Species-rich Tropical Forests Research Articles

Unveiling the Sources and Transfer of Mercury in Forest Bird Food Chains Using Techniques of Vivo-Nest Video Recording and Stable Isotopes.

Knowledge gaps in mercury (Hg) biomagnification in forest birds, especially in the most species-rich tropical and subtropical forests, limit our understanding of the ecological risks of Hg deposition to forest birds. This study aimed to quantify Hg bioaccumulation and transfer in the food chains of forest birds in a subtropical montane forest using a bird diet recorded by video and stable Hg isotope signals of biological and environmental samples. Results show that inorganic mercury (IHg) does not biomagnify along food chains, whereas methylmercury (MeHg) has trophic magnification factors of 7.4-8.1 for the basal resource-invertebrate-bird food chain. The video observations and MeHg mass balance model suggest that Niltava (Niltava sundara) nestlings ingest 78% of their MeHg from forest floor invertebrates, while Flycatcher (Eumyias thalassinus) nestlings ingest 59% from emergent aquatic invertebrates (which fly onto the canopy) and 40% from canopy invertebrates. The diet of Niltava nestlings contains 40% more MeHg than that of Flycatcher nestlings, resulting in a 60% higher MeHg concentration in their feather. Hg isotopic model shows that atmospheric Hg0 is the main Hg source in the forest bird food chains and contributes >68% in most organisms. However, three categories of canopy invertebrates receive ∼50% Hg from atmospheric Hg2+. Overall, we highlight the ecological risk of MeHg exposure for understory insectivorous birds caused by atmospheric Hg0 deposition and methylation on the forest floor.

Community-based plant diversity monitoring of a dense-canopy and species-rich tropical forest using airborne LiDAR data

Tropical forests are widely regarded as the Earth’s most important ecosystems, yet they are severely threatened by anthropogenic disturbances. Rapid and extensive monitoring of forest structure and biodiversity is crucial for developing ecologically sound conservation and restoration strategies. Airborne light detection and ranging (LiDAR) can effectively monitor three-dimensional forest canopy structures. Traditionally, LiDAR-based plant diversity estimation has relied on individual tree-based and area-based approaches. However, these approaches face significant challenges in tropical forests due to their complex canopy structures and diverse plant compositions. Therefore, by proposing a novel community-based approach, this study aims to examine the relationship between field-derived biodiversity indices and LiDAR-derived canopy structural metrics of plant communities in a species-rich ForestGEO forest dynamic plot in tropical Hong Kong. Our goal is to determine whether canopy structural metrics extracted from airborne LiDAR data can serve as a robust and efficient alternative for expediting plant diversity monitoring in highly dense and diverse tropical forests. Our results indicate that an integration watershed segmentation technique (for automatic patch-scale plant community delineation), LiDAR-derived canopy structural metrics, and machine learning-based random forest regression analysis can provide accurate predictions of community-based species diversity indices. Among various diversity indices, species richness and the Shannon-Wiener index are most accurately estimated using LiDAR-derived metrics. This study reveals that species richness is predominantly influenced by the existence of multi-layered canopy structures, whereas the Shannon-Wiener index is associated with both multi-layered structures and canopy morphologies. Overall, our findings showcase the immense potential of airborne LiDAR data in advancing the monitoring of structure and biodiversity in dense-canopy and species-rich tropical forests in a spatially explicit manner.

Diel and seasonal stem growth responses to climatic variation are consistent across species in a subtropical tree community.

Understanding how intra-annual stem growth responds to atmospheric and soil conditions is essential for assessing the effects of climate extremes on forest productivity. In species-poor forests, such understanding can be obtained by studying stem growth of the dominant species. Yet, in species-rich (sub-)tropical forests, it is unclear whether these responses are consistent among species. We monitored intra-annual stem growth with high-resolution dendrometers for 27 trees belonging to 14 species over 5 yr in a montane subtropical forest. We quantified diel and seasonal stem growth patterns, verified to what extent observed growth patterns coincide across species and analysed their main climatic drivers. We found very consistent intra-annual growth patterns across species. Species varied in the rate but little in the timing of growth. Diel growth patterns revealed that - across species - trees mainly grew before dawn when vapour pressure deficit (VPD) was low. Within the year, trees mainly grew between May and August driven by temperature and VPD, but not by soil moisture. Our study reveals highly consistent stem growth patterns and climatic drivers at community level. Further studies are needed to verify whether these results hold across climates and forests, and whether they can be scaled up to estimate forest productivity.

Mechanistic partitioning of species richness in diverse tropical forest tree communities with immigration and temporal environmental stochasticity

Abstract Hyperdiverse tropical forest tree communities illustrate a fundamental problem in ecology: How can many species coexist given relatively few limiting resources? Neutral theory provides a solution by positing that species have equal fitness and hence drift to extinction slowly. However, neutral theory seriously under‐predicts temporal changes in species abundances. This can be remedied by breaking neutrality and adding temporal environmental stochasticity (TES), but the mechanisms mediating the effects of TES on species richness remain unclear. Here, we make progress by analysing a local community model with species competing for a common resource under TES, to derive formulae partitioning species richness according to different mechanisms. By applying our formulae to generic parameter sets for tropical forest tree communities, we found that when the autocorrelation time of TES was short, the dominant mechanism driving species richness was non‐linear averaging of the interspecific competition term over time, which reduced the typical strength of interspecific competition and boosted richness relative to the neutral case. However, greater immigration to the community resulted in more species and hence weaker non‐linear averaging due to the law of large numbers. In contrast, when the autocorrelation time of TES was long, the dominant mechanism driving species richness was strong selection between changes in environmental conditions, which increased the typical strength of interspecific competition and reduced richness relative to the neutral case. By applying our formulae to a specific parameter set for a tropical forest tree community in Panama, we found that TES had minor effects on species richness because (i) the immigration rate was sufficiently large for non‐linear averaging of the interspecific competition term to be weak and (ii) the autocorrelation time was sufficiently short to suppress the effects of selection. Synthesis. We provide a novel mechanistic explanation of how TES affects tree species richness in tropical forests, in particular how TES often has minor effects on richness despite having substantial effects on temporal changes in species abundances. This provides a deeper insight into why a neutral model with added TES can accurately capture static and dynamic aspects of tree community diversity in the tropics.

Seedlings of shade-tolerant tree species are more vulnerable to chilling rain under a forest gap

The manner in which tree species differ in their responses to chilling rain in warm and species-rich (sub-)tropical forests is not well understood. Understanding this variation between species is essential for linking the responses of individual plants to chilling rain with ecological consequences at the forest community and ecosystem levels. We hypothesized that chilling rain can induce detrimental effects on leaf photochemical processes, and the negative impacts are more evident for shade-tolerant species than light-demanding species. This trade-off between species' tolerance to shade and chilling rain may depend on the light environment to which plants are exposed. To test these hypotheses, we conducted two sequential experiments with five subtropical tree species, measuring their leaf photochemical processes during the phases of a chilling rain event and assessing their resistance and recovery. We determined species shade tolerance by integrating their functional traits associated with resource acquisition in a shade environment. Our results showed that Fv/Fm, a measure of maximum quantum yield of photosystem II, was co-determined by the plant's exposure to light and chilling rain. Seedlings exposed to a gap before the chilling rain generally had lower Fv/Fm than those exposed to shade before the rain treatment. Chilling rain, relative to ambient rain, significantly reduced Fv/Fm during the cold and sunny phase. However, the effects of chilling rain were only evident for shade-tolerant species with gap-exposure history. The reduction in Fv/Fm induced by chilling rain led to higher resistance of Fv/Fm to chilling rain for light-demanding species than shade-tolerant species, leading to a trade-off between species' tolerances to shade and chilling rain for plants with gap-exposure history, thus supporting the hypotheses. This trade-off was primarily due to variation in functional traits related to light-use strategy, such as specific leaf area, leaf area ratio, leaf thickness, relative volume growth rate, and root-shoot ratio. As light availability and species' tolerance to shade are critical abiotic and biotic factors determining forest community succession, respectively, these findings may improve the scalability of the physiological responses of individual plants to chilling rain to the dynamics of forest communities. Our results suggest that frequent chilling rain events and canopy disturbances may favor light-demanding species and alter the species composition of subtropical forests.

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.

Contribution of tree community structure to forest productivity across a thermal gradient in eastern Asia

Despite their fundamental importance the links between forest productivity, diversity and climate remain contentious. We consider whether variation in productivity across climates reflects adjustment among tree species and individuals, or changes in tree community structure. We analysed data from 60 plots of humid old-growth forests spanning mean annual temperatures (MAT) from 2.0 to 26.6 °C. Comparing forests at equivalent aboveground biomass (160 Mg C ha–1), tropical forests ≥24 °C MAT averaged more than double the aboveground woody productivity of forests <12 °C (3.7 ± 0.3 versus 1.6 ± 0.1 Mg C ha–1 yr–1). Nonetheless, species with similar standing biomass and maximum stature had similar productivity across plots regardless of temperature. We find that differences in the relative contribution of smaller- and larger-biomass species explained 86% of the observed productivity differences. Species-rich tropical forests are more productive than other forests due to the high relative productivity of many short-stature, small-biomass species.

Diversified land conversion deepens understanding of impacts of rapid rubber plantation expansion on plant diversity in the tropics

Understanding the status and changes of plant diversity in rubber (Hevea brasiliensis) plantations is essential for sustainable plantation management in the context of rapid rubber expansion in the tropics, but remains very limited at the continental scale. In this study, we investigated plant diversity from 10-meter quadrats in 240 different rubber plantations in the six countries of the Great Mekong Subregion (GMS)—where nearly half of the world's rubber plantations are located—and analyzed the influence of original land cover types and stand age on plant diversity using Landsat and Sentinel-2 satellite imagery since the late 1980s. The results indicate that the average plant species richness of rubber plantations is 28.69 ± 7.35 (1061 species in total, of which 11.22 % are invasive), approximating half the species richness of tropical forests but roughly double that of the intensively managed croplands. Time-series satellite imagery analysis revealed that rubber plantations were primarily established in place of cropland (RPC, 37.72 %), old rubber plantations (RPORP, 27.63 %), and tropical forests (RPTF, 24.12 %). Plant species richness in RPTF (34.02 ± 7.62) was significantly (p < 0.001) higher than that in RPORP (26.41 ± 7.02) and RPC (26.34 ± 5.37). More importantly, species richness can be maintained for the duration of the 30-year economic cycle, and the number of invasive species decreases as the stand ages. Given diverse land conversions and changes in stand age, the total loss of species richness due to rapid rubber expansion in the GMS was 7.29 %, which is far below the traditional estimates that only consider tropical forest conversion. In general, maintaining higher species richness at the earliest stages of cultivation has significant implications for biodiversity conservation in rubber plantations.

Negative impact of slash-and-burn agriculture on the seed rain in a tropical dry forest

Forest’s recovery potential in human-modified landscapes is increasingly threatened by agricultural activities that disrupt critical sources of forest regeneration, such as the seed rain. Slash-and-burn agriculture is a good example. By slashing and burning the vegetation, this farming method can promote seed source and seed dispersal limitation, but this hypothesis remains poorly tested. Here, we sampled the seed rain during a complete year in nine plots exposed to slash-and-burn agriculture (i.e., burned plots) and in forest stands (control plots) in the Caatinga biome – a species-rich tropical dry forest endemic to Brazil that is increasingly threatened by slash-and-burn agriculture. We compared seed density, seed species diversity, and the taxonomic and functional composition of seed assemblages between burned and control plots. As expected, seed density was 15 times lower in burned plots than in control plots. Species diversity was also lower in burned plots, but only when considering the number of rare species. However, burned plots showed a higher β-diversity of rare species than forest plots, mainly caused by species replacement (i.e. species turnover) from plot to plot. Burned plots also showed 30% more species with dry fruits and abiotic dispersal than control plots, but this difference was not statistically significant. Taken together, our findings highlight the low tolerance of the seed rain to this dominant agricultural practice in tropical dry forests. This is likely related to the lack of seed sources and seed dispersers in burned plots. Therefore, increasing the availability of seed sources and ecological connectivity in the surrounding landscape are critical management strategies for enhancing seed dispersal and forest recovery in forest areas exposed to this farming method.

Revealing the Permanent and Transient Plant Understory in Gallery Forests in the Cerrado of Central Brazil

Abstract The understories of tropical forests comprise complex communities and can be divided into permanent understory, where the generally shade-tolerant plant growth forms are less developed in height, and transient understory, where young tree individuals are only temporarily present. Despite a high contribution to species richness in tropical forests, the understory is poorly studied. Here, we examined the species composition, richness, structure, diversity, and the relative contribution of growth forms in permanent and transient understories of gallery forests in the Brazilian Cerrado. A total of 211 species distributed into sixty-seven families and 153 genera were sampled. The most species-rich family was Rubiaceae, and Miconia was the genus with the highest species richness. The species Hildaea pallens had the highest importance in the forests. The best-represented growth forms were tree seedlings, followed by shrubs and lianas. The transient component of the understory in gallery forests was the most diverse. However, in terms of species relative cover, both transient and permanent understory species contributed equally to the understory structure, mainly due to the high cover of Poaceae species. Our study is the first to examine composition, structure, diversity, and growth forms in the permanent and transient understories of gallery forests. Study Implications: Our study is innovative in describing the plant community attributes of gallery forest understories in the Brazilian Cerrado. The understories of tropical forests comprise complex communities and can be divided into permanent and transient understory. The transient component of the understory in gallery forests was the most diverse, represented by seedlings and young tree specimens. However, in terms of species relative cover, both transient and permanent understory species contributed equally to the understory structure. Here, we provide evidence that may be useful to initiatives seeking to conduct ecological restoration and conservation of gallery forests in the Cerrado.

Population ecology and behaviour of two Afrotropical forest butterflies

Over the last decades, numerous natural habitats have been converted into settlement areas, agricultural land, and tree plantations on a large spatial scale. As a result, natural ecosystems have been destroyed. In consequence, many ecosystems exist today as small and geographically isolated remnants. To what extent the original species diversity can persist in such small habitat patches is questionable and strongly depends on the ecology of the species. A prominent example of severe habitat destruction are the species-rich tropical cloud forests of Taita Hills in southern Kenya, which have been deforested almost completely during past decades. However, there still exist typical forest species in the few remaining forest fragments. In this study, we investigate the population ecology and behaviour of two butterfly species present in the cloud forest remnants of Taita Hills, Protogoniomorpha parhassus and Precis tugela. Over a period of one month, we conducted Mark-Release-Recapture to study population sizes and demographic structures, lifespan, dispersal, and behaviour. We found that both species exhibited medium population sizes and are sedentary. However, some individuals performed dispersal throughout the forest. The behaviour of the two species differs: While P. tugela was mostly observed basking with open wings, P. parhassus was mostly sitting under leaves with closed wings. The life span was rather long for butterflies.Implications for insect conservationThis study documents the population ecology and behaviour of these two Afrotropical butterflies and underlines the relevance of the conservation of cloud forest remnants to preserve species, which mainly depends on these habitat remnants.

Insights on biodiversity drivers to predict species richness in tropical forests at the local scale

Disentangling the relative importance of different biodiversity drivers (i.e., climate, edaphic, historical factors, or human impact) to predict plant species richness at the local scale is one of the most important challenges in ecology. Biodiversity modelling is a key tool for the integration of these drivers and the predictions generated are essential, for example, for climate change forecast and conservation planning. However, the reliability of biodiversity models at the local scale remains poorly understood, especially in tropical species-rich areas, where they are required. We inventoried all woody plants with stems ≥ 2.5 cm in 397 plots across the Andes-Amazon gradient. We generated and mapped 19 uncorrelated biodiversity drivers at 90 m resolution, grouped into four categories: microclimatic, microtopographic, anthropic, and edaphic. In order to evaluate the importance of the different categories, we grouped biodiversity drivers into four different clusters by categories. For each of the four clusters of biodiversity drivers, we modelled the observed species richness using two statistical techniques (random forest and Bayesian inference) and two modelling procedures (including or excluding a spatial component). All the biodiversity models produced were evaluated by cross-validation. Species richness was accurately predicted by random forest (Spearman correlation up to 0.85 and explained variance up to 67%). The results suggest that precipitation and temperature are important driving forces of species richness in the region. Nonetheless, a spatial component should be considered to properly predict biodiversity. This could reflect macroevolutionary underlying forces not considered here, such as colonization time, dispersal capacities, or speciation rates. However, the proposed biodiversity modelling approach can predict accurately species richness at the local scale and detailed resolution (90 m) in tropical areas, something that previous works had found extremely challenging. The innovative methodology presented here could be employed in other areas with conservation needs.

The chemical ecology of tropical forest diversity: Environmental variation, chemical similarity, herbivory, and richness.

Species richness in tropical forests is correlated with other dimensions of diversity, including the diversity of plant-herbivore interactions and the phytochemical diversity that influences those interactions. Understanding the complexity of plant chemistry and the importance of phytochemical diversity for plant-insect interactions and overall forest richness has been enhanced significantly by the application of metabolomics to natural systems. The present work used proton nuclear magnetic resonance spectroscopy (1 H-NMR) profiling of crude leaf extracts to study phytochemical similarity and diversity among Piper plants growing naturally in the Atlantic Rainforest of Brazil. Spectral profile similarity and chemical diversity were quantified to examine the relationship between metrics of phytochemical diversity, specialist and generalist herbivory, and understory plant richness. Herbivory increased with understory species richness, while generalist herbivory increased and specialist herbivory decreased with the diversity of Piper leaf material available. Specialist herbivory increased when conspecific host plants were more spectroscopically dissimilar. Spectral similarity was lower among individuals of common species, and they were also more spectrally diverse, indicating phytochemical diversity is beneficial to plants. Canopy openness and soil nutrients also influenced chemistry and herbivory. The complex relationships uncovered in this study add information to our growing understanding of the importance of phytochemical diversity for plant-insect interactions and tropical plant species richness.

Drastic impoverishment of the soil seed bank in a tropical dry forest exposed to slash-and-burn agriculture

Forest ecosystems are increasingly threatened by unsustainable agricultural practices, especially by those that damage their regenerative potential. This can be the case of slash-and-burn agriculture – a farming method that can negatively impact the soil seed bank, potentially limiting the resilience of forest ecosystems. To test this hypothesis, and thus look for management practices aimed at enhancing forest recovery, we examined the impact of fire throughout an experiment of slash-and-burn agriculture on the soil seed bank of woody plants in the Caatinga tropical dry forest, northeast Brazil. We compared seed damage and viability, and the structure (seed density and diversity) and composition (taxonomic and functional) of seed bank assemblages before and after fire. We found a significant decrease in the frequency and proportion of intact (undamaged) seeds after fire, and a 3.6-fold decrease in the proportion of viable seeds. While seed density remained constant, species diversity drastically decreased after fire, especially the number of rare species. The compositional dissimilarity (β-diversity) between plots also dropped after fire, particularly its turnover component, thus causing the homogenization of seed assemblages across space. The functional composition of seed assemblages was also altered, with the relative frequency of shrub species increasing after fire, especially species with fleshy fruits and biotic dispersal. Taken together, our findings highlight the low resistance of the soil seed bank to this common farming method in tropical dry forests. Therefore, the recovery of this and potentially of other species-rich tropical forests exposed to slash-and-burn agriculture cannot rest on the soil seed bank, but on other processes such as seed dispersal and resprouting – an interesting avenue for future research.

Tropical forests are vulnerable in terms of functional redundancy

Many vegetation properties may depend upon the distribution of species among functional entities (unique combinations of functional traits). Understanding these distributions is fundamental to conserve biodiversity and maintain ecosystem functions. Here, we employed the functional indices based on trait probability density and functional entities in comparison with null model to assess the response of tree community to potential species loss in 17 1-ha forest dynamics plots across six old-growth forest types in a tropical nature reserve. We found that functional diversity, functional redundancy and functional over-redundancy were positively, while functional vulnerability was negatively related to species richness. Both functional redundancy and functional over-redundancy were low, while functional vulnerability was high across the six old-growth tropical forest types. The null model tests revealed that species in each of the tropical forest type were packed into a few functional entities, leading to functional over-redundancy and resulting in functional vulnerability. Our result highlighted that although species-rich tropical forests had high probability of functional redundancy, the insurance effect provided by that could not offset functional vulnerability in the ecosystems. Reducing loss of species with unique trait combinations and low local abundance is an effective and necessary way to avoid the loss of functions in tropical forest ecosystems.

Leaf trait variation in species-rich tropical Andean forests

Screening species-rich communities for the variation in functional traits along environmental gradients may help understanding the abiotic drivers of plant performance in a mechanistic way. We investigated tree leaf trait variation along an elevation gradient (1000–3000 m) in highly diverse neotropical montane forests to test the hypothesis that elevational trait change reflects a trend toward more conservative resource use strategies at higher elevations, with interspecific trait variation decreasing and trait integration increasing due to environmental filtering. Analysis of trait variance partitioning across the 52 tree species revealed for most traits a dominant influence of phylogeny, except for SLA, leaf thickness and foliar Ca, where elevation was most influential. The community-level means of SLA, foliar N and Ca, and foliar N/P ratio decreased with elevation, while leaf thickness and toughness increased. The contribution of intraspecific variation was substantial at the community level in most traits, yet smaller than the interspecific component. Both within-species and between-species trait variation did not change systematically with elevation. High phylogenetic diversity, together with small-scale edaphic heterogeneity, cause large interspecific leaf trait variation in these hyper-diverse Andean forests. Trait network analysis revealed increasing leaf trait integration with elevation, suggesting stronger environmental filtering at colder and nutrient-poorer sites.

Leaf turgor loss point shapes local and regional distributions of evergreen but not deciduous tropical trees.

Summary The effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits.We measured leaf water potential at turgor loss (i.e. ‘wilting point’; πtlp), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama.Among evergreen trees, species with lower πtlp were associated with drier habitats, with πtlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, πtlp did not predict habitat associations among deciduous species.Across spatial scales, πtlp is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

Topography as a factor driving small-scale variation in tree fine root traits and root functional diversity in a species-rich tropical montane forest.

We investigated the variation in tree fine root traits and their functional diversity along a local topographic gradient in a Neotropical montane forest to test if fine root trait variation along the gradient is consistent with the predictions of the root economics spectrum on a shift from acquisitive to conservative traits with decreasing resource supply. We measured five fine root functional traits in 179 randomly selected tree individuals of 100 species and analysed the variation of single traits (using Bayesian phylogenetic multilevel models) and of functional trait diversity with small-scale topography. Fine roots exhibited more conservative traits (thicker diameters, lower specific root length and nitrogen concentration) at upper slope compared with lower slope positions, but the largest proportion of variation (40-80%) was explained by species identity and phylogeny. Fine root functional diversity decreased towards the upper slopes. Our results suggest that local topography and the related soil fertility and moisture gradients cause considerable small-scale variation in fine root traits and functional diversity along tropical mountain slopes, with conservative root traits and greater trait convergence being associated with less favourable soil conditions due to environmental filtering. We provide evidence of a high degree of phylogenetic conservation in fine root traits.

Conspecific and heterospecific crowding facilitate tree survival in a tropical karst seasonal rainforest

Tree mortality plays a vital role in forest dynamics and contributes to species coexistence and community assembly. However, the mechanisms that control tree mortality are poorly understood, particularly in species-rich tropical forests. Size-dependent abiotic constraints and biotic interactions act simultaneously to cause tree mortality in natural forests. However, these drivers are often studied independently, which can limit our understanding of how they interact to affect tree mortality in natural forests. We employed a hierarchical Bayesian logistic regression modeling approach to quantify the simultaneous effects of tree size, topography, neighborhoods, and their interactions on tree mortality in a 15-ha fully mapped tropical karst seasonal rainforest in Southern China. Of the variables tested, tree size exhibited the most consistent and strongest negative effect on tree mortality, while topography and neighborhood competition were of secondary importance. Neighbors, particularly heterospecific neighbors, had a facilitative effect on lowering mortality, while only several species showed conspecific negative density dependent on mortality. The topographical wetness index had a significant positive effect on tree mortality. Size-dependent and neighborhood competition-induced tree mortality was stronger for shade-intolerant than for shade-tolerant species, and the size-dependent mortality was the strongest for shrub species among the three growth forms. Our results indicated that the size-dependent effect was the dominant cause of tree mortality; however, neighbors, particularly heterospecific neighbors, had a facilitative effect on lowering tree mortality. Furthermore, the relative importance of these mechanisms for tree mortality differed within life-history strategies guilds. Our study highlighted the value of simultaneously considering the individual and interactive effects of multiple mechanisms toward understanding the dynamics and coexistence of highly diverse metacommunities in harsh environments.

3D Segmentation of Trees Through a Flexible Multiclass Graph Cut Algorithm

Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of individual trees to be measured, enabling forest carbon stocks and dynamics to be tracked and understood. Many algorithms exist for structurally simple forests including coniferous forests and plantations. Finding a robust solution for structurally complex, species-rich tropical forests remains a challenge; existing segmentation algorithms often perform less well than simple area-based approaches when estimating plot-level biomass. Here we describe a Multi-Class Graph Cut (MCGC) approach to tree crown delineation. This uses local three-dimensional geometry and density information, alongside knowledge of crown allometries, to segment individual tree crowns from LiDAR point clouds. Our approach robustly identifies trees in the top and intermediate layers of the canopy, but cannot recognise small trees. From these three-dimensional crowns, we are able to measure individual tree biomass. Comparing these estimates to those from permanent inventory plots, our algorithm is able to produce robust estimates of hectare-scale carbon density, demonstrating the power of ITC approaches in monitoring forests. The flexibility of our method to add additional dimensions of information, such as spectral reflectance, make this approach an obvious avenue for future development and extension to other sources of three-dimensional data, such as structure from motion datasets.