Competition for Light in a Plant Monoculture Modelled as a Spatial Stochastic Process

Ford, E. David; Diggle, Peter J.

doi:10.1093/oxfordjournals.aob.a086152

Cited by 198 publications

(87 citation statements)

References 17 publications

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“…The first two approaches, approaches 1 and 2, were based on the concept of an influence-zone that assumes an imaginary circle whose centre is constituted by the subject tree (Staebler, 1951) and trees inside this circle are competitors. The last two approaches, approaches 3 and 4, identified competitors based on variable competition zone radii, often weighted by dimensions of the subject tree and its neighbours (Daniels, 1976;Ford & Diggle, 1981):…”

mentioning

confidence: 99%

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

2015

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Aim of study: The present study evaluates a set of competition indices including spatially explicit indices combined with different competitor selection approaches and non-spatially explicit competition indices. The aim was to quantify and describe the neighbouring effects on the tree diameter growth of silver birch trees.Area of study: Region throughout Estonia. Material and methods:Data from the Estonian Network of Forest Research Plots was used. After quantifying the selected indices, the best non-spatial indices and spatial indices (combined with neighbour selection methods) were separately devised into a growth model as a predictor variable to assess the ability of the diameter growth model before and after adding competition measures. To test the species-specific effect on the competition level, the superior indices were recalculated using Ellenberg's light indicators and incorporated into the diameter growth model.Main results: Statistical analyses showed that the diameter growth is a function of neighbourhood interactions and spatial indices were better growth predictors than non-spatial indices. In addition, the best selections of competitive neighbours were acquired based on the influence zone and the competition elimination angle concepts, and using Ellenberg's light values had no significant improvement in quantifying the competition effects.Research highlights: Although the best ranking spatial competition measures were superior to the best non-spatial indices, the differences were negligible.

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confidence: 99%

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

2015

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“…The correlation function (dashed) in Figure 5 suggests an interaction radius r 5.5 m, exhibiting attraction for small interpoint distances, inhibition, and absence of spatial correlation for distances larger than 5.5 m. Birches and pines seem to be competitors for light (cf. Ford and Diggle, 1981) within a range from 1.6 m to 5.5 m. This interaction between the two species is con®rmed by the mark correlation 6. CONCLUDING REMARKS Remark 1.…”

Section: Applicationsmentioning

confidence: 63%

Non‐parametric confidence intervals for correlations in nearest‐neighbour Markov point processes

Pallini

2002

Environmetrics

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SUMMARYWe study bootstrap con®dence intervals for correlation functions in nearest-neighbour Markov point processes, where the neighbours are characterized by an interaction of bounded radius r. In forestry statistics, the points are tree locations belonging to a region (forest) A, and the marks are qualitative or quantitative tree variables, such as tree species, the stem diameter, crown length or tree height. Estimating and analysing correlation functions between locations and marks, cross-correlations between different species and their marks, is typically a key step in statistical interpretation of mapped data sets from a forest stand. In order to de®ne the original sample, we propose coding schemes, which are ®xed and divide the observed region A of the point process into regular, conditionally independent subregions fB g located at Euclidean distance d ! 2r. Bootstrap con®dence intervals are then obtained directly, by considering kernel density estimates from all subregions fB g as conditionally independent replicates.

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“…On a ainsi pu proposer un modèle de dynamique forestière qui simule le glissement d'une répartition en agrégats à une répartition régulière avec la taille croissante des arbres, sous l'effet de la compétition [24]. Le passage d'une répartition agrégée à une répartition régu-lière sous l'action de la compétition est du reste une observation qui a été maintes fois faites aussi bien dans des peuplements hétérogènes [1,9,18,19,22] que réguliers [15,17], ou pour des plantes non ligneuses [11].…”

Section: Discussionunclassified

La corr�lation spatiale entre la surface terri�re des arbres et leur accroissement est-elle un bon indicateur de la comp�tition ?

Picard

Bar-Hen

2002

Ann. For. Sci.

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(Reçu le 26 juin 2000.; accepté le 21 juin 2001)Résumé -Une corrélation spatiale négative entre la surface terrière et l'accroissement en surface terrière des arbres est-elle révélatrice d'une compétition entre arbres, dans un peuplement forestier considéré comme une réalisation d'un processus ponctuel.? Pour un processus bivarié, la corrélation spatiale apparaît comme le fruit de deux composantes.: la valeur des marques (surface terrière et son accroissement) et la position des arbres, et il peut y avoir de la corrélation négative sans qu'il y ait de corrélation entre les marques conditionnellement à leur type. Dans un peuplement forestier de Guyane française, on observe de la corrélation spatiale négative. On observe également que les individus les plus gros sont répartis de façon régulière et indépendamment des petits qui sont répartis en agré-gats. Cette configuration suffit à expliquer la corrélation négative sans faire appel à la compétition. La compétition reste cependant un mécanisme explicatif du glissement de l'agrégat à la régularité avec la taille croissante des arbres. compétition / corrélation spatiale / processus ponctuel / répartition spatiale / dynamique forestière Abstract -Is the spatial correlation between the tree basal area and its increment a good indicator for competition? Is a negative spatial correlation between basal area and its increment indicative of tree competition, in a forest stand considered as a realisation of a point process? For a bivariate point process, the spatial correlation results from two components: the value of the marks and tree positions, and a negative spatial correlation can occur without any correlation between the marks knowing their type. In a forest stand in French Guiana, a negative spatial correlation is observed. Moreover, the big trees exhibit a regular pattern, independently from the small trees that are clustered. This configuration is sufficient to explain the negative correlation without involving competition. Competition however remains as a process that explains the shift from clustering to regularity with an increasing tree size. competition / spatial correlation / point process / spatial pattern / forest dynamics Ann. For. Sci. 59 (2002) [41][42][43][44][45][46][47][48][49][50][51] 41

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Competition for Light in a Plant Monoculture Modelled as a Spatial Stochastic Process

Cited by 198 publications

References 17 publications

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

Non‐parametric confidence intervals for correlations in nearest‐neighbour Markov point processes

La corr�lation spatiale entre la surface terri�re des arbres et leur accroissement est-elle un bon indicateur de la comp�tition ?

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