Modelling above- and below-ground mass loss and N dynamics in wooden dowels (LIDET) placed across North and Central America biomes at the decadal time scale

This article focuses on modelling above and below-ground mass loss and nitrogen (N) dynamics based on the wooden dowels (Gonystylus bancanus [Miq.] Kurz) of the decadal Long-term Intersite Decomposition Experiment (LIDET) data. These dowels were placed at 27 locations across North and Central America, involving tropical, temperate and boreal forests, grasslands, wetlands and the tundra. The dowel, inserted vertically into the soil with one half remaining exposed to the air, revealed fast mass and N losses under warm to humid conditions, and slow losses under wet as well as cold to dry conditions. The model formulation, referred to as the Wood Decomposition Model, or WDM, related these losses to (i) mean annual precipitation, mean monthly January and July air temperatures, and (ii) mean annual actual evapotranspiration (AET) at each location. The resulting calibrations conformed well to the time-in-field averages for mass remaining by location: R² = 0.83 and 0.90 for the lower and upper parts, respectively. These values dropped, respectively, to 0.41 and 0.55 for the N concentrations, and to 0.28 and 0.43 for N remaining. These reductions likely refer to error propagation and to as yet unresolved variations in N transference into and out of the wood specific to each individual dowel location. Recalibrating the model parameters by ecosystem type reduced the R² values for actual versus best-fitted mass loss by about 0.15. Doing the same without location- or ecosystem-specific adjustments reduced the R² values further, by about 0.3.     

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning

In order to simulate forest growth response to pre-commercial thinning (PCT), TRIPLEX1.0 - a process-based model designed to predict forest growth as well as carbon (C) and nitrogen (N) dynamics - was modified and improved to also simulate managed forest ecosystem thinning practices. A three-parameter Weibull distribution model was integrated to simulate thinning treatments within the newly developed TRIPLEX-Management model. The thinning intensity component within the model allows users to simulate thinning treatments by applying basal area, stand density and volume to quantify thinning intensity. Natural mortality decreased following thinning due to an increase in growing space for residual stems. Predicted litterfall pools also increased after thinning events took place. The TRIPLEX-Management model was tested against published observational data for Jack Pine (Pinus banksiana Lamb.) stands subjected to PCT in Northwestern Ontario, Canada. The coefficients of determination (R²) between the predicted and observed variables including stand density, mean DBH (diameter at breast height), the quadratic mean DBH, total volume and merchantable volume as well as belowground, aboveground, and total biomass ranged from 0.50 to 0.88 (n = 20, P < 0.001) with the exception of mean tree height (R² = 0.25, n = 20, P < 0.05). Overall, the Willmott index of agreement between predicted and observed variables ranged from 0.97 to 1.00. Results show that the TRIPLEX-Management model is generally capable of simulating growth response to PCT for Jack Pine stands.     

The effect of estimated PAR uncertainties on the physiological processes of biosphere models

Photosynthetically active radiation (PAR) energy reaching on the vegetated surface is a key determinant of plant physiological processes. Most of biosphere or crop models use the ratio of PAR to incoming solar radiation (R_s), PAR/R_s, to convert R_s into PAR in order to reduce weather data-input requirements. Several existing models simply specify a constant ratio, PAR/R_s = 0.5. However, some field experiments have reported that the ratio PAR/R_s may not be constant. Previous empirical equations of PAR/R_s were derived based on the data of monthly or daily timescales collected from only a few measurement sites, hence they may not be appropriate to be used in current global biosphere models usually with hourly simulation time steps. Here, we represent the exponential correlation between PAR/R_s and sky clearness index (0-1) using hourly data from 54 Ameriflux measurement sites. It is found that PAR/R_s increases up to 0.6 in cloudy conditions when the clearness index (CI) is below ∼0.2, whereas it is nearly constant at ∼0.42 when CI is above 0.2. When the identified empirical equation is used in the model simulation, it results in −4 to 2% difference in the stomatal conductance compared to that using the constant ratio PAR/R_s = 0.5.     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

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.     

Carbon, nitrogen, oxygen and sulfide budgets in the Black Sea: A biogeochemical model of the whole water column coupling the oxic and anoxic parts

Carbon, nitrogen, oxygen and sulfide budgets are derived for the Black Sea water column from a coupled physical-biogeochemical model. The model is applied in the deep part of the sea and simulates processes over the whole water column including the anoxic layer that extends from ?115 m to the bottom (?2000 m). The biogeochemical model involves a refined representation of the Black Sea foodweb from bacteria to gelatinous carnivores. It includes notably a series of biogeochemical processes typical for oxygen deficient conditions with, for instance, bacterial respiration using different types of oxidants (i.e denitrification, sulfate reduction), the lower efficiency of detritus degradation, the ANAMMOX (ANaerobic AMMonium OXidation) process and the occurrence of particular redox reactions. The model has been calibrated and validated against all available data gathered in the Black Sea TU Ocean Base and this exercise is described in Gregoire et al. (2008). In the present paper, we focus on the biogeochemical flows produced by the model and we compare model estimations with the measurements performed during the R.V. KNORR expedition conducted in the Black Sea from April to July 1988 (Murray and the Black Sea Knorr Expedition, 1991). Model estimations of hydrogen sulfide oxidation, metal sulfide precipitation, hydrogen sulfide formation in the sediments and water column, export flux to the anoxic layer and to the sediments, denitrification, primary and bacterial production are in the range of field observations.With a simulated Gross Primary Production (GPP) of 7.9 mol C m⁻² year⁻¹ and a Community Respiration (CR) of 6.3 mol C m⁻² year⁻¹, the system is net autotrophic with a Net Community Production (NCP) of 1.6 mol C m⁻² year⁻¹. This NCP corresponds to 20% of the GPP and is exported to the anoxic layer. In order to model Particulate Organic Matter (POM) fluxes to the bottom and hydrogen sulfide profiles in agreement with in situ observations, we have to consider that the degradation of POM in anoxic conditions is less efficient that in oxygenated waters as it has often been observed (see discussion in Hedges et al., 1999). The vertical POM profile produced by the model can be fitted to the classic power function describing the oceanic carbon rate (C_R=Z^−α) using an attenuation coefficient α of 0.36 which is the value proposed for another anoxic environment (i.e. the Mexico Margin) by Devol and Hartnett (2001). Due to the lower efficiency of detritus degradation in anoxic conditions and to the aggregation of particles that enhanced the sinking, an important part of the export to the anoxic layer (i.e. 33%, 0.52 mol C m⁻² year⁻¹) escapes remineralization in the water column and reaches the sediments. Therefore, sediments are active sites of sulfide production contributing to 26% of the total sulfide production.In the upper layer, the oxygen dynamics is mainly governed by photosynthesis and respiration processes as well as by air-sea exchanges. ?71% of the oxygen produced by phytoplankton (photosynthesis+nitrate reduction) is lost through respiration, ?21% by outgasing to the atmosphere, ?5% through nitrification and only ?2% in the oxidation of reduced components (e.g. Mn²⁺, Fe²⁺, H₂S).The model estimates the amount of nitrogen lost through denitrification at 307 mmol N m⁻² year⁻¹ that can be partitioned into a loss of ?55% through the use of nitrate for the oxidation of detritus in low oxygen conditions, ?40% in the ANAMMOX process and the remaining ?5% in the oxidation of reduced substances by nitrate.In agreement with data analysis performed on long time series collected since the 1960s (Konovalov and Murray, 2001), the sulfide and nitrogen budgets established for the anoxic layer are not balanced in response to the enhanced particle fluxes induced by eutrophication: the NH₄ and H₂S concentrations increase.     

Modelling the impact of defoliation and leaf damage on forest plantation function and production

After presenting a short review of process-based model requirements to capture the plant dynamic response to defoliation, this paper describes the development and testing of a model of crown damage and defoliation for Eucalyptus. A model that calculates light interception and photosynthetic production for canopies that vary spatially and temporally in leaf area and photosynthetic properties is linked to the forest growth model CABALA. The process of photosynthetic up-regulation following defoliation is modelled with a simple conditional switch that triggers up-regulation when foliar damage or removal causes the ratio of functional leaf area to living tissue in the tree to change.We show that the model predicts satisfactorily when validated with trees of Eucalyptus nitens and Eucalyptus globulus from a range of sites of different ages, subject to different types of stress and different types of defoliation events (R² = 0.96 across a range of sites). However, the complexity of particular situations can cause the model to fail (e.g. very heavy defoliation events where branch death occurs).It is concluded that while the model will not cope with all situations, an appropriate level of generality has been captured to represent many of the physiological processes and feedbacks that occur following defoliation or leaf damage. This makes the model useful for guiding management interventions following pest attack and allows the development of scenarios including climate change impact analyses and decision-making on the merits of post-defoliation fertilisation to expedite recovery.     

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.     

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.     

Formulation and testing of a novel river nitrification model

The nitrification process in many river water quality models has been approximated by a simple first order dependency on the water column ammonia concentration, while the benthic contribution has routinely been neglected. In this study a mathematical framework was developed for sediment bed nitrification based on mass transfer theory and Monod bacterial growth kinetics. The model describes ammonia transport across the boundary layer and consumption within the biofilm to quantify the overall nitrification flux. Model results suggest that nitrification is usually controlled by the boundary layer thickness, and we estimated a nitrification velocity range between 0.14 and 0.97 m d⁻¹, assuming typical boundary thicknesses of 0.1–1.0 mm. These ranges compared favorably with reported literature values, including our own measurements. The model was applied to several river systems of different depths where nitrification rates and river depths were available. Assuming that nitrification is exclusively a benthic process, the average velocity of all the rivers evaluated was 0.85 m d⁻¹ (r² = 0.72).     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Dissolved organic carbon concentrations and fluxes in forest catchments and streams: DOC-3 model

Dissolved organic carbon (DOC) concentrations in south-western Nova Scotia streams, sampled at weekly to biweekly intervals, varied across streams from about 3 to 40 mg L⁻¹, being highest mid-summer to fall, and lowest during winter to spring. A 3-parameter model (DOC-3) was proposed to project daily stream DOC concentrations and fluxes from modelled estimates for daily soil temperature and moisture, year-round, and in relation to basin size and wetness. The parameters of this model refer to (i) a basin-specific DOC release parameter “k_DOC^”, related to the wet- and open-water area percentages per basin, (ii) the lag time “τ” between DOC production and subsequent stream DOC emergence, related to the catchment area above the stream sampling location; and (iii) the activation energy “Ea”, to deal with the temperature effect on DOC production. This model was calibrated with the 1988-2006 DOC concentration data from three streams (Pine Marten, Moosepit Brook, and the Mersey River sampled at or near Kejimkujik National Park, or KNP), and was used to interpret the biweekly 1999-2003 DOC concentrations data (stream, ground and lake water, soil lysimeters) of the Pockwock-Bowater Watershed Project near Halifax, Nova Scotia. The data and the model revealed that the DOC concentrations within the streams were not correlated to the DOC concentrations within the soil- and groundwater, but were predictable based on (i) the hydrologically inferred weather-induced changes in soil moisture and temperature next to each stream, and (ii) the topographically inferred basin area and wet- and open-water area percentages associated with each stream (R² = 0.53; RMSE = 3.5 mg L⁻¹). Model-predicted fluxes accounted 74% of the hydrometrically determined DOC exports at KNP.     

中国地区大气汞的数值模拟研究

结合中国地区的汞排放,利用引入大气汞化学反应机制和干沉降模型的区域大气环境模式系统(Regional Atmospheric Environment Model System,Reg AEMS),对中国地区大气汞化物浓度和干沉降通量的时空分布特征进行模拟研究。研究结果表明,中国地区年均气态零价汞Hg0、氧化汞Hg O、氢氧化汞Hg(OH)2、氯化汞Hg Cl2和颗粒态汞HgP的沉降量分布类似。除西部、西北部地区Hg0的浓度较低外(0.5 ng·m-3),其他地区均高于全球背景浓度。各类汞化物浓度的季节变化明显,8月最低,2、3月最高。一次汞源区附近汞浓度随高度递减,在离源较远的地区,高层汞浓度较高。气态零价汞的干沉降速度的季节变化最明显,其干沉降通量在夏季最高。模拟区域中气态零价汞、氧化汞和颗粒态汞的年干沉降量分别为163.9、7.43和32.2 t。     

Modelling and mapping topographic variations in forest soils at high resolution: A case study

This article examines the utility of a digitally derived cartographic depth-to-water (DTW) index to model and map variations in drainage, vegetation and soil type and select soil properties within a forested area (40 ha) of the Swan Hills, Alberta, Canada. This index was derived from a LiDAR (Light Detection and Ranging) derived digital elevation model (DEM), with at least 1 ground return per m². The resulting DTW pattern was set to be zero along all DEM-derived flow channels, each with a 4 ha flow-initiation threshold. Soil type (luvisol, gleysol, mesisol), drainage type (very poor to excessive), vegetation type (hydric to xeric) and forest floor depth were determined along hillslope transects. These determinations conformed more closely to the DEM-derived log₁₀(DTW) variations (R² > 60%) than to the corresponding variations of the widely used topographic wetness index (TWI) (R² < 25%). Setting log₁₀(DTW) thresholds to represent the wet to moist to dry transitions between vegetation, drainage and soil type enabled a high-resolution mapping of these types across the study area. Also determined were soil moisture content, coarse fragment and soil particle composition (sand, silt, clay), pH, total C, N, S, P, Ca, Mg, K, Fe, Al, Mn, Zn, and available Ca, Mg, K, P and NH₄, by soil layer type and depth. Most of these variables were also more correlated with log₁₀(DTW) than with TWI, with and without soil layer depth as an additional regression variable. These variables are, therefore, subject to topographic controls to at least some extent, and can be modelled and mapped accordingly, as illustrated for soil moisture, forest floor depth and pH across the study area, from ridge tops to depressions. Further examinations revealed that the DEM-produced DTW and TWI patterns complemented one another, with DTW delineating soils in relation to local water-table influences, and with TWI delineating where the water would flow and accumulate.     

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.     

Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

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.     

Effects of climatic data low-pass filtering on the ICBM temperature- and moisture-based soil biological activity factors in a cool and humid climate

The air temperature (T_air), total precipitation (TP) and potential evapotranspiration (PET) are standard input data for soil carbon dynamic models, i.e., for calculating temperature and moisture effects on soil biological activity. The resolution needed depends on objectives, the complexity of models and inbuilt pedotransfer functions. The Introductory Carbon Balance Model (ICBM) soil climate front end model calculates a multiplicative soil-temperature (r_{e_temp}) and -moisture (r_{e_wat}) factor with a daily time-step to estimate soil biological activity, i.e., r_{e_crop} = r_{e_temp} × r_{e_wat}. Our objective was to determine how much r_{e_temp}, r_{e_wat} and r_{e_crop} are affected by low-pass filtering of the climatic input data for a cool, humid temperate region. To achieve this we conducted spectral analysis on T_air, TP, PET and r_{e_crop} in the frequency domain. Thereafter we applied Fourier low-pass filters of 5, 15, 30, 60 and 180 days on T_air, TP, PET and tracked their effects through the soil climate model's state variables and outputs. This was done using a sandy and a heavy clay soil and an 89-year daily time-series from a meteorological station in Quebec (Canada). The Fourier spectra showed that the variance for T_air, PET and r_{e_crop} was dominated by an annual cycle, as could be expected. There was no yearly cycle for TP. The variation in r_{e_temp} explained most of the variance in r_{e_crop}. The soil climate module outputs were not sensitive to low-pass filtering of PET. A daily time-step was needed to avoid overestimating r_{e_crop} for the sandy soil. Using a weekly time-step for TP and T_air allowed us to explain about 80% of the variance in r_{e_crop} for the heavy clay soil. This study also indicates that the standard leaf (and green) area index functions for calculating transpiration should receive more attention, since they have significant effects on the state and output variables.