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Punctuated changes in the morphology of an endemic diatom from Lake Titicaca

Published online by Cambridge University Press:  18 January 2018

Trisha L. Spanbauer
Affiliation:
Department of Earth and Atmospheric Sciences and School of Biological Sciences, University of Nebraska–Lincoln, Lincoln, Nebraska 68588, U.S.A. E-mail: tspanbauer@austin.utexas.edu; trishaspanbauer@gmail.com.
Sherilyn C. Fritz
Affiliation:
Department of Earth and Atmospheric Sciences and School of Biological Sciences, University of Nebraska–Lincoln, Lincoln, Nebraska 68588, U.S.A. E-mail: tspanbauer@austin.utexas.edu; trishaspanbauer@gmail.com.
Paul A. Baker
Affiliation:
Division of Earth and Ocean Sciences, Duke University, Durham, North Carolina 27708, U.S.A.

Abstract

High levels of biodiversity and endemism in ancient lakes have motivated research on evolutionary processes in these systems. Drill-core records from Lake Titicaca (Bolivia, Peru), an ancient lake in the high-elevation Altiplano, record the history of climate, landscape dynamics, and diatom evolution. That record was used to examine the patterns and drivers of morphological evolution of an endemic species complex of diatoms in the lake, the Cyclostephanos andinus complex. In an attempt to delineate species within the complex based on morphology, no discernible evidence was found for species separation based on an ordination analysis of multiple characters, but multiple populations were detected based on the distribution of valve size in individual samples. Likelihood modeling of phyletic evolution showed that size evolved through punctuated change. Correlation of size trends with environmental variables indicates that C. andinus size responded to regional environmental change driven by global processes that influenced Lake Titicaca by affecting lake level and thermal stratification.

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Copyright © 2018 The Paleontological Society. All rights reserved 
Figure 0

Figure 1 Map of Lake Titicaca with depth contours of Lago Grande and Lago Huiñaimarca (Fritz et al. 2012). The core material used in this study is from location 2B (star).

Figure 1

Figure 2 From left to right. The percent abundance of Chaetoceros muelleri, a diatom indicative of high saline concentrations. The relative abundance (percentage of total diatom flora) of lumped benthic species and percent calcium carbonate, which are both indicators of low lake levels. Cyclostephanos andinus sensu stricto and Cyclostephanos andinus sensu lato from the Lake Titicaca drill core (Fritz et al. 2012). Images on the far right show some of the morphological variability seen in C. andinus.

Figure 2

Figure 3 Diagram of the morphometric measurements (Tapia et al. 2004) that were used to evaluate phyletic evolution of Cyclostephanos andinus from the drill-core record. APF, areolae per 5 microns; BAD, biseriate areolae distance; FPV, fascicles per valve; UAD, uniseriate areolae distance; VFD, valve-face diameter.

Figure 3

Figure 4 Principal components 1 and 2 from the PCA of Cyclostephanos andinus morphological traits from the low-resolution analysis of Lake Titicaca sediment samples. Convex hulls group the samples into marine isotope stages (MIS).

Figure 4

Table 1 Correlation matrix of the morphometric measurements of Cyclostephanos andinus. The lower half of the matrix contains correlations and the upper half of the matrix reports p-values of the correlations. APF, areolae per 5 microns; BAD, biseriate areolae distance; FPV, fascicles per valve; UAD, uniseriate areolae distance; VFD, valve face diameter.

Figure 5

Figure 5 Right-skewed unimodal valve-size distribution from ~54,000 yr BP and bimodal valve-size distribution from ~180,000 yr BP.

Figure 6

Figure 6 Mean valve-face diameter of Cyclostephanos andinus for the history of the Lake Titicaca drill-core record. Marine isotope stages (MIS) are labeled above the timeline. Shaded area indicates the 95% probability interval for the best-fit punctuated change model.

Figure 7

Table 2 Model results for the size evolution of Cyclostephanos andinus. Models tested were unbiased random walk (URW), generalized random walk (GRW), stasis, punctuated change with one shift (Punc-1), and punctuated change with two shifts (Punc-2). Highest log likelihood (logL) and lowest corrected Akaike information criterion (AICc) scores indicate the best-fitting model. K is the number of parameters in the model. Model weighting (w) shows model support.