From plant traits to plant communities: a statistical mechanistic approach to biodiversity

Shaping beta diversity in arid landscape through native plant species contributions: synergy of climate, soil, and species traits

Understanding how species traits, climate aridity, and soil resources interact to influence beta diversity is critical for predicting changes in plant community composition. This study aims to investigate how these interactions shape species contributions to spatial turnover and beta diversity, focusing on the unique dryland ecosystems of the Saint Katherine Protectorate (SKP) in Egypt. To address this, we analyzed data from 84 vegetation plots, considering the direct and indirect effects of climatic aridity, soil resources, and species traits (e.g., plant height, leaf production, specific leaf area), as well as the relative abundance of C3 plants and phylogenetic diversity on species contribution to beta diversity (SCBDeff). Using Generalized Linear Models (GLMs) and Structural Equation Modelling (SEMs), the results revealed complex indirect effects of aridity and soil resources on SCBDeff mediated by plant traits. SCBDeff was positively influenced by climatic aridity, particularly in species with greater phylogenetic distance, taller plants, high leaf production, and a higher relative abundance of C3 plants. Conversely, specific leaf area (SLA) had a negative effect. Phylogenetic diversity emerged as a significant driver of beta diversity, with distantly related species contributing more due to functional differentiation and niche partitioning. The findings emphasize the critical role of species traits and environmental conditions in shaping beta diversity. These insights can inform conservation strategies aimed at enhancing ecosystem stability under shifting climatic conditions, particularly in dryland environments where species adaptive traits play a pivotal role.

A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry

Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides an example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable the use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.

Why ecologists struggle to predict coexistence from functional traits

The rationale behind trait-based ecology is that shifting focus from species' taxonomic names to their measurable characteristics ('functional traits') leads to greater generality and predictive power. This idea has been applied to one of ecology's most intractable problems: the coexistence of competing species. But after 20 years, we lack clear evidence that functional traits effectively predict coexistence. Here, we present a theory-based argument for why this might be the case. Specifically, we argue that coexistence often depends on special quantities called 'process-informed metrics' (PIMs), which combine multiple traits and demographic characteristics in non-intuitive ways, obscuring any direct ties between individual traits and coexistence. We then lay a path forward for trait-based coexistence research that builds on mechanistic models of competition.

Impacts of limits to adaptation on population and community persistence in a changing environment

A key issue in predicting how ecosystems will respond to environmental change is understanding why populations and communities are able to live and reproduce in some parts of ecological and geographical space, but not in others. The limits to adaptation that cause ecological niches to vary in position and width across taxa and environmental contexts determine how communities and ecosystems emerge from selection on phenotypes and genomes. Ecological trade-offs mean that phenotypes can only be optimal in some environments unless these trade-offs can be reshaped through evolution. However, the amount and rate of evolution are limited by genetic architectures, developmental systems (including phenotypic plasticity) and the legacies of recent evolutionary history. Here, we summarize adaptive limits and their ecological consequences in time (evolutionary rescue) and space (species' range limits), relating theoretical predictions to empirical tests. We then highlight key avenues for future research in this area, from better connections between evolution and demography to analysing the genomic architecture of adaptation, the dynamics of plasticity and interactions between the biotic and abiotic environment. Progress on these questions will help us understand when and where evolution and phenotypic plasticity will allow species and communities to persist in the face of rapid environmental change.This article is part of the discussion meeting issue 'Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future'.

Precipitation-induced biomass enhancement and differential allocation in Inner Mongolia's herbaceous and shrub communities

Changes in precipitation patterns induced by global climate change have profound implications for the structure and function of grassland ecosystems. However, the relationship between plant diversity and ecosystem function across different grassland types, particularly those with varying plant compositions and dominant species, remains inadequately understood. To address this knowledge gap, a five-year experimental manipulation of precipitation was conducted within herbaceous and shrub communities in the desert grasslands of Inner Mongolia. We found that increased precipitation significantly enhances aboveground biomass (AGB), belowground biomass (BGB), and community total biomass (CTB) in both herbaceous and shrub communities. In herbaceous communities, increased precipitation led to a disproportionate increase in both aboveground and belowground biomass, supporting the optimal allocation hypothesis. Structural equation modeling (SEM) further elucidated that precipitation regulates AGB and CTB through species richness and functional traits in herbaceous communities. In shrub communities, precipitation influences AGB, BGB, and CTB by affecting species richness and soil water content. This study highlights the critical role of precipitation in shaping biomass dynamics and allocation strategies within herbaceous and shrub communities in desert steppe of Inner Mongolia. These findings provide essential insights into the potential responses of desert grassland ecosystems to ongoing climate change.

Functional diversity of ground beetles improved aphid control but did not increase crop yields on European farms

Land-use intensification is often associated with a decline in functional diversity, potentially undermining the provision of ecosystem services. However, how changes in traits affect ecosystem processes remains poorly understood. Variation in trait values among species in a community may drive ecosystem processes. Alternatively, the mass ratio hypothesis proposes that trait values of the dominant species in a local community are related to ecosystem processes. Using data from 159 farms in six European countries, we quantified the impact of local and landscape-level land-use intensity on ground beetles as pest control agents. We then assessed the extent to which functional diversity and community-weighted mean trait values relate to pest control and cereal yield. In addition, we assessed how the responses to land use and the effects of different species on pest control and yield varied with their traits to compare the relative impact of the traits studied. Functional diversity of ground beetles improved aphid removal, but did not translate into higher crop yields. Pest control of aphids was enhanced by a higher proportion of smaller, mobile ground beetles with a preference for the vegetation layer. Smaller, predatory ground beetles in communities improved crop yield. The magnitude of responses to land-use intensification and the effects on pest control and yield were more strongly influenced by body size than other traits. Our study provides evidence that reduced management intensity can improve pest control by supporting small-sized, macropterous ground beetles. In contrast to the claims of ecological intensification, our joint analysis of the direct effects of land use on yield and indirect effects via functional diversity of ground beetles and pest control suggests that ecosystem services by ground beetles cannot compensate for the yield gap due to a reduction in land-use intensity.

A quick and effective trait-based protocol for selecting appropriate native plant species for the reforestation of degraded tropical mines

Introduction

A critical issue in tropical forests is that anthropogenic deforestation (i.e., mining) degrades the integrity of its ecosystem. Reforestation with appropriate native plant species helps to alleviate these detrimental impacts. A protocol to select appropriate plant species for this purpose currently lacks efficacy and timeliness.

Methods

We provided a trait-based protocol to quickly and effectively select native plant species for mining reforestation. A 0.2-km2 area of Baopoling (BPL) at Hainan Island, China, was used as a study site, which has been severely degraded by 20 years of limestone mining for cement production. First, we identified the tree species in nearby undisturbed tropical forests, followed by evaluating the similarities in functional traits of the most dominant one (target species) and 60 local candidate native plant species (candidate species) whose saplings can be purchased from a local market.

Results and discussion

This dataset was used in our trait-based protocol, and only within 1 month, we successfully selected eight plant species which are very similar to target species from the 60 candidate species. We also quantified whether the eight selected plant species were indeed suitable for sustained reforestation by testing their effects on landscape and also their survival rate and recruitment ability after using them to perform reforestation in BPL from 2016 to 2023. Finally, these eight plant species are indeed suitable for reforestation due to their huge influences on a significant shift from originally degraded landscape (comprising only barren rocks) to a forest landscape totally and also their high survival rate (90%-97%) and ability for natural recruitment after 7 years' reforestation in BPL. Thus, we anticipate that this protocol would be integral to species selection during reforestation of tropical mining areas.

Species Richness Net Primary Productivity and the Water Balance Problem

Species energy theory suggests that, because of limitations on reproduction efficiency, a minimum density of plant individuals per viable species exists and that this minimum correlates the total number of plant individuals N with the number of species S. The simplest assumption is that the mean energy input per individual plant is independent of the number of individuals, making N, and thus S as well, proportional to the total energy input into the system. The primary energy input to a plant-dominated ecosystem is estimated as its Net Primary Productivity (NPP). Thus, species energy theory draws a direct correspondence from NPP to S. Although investigations have verified a strong connection between S and NPP, strong influences of other factors, such as topography, ecological processes such as competition, and historical contingencies, are also at play. The lack of a simple model of NPP expressed in terms of the principal climate variables, precipitation P, and potential evapotranspiration, PET, introduces unnecessary uncertainty to the understanding of species richness across scales. Recent research combines percolation theory with the principle of ecological optimality to derive an expression for NPP(P, PET). Consistent with assuming S is proportional to NPP, we show here that the new expression for NPP(P, PET) predicts the number of plant species S in an ecosystem as a function of P and PET. As already demonstrated elsewhere, the results are consistent with some additional variation due to non-climatic inputs. We suggest that it may be easier to infer specific deviations from species energy predictions with increased accuracy and generality of the prediction of NPP(P, PET).

CoRRE Trait Data: A dataset of 17 categorical and continuous traits for 4079 grassland species worldwide

In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species' responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide.

Meso-scale environmental heterogeneity drives plant trait distributions in fragmented dry grasslands

Environmental heterogeneity shapes the patterns of resources and limiting factors and therefore can be an important driver of plant community composition through the selection of the most adaptive functional traits. In this study, we explored plant trait-environment relationships in environmentally heterogeneous microsite complexes at the meso-scale (few meters), and used ancient Bulgarian and Hungarian burial mounds covered by dry grasslands as a model habitat. We assessed within-site trait variability typical of certain microsites with different combinations of environmental parameters (mound slopes with different aspects, mound tops, and surrounding plain grasslands) using a dataset of 480 vegetation plots. For this we calculated community-weighted means (CWMs) and abundance models. We found that despite their small size, the vegetation on mounds was characterized by different sets of functional traits (higher canopy, higher level of clonality, and heavier seeds) compared to the plain grasslands. North-facing slopes with mild environmental conditions were characterized by perennial species with light seeds, short flowering period, and a high proportion of dwarf shrubs sharply contrasted from the plain grasslands and from the south-facing slopes and mound tops with harsh environmental conditions. Patterns predicted by CWMs and abundance models differed in the case of certain traits (perenniality, canopy height, and leaf dry matter content), suggesting that environmental factors do not necessarily affect trait optima directly, but influence them indirectly through correlating traits. Due to the large relative differences in environmental parameters, contrasts in trait composition among microsites were mostly consistent and independent from the macroclimate. Mounds with high environmental heterogeneity can considerably increase variability in plant functional traits and ecological strategies at the site and landscape levels. The large trait variation on topographically heterogeneous landscape features can increase community resilience against climate change or stochastic disturbances, which underlines their conservation importance.

Feedback loops drive ecological succession: towards a unified conceptual framework

The core principle shared by most theories and models of succession is that, following a major disturbance, plant-environment feedback dynamics drive a directional change in the plant community. The most commonly studied feedback loops are those in which the regrowth of the plant community causes changes to the abiotic (e.g. soil nutrients) or biotic (e.g. dispersers) environment, which differentially affect species availability or performance. This, in turn, leads to shifts in the species composition of the plant community. However, there are many other PE feedback loops that potentially drive succession, each of which can be considered a model of succession. While plant-environment feedback loops in principle generate predictable successional trajectories, succession is generally observed to be highly variable. Factors contributing to this variability are the stochastic processes involved in feedback dynamics, such as individual mortality and seed dispersal, and extrinsic causes of succession, which are not affected by changes in the plant community but do affect species performance or availability. Both can lead to variation in the identity of dominant species within communities. This, in turn, leads to further contingencies if these species differ in their effect on their environment (priority effects). Predictability and variability are thus intrinsically linked features of ecological succession. We present a new conceptual framework of ecological succession that integrates the propositions discussed above. This framework defines seven general causes: landscape context, disturbance and land-use, biotic factors, abiotic factors, species availability, species performance, and the plant community. When involved in a feedback loop, these general causes drive succession and when not, they are extrinsic causes that create variability in successional trajectories and dynamics. The proposed framework provides a guide for linking these general causes into causal pathways that represent specific models of succession. Our framework represents a systematic approach to identifying the main feedback processes and causes of variation at different successional stages. It can be used for systematic comparisons among study sites and along environmental gradients, to conceptualise studies, and to guide the formulation of research questions and design of field studies. Mapping an extensive field study onto our conceptual framework revealed that the pathways representing the study's empirical outcomes and conceptual model had important differences, underlining the need to move beyond the conceptual models that currently dominate in specific fields and to find ways to examine the importance of and interactions among alternative causal pathways of succession. To further this aim, we argue for integrating long-term studies across environmental and anthropogenic gradients, combined with controlled experiments and dynamic modelling.

Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Ecosystem response to climate change is complex. In order to forecast ecosystem dynamics, we need high-quality data on changes in past species abundance that can inform process-based models. Sedimentary ancient DNA (sedaDNA) has revolutionised our ability to document past ecosystems' dynamics. It provides time series of increased taxonomic resolution compared to microfossils (pollen, spores), and can often give species-level information, especially for past vascular plant and mammal abundances. Time series are much richer in information than contemporary spatial distribution information, which have been traditionally used to train models for predicting biodiversity and ecosystem responses to climate change. Here, we outline the potential contribution of sedaDNA to forecast ecosystem changes. We showcase how species-level time series may allow quantification of the effect of biotic interactions in ecosystem dynamics, and be used to estimate dispersal rates when a dense network of sites is available. By combining palaeo-time series, process-based models, and inverse modelling, we can recover the biotic and abiotic processes underlying ecosystem dynamics, which are traditionally very challenging to characterise. Dynamic models informed by sedaDNA can further be used to extrapolate beyond current dynamics and provide robust forecasts of ecosystem responses to future climate change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Relative contributions of taxonomic and functional diversity to the assembly of plant communities hosting endemic Dianthus species in a mountain steppe

Plant community assembly is the outcome of long-term evolutionary events (evident as taxonomic diversity; TD) and immediate adaptive fitness (functional diversity; FD); a balance expected to shift in favour of FD in 'harsh' habitats under intense selection pressures. We compared TD and FD responses along climatic and edaphic gradients for communities of two species (Dianthus pseudocrinitus and D. polylepis) endemic to the montane steppes of the Khorassan-Kopet Dagh floristic province, NE Iran. 75 plots at 15 sites were used to relate TD and FD to environmental gradients. In general, greater TD was associated with variation in soil factors (potassium, lime, organic matter contents), whereas FD was constrained by aridity (drought adaptation). Crucially, even plant communities hosting different subspecies of D. polylepis responded differently to aridity: D. polylepis subsp. binaludensis communities included a variety of broadly stress-tolerant taxa with no clear environmental response, but TD of D. polylepis subsp. polylepis communities was directly related to precipitation, with consistently low FD reflecting a few highly specialized stress-tolerators. Integrating taxonomic and functional diversity metrics is essential to understand the communities hosting even extremely closely related taxa, which respond idiosyncratically to climate and soil gradients.

Drivers of plant diversity, community composition, functional traits, and soil processes along an alpine gradient in the central Chilean Andes

High alpine regions are threatened but understudied ecosystems that harbor diverse endemic species, making them an important biome for testing the role of environmental factors in driving functional trait-mediated community assembly processes. We tested the hypothesis that plant community assembly along a climatic and elevation gradient is influenced by shifts in habitat suitability, which drive plant functional, phylogenetic, and spectral diversity. In a high mountain system (2400-3500 m) Región Metropolitana in the central Chilean Andes (33°S, 70°W). We surveyed vegetation and spectroscopic reflectance (400-2400 nm) to quantify taxonomic, phylogenetic, functional, and spectral diversity at five sites from 2400 to 3500 m elevation. We characterized soil attributes and processes by measuring water content, carbon and nitrogen, and net nitrogen mineralization rates. At high elevation, colder temperatures reduced available soil nitrogen, while at warmer, lower elevations, soil moisture was lower. Metrics of taxonomic, functional, and spectral alpha diversity peaked at mid-elevations, while phylogenetic species richness was highest at low elevation. Leaf nitrogen increased with elevation at the community level and within individual species, consistent with global patterns of increasing leaf nitrogen with colder temperatures. The increase in leaf nitrogen, coupled with shifts in taxonomic and functional diversity associated with turnover in lineages, indicate that the ability to acquire and retain nitrogen in colder temperatures may be important in plant community assembly in this range. Such environmental filters have important implications for forecasting shifts in alpine plant communities under a warming climate.

Prey selection along a predators' body size gradient evidences the role of different trait-based mechanisms in food web organization

An increase in prey richness, prey size and predator trophic position with predator body size has been consistently reported as prime features of food web organization. These trends have been explained by non-exclusive mechanisms. First, the increase in energy demand with body size determines that larger predators must reduce prey selectivity for achieving the required number of resources, being consumption relationships independent of prey traits. Second, when consumption is restricted by gape limitation, small predators are constrained to select among small prey. However, this selection weakens over large predators, which progressively consume more and larger prey. Finally, the optimal foraging mechanism predicts that larger predators optimize their diet by selecting only large prey with high energy reward. Each one of these mechanisms can individually explain the increase in prey richness, prey size and predator trophic position with predator body size but their relative importance or the direct evidence for their combined role was seldom considered. Here we use the community assembly by trait selection (CATS) theory for evaluating the support for each one of these mechanisms based on the prey selection patterns that they predict. We analyzed how prey body size and trophic guild determine prey selection by predators of increasing body size in a killifish guild from a temporary pond system. Results support the combination of the three mechanisms to explain the structural trends in our food web, although their strength is contingent on prey trophic group. Overall, high energy prey are preferred by larger predators, and small predators select small prey of all trophic status. However, large predators prefer large primary producers and avoid large carnivorous prey, probably because of the inherent risk of consuming other carnivorous. Our study provides a mechanistic understanding of how predator traits determine the selection of prey traits affecting food web assembly.

Alternative measures of trait-niche relationships: A test on dispersal traits in saproxylic beetles

Functional trait approaches are common in ecology, but a lack of clear hypotheses on how traits relate to environmental gradients (i.e., trait-niche relationships) often makes uncovering mechanisms difficult. Furthermore, measures of community functional structure differ in their implications, yet inferences are seldom compared among metrics. Community-weighted mean trait values (CWMs), a common measure, are largely driven by the most common species and thus do not reflect community-wide trait-niche relationships per se. Alternatively, trait-niche relationships can be estimated across a larger group of species using hierarchical joint species distribution models (JSDMs), quantified by a parameter Γ. We investigated how inferences about trait-niche relationships are affected by the choice of metric. Using deadwood-dependent (saproxylic) beetles in fragmented Finnish forests, we followed a protocol for investigating trait-niche relationships by (1) identifying environmental filters (climate, forest age, and deadwood volume), (2) relating these to an ecological function (dispersal ability), and (3) identifying traits related to this function (wing morphology). We tested 18 hypothesized dispersal relationships using both CWM and Γ estimates across these environmental gradients. CWMs were more likely than Γ to show support for trait-niche relationships. Up to 13% of species' realized niches were explained by dispersal traits, but the directions of effects were consistent with fewer than 11%-39% of our 18 trait-niche hypotheses (depending on the metric used). This highlights the difficulty in connecting morphological traits and ecological functions in insects, despite the clear conceptual link between landscape connectivity and flight-related traits. Caution is thus warranted in hypothesis development, particularly where apparent trait-function links are less clear. Inferences differ when CWMs versus Γ estimates are used, necessitating the choice of a metric that reflects study questions. CWMs help explain the effects of environmental gradients on community trait composition, whereas the effects of traits on species' niches are better estimated using hierarchical JSDMs.

A new fractal index to classify forest fragmentation and disorder

Context

Forest loss and fragmentation pose extreme threats to biodiversity. Their efficient characterization from remotely sensed data therefore has strong practical implications. Data are often separately analyzed for spatial fragmentation and disorder, but no existing metric simultaneously quantifies both the shape and arrangement of fragments.

Objectives

We present a fractal fragmentation and disorder index (FFDI), which advances a previously developed fractal index by merging it with the Rényi information dimension. The FFDI is designed to work across spatial scales, and to efficiently report both the fragmentation of images and their spatial disorder.

Methods

We validate the FFDI with 12,600 synthetic hierarchically structured random map (HRM) multiscale images, as well as several other categories of fractal and non-fractal test images (4880 images). We then apply the FFDI to satellite imagery of forest cover for 10 distinct regions of the Romanian Carpathian Mountains from 2000–2021.

Results

The FFDI outperformed its two individual components (fractal fragmentation index and Rényi information dimension) in resolving spatial patterns of disorder and fragmentation when tested on HRM classes and other image types. The FFDI thus offers a clear advantage when compared to the individual use of fractal fragmentation index and the Information Dimension, and provided good classification performance in an application to real data.

Conclusions

This work improves on previous characterizations of landscape patterns. With the FFDI, scientists will be able to better monitor and understand forest fragmentation from satellite imagery. The FFDI may also find wider applicability in biology wherever image analysis is used.

Linking plant and vertebrate species to Nature's Contributions to People in the Swiss Alps

Since the late 1990s, Nature's Contributions to People (NCPs; i.e. ecosystem services) were used as a putative leverage for fostering nature preservation. NCPs have largely been defined and mapped at the landscape level using land use and cover classifications. However, NCP mapping attempts based directly on individual species are still uncommon. Given that species shape ecosystems and ultimately deliver NCPs, mapping NCPs based on species distribution data should deliver highly meaningful results. This requires first establishing a census of the species-to-NCP relationships. However, datasets quantifying these relationships across several species and NCPs are rare. Here, we fill this gap by compiling literature and expert knowledge to establish the relationships of 1816 tracheophyte and 250 vertebrate species with 17 NCPs in the Swiss Alps. We illustrated the 31,098 identified species-NCP relationships for the two lineages and discuss why such a table is a key initial step in building spatial predictions of NCPs directly from species data, e.g. to ultimately complement spatial conservation planning.

Sex-specific outbreeding advantages and sexual dimorphism in the seedlings of dioecious trees

PREMISE

Dioecious trees are important components of many forest ecosystems. Outbreeding advantage and sexual dimorphism are two major mechanisms that explain the persistence of dioecious plants; however, they have rarely been studied in dioecious trees.

METHODS

We investigated the influence of sex and genetic distance between parental trees (GDPT) on the growth and functional traits of multiple seedlings of a dioecious tree, Diospyros morrisiana.

RESULTS

We found significant positive relationships between GDPT and seedling sizes and tissue density. However, the positive outbreeding effects on seedling growth mainly manifested in female seedlings, but were not prominent in males. Among seedlings, the male ones generally had higher biomass and leaf area than female seedlings, but such differences diminished as GDPT increased.

CONCLUSIONS

Our research highlights that outbreeding advantage in plants can be sex-specific and that sexual dimorphism begins from the seedling stage of dioecious trees.

Species richness drives selection of individuals within wetlands based on traits related to acquisition and utilization of light

Selection within natural communities has mainly been studied along large abiotic gradients, while the selection of individuals within populations should occur locally in response to biotic filters. To better leverage the role of the latter, we considered the hierarchal nature of environmental selection for the multiple dimensions of the trait space across biological levels, that is, from the species to the community and the ecosystem levels. We replicated a natural species richness gradient where communities included from two to 16 species within four wetlands (bog, fen, meadow, and marsh) contrasting in plant productivity. We sampled functional traits from individuals in each community and used hierarchical distributional modeling in order to analyze the independent variation of the mean and dispersion of functional trait space at ecosystem, community, and species levels. The plant productivity gradient observed between wetlands led to species turnover and selection of traits related to leaf nutrient conservation/acquisition strategy. Within wetlands, plant species richness drove trait variation across both communities and species. Among communities, variation of species richness correlated with the selection of individuals according to their use of vertical space and leaf adaptations to light conditions. Within species, intraspecific light-related trait variation in response to species richness was associated with stable population density for some species, while others reached low population density in more diverse communities. Within ecosystems, variation in biotic conditions selects individuals along functional dimensions that are independent of those selected across ecosystems. Within-species variations of light-related traits are related to demographic responses, linking biotic selection of individuals within communities to eco-evolutionary dynamics of species.

Net effects of life-history traits explain persistent differences in abundance among similar species

Life-history traits are promising tools to predict species commonness and rarity because they influence a population's fitness in a given environment. Yet, species with similar traits can have vastly different abundances, challenging the prospect of robust trait-based predictions. Using long-term demographic monitoring, we show that coral populations with similar morphological and life-history traits show persistent (decade-long) differences in abundance. Morphological groups predicted species positions along two, well known life-history axes (the fast-slow continuum and size-specific fecundity). However, integral projection models revealed that density-independent population growth (λ) was more variable within morphological groups, and was consistently higher in dominant species relative to rare species. Within-group λ differences projected large abundance differences among similar species in short timeframes, and were generated by small but compounding variation in growth, survival, and reproduction. Our study shows that easily measured morphological traits predict demographic strategies, yet small life-history differences can accumulate into large differences in λ and abundance among similar species. Quantifying the net effects of multiple traits on population dynamics is therefore essential to anticipate species commonness and rarity.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Changes in trait covariance along an orographic moisture gradient reveal the relative importance of light- and moisture-driven trade-offs in subtropical rainforest communities

A range of functional trait-based approaches have been developed to investigate community assembly processes, but most ignore how traits covary within communities. We combined existing approaches - community-weighted means (CWMs) and functional dispersion (FDis) - with a metric of trait covariance to examine assembly processes in five angiosperm assemblages along a moisture gradient in Australia's subtropics. In addition to testing hypotheses about habitat filtering along the gradient, we hypothesized that trait covariance would be strongest at both ends of the moisture gradient and weakest in the middle, reflecting trade-offs associated with light capture in productive sites and moisture stress in dry sites. CWMs revealed evidence of climatic filtering, but FDis patterns were less clear. As hypothesized, trait covariance was weakest in the middle of the gradient but unexpectedly peaked at the second driest site due to the emergence of a clear drought tolerance-drought avoidance spectrum. At the driest site, the same spectrum was truncated at the 'avoider' end, revealing important information about habitat filtering in this system. Our focus on trait covariance revealed the nature and strength of trade-offs imposed by light and moisture availability, complementing insights gained about community assembly from existing trait-based approaches.

Leaf spectroscopy reveals divergent inter- and intra-species foliar trait covariation and trait-environment relationships across NEON domains

Concurrent measurement of multiple foliar traits to assess the full range of trade-offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment. We analyzed leaf trait measurements from 32 sites along the wide eco-climatic gradient encompassed by the US National Ecological Observatory Network (NEON). We explored the relationships among 14 foliar traits of 1103 individuals across and within species, and with environmental factors. Across all species pooled, the relationships between leaf economic traits (leaf mass per area, nitrogen) and traits indicative of defense and stress tolerance (phenolics, nonstructural carbohydrates) were weak, but became strong within certain species. Elevation, mean annual temperature and precipitation weakly predicted trait variation across species, although some traits exhibited species-specific significant relationships with environmental factors. Foliar functional traits vary idiosyncratically and species express diverse combinations of leaf traits to achieve fitness. Leaf spectroscopy offers an effective approach to quantify intra-species trait variation and covariation, and potentially could be used to improve the characterization of vegetation in Earth system models.

Ontogenetic trait variation and metacommunity effects influence species relative abundances during tree community assembly

Predicting species abundance is one of the most fundamental pursuits of ecology. Combining the information encoded in functional traits and metacommunities provides a new perspective to predict the abundance of species in communities. We applied a community assembly via trait selection model to predict quadrat-scale species abundances using functional trait variation on ontogenetic stages and metacommunity information for over 490 plant species in a subtropical forest and a lowland tropical forest in Yunnan, China. The relative importance of trait-based selection, mass effects, and stochasticity in shaping local species abundances is evaluated using different null models. We found both mass effects and trait selection contribute to local abundance patterns. Trait selection was detectable at all studied spatial scales (0.04-1 ha), with its strength stronger at larger scales and in the subtropical forest. In contrast, the importance of stochasticity decreased with spatial scale. A significant mass effect of the metacommunity was observed at small spatial scales. Our results indicate that tree community assembly is primarily driven by ontogenetic traits and metacommunity effects. Our findings also demonstrate that including ontogenetic trait variation into predictive frameworks allows ecologists to infer ecological mechanisms operating in community assembly at the individual level.

Inferring spatial source of disease outbreaks using maximum entropy

Mathematical modeling of disease outbreaks can infer the future trajectory of an epidemic, allowing for making more informed policy decisions. Another task is inferring the origin of a disease, which is relatively difficult with current mathematical models. Such frameworks, across varying levels of complexity, are typically sensitive to input data on epidemic parameters, case counts, and mortality rates, which are generally noisy and incomplete. To alleviate these limitations, we propose a maximum entropy framework that fits epidemiological models, provides calibrated infection origin probabilities, and is robust to noise due to a prior belief model. Maximum entropy is agnostic to the parameters or model structure used and allows for flexible use when faced with sparse data conditions and incomplete knowledge in the dynamical phase of disease-spread, providing for more reliable modeling at early stages of outbreaks. We evaluate the performance of our model by predicting future disease trajectories based on simulated epidemiological data in synthetic graph networks and the real mobility network of New York State. In addition, unlike existing approaches, we demonstrate that the method can be used to infer the origin of the outbreak with accurate confidence. Indeed, despite the prevalent belief on the feasibility of contact-tracing being limited to the initial stages of an outbreak, we report the possibility of reconstructing early disease dynamics, including the epidemic seed, at advanced stages.

Changes in plant biodiversity facets of rocky outcrops and their surrounding rangelands across precipitation and soil gradients

Climate and soil factors induce substantial controls over plant biodiversity in stressful ecosystems. Despite of some studies on plant biodiversity in extreme ecosystems including rocky outcrops, simultaneous effects of climate and soil factors have rarely been studied on different facets of biodiversity including taxonomic and functional diversity in these ecosystems. In addition, we know little about plant biodiversity variations in such extreme ecosystems compared to natural environments. It seems that environmental factors acting in different spatial scales specifically influence some facets of plant biodiversity. Therefore, we studied changes in taxonomic and functional diversity along precipitation and soil gradients in both landscapes (i) rocky outcrops and (ii) their nearby rangeland sites in northeast of Iran. In this regard, we considered six sites across precipitation and soil gradients in each landscape, and established 90 1m² quadrates in them (i.e. 15 quadrats in each site; 15 × 6 = 90 in each landscape). Then, taxonomic and functional diversity were measured using RaoQ index, FDis and CWM indices. Finally, we assessed impacts of precipitation and soil factors on biodiversity indices in both landscapes by performing regression models and variation partitioning procedure. The patterns of taxonomic diversity similarly showed nonlinear changes along the precipitation and soil factors in both landscapes (i.e. outcrop and rangeland). However, we found a more negative and significant trends of variation in functional diversity indices (except for CWMSLA) across precipitation and soil factors in outcrops than their surrounding rangelands. Variations of plant biodiversity were more explained by precipitation factors in surrounding rangelands, whereas soil factors including organic carbon had more consistent and significant effects on plant biodiversity in outcrops. Therefore, our results represent important impacts of soil factors in structuring plant biodiversity facets in stressful ecosystems. While, environmental factors acting in regional and broad scales such as precipitation generally shape vegetation and plant biodiversity patterns in natural ecosystems. We can conclude that rocky outcrops provide suitable microenvironments to present plant species with similar yields that are less able to be present in rangeland ecosystems.

The acquisitive-conservative axis of leaf trait variation emerges even in homogeneous environments

BACKGROUND AND AIMS

The acquisitive-conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation.

METHODS

We analysed covariation of four leaf functional traits [specific leaf area (SLA) leaf dry matter content (LDMC), force to tear (Ft) and leaf nitrogen content (Nm)] in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern.

KEY RESULTS

We found negative correlations for the LDMC-SLA, Ft-SLA, LDMC-Nm and Ft-Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not explained by climatic or edaphic variation in the field follows the expected acquisitive-conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g. all the intraspecific LDMC-SLA and LDMC-Nm slopes tend to be shallower than the global pattern).

CONCLUSIONS

Our study indicates that the acquisitive-conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation-covariation in leaf functional traits not driven by environmental variables.

Effects of elevated CO2 concentration and nitrogen addition on the chemical compositions, construction cost and payback time of subtropical trees in Cd-contaminated mesocosm soil

Rising atmospheric CO2 concentration ([CO2]) and nitrogen (N) deposition are changing plant growth, physiological characteristics and chemical compositions; however, few studies have explored such impacts in a heavy metal-contaminated environment. In this study, we conducted an open-top chamber experiment to explore the impacts of 2 years of elevated atmospheric [CO2] and N addition on the growth, physiological characteristics and chemical compositions of five subtropical tree species in a cadmium (Cd)-contaminated environment. Results showed that N addition significantly increased concentration of leaf N and protein in five tree species and also decreased payback time (PBT) and leaf carbon:nitrogen ratios and increased tree relative height growth rate (RGR-H) and basal diameter growth rate (RGR-B) in Liquidambar formosana Hance and Syzygium hainanense Chang et Miau. Elevated [CO2] increased leaf maximum photosynthetic rate (Amax) and concentration of total non-structural carbohydrates and shortened PBT to offset the negative effect of Cd contamination on RGR-B in Acacia auriculiformis A. Cunn. ex Benth. The combined effects of elevated [CO2] and N addition did not exceed their separate effects on RGR-H and RGR-B in Castanopsis hystrix Hook. f. & Thomson ex A. DC. and Cinnamomum camphora (L.) presl. The addition of N significantly increased the concentration of leaf Cd by 162.1% and 338.0%, and plant Cd bio-concentration factor by 464% and 861% in C. hystrix and C. camphora, respectively, compared with only Cd addition. Among the five tree species, the decrease in PBT and the increase in Amax, RGR-B and concentrations of leaf protein in response to N and Cd addition under elevated [CO2] were on average 86.7% higher in A. auriculiformis than other species, suggesting that the mitigation of the negative effects of Cd pollution by elevated [CO2] and N addition among five species was species-specific. Overall, we concluded that N addition and elevated [CO2] reduced Cd toxicity and increased the growth rate in A. auriculiformis, S. hainanense and L. formosana, while it maintained the growth rate in C. hystrix and C. camphora by differently increasing photosynthetic rate, altering the leaf chemical compositions and shortening PBT.

Hydraulic tradeoffs underlie local variation in tropical forest functional diversity and sensitivity to drought

Tropical forests are important to the regulation of climate and the maintenance of biodiversity on Earth. However, these ecosystems are threatened by climate change, as temperatures rise and droughts' frequency and duration increase. Xylem anatomical traits are an essential component in understanding and predicting forest responses to changes in water availability. We calculated the community-weighted means and variances of xylem anatomical traits of hydraulic and structural importance (plot-level trait values weighted by species abundance) to assess their linkages to local adaptation and community assembly in response to varying soil water conditions in an environmentally diverse Brazilian Atlantic Forest habitat. Scaling approaches revealed community-level tradeoffs in xylem traits not observed at the species level. Towards drier sites, xylem structural reinforcement and integration balanced against hydraulic efficiency and capacitance xylem traits, leading to changes in plant community diversity. We show how general community assembly rules are reflected in persistent fiber-parenchyma and xylem hydraulic tradeoffs. Trait variation across a moisture gradient is larger between species than within species and is realized mainly through changes in species composition and abundance, suggesting habitat specialization. Modeling efforts to predict tropical forest diversity and drought sensitivity may benefit from adding hydraulic architecture traits into the analysis.

No complementarity no gain-Net diversity effects on tree productivity occur once complementarity emerges during early stand development

Although there is compelling evidence that tree diversity has an overall positive effect on forest productivity, there are important divergences among studies on the nature and strength of these diversity effects and their timing during forest stand development. To clarify conflicting results related to stand developmental stage, we explored how diversity effects on productivity change through time in a diversity experiment spanning 11 years. We show that the strength of diversity effects on productivity progressively increases through time, becoming significantly positive after 9 years. Moreover, we demonstrate that the strengthening of diversity effects is driven primarily by gradual increases in complementarity. We also show that mixing species with contrasting resource-acquisition strategies, and the dominance of deciduous, fast-developing species, promote positive diversity effects on productivity. Our results suggest that the canopy closure and subsequent stem exclusion phase are key for promoting niche complementarity in diverse tree communities.

Future landscape of renewable fuel resources: Current and future conservation and utilization of main biofuel crops in China

Biofuel crops are one of the most promising regenerative alternatives of energy resources to fossil fuels. Revealing the current and future resource distribution patterns of biofuel crops will promote the development of green energies and the mitigation of greenhouse gas emissions. In this study, we first conducted a comprehensive and systematic analysis on the distribution patterns of main biofuel crops in China, using 22,352 occurrence records of 31 biofuel plant species and thirty-year environmental variables (1970-2000) with maximum entropy modeling, as well as nine-year field investigation of land use (2011-2019). The results showed that there were six different sub-regions for main biofuel crops in China, while Southwest China and South China were determined as the main concentrated potential regions. Specifically, the ranges of these regions were wider than those of current land use of main biofuel crops in China, indicating great potential for industrial cultivation. Moreover, the main biofuel crops had diverse changing patterns including increase, decrease and unstable under future climate change. Among them, biofuel crops with increase pattern (six crops) and decrease pattern (seven crops) should receive high attention for future resource utilization and production. Further field validation results confirmed that the above distribution patterns were mainly determined by increasing global temperature and precipitation. Collectively, these results will provide valuable references for the utilization and development of main biofuel resources under climate change in China, thereby shedding light on studies regarding the production of green biofuels globally.

Devil in the details: how can we avoid potential pitfalls of CATS regression when our data do not follow a Poisson distribution?

BACKGROUND

Community assembly by trait selection (CATS) allows for the detection of environmental filtering and estimation of the relative role of local and regional (meta-community-level) effects on community composition from trait and abundance data without using environmental data. It has been shown that Poisson regression of abundances against trait data results in the same parameter estimates. Abundance data do not necessarily follow a Poisson distribution, and in these cases, other generalized linear models should be fitted to obtain unbiased parameter estimates.

AIMS

This paper discusses how the original algorithm for calculating the relative role of local and regional effects has to be modified if Poisson model is not appropriate.

RESULTS

It can be shown that the use of the logarithm of regional relative abundances as an offset is appropriate only if a log-link function is applied. Otherwise, the link function should be applied to the product of local total abundance and regional relative abundances. Since this product may be outside the domain of the link function, the use of log-link is recommended, even if it is not the canonical link. An algorithm is also suggested for calculating the offset when data are zero-inflated. The relative role of local and regional effects is measured by Kullback-Leibler R2. The formula for this measure presented by Shipley (2014) is valid only if the abundances follow a Poisson distribution. Otherwise, slightly different formulas have to be applied. Beyond theoretical considerations, the proposed refinements are illustrated by numerical examples. CATS regression could be a useful tool for community ecologists, but it has to be slightly modified when abundance data do not follow a Poisson distribution. This paper gives detailed instructions on the necessary refinement.

Biogeomorphological eco-evolutionary feedback between life and geomorphology: a theoretical framework using fossorial mammals

Engineer organisms not only adapt to pre-existing environmental conditions but also co-construct their physical environment. By doing so, they can subsequently change selection pressures for themselves and other species, as well as change community and ecosystem structures and functions. Focusing on one representative example, i.e., fossorial mammals, we show that geomorphological Earth system components are crucial for understanding and quantifying links between evolutionary and ecosystem dynamics and that feedbacks between geomorphology and engineer organisms constitute a major driver of geomorphological organization on the Earth's surface. We propose a biogeomorphological eco-evolutionary feedback synthesis from the gene to the landscape where eco-evolutionary feedbacks are mediated by the geomorphological dimensions of a niche that are affected by engineer organisms, such as fossorial mammals. Our concept encompasses (i) the initial responses of fossorial mammals to environmental constraints that enhance the evolution of their morphological and biomechanical traits for digging in the soil; (ii) specific adaptations of engineer fossorial mammals (morphological, biomechanical, physiological and behavioural feedback traits for living in burrows) to their constructed geomorphological environment; and (iii) ecological and evolutionary feedbacks diffusing at the community and ecological levels. Such a new perspective in geomorphology may lead to a better conceptualization and analysis of Earth surface processes and landforms as parts of complex adaptive systems in which Darwinian selection processes at lower landscape levels lead to self-organization of higher-level landforms and landscapes.

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed 'meta-metabolome ecology.' Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as 'thermodynamic redundancy,' which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable concepts, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Spatial Scale Dependence of Ecological Factors That Regulate Functional and Phylogenetic Assembly in a Mediterranean High Mountain Grassland

Understanding how functional and phylogenetic patterns vary among scales and along ecological gradients within a given species pool is critical for inferring community assembly processes. However, we lack a clear understanding of these patterns in stressful habitats such as Mediterranean high mountains where ongoing global warming is expected to affect species fitness and species interactions, and subsequently species turnover. In this study, we investigated 39 grasslands with the same type of plant community and very little species turnover across an elevation gradient above the treeline at Sierra de Guadarrama National Park in central Spain. In particular, we assessed functional and phylogenetic patterns, including functional heterogeneity, using a multi-scale approach (cells, subplots, and plots) and determined the relevance of key ecological factors (i.e., elevation, potential solar radiation, pH, soil organic carbon, species richness, and functional heterogeneity) that affect functional and phylogenetic patterns at each spatial scale. Overall, at the plot scale, coexisting species tended to be more functionally and phylogenetically similar. By contrast, at the subplot and cell scales, species tended to be more functionally different but phylogenetically similar. Functional heterogeneity at the cell scale was comparable to the variation across plots along the gradient. The relevance of ecological factors that regulate diversity patterns varied among spatial scales. An increase in elevation resulted in functional clustering at larger scales and phylogenetic overdispersion at a smaller scale. The soil pH and organic carbon levels exhibited complex functional patterns, especially at small spatial scales, where an increase in pH led to clustering patterns for the traits related to the leaf economic spectrum (i.e., foliar thickness, specific leaf area, and leaf dry matter content). Our findings confirm the presence of primary environmental filters (coldness and summer drought at our study sites) that constrain the regional species pool, suggesting the presence of additional assembly mechanisms that act at the smallest scale (e.g., micro-environmental gradients and/or species interactions). Functional and phylogenetic relatedness should be determined using a multi-scale approach to help interpret community assembly processes and understand the initial community responses to environmental changes, including ongoing global warming.

Quantifying the relationship linking the community-weighted means of plant traits and soil fertility

Is it possible to generalize relationships between certain plant traits and soil fertility? In particular, are there quantitative relationships between community-weighted mean (CWM) trait values of leaf dry-matter content (LDMC), specific leaf area (SLA), plant height, and Grime's competitor-stress tolerator-ruderal (CSR) strategy scores and the generalized soil fertility, F_G (i.e., the capacity of a soil to produce biomass when all nonsoil variables are held constant) that are generalizable across different species assemblages and geographical areas? We assessed F_G in 21 sites in southern Quebec and 7 sites in southern France using a previously published method based on structural equation modeling. We then determined the CWM values of LDMC, SLA, plant height, and CSR scores in the 21 Quebec sites to obtain quantitative relationships between F_G and these CWM traits. Using these relationships, we independently tested the generality of the trait-fertility relationships using data from French sites. The relationships between F_G and the CWM traits were nonlinear, but displayed the expected qualitative trends as reported in the literature. In particular, the S score and CWM LDMC decreased with increasing soil fertility, and the R score and CWM SLA increased. CWM traits were more strongly correlated to measures of F_G (r² up to 0.48) than to measures of other soil characteristics (r² up to 0.17 for nitrogen flux). Importantly, the independently tested French F_G -trait relationships showed no significant deviations from these quantitative relationships. Further investigation is necessary to confirm if the same trend applies to other regions and or ecosystems.

Functional Traits Are Good Predictors of Tree Species Abundance Across 101 Subtropical Forest Species in China

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

Above- and Belowground Plant Functional Composition Show Similar Changes During Temperate Forest Swamp Succession

Plant functional composition, defined by both community-weighted mean (CWM) traits and functional diversity, can provide insights into plant ecological strategies and community assembly. However, our understanding of plant functional composition during succession is largely based on aboveground traits. Here we investigated community-level traits and functional diversity for six pairs of analogous leaf and fine root traits of understory plants in a temperate forest swamp during succession with a decrease in soil pH and nutrient availability. CWMs of traits related to resource acquisition (including specific leaf area, specific root length, leaf N, leaf P, root N, and root P) decreased with succession, whereas those related to resource conservation (leaf dry matter content, root dry matter content, leaf tissue density, leaf C, and root C) increased along the forest swamp successional gradient. Multi-trait functional dispersion (FDis) of both leaf and fine root traits tended to decrease along the successional gradient, but functional richness and evenness were highest at the middle successional stage. Moreover, FDis of individual plant traits except N showed the same pattern as multi-trait FDis. Soil pH and nutrient availability were the main drivers of successional changes in both CWM traits and FDis. The changes of community-level traits along succession indicated a shift from acquisitive to conservative strategy of understory plants during forest swamp succession. Similar trends in leaf and fine root functional diversity along succession may indicate above- and belowground functional diversity are coordinated during the processes of plant community assembly. These findings of linkages between above- and belowground plant functional composition have important implications for plant community dynamics and assembly rules.

Successional syndromes of saplings in tropical secondary forests emerge from environment-dependent trait-demography relationships

Identifying generalisable processes that underpin population dynamics is crucial for understanding successional patterns. While longitudinal or chronosequence data are powerful tools for doing so, the traditional focus on community-level shifts in taxonomic and functional composition rather than species-level trait-demography relationships has made generalisation difficult. Using joint species distribution models, we demonstrate how three traits-photosynthetic rate, adult stature, and seed mass-moderate recruitment and sapling mortality rates of 46 woody species during secondary succession. We show that the pioneer syndrome emerges from higher photosynthetic rates, shorter adult statures and lighter seeds that facilitate exploitation of light in younger secondary forests, while 'long-lived pioneer' and 'late successional' syndromes are associated with trait values that enable species to persist in the understory or reach the upper canopy in older secondary forests. Our study highlights the context dependency of trait-demography relationships, which drive successional shifts in sapling's species composition in secondary forests.

Colonization process determines species diversity via competitive quasi-exclusion

A colonization model provides a useful basis to investigate a role of interspecific competition in species diversity. The model formulates colonization processes of propagules competing for spatially distinct habitats, which is known to result in stable coexistence of multiple species under various trade-off, for example, competition-colonization and fecundity-mortality trade-offs. Based on this model, we propose a new theory to explain patterns of species abundance, assuming a trade-off between competitive ability and fecundity among species. This model makes testable predictions about species positions in the rank abundance diagram under a discrete species competitiveness. The predictions were tested by three data of animal communities, which supported our model, suggesting the importance of interspecific competition in community structure. Our approach provides a new insight into understanding a mechanism of species diversity.

A Trait-Based Protocol for the Biological Control of Invasive Exotic Plant Species

Selecting appropriate native species for the biological control of invasive exotic plants is a recurring challenge for conservationists, ecologists, and land managers. Recently developed trait-based approaches may be an effective means of overcoming this challenge. However, we lack a protocol and software platform that can be used to quickly and effectively select potential native plant species for performing biological control of the invasive exotic plant species. Here, our study introduces a protocol and a software program that can be used for trait-based selection of appropriate native plant species for performing biocontrol of invasive exotic plant species. In particular, we illustrate the effectiveness of this software program and protocol by identifying native species that can be used for the biological control of Leucaena leucocephala (Lam.) de Wit, a highly invasive plant species found in many parts of the world. Bougainvillea spectabilis was the only native species selected by our software program as a potential biocontrol agent for L. leucocephala. When separately planting 4 seedlings of B. spectabilis and two unselected species (Bombax ceiba, and Ficus microcarpa) as neighbors of each individual of L. leucocephala for 3 years, we found that B. spectabilis, which was functionally similar to the invasive L. leucocephala, significantly limited the invasion of the latter, while the unselected native plant species could not. That was because all the seedling of B. spectabilis survived, while half seedlings of unselected species (B. ceiba and F. microcarpa) died, during the experimental period when planted with L. leucocephala seedlings. Moreover, the growth of L. leucocephala was restricted when planted with B. spectabilis, in contrast B. ceiba and F. microcarpa did not influence the growth of L. leucocephala. Overall, our software program and protocol can quickly and efficiently select native plant species for use in the biological control of invasive exotic plant species. We expect that this work will provide a general protocol to perform biological control of many different types of invasive exotic plant species.

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

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'; π_tlp ), 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 π_tlp were associated with drier habitats, with π_tlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, π_tlp did not predict habitat associations among deciduous species. Across spatial scales, π_tlp 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.