Stakeholder interpretation of probabilistic representations of uncertainty in spatial information: an example on the nutritional quality of staple crops

Christopher Chagumaira, Patson C. Nalivata, Joseph G. Chimungu, Dawd Gashu, Martin R. Broadley, Alice E. Milne & R. Murray Lark
Spatial information, inferred from samples, is needed for decision-making, but is uncertain. One way to convey uncertain information is with probabilities (e.g. that a value falls below a critical threshold). We examined how different professional groups (agricultural scientists or health and nutrition experts) interpret information, presented this way, when making a decision about interventions to address human selenium (Se) deficiency. The information provided was a map, either of the probability that Se concentration in local...
1 citation reported since publication in 2022.
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.