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The spatiotemporal pattern of earthworm community in the grass savannas of Lamto (Ivory Coast)
Abstract. BACKGROUND: The impact of earthworms on both soil physical properties and soil organic matter dynamics has been well documented (Lavelle and Spain 2001). There is a wealth of literature dedicated to the biological mechanisms at work or to empirical approaches based on field data. Assessing...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Pensoft Publishers
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4678800/ https://www.ncbi.nlm.nih.gov/pubmed/26696763 http://dx.doi.org/10.3897/BDJ.3.e6515 |
Sumario: | Abstract. BACKGROUND: The impact of earthworms on both soil physical properties and soil organic matter dynamics has been well documented (Lavelle and Spain 2001). There is a wealth of literature dedicated to the biological mechanisms at work or to empirical approaches based on field data. Assessing the functional role of a species or community implies establishing both time and space scales at which it is effectively the primary determinant of the process(es) at hand. In that context, space-time data analyses are powerful tools to process community data collected on numerous occasions but are, however, not widely disseminated in the community of ecologists. Although computer resources are available, one difficulty is that ad hoc field data are not always easily available which hinders the percolation of the methods. NEW INFORMATION: We provide the results of a 5 dates survey of earthworm community in a grass savanna of Lamto (Ivory Coast) conducted between 1995 and 1997. At each sampling date, earthworm community was assessed by hand-sorting a set of 100 soil monoliths distributed on a regular grid of 5 m mesh. These data were analyzed in Rossi (2003a) and are published here with the aim that they could be reanalyzed using new statistical tools (e.g. MEM analyses see Jiménez et al. 2014) or serve as example for researchers that train on space-time statistical methods. |
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