A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms

Disturbance‐mediated changes to boreal mammal spatial networks in industrializing landscapes

Funding: InnoTech Alberta. Grant Number: C2021000986; Alberta Innovates; Alberta Conservation Association; Petroleum Technology Alliance Canada. Grant Numbers: 17-ERPC-02, 18-ERPC-01, 19-ERPC-04; Algar Caribou Habitat Restoration Program. Grant Number: NXC-107980; Oil Sands Monitoring program; Natural Sciences and Engineering Research Council of Canada. Grant Numbers: RGPIN-2018–03958, Canada Research Chairs.Compound effects of anthropogenic disturbances on wildlife emerge through a complex network of direct responses and species interactions. Land‐use changes driven by energy and forestry industries are known to disrupt predator–prey dynamics in boreal ecosystems, yet how these disturbance effects propagate across mammal communities remains uncertain. Using structural equation modeling, we tested disturbance‐mediated pathways governing the spatial structure of multipredator multiprey boreal mammal networks across a landscape‐scale disturbance gradient within Canada's Athabasca oil sands region. Linear disturbances had pervasive direct effects, increasing site use for all focal species, except black bears and threatened caribou, in at least one landscape. Conversely, block (polygonal) disturbance effects were negative but less common. Indirect disturbance effects were widespread and mediated by caribou avoidance of wolves, tracking of primary prey by subordinate predators, and intraguild dependencies among predators and large prey. Context‐dependent responses to linear disturbances were most common among prey and within the landscape with intermediate disturbance. Our research suggests that industrial disturbances directly affect a suite of boreal mammals by altering forage availability and movement, leading to indirect effects across a range of interacting predators and prey, including the keystone snowshoe hare. The complexity of network‐level direct and indirect disturbance effects reinforces calls for increased investment in addressing habitat degradation as the root cause of threatened species declines and broader ecosystem change.Peer reviewe

Resources, mortality, and disease ecology: Importance of positive feedbacks between host growth rate and pathogen dynamics

This is an Accepted Manuscript of an article published by Taylor & Francis in Israel Journal of Ecology and Evolution in 2015, available online: http://www.tandfonline.com/10.1080/15659801.2015.1035508.Resource theory and metabolic scaling theory suggest that the dynamics of a pathogen within a host should strongly depend upon the rate of host cell metabolism. Once an infection occurs, key ecological interactions occur on or within the host organism that determine whether the pathogen dies out, persists as a chronic infection, or grows to densities that lead to host death. We hypothesize that, in general, conditions favoring rapid host growth rates should amplify the replication and proliferation of both fungal and viral pathogens. If a host population experiences an increase in mortality, to persist it must have a higher growth rate, per host, often reflecting greater resource availability per capita. We hypothesize that this could indirectly foster the pathogen, which also benefits from increased within-host resource turnover. We first bring together in a short review a number of key prior studies which illustrate resource effects on viral and fungal pathogen dynamics. We then report new results from a semi-continuous cell culture experiment with SHIV, demonstrating that higher mortality rates indeed can promote viral proliferation. We develop a simple model that illustrates dynamical consequences of these resource effects, including interesting effects such as alternative stable states and oscillatory dynamics. Our paper contributes to a growing body of literature at the interface of ecology and infectious disease epidemiology, emphasizing that host abundances alone do not drive community dynamics: the physiological state and resource content of infected hosts also strongly influence host-pathogen interactions

Escaping the extinction vortex: identifying factors affecting population performance and recovery in endangered Sierra Nevada bighorn sheep

An extinction vortex is one of the greatest threats to endangered species; when demographic, environmental, and genetic stochasticity interact with each other and with deterministic factors, such as habitat quality, to reinforce the demise of a small population. To successfully escape an extinction vortex and enable species recovery, all processes that affect endangered populations should be comprehensively assessed and incorporated into conservation plans. For my dissertation, I worked in conjunction with California Department of Fish and Game to develop a comprehensive research program to guide recovery efforts for federally endangered Sierra Nevada bighorn sheep, the rarest subspecies of mountain sheep in North America. I initiated a combination of demographic, habitat and genetic analyses to identify the stochastic and deterministic factors limiting the recovery of this subspecies, examine the relative and synergistic impacts of these factors on the performance of Sierra Nevada bighorn sheep, and the benefits of different management activities for stimulating recovery efforts. Just as the extinction vortex predicts, I found that small populations of Sierra Nevada bighorn sheep were driven by a number of stochastic and deterministic processes. Demographic, habitat, climate, predation, and genetic factors operated singly and in concert to shape the overall viability of this subspecies. The interaction of factors led to atypical demographic patterns that deviated from theoretical expectations and increased extinction risk. To alleviate extinction processes, I found that management strategies must be tailored to population-specific dynamics, targeting those vital rates and ecological drivers which have the greatest power to increase performance. Results from this study have elucidated critical aspects of Sierra Nevada bighorn sheep ecology, provided a recovery strategy for this subspecies, and supplied new quantitative tools for examining the dynamics of small and endangered populations. Ultimately, this work offers an example of assessing population viability, not in terms of probability of extinction, but in terms of quantifying conservation measures that will alleviate extinction dynamics and achieve endangered species recovery goals

Models for an Ecosystem Approach to Fisheries

This document is one outcome from a workshop held in Gizo in October 2010 attended by 82 representatives from government, NGO's private sector, and communities. The target audience for the document is primarily organizations planning to work with coastal communities of Solomon Islands to implement Community-Based Resource Management (CBRM). It is however also envisaged that the document will serve as a reference for communities to better understand what to expect from their partners and also for donors, to be informed about agreed approaches amongst Solomon Islands stakeholders. This document does not attempt to summarize all the outcomes of the workshop; rather it focuses on the Solomon Islands Coral Triangle Initiative (CTI) National Plan of Action (NPoA): Theme 1: Support and implementation of CBRM and specifically, the scaling up of CBRM in Solomon Islands. Most of the principles given in this document are derived from experiences in coastal communities and ecosystems as, until relatively recently, these have received most attention in Solomon Islands resource management. It is recognized however that the majority of these principles will be applicable to both coastal and terrestrial initiatives. This document synthesizes information provided by stakeholders at the October 2010 workshop and covers some basic principles of engagement and implementation that have been learned over more than twenty years of activities by the stakeholder partners in Solomon Islands. The document updates and expands on a summary of guiding principles for CBRM which was originally prepared by the Solomon Islands Locally Managed Marine Area Network (SILMMA) in 2007

Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries using Sparse Linear Regression

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the interactions between species from sequence data. Any algorithm for inferring species interactions must overcome three obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct "keystone species", Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome

Context Dependency of Community Dynamics: Predator-Prey Interactions Under Ecological Disturbances

Numerous studies have focused on the drivers of diversity and stability of communities, especially under global change. However, multi-dimensionality of ecosystems due to biotic components (e.g predation, competition and adaptive dynamics) and abiotic factors (e.g. disturbances, resource dynamics and their distinct attributes) cause context-dependent outcomes and challenge the predictions. There are still controversies around complex community dynamics under varying regimes, however, finding mechanistical explanations will illuminate the fate of multispecies assemblages. Using model microbial communities, consisting of bacterial prey and protist predator, combined with simulation modelling and advanced statistics, this thesis investigated the impact of imposed disturbances (i.e. increased dilution rates that simulate density-independent mortality as press or pulse disturbances) (i) on transient recovery dynamics of a simple microbial food web, and (ii) on bacterial abundance, diversity and community structure in the absence or presence of a protist predator. In addition, this thesis questioned the impacts of species interactions and rapid trait shifts, as a response to predation and competition, on the community dynamics and stability. Our results revealed that the predator suffered more from disturbances over longer time periods. Reduced predation pressure caused a transient phase of prey release during and even after disturbances. Recovery time depended on the strength and duration of disturbances, however, coupling to an alternative resource increased the chance of fast recovery and stabilized the communities. In multi-species prey communities, bacterial abundance, diversity, and community composition were more affected by predation than by the disturbances and resource dynamics. Predator abundance, on the other hand, was strongly affected by the type of disturbance imposed. Importantly, community attributes had differential sensitivities, as reflected by their different response and recovery dynamics. Prey community dynamics varied more temporally andwere less stable under predation stress, while prey diversity increased significantly. Predation rapidly induced anti-predation traits, which altered population dynamics of both prey and predator. More importantly, predator and the resistant prey, in turn, elevated the number of direct cause-effect relationships between the community members. Our findings are not limited to the studied system and can be used to understand the dynamic response and recovery potential of many natural predator-prey or host-pathogen systems. They can be used as a base for future studies to illuminate the debates on the future communities.:Summary Zusammenfassung 1 Scope and Outline 2 General Introduction 2.1 Context dependency of community dynamics 2.2 Ecological disturbances 2.2.1 Transient dynamics and stability 2.2.2 Catastrophic shifts 2.3 Species interactions and evolutionary dynamics under environmental change 2.3.1 Species interactions and coexistence 2.4 Eco-evolutionary dynamics 2.5 Community assembly mechanisms 2.6 Dealing with complexities 2.6.1 Microbial model systems as a tool in ecology 2.6.2 Correlation, causation and the future of predictions 2.7 Aims of this study 3 Community Dynamics under Disturbances 3.1 Transient recovery dynamics of a predator-prey system 4 Interactions of Community Drivers 4.1 Interactions between predation and disturbances shape prey communities 5 Species Interactions and Evolutionary Dynamics Shaping Communities 5.1 Summary 5.2 Introduction 5.2.1 Predator-Prey Dynamics and Community Stability 5.2.2 Causal inferences 5.3 Aim of the study 5.4 Methods 5.4.1 Organisms 5.4.2 Microcosm experiments and estimation of species abundances 5.4.3 Statistical analysis 5.5 Results 5.5.1 Community dynamics 5.5.2 Dynamics of prey diversity and community stability 5.5.3 Causal links between the species dynamics 5.6 Discussion 5.7 Synopsis 6 General Discussion 6.1 Communities under disturbances: Predator{ prey dynamics 6.2 Temporal species dynamics and community assembly Synthesis and Outlook 7.1 Increasing complexity of species interactions 7.2 Going further from causal links 7.3 Metacommunities References 8 Appendix 8.1 Declaration of the authorship 8.2 Author contributions of published articles 8.3 List of publications and conference contributions 8.4 Acknowledgments 8.5 Supplementary material for Chapter 3 8.6 Supplementary material for Chapter 4 8.7 Supplementary material for Chapter

The influence of dispersal on a predator-prey system with two habitats

Dispersal between different habitats influences the dynamics and stability of populations considerably. Furthermore, these effects depend on the local interactions of a population with other species. Here, we perform a general and comprehensive study of the simplest possible system that includes dispersal and local interactions, namely a 2-patch 2-species system. We evaluate the impact of dispersal on stability and on the occurrence of bifurcations, including pattern forming bifurcations that lead to spatial heterogeneity, in 19 different classes of models with the help of the generalized modelling approach. We find that dispersal often destabilizes equilibria, but it can stabilize them if it increases population losses. If dispersal is nonrandom, i.e. if emigration or immigration rates depend on population densities, the correlation of stability with migration rates is positive in part of the models. We also find that many systems show all four types of bifurcations and that antisynchronous oscillations occur mostly with nonrandom dispersal

Scale and Contingency in Plant Demography: Quantitative Approaches and Inference

Ecologists have long recognized that patterns measured in nature often depend upon the context in which they are observed and the scale at which they are observed. When studying plant populations, the role of scale and contingency becomes crucial. Thinking about a plant community as a system is essential as populations of plants are centered within a network that influences their dynamics in direct and indirect ways. Plant populations are inherently scale-dependent because they have properties as a group that can be independent of their properties as individual stems. Although the challenge of interpreting population patterns in the face of contingency and scale has been addressed conceptually, there has been less success in applying those concepts to observational and experimental studies. This dissertation addresses the challenges of modeling the demographic dynamics of a forest understory herb, Eurybia chlorolepis (Asteraceae) or mountain aster. The study population consisted of twenty patches containing between 20 and 70 individual stems in each patch. These patches spanned three sites within the Indian Camp Creek watershed in the Cosby Ranger district of Great Smoky Mountains National Park. Plants in the forest understory in this dense old-growth forest are influenced by a myriad of biotic and abiotic components of the community: light, soil characteristics, other plant species, herbivores, pollinators, seed predators, and the feet of bears. This dissertation shows that the mechanisms that influence sexual reproduction of this plant are structured almost entirely on the stem-to-stem scale, indicating little coarse-scale influence of the environment over sexual reproduction. The use of a Bayesian learning network showed that the environmental influences (soil in particular) operated most importantly in the transition from juvenile stage to adult stage. Taken together, these analyses indicate that the coarse-environtment (such as gaps, soil profiles, soil moisture, and the presence of other plants) dictates where E. chlorolepis becomes reproductive, while the success of that reproduction is dictated by mechanisms operating between individual stems

Temperature-dependence of minimum resource requirements alters competitive hierarchies in phytoplankton

Resource competition theory is a conceptual framework that provides mechanistic insights into competition and community assembly of species with different resource requirements. However, there has been little exploration of how resource requirements depend on other environmental factors, including temperature. Changes in resource requirements as influenced by environmental temperature would imply that climate warming can alter the outcomes of competition and community assembly