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

A Web-Based Software Platform for Restoration-Oriented Species Selection Based on Plant Functional Traits

Plant functional traits are fundamental to the understanding of plant adaptations and distributions. Recently, scientists proposed a trait-based species selection theory to support the selection of suitable plant species to restore the degraded ecosystems, to prevent the invasive exotic species and to manage the sustainable ecosystems. Based on this theory, in a previous study, we developed a species screening model and successfully applied it to a project where plant species were selected for restoring a tropical coral island. However, during this process we learned that a software platform is necessary to automate the selection process because it can flexible to assist users. Here, we developed a generalized software platform called the “Restoration Plant Species Selection (RPSS) Platform.” This flexible software is designed to assist users in selecting plant species for particular purposes (e.g., restore the degraded ecosystems and others). It is written in R language and integrated with external R packages, including the packages that computing similarity indexes, providing graphic outputs, and offering web functions. The software has a web-based graphical user interface that allows users to execute required functions via checkboxes and buttons. The platform has cross-platform functionality, which means that it can run on all common operating systems (e.g., Windows, Linux, macOS, and others). We also illustrate a successful case study in which the software platform was used to select suitable plant species for restoration purpose. The objective of this paper is to introduce the newly developed software platform RPSS and to provide useful guidances on using it for various applications. At this step, we also realized that the software platform should be constantly updated (e.g., add new features) in the future. Based on the existing successful application and the possible updates, we believe that our RPSS software platform will have broader applications in the future.

Using metacommunity ecology to understand environmental metabolomes

Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics ‘meta-metabolome ecology’ and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.

Despite growing interest in environmental metabolomics, we lack conceptual frameworks for considering how metabolites vary across space and time in ecological systems. Here, the authors apply (species) community assembly concepts to metabolomics data, offering a way forward in understanding the assembly of metabolite assemblages.

Trait coordination and environmental filters shape functional trait distributions of forest understory herbs

Understanding the drivers of trait selection is critical for resolving community assembly processes. Here, we test the importance of environmental filtering and trait covariance for structuring the functional traits of understory herbaceous communities distributed along a natural environmental resource gradient that varied in soil moisture, temperature, and nitrogen availability, produced by different topographic positions in the southern Appalachian Mountains.To uncover potential differences in community-level trait responses to the resource gradient, we quantified the averages and variances of both abundance-weighted and unweighted values for six functional traits (vegetative height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, and leaf δ13C) using 15 individuals of each of the 108 species of understory herbs found at two sites in the southern Appalachians of western North Carolina, USA.Environmental variables were better predictors of weighted than unweighted community-level average trait values for all but height and leaf N, indicating strong environmental filtering of plant abundance. Community-level variance patterns also showed increased convergence of abundance-weighted traits as resource limitation became more severe.Functional trait covariance patterns based on weighted averages were uniform across the gradient, whereas coordination based on unweighted averages was inconsistent and varied with environmental context. In line with these results, structural equation modeling revealed that unweighted community-average traits responded directly to local environmental variation, whereas weighted community-average traits responded indirectly to local environmental variation through trait coordination.Our finding that trait coordination is more important for explaining the distribution of weighted than unweighted average trait values along the gradient indicates that environmental filtering acts on multiple traits simultaneously, with abundant species possessing more favorable combinations of traits for maximizing fitness in a given environment.

Successional Categorization of European Hemi-boreal Forest Tree Species

Developing forest harvesting regimes that mimic natural forest dynamics requires knowledge on typical species behaviors and how they respond to environmental conditions. Species regeneration and survival after disturbance depends on a species' life history traits. Therefore, forest succession determines the extent to which forest communities are able to cope with environmental change. The aim of this review was to (i) review the life history dynamics of hemi-boreal tree species in the context of ecological succession, and (ii) categorize each of these tree species into one of four successional development groups (gap colonizers, gap competitors, forest colonizers, or forest competitors). To do this we embraced the super-organism approach to plant communities using their life history dynamics and traits. Our review touches on the importance and vulnerability of these four types of successional groups, their absence and presence in the community, and how they can be used as a core component to evaluate if the development of the community is progressing towards the restoration of the climatic climax. Applying a theoretical framework to generate ideas, we suggest that forests should be managed to maintain environmental conditions that support the natural variety and sequence of tree species' life histories by promoting genetic invariance and to help secure ecosystem resilience for the future. This could be achieved by employing harvesting methods that emulate natural disturbances and regeneration programs that contribute to maintenance of the four successional groups.

MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions

Macroecology is the study of patterns, and the processes that determine those patterns, in the distribution and abundance of organisms at large scales, whether they be spatial (from hundreds of kilometres to global), temporal (from decades to centuries), and organismal (numbers of species or higher taxa). In the context of invasion ecology, macroecological studies include, for example, analyses of the richness, diversity, distribution, and abundance of alien species in regional floras and faunas, spatio-temporal dynamics of alien species across regions, and cross-taxonomic analyses of species traits among comparable native and alien species pools. However, macroecological studies aiming to explain and predict plant and animal naturalisations and invasions, and the resulting impacts, have, to date, rarely considered the joint effects of species traits, environment, and socioeconomic characteristics. To address this, we present the MAcroecological Framework for Invasive Aliens (MAFIA). The MAFIA explains the invasion phenomenon using three interacting classes of factors – alien species traits, location characteristics, and factors related to introduction events – and explicitly maps these interactions onto the invasion sequence from transport to naturalisation to invasion. The framework therefore helps both to identify how anthropogenic effects interact with species traits and environmental characteristics to determine observed patterns in alien distribution, abundance, and richness; and to clarify why neglecting anthropogenic effects can generate spurious conclusions. Event-related factors include propagule pressure, colonisation pressure, and residence time that are important for mediating the outcome of invasion processes. However, because of context dependence, they can bias analyses, for example those that seek to elucidate the role of alien species traits. In the same vein, failure to recognise and explicitly incorporate interactions among the main factors impedes our understanding of which macroecological invasion patterns are shaped by the environment, and of the importance of interactions between the species and their environment. The MAFIA is based largely on insights from studies of plants and birds, but we believe it can be applied to all taxa, and hope that it will stimulate comparative research on other groups and environments. By making the biases in macroecological analyses of biological invasions explicit, the MAFIA offers an opportunity to guide assessments of the context dependence of invasions at broad geographical scales.

Using functional traits to model annual plant community dynamics

Predicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long-standing problem focus either on the role of the environment, using trait-based filtering approaches, or on quantifying biotic interactions with process-based community dynamics models. We introduce a novel approach that uses functional traits to parameterize a process-based model. By combining the two approaches we make use of the extensive literature on traits and community filtering as a convenient means of reducing the parameterization requirements of a complex population dynamics model whilst retaining the power to capture the processes underlying community assembly. Using arable weed communities as a case study, we demonstrate that this approach results in predictions that show realistic distributions of traits and that trait selection predicted by our simulations is consistent with in-field observations. We demonstrate that trait-based filtering approaches can be combined with process-based models to derive the emergent distribution of traits. While initially developed to predict the impact of crop management on functional shifts in weed communities, our approach has the potential to be applied to other annual plant communities if the generality of relationships between traits and model parameters can be confirmed.

Wetlands rise and fall: Six endangered wetland species showed different patterns of habitat shift under future climate change

Degradation and loss of species' suitable habitats in response to global warming are well documented, which are assumed to be affected by increasing temperature. Conversely, habitat increase of species is little reported and is often considered anomalous and unrelated to climate change. In this study, we first revealed the climate-change-driven habitat shifts of six endangered wetland plants - Bruguiera gymnorrhiza, Carex doniana, Glyptostrobus pensilis, Leersia hexandra, Metasequoia glyptostroboides, and Pedicularis longiflora. The current and future potential habitats of the six species in China were predicted using a maximum entropy model based on thirty-year occurrence records and climate monitoring (from 1960 to 1990). Furthermore, we observed the change of real habitats of the six species based on eight-year field observations (from 2011 to 2019). We found that the six species exhibited three different patterns of habitat shifts including decrease, unstable, and increase. The analysis on the main decisive environmental factors showed that these patterns of habitat shifts are counter to what would be expected global warming but are mostly determined by precipitation-related environmental factors rather than temperature. Collectively, our findings highlight the importance of combining multiple environmental factors including temperature and precipitation for understanding plant responses to climate change.

The Net Effect of Functional Traits on Fitness

Generalizing the effect of traits on performance across species may be achievable if traits explain variation in population fitness. However, testing relationships between traits and vital rates to infer effects on fitness can be misleading. Demographic trade-offs can generate variation in vital rates that yield equal population growth rates, thereby obscuring the net effect of traits on fitness. To address this problem, we describe a diversity of approaches to quantify intrinsic growth rates of plant populations, including experiments beyond range boundaries, density-dependent population models built from long-term demographic data, theoretical models, and methods that leverage widely available monitoring data. Linking plant traits directly to intrinsic growth rates is a fundamental step toward rigorous predictions of population dynamics and community assembly.

Revised SEDD (RSEDD) Model for Sediment Delivery Processes at the Basin Scale

Sediment transport to river channels in a basin is of great significance for a variety of reasons ranging from soil preservation to siltation prevention of reservoirs. Among the commonly used models of sediment transport, the SEdiment Delivery Distributed model (SEDD) uses an exponential function to model the likelihood of eroded soils reaching the rivers and denotes the probability as the Sediment Delivery Ratio of morphological unit i (SDRi). The use of probability to model SDRi in SEDD led us to examine the model and check for its statistical validity. As a result, we found that the SEDD model had several false assertions and needs to be revised to correct for the discrepancies with the statistical properties of the exponential distributions. The results of our study are presented here. We propose an alternative model, the Revised SEDD (RSEDD) model, to better estimate SDRi. We also show how to calibrate the model parameters and examine an example watershed to see if the travel time of sediments follows an exponential distribution. Finally, we reviewed studies citing the SEDD model to explore if they would be impacted by switching to the proposed RSEDD model.

Addressing trait selection patterns in temporary ponds in response to wildfire disturbance and seasonal succession

Mediterranean ecosystems are increasingly threatened by disturbances such as wildfires. These disturbances are expected to shift the selective pressures that determine trait-dependent community assembly. In addition, the stochasticity in species assembly may decrease because of the introduction of strong selection regimes or may increase because of random variation in recruitment. However, these changes in the selection profile and stochasticity in disturbed communities have seldom been evaluated. We examined the relative roles of wildfire disturbance, local conditions and successional dynamics on the assembly of aquatic macroinvertebrate communities. We used the theory of community assembly by trait selection (CATS) to identify traits under selection and to estimate their dependence on wildfire disturbance and environmental gradients. We took advantage of a natural wildfire that partially burned a Mediterranean system of temporary ponds, which were surveyed before and after the wildfire, creating a natural before-after-control-impact design. Before the wildfire, the burned and unburned ponds did not show differences in the selected traits. After the wildfire event, species with larger body sizes and scrapers were favoured in the burned ponds, while collectors and active dispersers were underrepresented. Nonetheless, local environmental conditions and successional dynamics had greater relevance in the selection of traits than the wildfire. This suggests that assembly mechanisms were largely determined by seasonal successional changes regardless of wildfire disturbance. Finally, the relevance of the analysed traits diminished during the hydroperiod, suggesting more stochastic assemblages and/or a replacement in the set of selected traits. Despite the prominent role of seasonal succession over wildfire, this disturbance was associated with a change in the selection strength over specific traits related with feeding strategies and species life histories. Both hydroperiod and wildfire highlighted a strong role of trait-mediated processes (i.e. niche assembly). Therefore, the predicted increase in the frequency and intensity of wildfires is likely to result in community functional shifts. Furthermore, stochasticity was also important for community assembly, particularly from the middle towards the end of the hydroperiod. Our results evidenced the strong relevance of successional changes in trait-mediated assembly mechanisms and its interplay with wildfire disturbance in temporary pond communities.

Organizing principles for vegetation dynamics

Plants and vegetation play a critical-but largely unpredictable-role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change.

Niche-processes induced differences in plant growth, carbon balance, stress resistance, and regeneration affect community assembly over succession

The relationship between plant traits and species relative abundance along environmental gradients can provide important insights on the determinants of community structure. Here we bring extensive data on six key traits (specific leaf area (SLA), seed mass, seed germination rate, height, leaf proline content and photosynthesis rate) to test trait-abundance relationships in a successional chronosequence of subalpine meadow plant communities. Our results show that in late-successional meadows, abundant species had higher values for seed mass, seed germination rate, and SLA, but had lower values for height, photosynthesis rate, and leaf proline content than rarer species. The opposite patterns of trait-abundance relationships were observed for early-successional meadows. Observations of strong trait convergence and divergence in these successional communities lend greater support for niche processes compared to neutral community assembly. We conclude that species' niches that determine plant growth (plant height and photosynthesis rate), carbon balance (SLA, photosynthesis rate), regeneration (seed mass and seed germination rate), and abiotic stress resistance (leaf proline content) under different environmental conditions have strong influence on species relative abundance in these sub-alpine meadow communities during succession.

Trait-environment interactions affect plant establishment success during restoration

Establishment and persistence are central to community assembly and are determined by how traits interact with the environment to determine performance (trait-environment interactions). Community assembly studies have rarely considered such trait-environment interactions, however, which can lead to incorrect inferences about how traits affect assembly. We evaluated how functional traits, environmental conditions, and trait-environment interactions structure plant establishment, as a measure of performance. Within 12 prairie restorations created by sowing 70 species, we quantified environmental conditions and counted individuals of each seeded species to quantify first-year establishment. Three trait-environment interactions structured establishment. Leaf nitrogen interacted with herbivore pressure, as low leaf nitrogen species established relatively better under higher herbivory than species with high leaf nitrogen. Soil moisture interacted with root mass fraction (RMF), with low-RMF species establishing better with low soil moisture and higher-RMF species better on wetter soils. Specific leaf area (SLA) interacted with light availability, as low-SLA species established better under high light conditions and high-SLA species under low light conditions. Our work illustrates how community assembly can be better described by trait-environment interactions than correlating traits or environment with performance. This knowledge can assist species selection to maximize restoration success.

Assessment of congruence between co-occurrence and functional networks: A new framework for revealing community assembly rules

Describing how communities change over space and time is crucial to better understand and predict the functioning of ecosystems. We propose a new methodological framework, based on network theory and modularity concept, to determine which type of mechanisms (i.e. deterministic versus stochastic processes) has the strongest influence on structuring communities. This framework is based on the computation and comparison of two networks: the co-occurrence (based on species abundances) and the functional networks (based on the species traits values). In this way we can assess whether the species belonging to a given functional group also belong to the same co-occurrence group. We adapted the Dg index of Gauzens et al. (2015) to analyze congruence between both networks. This offers the opportunity to identify which assembly rule(s) play(s) the major role in structuring the community. We illustrate our framework with two datasets corresponding to different faunal groups and ecosystems, and characterized by different scales (spatial and temporal scales). By considering both species abundance and multiple functional traits, our framework improves significantly the ability to discriminate the main assembly rules structuring the communities. This point is critical not only to understand community structuring but also its response to global changes and other disturbances.

Stable coexistence of equivalent nutrient competitors through niche differentiation in the light spectrum

Niche-based theories and the neutral theory of biodiversity differ in their predictions of how the species composition of natural communities will respond to changes in nutrient availability. This is an issue of major environmental relevance, as many ecosystems have experienced changes in nitrogen (N) and phosphorus (P) due to anthropogenic manipulation of nutrient loading. To understand how changes in N and P limitation may impact community structure, we conducted laboratory competition experiments using a multispecies phytoplankton community sampled from the North Sea. Results showed that picocyanobacteria (Cyanobium sp.) won the competition under N limitation, while picocyanobacteria and nonmotile nanophytoplankton (Nannochloropsis sp.) coexisted at equal abundances under P limitation. Additional experiments using isolated monocultures confirmed that Cyanobium sp. depleted N to lower levels than Nannochloropsis sp., but that both species had nearly identical P requirements, suggesting a potential for neutral coexistence under P-limited conditions. Pairwise competition experiments with the two isolates seemed to support the consistency of these results, but P limitation resulted in stable species coexistence irrespective of the initial conditions rather than the random drift of species abundances predicted by neutral theory. Comparison of the light absorption spectra indicates that coexistence of the two species was stabilized through differential use of the underwater light spectrum. Our results provide an interesting experimental example of modern coexistence theory, where species were equal competitors in one niche dimension but their competitive traits differed in other niche dimensions, thus enabling stable species coexistence on a single limiting nutrient through niche differentiation in the light spectrum.

A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales

Despite their differences, biological systems at different spatial scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are often hard to grasp due to the highly specialized nature of modern science and the parcelled terminology employed by various scientific sub-disciplines. To explore these common organizational features, this paper provides a comparative study of diverse applications of the maximum entropy principle, which has found many uses at different biological spatial scales ranging from amino acids up to societies. By presenting these studies under a common approach and language, this paper aims to establish a unified view over these seemingly highly heterogeneous scenarios.

Community phylogenetic structure reveals the imprint of dispersal-related dynamics and environmental filtering by nutrient availability in freshwater diatoms

Despite important progress, uncertainty persists regarding the ecological forces driving microbial community assembly. Here, we present the first study to use phylogenetic information to interpret the structure and diversity of diatom communities. We examined local phylogenetic divergence and beta- phylogenetic diversity in a large dataset of 595 freshwater benthic diatom communities and we investigated how this diversity is influenced by gradients in nutrients, pH, organic matter and catchment size. Overall, we found that diatom communities were phylogenetically clustered, i.e. species within communities were more closely related than expected by chance. Phylogenetic clustering was stronger in nutrient-poor environments and in sites with a small catchment area. The variation of the phylogenetic beta-diversity index was much better explained by space and environment than the variation of the taxonomic index was. Both approaches detected a significant effect of environment and space on diatom community turnover. Our results support the view that diatom communities are primarily shaped by environmental filtering, in particular by nutrient availability. Moreover, they highlight the importance of considering dispersal-related processes and the depth of phylogenetic signal in functional traits when interpreting patterns of diversity.

Is there coordination of leaf and fine root traits at local scales? A test in temperate forest swamps

Examining the coordination of leaf and fine root traits not only aids a better understanding of plant ecological strategies from a whole-plant perspective, but also helps improve the prediction of belowground properties from aboveground traits. The relationships between leaf and fine root traits have been extensively explored at global and regional scales, but remain unclear at local scales. Here, we measured six pairs of analogous leaf and fine root traits related to resource economy and organ size for coexisting dominant and subordinate vascular plants at three successional stages of temperate forest swamps in Lingfeng National Nature Reserve in the Greater Hinggan Mountains, NE China. Leaf and fine root traits related to resource acquisition (e.g., specific leaf area [SLA], leaf N, leaf P, root water content, and root P) decreased with succession. Overall, we found strong linear relationships between leaf dry matter content (LDMC) and root water content, and between leaf and root C, N, and P concentrations, but only weak correlations were observed between leaf area and root diameter, and between SLA and specific root length (SRL). The strong relationships between LDMC and root water content and between leaf and root C, N, and P held at the early and late stages, but disappeared at the middle stage. Besides, C and P of leaves were significantly correlated with those of roots for woody plants, while strong linkages existed between LDMC and root water content and between leaf N and root N for herbaceous species. These results provided evidence for the existence of strong coordination between leaf and root traits at the local scale. Meanwhile, the leaf-root trait relationships could be modulated by successional stage and growth form, indicating the complexity of coordination of aboveground and belowground traits at the local scale.

Intraspecific variation in traits and tree growth along an elevational gradient in a subtropical forest

A conspicuous feature of natural communities is that individuals within species exhibit broad variation in their phenotype. While the phenotypic differences among species are prominent and have received considerable attention in earlier studies, recent findings suggest that about 40% of the trait variation is found within species. How this intraspecific variation is related to underlying environmental gradients and ultimately linked to performance is an outstanding question in ecology and evolution. Here, we study six broadly distributed species across an elevational gradient in a subtropical forest. We focused on five functional traits reflecting plant functional differentiation in stem transport, leaf architecture, and leaf resource acquisition. We found that leaf thickness, leaf toughness, and specific leaf area generally varied with elevation, while wood density and leaf area exhibited constrained variation. Results on multivariate trait axes also showed mixed evidence with the PC1 values (positively related to leaf toughness and negatively related to specific leaf area) shifting with elevation, while PC2 values (negatively related to wood density) did not change with elevation. We also found that, despite the important variation in some traits along the gradient, growth performance did not follow this same trend. This suggests that strong directional changes in traits along the gradient may result in similar levels of demographic performance. The results, therefore, challenge the simple expectation that a trait will correlate with a demographic rate. More nuanced approaches and additional mechanisms must be considered to advance understanding of the performance-trait relationships.

Derivations of the Core Functions of the Maximum Entropy Theory of Ecology

The Maximum Entropy Theory of Ecology (METE), is a theoretical framework of macroecology that makes a variety of realistic ecological predictions about how species richness, abundance of species, metabolic rate distributions, and spatial aggregation of species interrelate in a given region. In the METE framework, "ecological state variables" (representing total area, total species richness, total abundance, and total metabolic energy) describe macroecological properties of an ecosystem. METE incorporates these state variables into constraints on underlying probability distributions. The method of Lagrange multipliers and maximization of information entropy (MaxEnt) lead to predicted functional forms of distributions of interest. We demonstrate how information entropy is maximized for the general case of a distribution, which has empirical information that provides constraints on the overall predictions. We then show how METE's two core functions are derived. These functions, called the "Spatial Structure Function" and the "Ecosystem Structure Function" are the core pieces of the theory, from which all the predictions of METE follow (including the Species Area Relationship, the Species Abundance Distribution, and various metabolic distributions). Primarily, we consider the discrete distributions predicted by METE. We also explore the parameter space defined by the METE's state variables and Lagrange multipliers. We aim to provide a comprehensive resource for ecologists who want to understand the derivations and assumptions of the basic mathematical structure of METE.

Trait-based life-history strategies explain succession scenario for complex bacterial communities under varying disturbance

Trait-based approaches are increasingly gaining importance in community ecology, as a way of finding general rules for the mechanisms driving changes in community structure and function under the influence of perturbations. Frameworks for life-history strategies have been successfully applied to describe changes in plant and animal communities upon disturbance. To evaluate their applicability to complex bacterial communities, we operated replicated wastewater treatment bioreactors for 35 days and subjected them to eight different disturbance frequencies of a toxic pollutant (3-chloroaniline), starting with a mixed inoculum from a full-scale treatment plant. Relevant ecosystem functions were tracked and microbial communities assessed through metagenomics and 16S rRNA gene sequencing. Combining a series of ordination, statistical and network analysis methods, we associated different life-history strategies with microbial communities across the disturbance range. These strategies were evaluated using tradeoffs in community function and genotypic potential, and changes in bacterial genus composition. We further compared our findings with other ecological studies and adopted a semi-quantitative competitors, stress-tolerants, ruderals (CSR) classification. The framework reduces complex data sets of microbial traits, functions and taxa into ecologically meaningful components to help understand the system response to disturbance and hence represents a promising tool for managing microbial communities.

Effects of livestock grazing on soil, plant functional diversity, and ecological traits vary between regions with different climates in northeastern Iran

Understanding the responses of vegetation characteristics and soil properties to grazing in different precipitation regimes is useful for the management of rangelands, especially in the arid regions. In northeastern Iran, we studied the responses of vegetation to livestock grazing in three regions with different climates: arid, semiarid, and subhumid. In each region, we selected 6-7 pairwise sampling areas of high versus low grazing intensity and six traits of the present species were recorded on 1 m2 plots-five grazed and five ungrazed in each area. The overall fertility was compared using the dissimilarity analysis, and linear mixed-effect models were used to compare the individual fertility parameters, functional diversity indices, and species traits between the plots with high and low grazing intensity and between the climatic regions. Both climate and grazing, as well as their interaction, affected fertility parameters, functional diversity indices, and the representation of species traits. Grazing reduced functional evenness, height of the community, the representation of annuals, but increased the community leaf area. In the subhumid region, grazing also reduced functional richness. Further, grazing decreased the share of annual species in the semiarid region and seed mass in the arid region. Larger leaf area and seed mass, smaller height and lower share of annuals were associated with intensive grazing. Species with large LA and seed mass, lower height and perennials can be therefore presumed to tolerate trampling and benefit from high nutrient levels, associated with intensive grazing. By providing a detailed view on the impacts of overgrazing, this study highlights the importance of protection from grazing as an effective management tool for maintaining the pastoral ecosystems. In general, the composition of plant traits across the pastures of northeastern Iran was more affected by intensive grazing than by the differences in climate.

Thermoregulatory traits combine with range shifts to alter the future of montane ant assemblages

Predicting and understanding the biological response to future climate change is a pressing challenge for humanity. In the 21st century, many species will move into higher latitudes and higher elevations as the climate warms. In addition, the relative abundances of species within local assemblages are likely to change. Both effects have implications for how ecosystems function. Few biodiversity forecasts, however, take account of both shifting ranges and changing abundances. We provide a novel analysis predicting the potential changes to assemblage-level relative abundances in the 21st century. We use an established relationship linking ant abundance and their colour and size traits to temperature and UV-B to predict future abundance changes. We also predict future temperature driven range shifts and use these to alter the available species pool for our trait-mediated abundance predictions. We do this across three continents under a low greenhouse gas emissions scenario (RCP2.6) and a business-as-usual scenario (RCP8.5). Under RCP2.6, predicted changes to ant assemblages by 2100 are moderate. On average, species richness will increase by 26%, while species composition and relative abundance structure will be 26% and 30% different, respectively, compared with modern assemblages. Under RCP8.5, however, highland assemblages face almost a tripling of species richness and compositional and relative abundance changes of 66% and 77%. Critically, we predict that future assemblages could be reorganized in terms of which species are common and which are rare: future highland assemblages will not simply comprise upslope shifts of modern lowland assemblages. These forecasts reveal the potential for radical change to montane ant assemblages by the end of the 21st century if temperature increases continue. Our results highlight the importance of incorporating trait-environment relationships into future biodiversity predictions. Looking forward, the major challenge is to understand how ecosystem processes will respond to compositional and relative abundance changes.

Trait-based ecology of terrestrial arthropods

In focusing on how organisms' generalizable functional properties (traits) interact mechanistically with environments across spatial scales and levels of biological organization, trait-based approaches provide a powerful framework for attaining synthesis, generality and prediction. Trait-based research has considerably improved understanding of the assembly, structure and functioning of plant communities. Further advances in ecology may be achieved by exploring the trait-environment relationships of non-sessile, heterotrophic organisms such as terrestrial arthropods, which are geographically ubiquitous, ecologically diverse, and often important functional components of ecosystems. Trait-based studies and trait databases have recently been compiled for groups such as ants, bees, beetles, butterflies, spiders and many others; however, the explicit justification, conceptual framework, and primary-evidence base for the burgeoning field of 'terrestrial arthropod trait-based ecology' have not been well established. Consequently, there is some confusion over the scope and relevance of this field, as well as a tendency for studies to overlook important assumptions of the trait-based approach. Here we aim to provide a broad and accessible overview of the trait-based ecology of terrestrial arthropods. We first define and illustrate foundational concepts in trait-based ecology with respect to terrestrial arthropods, and justify the application of trait-based approaches to the study of their ecology. Next, we review studies in community ecology where trait-based approaches have been used to elucidate how assembly processes for terrestrial arthropod communities are influenced by niche filtering along environmental gradients (e.g. climatic, structural, and land-use gradients) and by abiotic and biotic disturbances (e.g. fire, floods, and biological invasions). We also review studies in ecosystem ecology where trait-based approaches have been used to investigate biodiversity-ecosystem function relationships: how the functional diversity of arthropod communities relates to a host of ecosystem functions and services that they mediate, such as decomposition, pollination and predation. We then suggest how future work can address fundamental assumptions and limitations by investigating trait functionality and the effects of intraspecific variation, assessing the potential for sampling methods to bias the traits and trait values observed, and enhancing the quality and consolidation of trait information in databases. A roadmap to guide observational trait-based studies is also presented. Lastly, we highlight new areas where trait-based studies on terrestrial arthropods are well positioned to advance ecological understanding and application. These include examining the roles of competitive, non-competitive and (multi-)trophic interactions in shaping coexistence, and macro-scaling trait-environment relationships to explain and predict patterns in biodiversity and ecosystem functions across space and time. We hope this review will spur and guide future applications of the trait-based framework to advance ecological insights from the most diverse eukaryotic organisms on Earth.

Leaf nutrients, not specific leaf area, are consistent indicators of elevated nutrient inputs

Leaf traits are frequently measured in ecology to provide a 'common currency' for predicting how anthropogenic pressures impact ecosystem function. Here, we test whether leaf traits consistently respond to experimental treatments across 27 globally distributed grassland sites across 4 continents. We find that specific leaf area (leaf area per unit mass)-a commonly measured morphological trait inferring shifts between plant growth strategies-did not respond to up to four years of soil nutrient additions. Leaf nitrogen, phosphorus and potassium concentrations increased in response to the addition of each respective soil nutrient. We found few significant changes in leaf traits when vertebrate herbivores were excluded in the short-term. Leaf nitrogen and potassium concentrations were positively correlated with species turnover, suggesting that interspecific trait variation was a significant predictor of leaf nitrogen and potassium, but not of leaf phosphorus concentration. Climatic conditions and pretreatment soil nutrient levels also accounted for significant amounts of variation in the leaf traits measured. Overall, we find that leaf morphological traits, such as specific leaf area, are not appropriate indicators of plant response to anthropogenic perturbations in grasslands.

Univariate Community Assembly Analysis (UniCAA): Combining hierarchical models with null models to test the influence of spatially restricted dispersal, environmental filtering, and stochasticity on community assembly

Identifying the influence of stochastic processes and of deterministic processes, such as dispersal of individuals of different species and trait-based environmental filtering, has long been a challenge in studies of community assembly. Here, we present the Univariate Community Assembly Analysis (UniCAA) and test its ability to address three hypotheses: species occurrences within communities are (a) limited by spatially restricted dispersal; (b) environmentally filtered; or (c) the outcome of stochasticity-so that as community size decreases-species that are common outside a local community have a disproportionately higher probability of occurrence than rare species. The comparison with a null model allows assessing if the influence of each of the three processes differs from what one would expect under a purely stochastic distribution of species. We tested the framework by simulating "empirical" metacommunities under 15 scenarios that differed with respect to the strengths of spatially restricted dispersal (restricted vs. not restricted); habitat isolation (low, intermediate, and high immigration rates); and environmental filtering (strong, intermediate, and no filtering). Through these tests, we found that UniCAA rarely produced false positives for the influence of the three processes, yielding a type-I error rate ≤5%. The type-II error rate, that is, production of false negatives, was also acceptable and within the typical cutoff (20%). We demonstrate that the UniCAA provides a flexible framework for retrieving the processes behind community assembly and propose avenues for future developments of the framework.

Understanding the recruitment response of juvenile Neotropical trees to logging intensity using functional traits

Selective logging remains a widespread practice in tropical forests, yet the long-term effects of timber harvest on juvenile tree (i.e., sapling) recruitment across the hundreds of species occurring in most tropical forests remain difficult to predict. This uncertainty could potentially exacerbate threats to some of the thousands of timber-valuable tree species in the Amazon. Our objective was to determine to what extent long-term responses of tree species regeneration in logged forests can be explained by their functional traits. We integrate functional trait data for 13 leaf, stem, and seed traits from 25 canopy tree species with a range of life histories, such as the pioneer Goupia glabra and the shade-tolerant Iryanthera hostmannii, together with over 30 yr of sapling monitoring in permanent plots spanning a gradient of harvest intensity at the Paracou Forest Disturbance Experiment (PFDE), French Guiana. We anticipated that more intensive logging would increase recruitment of pioneer species with higher specific leaf area, lower wood densities, and smaller seeds, due to the removal of canopy trees. We define a recruitment response metric to compare sapling regeneration to timber harvest intensity across species. Although not statistically significant, sapling recruitment decreased with logging intensity for eight of 23 species and these species tended to have large seeds and dense wood. A generalized linear mixed model fit using specific leaf area, seed mass, and twig density data explained about 45% of the variability in sapling dynamics. Effects of specific leaf area outweighed those of seed mass and wood density in explaining recruitment dynamics of the sapling community in response to increasing logging intensity. The most intense treatment at the PFDE, which includes stand thinning of non-timber-valuable adult trees and poison-girdling for competitive release, showed evidence of shifting community composition in sapling regeneration at the 30-yr mark, toward species with less dense wood, lighter seeds, and higher specific leaf area. Our results indicate that high-intensity logging can have lasting effects on stand regeneration dynamics and that functional traits can help simplify general trends of sapling recruitment for highly diverse logged tropical forests.

An experimental test of the Community Assembly by Trait Selection (CATS) model

The Community Assembly by Trait Selection (CATS) model of community assembly predicts species abundances along environmental gradients in relatively undisturbed vegetation. Here we ask whether this model, when calibrated with data from natural plant communities, can predict the abundances of five dominant grass species (Bouteloua gracilis, Elymus elymoides, Festuca arizonica, Muhlenbergia montana, and Poa fendleriana) in a greenhouse experiment that manipulated light and soil properties. To address this question, we used generalized additive models (GAMs) to model community-weighted mean (CWM) seed mass, mean Julian flowering date, and specific root length (SRL) as non-linear functions of two environmental variables (soil pH and pine basal area) in natural vegetation. The model-fitted CWM traits were then used as constraints in the CATS model to predict the relative abundance of the five grass species that were seeded in a mixture at equal densities into a 2×2 factorial experiment with soil parent material and light level as crossed factors. Light was the most important factor influencing seedling community composition, especially the abundances of Bouteloua gracilis and Poa fendleriana. The model-predicted relative abundances were significantly correlated with the observed relative abundances, and the model accurately predicted the dominant species in every treatment. P. fendleriana was correctly predicted to be the most abundant species in both shade treatments and the sun-basalt treatment, and B. gracilis was correctly predicted to be the most abundant species in the sun-limestone treatment. Our results provide experimental evidence that environmental filtering of the species pool occurs in the early stages of community assembly (including germination, emergence, and early growth), and that trait-based models calibrated with data from natural plant communities can be used to predict the outcome of the early stages of community assembly under experimental conditions.

Late Quaternary climate legacies in contemporary plant functional composition

The functional composition of plant communities is commonly thought to be determined by contemporary climate. However, if rates of climate-driven immigration and/or exclusion of species are slow, then contemporary functional composition may be explained by paleoclimate as well as by contemporary climate. We tested this idea by coupling contemporary maps of plant functional trait composition across North and South America to paleoclimate means and temporal variation in temperature and precipitation from the Last Interglacial (120 ka) to the present. Paleoclimate predictors strongly improved prediction of contemporary functional composition compared to contemporary climate predictors, with a stronger influence of temperature in North America (especially during periods of ice melting) and of precipitation in South America (across all times). Thus, climate from tens of thousands of years ago influences contemporary functional composition via slow assemblage dynamics.

Shifts in functional trait-species abundance relationships over secondary subalpine meadow succession in the Qinghai-Tibetan Plateau

Although trait-based processes of community assembly during secondary succession invokes multiple factors that ultimately determine the presence or absence of a species, little is known regarding the impacts of functional traits on species abundance in successional plant communities. Here in species-rich subalpine secondary successional meadows of the Qinghai-Tibetan Plateau, we measured photosynthesis rate and leaf proline content that are related to plant growth and abiotic stress resistance, respectively, and seed germination rate that is closely correlated with plant germination strategy to test their influence on species abundance during succession. We used a linear mixed effects model framework to examine the shifts in trait-abundance relationships and the correlations among these three traits in successional communities. We observed significant shifts in trait-abundance relationships during succession, e.g., abundant species in early-successional meadows exhibited relatively high photosynthesis rates and leaf proline content, but showed low seed germination rates, whereas the converse were true in late successional communities. However, the correlations among the three traits were insignificant in most meadow communities. Our results show that functional traits associated with plant growth, stress resistance, and reproduction impose strong influence on species abundance during secondary subalpine meadow succession in the Qinghai-Tibetan Plateau.

Biodiversity monitoring, earth observations and the ecology of scale

Human activity and land-use change are dramatically altering the sizes, geographical distributions and functioning of biological populations worldwide, with tremendous consequences for human well-being. Yet our ability to measure, monitor and forecast biodiversity change - crucial to addressing it - remains limited. Biodiversity monitoring systems are being developed to improve this capacity by deriving metrics of change from an array of in situ data (e.g. field plots or species occurrence records) and Earth observations (EO; e.g. satellite or airborne imagery). However, there are few ecologically based frameworks for integrating these data into meaningful metrics of biodiversity change. Here, I describe how concepts of pattern and scale in ecology could be used to design such a framework. I review three core topics: the role of scale in measuring and modelling biodiversity patterns with EO, scale-dependent challenges linking in situ and EO data and opportunities to apply concepts of pattern and scale to EO to improve biodiversity mapping. From this analysis emerges an actionable approach for measuring, monitoring and forecasting biodiversity change, highlighting key opportunities to establish EO as the backbone of global-scale, science-driven conservation.

Functional traits associated with plant colonizing and competitive ability influence species abundance during secondary succession: Evidence from subalpine meadows of the Qinghai-Tibetan Plateau

It is widely recognized that colonists and competitors dominate early and late succession, respectively, with selected species having different colonizing and competitive abilities. However, it remains unknown whether colonizing and competitive ability can determine species abundance directly over succession. The data for five key functional traits were collected (photosynthesis rate, leaf turgor loss point, leaf proline content, seed mass, and seed germination rate), which are direct indicators of plant competitive and colonizing abilities including growth, drought and cold stress resistance, dispersal, and seed dormancy. Here, we tested the effects of colonizing and competitive abilities on species abundance, by employing a linear mixed-effects model to examine the shifts in the relationship between species abundance and these five colonization and competition-related traits in species-rich subalpine secondary successional meadows (at 4, 6, 10, 13 years of age, and undisturbed, respectively) of the Qinghai-Tibetan Plateau. The abundant species at the early-successional meadows tend to have high photosynthetic rate, high leaf proline content, low seed mass, and seed germination rate for having high colonizing ability, but low competitive ability. By contrast, late-successional communities tend to be dominated by species with high competitive ability, but low colonizing ability, indicated by large seeds, high seed germination rate, low photosynthetic rate, and leaf proline content. The observed directional shifts in the relationships between traits (photosynthetic rate, leaf proline content, seed mass, and seed germination rate) and abundance with successional age, bring two new understandings of community assembly during succession of subalpine meadows in the Qinghai-Tibetan Plateau. First, it discloses that the differences in species abundance over succession can be directly attributed to differences in colonizing and competitive abilities of different species. Second, it expands the effects of multiple life historical differences including growth, resource competitive ability, cold stress resistance, dispersal, and seed germination strategy, represented by functional traits on community assembly along succession, that is, from the species to the community level.

Using co-occurrence information and trait composition to understand individual plant performance in grassland communities

Depending on the strength of environmental filtering and competitive exclusion, successful colonizers of plant communities show varying degrees of similarity to resident species with respect to functional traits. For the present study, colonizer's performance was assessed in relation to the degree of fit with the resident community, and in addition, in relation to the community's trait profile and the environmental factors at the study locations. The two-year field experiment investigated the relative growth rates of 130 species that had been transplanted into German grassland communities varying in intensities of land-use. The transplanted species were selected in accordance with the following scenarios: species with highly similar or dissimilar traits to residents, species with highest degree of co-occurrence with resident species and species chosen randomly from the local species pool. The performance of transplanted phytometers depended on the scenario according to which the species were selected, on community trait diversity, and in addition, often on the interaction of both and on land use intensity. The total amount of explained variance in performance was low, but increased considerably when species identity was taken into account. In general, individuals in the co-occurrence scenario performed better than those selected based on trait information or those selected randomly. Different predictors were important in different seasons, demonstrating a limited temporal validity of performance models.

Delivering the promises of trait-based approaches to the needs of demographic approaches, and vice versa

Few facets of biology vary more than functional traits and life-history traits. To explore this vast variation, functional ecologists and population ecologists have developed independent approaches that identify the mechanisms behind and consequences of trait variation.Collaborative research between researchers using trait-based and demographic approaches remains scarce. We argue that this is a missed opportunity, as the strengths of both approaches could help boost the research agendas of functional ecology and population ecology.This special feature, which spans three journals of the British Ecological Society due to its interdisciplinary nature, showcases state-of-the-art research applying trait-based and demographic approaches to examine relationships between organismal function, life history strategies and population performance across multiple kingdoms. Examples include the exploration of how functional trait × environment interactions affect vital rates and thus explain population trends and species occurrence; the coordination of seed traits and dispersal ability with the pace of life in plants; the incorporation of functional traits in dynamic energy budget models; or the discovery of linkages between microbial functional traits and the fast-slow continuum.Despite their historical isolation, collaborative work between functional ecologists and population ecologists could unlock novel research pathways. We call for an integrative research agenda to evaluate which and when traits are functional, as well as their ability to describe and predict life history strategies and population dynamics. We highlight promising, complementary research avenues to overcome current limitations. These include a more explicit linkage of selection gradients in the context of functional trait-vital rate relationships, and the implementation of standardised protocols to track changes in traits and vital rates over time at the same location and individuals, thus allowing for the explicit incorporation of trade-offs in analyses of covariation of functional traits and life-history traits.

An introduction to the maximum entropy approach and its application to inference problems in biology

A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different contexts hinge upon its conceptual simplicity and mathematical soundness. Here we try to concisely review the basic elements of the maximum entropy principle, starting from the notion of 'entropy', and describe its usefulness for the analysis of biological systems. As examples, we focus specifically on the problem of reconstructing gene interaction networks from expression data and on recent work attempting to expand our system-level understanding of bacterial metabolism. Finally, we highlight some extensions and potential limitations of the maximum entropy approach, and point to more recent developments that are likely to play a key role in the upcoming challenges of extracting structures and information from increasingly rich, high-throughput biological data.

Characterizing the contribution of plasticity and genetic differentiation to community-level trait responses to environmental change

The match between functional trait variation in communities and environmental gradients is maintained by three processes: phenotypic plasticity and genetic differentiation (intraspecific processes), and species turnover (interspecific). Recently, evidence has emerged suggesting that intraspecific variation might have a potentially large role in driving functional community composition and response to environmental change. However, empirical evidence quantifying the respective importance of phenotypic plasticity and genetic differentiation relative to species turnover is still lacking. We performed a reciprocal transplant experiment using a common herbaceous plant species (Oxalis montana) among low‐, mid‐, and high‐elevation sites to first quantify the contributions of plasticity and genetic differentiation in driving intraspecific variation in three traits: height, specific leaf area, and leaf area. We next compared the contributions of these intraspecific drivers of community trait–environment matching to that of species turnover, which had been previously assessed along the same elevational gradient. Plasticity was the dominant driver of intraspecific trait variation across elevation in all traits, with only a small contribution of genetic differentiation among populations. Local adaptation was not detected to a major extent along the gradient. Fitness components were greatest in O. montana plants with trait values closest to the local community‐weighted means, thus supporting the common assumption that community‐weighted mean trait values represent selective optima. Our results suggest that community‐level trait responses to ongoing climate change should be mostly mediated by species turnover, even at the small spatial scale of our study, with an especially small contribution of evolutionary adaptation within species.