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Biodiversity in Mexico is threatened by Land Use/Cover Change (LUCC) and Climate Change (CC). Identifying what sites will be most vulnerable to these threats can help to prioritise conservation, mitigation and adaptation strategies and target limited resources. Therefore, the aims of this study are 1) to identify the most vulnerable sites to LUCCs under different socio-economic and CC scenarios, and 2) to assess the vulnerability of endemic and threatened vertebrate species to establish prioritization strategies for biodiversity conservation. Spatially explicit socio-economic scenarios were created at national and subnational level (Chapter 3). National LUCC models were then developed using the DINAMICA EGO software (Chapter 4). These models were run for three future time slices (2020s, 2050s and 2080s) and two contrasting future climate and socio-economic scenarios to determine biodiversity vulnerability (Chapter 5). Vulnerability was estimated by quantifying the exposure, sensitivity and adaptive capacity to LUCC and CC. This framework integrates national information about the priority sites of biodiversity conservation and their future extent of natural covers under future socio-economic and climate conditions. Finally, the vulnerability framework was also applied in a regional case-study in three municipalities of southern Mexico (Chapter 6). Results reveal that temperate forest is the most vulnerable ecosystem type in Mexico, followed by natural grasslands and tropical evergreen forests. Agriculture is the driver of this threat, which is projected to expand to feed an increasing population under dryer climatic conditions. More than 40% of endemic and endangered mammals are in places ranking from medium to extremely high vulnerability, followed by the 28% of the amphibians, 25% and 23% for reptiles and birds, respectively. These vertebrates are principally distributed on temperate forests and tropical dry forests. In the regional scale, rain-fed agriculture (RfA) and anthropogenic grasslands are the principal LUCC drivers, threatening 31 species of endangered vertebrates. A local strategy for creating corridors between patches close to rivers from the south to the north of one municipality is supported as conservation priority for the regional biodiversity. This research presents a novel approach for prioritising conservation strategies in highly biodiverse countries using readily available data sources, demonstrated at different spatial and temporal scales.

<p>Land use/cover has shown significant changes during the past three decades in Ethiopia especially in the highlands of the country. That resulted in changes in streamflows and other hydrological processes. The existing land and water resources system of the area is adversely affected due the rapid growth of population, deforestation, surface erosion and sediment transport. The main objective of this study is to evaluate the impact of land use/cover changes in the hydrology of <em>Beles</em> Basin, Ethiopia. The physically based hydrologic model, SWAT, was developed for the <em>Beles</em> basin, Ethiopia by combining geospatial and climatic data. ArcGIS has been used to process geospatial data which includes the Digital Elevation Model (DEM) which has a resolution of 90 m, land use/cover and soil maps. A simple Interpolation technique has been used to fill in the missing precipitation data. The GIS interface version of SWAT (ArcSWAT) has the capability to utilize ArcGIS to facilitate input data preparation and output data generation. Idrisi Andes in cooperation with ArcGIS 9.2 used to generate landuse/cover maps from Landsat data of three different years. Three SWAT models were set up using the three generated land use/cover maps and used to evaluate the land use/cover change and its impacts on the streamflow of study basin. The primary hydrological model was evaluated through sensitivity analysis, model calibration, and model validation for realistic prediction of the different hydrological components in the basin. Out of twenty six flow parameters sixteen parameters were found to be sensitive. But the most sensitive ten parameters were selected and used for model calibration. The model calibration was carried out using observed streamflow data from 01 January 2001 to 31 December 2002 and a validation period from 01 January 2003 to 31 December 2004. The coefficient of determinations (<em>R2</em>) was 0.74 and the Nash-Sutcliffe simulation efficiency (<em>NSE</em>) was 0.62which indicated that the model was able to predict streamflow with reasonable accuracy. However, the hydrograph of the cumulative hydrographs of the calibration and validation periods showed significant discrepancies between the observed and the simulated data of each period.  The average yearly flow volume of the observed streamflow on the cumulative hydrograph of the calibration period has exceeded the simulated streamflow. On the other hand on the cumulative hydrograph of the validation period the average yearly flow volume of the simulated streamflow was higher than the observed streamflow. The simulated result of the streamflow data from different land use/cover maps revealed that the change in the land use/cover classes of the basin throughout the study periods.</p> / QC 20100707

Watershed regulation of water, carbon and nutrient dynamics support food, drinking water and human development. Projected climate changes and land use/cover change (LUCC) have been identified as drivers of watershed nutrient and hydrological processes and are likely to happen jointly in the future decades. Studying climate change and LUCC impacts on watersheds' streamflow and nutrients dynamics is therefore essential for future watershed management. This research aimed to unveil how climate change and LUCC affect water and nutrient dynamics in the Missisquoi River watershed, Vermont. We used 12 scenarios of future climate data (2021 – 2050) generated by three GCMs (ccsm4, mri-cgcm3, and gfdl-esm2m) under four Representative Concentration Pathways (RCPs). For LUCC, we used three different scenarios generated by the Interactive Land Use Transition Agent-Based Model (ILUTABM). The three LUCC scenarios were Business As Usual (BAU), Prefer Forest (proForest), and Prefer Agriculture (proAg). New land use maps were generated every 10 years for the period of 2021 – 2050. Combining each climate change and LUCC scenario resulted in 36 scenarios that were used to drive Regional Hydro-Ecologic Simulation System (RHESSys) ecohydrological model. In chapter 3, we used RHESSys to study streamflow. We found climate was the main driver for streamflow because climate change directly controlled the system water input. For streamflow, climate change scenarios had larger impacts than LUCC, different LUCCs under the same climate change scenario had similar annual flow patterns. In chapter 4, we used RHESSys to study streamflow NO3-N and NH4-N load. Because fertilizer application is the major source for nitrogen export, LUCC had larger impacts; watersheds with more agricultural land had larger nitrogen loads. In chapter 5, we developed RHESSys-P by coupling the DayCent phosphorus module with RHESSys to study climate change and LUCC impacts on Dissolved Phosphorus (DP) load. RHESSys-P was calibrated with observed DP data for 2002 – 2004 and validated with data for 2009 - 2010. In both calibration and validation periods, simulated DP basically captured patterns of observed DP. In the validation period, the R2 of simulated vs observed DP was 0.788. Future projection results indicated BAU and proForest annual loads were around 4.0 × 104 kg under all climate change scenarios; proAg annual loads increased from around 4.0 × 104 kg in 2021 to 1.6 × 105 kg in 2050 under all climate change scenarios. The results showed LUCC was the dominant factor for dissolved phosphorus loading. Overall, our results suggest that, while climate drives streamflow, N and P fluxes are largely driven by land use and management decisions. To balance human development and environmental quality, BAU is a feasible future development strategy.

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The dynamic of land use/cover in Brazilian semiarid watershed is under influence not only by human actions in these areas, but also by the climatic seasonality in this region. It is necessary know the relationship between the mapping of the use and land cover using remote sensing techniques and the climate seasonality of semiarid regions. Thus, the aim of this study was to use remote sensing techniques to map and classify the land use/cover in the catchment of the OrÃs reservoir and identify the influence of the climate on the variations of type of classes mapped during the studied period. The OrÃs reservoir is located in the Southwestern of the state of CearÃ, Brazil, and its catchment has 24,900 kmÂ. The survey of land use/cover of Catchment in OrÃs Reservoir (BHAO) was performed by MAXVER method (Maximum Likelihood) classification image objects using satellites image Landsat 5 - TM and Landsat 8 â OLI. The LANDSAT 5 images to 2003, 2005 and 2008 were obtained from the National Institute of Spatial Research (INPE), and the Landsat 8 image to 2013 was obtained by the United States Geological Survey (USGS). Satellite images from the second semester period to each year were used to avoid clouds and rainfall above the vegetation of the studied area. The classes of land use/cover of the catchment in the OrÃs reservoir presented a dynamic that is influenced not only by human activity in that region, but they were influenced also by factors such as climate, topography and vegetation physiology, specifically the deciduous. It was observed that in those years that occurred heavy rainfall this factor helped the classes as Caatinga Rala and Caatinga Densa. However in those years named dry like 2013, the areas of the Antropizada class increased. Results showed that the changes occurred during the studied period were caused not only by the humansâ actions in that environment but they were caused by climatic factors too. Thus its important analyze the date of the satellite images were obtained. This decrease the action of the climate in the image classify. The deciduous characteristic of Caatinga vegetation, causes changes in the areas due to changes in vegetation of the region. With the leaves falling in dry season these areas present spectral response like the Antropizada class. Higher regions favored the presence of Caatinga Densa class, due to the microclimate and the greatest difficulty that these areas are under to human action. Despite the remote sensing techniques being important tools to help us classify the land use/cover, in regions with deciduous vegetation (Caatinga) it is necessary observe the climatic seasonality, because it has heavy influence in the type of land use/cover presented in regions like Caatinga. / A dinÃmica do uso e cobertura do solo de bacias hidrogrÃficas do semiÃrido brasileiro à influenciada nÃo apenas pela aÃÃo humana nessas Ãreas, mas tambÃm pela sazonalidade climÃtica dessa regiÃo. Verifica-se a necessidade do conhecimento da relaÃÃo existente entre o levantamento do uso e cobertura do solo a partir de tÃcnicas de sensoriamento remoto e a sazonalidade climÃtica de regiÃes semiÃridas. Dessa forma, objetivou-se com este estudo mapear e classificar o uso e cobertura do solo da bacia hidrogrÃfica do aÃude OrÃs atravÃs de tÃcnicas de sensoriamento remoto e identificar qual a influÃncia exercida pelo clima nas variaÃÃes das Ãreas das classes encontradas ao longo do perÃodo objeto de estudo. O aÃude OrÃs està localizado no sudoeste do estado do CearÃ, e sua bacia possui uma Ãrea de 24.900 km2. O levantamento de uso e cobertura do solo da Bacia HidrogrÃfica do AÃude OrÃs (BHAO) foi realizado atravÃs de classificaÃÃo pelo mÃtodo MAXVER (MÃxima VerossimilhanÃa) das imagens dos satÃlites LANDSAT 5 - TM e LANDSAT 8 - OLI. As imagens LANDSAT 5 dos anos de 2003, 2005 e 2008 foram obtidas junto ao Instituto Nacional de Pesquisas Espaciais (INPE), jà a imagem LANDSAT 8 do ano de 2013 foi obtida junto ao USGS (United States Geological Survey). Foram selecionadas imagens do segundo semestre de cada ano de estudo por conta da menor presenÃa de nuvens, bem como para que dessa forma fosse minimizado o efeito das precipitaÃÃes pluviomÃtricas sobre a vegetaÃÃo da regiÃo. As Ãreas das classes de uso e cobertura do solo da bacia hidrogrÃfica do aÃude OrÃs apresentaram uma dinÃmica influenciada nÃo apenas pela aÃÃo humana na Ãrea, mas tambÃm fatores como o clima, topografia e a fisiologia da vegetaÃÃo, mais precisamente a caducifÃlia. Anos com uma elevada precipitaÃÃo pluviomÃtrica favoreceram classes como Caatinga Rala e Caatinga Densa, sendo observado o contrÃrio em anos considerados secos como 2013, onde as Ãreas da classe Antropizada obtiveram um aumento considerÃvel em suas Ãreas. Observou-se que as modificaÃÃes ocorridas durante o perÃodo analisado nÃo sÃo resultantes apenas das intervenÃÃes humanas no ambiente, mas tambÃm dos fatores climÃticos. Assim deve-se levar em conta tambÃm a Ãpoca em que as imagens foram geradas para que se evite ou amenize a influencia do clima na classificaÃÃo das imagens. A caducifÃlia, caracterÃstica da vegetaÃÃo Caatinga, provoca mudanÃas nas Ãreas devido a alteraÃÃes na vegetaÃÃo da regiÃo. Com a queda das folhas na Ãpoca seca do ano essas Ãreas passam a ter a resposta espectral de Ãreas com caracterÃsticas da classe Antropizada. RegiÃes mais elevadas favoreceram a presenÃa da classe Caatinga Densa, devido ao microclima e a maior dificuldade que essas Ãreas apresentam à aÃÃo humana. Apesar das tÃcnicas de sensoriamento remoto se apresentarem como uma importante ferramenta por facilitar o levantamento das classes de uso e cobertura do solo, entende-se que em regiÃes onde a vegetaÃÃo apresenta caracterÃsticas de caducifÃlia (Caatinga), deve-se levar em conta ao sazonalidade climÃtica, pois esse fator influencia diretamente o levantamento das classes de uso e cobertura do solo presentes nas regiÃes da Caatinga.

京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24954号 / 地環博第245号 / 新制||地環||49(附属図書館) / 京都大学大学院地球環境学舎環境マネジメント専攻 / (主査)教授 星野 敏, 准教授 鬼塚 健一郎, 教授 伊藤 孝行 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DFAM

Land use/cover has shown significant changes during the past three decades in Ethiopia especially in the highlands of the country. That resulted in changes in streamflows and other hydrological processes. The existing land and water resources system of the area is adversely affected due the rapid growth of population, deforestation, surface erosion and sediment transport. The main objective of this study is to evaluate the impact of land use/cover changes in the hydrology of Beles Basin, Ethiopia. The physically based hydrologic model, SWAT, was developed for the Beles basin, Ethiopia by combining geospatial and climatic data. ArcGIS has been used to process geospatial data which includes the Digital Elevation Model (DEM) which has a resolution of 90 m, land use/cover and soil maps. A simple Interpolation technique has been used to fill in the missing precipitation data. The GIS interface version of SWAT (ArcSWAT) has the capability to utilize ArcGIS to facilitate input data preparation and output data generation. Idrisi Andes in cooperation with ArcGIS 9.2 used to generate landuse/cover maps from Landsat data of three different years. Three SWAT models were set up using the three generated land use/cover maps and used to evaluate the land use/cover change and its impacts on the streamflow of study basin. The primary hydrological model was evaluated through sensitivity analysis, model calibration, and model validation for realistic prediction of the different hydrological components in the basin. Out of twenty six flow parameters sixteen parameters were found to be sensitive. But the most sensitive ten parameters were selected and used for model calibration. The model calibration was carried out using observed streamflow data from 01 January 2001 to 31 December 2002 and a validation period from 01 January 2003 to 31 December 2004. The coefficient of determinations (R2) was 0.74 and the Nash-Sutcliffe simulation efficiency (NSE) was 0.62which indicated that the model was able to predict streamflow with reasonable accuracy. However, the hydrograph of the cumulative hydrographs of the calibration and validation periods showed significant discrepancies between the observed and the simulated data of each period.  The average yearly flow volume of the observed streamflow on the cumulative hydrograph of the calibration period has exceeded the simulated streamflow. On the other hand on the cumulative hydrograph of the validation period the average yearly flow volume of the simulated streamflow was higher than the observed streamflow. The simulated result of the streamflow data from different land use/cover maps revealed that the change in the land use/cover classes of the basin throughout the study periods.

Land use/cover change (LUCC) is a major force affecting ecosystems and the services theyprovide at local, regional and global levels. Traditionally, LUCC has been approached as aseries of linear and unidirectional single cause–effect processes, but it is now increasinglyincorporating notions from complex systems to enrich this view. This study explores thepotential benefits of using the concept of regime shifts to understand LUCC. A globalcropland cover dataset was analyzed to empirically identify patterns that suggest theexistence of alternate regimes. Results indicate that in some countries cropland-dominatedand (semi)wild landscapes likely represent alternate social-ecological regimes.Furthermore, results suggest that a theoretical feedback relating market access andagglomeration of economic activates plays a strong role in maintaining these alternate regimes in some contexts. These results highlight the need for LUCC studies to go beyondthe focus on external drivers and environmental template conditions, to incorporate feedback mechanisms and the potential for regime shifts to better understand the nature of LUCC.

MAIA, Anthony Rafael Soares. Influência da sazonalidade climática no levantamento do uso e cobertura do solo, com uso de geotecnologias, em uma bacia hidrográfica do semiárido. 2015. 67 f. Dissertação (mestrado em engenharia agrícola)- Universidade Federal do Ceará, Fortaleza-CE, 2015. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-03-22T19:38:11Z No. of bitstreams: 1 2016_dis_arsmaia.pdf: 1298594 bytes, checksum: 1df5ae7d6e79f3715ef35fea2864b14e (MD5) / Approved for entry into archive by José Jairo Viana de Sousa (jairo@ufc.br) on 2016-05-18T19:34:31Z (GMT) No. of bitstreams: 1 2016_dis_arsmaia.pdf: 1298594 bytes, checksum: 1df5ae7d6e79f3715ef35fea2864b14e (MD5) / Made available in DSpace on 2016-05-18T19:34:31Z (GMT). No. of bitstreams: 1 2016_dis_arsmaia.pdf: 1298594 bytes, checksum: 1df5ae7d6e79f3715ef35fea2864b14e (MD5) Previous issue date: 2015 / The dynamic of land use/cover in Brazilian semiarid watershed is under influence not only by human actions in these areas, but also by the climatic seasonality in this region. It is necessary know the relationship between the mapping of the use and land cover using remote sensing techniques and the climate seasonality of semiarid regions. Thus, the aim of this study was to use remote sensing techniques to map and classify the land use/cover in the catchment of the Orós reservoir and identify the influence of the climate on the variations of type of classes mapped during the studied period. The Orós reservoir is located in the Southwestern of the state of Ceará, Brazil, and its catchment has 24,900 km². The survey of land use/cover of Catchment in Orós Reservoir (BHAO) was performed by MAXVER method (Maximum Likelihood) classification image objects using satellites image Landsat 5 - TM and Landsat 8 – OLI. The LANDSAT 5 images to 2003, 2005 and 2008 were obtained from the National Institute of Spatial Research (INPE), and the Landsat 8 image to 2013 was obtained by the United States Geological Survey (USGS). Satellite images from the second semester period to each year were used to avoid clouds and rainfall above the vegetation of the studied area. The classes of land use/cover of the catchment in the Orós reservoir presented a dynamic that is influenced not only by human activity in that region, but they were influenced also by factors such as climate, topography and vegetation physiology, specifically the deciduous. It was observed that in those years that occurred heavy rainfall this factor helped the classes as Caatinga Rala and Caatinga Densa. However in those years named dry like 2013, the areas of the Antropizada class increased. Results showed that the changes occurred during the studied period were caused not only by the humans’ actions in that environment but they were caused by climatic factors too. Thus its important analyze the date of the satellite images were obtained. This decrease the action of the climate in the image classify. The deciduous characteristic of Caatinga vegetation, causes changes in the areas due to changes in vegetation of the region. With the leaves falling in dry season these areas present spectral response like the Antropizada class. Higher regions favored the presence of Caatinga Densa class, due to the microclimate and the greatest difficulty that these areas are under to human action. Despite the remote sensing techniques being important tools to help us classify the land use/cover, in regions with deciduous vegetation (Caatinga) it is necessary observe the climatic seasonality, because it has heavy influence in the type of land use/cover presented in regions like Caatinga. / A dinâmica do uso e cobertura do solo de bacias hidrográficas do semiárido brasileiro é influenciada não apenas pela ação humana nessas áreas, mas também pela sazonalidade climática dessa região. Verifica-se a necessidade do conhecimento da relação existente entre o levantamento do uso e cobertura do solo a partir de técnicas de sensoriamento remoto e a sazonalidade climática de regiões semiáridas. Dessa forma, objetivou-se com este estudo mapear e classificar o uso e cobertura do solo da bacia hidrográfica do açude Orós através de técnicas de sensoriamento remoto e identificar qual a influência exercida pelo clima nas variações das áreas das classes encontradas ao longo do período objeto de estudo. O açude Orós está localizado no sudoeste do estado do Ceará, e sua bacia possui uma área de 24.900 km2. O levantamento de uso e cobertura do solo da Bacia Hidrográfica do Açude Orós (BHAO) foi realizado através de classificação pelo método MAXVER (Máxima Verossimilhança) das imagens dos satélites LANDSAT 5 - TM e LANDSAT 8 - OLI. As imagens LANDSAT 5 dos anos de 2003, 2005 e 2008 foram obtidas junto ao Instituto Nacional de Pesquisas Espaciais (INPE), já a imagem LANDSAT 8 do ano de 2013 foi obtida junto ao USGS (United States Geological Survey). Foram selecionadas imagens do segundo semestre de cada ano de estudo por conta da menor presença de nuvens, bem como para que dessa forma fosse minimizado o efeito das precipitações pluviométricas sobre a vegetação da região. As áreas das classes de uso e cobertura do solo da bacia hidrográfica do açude Orós apresentaram uma dinâmica influenciada não apenas pela ação humana na área, mas também fatores como o clima, topografia e a fisiologia da vegetação, mais precisamente a caducifólia. Anos com uma elevada precipitação pluviométrica favoreceram classes como Caatinga Rala e Caatinga Densa, sendo observado o contrário em anos considerados secos como 2013, onde as áreas da classe Antropizada obtiveram um aumento considerável em suas áreas. Observou-se que as modificações ocorridas durante o período analisado não são resultantes apenas das intervenções humanas no ambiente, mas também dos fatores climáticos. Assim deve-se levar em conta também a época em que as imagens foram geradas para que se evite ou amenize a influencia do clima na classificação das imagens. A caducifólia, característica da vegetação Caatinga, provoca mudanças nas áreas devido a alterações na vegetação da região. Com a queda das folhas na época seca do ano essas áreas passam a ter a resposta espectral de áreas com características da classe Antropizada. Regiões mais elevadas favoreceram a presença da classe Caatinga Densa, devido ao microclima e a maior dificuldade que essas áreas apresentam à ação humana. Apesar das técnicas de sensoriamento remoto se apresentarem como uma importante ferramenta por facilitar o levantamento das classes de uso e cobertura do solo, entende-se que em regiões onde a vegetação apresenta características de caducifólia (Caatinga), deve-se levar em conta ao sazonalidade climática, pois esse fator influencia diretamente o levantamento das classes de uso e cobertura do solo presentes nas regiões da Caatinga.