Summary Species absent from a community but with the potential to establish (dark diversity) are an important, yet rarely considered component of habitat‐specific species pools. Quantifying this component remains a challenge as dark diversity cannot be observed directly and must be estimated. Here, we empirically test whether species ecological requirements or species co‐occurrences provide accurate estimates of dark diversity. We used two spatially nested independent datasets, one comprising 3033 samples of coastal grassland vegetation from 4 m2 and 200 m2 plots from Scotland, UK, and another comprising 780 samples of forest vegetation plots from 30 m2 and 500 m2 plots from Switzerland. Dark diversity for each of the smaller scaled plots was estimated through investigating the degree of (i) similarity in ecological requirements (measured as Ellenberg values); and (ii) co‐occurrence likelihood. Estimates were validated using species from the larger spatial scales. Estimates were further validated using observations from all larger scale plots surrounding a focal assemblage within a 2 km (Scottish grassland) and 10 km (Swiss forest) radius. The co‐occurrence method was shown to be more accurate resulting in far fewer negative mismatches (i.e. species observed but not predicted), as well as higher proportions of observed and predicted species, relative to the Ellenberg method. Of the species observed in the large‐scale samples, 18% were estimated as part of the smaller scale dark diversity via the co‐occurrence approach relative to 8% for the Ellenberg method for both the Scottish and Swiss data, respectively. These values increased to 67% & 60% and 32% & 35%, respectively, across all observations within a 2 km (Scottish grasslands) and 10 km (Swiss forests) radius. The study demonstrates that dark diversity for a community can be successfully estimated using readily available data, through exploring species co‐occurrence patterns. This work substantiates that habitat‐specific species pools can be accurately quantified and should prove valuable for understanding underlying community processes and improving our knowledge of the mechanisms governing species co‐existence.

1. Trait differences among plants are expected to influence the outcome of competition; competition should be strongest between similar species (or individuals) under limiting similarity, and between dissimilar species within competitive hierarchies. These hypotheses are often used to infer competitive dynamics from trait patterns within communities. However, plant traits are frequently plastic in response to competition. This variation is poorly accounted for in trait-based studies of competition and community assembly. 2. To explore the relationship between trait responses and competitive outcomes, we grew 15 species alone, in monoculture and in mixture. We measured traits relating to leaf and root tissue morphology as well as biomass allocation and related competition-induced changes in these traits to intra-and interspecific competition using multi-model inference. Additionally, we tested how traits from different competitive environments influenced potential community assembly inferences. 3. The competitive environment had large effects on species' traits, although many effects were species specific. Differences among species in how competition affected trait expression were linked to both intra-and interspecific competition, frequently affecting competitive hierarchies. Intraspecific competition was lower for species that limited competition-induced increases in root allocation and had less variability in this trait overall. Interspecific competition was lower for species with larger leaves and lower specific leaf area than their neighbours. Switching to more stress-tolerant strategies by increasing root diameter and leaf tissue density also reduced competition. However, dissimilarity in root tissue density also minimized competition, consistent with limiting similarity affecting competitive outcomes. Moreover, changes in these traits were linked to changes in functional diversity, suggesting that competition affects functional diversity by affecting trait expression. 4. Synthesis. Both trait hierarchies and trait dissimilarity affect the outcome of competition by acting on different traits, although competition-induced changes in trait expression can alter competitive outcomes. Moreover, the magnitude of these trait changes suggests that the source environment where plant traits are collected can affect the inferences drawn from trait patterns within communities. Combined, our results suggest that considering the effect of competition on trait expression is critical to understanding the relationship between traits and community assembly.

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.