TY - JOUR
T1 - Transferring the impacts of pilot-scale studies to other scales
T2 - Understanding the role of non-biophysical factors using field-based irrigation studies
AU - Nicholas, Graeme
AU - Srinivasan, M. S.
AU - Beechener, Sam
AU - Foote, Jeff
AU - Robson-Williams, Melissa
AU - FitzHerbert, Stephen
N1 - © 2020 Elsevier B.V. All rights reserved.
PY - 2020/4/30
Y1 - 2020/4/30
N2 - Researchers are challenged to design research that can generate credible claims regarding cross-scale impact and adoption. However, the context in which new knowledge or innovation is developed and tested may differ from that for the uptake and use of those findings. This paper reports insight into the problem of designing impactful research and proposes a model to assist bio-physical researchers in accounting for non-biophysical context when moving between scales or settings. We treat the scaling problem as the one shifting contexts. The use of the model is illustrated by application in two New Zealand-based irrigation water use efficiency (WUE) field studies. We hypothesised that to successfully transfer the learnings from these two pilot studies to other scales it would be important to understand the influence of context on WUE practices. To support this process, we developed a social dynamics model (Composite Context Model, CCM) from existing social systems frameworks. The CCM maps influential non-biophysical dynamics to help interpret the WUE field study findings for other scales. The paper represents a contribution to researchers addressing two related challenges: that of making credible claims regarding the possible future impact of their research, and that of translating innovations across scales. By demonstrating the use of our CCM for documenting key non-biophysical variables, we aim to equip researchers with a practical tool to assist in the interpretation of findings across contexts, that include both biophysical and non-biophysical factors.
AB - Researchers are challenged to design research that can generate credible claims regarding cross-scale impact and adoption. However, the context in which new knowledge or innovation is developed and tested may differ from that for the uptake and use of those findings. This paper reports insight into the problem of designing impactful research and proposes a model to assist bio-physical researchers in accounting for non-biophysical context when moving between scales or settings. We treat the scaling problem as the one shifting contexts. The use of the model is illustrated by application in two New Zealand-based irrigation water use efficiency (WUE) field studies. We hypothesised that to successfully transfer the learnings from these two pilot studies to other scales it would be important to understand the influence of context on WUE practices. To support this process, we developed a social dynamics model (Composite Context Model, CCM) from existing social systems frameworks. The CCM maps influential non-biophysical dynamics to help interpret the WUE field study findings for other scales. The paper represents a contribution to researchers addressing two related challenges: that of making credible claims regarding the possible future impact of their research, and that of translating innovations across scales. By demonstrating the use of our CCM for documenting key non-biophysical variables, we aim to equip researchers with a practical tool to assist in the interpretation of findings across contexts, that include both biophysical and non-biophysical factors.
KW - Hydrology
KW - Irrigation efficiency
KW - Non-biophysical context
KW - Scale
KW - Science impact
KW - Science uptake
UR - http://www.scopus.com/inward/record.url?scp=85079359235&partnerID=8YFLogxK
U2 - 10.1016/j.agwat.2020.106075
DO - 10.1016/j.agwat.2020.106075
M3 - Article
AN - SCOPUS:85079359235
SN - 0378-3774
VL - 233
JO - Agricultural Water Management
JF - Agricultural Water Management
M1 - 106075
ER -