Spatial structure of deciduous forest stands with contrasting human influence in northwest Spain

Rozas, Vicente; Zas, Rafael; Solla, Alejandro

doi:10.1007/s10342-009-0263-9

Cited by 26 publications

(16 citation statements)

References 40 publications

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“…This reflects the vegetative origin of stems in stools. At Lipina, stems had clustering at all study intervals up to 20 m. A similar spatial distribution was observed in the Mondariz and Pantón coppice forests in Spain (Rozas et al 2009). The maximum intensity of clumping in our study and in Mondariz and Pantón is almost identical, with ranges at ca.…”

Section: Tree Spatial Patternssupporting

confidence: 52%

Below- and above-ground biomass, structure and patterns in ancient lowland coppices

Vrška¹,

Janík²,

Pálková³

et al. 2017

iForest

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Ancient coppice woods are areas that reflect long-term human influence and contain high species biodiversity. In this type of forest we aimed to: (i) analyze the below-and above ground biomass of stools and estimate the age of largest stool; (ii) define a "zone of interference" for coppices; (iii) describe and classify variability in the shape and size of coppice stools; (iv) define the specific characteristics of the spatial distribution of stems and stools. The study was conducted in the Podyjí National Park, Czech Republic, where two old oak coppice stands were fully stem mapped: Lipina (3.90 ha) and Šobes (2.37 ha). Cores were processed using TimeTable and PAST4. Below-and above-ground biomass of the largest stools was computed using the data from terrestrial laser scanner. Tree zones of influence were analyzed with V-Late landscape analysis tools using Shape Index for singles and 0.87 m 2 for stools. The Matérn cluster process was successfully fitted to our empirical data. In this model, the mean cluster radius ranged between 1.9 to 2.1 m and mean number of points per cluster was 1.7 and 1.9. The most prevalent characteristics of these ancient oak coppices were their compact shape and clustered spatial distribution up to 10 m.

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Section: Tree Spatial Patternssupporting

confidence: 52%

Below- and above-ground biomass, structure and patterns in ancient lowland coppices

Vrška¹,

Janík²,

Pálková³

et al. 2017

iForest

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“…As a result, the post-mortality spatial pattern of surviving trees shifts towards a more regularly spaced pattern (see plot 2 and 3 in Figure 3), providing evidence of density-dependent competition over the initial succession stages. This shift has been reported in uneven-aged temperate forests [35][36][37][38] and can be used to infer intra-and inter-specific interactions in mixed hardwood Caspian beech stands [21]. Moreover, if density-dependent competition is a decisive mechanism in the development of stand structure throughout succession, spatial regularity among older trees should increase over succession as individuals become larger and more effective competitors [34].…”

Section: Discussionmentioning

confidence: 99%

Spatial Distribution and Volume of Dead Wood in Unmanaged Caspian Beech (Fagus orientalis) Forests from Northern Iran

Amanzadeh¹,

Sagheb-Talebi²,

Foumani³

et al. 2013

Forests

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Unmanaged forests are remnants of natural ecosystems that provide a basis for close-to-nature silvicultural research and applications. These forests have high amounts of dead wood, and although this material is being increasingly studied, the diversity of dead wood in terms of different diameters, decay stages, and spatial distribution patterns is as important as its volume for understanding forest dynamics. Here, we study natural forests in northern Iran to investigate the spatial distribution, decay stages, and volume of dead wood in unmanaged temperate forests at different developmental stages. Three stem-mapped sampling plots (100 m × 100 m) were established in uneven-aged stands dominated by Caspian beech (Fagus orientalis Lispsky). The total dead wood ranged from 37 to 119 m 2 ha −1 . Our results imply a spatial distribution shift from aggregation to OPEN ACCESSForests 2013, 4 752 randomness for dead trees in Caspian beech forest succession. We detected significant spatial interactions (attraction) between living and dead trees at short to medium spatial scales (1-20 m) in the plot with the earlier successional stage, suggesting that intra-specific competition is a prevailing force causing tree mortality at the stem-exclusion phase. By contrast, as trees become dominant with the mortality of other trees, the random tree-mortality pattern prevails. The spatial distribution and volume of dead wood may serve as a management target in near-to-natural Caspian beech forest. On the basis of our results, conservation-oriented management strategies should take into account the increasing amount of dead wood, particularly of large diameter in a late stage of decay.

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“…Examples of applications of different functions mentioned above can be found in Kuuluvainen et al (1996), Kenkel (1997), Rozas (2003), Getzin et al (2006), Wiegand et al (2007), Illian et al (2008), Suzuki et al (2008), Wälder and Wälder (2008), Gray and He (2009), Nuske et al (2009), Picard et al (2009, Rozas et al (2009), Zhang et al (2010, Ledo et al (2011);Nanami et al (2011), Iszkuło et al (2012 and Pommerening et al (2013). …”

Section: Marks and Mark Hypothesis Testingmentioning

confidence: 99%

“…The answer to the question focused on biological processes at the origin of a certain spatial pattern in the population seems to be crucial (Goreaud and Pélissier 2003;Wiegand and Moloney 2004). Goreaud and Pélissier (2003), Rozas et al (2009), Illian et al (2008, Grabarnik et al (2011) stated that at least two different null hypotheses can be considered: independence (also called random superposition) and random labeling. Wiegand and Moloney (2004) propose also the third null hypotheses -antecedent conditions.…”

Section: Marks and Mark Hypothesis Testingmentioning

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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Spatial structure of deciduous forest stands with contrasting human influence in northwest Spain

Cited by 26 publications

References 40 publications

Below- and above-ground biomass, structure and patterns in ancient lowland coppices

Below- and above-ground biomass, structure and patterns in ancient lowland coppices

Spatial Distribution and Volume of Dead Wood in Unmanaged Caspian Beech (Fagus orientalis) Forests from Northern Iran

Spatial statistics in ecological analysis: from indices to functions

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