Scaling point and plot measurements of greenhouse gas fluxes, balances, and intensities to whole farms and landscapes

Rosenstock, Todd S. and Rufino, Mariana C. and Chirinda, Ngonidzashe and Van Bussel, Lenny and Reidsma, Pytrik and Butterbach-Bahl, Klaus (2016) Scaling point and plot measurements of greenhouse gas fluxes, balances, and intensities to whole farms and landscapes. In: Methods for Measuring Greenhouse Gas Balances and Evaluating Mitigation Options in Smallholder Agriculture :. Springer International Publishing AG, Cham, pp. 175-188. ISBN 9783319297927

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Abstract

Measurements of nutrient stocks and greenhouse gas (GHG) fluxes are typically collected at very local scales (2) and then extrapolated to estimate impacts at larger spatial extents (farms, landscapes, or even countries). Translating point measurements to higher levels of aggregation is called scaling. Scaling fundamentally involves conversion of data through integration or interpolation and/or simplifying or nesting models. Model and data manipulation techniques to scale estimates are referred to as scaling methods. In this chapter, we first discuss the necessity and underlying premise of scaling and scaling methods. Almost all cases of agricultural GHG emissions and carbon (C) stock change research relies on disaggregated data, either spatially or by farming activity, as a fundamental input of scaling. Therefore, we then assess the utility of using empirical and process-based models with disaggregated data, specifically concentrating on the opportunities and challenges for their application to diverse smallholder farming systems in tropical regions. We describe key advancements needed to improve the confidence in results from these scaling methods in the future.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300/2300
Subjects:
?? general environmental science ??
ID Code:
88833
Deposited By:
Deposited On:
20 Nov 2017 21:30
Refereed?:
No
Published?:
Published
Last Modified:
16 Jul 2024 04:08