Applying specific habitat indicators to study Asteraceae species diversity patterns in mountainous area of Beijing, China

Applying specific habitat indicators to study Asteraceae species diversity patterns in mountainous area of Beijing, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Applying specific habitat indicators to study Asteraceae species diversity patterns in mountainous area of Beijing, China lin zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4039102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Determining the distribution pattern and drivers of specific species diversity is significant for predicting the response to biodiversity and formulating conservation programs to reduce biodiversity loss. How to apply regional habitat indicators to study specific species diversity patterns is a hot spot in recent years. In this study, we investigated 112 Asteraceae plants sample plots and explored the effects of topography, soil nutrients and stand factors on Asteraceae species diversity by using SEM model. And the responses of Asteraceae species diversity to specific habitat factors was simulated by Maxent model. The results shown that soil nutrients had the highest, but topography and canopy closure had the lowest relative contributions to the Asteraceae species diversity among these factors. Topography and soil nutrients affected Asteraceae species diversity by direct and indirect effects. The contribution rate of each potential environmental variable’s impact on the Asteraceae species diversity was ranked as the following: STN (29.7%)> SOC (28.5%) > slope (8.5%)> Ele (8.1%). Asteraceae species diversity was abundant at high SOC (＞27g/kg), STN (＞1.8 g/kg), low Ele (165–333 m) and gentle slopes (5–12 degrees). Our study indicates that the Asteraceae species diversity could as an indicator to reflect or evaluate the level of soil nutrient content. Asteraceae species habitat indicators biodiversity conservation Maxent Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The biodiversity maintenance function is one of the most important functions provided by ecosystems, and it plays an irreplaceable role in maintaining genetic, species and ecosystem diversity (Echiverri and Macdonald 2020; Bilal et al. 2018). Biodiversity is also the basis of other ecosystem service functions, which is related to human well-being, and it is an important foundation for human survival and sustainable development (Li et al. 2021; J. et al. 2022; Zhang et al. 2020). With the intensification of global climate change and the impact of human activities, biodiversity has been sharply reduced, and ecosystem protection is facing with unprecedented difficulties. Despite a lot of effort was made by countries around the world over the past decades, the mechanism of maintaining biodiversity remains controversial (Li et al. 2021; Jing. et al. 2022; Zhang et al. 2020). As an important part of forest ecosystem, understory herbaceous plants play an irreplaceable role in improving soil quality, maintaining ecosystem stability and promoting the coordinated development of forest ecosystem (Makse et al. 2020; Shi et al. 2022; Wei et al. 2020). Abundant plant diversity can not only maintain the stability of the ecosystem, but also promote the optimization of ecosystem functions(Markus et al. 2023; Cian et al. 2023; Li et al. 2022; Qian et al. 2022). Therefore, the maintenance mechanism of understory herbaceous plant diversity has become one of the core and hot issues of current ecological research, analyzing the effects of environmental factors and stand factors on understory herbaceous plant diversity can provide important theoretical guidance for the sustainable management of forests. The composition and distribution of understory species are the result of the comprehensive action of multiple environmental factors (Brodie et al. 2021; 2018; Pablo et al. 2018). Climatic factors such as temperature and precipitation are the most important factors affecting the growth and distribution of understory vegetation at large regional scale (Baohui et al. 2022; Donghai et al. 2015). In small areas of woodland, site type plays a decisive role in the growth and distribution of understory plants (Dong et al.2020;Wen et al.2020). Relevant studies have shown that site factors such as altitude, aspect, and slope were the most significant factors limiting the growth and diversity of understory vegetation (Han et al. 2022; Mi et al. 2022; Wan et al.2023). In addition, soil nutrients are also the main factors affecting the growth and distribution of understory plants, the level of soil nutrients directly determines the composition and distribution of understory species (Wu et al.2021; Wang et al.2021). In the current research, the research on understory species diversity mainly focuses on the effects of environmental factors on species composition and diversity, the effects of stand structure or stand types on understory species composition, the soil environment and ecological services improvement by understory species etc (Xian et al. 2020; Wei et al.2020; Cui et al.2022; Reza et al.2021). Most studies use statistical analysis methods to qualitatively analyze understory plant diversity and environmental variables, which makes it difficult to obtain the optimal distribution range of abundant plant diversity, and it is thus challenging to put forward accurate forest management strategies. A few scholars have paid attention to the significant role of understory specific species in indicating geographical environmental factors. Asteraceae plants , as the group with the largest number of invasive plants in China, it has a high economic value. Relevant studies have shown that the improvement of soil nutrients can promote the invasion and reproduction ability of Asteraceae plants (Xu et al., 2004; Tang et al., 2010). Therefore, we believe that the Asteraceae species diversity patterns can indicate the level of soil nutrient content. The main objectives of this study were (1) to study the main habitat factors affecting the Asteraceae species diversity, (2) determining the response of the abundant Asteraceae species diversity to soil nutrients, (3) predicting the distribution range of abundant Asteraceae species diversity. Materials And Methods 2.1 Study area The Beijing-Tianjin Sandstorm Source Phase II Forestry Project in Beijing city is mainly distributed in the mountainous areas, including Fangshan, Changping, Huairou, Miyun and Pinggu district. Beijing mountainous region is located in the north and west of Beijing(39°12’-41°05’N, 115°25’- 117°30’ E.), and the area is about 10,400 km 2 . The climate belongs to a warm temperate semi-humid monsoon region, with noticeable vertical differentiation. with an average annual precipitation from 470 to 660mm and an average yearly temperature is 11°C. Land use types are mainly woodland and grassland. Zonal soils are mainly meadow soil, mountainous brown forest soil and mountainous cinnamon soil. 2.2 Survey of Asteraceae plants Based on the Asteraceae species distribution data provided by the China National Earth Center, we selected 112 representative sample sites for investigation (as shown in Figure 1). We measured stand density, Canopy closure, elevation, aspect, slope, and geographic coordinates of the sample plots. We randomly collected ten soil samples from the 0-10 cm soil layer using a 100 cm 3 standard soil sampler. We randomly laid out ten 1 m × 1 m samples in each standard sample plot, and the names of Asteraceae plants and the number of plants of each species in each sample plot were recorded for calculating the diversity of its understory herbaceous plants. Table 1 Environmental and stand factors data of standard plots Environmental and stand factors Ranges Mean Standard deviation Elevation (m) 114-770 359.69 116.12 Slope (°) 3-39 18.81 10.02 Soil organic matte content (g/kg) 13.84-116.58 44.68 21.35 Soil total nitrogen content (g/kg) 0.98-6.58 2.97 1.25 Soil total phosphorus content (g/kg) 0.24-1.12 0.57 0.15 Soil total potassium content (g/kg) 9.25-40.72 20.25 6.06 Soil available nitrogen content (mg/kg) 91.57-415.24 135.39 80.62 Soil available phosphorus content (mg/kg) 0.09-4.005 6.91 1.59 Soil available potassium content (mg/kg) 37.533-444.82 1.01 0.34 Stand density (plant•hm -2 ) 500-1975 1035.18 286.71 Canopy closure 0.5-0.95 0.76 0.11 2.3.2 MaxEnt model The maximum entropy model is a spatial distribution model of species at the geographical scale based on the maximum entropy theory, which is a measurement of the maximum likelihood of the sample, and its core is to infer the location information through incomplete information and find the conditions when the probability reaches the maximum (Wen et al., 2021; Wang et al., 2024). The accuracy of the model was verified by using the receiver operating characteristic curve (ROC), and the accuracy was judged by calculating the area (AUC) enclosed by the curve and the abscissa (Liu et al., 2022; Zhou et al., 2023). Two sets of data are required for the operation of the maximum entropy model: one is the geographical distribution data of plant species, which is expressed by the latitude and longitude of each species; The second is the raster data of environmental factors in the study area, the elevation of Beijing is derived from the 30 m×30 m digital elevation model (DEM), the slope aspect and slope are extracted from the DEM (http://westdc.westgis.ac.cn), and the soil raster data is derived from the measured data of the sample plots. Results 3.1 The relationship between the Asteraceae species diversity indices The correlation of these diversity indices was shown in Figure 2. It can be seen that Shannon-Wiener index had the highest correlation with the other three indices, with R 2 of 0.87, 0.74 and 0.70. After comprehensive compared the correlations of these indices, we chose Shannon-Wiener index to measure the overall level of Asteraceae species diversity. 3.2 Effects of stand and environmental factors on Asteraceae species diversity The direct and indirect effects of elevation, slope, canopy closure and soil nutrient factors on understory plant diversity were shown in Figure 3.elevation and slope had a significant effect on the understory plant diversity ( P < 0.001), and canopy closure and soil nutrients significantly affected the understory diversity( P slope (-0.19) >elevation(-0.14) > canopy closure (-0.17), and the indirect effect was: elevation (-0.05) >slope (-0.02) > soil nutrients (-0.01). Overall, soil nutrients were the dominant factors affecting species diversity, with direct effects being the primary mechanism. Elevation, slope and canopy closure and also had important impacts on Asteraceae species diversity. Table 2 Standardized effects of these factors on the understory plant diversity. Impact factors Direct effect Indirect effect Total effect Elevation -0.14 -0.05 -0.19 Slope -0.19 -0.02 -0.21 Canopy closure -0.11 - -0.11 Soil nutrient 0.58 0.01 0.59 3.3 Maximum entropy model results In this study, the Shannon-Wiener diversity index ranges from 0.27 to 2.01, the average value is 1.01, a screening value equal to the average Asteraceae species diversity at sample sites was determined, and those values beyond this screening value were considered the sample plots with abundant Asteraceae species diversity. A total of 49 sample sites were selected for use as point data in the MaxEnt model. The MaxEnt model was constructed based on all environmental factors to obtain ROC curves, as shown in Figure. 3. The contribution rate of each potential environmental variable’s impact on the Asteraceae species diversity was ranked as the following: soil total nitrogen (29.7%)> soil organic matter (28.5%)> slope (8.5%)> elevation (8.1%), and the cumulative contribution rate is 74.8% (Table 4). The contribution rate of other environmental variables was between 3.5% and 4.9%, which had little impact. The above analysis shows that the main environmental variables that affect the Asteraceae species diversity were soil nutrient factors (soil organic matter and soil total nitrogen), of which the cumulative contribution rate of topography factors was 58.2%. Taking the probability of existence greater than 0.7 as the threshold value. The contribution rate of SOC was the highest among soil factors, reaching 28.5%, when the soil organic matter content was greater than 27 g/kg, the probability of existence was greater than 0.7. It shows that when the soil total nitrogen content was greater than 27g/kg, the contribution rate of soil total nitrogen in soil variables ranked second, that is 29.7%. It can be seen from Figure. 5 that when the total nitrogen content was greater than 1.8 g/kg, the probability of existence was greater than 0.7; when the total nitrogen content was 2 g/kg, it reaches the peak and remains unchanged. Obviously, it was suitable for the distribution of abundant Asteraceae species diversity level when the total nitrogen content of soil was more than 1.8 g/kg. Moreover, the probability distribution remains the largest when it reaches 2g/kg. Elevation contributed the most to the herbaceous productivity, reaching 39.7%. It can be seen from Figure. 4 that when the elevation ranges from 165 to 333 m, the probability of existence was greater than 0.7. The probability of existence reaches the peak at about 230 m, indicating that low mountain areas were most suitable for the Asteraceae species growth; when the elevation was less than 100m or more than 500m, the probability of existence decreases, indicating that these two elevations were not conducive to their distribution. The contribution rate of the slope degree to the herbaceous diversity was 18.5%. It can be seen from Figure. 4 that when the slope range was 5 to 12°, the probability of existence is greater than 0.7. The probability of existence reaches the peak value when the slope degree was about 8 degrees, indicating that the gentle slope area was most suitable for their distribution; when the slope degree was less than 2 degrees or more than 22 degrees, there was a rapid decline in the probability, indicating that the two slopes were not conducive to their distribution. Table 4 Contribution and cumulative contributions of environmental factors to the herbaceous diversity Variable factors Contribution rate (%) Cumulative contribution rate (%) Elevation 29.7 29.7 Slope 28.5 58.2 SOC 8.5 66.7 STN 8.1 74.8 SAN 4.9 79.7 Aspect 4.7 84.4 SAP 4.4 88.8 SAP 3.9 92.7 STP 3.5 96.2 Discussion This study found that the soil organic matter and soil total nitrogen content were the dominant soil factors affecting the Asteraceae species diversity, with a cumulative contribution rate of 58.4%. The main reason was that soil organic matter contains various nutrients required for plant growth, which was one of the main sources of vegetation nutrition and can promote the growth and development of plants (Wu et al., 2021). A large amount of nitrogen is necessary for plant growth. Its abundance, shortage, and supply directly affect the growth level of plants (Tan et al., 2023). When the soil organic matter content was less than 27g/kg and total nitrogen content was less than 1.8 g/kg, the probability of the existence with abundant Asteraceae species diversity decreases rapidly. Therefore, for the land with a soil organic matter content less than 27g/kg and soil total nitrogen content less than 1.8g/kg in the Beijing Mountain area, a reasonable application of organic fertilizer and nitrogen fertilizer is conducive to increasing the Asteraceae species diversity. Our results indicated that the change of soil nutrients would affect the suitability distribution of some specific species, and the appearance of some Asteraceae species is the sign for soil nutrient improvement, these findings have same conclusions with relevant studies (Xu et al., 2004; Tang et al., 2010; Jia et al., 2015). In this study, we found that topographic factors (elevation and slope) were the important factors affecting Asteraceae species diversity, with a cumulative contribution rate of 16.6%. Topographic factors such as altitude, slope and aspect have a great influence on species distribution, mainly because they are the fundamental factors affecting energy and material variation at the site scale. Altitude is the most common environmental factor used to explain species diversity differences, and many studies have suggested that it is the first influencing factor on the composition and distribution of shrub and herbaceous, and species distribution shows obvious differences along the altitudinal gradient, which is consistent with the results of this study. In general, the influence of slope on species diversity is the second only to that of altitude and the influence of aspect relatively is small. In addition, we found that canopy closure was also an important factor affecting Asteraceae species diversity, and Wagner et al (2011) also concluded that the canopy closure was the main stand factor governing the diversity and productivity of understory herbaceous, which was basically consistent with the findings of this study, probably because the canopy closure directly determines the effective light intensity within the forest, which has a redistributive effect on the resources of light, heat, water and fertilizer in the forest, thus directly affecting the distribution and individual growth of understory herbaceous species, especially for some sun-loving and non-shade tolerant plants (Chavzv et al., 2012). On the other hand, in low-density forests, the increase in light intensity promoted the decomposition of understory litter and soil microbial activities, accelerated the formation of soil organic matter, which in turn facilitated the absorption of more soil nutrients by herbaceous plants, thus indirectly changing the composition and growth of understory herbaceous species (Chastain et al., 2006; Sabatini et al., 2014). Conclusion Soil nutrient was the main factors affecting the Asteraceae species diversity, the total impact effect was 0.59. slope and elevation factors had a significant effect on herbaceous diversity, the total impact effect is -0.11and -0.19. The contribution rate of each potential environmental variable’s impact on the Asteraceae species diversity was ranked as the following: STN (29.7%)> SOC (28.5%) > slope (8.5%)> Ele (8.1%). Asteraceae species diversity was abundant at high SOC (＞27g/kg), STN (＞1.8 g/kg), low Ele (165–333 m) and gentle slopes (5–12 degrees). References Amale, M., Leila, K., Souad, N., Haroun,C..2021. Environmental drivers of taxonomic and phylogenetic diversity patterns of plant communities in semi-arid steppe rangelands of North Africa. Remote Sensing132. Bilal, A.,Wang,Y., Jia, H., Liu,Y., Eve, B., Zhang,K.,2018. Optimizing stand structure for trade‐offs between overstory timber production and understory plant diversity: A case‐study of a larch plantation in northwest China. Land Degradation & Development 29. Brodie, E.G., Miller, J., Safford. H.D.. 2021. Productivity modifies the effects of fire severity on understory diversity. Ecology. Cao,X.Y., Zhao, W.F., Li,J.P., Yan,W.D., Pang, Y.F., Sun, Y.P., Xie, Z.C.. 2022. Soil nutrient content analysis and comprehensive evaluation of several typical forests in the Middle subtropical region. Acta Ecologica Sinica 42(09):3525-3535. Chao ,M., Jun ,W., Sheng, L.J.. 2023. Utilization of soil and fertilizer nitrogen supply under mulched drip irrigation with various water qualities in arid regions. Agricultural Water Management. 280. Chastain,R.A.,Currie, W.S., Townsend,P.A..2006. Carbon sequestration and nutrient cycling implications of the evergreen understory layer in Appalachian forests. Forest Ecology and Management.231(1). Chen, M.H., Zeng. S.D., Bo, J., Wen, Z.F., Wu. J., Xia, J.. 2023. The comprehensive evaluation of how water level fluctuation and temperature change affect vegetation cover variations at a lake of ecological importance (Poyang Lake), China. Ecological Indicators. 148. Chávez,V., Macdonald.E.S.,Partitioning vascular understory diversity in mixedwood boreal forests: The importance of mixed canopies for diversity conservation[J]. Forest Ecology and Management,2012,271. Cian, B., Olivier, C., Didier, A., Manuella, C., Sylvain, D., Thierry, D., Jérôme, L., Grégory, L., Alice, M., Marine, P., Antoine, T., Servane, L., Anne,B.. 2023. Forage nutritive value shows synergies with plant diversity in a wide range of semi-natural grassland habitats. Agriculture, Ecosystems and Environment 347. Cui,R.R.,Qi,S.,Wu,B.C.,Zhang,D.,Zhang,L.,Zhou, P.,Ma,N,Huang,X., The Influence of Stand Structure on Understory Herbaceous Plants Species Diversity of Platycladus orientalis Plantations in Beijing, China[J]. Forests,2022,13(11). Dong,D.,Ashfaq ,A., Huang,X., Teng,M.J., Wu,C.G.,Zhou,Z.X., Liu,Yu..Soil Available Phosphorus Loss Caused by Periodical Understory Management Reduce Understory Plant Diversity in a Northern Subtropical Pinus massoniana Plantation Chronosequence[J]. Forests,2020,11(2). Echiverri,L.,and S.E. Macdonald. 2020. A topographic moisture index explains understory vegetation response to retention harvesting. Forest Ecology and Management, 474:118358. Gautam, M.K., Manhas, R.K., Tripathi A.K..2016. Overstory structure and soil nutrients effect on plant diversity in unmanaged moist tropical forest. Acta Oecologica 75. Han,W.J.,Chen,D.H. Hu,L., Zhu, C., Chen ,J,,Ye L.Z.,Liu ,S.S., Zuo. W.,Spatiotemporal Variation of NDVI in Anhui Province from 2001 to 2019 and Its Response to Climatic Factors[J]. Forests,2022,13(10). He,Y.Y.,Yu M.H.,Ding,G.D,Wang,C.Y.,Zhang, F.C.. Precipitation amount and event intervals interact to change plant diversity during dry years in a desert shrubland[J]. Ecological Indicators,2022,145. Hou, G.R., Bi, Huo,Y.M.,Wei,X.Y., Zhu, Y.J., Wang, X.X., Liao,W.C.. 2020. Determining the optimal vegetation coverage for controlling soil erosion in Cynodon dactylon grassland in North China. Journal of Cleaner Production, 244(C). Huang, Y.Y., Chen ,Y.X., Nadia,C.I. .2018. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362(6410):80-83. He, K.J., Huang.,Y.M., Qi,Y., Sheng,Z.L., Chen. H.Y., 2021. Effects of nitrogen addition on vegetation and soil and its linkages to plant diversity and productivity in a semi-arid steppe. Science of the Total Environment, 778. He, Y .Y., Yu. M.H., Ding ,G.D., Wang,C.Y., Zhang. F.C.. 2022. Precipitation amount and event intervals interact to change plant diversity during dry years in a desert shrubland. ECOL INDIC 145. Han,W.J., Chen, D.H., Hu, L.,Chang. Z., Chen,J., Ye. L.Z., Liu. S.S., Wang,Z.. 2022a. Spatiotemporal Variation of NDVI in Anhui Province from 2001 to 2019 and Its Response to Climatic Factors. Forests. 13(10). Hu, D., Lv, G.H., Wang, H.F., Yang, Q., Cai, Y.. 2021. Responses of desert plant diversity and stability to soil factors under water gradient. Acta Ecologica Sinica 41(17):6738-6748. Huang, Q.Y., Cao, H.J., Xie ,L.H., Luo, C.Y., Yang, F., Wang, L.M., Ni,H,W.. 2020. Species diversity and environmental interpretation of herbaceous layer in the lava platform of Wudalianchi Volcano. Biological Diversity 28(06):658-667. Iqra, P., Iftikhar, A., Mansoor, H., Aqeel,A.M.S..2023. Plasticity in anatomical traits of;Cyperus niveus;Retz. along elevational gradient of dry sub-Himalayan mountains. Arid Land Research and Management, 37(2). Jian, S.Q.,Zhang.,Q.K., Wang. H.L.. 2022. Spatial–Temporal Trends in and Attribution Analysis of Vegetation Change in the Yellow River Basin, China. Remote Sensing. 14(18). Joseph,O.,Marijn,B., Hans,V., Samuel,B., John,K., Astrid,F.,Till,E., Klaus,B.B., Ralf,K., Pascal.,B.. Temperature sensitivity of soil organic carbon respiration along a forested elevation gradient in the Rwenzori Mountains, Uganda[J]. Biogeosciences,2023,20(3). Lan, G.Y., Chen, B.Q., Yang,C., Sun. R., Wu, Z.X., Zhang. X.C..2022. Main drivers of plant diversity patterns of rubber plantations in the Greater Mekong Subregion. Biogeosciences, 19(7). Lea, V., Shiro.T.. 2022. Differences in canopy and understorey diversities after the eruptions of Mount Usu, northern Japan — Impacts of early forest management. FOREST ECOL MANAG 510. Lei,B.Y., Tian,Y.Y., Cui,J.F., Zhao,J., Zhou,Y.B.. 2023. Effects of plant species richness on the structure of plant-bird interaction networks along a 3000-m elevational gradient in subtropical forests. Forest Ecology and Management.532. Li ,Y.,Wang ,J.,Shen ,CC.,Wang, J.C.,Singh,B. K.,Ge, Y.. Plant diversity improves resistance of plant biomass and soil microbial communities to drought[J]. Journal of Ecology,2022,110(7). Li, X.K., Li, Y.N., Zhang, J.. Peng, S.Z. Chen, Y.M. Yang,C.. The effects of forest thinning on understory diversity in China: A meta‐analysis[J]. Land Degradation & Development,2020,31(10). Li, T.T., Tang, Y.B., Zhou, R.H., Yu, F.Y., Dong, H.J., Wang, M., Hao, J,F.. 2021. Relationship between understory plant diversity and soil physicochemical properties of different plantations in Genting Mountain. Acta Ecologica Sinica 41(03):1168-1177. Li, T.F., Kamran,M., Chang, S.H., Peng, Z.C., Wang.,Z.F., Ran,.L.J., Qi, J.W.,Jin.,Y.S., Zhang,X.Y., Yang, Y., Lan, L., Hou,F.J.. 2022. Climate-soil interactions improve the stability of grassland ecosystem by driving alpine plant diversity. Ecological Indicators. 141. Liang, W.J., Wei ,Xi.. Relationships between ecosystems above and below ground including forest structure, herb diversity and soil properties in the mountainous area of Northern China[J]. Global Ecology and Conservation,2020,24. Lin, L., Dai, L., Lin, Z. T., Wu, J.T., Yan, W., Wang, Z.J.. 2021. Relationship between plant diversity and soil physicochemical properties in urban forest communities in central Guizhou. Journal of Ecology and Environment 30(11):2130-2141. Lin, S.Y.,Zhao. L., Feng, J. L.,2022. Predicted changes in the distribution of Antarctic krill in the Cosmonaut Sea under future climate change scenarios. Ecological Indicators.142. Liu, C., Li, W., Wang, W., Zhou, H., Liang, T., Hou, F., Xu, J., Xue, P.. Quantitative spatial analysis of vegetation dynamics and potential driving factors in a typical alpine region on the northeastern Tibetan Plateau using the Google Earth Engine. Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution.2021. (206-):206. Luo, Y.S., Zhou, M.L., Jin S.S., Wang,Q.X., Yan,D.F.. 2023. Changes in phylogenetic structure and species composition of woody plant communities across an elevational gradient in the southern Taihang Mountains, China. Global Ecology and Conservation,42. Lv,K.T., Zhou. M.L., Ding, Y., Zang. R.G., Yao, J., Luo. Y.S., Yan. D.F.. 2023. Regeneration characteristics and influencing factors of woody plant on natural evergreen secondary broad-leaved forests in the subtropical, China. Global Ecology and Conservation, 42. Lotte, K., Harald, A., Jonathan,C.M., Stanley, H.W., Tiffany,K.M., Responses of plant diversity to precipitation change are strongest at local spatial scales and in drylands. Nature Communications. 2021.12(1). Mi, J., Ou, J., Liu, H., Shi, J., Chen,D.M., Bai,.Y.F.. 2022. The loss of plant species diversity dominated by temperature promotes local productivity in the steppe of eastern Inner Mongolia. Ecological Indicators, 139. Makse, H.A., Lucini, F.A., Morone, F., Tomassone,M.S.. 2020. Diversity increases the stability of ecosystems. Cold Spring Harbor Laboratory(4). Markus, L., Nico, E., Hongmei, C., Gerd.,G.. 2023. Increased soil carbon storage through plant diversity strengthens with time and extends into the subsoil. Global change biology. Mi,J.,Ou,J.,Liu ,H.,Shi, J.,Chen, D.M.,Bai,Y.F..The loss of plant species diversity dominated by temperature promotes local productivity in the steppe of eastern Inner Mongolia[J]. Ecological Indicators,2022,139. Mu ,B.H., Zhao,X., Zhao,J.C., Liu,N.J., Si,L.P., Wang,Q., Sun,Na., Sun,M.M., Guo,Y.K., Zhao,S.Q. 2022. Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities. Remote Sensing 14(4). Monika, M., Łukasz, C., Paweł, P., Elżbieta, R., Marcin, S., Małgorzata.,S.. 2023. Potential role of high-altitude wetlands in preservation of plant biodiversity under changing climatic conditions in the arid Eastern Pamir. Catena 220(PA). Mulatijiang, C., Ekbair, I., Amanullah, I.. 2022. Effects of slope aspect and elevation on plant community characteristics and species diversity of grassland in Wusun Mountain. Xinjiang Agricultural Sciences 59(11):2724-2733. Pablo, G., Nicolas, G., Juan, G., Maestre.,F.T.,2018. Climate mediates the biodiversity–ecosystem stability relationship globally. Proceedings of the National Academy of ences 115:201800425. Pan, H.H., Wang,J.Q., Du,Z.Q., Wu. Z.T., Hong, Z., Ma, K.M., 2023. Spatiotemporal evolution of ecosystem services and its potential drivers in coalfields of Shanxi Province, China. Ecological Indicators,148. Qian,Z.Y.,Gu,R., Gao, K., Li,D.J.. 2022. High plant species diversity enhances lignin accumulation in a subtropical forest of southwest China. The Science of the total environment 865. Rebecca, F., B.T.B. B, B. Jayne, G.E. L, G.E. E, H.D. L, R. Sasha, Michael.D. C.. 2023. Droughting a megadrought: ecological consequences of a decade of experimental drought atop aridification on the Colorado Plateau. Global change biology.. Ravhel,J.S.,Ryan, B., Morald,T., Richard,J. H., Suzanne,M.P.2022. Contribution of species and functional richness to carbon storage in eucalypt woodland restoration. Forest Ecology and Management 523. Reza, E., Moslem, Y., Mosleh,A.A.,Effect of different shrub species on their sub‐canopy soil and vegetation properties in semiarid regions[J]. Land Degradation & Development,2021,32(11). Sabatini, F., Jiménez-Alfaro, B., Burrascano, S., Blasi,C..2014. Drivers of herb-layer species diversity in two unmanaged temperate forests in northern Spain. Community Ecology 15(2). Sheng, W., Ren, S., Yu, G., Fang, H., Jiang, C., Mi.,Z.. 2011. Patterns and driving factors of WUE and NUE in natural forest ecosystems along the North-South Transect of Eastern China. Journal of Geographical Sciences. 21(4):651-665. Shi X.D., Wang. J.W., Zhang. L., Chen, S.X., Zhao. A.L., Ning. X.D., Fan, G.R., Wu,N.S., Zhang L., Wang. Z.D.. 2023. Prediction of the potentially suitable areas of Litsea cubeba in China based on future climate change using the optimized MaxEnt model. Ecological Indicators. 148. Shi, P., Li, P. , Li, Z. , Sun, J., Wang, D., Min, Z.. 2022. Effects of grass vegetation coverage and position on runoff and sediment yields on the slope of Loess Plateau, China. Agricultural Water Management. 259. Tiit,H., Kadri, T., Indrek, M., Katrin. H., How is plant biodiversity inside grassland type related to economic and ecosystem services: An Estonian case study[J]. Agriculture, Ecosystems and Environment,2023,349. T., M.A.D., T.L.R. Dongmo, I.D. J., B.V. A., N.I.C. NFOR, and M.T. B. 2023. Maximum entropy modeling of giant pangolin Smutsia gigantea (Illiger, 1815) habitat suitability in a protected forest-savannah transition area of central Cameroon. Global Ecology and Conservation.43. Vanhellemont, Margot, Baeten, Lander, Verheyen, and Kris. 2014. Relating changes in understorey diversity to environmental drivers in an ancient forest in northern Belgium. Plant Ecology and Evolution. 147(1). Wang,G.R., Sun,Y., Zhou,M., Guan, N.Q., Wang, Y.W., Jiang, R.H., Liu, Z.Y., Wu, M.G., Xia. F.C.,Effect of thinning intensity on understory herbaceous diversity and biomass in mixed coniferous and broad-leaved forests of Changbai Mountain[J].Forest Ecosystems,2021,8(04):713-725. Wang, J., Zhao, W.W., Zhang, X., Liu, Y., Wang, S., Liu, Y.X.. Effects of reforestation on plant species diversity on the Loess Plateau of China: A case study in Danangou catchment[J]. Science of the Total Environment,2019,651(Pt 1). Wang, D. J., Han, G. J., Gao, Z. H., Wang Y G. 2020. Response of plant community species diversity to altitude gradient in Lianhua Mountain, Gansu Province. Journal of Northwest Forestry College 35(06):96-102. Wagner, S., Fischer, H., Huth, F., 2011. Canopy effects on vegetation caused by harvesting and regeneration treatments. European Journal of Forest Research.130(1). Wani,Z.A.,Negi,V.S.,Bhat, J. A.,Satish ,K.V.,Kumar,A.,Khan,S.,Dhyani,R,, Sazada, S., Rahmah, A,Q.N., Shreekar ,P.. Elevation, aspect, and habitat heterogeneity determine plant diversity and compositional patterns in the Kashmir Himalaya [J]. Frontiers in Forests and Global Change,2023.Influence of environmental factors on tree species diversity and composition in the Indian western Himalaya. Wei, L., Archaux, F., Hu, F. l., Bilger, I., Gosselin,F.. 2020. Stand attributes or soil micro-environment exert greater influence than management type on understory plant diversity in even-aged oak high forests. Forest Ecology and Management 460(C). Wei, X., Bi, H.X. Liang, W.J., Hou, G.R., Kong, L.X., Zhou. Q.Z. 2018. Relationship between Soil Characteristics and Stand Structure of Robinia pseudoacacia L. and Pinus tabulaeformis Carr. Mixed Plantations in the Caijiachuan Watershed: An Application of Structural Equation Modeling. Forests. 9(3). Wei,L.P.,Frédéric,A.,Florian,H.,Isabelle, B.,Frédéric,G.. Stand attributes or soil micro-environment exert greater influence than management type on understory plant diversity in even-aged oak high forests[J]. Forest Ecology and Management,2020,460(C). Wu,D.H., Zhao,X., Liang,S.L., Zhou,T., Huang.,K.C., Tang,B.J., Zhao,W.Q., 2015. Time-lag effects of global vegetation responses to climate change. Global change biology 21(9). Wu,B.C.,Zhou,L.J.,Qi ,S.,Jin,M.L.,Hu,J.,Lu J.S.. Effect of habitat factors on the understory plant diversity of Platycladus orientalis plantations in Beijing mountainous areas based on MaxEnt model[J]. Ecological Indicators,2021,129. Wang,S.A., Li. R.P., Wu,Y.J., Wang,W.J..2023. Estimation of surface soil moisture by combining a structural equation model and an artificial neural network (SEM-ANN). The Science of the total environment 876. Yang, S.L., Wang. H.M., Tong,J.G., Bai,Y., Juha. M .A., Liu. G., Zhou, F.. Zhou.,F.. 2022. Impacts of environment and human activity on grid-scale land cropping suitability and optimization of planting structure, measured based on the MaxEnt model. The Science of the total environment 836. Zhang, T, Ding, G.J., Z. Jiangping, and Q. Yujiao. 2023. Stand, plot characteristics, and tree species diversity jointly dominate the recruitment biomass of subtropical forests. Forest Ecology and Management. 531. Zhang, X., Li. X., Ji.,X.D., Zhang,Z.Q., Zahng,H.S., Zha, T.G., Li. J.. 2021. Elevation and total nitrogen are the critical factors that control the spatial distribution of soil organic carbon content in the shrubland on the Bashang Plateau, China. Catena 204. Zhao,X.F., Lei. M., Wei. C.H., Guo. X.X.. 2022. Assessing the suitable regions and the key factors for three Cd-accumulating plants (Sedum alfredii, Phytolacca americana, and Hylotelephium spectabile) in China using MaxEnt model. The Science of the total environment 852. Zhang,Y.X., Z., Sun. J.Y., Song, X.Q., Lu. Y.F.. 2023. Revealing the main factors affecting global forest change at distinct altitude gradients. Ecological Indicators. 148. Zhao,X.N., Zheng,Y.T.,Wei,W.. 2023. Habitat Suitability Evaluation of Different Forest Species in Lvliang Mountain by Combining Prior Knowledge and MaxEnt Model. Forests. 14(2). Zilliox, C., Gosselin,F.. 2014. Tree species diversity and abundance as indicators of understory diversity in French mountain forests: Variations of the relationship in geographical and ecological space. FOREST ECOL MANAG 321. Zhang,Li., Qi, S., Zhou, P., Wu, B.C., Zhang, D., Cui, R.R., Huang, X., Ma, N.. 2022. Influencing factors on herb diversity of Platycladus platycladus understory in Beijing Mountain area. Journal of Grassland Science 30(8):8. Zhang, Y.Q., Li, Z.C., Hou, L.Y., Song, L.G., Yang, H.G., Sun, Q.W.. 2020. Effects of stand density on understory species diversity and soil nutrients of Chinese fir plantation. Acta Pedologica Sinica 57(01):239-250. Zhang, Q.P., Fang,R.Y., Deng, C.Y., Zhao,H.J., Shen, M.H., Wang,Q.. 2022. Slope aspect effects on plant community characteristics and soil properties of alpine meadows on Eastern Qinghai-Tibetan plateau. Ecological Indicators. 143. Zu,K.L., Zhang,C.C., Chen,F.S., Shahid, A., Ghulam, N., 2023. Latitudinal gradients of angiosperm plant diversity and phylogenetic structure in China’s nature reserves. Global Ecology and Conservation, 42. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4039102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278356802,"identity":"0a9ccc3d-5797-488e-a262-fe96bd8f85af","order_by":0,"name":"lin zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBACNvbmgw8+VNgw27c3HyBOCx/PsWTDGWfS2A14jiUQp0VOIsdMmrftML+BRI4BkQ7jOWAgObONWdpcIufjjTcMdnK6DYS0sDckGHw4x2Zs2fN2s+UchmRjswOEbTmQOKOMJ5nheO42aR6GA4nbCGqRSGw4zMMmUd9wIOcZsVqSGZt52gyYDU7ksBGphecYM+OMMwnMkj3HjC3nGBDhF/n2/u8/PlT8Z+Znb354402FnRxBLShAgofIqEHWQqqOUTAKRsEoGBEAAO3tRBXxV8+eAAAAAElFTkSuQmCC","orcid":"","institution":"Beijing Forestry University","correspondingAuthor":true,"prefix":"","firstName":"lin","middleName":"","lastName":"zhang","suffix":""}],"badges":[],"createdAt":"2024-03-08 07:46:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4039102/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4039102/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52592433,"identity":"13a78a53-0669-4818-bb58-b1fab1db8b27","added_by":"auto","created_at":"2024-03-13 10:59:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":146612,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study area\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/9904cd7b50010dabbbf5b1da.png"},{"id":52592431,"identity":"d919fe3c-25e5-448c-907f-ec749a5f07db","added_by":"auto","created_at":"2024-03-13 10:59:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":355883,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of the four herbaceous diversity indices\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/2b619db890e0d18463b425a9.png"},{"id":52592434,"identity":"e955ce7c-0f43-478c-8b6c-8eb39ca44821","added_by":"auto","created_at":"2024-03-13 10:59:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":94747,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of elevation, slope, canopy closure and soil nutrient factors on Asteraceae species diversity (CMIN/DF=1.1, CFI=0.99, RSMEA=0.03)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/b57b25b5acb8f018408d4068.png"},{"id":52592729,"identity":"6e26b84f-af91-4e9e-a8d4-55e63275bbed","added_by":"auto","created_at":"2024-03-13 11:07:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48372,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. 3.\u003c/strong\u003e ROC curve\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/b398857bbec6a2599a75954f.png"},{"id":52592435,"identity":"e8221743-0df4-4965-9b48-eea684881b07","added_by":"auto","created_at":"2024-03-13 10:59:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84699,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4. Response curve of the existence probability of abundant Asteraceae species diversity areas in relation to environmental factors.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/a647895a9e9bbcc59082c958.png"},{"id":52637410,"identity":"6d3cfc54-29c0-41e4-acd3-bc8cc6c76e75","added_by":"auto","created_at":"2024-03-14 00:07:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":643424,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4039102/v1/4f1ee63d-9ce6-46ff-9ae8-ec13eb2fa651.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Applying specific habitat indicators to study Asteraceae species diversity patterns in mountainous area of Beijing, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe biodiversity maintenance function is one of the most important functions provided by ecosystems, and it plays an irreplaceable role in maintaining genetic, species and ecosystem diversity (Echiverri and Macdonald 2020; Bilal et al. 2018). Biodiversity is also the basis of other ecosystem service functions, which is related to human well-being, and it is an important foundation for human survival and sustainable development\u0026nbsp;(Li et al. 2021; J. et al. 2022; Zhang et al. 2020). With the intensification of global climate change and the impact of human activities, biodiversity has been sharply reduced, and ecosystem protection is facing with unprecedented difficulties. Despite a lot of effort was made by countries around the world over the past decades, the mechanism of maintaining biodiversity remains controversial\u0026nbsp;(Li et al. 2021; Jing. et al. 2022; Zhang et al. 2020). As an important part of forest ecosystem, understory herbaceous plants play an irreplaceable role in improving soil quality, maintaining ecosystem stability and promoting the coordinated development of forest ecosystem\u0026nbsp;(Makse et al. 2020; Shi et al. 2022; Wei et al. 2020). Abundant plant diversity can not only maintain the stability of the ecosystem, but also promote the optimization of ecosystem functions(Markus et al. 2023; Cian et al. 2023; Li et al. 2022; Qian et al. 2022). Therefore, the maintenance mechanism of understory herbaceous plant diversity has become one of the core and hot issues of current ecological research, analyzing the effects of environmental factors and stand factors on understory herbaceous plant diversity can provide important theoretical guidance for the sustainable management of forests.\u003c/p\u003e\n\u003cp\u003eThe composition and distribution of understory species are the result of the comprehensive action of multiple environmental factors\u0026nbsp;(Brodie et al. 2021; 2018; Pablo et al. 2018). Climatic factors such as temperature and precipitation are the most important factors affecting the growth and distribution of understory vegetation at large regional scale\u0026nbsp;(Baohui et al. 2022; Donghai et al. 2015). In small areas of woodland, site type plays a decisive role in the growth and distribution of understory plants (Dong et al.2020;Wen et al.2020). Relevant studies have shown that site factors such as altitude, aspect, and slope were the most significant factors limiting the growth and diversity of understory vegetation (Han et al. 2022; Mi et al. 2022; Wan et al.2023). In addition, soil nutrients are also the main factors affecting the growth and distribution of understory plants, the level of soil nutrients directly determines the composition and distribution of understory species (Wu et al.2021; Wang et al.2021). In the current research, the research on understory species diversity mainly focuses on the effects of environmental factors on species composition and diversity, the effects of stand structure or stand types on understory species composition, the soil environment and ecological services improvement by understory species etc (Xian et al. 2020; Wei et al.2020; Cui et al.2022; Reza et al.2021). Most studies use statistical analysis methods to qualitatively analyze understory plant diversity and environmental variables, which makes it difficult to obtain the optimal distribution range of abundant plant diversity, and it is thus challenging to put forward accurate forest management strategies. A few scholars have paid attention to the significant role of understory specific species in indicating geographical environmental factors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAsteraceae\u0026nbsp;\u003c/em\u003eplants\u003cem\u003e,\u0026nbsp;\u003c/em\u003eas the group with the largest number of invasive plants in China, it has a high economic value.\u0026nbsp;Relevant studies have shown that the improvement of soil nutrients can promote the invasion and reproduction ability of Asteraceae plants (Xu et al., 2004; Tang et al., 2010).\u0026nbsp;Therefore, we believe that the\u0026nbsp;Asteraceae species diversity patterns can indicate the level of soil nutrient content.\u003cem\u003e\u0026nbsp;\u003c/em\u003eThe main objectives of this study were (1) to study the main habitat factors affecting the Asteraceae species diversity, (2) determining the response of the abundant Asteraceae species diversity to soil nutrients, (3) predicting the distribution range of abundant Asteraceae species diversity.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e2.1 Study area\u003c/p\u003e\n\u003cp\u003eThe Beijing-Tianjin Sandstorm Source Phase II Forestry Project in Beijing city is mainly distributed in the mountainous areas, including Fangshan, Changping, Huairou, Miyun and Pinggu district. Beijing mountainous region is located in the north and west of Beijing(39\u0026deg;12\u0026rsquo;-41\u0026deg;05\u0026rsquo;N, 115\u0026deg;25\u0026rsquo;- 117\u0026deg;30\u0026rsquo; E.), and the area is about 10,400 km\u003csup\u003e2\u003c/sup\u003e. The climate belongs to a warm temperate semi-humid monsoon region, with noticeable vertical differentiation. with an average annual precipitation from 470 to 660mm and an average yearly temperature is 11\u0026deg;C. Land use types are mainly woodland and grassland. Zonal soils are mainly meadow soil, mountainous brown forest soil and mountainous cinnamon soil.\u003c/p\u003e\n\u003cp\u003e2.2 Survey of Asteraceae plants\u003c/p\u003e\n\u003cp\u003eBased on the Asteraceae species distribution data provided by the China National Earth Center, we selected 112 representative sample sites for investigation (as shown in Figure 1). We measured stand density, Canopy closure, elevation, aspect, slope, and geographic coordinates of the sample plots. We randomly collected ten soil samples from the 0-10 cm soil layer using a 100 cm\u003csup\u003e3\u003c/sup\u003e standard soil sampler.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe randomly laid out ten 1 m \u0026times; 1 m samples in each standard sample plot, and the names of Asteraceae plants and the number of plants of each species in each sample plot were recorded for calculating the diversity of its understory herbaceous plants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Environmental and stand factors data of standard plots\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eEnvironmental and stand factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003eRanges\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eElevation\u0026nbsp;(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e114-770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e359.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e116.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSlope (\u0026deg;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e3-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e18.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e10.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil\u0026nbsp;organic\u0026nbsp;matte\u0026nbsp;content (g/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e13.84-116.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e44.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e21.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil total nitrogen content (g/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e0.98-6.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil total phosphorus content (g/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e0.24-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil total potassium content (g/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e9.25-40.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e20.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e6.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil available nitrogen content (mg/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e91.57-415.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e135.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e80.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil available phosphorus content (mg/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e0.09-4.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e6.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eSoil available potassium content\u0026nbsp;(mg/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e37.533-444.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eStand density\u0026nbsp;(plant\u0026bull;hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e500-1975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e1035.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e286.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.860759493670884%\" valign=\"top\"\u003e\n \u003cp\u003eCanopy closure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.367088607594937%\" valign=\"top\"\u003e\n \u003cp\u003e0.5-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.89240506329114%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1710326926.png\"\u003e\u003c/p\u003e\n\u003cp\u003e2.3.2 MaxEnt model\u003c/p\u003e\n\u003cp\u003eThe maximum entropy model is a spatial distribution model of species at the geographical scale based on the maximum entropy theory, which is a measurement of the maximum likelihood of the sample, and its core is to infer the location information through incomplete information and find the conditions when the probability reaches the maximum (Wen et al., 2021; Wang et al., 2024). The accuracy of the model was verified by using the receiver operating characteristic curve (ROC), and the accuracy was judged by calculating the area (AUC) enclosed by the curve and the abscissa (Liu et al., 2022; Zhou et al., 2023). Two sets of data are required for the operation of the maximum entropy model: one is the geographical distribution data of plant species, which is expressed by the latitude and longitude of each species; The second is the raster data of environmental factors in the study area, the elevation of Beijing is derived from the 30 m\u0026times;30 m digital elevation model (DEM), the slope aspect and slope are extracted from the DEM (http://westdc.westgis.ac.cn), and the soil raster data is derived from the measured data of the sample plots.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e3.1 The relationship between the Asteraceae species diversity indices\u003c/p\u003e\n\u003cp\u003eThe correlation of these diversity indices was shown in Figure 2. It can be seen that Shannon-Wiener index had the highest correlation with the other three indices, with R\u003csup\u003e2\u003c/sup\u003e of 0.87, 0.74 and 0.70. After comprehensive compared the correlations of these indices, we chose Shannon-Wiener index to measure the overall level of Asteraceae species diversity.\u003c/p\u003e\n\u003cp\u003e3.2 Effects of stand and environmental factors on Asteraceae\u0026nbsp;species\u0026nbsp;diversity\u003c/p\u003e\n\u003cp\u003eThe direct and indirect effects of elevation, slope, canopy closure\u0026nbsp;and soil nutrient factors on understory plant diversity were shown in Figure 3.elevation and slope had a significant effect on the understory plant diversity (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and canopy closure and soil nutrients significantly affected the understory diversity(\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01), The direct effect was: soil nutrients (0.58) \u0026gt; slope (-0.19) \u0026gt;elevation(-0.14) \u0026gt; canopy closure (-0.17), and the indirect effect was: elevation (-0.05) \u0026gt;slope (-0.02) \u0026gt; soil nutrients (-0.01). Overall, soil nutrients were the dominant factors affecting species diversity, with direct effects being the primary mechanism. Elevation, slope and canopy closure and also had important impacts on Asteraceae species diversity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Standardized effects of these factors on the understory plant diversity.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eImpact factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eDirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eIndirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eTotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eElevation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eCanopy closure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSoil nutrient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.3 Maximum entropy model results\u003c/p\u003e\n\u003cp\u003eIn this study, the Shannon-Wiener diversity index ranges from 0.27 to 2.01, the average value is 1.01, a screening value equal to the average Asteraceae species diversity at sample sites was determined, and those values beyond this screening value were considered the sample plots with abundant Asteraceae species diversity. A total of 49 sample sites were selected for use as point data in the MaxEnt model. The MaxEnt model was constructed based on all environmental factors to obtain ROC curves, as shown in Figure. 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe contribution rate of each potential environmental variable\u0026rsquo;s impact on the Asteraceae species diversity was ranked as the following: soil total nitrogen (29.7%)\u0026gt; soil organic matter (28.5%)\u0026gt; slope (8.5%)\u0026gt; elevation (8.1%), and the cumulative contribution rate is 74.8% (Table 4). The contribution rate of other environmental variables was between 3.5% and 4.9%, which had little impact. The above analysis shows that the main environmental variables that affect the Asteraceae species diversity were soil nutrient factors (soil organic matter and soil total nitrogen), of which the cumulative contribution rate of topography factors was 58.2%. Taking the probability of existence greater than 0.7 as the threshold value. The contribution rate of SOC was the highest among soil factors, reaching 28.5%, when the soil organic matter content was greater than 27 g/kg, the probability of existence was greater than 0.7. It shows that when the soil total nitrogen content was greater than 27g/kg, the contribution rate of soil total nitrogen in soil variables ranked second, that is 29.7%. It can be seen from Figure. 5 that when the total nitrogen content was greater than 1.8 g/kg, the probability of existence was greater than 0.7; when the total nitrogen content was 2 g/kg, it reaches the peak and remains unchanged. Obviously, it was suitable for the distribution of abundant Asteraceae species diversity level when the total nitrogen content of soil was more than 1.8 g/kg. Moreover, the probability distribution remains the largest when it reaches 2g/kg. Elevation contributed the most to the herbaceous productivity, reaching 39.7%. It can be seen from Figure. 4 that when the elevation ranges from 165 to 333 m, the probability of existence was greater than 0.7. The probability of existence reaches the peak at about 230 m, indicating that low mountain areas were most suitable for the Asteraceae species growth; when the elevation was less than 100m or more than 500m, the probability of existence decreases, indicating that these two elevations were not conducive to their distribution. The contribution rate of the slope degree to the herbaceous diversity was 18.5%. It can be seen from Figure. 4 that when the slope range was 5 to 12\u0026deg;, the probability of existence is greater than 0.7. The probability of existence reaches the peak value when the slope degree was about 8 degrees, indicating that the gentle slope area was most suitable for their distribution; when the slope degree was less than 2 degrees or more than 22 degrees, there was a rapid decline in the probability, indicating that the two slopes were not conducive to their distribution.\u003c/p\u003e\n\u003cp\u003eTable 4 Contribution and cumulative contributions of environmental factors to the herbaceous diversity\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eVariable factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eContribution rate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eCumulative contribution rate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eElevation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e58.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSOC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e74.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e79.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eAspect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e84.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e88.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e92.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e96.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study found that the soil organic matter and soil total nitrogen content were the dominant soil factors affecting the Asteraceae species diversity, with a cumulative contribution rate of 58.4%. The main reason was that soil organic matter contains various nutrients required for plant growth, which was one of the main sources of vegetation nutrition and can promote the growth and development of plants (Wu et al., 2021). A large amount of nitrogen is necessary for plant growth. Its abundance, shortage, and supply directly affect the growth level of plants (Tan et al., 2023). When the soil organic matter content was less than 27g/kg and total nitrogen content was less than 1.8 g/kg, the probability of the existence with abundant Asteraceae species diversity decreases rapidly. Therefore, for the land with a soil organic matter content less than 27g/kg and soil total nitrogen content less than 1.8g/kg in the Beijing Mountain area, a reasonable application of organic fertilizer and nitrogen fertilizer is conducive to increasing the Asteraceae species diversity. Our results indicated that the change of soil nutrients would affect the suitability distribution of some specific species, and the appearance of some Asteraceae species is the sign for soil nutrient improvement, these findings have same conclusions with relevant studies (Xu et al., 2004; Tang et al., 2010; Jia et al., 2015).\u003c/p\u003e\n\u003cp\u003eIn this study, we found that topographic factors (elevation and slope) were the important factors affecting Asteraceae species diversity, with a cumulative contribution rate of 16.6%. Topographic factors such as altitude, slope and aspect have a great influence on species distribution, mainly because they are the fundamental factors affecting energy and material variation at the site scale. Altitude is the most common environmental factor used to explain species diversity differences, and many studies have suggested that it is the first influencing factor on the composition and distribution of shrub and herbaceous, and species distribution shows obvious differences along the altitudinal gradient, which is consistent with the results of this study. In general, the influence of slope on species diversity is the second only to that of altitude and the influence of aspect relatively is small.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, we found that canopy closure was also an important factor affecting Asteraceae species diversity, and Wagner et al (2011) also concluded that the canopy closure was the main stand factor governing the diversity and productivity of understory herbaceous, which was basically consistent with the findings of this study, probably because the canopy closure directly determines the effective light intensity within the forest, which has a redistributive effect on the resources of light, heat, water and fertilizer in the forest, thus directly affecting the distribution and individual growth of understory herbaceous species, especially for some sun-loving and non-shade tolerant plants (Chavzv et al., 2012). On the other hand, in low-density forests, the increase in light intensity promoted the decomposition of understory litter and soil microbial activities, accelerated the formation of soil organic matter, which in turn facilitated the absorption of more soil nutrients by herbaceous plants, thus indirectly changing the composition and growth of understory herbaceous species (Chastain et al., 2006; Sabatini et al., 2014).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSoil nutrient was the main factors affecting the Asteraceae species diversity, the total impact effect was 0.59. slope and elevation factors had a significant effect on herbaceous diversity, the total impact effect is -0.11and -0.19. The contribution rate of each potential environmental variable\u0026rsquo;s impact on the Asteraceae species diversity was ranked as the following: STN (29.7%)\u0026gt; SOC (28.5%) \u0026gt; slope (8.5%)\u0026gt; Ele (8.1%). Asteraceae species diversity was abundant at high SOC (＞27g/kg), STN (＞1.8 g/kg), low Ele (165\u0026ndash;333 m) and gentle slopes (5\u0026ndash;12 degrees).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmale, M., Leila, K., Souad, N., Haroun,C..2021. Environmental drivers of taxonomic and phylogenetic diversity patterns of plant communities in semi-arid steppe rangelands of North Africa. Remote Sensing132.\u003c/li\u003e\n\u003cli\u003eBilal, A.,Wang,Y., Jia, H., Liu,Y., Eve, B., Zhang,K.,2018. Optimizing stand structure for trade‐offs between overstory timber production and understory plant diversity: A case‐study of a larch plantation in northwest China. Land Degradation \u0026amp; Development 29.\u003c/li\u003e\n\u003cli\u003eBrodie, E.G., Miller, J., Safford. H.D.. 2021. Productivity modifies the effects of fire severity on understory diversity. Ecology.\u003c/li\u003e\n\u003cli\u003eCao,X.Y., Zhao, W.F., Li,J.P., Yan,W.D., Pang, Y.F., Sun, Y.P., Xie, Z.C.. 2022. Soil nutrient content analysis and comprehensive evaluation of several typical forests in the Middle subtropical region. Acta Ecologica Sinica 42(09):3525-3535.\u003c/li\u003e\n\u003cli\u003eChao ,M., Jun ,W., Sheng, L.J.. 2023. Utilization of soil and fertilizer nitrogen supply under mulched drip irrigation with various water qualities in arid regions. Agricultural Water Management. 280.\u003c/li\u003e\n\u003cli\u003eChastain,R.A.,Currie, W.S., Townsend,P.A..2006. Carbon sequestration and nutrient cycling implications of the evergreen understory layer in Appalachian forests. Forest Ecology and Management.231(1).\u003c/li\u003e\n\u003cli\u003eChen, M.H., Zeng. S.D., Bo, J., Wen, Z.F., Wu. J., Xia, J.. 2023. The comprehensive evaluation of how water level fluctuation and temperature change affect vegetation cover variations at a lake of ecological importance (Poyang Lake), China. Ecological Indicators. 148.\u003c/li\u003e\n\u003cli\u003eCh\u0026aacute;vez,V., Macdonald.E.S.,Partitioning vascular understory diversity in mixedwood boreal forests: The importance of mixed canopies for diversity conservation[J]. Forest Ecology and Management,2012,271.\u003c/li\u003e\n\u003cli\u003eCian, B., Olivier, C., Didier, A., Manuella, C., Sylvain, D., Thierry, D., J\u0026eacute;r\u0026ocirc;me, L., Gr\u0026eacute;gory, L., Alice, M., Marine, P., Antoine, T., Servane, L., Anne,B.. 2023. Forage nutritive value shows synergies with plant diversity in a wide range of semi-natural grassland habitats. Agriculture, Ecosystems and Environment 347.\u003c/li\u003e\n\u003cli\u003eCui,R.R.,Qi,S.,Wu,B.C.,Zhang,D.,Zhang,L.,Zhou, P.,Ma,N,Huang,X., The Influence of Stand Structure on Understory Herbaceous Plants Species Diversity of Platycladus orientalis Plantations in Beijing, China[J]. Forests,2022,13(11).\u003c/li\u003e\n\u003cli\u003eDong,D.,Ashfaq ,A., Huang,X., Teng,M.J., Wu,C.G.,Zhou,Z.X., Liu,Yu..Soil Available Phosphorus Loss Caused by Periodical Understory Management Reduce Understory Plant Diversity in a Northern Subtropical Pinus massoniana Plantation Chronosequence[J]. Forests,2020,11(2).\u003c/li\u003e\n\u003cli\u003eEchiverri,L.,and S.E. Macdonald. 2020. A topographic moisture index explains understory vegetation response to retention harvesting. Forest Ecology and Management, 474:118358.\u003c/li\u003e\n\u003cli\u003eGautam, M.K., Manhas, R.K., Tripathi A.K..2016. Overstory structure and soil nutrients effect on plant diversity in unmanaged moist tropical forest. Acta Oecologica 75.\u003c/li\u003e\n\u003cli\u003eHan,W.J.,Chen,D.H. Hu,L., Zhu, C., Chen ,J,,Ye L.Z.,Liu ,S.S., Zuo. W.,Spatiotemporal Variation of NDVI in Anhui Province from 2001 to 2019 and Its Response to Climatic Factors[J]. Forests,2022,13(10).\u003c/li\u003e\n\u003cli\u003eHe,Y.Y.,Yu M.H.,Ding,G.D,Wang,C.Y.,Zhang, F.C.. Precipitation amount and event intervals interact to change plant diversity during dry years in a desert shrubland[J]. Ecological Indicators,2022,145.\u003c/li\u003e\n\u003cli\u003eHou, G.R., Bi, Huo,Y.M.,Wei,X.Y., Zhu, Y.J., Wang, X.X., Liao,W.C.. 2020. Determining the optimal vegetation coverage for controlling soil erosion in Cynodon dactylon grassland in North China. Journal of Cleaner Production, 244(C).\u003c/li\u003e\n\u003cli\u003eHuang, Y.Y., Chen ,Y.X., Nadia,C.I. .2018. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362(6410):80-83.\u003c/li\u003e\n\u003cli\u003eHe, K.J., Huang.,Y.M., Qi,Y., Sheng,Z.L., Chen. H.Y., 2021. Effects of nitrogen addition on vegetation and soil and its linkages to plant diversity and productivity in a semi-arid steppe. Science of the Total Environment, 778.\u003c/li\u003e\n\u003cli\u003eHe,\u003cu\u003e Y\u003c/u\u003e.Y., Yu. M.H., Ding ,G.D., Wang,C.Y., Zhang. F.C.. 2022. Precipitation amount and event intervals interact to change plant diversity during dry years in a desert shrubland. ECOL INDIC 145.\u003c/li\u003e\n\u003cli\u003eHan,W.J., Chen, D.H., Hu, L.,Chang. Z., Chen,J., Ye. L.Z., Liu. S.S., Wang,Z.. 2022a. Spatiotemporal Variation of NDVI in Anhui Province from 2001 to 2019 and Its Response to Climatic Factors. Forests. 13(10).\u003c/li\u003e\n\u003cli\u003eHu, D., Lv, G.H., Wang, H.F., Yang, Q., Cai, Y.. 2021. Responses of desert plant diversity and stability to soil factors under water gradient. Acta Ecologica Sinica 41(17):6738-6748.\u003c/li\u003e\n\u003cli\u003eHuang, Q.Y., Cao, H.J., Xie ,L.H., Luo, C.Y., Yang, F., Wang, L.M., Ni,H,W.. 2020. Species diversity and environmental interpretation of herbaceous layer in the lava platform of Wudalianchi Volcano. Biological Diversity 28(06):658-667.\u003c/li\u003e\n\u003cli\u003eIqra, P., Iftikhar, A., Mansoor, H., Aqeel,A.M.S..2023. Plasticity in anatomical traits of;Cyperus niveus;Retz. along elevational gradient of dry sub-Himalayan mountains. Arid Land Research and Management, 37(2).\u003c/li\u003e\n\u003cli\u003eJian, S.Q.,Zhang.,Q.K., Wang. H.L.. 2022. Spatial\u0026ndash;Temporal Trends in and Attribution Analysis of Vegetation Change in the Yellow River Basin, China. Remote Sensing. 14(18).\u003c/li\u003e\n\u003cli\u003eJoseph,O.,Marijn,B., Hans,V., Samuel,B., John,K., Astrid,F.,Till,E., Klaus,B.B., Ralf,K., Pascal.,B.. Temperature sensitivity of soil organic carbon respiration along a forested elevation gradient in the Rwenzori Mountains, Uganda[J]. Biogeosciences,2023,20(3).\u003c/li\u003e\n\u003cli\u003eLan, G.Y., Chen, B.Q., Yang,C., Sun. R., Wu, Z.X., Zhang. X.C..2022. Main drivers of plant diversity patterns of rubber plantations in the Greater Mekong Subregion. Biogeosciences, 19(7).\u003c/li\u003e\n\u003cli\u003eLea, V., Shiro.T.. 2022. Differences in canopy and understorey diversities after the eruptions of Mount Usu, northern Japan \u0026mdash; Impacts of early forest management. FOREST ECOL MANAG 510.\u003c/li\u003e\n\u003cli\u003eLei,B.Y., Tian,Y.Y., Cui,J.F., Zhao,J., Zhou,Y.B.. 2023. Effects of plant species richness on the structure of plant-bird interaction networks along a 3000-m elevational gradient in subtropical forests. Forest Ecology and Management.532.\u003c/li\u003e\n\u003cli\u003eLi ,Y.,Wang ,J.,Shen ,CC.,Wang, J.C.,Singh,B. K.,Ge, Y.. Plant diversity improves resistance of plant biomass and soil microbial communities to drought[J]. Journal of Ecology,2022,110(7).\u003c/li\u003e\n\u003cli\u003eLi, X.K., Li, Y.N., Zhang, J.. Peng, S.Z. Chen, Y.M. Yang,C.. The effects of forest thinning on understory diversity in China: A meta‐analysis[J]. Land Degradation \u0026amp; Development,2020,31(10).\u003c/li\u003e\n\u003cli\u003eLi, T.T., Tang, Y.B., Zhou, R.H., Yu, F.Y., Dong, H.J., Wang, M., Hao, J,F.. 2021. Relationship between understory plant diversity and soil physicochemical properties of different plantations in Genting Mountain. Acta Ecologica Sinica 41(03):1168-1177.\u003c/li\u003e\n\u003cli\u003eLi, T.F., Kamran,M., Chang, S.H., Peng, Z.C., Wang.,Z.F., Ran,.L.J., Qi, J.W.,Jin.,Y.S., Zhang,X.Y., Yang, Y., Lan, L., Hou,F.J.. 2022. Climate-soil interactions improve the stability of grassland ecosystem by driving alpine plant diversity. Ecological Indicators. 141.\u003c/li\u003e\n\u003cli\u003eLiang, W.J., Wei ,Xi.. Relationships between ecosystems above and below ground including forest structure, herb diversity and soil properties in the mountainous area of Northern China[J]. Global Ecology and Conservation,2020,24.\u003c/li\u003e\n\u003cli\u003eLin, L., Dai, L., Lin, Z. T., Wu, J.T., Yan, W., Wang, Z.J.. 2021. Relationship between plant diversity and soil physicochemical properties in urban forest communities in central Guizhou. Journal of Ecology and Environment 30(11):2130-2141.\u003c/li\u003e\n\u003cli\u003eLin, S.Y.,Zhao. L., Feng, J. L.,2022. Predicted changes in the distribution of Antarctic krill in the Cosmonaut Sea under future climate change scenarios. Ecological Indicators.142.\u003c/li\u003e\n\u003cli\u003eLiu, C., Li, W., Wang, W., Zhou, H., Liang, T., Hou, F., Xu, J., Xue, P.. Quantitative spatial analysis of vegetation dynamics and potential driving factors in a typical alpine region on the northeastern Tibetan Plateau using the Google Earth Engine. Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution.2021. (206-):206.\u003c/li\u003e\n\u003cli\u003eLuo, Y.S., Zhou, M.L., Jin S.S., Wang,Q.X., Yan,D.F.. 2023. Changes in phylogenetic structure and species composition of woody plant communities across an elevational gradient in the southern Taihang Mountains, China. Global Ecology and Conservation,42.\u003c/li\u003e\n\u003cli\u003eLv,K.T., Zhou. M.L., Ding, Y., Zang. R.G., Yao, J., Luo. Y.S., Yan. D.F.. 2023. Regeneration characteristics and influencing factors of woody plant on natural evergreen secondary broad-leaved forests in the subtropical, China. Global Ecology and Conservation, 42.\u003c/li\u003e\n\u003cli\u003eLotte, K., Harald, A., Jonathan,C.M., Stanley, H.W., Tiffany,K.M., Responses of plant diversity to precipitation change are strongest at local spatial scales and in drylands. Nature Communications. 2021.12(1).\u003c/li\u003e\n\u003cli\u003eMi, J., Ou, J., Liu, H., Shi, J., Chen,D.M., Bai,.Y.F.. 2022. The loss of plant species diversity dominated by temperature promotes local productivity in the steppe of eastern Inner Mongolia. Ecological Indicators, 139.\u003c/li\u003e\n\u003cli\u003eMakse, H.A., Lucini, F.A., Morone, F., Tomassone,M.S.. 2020. Diversity increases the stability of ecosystems. Cold Spring Harbor Laboratory(4).\u003c/li\u003e\n\u003cli\u003eMarkus, L., Nico, E., Hongmei, C., Gerd.,G.. 2023. Increased soil carbon storage through plant diversity strengthens with time and extends into the subsoil. Global change biology.\u003c/li\u003e\n\u003cli\u003eMi,J.,Ou,J.,Liu ,H.,Shi, J.,Chen, D.M.,Bai,Y.F..The loss of plant species diversity dominated by temperature promotes local productivity in the steppe of eastern Inner Mongolia[J]. Ecological Indicators,2022,139.\u003c/li\u003e\n\u003cli\u003eMu ,B.H., Zhao,X., Zhao,J.C., Liu,N.J., Si,L.P., Wang,Q., Sun,Na., Sun,M.M., Guo,Y.K., Zhao,S.Q. 2022. Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China\u0026rsquo;s 32 Major Cities. Remote Sensing 14(4).\u003c/li\u003e\n\u003cli\u003eMonika, M., Łukasz, C., Paweł, P., Elżbieta, R., Marcin, S., Małgorzata.,S.. 2023. Potential role of high-altitude wetlands in preservation of plant biodiversity under changing climatic conditions in the arid Eastern Pamir. Catena 220(PA).\u003c/li\u003e\n\u003cli\u003eMulatijiang, C., Ekbair, I., Amanullah, I.. 2022. Effects of slope aspect and elevation on plant community characteristics and species diversity of grassland in Wusun Mountain. Xinjiang Agricultural Sciences 59(11):2724-2733.\u003c/li\u003e\n\u003cli\u003ePablo, G., Nicolas, G., Juan, G., Maestre.,F.T.,2018. Climate mediates the biodiversity\u0026ndash;ecosystem stability relationship globally. Proceedings of the National Academy of ences 115:201800425.\u003c/li\u003e\n\u003cli\u003ePan, H.H., Wang,J.Q., Du,Z.Q., Wu. Z.T., Hong, Z., Ma, K.M., 2023. Spatiotemporal evolution of ecosystem services and its potential drivers in coalfields of Shanxi Province, China. Ecological Indicators,148.\u003c/li\u003e\n\u003cli\u003eQian,Z.Y.,Gu,R., Gao, K., Li,D.J.. 2022. High plant species diversity enhances lignin accumulation in a subtropical forest of southwest China. The Science of the total environment 865.\u003c/li\u003e\n\u003cli\u003eRebecca, F., B.T.B. B, B. Jayne, G.E. L, G.E. E, H.D. L, R. Sasha, Michael.D. C.. 2023. Droughting a megadrought: ecological consequences of a decade of experimental drought atop aridification on the Colorado Plateau. Global change biology..\u003c/li\u003e\n\u003cli\u003eRavhel,J.S.,Ryan, B., Morald,T., Richard,J. H., Suzanne,M.P.2022. Contribution of species and functional richness to carbon storage in eucalypt woodland restoration. Forest Ecology and Management 523.\u003c/li\u003e\n\u003cli\u003eReza, E., Moslem, Y., Mosleh,A.A.,Effect of different shrub species on their sub‐canopy soil and vegetation properties in semiarid regions[J]. Land Degradation \u0026amp; Development,2021,32(11).\u003c/li\u003e\n\u003cli\u003eSabatini, F., Jim\u0026eacute;nez-Alfaro, B., Burrascano, S., Blasi,C..2014. Drivers of herb-layer species diversity in two unmanaged temperate forests in northern Spain. Community Ecology 15(2).\u003c/li\u003e\n\u003cli\u003eSheng, W., Ren, S., Yu, G., Fang, H., Jiang, C., Mi.,Z.. 2011. Patterns and driving factors of WUE and NUE in natural forest ecosystems along the North-South Transect of Eastern China. Journal of Geographical Sciences. 21(4):651-665.\u003c/li\u003e\n\u003cli\u003eShi X.D., Wang. J.W., Zhang. L., Chen, S.X., Zhao. A.L., Ning. X.D., Fan, G.R., Wu,N.S., Zhang L., Wang. Z.D.. 2023. Prediction of the potentially suitable areas of Litsea cubeba in China based on future climate change using the optimized MaxEnt model. Ecological Indicators. 148.\u003c/li\u003e\n\u003cli\u003eShi, P., Li, P. , Li, Z. , Sun, J., Wang, D., Min, Z.. 2022. Effects of grass vegetation coverage and position on runoff and sediment yields on the slope of Loess Plateau, China. Agricultural Water Management. 259.\u003c/li\u003e\n\u003cli\u003eTiit,H., Kadri, T., Indrek, M., Katrin. H., How is plant biodiversity inside grassland type related to economic and ecosystem services: An Estonian case study[J]. Agriculture, Ecosystems and Environment,2023,349.\u003c/li\u003e\n\u003cli\u003eT., M.A.D., T.L.R. Dongmo, I.D. J., B.V. A., N.I.C. NFOR, and M.T. B. 2023. Maximum entropy modeling of giant pangolin Smutsia gigantea (Illiger, 1815) habitat suitability in a protected forest-savannah transition area of central Cameroon. Global Ecology and Conservation.43.\u003c/li\u003e\n\u003cli\u003eVanhellemont, Margot, Baeten, Lander, Verheyen, and Kris. 2014. Relating changes in understorey diversity to environmental drivers in an ancient forest in northern Belgium. Plant Ecology and Evolution. 147(1).\u003c/li\u003e\n\u003cli\u003eWang,G.R., Sun,Y., Zhou,M., Guan, N.Q., Wang, Y.W., Jiang, R.H., Liu, Z.Y., Wu, M.G., Xia. F.C.,Effect of thinning intensity on understory herbaceous diversity and biomass in mixed coniferous and broad-leaved forests of Changbai Mountain[J].Forest Ecosystems,2021,8(04):713-725.\u003c/li\u003e\n\u003cli\u003eWang, J., Zhao, W.W., Zhang, X., Liu, Y., Wang, S., Liu, Y.X.. Effects of reforestation on plant species diversity on the Loess Plateau of China: A case study in Danangou catchment[J]. Science of the Total Environment,2019,651(Pt 1).\u003c/li\u003e\n\u003cli\u003eWang, D. J., Han, G. J., Gao, Z. H., Wang Y G. 2020. Response of plant community species diversity to altitude gradient in Lianhua Mountain, Gansu Province. Journal of Northwest Forestry College 35(06):96-102.\u003c/li\u003e\n\u003cli\u003eWagner, S., Fischer, H., Huth, F., 2011. Canopy effects on vegetation caused by harvesting and regeneration treatments. European Journal of Forest Research.130(1).\u003c/li\u003e\n\u003cli\u003eWani,Z.A.,Negi,V.S.,Bhat, J. A.,Satish ,K.V.,Kumar,A.,Khan,S.,Dhyani,R,, Sazada, S., Rahmah, A,Q.N., Shreekar ,P.. Elevation, aspect, and habitat heterogeneity determine plant diversity and compositional patterns in the Kashmir Himalaya [J]. Frontiers in Forests and Global Change,2023.Influence of environmental factors on tree species diversity and composition in the Indian western Himalaya.\u003c/li\u003e\n\u003cli\u003eWei, L., Archaux, F., Hu, F. l., Bilger, I., Gosselin,F.. 2020. Stand attributes or soil micro-environment exert greater influence than management type on understory plant diversity in even-aged oak high forests. Forest Ecology and Management 460(C).\u003c/li\u003e\n\u003cli\u003eWei, X., Bi, H.X. Liang, W.J., Hou, G.R., Kong, L.X., Zhou. Q.Z. 2018. Relationship between Soil Characteristics and Stand Structure of Robinia pseudoacacia L. and Pinus tabulaeformis Carr. Mixed Plantations in the Caijiachuan Watershed: An Application of Structural Equation Modeling. Forests. 9(3).\u003c/li\u003e\n\u003cli\u003eWei,L.P.,Fr\u0026eacute;d\u0026eacute;ric,A.,Florian,H.,Isabelle, B.,Fr\u0026eacute;d\u0026eacute;ric,G.. Stand attributes or soil micro-environment exert greater influence than management type on understory plant diversity in even-aged oak high forests[J]. Forest Ecology and Management,2020,460(C).\u003c/li\u003e\n\u003cli\u003eWu,D.H., Zhao,X., Liang,S.L., Zhou,T., Huang.,K.C., Tang,B.J., Zhao,W.Q., 2015. Time-lag effects of global vegetation responses to climate change. Global change biology 21(9).\u003c/li\u003e\n\u003cli\u003eWu,B.C.,Zhou,L.J.,Qi ,S.,Jin,M.L.,Hu,J.,Lu J.S.. Effect of habitat factors on the understory plant diversity of Platycladus orientalis plantations in Beijing mountainous areas based on MaxEnt model[J]. Ecological Indicators,2021,129.\u003c/li\u003e\n\u003cli\u003eWang,S.A., Li. R.P., Wu,Y.J., Wang,W.J..2023. Estimation of surface soil moisture by combining a structural equation model and an artificial neural network (SEM-ANN). The Science of the total environment 876.\u003c/li\u003e\n\u003cli\u003eYang, S.L., Wang. H.M., Tong,J.G., Bai,Y., Juha. M .A., Liu. G., Zhou, F.. Zhou.,F.. 2022. Impacts of environment and human activity on grid-scale land cropping suitability and optimization of planting structure, measured based on the MaxEnt model. The Science of the total environment 836.\u003c/li\u003e\n\u003cli\u003eZhang, T, Ding, G.J., Z. Jiangping, and Q. Yujiao. 2023. Stand, plot characteristics, and tree species diversity jointly dominate the recruitment biomass of subtropical forests. Forest Ecology and Management. 531.\u003c/li\u003e\n\u003cli\u003eZhang, X., Li. X., Ji.,X.D., Zhang,Z.Q., Zahng,H.S., Zha, T.G., Li. J.. 2021. Elevation and total nitrogen are the critical factors that control the spatial distribution of soil organic carbon content in the shrubland on the Bashang Plateau, China. Catena 204.\u003c/li\u003e\n\u003cli\u003eZhao,X.F., Lei. M., Wei. C.H., Guo. X.X.. 2022. Assessing the suitable regions and the key factors for three Cd-accumulating plants (Sedum alfredii, Phytolacca americana, and Hylotelephium spectabile) in China using MaxEnt model. The Science of the total environment 852.\u003c/li\u003e\n\u003cli\u003eZhang,Y.X., Z., Sun. J.Y., Song, X.Q., Lu. Y.F.. 2023. Revealing the main factors affecting global forest change at distinct altitude gradients. Ecological Indicators. 148.\u003c/li\u003e\n\u003cli\u003eZhao,X.N., Zheng,Y.T.,Wei,W.. 2023. Habitat Suitability Evaluation of Different Forest Species in Lvliang Mountain by Combining Prior Knowledge and MaxEnt Model. Forests. 14(2).\u003c/li\u003e\n\u003cli\u003eZilliox, C., Gosselin,F.. 2014. Tree species diversity and abundance as indicators of understory diversity in French mountain forests: Variations of the relationship in geographical and ecological space. FOREST ECOL MANAG 321.\u003c/li\u003e\n\u003cli\u003eZhang,Li., Qi, S., Zhou, P., Wu, B.C., Zhang, D., Cui, R.R., Huang, X., Ma, N.. 2022. Influencing factors on herb diversity of Platycladus platycladus understory in Beijing Mountain area. Journal of Grassland Science 30(8):8.\u003c/li\u003e\n\u003cli\u003eZhang, Y.Q., Li, Z.C., Hou, L.Y., Song, L.G., Yang, H.G., Sun, Q.W.. 2020. Effects of stand density on understory species diversity and soil nutrients of Chinese fir plantation. Acta Pedologica Sinica 57(01):239-250.\u003c/li\u003e\n\u003cli\u003eZhang, Q.P., Fang,R.Y., Deng, C.Y., Zhao,H.J., Shen, M.H., Wang,Q.. 2022. Slope aspect effects on plant community characteristics and soil properties of alpine meadows on Eastern Qinghai-Tibetan plateau. Ecological Indicators. 143.\u003c/li\u003e\n\u003cli\u003eZu,K.L., Zhang,C.C., Chen,F.S., Shahid, A., Ghulam, N., 2023. Latitudinal gradients of angiosperm plant diversity and phylogenetic structure in China\u0026rsquo;s nature reserves. Global Ecology and Conservation, 42.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Asteraceae species, habitat indicators, biodiversity conservation, Maxent ","lastPublishedDoi":"10.21203/rs.3.rs-4039102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4039102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Determining the distribution pattern and drivers of specific species diversity is significant for predicting the response to biodiversity and formulating conservation programs to reduce biodiversity loss. How to apply regional habitat indicators to study specific species diversity patterns is a hot spot in recent years. In this study, we investigated 112 Asteraceae plants sample plots and explored the effects of topography, soil nutrients and stand factors on Asteraceae species diversity by using SEM model. And the responses of Asteraceae species diversity to specific habitat factors was simulated by Maxent model. The results shown that soil nutrients had the highest, but topography and canopy closure had the lowest relative contributions to the Asteraceae species diversity among these factors. Topography and soil nutrients affected Asteraceae species diversity by direct and indirect effects. The contribution rate of each potential environmental variable’s impact on the Asteraceae species diversity was ranked as the following: STN (29.7%)\u003e SOC (28.5%) \u003e slope (8.5%)\u003e Ele (8.1%). Asteraceae species diversity was abundant at high SOC (＞27g/kg), STN (＞1.8 g/kg), low Ele (165–333 m) and gentle slopes (5–12 degrees). Our study indicates that the Asteraceae species diversity could as an indicator to reflect or evaluate the level of soil nutrient content.","manuscriptTitle":"Applying specific habitat indicators to study Asteraceae species diversity patterns in mountainous area of Beijing, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-13 10:59:11","doi":"10.21203/rs.3.rs-4039102/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c684dc6c-b330-4cbf-8c81-4884e5e90a38","owner":[],"postedDate":"March 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-13T23:59:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-13 10:59:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4039102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4039102","identity":"rs-4039102","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}