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Arbustos y pastos para restablecer la cobertura vegetal en zonas áridas del Sur de Bolivia
Santiago Lopez-Ridaura Ravi Gopal Singh (2022, [Libro])
Pastos CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURA DE CONSERVACIÓN SUELO COBERTURA DE SUELOS FERTILIDAD DEL SUELO CAMBIO CLIMÁTICO GANADERÍA VEGETACIÓN ARBUSTOS CONSERVATION AGRICULTURE SOIL LAND COVER CLIMATE CHANGE ANIMAL HUSBANDRY VEGETATION SHRUBS
Ana Luisa Garcia-Oliveira Mahalingam Govindaraj Rodomiro Ortiz (2023, [Artículo])
Bioaccessibility and Absorption Biofortified Crop Cultivars Genes and Genetic Markers Nutrient Acquisition Transport and Storage CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOAVAILABILITY ABSORPTION CLIMATE CHANGE GENETIC MARKERS GENETIC ENGINEERING NUTRIENTS TRANSPORT STORAGE
Adaptation to current and future climatic risks in agriculture: Maharashtra, India
Paresh Shirsath Anil Pimpale Pramod Aggarwal (2022, [Libro])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RISK CLIMATE RESILIENCE AGRICULTURE CLIMATE CHANGE ADAPTATION
Calibrated multi-model ensemble seasonal prediction of Bangladesh summer monsoon rainfall
Nachiketa Acharya Carlo Montes Timothy Joseph Krupnik (2023, [Artículo])
Bangladesh summer monsoon rainfall (BSMR), typically from June through September (JJAS), represents the main source of water for multiple sectors. However, its high spatial and interannual variability makes the seasonal prediction of BSMR crucial for building resilience to natural disasters and for food security in a climate-risk-prone country. This study describes the development and implementation of an objective system for the seasonal forecasting of BSMR, recently adopted by the Bangladesh Meteorological Department (BMD). The approach is based on the use of a calibrated multi-model ensemble (CMME) of seven state-of-the-art general circulation models (GCMs) from the North American Multi-Model Ensemble project. The lead-1 (initial conditions of May for forecasting JJAS total rainfall) hindcasts (spanning 1982–2010) and forecasts (spanning 2011–2018) of seasonal total rainfall for the JJAS season from these seven GCMs were used. A canonical correlation analysis (CCA) regression is used to calibrate the raw GCMs outputs against observations, which are then combined with equal weight to generate final CMME predictions. Results show, compared to individual calibrated GCMs and uncalibrated MME, that the CCA-based calibration generates significant improvements over individual raw GCM in terms of the magnitude of systematic errors, Spearman's correlation coefficients, and generalised discrimination scores over most of Bangladesh areas, especially in the northern part of the country. Since October 2019, the BMD has been issuing real-time seasonal rainfall forecasts using this new forecast system.
Multi-Model Ensemble Seasonal Forecasting CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES FORECASTING MONSOONS
Jelle Van Loon (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRIFOOD SYSTEMS SUSTAINABLE INTENSIFICATION COVID-19 CONFLICTS CLIMATE CHANGE
Carbon credits from AFOLU projects in Kodagu
A G ADEETH CARIAPPA (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CARBON AGRICULTURE CLIMATE CHANGE METHODOLOGY
Manejo de pasturas para la crianza de llamas
Santiago Lopez-Ridaura Ravi Gopal Singh (2022, [Libro])
Pasturas CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURA DE CONSERVACIÓN GANADERÍA ARBUSTOS LEGUMINOSAS FORRAJES PASTOREO SUELO CAMBIO CLIMÁTICO CONSERVATION AGRICULTURE ANIMAL HUSBANDRY SHRUBS LEGUMES FORAGE GRAZING SOIL CLIMATE CHANGE LLAMAS AGACHO
Women, economic resilience, gender norms in a time of climate change: what do we know?
Cathy Farnworth Anne Rietveld Rachel Voss Angela Meentzen (2023, [Artículo])
This literature delves into 82 research articles, published between 2016 and 2022, to develop a deep understanding of how women manage their lives and livelihoods within their agrifood systems when these systems are being affected, sometimes devastatingly, by climate change. The Findings show that four core gender norms affect the ability of women to achieve economic resilience in the face of climate change operate in agrifood production systems. Each of these gender norms speaks to male privilege: (i) Men are primary decision-makers, (ii) Men are breadwinners, (iii) Men control assets, and (iv) Men are food system actors. These gender norms are widely held and challenge women’s abilities to become economically resilient. These norms are made more powerful still because they fuse with each other and act on multiple levels, and they serve to support other norms which limit women’s scope to act. It is particularly noteworthy that many institutional actors, ranging from community decision-makers to development partners, tend to reinforce rather than challenge gender norms because they do not critically review their own assumptions.
However, the four gender norms cited are not hegemonic. First, there is limited and intriguing evidence that intersectional identities can influence women’s resilience in significant ways. Second, gender norms governing women’s roles and power in agrifood systems are changing in response to climate change and other forces, with implications for how women respond to future climate shocks. Third, paying attention to local realities is important – behaviours do not necessarily substantiate local norms. Fourth, women experience strong support from other women in savings groups, religious organisations, reciprocal labour, and others. Fifth, critical moments, such as climate disasters, offer potentially pivotal moments of change which could permit women unusually high levels of agency to overcome restrictive gender norms without being negatively sanctioned. The article concludes with recommendations for further research.
Economic Resilience Intersectional Identities Women Groups Support CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ECONOMICS RESILIENCE CLIMATE CHANGE GENDER NORMS AGRIFOOD SYSTEMS WOMEN
Lovemore Chipindu Walter Mupangwa Isaiah Nyagumbo Mainassara Zaman-Allah (2023, [Artículo])
Autoregressive Integrated Moving Average Facebook Prophet Hidden Markov Model Regression Regression with Hidden Logistic Process CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COASTAL AREAS SEMIARID ZONES SUBHUMID ZONES RAINFALL CLIMATE CHANGE