Correction
18 Sep 2012: Avaria-Llautureo J, Hernández CE, Boric-Bargetto D, Canales-Aguirre CB, Morales-Pallero B, et al. (2012) Correction: Body Size Evolution in Extant Oryzomyini Rodents: Cope's Rule or Miniaturization?. PLOS ONE 7(9): 10.1371/annotation/56843298-87aa-418c-9f6c-db469d0abd20. https://doi.org/10.1371/annotation/56843298-87aa-418c-9f6c-db469d0abd20 View correction
Figures
Abstract
At the macroevolutionary level, one of the first and most important hypotheses that proposes an evolutionary tendency in the evolution of body sizes is “Cope's rule". This rule has considerable empirical support in the fossil record and predicts that the size of species within a lineage increases over evolutionary time. Nevertheless, there is also a large amount of evidence indicating the opposite pattern of miniaturization over evolutionary time. A recent analysis using a single phylogenetic tree approach and a Bayesian based model of evolution found no evidence for Cope's rule in extant mammal species. Here we utilize a likelihood-based phylogenetic method, to test the evolutionary trend in body size, which considers phylogenetic uncertainty, to discern between Cope's rule and miniaturization, using extant Oryzomyini rodents as a study model. We evaluated body size trends using two principal predictions: (a) phylogenetically related species are more similar in their body size, than expected by chance; (b) body size increased (Cope's rule)/decreased (miniaturization) over time. Consequently the distribution of forces and/or constraints that affect the tendency are homogenous and generate this directional process from a small/large sized ancestor. Results showed that body size in the Oryzomyini tribe evolved according to phylogenetic relationships, with a positive trend, from a small sized ancestor. Our results support that the high diversity and specialization currently observed in the Oryzomyini tribe is a consequence of the evolutionary trend of increased body size, following and supporting Cope's rule.
Citation: Avaria-Llautureo J, Hernández CE, Boric-Bargetto D, Canales-Aguirre CB, Morales-Pallero B, Rodríguez-Serrano E (2012) Body Size Evolution in Extant Oryzomyini Rodents: Cope's Rule or Miniaturization? PLoS ONE 7(4): e34654. https://doi.org/10.1371/journal.pone.0034654
Editor: Nicolas Salamin, University of Lausanne, Switzerland
Received: May 10, 2011; Accepted: March 8, 2012; Published: April 3, 2012
Copyright: © 2012 Avaria-Llautureo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded by Fondo de Desarrollo en Ciencia y Tecnología Grant # 11080110 to CEH (http://www.fondecyt.cl/578/channel.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Body size is one of the most significant traits of animals, not only because it is correlated with many life-history and ecological characteristics [1]–[4], but also given its importance in the evolution of taxa [5], [6]. At the macroevolutionary level, one of the first and most important hypotheses that proposes an evolutionary tendency in the evolution of body sizes is “Cope's rule" [3], [7]. This rule predicts that the size of species within a lineage increases over evolutionary time [8]–[13]. In fact, using fossil data from Cenozoic North American mammals, Alroy [9] found that on average, the increment of body size from ancestor to descendant is 9%. Explanations for Cope's rule principally include: 1.- the consideration that the greatest body sizes have the greatest fitness (e.g., [14]); and 2.- an increase in the variance of body size is the result of diversification by passive diffusion from a small sized ancestor (e.g., [8], [15], [16]). The first explanation generates the prediction that the distribution of forces and/or constraints that affect the tendency are homogenous [16] and generate a directional process [17]. The second explanation predicts that there is no dominant force determining the evolutionary tendency. In this sense, the distribution of forces and/or restrictions that affect the tendency would be heterogeneous [16] and generate a random process [17] in which the only restrictions are given by the minimum viable body size and the small sized common ancestor [8], [15], [16], [18].
Alternatively, an important, but less explored, pattern of body size evolution is miniaturization [5], for which there is ample evidence in a variety of taxa [19]–[22], for a review see 5]. This trend has been understood as an extreme reduction of body size, leading to a shift in physiology, ecology, life history and behavioral traits. However, a less severe reduction in body size can also be part of a miniaturization trend, which can be assessed in an explicit phylogenetic framework [5], [23], [24]. The consequences of miniaturization are results of heterochronic underlying process that induce bauplan reduction or simplification, phenotypic novelties, as well as the increase in variability of late ontogeny elements that can facilitate diversification [5]. These alternative historical body size trends (i.e., Cope's rule versus miniaturization) suggest that in a monophyletic group the processes that generate these patterns are based on selection or any other within-lineage process that has a directional tendency [25].
Both Cope's rule and miniaturization have considerable empirical support in the animal fossil record [9], [11]–[13], [23], [26]–[28]. However, Monroe & Bokma [29] find no evidence for Cope's rule in extant mammals using a single phylogenetic tree approach and a Bayesian based model of evolution. Their study analyzed the evolution of body size in 4,554 existing mammal species, in a phylogenetic tree that comprises nearly all mammals, and is currently the most comprehensive of its kind using extant species. This is interesting given that their results contrast with the fossil evidence of mammals found by Alroy [9], Smith et al. [28] and McFadden [30].
This contrasting result could be due to the use of a one phylogenetic tree approach, which implies that parameters that define the evolutionary patterns were estimated assuming that the phylogeny or the evolutionary history of the group under study is known without error [31], [32]. Nevertheless, phylogenies are rarely known with complete certainty [33], and are usually inferred from groups of morphological or molecular data [34], which are themselves subject to error and uncertainty. This presents a problem because different phylogenetic trees could give different answers to the same comparative questions. As a result, all of the conclusions derived from the comparative analyses using a single phylogenetic tree are conditional to this particular phylogeny. It has recently been suggested that the Bayesian method using Markov Chain Monte Carlo (hereafter BMCMC) offers a solution to the problem of sampling phylogenies by using a formal statistical procedure to sample from the probability of phylogenetic trees [31], [35]–[39]. This method can be applied to comparative analyses for the study of ancestral character reconstruction [40]–[44], and potentially to evaluate modes and patterns of character evolution, such as evolutionary trends in body size.
Here we utilize the phylogenetic comparative method, incorporating phylogenetic uncertainty, to assess Cope's rule/miniaturization using extant Sigmodontinae (Rodentia: Cricetidae) rodents of the Oryzomyini tribe as a study model. Oryzomyini are the most diverse tribe of endemic rodents in South America, with about 121 species and 28 genera [45]. It is also the most widely distributed tribe, from Tierra del Fuego to the southern United States, including many oceanic islands [46], [47]. This group inhabits a variety of environments, including tropical and temperate rain forests, subtropical and desert open areas and the high Andean plateau. Species have a wide range of body sizes, ranging from 62 to 254 mm [47]. To date there has only been one empirical evaluation with respect to body size evolution in this monophyletic group, which suggested that current body size diversity originated from a medium sized ancestor [47]. This neontological study was based on a single phylogenetic tree approach and parsimony to reconstruct ancestral nodes. Nevertheless, such reconstruction techniques have been shown to be inadequate in the study of evolutionary trends, as they are constrained to reconstruct ancestral nodes at values that are intermediate to values in extant species [48]–[52], and assume a simple random walk model. However, evaluating whether the diversification of the traits are the result of random or directional (i.e., an increase or decrease) diversification mechanisms, has important implications for understanding the origin and diversification of lineages [16], [52]–[57]. To this respect, a new method proposed by FitzJohn [25] based on the birth-death processes, allows for evaluation of Cope's rule/miniaturization hypothesis, and their relationship with diversification rate.
We utilized this recently developed phylogenetic birth-death method (quantitative state speciation and extinction [QuaSSE]) proposed by FitzJohn [25], to test the evolutionary trend in body size, incorporating the uncertainty of phylogenetic trees obtained from Bayesian analysis, and to compare with a single phylogenetic tree approach, by assessing body size evolution in a Maximum Likelihood and Bayesian consensus tree. We evaluated Cope's rule/miniaturization using two principal predictions: (a) phylogenetically related species are more similar in their body size, than expected by chance; (b) body size increased/decreased over time. Consequently the distribution of forces and/or constraints that affect the tendency are homogenous and generate this directional process from a small/large sized ancestor.
Materials and Methods
Body size and DNA data collection
We compiled a bibliographic database containing the maximum head-body length for 51 extant Oryzomyini species for which molecular data was available for phylogenetic analyses (Table S1). We selected this trait because it is less temporally variable than other metrics such as body mass [52], and because it is robustly related to overall body size distribution, and hence to mean and median body size [58]. Analyses were performed using natural logarithm transformation of the data in millimeters to normalize.
We used sequences of the Interphotoreceptor retinoid-binding protein nuclear gene, and Cytochrome-b mitochondrial gene (hereafter IRBP, and Cyt b, respectively) from GenBank [59], because sequences are available for a large number of Oryzomyini species (Table S1). Four sigmodontines pertaining to other tribes (Calomys callosus, Bibimys labiosus, Juliomys pictipes, and Eligmodontia typus) were selected as outgroups, based on the phylogeny of D'Elia [60], D'Elia et al. [61], and Smith & Patton [62] (Table S1).
BMCMC molecular phylogeny and estimates of divergence times
Given that Oryzomyini diversification has been dated around 7 million years ago [63], [64], the selected molecular marker could be saturated, and provide spurious phylogeny. Therefore we evaluated whether the sequences were saturated and thus useful for the phylogenetic analysis, using Xia's test [65] implemented in DAMBE v5.1.5 [66]. This is an entropy-based index that estimates a substitution saturation index (Iss) and compares it to a critical substitution saturation index (Iss.c) via a randomization process with 95% confidence intervals [67], [68]. We used concatenated aligned DNA sequence data of the IRBP-Cyt b genes from the 55 species, corresponding to the ingroup and outgroups (Table S1). We aligned the sequences using Clustal W [69], and by eye. Additionally, given that this study did not contain all known current species, we performed the node-density artifact test to determine any possible effect caused by missing taxa on the reconstructed sample of phylogenetic trees [70]. This test fits two parameters that describe the rate of change between the path lengths of a tree and the number of nodes (β*), and the curvature of this relationship (δ). When the data do not suffer from sparse taxon sampling the parameters should be β*>0 and δ≤1 [71].
With concatenated aligned sequences we simultaneously estimated phylogenetic relationships, branch lengths, and divergence times for the Oryzomyini tribe using BEAST 1.6.2 software [72]. This analysis was conducted using a BMCMC framework to estimate the posterior probability of phylogenetics trees, and includes this uncertainty in the comparative analysis. As prior information we used a GTR+Γ+I model of sequence evolution, the Yule process of speciation, and two points of fossil calibration: 1.6±0.64 Mya. for the origin of Oligoryzomys flavescens (see [73]), and 1.5±0.8 Mya. for the origin of Holochilus (see [74]). Analyses were based on four models of mutation rate: 1) A strict molecular clock; 2) an uncorrelated lognormal relaxed clock; 3) an uncorrelated exponential relaxed clock; and 4) a random local clock. The MCMC chain was run for 21,000,000 generations (10,000 generations were discarded as burn in, before the posterior probabilities distribution of the selected diversification model converged), with parameters sampled every 10,000 steps, and we resampled every 15 trees to obtain a final sample of 139 trees, with an autocorrelation of 0.006 in ln-likelihood of the sample. Examination of MCMC samples using TRACER v. 1.5 software [75] suggested that the independent chains were each adequately sampling the same probability distribution; and that effective sample sizes for all parameters of interest were greater than 500. In order to find the best molecular clock model we used Bayes factor [76] to compare the four clock models, given that it is the soundest theoretical framework for model comparison in a Bayesian framework [72].
Evaluation of evolutionary trends
Using the GLS model [49], [77]–[80] we first evaluated the influence of phylogeny or phylogenetic signal on body size with the phylogeny scaling parameter λ [49], [79], [81], using the consensus tree obtained from Bayesian analyses. The parameter λ evaluates the extent to which the phylogeny correctly predicts the patterns of similarity of traits among species [49], [79], or if the traits are evolving according to the PGLS model on the given phylogeny [81]. In this approach λ reveals whether the phylogeny fits to the patterns of covariance among close species for a given trait. This analysis is based on the V matrix of variance–covariance, where the variance is assumed to be directly proportional to the sum of the branch lengths from the root to the tips. The expected covariance between any two species is assumed to be proportional to the sum of their shared branch lengths, and the parameter λ is the multiplier of the elements outside the diagonal of V. This parameter evaluates one of the key assumptions underlying the use of the Comparative Method (i.e., that species are not independent). If trait evolution is independent of phylogenetic relationships, then this parameter will take the value of 0, indicating that a trait's values are not predicted by the ancestor-descendant relationships and, consequently, analysis of body size using the phylogeny is not appropriate [80]. If traits are evolving as expected, given the tree topology and branch length, λ takes the value of 1 [81].Values of λ between 0 and 1 indicate different levels of phylogenetic signal [49]. The random-walk model with the observed λ parameter was contrasted with the random-walk model forcing λ = 0; and λ = 1, respectively.
Using the birth-death model [25] implemented in a maximum likelihood framework we evaluated body size evolution and its relationship with speciation rate over the Bayesian sample of ultrametric-phylogenetic trees. This model takes a phylogeny and set of trait measurements for the tip species, and fits a series of birth–death models in which the speciation and extinction probabilities are independent of trait evolution, or vary along branches as a function of a continuous trait that evolves according to a diffusion process, with or without an evolutionary tendency (i.e., increase or decrease over time) [25]. The anagenetic component of character evolution is incorporated by the change described in the diffusion model, and the cladogenetic component is incorporated with the effect of speciation event in the estimation of ancestral character states. To test if a directional tendency in body size evolution exists we compared models in which speciation rates were constant and independent of body size evolution, and where speciation rates vary as a linear, sigmoidal, or hump-shaped function of body size, evolving by a diffusion process, with and without a directional trend. In a linear model the speciation rate varies proportional to body size, in a sigmoidal model smaller species have a low speciation rate compared to larger species, and in a hump model species with the mean body size have the highest speciation rate.
Specifically we used seven models of speciation rate: 1) a constant model of speciation; 2) speciation that varies as a linear function of body size, evolving by a diffusion process; 3) speciation that varies as a sigmoidal function of body size, evolving by a diffusion process; 4) speciation that varies as a hump function of body size, evolving by a diffusion process; 5) speciation that varies as a linear function of body size, evolving by a diffusion process with a directional trend; 6) speciation that varies as a sigmoidal function of body size, evolving by a diffusion process with a directional trend; and 7) speciation that varies as a hump function of body size, evolving by a diffusion process with a directional trend. These models have the following parameters: the speciation and extinction rate parameters (λS, μ); the diffusion parameter (σ2), which is the expected squared rate of change and captures the stochastic elements of character evolution; and the directional trend “drift" parameter (θ), which captures the deterministic or directional component of character evolution, this is the expected rate of change of the character over time and may be due to selection or any other within-lineage process that has a directional tendency [25]. These models were implemented in QuaSSE software [25], and the analyses were done using the Diversitree package of R software [82]. The parameter values of birth-death models were estimated on each tree of the sample of trees (Nexus trees S1) from the BMCMC molecular phylogenetic approach implemented in BEAST (i.e., the analyses were done 139 times). To select the best model that describes body size evolution in the sample of trees we used Bayes Factor. Given issues with the power for detecting and estimating extinction from molecular phylogenies [25], [83], we did not test extinction-variable models.
Finally, to compare the obtained results based on a sample of trees with a single phylogenetic tree approach, we assessed body size evolution in a Maximum Likelihood (ML), and Bayesian consensus (BC) tree. For these one phylogenetic tree approaches we selected the best model using the Akaike information criterion (AIC).
Results
The analyzed IRBP-Cyt b sequences presented low saturation, as the critical index of substitution saturation values (Iss.c = 0.469) was significantly higher than the observed index of substitution saturation values (Iss = 0. 209; p<0.0001), therefore, the sequences are suitable for performing phylogenetic analyses. The Bayes factor analysis suggests that, for this data set, the relaxed molecular clock model using exponential distribution is both a more precise estimator and has a better fit to the data (Table 1). The consensus tree obtained from this clock model (Fig. 1), showed high posterior probability for the majority of nodes, and the topology and divergence time estimates were consistent with previous work [63], [64]. Maximum likelihood, Bayesian consensus and the sample of trees are available as a Nexus file in Nexus Trees S1. The node-density artifact analysis did not detect evidence of an effect caused by missing taxa or sparse taxon sampling in the reconstructed phylogenies (δ<1 when β is significant = 25.15%).
Blue branches indicate posterior probability values of a node below 0.5. Horizontal blue bars indicate the 95% HPD of divergence times, and the scale axis shows divergence times as millions of years ago (Mya).
The variability of body size was significantly influenced by phylogenetic relationships (λ = 1; Table 2; Fig. 2). The Bayes Factor comparison between the seven birth-death models, that considered uncertainty in phylogenetic trees, showed that the best predictor of body size evolution in Oryzomyini rodents was a Drift Linear model with a positive trend (θ = 0.33; Table 3, 4), where larger species have higher speciation rates. Similarly, analyses based on a single phylogenetic tree approach and AIC values (Table 5, 6), showed that the same Drift Linear model with a positive trend was the best predictor of body size evolution (AIC = 135.1 and 140.5 for Bayesian consensus and Maximum likelihood trees, respectively). The positive trend for body size evolution was described by θ = 0.48, and θ = 0.45 for Bayesian consensus and Maximum likelihood trees, respectively (Table 5, 6).These results support the general tendency to increase body size over time, and that larger species have a higher speciation rate.
Vertical blue bars indicate the 95% HPD.
Discussion
There has been a succession of improving studies regarding the evolutionary processes that gave rise to the current patterns of biodiversity in Oryzomyini rodents, which has primarily focused on the time of origin, biogeography and phylogenetic affinities of several species [47], [60]–[62], [85], [86]. Some progress has been made towards understanding these processes, especially through the discovery of fossil records [74], [84], [85], [87]–[95]. However, the incomplete fossil record of early Oryzomyini forms has hindered the description of the evolutionary history of this tribe. This difficulty is augmented when researchers attempt to understand the evolutionary history of particular traits like body size, since there are no fossil data that allow researchers to evaluate ancient character evolution and diversification [70]. Our results –based on extant species and the use of the comparative method in a sample of Bayesian trees– suggest that the current body size distribution in the oryzomyine tribe is explained by phylogenetic relationships (i.e., phylogenetic signal, Table 2; Fig. 2), and that during the evolutionary history of oryzomyines there was an evolutionary trend towards increased body size, which suggests that the distribution of forces and/or constraints that determine the tendency for larger body size over time are homogenous and generate a directional process (i.e., Cope's rule hypothesis, Table 3, 4). Alternatively, it is also possible that the increase in the body size of oryzomine rodents is caused by passive diffusion from the minimum viable body size, as postulated by Stanley [8] (but see [16], [96]). In fact, Stanley [8] studied teeth from fossil rodent species and found that body size distributions became progressively skewed towards large size as time went on, whereas the modal size category remained constant; near the small end of the observed range. He suggested that although most of the rodents he studied remained small, a few became larger and were able to invade different niches. Stanley cautioned that because there are smaller than large-bodied mammals, there may be a passive tendency for evolution from small to large body size (taken from Monroe & Bokma [29]).
However, recently Raia et al. [97] demonstrated that derived fossil mammal species were characteristically larger, less abundant, had smaller geographic ranges, and persisted for shorter time periods than their smaller ancestors. As these traits are typical of specialist species, these authors proposed that Cope's rule could be explained in terms of the increase in specialization and niche expansion at the clade level, which Cope termed “the law of the unspecialized" [98]. The consequence of this mode of evolution is that narrow ecological specialization results in fewer opportunities for speciation, and thus lower rates of diversification compared to less specialized clades. The extant species of the oryzomyini tribe are characterized by their high level of specialization, possibly derived from generalist ancestors [47]. Over time, larger species have experienced a higher rate of speciation, which agrees with the predictions of Cope's rule and the law of the unspecialized. It is possible that the success of the specialized species and the larger body sizes of the group are a consequence of their wide geographical ranges, which are more susceptible to allopatric speciation events, and thus a higher rate of speciation.
We find no evidence for miniaturization from extant oryzomyine, in accordance with Monroe & Bokma [29] who did not observe any trend for mammals in general. However, our results support Cope's rule in extant species, in accordance with the work of FitzJohn [25], which focused on primates, but determined a different drift model (i.e., a modal curve). These exclusive studies that support Cope's rule using extant taxa suggest that this pattern of evolution is both taxonomic level and model dependent. With respect to taxonomic level, the use of the most inclusive level of mammal diversity could be mixing different trends and histories of body size evolution, and thus obscure the potential trends that can be found in more exclusive monophyletic groups, like Primates and oryzomines. Moreover, recent work by Vendetti et al. [99], using the same phylogeny used by Monroe & Bokma [29], demonstrated that different clades of mammals have different rates of body size evolution, and consequently different histories. With respect to model dependence, we suggest that the appropriate way to test trends in body size evolution in extant taxa is to evaluate the fits of different models of body size evolution for particular monophyletic taxa, as we have done here and as has been done by FitzJohn [25].
This evolutionary scenario based on the results of a likelihood-based method of the birth-death model, uses a sample of trees which takes into account phylogenetic uncertainty, and is consistent with the results based on the single phylogenetic tree approach. Both approaches support the tendency for body sizes to increase over time, or Cope's rule (Tables 3, 4, 5, and 6). These similar results are a consequence of the low uncertainty in the phylogenetic history of Oryzomyini tribe, reflected in the higher values of posterior probability in the Bayesian consensus tree (Fig. 1).
In the oryzomyine tribe the evolution of body size began with a small body sized ancestor, which could have colonized the current main distribution in South America from the Northern Hemisphere. Previously, it has been proposed that, given the estimated time for initial diversification of oryzomyines based on molecular studies around 7 Mya [63], [64], the oryzomyine ancestor likely arrived in South America prior to the formation of the Panamanian land bridge at 3.5–4.0 Mya [99], [100] by over-water dispersal. In fact, the ability of oryzomyines to undertake long-distance water dispersal is well-known [101].
We propose that during the early diversification of the tribe, body size increased (i.e., Drift Linear model with a positive trend). The colonization and use of a new and heterogeneous environment, with a wide variability of habitats in South America, allowed for an explosive radiation of Oryzomiyini during the Late Miocene [Fig. 1]. The body size of the Oryzomyini should have undergone change highly influenced by this complex ecological scenario, as observed in the current conspicuous anatomical and ecological deviations from the original generalized bauplan [47], including arboreal, fossorial, dietary and extreme environments specialization [47], [73]. We suggest that during evolutionary history, the consequence of increased body size was an increase in the range of distribution, ultimately increasing the probability of speciation by posterior vicariant processes. The Drift Linear model of evolution supports this idea, given that speciation rate is a linear function of a general trend of body size evolution (Tables 3, 4, 5, and 6). This proposed scenario is coherent with the idea of explosive radiation [64] and Cope's rule, which is observed in the oryzomyine tribe. However, the explosive radiation hypothesis requires an explicit test, utilizing new methods, as proposed by Stadler [102] and Silvestro et al. [103] who evaluates the variation of diversification rate over time. Finally, our finding of an increase in body size allows us to reinforce the idea that, in spite of the difficulty of encountering fossils that represent important evolutionary steps, phylogenetic studies of extant taxa can shed new light on the evolutionary history of sigmodontines [60]–[62]. In particular, inter-specific phylogenetic studies are very valuable for describing the origin and radiation of some important traits (like body size). Easy access to these new tools for evaluating evolutionary patterns (i.e., Cope's rule and miniaturization hypotheses) makes it possible to build more complete scenarios using available evidence from extant taxa to complement (or in the absence of) information from the fossil record.
Supporting Information
Table S1.
Maximum Head-Body length (mm), and GenBank Access Number for Oryzomyini' species used in phylogenetic comparative analysis. Missing data for maximum head-body length are indicated by gap (−). (*) species used as outgroup.
https://doi.org/10.1371/journal.pone.0034654.s001
(DOC)
Nexus Trees S1.
Bayesian tree sample, Bayesian consensus tree, and Maximum Likelihood tree used for comparative analyses. All trees are calibrated with fossil data (see methods).
https://doi.org/10.1371/journal.pone.0034654.s002
(TXT)
Acknowledgments
The authors are very grateful to Paula E. Neill, Michel Laurin, Nicolas Salamin, Melanie Monroe, and two anonymous reviewers for comments and suggestions that greatly improved the final version of the manuscript. We also thank Eduardo Palma for facilitating bibliographic data and literature about oryzomines. Previous versions of this paper were improved by comments from Guillermo D'Elía. Jorge Avaria-Llautureo and Bryan Morales-Pallero were supported by a CONICYT Master's Fellowship. Dusan Boric-Bargetto was supported by a CONICYT Doctoral Fellowship, and Cristián B. Canales-Aguirre was supported by a Doctoral Fellowship from the Escuela de Graduados of the Universidad de Concepción.
Author Contributions
Conceived and designed the experiments: JAL CEH. Performed the experiments: JAL. Analyzed the data: JAL CEH. Contributed reagents/materials/analysis tools: BMP DBB CBCA. Wrote the paper: JAL CEH ERS.
References
- 1.
Brown JH (1995) Macroecology. Chicago, Illinois: University of Chicago Press. 269 p.
- 2. Gaston KJ, Chown SL, Mercer RD (2001) The animal species-body size distribution of Marion Island. Proc Natl Acad Sci U S A 98: 14493–14496.
- 3.
Peters RH (1983) The ecological implications of body size. New York: Cambridge University Press. 329 p.
- 4.
Schmidt-Nielsen K (1984) Scaling, why is animal size so important? New York: Cambridge University Press. 241 p.
- 5. Hanken J, Wake DB (1993) Miniaturization of body size: organismal consequences and evolutionary significance. Annu Rev Ecol Syst 24: 501–519.
- 6. Sibly RM, Brown JH (2007) Effects of body size and lifestyle on evolution of mammal life histories. Proc Natl Am Sci 104: 17707–17712.
- 7.
Cope CD (1887) The origin of the fittest. New York: Arno Press.
- 8. Stanley SM (1973) An explanation for Cope's rule. Evolution 27: 1–26.
- 9. Alroy J (1998) Cope's rule and the dynamics of body mass evolution in North American fossil mammals. Science 280: 731–734.
- 10. Brown JH, Maurer BA (1986) Body size, ecological dominance and Cope's rule. Nature 324: 248–250.
- 11. Damuth J (1993) Cope's rule, the island rule and the scaling of mammalian population density. Nature 365: 748–750.
- 12. Demetrius L (2000) Directionality theory and the evolution of body size. Proc Biol Sci 267: 2385–2391.
- 13. Novack-Gottshall PM, Lanier MA (2008) Scale-dependence of Cope's rule in body size evolution of Paleozoic brachiopods. Proc Natl Acad Sci U S A 105: 5430–5434.
- 14. Kingsolver JG, Pfenning DW (2004) Individual-level selection as a cause of Cope's rule of phyletic size increase. Evolution 58: 1608–1612.
- 15. Dial KP, Marzluff JM (1988) Are the smallest organisms the most diverse? Ecology 69: 1620–1624.
- 16. McShea DW (1994) Mechanisms of large-scale evolutionary trends. Evolution 48: 1747–1763.
- 17. Maurer BA (1998) The evolution of body size in birds. I. Evidence for non-random diversification. Evol Ecol 12: 925–934.
- 18. Clauset A, Erwin DH (2008) The evolution and distribution of species body size. Science 321: 399.
- 19. Rüber L, Kottelat M, Tan HH, Ng PKL, Britz R (2007) Evolution of miniaturization and the phylogenetic position of Paedocypris, comprising the world's smallest vertebrate. BMC Evol Biol 7: 38.
- 20. Yeh J (2002) The effect of miniaturized body size on skeletal morphology in frogs. Evolution 56(3): 628–641.
- 21. Pianka E (1995) Evolution of body size: varanid lizards as a model system. Am Nat 146: 398–414.
- 22. Knouft JH, Page LM (2003) The evolution of body size in extant groups of North American freshwater fishes: speciation, size distributions, and Cope's rule. Am Nat 161: 413–421.
- 23. Fröbisch NB, Schoch RR (2009) Testing the impact of miniaturization on phylogeny: Paleozoic dissorophoid amphibians. Syst Biol 58: 312–327.
- 24. Hanken J (1992) Life history and morphological evolution. J Evol Biol 5: 549–557.
- 25. FitzJohn RG (2010) Quantitative traits and diversification. Syst Biol 59(6): 619–633.
- 26. Hone DWE, Benton MJ (2007) Cope's rule in the Pterosauria, and differing perceptions of Cope's rule at different taxonomic levels. J Evol Biol 20: 1164–1170.
- 27. Hone DWE, Keesey TM, Pisani D, Purvis A (2005) Macroevolutionary trends in the Dinosauria: Cope's rule. J Evol Biol 18: 587–595.
- 28. Smith FA, Boyer AG, Brown JH, Costa DP, Dayan T, et al. (2010) The evolution of maximum body size of terrestrial mammals. Science 330: 1216–1219.
- 29. Monroe MJ, Bokma F (2010) Little evidence for Cope's rule from Bayesian phylogenetic analysis of extant mammals. J Evol Biol 23: 2017–2021.
- 30.
McFadden BJ (1992) Fossil Horses: Systematics, Palaeobiology and Evolution of the Family Equidae. New York: Cambridge University Press. 369 p.
- 31. Huelsenbeck JP, Rannala B, Masly JP (2000) Accommodating phylogenetic uncertainty in evolutionary studies. Science 288: 2349–2350.
- 32.
Rezende EL, Garland T Jr (2003) Comparaciones interespecíficas y métodos estadísticos filogenéticos. In: Bozinovic F, editor. Fisiología ecológica y evolutiva. Teoría y casos de estudio en animales. Santiago, Chile: Ediciones Universidad Católica de Chile. pp. 79–98.
- 33. Schluter D (1995) Uncertainty in ancient phylogenies. Nature 377: 108–109.
- 34.
Felsenstein J (2004) Inferring Phylogenies. Massachusetts, Sunderland: University of Washington, Sinauer Associates Inc. 664 p.
- 35. Holder MT, Lewis PO (2003) Phylogeny estimation: traditional and Bayesian approaches. Nature Rev Genet 4: 275–284.
- 36. Huelsenbeck JP, Ronquist F, Nielsen R, Bollback JP (2001) Bayesian inference of phylogeny and its impact on evolutionary biology. Science 294: 2310–2314.
- 37. Larget B, Simon DL (1999) Markov Chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees. Mol Biol Evol 16: 750–759.
- 38. Pagel MD, Meade A (2004) A Phylogenetic Mixture Model for detecting pattern-heterogeneity in gene sequence or character-state data. Syst Biol 53(4): 571–581.
- 39.
Pagel MD, Meade A (2005) Mixture models in phylogenetic inference. In: Gascuel O, editor. Mathematics of evolution and phylogeny. Oxford: Oxford University Press. pp. 121–142.
- 40. Huelsenbeck JP, Bollback JP (2001) Empirical and hierarchical Bayesian estimation of ancestral states. Syst Biol 50: 351–366.
- 41. Lutzoni F, Pagel M, Reeb V (2001) Major fungal lineages derived from lichen-symbiotic ancestors. Nature 411: 937–940.
- 42.
Pagel MD, Lutzoni F (2002) Accounting for phylogenetic uncertainty in comparative studies of evolution and adaptation. In: Lässig M, Valleriani A, editors. Biological evolution and statistical physics. Berlin: Springer-Verlag. pp. 148–161.
- 43.
Pagel M, Meade A (2005) Bayesian estimation of correlated evolution across cultures: A case study of marriage systems and wealth transfer at marriage. In: Mace R, Holden CJ, Shennan S, editors. The evolution of cultural diversity: a phylogenetic approach. London: University College London Press. pp. 235–256.
- 44. Pagel MD, Meade A (2006) Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo. Am Nat 67: 808–825.
- 45. Weksler M, Percequillo AR, Voss RS (2006) Ten new genera of Oryzomyine rodents (Cricetidae:Sigmodontinae). Am Mus Novit 3537: 1–29.
- 46. Weksler M (2003) Phylogeny of Neotropical oryzomyine rodents (Muridae: Sigmodontinae) based on the nuclear IRBP exon. Mol Phylogenet Evol 29(2): 331–349.
- 47. Weksler M (2006) Phylogenetic relationships of oryzomyine rodents (Muroidea: Sigmodontinae): separate and combined analyses of morphological and molecular data. Bull Am Mus Nat Hist 196: 1–149.
- 48. Oakley TH, Cunningham CW (2000) Independent contrasts succeed where ancestor reconstruction fails in a known bacteriophage phylogeny. Evolution 54: 397–405.
- 49.
Pagel MD (2002) Modelling the evolution of continuously varying characters on phylogenetic trees. In: MacLeod N, Foley FL, editors. Morphology, shape and phylogeny. London: Taylor & Francis. pp. 269–286.
- 50. Ronquist F (2004) Phylogenetics Series. Bayesian inference of character evolution. Trends Ecol Evol 19: 475–481.
- 51. Webster AJ, Purvis A (2001) Testing the accuracy of methods for reconstructing ancestral states of continuous characters. Proc R Soc Lond B 269: 143–149.
- 52. Moen DS (2006) Cope's rule in cryptodiran turtles: do they body sizes of extant species reflect a trend of phyletic size increase? J Evol Biol 19: 1210–1221.
- 53. Alroy J (2000) New methods for quantifying macroevolutionary patterns and processes. Paleobiology 26(4): 707–733.
- 54. Alroy J (2000) Understanding the dynamics of trends within evolving lineages. Paleobiology 26(3): 319–329.
- 55. Gaston KJ, He F (2002) The distribution of species range size: a stochastic process. Proc R Soc Lond B 269: 1079–1086.
- 56. Gould SJ (1988) Trends as changes in variance: a new slant on progress and directionality in evolution. J Paleontol 62: 319–329.
- 57. Wang SC (2001) Quantifying passive and driven large-scale evolutionary trends. Evolution 55(5): 849–858.
- 58. Trites AW, Pauly D (1998) Estimating mean body masses of marine mammals from maximum body lengths. Canad J Zool 76: 886–896.
- 59.
GenBank website. Available: http://www.ncbi.nlm.nih.gov/genbank. Accessed 2011 November 10.
- 60. D'Elia G (2003) Phylogenetics of Sigmodontinae (Rodentia, Muroidea, Cricetidae), with special reference to the akodont group, and with additional comments on historical biogeography. Cladistics 19: 307–323.
- 61. D'Elia G, Luna L, González EM, Patterson BD (2006) On the Sigmodontinae radiation (Rodentia, Cricetidae): An appraisal of the phylogenetic position of Rhagomys. Mol Phylogenet Evol 38: 558–564.
- 62. Smith MF, Patton JL (1999) Phylogenetic relationships and the radiation of sigmodontine rodents in South America: Evidence from Cytochrome b. J Mamm Evol 6: 89–128.
- 63. Engel SR, Hogan KM, Taylor JF, Davis SK (1998) Molecular systematic and paleobiogeography of the South American sigmodontine rodents. Mol Biol Evol 15(1): 35–49.
- 64. Steppan SJ, Adkins RM, Anderson J (2004) Phylogeny and divergence-date estimates of rapid radiations in Muroid rodents based on multiple nuclear genes. Syst Biol 53: 533–553.
- 65. Xia X, Xie Z, Salemi M, Chen L, Wang Y (2003) An index of substitution saturation and its application. Mol Phylogenet Evol 26: 1–7.
- 66. Xia X, Xie Z (2001) DAMBE: data analysis in molecular biology and evolution. J Hered 92: 371–373.
- 67.
Xia X (2000) Data analysis in molecular biology and evolution. Boston: Kluwer Academic publishers. 296 p.
- 68.
Xia X, Lemey P (2009) Assessing substitution saturation with DAMBE. In: Lemey P, Salemi M, Vandamme AM, editors. The phylogenetic handbook: A practical approach to DNA and protein phylogeny. Cambridge: Cambridge University Press. pp. 615–630.
- 69. Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucl Ac Research 22: 4673–4680.
- 70.
Test for Punctuational Evolution and the Node-Density Artifact website. Available: http://www.evolution.rdg.ac.uk/pe/index.html. Accessed 2011 October 25.
- 71. Venditti C, Meade A, Pagel M (2006) Detecting the node-density artifact in phylogeny reconstruction. Syst Biol 55: 637–643.
- 72. Drummond AJ, Rambuat A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7: 214.
- 73. Palma RE, Rodríguez-Serrano E, Rivera-Milla E, Hernández CE, Salazar-Bravo J, et al. (2010) Phylogenetic relationships of the pygmy rice rats of the genus Oligoryzomys Bangs, 1900 (Rodentia, Sigmodontinae). Zoolog J Linn Soc 160(3): 551–566.
- 74. Pardiñas UFJ, D'Elía G, Ortíz PE (2002) Sigmodontinos fósiles (Rodentia, Muroidea, Sigmodontinae) de América del Sur: estado actual de su conocimiento y prospectiva. Mastozoolog Neotrop 9: 209–252.
- 75.
Rambaut A, Drummond AJ (2007) Molecular evolution, phylogenetics and epidemiology website. Available: http://beast.bio.ed.ac.uk/Tracer. Accessed 2011 August 10.
- 76.
Gelman A, Carlin JB, Stern HS, Rubin DB (1995) Bayesian data analysis. London: Chapman and Hall. 552 p.
- 77. Martins EP, Hansen TE (1997) Phylogenies and the comparative method: general approach to incorporating phylogenetic information into the analysis of interspecific data. Am Nat 149: 646–667.
- 78. Pagel MD (1997) Inferring evolutionary processes from phylogenies. Zoolog Scripta 26: 331–348.
- 79. Pagel MD (1999) Inferring the historical patterns of biological evolution. Nature 401: 877–884.
- 80. Pagel MD (1999) The maximum likelihood approach to reconstructing ancestral character states of discrete characters on phylogenies. Syst Biol 48: 612–622.
- 81. Freckleton RP, Harvey PH, Pagel M (2002) Phylogenetic analysis and comparative data: A test and review of evidence. Am Nat 160: 712–726.
- 82.
R Development Core Team (2008) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
- 83. Rabosky DL (2010) Extinction rates should not be estimated from molecular phylogenies. Evolution 64: 1816–1824.
- 84. Percequillo AR, Weksler M, Costa LP (2011) A new genus and species of rodent from the Brazilian Atlantic Forest (Rodentia: Cricetidae: Sigmodontinae: Oryzomyini), with comments on oryzomyine biogeography. Zoolog J Linn Soc 161: 357–390.
- 85. D' Elía G (2000) Comments on recent advances in understanding sigmodontine phylogeny and evolution. Mastozool Neot 7: 47–54.
- 86. Jansa SA, Weksler M (2004) Phylogeny of Muroid rodents: relationships within and among major lineages as determined by IRBP gene sequences. Mol Phylogenet Evol 31: 256–276.
- 87. McFarlane DA, Debrot AO (2001) A new species of extinct oryzomyine rodent from the Quaternary of Curaçao, Netherlands Antilles. Carib J Sci 37: 182–184.
- 88. Pardiñas UFJ (2008) A new genus of Oryzomyini rodent (Cricetidae: Sigmodontinae) from the Pleistocene of Argentina. J Mammal 89: 1270–1278.
- 89. Pardiñas UFJ, Deschamps C (1996) Sigmodontinos (Mammalia, Rodentia) pleistocénicos del sudoeste de la provincia de Buenos Aires (Argentina): aspectos sistemáticos, paleozoogeográficos y paleoambientales. Estud Geolog 52: 367–379.
- 90. Pardiñas UFJ, Teta P, Cirignoli S, Podestá DH (2003) Micromamíferos (Didelphimorphia y Rodentia) de norpatagonia extra andina, Argentina: taxonomía alfa y biogeografía. Mastozoolog Neotrop 10(1): 69–113.
- 91. Teta P, Loponte D, Acosta A (2004) Sigmodontinos (Mammalia, Rodentia) del Holoceno tardío del nordeste de la provincia de Buenos Aires (Argentina). Mastozoolog Neotrop 11(1): 69–80.
- 92. Turvey ST, Weksler M, Morris EL, Nokkert M (2010) Taxonomy, phylogeny and diversity of the extinct Lesser Antillean rice rats (Sigmodontinae: Oryzomyini), with description of a new genus and species. Zoolog J Linn Soc 160: 748–772.
- 93. Voss RS, Weksler M (2009) On the taxonomic status of Oryzomys curasoae McFarlane and Debrot, 2001, with remarks on the phylogenetic relationships of O. gorgasi Hershkovitz, 1971. Carib J Sci 45: 1–7.
- 94. Ziljstra JS, Madern PA, van den Hoek Ostende LW (2010) New genus and two new species of Pleistocene oryzomyines (Cricetidae: Sigmodontinae) from Bonaire, Netherlands Antilles. J Mammal 91(4): 860–873.
- 95. Steppan SJ (1996) A new species Holochilus (Rodentia: Sigmodontinae) from the middle Pleistocene of Bolivia and its phylogenetic significance. J Vert Paleont 16: 522–530.
- 96. McShea DW (2000) Matters of the record. Paleobiology 26: 330–333.
- 97. Raia P, Carotenuto F, Passaro F, Fulgione D, Fortelius M (2011) Ecological specialization in fossil mammals explain Cope's rule. Am Nat 179(3): 328–337.
- 98. Agrawal AA, Dorken ME (2001) Law of the unspecialized: broken?. Trends Ecol Evol 16(8): 426.
- 99. Venditti C, Meade A, Pagel M (2011) Multiple routes of mammalian diversification. Nature 479: 393–396.
- 100. Coates AG, Jackson JB, Collins LS, Cronin TM, Dowsett HJ, et al. (1992) Closure of the Isthmus of Panama: the near-shore marine record of Costa Rica and western Panama. Geolog Soc Am Bull 104: 814–828.
- 101. Ibaraki M (1997) Closing of the Central American seaway and Neogene coastal upwelling along the Pacific coast of South America. Tectonophysics 281: 99–104.
- 102. Stadler T (2011) Mammalian phylogeny reveals recent diversification rate shifts. Proc Natl Acad Sci U S A 108: 6187–6192.
- 103. Silvestro D, Schnitzler J, Zizka G (2011) A bayesian framework to estimate diversification rates and their variation through time and space. BMC Evol Biol 11: 311.