Spatial Pattern of Trees in the Major Forest Types of Northern Ontario

Payandeh, Bijan

doi:10.1139/x74-002

Cited by 26 publications

(14 citation statements)

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“…The other published until now results have shown a big diversity of patterns, usually with a dominance of random or aggregated ones (Payandeh 1974;Veblen etal. 1980;Hara 1983;Abbott 1984;Buzykin eta/.…”

Section: Discussionmentioning

confidence: 94%

“…Of course, it is not a problem as far as big gaps in relatively dense forests are being considered -but in case of smaller gaps in forests which are not very dense, it is. Especially, if we think about the fact, that spatial distribution of trees in natural forest is usually not regular (Payandeh 1974;Armesto et al 1986), and that sizes of gaps may create a continuum -from small, negligible holes in the canopy, to those, which are probably too large to be considered 'gaps' any longer, and are in fact open areas within the forest. Moreover -gaps sizes are not stable, gaps are being reduced by the lateral growth of branches of adjacent trees, or they expand as one or a few of neighbouring trees die (Hubbell & Foster 1986;Runkle & Yetter 1987).…”

Section: Introductionmentioning

confidence: 99%

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Natural regeneration of forest related to the spatial structure of trees: A study of two forest communities in Western Carpathians, southern Poland

Szwagrzyk

1990

Vegetatio

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The existence of a relationship between the spatial pattern of trees and the distribution of young individuals beneath the canopy has been tested in the beech (Fagus sylvatica) and spruce (Picea abies) -fir (Abies alba) forests in the mountainous region, using two different methods. The first method was the analysis of spatial pattern of individuals, the second one was based on calculating sums of influences of all trees occurring within analysed plot on a given point on the forest floor. Results of spatial pattern analyses were surprisingly consistent: almost all mature trees and seedlings didplayed a random pattern of spatial arrangement. However, there is a clear, although statistically insignificant tendency towards uniformity of spatial pattern with increasing sizes of analysed trees. Results of comparing sums of influences on regularly distributed points with sums of influences on seedlings or saplings revealed no tendency in forest regeneration to concentrate in places, where the sums were smaller than the average for a plot. This, coupled with the dominance of random spatial pattern of trees, suggests, that viewed on a small spatial scale, influence of competition among forest trees on their spatial arrangement is obscured by other factors, which are not closely related to the distribution of individuals.

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Section: Discussionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Natural regeneration of forest related to the spatial structure of trees: A study of two forest communities in Western Carpathians, southern Poland

Szwagrzyk

1990

Vegetatio

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“…The significance of any deviations from the expected value for the Poisson distribution can be tested using χ 2 distribution with 2n degrees of freedom (n -number of distance measurements). Payandeh (1974) gave an example of this index applied to forests located in Ontario, Canada.…”

Section: Distance-dependent Indicesmentioning

confidence: 99%

Spatial statistics in ecological analysis: from indices to functions

Szmyt¹

2014

Silva Fenn.

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• Spatial statistics provides a quantitative description of natural variables distributed in space and time.• The objectives of spatial analysis are to detect spatial patterns and to confirm if a pattern found is significant. • Spatially explicit indices and functions may be applied depending on the information collected from the field. • Development of the specific software supports spatial analyses. AbstractThis paper presents a review of the most common methods in ecological studies aimed at spatial analysis of population structures (horizontal and vertical), based on point process statistics. Methods based on simple spatially explicit indices as well as more sophisticated methods relying on functions are described in a comprehensible manner. Simple indices revealing the information on spatial structure at the scale of the nearest neighbor can be easily implemented in practical forestry. On the other hand, spatial functions, based on much more detailed data, describe the spatial structure in terms of the spatial relationships between the natural processes and population structures and because of this complexity they are rarely used in forest practice. Including both methods in a single paper is also valuable from the potential reader's point of view saving their time for searching and choosing the appropriate method to make their spatial analysis. This paper can also serve as an initial guide for young researchers or those who are going to start their studies on spatial aspects of bio-systems. Avoiding the statistical and mathematical details makes this paper understandable for readers who are not statisticians or mathematicians. Readers will find many references related to each method described here, allowing them to find solutions to different problems observed in practice. This paper ends with a list of the most common specific software packages available to support spatial analysis.

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“…However, it is generally accepted that natural regeneration follows a strongly clustered .rather than a random distribution in most situations (Wellner 1940, Gill 1950, and others). Payandeh (1974) found that even trees in mature stands are generally clustered.…”

Section: The Use Of Computer-generated Seedling Populationsmentioning

confidence: 99%

Accuracy of Regeneration Stocking Estimates: Tests with Simulated Data

MacLeod¹

1977

The Forestry Chronicle

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A computer was used to generate points representing tree seedlings in an area of natural regeneration. These seedlings were than sampled and the per cent stocking calculated for 2 m x 2 m (milacre) plots. A systematic survey design was used, employing a wide variety of plot spacings. Groups of plots were included as well as single plots. For each spacing, repeated surveys were run and a standard error was estimated for the stocking level. Graphs were drawn to show the approximate sampling intensity required to estimate stocking to a given accuracy, for 10-ha and 40-ha sample areas. ResumeL'auteur utilisa un ordinateur pour creer des points representant des populations de semis dans un terrain a reboiser. Puis il echantillonna ces semis, et le pourcentage de densite, dans des placettes de 2 m sur 2 m, fut calcule. II utilisa plusieurs methodes de relev6 et f i t varier de beaucoup la distance d'une placette a I'autre. II inclut des groupes de placettes, outre des placettes seules. Pour chaque design, il effectua plusieurs releves et il estima I'erreur type de niveau de densite. II traCa des graphiques pour montrer I'intensit6 approximative des Bchantillonnages necessaire pour estimer la densite a un niveau de precision donne dans des aires d'Bchantillonnage de 10 ha et 40 ha.

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Spatial Pattern of Trees in the Major Forest Types of Northern Ontario

Cited by 26 publications

References 0 publications

Natural regeneration of forest related to the spatial structure of trees: A study of two forest communities in Western Carpathians, southern Poland

Natural regeneration of forest related to the spatial structure of trees: A study of two forest communities in Western Carpathians, southern Poland

Spatial statistics in ecological analysis: from indices to functions

Accuracy of Regeneration Stocking Estimates: Tests with Simulated Data

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