Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

Control concept and countermeasures for shallow lakes’ eutrophication in China

Research on lake eutrophication in China began in the early 1970s, and many lakes in China are now known to be in meso-eutrophic status. Lake eutrophication has been showing a rapidly increasing trend since 2000. Investigations show that the main reasons for lake eutrophication include a fragile lake background environment, excessive nutrient loading into lakes, excessive human activities, ecological degeneration, weak environmental protection awareness, and lax lake management. Major mechanisms resulting from lake eutrophication include nutrient recycling imbalance, major changes in water chemistry (pH, oxygen, and carbon), lake ecosystem imbalance, and algal prevalence in lakes. Some concepts for controlling eutrophication should be persistently proposed, including lake catchment control, combination of pollutant source control with ecological restoration, protection of three important aspects (terrestrial ecology, lake coast zone, and submerged plant), and combination of lake management with regulation. Measures to control lake eutrophication should include pollution source control (i.e., optimize industrial structural adjustments in the lake catchment, reduce nitrogen and phosphorus emission amounts, and control endogenous pollution) and lake ecological restoration (i.e. establish a zone-lake buffer region and lakeside zone, protect regional vegetation, utilize hydrophytes in renovation technology); countermeasures for lake management should include implementing water quality management, identifying environmental and lake water goals, legislating and formulating laws and regulations to protect lakes, strengthening publicity and the education of people, increasing public awareness through participation in systems and mechanic innovations, establishing lake region management institutions, and ensuring implementation of governance and management measures.     

Spatial and temporal hydrodynamic and water quality modeling analysis of a large reservoir on the South Carolina (USA) coastal plain

Two-dimensional, 31-segment, 61-channel hydrodynamic and water quality models of Lake Marion (surface area 330.7 km²; volume 1548.3×10⁶ m³) were developed using the WASP5 modeling system. Field data from 1985 to 1990 were used to parameterize the models. Phytoplankton kinetic rates and constants were obtained from a related in situ study; others from modeling literature. The hydrodynamic model was calibrated to estimates of daily lake volume; the water quality model was calibrated for ammonia, nitrate, ortho-phosphate, dissolved oxygen, chlorophyll-a, biochemical oxygen demand, organic nitrogen, and organic phosphorus. Water quality calibration suggested the model characterized phytoplankton and nutrient dynamics quite well. The model was validated (Kolmogorov–Smirnov two-sample goodness-of-fit test at P<0.05) by reparameterizing the nutrient loading functions using an independent set of field data. The models identified several factors that may contribute to the spatial variability previously reported from other research in the reservoir, despite the superficial absence of complex structure. Sensitivity analysis of the phytoplankton kinetic rates suggest that study site-specific estimates were important for obtaining model fit to field data. Sediment sources of ammonia (10–60 mg m⁻² day⁻¹) and phosphate (1–6 mg m⁻² day⁻¹) were important to achieve model calibration, especially during periods of high temperatures and low dissolved oxygen. This sediment flux accounted for 78% (nitrogen) and 50% (phosphorus) of the annual load. Spatial and temporal variability in the lake, reflected in the calibrated and validated models, suggest that ecological factors that influence phytoplankton productivity and nutrient dynamics are different in various parts of the lake. The WASP5 model as implemented here does not fully accommodate the ecological variability in Lake Marion due to model constraints on the specification of rate constants. This level of spatial detail may not be appropriate for an operational reservoir model, but as a research tool the models are both versatile and useful.     

Analysing the effects of soil properties changes associated with land use changes on the simulated water balance: A comparison of three hydrological catchment models for scenario analysis

This paper presents results of a model comparison study within the LUCHEM framework (‘assessing the impact of Land Use Change on Hydrology by Ensemble Modelling’) where the effects of land use change on catchment water balances were assessed with various hydrological catchment models. The motivation for this part of LUCHEM is that it is well known that land use changes may induce changes in soil chemical and soil physical properties (e.g. bulk density). Unfortunately the effects of land use change on soil hydraulic properties are seldom investigated directly, but some information on changes in bulk density is available. Changes in bulk density can be used as input for pedotransfer functions to derive changes in soil hydraulic model parameters. In this study, three different catchment models (SWAT, TOPLATS, WASIM) are compared with respect to their sensitivity to land use change with and without consideration of associated changes in soil parameterisation. The results reveal that different models show a different sensitivity to the change in soil parameterisation while the magnitude of absolute changes in simulated evapotranspiration and discharge is similar. SWAT calculates largest changes in the water balance in a German mesoscale catchment. TOPLATS also shows significant changes in the calculated catchment water balances as well as in the runoff generation while WASIM reacts least sensitive. While TOPLATS and WASIM show similar patterns with respect to changes in the water flows for all subcatchments and land use scenarios, SWAT results are similar for the different catchments, but show scenario specific patterns. In relation to the magnitude of the effects on simulated water flows induced by land use change, the significance of considering soil change effects depends on both, the scenario definition and on the model sensitivity to soil parameterisation. For two of the three land use scenarios representing an intensified land use, SWAT and TOPLATS simulate water balance changes in the same order of magnitude due to both, land use and soil property changes. Therefore, a consideration of changes in soil properties as part of land use change scenario analysis is recommended. Future field work needs to aim at the validation of the assumed dependency of soil hydrologic properties on land use change.     

Eco-hydrological modelling in a highly regulated lowland catchment to find measures for improving water quality

Water quality modelling in the meso-scale Rhin catchment in the German federal state Brandenburg was done (1) to answer some specific questions concerning identification of point and diffuse sources of nutrient pollution in the catchment, (2) to assess the influences of possible climate and land use changes on water quantity and quality and (3) to evaluate potential measures to be done in order to achieve a “good ecological status” of the river and its lakes as required by the Water Framework Directive (WFD).The Rhin catchment is a typical highly regulated lowland river basin in Northern Germany. The regulations complicate water quantity and quality modelling in the catchment. The research was done by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modelling period was from 1981 until 2005. After calibrating the hydrological processes at different gauges within the basin with satisfactory results, water quality (nitrogen and phosphorus) modelling was done taking into account the emissions of different point sources (sewage treatment plants, etc.) and identifying the amount of diffuse pollution caused mainly by agriculture.For suggesting some feasible measures to improve water quality and to reduce diffuse pollution considering possible climate and land use changes, different reasonable scenarios were applied in consultation with the Environmental Agency of Brandenburg (LUA). The study revealed that the amount of water discharge has significant influence on the concentration of nutrients in the river network, and that nitrogen pollution, caused mainly by diffuse sources, could be notably reduced by application of agricultural measures, whereas the pollution by phosphorus could be diminished most effectively by the reduction of point source emissions.     

长江中下游湖泊富营养化过程的湖泊沉积记录

长江中下游湖群区，历来是人类最活跃的场所，但由于近年来社会经济的迅速发展，湖泊富营养化问题日趋严重，对湖泊湿地变化与湖泊营养盐状况关系的分析是制定湖泊环境整治和生态修复的重要科学依据。长江中游湖泊——龙感湖的湖中心钻孔沉积物中硅藻组合和总磷变化记录了近百年来龙感湖富营养化过程。沉积物中湿地花粉与人湖营养盐关系以及磁化率的分析表明，流域内人类活动对湖周滩地的改造，破坏了湿地植被，助长了人湖物质的增加，湖泊营养相对富集，而流域农业化肥的使用导致了水质的进一步恶化。     

Future distribution modelling: A stitch in time is not enough

The last two decades have seen an increasing number of studies assessing the impact of climate change upon biodiversity. A central assumption underpinning research into the potential future habitat of terrestrial biota is that species are presently in equilibrium with their environments and that quantitative climate models adequately represent the distribution of species. Recently, many alarming predictions have emerged concerning the extinction and redistribution of species. Here, we show that even large-scale models of the climatic niche dimensions of species are temporally variable. Distributional models were developed for Salix (willow) species occurring in the province of Ontario, Canada, using three historical climate data sets. Although historical data very accurately represented the distributions of willows, the inherent variability within the models of species based on different periods greatly influenced the direction and magnitude of projected distributional change. We expose a fundamental uncertainty with respect to predicting the responses of species to climate change.     

A thermodynamic model of freshwater Antarctic lake ice

Antarctic lakes with simple plankton ecosystems are believed to be sensitive biological indicators of climate change. Models of the physical environment, in particular the ice layer, support understanding of how the ecosystems respond to meteorological variables. This paper describes how data from a previously reported automatic measuring probe and meteorological data from Davis station were used to develop a detailed thermodynamic model of the ice layer on Crooked Lake, one of the largest and deepest freshwater lakes in Antarctica. The general model structure is similar to a previously reported model of sea ice but with modifications specific to the Antarctic freshwater lake case informed by the data. The model inputs are atmospheric variables as well as water temperature, ice albedo and the radiation extinction coefficient for the ice. Heat and radiation fluxes at the ice–air and ice–water boundaries are calculated using equations chosen for their suitability for the Antarctic. In the case of shortwave radiation, equations were fitted to data from the automatic probe. Using the heat fluxes to establish boundary conditions, and incorporating the known thermodynamic properties of ice, the temperature profile within the ice and the resulting growth and melt of the ice can be calculated. The model uses a largely mechanistic approach, with most equations taken from established thermodynamic theories or empirical studies and only one adjustable parameter related to the sensible heat flux from the water, which is not easily calculated from the available data. It was found to accurately reproduce ice temperature and ice thickness data for the year 2003, with r² = 0.89, n = 2005. Finally, the model was simplified to run with air temperature as the only input variable and was shown to perform well—this suggests that freshwater lake ice is affected more by air temperature than any other variable, and is therefore a useful indicator of climate change in its own right.     

Modeling compensated root water and nutrient uptake

Plant root water and nutrient uptake is one of the most important processes in subsurface unsaturated flow and transport modeling, as root uptake controls actual plant evapotranspiration, water recharge and nutrient leaching to the groundwater, and exerts a major influence on predictions of global climate models. In general, unsaturated models describe root uptake relatively simple. For example, root water uptake is mostly uncompensated and nutrient uptake is simulated assuming that all uptake is passive, through the water uptake pathway only. We present a new compensated root water and nutrient uptake model, implemented in HYDRUS. The so-called root adaptability factor represents a threshold value above which reduced root water or nutrient uptake in water- or nutrient-stressed parts of the root zone is fully compensated for by increased uptake in other soil regions that are less stressed. Using a critical value of the water stress index, water uptake compensation is proportional to the water stress response function. Total root nutrient uptake is determined from the total of active and passive nutrient uptake. The partitioning between passive and active uptake is controlled by the a priori defined concentration value c_max. Passive nutrient uptake is simulated by multiplying root water uptake with the dissolved nutrient concentration, for soil solution concentration values below c_max. Passive nutrient uptake is thus zero when c_max is equal to zero. As the active nutrient uptake is obtained from the difference between plant nutrient demand and passive nutrient uptake (using Michaelis–Menten kinetics), the presented model thus implies that reduced passive nutrient uptake is compensated for by active nutrient uptake. In addition, the proposed root uptake model includes compensation for active nutrient uptake, in a similar way as used for root water uptake. The proposed root water and nutrient uptake model is demonstrated by several hypothetical examples, for plants supplied by water due to capillary rise from groundwater and surface drip irrigation.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Using a model selection criterion to identify appropriate complexity in aquatic biogeochemical models

Aquatic biogeochemical models are widely used as tools for understanding aquatic ecosystems and predicting their response to various stimuli (e.g., nutrient loading, toxic substances, climate change). Due to the complexity of these systems, such models are often elaborate and include a large number of estimated parameters. However, correspondingly large data sets are rarely available for calibration purposes, leading to models that may be overfit and possess reduced predictive capabilities. We apply, for the first time, information-theoretic model-selection techniques to a set of spatially explicit (1D) algal dynamics models of varying parameter dimension. We demonstrate that increases in complexity tend to produce a better model fit to calibration data, but beyond a certain degree of complexity the benefits of adding parameters are diminished (the risk of overfitting becomes greater). The particular approach taken here is computationally expensive, but several suggestions are made as to how multimodel methods may practically be extended to more sophisticated models.     

Watershed land use effects on lake water quality in Denmark

Mitigating nutrient losses from anthropogenic nonpoint sources is today of particular importance for improving the water quality of numerous freshwater lakes worldwide. Several empirical relationships between land use and in-lake water quality variables have been developed, but they are often weak, which can in part be attributed to lack of detailed information about land use activities or point sources. We examined a comprehensive data set comprising land use data, point-source information, and in-lake water quality for 414 Danish lakes. By excluding point-source-influenced lakes (n = 210), the strength in relationship (R2) between in-lake total nitrogen (TN) and total phosphorus (TP) concentrations and the proportion of agricultural land use in the watershed increased markedly, from 10-12% to 39-42% for deep lakes and from 10-12% to 21-23% for shallow lakes, with the highest increase for TN. Relationships between TP and agricultural land use were even stronger for lakes with rivers in their watershed (55%) compared to lakes without (28%), indicating that rivers mediate a stronger linkage between landscape activity and lake water quality by providing a "delivery" mechanism for excess nutrients in the watershed. When examining the effect of different near-freshwater land zones in contrast to the entire watershed, relationships generally improved with size of zone (25, 50, 100, 200, and 400 m from the edge of lake and streams) but were by far strongest using the entire watershed. The proportion of agricultural land use in the entire watershed was best in explaining lake water quality, both relative to estimated nutrient surplus at agricultural field level and near-lake land use, which somewhat contrasts typical strategies of management policies that mainly target agricultural nutrient applications and implementation of near-water buffer zones. This study suggests that transport mechanisms within the whole catchment are important for the nutrient export to lakes. Hence, the whole watershed should be considered when managing nutrient loadings to lakes, and future policies should ideally target measures that reduce the proportion of cultivated land in the watershed to successfully improve lake water quality.     

Is catchment productivity a useful predictor of taxa richness in lake plankton communities?

The influence of catchment variables on lake organisms is understudied. The terrestrial zone in the vicinity of lakes is, however, probably highly important for biota due to the effects on water chemistry and to various processes operating across ecosystem boundaries. We examined the relative importance of lake and catchment variables, as well as large-scale geographical factors, on the taxa richness of phyto- and zooplankton in 100 small lakes in Finland. In variation partitioning, the variability of phytoplankton richness was most strongly related to the effects of lake variables, the joint effects of lake and catchment variables, and the joint effects of all three groups of variables. Zooplankton richness, in turn, was most strongly related to the effects of lake and catchment variables and the joint effect of lake and catchment variables. The exact results of the variation partitioning depended on the catchment sizes considered in the regression models. Among lake variables, planktonic richness was strongly related to variables indicating productivity. Among catchment variables, the normalized difference vegetation index (NDVI), indicating catchment productivity, showed a relatively strong association with planktonic richness. These results provide evidence that catchment variables such as the NDVI may be efficient predictors of planktonic richness in small lakes. It is possible that individual lakes embedded in a highly productive landscape have higher taxa richness than solitary, potentially productive lakes because of the high influx of dispersing propagules from the regional pool. We also suggest that catchment variables may respond to environmental changes at different scales than the lake variables, and explicit consideration of catchment productivity would therefore be useful when planning research and monitoring programs for freshwater organisms.     

Management of nutrient emissions of Axios River catchment: Their effect in the coastal zone of Thermaikos Gulf,Greece

The estimation of nutrient fluxes, the determination of spatial and temporal response and the understanding of biogeochemical changes in the past, present and future in the Axios River catchment, in Greece, as well as the impacts to the coastal zone of Thermaikos Gulf were accomplished by the use of harmonized watershed and coastal zone models. The mathematical model MONERIS was the watershed management model that was used to model the export loads of nutrients in Axios River. MONERIS was developed to estimate the nutrient inputs into river basins by point sources and various diffuse pathways. Watershed hydrologic and water quality data were collected and synthesized to develop input data sets for the simulation of Axios River catchment. The model was modified to better assess organic nitrogen export loads in Mediterranean watersheds. The results showed the importance of agricultural and livestock activities, concerning their nutrients emissions in the River. MONERIS was integrated with the coastal zone model WASP 6.0 to assess the impacts of the nutrient loads to the eutrophication status of the coastal zone. Several management scenarios were assessed. Management scenarios included measures for reduction in the emissions from the fertilizer plant of Veles, removal of phosphorous from the detergents in FYROM, treatment of urban wastes to EU Standards, reduction in N-fertilizer input, reduction in erosion and the green scenario that represented the maximum reduction scenario of all the measures together. The model simulations indicated that the coastal zone of Axios mouth will be eutrophic for nitrate (2.69–3.34 μM) and phosphate (0.2–0.68 μM) and upper mesotrophic for chlorophyll-a (0.74–1.45 μg/l) for the scenarios tested. The results suggest that the impact of the management scenarios will be largely negligible (no change in trophic status) for the Thermaikos Gulf sector nearby the Axios River due to additional sources such as the loads from Thessaloniki's waste water treatment plant which appear to affect the region to a greater extent. The integration of watershed and coastal zone models can be used to assess management scenarios in order to illustrate the significance of various land use practices to the eutrophication of the Gulf.     

Estimating the critical phosphorus loading of shallow lakes with the ecosystem model PCLake: Sensitivity, calibration and uncertainty

There is a vast body of knowledge that eutrophication of lakes may cause algal blooms. Among lakes, shallow lakes are peculiar systems in that they typically can be in one of two contrasting (equilibrium) states that are self-stabilizing: a ‘clear’ state with submerged macrophytes or a ‘turbid’ state dominated by phytoplankton. Eutrophication may cause a switch from the clear to the turbid state, if the P loading exceeds a critical value. The ecological processes governing this switch are covered by the ecosystem model PCLake, a dynamic model of nutrient cycling and the biota in shallow lakes. Here we present an extensive analysis of the model, using a three-step procedure. (1) A sensitivity analysis revealed the key parameters for the model output. (2) These parameters were calibrated on the combined data on total phosphorus, chlorophyll-a, macrophytes cover and Secchi depth in over 40 lakes. This was done by a Bayesian procedure, giving a weight to each parameter setting based on its likelihood. (3) These weights were used for an uncertainty analysis, applied to the switchpoints (critical phosphorus loading levels) calculated by the model. The model was most sensitive to changes in water depth, P and N loading, retention time and lake size as external input factors, and to zooplankton growth rate, settling rates and maximum growth rates of phytoplankton and macrophytes as process parameters. The results for the ‘best run’ showed an acceptable agreement between model and data and classified nearly all lakes to which the model was applied correctly as either ‘clear’ (macrophyte-dominated) or ‘turbid’ (phytoplankton-dominated). The critical loading levels for a standard lake showed about a factor two uncertainty due to the variation in the posterior parameter distribution. This study calculates in one coherent analysis uncertainties in critical phosphorus loading, a parameter that is of great importance to water quality managers.     

Modeling linkages between sediment resuspension and water quality in a shallow,eutrophic, wind-exposed lake

The interactions between bed sediments and the water column in shallow, eutrophic lakes have tremendous implications for the fate and transport of nutrients in those water bodies. This has resulted in the development of water quality models for lakes incorporating the processes of sediment resuspension. Reliable resuspension models are thus needed to accurately represent this phenomenon. In this paper, three different sediment-resuspension models are combined with a hydrodynamic and water quality model, dynamic lake model-water quality (DLM-WQ), and the resulting models are used to simulate nutrient distributions in the highly eutrophic Salton Sea, California, USA. One of the resuspension formulas is based upon sediment characteristics as well as the bed shear stress exerted by wind-induced waves and currents, while the other two are standard, power-law-type formulas for cohesive sediments with two different exponents. The outputs for water quality variables, such as temperature, chlorophyll a, dissolved oxygen and nutrients, obtained from the three resulting models and from an earlier DLM-WQ run with a simple empirical sediment-resuspension model are compared with measured data. The level of agreement between the simulations and the measured data is assessed by using both statistical and graphical model evaluation methods, including measures of residual errors, sample autocorrelations, t-tests, and box plots. Based on these assessments, DLM-WQ with an extended version of the García and Parker [García, M.H., Parker, G., 1993. Experiments on the entrainment of sediment into suspension by a dense bottom current. J. Geophys. Res.-Oceans 98, 4793–4807] relationship gave the best results for water quality in the Salton Sea, confirming that the use of formulas with more information on the sediment characteristics yields more accurate results. To the best of our knowledge, this is the first effort to combine water quality models for lakes and reservoirs with a sediment-resuspension model which was originally intended for open-channel flows. The simulations confirm that sediment resuspension is the most dominant process in the Salton Sea's nutrient cycling. The effect of proposed physical changes to the Salton Sea on water quality characteristics is also addressed.     

Integration of a fish bioenergetics model into a spatially explicit water quality model: Application to menhaden in Chesapeake Bay

Although fish are usually thought of as victims of water quality degradation, it has been proposed that some planktivorous species may improve water quality through consumption of algae and sequestering of nutrients via growth. Within most numerical water quality models, the highest trophic level modeled explicitly is zooplankton, prohibiting an investigation of the effect a fish species may be having on its environment. Conversely, numerical models of fish consumption do not typically include feedback mechanisms to capture the effects of fish on primary production and nutrient recycling. In the present study, a fish bioenergetics model is incorporated into CE-QUAL-ICM, a spatially explicit eutrophication model. In addition to fish consumption of algae, zooplankton, and detritus, fish biomass accumulation and nutrient recycling to the water column are explicitly accounted for. These developments advance prior modeling efforts of the impact of fish on water quality, many of which are based on integrated estimates over an entire system and which omit the feedback the fish have through nutrient recycling and excretion. To validate the developments, a pilot application was undertaken for Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay. The model indicates menhaden may reduce the algal biomass while simultaneously increasing primary productivity.     

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.     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.