Illuminating biodiversity changes in the ‘Black Box’

土壤通常被描述为一个“黑匣子”，因为令人惊讶的是，人们对那里的高水平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的变化有很好的了解。然而，尽管土壤生物提供了多种多样的生态系统功能，我们对它们的分布以及它们的多样性在未来如何变化的知识非常有限。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仪。然而，即使我们最近编制的全球超过11000个站点的数据集，在大区域之间也存在差距。这些差距在许多其他地上和地下多样性数据集上是一致的。为了填补空白，我们提出了一个采样网络（SoilFaUNa），以创建一个全面的土壤动物多样性和土壤功能数据库（例如，基于现有的蚯蚓多样性数据集和SoilFaUNa项目的早期数据，我们将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植被多样性的主要驱动力，但在未来情景下，两者都将发生变化，并可能改变生态系统功能。我们将使用时空替代模型，估计植被多样性及其功能在未来可能发生的变化，将植被多样性建模为气候、土地利用和土壤特性的函数，并根据未来情景进行预测。以前的研究，地上多样性变化随着时间的推移，使用时间序列分析发现，没有净损失的丰富性，但分析已被批评。我们的目标是利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解决这些批评，同时增加我们对这一未研究的土壤组的知识。通过田间试验和微观/中观实验，研究了在少数环境条件下，土壤生物与生态系统功能之间的关系。荟萃分析，可以产生概括性的结果，只能回答有数据的问题。因此，我们缺乏关于整个土壤动物群落与生态系统功能之间联系的信息，以及土壤动物群落变化对环境背景的影响。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，以模拟大型土壤动物群落组成的变化（由于内陆使用，气候或土壤特性的变化）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.