The identification of patterns and mechanisms behind species’ distribution is one of the major challenges in ecology, having important outcomes for the conservation and management of ecosystems. This is especially true for those components of biodiversity providing essential ecosystem functions and for which standard surveys may underestimate their real taxonomic diversity due to high degree of cryptic diversity and inherent diagnosis difficulties, such as meiofaunal communities. Within this context, environmental DNA (eDNA) metabarcoding may provide a fast and reliable way to refine and scale-up the characterization of biological diversity in complex environmental samples, allowing to bypass issues related to biodiversity estimation. Moreover, the possibility of integrating eDNA metabarcoding-derived data with tools and methods rooted in network theory would deepen the knowledge on the structuring processes of ecological communities in ways that cannot be predicted from studying individual species/communities in isolation. Here, a sediment eDNA metabarcoding of mitochondrial cytochrome c oxidase I (COI) and nuclear hypervariable V4 region of the 18S rDNA (18S) was used to reconstruct the bipartite networks linking intertidal meiofaunal OTUs and sampling stations from three estuaries of the North-Western Iberian Peninsula. Null models were used to identify the role of environmental and spatial constraints on the structure of COI- and 18S-derived networks and to characterize the macroecological features of surveyed phyla. Our results show the feasibility of eDNA metabarcoding to capture a fair amount of diversity hard to detect with standard survey procedures and to identify hierarchical spatial structures in intertidal meiofaunal assemblages, ultimately suggesting a restricted distributional range mostly driven by niche-based processes.

识别物种分布背后的模式和机制是生态学的主要挑战之一，对生态系统的保护和管理具有重要意义。对于提供基本生态系统功能的生物多样性组成部分尤其如此，并且由于高度神秘的多样性和固有的诊断困难，标准调查可能会低估其真正的分类多样性，例如小型动物群落。在这种情况下，环境 DNA (eDNA) 元条形码可以提供一种快速可靠的方法来完善和扩大复杂环境样本中生物多样性的表征，从而绕过与生物多样性估计相关的问题。而且，将 eDNA 元条形码衍生的数据与植根于网络理论的工具和方法相结合的可能性将加深对生态群落结构过程的认识，这些方式无法通过单独研究单个物种/群落来预测。在这里，线粒体细胞色素 c 氧化酶 I (COI) 和 18S rDNA (18S) 的核高变 V4 区域的沉积物 eDNA 宏条形码用于重建连接潮间带小型动物 OTU 和来自伊比利亚西北部三个河口的采样站的二分网络半岛。空模型用于确定环境和空间约束对 COI 和 18S 衍生网络结构的作用，并表征所调查门的宏观生态特征。