Watershed systems are experiencing rapid changes to water quality and hydrologic regimes due in part to climate-induced changes in temperature and precipitation, urbanization, and increases in aquatic invasive species. Aquatic invasive species are one of the primary threats to ecosystems, contributing to loss of biodiversity, altered hydrologic regimes, and stream degradation. Urban land use and climatic factors influence the spread of invasive species, presenting greater challenges for future invasive species management. There is a need for more research that evaluates the watershed process in connection with urban land use and climate change factors in relation to invasive species spread. This study will examine factors of climate change and land use that may be influencing the spread and occurrence of aquatic invasive plants within the Connecticut River watershed. There will be four species involved in this study: Eurasian milfoil (Myriophyllum spicatum), Variable milfoil (Myriophyllum heterophyllum), Hydrilla (Hydrilla verticillate), and the European water chestnut (Trapa natans). Hydrological conditions within the watershed will be analyzed using the SWAT model through the HAWQS interface. ArcGIS Pro will be used to combine and prepare data so that it may be utilized through MaxEnt. MaxEnt will be used to create species distribution models to estimate the probability of the presence of invasive aquatic plant species in the Connecticut river watershed.

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.

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Aedes aegypti is the principal vector for dengue transmission across large areas of the world. Understanding where this critically important vector lives is paramount to preventing the continued expansion of dengue globally. Using 1981-2010 bioclimatic (bioclim) variables, as well as additional environmental variables and elevation data, multiple MaxEnt models were constructed for Ae. aegypti within the South American continent to identify ecologically important variables and areas of persistent high suitability. All models had acceptable AUC scores (> 0.70), indicating accurate model fitting. Annual mean precipitation and temperature were found to be important model variables; however, when added, humidity became the more predictive variable. Elevation had minimal, if any, impact on model construction predictability. When utilizing MaxEnt models, non-traditional climatic variables, i.e., humidity, were significantly more predictive for Ae. aegypti than the standard bioclim variables. Optimal variable selection is critical to understanding current and potential future areas of high transmission risk.

Invasive species are a growing issue that will compound under climate change. Rising temperatures, fluctuating precipitation and new transportation pathways will create new opportunities for invasive establishment. A direct and impactful consequence of climate change is the removal of climatic barriers to invasive survival. Species distribution modeling (SDM) for invasives must include an evaluation of future establishment potential so that managers can prioritize regions forecasted as high risk under climate change. Climatic SDMs effectively support pan-invasion risk assessments by forecasting potential invaded areas globally where climatic barriers have shifted the potential for establishment. Rarely is regional-scale climate variation considered in invasive SDMs, despite its relevance for pests that establish outside their native regional climate. Here, I apply a climatic pest risk framework to the Spotted Lanternfly grape pest (Lycorma delicatula, SLF). I assess how climate change shifts the establishment potential of SLF across important viticultural regions worldwide. I contrast an ensemble of three regional-scale SDMs to a global-scale SDM, which provided multiple predictions on how future regional climate variation might shift national SLF risk levels, impacting the global wine market. I found that the global suitable area for SLF will increase under climate change, with range expansion outpacing contractions by about 1.1 million km2. Expansions will primarily occur at present northern range edges in Europe, North America, and East Asia, and contractions will occur across the southern hemisphere. Next, 307 global viticultural regions (29% of 1,063 total sampled) will decrease in risk for SLF establishment and only 532 (50% of 1,063) will remain at any risk under climate change. Loss in SLF establishment risk under climate change followed a latitudinal gradient in the northern hemisphere. Meanwhile, only 85 known SLF populations (11% of 769 rarefied sample) will destabilize under climate change. Populations within the US and South Korean invaded ranges will remain stable with respect to climate. Our regional-scale ensemble emphasized the importance of mean winter temperature as a constraint on SLF establishment, with activity dropping sharply at -3°C. This method for regional-scale ensemble modeling should be utilized in similar invasive or climate change SDM applications to make more refined SDM predictions and to reduce uncertainty. Viticulturalists can and should use our provided tools and model framework to understand the risk of SLF establishment at their locality as climate change removes barriers to this pest’s establishment globally. / Biology

Made available in DSpace on 2016-06-02T19:26:23Z (GMT). No. of bitstreams: 1 TOCHET_Caroline_2013_V_ 1.pdf: 367702 bytes, checksum: e45cebba8c597ec047bc77ddd848aef5 (MD5) Previous issue date: 2013-11-29 / Universidade Federal de Sao Carlos / The Cerrado biome is located in Central Brazil Plateau occupying 2,036.448 km². Its weather is characterized by seasonality and the landscape by a vegetation mosaic. Those factors contribute for Cerrado to be known as the richest savanna in the world. It is considered one of the 20 World Hotspots, because of its high level of diversity and threat. The Cerrado is still poorly known, especially in relation to its history, origin and distribution through time, which are important factors to comprehend its recent diversity. This project aims to determine the historically stable areas within Cerrado by modelling 14 marsupial and small rodent species potential distribution for past and present scenarios, to relate the detected areas with endemism levels, to compare the identified patterns with known biogeography hypothesis of other Cerrado organism groups, and to suggest priority areas for inventory. To generate the potential distribution maps I used the digital bases available by WWF and IBGE and the SIG ARCMAP 10.1 software. The potential distribution modelling was implemented by maximum-entropy algorithm (MAXENT), using WORLDCLIM 1.4 and PALEOCLIMATE MODELING INTERCOMPARISON PROJECT (PMIP) climate variables data. The open vegetation biomes of South America were the base area for modelling, with 2.5 layers resolution (ca. 5 km²). To statistically evaluate model performance, I used the area under the curve (AUC) of the receiver operating characteristic (ROC) plot. All models presented high AUC values. The hypothesis that during the Last Glacial Maximum (LGM) the open formations expanded and the forest ones retracted, while the open formations retracted and forests expanded during the Last Interglacial (LIG) were supported by 20 of the 28 proposed models. The historically stable areas include the Parecis , Chapada dos Guimarães, Chapada Diamantina and Central Brazil Plateaus, the western Minas Gerais and the Espinhaço range. Those areas agree to other historically stable areas and/or endemism areas already proposed for other taxa, such as birds, squamate reptiles, anuran, lepdoptera and plants. They also reflect lack of inventory data. So, the fauna of those areas should be better investigated and its material used in future phylogenetic and phylogeographic studies. Conservation should also be considered in the light of their climatic stability, resulting in the possible creation, increasing or maintaining of Conservation Units. / O bioma Cerrado localiza-se no planalto do Brasil Central e ocupa uma área de 2.036.448 km²; tem seu clima marcado pela sazonalidade e é constituído por um mosaico de diferentes fitofisionomias, um dos fatores que mais contribui para que seja a savana com maior riqueza de espécies do mundo. Por ser um bioma com alto nível de diversidade e estar dentre os mais ameaçados do planeta, é considerado um dos 20 hotspots mundiais. Apesar disto, pouco se conhece a respeito do Cerrado, em especial sobre sua história, incluindo sua origem e distribuição ao longo do tempo, fatores muito importantes para a compreensão da atual diversidade presente no bioma. Este projeto tem como objetivos determinar áreas historicamente estáveis no Cerrado a partir de modelos de distribuição potencial de 14 espécies de marsupiais e pequenos roedores para cenários passados e atuais, relacionar as áreas detectadas com aquelas que atualmente possuem maior concentração de espécies endêmicas, e comparar os padrões levantados em relação a hipóteses biogeográficas já propostas para outros organismos que habitam o Cerrado, além de sugerir áreas prioritárias para inventário. Para produzir os mapas de distribuição potencial foram utilizadas bases digitalizadas disponibilizadas pela WWF e pelo IBGE e o software SIG ARCMAP 10.1. Para a modelagem foi utilizado o algoritmo de máxima entropia (MAXENT). As variáveis climáticas foram obtidas a partir da base de dados do WORLDCLIM 1.4 e do PALEOCLIMATE MODELING INTERCOMPARISON PROJECT (PMIP) e a área considerada para gerar os modelos foi aquela que incluiu as formações abertas da América do Sul, conhecida como Diagonal Seca , com resolução das camadas ambientais de 2.5 (ca. 5 km²). Para verificar o desempenho dos modelos produzidos foi utilizada a análise da área sob a curva (area under the curve, AUC) ROC (Receiver Operating Characteristic). Todos os modelos gerados apresentaram alto valor de AUC. A hipótese de que durante os períodos glaciais, como o Último Máximo Glacial (Last Glacial Maximum LGM), as formações abertas teriam se expandido e as áreas florestadas se retraído, e durante os períodos inter-glaciais, como o Último Inter-glacial (Last Interglacial LIG), o oposto teria acontecido, isto é, expansão das formações florestais e retração das áreas abertas, foi corroborada por 20 dos 28 modelos propostos. As áreas historicamente estáveis geradas pelos modelos das 14 espécies incluem o Planalto dos Parecis e a Chapada dos Guimarães (MT), o Planalto Central brasileiro (GO e DF), o oeste de Minas Gerais, na região leste do Triângulo Mineiro, a Serra do Espinhaço (MG) e a Chapada Diamantina (BA). Essas áreas aqui identificadas condizem com áreas historicamente estáveis e/ou áreas de concentração de endemismos anteriormente propostas para outros táxons como aves, répteis Squamata, anuros, lepidópteros e plantas. Os modelos também apontaram estas áreas como áreas de lacunas de amostragem, representando regiões a serem melhor investigadas em campo quanto à sua fauna e possível fonte de material para estudos futuros de filogenia e filogeografia. Além disso, são importantes para conservação, tendo em vista sua estabilidade climática, representando possíveis áreas alvo de criação, ampliação e manutenção de Unidades de Conservação.

I denna uppsats analyseras utbredningen av fornlämningar i Mälardalen och deras förhållande till miljö och geologi, med fokus på att hitta okända fornlämningar med hjälp av digitala verktyg. Kulturmiljöregistret baserat på inventeringar genomförda över tid studeras. Verktygen GIS och MaxEnt beskrivs, samt deras användning för arkeologiska landskapsstudier. De används för analys av fornlämningarnas spridningsbild. Ett antal lämningskategorier valdes ut för analys, och resultaten jämförs med tidigare forskning. Arkeologi och statistik kombinerat med naturvetenskapliga metoder används för att skapa modeller av okända lämningar som kan användas för att försöka återfinna dessa genom historiska kartor, LiDAR eller med geofysik. Spridningsmönster av figurristningar från bronsåldern påvisas ha en stark korrelation till bergarten kvartsarenit, en upptäckt som kan leda till nya tolkningar av lämningskategorin och landskapsutnyttjandet i Uppland. Uppsatsen visar på modeller och tekniker för landskapsanalys som kan vara användbara för att identifiera tidigare okända mönster och bättre förstå förhistoriska landskap samt för att skapa en brygga till framtida arkeologisk forskning med stöd av AI, drönare och stora datamängder. / In this paper, the distribution of ancient remains in the Mälardalen and their relationship to the environment and geology is analysed, focusing on finding unknown ancient remains using digital tools. Kulturmiljöregistret created from inventories carried out over time is studied. The tools GIS and MaxEnt are described, as well as their use for archaeological landscape studies and for analysis of distribution patterns of ancient remains. A number of categories of remains were selected for analysis, and the results were compared with previous research. Archaeology and statistics combined with natural science are used to create models of unknown remains for recovering them with the aid of historical maps, LiDAR or geophysics. Distribution patterns of figure carvings from the Bronze Age are shown to have a strong correlation to the rock type quartz arenite, a discovery that can lead to new interpretations of this category of remains and the landscape utilization in Uppland. The paper shows models for landscape analysis which can be useful for identifying previously unknown patterns and for better understanding of prehistoric landscapes, as well as to create a bridge to future archaeological research supported by AI, drones and large data sets.

Tanzania’s Ruaha landscape is an international priority area for large carnivore conservation, harbouring roughly 10% of the world’s lions, and important populations of leopards and spotted hyaenas. However, these large carnivore populations are threatened by intense retaliatory killing due to human-carnivore conflict on village land around Ruaha National Park (RNP), mostly as a result of livestock predation by lions, leopards and spotted hyaenas. Moreover, a current lack of ecological data on the distribution of these carnivores hinders the development of effective strategies for conservation and targeted conflict mitigation in this landscape. This study aimed to identify the most significant ecogeographical variables (EGVs) influencing the distribution of lions, leopards and spotted hyaenas across the Ruaha landscape, and to map areas of conservation importance for these species. In addition, the study assessed the influence of EGVs on livestock predation risk by these carnivores in the village land around RNP, and generated a predictive map of predation risk. The relative importance of livestock husbandry practices and EGVs in terms of influencing predation risk within enclosures was also investigated. Proximity to rivers was the most important variable influencing the distribution of large carnivores in Ruaha, and contributed to predation risk of grazing livestock. The traditional livestock husbandry adopted in bomas appeared insufficient to alleviate the inherent risk of predation by large carnivores. The study produced the first detailed maps of lion, leopard and spotted hyaena distribution in the critically important Ruaha landscape, and identified likely livestock depredation hotspots. These results will target conflict mitigation approaches around Ruaha, by identifying particularly high-risk areas for livestock enclosures and grazing stock. Improving husbandry in these areas could help reduce livestock depredation and retaliatory carnivore killing, therefore reducing one of the most significant conservation threats in this critically important landscape.