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\section{Introduction}  A central goal in ecology is to identify and understand the processes that influence the distributions of species in space and time. Often, these assembly processes are not directly observable over feasible time scales and must instead by inferred through pattern \cite{Levin_1992}. One increasingly popular approach is to use the values and abundances of species traits in a community as evidence for the influence of particular assembly processes \cite{Cavender_Bares_2004,Ackerly_2007,Kraft_2008}. Trait-based approaches have several advantages over strictly taxonomic approaches in that they are quantitative, easily generalizable, and have explicit ties to ecological strategy and performance \cite{McGill2006,Violle_2007}.  Unfortunately, inferring process from community trait patterns is not always straightforward because different processes can lead to similar patterns, multiple processes can operate simultaneously on multiple traits, and patterns can be affected by exogenous forces. For example: community assembly is sometimes depicted as a balance between environmental filtering, in which species unable to tolerate environmental conditions are filtered out resulting in a clustering of trait values, and niche differentiation, in which competition and limiting similarity result in trait values that are more evenly spaced than expected by chance \cite{Cavender_Bares_2004,Kraft_2007}. But recent work has shown that environmentally-filtered communities can result in random or overdispersed trait patterns (e.g. when there is sufficient within-community environmental heterogeneity) \cite{DAndrea2016}, and competition-structured communities can result in clustering patterns \cite{Mayfield_2010}. In addition, pattern-based evidence of assembly processes can be obfuscated by propagule pressure from adjacent communitiesa framework for multi-scale community ecology  \cite{Leibold_2004}, or by fluctuating environmental conditions that favor different species over time \cite{Chesson_1981,Chesson_1994}. Although it is unlikely that a single pattern-based test will ever provide incontrovertible evidence for niche differentiation, analysis of community trait structure can still shed light on assembly processes if used properly. Different metrics should be used in complementary ways to provide more detailed, and thus more interpretable characterizations of community trait structure. In one recent study, \cite{DAndrea2017} suggest a stepwise analysis pipeline in which potential niches along trait axes are identified using a clustering algorithm, and if clusters are identified, then the fine-scale abundance structure within each cluster is examined for evidence of distance-based competition. Next, tests of community trait structure should be conducted along environmental gradients where they can potentially be tied to mechanistic predictions derived from existing ecological theory \cite{Webb_2010}. Lastly, analyses of community trait structure should be used to develop and select hypotheses for experimental testing in the field, rather than be considered as compelling standalone evidence.