BREVIA These changes in inferred trophic ecology are significantly correlated with evolutionary changes in armor phenotype through time (3) (Fig. 1E). DF scores are correlated with dorsal [nonparametric Spearman rank correlation (rs) = 0.23, P = 0.03, n = 89 fish] and pelvic armor (rs = 0.21, P = 0.05), feature density with dorsal armor (rs = 0.24, P = 0.02). Interestingly, the shift to a more benthic Mark A. Purnell,1* Michael A. Bell,2 David C. Baines,1 Paul J. B. Hart,3 Matthew P. Travis2 ecology within sample 19.8 (Fig. 1, D and E) odels, experiments, and field studies high-resolution record of evolutionary change precedes the increase in mean armor scores in 19.6 provide evidence of the ecological within a lineage spanning tens of thousands of (a time lag of circa 100 years). This evidence of an ecological shift preceding phenotypic change controls on evolution, but extrapolating years (3). We investigated the relationship between troph- suggests that this part of the sequence may record results over longer time scales is a perennial problem in evolutionary biology. Trophic ecology ic resource use and evolutionary change through rapid evolution driven by shifts in trophic ecology and competition for food, for example, are thought quantitative analysis of dental microwear (4). and adaptation to benthic niches. If this hypothesis to drive speciation through niche differentiation, Laboratory feeding experiments and analyses of is correct, however, the low number of specimens character displacement, and phenotypic wild stickleback populations show that microwear displaying intermediate phenotypes is puzzling, divergence (1). Yet direct evidence that feeding exhibits a progressive shift from planktivores to and the scenario of replacement of one lineage by controls evolution over extended time scales, benthic feeders (Fig. 1, A and B) (5). Discriminant another (3) cannot be ruled out. The gradual shift to less benthic ecology over the next 17,000 years supports the 2.9 Mud (94%B; 17.8) C ssample 19.6 50 D E 20 A 3.8 50 B Corcoran (76%B; 20.4) 19.7 interpretation that a return to lowKashwitna (51%B; 20.9) 19.8 40 armor phenotypes reflects direcLong (47%B; 21.9) 6.9 6.9 40 3.8 30 tional natural selection (3). 15 2.9 21.5 20 Our analysis shows that dental 30 10 microwear analysis can provide 10 direct evidence for changes in 20 0 1 2 3 4 trophic niche and resource exploiBenthic-Planktivore Benthic-planktivore 10 trend tation in fossil fishes. That changes 19.6 5 19.7 in feeding can be detected in19.8 21.5 0 dependently of morphological 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 20 25 30 change highlights the potential of Dorsal spine / pelvic score Mean feature density Feature length (µm) this approach to provide important Fig. 1. Microwear in stickleback teeth and correlated evolutionary change. (A) Scanning electron micrographs showing tooth microwear in fossil (top) and extant benthic feeding (bottom) stickleback. For details, see fig. S1. insights into trophic ecology dur(B) Microwear in wild-caught and lab-raised stickleback. Open ellipses indicate lab distributions (blue, benthic ing adaptive radiations of fishes treatments; red, planktivore; solid, dashed, and dotted lines are course, medium, and no sand substrate, and other evolutionary events. respectively). In wild fish, microwear tracks trophic ecology as indicated by % benthic stomach contents and mean References and Notes gill raker count (Mud Lake, most benthic; Long Lake, least benthic). (C) Fossil stickleback microwear; inset (D) 1. D. Schluter, The Ecology of Adaptive shows sample 19.8 divided into earlier (1746 to 1753 years) and later (1757 to 1771 years) subsamples with shift Radiations (Oxford Univ. Press, toward more benthic trophic ecology in later interval. Ky, thousand years. (E) Trophic niche and morphology in Oxford, 2000). fossil stickleback through time [○ dorsal armor; + pelvic armor; ◊ mean feature density; × DF scores (minimum of 2. D. Schluter, J. D. McPhail, Am. Nat. 140, 85 (1992). 0.38 and maximum of 2.51)]. Colored horizontal bars show niche scores reflecting the position of the samples in 3. M. A. Bell, M. P. Travis, D. M. Blouw, the benthic-planktivore microwear spectrum (C). Time scale follows (3).
Correlated Evolution and Dietary Change in Fossil Stickleback
available only from the fossil record, is difficult to obtain because it is rarely possible to directly analyze dietary change in long-dead animals. Functional changes must be inferred from changes in morphology, and attempts to determine whether morphological changes were caused by shifts in feeding can become circular. Here, we report an investigation of trophic resource use in a fossil sequence preserving an evolving lineage of threespine stickleback (Gasterosteus). We focus on stickleback for two reasons. First, perhaps the best-known work on speciation in fishes concerns stickleback in postglacial coastal lakes in Canada, where planktivores and benthic feeders coexist as two reproductively isolated and phenotypically distinct trophic forms. The differences between these forms result from competition for food (1, 2). Second, fossil stickleback from the Miocene Truckee Formation (Nevada) provide a detailed,
analysis using feature length and density indicates that scores for the first discriminant function (DF) are a good predictor of trophic ecology. For wild fish populations (n = 4), mean scores were significantly correlated with diet (r = 0.95, P = 0.05) and gill raker number (r = –0.996, P = 0.004). Analysis of fossil stickleback teeth revealed an overall range and pattern of feature densities and lengths similar to that of extant fish (Fig. 1C), suggesting that the fossil microwear records a similar benthic-planktonic feeding spectrum. This was supported by application of the DF derived from wild fish to the fossils: DF scores vary significantly between samples (F = 10.8, df of 7 and 87, P = 0.0001), and a Tukey-Kramer procedure revealed significant pairwise differences. This procedure also grouped some fossil samples with benthic-feeding wild populations (samples 19.6, 19.7, 19.6, and 6.9), others with planktivore populations (21.5), with some placed between (2.9 and 3.8).
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Paleobiology 32, 562 (2006). 4. Materials and methods are available as supporting material on Science Online. 5. M. A. Purnell, P. J. B. Hart, D. C. Baines, M. A. Bell, J. Anim. Ecol. 75, 967 (2006). 6. Funded by Natural Environment Research Council (NERC) grants NER/B/S/2000/00338 and NE/B000125/1 to M.A.P. and P.J.B.H.; M.A.P. also supported by NERC Advanced Fellowship NER/J/S/2002/00673. Fossil stickleback collected and prepared under NSF grants EAR9870337 and DEB0322818 to M.A.B. and F. J. Rohlf.
Supporting Online Material www.sciencemag.org/cgi/content/full/317/5846/1887/DC1 Materials and Methods Fig. S1 3 July 2007; accepted 15 August 2007 10.1126/science.1147337
1 Department of Geology, University of Leicester, Leicester LE1 7RH, UK. 2Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794–5245, USA. 3Department of Biology, University of Leicester, Leicester LE1 7RH, UK.
*To whom correspondence should be addressed. E-mail:
[email protected]
28 SEPTEMBER 2007
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Supporting Online Material Materials and Methods For details of analysis of teeth from laboratory and wild-caught fish see ref (1). The fossil teeth were collected by one of us (MPT) from a section through the Miocene Truckee Formation of Nevada (2). In the laboratory at Stony Brook, a fine moistened paint brush was used to extract teeth from articulated fish collected from seven intervals (see ref 2 for details of collecting and dating fish). Each interval spans roughly 100 years except for samples 19.7 and 19.8. These are narrower in order to capture changes during the interval of most rapid morphological change. In years from base of section samples are: sample 21.5 = 88 - 207 yrs (estimated); sample 19.8 = 1,746 - 1,771 yrs; sample 19.7 = 1,776 1,828 yrs; sample 19.6 = 1,863 - 1,978 yrs; sample 6.9 = 14,456 - 14,635 yrs; sample 3.8 = 17,705 17,813 yrs; sample 2.9 = 18,595 - 18,701 yrs. After initial analysis revealed that samples below 19.8 exhibit more planktonic microwear and those above more benthic, this sample was further subdivided into earlier (1,746 - 1,753 yrs) and later (1,757 – 1,771 yrs) subsamples to determine whether changes in microwear occurred within it. In sampling teeth, fish size was not an explicit criterion for selection, but the size of the majority of fishes in the collections indicates they were adults, and the temporal trends in microwear results cannot reflect ontogenetic diet change. That tooth size (as recorded by the area analysed for microwear) does not vary between samples (ANOVA, F = 0.77, d.f = 6, 88, P = 0.60) provides further support for this. Teeth were sent to Leicester in micropalaeontological slides, and after cleaning in acetone and coating with silver, scanning electron micrographs of an 80 x 100 µm area of the distal portion of the labial surface of one dentary tooth from each fish in each sample were obtained using a Hitachi S-520 (Fig. S1). Microwear features were scored for the distal most 75µm and summary data calculated using the custom software package Microware 4.02 (3, 4). This is a semi-automatic method, requiring operator input to determine microwear feature boundaries. All microwear data were acquired by the same operator (DCB); analysis of operator error indicates that replicate data sets acquired by DCB over a period of weeks did not differ significantly from one another (1). We focussed on microwear feature density and feature length, which for trophic analysis of stickleback are the most informative of the data generated by the Microware software. For further details of our methods, see ref (1). Analysis of tooth microwear and trophic interpretation was carried out blind: the investigators who scored and interpreted microwear did not know the relative stratigraphic positions of the fossil fish horizons
sampled until the analysis and trophic interpretation were complete. Because pelvic armor phenotypes are scored using an ordinal scale, correlations between microwear and armor were tested using nonparametric Spearman Rank Correlation (rs). Density ellipses in Fig. 1B-C, intended only as a guide to the pattern of distribution of the data, are drawn to include 80% of the data for each sample, assuming a bivariate normal distribution (sample 21.5 extreme outlier excluded). It is unlikely that changes in sediment are influencing fossil microwear to any significant degree because although experimental data indicate that microwear in treatments with course and medium sand substrates differs from those with fine sand or no substrates (1) there is no evidence for grain size changes of this magnitude in the Truckee Formation sequence (5). Difference between planktivore and benthic microwear in the fossils is unlikely to be the result of increased variance resulting from time averaging. Compared to samples exhibiting benthic microwear patterns, samples with planktivore microwear have lower minimum and lower maximum values for feature density (i.e. less variance), combined with greater range and higher values for feature length; this is not what would be expected from time averaging (6). Furthermore, recent work has shown that the effects of time averaging on phenotypic variance are less than has been thought, and that data are generally comparable to their population-level equivalents (7). Some of our samples have very different durations but the variance of the microwear data does not differ significantly. For example, samples 6.9 and 19.8 have similar microwear patterns, both falling between the mid-range and the benthic end of the spectrum. Results of ANOVA indicate that microwear data is not significantly different (for feature density and length, respectively, F = 0.78, P = 0.38; F = 0.02, P = 0.88, d.f. 1, 37 in both cases), even though sample 6.9, spans 179 years, and sample 19.8 spans only 25 years. The data for stomach contents of wild fish populations shown in Fig. 1 indicate trophic niche, but the mean of percentage food types found in each fish cannot capture some important aspects of the pattern of variation. For example, although by any measure it is the most planktivorous of the populations analysed, fish from Long Lake have a bimodal distribution of stomach contents (i.e. 30% of fish had 100% planktonic food items, 25% of fish had 100% benthic items). This is probably why the distribution of microwear data differs from the laboratory planktivore treatments. Kashwitna Lake fish were genuinely mixed feeders (20% of fish had 100% benthic items, the remainder spread across the 095% range). Fifty percent of Corcoran Lake fish had 100% benthic food items, and the remainder were spread. 80% of Mud Lake fish had 100% benthic prey, and of the remainder, none had less than 35%. Fish from Lynda Lake (1) exhibit no preferences regarding plankton/benthic food (no more than 11% of fish in any % prey bin) and were not included in the present analysis.
Figure S1. Scanning electron micrographs of Miocene and recent stickleback teeth. A. Tooth from fossil benthic sample 19.7 (image no. 04808). B. Tooth from wild benthic population from Mud Lake (image no. 92109). C. Tooth from laboratory benthic treatment, course sand substrate (image no. 84403). D. Tooth from fossil planktivore sample 21.5 (image no. 00832). E. Tooth from wild planktivore population from Long Lake (image no. 94309). F. Tooth from laboratory planktivore treatment, medium sand substrate (image no. 81106). Wild fish were obtained from lakes in the Matanuska-Susitina Valley, Alaska . Fossil fish were obtained from the Miocene Age Truckee Formation, Nevada. Scale bar 50 µm. Supplementary references S1. M. A. Purnell, P. J. B. Hart, D. C. Baines, M. A. Bell, J. Anim. Ecol. 75, 967 (2006). S2. M. A. Bell, M. P. Travis, D. M. Blouw, Paleobiology 32, 562 (2006). S3. P. S. Ungar. (Privately published, Fayetteville, Arizona, USA, 2001). S4. P. S. Ungar, Scanning 17, 57 (1995). S5. M. A. Bell, in Evolutionary Biology of the Threespine Stickleback M. A. Bell, S. A. Foster, Eds. (Oxford University Press, Oxford, 1994) pp. 438-471. S6. M. A. Bell, M. S. Sadagursky, J. V. Baumgartner, Palaios 2, 455 (1987). S7. G. Hunt, Paleobiology 30, 487 (2004).
