Climatic factors are usually temp (mean) and rain. Min and Max can be used to student extremes but test for collinearity with other similar variables, GHG emissions are indirect in effect.

For non climate factors most of the variables could be included to test. You can remove those with area (cropped area as they are already used in productivity calculation). Forest area can be removed unless there is extensive agroforest considerations.

I recommend, testing pair-wide relations with a scatter plot. They use a var-covariance matrix to remove independent variables that are highly correlated.

Hi,

there have been much discussion on the impact of climate change on productivity but the impact cannot be generalised as the impact can be felt depending on region and level of technology. Like countries with low technology like Western Africa, the impact affect the output of farmers and the only suggested measure to ruduce impact is adaptation measures. However, there are also questions to be answer in this regard, who are the actors of adaptation, what measure is feasible and how can this measures contribute to production.

If all this can be sorted out then, it makes it easy to adjust to the changes in climatic condition.

thank you.

Hi Sodiq,

Thanks for your good line of thoughts! The issue of adaptation to climate change is context-specific and a whole lot of damage could be done if someone makes a mistake of generalization. Some farmers in West Africa, are already adapting to the effects of climate change but their efforts are sometimes insufficient. In certain cases, some farmers do take wrong coping or adaptation approaches, which could lead to maladaptation.

Concerning the questions on "who, what, and how" of adaptation with effect on farmers' productivity, we need to look at the various stakeholders and their roles. However, ways to ensure synergies and effective collaboration between these group of stakeholders, which include the farmers, is the key challenge in this perspective.