Plant Community Patterns Research Articles

Temporal variability and predictability predict alpine plant community composition and distribution patterns.

One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species-environment associations. In this study, we evaluated how two components of temporal environmental variation-variability and predictability-impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long-Term Ecological Research site, we used in situ, high-resolution temporal measurements of soil moisture and temperature from 13 locations ("nodes") distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within-day) and seasonal (2- to 4-month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.

Diversity Patterns of Plant Communities along an Elevational Gradient in Arid and Semi-Arid Mountain Ecosystems in China

Quantitative classification and ordination are instrumental in improving our understanding of plant community patterns and facilitating effective conservation efforts in national mountain ecosystems worldwide. However, there has been a lack of relevant research focused on arid and semi-arid mountain ecosystems. This study aims to address this gap by investigating the Ningxia Helan Mountain National Nature Reserve (located in Northwest China). We conducted a comprehensive study on the patterns of plant communities and their association with environmental factors across a broad elevation range from 1200 m a.s.l. to 2600 m a.s.l. Our findings revealed the presence of 121 angiosperm species across 41 families, with vegetation classified into six distinct groups through two-way indicator species analysis (TWINSPAN) along the elevational gradient. Notably, the communities of Ulmus, Prunus, and Stipa in the middle elevation range exhibited the highest Shannon–Wiener (SW) and Simpson (SN) diversity indices, and these indices followed a single-peak pattern with increasing elevation. Canonical correspondence analysis (CCA) further revealed six distinct yet interrelated plant communities, revealing elevation (ELE) and the biological aridity index (BK) as the most influential environmental factors influencing plant communities’ distribution. This understanding is critically important for biodiversity conservation and the management of ecosystems in arid and semi-arid mountain ecosystems.

The species diversity and phylogenetic structure patterns of desert plant communities in the Turpan-Hami region, Xinjiang

Desert plant communities play a crucial role in enhancing desert ecosystem productivity and stability but are highly susceptible to environmental changes owing to their limited resilience and resistance to disturbances, making it essential to understand the factors influencing their diversity patterns and community structure, particularly under the threat of climate change and intensifying droughts. This study focused on the Turpan-Hami desert region, a typical desert ecosystem in which diversity patterns and community structures remain unclear. We established 101 sampling sites ranging from elevations of -134 to 2056m and recorded community information, including species composition, height, coverage, and density, using the sample plot method. The diversity patterns were analyzed using regression analysis, and the phylogenetic structure was assessed. Additionally, Canonical Correspondence Analysis, Mantel tests, and General Linear Models were used to identify the key factors affecting community structure. Our results demonstrated that the species richness and phylogenetic diversity of plant communities exhibited a monotonic increase with elevation, and the phylogenetic structure exhibited low clustering and high dispersion along the elevational gradient. The annual mean temperature emerged as the most significant factor influencing diversity patterns, with soil nutrients, such as total potassium and available phosphorus, also affecting the spatial distribution of diversity. Notably, no significant correlations were found between community phylogenetic structure and abiotic factors, highlighting the complex interactions that drive diversity in the Turpan-Hami region. This study offers valuable insights into the mechanisms shaping desert plant community diversity and is essential for biodiversity conservation efforts in fragile desert ecosystems amid climate change.

Beta diversity subcomponents of plant species turnover and nestedness reveal drivers of community assembly in a regenerating subtropical forest.

Secondary forests represent a significant proportion of global forest cover, with over 70% of forests in East Asia classified as regenerating. While succession has been studied extensively in temperate systems, trajectories of subtropical succession remain poorly characterized in highly disturbed, urban-adjacent forests. Investigating the additive beta diversity components of turnover and nestedness may reveal community assembly mechanisms driving secondary succession. The present study investigates plant community assembly along a successional gradient from 7 to 70 years following the onset of succession in secondary subtropical forests in Hong Kong, China. Plant survey data for 28 plots were analysed, generating additive Simpsons turnover and nestedness beta diversity metrics. Dissimilarity matrices were generated and modelled as a function of environmental matrices including forest plant community age (years following onset of secondary succession), inter-community distance (metres), and soil moisture saturation (%) across three elevational bands using generalized dissimilarity models. Nonmetric multidimensional scaling of plant communities was conducted with Bray-Curtis dissimilarity matrices. Inter-community distance and successional age differentially influenced plant species turnover between lowland and Montane forest types. Models of nestedness found that plot age and soil moisture saturation were significant drivers of nestedness patterns in plant communities across elevational classes. Turnover represented a higher proportion of Sorensen beta diversity than nestedness, while ANOSIM found significant differentiation between plant communities at different successional stages. Turnover patterns suggest a deterministic model of community assembly, with strong patterns of species replacement between communities at fine spatial scales and successional stages, as well as clear compositional shifts between lowland and montane forest types. NMDS analysis and functional compositional assessments suggested a transition from early successional communities with a high proportion of shrub species, to later successional communities with a higher proportion of tree species, with an increase in species turnover with greater age dissimilarity.

Vitality behind desolation: Characteristics and succession process of plant communities in the Chongqing special steel plant brownfield

Phytoremediation is a sustainable way to clean contaminated urban soil, but selecting the right plants and designing communities is crucial. This study focuses on the vegetation in a disused steel plant in Chongqing, China, abandoned for nearly two decades. The goal is to reveal the plant community and succession patterns to inform the restoration of brownfield sites. This study combined the sample line and plot to investigate the vegetation and its growth environment in the Steel Plant. Information was recorded, including plant species, quantity, distribution, soil nutrients, humidity, and light. Cluster analysis categorized plant community types, and redundancy analysis examined the link between environmental conditions and plant types. The study found that: 1) There are 65 plant species (including 13 native trees) in the steel plant’s brownfield area, with Broussonetia papyrifera, Pteris vittata, and Debregeasia orientalis being the most abundant. The plants inside the plant were divided into seven groups based on species composition. 2) Soil moisture showed a significant positive correlation (Pearson index of 0.628) with plant survival, followed by a notable correlation with light intensity. 3) Environmental conditions partly influenced plant species composition and abundance variations. 4) 11 hyper-accumulating plant species were identified, focusing on three: the As hyper-accumulator Pteris vittata and the Cd hyper-accumulators Solanum nigrum and Debregeasia orientalis. The findings of this research will offer valuable insights for applying phytoremediation techniques in addressing contamination issues in brownfields within steel plants.

Cross-taxon analysis in the highly threatened Mediterranean dunes reveals consistent diversity patterns in butterfly and plant communities

AbstractButterflies and plant species are widely used as model systems in biodiversity and conservation research. However, little is known about spatial patterns of butterfly diversity linked to plant communities across coastal dune ecotones. We explored the relation between butterfly and vegetation diversity in a Mediterranean protected dune system in Central Italy. We sampled butterfly and plant communities on shifting and fixed dunes and investigated their distribution patterns by diversity indexes and Species Abundance Diversity models (SADs). We also computed species beta-diversity and analyzed the relation between butterfly communities and vegetation by correlation analyses. Cross-taxon congruence in species richness, composition and abundance was assessed using Mantel correlation tests. Both butterfly and plant diversity were higher on the fixed dunes than on the shifting dunes. In both communities, SADs were adequately described by the geometric series model, which is typical of harsh environments with simple communities dominated by few species. Among both butterflies and plants, we identified species found only on either the shifting or the fixed dunes. Correlation between plant and butterfly diversity was higher for entomophilous plant species than for the more abundant anemophilous ones. Our results indicate that both plant and butterfly communities respond to the sea-inland environmental gradient, forming distinct communities with specialized taxa. Our findings also provide evidence of the importance of butterfly-plant relations for preserving biological diversity and ecosystem functioning in Mediterranean coastal areas.

Understanding the influence of environmental factors on forest composition along the vertical gradient of Northwestern Himalaya

Temperate and alpine ecosystems are considered the most sensitive and vulnerable region towards climate change in the Indian Himalayan region. The current study investigates forest composition in relation to environmental and edaphic factors, which is critical for determining plant community patterns. The impact of climatic and soil properties was studied to better understand species diversity and composition over an elevational gradient (2500–4800 m) in Beas Valley, Northwestern Himalaya. A total of 181 species from 15 community types, representing 122 genera and 53 families (9 Trees, 13 shrubs, and 142 herbs) were recorded from the valley. Non-metric multidimensional scaling (NMDS) analysis revealed significant compositional dissimilarity (PseudoF = 10.16, R2 = 0.48, p < 0.001) among vegetation types. Structural equation modeling (SEM) results indicated that tree species diversity was significantly influenced by solar radiation (β=0.17, p = 0.001) and winter temperature (β=41.95, p = 0.017). It was observed that solar radiation and winter temperature shape the community types in high elevation temperate regions. In contrast, precipitation, solar radiation along with summer temperature determine the composition of sub-alpine communities, whereas solar radiation, winter temperature and soil pH determine the composition of alpine communities. This indicated that multiple environmental factors are responsible for this diversity. The research findings shed light on crucial factors influencing high elevation plant diversity, emphasizing the significance of understanding environmental correlations for effective conservation. This is pioneer study, which will act as a reference for future studies in Beas valley. This scientific foundation allows for prioritized conservation efforts, focusing on areas with specific environmental conditions influencing forest composition and plant diversity, ultimately contributing to better management and preservation of high elevation plant communities.

Time since fire as a driver of taxonomic and phylogenetic patterns of grassland plant communities

Fire plays a key role in grasslands, determining the distribution and evolution of species and boundaries with neighboring ecosystems. Evidence of community-wide responses to fire is largely based on taxonomic and functional descriptors, while the phylogenetic dimension is overlooked. Here we evaluated how the taxonomic and phylogenetic structure of grassland plant communities responded to a time since fire (TSF) gradient. We sampled 12 communities in Southern Brazil under varying TSF and calculated taxonomic species richness (S) and dominance (D), phylogenetic diversity (PD), and mean phylogenetic distances (MPD). We used Structural Equation Models to test the relationships between the environmental gradient and community descriptors. Communities with longer TSF presented higher PD and MPD but lower species richness and increased taxonomic dominance. These sites were dominated by monocots, specifically C4 grasses, but also presented exclusive clades, whereas recently-burned sites presented lower taxonomic dominance and more species distributed in a wider variety of clades. Our results indicate that these scenarios are interchangeable and dependent on fire management. Fire adaptation was not constrained by phylogenetic relatedness, contrasting with previous findings for tropical savannahs and indicating that temperate and tropical non-forest ecosystems from South America respond differently to fire, possibly due to different evolutionary histories.

Dispersal limitations and ecological adaptions shape phylogenetic diversity patterns of angiosperm woody plant communities along latitudinal and elevational gradients in East Asian islands

For centuries, ecologists have been captivated by the assembly of local communities from regional species pools, which gives rise to spatial diversity patterns. This study focused on hierarchical filtering process, which involves dispersal limitation and climatic constraint across regional to local scale, that underpins plant biodiversity patterns in East Asian islands, as one of the biodiversity hotspots with high endemicity. We used vegetation and species pool datasets of angiosperm woody plant communities collected from seven mountains across Japan to Taiwan to explore the relative contributions of local factors of individual plots, islands, latitude, elevation, and climatic variables related to the pattern of phylogenetic community assembly. Using linear regression and variation partitioning, we found that the island factor had the strongest filtering effect followed by latitude. Elevation and local factors (slope, aspect) accounted for a very small proportion of the variance in phylogenetic dispersion and community clade age between member species. Geographical factors involving islands, distance, and elevation had overriding filtering effects over climatic factors (minimum temperature of the coldest month, precipitation of the driest month) in shaping woody plant assembly patterns at the regional scale across East Asia islands. Tropical niche conservatism contributed to shaping woody plant communities in temperate region and high elevational regions on subtropical mountains as young and closely related species coexisted in those regions due to their adaptation to cold climates. This also explained the minor climate effects on species sorting in temperate mountains characterized by temperate-specific species pool which had already been filtered by cold climates. Inconsistent elevational phylogenetic diversity patterns in East Asia islands suggest a mountain-specific process that governs community assembly along elevational gradients, likely attributed to the location and climate of the mountain. These results suggest that historical factors (geohistorical isolation) related to islands and mountains contribute to in situ diversification that shaped plant diversity gradient from subtropical to temperate forests.

Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis

AbstractImaging spectroscopy is emerging as a leading remote sensing method for quantifying plant biodiversity. The spectral variation hypothesis predicts that variation in plant hyperspectral reflectance is related to variation in taxonomic and functional identity. While most studies report some correlation between spectral and field‐based (i.e., taxonomic and functional) expressions of biodiversity, the observed strength of association is highly variable, and the utility in applying spectral community properties to examine environmental drivers of communities remains unknown. We linked hyperspectral data acquired by airborne imaging spectrometers with precisely geolocated field plots to examine the spectral variation hypothesis along a temperate‐to‐boreal forest gradient in southern Québec, Canada. First, we examine the degree of association between spectral and field‐based dimensions of canopy tree composition and diversity. Second, we ask whether the relationships between field‐based community properties and the environment are reproduced when using spectral community properties. We found support for the spectral variation hypothesis with the strength of association generally greater for the functional than taxonomic dimension, but the strength of relationships was highly variable and dependent on the choice of method or metric used to quantify spectral and field‐based community properties. Using a multivariate approach (comparisons of separate ordinations), spectral composition was moderately well correlated with field‐based composition; however, the degree of association increased when univariately relating the main axes of compositional variation. Spectral diversity was most tightly associated with functional diversity metrics that quantify functional richness and divergence. For predicting canopy tree composition and diversity using environmental variables, the same qualitative conclusions emerge when hyperspectral or field‐based data are used. Spatial patterns of canopy tree community properties were strongly related to the turnover from temperate‐to‐boreal communities, with most variation explained by elevation. Spectral composition and diversity provide a straightforward way to quantify plant biodiversity across large spatial extents without the need for a priori field observations. While commonly framed as a potential tool for biodiversity monitoring, we show that spectral community properties can be applied more widely to assess the environmental drivers of biodiversity, thereby helping to advance our understanding of the drivers of biogeographical patterns of plant communities.

Wetland vegetation composition and ecology of Lake Abaya in southern Ethiopia.

Wetland vegetation and ecology of Lake Abaya in the southern Ethiopia was studied to determine floristic composition, plant community type and vegetation ecology. A total of 102 plots were laid along transects that were set up preferentially across areas where there were rapid changes in vegetation or marked environmental gradients to collect data on estimate of percentage aerial cover of plant species and environmental variables. Vegetation data was analyzed by agglomerative hierarchical cluster analysis using similarity ratio as a resemblance index and Ward's linkage method. Multivariate data analysis was performed using appropriate packages in R version 2.14.0. Canonical Correspondence Analysis (CCA) was used to explore the relationship between the species composition and environmental variables. The environmental data included in the CCA were determined using stepwise backward and forward selection of variables by ANOVA test. Statistical measurement regarding species diversity, richness and evenness of the plant community types was carried out by using Shannon-Wiener diversity indices. A total of 92 plant species belonging to 66 genera and 34 families were identified. Families Poaceae, Asteraceae, Fabaceae, Cyperaceae, Solanaceae, Euphorbiaceae and Amaranthaceae account for about 56.99% of the total proportion. Based on the cluster analysis, five plant community types were identified. The most important factors influencing the plant species composition and pattern of wetland plant communities were water drainage, water depth, land use, slope, altitude, and hydrogeomorphology. Therefore, these factors should be considered in future management and protection under the circumstance of climate change and human activities.

Plant spectral diversity from high‐resolution multispectral imagery detects functional diversity patterns in coastal dune communities

AbstractQuestionRemote sensing is a fundamental tool to monitor biodiversity and spectral diversity may represent a proxy for different biodiversity facets such as taxonomic (TD) and functional diversity (FD). We used fine‐resolution multispectral imagery to explore spectral diversity (SD) patterns across spatial scales (i.e., plot, transect, area), and assess SD relationships with TD and FD along an environmental gradient.LocationCoastal sand dune, Viareggio, Italy (“Migliarino–San Rossore–Massaciuccoli” Regional Park, 43°83′ N, 10°25′ E).MethodsWe measured TD as species richness, while SD and FD were computed using probability density functions based on pixel and species position in multivariate spaces. We compared SD and FD patterns in space occupation, and we tested whether these patterns are coordinated along the sea–inland gradient. We also assessed univariate relationships between SD and biodiversity facets, and we tested how these facets were partitioned across scales.ResultsWe found a strong correspondence between functional and spectral patterns in space occupation and along the environmental gradient, with a lack of significance when considering TD. However, TD and SD showed higher variation at broader scale while most FD variation occurred at plot level.ConclusionBy measuring FD and SD with a common methodological framework, we demonstrate that SD approximates functional patterns in plant communities. Moreover, we show that SD retrieved using high‐resolution images can capture different aspects of FD, and that the occupation of the spectral space is analogous to the occupation of the functional space.

A more effective approach for species-level classifications using multi-source remote sensing data: Validation and application to an arid and semi-arid grassland

The distribution of grassland communities significantly influences biodiversity conservation and resource management. Remote sensing datasets, such as Sentinel land cover images with high spatial and temporal resolution, have been commonly employed to simulate the distribution and community structure of plant species in grasslands. Nevertheless, the precision of grassland and community classification requires further enhancement for more effective grassland management. In response, our study presents a dynamic workflow for simulating the distribution of grassland plant species under different hydroclimatic conditions. Leveraging a random forest classifier with multi-source remote sensing features, we mapped the distribution of nine plant communities and six types of land cover in the upstream grasslands of the Xilingol River Basin, Inner Mongolia from 2017 to 2022. Utilizing the Google Earth Engine platform, our findings reveal a remarkable consistency in the overall spatiotemporal accuracy and classification precision of grassland communities across different years, even under varying hydroclimatic conditions. When critical features were carefully selected, the integration of Sentinel-1 (C-band synthetic aperture radar), Sentinel-2 (surface reflectance), SRTM DEM 30 m (Digital Elevation Model data), and MOD16A2.006 (evapotranspiration/latent heat flux product) data yielded a high overall accuracy ranging from 87.0 % to 89.5 % over multiple years. Our study not only determined the spatial patterns of various grassland plant communities but also explored the mechanism of their responses to different hydroclimatic conditions. The proposed approach holds practical implications for fine-scale grassland classification, providing valuable support for landscape classification and monitoring efforts. Furthermore, the insights derived from our findings offer valuable guidance for land managers and policymakers, aiding them in making informed decisions related to grassland conservation and sustainable land use planning.

Driving mechanisms of community biomass allocation along environmental gradients in different grasslands in China

A variable future climate would lead to changes in the biomass allocation pattern of plant communities, but its divergent changes under different environments have not been clearly explored, greatly limiting a better understanding of the responsess of grassland ecosystems to environmental changes. Herein, we conducted field samplings at 215 grassland sites in the Qinghai-Tibetan and Inner Mongolian Plateaus to analyze community biomass allocation patterns (specifically, the ratio of root to shoot, R/S) in various grasslands along environmental gradients. We found a gradual increase in R/S from humid to semi-arid and arid environments across both plateaus. In humid environment, soil factor had a significant effect on the R/S of alpine humid grassland, while climate factor had a significant effect on the R/S of humid grassland. In semi-arid environment, both climate and plant factors had significant effects on R/S in semi-arid grassland. In arid environments, climate and plant factors had significant effects on R/S in arid grassland. These findings emphasize the multifaceted role of environmental factors in shaping biomass allocations across diverse ecosystems, enriching our understanding of ecological dynamics. The current results are timely in advancing the fundamental understanding of the mechanisms of biomass allocation in grasslands and are useful for global research on grasslands in different environments.

Forest tree community ecology and plant–soil feedback: Theory and evidence

AbstractMounting evidence suggests that reciprocal interactions between plants and the soil microbiota can be a primary force that generates key macroscopic patterns of plant communities (coexistence, dominance, and succession) in forest ecosystems. The aim of this article is to review empirical and theoretical perspectives of plant–soil feedback research in the context of forest community ecology. I first use a simple theoretical model to get insights into an array of the dynamics generated by plant–soil feedback: negative plant–soil feedback maintains plant species diversity and reduces plant growth, while positive plant–soil feedback drives plant growth of certain species and hence their dominance. I then describe how ecologists have unveiled the enormously complex plant‐microbiota interaction (i.e., the soil conditioning experiment) and review the linkage of plant–soil feedback with three key plant community patterns: (i) dominance, (ii) spatial structure and (iii) succession. I highlight one belowground plant trait (mycorrhizal type) that can mediate these linkages: arbuscular mycorrhizal species tend to exhibit negative plant–soil feedback while ectomycorrhizal species tend to exhibit positive plant–soil feedback. Although mycorrhizal plant–soil feedback potentially explains the patterns of tree diversity from local to global scales, many questions remain. Future studies should expand plant–soil feedback theory to incorporate numerous other feedback mechanisms and test how mycorrhizal types mediate the net feedback effects that could propagate to shape large‐scale forest structures and dynamics.

Effects of Abiotic Factors on Plant Community Composition and Functional Traits in the Liaohe Estuary

The composition and functional traits of plant communities and their changes along an environmental gradient are important bases for maintaining the carbon sinks of estuarine wetlands. To clarify the succession pattern of plant community in an estuary along an environmental gradient, this study considered the Liaohe Estuary wetland as the research object and divided the dominant plant community into a Phragmites australis community and high-, medium-, and low-density Suaeda salsa communities. We employed redundancy analysis, variance decomposition, and multiple regression to examine the impact of an environmental gradient on the functional traits and spatial distributions of plant communities in the Liaohe Estuary wetland. The findings revealed that as the elevation decreased, the soil salinity increased and the water content decreased. The distribution of plant communities followed the order of P. australis, high-density S. salsa, medium-density S. salsa, low-density S. salsa, and bare flat areas. When the soil salinity exceeded 21 g/kg and the soil moisture content was below 17%, the conditions were no longer suitable for the growth of S. salsa or P. australis. Soil salinity, total nitrogen content, clay content, and elevation were the most critical environmental factors affecting the functional traits of the plant communities. Soil biochemical characteristics, soil texture, and the physical environment accounted for 28.9%, 23.12%, and 11.51%, respectively, of the variation in the spatial distribution of plant communities. The proportions of the suitable area for the high-, medium-, and low-density S. salsa were 13.1%, 53.78%, and 33.12%, respectively. The results provide a theoretical basis for further elucidating the degradation mechanisms of estuarine wetlands, developing an evaluation index system for estuarine wetland ecological restoration, and optimizing ecological protection and restoration strategies.

Global patterns and drivers of spatial autocorrelation in plant communities in protected areas

AbstractAimStochastic and deterministic (biotic factors such as intraspecies competition or abiotic factors) processes affect the spatial patterns of ecological communities. These processes can be quantitatively assessed based on spatial autocorrelation (SAC) parameters. However, the global patterns of SAC and their differences across vegetation types remain unknown. We aimed to (1) quantitatively assess the SAC global pattern in plant communities and their variation from 1990 to 2020 and (2) identify the key drivers of SAC in plant communities in protected areas (PAs).LocationGlobal.Time Period1990–2020.Major Taxa StudiedTerrestrial plants.MethodsUsing normalized difference vegetation index data extracted from remote sensing datasets, we calculated the SAC parameters, including the Nugget, Partial Sill (PSill), and Sill, in 147 samples from 49 PAs in 1990, 2000, 2010, and 2020. The random forest model was employed to identify the drivers among 10 annual and 120 monthly climatic variables.ResultsThe SAC patterns of plant communities in global PAs differed across vegetation types. It reached the highest in grasslands and evergreen needleleaved forests, mainly explained by annual energy metrics, and the lowest in tropical evergreen rain forests around equator and boreal coniferous forests near the Arctic Circle. From 1990 to 2020, the Nugget, PSill, and Sill decreased by 92.36%, 58.36%, and 60.61%, respectively, indicating biological homogeneity. Monthly climatic variables explain SAC variations better than annual ones.Main ConclusionsFrom 1990 to 2020, the SAC parameters decreased sharply across vegetation types, indicating an obvious biologically homogenous trend that was mainly driven by monthly climatic variation, vary across sites and vegetation types. Our results highlight the need to assess the SAC in different vegetation types separately to understand the shifts of global plant communities under climate change.

A study of plant community diversity based on quantitative analysis model and prediction model

Plant community species diversity is the pivot that connects ecosystem multi functionality and environmental change. In order to explore the influence of community species number on drought adaptation, this paper uses logistic fitting and residual verification formed by grayscale accumulation to obtain the population dynamics change curve under ideal conditions, followed by selecting indicators such as soil moisture amount and plant growth rate, and establishing a prediction model based on the plant growth pattern of plant communities under different weather cycles and the interaction mechanism between different species, and The conclusions were drawn, which provided a theoretical basis of the subsequent research on the population size under drought conditions.

Bidens pilosa (Asteraceae) invasion reshapes the pattern of plant communities and edaphic properties across the north-western Himalayan landscape

Development and economic growth, coupled with climate change and other environmental shifts, have made the unique and pristine mountainous regions vulnerable to plant invasions. While the effects of exotic plant invasions on community structure have been extensively studied in the lowlands, there is a dearth of such research in the altitudinal ecosystems. The objective of the present study was to investigate the ecological impact of Bidens pilosa (blackjack, Beggars tick; Asteraceae) on vegetation and soil dynamics across the north-western Himalayan landscape. Vegetation and soil sampling were conducted in paired invaded and control quadrats along an altitudinal gradient (300–1500 m asl) in the outer Himalayan region of Kangra, Himachal Pradesh, India. The presence of B. pilosa has a notable impact on reducing alpha diversity, with a more pronounced effect observed above 600 m asl. Pairwise beta diversity indices indicate that the invasion of B. pilosa has changed the natural species composition above 700 m asl, likely due to species turnover (i.e., species replacement). The results of NMDS and PERMANOVA analyses further support the notion that the invasion of B. pilosa has considerably homogenized the species composition along the selected elevational gradient. Further, significant variations in most of the soil parameters between the two invasion classes were observed within the elevation range of 600–1200 m asl. Overall, the results indicate that invasion by B. pilosa reshaped the patterns of floristic composition and soil properties in the north-western Himalayan landscape, leading to biotic and edaphic homogenization across an altitudinal gradient. The most substantial impact was noticed above the altitudinal range of 600 m asl, indicating that B. pilosa prefers mildly temperate climates over tropical ones in the studied area. It is pertinent to monitor and control the spread of B. pilosa in the Himalayan ecosystem to ensure the conservation of its unique biodiversity.

Environmental filtering and environmental stress shape regional patterns of riparian community assembly and functional diversity

Abstract Riparian plant communities are key to ecosystem functioning and important providers of ecosystem services on which wildlife and people depend. Ecosystem functioning and stability depend on functional diversity and redundancy. Therefore, understanding which and how different drivers shape community assembly processes and functional patterns is crucial. However, there is limited knowledge of these processes at larger scales for the entire riparian vascular plant community. Two community assembly processes dominate: environmental filtering, where species living in similar environments have similar traits leading to trait convergence; and limiting similarity, where similar traits cause species to compete more strongly leading to trait divergence. We assessed functional diversity patterns of riparian vascular plant communities across an Atlantic–Mediterranean biogeographical gradient in north Portugal. We used functional diversity indices and null models to detect community assembly processes and whether these processes change along environmental gradients. We hypothesised that environmental filtering associated with precipitation and aridity would be the prevailing assembly process at a regional scale. We also expected a shift from environmental filtering to limiting similarity as precipitation‐related stress declined. As hypothesised, patterns of functional diversity were consistent with environmental filtering of species occurrences at the regional scale. Functional patterns were also consistent with a shift between environmental filtering and limiting similarity as cold and aridity stress declined. Under stressful environmental conditions, communities showed lower functional divergence and richness than expected by chance. Environmental filtering was more strongly associated with minimum temperatures than precipitation and aridity. Underlining the need for hierarchical approaches and the analysis of multiple climatic stressors, our results highlighted the relevance of large‐scale environmental stress gradients and the potential role of community assembly in influencing riparian functional diversity. Alterations in stress filters due to climate change will affect assembly processes and functional patterns, probably affecting ecosystem functioning and stability.