Soil δ13C and δ15N baselines clarify biogeographic heterogeneity in isotopic discrimination of European badgers (Meles meles)

Isotopic techniques have been used to study phenomena in the geological, environmental, and ecological sciences. For example, isotopic values of multiple elements elucidate the pathways energy and nutrients take in the environment. Isoscapes interpolate isotopic values across a geographical surface and are used to study environmental processes in space and time. Thus, isoscapes can reveal ecological shifts at local scales, and show distribution thresholds in the wider environment at the macro-scale. This study demonstrates a further application of isoscapes, using soil isoscapes of 13C/12C and 15N/14N as an environmental baseline, to understand variation in trophic ecology across a population of Eurasian badgers (Meles meles) at a regional scale. The use of soil isoscapes reduced error, and elevated the statistical signal, where aggregated badger hairs were used, and where individuals were identified using genetic microarray analysis. Stable isotope values were affected by land-use type, elevation, and meteorology. Badgers in lowland habitats had diets richer in protein and were adversely affected by poor weather conditions in all land classes. It is concluded that soil isoscapes are an effective way of reducing confounding biases in macroscale, isotopic studies. The method elucidated variation in the trophic and spatial ecology of economically important taxa at a landscape level. These results have implications for the management of badgers and other carnivores with omnivorous tendencies in heterogeneous landscapes.

Variable signatures of selection despite conserved recombination landscapes early in speciation

Recently diverged taxa often exhibit heterogeneous landscapes of genomic differentiation, characterized by regions of elevated differentiation on an otherwise homogeneous background. While divergence peaks are generally interpreted as regions responsible for reproductive isolation, they can also arise due to background selection, selective sweeps unrelated to speciation, and variation in recombination and mutation rates. To investigate the association between patterns of recombination and landscapes of genomic differentiation during the early stages of speciation, we generated fine-scale recombination maps for six southern capuchino seedeaters (Sporophila) and two subspecies of White Wagtail (Motacilla alba), two recent avian radiations in which divergent selection on pigmentation genes has likely generated peaks of differentiation. We compared these recombination maps to those of Collared (Ficedula albicollis) and Pied Flycatchers (Ficedula hypoleuca), non-sister taxa characterized by moderate genomic divergence and a heterogenous landscape of genomic differentiation shaped in part by background selection. Although recombination landscapes were conserved within all three systems, we documented a weaker negative correlation between recombination rate and genomic differentiation in the recent radiations. All divergence peaks between capuchinos, wagtails, and flycatchers were located in regions with lower-than-average recombination rates, and most divergence peaks in capuchinos and flycatchers fell in regions of exceptionally reduced recombination. Thus, co-adapted allelic combinations in these regions may have been protected early in divergence, facilitating rapid diversification. Despite largely conserved recombination landscapes, divergence peaks are specific to each focal comparison in capuchinos, suggesting that regions of elevated differentiation have not been generated by variation in recombination rate alone.

An integrative approach to mosquito dynamics reveals differences in people's everyday experiences of mosquitoes

Urban environments are heterogeneous landscapes of social and environmental features, with important consequences for human-nature entanglements, such as that of mosquito-borne disease. Investigations into this intra-urban heterogeneity in mosquito dynamics find conflicting results, likely due to the complex socio-ecological interactions and the importance of place-based context. Integrative research, which synthesizes multiple disciplines and epistemologies, can help place ecological results into their social context to explore these place-based differences. Here, we develop an integrative approach to understanding spatial patterns of mosquito burdens in urban systems by combining entomological surveys, semi-structured interviews, and sketch maps. Although we found no evidence for a difference in mosquito abundance across an urban gradient, there were differences in individuals' everyday experiences with mosquitoes. These differences were mediated by how individuals moved through public space and their vulnerability to hazards in these spaces. This example of integrative research illustrates what can be gained from the inclusion of multiple epistemologies, particularly for research in socio-ecological systems.

Mechanistic movement models reveal ecological drivers of tick-borne pathogen spread

Identifying ecological drivers of tick-borne pathogen spread has great value for tick-borne disease management. However, theoretical investigations into the consequences of host movement behaviour on pathogen spread dynamics in heterogeneous landscapes remain limited because spatially explicit epidemiological models that incorporate more realistic mechanisms governing host movement are rare. We built a mechanistic movement model to investigate how the interplay between multiple ecological drivers affects the risk of tick-borne pathogen spread across heterogeneous landscapes. We used the model to generate simulations of tick dispersal by migratory birds and terrestrial hosts across theoretical landscapes varying in resource aggregation, and we performed a sensitivity analysis to explore the impacts of different parameters on the infected tick spread rate, tick infection prevalence and infected tick density. Our findings highlight the importance of host movement and tick population dynamics in explaining the infected tick spread rate into new regions. Tick infection prevalence and infected tick density were driven by predictors related to the infection process and tick population dynamics, respectively. Our results suggest that control strategies aiming to reduce tick burden on tick reproduction hosts and encounter rate between immature ticks and pathogen amplification hosts will be most effective at reducing tick-borne disease risk.

Upscaling Tree Demography to Heterogenous Landscapes Using Models and Remote Sensing

Tree demography is foundational to ecology and conservation, from mass tree die-offs to forest recovery. Plot-level studies of tree demography, including field measurements of tagged individuals, have been fundamental for developing ecological theory and forest management strategies. However, the limited spatial extent of field plots impedes generalizing plot-level models for spatial predictions across heterogeneous landscapes. Novel high-spatial resolution remote sensing imagery has opened the possibility for measuring tree demographic rates with continuous spatial coverage at landscape to regional extents. Remote sensing derived measurements could address pressing research questions, including disentangling causes of high variation in natural regeneration across secondary forest landscapes. Despite the promise of high-spatial resolution imagery for ecology, applying these data to ecological questions will require novel modeling approaches that can account for large amounts of spatial data that often include hierarchical structure. In this thesis, I apply high-resolution remote sensing to upscale tree demography at landscape scales, and provide guidelines for ecologists seeking to parametrize spatially explicit models for neighbor interactions by combining field data, high-resolution remote sensing, and Bayesian quantitative methods. Chapter 1 demonstrates how high-spatial resolution remote sensing can help improve predictions of tree recruitment at the landscape scale. This chapter is the first step towards new support tools that inform restoration projects about where and which species will regenerate naturally in agricultural landscapes. Chapter 2 addresses how to optimize neighbor interaction models using the Hamiltonian Monte Carlo algorithm. I demonstrate how ragged matrices could solve data storage inefficiencies associated with the neighbor interaction models' pairwise structure. I also provide code for a model parametrization that solves a sampling pathology associated with high correlation in hierarchical structures and an overview of metrics to assess when this hierarchical structure pathology is present. Chapter 3 explores the influence of biophysical and anthropogenic drivers on tree mortality in agricultural landscapes using high-resolution remote sensing data. The results suggest that accessibility and land management are core factors that could be managed to prevent the mortality of agricultural trees. Educational initiatives and new policies that address anthropogenic factors could be the answer to reduce agricultural tree loss. Overall, this thesis brings together Bayesian statistical methods with novel high-resolution remote sensing to overcome the spatial limitation of field measurements and produce spatial predictions and inference on drivers of tree demography across heterogeneous landscapes.