Articles | Volume 8, issue 4
https://doi.org/10.5194/gc-8-267-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gc-8-267-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Communicating expected uncertainty in a geostatistical survey to support co-design with users of information
Christopher Chagumaira
CORRESPONDING AUTHOR
School of Biosciences, Sutton Bonington Campus, University of Nottingham, Loughborough, LE12 5RD, United Kingdom
Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
Crop and Soil Sciences Department, Lilongwe University of Agriculture and Natural Resources, Bunda College, P.O. Box 219, Lilongwe, Malawi
Agri-Food and Biosciences Institute, Newforge Lane, Belfast, BT9 5PX, United Kingdom
Joseph G. Chimungu
Crop and Soil Sciences Department, Lilongwe University of Agriculture and Natural Resources, Bunda College, P.O. Box 219, Lilongwe, Malawi
Patson C. Nalivata
Crop and Soil Sciences Department, Lilongwe University of Agriculture and Natural Resources, Bunda College, P.O. Box 219, Lilongwe, Malawi
Martin R. Broadley
School of Biosciences, Sutton Bonington Campus, University of Nottingham, Loughborough, LE12 5RD, United Kingdom
Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
Alice E. Milne
Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
Richard Murray Lark
School of Biosciences, Sutton Bonington Campus, University of Nottingham, Loughborough, LE12 5RD, United Kingdom
Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom
Related authors
Christopher Chagumaira, Joseph G. Chimungu, Patson C. Nalivata, Martin R. Broadley, Madlene Nussbaum, Alice E. Milne, and R. Murray Lark
EGUsphere, https://doi.org/10.5194/egusphere-2022-583, https://doi.org/10.5194/egusphere-2022-583, 2022
Preprint archived
Short summary
Short summary
Our study examines different quantitative methods to predict concentrations of micronutrients in the soil from field samples. However, we emphasize the concerns of stakeholders, who use such information to make decisions, in this case in relation to the study and management of micronutrient deficiency risk in the human population. We propose a framework to think about these concerns then compare common approaches for digital soil mapping within this framework.
Christopher Chagumaira, Joseph G. Chimungu, Dawd Gashu, Patson C. Nalivata, Martin R. Broadley, Alice E. Milne, and R. Murray Lark
Geosci. Commun., 4, 245–265, https://doi.org/10.5194/gc-4-245-2021, https://doi.org/10.5194/gc-4-245-2021, 2021
Short summary
Short summary
Our study is concerned with how the uncertainty in spatial information about environmental variables can be communicated to stakeholders who must use this information to make decisions. We tested five methods for communicating the uncertainty in spatial predictions by eliciting the opinions of end-users about the usefulness of the methods. End-users preferred methods based on the probability that concentrations are below or above a nutritionally significant threshold.
Nalumino L. Namwanyi, Maurice J. Hutton, Ikabongo Mukumbuta, Lydia M. Chabala, Clarence Chongo, Stalin Sichinga, and R. Murray Lark
SOIL, 10, 887–911, https://doi.org/10.5194/soil-10-887-2024, https://doi.org/10.5194/soil-10-887-2024, 2024
Short summary
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We examined historical sources for the Ecological Survey of Zambia, 1932–1943. This found how normal erosion gave rise to soil variation in the upper Zambezi valley, which was expressed in vegetation patterns which African farmers interpreted to select sites for cultivation and traditional production systems. The survey challenged colonial assumptions about traditional practices. We identify lessons for modern-day approaches to traditional agricultural knowledge in Africa.
Christopher Chagumaira, Joseph G. Chimungu, Patson C. Nalivata, Martin R. Broadley, Madlene Nussbaum, Alice E. Milne, and R. Murray Lark
EGUsphere, https://doi.org/10.5194/egusphere-2022-583, https://doi.org/10.5194/egusphere-2022-583, 2022
Preprint archived
Short summary
Short summary
Our study examines different quantitative methods to predict concentrations of micronutrients in the soil from field samples. However, we emphasize the concerns of stakeholders, who use such information to make decisions, in this case in relation to the study and management of micronutrient deficiency risk in the human population. We propose a framework to think about these concerns then compare common approaches for digital soil mapping within this framework.
Christopher Chagumaira, Joseph G. Chimungu, Dawd Gashu, Patson C. Nalivata, Martin R. Broadley, Alice E. Milne, and R. Murray Lark
Geosci. Commun., 4, 245–265, https://doi.org/10.5194/gc-4-245-2021, https://doi.org/10.5194/gc-4-245-2021, 2021
Short summary
Short summary
Our study is concerned with how the uncertainty in spatial information about environmental variables can be communicated to stakeholders who must use this information to make decisions. We tested five methods for communicating the uncertainty in spatial predictions by eliciting the opinions of end-users about the usefulness of the methods. End-users preferred methods based on the probability that concentrations are below or above a nutritionally significant threshold.
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Short summary
Our study is concerned with how uncertainty in spatial information about environmental variables can be communicated to stakeholders to make decisions about sampling whilst also considering the trade-off between sampling effort and reducing uncertainty. We tested four approaches that relate sampling density and uncertainty by eliciting the opinions of end-users. End-users preferred the method not directly linked to decision-making. More work is needed to develop and elucidate decision-specific approaches.
Our study is concerned with how uncertainty in spatial information about environmental variables...
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