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Fig. 2. Plots show diversity versus geologic age for modules in the non- weighted networks. The value of each bin equals the total number of boundary crossing genera, i.e., total diversity minus singletons (4). (A) The o- n network of marine animal orders (Fig. 1A and S/ Appendix, Fig. S4A). (B) The f-n network of marine animal families (Fig. 1B and S/ Appendix, Fig. S5A). (C) The g7-n network of marine animal genera (n= 26,525; S/ Ap- pendix, Fig. S6A). (D) The g2-n network of reef-occurring animal genera (n = 7,621; SI Appendix, Fig. S7A). (E) The g3-n network of reef-building animal genera (n = 2,793; SI Appendix, Fig. S8A).

Figure 2 Plots show diversity versus geologic age for modules in the non- weighted networks. The value of each bin equals the total number of boundary crossing genera, i.e., total diversity minus singletons (4). (A) The o- n network of marine animal orders (Fig. 1A and S/ Appendix, Fig. S4A). (B) The f-n network of marine animal families (Fig. 1B and S/ Appendix, Fig. S5A). (C) The g7-n network of marine animal genera (n= 26,525; S/ Ap- pendix, Fig. S6A). (D) The g2-n network of reef-occurring animal genera (n = 7,621; SI Appendix, Fig. S7A). (E) The g3-n network of reef-building animal genera (n = 2,793; SI Appendix, Fig. S8A).

Related Figures (3)

Fig. 1. Graphs of nonweighted networks partitioned with the Louvain al- gorithm. (A) The o-n network of marine animal orders (n = 621), which fall into three main modules, resembling the Cambrian, Paleozoic, and Modern evolutionary faunas (1). (B) The fn network of marine animal families (n = 3,729), which fall into five modules, similar to the main clusters in the cor- responding generic-level (g7-n and g2-n) networks. Values in parentheses indicate the modules’ proportions of their respective networks. See figures in S! Appendix for additional graphs (S/ Appendix, Figs. S4—-S8).
Fig. 1. Graphs of nonweighted networks partitioned with the Louvain al- gorithm. (A) The o-n network of marine animal orders (n = 621), which fall into three main modules, resembling the Cambrian, Paleozoic, and Modern evolutionary faunas (1). (B) The fn network of marine animal families (n = 3,729), which fall into five modules, similar to the main clusters in the cor- responding generic-level (g7-n and g2-n) networks. Values in parentheses indicate the modules’ proportions of their respective networks. See figures in S! Appendix for additional graphs (S/ Appendix, Figs. S4—-S8).
Fig. 4. Ecological severities of biotic crises and critical transitions. Plot shows the total swing in diversity of each Phanerozoic (post-Fortunian) geologic stage for the nonweighted (o-n, f-n, and g1-n) networks. A swing is a rel- ative change in representation (i.e., growth of one module and reduction of another) across an interval, and is expressed in terms of percent total di- versity minus singletons (data downloaded from the PBDB using the contain method of time binning). To calculate total swing for a geologic stage, the absolute difference in percent total diversity between the upper and lower boundaries was determined for each module. The sum of these values was then determined and divided by 2. Results did not significantly vary with binning approach (S/ Appendix, Fig. $13).
Fig. 4. Ecological severities of biotic crises and critical transitions. Plot shows the total swing in diversity of each Phanerozoic (post-Fortunian) geologic stage for the nonweighted (o-n, f-n, and g1-n) networks. A swing is a rel- ative change in representation (i.e., growth of one module and reduction of another) across an interval, and is expressed in terms of percent total di- versity minus singletons (data downloaded from the PBDB using the contain method of time binning). To calculate total swing for a geologic stage, the absolute difference in percent total diversity between the upper and lower boundaries was determined for each module. The sum of these values was then determined and divided by 2. Results did not significantly vary with binning approach (S/ Appendix, Fig. $13).
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GeologyBiodiversityInvertebrate ZoologyData sciencesInvertebrate PaleontologyConservation PaleobiologyData ScienceMass ExtinctionBiological evolutionMarine Community Ecology
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