Interpreting spatial heterogeneity of crop yield with a process model and remote sensing

A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter—maximum catalytic capacity of Rubisco (V_cmax) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R² being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 μmol C m⁻² s⁻¹ and 3000 kg ha⁻¹, respectively, which are much lower than that in non-salinized region, 84.5 μmol C m⁻² s⁻¹ and 5700 kg ha⁻¹. The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha⁻¹, which is significantly larger than that of rainfed, 1500-3000 kg ha⁻¹. According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model.     

Modeling carbon sequestration under zero-tillage at the regional scale. II. The influence of crop rotation and soil type

For policy decisions with respect to CO₂-mitigation measures in the agricultural sector, national and regional estimations of the efficiency of such measures are required. The conversion of ploughed cropland to zero-tillage is discussed as an option to reduce CO₂ emissions and promises at the same time effective soil and water conservation. Based on the upscaling of simulation results with the soil and land resources information system SLISYS-BW, estimations of CO₂-mitigation rates in relation to crop rotations and soil type have been made for the state of Baden-Württemberg (Germany). The results indicate considerable differences in the CO₂-mitigation rates between crop rotations ranging from 0.48 to 0.03 Mg C ha⁻¹ a⁻¹ for winter cereals–spring cereals–rape rotations and winter cereals–spring cereals–corn silage rotations, respectively. The efficiency of the crop rotations is strongly related to the total carbon input and in particular the amount of crop residues. Among the considered soil types, highest CO₂-mitigation rates are associated with Cumulic Anthrosols (0.62 Mg C ha⁻¹ a⁻¹) and the lowest with Gleysols (−0.01 Mg C ha⁻¹ a⁻¹). An agricultural extensification scenario with conventional plowing but conversion of the presently applied intensive crop rotations to a clover–clover–winter cereals rotation indicated a CO₂-mitigation potential of 466 Gg C a⁻¹. However, the present high market prices for cereals and increasing demand for energy production from biomass encourages an intensification of the agricultural production and an excessive removal of biomass which in future will seriously reduce the potential for carbon sequestration on cropland.     

The sensitivity of carbon sequestration to harvesting and climate conditions in a temperate cypress forest: Observations and modeling

The role of disturbance and climate factors in determining the forest carbon balance was investigated at a Japanese cypress forest in central Japan with eddy flux measurements, tree-ring analyses, and a terrestrial biosphere model. The forest was established as a plantation after intermittent harvesting and replanting between 1959 and 1977, and acted as a strong carbon sink of approximately 500 g C m⁻² year⁻¹ for the measurement years between 2001 and 2007. A terrestrial biosphere model, BIOME-BGC, was validated using the eddy flux data at daily to interannual timescales, and the tree-ring width data at interannual to decadal timescales. According to the model simulation, during the observation period 270 ± 55 g C m⁻² year⁻¹ was additionally sequestered due to the indirect effects of the harvesting and planting, whereas the increase of CO₂ concentration and the change in climate increased the sink of 110 ± 40 and 30 ± 80 g C m⁻² year⁻¹, respectively. The model simulation shows that the forest is now recovering from harvesting, and that harvesting is a more important determinant of the current carbon sink than either interannual climate anomalies or increased atmospheric CO₂ concentration. We found that harvesting with long rotation length could be effective management activity in order to increase carbon sequestration, if the harvested timber is converted into products with long lifecycles.     

Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations

Global emissions trading allows for agricultural measures to be accounted for the carbon sequestration in soils. The Environmental Policy Integrated Climate (EPIC) model was tested for central European site conditions by means of agricultural extensification scenarios. Results of soil and management analyses of different management systems (cultivation with mouldboard plough, reduced tillage, and grassland/fallow establishment) on 13 representative sites in the German State Baden-Württemberg were used to calibrate the EPIC model. Calibration results were compared to those of the Intergovernmental Panel on Climate Change (IPCC) prognosis tool. The first calibration step included adjustments in (a) N depositions, (b) N₂-fixation by bacteria during fallow, and (c) nutrient content of organic fertilisers according to regional values. The mixing efficiency of implements used for reduced tillage and four crop parameters were adapted to site conditions as a second step of the iterative calibration process, which should optimise the agreement between measured and simulated humus changes. Thus, general rules were obtained for the calibration of EPIC for different criteria and regions. EPIC simulated an average increase of +0.341 Mg humus-C ha⁻¹ a⁻¹ for on average 11.3 years of reduced tillage compared to land cultivated with mouldboard plough during the same time scale. Field measurements revealed an average increase of +0.343 Mg C ha⁻¹ a⁻¹ and the IPCC prognosis tool +0.345 Mg C ha⁻¹ a⁻¹. EPIC simulated an average increase of +1.253 Mg C ha⁻¹ a⁻¹ for on average 10.6 years of grassland/fallow establishment compared to an average increase of +1.342 Mg humus-C ha⁻¹ a⁻¹ measured by field measurements and +1.254 Mg C ha⁻¹ a⁻¹ according to the IPCC prognosis tool. The comparison of simulated and measured humus C stocks was r² ≥ 0.825 for all treatments. However, on some sites deviations between simulated and measured results were considerable. The result for the simulation of yields was similar. In 49% of the cases the simulated yields differed from the surveyed ones by more than 20%. Some explanations could be found by qualitative cause analyses. Yet, for quantitative analyses the available information from farmers was not sufficient. Altogether EPIC is able to represent the expected changes by reduced tillage or grassland/fallow establishment acceptably under central European site conditions of south-western Germany.     

Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia

Turnover rates of soil carbon for 20 soil types typical for a 3.7 million km² area of European Russia were estimated based on ¹⁴C data. The rates are corrected for bomb radiocarbon which strongly affects the topsoil ¹⁴C balance. The approach is applied for carbon stored in the organic and mineral layers of the upper 1 m of the soil profile. The turnover rates of carbon in the upper 20 cm are relatively high for forest soils (0.16–0.78% year⁻¹), intermediate for tundra soils (0.25% year⁻¹), and low for grassland soils (0.02–0.08% year⁻¹) with the exception of southern Chernozems (0.32% year⁻¹). In the soil layer of 20–100 cm depth, the turnover rates were much lower for all soil types (0.01–0.06% year⁻¹) except for peat bog soils of the southern taiga (0.14% year⁻¹). Combined with a map of soil type distribution and a dataset of several hundred soil carbon profiles, the method provides annual fluxes for the slowest components of soil carbon assuming that the latter is in equilibrium with climate and vegetation cover. The estimated carbon flux from the soil is highest for forest soils (12–147 gC/(m² year)), intermediate for tundra soils (33 gC/(m² year)), and lowest for grassland soils (1–26 gC/(m² year)). The approach does not distinguish active and recalcitrant carbon fractions and this explains the low turnover rates in the top layer. Since changes in soil types will follow changes in climate and land cover, we suggest that pedogenesis is an important factor influencing the future dynamics of soil carbon fluxes. Up to now, both the effect of soil type changes and the clear evidence from ¹⁴C measurements that most soil organic carbon has a millennial time scale, are basically neglected in the global carbon cycle models used for projections of atmospheric CO₂ in 21st century and beyond.     

Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951-2000

Land use change, natural disturbance, and climate change directly alter ecosystem productivity and carbon stock level. The estimation of ecosystem carbon dynamics depends on the quality of land cover change data and the effectiveness of the ecosystem models that represent the vegetation growth processes and disturbance effects. We used the Integrated Biosphere Simulator (IBIS) and a set of 30- to 60-m resolution fire and land cover change data to examine the carbon changes of California's forests, shrublands, and grasslands. Simulation results indicate that during 1951-2000, the net primary productivity (NPP) increased by 7%, from 72.2 to 77.1 Tg C yr⁻¹ (1 teragram = 10¹² g), mainly due to CO₂ fertilization, since the climate hardly changed during this period. Similarly, heterotrophic respiration increased by 5%, from 69.4 to 73.1 Tg C yr⁻¹, mainly due to increased forest soil carbon and temperature. Net ecosystem production (NEP) was highly variable in the 50-year period but on average equalled 3.0 Tg C yr⁻¹ (total of 149 Tg C). As with NEP, the net biome production (NBP) was also highly variable but averaged −0.55 Tg C yr⁻¹ (total of -27.3 Tg C) because NBP in the 1980s was very low (-5.34 Tg C yr⁻¹). During the study period, a total of 126 Tg carbon were removed by logging and land use change, and 50 Tg carbon were directly removed by wildland fires. For carbon pools, the estimated total living upper canopy (tree) biomass decreased from 928 to 834 Tg C, and the understory (including shrub and grass) biomass increased from 59 to 63 Tg C. Soil carbon and dead biomass carbon increased from 1136 to 1197 Tg C.Our analyses suggest that both natural and human processes have significant influence on the carbon change in California. During 1951-2000, climate interannual variability was the key driving force for the large interannual changes of ecosystem carbon source and sink at the state level, while logging and fire were the dominant driving forces for carbon balances in several specific ecoregions. From a long-term perspective, CO₂ fertilization plays a key role in maintaining higher NPP. However, our study shows that the increase in C sequestration by CO₂ fertilization is largely offset by logging/land use change and wildland fires.     

Modelling the impact of thermal adaptation of soil microorganisms and crop system on the dynamics of organic matter in a tropical soil under a climate change scenario

No consensus currently exists about how climate change should affect the status of soil organic matter (SOM) in the tropics. In this study, we analyse the impact of climate change on the underlying mechanisms controlling SOM dynamics in a ferralsol under two contrasting tropical crops: maize (C4 plant) and banana (C3 plant). We model the effect of microbial thermal adaptation on carbon (C) mineralisation at the crop system scale and introduce it in the model STICS, which was previously calibrated for the soil-crop systems tested in this study. Microbial thermal adaptation modelling is based on a reported theory for thermal acclimation of plant and soil respiration. The climate is simulated from 1950 to 2099 for the tropical humid conditions of Guadeloupe (French Antilles), using the ARPEGE model and the IPCC emission scenario A1B. The model predicts increases of 3.4 °C for air temperature and 1100 mm yr⁻¹ for rainfall as a response to an increase of 375 ppm for atmospheric carbon dioxide concentration in the 2090-2099 decade compared with the 1950-1959 decade. The results of the STICS model indicate that the crop affects the response of SOM to climate change by controlling the change in several variables involved in C dynamics: C input, soil temperature and soil moisture. SOM content varies little until 2020, and then it decreases faster for maize than for banana. The decrease is weakened under the hypothesis of thermal adaptation, and this effect is greater for maize (−180 kg C ha⁻¹ yr⁻¹ without adaptation and −140 kg C ha⁻¹ yr⁻¹ with adaptation) than for banana (−60 kg C ha⁻¹ yr⁻¹ and −40 kg C ha⁻¹ yr⁻¹, respectively). The greater SOM loss in maize is mainly due to the negative effect of warming on maize growth decreasing C input from residues. Climate change has a small effect on banana growth, and SOM loss is linked to its effect on C mineralisation. For both crops, annual C mineralisation increases until 2040, and then it decreases continuously. Thermal adaptation reduces the initial increase in mineralisation, but its effect is lower on the final decrease, which is mainly controlled by substrate limitation. No stabilisation in SOM status is attained at the end of the analysed period because C mineralisation is always greater than C input. Model predictions indicate that microbial thermal adaptation modifies, but does not fundamentally change the temporal pattern of SOM dynamics. The vegetation type (C3 or C4) plays a major role in SOM dynamics in this tropical soil because of the different impact of climate change on crop growth and then on C inputs.     

Local calibration of coliforms parameters of water quality problem at Igapó I Lake, Londrina, Paraná, Brazil

This article presents results concerning the local calibration of the transport parameters (longitudinal and transversal diffusions and decay coefficient) for a two-dimensional problem of water quality at Igapó I Lake, located in Londrina, Paraná, Brazil, using fecal coliforms as an indicator of water quality. The simulation of fecal coliforms concentrations all over the water body is conducted by means of a structured discretization of the geometry of Igapó I Lake, together with the finite difference and finite element methods. By using the velocity field, modeled by the Navier-Stokes and Poisson equations, the flow of fecal coliforms is described by means of a transport model, which considers advective and diffusive processes, as well as a process of fecal coliforms decay. In the checkpoint, the longitudinal and transversal diffusion coefficients and the coliforms decay coefficient that best fitted the value of the fecal coliforms concentration were D_x = D_y = 0.001 m²/h and k = 0.5 d⁻¹ = 0.02083 h⁻¹. A qualitative and quantitative analysis of the numerical simulations conducted in function of the diffusion coefficients and of the coliforms decay parameter provided a better understanding of the local water quality at Igapó I Lake.     

Ecological role of stomatopods (mantis shrimps) and potential impacts of trawling in a marine ecosystem of the southeast coast of India

Ecosystems are balanced by nature and each component in the system has a role in the sustenance of other components. A change in one component would invariably have an effect on others. Stomatopods (mantis shrimps) are common and ecologically important predatory crustaceans in tropical marine waters. The ecological role of mantis shrimps and potential impacts of trawling in a marine ecosystem were estimated using Ecopath with Ecosim (EwE) Version 5.0 software, by constructing a mass balanced Ecopath model of Parangipettai (Porto Novo) ecosystem. Based on fisheries information from the region, 17 ecological groups were defined including stomatopods. Both primary and secondary data on biomass, P/B, Q/B and diet composition were used as basic inputs. The mass balanced model gave a total system throughput of 14,756 t km⁻² year⁻¹. The gross efficiency of 0.000942 indicated higher contribution of lower food chain groups in the fishery though the mean trophic level was 3.08. The immature and developing stage of the ecosystem was indicated by the ratio of total primary production and total respiration (1.832) and the net system production (2643.30 t km⁻² year⁻¹). Key indices (flow to detritus, net efficiency and omnivory index), split mortality rates and mixed trophic impact of different ecological groups were obtained from the model. A flow diagram was constructed to illustrate the trophic interactions, which explained the biomass flows in the ecosystem with reference to stomatopods. Two temporal simulations were made, with 10 year durations in the mass balanced Ecopath model by using ecosim routine incorporated in EwE software. The effect of decrease in biomass of stomatopods in the ecosystem was well defined, in the first run with increase in stomatopod fishing mortality, and the group showed a high positive impact on benthopelagic fish biomass increase (129%). The simulation with increase in trawling efforts resulted in the biomass decline of different ecological groups as elasmobranchs to 1%, stomatopods to 2%, crabs and lobsters to 36%, cephalopods to 63%, mackerel to 78%, and shrimps to 89%. Present study warns stomatopod discards and further increase in trawling efforts in the region and it explained the need for ecosystem based fisheries management practices for the sustainability of marine fisheries.     

Spatially distributed modeling of the long-term carbon balance of a boreal landscape

Spatially and temporally distributed information on the sizes of biomass carbon (C) pools (BCPs) and soil C pools (SCPs) is vital for improving our understanding of biosphere-atmosphere C fluxes. Because the sizes of C pools result from the integrated effects of primary production, age-effects, changes in climate, atmospheric CO₂ concentration, N deposition, and disturbances, a modeling scheme that interactively considers these processes is important. We used the InTEC model, driven by various spatio-temporal datasets to simulate the long-term C-balance in a boreal landscape in eastern Canada. Our results suggested that in this boreal landscape, mature coniferous stands had stabilized their productivity and fluctuated as a weak C-sink or C-source depending on the interannual variations in hydrometeorological factors. Disturbed deciduous stands were larger C-sinks (NEP₂₀₀₄ = 150 gC m⁻² yr⁻¹) than undisturbed coniferous stands (e.g. NEP₂₀₀₄ = 8 gC m⁻² yr⁻¹). Wetlands had lower NPP but showed temporally consistent C accumulation patterns. The simulated spatio-temporal patterns of BCPs and SCPs were unique and reflected the integrated effects of climate, plant growth and atmospheric chemistry besides the inherent properties of the C pool themselves. The simulated BCPs and SCPs generally compared well with the biometric estimates (BCPs: r = 0.86, SCPs: r = 0.84). The largest BCP biases were found in recently disturbed stands and the largest SCP biases were seen in locations where moss necro-masses were abundant. Reconstructing C pools and C fluxes in the ecosystem in such a spatio-temporal manner could help reduce the uncertainties in our understanding of terrestrial C-cycle.     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.     

Dynamics of a chemostat with three competitive hydrogen oxidizing denitrifying microbial populations and their efficiency for denitrification

In this work, competition for two nitrogen resources (nitrate-, nitrite-nitrogen) between three hydrogen oxidizing denitrifying populations (Acidovorax sp. strain Ic3 (X₁), Paracoccus sp. strain Ic1 (X₂), and Acinetobacter sp. strain Ic2 (X₃)) was examined. The dynamics of three systems of microbial populations (system I: X₁ − X₃, system II: X₂ − X₃, and system III: X₁ − X₂ − X₃), grown in a chemostat, was studied using bifurcation analysis. The chemostat is the most common type of biological reactor used for the study of microbial growth under controlled conditions. The effect of the operating parameters (i.e., dilution rate and feed nitrate nitrogen concentration) on the long-term behavior of the systems showed that X₃ was the predominant population for a wide range of combinations of dilution rate and feed nitrate nitrogen concentration. Also, coexistence of two populations (X₂X₃, X₁X₃) was observed. The results of the bifurcation analysis were also used to determine the denitrification rate and the nitrite nitrogen accumulation for each of the three systems as a function of the dilution rate (up to 0.17 h⁻¹) and the feed nitrate nitrogen concentration (up to 300 mg/L). The highest denitrification rate was achieved by system I (28 mg/Lh). A comparison between the three systems showed that the nitrite nitrogen concentration in system I was less than the one in system III, while the two systems gave similar denitrification rates. The second system had the greatest accumulation of nitrites with the lowest denitrification rate.     

Estimation of annual potential evapotranspiration at regional scale based on the effect of moisture on soil respiration

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.     

Residual levels and health risk of polycyclic aromatic hydrocarbons in freshwater fishes from Lake Small Bai-Yang-Dian, Northern China

The residual levels of polycyclic aromatic hydrocarbons (PAHs) in the liver, brain, gill and muscle tissues of four common edible freshwater fish species including crucian carp, snakehead fish, grass carp and silver carp collected from Lake Small Bai-Yang-Dian in northern China were measured by GC-MS. The distribution and composition pattern of PAHs in the fish tissues, and the effects of lipid contents in fish tissues and the octanol-water partition coefficient (Kow) of PAHs congeners on them were analyzed. The human health risk of PAHs though fish consumptions was estimated. The following results were obtained: (1) The average residual levels of total PAHs (PAH₁₆) on wet weight base in the different tissues of each fish species ranged from 4.764 to 144.254 ng/g ww. The differences in the average residual levels on wet weight base for PAH₁₆ within four fish species were not statistically significant (P > 0.05); however, these within four fish tissues were statistically significant (P < 0.01). (2) There were very similar distribution patterns of PAH congeners among both the fish tissues and the fish species, as indicated by statistically significant positive interrelationships (R = 0.58-0.97, P < 0.01 or P < 0.05). Low molecular weight (LMW) PAHs predominated the distribution in the fish tissues, accounting for 89.97% of total PAHs. Phe was the most dominant component, according for 37.79% of total PAHs, followed by Ant (18.59%), Flo (12.59%), Nap (10.79%), Fla (9.82%) and Pyr (6.43%). (3) The PAHs residues and distribution in the fish tissues are dependent on both the Kow of PAH congeners and the lipid contents in the fish tissues. There was a significant positive relationship (R = 0.7116, P < 0.0001) between lipid contents and PAHs residual levels. The statistically significant negative relationships (P < 0.05) were found between LogKow and log-transformed PAHs contents on wet weight base for all fish tissues except for the muscle tissue of snakehead fish, the brain and liver tissues of crucian carp. (4) The risk levels of total PAHs were lower than 10⁻⁵ for the muscle tissues of four studied fish species and for the brain tissues of grass carp and snakehead fish; while these were higher than 10⁻⁵ for the brain tissues of crucian carp and silver carp. The risk levels of total PAHs in the liver tissues of four studied fish species except for snakehead fish exceeded 10⁻⁵ for 2-4.5 times. However, the potency equivalent concentration (PEC) of total PAHs in four studied fish tissues were still lower than the maximum permissible BaP limits for crops and baked meat and for plants in the national criterions. The distributions of PAH congeners in fish were well simulated by a level III fugacity model, especially for low molecule weight PAHs.     

Estimating the potential impact of vegetation on the water cycle requires accurate soil water parameter estimation

It is well known that vegetation dynamics at the catchment scale depends on the prevailing weather and soil moisture conditions. Soil moisture, however, is not equally distributed in space due to differences in topography, weather patterns, soil properties and the type and amount of vegetation cover. To elucidate the complex interaction between vegetation and soil moisture, the dynamic vegetation model LPJ-GUESS (Smith et al., 2001), which provides estimations of vegetation dynamics, but does not consider lateral water fluxes was coupled with the hydrological TOPMODEL (cf. Beven, 2001) in order to be able to evaluate the importance of these lateral fluxes. The new model LG-TM was calibrated and validated in two climatically different mountain catchments. The estimations of runoff were good, when monthly and weekly time scales were considered, although the low flow periods at winter time were somewhat underestimated. The uncertainty in the climate induced change vegetation carbon storage caused by the uncertainty in soil parameters was up to 3-5 kg C m⁻² (depending on elevation and catchment), compared to the total change in vegetation carbon storage of 5-9 kg C m⁻². Therefore accurate estimates of the parameters influencing the water holding capacity of the soil, for example depth and porosity, are necessary when estimating future changes in vegetation carbon storage. Similarly, changes in plant transpiration due to climatic changes could be almost double as high (88 mm m⁻²) in the not calibrated model compared to the new model version (ca 50 mm m⁻² transpiration change). The uncertainties in these soil properties were found to be more important than the lateral water exchange between grid cells, even in steep topography at least for the temporal and spatial resolution used here.     

Dealing with microtopography of an ombrotrophic bog for simulating ecosystem-level CO2 exchanges

Peatlands contain approximately 25% of the global soil carbon (C), despite covering only 3% of the earth's land surface. In order to evaluate the role of peatlands in global C cycling, models of ecosystem biogeochemistry are required, but peatland ecosystems present a number of unique challenges, particularly how to deal with the large variability that occurs at scales of one to several metres. In models, spatial variability is considered either explicitly for each individual unit and the outputs averaged, referred to as flux upscaling, or implicitly by weighting model parameters by the fractional occurrence of the individual units, referred to as parameter upscaling. The advantage of parameter upscaling is that it is much more computationally efficient: a requirement for hemispheric scale simulations. In this study we determined the differences between modelling a raised bog peatland with hummock-hollow microtopography using flux and parameter upscaling. We used the McGill Wetland Model (MWM), a process-based ecosystem C model for peatlands, configured for hummocks and hollows separately and then a weighted mixture of both. The simulated output based on flux and parameter upscaling was compared with eddy-covariance tower measurements. We found that net ecosystem production (NEP) for hollows was much larger than that for hummocks because total ecosystem respiration (TER) for hummocks was greater while gross primary production (GPP) did not differ significantly between the two topographic features. However, despite differences in components of NEP between hummocks and hollows, there was no statistically significant difference between the NEP based on flux and parameter upscaling using the MWM. Both flux and parameter upscaling show equivalent capability to capture the magnitude, direction, seasonality and inter-annual variability. The root-mean-square-errors (RMSE) are 0.66, 0.45, and 0.49 g C m⁻² day⁻¹, respectively for GPP, TER and NEP based on the flux upscaling, while 0.67, 0.44, and 0.48 g C m⁻² day⁻¹, respectively based on the parameter upscaling. The degree of agreement (d*) is 0.96, 0.97, and 0.88, respectively for GPP, TER and NEP based on the flux upscaling, while 0.96, 0.97, and 0.89, respectively based on the parameter upscaling. This result suggests that differences in processes caused by peatland microtopography scale linearly, which means an ecosystem-level model set-up (i.e. parameter upscaling scheme), is sufficient to simulate the C cycling.     

Seafloor ecosystem functioning: the importance of organic matter priming

Organic matter (OM) remineralization may be considered a key function of the benthic compartment of marine ecosystems and in this study we investigated if the input of labile organic carbon alters mineralization of indigenous sediment OM (OM priming). Using ¹³C-enriched diatoms as labile tracer carbon, we examined shallow-water sediments (surface and subsurface layers) containing organic carbon of different reactivity under oxic versus anoxic conditions. The background OM decomposition rates of the sediment used ranged from 0.08 to 0.44 μmol C ml_ws⁻¹ day⁻¹. Algal OM additions induced enhanced levels of background remineralization (priming) up to 31% and these measured excess fluxes were similar to mineralization of the added highly degradable tracer algal carbon. This suggests that OM priming may be important in marine sediments.     

Sulfide and thiosulfate-oxidizing bacteria in anoxic marine basins

The occurrence of sulfide and thiosulfate-oxidizing bacteria was examined in waters and sediments of the Black Sea and the Caraco Trench. Isolates obtained by enrichment-culture techniques exhibited facultative autotrophic-growth characteristics and oxidized thiosulfate or sulfide. Acid was not formed during growth in mineral medium. Most of the isolates were facultatively anaerobic, using nitrate as the terminal hydrogen acceptor. Strictly aerobic bacteria were found only in oxygenated waters. Comparison of the metabolic capabilities of the isolates during growth in sulfide and thiosulfate media with chemical parameters measured in the Black Sea and Cariaco Trench waters suggests that the biological oxidation of thiosulfate is the rate-limiting step in the oxidative turnover of sulfur compounds in the basins. Evidence for the oxidation of sulfide in the anoxic waters is presented, and possible explanations for the occurrence of this process in the absence of suitable electron acceptors (O₂. NO₃) are discussed. A maximum dark assimilation of carbon dioxide was located just below the oxygen-sulfide interface in the Cariaco Trench. Problems of interpreting these data are considered.Contribution No. 2958 of the Woods Hole Occanographic Institution. Supported by the National Science Foundation Grants GA 29665 and GA 33405.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.