Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes.

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO2 exchange, soil CO2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSCi ), C translocation (dCi ), and the biomass production efficiency (BPEi ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dCi and BPEi varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPEbgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil-plant-climate interactions.

Aquaporins, and not changes in root structure, provide new insights into physiological responses to drought, flooding, and salinity.

The influence of aquaporin (AQP) activity on plant water movement remains unclear, especially in plants subject to unfavorable conditions. We applied a multitiered approach at a range of plant scales to (i) characterize the resistances controlling water transport under drought, flooding, and flooding plus salinity conditions; (ii) quantify the respective effects of AQP activity and xylem structure on root (Kroot), stem (Kstem), and leaf (Kleaf) conductances; and (iii) evaluate the impact of AQP-regulated transport capacity on gas exchange. We found that drought, flooding, and flooding plus salinity reduced Kroot and root AQP activity in Pinus taeda, whereas Kroot of the flood-tolerant Taxodium distichum did not decline under flooding. The extent of the AQP control of transport efficiency varied among organs and species, ranging from 35-55% in Kroot to 10-30% in Kstem and Kleaf. In response to treatments, AQP-mediated inhibition of Kroot rather than changes in xylem acclimation controlled the fluctuations in Kroot. The reduction in stomatal conductance and its sensitivity to vapor pressure deficit were direct responses to decreased whole-plant conductance triggered by lower Kroot and larger resistance belowground. Our results provide new mechanistic and functional insights on plant hydraulics that are essential to quantifying the influences of future stress on ecosystem function.

COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Field evidences for the positive effects of aerosols on tree growth.

Theoretical and eddy covariance studies demonstrate that aerosol-loading stimulates canopy photosynthesis, but field evidence for the aerosol effect on tree growth is limited. Here, we measured in situ daily stem growth rates of aspen trees under a wide range of aerosol-loading in China. The results showed that daily stem growth rates were positively correlated with aerosol-loading, even at exceptionally high aerosol levels. Using structural equation modeling analysis, we showed that variations in stem growth rates can be largely attributed to two environmental variables covarying with aerosol loading: diffuse fraction of radiation and vapor pressure deficit (VPD). Furthermore, we found that these two factors influence stem growth by influencing photosynthesis from different parts of canopy. Using field observations and a mechanistic photosynthesis model, we demonstrate that photosynthetic rates of both sun and shade leaves increased under high aerosol-loading conditions but for different reasons. For sun leaves, the photosynthetic increase was primarily attributed to the concurrent lower VPD; for shade leaves, the positive aerosol effect was tightly connected with increased diffuse light. Overall, our study provides the first field evidence of increased tree growth under high aerosol loading. We highlight the importance of understanding biophysical mechanisms of aerosol-meteorology interactions, and incorporating the different pathways of aerosol effects into earth system models to improve the prediction of large-scale aerosol impacts, and the associated vegetation-mediated climate feedbacks.

FluoSpec 2-An Automated Field Spectroscopy System to Monitor Canopy Solar-Induced Fluorescence.

Accurate estimation of terrestrial photosynthesis has broad scientific and societal impacts. Measurements of photosynthesis can be used to assess plant health, quantify crop yield, and determine the largest CO2 flux in the carbon cycle. Long-term and continuous monitoring of vegetation optical properties can provide valuable information about plant physiology. Recent developments of the remote sensing of solar-induced chlorophyll fluorescence (SIF) and vegetation spectroscopy have shown promising results in using this information to quantify plant photosynthetic activities and stresses at the ecosystem scale. However, there are few automated systems that allow for unattended observations over months to years. Here we present FluoSpec 2, an automated system for collecting irradiance and canopy radiance that has been deployed in various ecosystems in the past years. The instrument design, calibration, and tests are recorded in detail. We discuss the future directions of this field spectroscopy system. A network of SIF sensors, FluoNet, is established to measure the diurnal and seasonal variations of SIF in several ecosystems. Automated systems such as FluoSpec 2 can provide unique information on ecosystem functioning and provide important support to the satellite remote sensing of canopy photosynthesis.

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales.

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2  = 0.77) to interannual (R2  = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.

A cross-biome synthesis of soil respiration and its determinants under simulated precipitation changes.

Soil respiration (Rs) is the second-largest terrestrial carbon (C) flux. Although Rs has been extensively studied across a broad range of biomes, there is surprisingly little consensus on how the spatiotemporal patterns of Rs will be altered in a warming climate with changing precipitation regimes. Here, we present a global synthesis Rs data from studies that have manipulated precipitation in the field by collating studies from 113 increased precipitation treatments, 91 decreased precipitation treatments, and 14 prolonged drought treatments. Our meta-analysis indicated that when the increased precipitation treatments were normalized to 28% above the ambient level, the soil moisture, Rs, and the temperature sensitivity (Q10) values increased by an average of 17%, 16%, and 6%, respectively, and the soil temperature decreased by -1.3%. The greatest increases in Rs and Q10 were observed in arid areas, and the stimulation rates decreased with increases in climate humidity. When the decreased precipitation treatments were normalized to 28% below the ambient level, the soil moisture and Rs values decreased by an average of -14% and -17%, respectively, and the soil temperature and Q10 values were not altered. The reductions in soil moisture tended to be greater in more humid areas. Prolonged drought without alterations in the amount of precipitation reduced the soil moisture and Rs by -12% and -6%, respectively, but did not alter Q10. Overall, our synthesis suggests that soil moisture and Rs tend to be more sensitive to increased precipitation in more arid areas and more responsive to decreased precipitation in more humid areas. The responses of Rs and Q10 were predominantly driven by precipitation-induced changes in the soil moisture, whereas changes in the soil temperature had limited impacts. Finally, our synthesis of prolonged drought experiments also emphasizes the importance of the timing and frequency of precipitation events on ecosystem C cycles. Given these findings, we urge future studies to focus on manipulating the frequency, intensity, and seasonality of precipitation with an aim to improving our ability to predict and model feedback between Rs and climate change.

Ground far-red sun-induced chlorophyll fluorescence and vegetation indices in the US Midwestern agroecosystems.

Sun-induced chlorophyll fluorescence (SIF) provides an opportunity to study terrestrial ecosystem photosynthesis dynamics. However, the current coarse spatiotemporal satellite SIF products are challenging for mechanistic interpretations of SIF signals. Long-term ground SIF and vegetation indices (VIs) are important for satellite SIF validation and mechanistic understanding of the relationship between SIF and photosynthesis when combined with leaf- and canopy-level auxiliary measurements. In this study, we present and analyze a total of 15 site-years of ground far-red SIF (SIF at 760 nm, SIF760) and VIs datasets from soybean, corn, and miscanthus grown in the U.S. Corn Belt from 2016 to 2021. We introduce a comprehensive data processing protocol, including different retrieval methods, calibration coefficient adjustment, and nadir SIF footprint upscaling to match the eddy covariance footprint. This long-term ground far-red SIF and VIs dataset provides important and first-hand data for far-red SIF interpretation and understanding the mechanistic relationship between far-red SIF and canopy photosynthesis across various crop species and environmental conditions.

Phytoremediation: Climate change resilience and sustainability assessment at a coastal brownfield redevelopment.

Phytoremediation offers a nature based solution (NBS) for contaminated soil remediation; however, its application under a brownfield redevelopment context has not been well studied. Moreover, climate change could impact large numbers of contaminated sites, yet there remains little research on the potential impacts for remediation. This study examined phytoremediation at a brownfield redevelopment in the San Francisco Bay area, where thousands of cleanup sites are vulnerable to rising sea levels. Life cycle assessment (LCA) was used to determine both primary and secondary impacts and the system's resilience to various sea level scenarios and hydroclimatic conditions was investigated. It was found that the phytoremediation project rendered only a small environmental footprint, and was associated with low cost and substantial socioeconomic benefits. For instance, it fitted well with the site redevelopment setting by offering attractive landscape features. Moreover, under a modeled moderate sea level rise scenario, the groundwater hydraulic gradient at the site decreased, which was coupled with greater natural biodegradation and reduced plume migration, and, therefore, lower life cycle impact. There was also minimal increase in the vapor intrusion risk with increased sea level. Overall, phytoremediation at the site was found to be resilient to a moderate sea level rise and other hydroclimatic effects induced by climate change. However, the system performance responded to increasing sea level rise in a non-linear manner. Under a high sea level rise scenario, the system is predicted to perform abruptly worse.

Organochlorine pesticides in the air around the Taihu Lake, China.

Organochlorine (OC) pesticides have been used broadly in China's past, yet very little is known about their atmospheric concentrations and transport. In this work, air samples were collected in the Taihu Lake Region, China, from July 23 to August 11, 2002, to measure concentrations of OC pesticides in air. The average concentrations of alpha and gamma- hexachlorocyclohexane (HCH), hexachlorobenzene (HCB), heptachlor (HEPT), alpha-endosulfan, p,p'-DDT, p,p'-DDE, p,p'-DDD, and o,p'-DDT in the air were 74 and 46, 47, 53, 307, 124, 212, 36, and 767 pg m(-3), respectively. It was interesting to note that the concentrations of p,p'-DDT, p,p'-DDE, and o,p'-DDT were all very high, even though the use of technical DDT has been banned in China since 1983. Moreover, the average concentration ratios of o,p'-DDT/p,p'-DDT and p,p'-DDE/p,p'-DDT were as high as 6.3 and 1.8. This suggested that there could be an unknown source of DDT-related compounds (DDTs), especially o,p'-DDT and p,p'-DDE. It is very likely that this unknown source was the application of dicofol, an acaricide manufactured from technical DDT and used mainly on cotton fields to treat mites in China. Backward trajectory analysis also provided consistent evidence that the high air concentrations of DDTs were related to trajectories from the area north of the Yangtze River, where cotton fields account for a significant fraction of land use.

[Determination and characteristics of OH radical in urban atmosphere in Beijing].

The measurement of atmospheric hydroxyl radicals (OH) in Beijing was carried out using two methods based on high performance liquid chromatography (HPLC). The diurnal variation of OH concentration was obtained. The maximum concentration during sunny daytime was about 8 x 10(7) cm-3 in summer, while it decreased to about 2 x 10(7)-4 x 10(7) cm-3 in autumn. The relationships between OH and other pollutants were studied and discussed. Positive linear correlation between OH and UV-B intensity, O3, HNO2 was observed, while negative correlation between OH and NOx was found.