Ecological communities in variable environments : dynamics and diversity under coloured environmental stochasticity

While environmental variation is an ubiquitous phenomenon in the natural world which has for long been appreciated by the scientific community recent changes in global climatic conditions have begun to raise consciousness about the economical, political and sociological ramifications of global climate change. Climate warming has already resulted in documented changes in ecosystem functioning, with direct repercussions on ecosystem services. While predicting the influence of ecosystem changes on vital ecosystem services can be extremely difficult, knowledge of the organisation of ecological interactions within natural communities can help us better understand climate driven changes in ecosystems. The role of environmental variation as an agent mediating population extinctions is likely to become increasingly important in the future. In previous studies population extinction risk in stochastic environmental conditions has been tied to an interaction between population density dependence and the temporal autocorrelation of environmental fluctuations. When populations interact with each other, forming ecological communities, the response of such species assemblages to environmental stochasticity can depend, e.g., on trophic structure in the food web and the similarity in species-specific responses to environmental conditions. The results presented in this thesis indicate that variation in the correlation structure between species-specific environmental responses (environmental correlation) can have important qualitative and quantitative effects on community persistence and biomass stability in autocorrelated (coloured) environments. In addition, reddened environmental stochasticity and ecological drift processes (such as demographic stochasticity and dispersal limitation) have important implications for patterns in species relative abundances and community dynamics over time and space. Our understanding of patterns in biodiversity at local and global scale can be enhanced by considering the relevance of different drift processes for community organisation and dynamics. Although the results laid out in this thesis are based on mathematical simulation models, they can be valuable in planning effective empirical studies as well as in interpreting existing empirical results. Most of the metrics considered here are directly applicable to empirical data.

Field-tunable stochasticity in the magnetization reversal of a cylindrical nanomagnet

The nature of magnetization reversal in an isolated cylindrical nanomagnet has been studied employing time-resolved magnetoresistance measurement. We find that the reversal mode is highly stochastic, occurring either by multimode or single-step switching. Intriguingly, the stochasticity was found to depend on the alignment of the driving magnetic field to the long axis of the nanowires, where predominantly multimode switching gives way to single-step switching behavior as the field direction is rotated from parallel to transverse with respect to the nanowire axis.

A stochasticity threshold in holography and the instability of AdS

We give strong numerical evidence that a self-interacting probe scalar field in AdS, with only a few modes turned on initially, will undergo fast thermalization only if it is above a certain energetic threshold. Below the threshold the energy stays close to constant in a few modes for a very long time instead of cascading quickly. This indicates the existence of a Strong Stochasticity Threshold (SST) in holography. The idea of SST is familiar from certain statistical mechanical systems, and we suggest that it exists also in AdS gravity. This would naturally reconcile the generic nonlinear instability of AdS observed by Bizon and Rostworowski, with the Fermi-Pasta-Ulam-Tsingou-like quasiperiodicity noticed recently for some classes of initial conditions. We show that our simple setup captures many of the relevant features of the full gravity-scalar system.

HPV clearance and the neglected role of stochasticity.

Clearance of anogenital and oropharyngeal HPV infections is attributed primarily to a successful adaptive immune response. To date, little attention has been paid to the potential role of stochastic cell dynamics in the time it takes to clear an HPV infection. In this study, we combine mechanistic mathematical models at the cellular level with epidemiological data at the population level to disentangle the respective roles of immune capacity and cell dynamics in the clearing mechanism. Our results suggest that chance-in form of the stochastic dynamics of basal stem cells-plays a critical role in the elimination of HPV-infected cell clones. In particular, we find that in immunocompetent adolescents with cervical HPV infections, the immune response may contribute less than 20% to virus clearance-the rest is taken care of by the stochastic proliferation dynamics in the basal layer. In HIV-negative individuals, the contribution of the immune response may be negligible.

Complex pattern of genetic structuring in the Atlantic salmon (Salmo salar L.) of the River Foyle system in northwest Ireland: disentangling the evolutionary signal from population stochasticity

Little is known about the microevolutionary processes shaping within river population genetic structure of aquatic organisms characterized by high levels of homing and spawning site fidelity. Using a microsatellite panel, we observed complex and highly significant levels of intrariver population genetic substructure and Isolation-by-Distance, in the Atlantic salmon stock of a large river system. Two evolutionary models have been considered explaining mechanisms promoting genetic substructuring in Atlantic salmon, the member-vagrant and metapopulation models. We show that both models can be simultaneously used to explain patterns and levels of population structuring within the Foyle system. We show that anthropogenic factors have had a large influence on contemporary population structure observed. In an analytical development, we found that the frequently used estimator of genetic differentiation, F-ST, routinely underestimated genetic differentiation by a factor three to four compared to the equivalent statistic Jost's D-est (Jost 2008). These statistics also showed a near-perfect correlation. Despite ongoing discussions regarding the usefulness of "adjusted" F-ST statistics, we argue that these could be useful to identify and quantify qualitative differences between populations, which are important from management and conservation perspectives as an indicator of existence of biologically significant variation among tributary populations or a warning of critical environmental damage.

Ecological dynamics of extinct species in empty habitat networks. 1. The role of habitat pattern and quantity, stochasticity and dispersal

We examined a remnant host plant (Primula veris L.) habitat network that was last inhabited by the rare butterfly Hamearis lucina L. in north Wales in 1943, to assess the relative contribution of several spatial parameters to its regional extinction. We first examined relationships between P. veris characteristics and H. lucina eggs in surviving H. lucina populations, and used these to predict the suitability and potential carrying capacity of the habitat network in north Wales. This resulted in an estimate of roughly 4500 eggs (ca 227 adults). We developed a discrete space, discrete time metapopulation model to evaluate the relative contribution of dispersal distance, habitat and environmental stochasticity as possible causes of extinction. We simulated the potential persistence of the butterfly in the current network as well as in three artificial (historical and present) habitat networks that differed in the quantity (current and X3) and fragmentation of the habitat (current and aggregated). We identified that reduced habitat quantity and increased isolation would have increased the probability of regional extinction, in conjunction with environmental stochasticity and H. lucina's dispersal distance. This general trend did not change in a qualitative manner when we modified the ability of dispersing females to stay in, and find suitable habitats (by changing the size of the grid cells used in the model). Contrary to most metapopulation model predictions, system persistence declined with increasing migration rate, suggesting that the mortality of migrating individuals in fragmented landscapes may pose significant risks to system-wide persistence. Based on model predictions for the present landscape we argue that a major programme of habitat restoration would be required for a re-established metapopulation to persist for > 100 years.

Declining survival rates in a reintroduced population of the Mauritius kestrel: evidence for non-linear density dependence and environmental stochasticity

1. We studied a reintroduced population of the formerly critically endangered Mauritius kestrel Falco punctatus Temmink from its inception in 1987 until 2002, by which time the population had attained carrying capacity for the study area. Post-1994 the population received minimal management other than the provision of nestboxes. 2. We analysed data collected on survival (1987-2002) using program MARK to explore the influence of density-dependent and independent processes on survival over the course of the population's development. 3.We found evidence for non-linear, threshold density dependence in juvenile survival rates. Juvenile survival was also strongly influenced by climate, with the temporal distribution of rainfall during the cyclone season being the most influential climatic variable. Adult survival remained constant throughout. 4. Our most parsimonious capture-mark-recapture statistical model, which was constrained by density and climate, explained 75.4% of the temporal variation exhibited in juvenile survival rates over the course of the population's development. 5. This study is an example of how data collected as part of a threatened species recovery programme can be used to explore the role and functional form of natural population regulatory processes. With the improvements in conservation management techniques and the resulting success stories, formerly threatened species offer unique opportunities to further our understanding of the fundamental principles of population ecology.

Dynamic behavior, stochasticity and enviromental heterogeneity in Tribolium castaneum

In this study we analyzed the influence of demographic parameters on the population dynamics of Tribolium castaneum, combining empiricism and population theory to analyze the different effects of environmental heterogeneity, by employing Ricker models, designed to study a two-patch system taking into account deterministic and stochastic analysis. Results were expressed by bifurcation diagrams and stochastic simulations. Dynamic equilibrium was widely investigated with results suggesting specific parametric spaces in response to environmental heterogeneity and migration. Population equilibrium patterns, synchrony and persistence in T. castaneum were discussed

Interlinked dual-time feedback loops can enhance robustness to stochasticity and persistence of memory.

Multiple interlinked positive feedback loops shape the stimulus responses of various biochemical systems, such as the cell cycle or intracellular Ca2+ release. Recent studies with simplified models have identified two advantages of coupling fast and slow feedback loops. This dual-time structure enables a fast response while enhancing resistances of responses and bistability to stimulus noise. We now find that (1) the dual-time structure similarly confers resistance to internal noise due to molecule number fluctuations, and (2) model variants with altered coupling, which better represent some specific biochemical systems, share all the above advantages. We also develop a similar bistable model with coupling of a fast autoactivation loop to a slow loop. This model's topology was suggested by positive feedback proposed to play a role in long-term synaptic potentiation (LTP). The advantages of fast response and noise resistance are also present in this autoactivation model. Empirically, LTP develops resistance to reversal over approximately 1h . The model suggests this resistance may result from increased amounts of synaptic kinases involved in positive feedback.

Runup variability due to time dependence and stochasticity in the beach profiles: two extreme cases of the Spanish coast

Equations for extreme runup worked out from several experimental studies are compared. Infragraviatory oscillations dominate the swash in a dissipative state but not in intermediate - reflective states. Therefore two kinds of equation depending on either significant wave height, H-0, or the Iribarren number, xi(0), should be used. Through a sand bed physical model with a uniform sand bed slope, equations are proposed for both beach states, and results are compared with precedent field and physical model experiments. Once the equations are chosen, the time-longshore variability in a medium - long term time scale of the foreshore slope is evaluated in two extreme cases relating to the Spanish coast. The Salinas beach on the North coast (Bay of Biscay) displayed a permanent dissipative beach state with small variations in the beach foreshore slope both along the shore and in time, so foreshore slope deviations in a medium-long term period were irrelevant and extreme runup is predicted with the wave height worked out from the design return period. Peniscola beach on the East coast (Mediterranean sea) displayed an intermediate state. If only time variations are analysed, variations in determining extreme runup are irrelevant. In contrast, significant differences were found when the longshore variations were studied in this Mediterranean beach.

Population dynamics, demographic stochasticity, and the evolution of cooperation

A basic evolutionary problem posed by the Iterated Prisoner’s Dilemma game is to understand when the paradigmatic cooperative strategy Tit-for-Tat can invade a population of pure defectors. Deterministically, this is impossible. We consider the role of demographic stochasticity by embedding the Iterated Prisoner’s Dilemma into a population dynamic framework. Tit-for-Tat can invade a population of defectors when their dynamics exhibit short episodes of high population densities with subsequent crashes and long low density periods with strong genetic drift. Such dynamics tend to have reddened power spectra and temporal distributions of population size that are asymmetric and skewed toward low densities. The results indicate that ecological dynamics are important for evolutionary shifts between adaptive peaks.

Generalized flows, intrinsic stochasticity, and turbulent transport

The study of passive scalar transport in a turbulent velocity field leads naturally to the notion of generalized flows, which are families of probability distributions on the space of solutions to the associated ordinary differential equations which no longer satisfy the uniqueness theorem for ordinary differential equations. Two most natural regularizations of this problem, namely the regularization via adding small molecular diffusion and the regularization via smoothing out the velocity field, are considered. White-in-time random velocity fields are used as an example to examine the variety of phenomena that take place when the velocity field is not spatially regular. Three different regimes, characterized by their degrees of compressibility, are isolated in the parameter space. In the regime of intermediate compressibility, the two different regularizations give rise to two different scaling behaviors for the structure functions of the passive scalar. Physically, this means that the scaling depends on Prandtl number. In the other two regimes, the two different regularizations give rise to the same generalized flows even though the sense of convergence can be very different. The “one force, one solution” principle is established for the scalar field in the weakly compressible regime, and for the difference of the scalar in the strongly compressible regime, which is the regime of inverse cascade. Existence and uniqueness of an invariant measure are also proved in these regimes when the transport equation is suitably forced. Finally incomplete self similarity in the sense of Barenblatt and Chorin is established.

The role of stochasticity in an information-optimal neural population code

In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise, in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and; hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.