Variable climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum) in Asia: results from a continental-scale modeling approach

Crop fungal diseases constitute a major cause of yield loss. The development of crop disease monitoring and forecasting tools is an important effort to aid farmers in adapting to climate variability and change. Recognizing weather as a main driver of fungal disease outbreaks, this work assesses the climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum, MoT) development in Asian wheat-producing countries. MOT was reported for the first time in Bangladesh in 2016 and could spread to other countries, provided that environmental conditions are suitable to spore development, distribution, and infection. With results from a generic infection model driven by air temperature and humidity, and motivated by the necessity to assess the potential distribution of MoT based on the response to weather drivers only, we quantify potential MOT infection events across Asia for the period 1980–2019. The results show a potential higher incidence of MOT in Bangladesh, Myanmar, and some areas of India, where the number of potential infection (NPI) events averaged up to 15 during wheat heading. Interannual trends show an increase in NPI over those three countries, which in turns show their higher interannual variability. Cold/dry conditions in countries such as Afghanistan and Pakistan appear to render them unlikely candidates for MOT establishment. The relationship between seasonal climate anomalies and NPI suggests a greater association with relative humidity than with temperature. These results could help to focus future efforts to develop management strategies where weather conditions are conducive for the establishment of MOT

On the Utility of Agronomic Monsoon Onset Definitions for Rainfed Aman Rice in Bangladesh

The monsoon-season ‘aman' rice crop contributes approximately 40% of total rice production in Bangladesh, where per-capita rice consumption rates are among the highest in the world. Aman rice is primarily rainfed and relies largely on monsoon rainfall, more specifically monsoon onset and withdrawal. Aman rice farmers’ perception on the monsoon onset for the preparation of seedling does not necessarily coincide with typical meteorological onset definitions and varies with different locations. Therefore, agronomic definitions of monsoon onset, rather than meteorological definitions are needed in order to produce climate forecast information that can better support smallholder farmers’ decision making, and the definitions should be tailored for different regions. In this study, we analyzed historical daily rainfall from three regional weather stations across a north-south gradient in Bangladesh where rainfed transplanted rice is the dominant summer crop. We defined threshold numbers including the duration of the initial wet spell, amount of rainfall received during the initial wet spell, length of dry spell during the monsoon, and the maximum amount of rainfall received during the dry spell to develop a set of actionable and region-specific agronomic onset definitions. Because transplanting dates can affect crop productivity, a region-specific onset definition was evaluated in terms of crop model simulated attainable yields in comparison with the results of (a) conventional meteorological onset defined by the quantity of rainfall received and (b) static onset date definitions. When year-to-year varying agronomic onset definition was used predicted attainable yields were higher than those derived from traditional fixed onset date in the case of fully rainfed condition. If irrigation is available at the time of transplanting, however, simulated yields did not show distinctive differences between the different onset methods, underscoring how irrigation can be used as a climate-smart adaptive strategy to cope with monsoon variability. Our tailored agronomic definitions of monsoon onset can be used to assist rainfed rice farmers in choosing more favourable dates for the establishment of seedbeds and transplanting, especially when more advanced seasonal or sub- seasonal forecasts are available in addition to real-time and high-resolution rainfall monitoring

An Action Plan for Adaptation in Bangladesh Agriculture under Climate Change

This report is the outcome of a study titled 'An Action Plan for Adaptation in Bangladesh Agriculture under Climate Change', carried out with support from the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). This report prepared by the Center for Environmental and Geographic Information Services (CEGIS) delineates an action plan to prioritize adaptation options after considering the inputs by experts and scrutiny by stakeholders. It aims to promote precision agriculture and commercialization of crop agriculture with strong institutional and financial footing to tackle climate change

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh

Acknowledgments: The International Maize and Wheat Improvement Center (CIMMYT) carried out this work with support of the CGIAR research program on Climate Change, Agriculture and Food Security (CCAFS) and the Climate Services for Resilient Development (CSRD; https://ccafs.cgiar.org/research/projects/climate-services-resilient-development-south-asia) for South Asia project supported by USAID. This work was also supported by the USAID and Bill and Melinda Gates Foundation (BMGF) supported Cereal Systems Initiative for South Asia (CSISA; https://csisa.org) CCAFS’ work is supported by CGIAR Fund Donors and through bilateral funding agreements. For details please visit https://ccafs.cgiar.org/donors. The views expressed in this paper cannot be taken to reflect the official opinions of CCAFS, USAID, or BMGF, and shall not be used for advertising.Peer reviewedPublisher PD

Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh

Funding Information: The International Maize and Wheat Improvement Center (CIMMYT) carried out this work with support of the CGIAR research program on Climate Change, Agriculture and Food Security (CCAFS) and the Climate Services for Resilient Development (CSRD; https://ccafs.cgiar.org/research/projects/climate-services-resilient-development-south-asia ) for South Asia project supported by USAID . This work was also supported by the USAID and Bill and Melinda Gates Foundation (BMGF) supported Cereal Systems Initiative for South Asia (CSISA; https://csisa.org ). CCAFS' work is supported by CGIAR Fund Donors and through bilateral funding agreements. For details please visit https://ccafs.cgiar.org/donors . The views expressed in this paper cannot be taken to reflect the official opinions of CCAFS, USAID, or BMGF, and shall not be used for advertising. We sincerely acknowledge the input and support provided by various stakeholders in Bangladesh during stakeholder meetings. We are thankful to Robel Takele and Sanjay Pothireddy for graphics assistance.Peer reviewedPublisher PD

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040-2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins' hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario

Participatory and Institutional Approaches to Agricultural Climate Services: A South and Southeast Asia Regional Technical & Learning Exchange

In order to share experience and boost capacity in agricultural climate services, a three-day workshop titled ‘Participatory and Institutional Approaches to Agricultural Climate Services Development: A South and South East Asia Regional Technical and Learning exchange” was held between September 17-19, 2017, in Dhaka, Bangladesh, with more than 50 leaders in agricultural climate services from 11 countries attending. The workshop was sponsored by the U.S. Agency for International Development (USAID) behalf of the Climate Services for Resilient Development (CSRD). The workshop was organized by the International Maize and Wheat Improvement Center (CIMMYT) alongside the SERVIR and Climate Services Support Activity and CSRD South Asian partners

Decision support system for assessing rice yield losses from annual flooding in Bangladesh

Thesis (Ph. D.)--University of Hawaii at Manoa, 1995.Includes bibliographical references (leaves 132-137).Microfiche.xviii, 137 leaves, bound maps (some col.) 29 cmIn one out of every two years, 20 percent of Bangladesh is inundated. Floods that occur at frequencies of one in 5, 10, 20 and 50 years inundate 30, 37, 43, and 52 percent of the country, respectively. The nation pays a heavy price in human sufferings and property from these floods. The purpose of this research is to assemble a prototype decision support system that could enable extension agents to search for alternative ways to minimize flood damage to agricultural crops and policy makers to assess yield losses and prepare for food shortages. The prototype system consists of a crop simulation model for rice, a rule-based system for assessing rice yield loss from flooding and a geographic information system for aggregating site-specific flood damage into yield loss for the entire nation. The system is designed to accommodate more than one crop, but this study was restricted to the rice crop. It is able to simulate the growth, development and grain yield of rice varieties cultivated by Bangladeshi farmers in any location and season under a wide range of management options. Simulated rice yields for a flood-free crop is used as a basis for computing yield loss from floods of varying severity. A rule-based system called FLOODEX was developed to compute yield loss from flooding which is expressed as a percent of the simulated non-flooded grain yield and computed on the bases of yield loss from depth of submergence, duration of submergence, growth stage and clarity of water. The expected yield is a fraction of the simulated yield, and production for a homogeneous area is the product of yield and area. The geographic information system enables yield loss and production levels to be displayed spatially. A major constraint to early application of the system was the lack of site-specific input data to operate the crop simulation models. These data include a minimum set of crop, soil, and weather data for benchmark locations in the country. The immediate value of this system may lie in its capacity to serve as a framework for organizing interdisciplinary research and prioritizing resource allocation