Browsing by Author "Lin, Wen"

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    Heterotrophic Respiration and the Divergence of Productivity and Carbon Sequestration
    Noormets, Asko; Bracho, Rosvel; Ward, Eric J.; Seiler, John R.; Strahm, Brian D.; Lin, Wen; McElligott, Kristin M.; Domec, Jean-Christophe; González-Benecke, Carlos; Jokela, Eric J.; Markewitz, Daniel; Meek, Cassandra; Miao, Guofang; McNulty, Steve G.; King, John S.; Samuelson, Lisa; Sun, Ge; Teskey, Robert O.; Vogel, Jason G.; Will, Rodney E.; Yang, Jinyan; Martin, Timothy A. (2021-04-16)
    Net primary productivity (NPP) and net ecosystem production (NEP) are often used interchangeably, as their difference, heterotrophic respiration (soil heterotrophic CO2 efflux, R-SH = NPP-NEP), is assumed a near-fixed fraction of NPP. Here, we show, using a range-wide replicated experimental study in loblolly pine (Pinus taeda) plantations that R-SH responds differently than NPP to fertilization and drought treatments, leading to the divergent responses of NPP and NEP. Across the natural range of the species, the moderate responses of NPP (+11%) and R-SH (-7%) to fertilization combined such that NEP increased nearly threefold in ambient control and 43% under drought treatment. A 13% decline in R-SH under drought led to a 26% increase in NEP while NPP was unaltered. Such drought benefit for carbon sequestration was nearly twofold in control, but disappeared under fertilization. Carbon sequestration efficiency, NEP:NPP, varied twofold among sites, and increased up to threefold under both drought and fertilization.
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    Nutrient Uptake Estimates for Woody Species as Described by the NST 3.0, SSAND, and PCATS Mechanistic Nutrient Uptake Models
    Lin, Wen (Virginia Tech, 2009-07-17)
    With the advent of the personal computer, mechanistic nutrient uptake models have become widely used as research and teaching tools in plant and soil science. Three models NST 3.0, SSAND, and PCATS have evolved to represent the current state of the art. There are two major categories of mechanistic models, transient state models with numerical solutions and steady state models. NST 3.0 belongs to the former model type, while SSAND and PCATS belong to the latter. NST 3.0 has been used extensively in crop research but has not been used with woody species. Only a few studies using SSAND and PCATS are available. To better understand the similarities and differences of these three models, it would be useful to compare model predictions with experimental observations using multiple datasets from the literature to represent various situations for woody species. Therefore, the objectives of this study are to: (i) compare the predictions of uptake by the NST 3.0, SSAND, and PCATS models for a suite of nutrients against experimentally measured values, (ii) compare the behavior of the three models using a one dimensional sensitivity analysis; and (iii) compare and contrast the behavior of NST 3.0 and SSAND using a multiple dimensional sensitivity analysis approach. Predictions of nutrient uptake by the three models when run with a common data set were diverse, indicating a need for a reexamination of model structure. The failure of many of the predictions to match observations indicates the need for further studies which produce representative datasets so that the predictive accuracy of each model can be evaluated. Both types of sensitivity analyses suggest that the effect of soil moisture on simulation can be influential when nutrient concentration in the soil solution (CLi) is low. One dimensional sensitivity analysis also revealed that Imax negatively influenced the uptake estimates from the SSAND and PCATS models. Further analysis indicates that this counter intuitive response of Imax is probably related to low soil nutrient supply. The predictions of SSAND under low-nutrient-supply scenarios are generally lower than those of NST 3.0. We suspect that both of these results are artifacts of the steady state models and further studies to improve them, such as incorporating important rhizospheric effects, are needed if they are to be used successfully for the longer growth periods and lower soil nutrient supply situations more typical of woody species.
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    Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization
    Lin, Wen; Domec, Jean-Christophe; Ward, Eric J.; Marshall, John; Kin, John S.; Laviner, Marshall A.; Fox, Thomas R.; West, Jason B.; Sun, Ge; McNulty, Steve G.; Noormets, Asko (2019-12)
    Drought frequency and intensity are projected to increase throughout the southeastern USA, the natural range of loblolly pine (Pinus taeda L.), and are expected to have major ecological and economic implications. We analyzed the carbon and oxygen isotopic compositions in tree ring cellulose of loblolly pine in a factorial drought (similar to 30% throughfall reduction) and fertilization experiment, supplemented with trunk sap flow, allometry and microclimate data. We then simulated leaf temperature and applied a multi-dimensional sensitivity analysis to interpret the changes in the oxygen isotope data. This analysis found that the observed changes in tree ring cellulose could only be accounted for by inferring a change in the isotopic composition of the source water, indicating that the drought treatment increased the uptake of stored moisture from earlier precipitation events. The drought treatment also increased intrinsic water-use efficiency, but had no effect on growth, indicating that photosynthesis remained relatively unaffected despite 19% decrease in canopy conductance. In contrast, fertilization increased growth, but had no effect on the isotopic composition of tree ring cellulose, indicating that the fertilizer gains in biomass were attributable to greater leaf area and not to changes in leaf-level gas exchange. The multi-dimensional sensitivity analysis explored model behavior under different scenarios, highlighting the importance of explicit consideration of leaf temperature in the oxygen isotope discrimination (Delta O-18(c)) simulation and is expected to expand the inference space of the Delta O-18(c) models for plant ecophysiological studies.