Intraspecific variability of leaf form and function across habitat types.

Trait-based ecology has already revealed main independent axes of trait variation defining trait spaces that summarize plant adaptive strategies, but often ignoring intraspecific trait variability (ITV). By using empirical ITV-level data for two independent dimensions of leaf form and function and 167 species across five habitat types (coastal dunes, forests, grasslands, heathlands, wetlands) in the Italian peninsula, we found that ITV: (i) rotated the axes of trait variation that define the trait space; (ii) increased the variance explained by these axes and (iii) affected the functional structure of the target trait space. However, the magnitude of these effects was rather small and depended on the trait and habitat type. Our results reinforce the idea that ITV is context-dependent, calling for careful extrapolations of ITV patterns across traits and spatial scales. Importantly, our study provides a framework that can be used to start integrating ITV into trait space analyses.

Multiple drivers of functional diversity in temperate forest understories: Climate, soil, and forest structure effects.

In macroecology, shifting from coarse- to local-scale explanatory factors is crucial for understanding how global change impacts functional diversity (FD). Plants possess diverse traits allowing them to differentially respond across a spectrum of environmental conditions. We aim to assess how macro- to microclimate, stand-scale measured soil properties, forest structure, and management type, influence forest understorey FD at the macroecological scale. Our study covers Italian forests, using thirteen predictors categorized into climate, soil, forest structure, and management. We analyzed five traits (i.e., specific leaf area, plant size, seed mass, belowground bud bank size, and clonal lateral spread) capturing independent functional dimensions to calculate the standardized effect size of functional diversity (SES-FD) for all traits (multi-trait) and for single traits. Multiple regression models were applied to assess the effect of predictors on SES-FD. We revealed that climate, soil, and forest structure significantly drive SES-FD of specific leaf area, plant size, seed mass, and bud bank. Forest management had a limited effect. However, differences emerged between herbaceous and woody growth forms of the understorey layer, with herbaceous species mainly responding to climate and soil features, while woody species were mainly affected by forest structure. Future warmer and more seasonal climate could reduce the diversity of resource economics, plant size, and persistence strategies of the forest understorey. Soil eutrophication and acidification may impact the diversity of regeneration strategies; canopy closure affects the diversity of above- and belowground traits, with a larger effect on woody species. Multifunctional approaches are vital to disentangle the effect of global changes on functional diversity since independent functional specialization axes are modulated by different drivers.

Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency.

Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine (i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and (ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs. high). Our results revealed that bacteria were associated with particular soil properties (such as base saturation) and both bacteria and fungi were associated with plant community composition across sites and within the majority of sites. Moreover, a discernible microbial community signal emerged, clearly distinguishing high and low-productivity soils across different grasslands independent of their location in the world. Hence, regional productivity differences may be typified by characteristic soil microbial communities across the grassland biome. These results could encourage future research aiming to predict the general effects of global changes on soil microbial community composition in grasslands and to discriminate fertile from infertile systems using generally applicable microbial indicators.

The global spectrum of plant form and function: enhanced species-level trait dataset.

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.

Incorporating clonality into the plant ecology research agenda.

A longstanding research divide exists in plant ecology: either focusing on plant clonality, with no ambition to address nonclonal plants, or focusing on all plants, ignoring that many ecological processes can be affected by the fact that some plants are clonal while others are not. This gap cascades into a lack of distinction and knowledge about the similarities and differences between clonal and nonclonal plants. Here we aim to bridge this gap by identifying areas that would benefit from the incorporation of clonal growth into one integrated research platform: namely, response to productivity and disturbance, biotic interactions, and population dynamics. We are convinced that this will provide a roadmap to gain valuable insights into the ecoevolutionary dynamics relevant to all plants.

Plant functional traits are correlated with species persistence in the herb layer of old-growth beech forests.

This paper explores which traits are correlated with fine-scale (0.25 m2) species persistence patterns in the herb layer of old-growth forests. Four old-growth beech forests representing different climatic contexts (presence or absence of summer drought period) were selected along a north-south gradient in Italy. Eight surveys were conducted in each of the sites during the period spanning 1999-2011. We found that fine-scale species persistence was correlated with different sets of plant functional traits, depending on local ecological context. Seed mass was found to be as important for the fine-scale species persistence in the northern sites, while clonal and bud-bank traits were markedly correlated with the southern sites characterised by summer drought. Leaf traits appeared to correlate with species persistence in the drier and wetter sites. However, we found that different attributes, i.e. helomorphic vs scleromorphic leaves, were correlated to species persistence in the northernmost and southernmost sites, respectively. These differences appear to be dependent on local trait adaptation rather than plant phylogenetic history. Our findings suggest that the persistent species in the old-growth forests might adopt an acquisitive resource-use strategy (i.e. helomorphic leaves with high SLA) with higher seed mass in sites without summer drought, while under water-stressed conditions persistent species have a conservative resource-use strategy (i.e. scleromorphic leaves with low SLA) with an increased importance of clonal and resprouting ability.

The Neglected Belowground Dimension of Plant Dominance.

Dominants are key species that shape ecosystem functioning. Plant dominance is typically assessed on aboveground features. However, belowground, individual species may not scale proportionally in relation to their aboveground dimension. This is especially important in ecosystems where most biomass is allocated belowground, including grassy and shrubby biomes.

Community weighted mean trait data of Italian forest understories.

Plant functional trait data aggregated at the community level (i.e., community weighted mean, CWM) are fundamental to study plant-environment relationships. Here, we provide a large database of CWM values of twelve traits reflecting several plant functions, including leaf, seed, whole-plant, clonal and bud bank traits. The CWMs were calculated in 201 forest stands (a statistically representative sample of all the Italian forests) across three biogeographic regions: Alpine, Continental, and Mediterranean.

Exploring patterns of beta-diversity to test the consistency of biogeographical boundaries: A case study across forest plant communities of Italy.

AIM: To date, despite their great potential biogeographical regionalization models have been mostly developed on descriptive and empirical bases. This paper aims at applying the beta-diversity framework on a statistically representative data set to analytically test the consistency of the biogeographical regionalization of Italian forests. LOCATION: Italy. TAXON: Vascular plants. METHODS: Forest plant communities were surveyed in 804 plots made in a statistically representative sample of forest communities made by 201 sites of Italian forests across the three biogeographical regions of the country: Alpine, Continental, and Mediterranean. We conducted an ordination analysis and an analysis of beta-diversity, decomposing it into its turnover and nestedness components. RESULTS: Our results provide only partial support to the consistency of the biogeographical regionalization of Italy. While the differences in forest plant communities support the distinction between the Alpine and the other two regions, differences between Continental and Mediterranean regions had lower statistical support. Pairwise beta-diversity and its turnover component are higher between- than within-biogeographical regions. This suggests that different regional species pools contribute to assembly of local communities and that spatial distance between-regions has a stronger effect than that within-regions. MAIN CONCLUSIONS: Our findings confirm a biogeographical structure of the species pools that is captured by the biogeographical regionalization. However, nonsignificant differences between the Mediterranean and Continental biogeographical regions suggest that this biogeographical regionalization is not consistent for forest plant communities. Our results demonstrate that an analytical evaluation of species composition differences among regions using beta-diversity analysis is a promising approach for testing the consistency of biogeographical regionalization models. This approach is recommended to provide support to the biogeographical regionalization used in some environmental conservation polices adopted by EU.

Evaluation of factors affecting gully headcut location using summary statistics and the maximum entropy model: Golestan Province, NE Iran.

Gully erosion is an important soil degradation process, which under climate changes is projected to increase. Therefore, better understating of factors controlling gully erosion and prediction of gully headcuts' (GHs) location is still highly relevant. This study aimed to examine the spatial distribution of GHs and to assess the importance of pedological (i.e. aggregate stability, organic matter, bulk density, silt, clay, and sand content) and topographical factors (i.e. altitude, slope length, gradient, and aspect) using summary statistics and the maximum entropy (MaxEnt) model. The study was conducted in the loess-covered region of NE Iran. The highly precise data of 287 GHs locations were obtained by extensive fieldwork and the interpretation of UAV images. The spatial distribution of GHs was evaluated by univariate pair correlation function and O-ring statistics. The spatial effect of GHs density controlling factors was assessed by the cumulative density correlation function Cm,K(r). Variable importance was analyzed using the MaxEnt model, which was also for the susceptibility modelling of GHs. The results of univariate tests showed the aggregated distribution of GHs. The Cm,K(r) analyses indicated that the areas characterized by higher values of bulk density, aggregate stability, and organic matter content have lower GHs density, whereas the areas with high silt content and higher slope gradient have higher GHs density. According to the MaxEnt, there is no one single factor responsible for GHs location, but rather the combination of topographical and pedological factors with the predominance of slope gradient (0.86) and silt content (0.57). The MaxEnt modelling of GHs susceptibility has revealed that the best accuracy (0.958) is given when all pedological and topographical factors are used in the model. The susceptibility maps prepared in the study can be used for soil conversation and land use planning and, consequently, for sustainable development in the region.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Species richness effects on grassland recovery from drought depend on community productivity in a multisite experiment.

Biodiversity can buffer ecosystem functioning against extreme climatic events, but few experiments have explicitly tested this. Here, we present the first multisite biodiversity × drought manipulation experiment to examine drought resistance and recovery at five temperate and Mediterranean grassland sites. Aboveground biomass production declined by 30% due to experimental drought (standardised local extremity by rainfall exclusion for 72-98 consecutive days). Species richness did not affect resistance but promoted recovery. Recovery was only positively affected by species richness in low-productive communities, with most diverse communities even showing overcompensation. This positive diversity effect could be linked to asynchrony of species responses. Our results suggest that a more context-dependent view considering the nature of the climatic disturbance as well as the productivity of the studied system will help identify under which circumstances biodiversity promotes drought resistance or recovery. Stability of biomass production can generally be expected to decrease with biodiversity loss and climate change.

Effects of extreme drought on specific leaf area of grassland species: A meta-analysis of experimental studies in temperate and sub-Mediterranean systems.

Here, we conducted a meta-analysis of experimental drought manipulation studies using rainout shelters in five sites of natural grassland ecosystems of Europe. The single studies assess the effects of extreme drought on the intraspecific variation of the specific leaf area (SLA), a proxy of plant growth. We evaluate and compare the effect size of the SLA response for the functional groups of forbs and grasses in temperate and sub-Mediterranean systems. We hypothesized that the functional groups of grasses and forbs from temperate grassland systems have different strategies in short-term drought response, measured as adjustment of SLA, with SLA-reduction in grasses and SLA-maintenance in forbs. Second, we hypothesized that grasses and forbs from sub-Mediterranean systems do not differ in their drought response as both groups maintain their SLA. We found a significant decrease of SLA in grasses of the temperate systems in response to drought while SLA of forbs showed no significant response. Lower SLA is associated with enhanced water-use efficiency under water stress and thus can be seen as a strategy of phenotypic adjustment. By contrast, in the sub-Mediterranean systems, grasses significantly increased their SLA in the drought treatment. This result points towards a better growth performance of these grasses, which is most likely related to their strategy to allocate resources to belowground parts. The observed SLA reduction of forbs is most likely a direct drought response given that competitive effect of grasses is unlikely due to the scanty vegetation cover. We point out that phenotypic adjustment is an important driver of short-term functional plant response to climatic extremes such as drought. Differential reactions of functional groups have to be interpreted against the background of the group's evolutionary configuration that can differ between climatic zones.

Response to Comment on "Worldwide evidence of a unimodal relationship between productivity and plant species richness".

Tredennick et al. criticize one of our statistical analyses and emphasize the low explanatory power of models relating productivity to diversity. These criticisms do not detract from our key findings, including evidence consistent with the unimodal constraint relationship predicted by the humped-back model and evidence of scale sensitivities in the form and strength of the relationship.

Plant ecology. Worldwide evidence of a unimodal relationship between productivity and plant species richness.

The search for predictions of species diversity across environmental gradients has challenged ecologists for decades. The humped-back model (HBM) suggests that plant diversity peaks at intermediate productivity; at low productivity few species can tolerate the environmental stresses, and at high productivity a few highly competitive species dominate. Over time the HBM has become increasingly controversial, and recent studies claim to have refuted it. Here, by using data from coordinated surveys conducted throughout grasslands worldwide and comprising a wide range of site productivities, we provide evidence in support of the HBM pattern at both global and regional extents. The relationships described here provide a foundation for further research into the local, landscape, and historical factors that maintain biodiversity.

ICP-Forests (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests): Quality Assurance procedure in plant diversity monitoring.

Knowledge of accuracy and precision rates is particularly important for long-term studies. Vegetation assessments include many sources of error related to overlooking and misidentification, that are usually influenced by some factors, such as cover estimate subjectivity, observer biased species lists and experience of the botanist. The vegetation assessment protocol adopted in the Italian forest monitoring programme (CONECOFOR) contains a Quality Assurance programme. The paper presents the different phases of QA, separates the 5 main critical points of the whole protocol as sources of random or systematic errors. Examples of Measurement Quality Objectives (MQOs) expressed as Data Quality Limits (DQLs) are given for vascular plant cover estimates, in order to establish the reproducibility of the data. Quality control activities were used to determine the "distance" between the surveyor teams and the control team. Selected data were acquired during the training and inter-calibration courses. In particular, an index of average cover by species groups was used to evaluate the random error (CV 4%) as the dispersion around the "true values" of the control team. The systematic error in the evaluation of species composition, caused by overlooking or misidentification of species, was calculated following the pseudo-turnover rate; detailed species censuses on smaller sampling units were accepted as the pseudo-turnover which always fell below the 25% established threshold; species density scores recorded at community level (100 m(2) surface) rarely exceeded that limit.