Influence of C02 enrichment and nitrogen fertilization on tissue chemistry and carbon allocation in longleaf pine seedlings

One-year old, nursery-grown longleaf pine (Pinus palustris Mill.) seedlings were grown in 45-L pots containing a coarse sandy medium and were exposed to two concentrations of atmospheric CO2 (365 or 720 µmol?1) and two levels of nitrogen (N) fertility (40 or 400 kg N ha?1 yr?1) within open top chambers for 20 months. At harvest, needles, stems, coarse roots, and fine roots were separated and weighed. Subsamples of each tissue were frozen in liquid N, lyophilized at ?50 ?C, and ground to pass a 0.2 mm sieve. Tissue samples were analyzed for carbon (C), N, nonpolar extractives (fats, waxes, and oils = FWO), nonstructural carbohydrates (total sugars and starch), and structural carbohydrates (cellulose, lignin, and tannins). Increased dry weights of each tissue were observed under elevated CO2 and with high N; however, main effects of CO2 were significant only on belowground tissues. The high N fertility tended to result in increased partitioning of biomass aboveground, resulting in significantly lower root to shoot ratios. Elevated CO2 did not affect biomass allocation among tissues. Both atmospheric CO2 and N fertility tended to affect concentration of C compounds in belowground, more than aboveground, tissues. Elevated CO2 resulted in lower concentrations of starch, cellulose, and lignin, but increased concentrations of FWO in root tissues. High N fertility increased the concentration of starch, cellulose, and tannins, but resulted in lower concentrations of lignin and FWO in roots. Differences between CO2 concentrations tended to occur only with high N fertility. Atmospheric CO2 did not affect allocation patterns for any compound; however the high N treatment tended to result in a lower percentage of sugars, cellulose, and lignin belowgroun

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (V-c,V-max) and maximum electron transport rate supporting RuBP regeneration (J(max)), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate V-c,V-max and J(max) based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for V-c,V-max (R-2 = 0.70) and J(max) (R-2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral propertiesThe authors would like to thank the technical help during the experiment of Mr. Robert Icenogle, Barry Dorman (USDA-ARS), Seth Johnston, and Mary Durstock (Crop Physiology Laboratory, Auburn University). The authors also would like to thank to Dr. Jose A. Jimenez Berni for statistical support to analyze the data. This research was supported by the Action CA17134 SENSECO (Optical Synergies for Spatiotemporal Sensing of Scalable Ecophysiological Traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu).This research was also supported by Auburn University and Alabama Agricultural Experimental Station Seed Grant

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties

Effects of Atmospheric CO2 Enrichment on Crop Nutrient Dynamics under No-Till Conditions

Increasing atmospheric CO2 concentration could increase crop productivity and alter crop nutrient dynamics. This study was conducted (3 yrs) with two crops ([Glycine max (L.) Merr.] and grain sorghum [Sorghum bicolor (L.) Moench.]) grown under two CO2 levels (ambient and twice ambient) using open top field chambers on a Blanton loamy sand under no-tillage. Macronutrient and micronutrient concentrations and contents were determined for grain, stover, and roots. Although elevated CO2 tended to reduce nutrient concentrations, high CO2 consistently increased nutrient content especially in grain tissue; this response pattern was more notable with macronutrients. The CO2 effect was observed primarily in soybean. The consistent CO2-induced increases in grain macronutrient contents favors reliable predictions of system outputs, however, predictions of crop nutrient inputs (i.e., stover and root contents) to the soil are less robust due to observed variability. Again, this is particularly true in regards to micronutrient dynamics in CO2-enriched cropping systems

Belowground Response of a Bahiagrass Pasture to Long-Term Elevated [CO₂] and Soil Fertility Management

Effects of rising atmospheric CO2 concentration [CO2] on pastures and grazing lands are beginning to be researched, but these important systems remain understudied compared to other agronomic and forest ecosystems. Therefore, we conducted a long-term (2005–2015) study of bahiagrass (Paspalum notatum Flüggé) response to elevated [CO2] and fertility management. The study was conducted at the USDA-ARS, National Soil Dynamics Laboratory open-top field chamber facility, Auburn, AL. A newly established bahiagrass pasture was exposed to either ambient or elevated (ambient + 200 µmol mol−1) [CO2]. Following one year of pasture establishment, half the plots received a fertilizer treatment [N at 90 kg ha−1 three times yearly plus P, K, and lime as recommended by soil testing]; the remaining plots received no fertilization. These treatments were implemented to represent managed (M) and unmanaged (U) pastures; both are common in the southeastern US. Root cores (0–60 cm depth) were collected annually in October and processed using standard procedures. Fertility additions consistently increased both root length density (53.8%) and root dry weight density (68.2%) compared to unmanaged plots, but these root variables were generally unaffected by either [CO2] or its interaction with management. The results suggest that southern bahiagrass pastures could benefit greatly from fertilizer additions. However, bahiagrass pasture root growth is unlikely to be greatly affected by rising atmospheric [CO2], at least by those levels expected during this century

Effects of Atmospheric CO2 Enrichment on Soil CO2 Efflux in a Young Longleaf Pine System

The southeastern landscape is composed of agricultural and forest systems that can store carbon (C) in standing biomass and soil. Research is needed to quantify the effects of elevated atmospheric carbon dioxide (CO2) on terrestrial C dynamics including CO2 release back to the atmosphere and soil sequestration. Longleaf pine savannahs are an ecologically and economically important, yet understudied, component of the southeastern landscape. We investigated the effects of ambient and elevated CO2 on soil CO2 efflux in a young longleaf pine system using a continuous monitoring system. A significant increase (26.5%) in soil CO2 efflux across 90 days was observed under elevated CO2; this occurred for all weekly and daily averages except for two days when soil temperature was the lowest. Soil CO2 efflux was positively correlated with soil temperature with a trend towards increased efflux response to temperature under elevated CO2. Efflux was negatively correlated with soil moisture and was best represented using a quadratic relationship. Soil CO2 efflux was not correlated with root biomass. Our data indicate that, while elevated CO2 will increase feedback of CO2 to the atmosphere via soil efflux, terrestrial ecosystems will remain potential sinks for atmospheric CO2 due to greater biomass production and increased soil C sequestration

Influence of C02 enrichment and nitrogen fertilization on tissue chemistry and carbon allocation in longleaf pine seedlings

One-year old, nursery-grown longleaf pine (Pinus palustris Mill.) seedlings were grown in 45-L pots containing a coarse sandy medium and were exposed to two concentrations of atmospheric CO2 (365 or 720 µmol?1) and two levels of nitrogen (N) fertility (40 or 400 kg N ha?1 yr?1) within open top chambers for 20 months. At harvest, needles, stems, coarse roots, and fine roots were separated and weighed. Subsamples of each tissue were frozen in liquid N, lyophilized at ?50 ?C, and ground to pass a 0.2 mm sieve. Tissue samples were analyzed for carbon (C), N, nonpolar extractives (fats, waxes, and oils = FWO), nonstructural carbohydrates (total sugars and starch), and structural carbohydrates (cellulose, lignin, and tannins). Increased dry weights of each tissue were observed under elevated CO2 and with high N; however, main effects of CO2 were significant only on belowground tissues. The high N fertility tended to result in increased partitioning of biomass aboveground, resulting in significantly lower root to shoot ratios. Elevated CO2 did not affect biomass allocation among tissues. Both atmospheric CO2 and N fertility tended to affect concentration of C compounds in belowground, more than aboveground, tissues. Elevated CO2 resulted in lower concentrations of starch, cellulose, and lignin, but increased concentrations of FWO in root tissues. High N fertility increased the concentration of starch, cellulose, and tannins, but resulted in lower concentrations of lignin and FWO in roots. Differences between CO2 concentrations tended to occur only with high N fertility. Atmospheric CO2 did not affect allocation patterns for any compound; however the high N treatment tended to result in a lower percentage of sugars, cellulose, and lignin belowgroun

Elevated Atmospheric CO\u3csub\u3e2\u3c/sub\u3e Affects Structure of a Model Regenerating Longleaf Pine Community

Differences in plant morphology, physiology, life form, and symbiotic relationships can generate differences in species responses to CO2-enrichment, which can alter competitive interactions, thus affecting community structure and function. Here, we present data from a two-year study, examining the species and community responses to elevated [CO2] of a model regenerating longleaf pine community. The model community was constructed from an assemblage of early successional forest species representing maojr vunctional guilds within a typical longleaf pine-wiregrass community: (1) a C3 evergreen conifer (Pinus palustris); (2) a C4 bunch grass (Aristida stricta); (3) a C3 broadleaf tree (Quercus margaretta); (4) a C3 perennial herbaceous legume (Crotalaria rotundifolia); and (5) a C3 herbaceous perennial (Asclepias tuberosa). After 2 years, CO2-enriched plots had 109% greater above-ground biomass than ambient plots, mainy due to a 117% increase in pine biomass. Community structure was altered by CO2 enrichment; Crotalaria and Asclepias had higher mortality and less biomass in high-CO2 plots suggesting that not all species will perform well as global [CO2] rises. Our data suggest that longleaf pine communities as a whole will perform well in a future higher CO2 world, but some species may fall prey to altered competitive interactions for light and soil moisture

Nitrogen and Carbon Cycling in a Model Longleaf Pine Community as Affected by Elevated Atmospheric CO\u3csub\u3e2\u3c/sub\u3e

Increasing global atmospheric CO2 concentration has led to concerns regarding its potential effects on terrestrial ecosystem and the long-term storage of C and N in soil. This study examined responses to elevated CO2 in a typical regenerating longleaf pine-wiregrass community. The model community consisted of five plant species: (1) an evergreen conifer (Pinus palustris), (2) a bunch grass (Aristida stricta), (3) a broadleaf tree (Quercus margaretta), (4) a perennial herbaceous legume (Crotalaria rotundifolia), and (5) a herbaceous perennial (Asclepias tuberosa) grown at two CO2 concentrations (ambient and twice ambient). The CO2-enriched plots had greater aboveground biomass than ambient plots, mainly due to increased pine biomass. After 3 years, samples of the soil (Blanton loamy sand: loamy, siliceous, semiactive, thermic Grossarenic Paleudult) were collected from 0- to 5-, 5- to 10-, and 10- to 20-cm depth increments. Microbial respiration, potential C and N mineralization, and C turnover were measured during a 120-day incubation of the soil samples. Elevated CO2 decreased soil C respiration and C turnover, but increased N mineralization. Results indicate that soil C sequestration is likely for soils in this longleaf pine ecosystem