Disturbance regime changes the trait distribution,phylogenetic structure and community assembly of tropical rain forests

A rapidly increasing effort to merge functional community ecology and phylogenetic biology has increased our understanding of community assembly. However, studies using both phylogenetic‐ and trait‐based methods have been mainly conducted in old‐growth forests, with fewer studies in human‐disturbed communities, which play an increasingly important role in providing ecosystem services as primary forests are degraded. We used data from 18 1‐ha plots in tropical old‐growth forests and secondary forests with different disturbance histories (logging and shifting cultivation) and vegetation types (tropical lowland and montane forests) on Hainan Island, southern China. The distributions of 11 functional traits were compared among these six forest types. We used a null model approach to assess the effects of disturbance regimes on variation in response and effect traits and community phylogenetic structure across different stem sizes (saplings, treelets, and adult trees) and spatial scales (10–50 m). We found significant differences in the distribution of functional traits in highly disturbed lowland sites versus other forest types. Many individuals in highly disturbed lowland sites were deciduous, spiny, with non‐fleshy fruits and seeds dispersed passively or by wind, and low SLA. The response traits of coexisting species were clustered in all sites except for highly disturbed lowland sites where evenness was evident. There were different distributions of effect traits for saplings and treelets among different forest types but adult trees showed stronger clustering of trait values with increasing spatial scale among all forest types. Phylogenetic clustering predominated across all size classes and spatial scales in the highly disturbed lowland sites, and evenness in other forest types. High disturbance can lead to abiotic filtering, generating a community dominated by closely related species with disturbance‐adapted traits, where biotic interactions play a relatively minor role. In lightly disturbed and old growth forests, multiple processes simultaneously drive the community assembly, but biotic processes dominate at the fine scale.     

Towards a functional basis for predicting vegetation patterns; incorporating plant traits in habitat distribution models

Reliably predicting vegetation distribution requires habitat distribution models (HDMs) that are ecologically sound. Current correlative HDMs are increasingly criticized because they lack sufficient functional basis. To include functional information into these models, we integrated two concepts from community ecology into a new type of HDM. We incorporated: 1) species selection by their traits in which only those species that pass the environmental filter can be part of the community (assembly theory); 2) that the occurrence probability of a community is determined by the extent to which the community mean traits fit the required traits as set by the environment. In this paper, our trait‐based HDM is presented and its predictive capacity explored. Our approach consists of two steps. In step 1, four plant traits (stem‐specific density and indicator values for nutrients, moisture and acidity) are predicted from four dominant environmental drivers (disturbance, nutrient supply, moisture supply and acidity) using regression. In step 2, these traits are used to predict the occurrence probability of 13 vegetation types, covering the majority of vegetation types across the Netherlands. The model was validated by comparison to the observed vegetation type for 263 plots in the Netherlands. Model performance was within the range of conventional HDMs and decreased with increasing uncertainty in the environment‐trait relationships and with an increasing number of vegetation types. This study shows that including functionality into HDMs is not necessarily at the cost of model performance, while it has several conceptual advantages among including an increased insight in the functional characteristics of the vegetation and sources of unpredictability in community assembly. As such it is a promising first step towards more functional HDMs. Further development of a trait‐based HDM hinges on replacing indicator values by truly functional traits and the translation of these relationships into mechanistic relationships.     

高原鼠兔干扰对高寒草甸植物物种和功能性状beta多样性的影响

采用野外空间多点同步取样,分析了高原鼠兔干扰对高寒草甸植物物种beta多样性和植物功能性状beta多样性的影响,确定了高原鼠兔干扰下高寒草甸植物物种和功能性状beta多样性的变化途径,分别提出了高原鼠兔干扰区域内,基于植物物种多样性和功能性状多样性的高寒草甸植物多样性维持策略。结果表明,高原鼠兔干扰使高寒草甸植物物种相似性显著降低了28.1%,植物功能相似性降低了28.7%。尽管高原鼠兔干扰没有改变高寒草甸植物物种和功能性状beta多样性的变化途径,且对植物物种和功能性状的嵌套组分不存在显著影响,但高原鼠兔干扰显著降低了植物物种和功能性状周转组分所占的比例,降幅分别为36.6%和34.3%。高原鼠兔干扰区域内,高寒草甸植物物种beta多样性的变化以周转为主导(周转占比81.4%;嵌套占比:18.6%),植物功能性状beta多样性的变化以嵌套为主导(嵌套占比64.9%;周转占比35.1%)。因此,针对划定的高原鼠兔干扰区,需要同时保护区域内所有高原鼠兔栖息地(多位点保护),以达到维持植物物种多样性的目的,而可以仅通过保护该区域内植物功能性状丰富的位点,即可维持较高的植物功能多样性。     

Defining a spectrum of integrative trait‐based vegetation canopy structural types

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest sub‐set of this spectrum, we assess gradients in canopy structural traits, characterise canopy structural types (CST) and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within‐ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub‐continental variation in forest types and eco‐climatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modelling structure–function relationships in vegetated ecosystems.     

Integrating multi-scale data to model the relationship between food resources, waterbird distribution and human activities in freshwater systems: preliminary findings and potential uses

Understanding and predicting the likely consequences of anthropogenic disturbance on species and ecosystems is a major prerequisite of achieving the sustainable use of natural resources. It is also a key element in the management of sites with statutory designation. During planning and decision-making processes involving potential disturbance issues, land managers and responsible authorities are often required to take account of the needs and views of a diversity of site user groups. The effects and impacts of disturbance can occur over a range of spatial and temporal scales, and research into these consequences must address this problem. This paper provides (1) an overview of the field and analytical methodologies contributing to the development of an integrated method for collecting multi-scale bird, resource and disturbance data in freshwater systems, and (2) an overview of the drivers and need for such data in sustainable resource management. Whilst the results of the bird–habitat–disturbance modelling arising from these data will be published elsewhere, the types of information that will be generated are illustrated and their potential use within planning and decision-making processes discussed.     

A rule-based model for the functional analysis of vegetation change in Australasian grasslands

Abstract. Grasslands encompass a broad array of vegetation and climatic zones. We describe the first developments towards a rule-based functional model for predicting vegetation structure in Australian and New Zealand pastures and rangelands. The approach aims to predict the combined effects of climate and disturbance by humans and grazing livestock, and to provide a level of resolution needed for predicting changes in pastures and rangelands. We enlisted expert knowledge to develop: (1) a minimum set of critical traits; (2) rules relating site variables to favoured plant attributes; (3) rules relating attributes to plant functional traits, and (4) rules relating plant functional types to likely plant communities. We tested the resulting model by deriving some simple predictions of plant communities of some existing pasture and rangeland sites in Australia and New Zealand, with differing climatic and human disturbance inputs. The results indicate that this first model is able to predict plant communities with varying success rates, and with the best results in cases where there are extreme climates or high management inputs. Key sensitivities in the model where further research is required include: (1) the urgent need for more explicit understanding of the key plant functional attributes favoured by differing climates and disturbance regimes, (2) the functional relationships between these plant functional attributes and recognisable plant functional types in vegetation, and (3) the assembly rules for the coexistence of these different plant functional types in major plant communities. The same understanding is required for subsequent process-based modelling development.     

Assessing among‐lineage variability in phylogenetic imputation of functional trait datasets

Phylogenetic imputation has recently emerged as a potentially powerful tool for predicting missing data in functional traits datasets. As such, understanding the limitations of phylogenetic modelling in predicting trait values is critical if we are to use them in subsequent analyses. Previous studies have focused on the relationship between phylogenetic signal and clade‐level prediction accuracy, yet variability in prediction accuracy among individual tips of phylogenies remains largely unexplored. Here, we used simulations of trait evolution along the branches of phylogenetic trees to show how the accuracy of phylogenetic imputations is influenced by the combined effects of 1) the amount of phylogenetic signal in the traits and 2) the branch length of the tips to be imputed. Specifically, we conducted cross‐validation trials to estimate the variability in prediction accuracy among individual tips on the phylogenies (hereafter ‘tip‐level accuracy’). We found that under a Brownian motion model of evolution (BM, Pagel't λ = 1), tip‐level accuracy rapidly decreased with increasing tip branch‐lengths, and only tips of approximately 10% or less of the total height of the trees showed consistently accurate predictions (i.e. cross‐validation R‐squared >0.75). When phylogenetic signal was weak, the effect of tip branch‐length was reduced, becoming negligible for traits simulated with λ < 0.7, where accuracy was in any case low. Our study shows that variability in prediction accuracy among individual tips of the phylogeny should be considered when evaluating the reliability of phylogenetically imputed trait values. To address this challenge, we describe a Monte Carlo‐based method that allows one to estimate the expected tip‐level accuracy of phylogenetic predictions for continuous traits. Our approach identifies gaps in functional trait datasets for which phylogenetic imputation performs poorly, and will help ecologists to design more efficient trait collection campaigns by focusing resources on lineages whose trait values are more uncertain.     

Quantifying relationships between traits and explicitly measured gradients of stress and disturbance in early successional plant communities

Questions: How can one explicitly quantify, and separately measure, stress and disturbance gradients? How do these gradients affect functional composition in early successional plant communities and to what extent? Can we accurately predict trait composition from knowledge of these gradients? Location: Southern Quebec, Canada. Methods: Using eight environmental variables measured in 48 early successional plant communities, we estimated stress and disturbance gradients through structural equation modelling. We then measured 10 functional traits on the most abundant species of these 48 communities and calculated their community‐level mean and variance weighted by the relative abundance of each species. Finally, we related these community‐weighted means and variances to the estimated stress and disturbance gradients using general linear models or generalized additive models. Results: We obtained a well‐fitting measurement model of the stress and disturbance gradients existing in our sites. Of the 10 studied traits, only average plant reproductive height was strongly correlated with the stress (r²=0.464) and disturbance (r²=0.543) gradients. Leaf traits were not significantly related to either the stress or disturbance gradients. Conclusions: The well‐fitting measurement model of the stress and disturbance gradients, combined with the generally weak trait–environment linkages, suggests that community assembly in these early successional plant communities is driven primarily by stochastic processes linked to the history of arrival of propagules and not to trait‐based environmental filtering.     

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

Background  

The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved.     

Mapping functional similarity of predators on the basis of trait similarities

Theoretical and empirical studies in community ecology often simplify their study system by lumping together species on the basis of trait similarities (e.g., their taxonomy, resource or microhabitat usage) and then assume species sharing similar traits are functionally similar. To date, no study has directly tested whether species more similar with respect to any of these traits are more similar in their functional effects on population or ecosystem processes. In this study, we examined the association between traits and functional effects of six different aquatic predatory vertebrates. We demonstrated that functional similarity across multiple response variables was not correlated with trait similarity, but differences in trait values were associated with significantly different effects on individual response variables. The exact relationship between species traits and functional effect of predators, however, was different for each response variable. Using traits to predict functional similarity among species may be useful when considering individual response variables, but only if it is known which traits have the greatest influence on the response variable of interest. It is doubtful that any one scheme will predict the functional similarity of species across a diverse array of response variables because each response will likely be strongly influenced by different traits.     

How functional is functional? Ecological groupings in terrestrial animal ecology: towards an animal functional type approach

Understanding mechanisms to predict changes in plant and animal communities is a key challenge in ecology. The need to transfer knowledge gained from single species to a more generalized approach has led to the development of categorization systems where species’ similarities in life strategies and traits are classified into ecological groups (EGs) like functional groups/types or guilds. While approaches in plant ecology undergo a steady improvement and refinement of methodologies, progression in animal ecology is lagging behind. With this review, we aim to initiate a further development of functional classification systems in animal ecology, comparable to recent developments in plant ecology. We here (i) give an overview of terms and definitions of EGs in animal ecology, (ii) discuss existing classification systems, methods and application areas of EGs (focusing on terrestrial vertebrates), and (iii) provide a “roadmap towards an animal functional type approach” for improving the application of EGs and classifications in animal ecology. We found that an animal functional type approach requires: (i) the identification of core traits describing species’ dependency on their habitat and life history traits, (ii) an optimization of trait selection by clustering traits into hierarchies, (iii) the assessment of “soft traits” as substitute for hardly measurable traits, e.g. body size for dispersal ability, and (iv) testing of delineated groups for validation including experiments.     

Assessing the generality of global leaf trait relationships

Global-scale quantification of relationships between plant traits gives insight into the evolution of the world's vegetation, and is crucial for parameterizing vegetation-climate models. A database was compiled, comprising data for hundreds to thousands of species for the core 'leaf economics' traits leaf lifespan, leaf mass per area, photosynthetic capacity, dark respiration, and leaf nitrogen and phosphorus concentrations, as well as leaf potassium, photosynthetic N-use efficiency (PNUE), and leaf N : P ratio. While mean trait values differed between plant functional types, the range found within groups was often larger than differences among them. Future vegetation-climate models could incorporate this knowledge. The core leaf traits were intercorrelated, both globally and within plant functional types, forming a 'leaf economics spectrum'. While these relationships are very general, they are not universal, as significant heterogeneity exists between relationships fitted to individual sites. Much, but not all, heterogeneity can be explained by variation in sample size alone. PNUE can also be considered as part of this trait spectrum, whereas leaf K and N : P ratios are only loosely related.     

鼎湖山南亚热带常绿阔叶林植物功能性状变异与不同垂直层次个体生长的关联

建立植物功能性状与群落动态之间的关联是功能生态学的核心问题之一。本文基于鼎湖山1.44 ha塔吊样地的两次调查数据, 通过采集样地内所有4,142株个体的6种植物功能性状, 对比分析了个体水平植物功能性状和物种水平功能性状均值对不同垂直层次(灌木层、亚冠层和林冠层)个体生长的影响差异。首先, 分析了不同垂直层次下各植物功能性状的变化趋势; 其次, 计算了不同垂直层次下各植物功能性状的种内和种间变异水平; 最后, 运用结构方程模型探讨了植物功能性状、光竞争以及地下竞争对不同垂直层次树木生长的影响。结果表明: (1)不同垂直层次下的植物功能性状表现出明显的分异, 由灌木层至林冠层, 叶面积、比叶面积和能量供求关系指数显著降低, 而叶片厚度和叶片干物质含量显著升高; (2)不同垂直层次下植物功能性状的种间变异均大于种内变异, 且林冠层的种内功能性状变异均大于灌木层和亚冠层; (3)基于个体水平植物功能性状的结构方程模型较物种水平功能性状均值对生长具有更高的解释程度, 且个体水平植物功能性状的引入更有利于提高对灌木层个体生长的预测能力; (4)光竞争和地下竞争主要通过影响功能性状间接影响植物生长。由灌木层至林冠层, 同种间的相互作用逐渐减弱, 异种间的相互作用逐渐增强。综上, 将个体水平植物功能性状纳入分析有助于更好地理解群落的结构和动态。     

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N_area), the maximum carboxylation rate of Rubisco per leaf area (), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.     

Going beyond limitations of plant functional types when predicting global ecosystem–atmosphere fluxes: exploring the merits of traits‐based approaches

Aim Despite their importance for predicting fluxes to and from terrestrial ecosystems, dynamic global vegetation models have insufficient realism because of their use of plant functional types (PFTs) with constant attributes. Based on recent advances in community ecology, we explore the merits of a traits‐based vegetation model to deal with current shortcomings. Location Global. Methods A research review of current concepts and information, providing a new perspective, supported by quantitative analysis of a global traits database. Results Continuous and process‐based trait–environment relations are central to a traits‐based approach and allow us to directly calculate fluxes based on functional characteristics. By quantifying community assembly concepts, it is possible to predict trait values from environmental drivers, although these relations are still imperfect. Through the quantification of these relations, effects of adaptation and species replacement upon environmental changes are implicitly accounted for. Such functional links also allow direct calculation of fluxes, including those related to feedbacks through the nitrogen and water cycle. Finally, a traits‐based model allows the prediction of new trait combinations and no‐analogue ecosystem functions projected to arise in the near future, which is not feasible in current vegetation models. A separate calculation of ecosystem fluxes and PFT occurrences in traits‐based models allows for flexible vegetation classifications. Main conclusions Given the advantages described above, we argue that traits‐based modelling deserves consideration (although it will not be easy) if one is to aim for better climate projections.     

Lifestyle and threat of macromycetes,and functional traits correlated with it

Regarding the functional traits of macromycetes, at present there are only few studies available, and these mostly deal with more specific questions or single traits. In the present study we are interested in functional traits that may explain the lifestyle and threat of these fungi. For this purpose, we assembled a database on 31 traits that cover a broad range of features of, e.g., fruit body morphology, hymenial structure, spore morphology, and propagule dispersal of 636 macromycete species. To allow an easier classification of hymenium size we introduce two new measures, volume index and surface index. Lifestyle and Red List classification were used to detect differences in functional trait adaptation of species. Both were used as predictors in these analyses. Lifestyle type accounts for significant differences in 28 traits, which shows that different lifestyle types are based on specific trait combinations. Red List classification accounted for significant differences in four traits. We describe the differentiations and discuss them against the background of ecological and morphological research, including the causes of threat and niche adaptation.