Dataset Information

Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests.

ABSTRACT: BACKGROUND AND AIMS: When ecologically important plant traits are correlated they may be said to constitute an ecological 'strategy' dimension. Through identifying these dimensions and understanding their inter-relationships we gain insight into why particular trait combinations are favoured over others and into the implications of trait differences among species. Here we investigated relationships among several traits, and thus the strategy dimensions they represented, across 2134 woody species from seven Neotropical forests. METHODS: Six traits were studied: specific leaf area (SLA), the average size of leaves, seed and fruit, typical maximum plant height, and wood density (WD). Trait relationships were quantified across species at each individual forest as well as across the dataset as a whole. 'Phylogenetic' analyses were used to test for correlations among evolutionary trait-divergences and to ascertain whether interspecific relationships were biased by strong taxonomic patterning in the traits. KEY RESULTS: The interspecific and phylogenetic analyses yielded congruent results. Seed and fruit size were expected, and confirmed, to be tightly related. As expected, plant height was correlated with each of seed and fruit size, albeit weakly. Weak support was found for an expected positive relationship between leaf and fruit size. The prediction that SLA and WD would be negatively correlated was not supported. Otherwise the traits were predicted to be largely unrelated, being representatives of putatively independent strategy dimensions. This was indeed the case, although WD was consistently, negatively related to leaf size. CONCLUSIONS: The dimensions represented by SLA, seed/fruit size and leaf size were essentially independent and thus conveyed largely independent information about plant strategies. To a lesser extent the same was true for plant height and WD. Our tentative explanation for negative WD-leaf size relationships, now also known from other habitats, is that the traits are indirectly linked via plant hydraulics.

SUBMITTER: Wright IJ

PROVIDER: S-EPMC2802905 | biostudies-other | 2007 May

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests.

Wright Ian J IJ Ackerly David D DD Bongers Frans F Harms Kyle E KE Ibarra-Manriquez Guillermo G Martinez-Ramos Miguel M Mazer Susan J SJ Muller-Landau Helene C HC Paz Horacio H Pitman Nigel C A NC Poorter Lourens L Silman Miles R MR Vriesendorp Corine F CF Webb Cam O CO Westoby Mark M Wright S Joseph SJ

Annals of botany. 20060404 5

<h4>Background and aims</h4>When ecologically important plant traits are correlated they may be said to constitute an ecological 'strategy' dimension. Through identifying these dimensions and understanding their inter-relationships we gain insight into why particular trait combinations are favoured over others and into the implications of trait differences among species. Here we investigated relationships among several traits, and thus the strategy dimensions they represented, across 2134 woody ...[more]

PMID: 16595553

Similar Datasets

Project description:Plant structural and biochemical traits are frequently used to characterise the life history of plants. Although some common patterns of trait covariation have been identified, recent studies suggest these patterns of covariation may differ with growing location and/or plant functional type (PFT). Mediterranean forest tree/shrub species are often divided into three PFTs based on their leaf habit and form, being classified as either needleleaf evergreen (Ne), broadleaf evergreen (Be), or broadleaf deciduous (Bd). Working across 61 mountainous Mediterranean forest sites of contrasting climate and soil type, we sampled and analysed 626 individuals in order to evaluate differences in key foliage trait covariation as modulated by growing conditions both within and between the Ne, Be, and Bd functional types. We found significant differences between PFTs for most traits. When considered across PFTs and by ignoring intraspecific variation, three independent functional dimensions supporting the Leaf-Height-Seed framework were identified. Some traits illustrated a common scaling relationship across and within PFTs, but others scaled differently when considered across PFTs or even within PFTs. For most traits much of the observed variation was attributable to PFT identity and not to growing location, although for some traits there was a strong environmental component and considerable intraspecific and residual variation. Nevertheless, environmental conditions as related to water availability during the dry season and to a smaller extend to soil nutrient status and soil texture, clearly influenced trait values. When compared across species, about half of the trait-environment relationships were species-specific. Our study highlights the importance of the ecological scale within which trait covariation is considered and suggests that at regional to local scales, common trait-by-trait scaling relationships should be treated with caution. PFT definitions by themselves can potentially be an important predictor variable when inferring one trait from another. These findings have important implications for local scale dynamic vegetation models.

Project description:Understanding the trait-environment relationships has been a core ecological research topic in the face of global climate change. However, the strength of trait-environment relationships at the local and regional scales in temperate forests remains poorly known. In this study, we investigated the local and regional scale forest plots of the natural broad-leaved temperate forest in northeastern China, to assess what extent community-level trait composition depends on environmental drivers across spatial scales. We measured five key functional traits (leaf area, specific leaf area, leaf carbon content, leaf nitrogen content, and wood density) of woody plant, and quantified functional compositions of communities by calculating the "specific" community-weighted mean (CWM) traits. The sum of squares decomposition method was used to quantify the relative contribution of intraspecific trait variation to total trait variation among communities. Multiple linear regression model was then used to explore the community-level trait-environment relationships. We found that (i) intraspecific trait variation contributed considerably to total trait variation and decreased with the spatial scale from local to regional; (ii) functional composition was mainly affected by soil and topography factors at the local scale and climate factor at the regional scale, while explaining that variance of environment factors were decreased with increasing spatial scale; and (iii) the main environment driver of functional composition was varied depending on the traits and spatial scale. This work is one of the few multi-scale analyses to investigate the environmental drivers of community functional compositions. The extent of intraspecific trait variation and the strength of trait-environment relationship showed consistent trends with increasing spatial scale. Our findings demonstrate the influence of environmental filtering on both local- and regional-scale temperate forest communities, and contribute to a comprehensive understanding of trait-environment relationships across spatial scales.

Project description:Seed size is a key trait for understanding and predicting ecological processes in a plant community. In a tropical forest, trees and lianas are major components driving ecosystem function and biogeochemical processes. However, seed ecological research on both components remains limited, particularly phylogenetic patterns and relationships with other traits. Here, we compiled a unique dataset of seed size (seed mass and geometrical size metrics) based on collections of more than 5,200 seeds of 196 woody plant species, covering >98 and 70% of tree and liana stems, respectively, located on a 30-ha plot in a tropical evergreen forest in central Thailand. We aimed to (1) develop allometric equations among seed size metrics to predict seed mass; (2) examine phylogenetic influence on seed size variation; and (3) examine relationships among seed traits and several other functional plant traits. Our allometric equations relating seed mass, seed volume, and width were well-fitted with data (R 2 = 0.94, 0.87 respectively). A phylogenetic signal test found that seed size was randomly distributed across the phylogeny. To study the functional trait relationships, we separately tested seed size data of the tree and liana communities (146 and 50 species, respectively), against mean body size of frugivores, successional niches, leaf, and structural traits. For the tree community, seed size was significantly related to mean body size of frugivores, which we believe is a basic driver of seed size because it is related to the gape width affecting dispersal effectiveness. Nearly all leaf traits were significantly positively correlated with seed size (p < 0.03). The significant positive correlation of leaf area and greenness suggested the high-energy demand of large-seeded species. We found a strong positive correlation between seed size and leaf toughness, suggesting a coordination between seed size and leaf defense. However, all these patterns disappeared in the same analysis applied to the liana community. Liana seed size variation was lower than that of trees, perhaps because lianas grow in relatively more uniform conditions in the forest canopy. Frugivore size was the strongest driver of seed size variation. Our study shows a surprising contrast between trees and lianas that is worth further investigation.

Project description:Ecological theory differentiates rainforest and open vegetation in many regions as functionally divergent alternative stable states with transitional (ecotonal) vegetation between the two forming transient unstable states. This transitional vegetation is of considerable significance, not only as a test case for theories of vegetation dynamics, but also because this type of vegetation is of major economic importance, and is home to a suite of species of conservation significance, including the world's tallest flowering plants. We therefore created predictions of patterns in plant functional traits that would test the alternative stable states model of these systems. We measured functional traits of 128 trees and shrubs across tropical and temperate rainforest - open vegetation transitions in Australia, with giant eucalypt forests situated between these vegetation types. We analysed a set of functional traits: leaf carbon isotopes, leaf area, leaf mass per area, leaf slenderness, wood density, maximum height and bark thickness, using univariate and multivariate methods. For most traits, giant eucalypt forest was similar to rainforest, while rainforest, particularly tropical rainforest, was significantly different from the open vegetation. In multivariate analyses, tropical and temperate rainforest diverged functionally, and both segregated from open vegetation. Furthermore, the giant eucalypt forests overlapped in function with their respective rainforests. The two types of giant eucalypt forests also exhibited greater overall functional similarity to each other than to any of the open vegetation types. We conclude that tropical and temperate giant eucalypt forests are ecologically and functionally convergent. The lack of clear functional differentiation from rainforest suggests that giant eucalypt forests are unstable states within the basin of attraction of rainforest. Our results have important implications for giant eucalypt forest management.

Dataset Information

Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests.

Publications

Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets