Search

Future anticipated warming could reduce the terrestrial carbon sink by ~50% by mid-century., The temperature dependence of global photosynthesis and respiration determine land carbon sink strength. While the land sink currently mitigates ~30% of anthropogenic carbon emissions, it is unclear whether this ecosystem service will persist and, more specifically, what hard temperature limits, if any, regulate carbon uptake. Here, we use the largest continuous carbon flux monitoring network to construct the first observationally derived temperature response curves for global land carbon uptake. We show that the mean temperature of the warmest quarter (3-month period) passed the thermal maximum for photosynthesis during the past decade. At higher temperatures, respiration rates continue to rise in contrast to sharply declining rates of photosynthesis. Under business-as-usual emissions, this divergence elicits a near halving of the land sink strength by as early as 2040.

The temperature dependence of biological rates at different scales (from individual enzymes to isolated organisms to ecosystem processes such as soil respiration and photosynthesis) is the subject of much historical and contemporary research. The precise relationship between the temperature dependence of enzyme rates and those at larger scales is not well understood. We have developed macromolecular rate theory (MMRT) to describe the temperature dependence of biological processes at all scales. Here we formalize the scaling relationship by investigating MMRT both at the molecular scale (constituent enzymes) and for growth of the parent organism. We demonstrate that the inflection point (Tinf) for the temperature dependence of individual metabolic enzymes coincides with the optimal growth temperature for the parent organism, and we rationalize this concordance in terms of the necessity for linearly correlated rates for metabolic enzymes over fluctuating environmental temperatures to maintain homeostasis. Indeed, Tinf is likely to be under strong selection pressure to maintain coordinated rates across environmental temperature ranges. At temperatures at which rates become uncorrelated, we postulate a regulatory catastrophe and organism growth rates precipitously decline at temperatures where this occurs. We show that the curvature in the plots of the natural log of the rate versus temperature for individual enzymes determines the curvature for the metabolic process overall and the curvature for the temperature dependence of the growth of the organism. We have called this "the inflection point hypothesis", and this hypothesis suggests many avenues for future investigation, including avenues for engineering the thermal tolerance of organisms.

Nitrous oxide (N2O) is a prominent greenhouse gas. Our understanding of environmental controls on N2O fluxes has mainly come from small-scale experiments, for example, static chamber measurements on plots or lab incubations. However, studies of the environmental controls for N2O fluxes at ecosystem scales have been limited. Using eddy covariance (EC) measurements, this study evaluated the environmental drivers of N2O fluxes for a one-year period at a farm grazed year-round by dairy cows in the Waikato region, New Zealand. We identified an optimum soil moisture/temperature zone that favours maximal N2O emissions, demonstrating maximum N2O fluxes at ∼70% water-filled pore space (WFPS) and moderate soil temperatures. Our measurements consistently identified significant N2O flux pulses associated with rainfall following grazing events in warm-dry months. In contrast, during cold-wet months when WFPS was consistently high, pulses after rainfall did not occur. A clear positive temperature response for N2O fluxes was observed above 70% WFPS while a negative relationship was detected when WFPS was less than 70%. Distinctive diurnal flux patterns emerged in both pulses and background fluxes, implying that soil temperature regulates N2O fluxes at sub-daily timescales. Over the annual period, N2O emissions were 6.5 kg N2O-N ha−1. We found the highest cumulative rates (maximum 35.7 g N2O-N ha−1 day−1) in autumn but the rates were low during both summer and winter. Our results highlighted the combined effects of environmental factors on N2O fluxes, and quantified N2O flux variations at seasonal and daily scales, suggesting that continuous measurement techniques, such as EC, could serve as an alternative in national N2O inventories.

The temperature response of soil microbial respiration (Rh) is of significance, with the optimum temperature of Rh being the key parameter for accurately modeling how it responds to temperature change under climate warming scenarios. However, knowledge about Topt in natural ecosystems remains limited, especially at large scales, which increases the uncertainty of climate projections. Here, we collected 25 soils from tropical to cold-temperate forests in the northern hemisphere to quantify regional variation in Topt and the controls underlying this variation. Rh was measured at high frequency using a novel system under the mode, with temperature gradually increasing from 5 to 50 °C. The results showed that Topt ranged from 38.5 to 46.0 °C (mean: 42.4 °C). Of note, this study is the first to demonstrate that Topt is far higher than the assumed value used in models (35 °C), varying greatly across different climatic zones and increasing with latitude from tropical to cold-temperate forest soils. To some extent, our results supported the substrate supply hypothesis, and contrast with the climate adaption hypothesis. In addition, climate, nutrient, and soil microorganisms jointly regulate regional variation in Topt, together explaining 53% of variation in Topt. The higher Topt in northern regions indicated that these regions have a greater potential to release more CO2 from soil, which might lead to a positive feedback to global warming. In conclusion, process-based models should incorporate the high variability of Topt across regions to improve predictions of the carbon dynamics of terrestrial ecosystems under climate warming scenarios.

Our understanding of how enzymes work is coloured by static structure depictions where the enzyme scaffold is presented as either immobile, or in equilibrium between well-defined static conformations. Proteins, however, exhibit a large degree of motion over a broad range of timescales and magnitudes and this is defined thermodynamically by the enzyme free energy landscape (FEL). The role and importance of enzyme motion is extremely contentious. Much of the challenge is in the experimental detection of so called 'conformational sampling' involved in enzyme turnover. Herein we apply combined pressure and temperature kinetics studies to elucidate the full suite of thermodynamic parameters defining an enzyme FEL as it relates to enzyme turnover. We find that the key thermodynamic parameters governing vibrational modes related to enzyme turnover are the isobaric expansivity term and the change in heat capacity for enzyme catalysis. Variation in the enzyme FEL affects these terms. Our analysis is supported by a range of biophysical and computational approaches that specifically capture information on protein vibrational modes and the FEL (all atom flexibility calculations, red edge excitation shift spectroscopy and viscosity studies) that provide independent evidence for our findings. Our data suggest that restricting the enzyme FEL may be a powerful strategy when attempting to rationally engineer enzymes, particularly to alter thermal activity. Moreover, we demonstrate how rational predictions can be made with a rapid computational approach.

Determining the temperature dependence of soil respiration is needed to test predictive models such as Arrhenius-like functions and macro-molecular rate theory (MMRT). We tested a method for rapid measurement of respiration using a temperature gradient block, cooled at one end (~2 °C) and heated at the other (~50 °C) that accommodated 44 tubes containing soil incubated at roughly 1 °C increments. Gas samples were taken after 5 h incubation and analysed for CO2. The temperature gradient block allowed rapid assessment of temperature dependence of soil respiration with the precision needed to test models and explore existing theories of how temperature and moisture interact to control biochemical processes. Temperature response curves were well fitted by MMRT and allowed calculation of the temperature at which absolute temperature sensitivity was maximal (Tinf). We measured temperature response of three soils at seven moisture contents and showed that the absolute rate and sensitivity of respiration was partly dependent on adjusted moisture content. This result implied that comparisons between soils need to be made at a common moisture content. We also measured potential changes in the temperature dependence (and sensitivity) of respiration for three different soils collected at one site throughout a year. Tinf ranged from 43 to 51 °C for the three soils. Tinf and temperature sensitivity were not dependent on soil type collected but was partly dependent on time of year of collection. Temporal changes in temperature response suggested that the microbial communities may tune their metabolisms in response to changes in soil temperatures.

Agricultural production in the hot and arid low desert systems of southern California relies heavily on irrigation. A better understanding of how much and to what extent irrigated water is transpired by crops relative to being lost through evaporation would improve the management of increasingly limited water resources. In this study, we examined the partitioning of evapotranspiration (ET) over a field of forage sorghum (Sorghum bicolor), which was under evaluation as a potential biofuel feedstock, based on isotope measurements of three irrigation cycles at the vegetative stage. This study employed customized transparent chambers coupled with a laser-based isotope analyzer to continuously measure near-surface variations in the stable isotopic composition of evaporation (E, δE), transpiration (T, δT) and ET (δET) to partition the total water flux. Due to the extreme heat and aridity, δE and δT were very similar, which makes this system highly unusual. Contrary to an expectation that the isotopic signatures of T, E, and ET would become increasingly enriched as soils became drier, our results showed an interesting pattern that δE, δT, and δET increased initially as soil water was depleted following irrigation, but decreased with further soil drying in mid to late irrigation cycle. These changes are likely caused by root water transport from deeper to shallower soil layers. Results indicate that about 46% of the irrigated water delivered to the crop was used as transpiration, with 54% lost as direct evaporation. This implies that 28 − 39% of the total source water was used by the crop, considering the typical 60 − 85% efficiency of flood irrigation. The stable isotope technique provided an effective means of determining surface partitioning of irrigation water in this unusually harsh production environment. The results suggest the potential to further minimize unproductive water losses in these production systems.

Increasing atmospheric nitrogen (N) inputs have the potential to alter terrestrial ecosystem function through impacts on plant-herbivore interactions. The goal of our study is to search for a general pattern in responses of tree characteristics important for herbivores and insect herbivorous performance to elevated N inputs. We conducted a meta-analysis based on 109 papers describing impacts of nitrogen inputs on tree characteristics and 16 papers on insect performance. The differences in plant characteristics and insect performance between broadleaves and conifers were also explored. Tree aboveground biomass, leaf biomass and leaf N concentration significantly increased under elevated N inputs. Elevated N inputs had no significantly overall effect on concentrations of phenolic compounds and lignin but adversely affected tannin, as defensive chemicals for insect herbivores. Additionally, the overall effect of insect herbivore performance (including development time, insect biomass, relative growth rate, and so on) was significantly increased by elevated N inputs. According to the inconsistent responses between broadleaves and conifers, broadleaves would be more likely to increase growth by light interception and photosynthesis rather than producing more defensive chemicals to elevated N inputs by comparison with conifers. Moreover, the overall carbohydrate concentration was significantly reduced by 13.12% in broadleaves while increased slightly in conifers. The overall tannin concentration decreased significantly by 39.21% in broadleaves but a 5.8% decrease in conifers was not significant. The results of the analysis indicated that elevated N inputs would provide more food sources and ameliorate tree palatability for insects, while the resistance of trees against their insect herbivores was weakened, especially for broadleaves. Thus, global forest insect pest problems would be aggravated by elevated N inputs. As N inputs continue to rise in the future, forest ecosystem management should pay more attention to insect pest, especially in the regions dominated by broadleaves.

Linking variation in ecosystem functioning to physiological and landscape drivers has become an important research need for understanding ecosystem responses to global changes. We investigate how these contrasting scale dependent ecosystem drivers influence soil respiration (Rs), a key ecosystem process, using in-situ landscape surveys and experimental subsidies of water and labile carbon. Surveys and experiments were conducted in summer and winter seasons and were distributed along a coastal to desert climate gradient and among the dominant land-use classes in southern California, USA. We found Rs decreased from lawn to agricultural and wildland land-uses for both seasons and along the climate gradient in the summer while increasing along the climate gradient in the winter. Rs variation was positively correlated with soil temperature, and negatively to soil moisture and substrate. Water additions increased Rs in wildland land-uses, while urban land-uses responded little or negatively. However, most land-uses exhibited carbon limitation, with wildlands experiencing largest responses to labile carbon additions. These findings show intensively managed land-uses have increased rates, decreased spatial variation, and decreased sensitivity to environmental conditions in Rs compared to wild lands while increasing aridity has the opposite effect. In linking scales, physiological drivers were correlated with Rs but landscape position influenced Rs by altering both the physiological drivers and the sensitivity to the drivers. Systematic evaluation of physiological and landscape variation provides a framework for understanding the effects of interactive global change drivers to ecosystem metabolism across multiple scales.

Biogeochemical processes driving the spatial variability of soil CO2 production and flux are well studied, but little is known about the variability in the spatial distribution of the stable carbon isotopes that make up soil CO2, particularly in complex terrain. Spatial differences in stable isotopes of soil CO2 could indicate fundamental differences in isotopic fractionation at the landscape level and may be useful to inform modeling of carbon cycling over large areas. We measured the spatial and seasonal variabilities of the δ13C of soil CO2 (δS) and the δ13C of soil CO2 flux (δP) in a subalpine forest ecosystem located in the Rocky Mountains of Montana. We found consistently more isotopically depleted values of δS and δP in low and wet areas of the landscape relative to steep and dry areas. Our results suggest that the spatial patterns of δS and δP are strongly mediated by soil water and soil respiration rate. More interestingly, our analysis revealed different temporal trends in δP across the landscape; in high landscape positions δP became more positive, whereas in low landscape positions δP became more negative with time. These trends might be the result of differential dynamics in the seasonality of soil moisture and its effects on soil CO2 production and flux. Our results suggest concomitant yet independent effects of water on physical (soil gas diffusivity) and biological (photosynthetic discrimination) processes that mediate δS and δP and are important when evaluating the δ13C of CO2 exchanged between soils and the atmosphere in complex terrain.

Landscape plants have great potentials in heavy metals (HMs) removal as sewage sludge compost (SSC) is increasingly used in urban forestry. We hypothesize that woody plants might perform better in HMs phytoremediation because they have greater biomass and deeper roots than herbaceous plants. We tested the differences in growth responses and HMs phytoremediation among several herbaceous and woody species growing under different SSC concentrations through pot experiments. The mixing percentage of SSC with soil at 0%, 15%, 30%, 60, and 100% were used as growth substrate for three woody (Ficus altissima Bl., Neolamarckia cadamba (Roxb.) Bosser, and Bischofia javanica Bl.) and two herbaceous (Alocasia macrorrhiza (L.) G. Don and Dianella ensifolia (L.) DC) plants. Results showed that the biomass, relative growth rate, and nutrient uptake for all plants increased significantly at each SSC concentration compared to the control; woody plants had higher biomass and nutrient use efficiency than herbaceous plants. All plants growing in SSC-amended soils accumulated appreciable amounts of HMs and reduced the contents of HMs present in the substrates. The woody plants were generally more effective than herbaceous plants in potentials of HMs phytoextraction, but A. macrorrhiza showed higher bioconcentration and translocation of Cu and Zn and D. ensifolia had higher bioconcentration and translocation of Cd than woody plants. The optimal application concentrations were 30% or less for woody plants and 15% for herbaceous plants for plant growth and ecological risk control, respectively. Intercropping suitable woody and herbaceous landscape plants in urban forestry might have promising potentials to minimize the ecological risks in the phytoremediation of SSC.

Application of sewage sludge compost (SSC) as a fertilizer on landscaping provides a potential way for the effective disposal of sludge. However, the response of landscape trees to SSC application and the impacts of heavy metals from SSC on soil are poorly understood. We conducted a pot experiment to investigate the effects of SSC addition on Mangifera persiciforma growth and quantified its uptake of heavy metals from SSC by setting five treatments with mass ratios of SSC to lateritic soil as 0%:100% (CK), 15%:85% (S15), 30%:70% (S30), 60%:40% (S60), and 100%:0% (S100). As expected, the fertility and heavy metal concentrations (Cu, Zn, Pb and Cd) in substrate significantly increased with SSC addition. The best performance in terms of plant height, ground diameter, biomass and N, P, K uptake were found in S30, implying a reasonable amount of SSC could benefit the growth of M. persiciforma. The concentrations of Cu, Pb and Cd in S30 were insignificantly different from CK after harvest, indicating that M. persiciforma reduced the risk of heavy metal contamination of soil arising from SSC application. This study suggests that a reasonable rate of SSC addition can enhance M. persiciforma growth without causing the contamination of landscaping soil by heavy metals.

Temperature is a crucial factor in determining the rates of ecosystem processes, for example, leaf respiration (R) - the flux of plant respired CO2 from leaves to the atmosphere. Generally, R increases exponentially with temperature and formulations such as the Arrhenius equation are widely used in earth system models. However, experimental observations have shown a consequential and consistent departure from an exponential increase in R. What are the principles that underlie these observed patterns? Here, we demonstrate that macromolecular rate theory (MMRT), based on transition state theory (TST) for enzyme-catalyzed kinetics, provides a thermodynamic explanation for the observed departure and the convergent temperature response of R using a global database. Three meaningful parameters emerge from MMRT analysis: the temperature at which the rate of respiration would theoretically reach a maximum (the optimum temperature, Topt ), the temperature at which the respiration rate is most sensitive to changes in temperature (the inflection temperature, Tinf ) and the overall curvature of the log(rate) versus temperature plot (the change in heat capacity for the system, ΔCP‡). On average, the highest potential enzyme-catalyzed rates of respiratory enzymes for R are predicted to occur at 67.0 ± 1.2°C and the maximum temperature sensitivity at 41.4 ± 0.7°C from MMRT. The average curvature (average negative ΔCP‡) was -1.2 ± 0.1 kJ mol-1 K-1 . Interestingly, Topt , Tinf and ΔCP‡ appear insignificantly different across biomes and plant functional types, suggesting that thermal response of respiratory enzymes in leaves could be conserved. The derived parameters from MMRT can serve as thermal traits for plant leaves that represent the collective temperature response of metabolic respiratory enzymes and could be useful to understand regulations of R under a warmer climate. MMRT extends the classic TST to enzyme-catalyzed reactions and provides an accurate and mechanistic model for the short-term temperature response of R around the globe.

a b s t r a c t Rivers provide critically important ecosystem services to society, and play an essential role in maintaining the structure, function, and integrity of landscapes in which the rivers reside. Better understanding of the patterns and processes in river systems requires a broader landscape approach that goes beyond the traditional linear and longitudinal focus. Such a landscape approach is especially important for effectively restoring and managing already damaged or degraded rivers around the world. Toward this end, here we develop a riverscape transect approach by adapting landscape gradient analysis with pattern metrics so as to quantify the longitudinal variations in the spatial pattern of the river-land complex from headwater to mouth. Two rivers systems in southern China were used to develop and demonstrate the approach. For each river, we first constructed a riverscape transect, consisting of a spatial series of overlapping neighborhood landscapes, then computed a selected set of landscape metrics, and finally depicted the longitudinal profile of riverscape pattern with relative location-based plots. Our results have shown that this riverscape transect approach is conceptually consistent with the increasingly prominent riverine landscape perspective and technically feasible with the aid of remote sensing data and landscape pattern analysis methods. In particular, landscape metrics, such as percentages of urban and native vegetation, patch density, and Shannon diversity, can be used to reveal important variations in riverscape structure along the river. These longitudinal profiles of riverscape pattern, used as spatial indicators, can help identify key socioeconomic drivers and ecological impacts of land use and land cover change in the watershed. Our study demonstrates that this riverscape transect approach can be a new and effective way of facilitating the planning and evaluation of river restoration and management efforts.

Soil temperature is a key control on belowground chemical and biological processes. Typically, models of soil temperature are developed and validated for large geographic regions. However, modeling frameworks intended for higher spatial resolutions (much finer than 1 km2) are lacking across areas of complex topography. Here we propose a simple modeling framework for predicting distributed soil temperature at high temporal (i.e., 1 h steps) and spatial (i.e., 5 × 5 m) resolutions in mountainous terrain, based on a few discrete air temperature measurements. In this context, two steps were necessary to estimate the soil temperature. First, we applied the potential temperature equation to generate the air temperature distribution from a 5 m digital elevation model and Inverse Distance Weighting interpolation. Second, we applied a hybrid model to estimate the distribution of soil temperature based on the generated air temperature surfaces. Our results show that this approach simulated the spatial distribution of soil temperature well, with a root-mean-square error ranging from ~2.1 to 2.9°C. Furthermore, our approach predicted the daily and monthly variability of soil temperature well. The proposed framework can be applied to estimate the spatial variability of soil temperature in mountainous regions where direct observations are scarce.

Our study examines the urban vegetation - air temperature (Ta) - land surface temperature (LST) nexus at micro- and regional-scales to better understand urban climate dynamics and the uncertainty in using satellite-based LST for characterizing Ta. While vegetated cooling has been repeatedly linked to reductions in urban LST, the effects of vegetation on Ta, the quantity often used to characterize urban heat islands and global warming, and on the interactions between LST and Ta are less well characterized. To address this need we quantified summer temporal and spatial variation in Ta through a network of 300 air temperature sensors in three sub-regions of greater Los Angeles, CA, which spans a coastal to desert climate gradient. Additional sensors were placed within the inland sub-region at two heights (0.1m and 2m) within three groundcover types: bare soil, irrigated grass, and underneath citrus canopy. For the entire study region, we acquired new imagery data, which allowed calculation of the normalized difference vegetation index (NDVI) and LST. At the microscale, daytime Ta measured along a vertical gradient, ranged from 6 to 3°C cooler at 0.1 and 2m, underneath tall canopy compared to bare ground respectively. At the regional scale NDVI and LST were negatively correlated (p

Potential evapotranspiration (PET) is an important component of water cycle. For traditional models derived from the principle of aerodynamics and the surface energy balance, its calculation always includes many parameters, such as net radiation, water vapor pressure, air temperature and wind speed. We found that it can be acquired in an easier way in specific regions. In this study, a new PET model (PETP model) derived from two empirical models of soil respiration was evaluated using the Penman–Monteith equation as a standard method. The results indicate that the PETP model estimation concur with the Penman–Monteith equation in sites where annual precipitation ranges from 717.71 mm to 1727.37 mm (R2 = 0.68, p = 0.0002), but show large discrepancies in all sites (R2 = 0.07, p = 0.1280). Then we applied our PETP model at the global scale to the regions with precipitation higher than 700 mm using 2.5° CMAP data to obtain the annual PET for 2006. As expected, the spatial pattern is satisfactory overall, with the highest PET values distributed in the lower latitudes or coastal regions, and with an average of 1292.60 ± 540.15 mm year−1. This PETP model provides a convenient approach to estimate PET at regional scales.

The spatial pattern of vegetation changes during ecologicalrestoration, and these changes are affected by the processof restoration. The objective of this study was to integratethe pattern and mechanism of forest restoration in theDinghushan Nature Reserve (DNR), Guangdong, China,based on data from remote sensing and long-term fieldobservations. We studied the pattern dynamics of threemain forest types and their underlying mechanisms dur-ing restoration following a multiscale, hierarchical patchdynamics framework that integrates population, commu-nity, and landscape processes. Remote sensing data wereused to determine the changes in landscape pattern duringdifferent periods of forest restoration from 1978 to 2006.At the landscape scale, the number, area, and perimeter ofthe needle/broad-leaved mixed forest (MF) and the ever-green broad-leaved forest (BF) increased, whereas thoseof the tropical needle-leaved forest (NF) decreased duringsuccession. Our analysis based on long-term field observa-tions indicated that the change rate of NF was lower thanthat of MF during 1981–1996, but became much higherduring 1996–2007. The rate of change in landscape patternand the progression of succession stages were consistentwith each other. Our results also showed that species regen-eration and community succession are the biological basisof forest landscape dynamics during vegetation restora-tion. Landscapepatternanalysisallowedustoshow“what”happened during vegetation restoration and “where,” andpopulation and community analysis indicated “why” and“how” it happened.Key words: 3S, community succession, landscape pattern,long-term field observations, species composition, vegeta-tion restoration.Introduction

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality., Soil NOx emissions can significantly impact air quality in agricultural regions, particularly high temperature fertilized systems. Here, the authors investigate NOx emissions in one such system in California and suggest that the NOx emissions are the highest ever observed, with implications for air quality.

Climate and land use models project increasing occurrence of high temperature and water deficit in both agricultural production systems and terrestrial ecosystems. Episodic soil wetting and subsequent drying may increase the occurrence and magnitude of pulsed biogeochemical activity, affecting carbon (C) and nitrogen (N) cycles and influencing greenhouse gas (GHG) emissions. In this study, we provide the first data to explore the responses of CO2 and N2O fluxes to (1) temperature, (2) soil water content as percent water holding capacity (%WHC), and (3) substrate availability throughout (4) multiple soil drying and rewetting (DW) events. Each of these factors and their interactions exerted effects on GHG emissions over a range of four (CO2) and six (N2O) orders of magnitude. Maximal CO2 and N2O fluxes were observed in environments combining intermediate %WHC, elevated temperature, and sufficient substrate availability. Amendments of C and N and their interactions significantly affected CO2 and N2O fluxes, and altered their temperature sensitivities (Q10) over successive DW cycles. C amendments significantly enhanced CO2 flux, reduced N2O flux, and decreased the Q10 of both. N amendments had no effect on CO2 flux and increased N2O flux, while significantly depressing the Q10 for CO2, and having no effect on the Q10 for N2O. The dynamics across DW cycles could be attributed to changes in soil microbial communities since the different responses to wetting events in specific group of microorganisms, to the altered substrate availabilities, or to both. The complex interactions among parameters influencing trace gas fluxes should be incorporated into next generation earth system models to improve estimation of GHG emissions. This article is protected by copyright. All rights reserved.

Urban vegetation provides many highly valued ecosystem services but also requires extensive urban water resources. Increasingly, cities are experiencing water limitations and managing outdoor urban water use is an important concern. Quantifying the water lost via evapotranspiration (ET) is critical for urban water management and conservation, especially in arid or semi-arid regions. In this study, we deployed a mobile energy balance platform to measure evaporative fraction throughout Riverside, California, a warm, semi-arid, city. We observed the relationship between evaporative fraction and satellite derived vegetation index across 29 sites, which was then used to map whole-city ET for a representative mid-summer period. Resulting ET distributions were strongly associated with both neighborhood population density and income. By comparing 2014 and 2015 summer-period water uses, our results show 7.8% reductions in evapotranspiration, which were also correlated with neighborhood demographic characteristics. Our findings suggest a mobile energy balance measurement platform coupled with satellite imagery could serve as an effective tool in assessing the outdoor water use at neighborhood to whole city scales.

Carbon (C) and nitrogen (N) interactions contribute to uncertainty in current biogeochemical models that aim to estimate greenhouse gas (GHG, including CO2 and N2O) emissions from soil to atmosphere. In this study, we quantified CO2 and N2O flux patterns and their relationship along with increasing C additions only, N additions only, a C gradient combined with excess N, and an N gradient with excess C via laboratory incubations. Conventional trends, where labile C or N addition results in higher CO2 or N2O fluxes, were observed. However, at low levels of C availability, saturating N amendments reduced soil CO2 flux while with high C availability N amendments enhanced it. At saturating C conditions increasing N amendments first reduced and then increased CO2 fluxes. Similarly, N2O fluxes were initially reduced by adding labile C under N limited conditions, but additional C enhanced N2O fluxes by more than two orders of magnitude in the saturating N environment. Changes in C or N use efficiency could explain the altered gas flux patterns and imply a critical level in the interactions between N and C availability that regulate soil trace gas emissions and biogeochemical cycling. Compared to either N or C amendment alone, the interaction of N and C caused ~60 and ~5 times the total GHG emission, respectively. Our findings suggested that the response of CO2 and N2O fluxes along stoichiometric gradients in C and N availability should be accounted for interpreting or modeling the biogeochemistry of GHG emissions.