973 resultados para plant functional traits
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Habitat suitability models, which relate species occurrences to environmental variables, are assumed to predict suitable conditions for a given species. If these models are reliable, they should relate to change in plant growth and function. In this paper, we ask the question whether habitat suitability models are able to predict variation in plant functional traits, often assumed to be a good surrogate for a species' overall health and vigour. Using a thorough sampling design, we show a tight link between variation in plant functional traits and habitat suitability for some species, but not for others. Our contrasting results pave the way towards a better understanding of how species cope with varying habitat conditions and demonstrate that habitat suitability models can provide meaningful descriptions of the functional niche in some cases, but not in others.
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Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
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Plant functional traits reflect different evolutionary responses to environmental variation, and among extant species determine the outcomes of interactions between plants and their environment, including other plant species. Thus, combining phylogenetic and trait-based information can be a powerful approach for understanding community assembly processes across a range of spatial scales. We used this approach to investigate tree community composition at Phou Khao Khouay National Park (18°14’-18°32’N; 102°38’- 102°59’E), Laos, where several distinct forest types occur in close proximity. The aim of our study was to examine patterns of plant community assembly across the strong environmental gradients evident at our site. We hypothesized that differences in tree community composition were being driven by an underlying gradient in soil conditions. Thus, we predicted that environmental filtering would predominate at the site and that the filtering would be strongest on sandier soil with low pH, as these are the conditions least favorable to plant growth. We surveyed eleven 0.25 ha (50x50 m) plots for all trees above 10 cm dbh (1221 individual trees, including 47 families, 70 genera and 123 species) and sampled soils in each plot. For each species in the community, we measured 11 commonly studied plant functional traits covering both the leaf and wood economic spectrum traits and we reconstructed a phylogenetic tree for 115 of the species in the community using rbcL and matK sequences downloaded from Genebank (other species were not available). Finally we compared the distribution of trait values and species at two scales (among plots and 10x10m subplots) to examine trait and phylogenetic community structures. Although there was strong evidence that an underlying soil gradient was determining patterns of species composition at the site, our results did not support the hypothesis that the environmental filtering dominated community assembly processes. For the measured plant functional traits there was no consistent pattern of trait dispersion across the site, either when traits were considered individually or when combined in a multivariate analysis. However, there was a significant correlation between the degree of phylogenetic dispersion and the first principle component axis (PCA1) for the soil parameters.Moreover, the more phylogenetically clustered plots were on sandier soils with lower pH. Hence, we suggest that the community assembly processes across our sitemay reflect the influence ofmore conserved traits that we did not measure. Nevertheless, our results are equivocal and other interpretations are possible. Our study illustrates some difficulties in combining trait and phylogenetic approaches that may result from the complexities of integrating spatial and evolutionary processes that vary at different scales.
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This data set describes different vegetation, soil and plant functional traits (PFTs) of 15 plant species in 30 sampling plots of an agricultural landscape in the Haean-myun catchment in South Korea. We divided the data set into two main tables, the first one includes the PFTs data of the 15 studied plant species, and the second one includes the soil and vegetation characteristics of the 30 sampling plots. For a total of 150 individuals, we measures the maximum plant height (cm) and leaf size (cm**2), which means the leaf surface area for the aboveground compartment of each individual. For the belowground compartment, we measured root horizontal width, which is the maximum horizontal spread of the root, rooting length, which is the maximum rooting depth, root diameter, which is the average root diameter of a the whole root, specific root length (SRL), which is the root length divided by the root dry mass, and root/shoot ratio, which is the root dry mass divided by the shoot dry mass. At each of the 30 studied plots, we estimated three different variables describing the vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and root density (estimated using a 30 cm x 30 cm metallic frame divided into nine 10 cm x 10 cm grids placed on the soil profile), as we calculated the total number of roots that appear in each of the nine grids and then we converted it into percentage based on the root count, following. Moreover, in each plot we estimated six different soil variables: Bulk density (g/cm**3), clay % (i.e. percentage of clay), silt % (i.e. percentage of silt), soil aggregate stability, using mean weight diameter (MWD), penetration resistance (kg/cm**2), using pocket penetrometer and soil shear vane strength (kPa).
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Fire is a globally distributed disturbance that impacts terrestrial ecosystems and has been proposed to be a global “herbivore.” Fire, like herbivory, is a top-down driver that converts organic materials into inorganic products, alters community structure, and acts as an evolutionary agent. Though grazing and fire may have some comparable effects in grasslands, they do not have similar impacts on species composition and community structure. However, the concept of fire as a global herbivore implies that fire and herbivory may have similar effects on plant functional traits. Using 22 years of data from a mesic, native tallgrass prairie with a long evolutionary history of fire and grazing, we tested if trait composition between grazed and burned grassland communities would converge, and if the degree of convergence depended on fire frequency. Additionally, we tested if eliminating fire from frequently burned grasslands would result in a state similar to unburned grasslands, and if adding fire into a previously unburned grassland would cause composition to become more similar to that of frequently burned grasslands. We found that grazing and burning once every four years showed the most convergence in traits, suggesting that these communities operate under similar deterministic assembly rules and that fire and herbivory are similar disturbances to grasslands at the trait-group level of organization. Three years after reversal of the fire treatment we found that fire reversal had different effects depending on treatment. The formerly unburned community that was then burned annually became more similar to the annually burned community in trait composition suggesting that function may be rapidly restored if fire is reintroduced. Conversely, after fire was removed from the annually burned community trait composition developed along a unique trajectory indicating hysteresis, or a time lag for structure and function to return following a change in this disturbance regime. We conclude that functional traits and species-based metrics should be considered when determining and evaluating goals for fire management in mesic grassland ecosystems.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Plant-plant interactions are driven by environmental conditions, evolutionary relationships (ER) and the functional traits of the plants involved. However, studies addressing the relative importance of these drivers are rare, but crucial to improve our predictions of the effects of plant-plant interactions on plant communities and of how they respond to differing environmental conditions. To analyze the relative importance of - and interrelationships among - these factors as drivers of plant-plant interactions, we analyzed perennial plant co-occurrence at 106 dryland plant communities established across rainfall gradients in nine countries. We used structural equation modelling to disentangle the relationships between environmental conditions (aridity and soil fertility), functional traits extracted from the literature, and ER, and to assess their relative importance as drivers of the 929 pairwise plant-plant co-occurrence levels measured. Functional traits, specifically facilitated plants' height and nurse growth form, were of primary importance, and modulated the effect of the environment and ER on plant-plant interactions. Environmental conditions and ER were important mainly for those interactions involving woody and graminoid nurses, respectively. The relative importance of different plant-plant interaction drivers (ER, functional traits, and the environment) varied depending on the region considered, illustrating the difficulty of predicting the outcome of plant-plant interactions at broader spatial scales. In our global-scale study on drylands, plant-plant interactions were more strongly related to functional traits of the species involved than to the environmental variables considered. Thus, moving to a trait-based facilitation/competition approach help to predict that: (1) positive plant-plant interactions are more likely to occur for taller facilitated species in drylands, and (2) plant-plant interactions within woody-dominated ecosystems might be more sensitive to changing environmental conditions than those within grasslands. By providing insights on which species are likely to better perform beneath a given neighbour, our results will also help to succeed in restoration practices involving the use of nurse plants. (C) 2014 Geobotanisches Institut ETH, Stiftung Ruebel. Published by Elsevier GmbH. All rights reserved.
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Understanding the relative importance of historical and environmental processes in the structure and composition of communities is one of the longest quests in ecological research. Increasingly, researchers are relying on the functional and phylogenetic β-diversity of natural communities to provide concise explanations on the mechanistic basis of community assembly and the drivers of trait variation among species. The present study investigated how plant functional and phylogenetic β-diversity change along key environmental and spatial gradients in the Western Swiss Alps. Methods Using the quadratic diversity measure based on six functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height (H), leaf carbon content (C), leaf nitrogen content (N), and leaf carbon to nitrogen content (C/N) alongside a species-resolved phylogenetic tree, we relate variations in climate, spatial geographic, land use and soil gradients to plant functional and phylogenetic turnover in mountain communities of the Western Swiss Alps. Important findings Our study highlights two main points. First, climate and land use factors play an important role in mountain plant community turnover. Second, the overlap between plant functional and phylogenetic turnover along these gradients correlates with the low phylogenetic signal in traits, suggesting that in mountain landscapes, trait lability is likely an important factor in driving plant community assembly. Overall, we demonstrate the importance of climate and land use factors in plant functional and phylogenetic community turnover, and provide valuable complementary insights into understanding patterns of β-diversity along several ecological gradients.
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The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.
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We assessed the potential for using optical functional types as effective markers to monitor changes in vegetation in floodplain meadows associated with changes in their local environment. Floodplain meadows are challenging ecosystems for monitoring and conservation because of their highly biodiverse nature. Our aim was to understand and explain spectral differences among key members of floodplain meadows and also characterize differences with respect to functional traits. The study was conducted on a typical floodplain meadow in UK (MG4-type, mesotrophic grassland type 4, according to British National Vegetation Classification). We compared two approaches to characterize floodplain communities using field spectroscopy. The first approach was sub-community based, in which we collected spectral signatures for species groupings indicating two distinct eco-hydrological conditions (dry and wet soil indicator species). The other approach was “species-specific”, in which we focused on the spectral reflectance of three key species found on the meadow. One herb species is a typical member of the MG4 floodplain meadow community, while the other two species, sedge and rush, represent wetland vegetation. We also monitored vegetation biophysical and functional properties as well as soil nutrients and ground water levels. We found that the vegetation classes representing meadow sub-communities could not be spectrally distinguished from each other, whereas the individual herb species was found to have a distinctly different spectral signature from the sedge and rush species. The spectral differences between these three species could be explained by their observed differences in plant biophysical parameters, as corroborated through radiative transfer model simulations. These parameters, such as leaf area index, leaf dry matter content, leaf water content, and specific leaf area, along with other functional parameters, such as maximum carboxylation capacity and leaf nitrogen content, also helped explain the species’ differences in functional dynamics. Groundwater level and soil nitrogen availability, which are important factors governing plant nutrient status, were also found to be significantly different for the herb/wetland species’ locations. The study concludes that spectrally distinguishable species, typical for a highly biodiverse site such as a floodplain meadow, could potentially be used as target species to monitor vegetation dynamics under changing environmental conditions.
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The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community- weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.
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Question: What plant properties might define plant functional types (PFTs) for the analysis of global vegetation responses to climate change, and what aspects of the physical environment might be expected to predict the distributions of PFTs? Methods: We review principles to explain the distribution of key plant traits as a function of bioclimatic variables. We focus on those whole-plant and leaf traits that are commonly used to define biomes and PFTs in global maps and models. Results: Raunkiær's plant life forms (underlying most later classifications) describe different adaptive strategies for surviving low temperature or drought, while satisfying requirements for reproduction and growth. Simple conceptual models and published observations are used to quantify the adaptive significance of leaf size for temperature regulation, leaf consistency for maintaining transpiration under drought, and phenology for the optimization of annual carbon balance. A new compilation of experimental data supports the functional definition of tropical, warm-temperate, temperate and boreal phanerophytes based on mechanisms for withstanding low temperature extremes. Chilling requirements are less well quantified, but are a necessary adjunct to cold tolerance. Functional traits generally confer both advantages and restrictions; the existence of trade-offs contributes to the diversity of plants along bioclimatic gradients. Conclusions: Quantitative analysis of plant trait distributions against bioclimatic variables is becoming possible; this opens up new opportunities for PFT classification. A PFT classification based on bioclimatic responses will need to be enhanced by information on traits related to competition, successional dynamics and disturbance.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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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.