Biological invasions are both a pressing environmental challenge and an opportunity to investigate fundamental ecological processes, such as the role of top predators in regulating biodiversity and food-web structure. In whole-ecosystem manipulations of small Caribbean islands on which brown anole lizards (Anolis sagrei) were the native top predator, we experimentally staged invasions by competitors (green anoles, Anolis smaragdinus) and/or new top predators (curly-tailed lizards, Leiocephalus carinatus). We show that curly-tailed lizards destabilized the coexistence of competing prey species, contrary to the classic idea of keystone predation. Fear-driven avoidance of predators collapsed the spatial and dietary niche structure that otherwise stabilized coexistence, which intensified interspecific competition within predator-free refuges and contributed to the extinction of green-anole populations on two islands. Moreover, whereas adding either green anoles or curly-tailed lizards lengthened food chains on the islands, adding both species reversed this effect—in part because the apex predators were trophic omnivores. Our results underscore the importance of top-down control in ecological communities, but show that its outcomes depend on prey behaviour, spatial structure, and omnivory. Diversity-enhancing effects of top predators cannot be assumed, and non-consumptive effects of predation risk may be a widespread constraint on species coexistence.
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The datasets that support the findings of this study are provided in Supplementary Data 1–6. Illumina sequence data from the DNA metabarcoding diet analyses are deposited in Dryad (https://doi.org/10.5061/dryad.2h87r1f). Arthropod DNA reference sequences and associated specimen information are deposited in the Barcode of Life Data System (dataset DS-BAHARTR2, available via https://doi.org/10.5883/DS-BAHARTR2) and in GenBank (accessions MK936608–MK936799). Lizard DNA reference sequences are deposited in GenBank (accessions MK867972–MK868027).
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Helmus, M. R., Mahler, D. L. & Losos, J. B. Island biogeography of the Anthropocene. Nature 513, 543–546 (2014).
Simberloff, D. et al. Impacts of biological invasions: what’s what and the way forward. Trends Ecol. Evol. 28, 58–66 (2013).
Doherty, T. S., Glen, A. S., Nimmo, D. G., Ritchie, E. G. & Dickman, C. R. Invasive predators and global biodiversity loss. Proc. Natl Acad. Sci. USA 113, 11261–11265 (2016).
Schmitz, O. J., Hawlena, D. & Trussell, G. C. Predator control of ecosystem nutrient dynamics. Ecol. Lett. 13, 1199–1209 (2010).
Sih, A. et al. Predator–prey naïveté, antipredator behavior, and the ecology of predator invasions. Oikos 119, 610–621 (2010).
Chase, J. M. et al. The interaction between predation and competition: a review and synthesis. Ecol. Lett. 5, 302–315 (2002).
Chesson, P. & Kuang, J. J. The interaction between predation and competition. Nature 456, 235–238 (2008).
Sommers, P. & Chesson, P. Effects of predator avoidance behavior on the coexistence of competing prey. Am. Nat. 193, E132–E148 (2019).
Takimoto, G., Post, D. M., Spiller, D. A. & Holt, R. D. Effects of productivity, disturbance, and ecosystem size on food-chain length: insights from a metacommunity model of intraguild predation. Ecol. Res. 27, 481–493 (2012).
Tunney, T. D., McCann, K. S., Lester, N. P. & Shuter, B. J. Food web expansion and contraction in response to changing environmental conditions. Nat. Commun. 3, 1105 (2012).
Ward, C. L. & McCann, K. S. A mechanistic theory for aquatic food chain length. Nat. Commun. 8, 2028 (2017).
Sax, D. F. et al. Ecological and evolutionary insights from species invasions. Trends Ecol. Evol. 22, 465–471 (2007).
Paine, R. T. Food web complexity and species diversity. Am. Nat. 100, 65–75 (1966).
Murdoch, W. W. Switching in general predators: experiments on predator specificity and stability of prey populations. Ecol. Monogr. 39, 335–354 (1969).
Connell, J. H. in Dynamics of Populations (eds den Boer, P. J. & Gradwell, G. R.) 298–312 (Center for Agricultural Publication and Documentation, 1970).
Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).
Noonburg, E. G. & Abrams, P. A. Transient dynamics limit the effectiveness of keystone predation in bringing about coexistence. Am. Nat. 165, 322–335 (2005).
Spiller, D. A. & Schoener, T. W. Lizards reduce spider species richness by excluding rare species. Ecology 79, 503–516 (1998).
Wallach, A. D., Ripple, W. J. & Carroll, S. P. Novel trophic cascades: apex predators enable coexistence. Trends Ecol. Evol. 30, 146–153 (2015).
Terborgh, J. W. Toward a trophic theory of species diversity. Proc. Natl Acad. Sci. USA 112, 11415–11422 (2015).
Peckarsky, B. L. et al. Revisiting the classics: considering nonconsumptive effects in textbook examples of predator–prey interactions. Ecology 89, 2416–2425 (2008).
Schmitz, O. J. Effects of predator hunting mode on grassland ecosystem function. Science 319, 952–954 (2008).
Holt, R. A. & Lawton, J. H. The ecological consequences of shared natural enemies. Annu. Rev. Ecol. Syst. 25, 495–520 (1994).
Orrock, J. L., Preisser, E. L., Grabowski, J. H. & Trussell, G. C. The cost of safety: refuges increase the impact of predation risk in aquatic systems. Ecology 94, 573–579 (2013).
Post, D. M. & Takimoto, G. Proximate structural mechanisms for variation in food-chain length. Oikos 116, 775–782 (2007).
Schoener, T. W. Food webs from the small to the large. Ecology 70, 1559–1589 (1989).
Vander Zanden, M. J., Casselman, J. M. & Rasmussen, J. B. Stable isotope evidence for the food web consequences of species invasions in lakes. Nature 401, 464–467 (1999).
Post, D. M., Pace, M. L. & Hairston, N. G. Jr. Ecosystem size determines food-chain length in lakes. Nature 405, 1047–1049 (2000).
McCann, K. S., Rasmussen, J. B. & Umbanhowar, J. The dynamics of spatially coupled food webs. Ecol. Lett. 8, 513–523 (2005).
Takimoto, G., Spiller, D. A. & Post, D. M. Ecosystem size, but not disturbance, determines food-chain length on islands of the Bahamas. Ecology 89, 3001–3007 (2008).
Schoener, T. W. & Spiller, D. A. Devastation of prey diversity by experimentally introduced predators in the field. Nature 381, 691–694 (1996).
Losos, J. B. & Spiller, D. A. Differential colonization success and asymmetrical interactions between two lizard species. Ecology 80, 252–258 (1999).
Schoener, T. W., Spiller, D. A. & Losos, J. B. Predators increase the risk of catastrophic extinction of prey populations. Nature 412, 183–186 (2001).
Schoener, T. W., Losos, J. B. & Spiller, D. A. Island biogeography of populations: an introduced species transforms survival patterns. Science 310, 1807–1809 (2005).
Losos, J. B. Lizards in an Evolutionary Tree: Ecology and Adaptive Radiation of Anoles (Univ. California Press, 2009).
Schoener, T. W., Slade, J. B. & Stinson, C. H. Diet and sexual dimorphism in the very catholic lizard genus, Leiocephalus of the Bahamas. Oecologia 53, 160–169 (1982).
Holt, R. D. & Polis, G. A. A theoretical framework for intraguild predation. Am. Nat. 149, 745–764 (1997).
Kartzinel, T. R. & Pringle, R. M. Molecular detection of invertebrate prey in vertebrate diets: trophic ecology of Caribbean island lizards. Mol. Ecol. Resour. 15, 903–914 (2015).
Beaupre, S. J., Dunham, A. E. & Overall, K. L. The effects of consumption rate and temperature on apparent digestibility coefficient, urate production, metabolizable energy coefficient and passage time in canyon lizards. Funct. Ecol. 7, 273–280 (1993).
Murakami, M. & Hirao, T. Lizard predation alters the effect of habitat area on the species richness of insect assemblages on Bahamian isles. Divers. Distrib. 16, 952–958 (2010).
Schluter, D. The Ecology of Adaptive Radiation (Oxford Univ. Press, 2000).
Stroud, J. T. & Losos, J. B. Ecological opportunity and adaptive radiation. Annu. Rev. Ecol. Evol. Syst. 47, 507–532 (2016).
Fukami, T. Historical contingency in community assembly: integrating niches, species pools, and priority effects. Annu. Rev. Ecol. Evol. Syst. 46, 1–23 (2015).
Stuart, Y. E. et al. Rapid evolution of a native species following invasion by a congener. Science 346, 463–466 (2014).
Holt, R. D. & Bonsall, M. B. Apparent competition. Annu. Rev. Ecol. Evol. Syst. 48, 447–471 (2017).
Gillespie, R. Community assembly through adaptive radiation in Hawaiian spiders. Science 303, 356–359 (2004).
Chrétien, E. & Chapman, L. J. Habitat heterogeneity facilitates coexistence of native fishes with an introduced predator: the resilience of a fish community 5 decades after the introduction of Nile perch. Biol. Invas. 18, 3449–3464 (2016).
Ziegler, J. P., Gregory-Eaves, I. & Solomon, C. T. Refuge increases food chain length: modeled impacts of littoral structure in lake food webs. Oikos 126, 1347–1356 (2017).
Amarasekare, P. Spatial dynamics of keystone predation. J. Anim. Ecol. 77, 1306–1315 (2008).
McPeek, M. A. Keystone and intraguild predation, intraspecific density dependence, and a guild of coexisting consumers. Am. Nat. 183, E1–E16 (2014).
Schoener, T. W. & Schoener, A. The time to extinction of a colonizing propagule of lizards increases with island area. Nature 302, 332–334 (1983).
Heckel, D. G. & Roughgarden, J. A technique for estimating the size of lizard populations. Ecology 60, 966–975 (1979).
Pringle, R. M., Young, T. P., Rubenstein, D. I. & McCauley, D. J. Herbivore-initiated interaction cascades and their modulation by productivity in an African savanna. Proc. Natl Acad. Sci. USA 104, 193–197 (2007).
Pringle, R. M. et al. Synergistic effects of fire and elephants on arboreal animals in an African savanna. J. Anim. Ecol. 84, 1637–1645 (2015).
Schoener, T. W., Spiller, D. A. & Losos, J. B. Variable ecological effects of hurricanes: the importance of seasonal timing for survival of lizards on Bahamian islands. Proc. Natl Acad. Sci. USA 101, 177–181 (2004).
Pinheiro, J. & Bates, D., DebRoy, S., Sarkar, D. & Core Team, R. nlme: linear and nonlinear mixed effects models. R package version 3.1-117 https://CRAN.R-project.org/package=nlme (2017).
R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016).
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).
Boyer, F. et al. obitools: a unix-inspired software package for DNA metabarcoding. Mol. Ecol. Resour. 16, 176–182 (2016).
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).
Deagle, B. E. et al. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? Mol. Ecol. 28, 391–406 (2019).
Dormann, C. F. et al. bipartite: visualising bipartite networks and calculating some (ecological) indices. R package version 2.11 https://github.com/biometry/bipartite (2018).
Oksanen, J. et al. vegan: community ecology package. R package version 2.4-5. https://CRAN.R-project.org/package=vegan (2017).
de Cáceres, M. & Legendre, P. Associations between species and groups of sites: indices and statistical inference. Ecology 90, 3566–3574 (2009).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Untergasser, A. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).
Spiller, D. A. et al. Marine subsidies have multiple effects on coastal food webs. Ecology 91, 1424–1434 (2010).
Piovia-Scott, J., Spiller, D. A. & Schoener, T. W. Effects of experimental seaweed deposition on lizard and ant predation in an island food web. Science 331, 461–463 (2011).
Young, H. S. et al. The roles of productivity and ecosystem size in determining food chain length in tropical terrestrial ecosystems. Ecology 94, 692–701 (2013).
Pringle, R. M. & Fox-Dobbs, K. Coupling of canopy and understory food webs by ground-dwelling predators. Ecol. Lett. 11, 1328–1337 (2008).
Logan, J. M. et al. Lipid corrections in carbon and nitrogen stable isotope analyses: comparison of chemical extraction and modelling methods. J. Anim. Ecol. 77, 838–846 (2008).
Post, D. M. Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83, 703–718 (2002).
Lattanzio, M. & Miles, D. Stable carbon and nitrogen isotope discrimination and turnover in a small-bodied insectivorous lizard. Isotopes Environ. Health Stud. 52, 673–681 (2016).
Schoener, T. W., Spiller, D. A. & Losos, J. B. Predation on a common Anolis lizard: can the food-web effects of a devastating predator be reversed? Ecol. Monogr. 72, 383–407 (2002).
This work is a product of US National Science Foundation grant DEB-1457697 to R.M.P. and R.D.H.B. T.W.S., D.A.S., and J.B.L. acknowledge NSF DEB-1314691. Support was provided by the Princeton Environmental Institute (R.M.P.), a Canada Research Chair (R.D.H.B.), and a Vanier Canada Scholarship (C.C.Y.X.). Research was conducted under permits from The Bahamas Environment, Science & Technology Commission, the Bahamas Department of Agriculture, and Princeton University’s Institutional Animal Care and Use Committee (protocols 1922-13, 1922-F16). We thank S. Lubin-Gray, L. Hanna, the Chamberlain family, A. Askary, P. Chen, N. and A. Dappen, T. Ingram, O. Lapiedra, N. Losin, L. Revell, C. Tarnita, J. Ware, and L. Wyman.
Nature thanks Raymond Huey, Oswald Schmitz and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
a–c, Agonistic interaction between brown and green anoles on +GA+CT island 312, where green anoles later went extinct (Fig. 2c). Both lizards displayed dewlaps, and the green anole chased the brown anole away. d, Interference competition between adult male brown anole and two juvenile curly-tailed lizards; the anole was excluded from the food resource (a termite trail). e, Predation by adult curly-tailed lizard on a small brown anole, the only such event observed during the 6-year study. f, Non-consumptive interaction in which a subadult curly-tailed lizard chased an adult male brown anole into a low-hanging thin perch. g, Intraspecific combat between male brown anoles, revealing how agonistic interactions can lead to injuries. h, Brown anole eating a lycosid spider on the ground. i, j, Female brown anole first eyeing (i) and then eating (j) a pentatomoid bug (possibly Loxa viridis) on control island 5; the lizard was marked with yellow paint in between the two photographs. k, Brown anole on a low perch consuming a millipede that it caught on the ground. l–o, Brown anole (l) and three different curly-tailed lizards (m–o) eating cockroaches (H. pabulator), the predominant prey taxon of curly-tailed lizards and brown anoles (Fig. 4). p, q, Island 311 (p), a +GA island, and island 930 (q), a +CT island, showing vegetation structure (see also Fig. 1e, f). Lizards show paint marks used during censuses (blue, day 1; red, day 2; and yellow, day 3). The interactions in d and o, along with other events, are shown in Supplementary Video 1. Imagery, a–o, the authors; p, q, Day’s Edge Productions.
In all panels, line widths signify relative interaction strengths (solid black arrows, direct effects; dashed arrows, indirect effects; bi-directional red arrows, competitive effects). Circle diameters indicate the relative population sizes of anole species. Habitat use is indicated by the vertical position of shapes within each panel; grey arrows pointing upwards from bars signify behavioural habitat shifts. a, On control islands, brown anoles (B) are semi-terrestrial and primarily use terrestrial resources (RT) along with a smaller proportion of arboreal resources (RA). b, On +GA islands, introduced green anoles (G) compete for space and food with brown anoles, which reduces the size of brown-anole populations (smaller circle) and limits the growth of green-anole populations, but the two species coexist owing to spatial niche separation. c, On +CT islands, curly-tailed lizards (CT) consume terrestrial arthropod prey in addition to preying on brown anoles; the size of the brown-anole population is reduced, and surviving brown anoles respond by moving into arboreal habitat and consuming arboreal prey (a non-consumptive behavioural effect of predation risk). d, e, On +GA+CT islands, we considered two mutually exclusive hypotheses. d, Under a keystone-predation model, heavy predation by curly-tailed lizards on brown anoles strongly and rapidly reduces the size of brown-anole populations, which relaxes the competitive constraint on the growth of the green-anole populations and stabilizes species coexistence (a net positive indirect effect of curly-tailed lizards on green anoles). e, Alternatively, the refuge-competition model posits that the direct effect of predation on the size of brown-anole populations is weak and slow relative to the non-consumptive effect on brown-anole behaviour; the resulting habitat shift intensifies competition between brown and green anoles and destabilizes coexistence (a negative indirect effect of curly-tailed lizards on both anole species). Our results are consistent with all of the predictions illustrated in a–c and e, and they refute the keystone-predation model (d) by falsifying its predicted positive effect of curly-tailed lizards on green anoles (Fig. 2b, c).
Extended Data Fig. 3 Predators increase spatial overlap between anole species and reduce variability in habitat use by brown anoles.
a, b, Relative perch heights (see Fig. 3g–i) of brown and green anoles on +GA islands (a, n = 1,083 and 271 observations, respectively) and +GA+CT islands (b, n = 287 and 101 observations, respectively) in 2015. Box plots, medians and interquartile ranges; circles, means; whiskers, 5th to 95th percentiles for all lizards pooled across islands in each treatment. c, d, As in a, b, but for the 2016 census (n = 1,162 and 240 brown and green anoles, respectively (c); n = 232 and 61 brown and green anoles, respectively (d)). Shaded horizontal bars in b and d indicate overlap in the interquartile ranges of relative perch height on islands with curly-tailed lizards. e–h, Coefficient of variation in relative perch height as a function of treatment for brown anoles in 2015 (e) and 2016 (f), and for green anoles in 2015 (g) and 2016 (h). Box plots, medians and interquartile ranges; circles, means; whiskers, 5th to 95th percentiles for all islands in each treatment (n = 4 for +GA islands; n = 3 for +GA+CT islands owing to the extinction of green anoles on island 926 before the 2015 survey). Predators constrained variability in the relative perch heights of brown anoles on +GA+CT islands relative to +GA islands; variability in the relative perch height of green anoles was both lower overall and less affected by predators than that of brown anoles, because green anoles occurred at close to the maximum available perch height on all islands (a–d).
Extended Data Fig. 4 Principal coordinates analysis of Bray–Curtis dietary dissimilarities on each island.
Each point represents a faecal sample from a different individual (distance reflects dissimilarity); ellipses, 95% confidence intervals (calculated only for populations represented by ≥3 samples). All plots are based on the same ordination and share the same coordinates, such that the dietary niche of any species on any island can be compared with that of any other species on any other island. Sample size and PERMANOVA test of dissimilarity between species on each island is shown in each panel; note that these statistical tests were island-specific, whereas the coordinates of points in each panel were calculated based on a single ordination including all samples from all islands. No samples were collected from control island 332. See Fig. 4 for species- and treatment-wise contrasts.
This figure corresponds to Fig. 4, but with data modified to reflect the presence–absence of mOTUs instead of relative read abundance. mOTUs were counted as present if they accounted for at least 1% of relative read abundance in the rarefied sequence data. a, Bipartite network showing the frequency of occurrence of the top-50 prey mOTUs (bottom bars, coloured by taxonomic group), across all lizard species (top bars) and treatments. Width of connecting lines reflects the proportion of faecal samples in which each mOTU was detected for each lizard species. The three most-frequent prey taxa are indicated by numerals (1, H. pabulator; 2, A. floridanus; 3, Brachymyrmex spp.). b–e, Principal coordinates analysis of Bray–Curtis dietary dissimilarity based on presence–absence of mOTUs within samples. Points, individual samples (distance reflects dissimilarity); ellipses, 95% confidence intervals. All plots are based on the same ordination with identical coordinates to facilitate comparison across panels, but confidence intervals were calculated separately for each treatment in c–e. b, Each species, pooled across treatments, with PERMANOVA testing the effect of species identity (P ≤ 0.001, n = 315 samples). c, Brown anoles by treatment, with PERMANOVA testing the independent and interactive effects of green anoles and curly-tailed lizards (all P ≤ 0.026, n = 209 samples). d, Green anoles by treatment, with PERMANOVA testing the effect of curly-tailed lizards (P = 0.076, n = 43 samples). e, Curly-tailed lizards by treatment, with PERMANOVA testing the effect of green anoles (P = 0.11, n = 63 samples). f–n, Frequency of occurrence by species and treatment of H. pabulator (f–h), A. floridanus (i–k), and Brachymyrmex spp. (l–n). Sample sizes for each species match those in c–e. Lizard images from Dreamstime, Shutterstock, and Alamy.
This figure corresponds to Fig. 5, but includes trophic-position values for the most-abundant spider species (M. datona), showing that our conclusions are robust to the inclusion of spiders in analyses. Trophic position was quantified for a total of 108 spiders from 7 experimental islands (2 control, 3 +GA, 1 +CT and 1 +GA+CT) (range, 13–22 spider samples per island). a, Trophic position of each consumer species by experimental treatment, not accounting for effects of island area. Bars, means of island-wide averages for each species (±1 s.e.m.) in each treatment (see also Fig. 5a). Dots, values for each population. b, Mean trophic position of each lizard and spider population (±1 s.e.m.) on each island, showing an influence of ecosystem size but no effect of species identity (see also Fig. 5b) (ANCOVA effect tests: island area F1,32 = 4.47, P = 0.042; consumer species F3,32 = 0.92, P = 0.44; n = 37 populations). c, Increase in food-chain length as a function of island area (linear regression r = 0.62, F1,13 = 8.33, P = 0.013, n = 15 islands); orange points indicate the two islands on which food-chain length increased when spiders were included (see also Fig. 5c). d, Mean food-chain length in each experimental treatment, after accounting for the effects of island size and all first-order interactions (Extended Data Table 2b). Bars, least-squares means (±1 s.e.m.) from the green anole × curly-tailed lizard interaction term in the generalized least-squares linear model (whole model F6,8 = 5.28, P = 0.018; green anole × curly-tailed lizard interaction t = −2.79, d.f. = 8, P = 0.024, n = 15 islands). Letters indicate statistically significant differences (P ≤ 0.05) between treatments in pairwise two-sided t-tests (see also Fig. 5d).
a, Original food-chain length result from Fig. 5d, showing mean trophic position (from stable-isotope data) of the apical consumer in each treatment. Bars, least-squares means (±s.e.m.) from the generalized least-squares model in Extended Data Table 2a (n = 15 islands). b, c, Corresponding plots of mean per-sample dietary Shannon diversity (b) and species richness (c), from DNA metabarcoding, of the apical consumer on each island (n = 15 islands). Dietary diversity and richness are used here as proxies for trophic omnivory; these metrics were analysed with the same model structure as in a and show the inverse pattern, which is consistent with the possibility that changes in food-chain length were driven by changes in trophic omnivory by apical consumers (higher omnivory and shorter food chains on control and +GA+CT islands, and vice versa on +GA and +CT islands). The green anole × curly-tailed lizard interaction terms from the models are shown in the top right. Letters denote significant differences (P ≤ 0.05) between treatments in pairwise two-sided t-tests. d, Food-chain length as a function of island area, as in Fig. 5c, but here including only islands with curly-tailed lizards (n = 8) and analysed using ANCOVA to highlight the area × treatment interaction. Food-chain length was uncorrelated with ecosystem size on +GA+CT islands (see also Fig. 5c, Extended Data Table 2). e, f, Corresponding ANCOVA analyses of mean per-sample dietary diversity (e) and richness (f) of curly-tailed lizards, consistent with the possibility that changes in top-predator omnivory influenced food-chain length (n = 7 islands). Mean per-sample diversity (e) was greater on small islands (which is consistent with higher trophic omnivory in small ecosystems10) and on +GA+CT islands, and decreased with island area on +CT but not +GA+CT islands (as expected if higher levels of trophic omnivory on +GA+CT islands of all sizes resulted in shorter food chains and contributed to the pattern seen in a). Per-sample dietary richness (f) showed a similar response to the island area × treatment interaction. For d–f, ANCOVA statistics are shown in the top right. Points, island-level means; error bars, ±1 s.e.m. g, h, The trophic position of curly-tailed lizard was negatively correlated with dietary diversity (g) and richness (h) in linear regressions, consistent with our conjecture that arthropod prey breadth is a proxy for trophic omnivory by the top predator. Points, means; error bars, ±1 s.e.m.; n = 7 islands. Regression statistics are shown in the top right. Island 204 (open circles) was represented by 3 curly-tailed lizard isotope samples (n ≥ 5 samples for all other islands) but only one faecal sample (n ≥ 3 samples for all other islands). Thus, in b, c we used brown anoles as the apical consumer on island 204 (trophic position 2.37 versus 2.43 for curly-tailed lizards). In e–h, we omitted island 204 from statistical analyses but show it for reference. In all panels, including the curly-tailed lizard data from island 204 (or omitting island 204 entirely from b, c) gives similar statistical results. Island names corresponding to each point are shown in d–h.
Summary information for each arthropod taxon in the rarefied diet dataset. For each arthropod mOTU (n = 813), we provide the unique sequence identifier used in this study (seq_######); the best taxonomic identification currently possible based on matching (% identity) to local and global reference databases (‘Accepted mOTU information’); the average relative read abundance (RRA) for all samples across all species and treatments (‘Total RRA’), for each lizard species across all treatments (‘Species-level RRA’), and for each lizard species within each treatment (‘RRA by treatment’); the frequency of occurrence (FOO) for all lizard species across all treatments (‘Total FOO’), for each lizard species across all treatments (‘Species-level FOO’), and for each lizard species within each treatment (‘FOO by treatment’). We also present indicator species analyses, based on RRA, testing for significant associations between each mOTU and each lizard species (‘Species-level indicator analysis’), and between each mOTU and each experimental treatment for brown anoles (‘Brown anole indicator analysis by treatment’). The species-level indicator analysis tests whether the dietary mOTU was significantly more abundant overall (across all treatments) in the specified lizard species than in those not specified; similarly, the treatment indicator analysis tests whether the mOTU was significantly more abundant in brown-anole diets in the specified treatments than in those not specified. Asterisks indicate level of statistical significance in two-sided permutation tests (*P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001). Finally, we provide the DNA sequence corresponding to each mOTU (‘Representative sequence’). The table includes 35 mOTUs that were detected only in samples that we collected and sequenced as duplicates from a single captured lizard; we excluded these samples from analysis to avoid pseudoreplication, but the mOTUs they contained are listed for completeness (with RRA and FOO equal to zero across all groups).
Unrarefied sequence-read abundances from the DNA-metabarcoding analysis. For each of the 368 lizard faecal samples sequenced in this study (rows), we report the unique alphanumeric sample identifier, lizard species, source island, experimental treatment, sampling period, sex, and lizard body-size dimensions (snout-vent length, head width, weight). Because we sequenced multiple faecal samples obtained from a subset of captured individuals, we distinguish the 315 samples that were included in statistical analyses from the 53 that were removed to avoid pseudoreplication (‘Included in analysis’). Subsequent columns show the unrarefied DNA sequence-read abundance for each arthropod mOTU. These unrarefied sequence-read abundances were used only in DESeq2 analysis; all other analyses used rarefied sequence-read abundances (Supplementary Data 2) to calculate both relative read abundance and presence-absence. This table contains 1647 mOTUs; the taxonomy for 813 of these can be obtained by matching the column headings (seq_######) to Supplementary Table 1; the remaining 834 occurred at low relative abundance and were eliminated by rarefying.
Rarefied sequence-read abundances from the DNA-metabarcoding analysis. For each of the 368 lizard faecal samples analyzed in this study (rows), we report the unique alphanumeric sample identifier, lizard species, source island, experimental treatment, sampling period, lizard sex, and body-size dimensions (snout-vent length, head width, weight). Because we sequenced multiple faecal samples obtained from a subset of captured individuals, we distinguish the 315 samples that were included statistical analyses from the 53 that were removed to avoid pseudoreplication (‘Included in analysis’). Subsequent columns show the rarefied DNA sequence-read abundance for each arthropod mOTU. The relative sequence-read abundance of each mOTU in each lizard’s diet profile (as used in our primary analyses) can be obtained by dividing these raw sequence-read counts by 1142, which is the total rarefied number of sequence reads in each sample (i.e., the sum across all columns for each row). To convert sequence count data to presence-absence for presentation in Extended Data Fig. 5 and Supplementary Table 1, we inferred a taxon to be ‘present’ if it accounted for at least 1% of the rarefied sequence-read depth (i.e., >11 reads). The best possible taxonomic identifications for the 813 mOTUs in this table can be obtained by matching the column headings (seq_######) to the taxonomy in Supplementary Table 1.
Lizard population-size estimates and habitat use. For each island, we provide vegetated area, experimental treatment, and, for each lizard species in each year, estimated population size, mean absolute and relative perch heights, mean perch diameter, and mean proportion of individuals on the ground. Empty cells indicate either that no data are available for that island/year, or that the island was excluded from analysis in that year owing to extirpation of green anoles (island 926 in 2015-2016). Population sizes of green anoles and curly-tails in 2011 are numbers of individuals introduced after the initial census of brown-anole populations; thus, there are no habitat-use data for those species in that year. These data were used to generate Figs 2 and 3a-f and the statistical analyses in Extended Data Table 3.
Quantitative PCR (qPCR) cycle-threshold values of faecal samples from curly-tailed lizards. For each of 61 faecal samples tested for lizard DNA (rows), we report the unique alphanumeric sample identifier (corresponding with those in Supplementary Data 1, 2, 4), an additional individual-identity number (replicate samples obtained from the same individual lizard share the same number and are shaded gray), source island, experimental treatment, sampling period, and lizard body-size dimensions (snout-vent length and weight). Subsequent columns show the cycle-threshold (Ct) values of each faecal sample for the species-specific curly-tailed lizard, brown anole, and green anole SYBR Green qPCR assays. We used the amplification-based threshold option in the MxPro software to automatically determine fluorescence thresholds for each qPCR run, with the exception of values reported in column ‘Manual curly-tailed lizard Ct’, where the threshold was set manually for a single qPCR run owing to late amplification of the positive control causing errors in the automatic threshold algorithm. Manually setting the fluorescence threshold did not change presence–absence results. Target DNA was considered present wherever numeric Ct values are reported. We failed to detect curly-tailed lizard DNA in five samples (yellow shading in ‘Curly-tailed lizard Ct’ column), which were therefore excluded from analysis.
Stable-isotope data and trophic-position estimates for lizards and spiders. For each individual lizard and Metepeira datona spider sampled for stable-isotope analysis, we present the unique alphanumeric individual identifier (corresponding to those in Supplementary Data 1 and 2 where applicable), species identity, source island, experimental treatment, sampling period, sex, and lizard body-size dimensions (snout-vent length, head width, weight). Subsequent columns present the δ13C and δ15N values of each consumer; mean δ13C and δ15N of buttonwood trees from each island; mean δ13C and δ15N of marine macroalgae averaged across sites; α, the proportional contribution of marine resources to diet, assuming Δ13C = 3.8‰; and estimated trophic position of each individual consumer, assuming Δ15N = 3.4‰. These data were used in generating Fig. 5, Extended Data Figs 6 and 7, and the statistical analyses in Extended Data Table 2. Trophic-position estimates based on other assumptions about Δ13C and Δ15N (per Extended Data Table 2) can be derived from these data and the equations presented in the Methods.
Raw survey data. For each of the 20,937 individual lizard observations in annual population censuses from 2011 to 2016, we list a record-locator number, the year, island, treatment, calendar date, day number within the three-day census, and lizard species. Subsequent columns identify each lizard’s sex or age (M, male; F, female; J, juvenile; A, adult; Unk, unknown; slashes, uncertain categorization); perch height (cm); maximum vegetation height within a 1-m radius of the lizard (cm), used to calculate relative perch height (recorded from 2014 to 2016 only); perch diameter (in mm); substrate on which lizard was observed (G, ground; T, tree trunk; B, branch; L, leaf; O, other); binary indicator of whether lizard was on the ground (1) or not (0); whether the lizard was marked (1) or not (0) on census days 1, 2, and 3 (entries of 0.25, 0.5, and 0.75 represent estimated likelihood in cases of observer uncertainty); and the observer who recorded the data in the field (RMP, Robert M. Pringle; TRK, Tyler R. Kartzinel; TMP, Todd M. Palmer; TJT, Timothy J. Thurman; JHD, Joshua H. Daskin; NMV, Naomi Man in ‘t Veld; RDHB, Rowan D.H. Barrett; AA, Arash Askary; CET, Corina E. Tarnita; LW, Lauren Wyman; TI, Travis Ingram). Blank cells indicate that no datum was recorded for that observation. These raw data are the basis for Supplementary Data 3 (which contains the island-level values used in analyses) and can be used to reproduce the descriptive graphs in Fig. 3g-i and Extended Data Fig. 4. No perch diameters were estimated for lizards on the ground; for analysis, we assumed an upper-bound perch diameter of 200 mm and assigned this value for all lizards on the ground and any for which the perch diameter recorded in the field was >200 mm (see Methods).
Lizard behavior and species interactions on islands. This video includes some of the interactions shown in Extended Data Figure 1, along with selected other footage.