Time since fire as a driver of taxonomic and phylogenetic patterns of grassland plant communities.

Fire plays a key role in grasslands, determining the distribution and evolution of species and boundaries with neighboring ecosystems. Evidence of community-wide responses to fire is largely based on taxonomic and functional descriptors, while the phylogenetic dimension is overlooked. Here we evaluated how the taxonomic and phylogenetic structure of grassland plant communities responded to a time since fire (TSF) gradient. We sampled 12 communities in Southern Brazil under varying TSF and calculated taxonomic species richness (S) and dominance (D), phylogenetic diversity (PD), and mean phylogenetic distances (MPD). We used Structural Equation Models to test the relationships between the environmental gradient and community descriptors. Communities with longer TSF presented higher PD and MPD but lower species richness and increased taxonomic dominance. These sites were dominated by monocots, specifically C4 grasses, but also presented exclusive clades, whereas recently-burned sites presented lower taxonomic dominance and more species distributed in a wider variety of clades. Our results indicate that these scenarios are interchangeable and dependent on fire management. Fire adaptation was not constrained by phylogenetic relatedness, contrasting with previous findings for tropical savannahs and indicating that temperate and tropical non-forest ecosystems from South America respond differently to fire, possibly due to different evolutionary histories.

HEAD LOUSE PALEOEPIDEMIOLOGY IN THE OSMORE RIVER VALLEY, SOUTHERN PERU.

Recent studies of louse ectoparasites from mummies have developed robust data sets that allow a true epidemiological approach to the prehistory of louse parasitism. One epidemiological principle is that the binomial of overdispersion is normally negative, meaning that in a host population, parasites are aggregated in a few individuals. We demonstrate the overdispersion of lice in 3 different prehistoric communities that differ along 3 axes or variables: environmental setting, socioeconomic status, and cultural affiliation. Distinct cultural practices could have been involved in different patterns of louse infestation. Prevalence, intensity, and abundance of infestations exhibit statistically significant differences between the communities. We also find differences in prevalence between subadults and adults that contrasted by cultural affiliation and suggest conditions different from those seen today. We show that overall prevalence was affected primarily by ecological setting, not socioeconomic status nor cultural affiliation. These findings demonstrate that statistical analysis of archaeological data can reveal the states of infestation in past populations with lifestyles not seen in modern people. Our approach paves the way for future comparisons of subpopulations within archaeological communities.

Type I multivariate zero-inflated COM-Poisson regression model.

In this paper, we present the Type I multivariate zero-inflated Conway-Maxwell-Poisson distribution, whose development is based on the extension of the Type I multivariate zero-inflated Poisson distribution. We developed important properties of the distribution and present a regression model. The AIC and BIC criteria are used to select the best fitted model. Two real data sets have been used to illustrate the proposed model. Moreover, we conclude by stating that the Type I multivariate zero-inflated Conway-Maxwell-Poisson distribution produces a better fitted model for multivariate count data with excess of zeros.

Correcting notification delay and forecasting of COVID-19 data.

Since the first official case of COVID-19 was reported, many researchers around the world have spent their time trying to understand the dynamics of the virus by modeling and predicting the number of infected and deaths. The rapid spread and highly contagiousness motivate the necessity of monitoring cases in real-time, aiming to keep control of the epidemic. As pointed out by [3], some pitfalls like limited infrastructure, laboratory confirmation and logistical problems may cause reporting delay, leading to distortions of the real dynamics of the confirmed cases and deaths. The aim of this study is to propose a suitable statistical methodology for modeling and forecasting daily deaths and reported cases of COVID-19, considering key features as overdispersion of data and correction of notification delay. Both, reporting delays and forecasting consider a Bayesian approach in which the daily deaths and the confirmed cases are modelled using the negative binomial (NB) distribution in order to accommodate the population heterogeneity. For the correction of notification delay, the mean number of occurrences regarding time t notified at time t + j (mean delayed notifications) is associated to the temporal and the delay lag evolution of the notification process through a log link. With regard to daily forecasting, the functional form adopted for the number of deaths and reported cases of COVID-19 is related to the sigmoid growth equation. A variable regarding week days or days off was considered in order to account for possible reduction of the records due to the lower offer of tests on days off. To illustrate the methodology, we analyze data of deaths and infected cases of COVID-19 in Espírito Santo, Brazil. We also obtain long-term predictions.

A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data.

Count datasets are traditionally analyzed using the ordinary Poisson distribution. However, said model has its applicability limited, as it can be somewhat restrictive to handling specific data structures. In this case, the need arises for obtaining alternative models that accommodate, for example, overdispersion and zero modification (inflation/deflation at the frequency of zeros). In practical terms, these are the most prevalent structures ruling the nature of discrete phenomena nowadays. Hence, this paper's primary goal was to jointly address these issues by deriving a fixed-effects regression model based on the hurdle version of the Poisson-Sujatha distribution. In this framework, the zero modification is incorporated by considering that a binary probability model determines which outcomes are zero-valued, and a zero-truncated process is responsible for generating positive observations. Posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the g-prior method. Intensive Monte Carlo simulation studies were performed to assess the Bayesian estimators' empirical properties, and the obtained results have been discussed. The proposed model was considered for analyzing a real dataset, and its competitiveness regarding some well-established fixed-effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian p-value and the randomized quantile residuals were considered for the task of model validation.

A new mixed-effects regression model for the analysis of zero-modified hierarchical count data.

Count data sets are traditionally analyzed using the ordinary Poisson distribution. However, such a model has its applicability limited as it can be somewhat restrictive to handle specific data structures. In this case, it arises the need for obtaining alternative models that accommodate, for example, (a) zero-modification (inflation or deflation at the frequency of zeros), (b) overdispersion, and (c) individual heterogeneity arising from clustering or repeated (correlated) measurements made on the same subject. Cases (a)-(b) and (b)-(c) are often treated together in the statistical literature with several practical applications, but models supporting all at once are less common. Hence, this paper's primary goal was to jointly address these issues by deriving a mixed-effects regression model based on the hurdle version of the Poisson-Lindley distribution. In this framework, the zero-modification is incorporated by assuming that a binary probability model determines which outcomes are zero-valued, and a zero-truncated process is responsible for generating positive observations. Approximate posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the Adaptive Metropolis algorithm. Intensive Monte Carlo simulation studies were performed to assess the empirical properties of the Bayesian estimators. The proposed model was considered for the analysis of a real data set, and its competitiveness regarding some well-established mixed-effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian p -value and the randomized quantile residuals were considered for model diagnostics.

Zero-inflated Bell regression models for count data.

By starting from the one-parameter Bell distribution proposed recently in the statistic literature, we introduce the zero-inflated Bell family of distributions. Additionally, on the basis of the proposed zero-inflated distribution, a novel zero-inflated regression model is proposed, which is quite simple and may be an interesting alternative to usual zero-inflated regression models for count data. We consider a frequentist approach to perform inferences, and the maximum likelihood method is employed to estimate the zero-inflated Bell regression parameters. Monte Carlo simulations indicate that the maximum likelihood method is quite effective to estimate the zero-inflated Bell regression parameters. We also propose the Pearson residuals for the new zero-inflated regression model to assess departures from model assumptions. Additionally, the global and local influence methods are discussed. In particular, the normal curvature for studying local influence is derived under case weighting perturbation scheme. Finally, an application to the count of infected blood cells is considered to illustrate the usefulness of the zero-inflated Bell regression model in practice. The results suggest that the new zero-inflated Bell regression is more appropriate to model these count data than other familiar zero-inflated (or not) regression models commonly used in practice.

A new long-term survival model with dispersion induced by discrete frailty.

Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there are situations where a discretely-distributed frailty may be appropriate. In this paper, we propose extending the proportional hazards frailty models to allow a discrete distribution for the frailty variable. Having zero frailty can be interpreted as being immune or cured (long-term survivors). Thus, we develop a new survival model induced by discrete frailty with zero-inflated power series distribution, which can account for overdispersion. A numerical study is carried out under the scenario that the baseline distribution follows an exponential distribution, however this assumption can be easily relaxed and some other distributions can be considered. Moreover, this proposal allows for a more realistic description of the non-risk individuals, since individuals cured due to intrinsic factors (immune) are modeled by a deterministic fraction of zero-risk while those cured due to an intervention are modeled by a random fraction. Inference is developed by the maximum likelihood method for the estimation of the model parameters. A simulation study is performed in order to evaluate the performance of the proposed inferential method. Finally, the proposed model is applied to a data set on malignant cutaneous melanoma to illustrate the methodology.

Double Poisson-Tweedie Regression Models.

In this paper, we further extend the recently proposed Poisson-Tweedie regression models to include a linear predictor for the dispersion as well as for the expectation of the count response variable. The family of the considered models is specified using only second-moments assumptions, where the variance of the count response has the form µ+ϕµp $\mu + \phi \mu^p$, where µ is the expectation, ϕ and p are the dispersion and power parameters, respectively. Parameter estimations are carried out using an estimating function approach obtained by combining the quasi-score and Pearson estimating functions. The performance of the fitting algorithm is investigated through simulation studies. The results showed that our estimating function approach provides consistent estimators for both mean and dispersion parameters. The class of models is motivated by a data set concerning CD4 counting in HIV-positive pregnant women assisted in a public hospital in Curitiba, Paraná, Brazil. Specifically, we investigate the effects of a set of covariates in both expectation and dispersion structures. Our results showed that women living out of the capital Curitiba, with viral load equal or larger than 1000 copies and with previous diagnostic of HIV infection, present lower levels of CD4 cell count. Furthermore, we detected that the time to initiate the antiretroviral therapy decreases the data dispersion. The data set and R code are available as supplementary materials.

Landscape and Environmental Factors Influencing Stage Persistence and Abundance of the Bamboo Mosquito, Tripteroides bambusa (Diptera: Culicidae), across an Altitudinal Gradient.

The bamboo mosquito, Tripteroides bambusa (Yamada) (Diptera: Culicidae), is a common insect across East Asia. Several studies have looked at the ecology of Tr. bambusa developmental stages separately, but little is known about the factors associated with the persistence (how often) and abundance (how many individuals) of Tr. bambusa stages simultaneously studied across a heterogeneous landscape. Here, we ask what environmental and landscape factors are associated with the persistence and abundance of Tr. bambusa stages across the altitudinal gradient of Mt. Konpira, Nagasaki City, Japan. During a season-long study we counted 8065 (7297 4th instar larvae, 670 pupae and 98 adults) Tr. bambusa mosquitoes. We found that persistence and abundance patterns were not associated among stages, with the exception of large (4th instar) and small (1st to 3rd instars) larvae persistence, which were positively correlated. We also found that relative humidity was associated with the persistence of Tr. bambusa aquatic stages, being positively associated with large and small larvae, but negatively with pupae. Similarly, landscape aspect changed from positive to negative the sign of its association with Tr. bambusa pupae and adults, highlighting that environmental associations change with life stage. Meanwhile, Tr. bambusa abundance patterns were negatively impacted by more variable microenvironments, as measured by the negative impacts of kurtosis and standard deviation (SD) of environmental variables, indicating Tr. bambusa thrives in stable environments, suggesting this mosquito species has a finely grained response to environmental changes.

Recovering parasites from mummies and coprolites: an epidemiological approach.

In the field of archaeological parasitology, researchers have long documented the distribution of parasites in archaeological time and space through the analysis of coprolites and human remains. This area of research defined the origin and migration of parasites through presence/absence studies. By the end of the 20th century, the field of pathoecology had emerged as researchers developed an interest in the ancient ecology of parasite transmission. Supporting studies were conducted to establish the relationships between parasites and humans, including cultural, subsistence, and ecological reconstructions. Parasite prevalence data were collected to infer the impact of parasitism on human health. In the last few decades, a paleoepidemiological approach has emerged with a focus on applying statistical techniques for quantification. The application of egg per gram (EPG) quantification methods provide data about parasites' prevalence in ancient populations and also identify the pathological potential that parasitism presented in different time periods and geographic places. Herein, we compare the methods used in several laboratories for reporting parasite prevalence and EPG quantification. We present newer quantification methods to explore patterns of parasite overdispersion among ancient people. These new methods will be able to produce more realistic measures of parasite infections among people of the past. These measures allow researchers to compare epidemiological patterns in both ancient and modern populations.

Ecological versatility and the assembly of multiple competitors: cautionary notes for assembly inferences.

The role of niche differences and competition is invoked when one finds coexisting species to be more dissimilar in trait composition than expected at random in community assembly studies. This approach has been questioned as competition has been hypothesized to either lead to communities assembled by similar or dissimilar species, depending on whether species similarity reflects fitness or niche differences, respectively. A current problem is that the arguments used to draw relationships between competition and species similarity are based on pairwise theoretical examples, while in nature competition can occurs among a constellation of species with different levels of versatility in resources used. By versatility we mean the documented ability of some species to escape competition for commonly used resources by changing for marginal and unused resources. Thus, a versatile species will have the ability to decrease niche overlap with all other species when facing strong competitors. When these species are embedded in multiple interactions the role of pairwise niche and fitness differences could be reduced due to indirect effects and thus competition would not be detectable. Here we developed a coexistence theory where competition occurs simultaneously among multiple species with different levels of versatility and then used it in a simulation to unravel patterns of species similarity during community assembly. We found that simulated communities can be assembled by species with more, less or equal similarity compared to a null model when using a mean distance based metric (SES.MPD). However, contrasting these varied results, we consistently found species overdispersion using a nearest neighbor-based metric (SES.MNTD), even when species differences reflected more directly their competitive abilities than their niche differences. Strong tendency to overdispersion emerged when high ecological versatility promoted large niche differences and enabled coexistence. This is because versatility to use marginal resources compensates possible fitness differences among species. Our findings provide mounting evidence of the important role of minimum niche differences and versatility in resource consumption for species embedded in multiple direct and indirect interactions.

Conditional overdispersed models: Application to count area data.

This paper proposes alternative models for the analysis of count data featuring a given spatial structure, which corresponds to geographical areas. We assume that the overdispersion data structure partially results from the existing and well justified spatial correlation between geographical adjacent regions, so an extension of existing overdispersion models that include spatial neighborhood structures within a Bayesian framework is proposed. These models allow practitioners to quantify the association explained by the considered neighborhood structures and the one modelled by additional factors. Finally, using the information provided by the Colombian National Demographic and Health Survey, the usefulness of the proposed models is illustrated by fitting them to infant mortality rates and to data including the proportion of mothers who, after giving birth to their last child, underwent a postnatal screening period in Colombia.

Quantifying intraclass correlations for count and time-to-event data.

The intraclass correlation is commonly used with clustered data. It is often estimated based on fitting a model to hierarchical data and it leads, in turn, to several concepts such as reliability, heritability, inter-rater agreement, etc. For data where linear models can be used, such measures can be defined as ratios of variance components. Matters are more difficult for non-Gaussian outcomes. The focus here is on count and time-to-event outcomes where so-called combined models are used, extending generalized linear mixed models, to describe the data. These models combine normal and gamma random effects to allow for both correlation due to data hierarchies as well as for overdispersion. Furthermore, because the models admit closed-form expressions for the means, variances, higher moments, and even the joint marginal distribution, it is demonstrated that closed forms of intraclass correlations exist. The proposed methodology is illustrated using data from agricultural and livestock studies.

Structure of the parasites communities in two Erythrinidae fish from Amazon river system (Brazil) / Estrutura da comunidade de parasitos em dois Erythrinidae do sistema do Rio Amazonas (Brasil)

This study compared the parasite communities of Hoplias malabaricus and Hoplerythrinus unitaeniatus from Amazon river system. Hoplias malabaricus were infected by Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercariae of Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvae of Contracaecum sp. and larvae of Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus were also infected by these same species of protozoans, nematodes, digeneans and cestodes, except for Tetrahymena sp. and B. patagonica, which were replaced by Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju and Gorytocephalus spectabilis. For both hosts, I. multifiliis and P. pillulare were the predominant parasites. Most of the parasites presented an overdispersion. Parasite species richness, Brillouin diversity, evenness and Berger-Parker dominance were similar for the two hosts. The length and weight of H. malabaricus showed a positive correlation with the abundance of U. eremitus and Contracaecum sp., while the weight of H. unitaeniatus showed a positive correlation with the abundance of I. multifiliis. The diversity of ectoparasites seemed to be influenced by the behavior of these two hosts. This was shown by the similar parasite communities and was characterized by low species diversity, low evenness and low richness, and by a high prevalence of ectoparasites.(AU)

Este estudo comparou a comunidade parasitária de Hoplias malabaricus e Hoplerythrinus unitaeniatus do sistema do Rio Amazonas. Hoplias malabaricus estavam infectados por Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercarias de Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvas de Contracaecum sp. e larvas de Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus estavam também infectados por essas mesmas espécies de protozoários, nematoides, digeneas e cestóide, exceto Tetrahymena sp. e B. patagonica, que foram substituídos por Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju e Gorytocephalus spectabilis. Para ambos os hospedeiros, a dominância foi de I. multifiliis e P. pillulare. Houve dispersão agregada para a maioria dos parasitos e similar riqueza de espécies de parasitos, diversidade de Brillouin, uniformidade e dominância de Berger-Parker, para ambos os hospedeiros. O comprimento e peso de H. malabaricus mostrou correlação positiva com a abundância de U. eremitus e Contracaecum sp., enquanto o peso de H. unitaeniatus mostrou correlação positiva com abundância de I. multifiliis. A diversidade de ectoparasitos parece influenciada pelo comportamento desses dois hospedeiros. Isso é mostrado pela similar comunidade de parasitos e caracterizada por uma baixa diversidade de espécies, baixa uniformidade e baixa riqueza de espécies, e pela elevada prevalência de ectoparasitos.(AU)

Structure of the parasites communities in two Erythrinidae fish from Amazon river system (Brazil) / Estrutura da comunidade de parasitos em dois Erythrinidae do sistema do Rio Amazonas (Brasil)

This study compared the parasite communities of Hoplias malabaricus and Hoplerythrinus unitaeniatus from Amazon river system. Hoplias malabaricus were infected by Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercariae of Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvae of Contracaecum sp. and larvae of Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus were also infected by these same species of protozoans, nematodes, digeneans and cestodes, except for Tetrahymena sp. and B. patagonica, which were replaced by Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju and Gorytocephalus spectabilis. For both hosts, I. multifiliis and P. pillulare were the predominant parasites. Most of the parasites presented an overdispersion. Parasite species richness, Brillouin diversity, evenness and Berger-Parker dominance were similar for the two hosts. The length and weight of H. malabaricus showed a positive correlation with the abundance of U. eremitus and Contracaecum sp., while the weight of H. unitaeniatus showed a positive correlation with the abundance of I. multifiliis. The diversity of ectoparasites seemed to be influenced by the behavior of these two hosts. This was shown by the similar parasite communities and was characterized by low species diversity, low evenness and low richness, and by a high prevalence of ectoparasites.

Este estudo comparou a comunidade parasitária de Hoplias malabaricus e Hoplerythrinus unitaeniatus do sistema do Rio Amazonas. Hoplias malabaricus estavam infectados por Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercarias de Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvas de Contracaecum sp. e larvas de Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus estavam também infectados por essas mesmas espécies de protozoários, nematoides, digeneas e cestóide, exceto Tetrahymena sp. e B. patagonica, que foram substituídos por Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju e Gorytocephalus spectabilis. Para ambos os hospedeiros, a dominância foi de I. multifiliis e P. pillulare. Houve dispersão agregada para a maioria dos parasitos e similar riqueza de espécies de parasitos, diversidade de Brillouin, uniformidade e dominância de Berger-Parker, para ambos os hospedeiros. O comprimento e peso de H. malabaricus mostrou correlação positiva com a abundância de U. eremitus e Contracaecum sp., enquanto o peso de H. unitaeniatus mostrou correlação positiva com abundância de I. multifiliis. A diversidade de ectoparasitos parece influenciada pelo comportamento desses dois hospedeiros. Isso é mostrado pela similar comunidade de parasitos e caracterizada por uma baixa diversidade de espécies, baixa uniformidade e baixa riqueza de espécies, e pela elevada prevalência de ectoparasitos.

Assessing intervention efficacy on high-risk drinkers using generalized linear mixed models with a new class of link functions.

Unhealthy alcohol use is one of the leading causes of morbidity and mortality in the United States. Brief interventions with high-risk drinkers during an emergency department (ED) visit are of great interest due to their possible efficacy and low cost. In a collaborative study with patients recruited at 14 academic ED across the United States, we examined the self-reported number of drinks per week by each patient following the exposure to a brief intervention. Count data with overdispersion have been mostly analyzed with generalized linear mixed models (GLMMs), of which only a limited number of link functions are available. Different choices of link function provide different fit and predictive power for a particular dataset. We propose a class of link functions from an alternative way to incorporate random effects in a GLMM, which encompasses many existing link functions as special cases. The methodology is naturally implemented in a Bayesian framework, with competing links selected with Bayesian model selection criteria such as the conditional predictive ordinate (CPO). In application to the ED intervention study, all models suggest that the intervention was effective in reducing the number of drinks, but some new models are found to significantly outperform the traditional model as measured by CPO. The validity of CPO in link selection is confirmed in a simulation study that shared the same characteristics as the count data from high-risk drinkers. The dataset and the source code for the best fitting model are available in Supporting Information.

Phylogenetic overdispersion of plant species in southern Brazilian savannas / Dispersão filogenética de espécies de plantas em savanas no Sudeste do Brasil

Ecological communities are the result of not only present ecological processes, such as competition among species and environmental filtering, but also past and continuing evolutionary processes. Based on these assumptions, we may infer mechanisms of contemporary coexistence from the phylogenetic relationships of the species in a community. We studied the phylogenetic structure of plant communities in four cerrado sites, in southeastern Brazil. We calculated two raw phylogenetic distances among the species sampled. We estimated the phylogenetic structure by comparing the observed phylogenetic distances to the distribution of phylogenetic distances in null communities. We obtained null communities by randomizing the phylogenetic relationships of the regional pool of species. We found a phylogenetic overdispersion of the cerrado species. Phylogenetic overdispersion has several explanations, depending on the phylogenetic history of traits and contemporary ecological interactions. However, based on coexistence models between grasses and trees, density-dependent ecological forces, and the evolutionary history of the cerrado flora, we argue that the phylogenetic overdispersion of cerrado species is predominantly due to competitive interactions, herbivores and pathogen attacks, and ecological speciation. Future studies will need to include information on the phylogenetic history of plant traits.

Comunidades ecológicas resultam não somente de processos ecológicos atuais, como a competição e os filtros ambientais, mas também de processos evolutivos passados e contínuos. Com base nessas premissas, podemos inferir mecanismos de coexistência contemporânea a partir das relações filogenéticas das espécies em uma comunidade. Estudamos a estrutura filogenética das comunidades de plantas de quatro áreas de cerrado, no Sudeste do Brasil. Calculamos duas medidas das distâncias filogenéticas das espécies amostradas. Estimamos a estrutura filogenética comparando suas distâncias observadas com a distribuição dessas distâncias em comunidades nulas. Obtivemos comunidades nulas aleatorizando as relações filogenéticas do banco regional de espécies. Encontramos uma dispersão filogenética de espécies de cerrado. Há várias explicações para essa dispersão, dependendo da história filogenética dos traços e das interações ecológicas contemporâneas. Entretanto, com base nos modelos de coexistência entre árvores e gramíneas, nas forças ecológicas dependentes da densidade e na história evolutiva da flora do cerrado, argumentamos que a dispersão filogenética das espécies do cerrado é predominantemente devida às interações competitivas, aos ataques de herbívoros e patógenos e à especiação ecológica. Estudos futuros precisarão incluir informações sobre a história filogenética dos traços das plantas.

Phylogenetic overdispersion of plant species in southern Brazilian savannas

Ecological communities are the result of not only present ecological processes, such as competition among species and environmental filtering, but also past and continuing evolutionary processes. Based on these assumptions, we may infer mechanisms of contemporary coexistence from the phylogenetic relationships of the species in a community. We studied the phylogenetic structure of plant communities in four cerrado sites, in southeastern Brazil. We calculated two raw phylogenetic distances among the species sampled. We estimated the phylogenetic structure by comparing the observed phylogenetic distances to the distribution of phylogenetic distances in null communities. We obtained null communities by randomizing the phylogenetic relationships of the regional pool of species. We found a phylogenetic overdispersion of the cerrado species. Phylogenetic overdispersion has several explanations, depending on the phylogenetic history of traits and contemporary ecological interactions. However, based on coexistence models between grasses and trees, density-dependent ecological forces, and the evolutionary history of the cerrado flora, we argue that the phylogenetic overdispersion of cerrado species is predominantly due to competitive interactions, herbivores and pathogen attacks, and ecological speciation. Future studies will need to include information on the phylogenetic history of plant traits.

Comunidades ecológicas resultam não somente de processos ecológicos atuais, como a competição e os filtros ambientais, mas também de processos evolutivos passados e contínuos. Com base nessas premissas, podemos inferir mecanismos de coexistência contemporânea a partir das relações filogenéticas das espécies em uma comunidade. Estudamos a estrutura filogenética das comunidades de plantas de quatro áreas de cerrado, no Sudeste do Brasil. Calculamos duas medidas das distâncias filogenéticas das espécies amostradas. Estimamos a estrutura filogenética comparando suas distâncias observadas com a distribuição dessas distâncias em comunidades nulas. Obtivemos comunidades nulas aleatorizando as relações filogenéticas do banco regional de espécies. Encontramos uma dispersão filogenética de espécies de cerrado. Há várias explicações para essa dispersão, dependendo da história filogenética dos traços e das interações ecológicas contemporâneas. Entretanto, com base nos modelos de coexistência entre árvores e gramíneas, nas forças ecológicas dependentes da densidade e na história evolutiva da flora do cerrado, argumentamos que a dispersão filogenética das espécies do cerrado é predominantemente devida às interações competitivas, aos ataques de herbívoros e patógenos e à especiação ecológica. Estudos futuros precisarão incluir informações sobre a história filogenética dos traços das plantas.