Illuminating biodiversity changes in the ‘Black Box’

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Soil is often described as a ‘black box’, as surprisingly little is knownabout the high levels of biodiversity that reside there. Foraboveground organisms, we have good knowledge of the distributionof the species and how they might change under future humanimpacts. Yet despite the fact that soil organisms provide a wide varietyof ecosystem functions, we have very limited knowledge of theirdistribution, and how their diversity might change in the future. Inorder to create accurate and generalizable models of biodiversity, theunderlying data needs to be representative of the entire globe. Yeteven with our recently compiled global earthworm dataset of over11000 sites, there are gaps across large regions. These gaps areconsistent across many other datasets of both above- and belowgrounddiversity. In order to fill the gaps we propose a samplingnetwork (SoilFaUNa), to create a comprehensive database of soilmacrofauna diversity and soil functions (e.g., decomposition rates).Building on the existing dataset of earthworm diversity and early datafrom the SoilFaUNa project, we will investigate changes in earthwormdiversity. From our current work, we know that both climate and landuseare main drivers in predicting earthworm diversity, but both willchange under future scenarios and may alter ecosystem functions.We will, using space-for-time substitution models, estimate howearthworm diversity and their functions might change in the future,modelling earthworm diversity as a function of climate, land use andsoil properties and predicting based on future scenarios. Previousstudies of aboveground diversity changes over time using time-seriesanalysis have found no-net-loss in richness, but analyses have beencriticisms. We aim to use time-series data on earthworms to move thisdebate forward, by using data and statistical methods that wouldaddress the criticisms, whilst increasing our knowledge on thisunderstudied soil group. Field experiments and micro-/meso-cosmexperiments have been used to investigate the link between a numberof soil organisms and ecosystem functions under few environmentalconditions. Meta-analyses, which can produce generaliseable resultscan only answer questions for which there are data. Thus, we havelacking on information on the link between the entire community ofsoil fauna and ecosystem functions, and impact of changes to the soilfauna community across environmental contexts. Using data collectedfrom the SoilFaUNa project, we will for the first time synthesizeglobally distributed specifically-sampled data to model how changesin the community composition of soil macrofauna (due to changes inland use, climate or soil properties) impacts the ecosystem functions in the soil.