Topography and soil content contribute to plant community composition and structure in subtropical evergreen-deciduous broadleaved mixed forests

Abstract

Topography and soil factors are known to play crucial roles in the species composition of plant communities in subtropical evergreen-deciduous broadleaved mixed forests. In this study, we used a systematic quantitative approach to classify plant community types in the subtropical forests of Hubei Province (central China), and then quantified the relative contribution of drivers responsible for variation in species composition and diversity. We classified the subtropical forests in the study area into 12 community types. Of these, species diversity indices of three communities were significantly higher than those of others. In each community type, species richness, abundance, basal area and importance values of evergreen and deciduous species were different. In most community types, deciduous species richness was higher than that of evergreen species. Linear regression analysis showed that the dominant factors that affect species composition in each community type are elevation, slope, aspect, soil nitrogen content, and soil phosphorus content. Furthermore, structural equation modeling analysis showed that the majority of variance in species composition of plant communities can be explained by elevation, aspect, soil water content, litterfall, total nitrogen, and total phosphorus. Thus, the major factors that affect evergreen and deciduous species distribution across the 12 community types in subtropical evergreen-deciduous broadleaved mixed forests include elevation, slope and aspect, soil total nitrogen content, soil total phosphorus content, soil available nitrogen content and soil available phosphorus content.

Mapping Plant Diversity Based on Combined SENTINEL-1/2 Data—Opportunities for Subtropical Mountainous Forests

“…This type of map can also be applied to evaluate the relationships between environmental factors and plant diversity at a pixel level [89]. The prediction results associated with the large-scale confidence intervals captured in the satellite imagery can be defined by regional topographical conditions [63]. Spectral-temporal features were found to do not correspond to input data sets from which learns to identify forest types, resulting in inaccurate predictions, especially in the edges of the parcels (Figure 6).…”

“…The average rainfall of approximately 100-150 mm per month is caused by the influence of the southeast monsoon, while in the summer it can be approximately 150-200 mm per month [68]. The vertical zonal distribution of these forest vegetation types are distinct under the influence of topographic features [63]. The forests across the study area are comprised of about 72 dominant tree species.…”

“…The main goal of this study was to map plant diversity on a subtropical mountainous forest based on 24 months (two plant growing and dormancy seasons) freely and openly available S-1 and S-2 data sets along with the botanical field surveys dataset of Yang et al (2021) [63]. The following main objectives were addressed: (1) to prove the feasibility of using freely available remote sensing data and machine learning algorithm, combined with and referenced to botanical field surveys data, to map plant diversity at 10 m spatial resolution across the subtropical mountainous forests; (2) to evaluate whether the S-1, S-2 and several vegetation indices can promote prediction accuracy of plant diversity in the subtropical forest; (3) to estimate the potential of alone use of S-1, S-2 band features and acquisition dates to map plant diversity; (4) to build a flowchart that is highly reliable, as simple as possible, and reproducible.…”

Vegetation structure of forests over limestone and its influencing environmental factors in Samar Island Natural Park, Philippines

“…Thus, this study assumes that there is no general pattern along the elevational gradients (Cirimwami et al 2019) since it has little effect on vegetation structure in SINP. The elevation gradient is complex because it includes changes in climatic, edaphic, and biotic factors, as well as changes in plant community structure as a result of these factors (van Breugel et al 2013;Girardin et al 2014;Chen et al 2015;Malhi et al 2017;Yun et al 2020;Homeier and Leuschner 2021;Yang et al 2021).…”

Relationship of topography and soil chemistry with species richness in Chandragiri hill, central Nepal

“…Species richness was found to be decreasing with increasing degree of slope. Most of the previous studies depicted species richness was inversely correlated with degree of slope(Sharma et al 2009, Teshome et al 2020, Yang et al 2021 which could be due to the steepness. High degree of slope results in greater surface run-off accompanied by translocation of surface materials down slope through soil erosion and movement of the soil mass.…”