LETTERS TO NATURE domain of this protein and triggers the activation of the protein kinase moiety residing on the cytoplasmic side of the plasma membrane. The protein kinase then phosphorylates specific substrates, resulting in the production of second messengers, amplification of the signal and, ultimately, alteration or activation of cellular processes. This putative receptor is exceptional because it has sequence homology typical of the serine/ threonine protein kinases. Most transmembrane protein kinases described so far are of the tyrosine class. The only other putative receptor serine kinase that we are aware of is the daf-1 gene from the nematode Caenorhabditis elegans 4 • Although at this time there is no biochemical evidence that either the daf-1 or the ZmPK1 gene products are serine/threonine-specific protein kinases, the amino-acid sequence is strong evidence that these proteins represent a new type of signal-transducing molecule-receptor serine/threonine protein kinases. The identification of ZmPK1 as a putative receptor protein kinase-to our knowledge the first transmembrane receptor identified in higher plants-provides a unique opportunity to gain fresh insights into signal transduction in higher plants. D

No abstract

Nitrous oxide (N2O) is a greenhouse gas produced mainly by the microbial breakdown of agricultural fertilizer. ‘Emission factors’ (EFs, the fraction of nitrogen added that is released as N2O) are based on flux chamber measurements following the application of fertilizer. These measurements are very variable in space and time so that EFs are often uncertain, but this is rarely quantified. We developed a method that simplifies the calculation of EFs, incorporates prior knowledge and quantifies the uncertainty with a Bayesian approach to fit the parameters of a lognormal model. We compared this with the standard method for interpolating, extrapolating and integrating fluxes of N2O (trapezoidal integration). We verified both methods against process‐based model output where the true integral was known and against eddy covariance data where the integral was estimated more accurately because of the greater spatial and temporal coverage. We used the process‐based model to simulate flux chamber data and added a lognormal spatial distribution to the model output. The lognormal model performed better than the standard method, in terms of estimating the true underlying cumulative flux more accurately. Estimates based on chamber and eddy covariance data were sometimes substantially different, but with no clear systematic bias. The Bayesian approach with the lognormal model enabled us to combine both chamber and eddy covariance data to constrain cumulative fluxes. The standard trapezoidal method typically underestimates emission factors to some extent if fluxes are lognormally distributed in space. The Bayesian approach with the lognormal model is a robust method for quantifying the uncertainty in cumulative fluxes of N2O. Highlights Emission factors for N2O are based on sparse and variable measurements, and so are uncertain. We use a Bayesian approach to simplify the calculation and quantify the uncertainty. No observed systematic difference between eddy covariance and chamber measurement methods. The standard trapezoidal method will typically underestimate emission factors.

An evaluation of four years of nitrous oxide fluxes after application of ammonium nitrate and urea fertilisers measured using the eddy covariance method.