Scale and uncertainty in modeled soil organic carbon stock changes for US croplands using a process‐based model

Process‐based model analyses are often used to estimate changes in soil organic carbon (SOC), particularly at regional to continental scales. However, uncertainties are rarely evaluated, and so it is difficult to determine how much confidence can be placed in the results. Our objective was to quantify uncertainties across multiple scales in a process‐based model analysis, and provide 95% confidence intervals for the estimates. Specifically, we used the Century ecosystem model to estimate changes in SOC stocks for US croplands during the 1990s, addressing uncertainties in model inputs, structure and scaling of results from point locations to regions and the entire country. Overall, SOC stocks increased in US croplands by 14.6 Tg C yr^?1 from 1990 to 1995 and 17.5 Tg C yr^?1 during 1995 to 2000, and uncertainties were ±22% and ±16% for the two time periods, respectively. Uncertainties were inversely related to spatial scale, with median uncertainties at the regional scale estimated at ±118% and ±114% during the early and latter part of 1990s, and even higher at the site scale with estimates at ±739% and ±674% for the time periods, respectively. This relationship appeared to be driven by the amount of the SOC stock change; changes in stocks that exceeded 200 Gg C yr^?1 represented a threshold where uncertainties were always lower than ±100%. Consequently, the amount of uncertainty in estimates derived from process‐based models will partly depend on the level of SOC accumulation or loss. In general, the majority of uncertainty was associated with model structure in this application, and so attaining higher levels of precision in the estimates will largely depend on improving the model algorithms and parameterization, as well as increasing the number of measurement sites used to evaluate the structural uncertainty.     

Uncertainty in estimating land use and management impacts on soil organic carbon storage for US agricultural lands between 1982 and 1997

Uncertainty was quantified for an inventory estimating change in soil organic carbon (SOC) storage resulting from modifications in land use and management across US agricultural lands between 1982 and 1997. This inventory was conducted using a modified version of a carbon (C) accounting method developed by the Intergovernmental Panel on Climate Change (IPCC). Probability density functions (PDFs) were derived for each input to the IPCC model, including reference SOC stocks, land use/management activity data, and management factors. Change in C storage was estimated using a Monte‐Carlo approach with 50 000 iterations, by randomly selecting values from the PDFs after accounting for dependencies in the model inputs. Over the inventory period, mineral soils had a net gain of 10.8 Tg C yr^?1, with a 95% confidence interval ranging from 6.5 to 15.3 Tg C yr^?1. Most of this gain was due to setting‐aside lands in the Conservation Reserve Program. In contrast, managed organic soils lost 9.4 Tg C yr^?1, with a 95% confidence interval ranging from 6.4 to 13.3 Tg C yr^?1. Combining these gains and losses in SOC, US agricultural soils accrued 1.3 Tg C yr^?1 due to land use and management change, with a 95% confidence interval ranging from a loss of 4.4 Tg C yr^?1 to a gain of 6.9 Tg C yr^?1. Most of the uncertainty was attributed to management factors for tillage, land use change between cultivated and uncultivated conditions, and C loss rates from managed organic soils. Based on the uncertainty, we are not able to conclude with 95% confidence that change in US agricultural land use and management between 1982 and 1997 created a net C sink for atmospheric CO₂.     

Quantifying the importance of geographic replication and representativeness when estimating demographic rates,using a coastal species as a case study

Demographic rates are rarely estimated over an entire species range, limiting empirical tests of ecological patterns and theories, and raising questions about the representativeness of studies that use data from a small part of a range. The uncertainty that results from using demographic rates from just a few sites is especially pervasive in population projections, which are critical for a wide range of questions in ecology and conservation. We developed a simple simulation to quantify how this lack of geographic representativeness can affect inferences about the global mean and variance of growth rates, which has implications for the robust design of a wide range of population studies. Using a coastal songbird, saltmarsh sparrow Ammodramus caudacutus, as a case study, we first estimated survival, fecundity, and population growth rates at 21 sites distributed across much of their breeding range. We then subsampled this large, representative dataset according to five sampling scenarios in order to simulate a variety of geographic biases in study design. We found spatial variation in demographic rates, but no large systematic patterns. Estimating the global mean and variance of growth rates using subsets of the data suggested that at least 10–15 sites were required for reasonably unbiased estimates, highlighting how relying on demographic data from just a few sites can lead to biased results when extrapolating across a species range. Sampling at the full 21 sites, however, offered diminishing returns, raising the possibility that for some species accepting some geographical bias in sampling can still allow for robust range‐wide inferences. The subsampling approach presented here, while conceptually simple, could be used with both new and existing data to encourage efficiency in the design of long‐term or large‐scale ecological studies.     

A new estimation of global soil greenhouse gas fluxes using a simple data-oriented model

Soil greenhouse gas fluxes (particularly CO₂, CH₄, and N₂O) play important roles in climate change. However, despite the importance of these soil greenhouse gases, the number of reports on global soil greenhouse gas fluxes is limited. Here, new estimates are presented for global soil CO₂ emission (total soil respiration), CH₄ uptake, and N₂O emission fluxes, using a simple data-oriented model. The estimated global fluxes for CO₂ emission, CH₄ uptake, and N₂O emission were 78 Pg C yr⁻¹ (Monte Carlo 95% confidence interval, 64–95 Pg C yr⁻¹), 18 Tg C yr⁻¹ (11–23 Tg C yr⁻¹), and 4.4 Tg N yr⁻¹ (1.4–11.1 Tg N yr⁻¹), respectively. Tropical regions were the largest contributor of all of the gases, particularly the CO₂ and N₂O fluxes. The soil CO₂ and N₂O fluxes had more pronounced seasonal patterns than the soil CH₄ flux. The collected estimates, including both the previous and the present estimates, demonstrate that the means of the best estimates from each study were 79 Pg C yr⁻¹ (291 Pg CO₂ yr⁻¹; coefficient of variation, CV = 13%, N = 6) for CO₂, 21 Tg C yr⁻¹ (29 Tg CH₄ yr⁻¹; CV = 24%, N = 24) for CH₄, and 7.8 Tg N yr⁻¹ (12.2 Tg N₂O yr⁻¹; CV = 38%, N = 11) for N₂O. For N₂O, the mean of the estimates that was calculated by excluding the earliest two estimates was 6.6 Tg N yr⁻¹ (10.4 Tg N₂O yr⁻¹; CV = 22%, N = 9). The reported estimates vary and have large degrees of uncertainty but their overall magnitudes are in general agreement. To further minimize the uncertainty of soil greenhouse gas flux estimates, it is necessary to build global databases and identify key processes in describing global soil greenhouse gas fluxes.     

Regional application of PnET-N-DNDC for estimating the N2O source strength of tropical rainforests in the Wet Tropics of Australia

In contrast to the significant importance of tropical rainforest ecosystems as one of the major sources within the global atmospheric N₂O budget (2.2–3.7 Tg N yr^?1), regional estimates of their N₂O source strength are still limited and highly uncertain. To contribute toward more reliable estimates of the N₂O source strength of tropical rainforest ecosystems on a regional scale, we modified a process‐oriented biogeochemical model, PnET‐N‐DNDC, and parameterized it to simulate C and N turnover and associated N₂O emissions in and from tropical rainforest ecosystems. Model modifications included: (1) new parameterizations associated with plant physiology and soil hydrology and the addition of algorithms relating daily leaf litterfall to water stress as well as to daily rainfall to account for the effects of heavy rainfall damage; (2) the development of a denitrifier activity index that depends on soil moisture conditions and influences N turnover by denitrification; and (3) the addition of a biological N fixation algorithm. Daily simulated N₂O emissions based on site data were in good agreement (model efficiencies up to 0.83) with field observations in the Wet Tropics of Australia and Costa Rica. The model was even able to reproduce the highly dynamic pattern of N₂O emissions with short‐term increases during the wet season. Sensitivity analyses demonstrated that the PnET‐N‐DNDC model was sensitive to changes in soil properties such as pH, clay content, soil organic carbon and climatic factors such as rainfall and temperature. By linking the PnET‐N‐DNDC model to a geographic information systems database, tropical rainforests in a 9000 km² area of the Wet Tropics of Australia are estimated to emit 962 t N₂O‐N yr^?1 (2.4 kg N₂O‐N ha^?1 yr^?1) between July 1997 and June 1998.     

Regionalization of methane emissions in the Amazon Basin with microwave remote sensing

Wetlands of the Amazon River basin are globally significant sources of atmospheric methane. Satellite remote sensing (passive and active microwave) of the temporally varying extent of inundation and vegetation was combined with field measurements to calculate regional rates of methane emission for Amazonian wetlands. Monthly inundation areas for the fringing floodplains of the mainstem Solimões/Amazon River were derived from analysis of the 37 GHz polarization difference observed by the Scanning Multichannel Microwave Radiometer from 1979 to 1987. L‐band synthetic aperture radar data (Japanese Earth Resources Satellite‐1) were used to determine inundation and wetland vegetation for the Amazon basin (<500 m elevation) at high (May–June 1996) and low water (October 1995). An extensive set of measurements of methane emission is available from the literature for the fringing floodplains of the central Amazon, segregated into open water, flooded forest and floating macrophyte habitats. Uncertainties in the regional emission rates were determined by Monte Carlo error analyses that combined error estimates for the measurements of emission and for calculations of inundation and habitat areas. The mainstem Solimões/Amazon floodplain (54–70°W) emitted methane at a mean annual rate of 1.3 Tg C yr^?1, with a standard deviation (SD) of the mean of 0.3 Tg C yr^?1; 67% of this range in uncertainty is owed to the range in rates of methane emission and 33% is owed to uncertainty in the areal estimates of inundation and vegetative cover. Methane emission from a 1.77 million square kilometers area in the central basin had a mean of 6.8 Tg C yr^?1 with a SD of 1.3 Tg C yr^?1. If extrapolated to the whole basin below the 500 m contour, approximately 22 Tg C yr^?1 is emitted; this mean flux has a greenhouse warming potential of about 0.5 Pg C as CO₂. Improvement of these regional estimates will require many more field measurements of methane emission, further examination of remotely sensed data for types of wetlands not represented in the central basin, and process‐based models of methane production and emission.     

Estimation of forest carbon budget from land cover change in South and North Korea between 1981 and 2010

This paper quantified carbon budget in the past 30 years (1981–2010) and identified the impact of land cover change on carbon dynamics using vegetation integrated simulator for trace gases (VISIT) model. North Korea was converted from carbon sink to source with 10.72 ± 5.18 Tg C yr^?1 of net ecosystem production (NEP) in the 1980s, 3.00 ± 7.96 Tg C yr^?1 in the 1990s, and ?0.46 ± 5.13 Tg C yr^?1 in the 2000s. NEP in South Korea was 10.55 ± 1.09 Tg C yr^?1 in the 1980s, 10.47 ± 7.28 Tg C yr^?1 in the 1990s, and 6.32 ± 5.02 Tg C yr^?1 in the 2000s, showing a gradual decline. In North Korea, NEP was decreased by 0.52 Tg yr^?1 in the 1990s due to reduction of forest, and increased by 0.36 Tg yr^?1 in the 2000s due to expansion of cropland. In South Korea, it was decreased by 0.24 Tg yr^?1 in the 1990s as urban and built-up area expanded, and increased by 0.04 Tg yr^?1 in the 2000s with the expansion of forest. These results suggest the importance of forest and land cover management against deforestation for ensuring national carbon balance.     

Parameterization of Coulomb interaction in three-dimensional periodic systems

A simple method is proposed to calculate Coulomb interactions in three-dimensional periodic cubic systems. It is based on the parameterization of the interaction on polynomials and rational functions. The parameterized functions are compared to tabulation methods, to the Ewald calculations and cubic harmonic function fits found in the literature. Our parameterizations are computationally more efficient than, the use of tabulations at all cases and seem to be more efficient than the cubic harmonic parameterizations in the case of simultaneous potential energy and force calculations. In comparison to the Ewald method, it is feasible to use the parameterizations on small systems and on systems, where pair-wise additive short-range interactions are dominant. One also may prefer the parameterizations to the Ewald method for large systems, if limited accuracy is needed. The embedding of the method into existing molecular dynamics and Monte Carlo simulation codes is very simple. The presented investigation contains some numerical experimental data to support the correct theoretical partition of potential energy in periodic systems, as well.     

Methane emissions from rice paddies natural wetlands,lakes in China: synthesis new estimate

Sources of methane (CH₄) become highly variable for countries undergoing a heightened period of development due to both human activity and climate change. An urgent need therefore exists to budget key sources of CH₄, such as wetlands (rice paddies and natural wetlands) and lakes (including reservoirs and ponds), which are sensitive to these changes. For this study, references in relation to CH₄ emissions from rice paddies, natural wetlands, and lakes in China were first reviewed and then reestimated based on the review itself. Total emissions from the three CH₄ sources were 11.25 Tg CH₄ yr^?1 (ranging from 7.98 to 15.16 Tg CH₄ yr^?1). Among the emissions, 8.11 Tg CH₄ yr^?1 (ranging from 5.20 to 11.36 Tg CH₄ yr^?1) derived from rice paddies, 2.69 Tg CH₄ yr^?1 (ranging from 2.46 to 3.20 Tg CH₄ yr^?1) from natural wetlands, and 0.46 Tg CH₄ yr^?1 (ranging from 0.33 to 0.59 Tg CH₄ yr^?1) from lakes (including reservoirs and ponds). Plentiful water and warm conditions, as well as its large rice paddy area make rice paddies in southeastern China the greatest overall source of CH₄, accounting for approximately 55% of total paddy emissions. Natural wetland estimates were slightly higher than the other estimates owing to the higher CH₄ emissions recorded within Qinghai‐Tibetan Plateau peatlands. Total CH₄ emissions from lakes were estimated for the first time by this study, with three quarters from the littoral zone and one quarter from lake surfaces. Rice paddies, natural wetlands, and lakes are not constant sources of CH₄, but decreasing ones influenced by anthropogenic activity and climate change. A new progress‐based model used in conjunction with more observations through model‐data fusion approach could help obtain better estimates and insights with regard to CH₄ emissions deriving from wetlands and lakes in China.     

Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations

Engelmann spruce (Picea engelmannii Parry ex Engelm.) is a high-elevation species found in western Canada and western USA. As this species becomes increasingly targeted for harvesting, better height growth information is required for good management of this species. This project was initiated to fill this need. The objective of the project was threefold: develop a site index model for Engelmann spruce; compare the fits and modelling and application issues between three model formulations and four parameterizations; and more closely examine the grounded-Generalized Algebraic Difference Approach (g-GADA) model parameterization. The model fitting data consisted of 84 stem analyzed Engelmann spruce site trees sampled across the Engelmann Spruce – Subalpine Fir biogeoclimatic zone. The fitted models were based on the Chapman-Richards function, a modified Hossfeld IV function, and the Schumacher function. The model parameterizations that were tested are indicator variables, mixed-effects, GADA, and g-GADA. Model evaluation was based on the finite-sample corrected version of Akaike’s Information Criteria and the estimated variance. Model parameterization had more of an influence on the fit than did model formulation, with the indicator variable method providing the best fit, followed by the mixed-effects modelling (9% increase in the variance for the Chapman-Richards and Schumacher formulations over the indicator variable parameterization), g-GADA (optimal approach) (335% increase in the variance), and the GADA/g-GADA (with the GADA parameterization) (346% increase in the variance). Factors related to the application of the model must be considered when selecting the model for use as the best fitting methods have the most barriers in their application in terms of data and software requirements.     

Uncertainty analysis of soil organic carbon stock change in Canadian cropland from 1991 to 2001

National estimates of changes in the amount of soil organic carbon (SOC) in cropland requires an assessment of uncertainty for accounting and reporting under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. Canada has data sets on SOC stocks in croplands, historical changes in SOC levels due to management practices, and historical changes in the area of land devoted to certain soil management practices. We conducted an analysis of uncertainty of the change in SOC levels due to management practices in Canada from 1991 to 2001 using Monte Carlo analysis and a simple model. Probability distribution functions were determined for each of the inputs of the model, enabling us to assess the uncertainty for the output. The storage rate of SOC in cropland soils of Canada for the 10‐year period ranged from 3.2 to 8.3 Mt C yr^?1 at 95% confidence, with a mean of 5.7 Mt C yr^?1. Approximately 67% (about 3.8 Mt C yr^?1) of the increase in SOC storage in Canada occurred in Saskatchewan where the cropland area under no‐till increased from 10% to 35%, and the area of summer‐fallow declined from 43% to 20% during the study period. The large uncertainty in the effect of no‐till on SOC stock changes in the Gray‐Brown Luvisols of Ontario contributed most to the variance in the model output. If trends in agricultural management continue for the next 10‐year census period, the estimated SOC storage would comprise between 7% and 19% of the gap required to achieve the 6% reduction in 1990 greenhouse gas emission levels for Canada under the Kyoto Protocol.     

An inventory‐based analysis of Canada's managed forest carbon dynamics, 1990 to 2008

Canada's forests play an important role in the global carbon (C) cycle because of their large and dynamic C stocks. Detailed monitoring of C exchange between forests and the atmosphere and improved understanding of the processes that affect the net ecosystem exchange of C are needed to improve our understanding of the terrestrial C budget. We estimated the C budget of Canada's 2.3 × 10⁶ km² managed forests from 1990 to 2008 using an empirical modelling approach driven by detailed forestry datasets. We estimated that average net primary production (NPP) during this period was 809 ± 5 Tg C yr^?1 (352 g C m^?2 yr^?1) and net ecosystem production (NEP) was 71 ± 9 Tg C yr^?1 (31 g C m^?2 yr^?1). Harvesting transferred 45 ± 4 Tg C yr^?1 out of the ecosystem and 45 ± 4 Tg C yr^?1 within the ecosystem (from living biomass to dead organic matter pools). Fires released 23 ± 16 Tg C yr^?1 directly to the atmosphere, and fires, insects and other natural disturbances transferred 52 ± 41 Tg C yr^?1 from biomass to dead organic matter pools, from where C will gradually be released through decomposition. Net biome production (NBP) was only 2 ± 20 Tg C yr^?1 (1 g C m^?2 yr^?1); the low C sequestration ratio (NBP/NPP=0.3%) is attributed to the high average age of Canada's managed forests and the impact of natural disturbances. Although net losses of ecosystem C occurred during several years due to large fires and widespread bark beetle outbreak, Canada's managed forests were a sink for atmospheric CO₂ in all years, with an uptake of 50 ± 18 Tg C yr^?1 [net ecosystem exchange (NEE) of CO₂=?22 g C m^?2 yr^?1].     

Global trends and uncertainties in terrestrial denitrification and N2O emissions

Soil nitrogen (N) budgets are used in a global, distributed flow-path model with 0.5° × 0.5° resolution, representing denitrification and N₂O emissions from soils, groundwater and riparian zones for the period 1900–2000 and scenarios for the period 2000–2050 based on the Millennium Ecosystem Assessment. Total agricultural and natural N inputs from N fertilizers, animal manure, biological N₂ fixation and atmospheric N deposition increased from 155 to 345 Tg N yr⁻¹ (Tg = teragram; 1 Tg = 10¹² g) between 1900 and 2000. Depending on the scenario, inputs are estimated to further increase to 408–510 Tg N yr⁻¹ by 2050. In the period 1900–2000, the soil N budget surplus (inputs minus withdrawal by plants) increased from 118 to 202 Tg yr⁻¹, and this may remain stable or further increase to 275 Tg yr⁻¹ by 2050, depending on the scenario. N₂ production from denitrification increased from 52 to 96 Tg yr⁻¹ between 1900 and 2000, and N₂O–N emissions from 10 to 12 Tg N yr⁻¹. The scenarios foresee a further increase to 142 Tg N₂–N and 16 Tg N₂O–N yr⁻¹ by 2050. Our results indicate that riparian buffer zones are an important source of N₂O contributing an estimated 0.9 Tg N₂O–N yr⁻¹ in 2000. Soils are key sites for denitrification and are much more important than groundwater and riparian zones in controlling the N flow to rivers and the oceans.     

Cycling of nitrogen in modern agricultural systems

Summary Agro-ecosystems have developed from mixed- and multiple-cropping systems with relatively closed N cycles to intensively managed monocultures with large N inputs in the form of commercial fertilizers. Cultivation of increasingly larger areas of land has resulted in substantial losses of soil organic matter and N. Also, the move from slash and burn agriculture to intensively ploughed systems has resulted in losses through increased erosion.The use of N fertilizers has increased rapidly toca. 60 Tg N yr^–1 (1980/81), which is equivalent to at least 40% of the N fixed biologically in all terrestrial systems and 36% more than is fixed in all croplands. On a global scale, the major losses of N from agro-ecosystems are estimated to be: harvest, 30 Tg; leaching, 2 Tg; erosion, 2–20 Tg; denitrification 1–44 Tg; and ammonia volatilization, 13–23 Tg. However, the data base is very crude and several estimates may be wrong by as much as one order of magnitude.Additions of N fertilizers have both direct and indirect effects on soil microorganisms. The possible importance of such effects is briefly discussed and a specific example is given on long-term effects on soil microbial biomass and nitrification rates in 27-year-old cropping systems with different N additions: (i) 0 kg N ha^–1 yr^–1, (ii) 80 kg N ha^–1 yr^–1, (iii) farmyard manureca. 80 kg N ha^–1 yr^–1.Few detailed N budgets exist for agro-ecosystems, despite its major importance as a limiting plant nutrient and the large losses of N from such systems. In conclusion, preliminary nitrogen budgets for four cropping systems (barley receiving 0 or 120 kg N ha^–1 yr^–1; meadow fescue ley with 200 kg N ha^–1 yr^–1 and a lucerne ley) are presented, with special attention to N flow through the soil organisms.Keynote address     

半数致死量LD50的百分偏差和渐近方差

毒性试验中的剂量与致死百分率平方根反正弦变换仍呈Ｓ形,且方差趋于同质, 半数致死量ＬＤ_(５０)可表示为 Ｌｏｇｉｓｔｉｃ模型参数的函数·因而,通过参数估计值的偏差和渐 过协方差矩阵,可推导出半数致死量ＬＤ_(５０)的百分偏差,渐近方差和ＬＤ_(５０)的置信区间．通 过 ２７个实例分析后建议,若 ＬＤ_(５０)的百分偏差超过 ５％,则 ＬＤ_(５０)估计值的误差较大     

Likelihood and approximate likelihood analyses of genetic structure in a linear habitat: performance and robustness to model mis-specification

We evaluate the performance of maximum likelihood (ML) analysis of allele frequency data in a linear array of populations. The parameters are a mutation rate and either the dispersal rate in a stepping stone model or a dispersal rate and a scale parameter in a geometric dispersal model. An approximate procedure known as maximum product of approximate conditional (PAC) likelihood is found to perform as well as ML. Mis-specification biases may occur because the importance sampling algorithm is formally defined in term of mutation and migration rates scaled by the total size of the population, and this size may differ widely in the statistical model and in reality. As could be expected, ML generally performs well when the statistical model is correctly specified. Otherwise, mutation rate estimates are much closer to mutation probability scaled by number of demes in the statistical model than scaled by number of demes in reality when mutation probability is high and dispersal is most limited. This mis-specification bias actually has practical benefits. However, opposite results are found in opposite conditions. Migration rate estimates show roughly similar trends, but they may not always be easily interpreted as low-bias estimates of dispersal rate under any scaling. Estimation of the dispersal scale parameter is also affected by mis-specification of the number of demes, and the different biases compensate each other in such a way that good estimation of the so-called neighborhood size (or more precisely the product of population density and mean-squared parent-offspring dispersal distance) is achieved. Results congruent with these findings are found in an application to a damselfly data set.     

Terrestrial nitrogen–carbon cycle interactions at the global scale

Interactions between the terrestrial nitrogen (N) and carbon (C) cycles shape the response of ecosystems to global change. However, the global distribution of nitrogen availability and its importance in global biogeochemistry and biogeochemical interactions with the climate system remain uncertain. Based on projections of a terrestrial biosphere model scaling ecological understanding of nitrogen–carbon cycle interactions to global scales, anthropogenic nitrogen additions since 1860 are estimated to have enriched the terrestrial biosphere by 1.3 Pg N, supporting the sequestration of 11.2 Pg C. Over the same time period, CO₂ fertilization has increased terrestrial carbon storage by 134.0 Pg C, increasing the terrestrial nitrogen stock by 1.2 Pg N. In 2001–2010, terrestrial ecosystems sequestered an estimated total of 27 Tg N yr⁻¹ (1.9 Pg C yr⁻¹), of which 10 Tg N yr⁻¹ (0.2 Pg C yr⁻¹) are due to anthropogenic nitrogen deposition. Nitrogen availability already limits terrestrial carbon sequestration in the boreal and temperate zone, and will constrain future carbon sequestration in response to CO₂ fertilization (regionally by up to 70% compared with an estimate without considering nitrogen–carbon interactions). This reduced terrestrial carbon uptake will probably dominate the role of the terrestrial nitrogen cycle in the climate system, as it accelerates the accumulation of anthropogenic CO₂ in the atmosphere. However, increases of N₂O emissions owing to anthropogenic nitrogen and climate change (at a rate of approx. 0.5 Tg N yr⁻¹ per 1°C degree climate warming) will add an important long-term climate forcing.     

Historical and projected carbon balance of mature black spruce ecosystems across North America: the role of carbon–nitrogen interactions

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO₂ in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C–N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R ²= 0.77, 0.88 for GPP and RESP; uncoupled: R ² = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R ² = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and simulated NEP (R ² = 0.36, 0.20 for coupled and uncoupled simulations, respectively) was similar to the correlations at the northern site. To evaluate the role of N dynamics in C balance of black spruce ecosystems across North America, we simulated historical and projected C dynamics from 1900 to 2100 with a global-based climatology at 0.5° resolution (latitude × longitude) with both the coupled and uncoupled parameterizations of TEM. From analyses at the northern site, several consistent patterns emerge. There was greater inter-annual variability in net primary production (NPP) simulated by the uncoupled parameterization as compared to the coupled parameterization, which led to substantial differences in inter-annual variability in NEP between the parameterizations. The divergence between NPP and heterotrophic respiration was greater in the uncoupled simulation, resulting in more C sequestration during the projected period. These responses were the result of fundamentally different responses of the coupled and uncoupled parameterizations to changes in CO₂ and climate.