Species abundance distributions result from body size-energetics relationships

Abundance distributions are a central characteristic of ecosystems. Certain distributions have been derived from theoretical models of community organization, and therefore the fit of data to these distributions has been proposed as a test of these theories. However, it is shown here that the geometric sequence distribution can be derived directly from the empirical relationship between population density and body size, with the assumption of random or uniform body size distributions on a log scale (as holds at local scales). The geometric sequence model provides a good to excellent fit to empirical data. The presence of noise in the relationship between population density and body size creates a curve that begins to approximate a lognormal species abundance distribution as the noise term increases. For continental-scale data in which the body size distribution is not flat, the result of sampling tends again toward the lognormal. Repeat sampling over time smooths out species population fluctuations and damps out the noise, giving a more precise geometric sequence abundance distribution. It is argued that the direct derivation of this distribution from empirical relationships gives it priority over distributions derived from complex theoretical community models.     

南亚热带森林3层次物种多度之广义泊松分布模型

生物群落中物种多度分布(species abundance distribution)呈典型的倒J形,即其中存在许多稀有种、少量常见种.物种多度分布模型研究有助于解决森林生态恢复中的物种配置等实际问题.本研究考察了一种过分散(over-dispersion,或称超分布,即方差大于均值)的离散型分布,即具有λ和α两个参数...     

Joint modelling of breeding and survival in the kittiwake using frailty models

Assessment of population dynamics is central to population dynamics and conservation. In structured populations, matrix population models based on demographic data have been widely used to assess such dynamics. Although highlighted in several studies, the influence of heterogeneity among individuals in demographic parameters and of the possible correlation among these parameters has usually been ignored, mostly because of difficulties in estimating such individual-specific parameters. In the kittiwake (Rissa tridactyla), a long-lived seabird species, differences in survival and breeding probabilities among individual birds are well documented. Several approaches have been used in the animal ecology literature to establish the association between survival and breeding rates. However, most are based on observed heterogeneity between groups of individuals, an approach that seldom accounts for individual heterogeneity. Few attempts have been made to build models permitting estimation of the correlation between vital rates. For example, survival and breeding probability of individual birds were jointly modelled using logistic random effects models by [Cam, E., Link, W.A., Cooch, E.G., Monnat, J., Danchin, E., 2002. Individual covariation in life-history traits: seeing the trees despite the forest. Am. Naturalist, 159, in press]. This is the only example in wildlife animal populations we are aware of. Here we adopt the survival analysis approaches from epidemiology. We model the survival and the breeding probability jointly using a normally distributed random effect (frailty). Conditionally on this random effect, the survival time is modelled assuming a lognormal distribution, and breeding is modelled with a logistic model. Since the deaths are observed in year-intervals, we also take into account that the data are interval censored. The joint model is estimated using classic frequentist methods and also MCMC techniques in Winbugs. The association between survival and breeding attempt is quantified using the standard deviation of the random frailty parameters. We apply our joint model on a large data set of 862 birds, that was followed from 1984 to 1995 in Brittany (France). Survival is positively correlated with breeding indicating that birds with greater inclination to breed also had higher survival.     

Supralittoral amphipod abundances across habitats on Mediterranean temperate beaches

Community complexity and abiotic conditions are key components of environmental heterogeneity that affect the abundance and distribution of species. In this study we evaluated how environmental conditions affect abundances of supralittoral amphipods (Talitridae) in four habitats (sandy beach, rivermouth, wrack and lakeshore), along the Italian peninsula in the Mediterranean Sea. All samplings covered a 12 month period, and used the same sampling methodology thereby enabling comparison of abundances and species composition and richness. Four species (Talitrus saltator (Montagu, 1808), Orchestia gammarellus (Pallas, 1766), O. montagui Audouin 1826, O. cf. cavimana Heller 1865) were collected in the different habitats, but most species were found or were abundant in only one of the four habitats. Abundances of talitrids (numbers per sampling hour) differed significantly among the habitats with highest abundances found in the wrack and on the riverbank in proximity to an estuary, and lowest abundances observed on four sandy beach sites. Environmental conditions (temperature, moisture, substrate penetrability) differed among the habitats and were associated with some of the among-site variability in abundances. Our findings demonstrate that talitrids thrive better in some supralittoral habitats than others, and that some habitats could be considered to be “hotspots” of talitrid ecology and biodiversity.     

Integrated modelling of foraging behaviour, energy budget and memory properties

A predator's foraging performance is related to its ability to acquire sufficient information on environmental profitability. This process can be affected by the patchy distribution and clustering of food resources and by the food intake process dynamics.We simulated body mass growth and behaviour in a forager acting in a patchy environment with patchy distribution of both prey abundance and body mass by an individual-based model. In our model, food intake was a discrete and stochastic process and leaving decision was based on the estimate of net energy gain and searching time during their foraging activities. The study aimed to investigate the effects of learning processes and food resource exploitation on body mass and survival of foragers under different scenarios of intra-patch resource distribution.The simulation output showed that different sources of resource variability between patches affected foraging efficiency differently. When prey abundance varied across patches, the predator stayed longer in poorest patches to obtain the information needed and its performance was affected by the cost of sampling and the resulting assessment of the environment proved unreliable. On the other hand, when prey body mass, but not abundance, varied among the patches the predator was quickly able to assess local profitability. Both body mass and survival of the predator were greatly affected by learning processes and patterns of food resource distribution.     

Lifting a veil on diversity: a Bayesian approach to fitting relative-abundance models.

Bayesian methods incorporate prior knowledge into a statistical analysis. This prior knowledge is usually restricted to assumptions regarding the form of probability distributions of the parameters of interest, leaving their values to be determined mainly through the data. Here we show how a Bayesian approach can be applied to the problem of drawing inference regarding species abundance distributions and comparing diversity indices between sites. The classic log series and the lognormal models of relative- abundance distribution are apparently quite different in form. The first is a sampling distribution while the other is a model of abundance of the underlying population. Bayesian methods help unite these two models in a common framework. Markov chain Monte Carlo simulation can be used to fit both distributions as small hierarchical models with shared common assumptions. Sampling error can be assumed to follow a Poisson distribution. Species not found in a sample, but suspected to be present in the region or community of interest, can be given zero abundance. This not only simplifies the process of model fitting, but also provides a convenient way of calculating confidence intervals for diversity indices. The method is especially useful when a comparison of species diversity between sites with different sample sizes is the key motivation behind the research. We illustrate the potential of the approach using data on fruit-feeding butterflies in southern Mexico. We conclude that, once all assumptions have been made transparent, a single data set may provide support for the belief that diversity is negatively affected by anthropogenic forest disturbance. Bayesian methods help to apply theory regarding the distribution of abundance in ecological communities to applied conservation.     

物种多度对数正态分布模型的一种数值计算方法

物种多度分布格局是生物多样性研究的重要内容．本文针对物种多度分布的对数正态模型计算方法的缺陷,首次提出应用遗传算法计算对数正态模型参数,并与前人计算方法进行了比较,证明遗传算法具有较强的数值计算能力,对生态学中诸多非线性曲线的参数估计具有普遍意义．     

Determining patterns of variability in ecological communities: time lag analysis revisited

All ecological communities experience change over time. One method to quantify temporal variation in the patterns of relative abundance of communities is time lag analysis (TLA). It uses a distance-based approach to study temporal community dynamics by regressing community dissimilarity over increasing time lags (one-unit lags, two-unit lags, three-unit lags). Here, we suggest some modifications to the method and revaluate its potential for detecting patterns of community change. We apply Hellinger distance based TLA to artificial data simulating communities with different levels of directional and stochastic dynamics and analyse their effects on the slope and its statistical significance. We conclude that statistical significance of the TLA slope (obtained by a Monte Carlo permutation procedure) is a valid criterion to discriminate between (i) communities with directional change in species composition, regardless whether it is caused by directional abundance change of the species or by stochastic change according to a Markov process, and (ii) communities that are composed of species with population sizes oscillating around a constant mean or communities whose species abundances are governed by a white noise process. TLA slopes range between 0.02 and 0.25, depending on the proportions of species with different dynamics; higher proportions of species with constant means imply shallower slopes; and higher proportions of species with stochastic dynamics or directional change imply steeper slopes. These values are broadly in line with TLA slopes from real world data. Caution must be exercised when TLA is used for the comparison of community time series with different lengths since the slope depends on time series length and tends to decrease non-linearly with it.     

Composite forces shape population dynamics of copepod crustaceans

Understanding the processes that control species abundance and distribution is a major challenge in ecology, yet for a large number of potentially important organisms, we know little about the biotic and abiotic factors that influence population size. One group of aquatic organisms that defies traditional demographic analyses is the Crustacea, particularly those with complex life cycles. We used likelihood techniques and information theoretics to evaluate a suite of models representing alternative hypotheses on factors controlling the abundance of two copepod crustaceans in a small, tropical floodplain lake. Quantitative zooplankton samples were collected at three stations in a Venezuelan floodplain lake from June through December 1984; the average sampling interval was two days. We constructed a series of models with stage structure that incorporated six biotic and abiotic covariates in various combinations to account for temporal changes in abundance of these target species and in their population growth rates. Our analysis produced several novel insights into copepod population dynamics. We found that multiple forces affected the abundance of particular stages, that these factors differed between species as well as among stages within each species, and that biotic processes had the largest effects on copepod population dynamics. Density dependence had a large effect on the survival of Oithona amazonica copepodites and on population growth rate of Diaptomus negrensis.     

Efficiency of composite sampling for estimating a lognormal distribution

In many environmental studies measuring the amount of a contaminant in a sampling unit is expensive. In such cases, composite sampling is often used to reduce data collection cost. However, composite sampling is known to be beneficial for estimating the mean of a population, but not necessarily for estimating the variance or other parameters. As some applications, for example, Monte Carlo risk assessment, require an estimate of the entire distribution, and as the lognormal model is commonly used in environmental risk assessment, in this paper we investigate efficiency of composite sampling for estimating a lognormal distribution. In particular, we examine the magnitude of savings in the number of measurements over simple random sampling, and the nature of its dependence on composite size and the parameters of the distribution utilizing simulation and asymptotic calculations.     

Estimating trend precision and power to detect trends across grouped count data

Ecologists commonly use grouped or clustered count data to estimate temporal trends in counts, abundance indices, or abundance. For example, the U.S. Breeding Bird Survey data represent multiple counts of birds from within each of multiple, spatially defined routes. Despite a reliance on grouped counts, analytical methods for prospectively estimating precision of trend estimates or statistical power to detect trends that explicitly acknowledge the characteristics of grouped count data are undescribed. These characteristics include the fact that the sampling variance is an increasing function of the mean, and that sampling and group-level variance estimates are generally estimated on different scales (the sampling and log scales, respectively). We address these issues for repeated sampling of a single population using an analytical approach that has the flavor of a generalized linear mixed model, specifically that of a negative binomial-distributed count variable with random group effects. The count mean, including grand intercept, trend, and random group effects, is modeled linearly on the log scale, while sampling variance of the mean is estimated on the log scale via the delta method. Results compared favorably with those derived using Monte Carlo simulations. For example, at trend = 5% per temporal unit, differences in standard errors and in power were modest relative to those estimated by simulation (< or = /11/% and < or = /16/%, respectively), with relative differences among power estimates decreasing to < or = /7/% when power estimated by simulations was > or = 0.50. Similar findings were obtained using data from nine surveys of fingernail clams in the Mississippi River. The proposed method is suggested (1) where simulations are not practical and relative precision or power is desired, or (2) when multiple precision or power calculations are required and where the accuracy of a fraction of those calculations will be confirmed using simulations.     

A Bayesian state-space formulation of dynamic occupancy models

Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by non-detection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and WinBUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site-specific heterogeneity in model parameters. The results indicate relatively low turnover and a stable distribution of Cerulean Warblers which is in contrast to analyses of counts of individuals from the same survey that indicate important declines. This discrepancy illustrates the inertia in occupancy relative to actual abundance. Furthermore, the model reveals a declining patch survival probability, and increasing turnover, toward the edge of the range of the species, which is consistent with metapopulation perspectives on the genesis of range edges. Given detection/non-detection data, dynamic occupancy models as described here have considerable potential for the study of distributions and range dynamics.     

Spatial heterogeneity in distribution and ecology of Western Palearctic birds

Species vary in abundance and heterogeneity of spatial distribution, and the ecological and evolutionary consequences of such variability are poorly known. Evolutionary adaptation to heterogeneously distributed resources may arise from local adaptation with individuals of such locally adapted populations rarely dispersing long distances and hence having small populations and small overall ranges. We quantified mean population density and spatial heterogeneity in population density of 197 bird species across 12 similarly sized regions in the Western Palearctic. Variance in population density among regions differed significantly from a Poisson distribution, suggesting that random processes cannot explain the observed patterns. National estimates of means and variances in population density were positively correlated with continental estimates, suggesting that means and variances were maintained across spatial scales. We used Morisita's index of population abundance as an estimate of heterogeneity in distribution among regions to test a number of predictions. Heterogeneously distributed passerine bird species as reflected by Morisita's index had small populations, low population densities, and small breeding ranges. Their breeding populations had been consistently maintained at low levels for considerable periods of time, because the degree of genetic variation in a subsample of non-passerines and passerines was significantly negatively related to heterogeneity in distribution. Heterogeneously distributed passerine species were not more often habitat specialists than homogeneously distributed species. Furthermore, heterogeneously distributed passerine species had high annual adult survival rates but did not differ in annual fecundity from homogeneously distributed species. Heterogeneously distributed passerine species rarely colonized urban habitats. Finally, homogeneously distributed bird species were hosts to a greater diversity of blood parasite species than heterogeneously distributed species. In conclusion, small breeding ranges, population sizes, and population densities of heterogeneously distributed passerine bird species, combined with their low degree of genetic variability, and their inability to colonize urban areas may render such species particularly susceptible to human-influenced global climatic changes.     

Enchytraeid population dynamics: Resource limitation and size-dependent mortality

Enchytraeids are regarded as keystone soil organisms in forest ecosystems. Their abundance and biomass fluctuate widely. Predicting the consequences of anthropogenic disturbances requires an understanding of the mechanisms underlying enchytraeid population dynamics. Here I develop a simple model, which predicts that the type of dynamics is controlled by resource input rate. If fungal resource input is a discrete event once a year, an exponential growth phase is followed by starvation and sharp decline of enchytraeid abundance. Model simulations with three different forcing functions were compared to field data. Initial parameter values were obtained from various independent sources, and parameters were estimated by minimizing the residual sum of squares. The best fitting model with resource addition once a year explained 39% of the variation in enchytraeid biomass over an 8-year study period. Further, variation in rainfall explained 59% of the variation in R² of the exponential phase models, which is also an index of the stability of population size-structure. The results emphasize the importance of resource limitation for enchytraeid population dynamics and support the hypothesis that the mortality during the decline phase is size-dependent.     

Determinants of reproductive success of the White-browed Sparrow Weaver,Plocepasser mahali

Summary Variation in reproductive success among 26 communal groups in a sampled population of Plocepasser mahali (White-browed Sparrow Weaver) was studied over a 3-year period in Zambia, Africa. Potential determinants of reproductive success, namely resource variables and group size, were examined and statistically analyzed for their significance in explaining annual variance in reproductive success among these groups. Resource variables included abundance of grass seeds (dry season food) and grasshoppers (wet season food), nest tree quality, and percentage availability of preferred feeding cover. Only the latter two proved appropriate for this analysis. Patterns of utilization did not correlate positively with food abundance, and grasshopper abundance fluctuated too much among the groups in a given year to be treated as a stable variable.From an analysis of multiple correlation coefficients in a stepwise multiple regression model, both group size and ground cover explained independently of each other 20%–30% of the variance in annual production of young surviving 6 months. Explained variance by these two variables also revealed that their relative importance varied considerably between years. Hypotheses are offered to explain the possible causal mechanisms these variables may have in influencing intergroup reproductive success and the possible reasons why vagaries in explained variance were observed. It is suggested that effects of group size and habitat quality may be more important than age-specific effects in modeling population growth and regulation for species like P. mahali.     

Do plant–pollinator interaction networks result from stochastic processes?

Plant–pollinator interaction networks are characterized by several features that cannot be obtained from a totally random network (e.g. nestedness, power law distribution of degree specialization, temporal turnover). One reason is that both plants and pollinators are active for only a part of the year, and so a plant species flowering in spring cannot interact with a pollinator species that is active only in autumn. In this paper we build a stochastic model to simulate the plant–pollinator interaction network, taking into account the duration of activity of each species. To build the model we used an empirical plant–pollinator network from a Mediterranean scrub community surveyed over four years. In our simulated annual cycle we know which plant and pollinator species are active, and thus available to interact. We can obtain simulated plant–pollinator interaction networks with properties similar to the real ones in two different ways: (i) by assuming that the frequency distribution of both plant and pollinator duration of activity follow an exponential function, and that interaction among temporally coexisting species are totally random, and (ii) by assuming more realistic frequency distributions (exponential for pollinators, lognormal for plants) and that the interaction among coexisting species is occurring on a per capita basis. In the latter case we assume that there is a positive relationship between abundance and duration of activity. In our model the starting date of the species activity had little influence on the network structure. We conclude that the observed plant–pollinator network properties can be produced stochastically, and the mechanism shaping the network is not necessarily related to size constraints. Under such conditions co-evolutionary explanations should be given with caution.     

Effect of Small‐Scale Heterogeneity of Prey and Hunter Distributions on the Sustainability of Bushmeat Hunting

Abstract: Bushmeat is the main source of protein and the most important source of income for rural people in the Congo Basin, but intensive hunting of bushmeat species is also a major concern for conservationists. Although spatial heterogeneity in hunting effort and in prey populations at the landscape level plays a key role in the sustainability of hunted populations, the role of small‐scale heterogeneity within a village hunting territory in the sustainability of hunting has remained understudied. We built a spatially explicit multiagent model to capture the dynamics of a system in which hunters and preys interact within a village hunting territory. We examined the case of hunting of bay duikers (Cephalophus dorsalis) in the village of Ntsiété, northeastern Gabon. The impact of hunting on prey populations depended on the spatial heterogeneity of hunting and prey distribution at small scales within a hunting area. Within a village territory, the existence of areas hunted throughout the year, areas hunted only during certain seasons, and unhunted areas contributed to the sustainability of the system. Prey abundance and offtake per hunter were particularly sensitive to the frequency and length of hunting sessions and to the number of hunters sharing an area. Some biological parameters of the prey species, such as dispersal rate and territory size, determined their spatial distribution in a hunting area, which in turn influenced the sustainability of hunting. Detailed knowledge of species ecology and behavior, and of hunting practices are crucial to understanding the distribution of potential sinks and sources in space and time. Given the recognized failure of simple biological models to assess maximum sustainable yields, multiagent models provide an innovative path toward new approaches for the assessment of hunting sustainability, provided further research is conducted to increase knowledge of prey species’ and hunter behavior.     

Density dependence vs. independence, and irregular population dynamics of a swallow-wort fruit fly

Although most long-term studies of consumer-resource (e.g., predator-prey) interactions select species showing cyclic population dynamics, strong consumer-resource interactions can also produce irregular, noncyclic dynamics. Here, we present a case in which a seed predator, the tephritid fruit fly Euphranta connexa, shows fluctuations in density of more than two orders of magnitude over a 22-year period. To explain these fluctuations, we analyzed a stage-specific data set to quantify the density-dependent and density-independent components of larval survivorship and realized fecundity. Both larval survivorship and realized fecundity were strongly density dependent. Larval survivorship dropped from 0.62 at low larval density to 0.081 at high larval density, whereas fecundity dropped from 84.3 to 0.32 eggs per individual, more than a 100-fold decrease. We divided density-independent variation in E. connexa population dynamics into components for variability in (1) larval survivorship, (2) realized fecundity, and (3) annual fruit abundance. Of these components, 96% of the density-independent variance in per capita population growth rates was caused by fluctuations in fruit abundance. This highlights the importance of the strong consumer-resource interactions in driving fluctuations in E. connexa abundance. It also demonstrates that E. connexa dynamics are remarkably simple, and aside from the 4% of unexplained variance in per capita population growth rates, our understanding of E. connexa dynamics is remarkably complete.     

Modelling the horizontal spatial structure of planktonic community in Lake Trasimeno (Umbria,Italy) using multivariate geostatistical methods

Spatial heterogeneity of ecological systems has been recognised in recent years as an important ecological feature of an ecosystem, rather than a mere statistical nuisance. However, although considerable interest has been paid to the development of statistical methods for the analysis of spatial environmental data, when in presence of more species or environmental variables common analyses still fail to recognise the necessity of a joint modelling of the whole correlation structure. In this paper, we propose to study the multivariate spatial autocorrelation of a plankton community by making explicit reference to a spatial linear factor model entailing a set of constraints for the spatial structure of the planktonic species. The data set examined come from an intensive 2-day sampling survey performed in July 1991 on Lake Trasimeno (Italy) to investigate the horizontal spatial heterogeneity and distribution of the planktonic community, from small (50 m) to large (1000–10,000 m) scale. The analysis revealed that zooplankton and phytoplankton essentially have different degrees of heterogeneity and different spatial structures which required separate modelling. On the other hand, the similarity of the spatial autocorrelation found within zooplankton and phytoplankton communities, indicates that at the investigated scales of observation the horizontal organisation of both components is not appreciably affected by species-specific behaviours. The analysis of the multivariate spatial patterns emerging from the mapping of the extracted factors suggested an interpretation of the distribution of macrozooplankton and phytoplankton assemblages in terms of planktonic responses to environmental factors of a lake-size scale.     

Differential use of shelter holes by sympatric species of blennies (Blennidae)

Comparative use of shelter use by three sympatric species of combtooth blenny (Ecsenius stictus, Glyptoparus delicatulus, and Salarias patzneri) was studied among micro-atolls in the lagoon at Lizard Island (14°42′S, 145°30′E), northern Great Barrier Reef, Australia. Blenny species used different sized holes; however, the average diameter and depth of holes used by the smallest and largest species differed by only 4 and 25 mm, respectively, indicating interspecific differences in suitable refuge can be very subtle. Both hole diameter and depth were positively related to total length of fish, suggesting use of holes relates to interspecific differences in body size. Total abundance of blennies was best explained by a general linear model that included either the number of holes or total habitat area on individual micro-atolls, predictor variables that were positively correlated with each other. However, the relative importance of variables differed among the three species, feeding area being most important for S. patzneri, feeding area and number of holes for E. stictus, and variance in hole diameter being the best explanatory variable for G. delicatulus abundance. The number of blenny species on a micro-atoll was best explained by variance in hole diameter, emphasizing the influence of refuge size variety in fish diversity. It is likely that subtle habitat partitioning, which relates to interspecific differences in body size, contributes to the co-existence of blenny species within the same microhabitat, but presence of holes is unlikely to regulate abundance of these fish.