For q ≠ 1, ∞, the diversity profile calculation is thus where . The resulting q D Z (p) is an effective number, and for certain values of q and Z, q D Z (p) corresponds to a check details commonly used diversity index. For example, for naïve diversity profiles

that do not MK 8931 in vivo take into account similarity between species, q = 0 is equivalent species richness, q = 1 is proportional to Shannon Diversity [4], q = 2 is proportional to 1/D (inverse Simpson Diversity) [25], and as q moves toward ∞, it is a measure of 1/Berger-Parker Evenness [5]. We calculated diversity profiles for 0 ≤ q ≤ 5. When plotting the profiles, we created larger insets for 1 ≤ q ≤ 2 [26]. For a more detailed description of the formulae used to calculate diversity profiles (e.g., their relationship to well-known Captisol in vivo diversity metrics, their potential benefits in diversity studies, examples of diversity profiles applied to macro-organism community datasets), refer to

Leinster & Cobbold’s work [17]. Environmental microbial datasets Diversity profiles were used to quantify the diversity of four microbial datasets obtained from different environments containing bacterial, archaeal, fungal, and viral communities. The original four studies were conceived independently by co-authors of the current study, and we utilized these existing datasets to explore applications of diversity profiles to microbial community data. Providing complete details of each study is beyond the scope of the current study, but we have included brief descriptions of the studies’ methods below, and the research questions and hypotheses that shaped the design of each study are detailed in Table 1. We have also provided predicted outcomes of each of the studies, based on data and hypotheses from the original studies (Table 2). For further details of each study, please refer to Interleukin-3 receptor the publications cited below. Table 1 Research questions and hypotheses that shaped the design of the four environmental microbial community datasets   Research

questions Hypotheses Acid mine drainage bacteria and archaea 1) Are environmental (Env) samples more diverse than bioreactor (BR) biofilms? H1: Bioreactor growth conditions usually have a higher pH than the environment, and the geochemistry of the drainage might differ from growth media. Thus, environmental biofilms are expected to be more diverse than bioreactor-grown biofilms. 2) Is biofilm diversity higher at higher stages of biofilm development? H2: As biofilms begin to establish, early growth-stage biofilms are expected to be less diverse. As they mature, more organisms join the community, increasing diversity. Hypersaline lake viruses 1) How do viral diversities change across spatiotemporal replicates? H1: Viral diversity will be greatest in pools with larger volume (2010A and 2007A samples). H2: Community dissimilarity will cluster by site, then by year.