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Accurately estimating leaf functional traits across different species and canopy layers in subtropical evergreen broad-leaf forests remains a significant challenge due to the complexity of canopy structures and spectral noise. Although hyperspectral remote sensing holds substantial promise, existing methods struggle to deliver robust models capable of generalizing across diverse species and environmental conditions. This study aimed to develop a robust hyperspectral estimation approach for eight leaf traits across six species and three canopy layers, integrating successive projections algorithm (SPA) and random forest (RF) modeling. Utilizing 267 leaf samples and hyperspectral reflectance data acquired via a tower crane in Dinghushan National Nature Reserve, Guangdong Province, China, we demonstrated that the SPA-RF model, when applied to first derivative reflectance (FDR) data, significantly enhanced the accuracy and transferability of leaf trait estimations. The integration of SPA for wavelength selection and RF for modeling represented a robust approach, effectively mitigating the complexities introduced by species diversity and canopy heterogeneity. Leaf trait estimations derived from upper canopy layer samples generally yielded greater precision than those from lower and middle layers. Furthermore, species adapted to high-light environments (sun-tolerant) offered more accurate estimations than those adapted to low-light conditions (shade-tolerant). Among the eight leaf traits studied, flavonoid content, nitrogen balance index, and SPAD (relative leaf chlorophyll content) values emerged as more reliably estimated compared to carbon, nitrogen, phosphorus, equivalent water thickness, and specific leaf area. These findings illuminate the influence of canopy layer and species-specific traits on the precision of leaf trait estimations using hyperspectral remote sensing. The study’s insights emphasize the need for species- and canopy layer-specific approaches in ecological monitoring and conservation efforts.

The relationship of mycorrhizal associations with latitudinal gradients in tree beta-diversity is unexplored. Using a global dataset approach, this study examines how trees with arbuscular mycorrhizal and ectomycorrhizal associations contribute to latitudinal beta-diversity patterns and the environmental controls of these patterns.

Abstract Identifying patterns and drivers of plant community assembly has long been a central issue in ecology. Many studies have explored the above questions using a trait‐based approach; however, there are still unknowns around how patterns of plant functional traits vary with environmental gradients. In this study, the responses of individual and multivariate trait dispersions of 134 species to soil resource availability were examined based on correlational analysis and torus‐translation tests across four spatial scales in a subtropical forest, China. Results indicated that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource (available phosphorus) showed negative relationships with trait dispersions, non‐limited resource (available potassium) showed positive relationships with trait dispersions, and saturated resource (available nitrogen) had no effect on trait dispersions. Moreover, compared with the stem (wood density) and architectural trait (maximum height), we found that leaf functional traits can well reflect the response of plants to nutrient gradients. Lastly, the spatial scale only affected the magnitude but not the direction of the correlations between trait dispersions and environmental gradients. Overall, the results highlight the importance of soil resource availability and spatial scale in understanding how plant functional traits respond to environmental gradients.

Plant functional traits are rarely used in tree species classification, and the impact of vertical canopy positions on collecting samples for classification also remains unclear. We aim to explore the feasibility and effectiveness of leaf traits in classification, as well as to detect the effect of vertical position on classification accuracy. This work will deepen our understanding of the ecological mechanism of natural forest structure and succession from new perspectives. In this study, we collected foliar samples from three canopy layers (upper, middle and lower) and measured their spectra, as well as eight well-known leaf traits. We used a leaf hyperspectral reflectance (LHR) dataset, leaf functional traits (LFT) dataset and LFT + LHR dataset to classify six dominant tree species in a subtropical evergreen broad-leaved forest. Our results showed that the LFT + LHR dataset achieved the highest classification results (overall accuracy (OA) = 77.65% and Kappa = 0.73), followed by the LFT dataset (OA = 74.26% and Kappa = 0.69) and the LHR dataset (OA = 69.06% and Kappa = 0.63). Along the vertical canopy, the OA and Kappa increased from the lower to the upper layers, and the combination data of the three canopy layers achieved the highest accuracy. For the individual tree species, the shade-tolerant species (including Machilus chinensis, Cryptocarya chinensis and Cryptocarya concinna) produced higher accuracies than the light-demanding species (including Schima superba and Castanopsis chinensis). Our results provide an approach for enhancing tree species recognition from the plant physiology and biochemistry perspective and emphasize the importance of vertical direction in forest community research.

What causes variation in species abundance for a given site remains a central question in community ecology. Foundational to trait-based ecology is the expectation that functional traits determine species abundance. However, the relative success of using functional traits to predict relative abundance is questionable. One reason is that the diversity in plant function is greater than that characterized by the few most commonly and easily measurable traits. Here, we measured 10 functional traits and the stem density of 101 woody plant species in a 200,000 m2 permanent, mature, subtropical forest plot (high precipitation and high nitrogen, but generally light- and phosphorus-limited) in southern China to determine how well relative species abundance could be predicted by functional traits. We found that: (1) leaf phosphorus content, specific leaf area, maximum CO2 assimilation rate, maximum stomata conductance, and stem hydraulic conductivity were significantly and negatively associated with species abundance, (2) the ratio of leaf nitrogen content to leaf phosphorus content (N:P) and wood density were significantly positively correlated with species abundance; (3) neither leaf nitrogen content nor leaf turgor loss point were related to species abundance; (4) a combination of N:P and maximum stomata conductance accounted for 44% of the variation in species’ abundances. Taken together, our findings suggested that the combination of these functional traits are powerful predictors of species abundance. Species with a resource-conservative strategy that invest more in their tissues are dominant in the mature, subtropical, evergreen forest.

[This corrects the article DOI: 10.1371/journal.pone.0238478.].

Little attention has been paid to the impact of vertical canopy position on the leaf spectral properties of tall trees, and few studies have explored the ability of leaf spectra to characterize the variation of leaf traits across different canopy positions. Using a tower crane, we collected leaf samples from three canopy layers (lower, middle, and upper) and measured eight leaf traits (equivalent water thickness, specific leaf area, leaf carbon content, leaf nitrogen content, leaf phosphorus content, leaf chlorophyll content, flavonoid, and nitrogen balance index) in a subtropical evergreen broadleaved forest. We evaluated the variability of leaf traits and leaf spectral properties, as well as the ability of leaf spectra to track the variation of leaf traits among three canopy layers for six species within the entire reflectance spectrum. The results showed that the eight leaf traits that were moderately or highly correlated with each other showed significant differences along the vertical canopy profile. The three canopy layers of leaf spectra showed contrasting patterns for light-demanding (Castanopsis chinensis, Castanopsis fissa, Schima superba, and Machilus chinensis) and shade-tolerant species (Cryptocarya chinensis and Cryptocarya concinna) along the vertical canopy profile. The spectra at the lower and upper canopy layers were more sensitive than the middle layer for tracking the variation of leaf chlorophyll and flavonoid content. Our results revealed that it is important to choose an appropriate canopy layer for the field sampling of tall trees, and we suggest that flavonoid is an important leaf trait that can be used for mapping and monitoring plant growth with hyperspectral remote sensing.

Environments in both biotic and abiotic ecosystems have been affected by the colonization of non-native flora. In this study, we examined the effect of Bidens alba invasion on different land-use types along a coastline in southern China. Bacterial communities in each site were determined using 16S rDNA sequencing, and soil physicochemical properties were analyzed using standard methods. Although our results indicated that B. alba invasion did not have a significant effect on the alpha diversity of bacteria, it caused significant differences in soil bacterial community composition between invaded and uninvaded soil across different land-use types. Beta diversity and several physicochemical properties in forest, orchard and waterfront environments were recorded to be more susceptible to B. alba invasion. A high proportion of the variation of bacterial communities can be explained by a combination of environmental variables, indicating that environmental selection rather than plant invasion is a more effective process in coastal microbial assemblages. By comparing topological roles of shared OTUs among invaded and uninvaded soil, keystone taxa in invaded soil were identified. Acidobacteria was the major phyla involved in the invasive process which could be driven by environmental selection. How key phyla react in our experiment should be verified by further studies.

Tree size distributions have long been of interest to ecologists and foresters because they reflect fundamental demographic processes. Previous studies have assumed that size distributions are often associated with population trends or with the degree of shade tolerance. We tested these associations for 31 tree species in a 20 ha plot in a Dinghushan south subtropical forest in China. These species varied widely in growth form and shade-tolerance. We used 2005 and 2010 census data from that plot. We found that 23 species had reversed J shaped size distributions, and eight species had unimodal size distributions in 2005. On average, modal species had lower recruitment rates than reversed J species, while showing no significant difference in mortality rates, per capita population growth rates or shade-tolerance. We compared the observed size distributions with the equilibrium distributions projected from observed size-dependent growth and mortality. We found that observed distributions generally had the same shape as predicted equilibrium distributions in both unimodal and reversed J species, but there were statistically significant, important quantitative differences between observed and projected equilibrium size distributions in most species, suggesting that these populations are not at equilibrium and that this forest is changing over time. Almost all modal species had U-shaped size-dependent mortality and/or growth functions, with turning points of both mortality and growth at intermediate size classes close to the peak in the size distribution. These results show that modal size distributions do not necessarily indicate either population decline or shade-intolerance. Instead, the modal species in our study were characterized by a life history strategy of relatively strong conservatism in an intermediate size class, leading to very low growth and mortality in that size class, and thus to a peak in the size distribution at intermediate sizes.

We assessed the effects of topographic heterogeneity and stem density on species composition between grains of different sizes (20 × 20, 50 × 50, and 100 × 100 m), based on partial Mantel tests. Similarity in species composition was measured by the abundance-based Jaccard index (C_J) and by an index that incorporates phylogenetic information into C_J (pC_J). Plants were divided into five groups, arbor, subarbor, and shrub according to life form and two other groups: species that produce dry fruits (PDF) and that produce fleshy fruits (PFF). C_J and pC_J between any two grains at each grain size were calculated separately for these groups and for all species combined. In order to examine what influences C_J and pC_J, we analyzed their correlations with topographic heterogeneity variables and two dispersal limitation-related variables (stem and topographic resistance). Our data indicate that at all three grain sizes, C_J and pC_J decrease with increasing distance for all plant groups. Dispersal limitation and topographic heterogeneity were both important at 20 × 20 and 50 × 50 m grain sizes for C_J and pC_J of all plant groups; and at 100 × 100 m grain size, topographic heterogeneity dominates over dispersal limitation for some plant groups. C_J and pC_J of PDFs are less negatively correlated with stem resistance than those of PFFs. We conclude that both beta diversity and phylobetadiversity are dependent on plant groups and grain sizes. [ABSTRACT FROM AUTHOR]

The spatial dispersion of individuals in a species is an important pattern that is controlled by many mechanisms. In this study we analyzed spatial distributions of tree species in a large-scale (20 ha) stem-mapping plot in a species-rich subtropical forest of China. O-ring statistic was used to measure spatial patterns of species with abundance >10. Ω0–10, the mean conspecific density within 10 m of a tree, was used as a measure of the intensity of aggregation of a species. Our results showed: (1) aggregated distribution was the dominant pattern in the plot. The percentage of aggregated species decreased with increased spatial scale. (2) The percentages of significantly aggregated species decreased from abundant to intermediate and to rare species. Rare species was more strongly aggregated than common species. Aggregation was weaker in larger diameter classes. (3) Seed traits determined the spatial patterns of trees. Seed dispersal mode can influence spatial patterns of species, with species dispersed by both modes being less clumped than species dispersed by animal or wind, respectively. Considering these results, we concluded that seed dispersal limitation, self-thinning and habitat heterogeneity primarily contributed to spatial patterns and species coexistence in the forest. [ABSTRACT FROM AUTHOR]

Despite the wide variation in the structural characteristics in natural forests, tree size distribution show fundamental similarities that suggest general underlying principles. The metabolic ecology theory predicts the number of individual scales as the −2 power of tree diameter. The demographic equilibrium theory predicts tree size distribution starting from the relationship of size distributions with growth and mortality at demographic equilibrium. Several analytic predictions for tree size distributions are derived from the demographic equilibrium theory, based on different growth and mortality functions. In addition, some purely phenomenological functions, such as polynomial function, have been used to describe the tree size distributions. In this paper, we use the metabolic ecology theory, the demographic equilibrium theory and the polynomial function to predict the tree size distribution for both the whole community and each species in an old-growth temperate forest in northeastern China. The results show that metabolic ecology theory predictions for the scaling of tree abundance with diameter were unequivocally rejected in the studied forest. Although these predictions of demographic theory are the best models for most of the species in the temperate forest, the best models for some species ( Tilia amurensis, Quercus mongolica and Fraxinus mandshurica) are compound curves (i.e. rotated sigmoid curves), best predicted by the polynomial function. Hence, the size distributions of natural forests were unlikely to be invariant and the predictive ability of general models was limited. As a result, developing a more sophisticated theory to predict tree size distributions remains a complex, yet tantalizing, challenge. [ABSTRACT FROM AUTHOR]