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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.

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.

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.

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

In mountainous landscapes, soil moisture is highly dynamic due to the effects of topography and the temporal variability imposed by seasonal precipitation, including rainfall and snow. Soil moisture is known to affect ecosystem carbon exchange both aboveground and belowground, as well as the stable isotopic composition of exchanged CO2. In this study we used an extensive suite of measurements to examine the effects of seasonal changes in soil moisture on the isotopic composition of soil CO2 production at the landscape level. We show that the seasonal decline in soil moisture (i.e., summer dry-down) appeared to impose a trend in the δ13C of soil CO2 production (δP) with more negative δP early in the growing season when soils were wet, and more positive δP as the growing season progressed and soils dried out. This seemingly generalizable pattern for a snow-dominated watershed is likely to represent the variability of recently assimilated C, tracked through the plant-soil system and imprinted in the respired CO2. Thus, our observations suggest that, at least for mountainous environments, seasonal changes in δP are largely mediated by soil moisture and their spatial variability is partially organized by topography.

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.

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.