Distance decay of similarity,effects of environmental noise and ecological heterogeneity among species in the spatio‐temporal dynamics of a dispersal‐limited community

The joint spatial and temporal fluctuations in community structure may be due to dispersal, variation in environmental conditions, ecological heterogeneity among species and demographic stochasticity. These factors are not mutually exclusive, and their relative contribution towards shaping species abundance distributions and in causing species fluctuations have been hard to disentangle. To better understand community dynamics when the exchange of individuals between localities is very low, we studied the dynamics of the freshwater zooplankton communities in 17 lakes located in independent catchment areas, sampled at end of summer from 2002 to 2008 in Norway. We analysed the joint spatial and temporal fluctuations in the community structure by fitting the two‐dimensional Poisson lognormal model under a two‐stage sampling scheme. We partitioned the variance of the distribution of log abundance for a random species at a random time and location into components of demographic stochasticity, ecological heterogeneity among species, and independent environmental noise components for the different species. Non‐neutral mechanisms such as ecological heterogeneity among species (20%) and spatiotemporal variation in the environment (75%) explained the majority of the variance in log abundances. Overdispersion relative to Poisson sampling and demographic stochasticity had a small contribution to the variance (5%). Among a set of environmental variables, lake acidity was the environmental variable that was most strongly related to decay of community similarity in space and time.     

Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework

Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws – every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the study of SADs. Several key points emerge. (i) Literally dozens of models have been proposed to explain the hollow curve. Unfortunately, very few models are ever rejected, primarily because few theories make any predictions beyond the hollow-curve SAD itself. (ii) Interesting work has been performed both empirically and theoretically, which goes beyond the hollow-curve prediction to provide a rich variety of information about how SADs behave. These include the study of SADs along environmental gradients and theories that integrate SADs with other biodiversity patterns. Central to this body of work is an effort to move beyond treating the SAD in isolation and to integrate the SAD into its ecological context to enable making many predictions. (iii) Moving forward will entail understanding how sampling and scale affect SADs and developing statistical tools for describing and comparing SADs. We are optimistic that SADs can provide significant insights into basic and applied ecological science.     

A comparative analysis of alternative approaches to fitting species-abundance models

Aims Fits of species-abundance distributions to empirical data are increasingly used to evaluate models of diversity maintenance and community structure and to infer properties of communities, such as species richness. Two distributions predicted by several models are the Poisson lognormal (PLN) and the negative binomial (NB) distribution; however, at least three different ways to parameterize the PLN have been proposed, which differ in whether unobserved species contribute to the likelihood and in whether the likelihood is conditional upon the total number of individuals in the sample. Each of these has an analogue for the NB. Here, we propose a new formulation of the PLN and NB that includes the number of unobserved species as one of the estimated parameters. We investigate the performance of parameter estimates obtained from this reformulation, as well as the existing alternatives, for drawing inferences about the shape of species abundance distributions and estimation of species richness.Methods We simulate the random sampling of a fixed number of individuals from lognormal and gamma community relative abundance distributions, using a previously developed 'individual-based' bootstrap algorithm. We use a range of sample sizes, community species richness levels and shape parameters for the species abundance distributions that span much of the realistic range for empirical data, generating 1?000 simulated data sets for each parameter combination. We then fit each of the alternative likelihoods to each of the simulated data sets, and we assess the bias, sampling variance and estimation error for each method.Important findings Parameter estimates behave reasonably well for most parameter values, exhibiting modest levels of median error. However, for the NB, median error becomes extremely large as the NB approaches either of two limiting cases. For both the NB and PLN,>90% of the variation in the error in model parameters across parameter sets is explained by three quantities that corresponded to the proportion of species not observed in the sample, the expected number of species observed in the sample and the discrepancy between the true NB or PLN distribution and a Poisson distribution with the same mean. There are relatively few systematic differences between the four alternative likelihoods. In particular, failing to condition the likelihood on the total sample sizes does not appear to systematically increase the bias in parameter estimates. Indeed, overall, the classical likelihood performs slightly better than the alternatives. However, our reparameterized likelihood, for which species richness is a fitted parameter, has important advantages over existing approaches for estimating species richness from fitted species-abundance models.     

Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.     

Sampling species abundance distributions: resolving the veil-line debate

Preston's classic work on the theory of species abundance distributions (SADs) in ecology has been challenged by Dewdney. Dewdney contends that Preston's veil-line concept, relating to the shape of sample SADs, is flawed. Here, I show that Preston's and Dewdney's theories can be reconciled by considering the differing mathematical properties of the sampling process on logarithmic (Preston) versus linear (Dewdney) abundance scales. I also derive several related results and show, importantly, that one cannot reject the log-normal distribution as a plausible SAD based only on sampling arguments, as Dewdney and others have done.     

A unified model explains commonness and rarity on coral reefs

Abundance patterns in ecological communities have important implications for biodiversity maintenance and ecosystem functioning. However, ecological theory has been largely unsuccessful at capturing multiple macroecological abundance patterns simultaneously. Here, we propose a parsimonious model that unifies widespread ecological relationships involving local aggregation, species‐abundance distributions, and species associations, and we test this model against the metacommunity structure of reef‐building corals and coral reef fishes across the western and central Pacific. For both corals and fishes, the unified model simultaneously captures extremely well local species‐abundance distributions, interspecific variation in the strength of spatial aggregation, patterns of community similarity, species accumulation, and regional species richness, performing far better than alternative models also examined here and in previous work on coral reefs. Our approach contributes to the development of synthetic theory for large‐scale patterns of community structure in nature, and to addressing ongoing challenges in biodiversity conservation at macroecological scales.     

Occupancy frequency distributions: patterns,artefacts and mechanisms

Numerous hypotheses have been proposed to explain the shape of occupancy frequency distributions (distributions of the numbers of species occupying different numbers of areas). Artefactual effects include sampling characteristics, whereas biological mechanisms include organismal, niche-based and meta-population models. To date, there has been little testing of these models. In addition, although empirically derived occupancy distributions encompass an array of taxa and spatial scales, comparisons between them are often not possible because of differences in sampling protocol and method of construction. In this paper, the effects of sampling protocol (grain, sample number, extent, sampling coverage and intensity) on the shape of occupancy distributions are examined, and approaches for minimising artefactual effects recommended. Evidence for proposed biological determinants of the shape of occupancy distributions is then examined. Good support exists for some mechanisms (habitat and environmental heterogeneity), little for others (dispersal ability), while some hypotheses remain untested (landscape productivity, position in geographic range, range size frequency distributions), or are unlikely to be useful explanations for the shape of occupancy distributions 'species specificity and adaptation to habitat, extinction-colonization dynamics). The presence of a core (class containing species with the highest occupancy) mode in occupancy distributions is most likely to be associated with larger sample units, and small homogenous sampling areas positioned well within and towards the range centers of a sufficient proportion of the species in the assemblage. Satellite (class with species with the lowest occupancy) modes are associated with sampling large, heterogeneous areas that incorporate a large proportion of the assemblage range. However, satellite modes commonly also occur in the presence of a core mode, and rare species effects are likely to contribute to the presence of a satellite mode at most sampling scales. In most proposed hypotheses, spatial scale is an important determinant of the shape of the observed occupancy distribution. Because the attributes of the mechanisms associated with these hypotheses change with spatial scale, their predictions for the shape of occupancy distributions also change. To understand occupancy distributions and the mechanisms underlying them, a synthesis of pattern documentation and model testing across scales is thus needed. The development of null models, comparisons of occupancy distributions across spatial scales and taxa, documentation of the movement of individual species between occupancy classes with changes in spatial scale, as well as further testing of biological mechanisms are all necessary for an improved understanding of the distribution of species and assemblages within their geographic ranges.     

Analytical evidence for scale-invariance in the shape of species abundance distributions

The distribution of species abundances within an ecological community provides a window into ecological processes and has important applications in conservation biology as an indicator of disturbance. Previous work indicates that species abundance distributions might be independent of the scales at which they are measured which has implications for data interpretation. Here we formulate an analytically tractable model for the species abundance distribution at different scales and discuss the biological relevance of its assumptions. Our model shows that as scale increases, the shape of the species abundance distribution converges to a particular shape given uniquely by the Jaccard index of spatial species turnover and by a parameter for the spatial correlation of abundances. Our model indicates that the shape of the species abundance distribution is taxon specific but does not depend on sample area, provided this area is large. We conclude that the species abundance distribution may indeed serve as an indicator of disturbances affecting species spatial turnover and that the assumption of conservation of energy in ecosystems, which is part of the Maximum Entropy approach, should be re-evaluated.     

Two-phase species–time relationships in North American land birds

The species–time relationship (STR) is a macroecological pattern describing the increase in the observed species richness with the length of time censused. Understanding STRs is important for understanding the ecological processes underlying temporal turnover and species richness. However, accurate characterization of the STR has been hampered by the influence of sampling. I analysed STRs for 521 breeding bird survey communities. I used a model of sampling effects to demonstrate that the increase in richness was not due exclusively to sampling. I estimated the time scale at which ecological processes became dominant over sampling effects using a two‐phase model combining a sampling phase and either a power function or logarithmic ecological phase. These two‐phase models performed significantly better than sampling alone and better than simple power and logarithmic functions. Most community dynamics were dominated by ecological processes over scales <5 years. This technique provides an example of a rigorous, quantitative approach to separating sampling from ecological processes.     

Is genomic diversity a useful proxy for census population size? Evidence from a species‐rich community of desert lizards

Species abundance data are critical for testing ecological theory, but obtaining accurate empirical estimates for many taxa is challenging. Proxies for species abundance can help researchers circumvent time and cost constraints that are prohibitive for long‐term sampling. Under simple demographic models, genetic diversity is expected to correlate with census size, such that genome‐wide heterozygosity may provide a surrogate measure of species abundance. We tested whether nucleotide diversity is correlated with long‐term estimates of abundance, occupancy and degree of ecological specialization in a diverse lizard community from arid Australia. Using targeted sequence capture, we obtained estimates of genomic diversity from 30 species of lizards, recovering an average of 5,066 loci covering 3.6 Mb of DNA sequence per individual. We compared measures of individual heterozygosity to a metric of habitat specialization to investigate whether ecological preference exerts a measurable effect on genetic diversity. We find that heterozygosity is significantly correlated with species abundance and occupancy, but not habitat specialization. Demonstrating the power of genomic sampling, the correlation between heterozygosity and abundance/occupancy emerged from considering just one or two individuals per species. However, genetic diversity does no better at predicting abundance than a single day of traditional sampling in this community. We conclude that genetic diversity is a useful proxy for regional‐scale species abundance and occupancy, but a large amount of unexplained variation in heterozygosity suggests additional constraints or a failure of ecological sampling to adequately capture variation in true population size.     

Spatial scaling of species abundance distributions

Species abundance distributions are an essential tool in describing the biodiversity of ecological communities. We now know that their shape changes as a function of the size of area sampled. Here we analyze the scaling properties of species abundance distributions by using the moments of the logarithmically transformed number of individuals. We find that the moments as a function of area size are well fitted by power laws and we use this pattern to estimate the species abundance distribution for areas larger than those sampled. To reconstruct the species abundance distribution from its moments, we use discrete Tchebichef polynomials. We exemplify the method with data on tree and shrub species from a 50 ha plot of tropical rain forest on Barro Colorado Island, Panama. We test the method within the 50 ha plot, and then we extrapolate the species abundance distribution for areas up to 5 km². Our results project that for areas above 50 ha the species abundance distributions have a bimodal shape with a local maximum occurring for the singleton classes and that this maximum increases with sampled area size.     

The shape of abundance distributions across temperature gradients in reef fishes

Improving predictions of ecological responses to climate change requires understanding how local abundance relates to temperature gradients, yet many factors influence local abundance in wild populations. We evaluated the shape of thermal‐abundance distributions using 98 422 abundance estimates of 702 reef fish species worldwide. We found that curved ceilings in local abundance related to sea temperatures for most species, where local abundance declined from realised thermal ‘optima’ towards warmer and cooler environments. Although generally supporting the abundant‐centre hypothesis, many species also displayed asymmetrical thermal‐abundance distributions. For many tropical species, abundances did not decline at warm distribution edges due to an unavailability of warmer environments at the equator. Habitat transitions from coral to macroalgal dominance in subtropical zones also influenced abundance distribution shapes. By quantifying the factors constraining species’ abundance, we provide an important empirical basis for improving predictions of community re‐structuring in a warmer world.     

Climate change likely to reduce orchid bee abundance even in climatic suitable sites

Studies have tested whether model predictions based on species’ occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence–absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence–absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability–abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest.     

Complex patterns of temperature sensitivity,not ecological traits,dictate diverse species responses to climate change

Despite widespread interest in describing and forecasting the impacts of climate change on species distributions, poor understanding of the climate variables that shape distributions and conflicting perspectives on the role that species traits play in mediating shifts have limited our ability to interpret and project changes in species distributions. Using standardized survey data along the northeast US continental shelf, we assessed the historical exposure and sensitivity of 81 species of marine chordates, arthropods, and molluscs to 24 sea surface temperature (SST) variables in two seasons. By comparing temperature trends in geographies available to species against temperature trends in geographies used by them we were able to identify which variables species track consistently through space and time. Logistic regression analyses were then used to assess whether species traits affected the likelihood of niche tracking while accounting for the season and temporal window in which temperatures were summarized and methodological constraints that might have limited our ability to detect tracking responses. A slight majority of species (52%) clearly shifted their distributions to track at least one temperature variable through space and time. Tracking rates were much lower on a per variable basis (5.1% of 3432 variables), despite widespread exposure to changing temperatures (89.2% of 3432 variables). None of the twelve ecological traits we investigated – including traits related to dispersal ability, ecological specialization, reproductive capacity, and commercial harvest – accounted for differences in tracking responses across species even after accounting for differences in climate exposure. Our results suggest widespread behavioral or physiological flexibility among our study species, or ongoing genetic adaptation to changing temperatures. They also suggest that divergent selection on climate sensitivities of close relatives may limit the utility of ecological traits for predicting distributional responses to future climate change.     

The implicit assumption of symmetry and the species abundance distribution

Species abundance distributions (SADs) have played a historical role in the development of community ecology. They summarize information about the number and the relative abundance of the species encountered in a sample from a given community. For years ecologists have developed theory to characterize species abundance patterns, and the study of these patterns has received special attention in recent years. In particular, ecologists have developed statistical sampling theories to predict the SAD expected in a sample taken from a region. Here, we emphasize an important limitation of all current sampling theories: they ignore species identity. We present an alternative formulation of statistical sampling theory that incorporates species asymmetries in sampling and dynamics, and relate, in a general way, the community-level SAD to the distribution of population abundances of the species integrating the community. We illustrate the theory on a stochastic community model that can accommodate species asymmetry. Finally, we discuss the potentially important role of species asymmetries in shaping recently observed multi-humped SADs and in comparisons of the relative success of niche and neutral theories at predicting SADs.     

Diversity Over Time

Temporal turnover is a fundamental feature of ecological communities. Darwin 1859 noted the ecological and evolutionary significance of turnover, Fisher and Preston acknowledged its role in their models of species abundance, while this ongoing and entirely natural rearrangement of species underpins key ecological concepts such as MacArthur and Wilson’s theory of island biogeography. However, the current focus on spatial patterns of diversity means that temporal changes are often overlooked. Here I argue that failure to take heed of the time frame over which data are collected can lead to both artefacts and artifictions. There are also deeper issues, such as the consequences for species richness estimation and rarefaction methods of a constantly changing community. Moreover, some of the confusion surrounding species abundance distributions may be resolved by taking account of time. A better appreciation of temporal turnover is essential for accurate diversity measurement and assessment, and, more importantly, will also lead to improved understanding of the processes that underpin community structure.     

生物多样性与生态系统功能:最新的进展与动向

生物多样性与生态系统功能的关系及其内在机制是当前生态学领域的重大科学问题。 2 0 0 2年以来人们不再过多地纠缠于“抽样 -互补之争” ,对这一世纪课题的认识又有了新的进展。 (1)人们开始运用已有的知识揭示更大时间和空间尺度上的物种多样性 -生态系统功能关系。多样性作用机制可能存在着动态变化———“抽样向互补转型” :群落建立初期 ,抽样效应是主要的多样性作用机制 ;随时间推移 ,生态位互补成为主要机制。理论研究则预测 :局域尺度上生态系统功能与物种多样性呈现单峰曲线关系 ,在区域尺度上为单调上升关系 ;(2 )非生物因素与多样性 -生产力的交互关系吸引了许多实验研究。人们发现 :物种多样性 -生产力关系可能会受到资源供给率和环境扰动的修正 ,环境因素可能是多样性 -生产力关系的幕后操纵者 ;(3)人们开始重视营养级相互作用对于多样性 -生态系统功能关系的影响 ,生态位互补和抽样假说开始被扩展运用到消费者营养级上 ;(4 )人们开始认真思考物种共存机制在多样性 -生态系统功能关系的形成中所扮演的角色。理论模型研究表明 ,不同的物种共存机制会导致不同的多样性 -生产力关系     

Little evidence for climate effects on local-scale structure and dynamics of California kelp forest communities

Climatic variables such as temperature and precipitation play an important role in controlling local and regional scale differences in population dynamics and species distributions, and large-scale climatic events such as El Niño southern oscillation (ENSO) have been shown to affect population dynamics of key species in many ecosystems, particularly in kelp forests. Few studies have been able to evaluate the consequences of climate variables on the structure and dynamics of biological communities, in large part because the lack of data at appropriate spatial and temporal scales has made it difficult to adequately address local-scale responses of species and communities to such events over relevant time scales. Here, we combined an unprecedented dataset of kelp forest species' abundances from the Channel Islands, California with data for several local, regional, and global scale climatic variables to evaluate the temporal and spatial scale at which one can detect community-wide effects of climate variables, in particular ENSO events. We found large and significant local-scale differences in community structure, but these differences were not related to differences in climatic variables. Moreover, giant kelp abundance, which has been shown to be highly sensitive to water temperature and storm disturbance, was a poor predictor of community differences, and all communities tended to decline in abundance over the 20-year sampling period, suggesting a press perturbation to the system such as PDO cycles or sustained fishing pressure. Although ENSO events can have dramatic impacts on the abundance and distribution of giant kelp itself across the range of the species, such events appear to have little effect on local-scale kelp forest community structure or dynamics.     

A statistical theory for sampling species abundances

The pattern of species abundances is central to ecology. But direct measurements of species abundances at ecologically relevant scales are typically unfeasible. This limitation has motivated a long-standing interest in the relationship between the abundance distribution in a large, regional community and the distribution observed in a small sample from the community. Here, we develop a statistical sampling theory to describe how observed patterns of species abundances are influenced by the spatial distributions of populations. For a wide range of regional-scale abundance distributions we derive exact expressions for the sampled abundance distributions, as a function of sample size and the degree of conspecific spatial aggregation. We show that if populations are randomly distributed in space then the sampled and regional-scale species-abundance distribution typically have the same functional form: sampling can be expressed by a simple scaling relationship. In the case of aggregated spatial distributions, however, the shape of a sampled species-abundance distribution diverges from the regional-scale distribution. Conspecific aggregation results in sampled distributions that are skewed towards both rare and common species. We discuss our findings in light of recent results from neutral community theory, and in the context of estimating biodiversity.     

Temporal dynamics influenced by global change: bee community phenology in urban,agricultural, and natural landscapes

Urbanization and agricultural intensification of landscapes are important drivers of global change, which in turn have direct impacts on local ecological communities leading to shifts in species distributions and interactions. Here, we illustrate how human‐altered landscapes, with novel ornamental and crop plant communities, result not only in changes to local community diversity of floral‐dependent species, but also in shifts in seasonal abundance of bee pollinators. Three years of data on the spatio‐temporal distributions of 91 bee species show that seasonal patterns of abundance and species richness in human‐altered landscapes varied significantly less compared to natural habitats in which floral resources are relatively scarce in the dry summer months. These findings demonstrate that anthropogenic environmental changes in urban and agricultural systems, here mediated through changes in plant resources and water inputs, can alter the temporal dynamics of pollinators that depend on them. Changes in phenology of interactions can be an important, though frequently overlooked, mechanism of global change.