen the optimal fertilizers and application rates.

The application of microbial fertilizer significantly promoted the growth and photosynthetic characteristics of Camellia oleifera. Compared with the control group (CK), A4 and L2 treatments increased plant height by 71.74% and 67.94%, respectively; A2 and L2 treatments increased ground diameter by 60.00% and 45.40%, respectively. Chlorophyll and carotenoid contents were significantly increased by A3 and L3 treatments, where the increase in chlorophyll a, chlorophyll b, total chlorophyll and carotenoids were 147.64%, 90.62%, 122.08%, 213.43% and 130.27%, 121.03%, 126.85% and 280.07%, respectively. The A2 treatment increased the net photosynthetic rate (P_n) compared to the 93.03% and 66.66% in the control (CK) and nitrogen fertilizer treatment (N), respectively. qP and ETR of A2-treated leaves were 31.03% and 35.95% higher than that of CK, and 46.15% and 33.75% higher than that of N group, respectively. In addition, superoxide dismutase (SOD) activities of A4 and L2 treatments were significantly higher than CK and N by 24.69%, 28.57% and 51.82%, 56.54%, respectively, while peroxidase (POD) and catalase (CAT) activities were enhanced. The comprehensive evaluation of principal component analysis and affiliation function indicated that the growth, photosynthetic characteristics and antioxidant enzyme activities of Camellia oleifera performed best under A2 treatment.

The microbial fertilizer and Randidobond significantly promoted the growth of Camellia oleifera seedlings, and enhanced the antioxidant enzyme activities by increasing the chlorophyll content, gas exchange parameters, chlorophyll fluorescence parameters of the leaves, effectively enhanced the photosynthesis of the plants, and provided a strong support for the high-efficiency cultivation of Camellia oleifera.

In order to simulate and predict the suitable habitat distribution of rare and endangered Dipterocarpaceae tree species in China, conduct conservation priority area and conservation GAP analysis, and to provide a basis for their protection and management.

Based on climate, terrain, soil, and human impact factors, MaxEnt model optimized was used with R language to simulate and predict the suitable habitats and changing trends of eight rare and endangered Dipterocarpaceae trees in China. The Marxan model was combined to identify priority areas for the protection of rare and endangered Dipterocarpaceae tree species and conducted a protection GAP analysis.

The results showed that: 1) The optimized MaxEnt model simulated the suitability zone of various tree species with high accuracy, with AUC values greater than 0.971; 2) Rare and endangered Dipterocarpaceae plants in China are mainly distributed in southern tropical regions such as Yunnan, Hainan, and Guangxi, with a relatively concentrated distribution range; 3) Annual mean temperature, isothermality, and human impact factors are the dominant factors affecting the distribution of the suitable habitat of Dipterocarpaceae tree species. Among these, annual mean temperature has the greatest impact on Dipterocarpaceae tree species, with an average contribution rate of 52.9%; 4) Under the SSPs126 and SSPs585 scenarios, the suitable areas for Dipterocarpus retusus, Hopea chinensis, Parashorea chinensis, Vatica mangachapoi decrease by 0.29% to 60.00%, and the center of gravity of the suitable areas shifts southwestward. Shorea assamica and Vatica guangxiensis expand by 8.60% to 52.22%, migrating northwest and northeast, respectively. The suitable areas for Hopea hainanensis and Hopea reticulata land decrease by 21.70% and 1.61%, respectively, under the SSPs126 scenario, and expand by 26.14% and 13.01%, respectively, under the SSPs585 scenario, with their centers of gravity shifting northeastward; 5) The priority areas for the protection of rare and endangered tree species of the Dipterocarpaceae family are mainly distributed in southern Yunnan Province and central Hainan Province. Currently, the protected area is only 0.515 6×10⁴ km².

The optimized MaxEnt model can effectively predict the suitable habitats of various tree species in the Dipterocarpaceae. The priority suitable habitats are not sufficiently protected, so efforts should be made to strengthen their protection and expand the distribution range of each tree species.

To accurately predict the growth dynamics of Chinese fir and construct a dominant tree diameter at breast height (DBH) growth model that integrates site and climatic conditions, and to provide guidance for sustainable management and carbon sequestration assessment of Chinese fir plantations.

Utilizing 1 121 DBH-age datasets from 129 Chinese fir plantation plots, topographic, edaphic and climatic factors were incorporated. Significant environmental drivers affecting DBH growth were identified through Quantification Theory I. The optimal theoretical growth equation was selected from six candidate models. Site types and climate types were clustered into site type groups and climate type groups using the k-means algorithm. Nonlinear mixed-effects regression models were developed by incorporating site type, climate type, and their clustered groups as random effects, either individually or in combination.

Seven leading factors influencing DBH growth of dominant trees, including altitude, aspect, Climatic moisture deficit and extreme minimum temperature, were screened. Among the six basic models, the Korf model had the best fitting effect, with a determination coefficient R² of 0.782 0, 75 site types and 173 climate types clustered into 5 site type groups and 7 climate type groups, respectively, and the random effect model R² with site factor groups and climate factor groups only was 0.822 9 and 0.839 1, respectively, and the random effect model with site and climate factors was R²= 0.854 3 which was significantly better than the other models.

The nonlinear mixed-effects model developed in this study, which integrates site- and climate-effects, comprehensively incorporates environmental factors influencing the DBH growth of dominant Chinese fir trees. This model not only provides scientific guidance for predicting the DBH growth of dominant Chinese fir trees, but also establishes a generalizable modeling framework for analyzing and forecasting environmental impacts on the growth of subtropical Chinese fir plantations.

To investigate the effects of nitrogen addition on water use efficiency and related enzyme activities of P. massoniana seedlings under continuous drought and re-watering, and to provide reference for exploring whether nitrogen addition improves drought resistance of P. massoniana.

One-year-old P. massoniana seedlings were used as experimental materials, and a nitrogen application group (N) and a control group (CK, no nitrogen fertilizer applied) were set up. Continuous drought and re-watering experiments were conducted through potted plants. Samples were collected at 0, 20, 40, and 60 days during continuous drought, as well as two days after re-watering. Soil water content, physiological and biochemical indices, and water consumption were measured for drought resistance evaluation.

1) The nitrogen application group increased soil moisture content, stem water potential, amino acid content, and water consumption of seedlings during the severe extreme drought stage (20-60 days), while reducing soluble protein, superoxide anion, and malondialdehyde content during the extreme drought stage (40-60 days); 2) During 40-60 days of drought, the nitrogen application group showed a significant increase in amino acid, proline content, and CAT activity; 3) After re-watering, the soluble protein, superoxide anion, and malondialdehyde content, as well as the activities of superoxide dismutase and catalase, were significantly reduced in the nitrogen application group, while the control group maintained high levels, indicating weak recovery ability after drought; 4) The comprehensive evaluation of drought resistance was conducted on physiological and biochemical indicators using the membership function method. The results showed that during the extreme drought stage (40-60 days), the nitrogen application group exhibited strong drought resistance.

Nitrogen application can improve soil water retention during drought periods, increase the content of osmoregulatory substances in P. massoniana seedlings, and enhance antioxidant enzyme activity, thereby reducing cell dehydration and mitigating oxidative damage to seedlings, thus improving their drought resistance and post-drought recovery ability under drought stress.

In order to provide a reference for the maintenance and protection of the natural population of Picea neoveitchii, this study discussed the structure and development trend of Picea neoveitchii in the field, revealing the current situation and development trend.

This study investigated the population of Picea neoveitchii in two existing areas, Zhouqu and Tianshui, Gansu. Utilizing population ecology methods, statistical analyses are performed on aspects such as the age-class structure, population dynamics, and viability of the populations. Additionally, a time series model was employed to predict the characteristics of the population quantity structure.

The results showed that: 1) The population in Zhouqu had a relatively abundant number of seedlings and saplings, with an age structure approximating a bell shape, indicating a stable population. The population in Tianshui was in a remnant state, with fewer than 10 individuals and scarce seedlings, suggesting insufficient potential for regeneration and classifying it as a declining population. Both populations were highly sensitive to external disturbances and had weak anti-disturbance capabilities; 2) The survival curve of the Picea neoveitchii population followed Deevey-Ⅱ, with equal mortality rates at all age groups. The population was in a relatively stable state, and the survival curve showed two peaks of extinction occurring in the Ⅱ and Ⅵ age groups; 3) The survival analysis function indicated that the survival rate (S_t) decreased with increasing age, while the cumulative mortality rate (F_t) increased with increasing age. After diameter class IV, the survival rate of the Picea neoveitchii population balances with its cumulative mortality rate, and the changes in the mortality density curve (f_ti) and hazard rate curve (λ_ti) were basically consistent, showing an overall upward trend, the upward trend slowed down in age groups II to IV, and the increase was more significant after age group IV; 4) The analysis based on the time series prediction model revealed that after undergoing periods of 2, 3, 4, 5, 6, and 7 diameter classes in the future, the number of individuals across all diameter classes of the Picea neoveitchii population was projected to show an overall upward trend. Moreover, the longer the time span within the same diameter class, the more significant the increase in the number of individuals becomes. The population was a growth population, but normal updates were difficult to maintain in the long term without considering external factors.

This study suggested that the population stability of Picea neoveitchii was poor, it was highly sensitive to the environment, and its ability to resist external interference was weak. It is recommended that the species be included in conservation programs for extremely small populations, with protected areas established. Increased investment in scientific research is needed to enable long-term, systematic monitoring and evaluation of population dynamics. Explore the research and development of artificially modified and intervention-applicable technologies to construct suitable habitats that align with the characteristics of Picea neoveitchii; establish in-situ conservation demonstration zones and conduct research and demonstration of key techniques for wild reintroduction.

To explore the changing patterns of carbon storage at different development stages of forest stands, identify the factors influencing carbon storage, and to provide a theoretical foundation for the scientific management, operation, and enhancement of forest carbon storage.

Focusing on Quercus mongolica forests in the east of Liaoning mountainous area, the carbon storage in the arboreal layer was estimated using the anisotropic growth equation. Additionally, the carbon stocks of shrubs, herbs, litter, and soil within representative sample plots were measured utilizing the sampling method. Our analysis of these data elucidated the characteristics of ecosystem carbon storage across different developmental stages of Q. mongolica forests. Moreover, redundancy analysis was employed to identify the key environmental factors influencing variations in carbon storage.

1) The ecosystem carbon storage of Q. mongolica forests in the east of Liaoning mountainous area is 296.13, 332.65, 300.72, and 503.55 t·hm^-2 for young, half-mature, mature, and overmature forests, respectively. Notably, overmature forests exhibit the highest carbon stocks, significantly surpassing those of the other developmental stages. (P<0.05); 2) Among the ecosystem components, the carbon stock in the soil layer (0-30 cm) accounted for the largest proportion. As the forest progresses through its developmental stages, carbon storage in the vegetation layer gradually increases, while the proportion of soil carbon stock decreases; however, it consistently remains above 50%; 3) The proportion of carbon storage in the vegetation layer exhibits a trend of initially increasing and then decreasing with forest age, reaching its maximum of 48% in mature forests; 4) Elevation, aspect, and soil total phosphorus content are the primary environmental factors influencing variations in carbon storage, collectively accounting for 20.5%, 12.1%, and 3.6% of the total variation in ecosystem carbon storage, respectively.

Among the various development stages of Q. mongolica forests in the east of Liaoning mountainous area, carbon storage remains relatively stable from the young to mature stages, while overmature forests exhibit the highest ecosystem carbon stocks. The soil layer constitutes the primary component of carbon storage within the ecosystem, followed by the vegetation layer. Elevation is the most significant factor influencing changes in ecosystem carbon storage, followed by aspect and total phosphorus content in the soil.

The restoration and improvement of the degraded natural grassland ecosystem in the Qilian mountains rely heavily on the strong support of composite measures. This study aims to enhance grassland productivity and forage quality in the Qilian mountains, providing technical references for ecological restoration.

Compound measures for grassland improvement, including grass seed combination reseeding, reseeding with grass seed mixtures + compound fertilizer + pest control, were adopted to investigate their effects on species diversity, grassland productivity, and forage nutritional value in the grassland ecosystem.

1) After adopting composite measures, the species composition of the temperate grassland plant community in the northern foothills of the Qilian mountains significantly improved compared to the control grassland; the average vegetation height and grass yield also significantly increased by 20.9% and 56.8%, respectively. 2) After adopting the combined measures of “Poa pratensis + Elymus nutans + Dongnong 1 alfalfa” plus “Agropyron cristatum” or “Bromus inermis”, the Shannon-Wiener diversity index of the community significantly increased compared to the control. The combined measures of “Poa pratensis + Elymus nutans” plus “Dongnong 1 alfalfa + Agropyron cristatum” or “Elymus sibiricus + Bromus inermis” followed by the application of nitrogen, phosphorus, potassium compound fertilizer and nicotine-matrine insect control measures significantly increased the Pielou evenness index and Margalef richness index. The Simpson ecological dominance index and Simpson diversity index of the community in the experimental area showed no significant difference compared to the control; 3) After adopting the combined measures of “Poa pratensis + Elymus nutans” plus “Dongnong 1 alfalfa + Elymus sibiricus” or “Dongnong 1 alfalfa + Agropyron cristatum” or “Agropyron cristatum + Ganyin 1 rye”, the crude protein content of the grassland forage significantly increased compared to the control, by 30.2%, 19.8% and 32.7%, respectively. After adopting the combined measures of “Poa pratensis + Elymus nutans + Dongnong 1 alfalfa” plus “Ganyin 1 rye” or “Elymus sibiricus” or “Agropyron cristatum” followed by the application of nitrogen, phosphorus, potassium compound fertilizer and nicotine-matrine insect control measures, the crude protein content of the grassland forage significantly increased compared to the control, by 19.8%, 47.7% and 18.0%, respectively.

The combination of “Kentucky bluegrass + Elymus nutans + Dongnong No.1 alfalfa + Agropyron cristatum” and the application of nitrogen, phosphorus, and potassium compound fertilizer and nicotine-matrine insect control measures performed optimally, significantly enhancing grassland productivity and improving grassland quality, greatly increasing grassland carrying capacity, and providing a scientific basis for the restoration and management of the Qilian mountain grassland ecosystem.

The middle section of the Yinshan mountains in Inner Mongolia, as a representative area of the Three-North Shelter Forest Program, faces critical challenges in enhancing ecosystem carbon sequestration functions. This study aims to investigate the diurnal variation characteristics of photosynthesis and water use efficiency (WUE) in arbor and shrub species in the Middle Section of the Yinshan Mountains, analyze the influence of environmental factors on photosynthetic regulation, and comprehensively evaluate the ecological adaptability and carbon sequestration functions of different tree species. For the first time, a combination of random forest regression models and cluster analysis is applied to provide scientific insights for improving shelter forest ecosystem functions.

Seven arbor species and five shrub species were selected in the middle section of the Yinshan mountains, Inner Mongolia. Photosynthetic parameters were measured using a CI-340 portable photosynthesis system. Spearman's correlation analysis, principal component analysis (PCA), random forest regression modeling, and hierarchical cluster analysis were employed to explore the photosynthetic mechanisms and ecological adaptability of the species.

The study revealed distinct diurnal variation patterns in photosynthetic activity among arbor and shrub species. Net photosynthetic rate (P_n) and WUE exhibited significant interspecific differences, with single-peak and double-peak patterns observed. Temperature, stomatal conductance, and transpiration rate were identified as key regulators of photosynthesis, particularly in coniferous species, which demonstrated higher WUE. Random forest regression analysis highlighted the critical roles of temperature and water management in photosynthetic processes. Cluster analysis further revealed marked differences in carbon sequestration capacity and ecological adaptability among species, offering critical guidance for species selection and carbon sequestration assessments.

This study underscores the significant differences in photosynthesis and WUE between arbor and shrub species in the middle section of the Yinshan mountains. Temperature, stomatal conductance, and transpiration rate were pivotal in photosynthetic regulation. Unlike traditional linear regression methods, the random forest model effectively captured the nonlinear relationships between environmental variables and photosynthetic rates. The hierarchical cluster analysis, applied for the first time in this context, identified distinct functional groups of species based on their carbon sequestration potential and ecological adaptability. These findings fill a critical gap in understanding photosynthetic mechanisms and carbon sequestration capacity within the Three-North Shelter forest program, providing a novel framework for quantitative carbon sequestration assessment and informing future afforestation and restoration strategies.

This study utilized SSR markers to assess the genetic diversity and structure of natural Phyllanthus emblica populations in Guangxi, China, and revealed habitat factors influencing genetic variation, aiming to provide a theoretical foundation for germplasm conservation and elite variety breeding of P. emblica.

Genetic diversity and population structure of P. emblica were analyzed across 18 natural populations (398 individuals) from Guangxi using 13 SSR primer pairs. Genetic analyses were performed with PolyGene, GenAlEx and STRUCTURE software, and correlation heatmaps were generated using R software.

A total of 145 alleles were detected across 13 SSR loci, with an average of 11.154 alleles per locus. The mean observed heterozygosity (H_o), expected heterozygosity (H_e), polymorphism information content (PIC), and Shannon-Wiener diversity index (I) for each locus were 0.515, 0.635, 0.595, and 1.412, respectively. Among the 18 populations, BSLL exhibited the highest genetic diversity, with H_e and I of 0.630 and 1.327, while GLPL showed the lowest, with H_e and I of 0.494 and 0.875, respectively. Dry-hot valley populations displayed significantly higher H_e and I than humid area populations. Genetic diversity was significantly positively correlated with temperature-related factors (Bio6: minimum temperature of the coldest month; Bio8: mean temperature of the wettest quarter; Bio11: mean temperature of the coldest quarter) and negative correlation with precipitation-related variables (Bio12: Annual precipitation; Bio13: precipitation of the wettest month; Bio19: precipitation of the coldest quarter). Analysis of molecular variation (AMOVA) indicated that 9.134% of genetic variation occurred among populations, while 90.866% within populations. STRUCTURE analyses (Delta K=2, 3, 4) consistently group dry-hot valley populations into a distinct cluster, demonstrating significant differentiation from humid area population.

Natural P. emblica populations in Guangxi possess moderate genetic diversity, with significant inter-population differentiation. Notably, dry-hot valley populations are genetically distinct from humid area populations, driven by divergent temperature and rainfall regimes. Therefore, it is recommended to implement targeted conservation strategies, including germplasm collection, preservation, and utilization-specific to distinct ecotypes such as dry-hot valley and humid area populations. This approach will effectively conserve genetic diversity and facilitate the rational exploitation of germplasm resources for future breeding programs.

To resolve the issues of unclear parental origins and unstable offspring traits during Hibiscus syriacus L. breeding by farmers, the genetic variability analysis and correlation analysis on phenotypic traits and molecular makers were performed.

50 Hibiscus syriacus L. germplasms were used as experimental materials, with the data code method, the genetic variability analysis of ISSR and AFLP molecular makers were performed to trace the parentage of ‘local new variety’@@@. The correlations among 7 phenotypic indicators and their correlations with molecular markers were obtained by correlation analysis, and the phenotypic traits with strong genetic stability were selected to provide target phenotypes for the breeding of improved Hibiscus syriacus L.

The results showed that a total 62 polymorphism fragments and 59 polymorphic fragments of 50 germplasms are generated from of 7 pairs of ISSR primers. The polymorphism rate reaches 95.16%, the genetic similarity coefficients are 0.051 4-1.000 0. Simultaneously, a total 49 polymorphism fragments and 47 polymorphic fragments of 50 germplasms are generated from of 23 pairs of ISSR primers. The polymorphism rate reaches 95.92%, the genetic similarity coefficients are 0.000 0-1.000 0. By comparing the genetic similarity coefficients between ‘local new variety’@@@ and foreign varieties, parental origin tracing is successfully accomplished for four cultivars (No. 21、No. 22、No. 23、No. 24). It shows that there are the significantly different in 7 phenotypic traits. The mean coefficient of variation (CV) is 46.00, and the phenotypic diversity index (H) of 50 cultivars are 0.405-2.049. The results of correlation analysis show that the correlations of 4 phenotypic traits about petals type (PT), floral halo (FH), FR and seed shape (SS) are significant, and the correlations of 3 phenotypic traits about FC, leaf shape (LS) and leaf margin serration (LMS) are not significant. There are significance correlations between phenotypic traits and the polymorphism sites of molecular markers, among which PT, FH and FR possess more correlated polymorphism sites, all exceeding 15%. In contrast, FC, LS and LMS possess fewer correlated polymorphism sites, all below 5%. The correlation analyses indicate that this three traits, FC, LS and LMS, are not suitable as target phenotypes to avoid producing offspring with unstable trait expression during new cultivar breeding.

This study provides new research ideas and directions for the variety certification and improving the trait stability of ‘local new variety’@@@, obtained from the resource survey.

Wildlife plays a pivotal role in biodiversity conservation, and field resource surveys form the fundamental basis. Efficient recognition of monitoring images is a critical prerequisite for scientific wildlife resource investigation and protection. However, domain shift issues caused by varying lighting conditions, backgrounds, shooting scales, and species differences often degrade recognition model performance. This study aims to enhance the generalization capability of wildlife species recognition under complex unlabeled field environments, providing key technical support for open-environment wildlife classification research.

This paper proposed a deep convolutional domain adaptation model for wildlife image recognition to enhance cross-domain accuracy in unannotated scenarios. Specifically, the model employs a pre-trained ResNet50 network as a feature extractor to capture domain-invariant convolutional features of wildlife images through maximum mean discrepancy (MMD) constraints. A mixup-based probabilistic distribution feature alignment module is designed to map semantic spaces in fully connected layers, enhancing the model's ability to learn high-level semantic information. Finally, entropy regularization constraints and target domain correlation mining are integrated to optimize low-density separation boundaries between categories, further improving the model's generalization and robustness.

A series of experiments were performed on two wildlife datasets, which contain 8 and 11 species respectively, to validate the model's effectiveness. The results demonstrate that the proposed model achieves average accuracies of 98.3% and 81.7% on the two datasets, significantly outperforming adversarial learning-based baseline models in wildlife image recognition.

The proposed deep convolutional domain adaptation-integrated wildlife image recognition model effectively mitigates domain shifts caused by spatiotemporal scenario variations and species differences, thereby enhancing cross-domain wildlife species recognition accuracy. This approach offers a robust technical framework for advancing wildlife conservation and ecological monitoring.

To comprehensively elucidate the regulatory mechanisms of late embryogenesis abundant (LEA) proteins in higher plant embryogenesis and abiotic stress responses.

Hidden Markov model and bioinformatics were used to screen and identify LEA genes family from the whole genome of Malus sieversii, and their sequence features, conserved motifs, gene structures, cis-acting elements, and expression patterns were analyzed.

The 119 LEA genes were identified in the whole genome of Malus sieversii. According to their conserved structural domains and phylogenetic relationships, they were categorized into eight different groups (LEA1-LEA6, DHN, SMP), among which the MsiLEA2 group was the most gene-rich. Analysis of the cis-acting elements showed that most of the MsiLEA genes were associated with light response elements, abiotic stress response. In addition, some genes were related to biosynthetic pathways, such as abscisic acid response, growth hormone response, methyl jasmonate response, and meristematic tissue expression. The analysis of the expression pattern of Malus sieversii LEA genes in different periods of seed low-temperature stratification and in different organs showed that the expression of MsiDHN3 decreased during seed low-temperature stratification and was higher in all organs, indicating that MsiDHN3 plays a role in the low-temperature stratification of Malus sieversii seeds.

This study provides new insights into the formation of the MsiLEA genes family in Malus sieversii, it also deepens the understanding of the potential roles of these genes during embryonic developmental stages and abiotic stress response in Malus sieversii seeds. These results are instructive for future functional studies of the MsiLEA genes family and provide a theoretical basis for exploring the role of MsiLEA genes in the embryonic developmental stages of Malus sieversii seeds.

This study examined the spatial heterogeneity of 20 traditional villages in Meishan from a multiscale perspective, analyzes the spatial correlation with cultural heritage, and proposed preservation strategies for traditional village conservation and cultural continuity based on the village type identification of natural-cultural factors.

Utilizing ArcGIS, production-living-ecological space classification, and bivariate local spatial autocorrelation, spatial heterogeneity of villages and their spatial correlation with cultural heritage were analyzed, the characteristics of traditional villages through K-means clustering were classified.

1) Spatial distribution of villages follows strong topographic and functional orientations, 75% are located in plain-hilly areas with slopes of 10°-20° and elevations below 500 m, all near water, and 85% in medium and low geological hazard zones. Five layout types are identified: waterfront linear, axial extension, terraced slope, clustered aggregation, and multi-nuclei group pattern. Ecological space accounted for the largest proportion, while living and production spaces correlates with village function and spatial layout; 2) Cultural heritage exhibits a “large agglomeration, small dispersion” pattern, with weak spatial dependency on villages, only 15% of villages are in high-high clusters, 40% in high-low clusters, 45% in non-significant clusters; 3) Based on clustering of natural and cultural factors, villages are categorized into four typical groups: high risk, culture enriched, ecologically constrained, and moderately balanced.

Meishan villages possess a premium natural foundation and stable geological conditions, their spatial pattern demonstrating significant adaptation to the topographic features, but they show weak linkages to cultural heritage, and exhibit significant negative spatial correlation. This requires differentiated protection strategy, through strengthened graded risk management and heritage resource integration to fulfill the spatial governance requirements for the harmonious coexistence of nature and culture.

Tourism ecological resilience is an important indicator of the sustainable development capacity of the tourism ecosystem, and reveals the spatiotemporal evolution characteristics and driving factors, which is a reference basis for promoting the sustainable development of tourism.

Based on adaptive capacity, resilience, and transformative potential, an evaluation index system for tourism ecological resilience was constructed. Using the entropy weight-TOPSIS method, exploratory spatial data analysis, standard deviation ellipses, and the geographic detector model, the spatiotemporal evolution and driving factors of tourism ecological resilience in the Yangtze River Economic Belt from 2014 to 2023 were analyzed.

1) From 2014 to 2019, tourism ecological resilience showed a stable upward trend, while it exhibited a “W”-shaped pattern from 2019 to 2023, and the overall was low. There are significant spatial differences, with the distribution characterized by downstream regions>midstream regions>upstream regions. 2) The global autocorrelation of tourism ecological resilience is not significant, but local autocorrelation shows four types of clustering: high-high, high-low, low-high, and low-low. The number of districts with significant local autocorrelation has increased from 17 to 24. 3) The spatial discrete degree of tourism ecological resilience shows a pattern of contraction followed by expansion, with a clear directional trend. The azimuth angle expands each year, while the center of gravity remains largely stable. 4) Tourism resources, economic development, government regulation, and ecosystem resilience are the main factors influencing the spatiotemporal evolution of tourism ecological resilience in the Yangtze River economic belt.

The tourism ecological resilience is weak overall, and the spatial difference is obvious in the Yangtze River economic belt. Therefore, promoting the upgrading of the tourism industry, developing new tourism forms such as smart tourism and eco-tourism, increasing ecological protection and restoration, and implementing cross-regional tourism resource integration and optimal allocation are the key measures to enhance tourism ecological resilience.

Current wooden chairs commonly suffer from insufficient support, structural deformation, and poor stability, negatively impacting user experience and durability. To address these issues and enhance the structural performance and usability of wooden chairs, this study investigates the critical role of wood's mechanical properties in chair design and proposes an optimized design based on these characteristics. The aim is to improve load-bearing capacity, stability, and material utilization efficiency.

The compressive and flexural strength of different wood types (e.g., pine, oak, beech) was systematically analyzed, along with the influence of grain direction and moisture content on material strength. Based on these findings, a mechanics-driven optimization design was proposed, focusing on improving the connection structure between the chair frame and seat to enhance overall support. Finite element analysis (FEA) using ANSYS software was then conducted to simulate stress distribution and structural stability, ensuring design rationality.

Physical prototype testing demonstrated that the optimized chair exhibited a 22% increase in compressive efficiency under static and dynamic loads, a 37% improvement in backrest support, and a reduction of over 25% in lumbar pressure due to ergonomic enhancements. Additionally, material stiffness increased by 19%, stability improved by 23%, validating the effectiveness of grain optimization strategies. The optimized design also minimized material waste, improving wood utilization while maintaining cost-effectiveness and environmental sustainability.

Structural optimization based on wood's mechanical properties effectively enhances the durability and comfort of wooden chairs, providing a scientific foundation for furniture design. Future research could further explore the optimal pairing of different wood types with structural designs and incorporate sustainable materials (e.g., bamboo, engineered wood) to develop more efficient and eco-friendly solutions for the wooden furniture industry.