Julian R - Using the EcoCrop model and database to forecast impacts of cc

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Preliminary results on the assessment of global food security issues under changing climates. Presented at Tyndall Centre, Norwich, UK, by Julian Ramirez

Technologie

Using the EcoCrop niche model to forecast impacts of climate change on global crop production Julián Ramírez and Andy Jarvis International Centre for Tropical Agriculture (CIAT) Bioversity International Cali, Colombia

Impact assessment: methods and data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Model: EcoCrop ,[object Object],It evaluates on monthly basis if there are adequate climatic conditions within a growing season for temperature and precipitation… … and calculates the climatic suitability of the resulting interaction between rainfall and temperature…

Playing around with all this… ,[object Object]

More regional level impacts Percent of crops with significant gains /losses in each region… bad news for North and Sub-Saharan Africa, Latin America, the Caribbean and the Pacific… Maximum positive and negative changes per region… Europe: the big winner…

And a bit more… ,[object Object],[object Object]

Crop-based results ,[object Object],Contrasting responses on the same industry

Regional and crop-based results: contrasts EUROPE NORTH AFRICA SUB-SAHARAN AFRICA LATIN AMERICA

Country based results Current suitability and predicted changes to 2050s for geographic regions. Note the high variability in SSA and Asia, while relatively low variability in changes within Latin America Current suitability and number of crops with significant negative changes. Bubble size is Infant Mortality Rate

Average change in suitability for all crops in 2050s

Winners and losers Number of crops with more than 5% loss Number of crops with more than 5% gain

Next steps ,[object Object],[object Object],[object Object],[object Object],[object Object]

Next steps: validate and adjust the parameters ,[object Object],[object Object],Suitability prediction Visual validation Survey to gather validation data

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Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.

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Julian R - Using the EcoCrop model and database to forecast impacts of cc

1. Using the EcoCrop niche model to forecast impacts of climate change on global crop production Julián Ramírez and Andy Jarvis International Centre for Tropical Agriculture (CIAT) Bioversity International Cali, Colombia

6. More regional level impacts Percent of crops with significant gains /losses in each region… bad news for North and Sub-Saharan Africa, Latin America, the Caribbean and the Pacific… Maximum positive and negative changes per region… Europe: the big winner…

10. Regional and crop-based results: contrasts EUROPE NORTH AFRICA SUB-SAHARAN AFRICA LATIN AMERICA

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12. Country based results Current suitability and predicted changes to 2050s for geographic regions. Note the high variability in SSA and Asia, while relatively low variability in changes within Latin America Current suitability and number of crops with significant negative changes. Bubble size is Infant Mortality Rate

13. Average change in suitability for all crops in 2050s

14. Winners and losers Number of crops with more than 5% loss Number of crops with more than 5% gain

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