Re-assessment of the climatic controls on the carbon and water fluxes of a boreal aspen forest over 1996-2016: Changing sensitivity to long-term climatic conditions.

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (Re ) over 1996-2016, but Re was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R2 > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and Re ) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

Temperature thresholds of ecosystem respiration at a global scale.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.

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.

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.

Spatial and temporal variations in global soil respiration and their relationships with climate and land cover.

Soil respiration (R s) represents the largest flux of CO2 from terrestrial ecosystems to the atmosphere, but its spatial and temporal changes as well as the driving forces are not well understood. We derived a product of annual global R s from 2000 to 2014 at 1 km by 1 km spatial resolution using remote sensing data and biome-specific statistical models. Different from the existing view that climate change dominated changes in R s, we showed that land-cover change played a more important role in regulating R s changes in temperate and boreal regions during 2000-2014. Significant changes in R s occurred more frequently in areas with significant changes in short vegetation cover (i.e., all vegetation shorter than 5 m in height) than in areas with significant climate change. These results contribute to our understanding of global R s patterns and highlight the importance of land-cover change in driving global and regional R s changes.

No trends in spring and autumn phenology during the global warming hiatus.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks.

Divergent long-term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999-2017.

Long-term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999-2017 from a 120-year-old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long-term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO2 concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long-term trends in the RUEs were related to the increasing CO2 concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two-factor linear models combining CO2 concentration and air temperature performed well (R2 ~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long-term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the 'CO2 fertilization effect' on long-term variations in RUEs. Since most RUE-based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE-based modeling of C fluxes.

Biochar influences on soil CO2 and CH4 fluxes in response to wetting and drying cycles for a forest soil.

Biochar has been the focus of significant research efforts in agriculture, but little research has been conducted in forested ecosystems. Here, we assess CO2 and CH4 fluxes from a forest soil in response to biochar additions using a before-after-control-intervention experimental design. Soil CO2 and CH4 fluxes were measured over a series of wetting cycles by coupling soil mesocosms equipped with auto-chambers to a laser-based spectrometer for high-frequency measurements of gas fluxes and related soil processes. We found that soil CO2 fluxes were higher and CH4 fluxes were less negative (e.g. reduced CH4 uptake) for the biochar-amended soil compared to the no biochar condition. Furthermore, biochar improved soil infiltrability under wet conditions, and enhanced soil moisture levels under dry conditions. Biochar additions shifted the point of maximum soil respiration (i.e. soil CO2 efflux) to a slightly wetter soil moisture level. The point of maximum CH4 uptake was also shifted to a slightly wetter moisture level for soil with biochar. Overall differences in soil gas fluxes were found to be minor compared to the increase in soil carbon resulting from the biochar addition. Biochar may thus contribute to improved forest management through increases to soil carbon stocks and improved soil moisture levels.

Application of biochar and nitrogen influences fluxes of CO2, CH4 and N2O in a forest soil.

Nitrogen (N) fertilization of forests for increasing carbon sequestration and wood volume is expected to influence soil greenhouse gas (GHG) emissions, especially to increase N2O emissions. As biochar application is known to affect soil GHG emissions, we investigated the effect of biochar application, with and without N fertilization, to a forest soil on GHG emissions in a controlled laboratory study. We found that biochar application at high (10%) application rates increased CO2 and N2O emissions when applied without urea-N fertilizer. At both low (1%) and high biochar (10%) application rates CH4 consumption was reduced when applied without urea-N fertilizer. Biochar application with urea-N fertilization did not increase CO2 emissions compared to biochar amended soil without fertilizer. In terms of CO2-eq, the net change in GHG emissions was mainly controlled by CO2 emissions, regardless of treatment, with CH4 and N2O together accounting for less than 1.5% of the total emissions.

Nitrogen enrichment potential of biochar in relation to pyrolysis temperature and feedstock quality.

Nitrogen (N) enrichment of biochar from both inorganic and organic waste N sources has the potential to add economic and environmental value through its use as a slow release N fertilizer. We investigated the sorption of N by, and its release from, biochar made at pyrolysis temperatures of 400, 500 and 600 °C from three feedstocks: poultry litter (PL with a carbon (C) to N ratio (C:N) of 14), softwood chips of spruce-pine-fir (SPF with a C:N of 470), and a 50:50 mixture of PL and SPF (PL/SPF). The prepared biochars were enriched with ammonium nitrate (AN) and urea ammonium nitrate (UAN). PL biochars had the lowest C content (50-56% C), but the highest pH (9.3-9.9), electrical conductivity (EC, 780-960 dS m(-1)), cation exchange capacity (CEC, 40-46 cmol kg(-1)), and N content (3.3-4.5%). While N content and hydrogen (H) to C atomic ratio (H:C) decreased with increasing pyrolysis temperature irrespective of the feedstock used, both pH and EC slightly increased with pyrolysis temperature for all feedstocks. The PL and SPF biochars showed similar H:C and also similar N sorption and N release at all pyrolysis temperatures. These biochars sorbed up to 5% N by mass, irrespective of the source of N. However, PL/SPF biochar performed poorly in sorbing N from either AN or UAN. Biochar H:C was found to be unrelated to N sorption rates, suggesting that physical adsorption on active surfaces was the main mechanism of N sorption in these biochars. There were minor differences between N sorbed from NO3-N and NH4-N among different biochars. Very small amounts of sorbed N (0.2-0.4 mg N g(-1) biochar) was released when extracted with 1 M KCl solution, indicating that the retained N was strongly held in complex bonds, more so for NH4-N because the release of NO3-N was 3-4 times greater than that of NH4-N. NH4-N sorption far exceeded the effective CEC of the biochars, thereby suggesting that most of the sorption may be due to physical entrapment of NH4(+) in biochar pores. The results of this study suggest that biochar can be used to remove excess N from poultry and dairy manure and be a good mitigation option for reducing N leaching and gaseous losses.

Looking deeper into the soil: biophysical controls and seasonal lags of soil CO2 production and efflux.

We seek to understand how biophysical factors such as soil temperature (Ts), soil moisture (theta), and gross primary production (GPP) influence CO2 fluxes across terrestrial ecosystems. Recent advancements in automated measurements and remote-sensing approaches have provided time series in which lags and relationships among variables can be explored. The purpose of this study is to present new applications of continuous measurements of soil CO2 efflux (F0) and soil CO2 concentrations measurements. Here we explore how variation in Ts, theta, and GPP (derived from NASA's moderate-resolution imaging spectroradiometer [MODIS]) influence F0 and soil CO2 production (Ps). We focused on seasonal variation and used continuous measurements at a daily timescale across four vegetation types at 13 study sites to quantify: (1) differences in seasonal lags between soil CO2 fluxes and Ts, theta, and GPP and (2) interactions and relationships between CO2 fluxes with Ts, theta, and GPP. Mean annual Ts did not explain annual F0 and Ps among vegetation types, but GPP explained 73% and 30% of the variation, respectively. We found evidence that lags between soil CO2 fluxes and Ts or GPP provide insights into the role of plant phenology and information relevant about possible timing of controls of autotrophic and heterotrophic processes. The influences of biophysical factors that regulate daily F0 and Ps are different among vegetation types, but GPP is a dominant variable for explaining soil CO2 fluxes. The emergence of long-term automated soil CO2 flux measurement networks provides a unique opportunity for extended investigations into F0 and Ps processes in the near future.

Incorporating diffuse photosynthetically active radiation in a single-leaf model of canopy photosynthesis for a 56-year-old Douglas-fir forest.

A simple top-down model of canopy photosynthesis (P) was developed and tested in this study. The model (referred to as the Q(e)-MM model) is P = alphaQ (e) P (max)/(alphaQ ( e ) + P (max)), alpha and P (max) are quantum-use efficiency and potential P, respectively. Q (e) is given by Q (d) (0) + kQ (b) (0), where Q (d) (0) and Q (b) (0) are the diffuse and direct photosynthetically active radiation (PAR) incident on the canopy, respectively. Q (e) can be considered to be the effective incident PAR contributing to P and k is a measure of the contribution of Q (b) (0) to Q (e). When k = 1, the Q(e)-MM model becomes the regular Michaelis-Menten type model of P (referred to as the MM model). A major objective of this study was to determine how well the Q(e)-MM model could estimate P of a 56-year-old coastal Douglas-fir stand. To this end, we parameterized the Q(e)-MM model using five and half years of eddy-covariance measurements of CO(2) flux above the Douglas-fir stand. The Q(e)-MM model, with the incorporation of a function of air temperature, accounted for 74% of the variance in over 34,000 half-hourly P measurements. P estimated using the Q(e)-MM model had no systematic errors with respect to Q (d) (0). Although the Q(e)-MM model has only one more parameter than the MM model, it accounted for 30% more variance in P than the latter when total incident PAR exceeded 900 micromol m(-2) s(-1). On average, k was found to be 0.22. We show that this small value of k reflects the significant effect of the scattering of the solar beam and the fraction of light-limited sunlit leaves. We also show that the success of the Q(e)-MM model was due to the fact that a large fraction of the sunlit leaves were light-limited as a result of their orientation to the solar beam.

Effects of mutual shading of tree crowns on prediction of photosynthetic light-use efficiency in a coastal Douglas-fir forest.

Gross primary production (GPP) is often expressed as the product of absorbed photosynthetically active radiation and the efficiency (epsilon) with which a plant community uses absorbed radiation in biomass production. Light-use efficiency is affected by environmental stresses, and varies diurnally and seasonally. Uncertainty about epsilon can be a serious limitation when modeling GPP. An important determinant of epsilon is the amount and type of solar radiation incident on a canopy, because an abundance of light can trigger a photo-protective reaction, diminishing GPP. The radiation regime in a forest canopy is determined by the predominant sky conditions and by mutual shading of tree crowns. Shading effects, producing shifts in the amount of incident direct and diffuse solar radiation, have been largely ignored, however, because they depend on forest structure and are difficult to measure. We describe a new approach for estimating changes in mutual canopy shading throughout the day and year based on a canopy structure model derived from light detection and ranging (LiDAR). Proportions of canopy shading were then combined with eddy covariance data to assess the explanatory power for variance in epsilon by regression tree analysis over half-hourly, daily and weekly time scales. The approach explained between 75 and 97% of variance in epsilon, representing an increase of between 5 and 16% compared with models driven solely by meteorological variables.

Modelling environmental controls on ecosystem photosynthesis and the carbon isotope composition of ecosystem-respired CO2 in a coastal Douglas-fir forest.

We developed and applied an ecosystem-scale model that calculated leaf CO2 assimilation, stomatal conductance, chloroplast CO2 concentration and the carbon isotope composition of carbohydrate formed during photosynthesis separately for sunlit and shaded leaves within multiple canopy layers. The ecosystem photosynthesis model was validated by comparison to leaf-level gas exchange measurements and estimates of ecosystem-scale photosynthesis from eddy covariance measurements made in a coastal Douglas-fir forest on Vancouver Island. A good agreement was also observed between modelled and measured delta13C values of ecosystem-respired CO2 (deltaR). The modelled deltaR values showed strong responses to variation in photosynthetic photon flux density (PPFD), air temperature, vapour pressure deficit (VPD) and available soil moisture in a manner consistent with leaf-level studies of photosynthetic 13C discrimination. Sensitivity tests were conducted to evaluate the effect of (1) changes in the lag between the time of CO2 fixation and the conversion of organic matter back to CO2; (2) shifts in the proportion of autotrophic and heterotrophic respiration; (3) isotope fractionation during respiration; and (4) environmentally induced changes in mesophyll conductance, on modelled delta(R) values. Our results indicated that deltaR is a good proxy for canopy-level C(c)/C(a) and 13C discrimination during photosynthetic gas exchange, and therefore has several applications in ecosystem physiology.

Biophysical controls on rhizospheric and heterotrophic components of soil respiration in a boreal black spruce stand.

We conducted a root-exclusion experiment in a 125-year-old boreal black spruce (Picea mariana (Mill.) BSP) stand in 2004 to quantify the physical and biological controls on temporal dynamics of the rhizospheric (R(r)) and heterotrophic (R(h)) components of soil respiration (R(s)). Annual R(r), R(h) and estimated moss respiration were 285, 269 and 57 g C m(-2) year(-1), respectively, which accounted for 47, 44 and 9% of R(s) (611 g C m(-2) year(-1)), respectively. A gradual transition from R(h)-dominated (winter, spring and fall) to R(r)-dominated (summer) respiration was observed during the year. Soil thawing in spring and the subsequent increase in soil water content (theta) induced a small and sustained increase in R(h) but had no effect on R(r). During the remainder of the growing season, no effect of theta was observed on either component of R(s). Both components increased exponentially with soil temperature (T(s)) during the growing season, but R(r) showed greater temperature sensitivity than R(h) (Q(10) of 4.0 and 3.0, respectively). Temperature-normalized variations in R(r) were highly correlated with eddy covariance estimates of gross ecosystem photosynthesis, and the correlation was greatest when R(r) was lagged by 24 days. Within diurnal cycles, variations in T(s) were highly coupled to variations in R(h) but were significantly decoupled from R(r). The patterns observed at both time scales strongly suggest that the flow of photosynthates to the rhizosphere is a key driver of belowground respiration processes but that photosynthate supply may control these processes in several ways.

Measurement of CO2 exchange between Boreal forest and the atmosphere.

The Boreal forest is the world's second largest forested biome occupying the circumpolar region between 50 degrees N and 70 degrees N. This heterogeneous biome stores about 25% of all terrestrial carbon. We have reviewed EC measurements of CO2 exchange between the atmosphere and Boreal forests, and assessed progress in understanding the controlling processes. We have assessed net ecosystem productivity, the net balance between net primary productivity and heterotrophic respiration, measured using the EC method, for 38 Boreal forest sites. Gross ecosystem productivity has been estimated by adding day-time EC-measured CO2 fluxes to respiration estimated from night-time relationships between respiration and temperature. Maximum midday values of gross ecosystem productivity vary from 33 pmol m(-2) s(-1) for aspen to 6 micromol m(-2) s(-1) for larch stands. Long-term EC flux measurements, ongoing at nine Boreal sites, have shown the strong impact of spring weather and growing season water balance on annual net ecosystem productivity. Estimation of net biome production, incorporating the effects of disturbance resulting from forest fires and logging, has progressed significantly in recent years. After disturbance, summer measurements in Boreal chronosequences suggest that it takes about 10 years before growing season carbon uptake offsets the decomposition emissions. Small-scale exchange rate measurements using chambers and manipulative experiments such as stem girdling and soil heating help to understand the processes and mechanisms playing major roles in the carbon balance of terrestrial ecosystems. Aircraft EC flux measurements, convective boundary layer carbon budgets, and (13)C/12C changes in the atmosphere play an important role in validating estimates of regional carbon exchange based on scaled up EC measurements. Atmospheric inverse models are an important approach to studying regional and global carbon balance but need further improvement to yield reliable quantitative results.