6533b861fe1ef96bd12c5696

RESEARCH PRODUCT

Analysis of spatial patterns informs community assembly and sampling requirements for Collembola in forest soils

Pascal QuernerThomas BolgerTara DirilgenViesturs MelecisEdite Jucevica

subject

0106 biological sciencesCommunityEcologyBeta diversityNiche differentiationSampling (statistics)04 agricultural and veterinary sciences010603 evolutionary biology01 natural sciencesSpatial heterogeneityGeography040103 agronomy & agricultureSpatial ecology0401 agriculture forestry and fisheriesRarefaction (ecology)Species richnessEcology Evolution Behavior and SystematicsNature and Landscape Conservation

description

Abstract The relative importance of niche separation, non-equilibrial and neutral models of community assembly has been a theme in community ecology for many decades with none appearing to be applicable under all circumstances. In this study, Collembola species abundances were recorded over eleven consecutive years in a spatially explicit grid and used to examine (i) whether observed beta diversity differed from that expected under conditions of neutrality, (ii) whether sampling points differed in their relative contributions to overall beta diversity, and (iii) the number of samples required to provide comparable estimates of species richness across three forest sites. Neutrality could not be rejected for 26 of the forest by year combinations. However, there is a trend toward greater structure in the oldest forest, where beta diversity was greater than predicted by neutrality on five of the eleven sampling dates. The lack of difference in individual- and sample-based rarefaction curves also suggests randomness in the system at this particular scale of investigation. It seems that Collembola communities are not spatially aggregated and assembly is driven primarily by neutral processes particularly in the younger two sites. Whether this finding is due to small sample size or unaccounted for environmental variables cannot be determined. Variability between dates and sites illustrates the potential of drawing incorrect conclusions if data are collected at a single site and a single point in time.

https://doi.org/10.1016/j.actao.2017.11.010