Disentangling community functional components in a litter‐macrodetritivore model system reveals the predominance of the mass ratio hypothesis

Recent investigations have shown that two components of community trait composition are important for key ecosystem processes: (i) the community‐weighted mean trait value (CWM), related to the mass ratio hypothesis and dominant trait values in the community, and (ii) functional diversity (FD), related to the complementarity hypothesis and the divergence of trait values. However, no experiments controlling for the inherent dependence between CWM and FD have been conducted so far. We used a novel experimental framework to disentangle the unique and shared effects of CWM and FD in a leaf litter‐macrodetritivore model system. We manipulated isopod assemblages varying in species number, CWM and FD of litter consumption rate to test the relative contribution of these community parameters in the decomposition process. We showed that CWM, but also the combination of CWM and FD, is a main factor controlling litter decomposition. When we tested individual biodiversity components separately, CWM of litter consumption rate showed a significant effect on decomposition, while FD and species richness alone did not. Our study demonstrated that (i) trait composition rather than species diversity drives litter decomposition, (ii) dominant trait values in the community (CWM) play a chief role in driving ecosystem processes, corroborating the mass ratio hypothesis, and (iii) trait dissimilarity can contribute in modulating the overall biodiversity effects. Future challenge is to assess whether the generality of our finding, that is, that dominant trait values (CWM) predominate over trait dissimilarity (FD), holds for other ecosystem processes, environmental conditions and different spatial and temporal scales.     

Using root traits to understand temporal changes in biodiversity effects in grassland mixtures

Biodiversity–ecosystem functioning (BEF) studies typically show that species richness enhances community biomass, but the underlying mechanisms remain debated. Here, we combine metrics from BEF research that distinguish the contribution of dominant species (selection effects, SE) from those due to positive interactions such as resource partitioning (complementarity effects, CE) with a functional trait approach in an attempt to reveal the functional characteristics of species that drive community biomass in species mixtures. In a biodiversity experiment with 16 plant species in monocultures, 4‐species and 16‐species mixtures, we used aboveground biomass to determine the relative contributions of CE and SE to biomass production in mixtures in the second, dry year of the experiment. We also measured root traits (specific root length, root length density, root tissue density and the deep root fraction) of each species in monocultures and linked the calculated community weighted mean (CWM) trait values and trait diversity of mixtures to CE and SE. In the second year of the experiment, community biomass, CE and SE increased compared to the first year. The contribution of SE to this positive effect was greater than that of CE. The increased contribution of SE was associated with root traits: SE increased most in communities with high abundance of species with deep, thick and dense roots. In contrast, changes in CE were not related to trait diversity or CWM trait values. Together, these results suggest that increased positive effects of species richness on community biomass in a dry year were mainly driven by increased dominance of deep‐rooting species, supporting the insurance hypothesis of biodiversity. Positive CE indicates that other positive interactions did occur, but we could not find evidence that belowground resource partitioning or facilitation via root trait diversity was important for community productivity in our biodiversity experiment.     

Shifts in plant functional community composition under hydrological stress strongly decelerate litter decomposition

Litter decomposition is a key process of nutrient and carbon cycling in terrestrial ecosystems. The decomposition process will likely be altered under ongoing climate change, both through direct effects on decomposer activity and through indirect effects caused by changes in litter quality. We studied how hydrological change indirectly affects decomposition via plant functional community restructuring caused by changes in plant species’ relative abundances (community‐weighted mean (CWM) traits and functional diversity). We further assessed how those indirect litter quality effects compare to direct effects. We set up a mesocosm experiment, in which sown grassland communities and natural turf pieces were subjected to different hydrological conditions (dryness and waterlogging) for two growing seasons. Species‐level mean traits were obtained from trait databases and combined with species’ relative abundances to assess functional community restructuring. We studied decomposition of mixed litter from these communities in a common “litterbed.” These indirect effects were compared to effects of different hydrological conditions on soil respiration and on decomposition of standard litter (direct effects). Dryness reduced biomass production in sown communities and natural turf pieces, while waterlogging only reduced biomass in sown communities. Hydrological stress caused profound shifts in species’ abundances and consequently in plant functional community composition. Hydrologically stressed communities had higher CMW leaf dry matter content, lower CMW leaf nitrogen content, and lower functional diversity. Lower CWM leaf N content and functional diversity were strongly related to slower decomposition. These indirect effects paralleled direct effects, but were larger and longer‐lasting. Species mean traits from trait databases had therefore considerable predictive power for decomposition. Our results show that stressful soil moisture conditions, that are likely to occur more frequently in the future, quickly shift species’ abundances. The resulting functional community restructuring will decelerate decomposition under hydrological stress.     

Functional traits composition predict macrophytes community productivity along a water depth gradient in a freshwater lake

Functional trait composition of plant communities has been proposed as a helpful key for understanding the mechanisms of biodiversity effects on ecosystem functioning. In this study, we applied a step‐wise modeling procedure to test the relative effects of taxonomic diversity, functional identity, and functional diversity on macrophytes community productivity along water depth gradient. We sampled 42 plots and 1513 individual plants and measured 16 functional traits and abundance of 17 macrophyte species. Results showed that there was a significant decrease in taxonomic diversity, functional identity (i.e., stem dry mass content, leaf [C] and leaf [N]), and functional diversity (i.e., floating leaf, mean Julian flowering date and rooting depth) with increasing water depth. For the multiple‐trait functional diversity (FD) indices, functional richness decreased, while functional divergence increased with water depth gradient. Macrophyte community productivity was strongly determined by functional trait composition within community, but not significantly affected by taxonomic diversity. Community‐weighted means (CWM) showed a two times higher explanatory power relative to FD indices in determining variations in community productivity. For nine of sixteen traits, CWM and FD showed significant correlations with community productivity, although the strength and direction of those relations depended on selected trait. Furthermore, functional composition in a community affected productivity through either additive or opposite effects of CWM and FD, depending on the particular traits being considered. Our results suggested both mechanisms of mass ratio and niche complementarity can operate simultaneously on variations in community productivity, and considering both CWM and FD would lead to a more profound understanding of traits–productivity relationships.     

Shifts in community leaf functional traits are related to litter decomposition along a secondary forest succession series in subtropical China

Aims We investigated shifts in community-weighted mean traits (CWM) of 14 leaf functional traits along a secondary successional series in an evergreen broadleaf forest in subtropical southeast China. Most of the investigated traits have been reported to affect litter decomposition in previous studies. We asked whether changes in CWMs along secondary succession followed similar patterns for all investigated traits and whether the shifts in CWM indicated a change in resource use strategy along the successional gradient. Using community decomposition rates (k -rates) estimated from annual litter production and standing litter biomass, we asked whether the dynamics of litter decomposition were related to changes in leaf functional traits along the successional series.Methods Twenty-seven plots were examined for shifts in leaf CWM traits as well as in k -rates along a series of secondary forest succession covered in the framework of the BEF-China project. We investigated whether the changes in CWMs followed similar patterns for all traits with ongoing succession. Three alternative linear models were used to reveal the general patterns of shifts in CWM trait values. Moreover, multiple regression analysis was applied to investigate whether there were causal relationships between the changes in leaf functional traits and the dynamics of litter decomposition along secondary succession. We furthermore assessed which traits had the highest impact on community litter decomposition.Important findings Shifts in CWM values generally followed logarithmic patterns for all investigated traits, whereas community k -rates remained stable along the successional gradient. In summary, the shifts in CWM values indicate a change in community resource use strategy from high nutrient acquisition to nutrient retention with ongoing succession. Stands with higher CWM values of traits related to nutrient acquisition had also higher CWM values of traits related to chemical resistance, whereas stands with higher CWM values of traits related to nutrient retention exhibited higher CWM values in leaf physical defense. Moreover, high values in CWM values related to nutritional quality (such as high leaf phosphorus concentrations) were found to promote community k -rates, whereas high values in physical or chemical defense traits (such as high contents in polyphenols or high leaf toughness) decreased litter decomposition rates. In consequence, litter decomposition, which was simultaneously affected by these characteristics, did not change significantly along succession. Our findings show that leaf decomposition within the investigated communities is dependent on the interplay of several traits and is a result from interactions of traits that affect decomposition in opposing directions.     

Early subtropical forest growth is driven by community mean trait values and functional diversity rather than the abiotic environment

While functional diversity (FD) has been shown to be positively related to a number of ecosystem functions including biomass production, it may have a much less pronounced effect than that of environmental factors or species‐specific properties. Leaf and wood traits can be considered particularly relevant to tree growth, as they reflect a trade‐off between resources invested into growth and persistence. Our study focussed on the degree to which early forest growth was driven by FD, the environment (11 variables characterizing abiotic habitat conditions), and community‐weighted mean (CWM) values of species traits in the context of a large‐scale tree diversity experiment (BEF‐China). Growth rates of trees with respect to crown diameter were aggregated across 231 plots (hosting between one and 23 tree species) and related to environmental variables, FD, and CWM, the latter two of which were based on 41 plant functional traits. The effects of each of the three predictor groups were analyzed separately by mixed model optimization and jointly by variance partitioning. Numerous single traits predicted plot‐level tree growth, both in the models based on CWMs and FD, but none of the environmental variables was able to predict tree growth. In the best models, environment and FD explained only 4 and 31% of variation in crown growth rates, respectively, while CWM trait values explained 42%. In total, the best models accounted for 51% of crown growth. The marginal role of the selected environmental variables was unexpected, given the high topographic heterogeneity and large size of the experiment, as was the significant impact of FD, demonstrating that positive diversity effects already occur during the early stages in tree plantations.     

Leaf litter decomposition characteristics and controlling factors across two contrasting forest types

两种不同森林类型叶凋落物分解特征及影响因子研究 叶凋落物分解为森林生态系统提供了重要的能量和养分来源。除传统的环境因素外,叶凋落物的降解过程也受到绿叶功能性状和叶凋落物基质质量的影响。然而,在群落水平上,绿叶功能性状和叶凋落物基质质量对不同森林群落叶凋落物分解的相对重要性仍不清楚。因此,本研究以北京东灵山地区7种典型森林群落类型的混合叶凋落物为研究对象,利用分解袋法通过360天的野外相似环境分解实验对叶凋落物的分解过程进行了研究。这些森林群落包括6种分别以胡桃楸(Juglans mandshurica)、青杨(Populus cathayana)、棘皮桦(Betula dahurica)、白桦(Betula platyphylla)、油松(Pinus tabuliformis) 和华北落叶松(Larix gmelinii var. principis-rupprechtii) 为优势种的单优种群落,以及一种以大叶白蜡(Fraxinus rhynchophylla)、蒙古栎(Quercus mongolica)和蒙椴(Tilia mongolica)为优势种的共优种群落。研究结果表明,不同森林群落之间叶凋落物分解速率存在显著差异。群落聚合的植物功能性状和叶凋落物基质质量分别解释了群落叶凋落物分解速率变异的35.60%和9.05%,两者交互作用解释率为23.37%,表明群落聚合的植物功能性状及其与叶凋落物基质质量的共同作用是影响群落叶凋落物分解速率变异的主要因素。通过冗余分析发现,叶片氮含量、叶干物质含量、叶片单宁含量和比叶面积能显著影响群落叶凋落物分解速率的变异。因此,在对群落水平上叶凋落物分解的研究应该关注群落聚合的绿叶功能性状对分解的影响。     

Do temperate tree species diversity and identity influence soil microbial community function and composition?

Studies of biodiversity–ecosystem function in treed ecosystems have generally focused on aboveground functions. This study investigates intertrophic links between tree diversity and soil microbial community function and composition. We examined how microbial communities in surface mineral soil responded to experimental gradients of tree species richness (SR ), functional diversity (FD ), community‐weighted mean trait value (CWM ), and tree identity. The site was a 4‐year‐old common garden experiment near Montreal, Canada, consisting of deciduous and evergreen tree species mixtures. Microbial community composition, community‐level physiological profiles, and respiration were evaluated using phospholipid fatty acid (PLFA ) analysis and the MicroResp^? system, respectively. The relationship between tree species richness and glucose‐induced respiration (GIR ), basal respiration (BR ), metabolic quotient (qCO ₂) followed a positive but saturating shape. Microbial communities associated with species mixtures were more active (basal respiration [BR ]), with higher biomass (glucose‐induced respiration [GIR ]), and used a greater number of carbon sources than monocultures. Communities associated with deciduous tree species used a greater number of carbon sources than those associated with evergreen species, suggesting a greater soil carbon storage capacity. There were no differences in microbial composition (PLFA ) between monocultures and SR mixtures. The FD and the CWM of several functional traits affected both BR and GIR . In general, the CWM of traits had stronger effects than did FD , suggesting that certain traits of dominant species have more effect on ecosystem processes than does FD . Both the functions of GIR and BR were positively related to aboveground tree community productivity. Both tree diversity (SR ) and identity (species and functional identity—leaf habit) affected soil microbial community respiration, biomass, and composition. For the first time, we identified functional traits related to life‐history strategy, as well as root traits that influence another trophic level, soil microbial community function, via effects on BR and GIR .     

Temporal intraspecific trait variability drives responses of functional diversity to interannual aridity variation in grasslands

Interannual climate variation alters functional diversity through intraspecific trait variability and species turnover. We examined these diversity elements in three types of grasslands in northern China, including two temperate steppes and an alpine meadow. We evaluated the differences in community‐weighted means (CWM) of plant traits and functional dispersion (FDis) between 2 years with contrasting aridity in the growing season. Four traits were measured: specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen concentration (LNC), and the maximum plant height (H). CWM for SLA of the alpine meadow increased in the dry year while that of the temperate steppe in Qinghai showed opposing trends. CWM of LDMC in two temperate steppes became higher and CWM of LNC in all grasslands became lower in the dry year. Compared with the wet year, FDis of LDMC in the alpine meadow and FDis of LNC in the temperate steppe in Qinghai decreased in the dry year. FDis of H was higher in the dry year for two temperate steppes. Only in the temperate steppe in Qinghai did the multi‐FDis of all traits experience a significant increase in the dry year. Most of the changes in CWM and FDis between 2 years were explained by intraspecific trait variation rather than shifts in species composition. This study highlights that temporal intraspecific trait variation contributes to functional responses to environmental changes. Our results also suggest it would be necessary to consider habitat types when modeling ecosystem responses to climate changes, as different grasslands showed different response patterns.     

Potential trajectories of old‐growth Neotropical forest functional composition under climate change

Quantifying relationships between plant functional traits and abiotic gradients is valuable for evaluating potential responses of forest communities to climate change. However, the trajectories of change expected to occur in tropical forest functional characteristics as a function of future climate variation are largely unknown. We modeled community level trait values of Costa Rican rain forests as a function of current and future climate, and quantified potential changes in functional composition. We calculated per‐plot community weighted mean (CWM) trait values for leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen (N) and phosphorus (P) content, and wood basic specific gravity (WSG), for tree and palm species in 127 0.25 ha plots. We modeled the response of CWM traits to current temperature and precipitation gradients using generalized additive modeling. We then predicted and mapped CWM traits values under current and future climate, and quantified potential changes under a global warming scenario (RCP8.5, year 2050). We calculated the area within the multi trait functional space occupied by forest plots under both current and future climate, and determined potential changes in functional space occupied by forest plots. Overall, precipitation predicted CWM traits better than temperature. Models indicated increases in CWM SLA, N and P, and a decrease in CWM LDMC under climate change. Lowland forest communities converged on a single direction of change towards more acquisitive CWM trait values, indicating a change in forest functional composition resulting from a changed climate. Functional space occupied by forest plots was reduced by 50% under the future climate. Functional composition changes may have further effects on forests ecosystem services. Assessing functional trait spatial‐gradients can help bridge the gap between species‐based biogeography and biogeochemical approaches to strengthen biodiversity and ecosystem services conservation efforts.     

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.     

A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components

Plant functional traits vary both along environmental gradients and among species occupying similar conditions, creating a challenge for the synthesis of functional and community ecology. We present a trait-based approach that provides an additive decomposition of species' trait values into alpha and beta components: beta values refer to a species' position along a gradient defined by community-level mean trait values; alpha values are the difference between a species' trait values and the mean of co-occurring taxa. In woody plant communities of coastal California, beta trait values for specific leaf area, leaf size, wood density and maximum height all covary strongly, reflecting species distributions across a gradient of soil moisture availability. Alpha values, on the other hand, are generally not significantly correlated, suggesting several independent axes of differentiation within communities. This trait-based framework provides a novel approach to integrate functional ecology and gradient analysis with community ecology and coexistence theory.     

Traits of dominant plant species drive normalized difference vegetation index in grasslands globally

Aim

Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide.

Location

Two thousand nine hundred and forty-one grassland plots globally.

Time period

2000–2014.

Major taxa studied

Vascular plants.

Methods

We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure.

Results

Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships in natural communities.

Main conclusions

Our analysis provides empirical evidence that plant functional community structure and global patterns in primary productivity are linked through the resource economics and size traits of the dominant species. This is an important test of the hypotheses underlying BEF relationships at the global scale.     

Trait means,trait plasticity and trait differences to other species jointly explain species performances in grasslands of varying diversity

Functional traits may help to explain the great variety of species performances in plant communities, but it is not clear whether the magnitude of trait values of a focal species or trait differences to co‐occurring species are key for trait‐based predictions. In addition, trait expression within species is often plastic, but this variation has been widely neglected in trait‐based analyses. We studied functional traits and plant biomass of 59 species in 66 experimental grassland mixtures of varying species richness (Jena Experiment). We related mean species performances (species biomass and relative yield RY) and their plasticities along the diversity gradient to trait‐based pedictors involving mean species traits (T_mean), trait plasticities along the diversity gradient (T_slope), extents of trait variation across communities (T_CV; coefficient of variation) and hierarchical differences (T_diff) and trait distances (absolute values of trait differences T_dist) between focal and co‐occurring species. T_mean (30–55%) and T_diff (30–33%) explained most variation in mean species performances and their plasticities, but T_slope (20–25%) was also important in explaining mean species performances. The mean species traits and the trait differences between focal species and neighbors with the greatest explanatory power were related to plant size and stature (shoot length, mass:height ratios) and leaf photosynthetic capacity (specific leaf area, stable carbon isotopes and leaf nitrogen concentration). The contribution of trait plasticities in explaining species performances varied in direction (positive or negative) and involved traits related to photosynthetic capacity, nitrogen acquisition (nitrogen concentrations and stable isotopes) as well as structural stability (shoot carbon concentrations). Our results suggest that incorporating plasticity in trait expression as well as trait differences to co‐occurring species is critical for extending trait‐based analyses to understand the assembly of plant communities and the contribution of individual species in structuring plant communities.     

Predicting individual plant performance in grasslands

Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict individual plant performance in grasslands. To assess the relative importance of traits compared to environment, we planted seedlings of 20 common grassland species as phytometers into existing grassland communities varying in land‐use intensity. After 1 year, we dug out the plants and assessed root, leaf, and aboveground biomass, to measure plant performance. Furthermore, we determined the functional traits of the phytometers and of all plants growing in their local neighborhood. Neighborhood impacts were analyzed by calculating community‐weighted means (CWM) and functional diversity (FD) of every measured trait. We used model selection to identify the most important predictors of individual plant performance, which included phytometer traits, environmental conditions (climate, soil conditions, and land‐use intensity), as well as CWM and FD of the local neighborhood. Using variance partitioning, we found that most variation in individual plant performance was explained by the traits of the individual phytometer plant, ranging between 19.30% and 44.73% for leaf and aboveground dry mass, respectively. Similarly, in a linear mixed effects model across all species, performance was best predicted by phytometer traits. Among all environmental variables, only including land‐use intensity improved model quality. The models were also improved by functional characteristics of the local neighborhood, such as CWM of leaf dry matter content, root calcium concentration, and root mass per volume as well as FD of leaf potassium and root magnesium concentration and shoot dry matter content. However, their relative effect sizes were much lower than those of the phytometer traits. Our study clearly showed that under realistic field conditions, the performance of an individual plant can be predicted satisfyingly by its functional traits, presumably because traits also capture most of environmental and neighborhood conditions.     

Intraspecific trait variability shapes leaf trait response to altered fire regimes

Background and AimsUnderstanding impacts of altered disturbance regimes on community structure and function is a key goal for community ecology. Functional traits link species composition to ecosystem functioning. Changes in the distribution of functional traits at community scales in response to disturbance can be driven not only by shifts in species composition, but also by shifts in intraspecific trait values. Understanding the relative importance of these two processes has important implications for predicting community responses to altered disturbance regimes.MethodsWe experimentally manipulated fire return intervals in replicated blocks of a fire-adapted, longleaf pine (Pinus palustris) ecosystem in North Carolina, USA and measured specific leaf area (SLA), leaf dry matter content (LDMC) and compositional responses along a lowland to upland gradient over a 4 year period. Plots were burned between zero and four times. Using a trait-based approach, we simulate hypothetical scenarios which allow species presence, abundance or trait values to vary over time and compare these with observed traits to understand the relative contributions of each of these three processes to observed trait patterns at the study site. We addressed the following questions. (1) How do changes in the fire regime affect community composition, structure and community-level trait responses? (2) Are these effects consistent across a gradient of fire intensity? (3) What are the relative contributions of species turnover, changes in abundance and changes in intraspecific trait values to observed changes in community-weighted mean (CWM) traits in response to altered fire regime?Key ResultsWe found strong evidence that altered fire return interval impacted understorey plant communities. The number of fires a plot experienced significantly affected the magnitude of its compositional change and shifted the ecotone boundary separating shrub-dominated lowland areas from grass-dominated upland areas, with suppression sites (0 burns) experiencing an upland shift and annual burn sites a lowland shift. We found significant effects of burn regimes on the CWM of SLA, and that observed shifts in both SLA and LDMC were driven primarily by intraspecific changes in trait values.ConclusionsIn a fire-adapted ecosystem, increased fire frequency altered community composition and structure of the ecosystem through changes in the position of the shrub line. We also found that plant traits responded directionally to increased fire frequency, with SLA decreasing in response to fire frequency across the environmental gradient. For both SLA and LDMC, nearly all of the observed changes in CWM traits were driven by intraspecific variation.     

Differential effects of functional traits on aboveground biomass in semi-natural grasslands

Despite increasing evidence on the importance of species functional characteristics for ecosystem processes, two major hypotheses suggest different mechanisms: the ‘mass ratio hypothesis’ assumes that functional traits of the dominant species determine ecosystem processes, while the ‘complementarity hypothesis’ predicts that resource niches may be used more completely when a community is functionally more diverse. Here, we present a method which uses two different groups of biotic predictor variables being (1) abundance‐weighted mean (=aggregated) trait values and (2) functional trait diversity based on Rao's quadratic diversity (FD_Q) to test the competing hypotheses on biodiversity–ecosystem functioning relationships after accounting for co‐varying abiotic factors. We applied this method to data recorded on biodiversity–biomass relationships and environmental variables in 35 semi‐natural temperate grasslands and used a literature‐based matrix of fourteen plant functional traits to assess the explanatory power of models including different sets of predictor variables. Aboveground community biomass did not correlate with species richness. Abiotic factors, in particular soil nitrogen concentration, explained about 50% of variability in aboveground biomass. The best model incorporating functional trait diversity explained only about 30%, while the best model based on aggregated trait values explained about 54% of variability in aboveground biomass. The inclusion of all predictor variable groups in a combined model increased the predictive power to about 75%. This model comprised soil nitrogen concentration as abiotic factor, aggregated traits being indicative for species competitive dominance (rooting depth, leaf distribution, specific leaf area, perennial life cycle) and functional trait diversity in vegetative plant height, leaf area and life cycle. Our study strongly suggests that abiotic factors, trait values of the dominant species and functional trait diversity in combination may best explain differences in aboveground community biomass in natural ecosystems and that their isolated consideration may be misleading.     

Plant species traits are the predominant control on litter decomposition rates within biomes worldwide

Worldwide decomposition rates depend both on climate and the legacy of plant functional traits as litter quality. To quantify the degree to which functional differentiation among species affects their litter decomposition rates, we brought together leaf trait and litter mass loss data for 818 species from 66 decomposition experiments on six continents. We show that: (i) the magnitude of species-driven differences is much larger than previously thought and greater than climate-driven variation; (ii) the decomposability of a species' litter is consistently correlated with that species' ecological strategy within different ecosystems globally, representing a new connection between whole plant carbon strategy and biogeochemical cycling. This connection between plant strategies and decomposability is crucial for both understanding vegetation-soil feedbacks, and for improving forecasts of the global carbon cycle.     

Invasive plants in Minnesota are “joining the locals”: A trait‐based analysis

Questions

Predicting which newly arrived species will establish and become invasive is a problem that has long vexed researchers. In a study of cold temperate oak forest stands, we examined two contrasting hypotheses regarding plant functional traits to explain the success of certain non‐native species. Under the “join the locals” hypothesis, successful invaders are expected to share traits with resident species because they employ successful growth strategies under light‐limited understorey conditions. Instead, under the “try harder” hypothesis, successful invaders are expected to have traits different from native species in order to take advantage of unused niche space.

Location

Minnesota, USA.

Methods

We examined these two theories using 109 native and 11 non‐native plants in 68 oak forest stands. We focused on traits related to plant establishment and growth, including specific leaf area (SLA), leaf carbon‐to‐nitrogen ratio (C:N), wood density, plant maximum height, mycorrhizal type, seed mass and growth form. We compared traits of native and non‐native species using ordinations in multidimensional trait space and compared community‐weighted mean (CWM) trait values across sites.

Results

We found few differences between trait spaces occupied by native and non‐native species. Non‐native species occupied smaller areas of trait space than natives, yet were within that of the native species, indicating similar growth strategies. We observed a higher proportion of non‐native species in sites with higher native woody species CWM SLA and lower CWM C:N. Higher woody CWM SLA was observed in sites with higher soil pH, while lower CWM C:N was found in sites with higher light levels.

Conclusions

Non‐native plants in this system have functional traits similar to natives and are therefore “joining the locals.” However, non‐native plants may possess traits toward the acquisitive end of the native plant trait range, as evidenced by higher non‐native plant abundance in high‐resource environments.

     

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.