Facteurs contrôlant la variabilité spatiale de la macrofaune du sol dans une hêtraie pure et une hêtraie–charmaie

Aubert, Michaël; Hedde, Mickaël; Decaëns, Thibaud; Margerie, Pierre; Alard, Didier; Bureau, Fabrice

doi:10.1016/j.crvi.2004.10.008

Cited by 11 publications

(3 citation statements)

References 56 publications

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“…The reduced number of measurements or the density of samples increases the nugget effect (the microstructures of the phenomenon). Indeed, the increase in measurement density generally improves the reliability of experimental semi-variograms [30][31][32]. In this work, the variogram analysis was carried out within zones at a regional scale, because the number of sampling stations was sufficient (Table 1).…”

Section: Analysis Of the Spatial Structuresmentioning

confidence: 99%

“…This concept is often studied in the statistics applied to economic, demographic, and health studies, where the notion of spatial distribution is more commonly addressed [33,34]. Several dimension indices such as the Gini index (GI), also known as the Gini coefficient or the Theil index (TI) are used in the study of precipitation concentration [5,35] and in the analysis of rainfall characteristics [5,31,36,37]. The TI is related to a particular generalized entropy index and does not depend on any additional parameter [38].…”

Section: Study Of the Spatial Distribution Of Snow Survey Stationsmentioning

confidence: 99%

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Critical Analysis of the Snow Survey Network According to the Spatial Variability of Snow Water Equivalent (SWE) on Eastern Mainland Canada

et al. 2019

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In Eastern Canada, the snow survey network is highly optimized at the operational scale. However, it is commonly accepted that the network is limited when it comes to studying the spatial variability of the snow water equivalent (SWE), which forms different spatial structures that are active at multiple scales—from local to regional. The main objective of this study was to conduct a critical analysis of the existing snow survey network, based on the spatial variability of the existing SWE structures. To do so, we must (1) assess the snow survey network’s capacity to model spatial variability structures of SWE, and (2) study the spatial distribution based on the spatial variability structures of SWE. Initially, the snow survey network’s capacity to model the spatial variability structures of the SWE was evaluated by a variogram analysis. Second, the spatial distribution of the snow survey network’s data was analyzed through the Lorenz index curve and by measuring the spatial distribution using the Gini index. The results showed that, at a regional scale, the snow survey stations were evenly distributed within the spatial structures. However, at the local scale, the snow survey network was inadequate to model the spatial variability of SWE due to the reduced and uneven number of snow survey stations.

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Section: Analysis Of the Spatial Structuresmentioning

confidence: 99%

Section: Study Of the Spatial Distribution Of Snow Survey Stationsmentioning

confidence: 99%

Critical Analysis of the Snow Survey Network According to the Spatial Variability of Snow Water Equivalent (SWE) on Eastern Mainland Canada

et al. 2019

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“…nutrients, refuge or hiding-place, water content, permanent seed soil bank, edaphic mesofauna, symbiotic organisms etc. -and consequently for plant communities (Aubert et al, 2005;Mobaied et al, 2012;Morris and Blackwood, 2007;Ponge 2009, Ponge et al, 2010;…”

Section: Introductionmentioning

confidence: 99%

Humus forms in a Mediterranean area (Castelporziano Reserve, Rome, Italy): classification, functioning and organic carbon storage

Nicola¹,

Zanella

Testi³

et al. 2014

Geoderma

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Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments

et al. 2010

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The aim of this work was to investigate the potential of forest humus forms as indicators of soil C storage. To this purpose, Mediterranean forest soils in Southern and Central Italy were examined. Sites differed for elevation, climate, parent material and vegetation conditions, while summer drought was the common ecological factor. A morpho-functional criterion, based on holorganic layers thickness and A horizon properties, was used to classify humus forms, which ranged from Dysmoder to Eumull. Such variability allowed understanding of factors influencing organic matter storage. The relations between carbon stock and humus form were investigated for the topsoil layer (0–20 cm), which was supposed to contain the soil C pools most sensitive to climate change. We found that humus forms can be grouped in statistically different populations, with respect to topsoil C stocks. The use of A horizon structure was the main diagnostic criterion and represented the most effective approach to humus classification in Mediterranean conditions. It appears that humus forms have a clear potential as indicators of organic carbon status in Mediterranean forest soils

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Facteurs contrôlant la variabilité spatiale de la macrofaune du sol dans une hêtraie pure et une hêtraie–charmaie

Cited by 11 publications

References 56 publications

Critical Analysis of the Snow Survey Network According to the Spatial Variability of Snow Water Equivalent (SWE) on Eastern Mainland Canada

Critical Analysis of the Snow Survey Network According to the Spatial Variability of Snow Water Equivalent (SWE) on Eastern Mainland Canada

Humus forms in a Mediterranean area (Castelporziano Reserve, Rome, Italy): classification, functioning and organic carbon storage

Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments

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