Integrative trophic network assessments of a lentic ecosystem by key ecological approaches of water chemistry, trophic guilds, and ecosystem health assessments along with an ECOPATH model

The objective of this study was to describe the trophic structure and energy flow in a lentic ecosystem in South Korea. Physicochemical water conditions were evaluated along with the reservoir ecosystem health using a multimetric IBI model. Nutrient analyses of the reservoir showed a nutrient rich and hypereutrophic system. Guild analysis revealed that tolerant and omnivorous species dominated the ecosystem. Tolerant fish, as a proportion of the number of individuals, were associated (R² > 0.90, p < 0.01) with TN and TP, the key indicators of trophic state in lentic ecosystems. The mean Reservoir Ecosystem Health Assessment (REHA) score was 19.3 during the study, which was judged as in ‘fair to poor’ condition. A trophic analysis of the reservoir estimated by the ECOPATH model shows that most activity in terms of energy flow occurred in the lower part of the trophic web, where there was intensive use of primary producers as a food source. Consequently, of the 10 consumer groups, nine fell within trophic levels <2.8. Trophic levels (TL) estimated from the weighted average of prey trophic levels varied from 1.0 for phytoplankton, macrophytes, and detritus to 3.25 for the top predator, Pseudobagrus fulvidraco. Our integrated approach to trophic network analysis may provide a key tool for determining the effects of nutrient influx on energy flow pathways in lentic ecosystems.     

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.     

Modeling changes in the coastal ecosystem of the Pearl River Estuary from 1981 to 1998

The coastal ecosystem of the Pearl River Estuary (PRE) has been overfished and received a high level of combined pollution since the 1980s. Ecopath with Ecosim was used to construct two ecosystem models (for 1981 and 1998) to characterize the food web structure and functioning of the ecosystem. Pedigree work and simple sensitivity analysis were carried out to evaluate the quality of data and the uncertainty of the models. The two models seem reliable with regards to input data of good quality. Comparing the variations of outputs of these two models aimed to facilitate assessment of changes of the ecosystem during the past two decades.The trophic structure of the ecosystem has changed with an increase in the biomass proportion of lower trophic level (TL) organisms and a decrease in top predator biomass proportion. All the indices of ecosystem maturity examined show that the system was in a more mature condition in 1981 than in 1998, although the system has been in a condition of stress due to anthropogenic disturbances, such as environmental pollution and habitat destruction since 1981. The ecosystem was aggregated into six and seven integral TLs in 1981 and 1998, respectively, using the trophic aggregation routine of Ecopath. Most of the total system biomass and catch took place at TL II and III in both years. But the distribution of the total system biomass and catch at different TLs changed with decreasing proportions in higher TLs in 1998. The mean transfer efficiency was 9.1% and 10.2% in 1981 and 1998, respectively.Comparative network analysis allowed quantification of the importance of direct and indirect trophic interactions among functional groups. Moreover, a method derived from the mixed trophic impact (MTI) analysis allowed estimating importance of groups in terms of “keystoneness” and identifying the keystone species in the two models over the past two decades. The results indicate that there were no clear keystone species in 1998 but two keystone species at medium trophic levels were identified in 1981. Moreover, organisms located at low trophic levels such as phytoplankton, zooplankton and benthic invertebrates were identified to have relatively high keystoneness in the ecosystem.     

Assessing the carrying capacity of tilapia in an intertidal mangrove-based polyculture system of Pearl River Delta, China

A trophic model of an intertidal mangrove-based polyculture system in Pearl River Delta, China, was constructed using the Ecopath with Ecosim software. This polyculture system was chosen since it is the first integrated multi-trophic aquaculture (IMTA) system that was constructed on the basis of mangrove planting in China. The energy flows, ecosystem property, and carrying capacity of tilapia in the polyculture system were analyzed and evaluated. The results show the trophic level of 1.00 for primary producers and detritus to 2.85 for grass carp. The geometric mean of the trophic transfer efficiencies was 7.0%, with 7.2% from detritus and 6.8% from primary producers within the system. The ecosystem property indices show that this polyculture system has a high value of total primary production/total respiration (TPP/TR) and total primary production/total biomass (TPP/TB), together with low Finn's cycled index (FCI), Finn's mean path length (FML), and connectance index (CI), indicating that this system is at a development stage according to Odum's theory. The principal fish cultured in the system is tilapia, and mixed trophic impacts (MTI) show that tilapia has a marked impact on most compartments in this system, and the carrying capacity was found to be a tilapia culture biomass of 5.8 t ha⁻¹ in the system.     

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.     

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.     

Decadal changes in a NW Mediterranean Sea food web in relation to fishing exploitation

We analysed changes in the ecological roles of species, trophic structure and ecosystem functioning using four standardized mass-balance models of the South Catalan Sea (North-western Mediterranean). Models represented the ecosystem during the late 1970s, mid 1990s, early 2000s, and a simulated no-fishing scenario. The underlying hypothesis was that ecosystem models should quantitatively capture the increasing exploitation in the ecosystem from the 1970s to 2000s, as well as differences between the exploited and non-exploited scenarios. Biomass showed a general decrease, while there was an increase in biomass at lower trophic levels (TL) from the 1970s to 2000s. The efficiency of energy transfer (TE) from lower to higher TLs significantly increased with time. The ecosystem during the 1990s showed higher biomass and flows than during the 1970s and 2000s due to an increase in small pelagic fish biomass (especially sardines). Exploited food webs also showed similarities in terms of general structure and functioning due to high intensity of fishing already in the 1970s. This intensity was highlighted with low trophic levels in the catch, high consumption of production by fisheries, medium to high primary production required to sustain the catches and high losses in secondary production due to fishing. Significant differences on ecosystem structure and functioning were highlighted between the exploited and no-fishing scenarios. Biomass of higher TLs increased under the no-fishing scenario and the mean trophic level of the community and the fish/invertebrate biomass ratios were substantially lower in exploited food webs. The efficiency of energy transfer (TE) from lower to higher TLs was lower under the no-fishing scenario, and it showed a continuous decrease with increasing TL. Marine mammals, large hake, anglerfish and large pelagic fish were identified as keystone species of the ecosystem when there was no fishing, while their ecological importance notably decreased under the exploited periods. On the contrary, the importance of small-sized organisms such as benthic invertebrates and small pelagic fish was higher in exploited food webs.     

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.     

Simulation of thermodynamic transmission in green roof ecosystem

Green roofs entail the creation of vegetated space on the top of artificial structures. They can modify the thermal properties of buildings to bring cooling energy conservation and improve human comfort. This study evaluates the thermodynamic transmission in the green roof ecosystem under different vegetation treatments. Our model simulation is based on the traditional Bowen ratio energy balance model (BREBM) and a proposed solar radiation shield effectiveness model (SEM). The BREBM investigates energy absorption of different components of radiation, and the SEM evaluates the radiation shield effects. The proposed model is tested and validated to be efficient to simulate solar energy transmission in green roofs, with some major findings. Firstly, the solar radiation transmission processes might be considered as free vibration motion. Daytime positive heat storage of the green roof is 350-520 W·m⁻² on an hourly basis. Nighttime or afternoon negative value registers a rather constant magnitude of −60 W·m⁻². Daily net average is positive around 155-210 W·m⁻². Secondly, solar radiation vibration is highly correlated with plant structure. The canopy reflectance and transmittance are strongly correlated (R² = 0.87). The multi-layer shrub treatment has the highest shield effectiveness (0.34), followed by two-layer groundcover (0.27), and single-layer grass (0.16). Green roof vegetation absorbs and stores large amounts of heat to form an effective thermal buffer against daily temperature fluctuation. Vegetated roofs drastically depress air temperature in comparison with bare ground (control treatment). Finally, the thermodynamic model is relatively simple and efficient for investigating thermodynamic transmission in green roof ecosystem, and it could be developed into a broad solar radiant land cover model.     

Assessing biomass gains from marsh restoration in Delaware Bay using Ecopath with Ecosim

The Delaware Bay ecosystem has been the focus of extensive habitat restoration efforts to offset finfish losses due to mortality associated with power plant water intake. As a result, a 45 km² or a 3% increase in total marsh area was achieved by 1996-1997 through the restoration efforts of the Public Service Enterprise Group (PSEG). To quantify the impact of restoration efforts on system productivity, an Ecopath with Ecosim model was constructed that represented all major components of the ecosystem. The model consisted of 47 functional groups including: 27 fish species, 5 invertebrate groups, 4 multi-species benthic groups, 6 multi-species fish groups, 3 plankton groups, 1 shorebird group and 1 marine mammal group. Biomass, abundance, catch, and demographic data were obtained from the literature or from individual stock assessments conducted for principal ecosystem components. A base Ecosim model was fitted to time series of key species in the Bay representing the period 1966-2003. To access the gains from marsh restoration, model simulations reflecting no restoration were conducted to estimate the productivity that would have been lost if restoration efforts had not occurred. The results indicated that restoration increased total ecosystem biomass by 47.7 t km⁻² year⁻¹. Simulations indicated increased biomasses across a wide range of species including important forage and commercially important species. The marsh restoration also significantly impacted ecosystem structure increasing the ratio of production-to-respiration, increasing system path length and decreasing the ratio of production-to-biomass.     

Modeling the carbon dynamics of the La Grande hydroelectric complex in northern Quebec

A mechanistic semi-empirical carbon cycle model of the La Grande reservoir complex in northern Quebec, Canada was conceived in order to investigate the climate impact of such a large alteration of the continental water cycle. The model includes inputs from the drainage basin, organic matter release from flooded soils, CO₂ emissions across the water-atmosphere interface and sedimentation. Most input data stems from previous research by our group on those ecosystems. The model includes the seven reservoirs of the La Grande complex and was run for periods of 50 and 100 years. Terrigeneous dissolved, particulate and suspended soil carbon fluxes and concentrations were computed. Over 100 years, 31.3 × 10¹² g C are released from flooded soils, equivalent to 28-29% of inputs from the drainage basin. 40-74% of dissolved organic carbon is mineralized. CO₂ fluxes over 100 years are 50.5-79.8 × 10¹² g C, 46.4-67.9 × 10¹² g C more than in the absence of reservoirs. The increase in mineralization of organic matter and in CO₂ emissions is a result of the increase in cumulated water residence time due to the creation of the reservoirs. Changes in other carbon sinks and sources likely offset a part of this additional carbon flux to the atmosphere. In the first years following flooding of the reservoir, organic carbon release from flooded soils exceeds CO₂ emissions, implying the downstream export of large quantities of eroded soil organic carbon. After this initial period, CO₂ emissions are fuelled by organic carbon originating from the drainage basin.     

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.     

Modeling an exploited rocky coastal ecosystem: Bahia Tortugas, Mexico

A trophic structure model of the rocky coastal ecosystem in Bahia Tortugas, Mexico was constructed using Ecopath software to represent the main biomass flows in the system. Data for the model came from field observations (biomass estimates, stomach contents, and ecological observations for sea snails, abalones, lobster, some demersal finfishes, and macroalgae) carried out through ten field trips from 2006 to 2008. The results provide a snapshot of how the ecosystem operates. The model considers 23 functional groups. The total system throughput was 553 t/km²/year, 57% corresponds to internal consumption, 28% to respiration, 14% becomes detritus, and only 1% is removed through commercial fishing. The model suggests that even for exploited populations, predation and competition are heavier stresses than current fishing effort; however, because spiny lobster showed the second highest keystoneness’ index value, increasing fishing pressure on this group could strongly impact the entire ecosystem. We believe that this model has the potential to support management by allowing the exploration of the potential impacts of different fishing decisions at ecosystem level.     

Calculating ecological carrying capacity of shellfish aquaculture using mass-balance modeling: Narragansett Bay, Rhode Island

Increasing growth in the aquaculture industry demands ecosystem-based techniques for management if that growth is to be ecologically sustainable and promote equity among users of the ecosystems in which it occurs. Models of carrying capacity can be used to responsibly limit the growth of aquaculture in increasingly crowded coastal areas. Narragansett Bay, Rhode Island, USA is one such crowded coastal region experiencing a rapid increase in bivalve aquaculture. An ecosystem mass-balance model was used to calculate the ecological carrying capacity of bivalve aquaculture. Cultured oyster biomass is currently at 0.47 t km⁻² and could be increased 625 times without exceeding the ecological carrying capacity of 297 t km⁻². This translates to approximately 38,950 t of harvested cultured oysters annually which is 4 times the total estimated annual harvest of finfish. This potential for growth is due to the high primary productivity and large energy throughput to detritus of this ecosystem. Shellfish aquaculture has potential for continued growth and is unlikely to become food limited due, in part, to the large detritus pool.     

Food web structure and trophic interactions of the tropical highland lake Hayq, Ethiopia

We generated a mass-balance model to figure out the food web structure and trophic interactions of the major functional groups of the Ethiopian highland Lake Hayq. Moreover, the study lay down a baseline data for future ecosystem-based investigations and management activities. Extensive data collection has been taken place between October 2007 and May 2009. Ecotrophic efficiency (EE) of several functional groups including phytoplankton (0.8) and detritus (0.85) was high indicating the utilization of the groups within the system. However, the EE of Mesocyclops (0.03) and Thermocyclops (0.30) was very low implying these resources were rather a ‘sink’ in the trophic hierarchy. Flows based on aggregated trophic level sensu Lindeman revealed the importance of both phytoplankton and detritus to higher trophic levels. The computed average transfer efficiency of 11.5% for the first four trophic levels was within the range for highly efficient African lakes. The primary production to respiration (P/R) ratio (1.05) of Lake Hayq indicates the maturity of the ecosystem. We also modeled the food-web by excluding Tilapia and reduced phytoplankton biomass to get insight into the mass balance before Tilapia was introduced. The analysis resulted in a lower system omnivory index (SOI = 0.016) and a reduced P/R ratio (0.13) that described the lake as immature ecosystem, suggesting the introduction of Tilapia might have contributed to the maturity of the lake. Tilapia in Lake Hayq filled an ecological empty niche of pelagic planktivores, and contributed for the better transfer efficiency observed from primary production to fish yield.     

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.     

Optimization of ecosystem model parameters using spatio-temporal soil moisture information

Parameters in process-based terrestrial ecosystem models are often nonlinearly related to the water flux to the atmosphere, and they also change temporally and spatially. Therefore, for estimating soil moisture, process-based terrestrial ecosystem models inevitably need to specify spatially and temporally variant model parameters. This study presents a two-stage data assimilation scheme (TSDA) to spatially and temporally optimize some key parameters of an ecosystem model which are closely related to soil moisture. At the first stage, a simplified ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS), is used to obtain the prior estimation of daily soil moisture. After the spatial distribution of 0–10 cm surface soil moisture is derived from remote sensing, an Ensemble Kalman Filter is used to minimize the difference between the remote sensing model results, through optimizing some model parameters spatially. At the second stage, BEPS is reinitialized using the optimized parameters to provide the updated model predictions of daily soil moisture. TSDA has been applied to an arid and semi-arid area of northwest China, and the performance of the model for estimating daily 0–10 cm soil moisture after parameter optimization was validated using field measurements. Results indicate that the TSDA developed in this study is robust and efficient in both temporal and spatial model parameter optimization. After performing the optimization, the correlation (r²) between model-predicted 0–10 cm soil moisture and field measurement increased from 0.66 to 0.75. It is demonstrated that spatial and temporal optimization of ecosystem model parameters can not only improve the model prediction of daily soil moisture but also help to understand the spatial and temporal variation of some key parameters in an ecosystem model and the corresponding ecological mechanisms controlling the variation.