50-ha Plot Research Articles

High beta diversity of gaps contributes to plot-level tree diversity in a tropical forest.

Canopy gaps are widely recognized as being crucial for maintaining the diversity of forest tree communities. But empirical studies have found mixed results because the differences in diversity between individual gaps and non-gaps are often small and statistically undetectable. One overlooked factor, however, is how small individual gap versus non-gap differences may accumulate across sites and potentially have a large effect on forest diversity at the plot scale. Our study investigated sapling richness, density, and composition in 124 treefall gaps, and 200 non-gap sites in the 50-ha tropical forest plot at Barro Colorado Island (BCI), Panama. Additionally, we analyzed species accumulation curves to understand how species richness increases with increasing stem numbers. We observed that sapling richness and density were only slightly higher in gaps 7 years after formation and statistically indistinguishable from non-gaps after 12 years. However, species accumulation curves across multiple gaps were substantially higher than those across non-gaps. Species composition showed small differences between individual gaps and non-gaps but differed significantly between collections of gaps and non-gaps. Specifically, 55 species specialized in 7-year-old gaps compared with 24 in non-gaps; of these, 23 gap-specialized species and zero non-gap species were pioneers. Our results indicate that tree species richness is higher in gaps because of both higher stem density and the presence of gap-specialized species. Our study has finally provided compelling evidence to support the idea that gaps enhance the overall diversity of tropical forest tree communities.

Unraveling the drivers and impacts of leaf phenological diversity in a subtropical forest: A fine-scale analysis using PlanetScope CubeSats.

Leaf phenology variations within plant communities shape community assemblages and influence ecosystem properties and services. However, questions remain regarding quantification, drivers, and productivity impacts of intra-site leaf phenological diversity. With a 50-ha subtropical forest plot in China's Heishiding Provincial Nature Reserve (part of the global ForestGEO network) as a testbed, we gathered a unique dataset combining ground-derived abiotic (topography, soil) and biotic (taxonomic diversity, functional diversity, functional traits) factors. We investigated drivers underlying leaf phenological diversity extracted from high-resolution PlanetScope data, and its influence on aboveground biomass (AGB) using structural equation modeling (SEM). Our results reveal considerable fine-scale leaf phenological diversity across the subtropical forest landscape. This diversity is directly and indirectly influenced by abiotic and biotic factors (e.g. slope, soil, traits, taxonomic diversity; r2 = 0.43). While a notable bivariate relationship between AGB and leaf phenological diversity was identified (r = -0.24, P < 0.05), this relationship did not hold in SEM analysis after considering interactions with other biotic and abiotic factors (P > 0.05). These findings unveil the underlying mechanism regulating intra-site leaf phenological diversity. While leaf phenology is known to be associated with ecosystem properties, our findings confirm that AGB is primarily influenced by functional trait composition and taxonomic diversity rather than leaf phenological diversity.

Cost-effective and accurate monitoring of flowering across multiple tropical tree species over two years with a time series of high-resolution drone imagery and deep learning

Detection of flowering and quantification of flowering phenology are key to monitoring the reproduction of tropical trees and their response to global change. However, effective monitoring of flowering over various scales from individuals to forest ecosystem levels is lacking due to the relatively small sizes of flowers, diverse flowering strategies across species, and the short duration of flowering, making accurate flower detection difficult. Drone-based surveys require less time and human resources than traditional ground-based flower surveys and thus may be able to help address this in a cost-effective manner but remain underexplored in species-rich tropical forest ecosystems. Here, we developed a method that integrated the Residual Networks 50 (ResNet50) deep learning algorithm with high resolution imagery (c. 0.05 m) from monthly drone surveys done in a 50-ha tropical forest plot on Barro Colorado Island (BCI), Panamá, over 2018–2020 to detect a diversity of flowering species in this tree community and to track the timing of flowering throughout the year. We built a comprehensive training library of canopy components (flower, leaf, branch, and shade) from this forest plot throughout the study period, trained a single deep learning model across all drone imagery, and validated it using five-fold cross validation at the pixel scale. We further generated image- and tree-crown-specific supervised classifications to evaluate the deep learning model at the tree-crown scale. Our deep learning method accurately classified flowers (User’s accuracy = 95.3 %, Producer’s accuracy = 85.8 %) while maintaining high predictive power for the other three classes (Overall accuracy = 98.4 %). Our results also demonstrated high consistency against tree-crown-specific supervised classifications for flower (r2 = 0.85), leaf (r2 = 0.84), and branch (r2 = 0.92) components, with lower agreement observed for the shade component (r2 = 0.59). These results demonstrate the effectiveness of our method in advancing fine-scale flower monitoring in the tropics, with potential to be extended to other regions or other remote sensing platforms with frequent high-resolution monitoring. The method will allow us to better monitor flowering in tropical forests and improve our understanding of how phenology and reproductive success may be affected by climate change.

Monoculture plantations impede forest recovery: Evidence from the regeneration of lowland subtropical forest in Hong Kong

Anthropogenic disturbance has led to widespread clearance and degradation of tropical forests, and tree planting has been promoted as an effective solution for recovery. However, trees have been overwhelmingly planted in monocultures or low-diversity mixes and this is expected to have profound, lasting impacts on forest structure, diversity, and functioning. In this study, we tested the extent to which historical vegetation transition types (VTTs) constrain forest recovery in a secondary tropical landscape in Hong Kong, South China. To do so, we overlaid vegetation types (forest, shrubland, pine plantation, grassland) identified in aerial photographs taken in 1956 and 1963 of a 20-ha plot situated in Tai Po Kau Nature Reserve, allowing us to define six historic VTTs, namely: FF (forest to forest), GP (grassland to plantation), GS (grassland to shrubland), SS (shrubland to shrubland), SF (shrubland to forest), and SP (shrubland to plantation). We compared present-day forest structure and species diversity among these VTTs, as determined from a census conducted in 2015, using incidence- and abundance-based rarefaction and extrapolation, and we assessed species’ association within VTTs using a torus translation test. Our results reveal that stem density and species diversity in naturally regenerated forests were more similar to those of old-growth forest, whereas species diversity in areas occupied by pine plantations was significantly lower as compared with naturally regenerated areas. Despite 60 years of recovery, pine plantations were characterised by a significantly greater proportion of negatively associated species, and late-seral species were still predominantly confined to old-growth patches. Present-day species distribution is chiefly explained by the combined effects of topography and VTT (17.1%), with VTT alone explaining 4.4%. Our study demonstrates that VTT has a significant long-term impact on forest regeneration and community assembly and, importantly, that monocultural plantations (forest plantation) can greatly impede forest recovery. Remnant old-growth forest patches merit priority protection, and active restoration, including thinning and enhancement planting, is necessary to facilitate forest succession.

Effects of tree sex, maturity, local abiotic, and biotic neighborhoods on the growth of a subtropical dioecious tree species Diospyros morrisiana.

Understanding the drivers of the growth in long-lived woody trees is the key to predicting their responses to and maintaining their populations under global change. However, the role of tree sex and differential investment to reproduction are often not considered in models of individual tree growth, despite many gymnosperm and angiosperm species having separate male and female sexes. Thus, better models of tree growth should include tree sex and life stage along with the abiotic and biotic neighborhoods. We used a sex-specific molecular marker to determine the sex of 2188 individual trees >1 cm DBH of the dioecious tree species Diospyros morrisiana in a 50-ha subtropical forest plot in China. We used long-term census data from about 300,000 trees, together with 625 soil samples and 2352 hemispherical photographs to characterize the spatially explicit biotic and abiotic neighborhoods. We found a male-biased effective sex ratio and a female-biased overall population sex ratio of D. morrisiana. No sex spatial segregation was detected for the overall population, mature, or immature trees. Immature trees grew faster than mature trees and females grew slower than males. Further, conspecific neighbors significantly decreased tree growth, while the abiotic neighborhood showed no significant effect. Our findings suggest that variation in resource allocation patterns within and across individual trees of different sexes and life-history stages should be more widely accounted for in models of tree growth. In addition, our study highlights the importance of sex-specific molecular markers for studying populations of long-lived dioecious tree species.

How does functional distinctiveness affect single species contribution to β diversity? Evidence from a subtropical forest plot in southern China

To biologically interpret β diversity patterns, in terms of species characteristics, needs to quantify how each individual species contributes to overall β diversity (SCBD). However, the lack of studies linking SCBD to functional traits hinders to explore the full potential of the approach in biodiversity conservation. Here, we combined census data, species functional traits, and environmental variables from a 50-ha stem-mapped forest plot in southern China, with the aim to disentangle the relationship among SCBD, species functional traits and niche properties. We used nine functional traits to estimate species functional distinctiveness, and eleven environmental variables were used to compute species niche properties (niche position and niche breadth). Structural equation modeling (SEM) was applied to analyze how functional distinctiveness and niche properties jointly influenced SCBD. Results found that species with more unique trait combinations (higher functional distinctiveness) occupied marginal niche position and maintained smaller niche breadths and thus contributed less to overall β diversity. Meanwhile, functional distinctiveness and niche properties jointly determined SCBD. In addition, we found a negative effect of functional distinctiveness on SCBD, which implies the urgency of developing better biodiversity conservation strategies by unravelling the linkage between SCBD and ecosystem multifunctionality. These findings contribute to a better understanding of how species characteristics affect β diversity and making SCBD more applicable in biodiversity conservation.

Potential losses of animal-dispersed trees due to selective logging in Amazonian forest concessions

Fruits and seeds are key food resources for most Amazonian mammals and birds. Selective logging is an increasingly dominant land use in the region that can deplete these resources over large areas. However, this potential impact remains poorly studied. Here we assess potential losses of animal-dispersed (endozoochorous and synzoochorous) trees resulting from reduced-impact logging in Amazonian forest concessions. We use data from forestry surveys conducted by concession companies that include the location, identity and fate (logged or not) of large (≥ 40 cm diameter at breast height) individual trees within concessions to quantify absolute and relative losses of animal-dispersed trees in the landscape. We found that most individual trees (66%) within concessions belong to animal-dispersed genera. However, despite their predominance these trees were significantly less targeted for logging than abiotically-dispersed trees so that their losses were much lower than expected based on overall harvest intensities. However, at least ten percent of all large animal-dispersed trees were lost from the entire landscape, with site-level (50-ha plots) losses sometimes exceeding one third of all animal-dispersed trees. Results suggest that the relatively low level of logging for animal-dispersed trees can still deplete frugivore resources in selectively logged forests.

Body size determines multitrophic soil microbiota community assembly associated with soil and plant attributes in a tropical seasonal rainforest.

To understand soil biodiversity we need to know how soil communities are assembled. However, the relationship between soil community assembly and environmental factors, and the linkages between soil microbiota taxonomic groups and their body sizes, remain unexplored in tropical seasonal rainforests. Systematic and stratified random sampling was used to collect 243 soil and organism samples across a 20-ha plot in a tropical seasonal rainforest in southwestern China. High-throughput sequencing, variation analysis and principal coordinates of neighbourhood matrices were performed. Soil community composition, spatial distribution and assembly processes based on propagule size (including archaea, bacteria, fungi and nematodes) were investigated. The results showed that: (i) the community assembly of small soil microorganisms (bacteria, fungi) was mostly influenced by stochastic processes while that of larger soil organisms (nematodes) was more deterministic; (ii) the independent effects of habitat (including soil and topographic variables) and its interaction with plant attributes for community structure significantly decreased with increasing body size; and (iii) plant leaf phosphorus directly influenced the spatial distribution of soil-available phosphorus, which indicates their indirect impact on the assembly of the soil communities. Our data suggest that the assembly of multitrophic soil communities can be explained to some extent by changes in above-ground plant attributes. This highlights the importance of above- and below-ground linkages in influencing multitrophic soil microbiota community assembly.

Effects of fire disturbance on species and functional compositions vary with tree sizes in a tropical dry forest.

BackgroundDisturbances are crucial in determining forest biodiversity, dynamics, and ecosystem functions. Surface fire is a significant disturbance in tropical forests, but research on the effect of surface fire on structuring species and functional composition in a community through time remains scarce. Using a 20-year dataset of tree demography in a seasonal evergreen tropical forest in Thailand, we specifically addressed two essential questions: (1) What is the pattern of temporal turnover in species and functional composition in a community with frequent fire disturbance? (2) How did the temporal turnover vary with tree size?MethodsWe analyzed species compositional and functional temporal turnovers in four different tree size classes among five tree censuses. We quantified species turnover by calculating Bray-Curtis dissimilarity, and investigated its underlying mechanisms by comparing pairwise dissimilarity of functional traits with simulations from null models. If fire disturbances contribute more to a stochastic process, the functional composition would display a random pattern. However, if they contribute more towards a deterministic process, the functional composition should reveal a non-random pattern.ResultsOver 20 years (1994–2014), we observed changes in species composition, whereas functional composition remained relatively stable. The temporal turnover patterns of species and functional compositions varied with tree sizes. In particular, temporal functional turnover shifted very little for large trees, suggesting that changes in species composition of larger trees are contributed by species with similar functional traits through time. The temporal functional composition turnovers of smaller trees (DBH ≤ 5 cm) were mostly at random. We detected a higher functional turnover than expected by null models in some quadrats throughout the 50-ha study plot, and their observed turnover varied with diameter classes.ConclusionsSpecies compositional changes were caused by changes in the abundance of species with similar functional traits through time. Temporal functional turnover in small trees was random in most quadrats, suggesting that the recruits came from the equal proportions of surviving trees and new individuals of fast-growing species, which increased rapidly after fires. On the other hand, functional composition in big trees was more likely determined by surviving trees which maintained higher functional similarities than small trees through time. Fire disturbance is important for ecosystem functions, as changing forest fire frequency may alter forest turnover, particularly in functional composition in the new recruits of this forest.

Using intraspecific variation of functional traits and environmental factors to understand the formation of nestedness patterns of a local forest community

Abstract The concept of nestedness originated from the field of biogeography decades ago and has been widely used in metacommunities and biological interaction networks, but there is still a lack of research within local communities. Moreover, studies on nestedness usually rarely incorporate the functional traits of the species and the environmental characteristics of the sites. In this study, we constructed a species presence–absence matrix of a 50-ha forest plot, used the simulated annealing algorithm to reveal the maximum nested structure and further tested the significance of nestedness patterns by constructing null ensembles. The nested ranks were used to represent the orders of species and quadrats in the maximum nestedness matrix. The regression tree analysis was used to reveal the relationships of nested ranks with environmental factors and functional traits. We found that the co-occurrence pattern of local plant communities was significantly nested. The regression tree results showed that the nested ranks of quadrats were determined by soil available phosphorus, soil water content, soil organic carbon and soil pH. Intraspecific variation of functional traits, including leaf C, leaf pH, leaf dry matter content and maximum photosynthetic rate rather than means of functional traits, provided a better explanation for the formation of species’ nested ranks. Understanding the causes of species and quadrats nested ranks provides novel lens and useful insights into ecological processes underlying nestedness, and further improves our knowledge of how local plant communities are assembled.

Spatial-temporal dependence of the neighborhood interaction in regulating tree growth in a tropical rainforest

The intensity of interactions among tree individuals in forests is regulated by distance and time. However, few studies have considered the variability of neighborhood competition with varying spatial and temporal scales simultaneously. Based on census data of a 50-ha plot on Barro Colorado Island (BCI) during 1981–2015, we analyzed the variation in the relationship between the neighborhood interaction, represented as the neighborhood competition index (NCI), and the tree growth rate of 41,965 individuals from 211 species along a gradient of the neighborhood radius and over time. The results showed that the neighborhood interaction negatively impacted tree growth, especially for smaller trees, across spatial and temporal scales. The strength of the NCI–growth relationship was scale- and time-dependent. This relationship intensified initially with the increasing neighborhood radius and then plateaued at an average of about 20 m from the target trees, indicating the strong influence from neighbors could be detected at a distance up to 50 m or even 100 m. The intensifying tendency of the NCI–growth relationship over time probably results from the warming trend in recent years or the continuous radial growth of the BCI forest. We emphasize the importance of individual interactions in dynamic forest growth, and that an appropriate radius and forest age should be considered for the neighborhood analysis.

Root-associated fungal community reflects host spatial co-occurrence patterns in a subtropical forest

Plant roots harbor and interact with diverse fungal species. By changing these belowground fungal communities, focal plants can affect the performance of surrounding individuals and the outcome of coexistence. Although highly host related, the roles of these root-associated fungal communities per se in host plant spatial co-occurrence is largely unknown. Here, we evaluated the host dependency of root-associated communities for 39-plant species spatially mapped throughout a 50-ha subtropical forest plot with relevant environmental properties. In addition, we explored whether the differentiation in root fungal associations among plant species can reflect their observed co-occurrence patterns. We demonstrated a strong host-dependency by discriminating the differentiation of root-associated fungal communities regardless of background soil heterogeneity. Furthermore, Random Forest modeling indicated that these nonrandom root fungal associations significantly increased our ability to explain spatial co-occurrence patterns, and to a greater degree than the relative abundance, phylogenetic relatedness, and functional traits of the host plants. Our results further suggested that plants harbor more abundant shared, “generalist” pathogens are likely segregated, while hosting more abundant unique, “specialist” ectomycorrhizal fungi might be an important strategy for promoting spatial aggregation, particularly between early established trees and the heterospecific adults. Together, we provide a conceptual and testable approach to integrate this host-dependent root fungal “fingerprinting” into the plant diversity patterns. We highlight that this approach is complementary to the classic cultivation-based scheme and can deepen our understanding of the community-level effect from overall fungi and its contribution to the pairwise plant dynamics in local species-rich communities.

Common spatial patterns of trees in various tropical forests: Small trees are associated with increased diversity at small spatial scales.

Tropical forests are notable for their high species diversity, even on small spatial scales, and right‐skewed species and size abundance distributions. The role of individual species as drivers of the spatial organization of diversity in these forests has been explained by several hypotheses and processes, for example, stochastic dilution, negative density dependence, or gap dynamics. These processes leave a signature in spatial distribution of small trees, particularly in the vicinity of large trees, likely having stronger effects on their neighbors. We are exploring species diversity patterns within the framework of various diversity‐generating hypotheses using individual species–area relationships. We used the data from three tropical forest plots (Wanang—Papua New Guinea, Barro Colorado Island—Panama, and Sinharaja—Sri Lanka) and included also the saplings (DBH ≥ 1 cm). Resulting cross‐size patterns of species richness and evenness reflect the dynamics of saplings affected by the distribution of large trees. When all individuals with DBH ≥1 cm are included, ~50% of all tree species from the 25‐ or 50‐ha plot can be found within 35 m radius of an individual tree. For all trees, 72%–78% of species were identified as species richness accumulators, having more species present in their surroundings than expected by null models. This pattern was driven by small trees as the analysis of DBH >10 cm trees showed much lower proportion of accumulators, 14%–65% of species identified as richness repellers and had low richness of surrounding small trees. Only 11%–26% of species had lower species evenness than was expected by null models. High proportions of species richness accumulators were probably due to gap dynamics and support Janzen–Connell hypothesis driven by competition or top‐down control by pathogens and herbivores. Observed species diversity patterns show the importance of including small tree size classes in analyses of the spatial organization of diversity.

Traits, strategies, and niches of liana species in a tropical seasonal rainforest

Plant functional traits and strategies hold the promise to explain species distribution, but few studies have linked multiple traits to multiple niche dimensions (i.e., light, water, and nutrients). Here, we analyzed for 29 liana species in a Chinese tropical seasonal rainforest how: (1) trait associations and trade-offs lead to different plant strategies; and (2) how these traits shape species’ niche dimensions. Eighteen functional traits related to light, water, and nutrient use were measured and species niche dimensions were quantified using species distribution in a 20-ha plot combined with data on canopy gaps, topographic water availability, and soil nutrients. We found a tissue toughness spectrum ranging from soft to hard tissues along which species also varied from acquisitive to conservative water use, and a resource acquisition spectrum ranging from low to high light capture and nutrient use. Intriguingly, each spectrum partly reflected the conservative–acquisitive paradigm, but at the same time, the tissue toughness and the resource acquisition spectrum were uncoupled. Resource niche dimensions were better predicted by individual traits than by multivariate plant strategies. This suggests that trait components that underlie multivariate strategy axes, rather than the plant strategies themselves determine species distributions. Different traits were important for different niche dimensions. In conclusion, plant functional traits and strategies can indeed explain species distributions, but not in a simple and straight forward way. Although the identification of global plant strategies has significantly advanced the field, this research shows that global, multivariate generalizations are difficult to translate to local conditions, as different components of these strategies are important under different local conditions.

Trait hierarchies are stronger than trait dissimilarities in structuring spatial co-occurrence patterns of common tree species in a subtropical forest.

The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co‐occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co‐occur either due to environmental filtering or due to competitive exclusion of inferior competitors (hereafter hierarchical competition).We used a fully mapped 50‐ha subtropical forest plot in southern China to explore how pairwise spatial associations between saplings and between adult trees were influenced by trait dissimilarity and hierarchy in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering, and hierarchical competition on species co‐occurrence.We found that trait dissimilarity was generally negatively related to interspecific spatial associations for both saplings and adult trees across spatial scales, meaning that species with similar trait values were more likely to co‐occur and thus supporting environmental filtering or hierarchical competition. We further found that trait hierarchy outweighed trait dissimilarity in structuring pairwise spatial associations, suggesting that hierarchical competition played a more important role in structuring our forest community than environmental filtering across life stages.This study employed a novel method, by offering the integration of pairwise spatial association and trait dissimilarity as well as trait hierarchy, to disentangle the relative importance of multiple assembly mechanisms in structuring co‐occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co‐occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.

A method for predicting species trajectories tested with trees in barro colorado tropical forest

The ability to predict changes in the abundances of the species in ecological communities is essential for sustainable management, biodiversity conservation, and community restoration.We propose a framework to predict such changes. We test our method, which uses the linear Lotka-Volterra equations (LLVE) as well as other empirical predictors (linear least squares regression, quadratic extrapolation, simple exponential smoothing), against the measured abundances of trees from the long-term 50-ha plot on Barro Colorado Island (BCI), along eight censuses.To obtain the parameters of the LLVE -the intrinsic growth rate r and the carrying capacity K of each species and the interspecific interaction matrix A- we first estimate A through the Maximum Entropy (MaxEnt) method. Next, using A as input, we fit r and K. Then, feeding the LLVE with these parameters, we obtain predicted species trajectories along censuses. Since for this particular community the interspecific interaction coefficients are much smaller than the intraspecific ones, keeping only intraspecific competition is enough to predict the evolution of the abundances of several tree species, i.e. the LLVE reduce to a set of uncoupled logistic equations. However, this simplification is not a requirement of the method. We define P-values to establish when the predicted trajectory for a species is statistically significant; this is crucial in determining the set of species over which a particular predictor can be meaningfully applied.To illustrate a possible application of the method, we present our predictions for the abundances of tree species for the currently underway BCI 2020 census, which provide warnings regarding species that are likely to experience important population loss.

Species abundance is jointly determined by functional traits and negative density dependence in a subtropical forest in southern China

Abstract Aims The factors affecting species abundance are a subject of ongoing debates in community ecology. Empirical studies have demonstrated that tree abundance is affected by plant functional traits and negative density dependence (NDD). However, few studies have focused on the combined effects of NDD and plant functional traits on species abundance. Methods In this study, we used tree functional traits and two census data from a 50-ha forest dynamic plot in the Heishiding (HSD) Nature Reserve to explore the combined effects of functional traits and NDD on species abundance. Using hierarchical Bayesian models, we analyzed how neighbor densities affected the survival of saplings from 130 species and extracted posterior means of the coefficients to represent NDD. The structural equation modeling (SEM) analysis was then applied to investigate the causal relationships among species functional traits, NDD and species abundance. Important Findings SEM showed that tree functional traits, including specific leaf area (SLA), leaf area (LA), leaf dry matter content (LDMC), leaf N content (LNC), maximum electron transport rate (ETRmax) and conspecific adult negative density dependence (CNDDadult), together explained 20% of the total variation in tree abundance. Specifically, SLA affected tree abundance both directly and indirectly via CNDDadult, with a totally negative influence on abundance. LDMC and LNC had only indirect effects mediated by CNDDadult on tree abundance. ETRmax and LA had directly negative effects on abundance, but their direct connections with CNDDadult were not observed. In addition, CNDDadult was negatively correlated with species abundance, indicating that abundant species are under stronger NDD. Among these investigated traits, SLA contributed the most to the variation in CNDDadult and abundance. We argued that our findings of trait–CNDDadult–abundance relationships can improve our understanding of the determinants of species commonness and rarity in forests.

Limiting similarity shapes the functional and phylogenetic structure of root neighborhoods in a subtropical forest.

Environmental filtering and limiting similarity mechanisms can simultaneously structure community assemblages. However, how they shape the functional and phylogenetic structure of root neighborhoods remains unclear, hindering the understanding of belowground community assembly processes and diversity maintenance. In a 50-ha plot in a subtropical forest, China, we randomly sampled >2700 root clusters from 625 soil samples. Focusing on 10 root functional traits measured on 76 woody species, we examined the functional and phylogenetic structure of root neighborhoods and linked their distributions with environmental cues. Functional overdispersion was pervasive among individual root traits (50% of the traits) and accentuated when different traits were combined. Functional clustering (20% of the traits) seemed to be associated with a soil nutrient gradient with thick roots dominating fertile areas whereas thin roots dominated infertile soils. Nevertheless, such traits also were sorted along other environmental cues, showing multidimensional adaptive trait syndromes. Species relatedness also was an important factor defining root neighborhoods, resulting in significant phylogenetic overdispersion. These results suggest that limiting similarity may drive niche differentiation of coexisting species to reduce competition, and that alternative root strategies could be crucial in promoting root neighborhood resource use and species coexistence.

Reconstructing the historical patterns of forest stand based on CA-AdaBoost-ANN model

Understanding the long-term interaction between humans and the environment requires the reconstruction of historical forest dynamics. However, the accuracy of methods to reconstruct the patterns of historical forest stands using resurvey data has not been comprehensively evaluated. Previous simulations and statistical assessments of forests have focused on reconstructing land cover or single layer, but are not congruent with the specific data typically obtained by field survey. Additionally, most reconstruction studies have not reconstructed the patterns of the forest stand or the tree species distribution. In this work, we applied cellular automata (CA), which integrated artificial neural networks (ANN), to describe tree species dynamics in response to forest changes in Heishiding Nature Reserve of Guangdong province in south China. The top 70 dominant tree species represented by importance value (IV) and actual distribution were considered. The relationship of the current and historical forest distributions was modeled using an AdaBoost-based back-propagation neural network algorithm. The area under the receiver operating characteristics curve (AUC) values for the 70 studied tree species ranged from 0.8556 to 0.9981, which suggested that the reconstructed patterns were reasonable. The simulation of the forest stands of a 50-ha plot in 2012 achieved an overall accuracy of 94.14% and a Lee Sallee index of 0.7974. The results indicated that this method can be further improved to obtain a more accurate pattern of tree species by adjusting the CA transition rules and parameters. Overall, the results demonstrate that the CA-AdaBoost-ANN model can be applied as an effective path to obtain a distribution map of historical forest types, which will be extremely useful for effective forest management.

Effects of Fire Frequency on Seed Sources and Regeneration in Southeastern Amazonia

The trajectory and recovery time of fire-disturbed forests depend on the capacity of seedlings and resprouts to get established over time. Here, we investigated the mechanisms associated with fire effects on postfire regeneration in the context of a large-scale fire experiment located in southeastern Amazonia. Specifically, we tested the hypothesis that recurrent understory fires reduce forest regeneration capacity by reducing the recruitment of seedlings, the viability of the soil seed bank, the seed rain, and the resprouts. The experiment was comprised of three 50-ha plots: an unburned control, and two plots that were experimentally burned three (triennially) or six (annually) times between 2004 and 2010. Seedlings represented 2.4% and 0.6% of the seed rain and soil seed bank in the Control and burned treatment plots, respectively. Compared to the control, the triennial burns caused more reduction than the annual ones in seed rain (-42% versus -10%) and seed bank (-78% versus -50%). These fire-related reduction in seed rain in both treatments explain most of the low postfire density of seedlings (0.4 and 0.8 ind/m2, respectively), compared with the Control (2,9 ind/m2). The three-year interval between fires contributed to highest mortality of seeds stored in the soil than in the annual burn treatment, where fires were less severe. However, there were 5.5 times more resprouting in the plot burned triennially compared with the one burned annually. In both treatments, though, the number of resprouts declined over time. In conclusion, seeds from both seed rain and seed bank and resprouting were negatively affected by both fire frequencies, reducing the likelihood of native species recovery by altering the regeneration pathways. This situation is expected to be increasingly common in southeastern Amazon forests, particularly under warmer and dryer climate conditions.