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As more emphasis is put on biodiversity conservation, how best to select a system of protected areas for wildlife conservation is an issue of great importance. There is a rich economics literature on the reserve site selection problem. However, most economic studies assume the independence of risks that affect wildlife species, leaving the issue of spatially correlated risk largely unexplored. This study contributes to the literature in twoaspects. First, this study incorporates spatially correlated risk, into a reserve site selection model. And second, this study incorporates heterogeneous spatial risk, in the context of land development risk in Virginia, both with and without a budget constraint. To evaluate the significance of spatially correlated risk in conservation design, I apply the reserve site selection model to a Virginia landscape. In a basic setting, a hazard is introduced which is allowed to spread to adjacent land parcels, where I investigate the impact of spatially correlated risk at three spatial scales: one-county, four-county, and state-level. Optimal reserve designs are characterized by similar spatial patterns indicating that spatially correlated risk plays an important role in the selection of parcels for reserve. Specifically, as spatially correlated risk increases, I find that, in general, reserve connectivity decreases. I also examine a setting with heterogeneous risk and observe similar patterns in the optimal reserve design. I find that the reserve becomes more dispersed in higher risk areas primarily. Finally, I explore the tradeoffs between species protection and budget constraints in the presence of heterogeneous spatial risk. All comparative statics indicate that spatial correlated risk plays an important role in conservation reserve design. / Master of Science

Nesting and early life is a period of high mortality for many turtle species, so understanding how turtles select nest sites, and how those nest sites impact hatching success, may be important for successful species conservation. In this research, my objective was to 1) understand how the environment around potential nest sites (canopy, understory, and soil) influences gopher tortoise nest-site selection at burrows and 2) how that nest environment both directly (nest microclimate: temperature and moisture) and indirectly (nest characteristics: nest depth, distance from burrow, canopy and understory cover, percent clay in soil, and lay date) affects hatching success in naturally incubated tortoise nests. In the summers of 2022 and 2023, I conducted repeated searches at burrows to locate nests at the Jones Center at Ichauway and the Greenwood Ecological Reserve in southwestern Georgia. I collected soil samples, measured canopy and ground cover at gopher tortoise nest locations (n=132) and an equal number of comparison non-nest burrows. At nest sites, I also monitored temperature and moisture throughout incubation. To evaluate nest-site selection, I compared burrows with and without nests using multiple logistic regression to create a suite of five biologically relevant candidate models and compared models with Akaike's Information Criterion adjusted for small sample sizes. The top three models identified canopy cover and understory vegetation cover as the only significant predictors of nest presence at burrows, with tortoises in the sites nesting at burrows with lower understory and canopy cover. Furthermore, there was an interaction between the understory vegetation and canopy cover effects, where the effect of understory cover decreased as canopy cover increased. This suggests that the vegetation effect may be primarily driven by an avoidance of shade, whereby nests laid in burrows with high canopy cover were so shaded that understory vegetation had a weaker influence on nest-site selection. When tortoises nested in burrows with lower canopy cover, which was far more common than high canopy cover at our sites, they also avoided understory vegetation so that nest sites were least shaded. These results suggest that maintaining habitats with very open overstories may be most important for allowing gopher tortoises access to preferred nest sites. To quantify the direct and indirect effects of nest environment on hatching success, I built a structural equation model (SEM) in a Bayesian framework in which hatching success was affected by nest temperature and moisture, which were themselves affected by nest site characteristics. I found that nest microclimate could be predicted moderately well from characteristics of the nest environment (R2=0.25-0.49), with lay date influencing both temperature and moisture, vegetation affecting temperature, nest position influencing moisture and temperature variability, and percent clay in soil influencing moisture. Hatching success was highest at lower mean temperatures and moistures and at intermediate levels of temperature and moisture variability, but the ability of this model to predict hatching success was low (R2=0.10). I observed very high hatching success (87.5%) and, thus, eggs were generally receiving the conditions they needed to successfully develop and there was not much variation in hatching success to explain. This framework may be useful for investigating environmental causes of lower hatching success at less robust tortoise populations that may be experiencing low rates of natural hatching success. / Master of Science / Many turtle species experience high rates of mortality in early life, so understanding how turtles select areas to nest, and how those places impact hatching success, may be important for successful species conservation. In this research, my objective was to 1) understand how the environment around potential nest locations (vegetation and soil) influences where gopher tortoise place nests at burrows and 2) how the conditions of that nest location both directly and indirectly affect hatching success in natural gopher tortoise (Gopherus polyphemus) nests. In the summers of 2022 and 2023, I conducted repeated searches at burrows to locate nests at the Jones Center at Ichauway and the Greenwood Ecological Reserve in southwestern Georgia. I collected soil samples, measured canopy and vegetative ground cover at gopher tortoise nest locations and an equal number of burrows without nests. At nest sites, I also monitored temperature and moisture throughout incubation. To evaluate how tortoises chose nest locations, I created models to compare tortoise burrows with nests to burrows that were available for nesting, but where no nest was placed. The top three models identified canopy cover and understory vegetation cover as the only significant predictors of nest presence at burrows, with tortoises in my sites nesting at burrows with lower understory and canopy cover. Furthermore, there was an interaction between the understory vegetation and canopy cover effects, where the effect of understory cover decreased as canopy cover increased. This suggests that the vegetation effect may be primarily driven by an avoidance of shade, whereby nests laid in burrows with high canopy cover were so shaded that understory vegetation had a weaker influence on nest-site selection. When tortoises nested in burrows with lower canopy cover, which was far more common than high canopy cover at my sites, they also avoided understory vegetation so that nest sites were least shaded. These results suggest that maintaining habitats with open overstories may be most important for allowing gopher tortoises access to preferred nest sites. To quantify the direct and indirect effects of nest environment on hatching success, I built a structural equation model (SEM) in which hatching success was predicted by nest temperature and moisture, which were themselves predicted by nest-site characteristics. This allowed me to evaluate both the direct effects of nest temperature and soil and the indirect pathways by which nest environment may be influencing hatching success. I found that nest temperature and moisture could be predicted moderately well from characteristics of the nest environment (R2=0.25-0.49), with the date the nest was laid influencing both temperature and moisture, vegetation around the nest affecting temperature, nest position influencing moisture and temperature variability, and percent clay in soil influencing moisture. Hatching success was highest at lower mean temperatures and moistures and at intermediate levels of temperature and moisture variability, but the ability of this model to predict hatching success was low (R2=0.10). I observed very high hatching success (87.5%) and, thus, eggs were generally receiving the conditions they needed to successfully develop and there was not much variation in hatching success to explain. This framework may be useful for investigating environmental causes of lower hatching success at less robust tortoise populations that may be experiencing low rates of natural hatching success.

<p>Many cells spontaneously establish a polarity axis even in the absence of directional cues, a process called symmetry breaking. A central question concerns how cells polarize towards one, and only one, randomly oriented "front". The conserved Rhotype GTPase Cdc42p is an essential factor for both directed and spontaneous polarization in various organisms, whose local activation is thought to define the cell's front. We previously proposed that in yeast cells, a small stochastic cluster of GTP-Cdc42p at a random site on the cortex can grow into a large, dominating cluster via a positive feedback loop involving the scaffold protein Bem1p. As stochastic Cdc42p clusters could presumably arise at many sites, why does only one site become the dominating "front"? We speculated that competition between growing clusters for limiting factors would lead to growth of a single winning "front" at the expense of the others. Utilizing time-lapse imaging with high spatiotemporal resolution, we now document initiation of multiple polarized clusters that competed rapidly to resolve a winning cluster. Such multicluster intermediates are observed in wild-type yeast cells with functional directional cues, but the locations where they are initiated are biased by the spatial cues. In addition, we detected an unexpected oscillatory polarization in a majority of the cells breaking symmetry, in which polarity factors initially concentrated very brightly and then dimmed in an oscillatory manner, dampening down to a final intermediate level after 2-3 peaks. Dampened oscillation suggests that the polarity circuit contains an in-built negative feedback loop. Mathematical modeling predicts that negative feedback would confer robustness to the polarity circuit and make the kinetics of competition between polarity factor clusters relatively insensitive to polarity factor concentration.</p><p>We are trying to understand how competition between clusters occurs. We find that the yeast guanine-nucleotide dissociation inhibitor (GDI), Rdi1p, is needed for rapid competition between clusters. In the absence of Rdi1p the initial clustering of polarity</p><p>factors is slowed, and competition is also much slower: in some cases cells still have two clusters at the time of bud emergence and they form two buds. We suggest that in the absence of Rdi1p, the clusters compete for a limiting pool of Cdc42p, and that slow</p><p>exchange of Cdc42p on and off the membrane in the absence of Rdi1p leads to slow competition.</p> / Dissertation

Dendroclimatologists often approach field work with the intent of reconstructing a particular climate variable (e.g. temperature, streamflow, precipitation). Although guidelines exist for species and site selection, isolating the signal of interest is difficult in areas with complex terrain or a lack of ideal sites. In this case study, I suggest climatological techniques for a more efficient sampling scheme and apply these techniques to identify criteria for selecting sites sensitive to winter precipitation in the north-central Rocky Mountains. These techniques include examining factors influencing the regional response of tree growth to climate by utilizing the International Tree-Ring Databank (ITRDB), using eigenvector analyses to identify modes of variability between sites, and delineating climate regions based on the variable of interest through climate regionalization. Results suggest that low- or mid-elevation Pseudotsuga menziesii sites should be targeted for maximizing the winter precipitation signal in the case study area. The season of precipitation impacting growth was found to be a major component of the overall variability between sites.

Comprendre comment les processus de transmission non génétique comme la transmission sociale influencent l’évolution comportementale des espèces est une problématique importante en biologie de l’évolution. Cette thèse cherche à appréhender les mécanismes de diffusion et de maintien d’une information au sein d’un groupe par l’étude de la transmission sociale d’un choix de site d’oviposition chez Drosophila melanogaster. Le premier volet de cette thèse met en évidence l’existence d’une transmission du choix de site de ponte entre des femelles démonstratrices possédant l’information et des femelles observatrices naïves ainsi qu’à déterminer le processus d’apprentissage social sous-jacent. Le transfert de l’information sociale du choix d’oviposition se fait par le biais d’interactions directes entre les démonstratrices et observatrices. L’analyse de ces interactions par une méthode de vidéo tracking révèle l’existence d’un transfert de l’information bidirectionnel : plus les observatrices et les démonstratrices interagissent plus les observatrices acquièrent le choix d’oviposition et plus les démonstratrices le perdent. L’acquisition d’une information personnelle de la part les démonstratrices n’induit pas systématiquement sa transmission sociale aux observatrices suggérant que les deux processus sont dissociés. Le deuxième volet vise à comprendre dans quels contextes l’information sociale est employée et comment un individu réalise la balance entre l’utilisation des informations sociales et personnelles présentes dans son environnement. L’influence du groupe est examinée sur l’efficacité de la transmission par l’étude de paramètres tels que le ratio entre démonstratrices et observatrices, la taille du groupe, ou la présence d’une variabilité génétique. Les drosophiles montrent une stratégie d’apprentissage social de « copier la majorité » pour choisir leur site de ponte. Lorsque deux informations sociales sont présentes et contradictoires, les drosophiles acquièrent celle en adéquation avec leur préférence innée. La taille du groupe n’influence pas la transmission sociale mais perturbe l’utilisation de l’information personnelle des démonstratrices. La présence d’une variabilité génétique au sein du groupe, issue du polymorphisme du gène foraging, montre des différences de stratégies d’apprentissage social entre les individus des différents variants alléliques. L’utilisation de l’apprentissage social est parfaitement intégrée dans les prises de décision des drosophiles laissant envisager sa prévalence dans le règne animal. Cette thèse permet d’apporter de nouveaux éléments sur les mécanismes d'adaptation du comportement basé sur les processus de transmission sociale et de dégager les futurs enjeux liés à son étude. / Understanding how the process of non-genetic transmission as social transmission influence species behavioral evolution is an important issue in evolutionary biology. This thesis seeks to understand the diffusion mechanisms and information maintenance within a group studying social transmission of a choice of oviposition in Drosophila melanogaster. The first part of this thesis show social transmission occurrence of oviposition choice between informed demonstrator and naive observer females and try to determine social learning processes underlying. Social information transfer of oviposition choice occurs through direct interactions between demonstrators and observers. Analysis of these interactions by a video tracking method reveals a bidirectional information transfer: the more observers and demonstrators interact, the more observers gain oviposition choice behavior and the more demonstrators lose it. Personal information acquisition of oviposition choice by demonstrators is not sufficient to induce its transmission to observers, observers social learning seems to require special conditions. The second part of this thesis analyzes how social context influence social information use and how an individual realizes the balance between social and personal information use. The influence of group composition on social transmission efficiency is studied through different parameters such as the ratio between demonstrators and observers, group size, and the presence of genetic variability within the group. Flies show a “copy the majority” social learning strategy in their oviposition site choice behavior. Females acquire social information matching with their innate preference in presence of two contradictory social information. Group size does not affect the social transmission but perturbs demonstrator’s use of personal information. Genetic variability within the group stems from foraging gene polymorphism shows differences of social learning strategy between allelic variants. This thesis highlights a social learning use fully integrated into individuals’ decision-making and brings new elements on behavioral adaptation mechanisms based on social transmission processes.

Master of Science / Division of Biology / David A. Haukos / The ring-necked pheasant (Phasianus colchicus) is a popular and economically important upland gamebird in Kansas. Population declines have stakeholders seeking methods to manage populations on agricultural lands. Cover crops planted during the breeding period may provide important resources pheasants require for survival and successful reproduction. I evaluated three cover crop mixes; a custom mix, commercial mix, a wildlife mix, and a chemical fallow control in three counties in western Kansas, during 2017 and 2018 to determine their potential as a management practice for increasing pheasant habitat. I tested the relative effects of spring cover crops on female pheasant survival, nest survival, nest-site selection, and mesocarnivore occupancy. Females pheasants (73) were captured via nightlighting during February – April and fitted with 15-g very-high-frequency radio collars and monitored by telemetry. I placed 58 camera traps on field edges and within cover crop treatments from April to September. Vegetation data were collected at nests and random points to assess nest-site selection and weekly random vegetation points were sampled within treatments. I used known fate and nest survival models in the package RMark interface in R to investigate adult and nest survival (R Core Team 2018). Adult breeding season survival was 0.57 (SE < 0.0001, CI = 0.5739 – 0.5740). Percent spring cover crop positively influenced adult survival (AICc wi = 0.450). Nest survival was 0.36 (SE < 0.001, CI = 0.3614 - 0.3614). Daily nest survival followed a pattern of high survival that gradually declined over the breeding season. Resource selection functions suggest female ring-necked pheasants selected vegetation between 5-7 dm at 50% VOR for nest sites (AICc wi = 0.97). Chi-square analyses suggest females selected Conservation Reserve Program (CRP) patches for nest sites more than expected during both years (2017 χ²₄ = 26.49, P < 0.001; 2018 χ²₄ = 9.80, P = 0.04). CRP supported 57% of nests and 56% of successful nests relative to other cover types. All three of the monitored nests in cover crops were depredated. Ring-necked pheasant occupancy was greatest on edges of treatments (ψ = 0.97, SE = 0.081) and influenced by proportion of the Chick Magnet seed mix (AICc wi = 0.68). Mesocarnivore occupancy was greatest on treatment edges with a constant occupancy of 0.99 (SE = 0.47, AICc wi = 0.66). Spring cover crops provide cover and foraging resources when the majority of agricultural practices are fallow. Spring cover crops do not provide sufficient vertical cover for nesting until after peak nesting occurs, especially during cooler than average winter and spring conditions such as 2018. However, there are tangible benefits of spring cover crops to other biological periods, such as adult female survival, and brood resources if placement of cover crops is targeted near quality nest habitat. My results indicates wheat is an ecological trap for nesting due to increased predation and destruction during harvest. Providing quality nest structure will reduce females nesting in wheat. Incorporation of spring cover crops is a beneficial wildlife management tool that can increase ring-necked pheasant habitat on the landscape.

Climate change is threatening biodiversity, causing populations and species to adapt, or otherwise, become extinct. Sea turtles have survived dramatic climate changes in the past, however, due to a history of intense human exploitation, and the current anthropogenic threats, their current resilience may be jeopardized. The main pursuits of this thesis were to i) evaluate the resistance of green turtles to predicted climate change impacts, using a globally significant rookery, in Poilão, Guinea-Bissau, as a case study; and ii) assess key population parameters to inform the conservation management of this resource. As the work developed I additionally had the opportunity to study the dynamics of an emerging disease in a juvenile foraging aggregation from Puerto Rico, which contributed to a broader understanding of resilience in this species. Specifically, I investigate the nest site selection behaviour of green turtles, their nesting environment, and the outcomes for their offspring, at Poilão, and apply this information to infer on the resilience of this population under future scenarios of climate change. I explore the connectivity established by the dispersal of post-hatchlings from Poilão, followed by their recruitment to foraging grounds, to set the geographical context of this major population. Lastly, I model the dynamics of Fibropapillomatosis, which affects juvenile green turtles globally, and examine the potential for disease recovery. The green turtle rookery in Poilão shows some resilience to expected climate change impacts. This significant population likely contributes to all juvenile foraging aggregations along the west coast of Africa, and to some extent to those in South America. Currently, green turtles are capable of recovery from Fibropapillomatosis, however, the incidence of disease may be enhanced by climate change.

The red-headed woodpecker is a primary cavity excavator found throughout the Eastern Deciduous Forest and parts of the Great Plains. Although widespread, the red-headed woodpecker is generally considered uncommon, with patchily distributed populations. Over the past 50 years, this species has experienced precipitous, range-wide declines. The red-headed woodpecker uses a variety of cover types to meet resource needs across the annual cycle, ranging from oak savannas and wetlands, to mature beech forests and urban parks. Given their apparent adaptability to such a wide range of habitats, causes of declines are perplexing. To understand and stem declines, recent studies have focused on quantifying this species’ habitat requirements. Most of these studies have focused on a single cover type, often open forests, during the breeding season. However, effective management requires comprehensive knowledge of red-headed woodpecker habitat needs in a variety of cover types across the annual cycle. My thesis seeks to address this knowledge gap. I studied red-headed woodpecker habitat selection during both the breeding and non-breeding seasons at Fort A.P. Hill (FAPH) in Caroline County, Virginia. FAPH contains a variety of cover types that red-headed woodpeckers are known to use for breeding and overwintering, including: wetlands, open forests and closed forests. In Chapter 1, I investigated winter roost-site selection of red-headed woodpeckers in a burned forest stand. My study was the first to quantify winter habitat selection for this species. My aim was to identify variables driving winter roost-site selection at two relevant spatial scales, and estimate their parameter weights using logistic regression. I found that red-headed woodpeckers preferred habitat around the roost tree that contained a higher basal area of snags and mast-producing trees. They differentially selected roost trees based on taxon and decay state. My results indicate that managers should adopt practices that promote snag generation and retention, and mature oak recruitment. In chapter 2, I focused on red-headed woodpecker breeding season habitat requirements, as many other studies have done. However, unlike other studies that investigated habitat selection within a single cover type, I found and characterized nest-sites in three distinct cover types (wetlands, closed forests, open forests). I used a comparative approach to identify cover-type specific nest-habitat thresholds at the landscape, patch and tree scales using boosted regression trees (BRT). Although models at the landscape scale inadequately discriminated between nest and available sites, models at the patch and tree scales achieved excellent discrimination ability. I found that red-headed woodpeckers are consistent in their preference for a number of habitat features at the patch (high medium/large snag density, open canopy) and tree (large diameter tree with less bark) scales, irrespective of cover type context. However, I also found cover-type specific habitat preferences at the patch scale, indicating red-headed woodpeckers are flexible in their selection of features surrounding the nest and responsive to the broader habitat context. My findings suggest that there are a number of habitat features that facilitate breeding for red-headed woodpeckers generally, and management that promotes these features will be effective in a variety of habitat contexts. They also indicate that management can be tailored to provide the most suitable habitat for each of these three commonly used cover types. Together, Chapters 1 and Chapter 2 expand our knowledge of this declining keystone species’ habitat needs across the full annual cycle. But there is still much to know. The choices of habitat selection have consequences. Determining the conditions under which habitat features function to either help or harm populations is a necessary next step. While not a part of this thesis, I am currently investigating the factors that drive nest success among cover types, linking breeding-site selection to population dynamics. I also have behavioral data that will help reveal the mechanisms that either facilitate or constrain the exploitation of food resources across cover types. Finally, the red-headed woodpecker is a facultative migrant that often shifts habitat associations to take advantage of seasonally available resources. Data from my point count surveys—conducted over two successive winter and summer seasons—allow for development of dynamic occupancy models. Modeling shifts in occupancy across seasons will show the habitat factors underlying seasonal shifts. Site-specific differences in colonization, extinction and frequency of occupancy, within seasons but across years, will further our understanding of what constitutes habitat quality for this species, in both the breeding and non-breeding seasons.

In recent years, the popularity of wind energy has grown. It is starting to play a large role in generating renewable, clean energy around the world. In New Zealand, there is increasing recognition and awareness of global warming and the pollution caused by burning fossil fuels, as well as the increased difficulty of obtaining oil from foreign sources, and the fluctuating price of non-renewable energy products. This makes wind energy a very attractive alternative to keep New Zealand clean and green. There are many issues involved in wind farm development. These issues can be grouped into two categories - economic issues and environmental issues. Wind farm developers often use site selection process to minimise the impact of these issues. This thesis aims to develop GIS based models that provide effective decision support tool for evaluating, at a regional scale, potential wind farm locations. This thesis firstly identifies common issues involved in wind farm development. Then, by reviewing previous research on wind farm site selection, methods and models used by academic and corporate sector to solve issues are listed. Criteria for an effective decision support tool are also discussed. In this case, an effective decision support tool needs to be flexible, easy to implement and easy to use. More specifically, an effective decision support tool needs to provide users the ability to identify areas that are suitable for wind farm development based on different criteria. Having established the structure and criteria for a wind farm analysis model, a GIS based tool was implemented using AML code using a Boolean logic model approach. This method uses binary maps for the final analysis. There are a total of 3645 output maps produced based on different combination of criteria. These maps can be used to conduct sensitivity analysis. This research concludes that an effective GIS analysis tool can be developed for provide effective decision support for evaluating wind farm sites.