Geostatistical and multivariate analysis of the horizontal distribution of an earthworm community in El Molar (Madrid, Spain)

Hernández, Patricia; Fernández, Rosa; Novo, Marta; Trigo, Dolores; Cosín, Darío J. Díaz

doi:10.1016/j.pedobi.2006.11.002

Cited by 30 publications

(17 citation statements)

References 15 publications

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“…Spatial structure in earthworm communities has been related mainly to environmental heterogeneity posed by soil and vegetation patchiness and to environmental gradients at larger scale (Decaëns et al, 2009; Jiménez et al, 2011). Hernández et al (2007) used geostatistical and multivariate analysis to explain the relationships between the horizontal distribution of earthworm communities and some soil factors in grassland in Madrid Spain. Jiménez et al (2011) combined SADIE analysis to detect gap and patch clusters and association/dissociation between earthworm species with geostatistics, to investigate the spatial distribution of an earthworm community together with the heterogeneity of selected soil properties in a gallery forest of the Colombian “Llanos.” The degree of autocorrelation of spatial pattern was assessed with semi-variogram and they used the partial Mantel test to explain the relationship between the spatial pattern of earthworm density and soil environmental variables, concluding that the earthworm community of this gallery forest showed a random structure in a spatially clumped soil environment.…”

Section: Methods To Measure Spatial Structure Of Organisms In Field Amentioning

confidence: 99%

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

Campos‐Herrera¹,

Ali²,

Díaz³

et al. 2013

Front. Plant Sci.

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Modern agricultural systems can benefit from the application of concepts and models from applied ecology. When understood, multitrophic interactions among plants, pests, diseases and their natural enemies can be exploited to increase crop production and reduce undesirable environmental impacts. Although the understanding of subterranean ecology is rudimentary compared to the perspective aboveground, technologies today vastly reduce traditional obstacles to studying cryptic communities. Here we emphasize advantages to integrating as much as possible the use of these methods in order to leverage the information gained from studying communities of soil organisms. PCR-based approaches to identify and quantify species (real time qPCR and next generation sequencing) greatly expand the ability to investigate food web interactions because there is less need for wide taxonomic expertise within research programs. Improved methods to capture and measure volatiles in the soil atmosphere in situ make it possible to detect and study chemical cues that are critical to communication across trophic levels. The application of SADIE to directly assess rather than infer spatial patterns in belowground agroecosystems has improved the ability to characterize relationships between organisms in space and time. We review selected methodology and use of these tools and describe some of the ways they were integrated to study soil food webs in Florida citrus orchards with the goal of developing new biocontrol approaches.

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Section: Methods To Measure Spatial Structure Of Organisms In Field Amentioning

confidence: 99%

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

Campos‐Herrera¹,

Ali²,

Díaz³

et al. 2013

Front. Plant Sci.

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“…The most important factors affecting earthworm distribution such as soil texture, pH, total nitrogen and organic oxidable carbon were measured (see Hernández et al, 2007, and references herein for methods).…”

Section: Environmental Assessmentmentioning

confidence: 99%

“…Golldack (2006) indicated that the distribution of A. caliginosa genotypes was not related to soil properties. Nevertheless, the relationship between earthworm distribution and soil factors is well known (Edwards, 2004) and specifically H. elisae's abundance is proved to be positively correlated with total and coarse sands and negatively with clay, nitrogen, carbon and coarse loam contents (Hernández et al, 2007).…”

Section: What Causes These Deep Divergencesmentioning

confidence: 99%

Cryptic speciation of hormogastrid earthworms revealed by mitochondrial and nuclear data

Novo

Almodóvar

Fernández

et al. 2010

Molecular Phylogenetics and Evolution

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108

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“…Across a range of ecosystems, earthworm species are spatially distributed in clusters ranging from as small as 7 m in diameter (Rossi 2003b) to more than 100 m (Hernández et al 2007). However, the majority of spatial ranges of autocorrelation lies within 20-50 m. Adult individuals of L. terrestris consistently live in small clusters (~20 m) compared to other species, presumably related to its surface mating behaviour.…”

Section: Spatial Autocorrelation and Sampling Designmentioning

confidence: 99%

Optimizing Earthworm Sampling in Ecosystems

Valckx

Govers

Hermy

et al. 2010

Biology of Earthworms

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To quantify the role of earthworms in ecosystems, a precise and accurate estimation of their diversity, abundance and biomass is needed. To date, a diverse set of earthworm sampling methods is available, and a diverse amount of chemical expellants have been used to greater or lesser success. Earthworm ecologists have so far often relied on expert judgement or past experience when it comes to spatial sampling designs and determination of sample size. However, based on the ever increasing data available in the literature, we start to understand the spatial organisation of earthworm populations. Moreover, straightforward techniques exist to assess earthworm species richness and the corresponding sampling effort needed to capture it, but so far these were not used in earthworm ecology.In this chapter, we contribute to the optimization of earthworm sampling in terms of (1) how to sample, (2) where to sample and (3) how many samples to take.First, we assess optimal concentrations of chemical expellants (allyl isothiocyanate (AITC) and mustard) recently recommended for earthworm sampling. The efficiency of these vermifuges is then evaluated against formalin application using a combined earthworm sampling method (extraction followed by hand sorting). Practical considerations are discussed.Like many living organisms, earthworm populations are neither uniformly nor randomly distributed, but exhibit an aggregated distribution in patches. The range of spatial autocorrelation in these patches is an important variable to consider in spatial sampling designs. Based on a literature overview, guidelines for spatial sampling design are presented.

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Geostatistical and multivariate analysis of the horizontal distribution of an earthworm community in El Molar (Madrid, Spain)

Cited by 30 publications

References 15 publications

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

Cryptic speciation of hormogastrid earthworms revealed by mitochondrial and nuclear data

Optimizing Earthworm Sampling in Ecosystems

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