Climate change, global warming and anthropogenic disturbances are threatening freshwater ecosystems globally. The protection and preservation of freshwater environments, its biodiversity and all of its services for human well-being requires comprehensive knowledge of the impacts that climate change and anthropogenic disturbances have on freshwaters and freshwater species. In-depth knowledge needed for conservation strategies can be established through versatile assessments. Quantitative assessments and the investigation of prevailing environmental relationships within ecosystems constitute the basis for sustaining freshwater systems. However, it is a great challenge to quantify the multifaceted effects of climate change and to broaden the understanding of complex environmental relationships. This thesis aims at contributing to an extension of the understanding of climate change impacts on freshwater ecosystems and environmental relationships, which implies the provision of useful guidelines for the protection and preservation of freshwaters. For this, various statistical approaches based on comprehensive data sets are applied at different scales, ranging from local to global assessments. In particular, five research studies investigating the (1) water quality-nutrient and temperature relationships in European lakes, (2) drivers of freshwater fish species distributions across varying scales in the Danube River delta, (3) globally derived thermal response curves and thermal properties of native European freshwater species, (4) differences between thermal properties derived from native and global range data, and (5) thermal performances of freshwater fish species for different life stages and different global future dispersal scenarios are presented to address the effects of environmental change. Main results of this thesis comprise various aspects of conservation implications and planning. (i) The first study outlines drivers influencing water quality through studying multi-dimensional relationships and compares different modelling techniques in order to outline models that are suitable for the identification of complex driver interactions. (ii) The second study addresses scale effects on the performance of species distribution models, which are commonly used for assessments of climate change impacts, and identifies key predictors driving distributions for the varying scales and studied species. (iii) The third study parameterizes thermal responses of species from different taxonomic groups and assesses the potential resilience in terms of warming tolerance and additional thermal properties as well as the influence of future rising temperatures on current distributions. (iv) The fourth study quantifies the differences in thermal response curves and thermal properties for freshwater fishes derived from global and continental data in order to clarify the need for using global range data in studies making suggestions for conservation planning. (v) The last study estimates the impact of changing climatic conditions on species distribution ranges of two fish species for different time periods by including biotic information about thermal performances for various life stages. Overall, this thesis contributes to the broad field of studying consequences and impacts of climate change on freshwater ecosystems. By applying statistical methods tailored to the underlying investigations, useful implications for conservation planning are derived.

Historically, kit foxes (Vulpes macrotis) once occupied the desert and semi-arid regions of southwestern North America, ranging from Idaho to central Mexico. Their range-wide decline has warranted the kit fox to be listed as endangered in Colorado, threatened in California and Oregon, and designated as a state sensitive species in Idaho and Utah. Once considered the most abundant carnivore in western Utah, the kit fox has been in steep decline over the past decade, creating a demand to determine kit fox presence. Currently there is little consensus on which survey methodology is best to detect kit fox presence. We tested 4 survey methods (scat deposition, scent station, spotlight, trapping) along 15 5-km transects within a minimum known population of radio collar kit fox. Home range sizes for kit foxes on the study site were extremely large, averaging 20.5 km2. Scat deposition surveys had both the highest detection probabilities (= 0.88) and were the most closely related to known fox abundance (r2 =0.50, P = 0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. This method had low costs, was resilient to weather, had low labor requirements, and entailed no risk to the study animals.Next in determining kit fox presence is estimating kit fox distribution. We developed resource selection functions (RSF) using presence data from the noninvasive scat surveys to model kit fox distribution. We evaluated the predictive performance of RSFs built using three popular techniques (Maxent, fixed-effects and mixed-effects general linear models) combined with common environmental parameters (slope, aspect, elevation, soil type). Both the Maxent and fixed-effects models performed to an acceptable level with relatively high area under the curve (AUC) scores of 0.83 and 0.75, respectively. The mixed-effects model over valued higher elevations and had poor model fit. This study demonstrated that it was possible to create valid and informative predictive maps of a species distribution using a noninvasive survey method for detecting a carnivore existing at low density. By demonstrating the application of noninvasive surveying to model habitat quality for a small mesocarnivore, wildlife management agencies will be able to develop predictive maps for species of interest and provide more knowledge to help guide future management decisions.

While range-wide population declines have prompted extensive research on greater sage-grouse (Centrocercus urophasianus), basic information about southern periphery populations, such as the Bald Hills population in southern Utah, has not been documented. The objective of this research was to determine habitat preferences and space use patterns of the Bald Hills sage-grouse population which occurs in an area of high potential for renewable energy development. I tracked 66 birds via VHF telemetry in 2011 and 2012 and surveyed vegetation plots throughout the study area. I found that the population was primarily one-stage migratory with seasonal distributions that did not correspond well with previously developed suitable habitat maps (based on local biologist knowledge and lek data) for all seasons; I also found that mean home range sizes ranged from 82 km2 to 157 km2. Nesting hens did not select for any measured vegetation characteristics within the study area, while brood-rearing hens selected for high forb cover. Birds at summer sites (non-reproductive bird locations during the summer season) selected for greater grass and forb cover and lower shrub cover compared with random sites. Overall, Bald Hills sage-grouse used areas with greater shrub canopy cover and lower grass and forb cover than recommended in habitat guidelines. Ten predictor variables were used to model suitable seasonal habitat using Maximum Entropy (maxent). All models were created for the Bald Hills population and projected to the Bureau of Land Management Cedar City Field Office management area and produced excellent model fit (AUC > 0.900). The Bald Hills population had similar nesting and winter habitat preferences as other populations but different brood-rearing and summer habitat preferences. I found local management techniques to be an important driver of seasonal habitat selection; birds selected for areas that had undergone habitat treatments (such as broadcast burn and crushing) within the previous 10 years. My results indicated the Bald Hills periphery population occupies marginal habitat and has adapted unique seasonal habitat preferences. Managers of isolated, fringe, and low-density populations should develop locally specific management guidelines to address the unique adaptations and ensure the persistence of these populations.

Several reports of North American bumble bee (Bombus Latreille) decline have been documented across the continent, but no study has fully assessed the geographic scope of decline. In this study I discuss the importance of Natural History Collections (NHC) in estimating historic bumble bee distributions and abundances, as well as in informing current surveys. To estimate changes in distribution and relative abundance I compare historic data assembled from a >73,000 specimen database with a contemporary 3-year survey of North American bumble bees across 382 locations in the contiguous U.S.A. Based on my results, four historically abundant bumble bees, B. affinis, B. occidentalis, B. pensylvanicus and B. terricola, have declined by 72 - 96% relative abundance across their native distribution, while B. bifarius, B. bimaculatus, B. impatiens, and B. vosnesenskii appear to be relatively stable. Finally, I provide some notes on the distribution, abundance, and frequency of Nosema bombi infections in Alaskan B. occidentalis.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第20443号 / 農博第2228号 / 新制||農||1050(附属図書館) / 学位論文||H29||N5064(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 神﨑 護, 教授 北島 薫, 教授 大澤 晃 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第20586号 / 農博第2238号 / 新制||農||1052(附属図書館) / 学位論文||H29||N5075(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 神﨑 護, 教授 北島 薫, 教授 井鷺 裕司 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

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The developments of species distribution modeling techniques have brought new opportunities in the field of biological invasion management. In particular, statistical niche modeling for spatio-temporal predictions of species’ distribution is a widely spread tool that has proved its efficiency. The main purpose of this Master thesis is to study applicability of species distribution modeling to invasive alien species, with the aim of supporting efficient decision-making for their prevention. Some research questions are: how useful can species distribution modeling be for invasives’ prevention? Is distribution modeling technically feasible in the case of invasive species? What types of techniques are recommended to model distributions of IAS? What are the limits of such a tool? The methods employed to answer these questions are literature review and expert advice. I found that species distribution models can provide risk maps which are necessary to enable effective invasive alien species’ prevention. However intrinsic characteristics of invasives introduce uncertainties in the predictions made. Consequently several preliminary analyses should be conducted before applying the distribution model. Finally recommendations were made on the most appropriate distribution modeling technique to use depending on the urgency of the situation and the availability of data. / Utvecklingen av metoder för modelering av artdistribution har medfört nya möjligheter inom området hantering av biologiska invasioner. Statistisk nischmodelering för spatio-temporala förutsägelser av arters distribution är ett väl använt verktyg som har visat sig vara effektivt. Det övergripande målet med det här arbetet har varit att studera hur lämpad artmodelering är vid förebyggande av invasioner av främmande arter. Det har även undersökts huruvida metoden kan bidra till bättre och enklare beslutsfattande när det kommer till att förhindra sådana invasioner. Forskningsfrågorna lyder: hur användbart är fördelningsmodelering för förebyggande av spriding av invasiva arter? Är distributionsmodelering tekniskt genomförbar när det gäller invasiva arter? Vilka olika tekniker rekommenderas för att modelera spridningen av invasiva arter? Vilka begräsningar har modelerna? De metoder som används är litteraturöversikt och expertråd. Resultaten visar att artdistributionsmodelering kan bidra till att sammanställa riskkartor som är nödvändiga för att möjliggöra ett förebyggande arbete. Men speciella egenskaper hos de invasiva arterna som är svåra att förutse skapar osäkerheter i resultatet. Därför kan preliminära analyser med fördel genomföras innan modelering. I slutsatserna återfinns rekommendationer för vilken distributionsmodelteknik man bör använda, beroende av hur brådskande situationen är och om data finns tillgängligt.

Understanding how climate determines species’ geographic distributions is an important question in ecology with direct implications for predicting climate change-driven range shifts. For Lepidoptera, growing degree-days, a measure of growing season length, has been shown to be an important predictor of species’ distributions in some cases. Most studies use a standardized estimate of base development temperature in their calculations of growing degree-days instead of a species-specific threshold so past investigations of the influence of growing degree-days on Lepidoptera distributions may not have been optimal. Species distribution models (SDMs) are a commonly used approach in ecology that typically only implicitly capture the underlying processes that limit a species’ distribution. A species-specific estimate of growing degree-days should better characterize these processes than standard thermal thresholds and thus improve the accuracy of species distribution models. In this thesis, I use species distribution modelling to model the geographic distribution of 30 moth species native to North America. I ask whether a) growing degree-days are the best climatic predictor of these moth species distributions at broad scales; b) a lab-estimated biological threshold (i.e., BDT) can scale up and improve the predictive ability of SDMs; and c) the quality of experiments used to estimate species-specific BDT influences the predictive accuracy of SDMs. To do so, I compare the predictive accuracy of a correlative model based on a commonly-used thermal threshold to define growing degree-days to a hybrid model with degree-days defined based on a species-specific thermal threshold. I found that the predictive performance of the hybrid models was indistinguishable from the correlative models likely because growing degree-days was not the best climatic predictor of the geographic distributions of the majority of these moth species. I also found that there was no link between the quality of the lab experiments and the difference in performance of the hybrid and correlative models. My findings suggest that lab-estimated thermal thresholds may not always scale up to be predictive at a broad scale and that more work is needed to leverage the data from lab experiments into broad scale SDMs. Determining the ultimate factors that limit species’ distributions will be critical in accurately predicting species’ range shifts response to future climate change.

Woodpeckers are a group of avian species that cause damage to wooden power utility structures. In the southeastern United States, Tennessee Valley Authority (TVA), has accrued an estimated $5 million USD annually from woodpecker damage. Previous work has focused on effectiveness of reactive mitigation and restoration efforts with little investigation of preventative methods. To address this knowledge gap, this study will i) use species distribution model techniques to predict damage suitability across the TVA service area, ii) use Bayesian hierarchical community model techniques to estimate species richness of the woodpecker community in the service area, and iii) recommend target areas for increased preventative measures in the service area. The suitability map indicated that damage was most likely to occur in the southwestern portions of the TVA service area. Woodpecker species richness was stable across the environmental covariate values estimated with 2-3 species found throughout the service area.