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

Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes

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

Analysis of adoption of conservation agriculture practices in southern Africa: mixed-methods approach

Adane Tufa Hambulo Ngoma Paswel Marenya Christian Thierfelder (2023, [Artículo])

In southern Africa, conservation agriculture (CA) has been promoted to address low agricultural productivity, food insecurity, and land degradation. However, despite significant experimental evidence on the agronomic and economic benefits of CA and large scale investments by the donor community and national governments, adoption rates among smallholders remain below expectation. The main objective of this research project was thus to investigate why previous efforts and investments to scale CA technologies and practices in southern Africa have not led to widespread adoption. The paper applies a multivariate probit model and other methods to survey data from 4,373 households and 278 focus groups to identify the drivers and barriers of CA adoption in Malawi, Zambia, and Zimbabwe. The results show that declining soil fertility is a major constraint to maize production in Zambia and Malawi, and drought/heat is more pronounced in Zimbabwe. We also find gaps between (a) awareness and adoption, (b) training and adoption, and (c) demonstration and adoption rates of CA practices in all three countries. The gaps are much bigger between awareness and adoption and much smaller between hosting demonstration and adoption, suggesting that much of the awareness of CA practices has not translated to greater adoption. Training and demonstrations are better conduits to enhance adoption than mere awareness creation. Therefore, demonstrating the applications and benefits of CA practices is critical for promoting CA practices in all countries. Besides, greater adoption of CA practices requires enhancing farmers’ access to inputs, addressing drudgery associated with CA implementation, enhancing farmers’ technical know-how, and enacting and enforcing community bylaws regarding livestock grazing and wildfires. The paper concludes by discussing the implications for policy and investments in CA promotion.

Adoption Focus Group Discussion CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CONSERVATION AGRICULTURE CLIMATE CHANGE

Chapter 7. The climate–security nexus Securing resilient livelihoods through early warning systems and adaptive safety nets

Peter Läderach Paresh Shirsath Steven Prager (2023, [Capítulo de libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CONFLICTS VULNERABILITY EARLY WARNING SYSTEMS

Genetic improvement of global wheat, including progress for enhancing insect resistance

Leonardo Abdiel Crespo Herrera (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC IMPROVEMENT WHEAT BREEDING CLIMATE CHANGE DISEASE RESISTANCE YIELDS

Phenotypic assessment of genetic gain from selection for improved drought tolerance in semi-tropical maize populations

Terence Molnar Somak Dutta Thanda Dhliwayo Samuel Trachsel Michael Lee (2023, [Artículo])

Drought Tolerant Population Topcross Water Deficit CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DROUGHT TOLERANCE WATER MAIZE CLIMATE CHANGE GENETIC GAIN

Redesigning crop varieties to win the race between climate change and food security

Kevin Pixley Jill Cairns Santiago Lopez-Ridaura Chris Ojiewo Baloua Nébié Godfrey Asea Biswanath Das Benoit Joseph Batieno Clare Mukankusi Sarah Hearne Kanwarpal Dhugga Sieglinde Snapp Ernesto Adair Zepeda Villarreal (2023, [Artículo])

Crop Breeding Expert Survey CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPPING SYSTEMS FOOD SECURITY CROPS

Challenging the climate change effects on agriculture: need business unusual

ML JAT (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE FOOD SYSTEMS CONSERVATION AGRICULTURE SUSTAINABILITY INNOVATION

Mining alleles for tar spot complex resistance from CIMMYT's maize Germplasm Bank

Martha Willcox Juan Burgueño Daniel Jeffers Zakaria Kehel Rosemary Shrestha Kelly Swarts Edward Buckler Sarah Hearne Charles Chen (2022, [Artículo])

Maize Landraces Maize Genetic Resources Allelic Diversity Rare Alleles Phenotypic Characterization Tropical Maize Phyllachora maydis CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE LANDRACES GENETIC RESOURCES ALLELES FOLIAR DISEASES CLIMATE CHANGE

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

Mustafa Kamal Timothy Joseph Krupnik (2024, [Artículo])

High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks. To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April–May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF). Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season. In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.

Synthetic Aperture Radar Random Forest Boro Rice In-Season Maps CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SAR (RADAR) RICE FLOODING CLIMATE CHANGE