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Abstract Nitrogen (N)‐fixing trees fulfil a unique and important biogeochemical role in forests through their ability to convert atmospheric N2gas to plant‐available N. Due to their high N fixation rates, it is often assumed that N‐fixing trees facilitate neighbouring trees and enhance forest growth. This assumption is supported by some local studies but contradicted by others, leaving the overall effect of N‐fixing trees on forest growth unresolved.
Here we use the US Forest Service's Forest Inventory and Analysis database to evaluate the effects of N‐fixing trees on plot‐scale basal area change and individual‐scale neighbouring tree demography across the coterminous US.
First we discuss the average trends. At the plot and individual scales, N‐fixing trees do not affect the relative growth rates of neighbouring trees, but they facilitate recruitment and inhibit survival rates, suggesting that they are drivers of tree turnover in the coterminous US. At the plot scale, N‐fixing trees facilitate the basal area change of non‐fixing neighbours.
In addition to the average trends, there is wide variation in the effect of N‐fixing trees on forest growth, ranging from strong facilitation to strong inhibition. This variation does not show a clear geographical pattern, though it does vary with certain local factors. N‐fixing trees facilitate forest growth when they are likely to be less competitive: under high N deposition and high soil moisture or when neighbouring trees occupy different niches (e.g. high foliar C:N trees and non‐fixing trees).
Synthesis . N‐fixing trees have highly variable effects on forest growth and neighbour demographics across the coterminous US. This suggests that the effect of N‐fixing trees on forest development and carbon storage depends on local factors, which may help reconcile the conflicting results found in previous localized studies on the effect of N‐fixing trees on forest growth. -
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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.
