Population Density Effects on Carapace Growth in Clam Shrimp: Implications for Palaeontological Studies

© 2020 Academia Sinica, Taiwan Open Access Special Issue: Fossil and Modern Clam Shrimp (Branchiopoda: Spinicaudata, Laevicaudata) Population Density Effects on Carapace Growth in Clam Shrimp: Implications for Palaeontological Studies Manja Hethke1,* and Stephen C. Weeks2 1Institut für Geologische Wissenschaften, Freie Universität Berlin, Malteserstraße 74-100, D-12249 Berlin, Germany. *Correspondence: E-mail: [email protected] (Hethke) 2Department of Biology, The University of Akron, Akron, Ohio 44325-3908, USA. E-mail: [email protected] (Weeks) Received 30 January 2020 / Accepted 1 June 2020 / Published 5 August 2020 Special issue (articles 32-46) communicated by Thomas A. Hegna and D. Christopher Rogers Fossil morphological data are time-averaged and generally reflect an overlap of different sources of carapace variability. To examine whether a proposed relationship between size and population density in fossil spinicaudatans is biologically meaningful, we set up rearing experiments involving two extant species: Eulimnadia texana and Eocyzicus argillaquus. Three and five days after hydration, clam shrimp were transferred into cups of various population densities that ranged between 1 and 15 inds/400 ml. Size and shape were measured 14 and 16 days after hydration, respectively. Every second day, we recorded length and sex of E. texana, which matured faster in lower-density cups. According to our growth model, population density and maximal carapace length follow a logarithmic relationship. At maturity, hermaphrodites yielded similar lengths across all population densities (~4.7 mm at 24°C), independent of age. Hence, clam shrimp can put off reproductive maturity as a response to decreased growth under higher density conditions. Growth rate generally decreases at maturity, but that effect is more pronounced in clam shrimp of high population densities, while low-density adults keep growing. For both species, multivariate analyses reveal that carapace size of low-density individuals is significantly larger than carapace size of higher-density individuals, while size values of intermediate densities cannot be distinguished. Shape distinction is strong in hermaphrodites of E. texana: 39.8% of the density-dependent shape variation is associated with relative umbo height, which is generally higher in individuals of smaller population densities. The H/L ratio, which is often used as a simple shape indicator, does not contribute to the main variation in shape, but it forms one of several ratios significant for 18.3% of the shape variability. In turn, the H/L ratio drives 30% of the shape variation in E. argillaquus. In addition, higher densities triggered shifts in ontogenetic growth trajectories in one third of the individuals, which led to aberrant morphologies. The present rearing experiment shows that some of the morphological variability on fossil bedding planes can be explained by population density. Also, it implies a considerable amount of ecophenotypic variability in Spinicaudata that affects our understanding of fossil taxonomy and palaeoecology. Key words: Freshwater ecology, Morphometrics, Palaeontology, Phenotypic plasticity, Spinicaudata. Citation: Hethke M, Weeks SC. 2020. Population density effects on carapace growth in clam shrimp: implications for palaeontological studies. Zool Stud 59:33. doi:10.6620/ZS.2020.59-33. BACKGROUND Lake environments witnessed major reorganizations during the Late Cretaceous to Paleogene, exemplified by a dramatic decline of spinicaudatan presence in the fossil record (Chen and Shen 1981; Gallego and Mesquita 2000; Astrop et al. 2015; Stigall et al. 2017). Studying the role of Spinicaudata in fossil lake ecosystems will be crucial for understanding that decline in diversity. Zoological Studies 59:33 (2020) doi:10.6620/ZS.2020.59-33 1 © 2020 Academia Sinica, Taiwan To evaluate changes in fossil carapace size and shape through time, we require a sound understanding of intraspecific variability in extant species. Ontogenetic shape variability can be considerable in extant taxa (Brown et al. 2014), however, there is comparatively little information on ecophenotypic size and shape variability. Huang and Chou (2015 2017) reported strong temperature effects on developmental time and general life history traits in the androdioecious species Eulimnadia braueriana Ishikawa, 1895, including earliest hatching time and earliest maturation time; adaptations that may lead to niche differentiation between sympatric species. Rearing experiments of the present study follow hypotheses based on palaeontological observations. Data that are easily obtainable during excavations are size and population density (number of specimens preserved on respective bedding planes by area). Such specimen counts predict a strong density effect on carapace size, as demonstrated by Wang et al. (2019) and Hethke et al. (2019) for the Middle Jurassic Triglypta haifanggouensis (Chen, 1976 in Zhang et al. 1976) and the Early Cretaceous Eosestheria cf. middendorfii (Jones, 1862). Low population densities correlate with large carapace sizes and vice versa. However, such palaeontological observations are biased by time averaging and other sources of size and shape variation. Observed morphologies on bedding planes represent a combination of ontogenetic variability, sexual dimorphism, ecophenotypic variability, deformation, and species evolution. To evaluate whether the proposed density effect on morphology reflects a biologically meaningful relationship, we investigate the size and shape response to different population densities in two extant spinicaudatans: Eulimnadia texana (Packard, 1871) and Eocyzicus argillaquus (Timms and Richter, 2009). MATERIALS AND METHODS Rearing of Eulimnadia texana and Eocyzicus argillaquus Population density effects on carapace growth have been examined by rearing two species of two different extant families. Eulimnadia texana (Limnadiidae) was reared from sediment collected by SCW in Arizona (USA; “Wallace” pool) in 2003 and Eocyzicus argillaquus (Eocyzicidae, per Schwentner et al. 2020) from sediment collected in Western Australia in 2007 (Cullimbin Pool 5). Rearing tanks and cups remained constantly lit under sunlight-simulating fluorescent bulbs (Duro-Test Corp.) and were kept in a windowless room air-conditioned to 24°C. All individuals were reared under the same environmental conditions prior to their separation into cups of various population densities. Resting eggs of Eulimnadia texana were hydrated in a 10-gallon tank on 18 September 2017. Three days after hydration, we transferred 15, 10, 5, and 1 juveniles into 400 ml plastic cups (depth ~7.5 cm, diameter 8.3 to 11 cm), which were filled with wet-sieved (74 µm mesh size) aquarium water from an earlier (6-day old) branchiopod population reared from the same sediment. We replicated the experiment four times for singleindividual cups, and twice for fiveand ten-individual cups. Eocyzicus argillaquus eggs were hydrated in a five-liter tank on 25 September 2017, and we recorded a huge hatch (50–75/liter) a day later. Hence, all individuals experienced comparatively high population densities during the first few days. Juveniles were transferred into 400 ml plastic cups on 30 September 2017 using sieved water from an earlier branchiopod population reared from Wallace sediments. We replicated single-individual cups four times, while 3-, 5-, 7-, 10-, and 15-individual cups were replicated twice. Carapace size and shape were measured once, 16 days after hydration. Cup identifications indicate the initial density and the replicate (e.g., cup 5.2 = initial density of 5, replicate 2). Cups were monitored daily for mortality, and dead individuals were removed and measured. We ended each experiment when mortality rate increased substantially. Depending on mortality rate, per-cup population densities decreased during the experiment. We considered the influence of individuals that died during the experiment on population density by standardizing density: Per-day population density was calculated by multiplying the initial population density with the proportion between the sum of days each individual remained alive in a cup and the potential number of days over all individuals (i.e., if all individuals had survived). Example: initial density = 3, days = 4, and one individual found dead when the cup was examined on day 3 would result in a population density of 3×(3+3+2+2)/12 = 2.5. So, even though there were only eleven individuals of Eulimnadia texana remaining in cup 15 (= initial population density) 14 days after hydration, the standardized population density was a little higher: 12.75. Growth (length) of 49 male and hermaphrodite Eulimnadia texana was measured 3, 5, 7, 9, 11, 14, and 16 days after hydration, resulting in a set of 282 measurements. Several individuals died during the experiment; 37 clam shrimp were still alive 14 days after hydration, while there were only 27 individuals page 2 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan remaining two days later. To ensure an adequate sample size, we analysed size and shape of the 14-day old population. An Olympus microscope equipped with a COHU High Performance CCD Camera and the Scion Image software package were used for photography. To evaluate whether there was a population density effect on earliest maturation time, we documented sexual maturity during days of photography, resulting in a twoday resolution on maturation. Each 400 ml cup was fed 1 ml of food per day [food mixture contained 0.5 g yeast and 0.5 g ground fish flake food (Tetramin) per 100 ml]. Hence, higher density cups received less food per individual. Analytical methods Possible effects of population density on growth were tested by collecting size and shape data for all surviving individuals 14 days (Eulimnadia texana) and 16 days (Eocyzicus argillaquus) after hydration (Tables S1–4). Population survival for Eulimnadia texana was recorded for an extra two days. Size and shape data for Eulimnadia texana was restricted to a hermaphroditeonly dataset (33 outlines), while Eocyzicus argillaquus is represented by both males and females (52 outlines). In a separate study, we analysed sexual dimorphism in E. argillaquus. For each specimen, we documented the valve outlined. Right valves were horizontally mirrored for shape analysis. Finally, we ordinated size and shape data using principal component analysis (PCA) on a variance-covariance matrix. To identify the number of meaningful PC shape variables, we used a scree plot that plots eigenvalues against a random model (Jackson 1993). Data analyses were carried out using the JMP Pro 14 package and the PAST software (version 3.24, folk.uio.no/ohammer/past/; Hammer et al. 2001). Growth model for Eulimnadia texana We fitted the growth data of each population density to a nonlinear function that can be used to model growth in organisms (von Bertalanffy: y = a(1-be-cx); Brown and Rothery 1993). For each population density, the value of a represents an estimation of maximal carapace length according to the model (max. y). Size (Linear measurements) The size datasets in tables S1 and S3 each consist of nine linear variables (Fig. 1). While variable Cr was reconstructable for Eocyzicus argillaquus, it was not clear for Eulimnadia texana, for which we measured the distance from the dorsal margin to the highest point of the umbo (u). Size data has been log-transformed prior to PCA. PC axes have been interpreted by assessing associated eigenvector coefficients (loadings). Shape There is shape information in a multivariate dataset of linear measurements. It has been suggested to use Burnaby’s method (Burnaby 1966) for size Fig. 1. Linear carapace variables used for A, Eocyzicus argillaquus and B, Eulimnadia texana, following Defretin-Lefranc (1965) and Tasch (1987): A, most anterior point of the valve; B, most posterior point of the valve; C, most ventral point of the valve; D, anterior extremity of the dorsal margin; E, posterior extremity of the dorsal margin; U, midpoint of the larval valve (located on the umbo, but not necessarily the midpoint of the umbo). a, vertical distance of A to A'; b, vertical distance of B to B'; c, horizontal distance of C to A''; Arr, horizontal distance of E to B'; Av, horizontal distance of D to A'; Ch, length of the dorsal margin; Cr, horizontal distance of U' to A'; u, vertical distance of Ch to highest point of the umbo; L, valve length; H, valve height. page 3 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan correction (Rohlf and Bookstein 1987; Rohlf 1990; Hammer and Harper 2006), which eliminates variation parallel to PC1 by projecting log-transformed measurements onto a plane orthogonal to this axis. This transformation should remove the size-dependent variation in a multivariate set of linear measurements. A second method to explore shape is Fourier shape analysis (Crampton and Haines 1996; Haines and Crampton 2000). Outlines were transformed to 2000 xy-coordinates using the program tpsDig2 (version 2.31). Subsequently we used the program Hangle (Crampton and Haines 1996) to remove high frequency pixel noise that resulted from the automatic tracing of outlines by taking the weighted moving average over three coordinates (10 smoothing iterations). Hangle also performed the Fast Fourier Transform (FFT). As starting position, we chose the posterior extremity of the dorsal margin. A second program, Hmatch, normalized for starting position and orientation by minimizing the sums of the squares of all differences between the outlines (Haines and Crampton 2000). The highest order positive harmonic kept was 12, resulting in 22 shape variates (Fourier coefficients) for each specimen. In a final step, we projected the Fourier coefficient dataset (Tables S2 and S4) using principal component analysis (PCA). To interpret the shape plots, we fitted bivariate datasets using ordinary least squares regression and explored whether the shape variables PC1 and PC2 (scores from PCA of Fourier coefficients) were linearly related to ratios u/(u+H), H/L, and Ch/L. All residual plots have been checked for patterns indicating nonlinear relationships. Statistical testing We used non-parametric MANOVA (NPMANOVA) to test whether clam shrimp of various population densities form statistically distinct morphological groups, based on Euclidean distances. NPMANOVA estimates the significance by permutation across groups (N = 9.999; Hammer and Harper 2006). An a-priori group consisted of all individuals of a specific population density in a 400 ml cup. Significant pairwise comparisons at p < 0.05 were shaded in according tables. RESULTS Eulimnadia texana Population survival We ended the experiment 16 days after hydration. All single-density individuals and those in cup 5.2 survived, cup 5.1 went from a population density of 5 to 4.1 inds/400 ml, cup 10.1 to 9.3 inds/400 ml, cup 10.2 to 6.7 inds/400 ml and cup 15 to 12.1 inds/400 ml (Fig. 2A; Table 1A). Eulimnadia texana Carapace length According to the growth models in figures 2B and 3, the expected length in single-individual cups is 7.3 mm, while individuals of cup 15 reach Fig. 2. Eulimnadia texana experiment (number of individuals = 49). Individuals were transferred into cups of various population densities three days after hydration (1, 5, 10 and 15 individuals/400 ml). A, Population survival. All individuals in cup 5.2 and in the four single-individual cups survived, while density declined fast in cups 10.2 and 15. B, Superimposed growth curves for all nine cups (compare with Fig. 3). page 4 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan considerably smaller expected lengths of 5.1 mm. The superimposition of growth curves in figure 2B shows that maximal carapace lengths are ranked according to population density 16 days after hydration. Both, standardized population density and modelled maximal lengths are best fitted using natural log regression (Fig. 4A). In general, expected lengths decrease while population density increases. Also, the number of growth bands increases while length increases (Fig. 4B). Length at maturity A number of Eulimnadia texana hermaphrodites started carrying eggs on 25 September (seven days after hydration; Fig. 3). Two of three hermaphrodites were mature in cups 1.1–1.5, six of nine hermaphrodites in cups 5.1 and 5.2, and six of 15 hermaphrodites in cups 10.1 and 10.2 (Fig. 3). None of the clam shrimp in cup 15 were mature that day, implying a population density effect on earliest maturation time. Two days later, there was only one non-mature hermaphrodite in cup 15. At earliest maturation time, average hermaphrodite lengths were 4.7 mm, 4.3 mm, 4.9 mm, 4.7 mm and 4.8 mm at 1.0, 4.4, 5, 10 and 8.2 inds/400 ml, respectively. On the same day, immature clam shrimp (hermaphrodites and males) of cup 15 yielded distinct average lengths of 4.1 mm. Nine days after hydration, hermaphrodites of cup 15 reached 4.7 mm (density: 13.43 inds/400 ml). At maturity, hermaphrodite length of different population densities cannot be statistically distinguished (Table S5). These data suggest average hermaphrodite body lengths of 4.7 mm at earliest maturation time (n = 23; at 24°C), based on a resolution of two days. Eulimnadia texana Size PC1 and PC2 explain 82.4% and 9.9% of the variance in the log-transformed size dataset. All nine linear variables have positive loadings on PC1, which are illustrated by vectors in the biplot of figure 5A. So, all variables increase towards positive scores of PC1, which can thus be regarded as a general size axis, although log-transformation added an aspect of Table 1. Cup identification, initial density, and standardized population density. (A) Eulimnadia texana. (B) Eocyzicus argillaquus (A) Eulimnadia texana Cup ID Initial density Stand. density, 14 days Stand. density, 16 days 1.1 1 1.00 1.00 1.3 1 1.00 1.00 1.4 1 1.00 1.00 1.5 1 1.00 1.00 5.1 5 4.17 4.14 5.2 5 5.00 5.00 10.1 10 9.83 9.29 10.2 10 7.08 6.71 15.1 15 12.75 12.14 (B) Eocyzicus argillaquus Cup ID Initial density Stand. Density, 16 days 1.1 1 1.00 1.2 1 1.00 1.3 1 1.00 1.4 1 1.00 3.1 3 2.75 3.2 3 2.58 5.1 5 4.83 5.2 5 4.42 7.1 7 6.58 7.2 7 6.25 10.1 10 9.33 10.2 10 9.50 15.1 15 14.00 15.2 15 13.83 page 5 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan shape. Figure 5A also shows that specimens in cup 15 (= population density of 12.8 inds/400 ml, 14 days after hydration) mostly occupy negative scores on PC1 while single-individual cups (red) occupy positive scores on PC1. Hence, size in high-density cups is generally smaller than in low-density cups. Specimens of intermediate population densities occupy intermediate areas along PC1. Both, PC1 and PC2, are driven by Av, while PC2 is also strongly influenced by variables Arr and u. NPMANOVA of log-transformed linear measurements indicates that differences in size are significant across different population densities (Table 2A; p(same) = 0.0002). However, pairwise comparisons reveal that only density extremes (cups 1 and 15) yield significantly different carapace sizes compared to other population densities. Intermediate densities cannot be separated. In comparison to length (Fig. 4), size (PC1 scores) by population density can also be well fitted by a linear relationship for Eulimnadia texana (Fig. S1; that of Eocyzicus argillaquus is best fitted by a logarithmic relationship). During the outlining process, we noticed that the anterior dorsal extremity (landmark D in Fig. 1), which highly influences values of Av, was sometimes difficult to identify. Hence, we carried out a second analysis with a reduced set of log-transformed linear measurements (H, L, Ch, u) that resulted in an overall similar plot, except that PC2 now explained a larger proportion of the variance in the dataset (17.1%). All four variables drive PC1 at almost equal proportions. H, L, and Ch increase towards positive scores of PC2 while u decreases. In general, there seems to be little difference between the analyses of nine and four linear variables. NPMANOVA yielded almost the same result except for one pairwise comparison (cups 15 and 10.1) that cannot be statistically distinguished in table 2B. Eulimnadia texana Shape According to Fourier shape analysis (PC of Fourier coefficients in figure 5B, NPMANOVA in Table 3), there is an overall significant population density effect on carapace shape (p(same) = 0.0001). Nine of fifteen pairwise comparisons exhibit significantly different shapes. Most non-significant comparisons can be explained by similar population densities 14 days Fig. 3. Eulimnadia texana experiment, n = 282. Growth model curves follow the von Bertalanffy equation y = a(1-be-cx). The value of a represents an estimation of maximal length (max. y). Colours represent hermaphrodites (red), males (blue), and juvenile or unclear (black). Numbers in upper left corner represent initial population density and replicate. page 6 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan after hydration, except for two comparisons that include cup 10.2 (density 7.1 inds/400 ml), for which the p-value is, however, close to the significance level (set to α = 0.05). Eigenvalues plotted against a random model (scree plot) resulted in two significant components. PC1 and PC2 explain 39.8% and 18.3% of the variance in the Fourier dataset (Fig. 5B). Extreme shapes along PC1 indicate a much larger relative umbo height in lowdensity cups (Fig. 6). The shape plot can be further interpreted using ordinary least squares regression of PC1 and PC2 scores versus ratios u/(u+H), H/L, Ch/L (Fig. 7). According to figure 7A–C, PC1 is driven by relative umbo height, while the regression is not significant for the H/L ratio. Hence, the main difference in shape is not described by the H/L ratio, which is often used as a simple shape indicator for clam shrimp. But it forms one of several Fig. 5. Population density effect on size and shape in Eulimnadia texana. Colours represent standardized population densities 14 days after hydration that range between 1 and 12.8 individuals/400 ml. A, Biplot of principal component scores and variable vectors (loadings) on PC1 and PC2 of a set of log-transformed linear measurements. B, Fourier shape analysis. Although the analysis is shape-only, outlines have been scaled to size for better comparison with the size plot. PC1 represents relative umbo size, while PC2 is driven by several ratios, including the H/L ratio and relative size of the dorsal margin (compare with Fig. 7). Fig. 4. A, Bivariate fit of max. y (estimated from von Bertalanffy equation) by standardized population density 16 days after hydration. Natural log regression provides the best fit. B, Bivariate fit of mean length by mean number of growth bands (per cup). page 7 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan ratios driving PC2 (Fig. 7E; p < 0.001). PC2 is also influenced by relative length of the dorsal margin (Fig. 7F), with generally shorter dorsal margins compared to length in low-density cups. Burnaby transformation of linear measurements In contrast, NPMANOVA of the multivariate size dataset that has been transformed using Burnaby’s method did not yield overall statistically distinct groups Table 2. Non-parametric MANOVA of log-transformed linear measurements of Eulimnadia texana. Summary and pairwise comparisons. Significant pairwise comparisons (p < 0.05) are shaded. Pairwise comparisons reveal that linear measurements of density extremes (cups 1 and 15) are generally distinct. Intermediate densities cannot be statistically distinguished. (A) Nine linear variables. (B) Four linear variables (A) NPMANOVA of nine linear variables, log-transformed (E. texana) Permutation N: 9999 Total sum of squares: 5.736 Within-group sum of squares: 2.693 F: 6.102 p (same): 0.0002 Pairwise comparisons 5.1 5.2 10.1 10.2 15 1 0.0558 0.0153 0.0077 0.0581 0.0028 5.1 0.5639 0.3263 0.2841 0.0206 5.2 0.2106 0.1098 0.0043 10.1 0.3471 0.005 10.2 0.1195 (B) NPMANOVA of four linear variables Ch, u, H, L, log-transformed (E. texana) Permutation N: 9999 Total sum of squares: 0.6789 Within-group sum of squares: 0.3047 F: 6.632 p (same): 0.0001 Pairwise comparisons 5.1 5.2 10.1 10.2 15 1 0.0881 0.0179 0.018 0.0553 0.0041 5.1 0.6958 0.1082 0.1143 0.001 5.2 0.146 0.0766 0.0012 10.1 0.1662 0.1541 10.2 0.0779 Table 3. Non-parametric MANOVA of Fourier coefficients of Eulimnadia texana. Significant pairwise comparisons (p < 0.05) are shaded. Differences in shape are significant across different population densities (p(same) = 0.0001), reflected by multiple significant pairwise comparisons of intermediate population densities NPMANOVA of Fourier coefficients (E. texana) Permutation N: 9999 Total sum of squares: 0.06027 Within-group sum of squares: 0.0361 F: 3.616 p (same): 0.0001 Pairwise comparisons 5.1 5.2 10.1 10.2 15 1 0.0871 0.0174 0.009 0.0595 0.0035 5.1 0.4317 0.0249 0.0578 0.0021 5.2 0.1956 0.0241 0.0413 10.1 0.0038 0.3472 10.2 0.0065 page 8 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan (Table 4; p(same) = 0.218). Pairwise comparisons reveal just one significant pair (cups 1 and 10.1). Hence, shape variation between hermaphrodites of different population densities is too subtle to use this method for shape discrimination. Eocyzicus argillaquus Population survival Standardized densities of replicates in Eocyzicus argillaquus did not diverge much (Fig. 8, Table 1B). Survival remained at 100% until 10 days after hydration. Fig. 6. Size and shape variation in Eulimnadia texana. Pictured are the two extreme shapes that represent the most negative and most positive scores on PC1 in figure 5B. Individuals have been scaled to size (population densities of 12.8 individuals/400 ml, left, and 1 individual/400 ml, right; individuals 15.1_6 and 1.1_1). Fig. 7. Ordinary least squares regression of PC1 and PC2 scores of the Fourier shape analysis in figure 5B versus ratios u/(u+H), H/L, Ch/L. Shape change in PC1 is correlated with higher u/(u+H) ratios. The H/L ratio does not drive PC1, but it contributes to PC2. page 9 of 17Zoological Studies 59:33 (2020) © 2020 Academia Sinica, Taiwan Eulimnadia texana follows a logarithmic relationship, with lower densities triggering faster growth. In addition, Eulimnadia texana seems to mature faster in lower-density cups. At maturity, hermaphrodites yield similar lengths across all population densities but on different days. Subsequently, the growth rate of high-density clam shrimp strongly decreases, leading to maximal lengths that are only a little larger than length at maturity, while low-density clam shrimp keep growing. There is a significant effect of population density on size (defined as a combination of several linear variables). Low population densities are represented by larger carapaces in both species, Eulimnadia texana and Eocyzicus argillaquus. For data acquisition, it is not essential to worry about variability in linear variables, as robust variables yield similar results as the analysis of the full set of linear measurements. In addition, there is a strong density effect on hermaphrodite shape in Eulimnadia texana: low-density hermaphrodites yield larger relative umbo heights. The population density effect on shape in Eocyzicus argillaquus is less pronounced, yet significant for single-individual cups that yield smaller H/L ratios than clam shrimp of higherdensity cups. Our study demonstrates that some of the size and shape variability of fossils on bedding planes can be explained by population density, an important aspect of intraspecific variability in Spinicaudata. Acknowledgments: We acknowledge assistance in the field and laboratory by Jan Schmidt, Freie Universität Berlin, and Sarah Sheldon, The University of Akron. Also, we thank Melanie Hopkins, American Museum of Natural History, for discussion and Christopher Rogers, Kansas Biological Survey, for his helpful manuscript review. Authors’ contributions: Study design, data collection, analyses, writing, and revision by MH and SCW. Competing interests: The authors declare that they have no conflicts of interests. 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Notes on the life history of the clam shrimp, Eulimnadia texana. Hydrobiologia 359:191–197. Weeks SC, Marcus V, Crosser BR. 1999. Inbreeding depression in a self-compatible, androdioecious crustacean, Eulimnadia texana. Evolution 53:472–483. doi:10.1023/A:1003106702451. Weeks SC, Zofkova M, Knott B. 2006. Limnadiid clam shrimp distribution in Australia (Crustacea: Branchiopoda: Spinicaudata). Journal of the Royal Society of Western Australia 89:155–161. Zhang W, Chen P, Shen Y. 1976. Fossil Conchostraca of China. Beijing, Science Press. (in Chinese) Zucker N, Stafki B, Weeks SC. 2001. Maintenance of androdioecy in the freshwater clam shrimp Eulimnadia texana: longevity of males relative to hermaphrodites. Can J Zool 79:393–401. doi:10.1139/z00-211. Supplementary Materials Table S1. Eulimnadia texana size measurements and selected ratios. (download) Table S2. Fourier coefficients of 33 hermaphrodites of Eulimnadia texana. (download) Table S3. Eocyzicus argillaquus size variables and selected ratios. (download) Table S4. Fourier coefficients of 51 individuals of Eocyzicus argillaquus. (download) Table S5. Non-parametric MANOVA of lengths at maturity. Groups represent different population densities/400 ml. None of the pairwise comparisons of mature hermaphrodites are significant, indicating similar lengths at maturity. Juvenile lengths in cup 15 are distinct. There were only two mature individuals in cups 1, 5.1 and 10.2, hence they are not shown here. (download) Fig. S1. Hermaphrodite size (PC1 scores of logtransformed linear measurements) by population density. (download) Fig. S2. Population density effect on shape in Eocyzicus argillaquus. Principal component scores on PC2 and PC3 of a set of Fourier coefficients. (download) Fig. S3. Raw survival of Eulimnadia texana and Eocyzicus argillaquus. (download) Fig. S4. Sex discrimination based on Fourier shape analysis in Eocyzicus argillaquus, 14 females, 29 males. Mean female and mean male shape superimposed. (download) Fig. S5. Length over time by sex in Eocyzicus argillaquus. (download) Fig. S6. Size by population density of the Late Jurassic Liaoxiestheria linglongtaensis on nine bedding planes from the Tiaojishan Formation (n = 692). (download) page 17 of 17Zoological Studies 59:33 (2020)