Intraspecific alternative phenotypes contribute to variation in species' strategies for growth.

Ecologists have historically sought to identify the mechanisms underlying the maintenance of local species diversity. High-dimensional trait-based relationships, such as alternative phenotypes, have been hypothesized as important for maintaining species diversity such that phenotypically dissimilar individuals compete less for resources but have similar performance in a given environment. The presence of alternative phenotypes has primarily been investigated at the community level, despite the importance of intraspecific variation to diversity maintenance. The aims of this research are to (1) determine the presence or absence of intraspecific alternative phenotypes in three species of tropical tree seedlings, (2) investigate if these different species use the same alternative phenotypes for growth success, and (3) evaluate how findings align with species co-occurrence patterns. We model species-specific relative growth rate with individual-level measurements of leaf mass per area (LMA) and root mass fraction (RMF), environmental data, and their interactions. We find that two of the three species have intraspecific alternative phenotypes, with individuals within species having different functional forms leading to similar growth. Interestingly, individuals within these species use the same trait combinations, high LMA × low RMF and low LMA × high RMF, in high soil nutrient environments to acquire resources for higher growth. This similarity among species in intraspecific alternative phenotypes and variables that contribute most to growth may lead to their negative spatial co-occurrence. Overall, we find that multiple traits or interactions between traits and the environment drive species-specific strategies for growth, but that individuals within species leverage this multi-dimensionality in different ways for growth success.

Leaf gene expression trajectories during the growing season are consistent between sites and years in American beech.

Transcriptomics provides a versatile tool for ecological monitoring. Here, through genome-guided profiling of transcripts mapping to 33 042 gene models, expression differences can be discerned among multi-year and seasonal leaf samples collected from American beech trees at two latitudinally separated sites. Despite a bottleneck due to post-Columbian deforestation, the single nucleotide polymorphism-based population genetic background analysis has yielded sufficient variation to account for differences between populations and among individuals. Our expression analyses during spring-summer and summer-autumn transitions for two consecutive years involved 4197 differentially expressed protein coding genes. Using Populus orthologues we reconstructed a protein-protein interactome representing leaf physiological states of trees during the seasonal transitions. Gene set enrichment analysis revealed gene ontology terms that highlight molecular functions and biological processes possibly influenced by abiotic forcings such as recovery from drought and response to excess precipitation. Further, based on 324 co-regulated transcripts, we focused on a subset of GO terms that could be putatively attributed to late spring phenological shifts. Our conservative results indicate that extended transcriptome-based monitoring of forests can capture diverse ranges of responses including air quality, chronic disease, as well as herbivore outbreaks that require activation and/or downregulation of genes collectively tuning reaction norms maintaining the survival of long living trees such as the American beech.

On functional groups and forest dynamics.

Functional trait variation measured on continuous scales has helped ecologists to unravel important ecological processes. However, forest ecologists have recently moved back toward using functional groups. There are pragmatic and biological rationales for focusing on functional groups. Both of these approaches have inherent limitations including binning clearly continuous distributions, poor trait-group matching, and narrow conceptual frameworks for why groups exist and how they evolved. We believe the pragmatic use of functional groups due to data deficiencies will eventually erode. Conversely, we argue that existing conceptual frameworks for why a limited number of tree functional groups may exist is a useful, but flawed, starting point for modeling forests that can be improved through the consideration of unmeasured axes of functional variation.

Comparative transcriptomics reveals divergence in pathogen response gene families amongst 20 forest tree species.

Forest trees provide critical ecosystem services for humanity that are under threat due to ongoing global change. Measuring and characterizing genetic diversity are key to understanding adaptive potential and developing strategies to mitigate negative consequences arising from climate change. In the area of forest genetic diversity, genetic divergence caused by large-scale changes at the chromosomal level has been largely understudied. In this study, we used the RNA-seq data of 20 co-occurring forest trees species from genera including Acer, Alnus, Amelanchier, Betula, Cornus, Corylus, Dirca, Fraxinus, Ostrya, Populus, Prunus, Quercus, Ribes, Tilia, and Ulmus sampled from Upper Peninsula of Michigan. These data were used to infer the origin and maintenance of gene family variation, species divergence time, as well as gene family expansion and contraction. We identified a signal of common whole genome duplication events shared by core eudicots. We also found rapid evolution, namely fast expansion or fast contraction of gene families, in plant-pathogen interaction genes amongst the studied diploid species. Finally, the results lay the foundation for further research on the genetic diversity and adaptive capacity of forest trees, which will inform forest management and conservation policies.

Phytochemical diversity impacts herbivory in a tropical rainforest tree community.

Metabolomics provides an unprecedented window into diverse plant secondary metabolites that represent a potentially critical niche dimension in tropical forests underlying species coexistence. Here, we used untargeted metabolomics to evaluate chemical composition of 358 tree species and its relationship with phylogeny and variation in light environment, soil nutrients, and insect herbivore leaf damage in a tropical rainforest plot. We report no phylogenetic signal in most compound classes, indicating rapid diversification in tree metabolomes. We found that locally co-occurring species were more chemically dissimilar than random and that local chemical dispersion and metabolite diversity were associated with lower herbivory, especially that of specialist insect herbivores. Our results highlight the role of secondary metabolites in mediating plant-herbivore interactions and their potential to facilitate niche differentiation in a manner that contributes to species coexistence. Furthermore, our findings suggest that specialist herbivore pressure is an important mechanism promoting phytochemical diversity in tropical forests.

Biogeographic context is related to local scale tree demography, co-occurrence and functional differentiation.

Identifying the drivers of community structure and dynamics is a major pursuit in ecology. Emphasis is typically placed on the importance of local scale interactions when attempting to explain these fundamental ecological patterns. However, regional scale phenomena are also important predictors. The importance of regional scale context should be more evident in assemblages where multiple species are close to their range margins. Here, we test the importance of regional scale context using data from a temperate forest plot that contains two species groups - one near its northern range limit and one near its southern range limit. We show the proximity of species to their southern or northern range margins is linked to local scale co-occurrence, similarity in gene expression responses to a key environmental driver, demographic performance and inter-specific variation in conspecific negative density dependence. In sum, many of the key local scale patterns and processes of interest to community ecologists are linked to biogeographic context that is frequently ignored.

Height and crown allometries and their relationship with functional traits: An example from a subtropical wet forest.

Forest tree communities are largely structured by interactions between phenotypes and their environments. Functional traits have been popularized as providing key insights into plant functional tradeoffs. Similarly, tree crown-stem diameter and tree height-stem diameter allometric relationships are likely to be strongly coordinated with functional trait tradeoff axes. Specifically, species with functional traits indicative of conservative strategies (i.e., dense wood, heavy seeds) should be related to tree architectures that have lower heights and wider crowns for a given stem diameter. For example, shade-tolerant species in tropical forests are typically characterized as having dense wood, large seeds, and relatively broad crowns at early ontogenetic stages. Here, we focus on 14 dominant dicot tree species in a tropical forest. We utilized hierarchical Bayesian models to characterize species-specific height and crown size allometric parameters. We sampled from the posterior distributions for these parameters and correlated them with six functional traits. We also characterize the expected height and crown size for a series of reference stem diameters to quantify the relationship between traits and tree architecture across size classes. We find little interspecific variation in allometric slopes, but clear variation in allometric intercepts. Allometeric height intercepts were negatively correlated with wood density and crown size intercepts were positively related to wood density and seed mass and negatively related to leaf percent phosphorus. Thus, interspecific variation in tree architecture is generated by interspecific variation in allometric intercepts and not slopes. These intercepts could be predicted using a handful of functional traits where conservative traits were indicative of trees that are relatively short and have larger crown sizes. This demonstrates a coordination of tropical tree life histories that can be characterized simultaneously with functional traits and tree allometries.

Demographic trade-offs and functional shifts in a hurricane-impacted tropical forest.

BACKGROUND AND AIMS: Understanding shifts in the demographic and functional composition of forests after major natural disturbances has become increasingly relevant given the accelerating rates of climate change and elevated frequency of natural disturbances. Although plant demographic strategies are often described across a slow-fast continuum, severe and frequent disturbance events influencing demographic processes may alter the demographic trade-offs and the functional composition of forests. We examined demographic trade-offs and the shifts in functional traits in a hurricane-disturbed forest using long-term data from the Luquillo Forest Dynamics Plot (LFPD) in Puerto Rico. METHODS: We analysed information on growth, survival, seed rain and seedling recruitment for 30 woody species in the LFDP. In addition, we compiled data on leaf, seed and wood functional traits that capture the main ecological strategies for plants. We used this information to identify the main axes of demographic variation for this forest community and evaluate shifts in community-weighted means for traits from 2000 to 2016. KEY RESULTS: The previously identified growth-survival trade-off was not observed. Instead, we identified a fecundity-growth trade-off and an axis representing seedling-to-adult survival. Both axes formed dimensions independent of resprouting ability. Also, changes in tree species composition during the post-hurricane period reflected a directional shift from seedling and tree communities dominated by acquisitive towards conservative leaf economics traits and large seed mass. Wood specific gravity, however, did not show significant directional changes over time. CONCLUSIONS: Our study demonstrates that tree demographic strategies coping with frequent storms and hurricane disturbances deviate from strategies typically observed in undisturbed forests, yet the shifts in functional composition still conform to the expected changes from acquisitive to conservative resource-uptake strategies expected over succession. In the face of increased rates of natural and anthropogenic disturbance in tropical regions, our results anticipate shifts in species demographic trade-offs and different functional dimensions.

Functional trait space and redundancy of plant communities decrease toward cold temperature at high altitudes in Southwest China.

Plant communities in mountainous areas shift gradually as climatic conditions change with altitude. How trait structure in multivariate space adapts to these varying climates in natural forest stands is unclear. Studying the multivariate functional trait structure and redundancy of tree communities along altitude gradients is crucial to understanding how temperature change affects natural forest stands. In this study, the leaf area, specific leaf area, leaf carbon, nitrogen, and phosphorous content from 1,590 trees were collected and used to construct the functional trait space of 12 plant communities at altitudes ranging from 800 m to 3,800 m across three mountains. Hypervolume overlap was calculated to quantify species trait redundancy per community. First, hypervolumes of species exclusion and full species set were calculated, respectively. Second, the overlap between these two volumes was calculated to obtain hypervolume overlap. Results showed that the functional trait space significantly increased with mean annual temperature toward lower altitudes within and across three mountains, whereas species trait redundancy had different patterns between mountains. Thus, warming can widen functional trait space and alter the redundancy in plant communities. The inconsistent patterns of redundancy between mountains suggest that warming exerts varying influences on different ecosystems. Identification of climate-vulnerable ecosystems is important in the face of global warming.

Differential impacts of adult trees on offspring and non-offspring recruits in a subtropical forest.

An important mechanism promoting species coexistence is conspecific negative density dependence (CNDD), which inhibits conspecific neighbors by accumulating host-specific enemies near adult trees. Natural enemies may be genotype-specific and regulate offspring dynamics more strongly than non-offspring, which is often neglected due to the difficulty in ascertaining genetic relatedness. Here, we investigated whether offspring and non-offspring of a dominant species, Castanopsis eyrei, suffered from different strength of CNDD based on parentage assignment in a subtropical forest. We found decreased recruitment efficiency (proxy of survival probability) of offspring compared with non-offspring near adult trees during the seedling-sapling transition, suggesting genotype-dependent interactions drive tree demographic dynamics. Furthermore, the genetic similarity between individuals of same cohort decreased in late life history stages, indicating genetic-relatedness-dependent tree mortality throughout ontogeny. Our results demonstrate that within-species genetic relatedness significantly affects the strength of CNDD, implying genotype-specific natural enemies may contribute to population dynamics in natural forests.

Comparative transcriptomics of tropical woody plants supports fast and furious strategy along the leaf economics spectrum in lianas.

Lianas, climbing woody plants, influence the structure and function of tropical forests. Climbing traits have evolved multiple times, including ancestral groups such as gymnosperms and pteridophytes, but the genetic basis of the liana strategy is largely unknown. Here, we use a comparative transcriptomic approach for 47 tropical plant species, including ten lianas of diverse taxonomic origins, to identify genes that are consistently expressed or downregulated only in lianas. Our comparative analysis of full-length transcripts enabled the identification of a core interactomic network common to lianas. Sets of transcripts identified from our analysis reveal features related to functional traits pertinent to leaf economics spectrum in lianas, include upregulation of genes controlling epidermal cuticular properties, cell wall remodeling, carbon concentrating mechanism, cell cycle progression, DNA repair and a large suit of downregulated transcription factors and enzymes involved in ABA-mediated stress response as well as lignin and suberin synthesis. All together, these genes are known to be significant in shaping plant morphologies through responses such as gravitropism, phyllotaxy and shade avoidance.

Analyses of three-dimensional species associations reveal departures from neutrality in a tropical forest.

The study of community spatial structure is central to understanding diversity patterns over space and species co-occurrence at local scales. Although most analytical approaches consider horizontal and vertical dimensions separately, in this study we introduce a three-dimensional spatial analysis that simultaneously includes horizontal and vertical species associations. Using tree census data (2000-2016) and allometries from the Luquillo forest plot in Puerto Rico, we show that spatial organization becomes less random over time as the forest recovered from land-use legacy effects and hurricane disturbance. Tree species vertical segregation is predominant in the forest with almost all species that co-occur in the horizontal plane avoiding each other in the vertical dimension. Horizontal segregation is less common than vertical, whereas three-dimensional aggregation (a proxy for direct tree competition) is the least frequent type of spatial association. Furthermore, dominant species are involved in more non-random spatial associations, implying that species co-occurrence is facilitated by species segregation in space. This novel three-dimensional analysis allowed us to identify and quantify tree species spatial distributions, how interspecific competition was reduced through forest structure, and how it changed over time after disturbance, in ways not detectable from two-dimensional analyses alone.

Relating leaf traits to seedling performance in a tropical forest: building a hierarchical functional framework.

Trait-based approaches have been extensively used in community ecology to provide a mechanistic understanding of the drivers of community assembly. However, a foundational assumption of the trait framework, traits relate to performance, has been mainly examined through univariate relationships that simplify the complex phenotypic integration of organisms. We evaluate a conceptual framework in which traits are organized hierarchically combining trait information at the individual- and species-level from biomass allocation and organ-level traits. We focus on photosynthetic traits and predict that the positive effects of increasing plant leaf mass on growth depend on species-level leaf traits. We modeled growth data on more than 1,500 seedlings from 97 seedling species from a tropical forest in China. We found that seedling growth increases with allocation to leaves (high leaf area ratio and leaf mass fraction) and this effect is accentuated for species with high specific leaf area and leaf area. Also, we found that light has a significant effect on growth, and this effect is additive with leaf allocation traits. Our work offers an approach to gain further understanding of the effects of traits on the whole plant-level growth via a hierarchical framework including organ-level and biomass allocation traits at species and individual levels.

On the modelling of tropical tree growth: the importance of intra-specific trait variation, non-linear functions and phenotypic integration.

BACKGROUND AND AIMS: The composition and dynamics of plant communities arise from individual-level demographic outcomes, which are driven by interactions between phenotypes and the environment. Functional traits that can be measured across plants are frequently used to model plant growth and survival. Perhaps surprisingly, species average trait values are often used in these studies and, in some cases, these trait values come from other regions or averages calculated from global databases. This data aggregation potentially results in a large loss of valuable information that probably results in models of plant performance that are weak or even misleading. METHODS: We present individual-level trait and fine-scale growth data from >500 co-occurring individual trees from 20 species in a Chinese tropical rain forest. We construct Bayesian models of growth informed by theory and construct hierarchical Bayesian models that utilize both individual- and species-level trait data, and compare these models with models only using individual-level data. KEY RESULTS: We show that trait-growth relationships measured at the individual level vary across species, are often weak using commonly measured traits and do not align with the results of analyses conducted at the species level. However, when we construct individual-level models of growth using leaf area ratio approximations and integrated phenotypes, we generated strong predictive models of tree growth. CONCLUSIONS: Here, we have shown that individual-level models of tree growth that are built using integrative traits always outperform individual-level models of tree growth that use commonly measured traits. Furthermore, individual-level models, generally, do not support the findings of trait-growth relationships quantified at the species level. This indicates that aggregating trait and growth data to the species level results in poorer and probably misleading models of how traits are related to tree performance.

Tree seedling trait optimization and growth in response to local-scale soil and light variability.

At local scales, it has been suggested that high levels of resources lead to increased tree growth via trait optimization (highly peaked trait distribution). However, this contrasts with (1) theories that suggest that trait optimization and high growth occur in the most common resource level and (2) empirical evidence showing that high trait optimization can be also found at low resource levels. This raises the question of how are traits and growth optimized in highly diverse plant communities. Here, we propose a series of hypotheses about how traits and growth are expected to be maximized under different resource levels (low, the most common, and high) in tree seedling communities from a subtropical forest in Puerto Rico, USA. We studied the variation in the distribution of biomass allocation and leaf traits and seedlings growth rate along four resource gradients: light availability (canopy openness) and soil K, Mg, and N content. Our analyses consisted of comparing trait kurtosis (a measurement of trait optimization), community trait means, and relative growth rates at three resource levels (low, common, and high). Trait optimization varied across the three resource levels depending on the type of resource and trait, with leaf traits being optimized under high N and in the most common K and Mg conditions, but not at any of the light levels. Also, seedling growth increased at high-light conditions and high N and K but was not related to trait kurtosis. Our results indicate that local-scale variability of soil fertility and understory light conditions result in shifts in species ecological strategies that increase growth despite a weak trait optimization, suggesting the existence of alternative phenotypes that achieve similar high performance. Uncovering the links between abiotic factors, functional trait diversity and performance is necessary to better predict tree responses to future changes in abiotic conditions.

A phylogenetic and trait-based analysis of community assembly in a subtropical forest in central China.

Despite several decades of study in community ecology, the relative importance of the ecological processes that determine species co-occurrence across spatial scales remains uncertain. Some of this uncertainty may be reduced by studying the scale dependency of community assembly in the light of environmental variation. Phylogenetic information and functional trait information are often used to provide potentially valuable insights into the drivers of community assembly. Here, we combined phylogenetic and trait-based tests to gain insights into community processes at four spatial scales in a large stem-mapped subtropical forest dynamics plot in central China. We found that all of the six leaf economic traits measured in this study had weak, but significant, phylogenetic signal. Nonrandom phylogenetic and trait-based patterns associated with topographic variables indicate that deterministic processes tend to dominate community assembly in this plot. Specifically, we found that, on average, co-occurring species were more phylogenetically and functionally similar than expected throughout the plot at most spatial scales and assemblages of less similar than expected species could only be found on finer spatial scales. In sum, our results suggest that the trait-based effects on community assembly change with spatial scale in a predictable manner and the association of these patterns with topographic variables, indicates the importance of deterministic processes in community assembly relatively to random processes.

Linking patterns and processes of tree community assembly across spatial scales in tropical montane forests.

Many studies have tried to assess the role of both deterministic and stochastic processes in community assembly, yet a lack of consensus exists on which processes are more prevalent and at which spatial scales they operate. To shed light on this issue, we tested two nonmutually exclusive, scale-dependent hypotheses: (1) that competitive exclusion dominates at small spatial scales; and (2) that environmental filtering does so at larger ones. To accomplish this, we studied the functional patterns of tropical montane forest communities along two altitudinal gradients, in Ecuador and Peru, using floristic and functional data from 60 plots of 0.1 ha. We found no evidence of either functional overdispersion or clustering at small spatial scales, but we did find functional clustering at larger ones. The observed pattern of clustering, consistent with an environmental filtering process, was more evident when maximizing the environmental differences among any pair of plots. To strengthen the link between the observed community functional pattern and the underlying process of environmental filtering, we explored differences in the climatic preferences of the most abundant species found at lower and higher elevations and examined whether their abundances shifted along the elevation gradient. We found (1) that greater community functional differences (observed between lower and upper tropical montane forest assemblies) were mostly the result of strong climatic preferences, maintained across the Neotropics; and (2) that the abundances of such species shifted along the elevational gradient. Our findings support the conclusion that, at large spatial scales, environmental filtering is the overriding mechanism for community assembly, because the pattern of functional clustering was linked to species' similarities in their climatic preferences, which ultimately resulted in shifts in species abundances along the gradient. However, there was no evidence of competitive exclusion at more homogeneous, smaller spatial scales, where plant species effectively compete for resources.

Alternative designs and tropical tree seedling growth performance landscapes.

The functional trait values that constitute a whole-plant phenotype interact with the environment to determine demographic rates. Current approaches often fail to explicitly consider trait × trait and trait × environment interactions, which may lead to missed information that is valuable for understanding and predicting the drivers of demographic rates and functional diversity. Here, we consider these interactions by modeling growth performance landscapes that span multidimensional trait spaces along environmental gradients. We utilize individual-level leaf, stem, and root trait data combined with growth data from tree seedlings along soil nutrient and light gradients in a hyper-diverse tropical rainforest. We find that multiple trait combinations in phenotypic space (i.e., alternative designs) lead to multiple growth performance peaks that shift along light and soil axes such that no single or set of interacting traits consistently results in peak growth performance. Evidence from these growth performance peaks also generally indicates frequent independence of above- and belowground resource acquisition strategies. These results help explain how functional diversity is maintained in ecological communities and question the practice of utilizing a single trait or environmental variable, in isolation, to predict the growth performance of individual trees.

Differential soil fungus accumulation and density dependence of trees in a subtropical forest.

The mechanisms underlying interspecific variation in conspecific negative density dependence (CNDD) are poorly understood. Using a multilevel modeling approach, we combined long-term seedling demographic data from a subtropical forest plot with soil fungal community data by means of DNA sequencing to address the feedback of various guilds of soil fungi on the density dependence of trees. We show that mycorrhizal type mediates tree neighborhood interactions at the community level, and much of the interspecific variation in CNDD is explained by how tree species differ in their fungal density accumulation rates as they grow. Species with higher accumulation rates of pathogenic fungi suffered more from CNDD, whereas species with lower CNDD had higher accumulation rates of ectomycorrhizal fungi, suggesting that mutualistic and pathogenic fungi play important but opposing roles.