992 resultados para Neutral theory


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Aim Recent studies have suggested that global diatom distributions are not limited by dispersal, in the case of both extant species and fossil species, but rather that environmental filtering explains their spatial patterns. Hubbell's neutral theory of biodiversity provides a framework in which to test these alternatives. Our aim is to test whether the structure of marine phytoplankton (diatoms, dinoflagellates and coccolithophores) assemblages across the Atlantic agrees with neutral theory predictions. We asked: (1) whether intersite variance in phytoplankton diversity is explained predominantly by dispersal limitation or by environmental conditions; and (2) whether species abundance distributions are consistent with those expected by the neutral model. Location Meridional transect of the Atlantic (50 degrees N50 degrees S). Methods We estimated the relative contributions of environmental factors and geographic distance to phytoplankton composition using similarity matrices, Mantel tests and variation partitioning of the species composition based upon canonical ordination methods. We compared the species abundance distribution of phytoplankton with the neutral model using Etienne's maximum-likelihood inference method. Results Phytoplankton communities are slightly more determined by niche segregation (24%), than by dispersal limitation and ecological drift (17%). In 60% of communities, the assumption of neutrality in species' abundance distributions could not be rejected. In tropical zones, where oceanic gyres enclose large stable water masses, most communities showed low species immigration rates; in contrast, we infer that communities in temperate areas, out of oligotrophic gyres, have higher rates of species immigration. Conclusions Phytoplankton community structure is consistent with partial niche assembly and partial dispersal and drift assembly (neutral processes). The role of dispersal limitation is almost as important as habitat filtering, a fact that has been largely overlooked in previous studies. Furthermore, the polewards increase in immigration rates of species that we have discovered is probably caused by water mixing conditions and productivity.

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Beta diversity describes how local communities within an area or region differ in species composition/abundance. There have been attempts to use changes in beta diversity as a biotic indicator of disturbance, but lack of theory and methodological caveats have hampered progress. We here propose that the neutral theory of biodiversity plus the definition of beta diversity as the total variance of a community matrix provide a suitable, novel, starting point for ecological applications. Observed levels of beta diversity (BD) can be compared to neutral predictions with three possible outcomes: Observed BD equals neutral prediction or is larger (divergence) or smaller (convergence) than the neutral prediction. Disturbance might lead to either divergence or convergence, depending on type and strength. We here apply these ideas to datasets collected on oribatid mites (a key, very diverse soil taxon) under several regimes of disturbances. When disturbance is expected to increase the heterogeneity of soil spatial properties or the sampling strategy encompassed a range of diverging environmental conditions, we observed diverging assemblages. On the contrary, we observed patterns consistent with neutrality when disturbance could determine homogenization of soil properties in space or the sampling strategy encompassed fairly homogeneous areas. With our method, spatial and temporal changes in beta diversity can be directly and easily monitored to detect significant changes in community dynamics, although the method itself cannot inform on underlying mechanisms. However, human-driven disturbances and the spatial scales at which they operate are usually known. In this case, our approach allows the formulation of testable predictions in terms of expected changes in beta diversity, thereby offering a promising monitoring tool.

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Neutral and niche theories give contrasting explanations for the maintenance of tropical tree species diversity. Both have some empirical support, but methods to disentangle their effects have not yet been developed. We applied a statistical measure of spatial structure to data from 14 large tropical forest plots to test a prediction of niche theory that is incompatible with neutral theory: that species in heterogeneous environments should separate out in space according to their niche preferences. We chose plots across a range of topographic heterogeneity, and tested whether pairwise spatial associations among species were more variable in more heterogeneous sites. We found strong support for this prediction, based on a strong positive relationship between variance in the spatial structure of species pairs and topographic heterogeneity across sites. We interpret this pattern as evidence of pervasive niche differentiation, which increases in importance with increasing environmental heterogeneity.

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Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.

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1. Ecologists are debating the relative role of deterministic and stochastic determinants of community structure. Although the high diversity and strong spatial structure of soil animal assemblages could provide ecologists with an ideal ecological scenario, surprisingly little information is available on these assemblages.
2. We studied species-rich soil oribatid mite assemblages from a Mediterranean beech forest and a grassland. We applied multivariate regression approaches and analysed spatial autocorrelation at multiple spatial scales using Moran's eigenvectors. Results were used to partition community variance in terms of the amount of variation uniquely accounted for by environmental correlates (e.g. organic matter) and geographical position. Estimated neutral diversity and immigration parameters were also applied to a soil animal group for the first time to simulate patterns of community dissimilarity expected under neutrality, thereby testing neutral predictions.
3. After accounting for spatial autocorrelation, the correlation between community structure and key environmental parameters disappeared: about 40% of community variation consisted of spatial patterns independent of measured environmental variables such as organic matter. Environmentally independent spatial patterns encompassed the entire range of scales accounted for by the sampling design (from tens of cm to 100 m). This spatial variation could be due to either unmeasured but spatially structured variables or stochastic drift mediated by dispersal. Observed levels of community dissimilarity were significantly different from those predicted by neutral models.
4. Oribatid mite assemblages are dominated by processes involving both deterministic and stochastic components and operating at multiple scales. Spatial patterns independent of the measured environmental variables are a prominent feature of the targeted assemblages, but patterns of community dissimilarity do not match neutral predictions. This suggests that either niche-mediated competition or environmental filtering or both are contributing to the core structure of the community. This study indicates new lines of investigation for understanding the mechanisms that determine the signature of the deterministic component of animal community assembly.

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Extreme arid regions in the worlds' major deserts are typified by quartz pavement terrain. Cryptic hypolithic communities colonize the ventral surface of quartz rocks and this habitat is characterized by a relative lack of environmental and trophic complexity. Combined with readily identifiable major environmental stressors this provides a tractable model system for determining the relative role of stochastic and deterministic drivers in community assembly. Through analyzing an original, worldwide data set of 16S rRNA-gene defined bacterial communities from the most extreme deserts on the Earth, we show that functional assemblages within the communities were subject to different assembly influences. Null models applied to the photosynthetic assemblage revealed that stochastic processes exerted most effect on the assemblage, although the level of community dissimilarity varied between continents in a manner not always consistent with neutral models. The heterotrophic assemblages displayed signatures of niche processes across four continents, whereas in other cases they conformed to neutral predictions. Importantly, for continents where neutrality was either rejected or accepted, assembly drivers differed between the two functional groups. This study demonstrates that multi-trophic microbial systems may not be fully described by a single set of niche or neutral assembly rules and that stochasticity is likely a major determinant of such systems, with significant variation in the influence of these determinants on a global scale.

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In spite of the controversy that they have generated, neutral models provide ecologists with powerful tools for creating dynamic predictions about beta-diversity in ecological communities. Ecologists can achieve an understanding of the assembly rules operating in nature by noting when and how these predictions are met or not met. This is particularly valuable for those groups of organisms that are challenging to study under natural conditions (e.g., bacteria and fungi). Here, we focused on arbuscular mycorrhizal fungal (AMF) communities and performed an extensive literature search that allowed us to synthesize the information in 19 data sets with the minimal requisites for creating a null hypothesis in terms of community dissimilarity expected under neutral dynamics. In order to achieve this task, we calculated the first estimates of neutral parameters for several AMF communities from different ecosystems. Communities were shown either to be consistent with neutrality or to diverge or converge with respect to the levels of compositional dissimilarity expected under neutrality. These data support the hypothesis that divergence occurs in systems where the effect of limited dispersal is overwhelmed by anthropogenic disturbance or extreme biological and environmental heterogeneity, whereas communities converge when systems have the potential for niche divergence within a relatively homogeneous set of environmental conditions. Regarding the study cases that were consistent with neutrality, the sampling designs employed may have covered relatively homogeneous environments in which the effects of dispersal limitation overwhelmed minor differences among AMF taxa that would lead to environmental filtering. Using neutral models we showed for the first time for a soil microbial group the conditions under which different assembly processes may determine different patterns of beta-diversity. Our synthesis is an important step showing how the application of general ecological theories to a model microbial taxon has the potential to shed light on the assembly and ecological dynamics of communities.

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Ecologists usually estimate means, but devote much less attention to variation. The study of variation is a key aspect to understand natural systems and to make predictions regarding them. In community ecology, most studies focus on local species diversity (alpha diversity), but only in recent decades have ecologists devoted proper attention to variation in community composition among sites (beta diversity). This is in spite of the fact that the first attempts to estimate beta diversity date back to the pioneering work by Koch and Whittaker in the 1950s. Progress in the last decade has been made in the development both of methods and of hypotheses about the origin and maintenance of variation in community composition. For instance, methods are available to partition total diversity in a region (gamma diversity), in a local component (alpha), and several beta diversities, each corresponding to one scale in a hierarchy. The popularization of the so-called raw-data approach (based on partial constrained ordination techniques) and the distance-based approach (based on correlation of dissimilarity/distance matrices) have allowed many ecologists to address current hypotheses about beta diversity patterns. Overall, these hypotheses are based on niche and neutral theory, accounting for the relative roles of environmental and spatial processes (or a combination of them) in shaping metacommunities. Recent studies have addressed these issues on a variety of spatial and temporal scales, habitats and taxonomic groups. Moreover, life history and functional traits of species such as dispersal abilities and rarity have begun to be considered in studies of beta diversity. In this article we briefly review some of these new tools and approaches developed in recent years, and illustrate them by using case studies in aquatic ecosystems.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Metacommunity ecology focuses on the interaction between local communities and is inherently linked to dispersal as a result. Within this framework, communities are structured by a combination of in-site responses to the immediate environment (species sorting), stochasticity (patch dynamics), and connections to other communities via distance between communities and dispersal (neutrality), and source-sink dynamics (mass effects; see Chapter 1 for a detailed description of metacommunity theory, the study site, and macroinvertebrate communities found). In Chapter 2 I describe spatial scale of study and dispersal ability as both have the ability to influence the degree to which communities interact. However, little is known about how these factors influence the importance of all metacommunity dynamics. I compared dispersal mode of immature aquatic insects and dispersal ability of winged adults across multiple spatial scales in a large river. The strongest drivers of river communities were patch dynamics, followed by species sorting, then neutrality. Active dispersers during aquatic lifestages on average exhibited lower patch dynamics, higher species sorting, and significant mass effects compared to passive dispersers. Active and strong dispersers also had a scale-independent influence of neutrality, while neutrality was stronger at broader spatial scale for passive and weak dispersers. These results indicate as dispersal ability increases patch dynamics decreases, species sorting increases, and neutrality should decrease. The perceived influence of neutrality may also be dependent on spatial scale and dispersal ability. In Chapter 3 I describe how river benthic macroinvertebrate communities may influence tributary invertebrate communities via adult flight and tributaries may influence mainstem communities via immature drift. This relationship may also depend on relative mainstem and tributary size, as well as abiotic tributary influence on mainstem habitat. To investigate the interaction between a larger river and tributary I sampled mainstem benthic invertebrate communities and quantified habitat of a 7th order river (West Branch Susquehanna River) above and below a 5th order tributary confluence, as well as 0.95-3.2 km upstream in the tributary. Non-metric multidimensional scaling showed similar patterns of clustering between sampling locations for both habitat characteristics and invertebrate communities. In addition, mainstem river communities and habitat directly downstream of the tributary confluence cluster tightly together, intermediate between tributary and mid-channel river samples. In Bray-Curtis dissimilarity comparisons between tributary and mainstem river communities the furthest upstream tributary communities were least similar to river communities. Middle tributary samples were also closest by Euclidean distance to the upstream mainstem riffle and exhibited higher similarity to mid-channel samples than the furthest downstream tributary communities. My results indicate river and tributary benthic invertebrate communities may interact and likely result in direct and indirect mass effects of a tributary on the downstream mainstem community by invertebrate drift and habitat restructuring via material delivery from the tributary. I also showed likely direct effects of adult dispersal from the river and oviposition in proximal tributary locations where Euclidian, rather than river, distance may be more important in determining river-tributary interactions.

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Generalmente los patrones espaciales de puntos en ecología, se definen en el espacio bi-dimensional, donde cada punto representado por el par ordenado (x,y), resume la ubicación espacial de una planta. La importancia de los patrones espaciales de plantas radica en que proceden como respuesta ante importantes procesos ecológicos asociados a la estructura de una población o comunidad. Tales procesos incluyen fenómenos como la dispersión de semillas, la competencia por recursos, la facilitación, respuesta de las plantas ante algún tipo de estrés, entre otros. En esta tesis se evalúan los factores y potenciales procesos subyacentes, que explican los patrones de distribución espacial de la biodiversidad vegetal en diferentes ecosistemas como bosque mediterráneo, bosque tropical y matorral seco tropical; haciendo uso de nuevas metodologías para comprobar hipótesis relacionadas a los procesos espaciales. En este trabajo se utilizaron dos niveles ecológicos para analizar los procesos espaciales, el nivel de población y el nivel de comunidad, con el fin de evaluar la importancia relativa de las interacciones intraespecíficas e interespecíficas. Me centré en el uso de funciones estadísticas que resumen los patrones de puntos para explorar y hacer inferencias a partir de datos espaciales, empezando con la construcción de un nuevo modelo nulo para inferir variantes del síndrome de dispersión de una planta parásita en España central. Se analizó la dependencia de los patrones espaciales tanto de los hospedantes afectados como de los no-afectados y se observó fuerte dependencia a pequeña y mediana distancia. Se utilizaron dos funciones (kernel) para simular la dispersión de la especie parásita y se identificó consistencia de estos modelos con otros síndromes de dispersión adicionalmente a la autodispersión. Un segundo tema consistió en desarrollar un método ANOVA de dos vías? para patrones de puntos replicados donde el interés se concentró en evaluar la interacción de dos factores. Este método se aplicó a un caso de estudio que consitió en analizar la influencia de la topografía y la altitud sobre el patrón espacial de un arbusto dominante en matorral seco al sur del Ecuador, cuyos datos provienen de patrones de puntos replicados basados en diseño. Partiendo de una metodología desarrollada para procesos uni-factoriales, se construyó el método para procesos bi-factoriales y así poder evaluar el efecto de interacción. Se observó que la topografía por sí sola así como la interacción con la altitud presentaron efecto significativo sobre la formación del patrón espacial. Un tercer tema fue identificar la relación entre el patrón espacial y el síndrome de dispersión de la comunidad vegetal en el bosque tropical de la Isla de Barro Colorado (BCI), Panamá. Muchos estudios se han desarrollado en este bosque tropical y algunos han analizado la relación síndrome-patrón espacial, sin embargo lo novedoso de nuestro estudio es que se evaluaron un conjunto amplio de modelos (114 modelos) basados en procesos que incorporan la limitación de la dispersión y la heterogeneidad ambiental, y evalúan el efecto único y el efecto conjunto, para posteriormente seleccionar el modelo de mejor ajuste para cada especie. Más de la mitad de las especies presentaron patrón espacial consistente con el efecto conjutno de la limitación de la dispersión y heterogeneidad ambiental y el porcentaje restante de especies reveló en forma equitativa el efecto único de la heterogeneidad ambiental y efecto único de limitación de la dispersión. Finalmente, con la misma información del bosque tropical de BCI, y para entender las relaciones que subyacen para mantener el equilibrio de la biodiversidad, se desarrolló un índice de dispersión funcional local a nivel de individuo, que permita relacionar el patrón espacial con cuatro rasgos funcionales clave de las especies. Pese a que muchos estudios realizados involucran esta comunidad con la teoría neutral, se encontró que el ensamble de la comunidad de BCI está afectado por limitaciones de similaridad y de hábitat a diferentes escalas. ABSTRACT Overall the spatial point patterns in ecology are defined in two-dimensional space, where each point denoted by the (x,y) ordered pair, summarizes the spatial location of a plant. The spatial point patterns are essential because they arise in response to important ecological processes, associated with the structure of a population or community. Such processes include phenomena as seed dispersal, competition for resources, facilitation, and plant response to some type of stress, among others. In this thesis, some factors and potential underlying processes were evaluated in order to explain the spatial distribution patterns of plant biodiversity. It was done in different ecosystems such as Mediterranean forest, tropical forest and dry scrubland. For this purpose new methodologies were used to test hypothesis related to spatial processes. Two ecological levels were used to analyze the spatial processes, at population and community levels, in order to assess the relative importance of intraspecific and interspecific interactions. I focused on the use of spatial statistical functions to summarize point patterns to explore and make inferences from spatial data, starting with the construction of a new null model to infer variations about the dispersal syndrome of a parasitic plant in central Spain. Spatial dependence between point patterns in a multivariate point process of affected and unaffected hosts were analyzed and strong dependence was observed at small and medium distance. Two kernel functions were used to simulate the dispersion of parasitic plant and consistency of these models with other syndromes was identified, in addition to ballistic dispersion. A second issue was to analyze altitude and topography effects on the spatial population structure of a dominant shrub in the dry ecosystem in southern Ecuador, whose data come from replicated point patterns design-based. Based on a methodology developed for uni-factorial process, a method for bi-factorial processes was built to assess the interaction effect. The topography alone and interacting with altitude showed significant effect on the spatial pattern of shrub. A third issue was to identify the relationship between the spatial pattern and dispersal syndromes of plant community in the tropical forest of Barro Colorado Island (BCI), Panamá. Several studies have been developed in this tropical forest and some focused on the spatial pattern-syndrome relationship; however the novelty of our study is that a large set of models (114 models) including dispersal limitation and environmental heterogeneity were evaluated, used to identify the only and joint effect to subsequently select the best fit model for each species. Slightly more than fifty percent of the species showed spatial pattern consistent with only the dispersal limitation, and the remaining percentage of species revealed the only effect of environmental heterogeneity and habitat-dispersal limitation joined effect, equitably. Finally, with the same information from the tropical forest of BCI, and to understand the relationships underlying for balance of biodiversity, an index of the local functional dispersion was developed at the individual level, to relate the spatial pattern with four key functional traits of species. Although many studies involve this community with neutral theory, the assembly of the community is affected by similarity and habitat limitations at different scales.

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Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, can be analyzed in detail by using spatial autocorrelation statistics. This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesis tests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

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The molecular clock does not tick at a uniform rate in all taxa but maybe influenced by species characteristics. Eusocial species (those with reproductive division of labor) have been predicted to have faster rates of molecular evolution than their nonsocial relatives because of greatly reduced effective population size; if most individuals in a population are nonreproductive and only one or few queens produce all the offspring, then eusocial animals could have much lower effective population sizes than their solitary relatives, which should increase the rate of substitution of nearly neutral mutations. An earlier study reported faster rates in eusocial honeybees and vespid wasps but failed to correct for phylogenetic nonindependence or to distinguish between potential causes of rate variation. Because sociality has evolved independently in many different lineages, it is possible to conduct a more wide-ranging study to test the generality of the relationship. We have conducted a comparative analysis of 25 phylogenetically independent pairs of social lineages and their nonsocial relatives, including bees, wasps, ants, termites, shrimps, and mole rats, using a range of available DNA sequences (mitochondrial and nuclear DNA coding for proteins and RNAs, and nontranslated sequences). By including a wide range of social taxa, we were able to test whether there is a general influence of sociality on rates of molecular evolution and to test specific predictions of the hypothesis: (1) that social species have faster rates because they have reduced effective population sizes; (2) that mitochondrial genes would show a greater effect of sociality than nuclear genes; and (3) that rates of molecular evolution should be correlated with the degree of sociality. We find no consistent pattern in rates of molecular evolution between social and nonsocial lineages and no evidence that mitochondrial genes show faster rates in social taxa. However, we show that the most highly eusocial Hymenoptera do have faster rates than their nonsocial relatives. We also find that social parasites (that utilize the workers from related species to produce their own offspring) have faster rates than their social relatives, which is consistent with an effect of lower effective population size on rate of molecular evolution. Our results illustrate the importance of allowing for phylogenetic nonindependence when conducting investigations of determinants of variation in rate of molecular evolution.

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Numerous evolutionary studies have sought to explain the distribution of diversity across the limbs of the tree of life. At the same time, ecological studies have sought to explain differences in diversity and relative abundance within and among ecological communities. Traditionally, these patterns have been considered separately, but models that consider processes operating at the level of individuals, such as neutral biodiversity theory (NBT), can provide a link between them. Here, we compare evolutionary dynamics across a suite of NBT models. We show that NBT can yield phylogenetic tree topologies with imbalance closely resembling empirical observations. In general, metacommunities that exhibit greater disparity in abundance are characterized by more imbalanced phylogenetic trees. However, NBT fails to capture the tempo of diversification as represented by the distribution of branching events through time. We suggest that population-level processes might therefore help explain the asymmetry of phylogenetic trees, but that tree shape might mislead estimates of evolutionary rates unless the diversification process is modeled explicitly.

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The presented works aim at proposing a methodology for the simulation of offshore wind conditions using CFD. The main objective is the development of a numerical model for the characterization of atmospheric boundary layers of different stability levels, as the most important issue in offshore wind resource assessment. Based on Monin-Obukhov theory, the steady k-ε Standard turbulence model is modified to take into account thermal stratification in the surface layer. The validity of Monin-Obukhov theory in offshore conditions is discussed with an analysis of a three day episode at FINO-1 platform.