A framework and toolset for standardizing agroecosystem indicators

Authors: McCord, Sarah; BREHM, JOSEPH - New Mexico State University; BURNETT, SARAH - Bureau Of Land Management; DIETRICH, CHRIS - Bureau Of Land Management; EDWARDS, BRANDON - New Mexico State University; METZ, LORETTA - Natural Resources Conservation Service (NRCS, USDA); HERNANDEZ-NARVAEZ, MARIANO - University Of Arizona; Pierson Jr, Frederick; RAMIREZ, KELLY - University Of Texas - El Paso; Stauffer, Nelson; WEBB, NICHOLAS - New Mexico State University; TWEEDIE, CRAIG - University Of Texas - El Paso

Submitted to: Ecological Indicators
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/27/2022
Publication Date: 10/1/2022
Citation: Mccord, S.E., Brehm, J.R., Burnett, S.H., Dietrich, C., Edwards, B., Metz, L.J., Hernandez-Narvaez, M., Pierson Jr, F.B., Ramirez, K., Stauffer, N.G., Webb, N.P., Tweedie, C. 2022. A framework and toolset for standardizing agroecosystem indicators. Ecological Indicators. 144. Article 109511. https://doi.org/10.1016/j.ecolind.2022.109511.
DOI: https://doi.org/10.1016/j.ecolind.2022.109511

Interpretive Summary: Standard indicators and measurements are key to cross-scale agroecosystem assessments. While the need to standardize indicators is broadly recognized, inconsistencies in indicator calculations from common measurements may yield discrepancies in indicator meaning and consequently reduce the accuracy of agroecosystem assessments. Here we present a framework that provides a mechanism for standardizing indicator calculations across datasets and agroecosystems yet also provides flexibility for local or process specific indicators. This framework, implemented as an R package terradactyl, first harmonizes standardized agroecosystem measurements into analysis-friendly datasets, 2) produces a standard, yet flexible indicator calculation approach, 3) aggregates indicators into commonly used sets of indicators or data models. This paper provides a workflow that can be applied across agroecosystem measurements and indicators globally to produce scaleable indicators that are relevant for land managers and policy-makers alike.

Technical Abstract: Standard indicators and measurements are key to cross-scale agroecosystem assessments. While the need to standardize indicators is broadly recognized, inconsistencies in indicator calculations from common measurements may yield discrepancies in indicator meaning and consequently reduce the accuracy of agroecosystem assessments. Here we present a framework that provides a mechanism for standardizing indicator calculations across datasets and agroecosystems yet also provides flexibility for local or process specific indicators. This framework, implemented as an R package terradactyl, first harmonizes standardized agroecosystem measurements into analysis-friendly datasets, 2) produces a standard, yet flexible indicator calculation approach, 3) aggregates indicators into commonly used sets of indicators or data models. This paper provides a workflow that can be applied across agroecosystem measurements and indicators globally to produce scaleable indicators that are relevant for land managers and policy-makers alike.