An Evaluation of Different Partitioning Strategies for Bayesian Estimation of Species Divergence Times

This work was supported by UCL Impact studentship to K.A.; and Biotechnological and Biological Sciences Research Council (BBSRC) [BB/N000609/1 to Z.Y.]

New mathematical foundations for AI and Alife: Are the necessary conditions for animal consciousness sufficient for the design of intelligent machines?

Rodney Brooks' call for 'new mathematics' to revitalize the disciplines of artificial intelligence and artificial life can be answered by adaptation of what Adams has called 'the informational turn in philosophy' and by the novel perspectives that program gives into empirical studies of animal cognition and consciousness. Going backward from the necessary conditions communication theory imposes on cognition and consciousness to sufficient conditions for machine design is, however, an extraordinarily difficult engineering task. The most likely use of the first generations of conscious machines will be to model the various forms of psychopathology, since we have little or no understanding of how consciousness is stabilized in humans or other animals

RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.]

ECOLOGICAL SIGNIFICANCE OF NITRIFIER AND DENITRIFIER SPATIAL PATTERNS IN THREE ARCTIC ECOSYSTEMS

Owing to spatial variability of soil properties, microbial communities and their functional role in biogeochemical processes may also vary across multiple spatial scales. Soil and microbial spatial heterogeneity has been studied in various tropical and temperate ecosystems yet no information is available from Arctic permafrost ecosystems. These ecosystems represent a significant proportion of global land mass and contain about one fourth of total soil carbon pool. Soil microbial N transformations such as nitrification and denitrification have significant implications for N availability and N loss in nutrient-limited Arctic ecosystems. This study aims to elucidate 1) the spatial variability of soil attributes and the overall microbial communities 2) the spatial structure of ammonia oxidizer and denitrifier abundance and their activities, and 3) relationships among microbial communities, functional processes, and soil attributes in three Arctic Cryosolic ecosystems. The results show that despite challenging climatic conditions and the regular occurrence of cryopedogenic processes, soil properties and microbial abundance are highly spatially dependent and their spatial autocorrelation is consistent within and between the ecohabitats. Despite similar abundances, the zone of spatial autocorrelation is substantially smaller than other ecosystems. The correlations between moisture content and other soil attributes in Arctic are considerably higher than temperate agricultural and tropical grassland soils, suggesting the critical role of moisture in Arctic soil ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially dependent. Functional groups were spatially structured within 4 m whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1 m) by moisture and total organic carbon content whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1-10 m) and large (10-100 m) scales. Denitrifier functional groups and potential denitrification were spatially autocorrelated within a scale of 5 m. Soil moisture, organic carbon and nitrogen content were the predominant driving factors with nirK abundance also correlated to potential denitrification. This is the first study to report high spatial dependence of soil properties, overall microbial, ammonia oxidizing, and denitrifying communities, and functional processes in Canadian Arctic. It disentangles the associations among the aforementioned parameters to identify the key controls on nitrification and denitrification in Cryosolic ecosystems

Archaeal and bacterial ammonia-oxidisers in soil : the quest for niche specialisation and differentiation

Peer reviewedPublisher PD

The role of seed attributes in eastern gray squirrel foraging

Seed attributes are important predictors of rodent foraging behaviors. I examined the role of seed attributes in eastern gray squirrel (Sciurus carolinensis) foraging behavior from an evolutionary, economic, ecological and biochemical perspective. From an evolutionary perspective (chapter 2), I found that squirrel foraging behaviors are influenced by a combination of phylogenetically conserved and evolutionarily labile seed traits, which supports a diffuse coevolutionary relationship between hardwood trees and squirrels and provides indirect evidence supporting the Janzen-Connell and handling time hypotheses. From an economic perspective (chapter 3), I found that eastern gray squirrels are homogenous with respect to their preferences for seed attributes, which is likely due to natural selection favoring caching of specific seeds in the fall. I also provide evidence that squirrels trade between 3 attributes when selecting seeds for caching, which results in a variety of seed types being cached. In contrast, squirrels trade between 2 attributes when selecting seeds for consumption, which leads to fewer seed types being consumed in the fall. From an ecological context perspective (chapter 4), I provide evidence of seed traits interacting with relative seed availability to predict caching. Specifically, when seeds of different caching value (i.e., utility) were paired, relative frequency of availability played a minimal role in predicting seed caching. In contrast when seeds of similar caching utility were paired, relative frequency of availability significantly influenced probability of seed selection for caching. From a biochemical perspective (chapter 5), I identified biochemical and anatomical changes at the cellular level associated with radicle dormancy that serve as a signal of lack of dormancy to eastern gray squirrels. In combination, my dissertation chapters support the existence of complex reciprocal evolutionary effects between hardwood trees and eastern gray squirrels

The genes must flow: using movement ecology to understand connectivity of Mojave desert tortoise (Gopherus agassizii) populations in altered landscapes

Maintaining historic connectivity across animal populations is important to ensure a species can persist into the future. Human infrastructure and activities often fragment habitat, so understanding how connectivity functions is important in mitigation efforts. Connectivity arises from the movement of individuals within and between populations; understanding the movement ecology of a species can provide crucial information in how to best manage populations to maintain gene flow across a landscape. The Mojave desert tortoise (Gopherus agassizii) is a threatened species of the southwestern United States that historically had range-wide genetic connectivity. Human activity has and continues to alter and fragment tortoise habitat and maintaining/restoring connectivity across the range has been identified as an important conservation goal. In this work, I study the movement ecology of Mojave desert tortoises to understand how natural and anthropogenic features contribute to patterns of connectivity in the species. Corridors are important areas of a landscape that allow movement of animals between population centers through areas of unsuitable habitat. Due to assumed modest dispersal capabilities of the species, tortoises have been classified as corridor-dwellers that primarily rely on overlapping home ranges within an area for gene flow through a corridor. I studied tortoise movement selection and home ranges to understand what delineates both natural corridors through mountain passes and artificial corridors of suitable habitat left on the landscape after construction of utility-scale solar installations. Tortoises avoided areas of high slope and low perennial vegetation cover, avoided moving near low-density roads, and traveled along linear barriers. Results suggested that corridors through mountain passes can function differently in allowing tortoise movement, supporting prior findings using genetic differences. Artificial corridors created with fencing may not function the same way as natural corridors as a result of alteration of movement behavior. Although tortoises will avoid certain features such as roads, they will still interact with them. To better understand how anthropogenic and natural features alter tortoise movement behavior, I studied fine-scale tortoise movements using Hidden Markov movement models. My findings suggested that tortoises may respond to the same anthropogenic features (e.g. paved roads) differently depending on the context. Tortoises also alter movement in disturbed areas such as those with off-highway vehicle recreation or wildfire scars, suggesting that these disturbances degrade tortoise habitat. Using simulations of tortoise movement, I show that the behavioral responses to these disturbances may alter how tortoises are distributed on the landscape. Describing the long-term space use of individuals is key to understanding how genetic information flows across the landscape. Using historic and contemporary telemetry datasets (4,861 years of data from 950 tortoises), I related long-term site fidelity and dispersal in desert tortoises to intrinsic (size and sex) and extrinsic (seasonal precipitation) covariates. Tortoises display high site fidelity, though this fidelity is altered by seasonal precipitation and sex. Dispersal is more likely to occur in smaller tortoises and in years with high winter but low summer precipitation or years with low winter but high summer precipitation. I forecast future connectivity across the Ivanpah valley area with an agent-based model to estimate how future precipitation may influence connectivity by altering dispersal propensity. I found no differences in connectivity across emission scenarios, though other anthropogenic stressors will likely play a role in the future of connectivity in this species. This work provides insight into how tortoise movement at different spatial and temporal scales interact with habitat features and disturbances to alter connectivity of tortoise populations