Neighbor Density Research Articles

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

Nest relocation and excavation in the Florida harvester ant, Pogonomyrmex badius.

The Florida harvester ant (Pogonomyrmex badius) excavates deep nests in the sandy soils of the Gulf and Atlantic coastal plains. Nest relocations of over 400 colonies in a north Florida coastal plains pine forest were tracked and mapped from 2010 to 2013. Individual colonies varied from one move in two years to four times a year, averaging about one per year. Almost all moves occurred between May and November peaking in July when more than 1% of the colonies moved per day. Move directions were random, and averaged 4 m, with few moves exceeding 10 m. Distance moved was not related to colony size. Over multiple moves, paths were random walks around the original nest location. Relocation is probably intrinsic to the life history of this species, and the causes of relocation remain obscure— the architecture of old and new nests was very similar, and neither the forest canopy nor the density or size of neighbors was correlated with relocation. Monitoring entire relocations (n = 20) showed that they were usually completed in 4 to 6 days. Moves were diurnal, peaking in the mornings and afternoons dipping during mid-day, and ceasing before sundown. Workers excavated the new nest continuously during the daytime throughout the move and beyond. A minority of workers carried seeds, charcoal and brood, with seeds being by far the most common burden. The proportion of burdened workers increased throughout the move. Measured from year to year, small colonies gained size and large ones lost it. Colonies moving more than once in two years lost more size than those moving less often, suggesting that moving may bear a fitness cost. Colony relocation is a dramatic and consistent feature of the life history of the Florida harvester ant, inviting inquiry into its proximal and ultimate causes.

Slope Collapse Prediction Using Bayesian Framework with K-Nearest Neighbor Density Estimation: Case Study in Taiwan

AbstractSlope failures across mountain roads can damage man-made structures, interrupt traffic, and give rise to fatal accidents. Disastrous consequences of these hazards necessitate the approach for predicting their occurrences. In practice, slope collapse prediction can be formulated as a classification problem with two class labels: collapse and noncollapse. This study aims at proposing a novel approach for slope collapse assessment. The newly established method integrates the Bayesian framework and the K-nearest neighbor density estimation technique. The Bayesian framework is employed to achieve probabilistic slope stability estimations. Meanwhile, the K-nearest neighbor technique is a nonparametric approach to approximate the conditional probability density functions. In addition, a database that contains 211 slope evaluation samples has been collected in the Taiwan Provincial Highway Nos. 18 and 21 is used to construct and verify the slope assessment model. Experimental results point out that the pr...

Effects of interspecific alien versus intraspecific native competition on growth of native woody plants

The success of invasive plants and their impacts on community structure are commonly explained by referring to their supposed higher competitive ability. However, invasive plants do not consistently outperform native species; and the role of competition may also depend on the stage of the invasion process. This study investigated competitive effects of woody alien plant species at an early stage of invasion (Archontophoenix cunninghamiana and Psidium guajava) on closely related New Zealand native species of similar life form (Rhopalostylis sapida and Lophomyrtus bullata, respectively) at several points over time in a shadehouse experiment. Effects of interspecific competition from the paired alien species seedlings on a native seedling were compared to the effects from intraspecific competition of other seedlings of the native species over a 65 week period. Mortality was low throughout the experiment. The native species were affected by density-dependent competition generally, resulting in decreased performance with increasing neighbour density or biomass. The alien palm, A. cunninghamiana, however, had stronger competitive effects on the native palm, R. sapida, than intraspecific competition among R. sapida individuals. Also, P. guajava showed some stronger competitive effects on L. bullata than intraspecific competition among L. bullata individuals. These alien species displayed some traits often associated with invasive plants: A. cunninghamiana had higher RGR, height, biomass production and SLA than R. sapida, while P. guajava had higher SLA than L. bullata. Competitive ability of these newly naturalised species may be an important factor influencing their establishment success and subsequent invasion potential.

Crown responses to neighbor density and species identity in a young mixed deciduous stand

Density was more important in shaping crown structure than neighbor species identity. Both species showed high crown plasticity at alternative levels, which may explain species coexistence in mixed broadleaved forests with functionally similar species. Understanding crown response to local competition is essential to predicting stand development in mixed stands. We analyzed data from an 8-year-old field experimental plantation mixing two species according to a crossed gradient of density and species proportion to quantify the effect of a broad range of local neighborhood conditions on the development of young trees at multiple crown levels. We used Fagus sylvatica and Acer pseudoplatanus, as two model deciduous species. They are considered functionally equivalent at the young stages, but with contrasting architectural patterns. For both species: (1) changes in density explained more of the variation on crown development than species proportion (2) much of the effect of competition was accounted for by variables at the stem level, while branch and leaf development within crowns were not directly altered by competition. Both species were able to modify their crowns at the stem level to compete with intra- and inter-specific neighbors: Acer and Fagus were taller with a highest proportion of Fagus as neighbors; Fagus displayed a lower crown base when the proportion of Fagus decreased, while Acer had a lower crown base when the proportion of Fagus around it increased. Both species showed common shapes in allometric relationships but contrasting responses at alternative crown levels. Acer exhibited broader intra-specific variation in its height–diameter relationship and in its crown length, while Fagus displayed higher individual variation of branch development and leaf area than Acer. This study demonstrates that differences in crown development strategy of each species in response to changes in local neighborhood conditions are an important factor in maintaining species coexistence in broadleaved forests and designing mixtures that persist over time.

A CLASSIFICATION SCHEME FOR YOUNG STELLAR OBJECTS USING THEWIDE-FIELD INFRARED SURVEY EXPLORERAllWISE CATALOG: REVEALING LOW-DENSITY STAR FORMATION IN THE OUTER GALAXY

We present an assessment of the performance of WISE and the AllWISE data release in a section of the Galactic Plane. We lay out an approach to increasing the reliability of point source photometry extracted from the AllWISE catalog in Galactic Plane regions using parameters provided in the catalog. We use the resulting catalog to construct a new, revised young star detection and classification scheme combining WISE and 2MASS near and mid-infrared colors and magnitudes and test it in a section of the Outer Milky Way. The clustering properties of the candidate Class I and II stars using a nearest neighbor density calculation and the two-point correlation function suggest that the majority of stars do form in massive star forming regions, and any isolated mode of star formation is at most a small fraction of the total star forming output of the Galaxy. We also show that the isolated component may be very small and could represent the tail end of a single mechanism of star formation in line with models of molecular cloud collapse with supersonic turbulence and not a separate mode all to itself.

A novel groutability estimation model for ground improvement projects in sandy silt soil based on Bayesian framework

In construction engineering, permeation grouting with microfine cement is a widely utilized approach for soil improvement. Hence, estimating groutability is a very important task that should be carried out in the planning phase of any grouting project. This research aims at establishing a novel method for groutability prediction with the utilization of microfine cement in sandy silt soil. The newly proposed approach integrates the Bayesian framework and the K-nearest neighbor (K-NN) density estimation technique. The Bayesian framework is used to achieve probabilistic groutability estimations. Meanwhile, the K-NN method is employed to approximate the conditional probability density functions. Moreover, to establish the new approach, 240 in-situ grouting cases have been recorded during the progress of Mass Rapid Transit and highway projects in Taiwan. Experimental results point out that the proposed method can deliver superior prediction accuracy. Hence, the new groutability estimation approach is a promising alternative to help construction engineers in grouting process assessment.

The effects of resprouting natural forest on reproductive traits of blue tits (Cyanistes caeruleus) in a stone pine afforestation

The reproductive performance achieved by blue tits (Cyanistes caeruleus) in a low-quality habitat with a regular grid of nest boxes during a 6-year period (2007–2012) was tested. The variables used as sources of variation for analysis were the habitat quality (resprouted holm oak abundance) in the territories, the spatial distribution of territories (peripheral or interior nest boxes), the entrance-hole size of available nest boxes, the social context around the nesting territories (breeding neighbour density: conspecific or Great tits Parus major) and temporal pattern of reproduction (laying date). For whole breeding population, the proportion of successful nests and the breeding success were dependent on the location of territories and entrance-hole of nest boxes. The prediction concerning the relationship between habitat quality and reproductive performance is supported only for clutch size. This trait, but not the hatching and breeding success, clearly depended on resprouted holm oak abundance in the territories, increasing with the abundance of trees. Blue tits exhibited a clustered territoriality and the conspecific and Great tit P. major densities around blue tit territories were mutually influenced in a negative way. The breeding success variation in successful nests is positively associated to the conspecific density: individuals with more conspecific neighbours achieved best breeding success. For all nests pooled (successful and unsuccessful), reproductive performance was not dependent on the great tit density. Reproductive failure was higher in the large-holed nest boxes than in the small-holed ones. The clutch size also showed a significant gradient as a function of the egg-laying date: females laying eggs earlier in the season had larger clutch sizes than those who did later. From these results, we draw some implications for the management strategies of hole-nesting passerines using nest boxes in large areas of stone pines plantations.

Does relatedness matter? Phylogenetic density-dependent survival of seedlings in a tropical forest.

A complex set of interactions among neighbors influences plant performance and community structure. Understanding their joint operation requires extensive information on species characteristics and individual performance. We evaluated first-year survival of 35719 tropical forest seedlings of 222 species and 15 annual cohorts relative to the density of conspecific and heterospecific neighbors and the phylogenetic similarity of heterospecific neighbors. Neighbors were from two size classes, and size asymmetric interactions provided insight into likely mechanisms. Large heterospecific and conspecific neighbors reduced seedling survival equally, suggesting resource competition rather than host-specific enemies as a mechanism. In contrast, much stronger negative conspecific effects were associated with seedling neighbors capable of limited resource uptake, suggesting shared pests rather than competition as the mechanism. Survival improved, however, near phylogenetically similar heterospecific neighbors, suggesting habitat associations shared among closely related species affect spatial patterns of performance. Improved performance near phylogenetically similar neighbors is an emerging pattern in the handful of similar studies.

Local neighborhood competition following an extraordinary snow break event: implications for tree-individual growth

Abstract: Sustainable forest management practices and the increased interest of plantation forestry in species mixtures require an understanding of individual-tree growth in complex and diverse forests. Individual-tree growth has been found to be affected by factors such as species identity and size of the target tree as well as of neighboring trees, neighbor density and abiotic factors. However, most of these studies have been conducted in plantations or mixed forests with a very limited number of species. We conducted our study in a subtropical forest in China, which was very species rich and highly heterogeneous with regard to topography (slope inclination and aspect, elevation) and successional status. Prior to our study the forest was subjected to an exceptional snow break event. We asked whether individual-tree basal area increment (BAI) over three growing seasons following the snow break event was related to local biotic and abiotic conditions. We hypothesized that individual-tree BAI is negatively affected by local neighborhood competition, positively affected by local neighborhood diversity, negatively related to slope inclination, and positively related to aspect to south. Individual-tree BAI of four different species was mainly affected by tree size, local neighborhood competition and species identity. Contrary to our expectations, we did not observe significant effects of local neighborhood functional diversity and abiotic conditions. However, we did find a negative effect of plot functional diversity on BAI. This finding may be explained by a negative correlation of plot functional diversity and snow break damage, which was observed in mid- and late-successional stages. The disturbance event did considerably change the competitive local neighborhood interactions by reducing competition, which increased the BAI of target trees in more disturbed/more diverse plots.

LiNearN: A new approach to nearest neighbour density estimator

Despite their wide spread use, nearest neighbour density estimators have two fundamental limitations: O(n2) time complexity and O(n) space complexity. Both limitations constrain nearest neighbour density estimators to small data sets only. Recent progress using indexing schemes has improved to near linear time complexity only.We propose a new approach, called LiNearN for Linear time Nearest Neighbour algorithm, that yields the first nearest neighbour density estimator having O(n) time complexity and constant space complexity, as far as we know. This is achieved without using any indexing scheme because LiNearN uses a subsampling approach for which the subsample values are significantly less than the data size. Like existing density estimators, our asymptotic analysis reveals that the new density estimator has a parameter to trade off between bias and variance. We show that algorithms based on the new nearest neighbour density estimator can easily scale up to data sets with millions of instances in anomaly detection and clustering tasks.

Mergers as triggers for nuclear activity: a near-IR study of the close environment of AGN in the VISTA-VIDEO survey

There is an ongoing debate concerning the driver of nuclear activity in galaxies, with AGN either being triggered by major or minor galactic mergers or, alternatively, through secular processes like cooling gas accretion and/or formation of bars. We investigate the close environment of active galaxies selected in the X-ray, the radio, and the mid-IR. We utilise the first data release of the new near-IR VISTA Deep Extragalactic Observations (VIDEO) survey of the XMM-Large Scale Structure (LSS) field. We use two measures of environment density, namely counts within a given aperture and a finite redshift slice (pseudo-3D density) and closest neighbour density measures ${\Sigma}_{2}$ and ${\Sigma}_{5}$. We select both AGN and control samples, matching them in redshift and apparent Ks-band magnitude. We find that AGN are found in a range of environments, with a subset of the AGN samples residing in over-dense environments. Seyfert-like X-ray AGN and flat-spectrum radio-AGN are found to inhabit significantly over-dense environments compared to their control sample. The relation between over-densities and AGN luminosity does not however reveal any positive correlation. Given the absence of an environment density-AGN luminosity relation,we find no support for a scheme where high luminosity AGN are preferentially triggered by mergers. On the contrary, we find that AGN likely trace over dense environments at high redshift due to the fact that they inhabit the most massive galaxies, rather than being an AGN.

Airfoil shape optimization using improved Multiobjective Territorial Particle Swarm algorithm with the objective of improving stall characteristics

In this paper, a new robust optimization technique with the ability of solving multi-objective constrained design optimization problems in aerodynamics is presented. This new technique is Multi-objective Territorial Particle Swarm Optimization (MOTPSO) algorithm in which diversity is actively preserved by avoiding overcrowded clusters of particles and encouraging broader exploration. Adaptively varying "territories" are formed around promising individuals to prevent many of the lesser individuals from premature clustering and encouraged them to explore new neighborhoods based on a hybrid self-social metric. Also, a new social interaction scheme is introduced which guided particles towards the weighted average of their "elite" neighbors' best found positions instead of their own personal bests which in turn helps the particles to exploit the candidate local optima more effectively. The MOTPSO algorithm takes into account multiple objective functions using a Pareto-Based approach. The non-dominated solutions found by swarm are stored in an external archive and nearest neighbor density estimator method is used to select a leader for the individual particles in the swarm. Efficiency and robustness of the proposed algorithm is demonstrated using multiple traditional and newly-composed optimization benchmark functions and aerodynamic design problems. In final airfoil designs obtained from the Multi Objective Territorial Particle Swarm Optimization algorithm, separation point is delayed to make the airfoil less susceptible to stall in critical operating conditions and it also reveal an evident improvement over the test case airfoil across all objective functions presented.

Effects of field and landscape variables on crop colonization and biological control of the cabbage root fly Delia radicum

Agriculture intensification has deeply modified agroecosystems from field to landscape scales. To achieve successful pest control using natural enemies, understanding species interactions over all scales remains a challenge. Using the cabbage root fly as a model, we studied whether field and landscape characteristics influenced colonization and infestation of broccoli fields by the pest and its control by natural enemies. We also determined whether species of different trophic level or host specialization would respond to environmental characteristics at the same spatial extent. During a multiple-species and multiple-spatial extent study in northwestern France, we recorded pest colonization and infestation in 68 fields, collected associated natural enemies and assessed crop damages. In each field, we considered management practices and characterized the surrounding landscape in 50–500 m-wide buffers. Our main findings are that Delia radicum and its main natural enemies respond to both field and landscape characteristics. Semi-natural areas supported both crop colonization by pests and natural enemy action. The pest and its enemies differed in their responses to field or landscape variables. Landscape elements such as field banks favored the movement of the pest while impeding the movement of some natural enemies. Pest pressure did not increase with the neighboring density of Brassica crops. The presence of natural enemies did not reduce crop damage but reduced pest emerging rates. Finally, specialist parasitoids responded to the landscape at larger spatial extents than generalists. These results outline the complexity of improving pest control through landscape management.

THE TWO-DIMENSIONAL PROJECTED SPATIAL DISTRIBUTION OF GLOBULAR CLUSTERS. I. METHOD AND APPLICATION TO NGC 4261

We present a new method for the determination of the two-dimensional (2D) projected spatial distribution of globular clusters (GCs) in external galaxies. This method is based on the K-Nearest Neighbor density estimator of Dressler (1980), complemented by MonteCarlo simulations to establish the statistical significance of the results. We apply this method to NGC4261, a "test galaxy" where significant 2D anisotropy in the GC distribution has been reported. We confirm that the 2D distribution of GC is not azimuthally isotropic. Moreover, we demonstrate that the 2D distribution departures from the average GC radial distribution results in highly significant spiral-like or broken shell features. Overall, the same perturbations are found in "red" and "blue" GCs, but with some differences. In particular, we observe a central feature, roughly aligned with the minor axis of NGC4261, composed of red and most luminous GCs. Blue and fainter GCs are more frequent at large radial distances and follow the spiral-like features of the overall density structure. These results suggest a complex merging history for NGC4261.

Phonetic convergence in shadowed speech: The relation between acoustic and perceptual measures

Abstract The current study investigates the influence of lexical factors on phonetic convergence and explores the relationship between acoustic and perceptual measures of convergence. A set of talkers produced baseline and shadowed tokens of target words that varied in frequency and phonological neighbor density independently. Experiment 1 demonstrated the impact of lexical factors on vowel dispersion in speech production. In Experiment 2, separate listeners judged the relative similarity of shadowed to model tokens in an AXB perceptual test of phonetic convergence. Acoustic measures of inter-talker distances in duration, fundamental frequency, and vowel formants for baseline and shadowed speech were compared to the perceptual measures. A mixed-effects regression model using a combination of acoustic convergence measures predicted perceived phonetic convergence better than lexical factors or individual acoustic attributes alone. These findings have important methodological and theoretical implications for understanding the complexities of phonetic convergence. Studies of convergence should consider examining acoustic and perceptual measures in tandem. Lexical factors impact speech production and perception, but their effects appear to be independent of those that evoke phonetic convergence.

Ensemble estimators for multivariate entropy estimation.

The problem of estimation of density functionals like entropy and mutual information has received much attention in the statistics and information theory communities. A large class of estimators of functionals of the probability density suffer from the curse of dimensionality, wherein the mean squared error (MSE) decays increasingly slowly as a function of the sample size T as the dimension d of the samples increases. In particular, the rate is often glacially slow of order O(T-γ/d ), where γ > 0 is a rate parameter. Examples of such estimators include kernel density estimators, k-nearest neighbor (k-NN) density estimators, k-NN entropy estimators, intrinsic dimension estimators and other examples. In this paper, we propose a weighted affine combination of an ensemble of such estimators, where optimal weights can be chosen such that the weighted estimator converges at a much faster dimension invariant rate of O(T-1). Furthermore, we show that these optimal weights can be determined by solving a convex optimization problem which can be performed offline and does not require training data. We illustrate the superior performance of our weighted estimator for two important applications: (i) estimating the Panter-Dite distortion-rate factor and (ii) estimating the Shannon entropy for testing the probability distribution of a random sample.

DAWN: A density adaptive routing for deadline-based data collection in vehicular delay tolerant networks

Vehicular Delay Tolerant Networks (DTN) use moving vehicles to sample and relay sensory data for urban areas, making it a promising low-cost solution for the urban sensing and infotainment applications. However, routing in the DTN in real vehicle fleet is a great challenge due to uneven and fluctuant node density caused by vehicle mobility patterns. Moreover, the high vehicle density in urban areas makes the wireless channel capacity an impactful factor to network performance. In this paper, we propose a local capacity constrained density adaptive routing algorithm for large scale vehicular DTN in urban areas which targets to increase the packet delivery ratio within deadline, namely Density Adaptive routing With Node deadline awareness (DAWN). DAWN enables the mobile nodes awareness of their neighbor density, to which the nodes' transmission manners are adapted so as to better utilize the limited capacity and increase the data delivery probability within delay constraint based only on local information. Through simulations on Manhattan Grid Mobility Model and the real GPS traces of 4960 taxi cabs for 30 days in the Beijing city, DAWN is demonstrated to outperform other classical DTN routing schemes in performance of delivery ratio and coverage within delay constraint. These simulations suggest that DAWN is practically useful for the vehicular DTN in urban areas.

TU‐G‐141‐07: An Innovative Iterative Neighboring Volume Morphing Algorithm Based On Landmark Mesh to Create 3DCT During Treatment

Purpose: For the emerging 4D planning radiation treatment, 3DCT during treatment delivery is required. However, it is time consuming or impossible to acquire 3DCT during treatment delivery. This project will generate the 3DCT for any time instant based on a set of motion features (landmarks). Methods: Previously acquired 4DCT is used for landmark selection. The landmarks are monitored in real‐time during treatment delivery using two orthogonal x‐ray images. For any set of landmarks acquired at target phase T, the 3DCT of the nearest 4DCT phase will be selected as the source phase S based on landmark mesh similarity. The iterative morphing algorithm has 8 steps based on neighboring density volume, including landmark selection, isosurface and tumor center identification, landmark mapping using weighted 3‐layer mesh neighbors, landmark mesh similarity comparison, backward morphing based on density volume, and iterative volume morphing. It will generate the corresponding 3DCT at target phase. Results: To validate the morphing algorithm, first, the landmark mapping process using artificial deformation is assessed. The source 3DCT is deformed artificially by non‐linear matrices, which generated a ground truth to evaluate the resulting 3DCT. The iterative algorithm is appraised successfully with the artificial deformation approach. The second validation applies the landmark mapping and the volume morphing on real tumor data. Both the source and target 3DCTs are different phases of a lung 4DCT data. The statistical results, such as the min, max, and histogram of the density difference are summarized, which showed the resulting 3DCT is similar to the target 3DCT. The next step is to apply the whole algorithm to the unknown target 3DCT. Conclusion: The iterative morphing algorithm is innovative and time saving. It has many potential applications in real‐time image guided radiation treatment, such as online treatment error detection and intervention.Industrail Support from PerkinElmer Inc, Varian Medical Research

Competitive effect and response of savanna tree seedlings: Comparison of survival, growth and associated functional traits

Questions What is the effect of neighbour competition on the survival, growth and biomass of mesic and humid savanna tree species? Can competitive effect and response be linked to plant functional traits? Location Neil Tainton Arboretum, University of KwaZulu-Natal, Pietermaritzburg, ZA. Methods Using a target–neighbour design, all combinations of four humid and four mesic savanna tree seedlings were tested in a greenhouse experiment, to establish the effects of neighbourhood competition on target plant performance. The competitive response and effect of each species was quantified, and regressed against several functional traits to determine which traits are predictive of competitive ability. Results We found that neighbour density negatively affected the survival of mesic tree seedlings but not humid tree seedlings. Mesic plants were able to maintain their relative growth rates (RGRs) despite increasing neighbourhood competition. The RGRs of humid species significantly decreased as the density of neighbours increased, indicating that competition may be a factor affecting plants in savannas receiving more than 650 mm mean annual rainfall. We used the quantile regression method to show that the biomass of humid tree seedlings decreased with increased neighbour biomass, when considering competitive response only. We also found that resource-acquiring traits (such as maximum RGR, plant height and root biomass) were positively correlated with the competitive effect of mesic savanna seedlings, while specific leaf area captured the competitive response of humid savanna seedlings to neighbour competition. Conclusions Competitive interactions between savanna trees negatively affect survival and growth rate, although the competitive effect or response of a particular species depends on its adaptation to either high- or low-resource environments. Our results show significant relationships between plant traits and competitive ability, which may be used to predict competitive interactions between tree seedlings from humid and mesic savannas.