Resource‐based habitat associations in a neotropical liana community

Summary 1. Lianas are a conspicuous element of many tropical forests, accounting for up to 40% of woody stem density and 20% of species richness in seasonal forests. However, lianas have seldom been surveyed at sufficiently large spatial scales to allow an assessment of the importance of habitat variables in structuring liana communities. 2. We compare the association patterns of 82 liana species and an equivalent sample of tree species on the 50 ha Forest Dynamics Project plot on Barro Colorado Island, Panama, with topographic habitat variables (high and low plateau, slope, swamp and streamside), and thirteen mapped soil chemical variables. In addition, we test for liana species associations with canopy disturbance using a canopy height map of the plot generated using light detection and ranging. 3. For all liana species combined, densities differed among topographic habitat types in the plot, with significantly higher densities on the seasonally drier lower plateau habitat (1044 individuals ha−1) than the moister slope habitat (729 individuals ha−1). Lianas were also significantly more abundant than expected in areas with low canopy height. 4. The proportion of liana species associated with one or more topographic habitat variables (44%) was significantly lower than that for trees (66%). Similarly, liana species were significantly less frequently associated with PC axes derived from soil chemical variables (21%) than trees (52%). The majority of liana species (63%) were significantly associated with areas of the plot with low canopy height reflecting an affinity for treefall gaps. 5. Synthesis. The habitat associations detected here suggest that liana density is associated primarily with canopy disturbance, and to a lesser extent with topography and soil chemistry. Relative to trees, few liana species were associated with local variation in topography and soil chemistry, suggesting that nutrient availability exerts only weak effects on liana community composition compared to trees. Results from this study support the contention that increases in forest disturbance rates are a driver of recently observed increases in liana abundance and biomass in neotropical forests

Liana Abundance, Diversity, and Distribution on Barro Colorado Island, Panama

Lianas are a key component of tropical forests; however, most surveys are too small to accurately quantify liana community composition, diversity, abundance, and spatial distribution – critical components for measuring the contribution of lianas to forest processes. In 2007, we tagged, mapped, measured the diameter, and identified all lianas ≥1 cm rooted in a 50-ha plot on Barro Colorado Island, Panama (BCI). We calculated liana density, basal area, and species richness for both independently rooted lianas and all rooted liana stems (genets plus clones). We compared spatial aggregation patterns of liana and tree species, and among liana species that varied in the amount of clonal reproduction. We also tested whether liana and tree densities have increased on BCI compared to surveys conducted 30-years earlier. This study represents the most comprehensive spatially contiguous sampling of lianas ever conducted and, over the 50 ha area, we found 67,447 rooted liana stems comprising 162 species. Rooted lianas composed nearly 25% of the woody stems (trees and lianas), 35% of woody species richness, and 3% of woody basal area. Lianas were spatially aggregated within the 50-ha plot and the liana species with the highest proportion of clonal stems more spatially aggregated than the least clonal species, possibly indicating clonal stem recruitment following canopy disturbance. Over the past 30 years, liana density increased by 75% for stems ≥1 cm diameter and nearly 140% for stems ≥5 cm diameter, while tree density on BCI decreased 11.5%; a finding consistent with other neotropical forests. Our data confirm that lianas contribute substantially to tropical forest stem density and diversity, they have highly clumped distributions that appear to be driven by clonal stem recruitment into treefall gaps, and they are increasing relative to trees, thus indicating that lianas will play a greater role in the future dynamics of BCI and other neotropical forests

Soil resources and topography shape local tree community structure in tropical forests

Both habitat filtering and dispersal limitation influence the compositional structure of forest communities, but previous studies examining the relative contributions of these processes with variation partitioning have primarily used topography to represent the influence of the environment. Here, we bring together data on both topography and soil resource variation within eight large (24-50 ha) tropical forest plots, and use variation partitioning to decompose community compositional variation into fractions explained by spatial, soil resource and topographic variables. Both soil resources and topography account for significant and approximately equal variation in tree community composition (9-34% and 5-29%, respectively), and all environmental variables together explain 13-39% of compositional variation within a plot. A large fraction of variation (19-37%) was spatially structured, yet unexplained by the environment, suggesting an important role for dispersal processes and unmeasured environmental variables. For the majority of sites, adding soil resource variables to topography nearly doubled the inferred role of habitat filtering, accounting for variation in compositional structure that would previously have been attributable to dispersal. Our results, illustrated using a new graphical depiction of community structure within these plots, demonstrate the importance of small-scale environmental variation in shaping local community structure in diverse tropical forests around the globe. © 2012 The Author(s) Published by the Royal Society. All rights reserved

Estimating Vegetation Beta Diversity from Airborne Imaging Spectroscopy and Unsupervised Clustering

Airborne remote sensing has an important role to play in mapping and monitoring biodiversity over large spatial scales. Techniques for applying this technology to biodiversity mapping have focused on remote species identification of individual crowns; however, this requires collection of a large number of crowns to train a classifier, which may limit the usefulness of this approach in many study regions. Based on the premise that the spectral variation among sites is related to their ecological dissimilarity, we asked whether it is possible to estimate the beta diversity, or turnover in species composition, among sites without the use of training data. We evaluated alternative methods using simulated communities constructed from the spectra of field-identified tree and shrub crowns from an African savanna. A method based on the k-means clustering of crown spectra produced beta diversity estimates (measured as Bray-Curtis dissimilarity) among sites with an average pairwise correlation of ~0.5 with the true beta diversity, compared to an average correlation of ~0.8 obtained by a supervised species classification approach. When applied to savanna landscapes, the unsupervised clustering method produced beta diversity estimates similar to those obtained from supervised classification. The unsupervised method proposed here can be used to estimate the spatial structure of species turnover in a landscape when training data (e.g., tree crowns) are unavailable, providing top-down information for science, conservation and ecosystem management applications

Savanna tree height class distribution under different fire management histories

Tree height class and species data collected with airborne LiDAR and imaging spectroscopy across two savanna hill slopes with different fire histories in Kruger National Park, South Africa. Tree heights are in meters. Tree IDs are a random selection of 1000 individuals per species per fire history treatment. Airborne data was collected in April 2008

Data from: Demographic legacies of fire history in an African savanna

Fire is a key determinant of woody vegetation structure in savanna ecosystems, acting both independently and synergistically through interactions with herbivores. Fire influences biodiversity and ecological functioning, but quantifying its effects on woody structure is challenging at both species and community scales. Deeper insight into fire effects, and fire-herbivore interactions, can be gained through the examination of species-specific demographic and dynamic changes occurring across areas with different fire regimes in the presence of large herbivores. We used the Carnegie Airborne Observatory (an integrated LiDAR and imaging spectroscopy system) to map woody tree structure, species and dynamics over a four-year interval across two adjacent savanna landscapes with contrasting fire histories in Kruger National Park, South Africa. A history of higher fire frequency was associated with reduced woody canopy cover (17% vs. 23%) and an increased overall rate of treefall (27% vs. 18%). The landscape with a history of higher fire frequency displayed a shift in woody canopy height distribution from a unimodal curve to a bimodal pattern at the community scale, with large reductions in height classes < 7 m. Differences in tree height distributions and treefall rates across sites were underpinned by species-specific responses to fire frequency. Acacia nigrescens displayed the highest rates of treefall, most likely related to elephant activity, with losses exceeding 40% in the 6-9 m height classes. Synthesis. Our findings indicate that fire history imparts demographic legacies not only on vegetation structure, but also on current vegetation dynamics. Current treefall rates of certain tree species are exacerbated by a history of higher fire frequency. Species-specific and context-conscious investigations are critical for elucidating the driving mechanisms underlying broader community patterns

Tree Foliar Chemistry in an African Savanna and Its Relation to Life History Strategies and Environmental Filters

<div><p>Understanding the relative importance of environment and life history strategies in determining leaf chemical traits remains a key objective of plant ecology. We assessed 20 foliar chemical properties among 12 African savanna woody plant species and their relation to environmental variables (hillslope position, precipitation, geology) and two functional traits (thorn type and seed dispersal mechanism). We found that combinations of six leaf chemical traits (lignin, hemi-cellulose, zinc, boron, magnesium, and manganese) predicted the species with 91% accuracy. Hillslope position, precipitation, and geology accounted for only 12% of the total variance in these six chemical traits. However, thorn type and seed dispersal mechanism accounted for 46% of variance in these chemical traits. The physically defended species had the highest concentrations of hemi-cellulose and boron. Species without physical defense had the highest lignin content if dispersed by vertebrates, but threefold lower lignin content if dispersed by wind. One of the most abundant woody species in southern Africa, <i>Colophospermum mopane</i>, was found to have the highest foliar concentrations of zinc, phosphorus, and δ¹³C, suggesting that zinc chelation may be used by this species to bind metallic toxins and increase uptake of soil phosphorus. Across all studied species, taxonomy and physical traits accounted for the majority of variability in leaf chemistry.</p></div

Classification and regression tree (CART) predicting species using chemical properties.

<p>All 20 foliar chemical and elemental properties measured for each tree sample (n = 238) were used as input to the CART algorithm. The algorithm selected six properties while retaining 91% classification accuracy. This analysis illustrates the minimum number of foliar chemicals needed to classify species and the relative importance of each trait in minimizing error in the classification (in descending order, from top to bottom). The equation above each branch indicates the chemical concentration used to perform the split (e.g. “Lig < 14” means samples with lignin concentrations less than 14% by mass). The units of concentration varied for each trait as follows (all were on a mass basis): Lig = lignin (%), Hmcl = hemi-cellulose (%), Zn = zinc (μg g^-1), B = boron (μg g^-1), Mg = magnesium (%), Mn = manganese (μg g^-1). Numbers below species indicate the number of correct classifications divided by the total number of samples for that species. See text for key to species abbreviations.</p

Nonmetric Multidimensional Scaling (NMDS) scatter plot showing dissimilarity in foliar chemistry between species.

<p>Points represent individual trees (n = 219), with 20 foliar chemical properties measured per tree. These properties were transformed using NMDS to two axes to illustrate the dissimilarity in foliar chemistry between species.</p