Variability in cold front activities modulating cool-season evaporation from a southern inland water in the USA

Understanding seasonal variations in the evaporation of inland waters (e.g., lakes and reservoirs) is important for water resource management as well as the prediction of the hydrological cycles in response to climate change. We analyzed eddy covariance-based evaporation measurements from the Ross Barnett Reservoir (32◦26N, 90◦02W; which is always ice-free) in central Mississippi during the cool months (i.e., September–March) of 2007 and 2008, and found that the variability in cold front activities (i.e., passages of cold fronts and cold/dry air masses behind cold fronts) played an important role in modulating the exchange of sensible (H) and latent (λE) heat fluxes. Our analysis showed that 2007’s warmer cool season had smaller mean H and λE than 2008’s cooler cool season. This implies that the warmer cool season did not accelerate evaporation and heat exchange between the water surface and the atmosphere. Instead, more frequent cold fronts and longer periods of cold/dry air masses behind the cold fronts in 2008 resulted in overall larger H and λE as compared with 2007, this primarily taking the form of sporadic short-term rapid ‘pulses’ of H and λE losses from the water’s surface. These results suggest that future climate-induced changes in frequency of cold fronts and the meteorological properties of the air masses behind cold fronts (e.g., wind speeds, temperature, and humidity), rather than other factors of climate change, would produce significant variations in the water surface’s energy fluxes and subsequent evaporation rates.Peer reviewe

The fast and furious

Cocaine and amphetamines (‘stimulants’) are distinct central nervous system stimulants with similar effects (Pleuvry, 2009; Holman, 1994). Cocaine is a crystalline tropane alkaloid extracted from coca leaves. Amphetamines are a subclass of phenylethylamines with primarily stimulant effects, including amphetamine, methamphetamine, methcathinone and cathinone and referred to as ‘amphetamines’ in this review (Holman, 1994). MDMA (3,4-methylenedioxy-N-methamphetamine or ecstasy) is a substituted amphetamine known for its entactogenic, psychedelic, and stimulant effects (Morgan, 2000). Stimulants can produce increased wakefulness, focus and confidence, elevated mood, feelings of power, and decreased fatigue and appetite; stimulants also produce nervousness or anxiety and, in some cases, psychosis and suicidal thoughts (Holman, 1994; EMCDDA, 2007f; Hildrey et al., 2009; Pates and Riley, 2009). Although there is little evidence that stimulants cause physical dependence, tolerance may develop upon repetitive use and withdrawal may cause discomfort and depression (EMCDDA, 2007f; Pates and Riley, 2009). Users may engage in ‘coke or speed binges’ alternated with periods of withdrawal and abstinence (Beek et al., 2001)

Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest

Photosynthesis by terrestrial plants represents the majority of CO₂ uptake on Earth, yet it is difficult to measure directly from space. Estimation of gross primary production (GPP) from remote sensing indices represents a primary source of uncertainty, in particular for observing seasonal variations in evergreen forests. Recent vegetation remote sensing techniques have highlighted spectral regions sensitive to dynamic changes in leaf/needle carotenoid composition, showing promise for tracking seasonal changes in photosynthesis of evergreen forests. However, these have mostly been investigated with intermittent field campaigns or with narrow-band spectrometers in these ecosystems. To investigate this potential, we continuously measured vegetation reflectance (400–900 nm) using a canopy spectrometer system, PhotoSpec, mounted on top of an eddy-covariance flux tower in a subalpine evergreen forest at Niwot Ridge, Colorado, USA. We analyzed driving spectral components in the measured canopy reflectance using both statistical and process-based approaches. The decomposed spectral components co-varied with carotenoid content and GPP, supporting the interpretation of the photochemical reflectance index (PRI) and the chlorophyll/carotenoid index (CCI). Although the entire 400–900 nm range showed additional spectral changes near the red edge, it did not provide significant improvements in GPP predictions. We found little seasonal variation in both normalized difference vegetation index (NDVI) and the near-infrared vegetation index (NIRv) in this ecosystem. In addition, we quantitatively determined needle-scale chlorophyll-to-carotenoid ratios as well as anthocyanin contents using full-spectrum inversions, both of which were tightly correlated with seasonal GPP changes. Reconstructing GPP from vegetation reflectance using partial least-squares regression (PLSR) explained approximately 87 % of the variability in observed GPP. Our results linked the seasonal variation in reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests

Solar-Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States

Quantifying gross primary production (GPP), the largest flux of the terrestrial carbon cycle, remains difficult at the landscape scale. Evergreen needleleaf (coniferous) forests in the western United States constitute an important carbon reservoir whose annual GPP varies from year‐to‐year due to drought, mortality, and other ecosystem disturbances. Evergreen forest productivity is challenging to determine via traditional remote sensing indices (i.e., NDVI and EVI), because detecting environmental stress conditions is difficult. We investigated the utility of solar‐induced chlorophyll fluorescence (SIF) to detect year‐to‐year variation in GPP in four coniferous forests varying in species composition in the western United States (Sierra Nevada, Cascade, and Rocky Mountains). We show that annually averaged, satellite‐based observations of SIF (retrieved from GOME‐2) were significantly correlated with annual GPP observed at eddy covariance towers over several years. Further, SIF responded quantitatively to drought‐induced mortality, suggesting that SIF may be capable of detecting ecosystem disturbance in coniferous forests

Solar-Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States

Quantifying gross primary production (GPP), the largest flux of the terrestrial carbon cycle, remains difficult at the landscape scale. Evergreen needleleaf (coniferous) forests in the western United States constitute an important carbon reservoir whose annual GPP varies from year‐to‐year due to drought, mortality, and other ecosystem disturbances. Evergreen forest productivity is challenging to determine via traditional remote sensing indices (i.e., NDVI and EVI), because detecting environmental stress conditions is difficult. We investigated the utility of solar‐induced chlorophyll fluorescence (SIF) to detect year‐to‐year variation in GPP in four coniferous forests varying in species composition in the western United States (Sierra Nevada, Cascade, and Rocky Mountains). We show that annually averaged, satellite‐based observations of SIF (retrieved from GOME‐2) were significantly correlated with annual GPP observed at eddy covariance towers over several years. Further, SIF responded quantitatively to drought‐induced mortality, suggesting that SIF may be capable of detecting ecosystem disturbance in coniferous forests

Plasmas and Controlled Nuclear Fusion

Contains research objectives, summary of research and reports on six research projects.U. S. Atomic Energy Commission (Contract AT(11-1)-3070

Seasonal variation in the canopy color of temperate evergreen conifer forests

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near‐surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on‐the‐ground phenological observations, leaf‐level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower‐based CO₂ flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter‐dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy‐level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature‐based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color‐based vegetation indices

Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites:TL-LUE Parameterization and Validation

Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (εmsh) was 2.63 to 4.59 times that of sunlit leaves (εmsu). Generally, the relationships of εmsh and εmsu with εmax were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR

Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO_2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated (R^2 = 0.62–0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution