EDIACARAN DISTRIBUTIONS IN SPACE AND TIME
TABLE 1. List of Ediacaran locality codes used in NMDS analyses.
Code Nil
Nam Region
Nilpena, South Australia Namibia, Southern Africa
Mog_PUK Podolia, Ukraine WS ZG
Sol KR
Suz
Ong LR
Kh_khat Loc
MatoGDS Lubcl Brad NQ DP
Nain Muss Ferry Shin LMP
D_sur E_sur G_sur BC PC DC BV SB
GrH Car_SB
SB_Nor1/ SB_Nor2
Blu SecA
Dea_V3 Mont Jiang
Lijian Gaoj
Muz2Sh Miah1
Omn Sali1
Fitz Ural Mountains, Russia
Winter Coast, Arkhangelsk Region, Russia
Solza River, Arkhangelsk Region, Russia
Karakhta River, Arkhangelsk Region, Russia
Suzma River, Arkhangelsk Region, Russia
Onega River, Arkhangelsk Region, Russia
Lyamsta River, Arkhangelsk Region, Russia
Olenek Uplift, Siberia Rio Apa Block, Paraguay Mato Grosso do Sul, Brazil Lubcloud Assemblage, U.K. Bradgate Park, U.K. North Quarry, U.K. Finnmark, Norway
Nainital Syncline, Krol Belt, India Mussoorie Syncline, Krol Belt, India Ferryland, Newfoundland Shingle Head, Newfoundland
Lower Mistaken Point, Newfoundland D Surface, Newfoundland E Surface, Newfoundland G Surface, Newfoundland Bristy Cove, Newfoundland Pigeon Cove, Newfoundland Daley’s Cove, Newfoundland
Bonavista Penninsula, Newfoundland Spaniard’s Bay, Newfoundland Green Head, Newfoundland Carolina Slate Belt, U.S.A.
Bluefish Creek,NWCanada Wernecke Mountains, Yukon Death Valley Region, U.S.A. Montgomery Mountains, U.S.A.
Blueflower/June Beds, Sekwi Brook, NWCanada
577
Jiangkou County, Guizhou Province, China
Lijiangou, Shaanxi Province, China Gaojishan, Shaanxi Province, China Yangtze Gorges, Hubei Province, China
Miaohe, Yangtze Gorges, Hubei Province, China
Huqf Supergroup, Oman
Salient Mountain, Rocky Mountains, Canada
Mt. Fitzwilliam, Rocky Mountains, Canada
Data Analysis We used nonmetric multidimensional
scaling (NMDS) to ordinate the 86 Ediacaran localities in multidimensional space based on
taxonomic similarity (Jaccard distance).NMDS was chosen over other computational techniques that rely on a Euclidean (linear) relationship between variables and taxonomic composition (such as principal components analysis) as it: (1) uses rank orders, which can accommodate a variety of nonnumerical data types (e.g., presence/absence of taxa and qualitative geological properties used in this study), and (2) is widely accepted as a stan- dard statistical metric within contemporary ecological and community analysis studies (Clapham 2011, and references therein).NMDS collapses multidimensional ranked data into two-dimensional scatter plots (axes NMDS1 and NMDS2), which allows for visualization and interpretation of trends within large data sets. The calculated stress for this original taxonomic ordination was low (0.071), indicat- ing that the resulting biplot provides an excellent representation of rank orders in reduced dimensions (Clarke 1993). Once a taxonomic ordination using NMDS was generated, we then overlaid convex hulls (polygons) representing sites corresponding to the original three assemblages identified by Waggoner (1999, 2003). We then created a second set of polygons linking sites with similar temporal (i.e., time bin), paleoenviron- mental (depositional environment and water depth), and lithological characteristics. The degree to which these polygons overlap provides a visual indication of the extent to which the Waggoner assemblages are controlled by time, paleoenvironment, and lithology. We evaluated the statistical validity of these polygons using two methods. First, function “ordiellipse” draws 95% confidence intervals (CIs) around class centroids as ellipses. If the ellipses do not overlap, they are outside of the assigned level of confidence, and the polygons are therefore considered significantly different (Supplementary Table S.4). Second, we quantified the dissimilarity between polygons in partitioned (i.e., “assem- blage,”“lithology,”“time,” etc.) data sets using three beta-diversity metrics: (1) mean Jaccard dissimilarity of all pairwise compar- isons between categories, (2) multisite Soren- son’s dissimilarity, and (3) multisite Simpson’s dissimilarity metric using package betapart
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