Canadian Prairie agriculture, in general, is expected to benefit under climate change with increasing mean temperatures projected for the immediate future. However, a number of knowledge gaps still exist. Foremost among these is the measurement of the effects of extreme climate events in a given year as well as their long-term impact on the supply of agricultural products, and also the financial situation of farms. In addition, the economic impacts of climate change on livestock operations are relatively under-studied. In particular, knowledge of the impacts on Prairie beef cattle remains more guesswork than research-based evidence. This dissertation assesses the impact of changes in the normal climate as well as the impact of climate extremes by including projected inter-annual climate variability. The economic impact of these changes on crops, beef cattle activities and the viability of farms in mixed operation settings is measured. Correspondingly, this work presents alternative adaptation measures and their likely use in managing mixed farm operations for future extreme weather events. For the analysis, two study sites are selected: (1) the Oldman River Basin of Alberta, called Pincher Creek, and (2) the Swift Current Creek Basin of Saskatchewan, called Swift Current. This study is a part of a larger project entitled “Vulnerability and Adaptation to Climate Extremes in the Americas” and the study sites are intended to represent the project catchment areas in the provinces of Alberta and Saskatchewan. I develop what I call a MF-CCE model (Mixed Farm model for the economic impact assessment of Climate Change and Extremes). The MF-CCE is a whole farm simulation model that integrates models of beef cattle production, crop production and climate changes into farm level economic decisions. Simulations are conducted over a 30-year period in each climate scenario: the first of these is a baseline climate scenario from 1971-2000, and I also simulate future climate change impacts for the 2041-2070 era. The modelled farms produce enough crops, hay and pasture to support the beef cattle feed demand. Pasture demand and supply are linked by specific pasture requirements and productivity. Beef herd feed grain demand and on-farm supply are linked by a linear programming optimization algorithm. Crop mix for the market is selected through the development of a multi-year linear programming problem that maximizes the present value of gross margins. Crop and hay productivity are estimated through the Food and Agriculture Organization’s (FAO’s) AquaCrop (version 3) modeling framework, while annual pasture productivity is estimated using the Forage Calculator for Native Rangeland obtained from the Saskatchewan Research Council (SRC). The AquaCrop is a water-driven crop simulation model, termed a crop water productivity (WP) model which simulates the yield response of herbaceous crops to water availability and use. The model is believed to be superior in simulating crop yield in the conditions where water is a key limiting factor in crop production (FAO, 2011). Summarizing the results of the simulation, prairie crop production is expected to benefit under the simulated climate change scenario. Increases in crop productivity generate about 60% higher profits in the Pincher Creek site and about 57% more for the Swift Current site. Due to increases in grain and hay productivity, more area is made available to produce grain for the market. This effectively doubles the crop net return at the Pincher Creek site and triples the crop return at the Swift Current site. A consideration of future pasture response to the climate change scenario is important in estimating climate change consequences for live beef production as well as on the economic return of a mixed farm. If the pasture productivity decreases, as assumed under the regular pasture yield scenario in the study, appropriate adaptation is necessary for the farm to benefit from future climate change. Under this scenario, beef production activities in the future are projected to gain by 50% in Pincher Creek and 40% in Swift Current compared to the baseline scenario. If pasture productivity under the future scenario increases in a manner similar to crop yield increases, existing pastureland will be enough to maintain beef herds into the future. In turn, this strategy will mitigate the cost of beef herd adaptation during climate extremes, and instead gains from beef cattle production would be 35% higher in Swift Current and 6% higher in Pincher Creek relative to gains under regular pasture yield conditions. At the farm level, with beef cattle and crop production combined, substantial gains are projected for both of the study sites. Farm net profit is estimated to increase by more than 35% at the Pincher Creek site and more than 140% at the Swift Current site under the future scenario. Income risk will also be lower in this scenario, as highlighted by a lower coefficient of variation of net farm profit. Farm financial indicators tracked in this study – farm cash flow, family cash flow, and farm net worth – all indicate that the farm’s financial position will be much better in the future climate scenario. At the Pincher Creek site, a few problematic liquidity events are forecasted under the future climate scenario, but in light of significant improvements in other economic indicators, overall, this effect is negligible. The appropriate choice of adaptation strategies for managing beef herds during extreme climate events plays an important role in determining the profitability of not only beef cattle activities, but also the financial position at the whole farm level. However, the choice of adaptations is contextual: the preference of adaptation strategy differs across activities, farms and period of study. For beef cattle activities, maintaining the beef herd without any compromise on herd size and implementing a regular feeding plan is preferred to other adaptation alternatives. At the whole farm level for the Pincher Creek site, culling the herd is preferred under the baseline scenario, while the purchasing feed option is preferred under the future climate scenario. At the Swift Current site, culling the herd is the preferred strategy under both scenarios. Commodity prices and the cost of farm inputs profoundly affect the economic position of the farm under the future climate change scenario. If commodity prices and cost of production remain the same as under the baseline scenario, future farm net profit is estimated to be 50% higher for the Pincher Creek site and about 25% higher for the Swift Current site, compared to profits under projected future prices. This result implies that the pure effect of climate change could be much higher if costs and prices do not change. Results of this dissertation indicate that average Prairie mixed farms, as represented by these study farms, remain economically viable under both the baseline and future scenarios. The results also suggest that the overall gain to these farms under a future climate change scenario would be positive. The potential severity of extreme climate events in the future, at least for the future scenario period simulated in this study, would not be significant enough to threaten the future economic viability of Prairie agriculture. However, the research also highlights the importance of policies that support farmers when they endure losses in years of extreme climate events. Further research on evaluating different Best Management Practices (BMPs) in dealing with droughts, for example, would be helpful in taking advantage of future climate change. Policy development to enhance the longer-term adaptive capacity of Prairie farmers, such as development of early warning systems for climate extremes, or the development of drought tolerant cultivars of crops and forages, would be most helpful in coping with climate extremes in the future.

A wide range of ecological communities ranging from polar terrestrial to tropical marine environments are affectedby global climate change. Over the last century, atmospheric temperature has increased by an average of 0. 60 C andis expected to rise by 1.1- 6.40C over the next 100 years. This rising temperature has increased the intensity andfrequency of weather extremes due to which a large number of species are facing risk of extinction. Studies haveshown that species existing on lower latitude are more sensitive to temperature variability compared to speciesexisting on higher latitude but temperature is increasing rapidly in higher latitude compare to lower latitude. Thisuneven distribution of temperature sensitive species and warming rate has highlighted the need for combined studiesof temperature variability and sensitiveness of species to predict how the ecosystems will respond to increasinglyvariable climate. Using a generalized Rosenzweig-MacArthur model, I explored how temperature variability andsensitivity of species will affect the extinction risks of species and how the connectance and species-richness ofecological communities will govern this response. This study showed that the risk of extinction of species mostlydepends on their sensitivity to temperature deviation from the optimum value and level of temperature variability.Among these two, sensitivity of species to temperature deviation was most prominent factor affecting extinction risk.In this study, connectance did not show any effect on mean extinction risk and time taken by a certain proportion ofspecies to reach pre-defined extinction thresholds. But, species-richness showed some effect on mean extinction riskof species. It was found that risk of extinction of species in species-rich communities was higher compared tospecies-poor communities. Species-rich communities also took shorter time before they lost 1/6 of the species. Thepresent study also suggests a possible tipping point due to increasing temperature variability in near future. In furtherstudies, different sensitivity of species at different trophic levels and the possible evolution of sensitivity of speciesshould also be consider while predicting how ecological communities will respond to changing climate in the longrun.

A heterogeneidade dos elementos que compreendem a climatologia tropical se evidencia no comportamento das chuvas nessa região macroclimática. Para tanto, compreender seu comportamento temporal e espacial assume grande relevância, em função do impacto dessas na dinâmica urbana e rural, bem como para seu planejamento estratégico. Verificar seu curso interanual em episódios diários é grande desafio, nesse sentido. Com isso, o estudo objetivou analisar as chuvas diárias na região de São Carlos/SP, a fim de compreender sua evolução temporal e espacial, além de avaliar possíveis tendências para essa, que se insere na dinâmica tropical (sazonalmente chuvoso/estiagem). Foram analisados 39 anos de dados diários de chuvas, em 7 postos pluviométricos, e que estiveram com, ao menos, 95% dos dados consistentes. Utilizou-se de índices climáticos (script RClimdex) e do Laplace trend factor para analisar os dados temporais históricos e de tendência. Observou-se que os valores dos índices flutuam entre as estações, mas que esses estão associados aos fenômenos da ZCAS (Zona de Convergência do Atlântico Sul) e dos SFs (Sistemas Frontais), que regem o clima no sudeste da América do Sul. Além disso, notou-se que o sul da área estudada apresenta maior concentração pluviométrica, em função dos aspectos geomorfológicos (e até de ocupação), bem como notou-se o aumento de episódios extremos de chuvas diárias. As chuvas diárias, portanto, tendem a concentração, uma vez que os volumes anuais diminuem ou aumentam (ciclicamente), mas notam-se precipitações pluviométricas mais intensas (mm) em dias chuvosos, além do aumento da tendência dos dias com chuvas extremas. Futuros estudos que ampliem a área de estudo e possíveis correlações poder-se-ão reafirmar tais resultados, conforme verificado em estudos prévios. / Rainfall shows the heterogeneity of tropical climatology. Temporal and spatial behavior is highly relevant to verify the impact on urban and rural dynamics and strategic planning. The inter-annual course in daily episodes is the biggest challenge in that regard. The objective of this study was to analyze daily rainfall in the São Carlos/SP region, understand its temporal and spatial evolution, as well as to evaluate possible trends for this, which are part of tropical (seasonally rainy/dry) dynamics. A total of 39 years of daily rainfall data were analyzed in 7 pluviometric stations, with at least 95% of the data consistent using Climatic indexes (RClimdex script), and the Laplace trend factor to analyze temporal and trend data. It was observed that the values of the indexes fluctuate between the stations. These are associated with the phenomena of the South Atlantic Convergence Zone (SACZ) and SFs (Frontal Systems), which regulates the climate in the south-east of South America. Also, the south of the studied area presents a higher rainfall concentration, due to the geomorphological (and even occupation) aspects, as well as the increase of extreme episodes of daily rains. Therefore, daily rains tend to concentrate, since annual volumes decrease or increase (cyclically), but the rainfall (mm) is more intense on rainy days, in addition to the increase in the tendency of the days with extreme rains. Future studies that broaden the area of study and possible correlations may reaffirm such results, as verified in previous studies.

Made available in DSpace on 2015-04-11T14:02:58Z (GMT). No. of bitstreams: 1 Andre Alves Nogueira.pdf: 3385945 bytes, checksum: 5c7b555b59610b2dac767f2900bfe5be (MD5) Previous issue date: 2014-02-20 / Weather Extreme Events (WEE) can cause natural disasters because they are often accompanied by dangerous physical activities which cause significant damage to people and properties, including some deaths. A way to soften the damage caused by these disasters is to use Weather Warning System (WWS). These kind of systems can detect an imminent risk and, different types of alerts can be triggered in order to mobilize the emergency personnel in advance. This research aims to help the Amazon Protection System (SIPAM) to solve the communication problem with the alert and mobilization. It is intended, primarily, to assist the Civil Defense with the affected population by WEE. A comparative investigation was performed in ten studies aiming to understand and analyze the main characteristics of a Warning System, which were incorporated into this research, highlighting the support of a Multi-Agent System to assist the WWS, and the use of SMS (Short Message Service) technology and E-mail for sending the alert. System Tests showed that the approach proved promising, with shipping times smaller alerts those found in the literature with a high rate of confirmed users. Also the process of sending the alert factor being faster helps to minimize the effects of EME with the affected population. / Eventos Meteorológicos Extremos (EME) podem gerar desastres naturais, geralmente acompanhados de atividades físicas perigosas que provocam danos significativos a pessoas e propriedades, gerando um grande número de vítimas ou até mesmo mortes. Uma maneira de mitigar os danos causados por estes desastres é a utilização de Sistemas de Alertas Meteorológicos (SAM); sendo detectado um risco iminente, diferentes tipos de alertas podem ser acionados objetivando a mobilização antecipada das equipes de emergência. O presente trabalho visa contribuir com o Sistema de Proteção da Amazônia (SIPAM) ou com órgãos semelhantes para a resolução do problema de comunicação referente à emissão dos alertas e a mobilização, destinando-se principalmente à ação da Defesa Civil e órgãos competentes junto à população em função dos EME ocorridos. Nesta pesquisa foi realizada uma investigação comparativa com dez trabalhos objetivando conhecer e analisar as principais características de um Sistema de Alerta, as quais foram incorporadas neste projeto, destacando-se o apoio de um Sistema Multiagente para auxiliar o SAM, e o uso das tecnologias de SMS (Short Message Service) e E-mail para o envio do alerta. Testes do sistema evidenciaram que a abordagem adotada mostrou-se promissora, apresentando tempos de envio de alertas menores que os encontrados na literatura e com alta taxa de usuários confirmados, fator de muita importância para a minimização dos efeitos dos EME junto à população atingida.