25Environmental metabolomics, enabled by high-resolution mass spectrometric techniques, have 26 demonstrated the biogeochemical importance of the metabolites which comprise natural organic 27 matter (NOM). However, significant gaps exist in our understanding of the spatiotemporal 28 organization of NOM composition. We suggest that the underlying mechanisms governing NOM 29 can be revealed by applying tools and concepts from metacommunity ecology to environmental 30 metabolomics. After illustrating the similarities between metabolomes and ecological 31 communities, we call this conceptual synthesis 'meta-metabolome ecology' and demonstrate its 32 potential utility using a freshwater mass spectrometry dataset. Specifically, we developed three 33 relational metabolite dendrograms using combinations of molecular properties (i.e., aromaticity 34 index, double-bond equivalents, etc.) and putative biochemical transformations. Using these 35 dendrograms, which are similar to phylogenetic or functional trait trees in ecological communities, 36we illustrate potential analytical techniques by investigating relationally-informed α-diversity and 37 β-diversity metrics (e.g., MPD, MNTD, UniFrac), and null model analyses (e.g., NRI, NTI, and 38 βNTI). Furthermore, we demonstrate that this synthesis allows ecological communities (e.g., 39 microbes) and the metabolites they produce and consume using the same framework. We propose 40 that applying this framework to a broad range of ecosystems will reveal generalizable principles 41 that can advance our predictive capabilities regarding NOM dynamics. 42 43 44 45 46 47 48Environmental metabolomics enables the investigation of the metabolic processes and interactions 49 occurring within an ecosystem and can provide deep insight into ongoing biogeochemical cycles 50 (Graham et al. 2018;Stegen et al. 2018; Sengupta et al. 2019; Garayburu-Caruso et al. 2020). This 51 knowledge has been collected using high-resolution mass spectrometric techniques, such as like 52Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and Orbitrap, which 53 have allowed researchers to investigate the individual carbon compounds that constitute natural 54 organic matter (NOM). As these studies increasingly become spatiotemporally resolved, an 55 investigation of the underlying processes driving metabolome variability becomes necessary in 56 order to develop transitive principles and enhance predictive capabilities across ecosystems. While 57 many metabolomics studies have used multivariate methods to identify if differences exist between 58 metabolomes (Kellerman et al. 2014(Kellerman et al. , 2019 Dalcin Martins et al. 2017; Graham et al. 2017; Tfaily 59 et al. 2018;Zark & Dittmar 2018), they have limited capacity to reveal processes that constrain or 60 promote variation (Gilbert et al. 2012;Stegen et al. 2012; Cavaco et al. 2019). To better understand 61 the processes governing metabolome composition, we propose integrating concepts and tools 62 developed in metacommunity ecology, th...