Limiting similarity and functional diversity along environmental gradients

Recent developments in community models emphasize the importance of incorporating stochastic processes (e.g. ecological drift) in models of niche‐structured community assembly. We constructed a finite, spatially explicit, lottery model to simulate the distribution of species in a one‐dimensional landscape with an underlying gradient in environmental conditions. Our framework combines the potential for ecological drift with environmentally‐mediated competition for space in a heterogeneous environment. We examined the influence of niche breadth, dispersal distances, community size (total number of individuals) and the breadth of the environmental gradient on levels of species and functional trait diversity (i.e. differences in niche optima). Three novel results emerge from this model: (1) niche differences between adjacent species (e.g. limiting similarity) increase in smaller communities, because of the interaction of competitive effects and finite population sizes; (2) immigration from a regional species pool, stochasticity and niche‐assembly generate a bimodal distribution of species residence times (‘transient’ and ‘resident’) under a heterogeneous environment; and (3) the magnitude of environmental heterogeneity has a U‐shaped effect on diversity, because of shifts in species richness of resident vs. transient species. These predictions illustrate the potential importance of stochastic (although not necessarily neutral) processes in community assembly.     

Integrating the niche and neutral perspectives on community structure and dynamics

Elucidating the mechanisms underlying the assembly and dynamics of ecological communities is a fundamental goal of ecology. Two conceptual approaches have emerged in this respect: the niche-assembly view and the neutral perspective. The debate as to which approach best explains the biodiversity patterns observed in nature is becoming outdated, as ecologists increasingly agree on the existence of a niche-neutral continuum of community dynamical behaviors. However, attempts to make the continuum idea operational and measurable remain sparse. Here, we propose a model-based approach to achieving this. The proposed methodology consists of separating out fluctuations in species abundances into niche-mediated and stochastic factors, linking the niche configuration to community dynamics through competition, and adding demographic stochasticity. This results in a comprehensive framework including neutrality and strict niche segregation as extreme cases. We develop an index of departure from neutral drift as a surrogate for community position on the niche-neutral continuum. We evaluate the performance of our modeling approach with simulated data, and subsequently use the model to analyze rodent web-trapping data from a real-world system. The model fitting is carried out with a Bayesian approach using Markov chain Monte Carlo simulation methods.     

Non‐random correlation of species dynamics in tropical tree communities

The importance of environmental stochasticity for tropical tree dynamics has been recently stressed by several studies. This has spurred the development of a ‘time‐averaged neutral model’ of community dynamics by Kalyuzhny and colleagues that extends the neutral model by incorporating environmental stochasticity. We here show that this framework can be used to assess the presence of non‐random correlations between species dynamics. Indeed, the time‐averaged neutral model makes the simplifying assumption that species responses to environmental variation are uncorrelated. We therefore propose to use this model as a null hypothesis against which observed community dynamics can be compared. This study makes five contributions. First, we describe a novel time‐averaged neutral model of community dynamics that is close to, but more flexible than the one previously proposed by Kalyuzhny and colleagues. Second, we develop an inference method based on approximate Bayesian computation (ABC) and demonstrate the identifiability of the model parameters from community time series data. Third, we develop a test of the significance of environmental stochasticity, and a method to quantify its contribution to population variance. Fourth, we develop a test of non‐random correlation between species dynamics. Fifth, we apply these developments to three datasets of tropical tree dynamics. We evidence both a strong contribution of environmental stochasticity to population variance in the three datasets, and a non‐random correlation of species dynamics in one of them. We finally discuss the implications of these results for the modelling of tropical tree community dynamics.     

A coalescence approach to spatial neutral ecology

Neutral models in ecology have attracted much attention in recent literature. They can provide considerable insight into the roles of non-species-specific factors (e.g. stochasticity, dispersal, speciation) on community dynamics but often require intensive simulations, particularly in spatial settings. Here, we clearly explain existing techniques for modelling spatially explicit neutral processes in ecology using coalescence. Furthermore, we present several novel extensions to these methods including procedures for dealing with system boundaries which enable improved investigation of the effects of dispersal. We also present a semi-analytical algorithm that calculates the expected species richness in a sample, for any speciation rate. By eliminating the effect of stochasticity in the speciation process, we reduce the variance in estimates of species richness. Our benchmarks show that the combination of existing coalescence theory and our extensions produces higher quality results in vastly shorter time scales than previously possible: years of simulation time are reduced to minutes. As an example application, we find parameters for a spatially explicit neutral model to approximate the species richness of a tropical forest dataset.     

What can observational data reveal about metacommunity processes?

A key challenge for community ecology is to understand to what extent observational data can be used to infer the underlying community assembly processes. As different processes can lead to similar or even identical patterns, statistical analyses of non‐manipulative observational data never yield undisputable causal inference on the underlying processes. Still, most empirical studies in community ecology are based on observational data, and hence understanding under which circumstances such data can shed light on assembly processes is a central concern for community ecologists. We simulated a spatial agent‐based model that generates variation in metacommunity dynamics across multiple axes, including the four classic metacommunity paradigms as special cases. We further simulated a virtual ecologist who analysed snapshot data sampled from the simulations using eighteen output metrics derived from beta‐diversity and habitat variation indices, variation partitioning and joint species distribution modelling. Our results indicated two main axes of variation in the output metrics. The first axis of variation described whether the landscape has patchy or continuous variation, and thus was essentially independent of the properties of the species community. The second axis of variation related to the level of predictability of the metacommunity. The most predictable communities were niche‐based metacommunities inhabiting static landscapes with marked environmental heterogeneity, such as metacommunities following the species sorting paradigm or the mass effects paradigm. The most unpredictable communities were neutral‐based metacommunities inhabiting dynamics landscapes with little spatial heterogeneity, such as metacommunities following the neutral or patch sorting paradigms. The output metrics from joint species distribution modelling yielded generally the highest resolution to disentangle among the simulated scenarios. Yet, the different types of statistical approaches utilized in this study carried complementary information, and thus our results suggest that the most comprehensive evaluation of metacommunity structure can be obtained by combining them.     

A core‐transient framework for trait‐based community ecology: an example from a tropical tree seedling community

Trait‐based studies in community ecology have generally focused on the community as a unit where all species occur due to stochasticity, determinism or some mixture of the two. However, the processes governing population dynamics may vary greatly among species. We propose a core‐transient framework for trait‐based community studies where a core group of species has a strong link to the local environment while transient species have weaker responses to the environment. Consistent with the expectations of the framework, we found that common species exhibit clear linkages between performance and their environment and traits while rare species tend to have weaker or non‐significant relationships. Ultimately, trait‐based ecology should move beyond applying a set of processes to a community as a whole and towards quantifying inter‐specific variation in the drivers of population dynamics that ultimately scale up to determine community structure.     

Bottom‐up regulation of malaria population dynamics in mice co‐infected with lung‐migratory nematodes

When and how populations are regulated by bottom up vs. top down processes, and how those processes are affected by co‐occurring species, are poorly characterised across much of ecology. We are especially interested in the community ecology of parasites that must share a host. Here, we quantify how resources and immunity affect parasite propagation in experiments in near‐replicate ‘mesocosms’’ – i.e. mice infected with malaria (Plasmodium chabaudi) and nematodes (Nippostrongylus brasiliensis). Nematodes suppressed immune responses against malaria, and yet malaria populations were smaller in co‐infected hosts. Further analyses of within‐host epidemiology revealed that nematode co‐infection altered malaria propagation by suppressing target cell availability. This is the first demonstration that bottom‐up resource regulation may have earlier and stronger effects than top‐down immune mechanisms on within‐host community dynamics. Our findings demonstrate the potential power of experimental ecology to disentangle mechanisms of population regulation in complex communities.     

Local community size mediates ecological drift and competition in metacommunities

The outcome of competitive interactions is likely to be influenced by both competitive dominance (i.e. niche-based dynamics) and ecological drift (i.e. neutral dynamics governed by demographic stochasticity). However, spatial models of competition rarely consider the joint operation of these two processes. We develop a model based on the original competition-colonization trade-off model that incorporates niche and neutral processes and several realistic facets of ecological dynamics: it allows local competition (i.e. competition within a patch) to occur within communities of a finite size, it allows competitors to vary in the degree of competitive asymmetry, and it includes the role of local migration (i.e. propagule pressure). The model highlights the role of community size, i.e. the number of competitors in the local community, in mediating the relative importance of stochastic and deterministic forces. In metacommunities where local communities are small, ecological drift is substantial enough that strong competitors become effectively neutral, creating abrupt changes in the outcome of competition not predicted by the standard competition-colonization trade-off. Importantly, the model illustrates that, even when other aspects of species interactions (e.g. migration ability, competitive ability) are unchanged, local community size can alter the dynamics of metacommunity persistence. Our work demonstrates that activities which reduce the size of local communities, such as habitat destruction and degradation, effectively compound the extinction debt.     

Demographic stochasticity alters expected outcomes in experimental and simulated non‐neutral communities

Theory has shown that the effects of demographic stochasticity on communities may depend on the magnitude of fitness differences between species. In particular, it has been suggested that demographic stochasticity has the potential to significantly alter competitive outcomes when fitness differences are small (nearly neutral), but that it has negligible effects when fitness differences are large (highly non‐neutral). Here we test such theory experimentally and extend it to examine how demographic stochasticity affects exclusion frequency and mean densities of consumers in simple, but non‐neutral, consumer–resource communities. We used experimental microcosms of protists and rotifers feeding on a bacterial resource to test how varying absolute population sizes (a driver of demographic stochasticity) affected the probability of competitive exclusion of the weakest competitor. To explore whether demographic stochasticity could explain our experimental results, and to generalize beyond our experiment, we paired the experiment with a continuous‐time stochastic model of resource competition, which we simulated for 11 different fitness inequalities between competiting consumers. Consistent with theory, in both our experiments and our simulations we found that demographic stochasticity altered competitive outcomes in communities where fitness differences were small. However, we also found that demographic stochasticity alone could affect communities in other ways, even when fitness differences between competitors were large. Specifically, demographic stochasticity altered mean densities of both weak and strong competitors in experimental and simulated communities. These findings highlight how demographic stochasticity can change both competitive outcomes in non‐neutral communities and the processes underlying overall community dynamics.     

Quantifying the role of deterministic assembly and stochastic drift in a natural community of Arctic mosses

The interpretation of natural plant communities frequently invokes species‐sorting controlled by niche differences along spatial environmental gradients. This process of niche structuring can be explained by reference to functional traits, which provide a mechanistic explanation for community structure. In contrast, models explaining species coexistence obviate the limiting effect of niche difference, by invoking processes which cause species‐level drift, e.g. demographic stochasticity. This paper investigates a simple habitat with strong gradients (moss communities in a patterned arctic wetland) to identify signature‐patterns under‐pinning the relative importance of deterministic assembly and stochastic drift in a natural community. First, ordination analysis was used to confirm community composition structured by a range of nine carefully selected functional traits. Second, to determine whether traits explaining community composition might also explain species richness, local species richness (sR) was compared to (1) observed trait diversity and (2) expected trait diversity based on permutation tests, which are used to simulate null community assembly for different values of sR. Traits explaining species composition, consistent with deterministic niche structuring, do not appear to maintain sR. This surprising result was explained by decomposing the community into individual pair‐wise comparisons, i.e. species niche‐differences and association (χ²). Results support deterministic processes via the sorting of species with similar and contrasting niches, at opposite ends of a composite environmental gradient. Nevertheless, stochastic drift is apparent in the random structure of a majority of pair‐wise associations; in addition, a species’ abundance was in general not related to environmental distance from response‐optima. We suggest therefore that spatial pattern in the moss community is a balance between deterministic forces with respect to species traits and controlling environmental gradients, and stochastic drift, which weakens this deterministic structure.     

Population fluctuations affect inference in ecological networks of multi‐species interactions

Local abundance and population fluctuations are key factors affecting the realized interaction frequencies in biotic interactions, but they are commonly ignored when network metrics are calculated over aggregated sets of observations. Here we studied how abundance fluctuations (i.e. demographic and stochastic population dynamics in one of the trophic levels) may affect derived network‐level inferences in bipartite ecological networks. Variation at both the species and network level in network indices (d’, Dependence, Fisher's alpha diversity for both levels, H₂’, weighted NODF) were strongly correlated with the extent of abundance fluctuations, with a strong effect of environmental stochasticity on all indices except NODF; this was the only index for which considerable variation was caused by varying carrying capacities among species. Binary connectance, in turn, does not take interaction frequency (and thus abundance) into account and was only influenced by abundance fluctuations at low population sizes if this led to non‐occurrence of ‘true’ interactions. Overall, abundance and population dynamics are likely to play an important role in determining what is commonly observed and summarized into ecological networks. We suggest that ecological network inference should account for underlying population dynamics and uncertainty in what is observed as interaction frequencies, modelling mechanisms at operative organisational levels below the network rather than using aggregated data of observations. Modelling population dynamics may be a valuable tool in this field to conceptualize and tease apart different sources of variation and express uncertainty in our inference from small samples.     

Nitrotoga is selected over Nitrospira in newly assembled biofilm communities from a tap water source community at increased nitrite loading

Community assembly is a central topic in microbial ecology: how do assembly processes interact and what is the relative contribution of stochasticity and determinism? Here, we exposed replicate flow‐through biofilm systems, fed with nitrite‐supplemented tap water, to continuous immigration from a source community, present in the tap water, to determine the extent of selection and neutral processes in newly assembled biofilm communities at both the community and the functional guild (of nitrite‐oxidizing bacteria, NOB) levels. The community composition of biofilms assembled under low and high nitrite loading was described after 40 days of complete nitrite removal. The total community assembly, as well as the NOB guild assembly were largely governed by a combination of deterministic and stochastic processes. Furthermore, we observed deterministic enrichment of certain types of NOB in the biofilms. Specifically, elevated nitrite loading selected for a single Nitrotoga representative, while lower nitrite conditions selected for a number of Nitrospira. Therefore, even when focusing on ecologically coherent ensembles, assembly is the result of complex stochastic and deterministic processes that can only be interrogated by observing multiple assemblies under controlled conditions.     

Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre‐scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple‐like’ and ‘star‐like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size‐structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single‐species bacterial biofilms.     

种群统计随机性和环境随机性对种群绝灭的影响

影响种群绝灭的随机干扰可分为种群统计随机性、环境随机性和随机灾害三大类。在相对稳定的环境条件下和相对较短的时间内,以前两类随机干扰对种群绝灭的影响为生态学家关注的焦点。但是,由于自然种群动态及其影响因子的复杂特征,进一步深入研究随机干扰对种群绝灭的作用在理论上和实践上都必须发展新的技术手段。本文回顾了种群统计随机性与环境随机性的概念起源与发展,系统阐述了其分析方法。归纳了两类随机性在种群绝灭研究中的应用范围、作用方式和特点的异同和区别方法。各类随机作用与种群动态之间关系的理论研究与对种群绝灭机理的实践研究紧密相关。根据理论模型模拟和自然种群实际分析两方面的研究现状,作者提出了进一步深入研究随机作用与种群非线性动态方法的策略。指出了随机干扰影响种群绝灭过程的研究的方向：更多的研究将从单纯的定性分析随机干扰对种群动力学简单性质的作用,转向结合特定的种群非线性动态特征和各类随机力作用特点具体分析绝灭极端动态的成因,以期做出精确的预测。     

Linking community assembly and structure across scales in a wild mouse parasite community

Understanding what processes drive community structure is fundamental to ecology. Many wild animals are simultaneously infected by multiple parasite species, so host–parasite communities can be valuable tools for investigating connections between community structures at multiple scales, as each host can be considered a replicate parasite community. Like free‐living communities, within‐host–parasite communities are hierarchical; ecological interactions between hosts and parasites can occur at multiple scales (e.g., host community, host population, parasite community within the host), therefore, both extrinsic and intrinsic processes can determine parasite community structure. We combine analyses of community structure and assembly at both the host population and individual scales using extensive datasets on wild wood mice (Apodemus sylvaticus) and their parasite community. An analysis of parasite community nestedness at the host population scale provided predictions about the order of infection at the individual scale, which were then tested using parasite community assembly data from individual hosts from the same populations. Nestedness analyses revealed parasite communities were significantly more structured than random. However, observed nestedness did not differ from null models in which parasite species abundance was kept constant. We did not find consistency between observed community structure at the host population scale and within‐host order of infection. Multi‐state Markov models of parasite community assembly showed that a host's likelihood of infection with one parasite did not consistently follow previous infection by a different parasite species, suggesting there is not a deterministic order of infection among the species we investigated in wild wood mice. Our results demonstrate that patterns at one scale (i.e., host population) do not reliably predict processes at another scale (i.e., individual host), and that neutral or stochastic processes may be driving the patterns of nestedness observed in these communities. We suggest that experimental approaches that manipulate parasite communities are needed to better link processes at multiple ecological scales.     

Is invasion success explained by the enemy release hypothesis?

A recent trend in invasion ecology relates the success of non‐indigenous species (NIS) to reduced control by enemies such as pathogens, parasites and predators (i.e. the enemy release hypothesis, ERH). Despite the demonstrated importance of enemies to host population dynamics, studies of the ERH are split – biogeographical analyses primarily show a reduction in the diversity of enemies in the introduced range compared with the native range, while community studies imply that NIS are no less affected by enemies than native species in the invaded community. A broad review of the invasion literature implies at least eight non‐exclusive explanations for this enigma. In addition, we argue that the ERH has often been accepted uncritically wherever (i) NIS often appear larger, more fecund, or somehow ‘better’ than either congeners in the introduced region, or conspecifics in the native range; and (ii) known enemies are conspicuously absent from the introduced range. However, all NIS, regardless of their abundance or impact, will lose natural enemies at a biogeographical scale. Given the complexity of processes that underlie biological invasions, we argue against a simple relationship between enemy ‘release’ and the vigour, abundance or impact of NIS.     

Balance of Neutral and Deterministic Components in the Dynamics of Activated Sludge Floc Assembly

Understanding the processes that generate patterns of community structure is a central focus of ecological research. With that aim, we manipulated the structure of bacterial activated sludge to test the influence of the species richness and composition of bacterial communities on the dynamics of activated sludge floc assembly in lab-scale bioreactors. Bacterial community structure was analyzed using denaturing gradient gel electrophoresis of RT-PCR amplified 16S rRNA. Fingerprinting of four parallel reactors, started with the same source communities added in different proportions, converged to patterns that were more similar than expected by chance, suggesting a deterministic selection in floc development. Evidence for neutral dynamics was suggested by the dependence of the rate of replacement of species (bacterial taxa–time relationships) on the number of available species in the source community. Further indication of stochastic dynamics was obtained by the application of the Sloan neutral model for prokaryotes. The fitting of the observed data to the model predictions revealed that the importance of the stochastic component increased with the size of the reservoir of species richness from which the community is drawn. Taken together, the results illustrate how both neutral and deterministic dynamics operate simultaneously in the assembly of the bacterial floc and show that the balance of the two depends on the richness of the source community.     

Island biology and morphological divergence of the Skyros wall lizard <Emphasis Type="Italic">Podarcis gaigeae</Emphasis>: a combined role for local selection and genetic drift on color morph frequency divergence?

Background  

Patterns of spatial variation in discrete phenotypic traits can be used to draw inferences about the adaptive significance of traits and evolutionary processes, especially when compared to patterns of neutral genetic variation. Population divergence in adaptive traits such as color morphs can be influenced by both local ecology and stochastic factors such as genetic drift or founder events. Here, we use quantitative color measurements of males and females of Skyros wall lizard, Podarcis gaigeae, to demonstrate that this species is polymorphic with respect to throat color, and the morphs form discrete phenotypic clusters with limited overlap between categories. We use divergence in throat color morph frequencies and compare that to neutral genetic variation to infer the evolutionary processes acting on islet- and mainland populations.     

Metacommunity,mainland‐island system or island communities? Assessing the regional dynamics of plant communities in a fragmented landscape

Understanding the regional dynamics of plant communities is crucial for predicting the response of plant diversity to habitat fragmentation. However, for fragmented landscapes the importance of regional processes, such as seed dispersal among isolated habitat patches, has been controversially debated. Due to the stochasticity and rarity of among‐patch dispersal and colonization events, we still lack a quantitative understanding of the consequences of these processes at the landscape‐scale. In this study, we used extensive field data from a fragmented, semi‐arid landscape in Israel to parameterize a multi‐species incidence‐function model. This model simulates species occupancy pattern based on patch areas and habitat configuration and explicitly considers the locations and the shapes of habitat patches for the derivation of patch connectivity. We implemented an approximate Bayesian computation approach for parameter inference and uncertainty assessment. We tested which of the three types of regional dynamics – the metacommunity, the mainland‐island, or the island communities type – best represents the community dynamics in the study area and applied the simulation model to estimate the extinction debt in the investigated landscape. We found that the regional dynamics in the patch‐matrix study landscape is best represented as a system of highly isolated ‘island’ communities with low rates of propagule exchange among habitat patches and consequently low colonization rates in local communities. Accordingly, the extinction rates in the local communities are the main drivers of community dynamics. Our findings indicate that the landscape carries a significant extinction debt and in model projections 33–60% of all species went extinct within 1000 yr. Our study demonstrates that the combination of dynamic simulation models with field data provides a promising approach for understanding regional community dynamics and for projecting community responses to habitat fragmentation. The approach bears the potential for efficient tests of conservation activities aimed at mitigating future losses of biodiversity.