Dataset Information

Geological substrates shape tree species and trait distributions in African moist forests.

ABSTRACT:

Background

Understanding the factors that shape the distribution of tropical tree species at large scales is a central issue in ecology, conservation and forest management. The aims of this study were to (i) assess the importance of environmental factors relative to historical factors for tree species distributions in the semi-evergreen forests of the northern Congo basin; and to (ii) identify potential mechanisms explaining distribution patterns through a trait-based approach.

Methodology/principal findings

We analyzed the distribution patterns of 31 common tree species in an area of more than 700,000 km(2) spanning the borders of Cameroon, the Central African Republic, and the Republic of Congo using forest inventory data from 56,445 0.5-ha plots. Spatial variation of environmental (climate, topography and geology) and historical factors (human disturbance) were quantified from maps and satellite records. Four key functional traits (leaf phenology, shade tolerance, wood density, and maximum growth rate) were extracted from the literature. The geological substrate was of major importance for the distribution of the focal species, while climate and past human disturbances had a significant but lesser impact. Species distribution patterns were significantly related to functional traits. Species associated with sandy soils typical of sandstone and alluvium were characterized by slow growth rates, shade tolerance, evergreen leaves, and high wood density, traits allowing persistence on resource-poor soils. In contrast, fast-growing pioneer species rarely occurred on sandy soils, except for Lophira alata.

Conclusions/significance

The results indicate strong environmental filtering due to differential soil resource availability across geological substrates. Additionally, long-term human disturbances in resource-rich areas may have accentuated the observed patterns of species and trait distributions. Trait differences across geological substrates imply pronounced differences in population and ecosystem processes, and call for different conservation and management strategies.

SUBMITTER: Fayolle A

PROVIDER: S-EPMC3419707 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Geological substrates shape tree species and trait distributions in African moist forests.

Fayolle Adeline A Engelbrecht Bettina B Freycon Vincent V Mortier Frédéric F Swaine Michael M Réjou-Méchain Maxime M Doucet Jean-Louis JL Fauvet Nicolas N Cornu Guillaume G Gourlet-Fleury Sylvie S

PloS one 20120815 8

<h4>Background</h4>Understanding the factors that shape the distribution of tropical tree species at large scales is a central issue in ecology, conservation and forest management. The aims of this study were to (i) assess the importance of environmental factors relative to historical factors for tree species distributions in the semi-evergreen forests of the northern Congo basin; and to (ii) identify potential mechanisms explaining distribution patterns through a trait-based approach.<h4>Method ...[more]

PMID: 22905127

Similar Datasets

Project description:Abstract Understanding the drivers of trait selection is critical for resolving community assembly processes. Here, we test the importance of environmental filtering and trait covariance for structuring the functional traits of understory herbaceous communities distributed along a natural environmental resource gradient that varied in soil moisture, temperature, and nitrogen availability, produced by different topographic positions in the southern Appalachian Mountains. To uncover potential differences in community?level trait responses to the resource gradient, we quantified the averages and variances of both abundance?weighted and unweighted values for six functional traits (vegetative height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, and leaf ?13C) using 15 individuals of each of the 108 species of understory herbs found at two sites in the southern Appalachians of western North Carolina, USA. Environmental variables were better predictors of weighted than unweighted community?level average trait values for all but height and leaf N, indicating strong environmental filtering of plant abundance. Community?level variance patterns also showed increased convergence of abundance?weighted traits as resource limitation became more severe. Functional trait covariance patterns based on weighted averages were uniform across the gradient, whereas coordination based on unweighted averages was inconsistent and varied with environmental context. In line with these results, structural equation modeling revealed that unweighted community?average traits responded directly to local environmental variation, whereas weighted community?average traits responded indirectly to local environmental variation through trait coordination. Our finding that trait coordination is more important for explaining the distribution of weighted than unweighted average trait values along the gradient indicates that environmental filtering acts on multiple traits simultaneously, with abundant species possessing more favorable combinations of traits for maximizing fitness in a given environment. Understanding the drivers of trait selection is critical for resolving community assembly processes. Our finding that trait coordination is more important for explaining the distribution of weighted than unweighted average trait values along the gradient indicates that environmental filtering acts on multiple traits simultaneously, with abundant species possessing more favorable combinations of traits for maximizing fitness in a given environment.

Project description:The role of competition for light among plants has long been recognised at local scales, but its importance for plant species distributions at larger spatial scales has generally been ignored. Tree cover modifies the local abiotic conditions below the canopy, notably by reducing light availability, and thus, also the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains, by affecting colonisation probabilities and local extinction risks of herbs and shrubs. To assess the effect of tree cover at both the plot- and landscape-grain sizes (approximately 10-m and 1-km), we fit Generalised Linear Models (GLMs) for the plot-level distributions of 960 species of herbs and shrubs using 6,935 vegetation plots across the European Alps. We ran four models with different combinations of variables (climate, soil and tree cover) at both spatial grains for each species. We used partial regressions to evaluate the independent effects of plot- and landscape-grain tree cover on plot-level plant communities. Finally, the effects on species-specific elevational range limits were assessed by simulating a removal experiment comparing the species distributions under high and low tree cover. Accounting for tree cover improved the model performance, with the probability of the presence of shade-tolerant species increasing with increasing tree cover, whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both the plot and landscape spatial grains, albeit most strongly at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-level plant communities. With high tree cover, shade-intolerant species exhibited narrower elevational ranges than with low tree cover whereas shade-tolerant species showed wider elevational ranges at both limits. These findings suggest that forecasts of climate-related range shifts for herb and shrub species may be modified by tree cover dynamics.

Dataset Information

Geological substrates shape tree species and trait distributions in African moist forests.

Background

Methodology/principal findings

Conclusions/significance

Publications

Geological substrates shape tree species and trait distributions in African moist forests.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets