应用生态学报最新文献

Rosa multiflora, originated from East Asia, is one of the original ancestors of modern roses. It is also an important genetic resource and rootstock for rose cultivation. Due to its high resistance and vigorous growth, R. multiflora has become an invasive species in some introduction sites, such as North America. To explore the correlation between the suitable habitat of R. multiflora and climate change, we predicted its potential geographic distribution with an optimized MaxEnt model based on 1246 distribution records and nine bioclimatic variables. The results showed that the mean temperature of the coldest quarter, minimum temperature of the coldest month, precipitation of the warmest quarter, and isothermality were significant bioclimatic variables affecting the potential geographic distribution of R. multiflora. Under current climate conditions, R. multiflora naturally distributed in the plains and hilly areas to the east and south of the Loess Plateau. The distribution pattern in the mid-holocene was similar to its current distribution, but the highly suitable distribution area was in the south of North China Plain, the Sichuan Basin, and parts of the Middle-Lower Yangtze Plain. During the last interglacial, the suitable areas generally contrac-ted southward, while the highly suitable areas significantly expanded and mainly located in the Sichuan Basin, the Middle-Lower Yangtze Plains, the Yunnan-Guizhou Plateau, and the Southeast Hills. Beyond its natural distribution in East Asia, R. multiflora had been introduced and spread to most parts of Europe and the central and eastern United States. The distribution area of R. multiflora would expand under three warming scenarios of different shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) during 2041-2060 and 2081-2100. Its average distribution center (centroid) would shift towards higher latitude, indicating that the distribution of R. multiflora was closely related to climate change and that global warming might lead to an expansion of its distribution area. These results would improve our understanding of the ecological adaptability of R. multiflora, facilitate the predicting of its future distribution, and provide a theoretical basis for monitoring and early warning measures following its introduction.

The dynamics of soil arthropod communities in annual monoculture grasslands is still unclear, which restricts the understanding of the degradation mechanism of cultivated grasslands. We cultivated two annual gramineae species, Lolium multiflorum and Avena sativa, separately in Hongyuan County, located on the eastern edge of the Qinghai-Tibet Plateau, in April 2019. We investigated soil arthropods, plant communities and soil properties in the cultivated grasslands and natural grassland in the late September every year from 2019 to 2022. The results showed that: 1) The taxonomic composition of soil arthropod communities differed significantly among three grasslands and sampling years. 2) There was no significant difference in the density, taxonomic richness, Shannon index and evenness index of soil arthropod communities among three grasslands. 3) The density of soil arthropod communities significantly fluctuated across years in three grasslands, and the taxonomic richness and Shannon index decreased significantly in the L. multiflorum and A. sativa grasslands, with the evenness index declining significantly only in the fourth year. The Shannon index fluctuated significantly and the evenness index varied little in natural grassland. 4) The above- and below-ground biomass, the contents of soil total P, total K and available N were the main factors influencing the taxonomic composition, density and diversity indices of soil arthropod communities. The results suggested that the cultivation of annual gramineae grasslands have significant effects on taxonomic composition, but not on density and diversity of soil arthropod communities, and those variables change significantly across different years.

Real-time assessment of ecological environment quality in arid and semi-arid regions is crucial for the sustainable development of ecological environments in China. In this study, we constructed a topsoil remote sensing ecological index (TRSEI) by coupling five indicators, greenness, wetness, dryness, topsoil grain size, and heat, with the Google Earth Engine (GEE). With the index, we evaluated the ecological environment quality of Wuchuan County from 1990 to 2020, and examined the spatio-temporal variations of ecological environment quality and its driving factors by using univariate linear regression, multiple regression residual analysis, and Hurst index. Results showed that the first principal component of the TRSEI in the study area contributed over 70%, with a mean eigenvalue of 0.148, indicating the effective integration of various ecological indicators by TRSEI. The topsoil grain size index was essential for the assessment of ecological environment quality in arid and semi-arid regions. From 1990 to 2020, the fluctuation range of TRSEI in the study area was between 0.289 and 0.458, showing an overall slight deterioration trend. The ecological environment quality of cropland and de-farming region had improved, with the improved area accounting for 47.9% of the total area. The grassland, barren land, and construction land areas had deteriorated, with the deteriorated area accounting for 52.1% of the total area. In the future, 36.9% of the regions would experience continuous improvement in ecological environment quality, while 41.4% might continue to dete-riorate. Human activities were the primary driving factor for the changes in ecological environment quality in arid and semi-arid regions, accounting for 88.6% of the total area. Climate change also had a significant impact, accounting for 11.4% of the total area. The TRSEI could effectively assess the ecological environment quality of arid and semi-arid regions, providing a scientific basis for ecological conservation and construction in these areas.

Clarifying vegetation changes and the driving factors can provide references for ecological restoration and sustainable social development. We analyzed vegetation distribution and trend changes in Henan Province and its basin zoning (Haihe River basin zoning, Yellow River basin zoning, Huaihe River basin zoning, Yangtze River basin zoning), with fractional vegetation cover data from 2000 to 2020 based on the Google Earth Engine platform, and by combining Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index. We also utilized factor detection and factor interaction to explore the individual and mutual influences of natural and anthropogenic factors on vegetation at different scales. The results showed that the fractional vegetation cover (FVC) in Henan Province exhibited a distribution pattern of higher coverage in the south and lower in the north during the study period, predominantly characterized by moderate to high vegetation coverage. The Yangtze River basin zoning had the highest coverage. FVC in Henan Province and its zoning exhibited a consistent pattern of fluctuating upward trends, with all areas showing significant improvement. Particularly, the Yangtze River basin zoning had the largest area of improvement. According to the Hurst index, apart from the possibility of continued improvement in the Huaihe River basin zoning, other zoning would be likely to shift from improvement to degradation in the future. Vegetation changes in Henan Province and its zoning were the result of combined effects of anthropogenic and natural factors, with the influence of these factors changing over time and the dominant factors varying by region. Anthropogenic factors such as land use/cover type and nighttime lighting had a stronger impact on vegetation than natural factors like elevation, slope, and annual mean low temperature. The interaction between factors, particularly between anthropogenic and natural factors, exhibited a nonlinear enhancing pattern.

In order to provide a guide for plant selection of ecological restoration at antimony (Sb) mining ecological damaged sites, species composition, importance value, niche, and interspecific associations of tree, shrub, and herb layers were examined at Sb mining site in Nandan City, Guangxi, China. The results showed that 23 vascular plant species were recorded at the Sb mining ecological damaged site, belonging to 22 genera and 13 families, primarily Gramineae, Cyperaceae, Fabaceae, and Asteraceae. The highest importance values for trees, shrubs, and herbs were observed in Rhus chinensis (56.7%), Coriaria nepalensis (56.3%), and Eremochloa ciliaris (44.0%), which were characterized by fairly large niche widths of 1.58, 1.32 and 1.57, respectively. The highest niche overlap values were found between R. chinensis and Triadica sebifera in the tree layer, and between Thysanolaena latifolia and Bidens pilosa in the herb layer, with the value of 0.68 and 0.99, respectively. Shrub layer exhibited a lower range of niche overlap (0.30-0.42), suggesting significant niche differentiation among different species. In the tree and shrub layers, most species showed insignificantly negative associations, the proportion was 83.3% and 66.7%, respectively, indicating that the plant community was not stable. Herb layer generally exhibited significantly positive correlations, with 52.4% of species pairs showing positive correlation, indicating weak resource competition among species. Overall, plant community at Sb mining ecological damaged site was unstable. In the process of ecological restoration, trees and shrubs that can adapt to the conditions and have positive associations should be prioritized in species selection, such as R. chinensis, C. lanceolata, C. nepalensis, and B. nivea. This will promote vegetation positive succession, rehabilitate the ecosystem and ensure sustainable development at Sb mining ecological damaged sites.

Wildlife resources are strategic resources of a country, and the investigation of which is a key task for effective management in protection and utilization. Since the 1990s, two national surveys of terrestrial wildlife resources have been carried out in China, and the situation of wildlife resources has been known to a certain extent. Due to the complexity and difficulty of national wildlife survey, we are still not able to grasp the background and dynamics of wildlife resources as a whole promptly and effectively. The results and effectiveness of wildlife resources investigation will directly affect the decision-making related in wildlife protection. According to Law of the People's Republic of China on the Protection of Wildlife and Regulations of the People's Republic of China for the Implementation of the Protection of Terrestrial Wildlife, it is imperative to carry out the third national survey of terrestrial wildlife resources, and to be integrated with the national strategy of ecological civilization construction. The aims of this review were to summarize the earlier experiences in time, to further improve the investigation scheme and technical methods, to serve the third national survey of terrestrial wildlife resources, in addition to obtain more comprehensive and reliable data of wildlife resources, grasp the development trend of domestic wildlife resources, and provide more effective supports for the wildlife conservation in China.

Rodent-infested bald spots are crucial indicators of rodent infestation in grasslands. Leveraging Unmanned Aerial Vehicle (UAV) remote sensing technology for discerning detrimental bald spots among plateau pikas has significant implications for assessing associated ecological hazards. Based on UAV-visible light imagery, we classified and recognized the characteristics of plateau pika habitats with five supervised classification algorithms, i.e., minimum distance classification (MinD), maximum likelihood classification (ML), support vector machine classification (SVM), Mahalanobis distance classification (MD), and neural network classification (NN) . The accuracy of the five methods was evaluated using a confusion matrix. Results showed that NN and SVM exhibited superior performance than other methods in identifying and classifying features indicative of plateau pika habitats. The mapping accuracy of NN for grassland and bald spots was 98.1% and 98.5%, respectively, with corresponding user accuracy was 98.8% and 97.7%. The overall model accuracy was 98.3%, with a Kappa coefficient of 0.97, reflecting minimal misclassification and omission errors. Through practical verification, NN exhibited good stability. In conclusion, the neural network method was suitable for identifying rodent-damaged bald spots within alpine meadows.

Pollination is one of the important ecosystem services related to sustainable development of human society. However, the population diversity and abundance of wild bees, important pollinators, have been significantly reduced by climate change, agricultural intensification, and landscape transformation. Re-establishment of pollinator habitat by planting nectar-producing plants is an important way to maintain pollination service. In this study, we investigated the status of wild bees and the traits of flowering plants in 22 apple orchards during flowering stage in Changping District, Beijing in 2019. We analyzed the response of wild bee diversity to the flowering plant richness, flower color richness, inflorescence type richness, flowering plant coverage, herbaceous layer coverage and different flower color coverage in apple orchards, aiming to provide guidance for the selection of nectar-producing plants to establish the habitat of wild bees. A total of 3517 wild bees were captured during the apple flowering season, representing 49 species, 13 genera, and 5 families. We identified 21 flowering plants species that shared a similar flo-wering period with apple, exhibiting a range of 5 colors and 9 inflorescence types. The Shannon diversity index, evenness index, and social bee richness of wild bee community were positively correlated with flowering plant richness. The total wild bee community richness, social bee richness, underground nesting bee richness were positively correlated with the richness of flowering plant color, but Halictidae bee abundance was negatively correlated with the richness of flowering plant color. The Shannon diversity index and evenness index of wild bee community were positively correlated with the richness of inflorescence types. Megachilidae bee richness was negative correlated with the white flower coverage. Megachilidae bee richness, social bee abundance, and ground nesting bee richness were positively correlated with the purple flower coverage. There was no significant correlation between wild bees and flowering plant richness, flower color richness, inflorescence type richness, flowering plant coverage, herbaceous layer coverage and different flower color coverage in other communities of different families, lifestyles and nesting types. Maintaining diverse ground flowering plants with various traits in orchards is important to improve the diversity of wild bees. In particular, increasing the coverage of purple flower during apple flowering period is helpful to promote the diversity of Megachilidae bee, social bees, and ground nesting bees.

The mechanism for water-saving and high-yield of wide-range precision sowing technology remains unclear. We investigated the impact of wide-range precision sowing on the physiological characteristics of root system, water consumption, and grain yield of wheat 'Jimai 22' during the growing seasons of 2017-2019. We set up two planting modes: wide precision sowing and conventional strip sowing, and three row spacings of 20 cm, 25 cm, and 30 cm under water-saving cultivation with supplemental irrigation to examine the effects of planting modes on root biomass and senescence characteristics of wheat, water utilization characteristics, interplant evaporation, grain yield, and water utilization efficiency. The results showed that the 25 cm treatment (K25) led to an increase in root weight density, root soluble protein content, and root activity by 7.2%-23.9%, 8.7%-25.1%, 10.7%-29.9%, and 7.3%-27.6%, 8.0%-38.5%, 15.2%-32.7%, respectively, compared to the other treatments. At the same row spacing, the wide-range precision sowing treatment showed a significantly higher soil water storage consumption and proportion to total water consumption compared to the conventional strip-tillage treatment. Additionally, irrigation and interplant evaporation were lower in the wide-range precision sowing treatment. The K25 treatment exhibited significantly higher water consumption and modal coefficient of water consumption from flowering to ripening than other treatments. Furthermore, it had significantly higher seed yield, water utilization efficiency, and irrigation utilization efficiency than the other treatments. We found that a 25 cm spacing in the lower rows and density of 180-270 plants·m^-2 was the water-saving and high-yielding planting pattern of wide-range precision sowing wheat in Huang-Huai-Hai region.

Plants could effectively adsorb and remove particulate matter from the air, while could be suffered from the adverse effects. Therefore, exploring the interaction between plants and atmospheric particulate matter is crucial for profound understanding of ecological balance, microenvironmental climate, and environmental quality improvement. Few systematic literature have elaborated the adsorption and response mechanisms of atmospheric particulate matter by plants. We summarized the causes and composition of atmospheric particulate matter, as well as the adsorption methods and factors of plants on atmospheric particulate matter. Moreover, we elaborated the impact of atmospheric particulate matter stress on phenotypic and physiological characteristics, as well as molecular mechanisms. For the future researches, we proposed 1) to select plant species with strong adaptability and high dust retention capacity. Subsequently, there should be a universal green dust retention plan on account of comprehensive factors such as plant community structure, street morphology, and planting space; 2) to extend the research from urban areas to agricultural and pastoral areas, with a systematic analysis of the comprehensive dust retention capacity of communities with different plant configuration; 3) to effectively combine the dust retention capacity of plants with their own resistance. Subsequently, we should explore the physiological and molecular mechanisms of plants responding to atmospheric particulate matter stress and establish a comprehensive evaluation system and criteria; 4) to develop in situ labeling detection technology, which would be a valuable tool for accurately tracing and quanti-fying the dynamics of atmospheric particulate matter within plant at the cellular level.