The consequences of substituting the denominator Q 3(p) - Q 1(p) by Q 2 - Q 1(p) in Groeneveld's class of quantile measures of kurtosis (γ 2(p)) for symmetric distributions, are explored using the symmetric influence function. The relationship between the measure γ 2(p) and the alternative class of kurtosis measures κ2(p) is derived together with the relationship between their influence functions. The Laplace, Logistic, symmetric Two-sided Power, Tukey and Beta distributions are considered in the examples in order to discuss the results obtained pertaining to unimodal, heavy tailed, bounded domain and U-shaped distributions.

The Columbian sharp-tailed grouse (Tympanuchus phasianellus columbianus; CSTG) has experienced range-wide population declines, primarily as a result of habitat loss or degradation, and currently occupies <10% of its historic range. Expansion of wind energy developments across the remaining occupied CSTG range has been identified as a potential threat to the species. To assess the potential influence of wind energy development on CSTG breeding season ecology, I captured and radio-marked 135 female CSTG during 2014-2015 at leks located between 0.1-13.8 km from wind turbines in restored grassland habitats. I subsequently monitored 147 nests and 68 broods and used an information-theoretic model selection approach to assess the potential influence of wind energy distance and density variables, multi-scale habitat features, temporal factors, and precipitation on CSTG nest site selection, daily nest survival, brood success, and chick survival. The best nest site selection model suggested a positive functional response to the amount of restored grassland habitat with >30% forb cover at the nesting core use (60 ha) scale. Daily nest survival was positively associated with visual obstruction readings at the nest and the amount of restored grassland habitat containing >30% forb cover at the core use (60 ha) scale. Nest site selection and daily nest survival were not influenced by proximity to turbines or turbine density at the core use or breeding season home range (1385 ha) scales. Early (14-day) brood success was positively influenced by post-hatch precipitation and late (42-day) brood success was positively influenced by earlier hatch dates. Chick survival to 42 days post hatch was positively influenced by post-hatch precipitation and earlier hatch dates and negatively influenced by increasing densities of wind turbines at the breeding season home range scale. The probability of an individual chick surviving to 42 days decreased by 50% when there were ≥10 turbines within 2.1 km of the nest. In restored grassland habitats, such as Conservation Reserve Program fields, I recommend plantings and management practices that will result in diverse, bunchgrass-dominated nesting habitat with residual grass cover and >30% forb canopy cover during the nesting season. My results suggest that wind turbines occurring within 2.1 km of nesting habitats (i.e., 4.8 km of occupied leks) may negatively affect CSTG recruitment.

Population biology of the black-tailed jackrabbit population on a 250-square-mile area in Curlew Valley, northern Utah, was studied from 1962-70. During this period the fall population density index increased from 40.0 in 1962, to 60.6 in 1963, decreased progressively to a low of 21.2 in 1967, then increased the following 3 years to a high of 185.0 in 1970. Breeding was synchronous with four conception periods each year; in some years a fifth conception period was evident. The first conception period occurred about the last half of January; other periods followed at 40-day intervals indicating a 40-day gestation period and postpartum estrus with subsequent conception. Over the 9 years of study, the mean percentages of females breeding during the five conception periods were 88, 99, 100, 70, and 11 percent, respectively. The mean number of ova ovulated per breeding female for the five periods was 1.9, 5.1, 6.4, 4.9, and 3.6, respectively. During the period of decreasing density, 1963-67, the yearly mean number of ova ovulated per female surviving the breeding season ranged from 13.2-19.3, but varied independently of density. During the 3 consecutive years of density increase, 1968-70, however, the number of ova ovulated per female decreased progressively from 19.8 in 1968 to 14.2 in 1970. Mortality rates of the total population from October-March remained relatively constant (mean: 63 percent) during the years of population decline, but dropped to 33 percent during the first year of population increase (1968). March-October mortality of adults decreased to 9 percent during the first year of population increase from a previous mean of 73 percent, and juvenile mortality from parturition to fall census, decreased from a mean of 68 percent to 38 percent. The effects of variations in mortality rates on population density have overshadowed the effects of the relatively less extreme variations in natality rates. As a result the pattern of density change was almost entirely a result of changes in mortality rates. Changes in mortality rates of adults and juveniles were well correlated with the coyote/rabbit ratio on the study area. Exceptions occurred with juvenile mortality rates at the relatively high rabbit densities observed in 1969-70. During these two years, juvenile mortality rates from parturition to fall census (61 and 68 percent, respectively) were greater than could be accounted for by coyote predation. The factor or factors responsible for the increased juvenile mortality are not known. Observed annual density changes were described with the mathematical model: Nt+4 = Nt (1 - 37.8 - 988x1) (1 + 11.2 - 1130x2 - 0.0581x3 + 42000x22 + 0.00115x32) where Nt is the number of animals at the end of October, Nt+1 is the number of animals at the end of the following October, x1 is the coyote/rabbit ratio from October-March, x2 is the coyote/rabbit ratio from March-October, and x3 is the mean number of rabbits per square mile from March-October. The model accounts for 99 percent of the observed change in rabbit density from 1968-70.

Columbian sharp-tailed grouse (Tympanuchus phasianellus columbianus: hereafter sharp-tailed grouse) populations have been declining. These declines have been attributed to a number of factors, including habitat loss due to agriculture, habitat fragmentation, overgrazing by livestock, and the loss to fire. To gather information about their status in northern Utah, I radio-marked sharp-tailed grouse in 2003 (n=15) and 2004 (n=20) in two research areas. The study areas were located on the south end of Cache County and in eastern Box Elder County. In the Cache study area, I monitored 7 males and 1 female in 2003, and 6 males and 3 females in 2004. In the Box Elder study area, I monitored 6 males in 2003 and 6 males and 5 females in 2004. I then located the radio-marked sharp-tailed grouse using telemetry and collected Visual Obstruction Readings (VOR) and vegetation data on each flush site and on a randomly selected paired point. I completed an unsupervised classification of the two study areas to determine if habitats were used more than would be expected based on availability. I then used a paired point linear regression to determine if vegetation parameters were correlated with sharp-tailed grouse on the landscape. Sagebrush in the Box Elder County study area and forbs in the Cache County study area were significantly correlated with habitat use by sharp-tailed grouse. The VOR readings were higher at the flush sites than at the paired points. The unsupervised classification showed that in Box Elder County, sagebrush was used in greater proportion than is available, while in the Cache County study area there were no habitat types that were used in greater proportion than was available on the landscape. I collected information on nest sites, nest success, broods, and mortality of these 2 populations. Nest success was 75% combined over the 2-year study, and mortality was 72% for both populations over the 2 years. Seasonal habitat use and distance travelled were determined using Global Positioning System points collected at every flush point. The distance traveled ranged from 0.9 km to 14.7 km, with the longest distance being travelled in the winter.

Tick-borne diseases cause in enormous burden on human, livestock, and wildlife health globally and are driven by the increasing abundance and geographic expansion of medically important tick species. More recently, tick-borne disease emergence is occurring in urban landscapes due to complex feedbacks between the environment, humans, wildlife, and ticks. In this dissertation, I focus on the ecological conditions that allow for tick-borne disease emergence in a city. I use a combination of spatial landscape modeling, empirical data collection, wildlife movement tracking to determine drivers of zoonotic hazards in New York City, NY, and employ vector genomics to examine vector dispersal in the northeastern United States. In chapter one, I pair tick collection throughout the five boroughs of New York City with landscape connectivity modeling to examine how green space connectivity and habitat availability affects the density and infection of questing nymphs – an important epidemiological measure of human risk for tick-borne diseases. I found that green spaces that were highly connected for deer had higher nymph density and infection prevalence for Borrelia burgdorferi sensu stricto, the etiologic agent of Lyme disease. In chapter two, I use camera trapping, live trapping, and tick collection on Staten Island, NY, to examine how landscape fragmentation – through changing habitat size and connectivity – shapes the host community available for questing Ixodes scapularis nymphs. Further, I examined whether patterns in host species abundance and activity correlate with the density of nymphs and their infection prevalence with three different pathogens that vary in host-specificity, B. burgdorferi, Babesia microti, and Anaplasma phagocytophilum. I found associations between host species and the size and connectivity of the park habitat, identified host species which amplified and removed ticks in the environment, and determined links between host activity and abundance and the infection prevalence of nymphs with host-specific pathogens. In chapter three, I utilize movement data from 59 white-tailed deer on Staten Island, NY, to assess the drivers of movement and its impact on tick-borne disease hazard across the landscape. I found that white-tailed deer avoid anthropogenic development at fine spatial scales when establishing home ranges but select for anthropogenic resources within their home range, increasing the potential to distribute ticks into environments that interface with humans. Finally in chapter four, I use double digest Restriction Associated DNA sequencing to examine the genetic differentiation of six I. scapularis populations across the Northeast region. I found high levels of gene flow across a spatial scale of 400 km, likely resulting from frequent host-mediated dispersal events combined with large I. scapularis populations. Taken together, this work emphasizes that host movement and ecology are critical determinants of urban tick-borne disease emergence through directing vector and pathogen dispersal, serving as pathogen reservoirs in urban habitats, and interfacing with humans in unique ways that increase human exposure to zoonotic hazards.

京都大学 / 0048 / 新制・論文博士 / 博士(理学) / 乙第12814号 / 論理博第1540号 / 新制||理||1577(附属図書館) / 31301 / (主査)准教授 半谷 吾郎, 教授 湯本 貴和, 教授 高田 昌彦 / 学位規則第4条第2項該当 / Doctor of Science / Kyoto University / DFAM

No description available.

With increasingly warming climate, many bird species have been forced to respond to environmental changes, and the long-tailed duck (Clangula hyemalis) is no exception. The populations of the long-tailed duck have been in decline the past few decades and the species is classified as globally vulnerable and near threatened in both Iceland and Sweden. The long-tailed duck is a circumpolar, migratory sea duck. Its migratory routes and wintering and breeding sites might play an important part in gene flow between populations. The aim of this project was to get a clearer image of the substructure of the long-tailed duck in the northern hemisphere to help identify populations possibly at risk. This was investigated by exploring differences in mitochondrial DNA between the global populations, and by studying the Icelandic wintering and breeding populations in particular applying whole genome sequencing. To do this, samples were obtained for mitochondrial DNA analyses from a previous study by Wilson et al. (2016) from North America and East Russia, samples from other populations around the northern hemisphere as well and new samples from Iceland. Museum samples from Iceland were used for whole genome resequencing. Mitochondrial analyses included haplotype identification, population comparisons, mismatch and neutrality tests. Whole genome analyses included neutrality tests, principal component analysis and genetic admixture analysis.The mitochondrial results revealed two distinct lineages for the long-tailed duck. Two populations showed a difference from the other populations; the Icelandic breeding population and the Yukon-Kuskokwim Delta population from Alaska, which are the southernmost breeding populations. The Yukon population might have been previously isolated with refugial population intermixing. For the Icelandic populations, the mitochondrial results showed little intermixing between the winter and breeding populations. The whole genome results showed more complicated results for the Icelandic populations, with admixture in some individuals. This suggests that there seems to be more variation in the genome than implied by the mitochondrial DNA.

White-tailed deer (Odocoileus virginianus) dispersal and excursion movements impact gene flow, population dynamics, and disease spread. Knowledge of movement characteristics and habitat selection during dispersal could provide the ability to predict how deer may relocate themselves within the landscape while providing managers valuable information regarding corridors for gene flow and disease spread. My objectives were to 1) test the hypothesis that extra-home-range movements occur as a strategy to broaden mating opportunities or as a means of searching for higher quality resources in this fragmented landscape, 2) compare occurrence rates and path movement metrics for dispersal and excursion movements to determine if underlying differences in behavior exist that would allude to mechanisms for accepting the risk of leaving a home range, 3) create and test the performance of expert opinion and step selection function resistance models at predicting deer dispersal movements, and 4) fit single and multiple random walk models to dispersal path data to determine movement states occurring within this behavior. During 2011-2014, I placed GPS collars programmed to take hourly locations on 49 fawn and yearling white-tailed deer in agricultural east-central Illinois to record dispersal and excursion movement paths. Linear mixed effects models were used to test for differences in path characteristics between sexes and ages (e.g., distance, straightness, duration, and speed). I used known-fate models, with demographic, temporal, and home range variables as covariates, to obtain dispersal and excursion occurrence rate estimates. Ten dispersal and 54 excursion movement paths were recorded during the study. Dispersal paths were longer and straighter (P < 0.001), and trended toward being longer in duration (P = 0.080) and faster in speed (P = 0.085), than excursion paths. Dispersal rates differed by sex (annual estimate ± SE with ages pooled: males 0.81 ± 0.12, females 0.16 ± 0.15) and were greatest during the breeding season (14-day estimates for males: winter 0.00 ± 0.01, fawning 0.02 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.31 ± 0.15, and females: winter 0.00 ± 0.01, fawning 0.01 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.04 ± 0.03). In contrast, I found no evidence that excursion rates were influenced by demographic, temporal, or home range variables (annual: 0.78 ± 0.06). I compared 2 methods of resistance modeling for predicting deer dispersal paths. I created an expert opinion survey and calculated a dispersal step selection function (SSF) to rank habitat variables and create 2 types of resistance maps to dispersal movements. I created least-cost paths with the starting and ending points coinciding with recorded dispersal paths within these 2 resistance maps. I compared the created paths to actual paths and a null straight line path using a path deviation index (PDI), path straightness, and path cost/m as variables of interest. Experts ranked land cover variables differently by season, applying a lower resistance value to agriculture cover during the summer/fall period, so 2 versions of the expert opinion resistance maps were created. For the SSF, I found that both forest cover and streams had significant nonlinear effects on deer dispersal movements. Assuming that all other factors remained constant, deer were more likely (≥ 0.50 probability) to move toward forested habitat when located < 335 m and when > 2795 m away. Deer dispersal movement behavior relating to streams followed a similar trend but with deer always having > 0.56 probability to move toward a stream than away. For least-cost path comparison, I conducted 3 ANOVAs (α = 0.05 throughout) to test for mean differences in calculated path metrics for all paths with path type as a within-subjects effect. I found no difference between the expert opinion survey model, the SSF model, and the null straight line model at predicting dispersal paths. PDI values were similar among all models (F1,9 = 0.004, P = 0.99). The SSF paths (0.91 ± 0.02) were significantly straighter then both the expert opinion (0.57 ± 0.03) and actual deer paths (0.44 ± 0.06; F1, 9 = 32.65, P < 0.001), but the expert opinion path did not differ from the actual path (P = 0.08). Path costs differed within the expert opinion survey resistance map (F1, 9 = 14.21, P < 0.001) with the expert opinion least cost paths (23.64 ± 3.14) having lower resistance/m than both the actual (46.15 ± 3.85) and straight line paths (48.74 ± 3.94; P < 0.001 for both). However, the actual and straight line paths did not differ (P = 0.872). There were no difference in path costs between the actual, SSF least-cost path, and straight line paths within the SSF resistance map (F1, 9 = 0.454, P = 0.64). I constructed and attempted to fit single and multiple random models to collected dispersal locations using WinBUGS v. 1.4.3. I was able to fit a single random walk model to deer dispersal paths but the more complex random walk models did not converge. I used the average parameter values derived from the single model to simulate deer dispersal paths and compared them to observed Net Squared Displacement. My simulated paths underpredicted deer displacement for 0.90 of individuals. Deer in east-central Illinois are very mobile and commonly make excursion movements throughout the year. The fact that I recorded differing dispersal rates within the same study area over a temporally short period from a previous study highlight the need for managers to obtain recent estimates of population parameters when making management decisions. The frequency of excursion movements should not be overlooked by managers as it is a behavior that can influence gene flow and potentially spread disease across the landscape at a localized scale. The preference for forest and stream habitats during dispersal can allow managers to focus surveillance or culling efforts around these types of habitats. The application of the least-cost path modeling technique appears to be ineffective at predicting deer dispersal paths, which emphasizes the importance of validating these types of models with actual data. The results from the random walk analysis highlight the need to collect as many locations as possible during temporally-short movements to understand the mechanisms acting upon them.

Sheep were domesticated ~10 000 years ago from Asiatic Mouflon. They then spread to Europe via the migration of farming human populations and had reached Scandinavia by ~6000 years ago. Another migration of humans stemming from the Pontic-Caspian steppe reached Scandinavia around ~5000 years ago, possibly with new types of sheep. Ancient sheep have mostly been studied using mitochondrial DNA. The few examples to date that have applied genome wide sequencing have shown that modern northern European sheep are most closely related to ~9000-year-old Anatolian sheep. Northern European Short Tailed sheep are a group known for their “rustic” phenotype. Their visual appearance together with mitochondrial DNA studies has led to the hypothesis that these sheep are a relict of early migrations. In this study I present five new ancient domestic sheep genomes, from the islands Gotland and Åland in the Baltic Sea, covering the timespan ~4000-500 years ago. Most samples show exceptionally good preservation, with four having over 1x nuclear coverage, ranging up to 11.6x. I use these genomes together with two large panels of Eurasian genome wide SNPs, which includes the three Norther European Short Tailed breeds from these islands, Gotland- Gute-, and Åland sheep. I study how these ancient sheep relate to modern populations. I also evaluate their wool phenotype based on two genetic markers and find that these ancient sheep probably had medium-coarse wool fiber thickness. The results also show that sheep in the Baltic Sea area show a remarkable degree of continuity between 4000 and 500 years ago, and that these ancient sheep are closely related to modern breeds from the area, Åland sheep being the closest extant population.