17 research outputs found

    Interactions between all pairs of neighboring trees in 16 forests worldwide reveal details of unique ecological processes in each forest, and provide windows into their evolutionary histories

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    When Darwin visited the Galapagos archipelago, he observed that, in spite of the islands’ physical similarity, members of species that had dispersed to them recently were beginning to diverge from each other. He postulated that these divergences must have resulted primarily from interactions with sets of other species that had also diverged across these otherwise similar islands. By extrapolation, if Darwin is correct, such complex interactions must be driving species divergences across all ecosystems. However, many current general ecological theories that predict observed distributions of species in ecosystems do not take the details of between-species interactions into account. Here we quantify, in sixteen forest diversity plots (FDPs) worldwide, highly significant negative density-dependent (NDD) components of both conspecific and heterospecific between-tree interactions that affect the trees’ distributions, growth, recruitment, and mortality. These interactions decline smoothly in significance with increasing physical distance between trees. They also tend to decline in significance with increasing phylogenetic distance between the trees, but each FDP exhibits its own unique pattern of exceptions to this overall decline. Unique patterns of between-species interactions in ecosystems, of the general type that Darwin postulated, are likely to have contributed to the exceptions. We test the power of our null-model method by using a deliberately modified data set, and show that the method easily identifies the modifications. We examine how some of the exceptions, at the Wind River (USA) FDP, reveal new details of a known allelopathic effect of one of the Wind River gymnosperm species. Finally, we explore how similar analyses can be used to investigate details of many types of interactions in these complex ecosystems, and can provide clues to the evolution of these interactions

    Improved curvature estimation for watershed segmentation of 3-dimensional meshes. manuscript

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    Segmentation of a 3-dimensional (3D) polygonal mesh is a method of breaking the mesh down into \meaningful " connected subsets of vertices called regions. The method used here is based on the watershed segmentation scheme which appears prominently in the image segmentation literature and was later applied to the 3D segmentation problem. The watershed algorithm is based on a scalar value (curvature) assigned to every mesh vertex which purports to capture some essence of the local mesh shape. Accuracy of the curvature estimate at mesh vertices is critical to the quality of the resulting segmentation. The basis of this paper is one such watershed based 3D mesh segmentation scheme, described in [17], wherein two discrete curvature estimation schemes were used, i.e. the curvature was extracted directly from the mesh geometry. This paper considerably improves on the quality of segmentation in the original paper primarily by applying more accurate and robust curvature estimation techniques. The results are illustrated on data sets which are inherently noisy, such as the ones obtained from laser digitizers.

    Multidimensional tree niches in a tropical dry forest

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    The extent to which interspecific niche differences structure plant communities is highly debated, with extreme viewpoints ranging from fine-scaled niche partitioning, where every species in the community is specialized to a distinct niche, to neutrality, where species have no niche or fitness differences. However, there exists a default position wherein niches of species in a community are determined by their evolutionary and biogeographic histories, irrespective of other species within the community. According to this viewpoint, a broad range of pair-wise niche overlaps-from completely overlapping to completely distinct-are expected in any community without the need to invoke interspecific interactions. We develop a method that can test for both habitat associations and niche differences along an arbitrary number of spatial and temporal niche dimensions and apply it to a 24-yr data set of the eight dominant woody-plant species (representing 84% and 76% of total community abundance and basal area, respectively) from a 50-ha permanent plot in a southern Indian tropical dry forest, using edaphic, topographic, and precipitation variables as niche axes. Species separated into two broad groups in niche space-one consisting of three canopy species and the other of a canopy species and four understory species-along axes that corresponded mainly to variation in soil P, Al and a topographic index of wetness. Species within groups tended to have significantly greater niche overlap than expected by chance. Community-wide niche overlap in spatial and temporal niche axes was never smaller than expected by chance. Species-habitat associations were neither necessary nor sufficient preconditions for niche differences to be present. Our results suggest that this tropical dry-forest community consists of several tree species with broadly overlapping niches, and where significant niche differences do exist, they are not readily interpretable as evidence for niche differentiation. We argue, based on a survey of the literature, that many of the observed niche differences in tropical forests are more parsimoniously viewed as autecological differences between species that exist independently of interspecific interactions

    A digital herbarium for the flora of Karnataka

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    A herbarium-based database (virtual herbarium) is a referral system for plants that maximizes the usefulness of the collections. The information content of such a database is essentially built on the voucher specimens that the herbarium has in its care. The present article reports on the construction of a `virtual herbarium' for the state-wide collection of flowering plants in the Herbarium JCB housed at the Centre for Ecological Sciences, Indian Institute of Science, Bangalore, that is expected to be launched soon. The taxonomic data on each species include all information presented on the herbarium specimen label, namely species name, author citation, sub-species if any, variety if any, family, subfamily, collection number, locations, date of collection, habitat and the collector's name. The data further comprise `flora' in which the species are described. Additional information includes the nomenclature update according to `The Plant List', a detailed description, phenology, species distribution, threat status and comments on any special features of the taxon. The live images of the species provided in the database form an information synergy on the species. This initiative is the first of its kind for herbaria in peninsular India

    And yet it shrinks: a novel method for correcting bias in forest tree growth estimates caused by water-induced fluctuations

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    Accuracy in tree woody growth estimates is important to global carbon budget estimation and climate-change science. Tree growth in permanent sampling plots (PSPs) is commonly estimated by measuring stem diameter changes, but this method is susceptible to bias resulting from water-induced reversible stem shrinkage. In the absence of bias correction, temporal variability in growth is likely to be overestimated and incorrectly attributed to fluctuations in resource availability, especially in forests with high seasonal and inter-annual variability in water. We propose and test a novel approach for estimating and correcting this bias at the community level. In a 50-ha PSP from a seasonally dry tropical forest in southern India, where tape measurements have been taken every four years from 1988 to 2012, for nine trees we estimated bias due to reversible stem shrinkage as the difference between woody growth measured using tree rings and that estimated from tape. We tested if the bias estimated from these trees could be used as a proxy to correct bias in tape-based growth estimates at the PSP scale. We observed significant shrinkage-related bias in the growth estimates of the nine trees in some censuses. This bias was strongly linearly related to tape-based growth estimates at the level of the PSP, and could be used as a proxy. After bias was corrected, the temporal variance in growth rates of the PSP decreased, while the effect of exceptionally dry or wet periods was retained, indicating that at least a part of the temporal variability arose from reversible shrinkage-related bias. We also suggest that the efficacy of the bias correction could be improved by measuring the proxy on trees that belong to different size classes and census timing, but not necessarily to different species. Our approach allows for reanalysis - and possible reinterpretation of temporal trends in tree growth, above ground biomass change, or carbon fluxes in forests, and their relationships with resource availability in the context of climate change

    Spatial maps of topographic, vegetation and fire variables in the 50-ha plot.

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    <p>elev = elevation; slope = slope inclination; east = slope aspect (“eastness”); north = slope aspect (“northness”); curv = curvature; insol = insolation; twi = topographic wetness index; ba.fabaceae = basal area of woody Fabaceae species; fire = fire frequency (times burnt during 1988–2004). Elevation is in m; slope is in radians; insolation is in kWhm<sup>-2</sup>; fire is in 17 y<sup>-1</sup>.</p

    Summary of topographic and vegetation predictor variables used in soil variable regressions.

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    <p>Summary of topographic and vegetation predictor variables used in soil variable regressions.</p

    Spatial maps of soil properties sampled at 1250 points (centres of 20x20 m grid cells) in the 50-ha plot.

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    <p>A rainfall event modified soil moisture conditions during sampling; hence only soil moisture data prior to the event (left part of the plot) are shown.</p

    Correlations (Pearson’s r) between soil variable measurements from the 50-ha plot.

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    <p>Correlations (Pearson’s r) between soil variable measurements from the 50-ha plot.</p
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