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.

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.

No description available.

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 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.

Budongo Forest Reserve (BFR) is a flagship reserve for primate conservation due to its abundant chimpanzee (Pan troglodytes) population, and its current management policy for multiple economic, conservation and environmental benefits. The identification and better understanding of the structure and dynamics of the forest/plant community types, patterns of species distribution and quantitative properties of their diversity is important to the conservation and sustainable management of tropical rainforests. This study seeks to contribute to a better understanding of the BFR forest community types, species diversity patterns and environmental correlates, as well as natural regeneration processes (i.e. seedling establishment and sprouting). Data on vegetation and environmental variables were collected using rectangular 50 x 100m (0.5 ha) plots, sub-divided into five equal contiguous (20 x 50 m) 0.1 ha sub-plots. Data on land-use/cover changes, and relevant associated socio-economic parameters were collected through the analysis of multi-temporal satellite imagery and field observations, as well as interviews of local households and key informants. The study revealed significant land-use/cover changes, with the area under sugarcane cultivation increasing over 17-fold, from 690 ha in 1988 to 12729 ha in 2002, with a concomitant loss of about 4680 ha (8.2% loss) of forest/woodland, mainly in the southern part of BFR. These changes are attributed to agricultural expansion, a rapidly increasing human population, exacerbated by large influxes of refugees, lack of alternative sources of income, conflicts of interest and political interference in the management of BFR, and an unclear land tenure system. The need for more land for agricultural expansion and the loss of woodlands (a source of building materials and fuelwood for the local communities) is leading to the invasion of and encroachment on BFR, which threatens plant and wild animal conservation. The study revealed that the vegetation of BFR is formed by a mosaic of plant communities, with the major forest types being; Pseudospondias microcarpa Swamp Forest, Funtumia elastica - Pouteria altissima, Lasiodiscus mildbraedi - Khaya anthotheca and Cynometra alexandri - Rinorea ilicifolia forest communities. Canonical correspondence analysis (CCA) indicated that soil nutrients (Si, Ca, N, Fe and Li) and anthropogenic disturbances are the main factors controlling forest community patterns. The variances explained as a proportion of total inertia were relatively high (0.53 and 0.56 for basal area and abundance, respectively), showing how well the measured variables explained species composition. These plant communities differed significantly in terms of woody species diversity and richness; being highest in the Pseudospondias microcarpa swamp and lowest in the Cynometra alexandri-Rinorea ilicifolia forest. However, about 48 species were shared between the forest community types. A total of 269 species representing 171 genera and 51 families was recorded. Fisher’s alpha-diversity ranged 4.45-30.59 and 3.07-29.7 for stem diameters ≥2.0 cm and ≥10 cm, respectively, being significantly higher for stem diameters ≥2.0 cm. The use of stem diameters ≥2.0 cm unveiled 53 more species (19.7%), with only 216 species recorded for the standard ≥10 cm dbh minimum size usually applied in tropical forests. A SHE analysis also showed greater richness (ln(S)) and H diversity for the >2.0 cm than the ≥10cm stem diameters. Hence, the study reaffirmed that the use of 10 cm as a minimum dbh in woody plant diversity studies in forests, where many tree species rarely exceed 10 cm stem diameter, is highly likely to underestimate diversity and richness, potentially biasing the understanding of diversity patterns. The most speciose families were Euphorbiaceae, Fabaceae, Rubiaceae, Moraceae, Meliaceae, Rutaceae, Annonaceae, and Flacourtiaceae, accounting for 147 species. Families with the highest Familial Importance values (FIV) were; Fabaceae (17.5), followed by Euphorbiaceae (16.3), and Ulmaceae (8.35). The BFR exhibits characteristics intermediate between log-normal and log-series species-abundance distributions, indicating a community with a small number of abundant species and a relatively large proportion of rare species. Both Whittaker’s (βw) and the Morisita-Horn Index measures of β-diversity consistently showed higher β-diversity for logged and arboricide treated areas, followed by logged only, and then nature reserve historical management practice types. β-diversity was relatively high at the total forest community scale, but lower for stem diameter ≥2.0 cm than ≥10.0 cm data. Environmental variables significantly explained 66.5% and 61.9% of the variance in species composition for stem diameter ≥2.0 cm and ≥10.0 cm data, respectively. Hence, the variation in species composition of BFR is characterised by significant spatial patterns, and the patterns in β-diversity are to a great extent associated with environmental heterogeneity (i.e. soil nutrients, topographic and light gradients) and anthropogenic disturbances. Investigation of natural regeneration showed that sprouting is generally common among the woody species, with both canopy and sub-canopy trees sprouting prolifically. Of the 122 species affected by ii harvesting, and tree and branch fall disturbances, 199 (97.5%) from 31 families sprouted from the cut stumps, with only Caloncoba crepiniana (De Wild. & Th.Dur.) Gilg exhibiting both stem and root sprouting. Stump basal diameter, height, bark-thickness, and height of stump above the ground at which the first sprout emerged, were significant predictors of sprouting ability among individuals. Number of sprouts/stump differed significantly among families, species, and stump size-classes. Of the 241 seedling species, representing 46 families, about 30.3% were rare (only 2-10 individuals); while 12% were very rare (only 1 individual each). Cynometra alexandri C.H. Wright and Lasiodiscus mildbraedii Engl. were the most abundant seedlings and also among the most widely distributed species in the forest. Analysis of similarity (ANOSIM) revealed significant differences in seedling composition between transects, but not between topographic positions or historical management practice types. Canonical Correspondence Analysis (CCA) showed that the measured environmental variables significantly explained 59.4% of the variance in seedling species distributions, with the three most important variables being organic matter, titanium and leaf area index (LAI; an indicator of light availability below the canopy). Hence, the important mechanisms influencing regeneration via seedlings in BFR operate through the soil system, and the ground and canopy vegetation characteristics. Nine of the 15 intensively studied multiple-use species, namely L. mildbraedii, Celtis Mildbraedii Engl., Pouteria altissima (A. Chiev.) Aubrev. & Pellegr., Chrysophyllum albidum G. Don., C. alexandri, Diospyros abyssinica (Hiern) F. White, Funtumia elastica (Preuss) Stapf., Chrysophyllum perpulchrum Hutch. & Dalz, and Antiaris toxicaria (Pers.) Lesch. had highly negative size-class distribution (SCD) slopes and substantial seedling regeneration. While Alstonia boonei De Wild. and Cordia millenii Bak. had weakly negative SCD slopes and pulsed or sporadic regeneration patterns. The wide distribution of seedlings for a variety of species, and with most of the intensively studied species having population structures showing healthy regeneration patterns, suggests that BFR is currently experiencing a continuous regeneration phase. In conclusion, the gradients in the vegetation of BFR are a reflection not only of site conditions as shown by the edaphic and abiotic factors, but also the history of human interventions.

A expansão da cana-de-açúcar tem ocorrido de maneira intensa no cenário brasileiro, especialmente no estado de São Paulo e região Centro-Oeste do Brasil, com potencial de causar significativos impactos destacando-se a degradação do solo, a poluição dos recursos hídricos, a pressão sobre outras culturas ou matas nativas, conflitos pelo uso do solo, entre outros. O objetivo dessa pesquisa é avaliar a aplicação de técnicas de modelagem do uso do solo em conjunto com instrumentos de política ambiental por meio da modelagem da expansão da cana-de-açúcar na bacia do Tietê/Jacaré (UGRHI 13). A bacia hidrográfica em questão caracteriza-se pela presença de regiões de alta vulnerabilidade ambiental, em termos da fragilidade do território e presença de atributos ambientais de significativo interesse, bem como pelo fato de suas principais atividades econômicas estarem vinculadas ao agronegócio. Para a consecução dos objetivos estabelecidos, o modelo GEOMOD presente na plataforma IDRISI foi aplicado para a projeção da expansão da cana-de-açúcar em 2019. De modo a verificar a aplicabilidade das informações geradas, a projeção gerada foi cotejada a dois instrumentos de planejamento regional: o Zoneamento Agroambiental do Setor Sucroalcooleiro e o Plano de Bacia da UGRHI 13. Constatou-se que a aplicação de modelos de uso do solo para a projeção de alterações nos padrões de ocupação do território apresenta-se como prática promissora que pode ser integrada ao planejamento e gestão ambiental a nível regional, sendo, entretanto, necessário melhorar a performance do modelo elaborado a fim de gerar informações mais confiáveis para os tomadores de decisão. / Sugarcane expansion has been significant in Brazil, especially in São Paulo State and Midwest Region. This crop has potential of causing significant impacts, such as: soil degradation, pollution of water resources, pressure on other crops or native forests, conflicts regarding land use, among others. The purpose of this study is to verify the application of land use cover change models with environmental policy instruments by modeling sugarcane expansion in Tietê/Jacaré watershed (UGRHI 13). This water basin is characterized by high vulnerability environmental areas in terms of fragility territorial and presence of significant environmental attributes, as well as the fact that its main economic activities are linked to agribusiness. GEOMOD land use cover change model was applied to project sugarcane expansion in 2019. In order to verify the applicability of sugarcane projection, it was used in the context of the Sugarcane Agro-Industry Zoning and the Water Basin Plan. The results showed that land use cover change models application for sugarcane projection is presented as a promising practice that can be integrated to the regional environmental planning. However, it´s necessary to improve the performance of the model in order to generate more reliable information to the decision makers.

Economic changes such as rising açaí prices and the availability of off-farm employment are transforming the landscape of the Amazonian várzea, subject to decision-making at the farming household level. Land use change results from complex human-environment interactions which can be addressed by an agent-based model. An agent-based model is a simulation model composed of autonomous interacting entities known as agents, built from the bottom-up. Coupled with cellular automata, which forms the agents’ environment, agent-based models are becoming an important tool of land use science, complementing traditional methods of induction and deduction. The decision-making methods employed by agent-based models in recent years have included optimization, imitation, heuristics, classifier systems and genetic algorithms, among others, but multiple methods have rarely been comparatively analyzed. A modular agent-based model is designed to allow the researcher to substitute alternative decision-making methods. For a smallholder farming community in Marajó Island near Ponta de Pedras, Pará, Brazil, 21 households are simulated over a 40-year period. In three major scenarios of increasing complexity, these households first face an environment where goods sell at a constant price throughout the simulated period and there are no outside employment opportunities. This is followed by a scenario of variable prices based on empirical data. The third scenario combines variable prices with limited employment opportunities, creating multi-sited households as members emigrate. In each scenario, populations of optimizing agents and heuristic agents are analyzed in parallel. While optimizing agents allocate land cells to maximize revenue using linear programming, fast and frugal heuristic agents use decision trees to quickly pare down feasible solutions and probabilistically select between alternatives weighted by expected revenue. Using distributed computing, the model is run through several parameter sweeps and results are recorded to a cenral database. Land use trajectories and sensitivity analyses highlight the relative biases of each decision-making method and illustrate cases where alternative methods lead to significantly divergent outcomes. A hybrid approach is recommended, employing alternative decision-making methods in parallel to illustrate inefficiencies exogenous and endogenous to the decision-maker, or allowing agents to select among multiple methods to mitigate bias and best represent their real-world analogues.

Economic changes such as rising açaí prices and the availability of off-farm employment are transforming the landscape of the Amazonian várzea, subject to decision-making at the farming household level. Land use change results from complex human-environment interactions which can be addressed by an agent-based model. An agent-based model is a simulation model composed of autonomous interacting entities known as agents, built from the bottom-up. Coupled with cellular automata, which forms the agents’ environment, agent-based models are becoming an important tool of land use science, complementing traditional methods of induction and deduction. The decision-making methods employed by agent-based models in recent years have included optimization, imitation, heuristics, classifier systems and genetic algorithms, among others, but multiple methods have rarely been comparatively analyzed. A modular agent-based model is designed to allow the researcher to substitute alternative decision-making methods. For a smallholder farming community in Marajó Island near Ponta de Pedras, Pará, Brazil, 21 households are simulated over a 40-year period. In three major scenarios of increasing complexity, these households first face an environment where goods sell at a constant price throughout the simulated period and there are no outside employment opportunities. This is followed by a scenario of variable prices based on empirical data. The third scenario combines variable prices with limited employment opportunities, creating multi-sited households as members emigrate. In each scenario, populations of optimizing agents and heuristic agents are analyzed in parallel. While optimizing agents allocate land cells to maximize revenue using linear programming, fast and frugal heuristic agents use decision trees to quickly pare down feasible solutions and probabilistically select between alternatives weighted by expected revenue. Using distributed computing, the model is run through several parameter sweeps and results are recorded to a cenral database. Land use trajectories and sensitivity analyses highlight the relative biases of each decision-making method and illustrate cases where alternative methods lead to significantly divergent outcomes. A hybrid approach is recommended, employing alternative decision-making methods in parallel to illustrate inefficiencies exogenous and endogenous to the decision-maker, or allowing agents to select among multiple methods to mitigate bias and best represent their real-world analogues.

A expansão da cana-de-açúcar tem ocorrido de maneira intensa no cenário brasileiro, especialmente no estado de São Paulo e região Centro-Oeste do Brasil, com potencial de causar significativos impactos destacando-se a degradação do solo, a poluição dos recursos hídricos, a pressão sobre outras culturas ou matas nativas, conflitos pelo uso do solo, entre outros. O objetivo dessa pesquisa é avaliar a aplicação de técnicas de modelagem do uso do solo em conjunto com instrumentos de política ambiental por meio da modelagem da expansão da cana-de-açúcar na bacia do Tietê/Jacaré (UGRHI 13). A bacia hidrográfica em questão caracteriza-se pela presença de regiões de alta vulnerabilidade ambiental, em termos da fragilidade do território e presença de atributos ambientais de significativo interesse, bem como pelo fato de suas principais atividades econômicas estarem vinculadas ao agronegócio. Para a consecução dos objetivos estabelecidos, o modelo GEOMOD presente na plataforma IDRISI foi aplicado para a projeção da expansão da cana-de-açúcar em 2019. De modo a verificar a aplicabilidade das informações geradas, a projeção gerada foi cotejada a dois instrumentos de planejamento regional: o Zoneamento Agroambiental do Setor Sucroalcooleiro e o Plano de Bacia da UGRHI 13. Constatou-se que a aplicação de modelos de uso do solo para a projeção de alterações nos padrões de ocupação do território apresenta-se como prática promissora que pode ser integrada ao planejamento e gestão ambiental a nível regional, sendo, entretanto, necessário melhorar a performance do modelo elaborado a fim de gerar informações mais confiáveis para os tomadores de decisão. / Sugarcane expansion has been significant in Brazil, especially in São Paulo State and Midwest Region. This crop has potential of causing significant impacts, such as: soil degradation, pollution of water resources, pressure on other crops or native forests, conflicts regarding land use, among others. The purpose of this study is to verify the application of land use cover change models with environmental policy instruments by modeling sugarcane expansion in Tietê/Jacaré watershed (UGRHI 13). This water basin is characterized by high vulnerability environmental areas in terms of fragility territorial and presence of significant environmental attributes, as well as the fact that its main economic activities are linked to agribusiness. GEOMOD land use cover change model was applied to project sugarcane expansion in 2019. In order to verify the applicability of sugarcane projection, it was used in the context of the Sugarcane Agro-Industry Zoning and the Water Basin Plan. The results showed that land use cover change models application for sugarcane projection is presented as a promising practice that can be integrated to the regional environmental planning. However, it´s necessary to improve the performance of the model in order to generate more reliable information to the decision makers.