A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems. Issue 6 (13th March 2021)

• Record Type: Journal Article
• Authors: Soper, Fiona M.; Taylor, Benton N.; Winbourne, Joy B.; Wong, Michelle Y.; Dynarski, Katherine A.; Reis, Carla R. G.; Peoples, Mark B.; Cleveland, Cory C.; Reed, Sasha C.; Menge, Duncan N. L.; Perakis, Steven S.
• Is Part Of: Methods in ecology and evolution. Volume 12:Issue 6(2021)
• Page Start: 1122
• Page End: 1137
• Publication Date: 2021-03-13
• Subjects: asymbiotic -- biological nitrogen fixation -- free‐living -- nitrogen cycle -- spatial variation -- symbiotic -- temporal variation; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.13586
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Accurately quantifying rates and patterns of biological nitrogen fixation (BNF) in terrestrial ecosystems is essential to characterize ecological and biogeochemical interactions, identify mechanistic controls, improve BNF representation in conceptual and numerical modelling, and forecast nitrogen limitation constraints on future carbon (C) cycling. While many resources address the technical advantages and limitations of different methods for measuring BNF, less systematic consideration has been given to the broader decisions involved in planning studies, interpreting data, and extrapolating results. Here, we present a conceptual and practical road map to study design, study execution, data analysis and scaling, outlining key considerations at each step. We address issues including defining N‐fixing niches of interest, identifying important sources of temporal and spatial heterogeneity, designing a sampling scheme (including method selection, measurement conditions, replication, and consideration of hotspots and hot moments), and approaches to analysing, scaling and reporting BNF. We also review the comparability of estimates derived using different approaches in the literature, and provide sample R code for simulating symbiotic BNF data frames and upscaling. Improving and standardizing study design at each of these stages will improve the accuracy and interpretability of data, define limits of extrapolation, and facilitate broader use of BNF data for downstream applications. We highlight aspects—such as quantifying scales of heterogeneity, statistical approaches for dealing with non‐normality, and consideration of rates versus ecological significance—that are ripe for further development.