Illuminating biodiversity changes in the ‘Black Box’

土壤经常被描述为“黑匣子”，因为令人惊讶的是，人们对居住在那里的高度生物多样性知之甚少。对于地上生物，我们对物种的分布以及它们在未来人类影响下可能发生的变化有很好的了解。然而，尽管土壤生物提供了各种各样的生态系统功能，但我们对它们的分布以及它们的多样性未来可能如何变化的了解非常有限。为了建立准确和可推广的生物多样性模型，基础数据需要代表整个地球。然而，即使我们最近汇编了超过11000个地点的全球蚯蚓数据集，在大范围内仍存在差距。这些差距在许多其他地上和地下多样性的数据集上都是一致的。为了填补这一空白，我们提出了一个采样网络(SoilFaUNa)，以创建一个关于大型土壤动物多样性和土壤功能(如分解速率)的综合数据库。我们将在现有的蚯蚓多样性数据集和SoilFaUNa项目的早期数据的基础上，调查蚯蚓多样性的变化。从我们目前的工作中，我们知道气候和土地利用都是预测蚯蚓多样性的主要驱动因素，但两者都会在未来情景下发生变化，并可能改变生态系统功能。我们将使用空间换时间替代模型来估计蚯蚓多样性及其功能在未来可能发生的变化，建立蚯蚓多样性随气候、土地利用和土壤性质的函数模型，并根据未来情景进行预测。以前使用时间序列分析对地上多样性随时间变化的研究发现，丰富度没有净损失，但分析是批评性的。我们的目标是使用蚯蚓的时间序列数据来推动这场辩论，通过使用数据和统计方法来回应批评，同时增加我们对这一被研究的土类的了解。野外实验和微观/中观宇宙实验已经被用来研究在少数环境条件下一些土壤生物与生态系统功能之间的联系。元分析可以产生概括性的结果，只能回答有数据的问题。因此，我们掌握了土壤动物整个群落与生态系统功能之间的联系，以及各种环境变化对土壤动物群落的影响的信息。使用从SoilFaUNa项目收集的数据，我们将首次综合全球分布的特定采样数据，以模拟土壤大型动物群落组成的变化(由于内陆利用、气候或土壤性质的变化)如何影响土壤中的生态系统功能。

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.