生态系统性状对宏生态研究的启示与挑战

功能性状在器官-物种-种群-群落-生态系统水平都具有其特定的适应或功能优化的意义,但目前对功能性状的测定和研究大都局限于器官或物种水平。然而,当前高速发展的宏生态新研究技术和方法(如遥感观测、通量观测、模型模拟)的研究对象都是在生态系统或区域尺度上,如何将传统功能性状与其相连结并服务于生态环境问题和全球变化问题是科学界的一大难题。为了解决传统性状与宏生态研究"尺度不统一"和"量纲不统一"的难题,研究人员最新发展了"生态系统性状(Ecosystem traits, ESTs)"概念体系,并从"理念-数据源-推导方法-应用"等多角度为后续研究提供了可借鉴案例。生态系统性状将传统性状研究从器官水平拓展到了群落和生态系统水平,以单位土地面积为基础构建了传统性状与宏生态研究(或地学研究)的桥梁,开启了性状研究从"器官到群落"、从"经典理论验证到宏观应用"的美好愿景,为多学科交叉提供了新思路。然而,它在方法学和数据源等方面还存在诸多问题与挑战;在此,我们呼吁相关专家从研究方法、概念体系和应用实践上赋予"生态系统性状"更强大的生命力,尤其从动物群落性状和微生物群落性状等角度。本文在深入解读先前生态性状概念体系、理论意义和潜在挑战的基础上,结合最新进展进行了补充,希望通过广泛讨论,完善生态系统性状概念体系,逐步形成"以性状为基础的生态系统生态学"新研究框架,切实推动宏生态研究和区域生态环境问题的解决。     

植物性状研究的机遇与挑战:从器官到群落

植物性状(Plant trait)或植物功能性状(Plant functional trait)通常是指植物对外界环境长期适应与进化后所表现出的可量度、且与生产力优化或环境适应等密切相关的属性。近几十年来,植物性状研究在性状-生产力、性状-养分、性状间相互关系、性状-群落结构维持等方面取得了卓越成就。然而,由于大多数性状调查都是以植物群落内优势种或亚优势种为对象,使其在探讨群落尺度的性状-功能关系、性状数据如何用于改进或优化模型、性状数据如何与遥感连接等问题时,存在空间尺度和量纲不匹配的极大挑战。为了破解上述难题,亟需发展新的、基于单位土地面积的群落性状(Community trait)概念体系、数据源和计算方法等,推动植物性状数据与快速发展的宏观生态学新技术(遥感、模型和通量观测等)相结合,既拓展了植物性状研究范畴,又可推动其更好地服务于区域生态环境问题的解决。所定义的群落性状(如叶片氮含量、磷含量、比叶面积、气孔密度、叶绿素含量等),是在充分考虑群落内所有物种的性状实测数据,再结合比叶面积、生物量异速生长方程和群落结构数据等,推导而成的基于单位土地面积的群落性状。受测试方法的影响,传统的直接算术平均法或相对生物量加权平均法所获得的群落水平的植物性状(如叶片氮含量g/kg或%),虽然可以有效地探讨群落结构维持机制,由于无法实现对群落性状在量纲上向单位土地面积转换,使它很难与模型和遥感数据相匹配。基于单位土地面积的群落性状,可在空间尺度匹配(或量纲匹配)的前提下实现个体水平测定的植物性状数据与生态模型和遥感观测相联系,更好地探讨区域尺度下自然生态系统结构和功能的关系及其对全球变化的响应与适应。同时,它也可更好地建立群落水平的性状-功能的定量关系(非物种水平),为更好地探讨自然群落结构维持机制和生产力优化机制提供了新思路。     

Discriminating trait‐convergence and trait‐divergence assembly patterns in ecological community gradients

Question: Whereas similar ecological requirements lead to trait‐convergence assembly patterns (TCAP) of species in communities, the interactions controlling how species associate produce trait‐divergence assembly patterns (TDAP). Yet, the linking of the latter to community processes has so far only been suggested. We offer a method to elucidate TCAP and TDAP in ecological community gradients that will help fill this gap. Method: We evaluated the correlation between trait‐based described communities and ecological gradients, and using partial correlation, we separated the fractions reflecting TCAP and TDAP. The required input data matrices describe operational taxonomic units (OTUs) by traits, communities by the quantities or presence‐absence of these OTUs, and community sites by ecological variables. We defined plant functional types (PFTs) or species as community components after fuzzy weighting by the traits. The measured correlations for TCAP and TDAP were tested by permutation. The null model for TDAP preserves the trait convergence, the structure intrinsic in the fuzzy types, and community total abundances and autocorrelation. Results: We applied the method to trait‐based data from plant communities in south Brazil, one set in natural grassland experimental plots under different nitrogen and grazing levels, and another in sapling communities colonizing Araucaria forest patches of increasing size in a forest‐grassland mosaic. In these cases, depending on the traits considered, we found strong evidence of either TCAP or TDAP, or both, that was related to the environmental gradients. Conclusions: The method developed is able to reveal TCAP and TDAP that are more likely to be functional for specified ecological gradients, allowing establishment of objective hypotheses on their links to community processes.     

The influence of fire on phylogenetic and functional structure of woody savannas: Moving from species to individuals

Fire is a key determinant of tropical savanna structure and functioning. High fire frequencies are expected to assemble closely related species with a restricted range of functional trait values. Here we determined the effect of fire on phylogenetic and functional diversity of woody species and individuals in savanna communities under different fire frequencies. We found phylogenetic signals for one third of the functional traits studied. High numbers of fires simultaneously led to phylogenetic overdispersion and functional clustering when communities were represented by mean trait values with all traits that putatively should be affected or respond to fire. This finding is important, because it shows that the relationship between ecological processes and the phylogenetic structure of communities is not straightforward. Thus, we cannot always assume that close relatives are more similar in their ecological features. However, when considering a different set of traits representing different plant strategies (fire resistance/avoidance, physiological traits and regeneration traits), the results were not always congruent. When asking how communities are assembled in terms of individuals (not species) the outcome was different from the species-based approach, suggesting that the realised trait values – rather than mean species trait values – have an important role in driving community assembly. Thus, intraspecific trait variability should be taken into account if we want fully to improve our mechanistic understanding of assembly rules in plant communities.     

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete‐case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete‐case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.     

CWM and Rao’s quadratic diversity: a unified framework for functional ecology

Assessing the effects of environmental constraints on community structure often relies on methods that consider changes in species functional traits in response to environmental processes. Various indices have been proposed to measure relevant aspects of community trait composition from different viewpoints and perspectives. Among these, the ‘community-weighted mean trait value’ (CWM) and the Rao coefficient have been widely used in ecological research for summarizing different facets of functional composition and diversity. Analyzing changes in functional diversity of bee communities along a post-fire successional gradient in southern Switzerland we show that these two measures may be used to describe two complementary aspects of community structure, such as the mean and the dispersion of functional traits within a given species assemblage. While CWM can be adequately used to summarize shifts in mean trait values within communities due to environmental selection for certain functional traits, the Rao coefficient can be effectively applied to analyze patterns of trait convergence or divergence compared to a random expectation.     

Community functional trait composition at the continental scale: the effects of non‐ecological processes

Ecological communities and their response to environmental gradients are increasingly being described by measures of trait composition at the community level – the trait‐based approach. Whether ecological or non‐ecological processes influence trait composition between communities has been debated. Understanding the processes that influence trait composition is important for reconstructing paleoenvironmental conditions from fossil deposits and for understanding changes in community functionality through time. Here, we assess the influence of ecological and non‐ecological processes on the distribution of traits within North American mammals. We found that non‐ecological processes including historical contingency, spatial autocorrelation, and evolutionary history do not influence trait composition; however, the variance in trait composition is highly explained by climate gradients. Our results suggest that habitat breadth, terrestriality, diet breadth, and reproductive traits are strong candidates as proxies for measuring functional aspects of environments in the past and present.     

A conceptual framework for the spatial analysis of functional trait diversity

Functional trait diversity is a popular tool in modern ecology, mainly used to infer assembly processes and ecosystem functioning. Patterns of functional trait diversity are shaped by ecological processes such as environmental filtering, species interactions and dispersal that are inherently spatial, and different processes may operate at different spatial scales. Adding a spatial dimension to the analysis of functional trait diversity may thus increase our ability to infer community assembly processes and to predict change in assembly processes following disturbance or land‐use change. Richness, evenness and divergence of functional traits are commonly used indices of functional trait diversity that are known to respond differently to large‐scale filters related to environmental heterogeneity and dispersal and fine‐scale filters related to species interactions (competition). Recent developments in spatial statistics make it possible to separately quantify large‐scale patterns (variation in local means) and fine‐scale patterns (variation around local means) by decomposing overall spatial autocorrelation quantified by Moran's coefficient into its positive and negative components using Moran eigenvector maps (MEM). We thus propose to identify the spatial signature of multiple ecological processes that are potentially acting at different spatial scales by contrasting positive and negative components of spatial autocorrelation for each of the three indices of functional trait diversity. We illustrate this approach with a case study from riparian plant communities, where we test the effects of disturbance on spatial patterns of functional trait diversity. The fine‐scale pattern of all three indices was increased in the disturbed versus control habitat, suggesting an increase in local scale competition and an overall increase in unexplained variance in the post‐disturbance versus control community. Further research using simulation modeling should focus on establishing the proposed link between community assembly rules and spatial patterns of functional trait diversity to maximize our ability to infer multiple processes from spatial community structure.     

Species traits as drivers of food web structure

The use of functional traits to describe community structure is a promising approach to reveal generalities across organisms and ecosystems. Plant ecologists have demonstrated the importance of traits in explaining community structure, competitive interactions as well as ecosystem functioning. The application of trait‐based methods to more complex communities such as food webs is however more challenging owing to the diversity of animal characteristics and of interactions. The objective of this study was to determine how functional structure is related to food web structure. We consider that food web structure is the result of 1) the match between consumer and resource traits, which determine the occurence of a trophic interaction between them, and 2) the distribution of functional traits in the community. We implemented a statistical approach to assess whether or not 35 466 pairwise interactions between soil organisms are constrained by trait‐matching and then used a Procrustes analysis to investigate correlations between functional indices and network properties across 48 sites. We found that the occurrence of trophic interactions is well predicted by matching the traits of the resource with those of the consumer. Taxonomy and body mass of both species were the most important traits for the determination of an interaction. As a consequence, functional evenness and the variance of certain traits in the community were correlated to trophic complementarity between species, while trait identity, more than diversity, was related to network topology. The analysis was however limited by trait data availability, and a coarse resolution of certain taxonomic groups in our dataset. These limitations explain the importance of taxonomy, as well as the complexity of the statistical model needed. Our results outline the important implications of trait composition on ecological networks, opening promising avenues of research into the relationship between functional diversity and ecosystem functioning in multi‐trophic systems.     

Trait structure and redundancy determine sensitivity to disturbance in marine fish communities

Trait diversity is believed to influence ecosystem dynamics through links between organismal traits and ecosystem processes. Theory predicts that key traits and high trait redundancy—large species richness and abundance supporting the same traits—can buffer communities against environmental disturbances. While experiments and data from simple ecological systems lend support, large‐scale evidence from diverse, natural systems under major disturbance is lacking. Here, using long‐term data from both temperate (English Channel) and tropical (Seychelles Islands) fishes, we show that sensitivity to disturbance depends on communities’ initial trait structure and initial trait redundancy. In both ecosystems, we found that increasing dominance by climatically vulnerable traits (e.g., small, fast‐growing pelagics/corallivores) rendered fish communities more sensitive to environmental change, while communities with higher trait redundancy were more resistant. To our knowledge, this is the first study demonstrating the influence of trait structure and redundancy on community sensitivity over large temporal and spatial scales in natural systems. Our results exemplify a consistent link between biological structure and community sensitivity that may be transferable across ecosystems and taxa and could help anticipate future disturbance impacts on biodiversity and ecosystem functioning.     

Within‐species patterns challenge our understanding of the leaf economics spectrum

The utility of plant functional traits for predictive ecology relies on our ability to interpret trait variation across multiple taxonomic and ecological scales. Using extensive data sets of trait variation within species, across species and across communities, we analysed whether and at what scales leaf economics spectrum (LES) traits show predicted trait–trait covariation. We found that most variation in LES traits is often, but not universally, at high taxonomic levels (between families or genera in a family). However, we found that trait covariation shows distinct taxonomic scale dependence, with some trait correlations showing opposite signs within vs. across species. LES traits responded independently to environmental gradients within species, with few shared environmental responses across traits or across scales. We conclude that, at small taxonomic scales, plasticity may obscure or reverse the broad evolutionary linkages between leaf traits, meaning that variation in LES traits cannot always be interpreted as differences in resource use strategy.     

Revisiting the Holy Grail: using plant functional traits to understand ecological processes

One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a ‘Holy Grail’ in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community‐ and ecosystem‐level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait‐based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta‐analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.     

A combination of functionally different plant traits provides a means to quantitatively predict a broad range of species assemblages in NW Europe

Assembly theory predicts that filtering processes will select species by their attributes to build a community. Some filters increase functional similarity among species, while others lead to dissimilarity. Assuming converging processes to be dominant within habitats, we tested in this study whether species assemblages across a wide range of habitats can be distinguished quantitatively by their mean trait compositions. In addition, we investigated how many and which traits are needed to describe the differences between species assemblages best. The approach has been applied on a dataset that included 12 plant traits and 7644 vegetation relevés covering a wide range of habitats in the Netherlands. We demonstrate that due to the dominant role of converging processes 1) the functional composition can explain up to 80% of the floristic differences between species assemblages using seven plant traits, showing that plant trait combinations provide a powerful tool for predicting the occurrence of species assemblages across different habitats; 2) to achieve a high performance, traits should be taken from different strategy components, i.e. traits that are functionally orthogonal, which does not necessarily coincide with low trait‐trait correlations; 3) the different strategy components identified in this study correspond to the strategy components of some conventional plant ecological strategy schemes (PESS) – schemes to describe the variation between individual species. However, some PESS merge traits into one strategy component that are shown to be functionally different when predicting species assemblages. If such PESS is used to predict assemblages, this leads to a loss in predictive capacity. Potentially, our new approach is globally applicable to quantify community assembly patterns. However this needs to be tested.     

Two approaches using traits to assess ecological resilience: A case study on earthworm communities

The relation between biological diversity and ecosystem functioning is a central theme in ecology. Ecological traits of species are often regarded as a link between structure and function, and trait distributions in a community may change in response to environmental stressors. Likewise, resilience in a community may be derived from the diversity in traits and trait values relevant to a particular stressor. We combine two approaches to test this: a novel trait frequency analysis and a multivariate ordination approach. The two methods are applied on a case study of an earthworm community in a frequently flooded floodplain in the Netherlands. Periodic flooding in floodplains restricts population growth and recolonization of earthworms. The strategies employed by different earthworm species for coping with this stress can be described by a combination of ecological traits. From the literature we compiled 10 ecological traits for the earthworm species encountered along an inundation gradient in the Duursche Waarden floodplain area flanking the river IJssel. Trait frequency analysis showed a greater diversity at low elevation sites of traits considered to be associated to flood tolerance, suggesting greater community resilience to flooding. The ordination analysis using trait composition provided information on which trait classes in the community were related with the inundation stress. Results from both analyses showed that important traits in species to deal with flooding are active dispersal, high hydrophily, diapause and parthenogenetic reproduction. Thus, a further understanding of community resilience was gained by combining traditional ordination analysis with trait diversity analysis.     

A 7000‐year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate

Tropical forests are shifting in species and trait composition, but the main underlying causes remain unclear because of the short temporal scales of most studies. Here, we develop a novel approach by linking functional trait data with 7000 years of forest dynamics from a fossil pollen record of Lake Sauce in the Peruvian Amazon. We evaluate how climate and human disturbances affect community trait composition. We found weak relationships between environmental conditions and traits at the taxon level, but strong effects for community‐mean traits. Overall, community‐mean traits were more responsive to human disturbances than to climate change; human‐induced erosion increased the dominance of dense‐wooded, non‐zoochorous species with compound leaves, and human‐induced fire increased the dominance of tall, zoochorous taxa with large seeds and simple leaves. This information can help to enhance our understanding of forest responses to past environmental changes, and improve predictions of future changes in tropical forest composition.     

Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far.Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.     

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities

Recent studies have shown that accounting for intraspecific trait variation (ITV) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta‐analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole‐plant (e.g. plant height) vs. organ‐level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait‐based community and ecosystem studies.     

Phylogenetic diversity and the functioning of ecosystems

Phylogenetic diversity (PD) describes the total amount of phylogenetic distance among species in a community. Although there has been substantial research on the factors that determine community PD, exploration of the consequences of PD for ecosystem functioning is just beginning. We argue that PD may be useful in predicting ecosystem functions in a range of communities, from single-trophic to complex networks. Many traits show a phylogenetic signal, suggesting that PD can estimate the functional trait space of a community, and thus ecosystem functioning. Phylogeny also determines interactions among species, and so could help predict how extinctions cascade through ecological networks and thus impact ecosystem functions. Although the initial evidence available suggests patterns consistent with these predictions, we caution that the utility of PD depends critically on the strength of phylogenetic signals to both traits and interactions. We advocate for a synthetic approach that incorporates a deeper understanding of how traits and interactions are shaped by evolution, and outline key areas for future research. If these complexities can be incorporated into future studies, relationships between PD and ecosystem function bear promise in conceptually unifying evolutionary biology with ecosystem ecology.