Soil macroinvertebrate communities: A world-wide assessment

Patrick Lavelle, Jérôme Mathieu, Alister Spain, George Brown, Carlos Fragoso, Emmanuel Lapied, Adriana De Aquino, Isabelle Barois, Edmundo Barrios, Maria Eleusa Barros, Jose Camilo Bedano, Eric Blanchart, Mark Caulfield, Yamileth Chagueza, Jun Dai, Thibaud Decaëns, Anahi Dominguez, Yamileth Dominguez, Alexander Feijoo, Patricia FolgaraitSteven J. Fonte, Norma Gorosito, Esperanza Huerta, Juan Jose Jimenez, Courtland Kelly, Gladys Loranger, Robelio Marchão, Raphael Marichal, Catarina Praxedes, Leonardo Rodriguez, Guillaume Rousseau, Laurent Rousseau, Nuria Ruiz, Catalina Sanabria, Juan Carlos Suarez, Jerôme Ebagnerin Tondoh, Anne De Valença, Steven J. Vanek, Joel Vasquez, Elena Velasquez, Emily Webster, Chi Zhang

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

22 Citas (Scopus)

Resumen

Aim: Macroinvertebrates comprise a highly diverse set of taxa with great potential as indicators of soil quality. Communities were sampled at 3,694 sites distributed world-wide. We aimed to analyse the patterns of abundance, composition and network characteristics and their relationships to latitude, mean annual temperature and rainfall, land cover, soil texture and agricultural practices. Location: Sites are distributed in 41 countries, ranging from 55° S to 57° N latitude, from 0 to 4,000 m in elevation, with annual rainfall ranging from 500 to >3,000 mm and mean temperatures of 5–32°C. Time period: 1980–2018. Major taxa studied: All soil macroinvertebrates: Haplotaxida; Coleoptera; Formicidae; Arachnida; Chilopoda; Diplopoda; Diptera; Isoptera; Isopoda; Homoptera; Hemiptera; Gastropoda; Blattaria; Orthoptera; Lepidoptera; Dermaptera; and “others”. Methods: Standard ISO 23611-5 sampling protocol was applied at all sites. Data treatment used a set of multivariate analyses, principal components analysis (PCA) on macrofauna data transformed by Hellinger’s method, multiple correspondence analysis for environmental data (latitude, elevation, temperature and average annual rainfall, type of vegetation cover) transformed into discrete classes, coinertia analysis to compare these two data sets, and bias-corrected and accelerated bootstrap tests to evaluate the part of the variance of the macrofauna data attributable to each of the environmental factors. Network analysis was performed. Each pairwise association of taxonomic units was tested against a null model considering local and regional scales, in order to avoid spurious correlations. Results: Communities were separated into five clusters reflecting their densities and taxonomic richness. They were significantly influenced by climatic conditions, soil texture and vegetation cover. Abundance and diversity, highest in tropical forests (1,895 ± 234 individuals/m2) and savannahs (1,796 ± 72 individuals/m2), progressively decreased in tropical cropping systems (tree-associated crops, 1,358 ± 120 individuals/m2; pastures, 1,178 ± 154 individuals/m2; and annual crops, 867 ± 62 individuals/m2), temperate grasslands (529 ± 60 individuals/m2), forests (232 ± 20 individuals/m2) and annual crops (231 ± 24 individuals/m2) and temperate dry forests and shrubs (195 ± 11 individuals/m2). Agricultural management decreased overall abundance by ≤54% in tropical areas and 64% in temperate areas. Connectivity varied with taxa, with dominant positive connections in litter transformers and negative connections with ecosystem engineers and Arachnida. Connectivity and modularity were higher in communities with low abundance and taxonomic richness. Main conclusions: Soil macroinvertebrate communities respond to climatic, soil and land-cover conditions. All taxa, except termites, are found everywhere, and communities from the five clusters cover a wide range of geographical and environmental conditions. Agricultural practices significantly decrease abundance, although the presence of tree components alleviates this effect.

Idioma originalInglés
Páginas (desde-hasta)1261-1276
Número de páginas16
PublicaciónGlobal Ecology and Biogeography
Volumen31
N.º7
DOI
EstadoPublicada - jul. 2022

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