The Dynamic Hypercube as a Niche Community Model

Different models of community dynamics, such as the MacArthur–Wilson theory of island biogeography and Hubbell’s neutral theory, have given us useful insights into the workings of ecological communities. Here, we develop the niche-hypervolume concept of the community into a powerful model of community dynamics. We describe the community’s size through the volume of the hypercube and the dynamics of the populations in it through the fluctuations of the axes of the niche hypercube on different timescales. While the community’s size remains constant, the relative volumes of the niches within it change continuously, thus allowing the populations of different species to rise and fall in a zero-sum fashion. This dynamic hypercube model reproduces several key patterns in communities: lognormal species abundance distributions, 1/f-noise population abundance, multiscale patterns of extinction debt and logarithmic species-time curves. It also provides a powerful framework to explore significant ideas in ecology, such as the drift of ecological communities into evolutionary time.

The Shape of Species Abundance Distributions Across Spatial Scales

Species abundance distributions (SADs) describe community structure and are a key component of biodiversity theory and research. Although different distributions have been proposed to represent SADs at different scales, a systematic empirical assessment of how SAD shape varies across wide scale gradients is lacking. Here, we examined 11 empirical large-scale datasets for a wide range of taxa and used maximum likelihood methods to compare the fit of the logseries, lognormal, and multimodal (i.e., with multiple modes of abundance) models to SADs across a scale gradient spanning several orders of magnitude. Overall, there was a higher prevalence of multimodality for larger spatial extents, whereas the logseries was exclusively selected as best fit for smaller areas. For many communities the shape of the SAD at the largest spatial extent (either lognormal or multimodal) was conserved across the scale gradient, despite steep declines in area and taxonomic diversity sampled. Additionally, SAD shape was affected by species richness, but we did not detect a systematic effect of the total number of individuals. Our results reveal clear departures from the predictions of two major macroecological theories of biodiversity for SAD shape. Specifically, neither the Neutral Theory of Biodiversity (NTB) nor the Maximum Entropy Theory of Ecology (METE) are able to accommodate the variability in SAD shape we encountered. This is highlighted by the inadequacy of the logseries distribution at larger scales, contrary to predictions of the NTB, and by departures from METE expectation across scales. Importantly, neither theory accounts for multiple modes in SADs. We suggest our results are underpinned by both inter- and intraspecific spatial aggregation patterns, highlighting the importance of spatial distributions as determinants of biodiversity patterns. Critical developments for macroecological biodiversity theories remain in incorporating the effect of spatial scale, ecological heterogeneity and spatial aggregation patterns in determining SAD shape.

Changing foodwebs of Indian aquatic ecosystems under the threats of invasive species: An overview

Biological invasions are a worldwide threat to the aquatic systems and have the potential to homogenize entire foodwebs and shift species abundance distributions to more skewed ones. Invasion impacts include effects on the foodweb structure and ecosystem functioning leading to a loss in native fish biodiversity and commercially important fisheries in many open water systems. The impacts of invasives are generally devastating as they spread in the foodweb with each species potentially interacting with multiple species. The foodweb modeling studies conducted in different inland aquatic ecosystems show that not all exotics cause a detrimental effect on the resilience of an ecosystem. Information on the foodweb structure and ecosystem properties is a prerequisite for formulating management protocols for conserving biodiversity, enhancement programmes and sustaining fisheries. The present paper reviews the impacts of invasive fishes in Indian aquatic ecosystems in the context of a changing foodweb scenario due to exotic fish species invasions. The information generated here could be applied for future research on similar ecosystems for deducing management actions.

The concerted emergence of well-known spatial and temporal ecological patterns in an evolutionary food web model in space

Ecological systems show a variety of characteristic patterns of biodiversity in space and time. It is a challenge for theory to find models that can reproduce and explain the observed patterns. Since the advent of island biogeography these models revolve around speciation, dispersal, and extinction, but they usually neglect trophic structure. Here, we propose and study a spatially extended evolutionary food web model that allows us to study large spatial systems with several trophic layers. Our computer simulations show that the model gives rise simultaneously to several biodiversity patterns in space and time, from species abundance distributions to the waxing and waning of geographic ranges. We find that trophic position in the network plays a crucial role when it comes to the time evolution of range sizes, because the trophic context restricts the occurrence and survival of species especially on higher trophic levels.

Empirical abundance distributions are more uneven than expected given their statistical baseline

The prevalence of the species abundance distribution’s hollow-curve shape across many communities is frequently assumed to reflect ecological processes structuring communities. However, this hollow curve can also emerge as a statistical phenomenon of dividing a particular number of individuals into a given number of species. While the hollow curve may be a statistical artefact, ecological processes may induce subtle deviations between empirical species abundance distributions and their statistically most probable forms. Examining ~22,000 communities, we found that empirical species abundance distributions are more skewed and uneven than their statistical baselines. However, small communities – with few species or individuals – exhibit poorly-resolved statistical baselines, thereby reducing our capacity to detect deviations. The extraordinarily skewed and uneven nature of empirical species abundance distributions provides new avenues for testing ecological theory, while the issues posed by small communities illustrate the limitations of statistical baselines for studying ecological patterns in small samples.

Forest typological features of herb species abundance distributions of pine forests in the Ural Mountains

The problem of preserving biodiversity in the face of human influence and climate change is one of the most pressing problems of modern ecology. The aim of the study is to identify the characteristics of herb SAD for various mountain pine forest types in the Middle Urals. Studies conducted in various types of pine forests have shown that the SAD method is an effective method for analysing the species structure and biodiversity of forest vegetation. The results presented in the form of graphs are clear, intuitive and easy to interpret. The use of approximations by several functions and comparison with theoretical distributions allows a deeper understanding of the features of forest species diversity

Microbial Species Abundance Distributions Guide Human Population Size Estimation from Sewage Metagenomes

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we develop a new method to estimate human population size in light of recent developments in species-abundance distributions of microbial ecosystems. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships in response to human population size. We present a new non-parametric model, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxon relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Microbial community modelling and diversity estimation using the hierarchical Pitman-Yor process

BackgroundThe human microbiome comprises the microorganisms that inhabit the various locales of the human body and plays a vital role in human health. The composition of a microbial population is often quantified through measures of species diversity, which summarize the number of species along with their relative abundances into a single value. In a microbiome sample there will certainly be species missing from the target population which will affect the diversity estimates.MethodsWe employ a model based on the hierarchical Pitman-Yor (HPY) process to model the species abundance distributions over multiple microbiome populations. The model parameters are estimated using a Gibbs sampler. We also derive estimates of species diversity as a function of the HPY parameters.ResultsWe show that the Gibbs sampler for the HPY model performs well in the simulation study. We also show that the estimates of diversity from the HPY model improve over naïve estimates when species are missing. Similarly the HPY estimates tend to perform better than the naïve estimates when the number of individuals sampled from a population is small.

Measuring Abundance

Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring. This book brings together in one place, for the first time, the methods used to estimate the abundance of individuals in nature. The statistical basis of each method is detailed along with practical considerations for survey design and data collection. Methods are illustrated using data ranging from Alaskan shrubs to Yellowstone grizzly bears, not forgetting Costa Rican ants and Prince Edward Island lobsters. Where necessary, example code for use with the open source software R is supplied. When appropriate, reference is made to other widely used programs. After opening with a brief synopsis of relevant statistical methods, the first section deals with the abundance of stationary items such as trees, shrubs, coral, etc. Following a discussion of the use of quadrats and transects in the contexts of forestry sampling and the assessment of plant cover, there are chapters addressing line-intercept sampling, the use of nearest-neighbour distances, and variable sized plots. The second section deals with individuals that move, such as birds, mammals, reptiles, fish, etc. Approaches discussed include double-observer sampling, removal sampling, capture-recapture methods and distance sampling. The final section deals with the measurement of species richness; species diversity; species-abundance distributions; and other aspects of diversity such as evenness, similarity, turnover and rarity. This is an essential reference for anyone involved in advanced undergraduate or postgraduate ecological research and teaching, or those planning and carrying out data analysis as part of conservation survey and monitoring programmes.