Une régulation biologique plus efficace des ravageurs des grandes cultures par leurs ennemis naturels nécessite une meilleure compréhension de la biologie de ces espèces et de leurs patrons de dispersion dans les paysages agricoles. L’objectif de ce travail est d’améliorer les connaissances sur la dynamique des populations de méligèthes et de leur parasitoïde principal. A l’aide de microsatellites, nous avons montré que la structuration génétique des populations de méligèthes était faible en Europe, celle de T. heterocerus est sensiblement plus forte. Avec des modèles statistiques appliqués aux abondances de méligèthes, nous avons montré qu’ils parcourent en moyenne 1,2 km après l’hivernation. Cette distance moyenne de dispersion est comparable à celle estimée à partir de résultats d’assignation de parentés génétique entre paires d’individus. Avec des relevés de terrain, nous avons quantifié et identifié les déterminants de la présence de méligèthes dans d’autres habitats que le colza. Au printemps, ils peuvent être observés dans des prairies, des friches et des bords de champs, où se trouvent des fleurs jaunes. En été, les méligèthes sont présents dans ces habitats, partout où il y a des fleurs, sans distinction de couleurs, surtout sur les adventices des cultures. Enfin, la présence de parasitoïdes semble plus fortement déterminée par la présence de méligèthes que par des éléments paysagers. Le paysage joue un rôle déterminant sur ce couple d’espèces. De plus, les estimations des paramètres démographiques réalisées pourront aider par la modélisation à dimensionner les actions à mener pour limiter les dégâts causés par les méligèthes. / More effective biological regulation of field crop pests by their natural enemies requires a better understanding of the biology of these species and their patterns of dispersal in agricultural landscapes. The objective of this work is to increase knowledge on the dynamics of pollen beetles populations and their main parasitoid. Using an approach based on the analysis of microsatellites, we have shown that the genetic structuring of pollen beetle populations in Europe is weak. Populations of T. heterocerus are more structured. With statistical models applied to the abundance of pollen beetles, we have shown that they travel an average of 1.2 km, after overwintering. This average distance is comparable to that estimated from results of sibship analysis between pairs of individualsWith fieldwork, we quantified and identified the determinants of pollen beetles presence in habitats other than rapeseed. In spring, pollen beetles can be seen in grasslands, fallows and field edges with yellow flowers. In summer, pollen beetles are present in these habitats, wherever there are flowers, without distinction of colour, especially on the weeds of crops. Finally, the presence of parasitoids seems to be more strongly determined by the presence of pollen beetles than by landscape elements. The landscape plays a decisive role on this pair of species. Moreover, throught modelling, estimates of the demographic parameters carried out would help to shape the actions to be taken to limit the damage caused by pollen beetles.

Animals must balance multiple, fitness-related traits in environments that are complex and characterized by co-varying factors, such as co-variation in temperature and food availability. Thus, experiments manipulating multiple environmental factors provide valuable insight into the role of the environment in shaping not only important traits (e.g., dispersal capacity or reproduction), but also trait-trait interactions (e.g., trade-offs between traits). We employed a multi-factorial design to manipulate variation in temperature (constant 28°C vs. 28±5°C daily cycle) and food availability (unlimited vs. intermittent access) throughout development in the sand field cricket, Gryllus firmus. We found that fitness-related, life-history traits and trait trade-offs can be developmentally plastic in response to variation in temperature and food availability. Variability in temperature and food availability influenced development, growth, body size, reproductive investment, and/or flight capacity, and food availability also affected survival to adulthood. Further, both constant temperature and unlimited food availability promoted investment into key components of somatic and reproductive tissues while reducing investment into flight capacity. We develop an experimental and statistical framework to reveal shifts in correlative patterns of investment into different life-history traits. This approach can be applied to a range of animal systems to investigate how environmental complexity influences traits and trait trade-offs.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第21376号 / 農博第2300号 / 新制||農||1068(附属図書館) / 学位論文||H30||N5149(農学部図書室) / 京都大学大学院農学研究科森林科学専攻 / (主査)教授 井鷺 裕司, 教授 神﨑 護, 教授 北島 薫 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

No description available.

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.

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No description available.

The movement of individuals is foundational to many ecological processes. For example, the movement of an organism from one place to another alters population density at both sites and has potential for affecting the genetic dynamics within the new population. Individual movement events may be in synchrony with overall trends in populations, e.g. spawning migrations, or may be atypical (asynchronous). This latter movement type can affect population and metapopulation dynamics, depending on its prevalence within a population. Nevertheless, given the complexity of interactions, the causative factors of movement are understood vaguely, much less for aquatic organisms. Drivers of movement are extrinsic (e.g. habitat quality, predation or habitat heterogeneity) and intrinsic (e.g. sex, size, or behavioral tendencies). Interactions among these drivers provide crucial insight into the patterns of movement observed within populations. Habitat is here shown to affect observed movement patterns of populations of southern leatherside chub (Lepidomeda aliciae). Streams with higher-quality habitat were inhabited by populations exhibiting lower overall movement compared to lower-quality streams. However, observations of individual long distance movement relative to the norm within the population suggest that movement may also be behaviorally based. In further tests, it is shown that, indeed, behavioral tendencies of individuals can be measured and are predictive of annual movement by individuals. Other drivers, habitat availability and quality, were also found to influence movement on a yearly basis. Movement patterns are also affected by the presence or absence of predators. A tropical livebearer (Brachyrhaphis rhabdophora) has a higher percentage of individuals classified as generally moving when predators are absent from the environment compared to predator sites. Predation environment also significantly affects individual body shape with predator sites possessing caudal peduncles with greater surface area, an adaptation likely promoting burst speed for greater escape abilities. Classification of individuals as generally moving or generally not moving was also significantly related to variation of body shape of these fish. However, biological significance is ambiguous given the absence of obvious morphology trends explained by this factor. It is critical to understand these drivers to better understand the dynamic interface between ecology and evolution.

Whether active or passive, dispersal accompanied by gene flow shapes the population genetics and evolutionary divergence of species. Indirect methods which use genetic markers have the ability to assess effective dispersal—that which resulted in gene flow. My objective was to see if an aquatic insect and an obligate aquatic invertebrate show similar phylogeographic patterns and genetic uniqueness. Hyalella azteca and Callibaetis americanus were collected from 4-5 springs in each of six basins in the Great Basin of western North America. No dispersal or genetic studies of C. americanus have been conducted to date. However, several studies focusing on mtDNA diversity of H. azteca have revealed a tremendous degree of cryptic diversity in the desert springs of the Great Basin. Nested clade phylogeographical analysis (NCPA), FST values, AMOVA, and Mantel tests were used to examine geographical associations. I also used traditional phylogenetic approaches including maximum parsimony (MP) and likelihood (ML) analyses using cytochrome c oxidase subunit I (COI), 28S, and 16S as genetic markers. The mitochondrial COI sequence divergences in C. americanus were higher than H. azteca COI divergences within springs but lower among springs. FST values were very high in H. azteca reaching near fixation for certain alleles. C. americanus FST values were lower suggesting greater gene flow and, consequently, greater dispersal rates. Even though Mantel tests did not detect significant isolation by distance when evaluating all haplotypes together, nested clade analysis was able to examine smaller networks of related haplotypes and detect significant isolation by distance. Whereas the genetic structure in C. americanus was dominated by restricted gene flow with isolation by distance, H. azteca was characterized more by gradual range expansion followed by fragmentation. Mayflies likely showed more gene flow than amphipods because of their flight capabilities, but movement was still restricted by long distances between isolated springs.

The advent of GPS tracking technology has revolutionized the field of wildlife research. The ability to obtain fine-scale location data from collared animals allows for increased understanding of life-history events that have previously been difficult to research. An excellent candidate species for telemetry-based research is mule deer (Odocoileus hemionus). Mule deer are an important species economically due to their position as a harvested species. Additionally, they play an important role in the ecosystems they occupy; therefore information regarding important life history events would improve conservation and management efforts for this species. Our objectives were to use GPS tracking technology to explore two important life-history events in mule deer, parturition and natal dispersal. We developed and tested movement-based methods for detecting parturition in mule deer (Chapter One) and we used movement patterns to quantify the influence of various factors on dispersal of mule deer (Chapter Two). For Chapter One, we hypothesized that patterns of maternal movement could be used to predict the status and timing of parturition of mule deer. In order to test this hypothesis, we captured, collared, and confirmed parturition for 90 female deer in the state of Utah. We used the known dates of parturition to test the accuracy and precision of six different movement--based methods to identify parturition. We found that methods differed in both accuracy and precision, with the highest performing method displaying 98% accuracy and 93% precision (within seven days). For Chapter Two, we hypothesized that several factors (e.g. inbreeding avoidance, competition for mates, competition for resources, and migratory learning) would influence dispersal of mule deer. In order to evaluate the relative importance of these factors, we captured, collared, and tracked 303 six-month old mule deer fawns over the course of five years. We found evidence that inbreeding avoidance and migratory learning both influenced dispersal behavior of mule deer, while we found no evidence that competition for mates or resources influenced dispersal in this species.