Chaotic dynamics in a multispecies community

Environmental and Ecological Statistics - It is shown that community dynamics is neither haphazard nor completely directed. This is quite clear from our examination of a concrete example where...     

半干旱区草地生境中大型土壤动物群落季节动态

选择科尔沁沙地封育草地为研究对象,通过调查大型土壤动物个体数和类群数的季节变化特征及其与气候因子间的关系,分析大型土壤动物群落结构的季节变化规律。结果表明,伴随着气候因子(降雨量和气温)的季节变化,土壤含水量表现为春季>秋季>夏季,而土壤温度表现为夏季>春季>秋季。土壤温湿度的季节性变化显著影响了大型土壤动物群落结构(P<0.05)。大型土壤动物类群数和个体数以及Shannon指数均表现为夏季显著高于秋季(P<0.05),春季居中;而均匀度指数则与此相反(P<0.05),表现为夏季<春季<秋季。随着季节更替,不同大型土壤动物类群对气候因子变化产生了不同的响应和适应性,不同季节表现出了不同的大型土壤动物类群及其个体数分布,而且在夏季表现出较高的大型土壤动物多样性。     

Impact of curve construction and community dynamics on the species-time relationship

The species-time relationship (STR) describes how the species richness of a community increases with the time span over which the community is observed. This temporal scaling provides insight into theoretical questions on species diversity patterns as well as applied questions on the appropriate time scale for biodiversity assessments. To better understand STRs, we discuss the methods used to construct STRs in the literature and derive the impact of curve construction on STR properties. Using vegetation data from Mount St. Helens, Washington, USA, we illustrate the sensitivity of the STR to construction under colonization-dominated dynamics. This study highlights the importance of considering the type of STR when interpreting, comparing, and applying STRs, particularly in disturbed or successional systems.     

The interaction of cannibalism and omnivory: consequences for community dynamics

Although cannibalism is ubiquitous in food webs and frequent in systems where a predator and its prey also share a common resource (intraguild predation, IGP), its impacts on species interactions and the dynamics and structure of communities are still poorly understood. In addition, the few existing studies on cannibalism have generally focused on cannibalism in the top-predator, ignoring that it is frequent at intermediate trophic levels. A set of structured models shows that cannibalism can completely alter the dynamics and structure of three-species IGP systems depending on the trophic position where cannibalism occurs. Contrary to the expectations of simple models, the IG predator can exploit the resources more efficiently when it is cannibalistic, enabling the predator to persist at lower resource densities than the IG prey. Cannibalism in the IG predator can also alter the effect of enrichment, preventing predator-mediated extinction of the IG prey at high productivities predicted by simple models. Cannibalism in the IG prey can reverse the effect of top-down cascades, leading to an increase in the resource with decreasing IG predator density. These predictions are consistent with current data. Overall, cannibalism promotes the coexistence of the IG predator and IG prey. These results indicate that including cannibalism in current models can overcome the discrepancy between theory and empirical data. Thus, we need to measure and account for cannibalistic interactions to reliably predict the structure and dynamics of communities.     

镇江内江湿地植物群落演替进程中种群生态位动态

用定量分析法对镇江内江湿地植物群落演替进程中种群生态位动态进行了研究.先采用"空间代替时间"方法,选择四类典型样地,分别代表群落演替进程中四个不同阶段.再以每个调查样方作为多维资源的综合资源位,用Levins 生态位宽度公式和Pianka生态位重叠公式测算不同演替阶段内所有种群的生态位宽度以及同一演替阶段内所有种群间的生态位重叠,并分析它们的生态学意义.结果表明,不同演替阶段,群落的优势种群生态位占绝对优势,揭示了它们较强的环境适应能力和较高的资源利用能力.种群生态位动态较好地表征了演替过程中对应种群及生境的动态变化,尤其是优势种群的更迭.总体上,生态位较宽的种群间生态位重叠较大,有较多相似生态特性的种群间生态位重叠也较大.群落内种群的平均生态重叠随演替逐渐增加,至中后期最高,后期略有回落,这主要由群落内种群种内竞争和种间竞争共同作用的结果.     

Assessing tiger population dynamics using photographic capture-recapture sampling

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.     

Size-mediated non-trophic interactions and stochastic predation drive assembly and dynamics in a seabird community

Theoretical and empirical evidence suggests that body size is a major life-history trait impacting on the structure and functioning of complex food webs. However, long-term analyses of size-dependent interactions within simpler network modules, for instance, competitive guilds, are scant. Here, we model the assembly dynamics of the largest breeding seabird community in the Mediterranean basin during the last 30 years. This unique data set allowed us to test, through a "natural experiment," whether body size drove the assembly and dynamics of an ecological guild growing from very low numbers after habitat protection. Although environmental stochasticity accounted for most of community variability, the population variance explained by interspecific interactions, albeit small, decreased sharply with increasing body size. Since we found a demographic gradient along a body size continuum, in which population density and stability increase with increasing body size, the numerical effects of interspecific interactions were proportionally higher on smaller species than on larger ones. Moreover, we found that the per capita interaction coefficients were larger the higher the size ratio among competing species, but only for the set of interactions in which the species exerting the effect was greater. This provides empirical evidence for long-term asymmetric interspecific competition, which ultimately prompted the local extinction of two small species during the study period. During the assembly process stochastic predation by generalist carnivores further triggered community reorganizations and global decays in population synchrony, which disrupted the pattern of interspecific interactions. These results suggest that the major patterns detected in complex food webs can hold as well for simpler sub-modules of these networks involving non-trophic interactions, and highlight the shifting ecological processes impacting on assembling vs. asymptotic communities.     

Social information and community dynamics: nontarget effects from simulating social cues for management

Artificially creating social stimuli may be an effective tool for facilitating settlement by rare and/or declining species into suitable habitat. However, the potential consequences for other community members have not been explored and should be considered when evaluating the overall utility of using such management strategies. I report on nontarget, community-wide effects that occurred when manipulating social cues of two competitors that are species of concern in the western United States, the dominant Least Flycatcher (Empidonax minimus) and the subordinate American Redstart (Setophaga ruticilla). The experiment consisted of surveying birds during a pretreatment year, which allows for the control of baseline communities, and a treatment year, in which treatments were applied just prior to settlement by migratory birds. Treatments included broadcasting songs of flycatchers and redstarts and were compared to controls. While the addition of redstart cues did not significantly influence community structure, the addition of flycatcher cues reduced species richness of migratory birds by approximately 30%. This pattern was driven by an absence of local colonizations of small-bodied migrants to sites with added flycatcher cues, rather than by local extinctions occurring from manipulations. The artificial flycatcher stimuli were more responsible for declines in species richness than were changes in actual flycatcher densities. I conclude by identifying some fundamental issues that managers and conservation practitioners should weigh when considering simulating social cues for species conservation prior to implementation.     

Temporal variation in community interfaces: kelp-bed boundary dynamics adjacent to persistent urchin barrens

We examined, over 2 years, factors affecting the temporal stability of the lower limit of kelp beds (Alaria esculenta) at five subtidal sites in the Mingan Islands, northern Gulf of St. Lawrence. The position of the lower limit of the beds varied markedly among sites and over time and was largely controlled by the green sea urchin, Strongylocentrotus droebachiensis, which formed dense (up to 500 individuals m^–2) feeding fronts at the lower edge of the beds. These aggregations advanced over the kelp most rapidly during the summer (at rates as high as 2.5 m month^–1), and there appeared to be a threshold urchin biomass of ~5 kg m^–2 below which the fronts could not substantially reduce the limit of the beds. The fronts consisted mainly of large individuals, whereas smaller urchins predominated in the barrens zone below the kelp beds. At one site, we recorded large seasonal shifts in overall urchin densities, with large increases and decreases during the summer and winter, respectively. An urchin exclusion experiment indicated that algal recruitment in the barrens was two orders of magnitude greater in the absence than in the presence of urchins. The kelp Agarum cribrosum greatly restricted urchin movements, and the greater temporal stability of the kelp bed at one site appeared related to the gradual replacement of Alaria esculenta in the lower kelp bed by a large stand of Agarum cribrosum. We propose that perturbations by abiotic factors (e.g., ice scouring and water motion) trigger important but localized changes in urchin densities that, in turn, largely determine the limits of kelp bed distribution in this region of the Atlantic where urchin barrens are a persistent community state.Communicated by R.J. Thompson, St. Johns     

Statistical modeling of seasonal and environmental influences on the population dynamics of an estuarine fish community

A statistical modeling study was performed on the population fluctuations of the 15 commonest fish species frequenting the tidal Scheldt estuary in Belgium. These included marine juvenile and seasonal visitors, estuarine residents and diadromous fish species that were recorded on the filter screens of a power plant cooling-water intake between September 1991 and April 2001. The species population abundance was regressed against a candidate set of 6 environmental variables and 13 instrumental variables, accounting for seasonality and long-term trends present in the data. Population abundances of the different species were, in general, best described by seasonal variables. Seasonal components contributed, on average, up to 63.8% of the variance explained by the models. Ten species were found to show a slightly negative, though significant, trend over the period of the survey. Most models also included at least one environmental variable, and 25.4% of the explained variance could be attributed to environmental fluctuations. Of all physico-chemical variables, dissolved oxygen was the most important predictor of fish abundance, suggesting that the estuary suffered from poor water quality during the survey. Temperature, salinity, freshwater flow, suspended solids and chlorophyll a concentrations were minor determinants of fish abundance.Communicated by O. Kinne, Oldendorf/Luhe     

Disentangling the effects of heterogeneity, stochastic dynamics and sampling in a community of aquatic insects

A dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution is fitted to time series of species data from an assemblage of stoneflies and mayflies (Plecoptera and Ephemeroptera) of an aquatic insect community collected over a period of 15 years. In each year except one, we analyze 5 parallel samples taken at the same time of the season giving information about the over-dispersion in the sampling relative to the Poisson distribution. Results are derived from a correlation analysis, where the correlation in the bivariate normal distribution of log abundance is used as measurement of similarity between communities. The analysis enables decomposition of the variance of the lognormal species abundance distribution into three components due to heterogeneity among species, stochastic dynamics driven by environmental noise, and over-dispersion in sampling, accounting for 62.9, 30.6 and 6.5% of the total variance, respectively. Corrected for sampling the heterogeneity and stochastic components accordingly account for 67.3 and 32.7% of the among species variance in log abundance. By using this method, it is possible to disentangle the effect of heterogeneity and stochastic dynamics by quantifying these components and correctly remove sampling effects on the observed species abundance distribution.     

Clustering species using a model of population dynamics and aggregation theory

The high species diversity of some ecosystems like tropical rainforests goes in pair with the scarcity of data for most species. This hinders the development of models that require enough data for fitting. The solution commonly adopted by modellers consists in grouping species to form more sizeable data sets. Classical methods for grouping species such as hierarchical cluster analysis do not take account of the variability of the species characteristics used for clustering. In this study a clustering method based on aggregation theory is presented. It takes account of the variability of species characteristics by searching for the grouping that minimizes the quadratic error (square bias plus variance) of some model’s prediction. This method allows one to check whether the gain in variance brought by data pooling compensate for the bias that it introduces. This method was applied to a data set on 94 tree species in a tropical rainforest in French Guiana, using a Usher matrix model to predict species dynamics. An optimal trade-off between bias and variance was found when grouping species. Grouping species appeared to decrease the quadratic error, except when the number of groups was very small. This clustering method yielded species groups similar to those of the hierarchical cluster analysis using Ward’s method when variance was small, that is when the number of groups was small.     

The impact of the invasive shrub Lonicera maackii on the decomposition dynamics of a native plant community

Invasive plants may have variable effects within a given environment depending on their interactions with the dominant native species, yet little research has examined such species-species interactions within a site. Savanna trees with nonoverlapping canopies offer an ideal opportunity to assess associated changes in the ecosystem processes that result from interactions between an invasive species and different native tree species. We examined the influence of the exotic invasive shrub Lonicera maackii on decomposition dynamics under three native tree species: Fraxinus quadrangulata, Quercus muehlenbergii, and Carya ovata. Litter decomposition rates and litter C and N were evaluated over two years using single- and mixed-species litterbags (L. maackii and individual tree species litter); microarthropod abundance was measured at 6 weeks using Tulgren funnels. Litter from the invasive L. maackii decomposed and lost N more rapidly than the litter of the three native tree species. The rate at which L. maackii decomposed depended on its location, with L. maackii litter decomposing and losing N more rapidly under C. ovata than under the other two native tree species. Mixing L. maackii with the native species' litter did not accelerate litter mass loss overall but did result in synergistic N losses at variable times throughout the experiment, further highlighting the variable interaction between native species and L. maackii. Nitrogen loss was significantly higher than expected in mixtures of C. ovata + L. maackii litter at 6 weeks, in F. quadrangulata + L. maackii litter at 12 weeks, and in Q. muehlenbergii + L. maackii litter at 24 weeks. If the effects of invasive species on certain ecosystem processes, such as litter decomposition, are strongly influenced by their association with native species, this could suggest the need for a more nuanced understanding of the vulnerability of ecosystem processes to invasions of L. maackii and potentially other invasive species.     

Characterizing cumulative impacts using a brook trout population dynamics model

An individuals-based modelling framework is used to characterize the nature of exploitation and toxaphene stressors acting simultaneously on a population of brook trout (Salvelinus fontinalis) in terms of age 0 + and adult abundance, survivorship and population size-structure. A no-stressor control case was estimated against which exploitation-only, toxaphene-only and cumulative exploitation and toxaphene stressor cases were compared to determine the extent and significance of impacts. Single stressor case results were used to predict cumulative impacts by assuming additivity and predictions compared to modelled cumulative stressor results. Comparisons indicated the inadequacy of assuming additivity in predicting cumulative impacts. A factorial experimental design was used to estimate the size and significance of interactive effects. Effects are substantial and underscore the necessity of interpreting probable impacts of increases in a single stressor in conjunction with knowledge of other stressors acting on a population. A positive functional relationship between variability in population abundance and stress was estimated and is suggested as a potentially useful means of characterizing risks posed to populations by increases in, or additions to, population stressors. Multiple stressors were also demonstrated to effectively eliminate the significance of density-dependent mortality processes in determining age 0 + and adult abundance. Taken together, results indicate the inappropriateness of attempting to predict additional perturbation impacts without considering the sum of population stressors and their associated interactions.     

Estimating the complexity of bird song by using capture-recapture approaches from community ecology

Repertoire size, the number of unique song or syllable types in the repertoire, is a widely used measure of song complexity in birds, but it is difficult to calculate this exactly in species with large repertoires. A new method of repertoire size estimation applies species richness estimation procedures from community ecology, but such capture-recapture approaches have not been much tested. Here, we establish standardized sampling schemes and estimation procedures using capture-recapture models for syllable repertoires from 18 bird species, and suggest how these may be used to tackle problems of repertoire estimation. Different models, with different assumptions regarding the heterogeneity of the use of syllable types, performed best for different species with different song organizations. For most species, models assuming heterogeneous probability of occurrence of syllables (so-called detection probability) were selected due to the presence of both rare and frequent syllables. Capture-recapture estimates of syllable repertoire size from our small sample did not differ significantly from previous estimates using larger samples of count data. However, the enumeration of syllables in 15 songs yielded significantly lower estimates than previous reports. Hence, heterogeneity in detection probability of syllables should be addressed when estimating repertoire size. This is neglected using simple enumeration procedures, but is taken into account when repertoire size is estimated by appropriate capture-recapture models adjusted for species-specific song organization characteristics. We suggest that such approaches, in combination with standardized sampling, should be applied in species with potentially large repertoire size. On the other hand, in species with small repertoire size and homogenous syllable usage, enumerations may be satisfactory. Although researchers often use repertoire size as a measure of song complexity, listeners to songs are unlikely to count entire repertoires and they may rely on other cues, such as syllable detection probability.Communicated by A. Cockburn     

Modelling crayfish population dynamics using catch data: A size-structured model

In this study we explore a rather unique time series (1979–2002) of catch data of the crayfish Astacus astacus in Lake Steinsfjorden (SE Norway) in combination with temperature data and data on Canadian pondweed Elodea canadensis coverage. In 1977, E. canadensis was for the first time observed in the lake. Over the following years, the plant established dense covers over large parts of the shallow areas, excluding the crayfish from these areas and causing a sudden drop in population size. A size-structured model with bi-stability including a range of observed stage-specific life-cycle attributes (e.g. growth, fecundity, fertility, sex-ratio), population specific parameters and density-dependant (shelters, cannibalism, unspecified predators, competition between individuals, catch, number of traps) as well as density independent factors (temperature and Elodea coverage) were constructed to evaluate the various drivers for the population dynamics, and as a predictive tool for assessing the effects of future changes. Our model revealed that the decline primarily was due to density-dependant effect of the Elodea expansion with reduced number of hides and thus increased risk for predation and cannibalism, but also that temperature played an important role related to recruitment. The model should be relevant for crayfish stock management in general, and by demonstrating the major role of temperature, it is also relevant for predicting population responses under a changing climate. The model should also be applicable to other crustaceans and species with discrete growth and late maturation.     

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling.

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.     

Plankton community dynamics of the central Great Barrier Reef Lagoon: Analysis of data from Ikeda et al.

Plankton data collected by Ikeda et al. (1980) from the central region of the Great Barrier Reef, and spanning two years (1976 through 1978) of zooplankton records, have been analyzed extensively for spatial and temporal patterns. Estimates of net zooplankton (including chaetognaths, copepods, and larvaceans) and microzooplankton (juvenile copepods, encompassing nauplii and copepodites, and ciliates) were assessed at three stations across the 60 km lagoon. Temperature, salinity, and chlorophyll a were also measured. A cross-lagoonal gradient was identified in the plankton, concurring with results of related surveys of benthic taxa, such as scleractinian corals, soft corals, macro-algae, fish, sponges, crinoids, etc. Two associations of net zooplankton were identified. The first was associated primarily with the inner lagoon; the second with the outer lagoon. The inshore association was characterized by higher abundances of almost all net zooplankton taxa, particularly chaetognaths, copepods, polychaetes, decapods, and meroplanktonic larvae as well as higher concentrations of chlorophyll a. This inshore association wove back and forth across the lagoon through time, dominating the lagoon entirely during periods of high river discharge, reaching the mid-shelf platform reefs in this region, and sometimes being entirely absent during dry periods. Both seasonal and annual peaks in plankton abundance were generally linked with degree of runoff. Summer/autumn peaks of abundance were evident in chaetognaths, copepods, and larvaceans while annual variation was detected in the former two as well as in chlorophyll a concentrations. Depth stratification was noted in juvenile copepods and chlorophyll a concentrations at the center of the lagoon, with higher abundances recorded in deeper waters. The central Great Barrier Reef lagoon was found to be typical of other tropical coastal waters where plankton community dynamics are controlled primarily by physical factors. We suggest that any substantial changes in river discharge in this area will affect plankton production.A.I.M.S. Contribution No. 242     

Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach

Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.