Simplification of structured population dynamics in complex ecological communities

Goldstone's idea of slow dynamics resulting from spontaneously broken symmetries is applied to Hubbell's neutral hypothesis of community dynamics, to efficiently simplify stage-structured multi-species models-introducing the quasi-neutral approximation (QNA). Rather than assuming population-dynamical neutrality in the QNA, deviations from ideal neutrality, thought to be small, drive dynamics. The QNA is systematically derived to first and second order in a two-scale singular perturbation expansion. The total reproductive value of species, as computed from the effective life-history parameters resulting from the non-linear interactions with the surrounding community, emerges as the new dynamic variables in this aggregated description. Using a simple stage-structured community-assembly model, the QNA is demonstrated to accurately reproduce population dynamics in large, complex communities. Further, the utility of the QNA in building intuition for management problems is illustrated by estimating the responses of a fish stock to harvesting and variations in fecundity.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

A comparison of a range of models for dispersion in a partially stratified room

A comparative study of models used to predict contaminant dispersion in a partially stratified room is presented. The experiments were carried out in a ventilated test room, with an initially evenly dispersed pollutant. Air was extracted from the outlet in the ceiling of the room at 1 and 3 air changes per hour. A small temperature difference between the top and bottom of the room causes very low air velocities, and higher concentrations, in the lower half of the room. Grid-independent CFD calculations were compared with predictions from a zonal model and from CFD using a very coarse grid. All the calculations show broadly similar contaminant concentration decay rates for the three locations monitored in the experiments, with the zonal model performing surprisingly well. For the lower air change rate, the models predict a less well mixed contaminant distribution than the experimental measurements suggest. With run times of less than a few minutes, the zonal model is around two orders of magnitude faster than coarse-grid CFD and could therefore be used more easily in parametric studies and sensitivity analyses. For a more detailed picture of internal dispersion, a CFD study using coarse and standard grids may be more appropriate.

Characterisation of virus transport and attenuation in epikarst using short pulse and prolonged injection multi-tracer testing

Attenuation processes controlling virus fate and transport in the vadose zone of karstified systems can strongly influence groundwater quality. This research compares the breakthrough of two bacteriophage tracers (H40/1 and T7), with contrasting properties, at subsurface monitoring points following application onto an overlying composite sequence of thin organic soil and weathered limestone (epikarst). Short pulse multi-tracer test results revealed that T7 (Source concentration, Co=1.8x106pfu/mL) and H40/1(Co=5.9x106pfu/mL) could reach sampling points 10m below ground less than 30 minutes after tracer application. Contrasting deposition rates, determined from simulated tracer responses, reflected the potential of the ground to differentially attenuate viruses. Prolonged application of both T7 (Co=2.3x104pfu/mL) and H40/1 (Co=1.3x105pfu/mL) over a five hour period during a subsequent test, in which ionic strength levels observed at monitoring points rose consistently, corresponded to a rapid rise in T7 levels, followed by a gradual decline before the end of tracer injection; this reflected reaction-limited deposition in the system. T7’s response contrasted with that of H40/1, whose concentration remained constant over a three hour period before declining dramatically prior to the end of tracer injection. Subsequent application of lower ionic strength tracer-free flush water generated a rapid rise in H40/1 levels and a more gradual release of T7. Results highlight the benefits of employing prolonged injection multi-tracer tests for identifying processes not apparent from conventional short pulse tests. Study findings demonstrate that despite rapid transport rates, the epikarst is capable of physicochemical filtration of viruses and their remobilization, depending on virus type and hydrochemical conditions.

How trophic interaction strength depends on traits

A key problem in community ecology is to understand how individual-level traits give rise to population-level trophic interactions. Here, we propose a synthetic framework based on ecological considerations to address this question systematically. We derive a general functional form for the dependence of trophic interaction coefficients on trophically relevant quantitative traits of consumers and resources. The derived expression encompasses-and thus allows a unified comparison of-several functional forms previously proposed in the literature. Furthermore, we show how a community's, potentially low-dimensional, effective trophic niche space is related to its higher-dimensional phenotypic trait space. In this manner, we give ecological meaning to the notion of the "dimensionality of trophic niche space." Our framework implies a method for directly measuring this dimensionality. We suggest a procedure for estimating the relevant parameters from empirical data and for verifying that such data matches the assumptions underlying our derivation. © Springer Science+Business Media B.V. 2009.


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Stability and dynamical behavior in a lake-model and implications for regime shifts in real lakes

A modified abstract version of the Comprehensive Aquatic Simulation Model (CASM) is found to exhibit three types of folded bifurcations due to nutrient loading. The resulting bifurcation diagrams account for nonlinear dynamics such as regime shifts and cyclic changes between clear-water state and turbid state that have actually been observed in real lakes. In particular, pulse-perturbation simulations based on the model presented suggest that temporal behaviors of real lakes after biomanipulations can be explained by pulse-dynamics in complex ecosystems, and that not only the amplitude (manipulated abundance of organisms) but also the phase (timing) is important for restoring lakes by biomanipulation. Ecosystem management in terms of possible irreversible changes in ecosystems induced by regime shifts is also discussed. (c) 2007 Elsevier B.V All rights reserved.

The Movebank data model for animal tracking

Studies of animal movement are rapidly increasing as tracking technologies make it possible to collect more data of a larger variety of species. Comparisons of animal movement across sites, times, or species are key to asking questions about animal adaptation, responses to climate and land-use change. Thus, great gains can be made by sharing and exchanging animal tracking data. Here we present an animal movement data model that we use within the Movebank web application to describe tracked animals. The model facilitates data comparisons across a broad range of taxa, study designs, and technologies, and is based on the scientific questions that could be addressed with the data.

Treatment of estrogens and androgens in dairy wastewater by a constructed wetland system.

Constructed wetland systems (CWS) have been used as a low cost bio-filtration system to treat farm wastewater. While studies have shown that CWS are efficient in removing organic compounds and pathogens, there is limited data on the presence of hormones in this type of treatment system. The objective of this study was to evaluate the ability of the CWS to reduce estrogenic and androgenic hormone concentration in dairy wastewater. This was achieved through a year long study on dairy wastewater samples obtained froma surface flow CWS. Analysis of hormonal levels was performed using a solid phase extraction (SPE) sample clean-up method, combined with reporter gene assays (RGAs) which incorporate relevant receptors capable of measuring total estrogenic or androgenic concentrations as low as 0.24 ng L1 and 6.9 ng L1 respectively. Monthly analysis showed a mean removal efficiency for estrogens of 95.2%, corresponding to an average residual concentration of 3.2 ng L1 17b-estradiol equivalent (EEQ), below the proposed lowest observable effect concentration (LOEC) of 10 ng L1. However, for one month a peak EEQ concentration of 115 ng L1 was only reduced to 18.8 ng L1. The mean androgenic activity peaked at 360 ng L1 and a removal efficiency of 92.1% left an average residual concentration of 32.3 ng L1 testosterone equivalent (TEQ). The results obtained demonstrate that this type of CWS is an efficient system for the treatment of hormones in dairy wastewater. However, additional design improvements may be required to further enhance removal efficiency of peak hormone concentrations.

Haematite in Lateritic Soils Aids Groundwater Disinfection

Microbiologically contaminated water severely impacts public health in low-income countries, where treated water supplies are often inaccessible to much of the population. Groundwater represents a water source that commonly has better microbiological quality than surface water. A 2-month intensive flow and quality monitoring programme of a spring in a densely settled, unsewered parish of Kampala, Uganda, revealed the persistent presence of high chloride and nitrate concentrations that reflect intense loading of sewage in the spring’s catchment. Conversely, thermotolerant coliform bacteria counts in spring water samples remained very low outside of periods of intense rainfall. Laboratory investigations of mechanisms responsible for this behavior, achieved by injecting a pulse of H40/1 bacteriophage tracer into a column packed with locally derived granular laterite, resulted in near-total tracer adsorption. X-ray diffraction (XRD) analysis showed the laterite to consist predominantly of quartz and kaolinite, with minor amounts (<5%) of haematite. Batch studies comparing laterite adsorption capacity with a soil having comparable mineralogy, but with amorphous iron oxide rather than haematite, showed the laterite to have a significantly greater capacity to adsorb bacteriophage. Batch study results using pure haematite confirmed that its occurrence in laterite contributes substantially to micro-organism attenuation observed and serves to protect underlying groundwater.

Animal foraging from an individual perspective: an object orientated model

A model system, HOOFS (Hierarchical Object Orientated Foraging Simulator), has been developed to study foraging by animals in a complex environment. The model is implemented using an individual-based object-orientated structure. Different species of animals inherit their general properties from a generic animal object which inherits from the basic dynamic object class. Each dynamic object is a separate program thread under the control of a central scheduler. The environment is described as a map of small hexagonal patches, each with their own level of resources and a patch-specific rate of resource replenishment. Each group of seven patches (0th order) is grouped into a Ist order super-patch with seven nth order super-patches making up a n + 1th order super-patch for n up to a specified value. At any time each animal is associated with a single patch. Patch choice is made by combining the information on the resources available within different order patches and super-patches along with information on the spatial location of other animals. The degree of sociality of an animal is defined in terms of optimal spacing from other animals and by the weighting of patch choice based on social factors relative to that based on food availability. Information, available to each animal, about patch resources diminishes with distance from that patch. The model has been used to demonstrate that social interactions can constrain patch choice and result in a short-term reduction of intake and a greater degree of variability in the level of resources in patches. We used the model to show that the effect of this variability on the animal's intake depends on the pattern of patch replenishment. (C) 1998 Elsevier Science B.V. All rights reserved.</p>

Functional Complexity: The source of value in biodiversity.

Biodiversity may be seen as a scientific measure of the complexity of a biological system, implying an information basis. Complexity cannot be directly valued, so economists have tried to define the services it provides, though often just valuing the services of 'key' species. Here we provide a new definition of biodiversity as a measure of functional information, arguing that complexity embodies meaningful information as Gregory Bateson defined it. We argue that functional information content (FIC) is the potentially valuable component of total (algorithmic) information content (AIC), as it alone determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. Establishing substitutability is an essential foundation for valuation. From it, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and the production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science. © 2012 Elsevier B.V.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.