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  1. Free, publicly-accessible full text available November 1, 2022
  2. Abstract Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We findmore »global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.« less
    Free, publicly-accessible full text available December 1, 2022
  3. Free, publicly-accessible full text available August 1, 2022
  4. Abstract. For decades, predominant soil biogeochemical models have used conceptual soil organic matter (SOM) pools and only simulated them to a shallow depthin soil. Efforts to overcome these limitations have prompted the development of the new generation SOM models, including MEMS 1.0, which representsmeasurable biophysical SOM fractions, over the entire root zone, and embodies recent understanding of the processes that govern SOM dynamics. Herewe present the result of continued development of the MEMS model, version 2.0. MEMS 2.0 is a full ecosystem model with modules simulating plantgrowth with above- and belowground inputs, soil water and temperature by layer, decomposition ofmore »plant inputs and SOM, and mineralization andimmobilization of nitrogen (N). The model simulates two commonly measured SOM pools – particulate and mineral-associated organic matter (POM andMAOM, respectively). We present results of calibration and validation of the model with several grassland sites in the US. MEMS 2.0 generallycaptured the soil carbon (C) stocks (R2 of 0.89 and 0.6 for calibration and validation, respectively) and their distributions between POM andMAOM throughout the entire soil profile. The simulated soil N matches measurements but with lower accuracy (R2 of 0.73 and 0.31 for calibrationand validation of total N in SOM, respectively) than for soil C. Simulated soil water and temperature were compared with measurements, and theaccuracy is comparable to the other commonly used models. The seasonal variation in gross primary production (GPP; R2 = 0.83), ecosystemrespiration (ER; R2 = 0.89), net ecosystem exchange (NEE; R2 = 0.67), and evapotranspiration (ET; R2 = 0.71) was wellcaptured by the model. We will further develop the model to represent forest and agricultural systems and improve it to incorporate newunderstanding of SOM decomposition.« less