An individual based model of bearded pig abundance

We develop an individual based model of bearded pig abundance which predicts population dynamics based on the processes of energy accumulation and expenditure, reproduction and mortality of individual pigs. Because fatness is a key indicator of condition and reproductive potential in bearded pigs, processes are represented in terms of a fatness index variable. Only a small number of parameters are used in this simple model; these were chosen on the basis of fatness index data and qualitative observations of bearded pig population dynamics. The model was found to be accurate in predicting the timing of observed pig eruptions, and robust in that model results were unaffected by moderate variation in parameter values. There was insufficient quantitative data to obtain precise predictions of fatness and abundance, but qualitative insights about the effects of the size and timing of fruiting events on pig abundance were obtained. The results showed that a single fruiting peak will not produce a bearded pig eruption, no matter how large the fruiting event is, because the duration of the fruiting is too short to allow exponential growth of the population. Consecutive masting events are necessary for an eruption, because if events are separated by more than 1 year, the population will decline to its minimum fatness and abundance levels. It is also necessary for at least one of the fruiting events in a consecutive sequence to be a large event, as consecutive small fruiting events do not increase the fatness enough to cause an eruption. These insights help to explain and predict the effects of changes in mast fruiting patterns on bearded pig populations, such as the predicted increase in frequency and reduction in size of masting fruiting events as a result of climate change.     

Dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain)

In this study we developed a dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain). The data used to develop the model were obtained from a network of permanent plots, of between 10 and 55-year-old, which the Unidade de Xestión Forestal Sostible (Sustainable Forest Management Unit) of the University of Santiago de Compostela has set up in pure plantations of this species of pine in its area of distribution in Galicia. In this model, the initial stand conditions at any point in time are defined by three state variables (number of trees per hectare, stand basal area and dominant height), and are used to estimate stand volume, classified by commercial classes, for a given projection age. The model uses three transition functions expressed as algebraic difference equations of the three corresponding state variables used to project the stand state at any point in time. In addition, the model incorporates a function for predicting initial stand basal area, which can be used to establish the starting point for the simulation. This alternative should only be used when the stand is not yet established or when no inventory data are available. Once the state variables are known for a specific moment, a distribution function is used to estimate the number of trees in each diameter class, by recovering the parameters of the Weibull function, using the moments of first and second order of the distribution (arithmetic mean diameter and variance, respectively). By using a generalized height–diameter function to estimate the height of the average tree in each diameter class, combined with a taper function that uses the above predicted diameter and height, it is then possible to estimate total or merchantable stand volume.     

Assessing the past and future distribution and productivity of ponderosa pine in the Pacific Northwest using a process model, 3-PG

Climate variability at decadal scales influences not only the growth of widely distributed species such as Pinus ponderosa, but also can have an effect on the timing and severity of fire and insect outbreaks that may alter species distributions. In this paper, we present a spatial modelling technique to assess the influence of climatic variability on the annual productivity of P. ponderosa in the Pacific Northwest (PNW) of North America over the past 100 years and infer how a sustained change in climate might alter the geographic distribution of this species across defined ecotones. Field observations were used to establish criteria for P. ponderosa dominance including: (1) maximum summer leaf area index (LAI), ranges between 1.5 and 2.5; (2) 80% of available soil water is depleted during summer months; and (3) soil water will return to full capacity at least once during the year. Where these three criteria were not met, eventual replacement of P. ponderosa would be predicted. We utilized a simple physiological model, Physiological Principles for Predicting Growth (3-PG) to predict annual variation in LAI from climatic data provided by the Oregon Climate Service over the period from 1900 to 2000 and from broad scale 0.5°-spatial resolution future climate projections produced by the Hadley Climate Center, UK. From these simulations we produced a series of maps that display predicted shifts of zones where ponderosa pine might be expected to contract or expand its range if modeled climatic conditions at annual and decadal intervals were sustained. From the historical simulations, the most favorable year for pine dominance was 1958 and the least favorable, 1924. The most favorable decade was in the 1900s and the least favorable in the 1930s. The future predictions indicate a reduction in the current range of the P. ponderosa type along the western Cascade Range however, an increase along the east side and inland PNW. The model predicts that pine dominance should increase between 5 and 10% over the next century, mainly in inland Oregon, Idaho, and Washington.     

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.     

Mast seeding under increasing drought: results from a long-term data set and from a rainfall exclusion experiment

Mast seeding, the synchronous, highly variable seed production among years, is very common in tree species, but there is no consensus about its main causes and the main environmental factors affecting it. In this study, we first analyze a long-term data set on reproductive and vegetative growth of Quercus ilex in a mediterranean woodland in order to identify the main environmental drivers of interannual variation in flower and seed production and contrast the impact of climate vs. adaptive factors as main causes of masting. Second, we conducted an experiment of rainfall exclusion to evaluate the effects of an increasing drought (simulating predictions of global change models) on both reproductive processes. The annual seed crop was always affected by environmental factors related to the precipitation pattern, these abiotic factors disrupting the fruiting process at different periods of time. Seed production was strongly dependent upon water availability for the plant at initial (spring) and advanced (summer) stages of the acorn maturation cycle, whereas the final step of seed development was negatively affected by the frequency of torrential-rain events. We also found clear evidence that seed masting in the study species is not only regulated by selective endogenous rhythms, but is mainly a physiological response to the variable environment. Our results from the rainfall exclusion experiment corroborated the conclusions obtained from the 26-year fruiting record and demonstrated that the high interannual variation in seed crop was mainly determined by the success in seed development rather than by the flowering effort. Under a global change scenario, it could be expected that the drier conditions predicted by climate models reinforce the negative effects of summer drought on seed production, leading to negative consequences for tree recruitment and forest dynamics.     

Longleaf pine (Pinus palustris) and hardwood dynamics in a fire-maintained ecosystem: A simulation approach

Longleaf pine (Pinus palustris) savannas of the southeastern U.S. represent an archetype of a fire dependent ecosystem. They are known to have very short fire return intervals (∼1-3 years) that perpetuate understory plant diversity (up to 50 species m⁻²), support pine recruitment, and suppress fire sensitive hardwoods. Understanding the relationships that regulate longleaf and southern hardwoods is especially critical. With decreased fire frequency, insufficient intensity, or lack of underground competition, a woody mid-story rapidly develops, dominated by fire sensitive trees and shrubs that in-turn suppress more fire dependent species (including pine seedlings). This may occur in forest gaps, where pine-needle abundance is diminished, reducing fire spread potential. The interactions between longleaf pine, hardwoods, forest fuels, and fire frequency are complex and difficult to understand spatially. The objective of this study was to develop a spatially explicit longleaf pine-hardwood stochastic simulation model (LLM), incorporating tree demography, plant competition, and fuel and fire characteristics. Data from two longleaf pine study sites were used to develop and evaluate the model with the goal to incorporate simple site-specific calibration parameters for model versatility. Specific model components included pine seed masting, hardwood clonal sprouting, response to fire (re-sprouting, mortality), and tree density driven competition effects. LLM spatial outputs were consistent with observed forest gap dynamics associated with pine seedling establishment and hardwood encroachment. Changes in fire frequency (i.e., fire probability = 0.35-0.05) illustrated a shift in community structure from longleaf pine dominated to a hardwood dominated community. This approach to assessing model response may be useful in characterizing longleaf ecosystem resilience, especially at intermediate fire frequencies (e.g., 0.15) where the community may be sensitive to small changes in the fire regime. Height distributions and population densities were similar to in situ findings (field and LIDAR data) for both study sites. Height distributions output by the LLM illustrated fluctuations in population structure. The LLM was especially useful in determining knowledge gaps associated with fuel and fire heterogeneity, plant-plant interactions, population structure and its temporal fluctuations, and hardwood demography. This is the first known modeling work to simulate interactions between longleaf pine and hardwoods and provides a foundation for further studies on fire and forest management, especially in relation to ecological forestry practices, restoration, and site-specific applications.     

A mathematical model of field population dynamics of the southern pine beetle, dendroctonus frontalis

The southern pine beetle, Dendroctonus frontalis Zimmermann, is a major insect pest of pines in the southern U.S.A. A population dynamic model of D. frontalis within an infestation was developed. The model is based on the integration of several component submodels that describe individual life stage processes of the beetle. The inclusion of variable forest stand density and microclimate conditions results in a model response which closely follows actual field responses. A sensitivity analysis was performed to investigate effects of weather conditions and the importance of the spatial patterns within the forest.     

Modelling the response of tree growth to temperature and CO2 elevation as related to the fertility and current temperature sum of a site

A methodology for simulating climate change impacts on tree growth was introduced into a statistical growth and yield model in relation to variations in site fertility and location implemented with current temperature sum. This was based on a procedure in which the relative enhancement in stem volume growth was calculated from short-term runs of a physiological simulation model for Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and silver birch (Betula pendula Roth.) stands. These simulations were made for a set of stands with species-specific variations in stand characteristics, location and fertility type first in current climatic conditions and then in different combinations of CO₂ and temperature elevations. Based on these simulations, the relative enhancement of volume growth induced by the climate change (relative scenario effect, RSEv) was calculated and modelled in relation to: (i) CO₂ and temperature elevation, stand density and the competition status of the tree in its stand, and (ii) variations in site fertility type and current temperature sum of a stand. Finally, these transfer functions for RSEv were applied to adapt the stem volume growth in the statistical growth and yield model to reflect the response to climate change.     

Can forest management be used to sustain water-based ecosystem services in the face of climate change?

Forested watersheds, an important provider of ecosystems services related to water supply, can have their structure, function, and resulting streamflow substantially altered by land use and land cover. Using a retrospective analysis and synthesis of long-term climate and streamfiow data (75 years) from six watersheds differing in management histories we explored whether streamflow responded differently to variation in annual temperature and extreme precipitation than unmanaged watersheds. We show significant increases in temperature and the frequency of extreme wet and dry years since the 1980s. Response models explained almost all streamflow variability (adjusted R2 > 0.99). In all cases, changing land use altered streamflow. Observed watershed responses differed significantly in wet and dry extreme years in all but a stand managed as a coppice forest. Converting deciduous stands to pine altered the streamflow response to extreme annual precipitation the most; the apparent frequency of observed extreme wet years decreased on average by sevenfold. This increased soil water storage may reduce flood risk in wet years, but create conditions that could exacerbate drought. Forest management can potentially mitigate extreme annual precipitation associated with climate change; however, offsetting effects suggest the need for spatially explicit analyses of risk and vulnerability.     

Predictability of marine nematode biodiversity

In this paper, we investigated: (1) the predictability of different aspects of biodiversity, (2) the effect of spatial autocorrelation on the predictability and (3) the environmental variables affecting the biodiversity of free-living marine nematodes on the Belgian Continental Shelf. An extensive historical database of free-living marine nematodes was employed to model different aspects of biodiversity: species richness, evenness, and taxonomic diversity. Artificial neural networks (ANNs), often considered as “black boxes”, were applied as a modeling tool. Three methods were used to reveal these “black boxes” and to identify the contributions of each environmental variable to the diversity indices. Since spatial autocorrelation is known to introduce bias in spatial analyses, Moran's I was used to test the spatial dependency of the diversity indices and the residuals of the model. The best predictions were made for evenness. Although species richness was quite accurately predicted as well, the residuals indicated a lack of performance of the model. Pure taxonomic diversity shows high spatial variability and is difficult to model. The biodiversity indices show a strong spatial dependency, opposed to the residuals of the models, indicating that the environmental variables explain the spatial variability of the diversity indices adequately. The most important environmental variables structuring evenness are clay and sand fraction, and the minimum annual total suspended matter. Species richness is also affected by the intensity of sand extraction and the amount of gravel of the sea bed.     

A dynamic host selection model for mountain pine beetle,Dendroctonus ponderosae Hopkins

The link between individual habitat selection decisions (i.e., mechanism) and the resulting population distributions of dispersing organisms (i.e., outcome) has been little-studied in behavioural ecology. Here we consider density-dependent habitat (i.e., host) selection for an energy- and time-limited forager: the mountain pine beetle (Dendroctonus ponderosae Hopkins). We present a dynamic state variable model of individual beetle host selection behaviour, based on an individual’s energy state. Field data are incorporated into model parameterization which allows us to determine the effects of host availability (with respect to host size, quality, and vigour) on individuals’ decisions. Beetles choose larger trees with thicker phloem across a larger proportion of the state-space than smaller trees with thinner phloem, but accept lower quality trees more readily at low energy- and time-states. In addition, beetles make habitat selection decisions based on host availability, conspecific attack densities, and beetle distributions within a forest stand. This model provides a framework for the development of a spatial game model to examine the implications of these results for attack dynamics of beetle populations.     

Introducing effects of temperature and CO2 elevation on tree growth into a statistical growth and yield model

Impacts of elevated temperature and CO₂ on tree growth were introduced into a statistical growth and yield model for Finnish conditions based on corresponding predictions obtained from a physiological growth model. This one-way link between models was made by means of species-specific transfer functions describing the increase in stem volume growth of trees as a function of elevated temperature and CO₂, stand density and the tree's competition status in a stand of Scots pine (Pinus sylvestris), silver birch (Betula pendula) and Norway spruce (Picea abies). This method allows the inner dynamics of the statistical model to be followed when the impacts of temperature and CO₂ elevation on tree growth are introduced into the calculation of volume growth and further allocated between diameter and height growth. In this way compatibility with previous predictions of tree growth by means of statistical models and related model systems under current climatic conditions could be retained.The performance of the statistical model with species-specific transfer functions was evaluated by comparing its predictions with corresponding predictions given by a physiological model under conditions of elevated temperature and CO₂. These calculations revealed that the growth response of individual trees to elevated temperature and CO₂ can be introduced into the statistical model from a physiological growth model with an outcome that results in fairly satisfactory growth responses at the stand level as well.     

More asymmetric tree competition brings about more evapotranspiration and less runoff from the forest ecosystems: A simulation study

The present paper reports how stand size-structure dynamics due to competition between different-sized trees affect long-term forested water balance in Japanese cool-temperate planted stands (evergreen coniferous Cryptomeria japonica and deciduous coniferous Larix kaempferi stands) using a fully coupled multi-layered meteorological surface physics—terrestrial ecosystems model. The simulation captured the well-known annual variation in leaf area index (LAI) accurately with stand age in monocultured and even-aged stands; the occurrence of maximum LAI during the early growth stage and then a gradual decline followed by a steady state after the maximum LAI. The simulations also detected a high dependency of annual evapotranspiration (AETr) on LAI with stand age that is well known by prior observational researches. In the C. japonica (shade-tolerant late-successional species) stand, the relationship between annual net primary productivity of an individual tree (NPP_ind) and individual tree mass (w) changed from linear to a convex curve during self-thinning, indicating that the degree of asymmetric tree competition intensified with forest stand development. The higher degree of competitive asymmetry characterized by the convex-shaped NPPind-w relationship produced greater size inequality, i.e., the formation of trees stratified by height. Under such conditions, AETr and annual transpiration (ATr) were mainly regulated by larger trees. On the other hand, the NPPind-w relationships in the L. kaempferi (shade-intolerant early-successional species) stand were linear throughout the simulated period, indicating the lower degree of competitive asymmetry. Under such conditions, the growth of intermediate-sized trees was enhanced and these trees became a dominant source of AETr (and also ATr) during self-thinning. Furthermore, the sensitivity analysis of the effects of ecophysiological parameters such as foliage profile (i.e., vertical distribution of leaf area density) of an individual tree (distribution pattern is described by the parameter η), the maximum carboxylation velocity (V_cmax0) and biomass allocation pattern of individual plant growth (μ₁) on AETr, ATr and annual runoff (AR_off) showed that the temporal trends of AETr, ATr, AR_off and NPPind-w relationships were completely the same as those in the control simulations. However, the NPPind-w relationship during self-thinning indicated higher degrees of competitive asymmetry when η or V_cmax0 were greater than those in the control simulation and generated greater AETr and ATr and thus smaller AR_off. We found that more asymmetric tree competition brings about greater size inequality between different-sized trees and thus more evapotranspiration and less runoff in a forest stand. Overall, our simulation approach revealed that not only LAI dynamics but also plant competition, and thus size-structure dynamics, in a forest ecosystem are essential to long-term future projections of forested water balance.     

A simplified approach to implement forest eco-hydrological properties in regional hydrological modelling

The topic of this paper is a simplified model for simulating the hydrological properties of forest stands based on a robust computation of the temporal LAI (leaf area index) dynamics. The approach allows the simulation of all hydrologically relevant processes. It includes interception of precipitation and transpiration of forest stands with and without groundwater in the rooting zone. The model also considers phenology, mortality and simple management practice. It was implemented as a module in the eco-hydrological model SWIM (Soil and Water Integrated Model). The approach was tested on Scots pine (Pinus sylvestris) and common oak (Quercus robur and Q. petraea).The results demonstrate a good simulation of annual biomass increase and LAI and satisfactory simulation of litter production (annual mean value). A comparison of the date of May sprout for Scots pine and leaf unfolding for Oak (1980–1990) with observed data of the DWD (German Weather Service) shows a good reproduction of the temporal dynamic. The daily simulation of transpiration shows an excellent correlation of r = 0.81 for the year 1998 but only r = 0.65 for 1999. The interception losses were also simulated and compared with weekly observed data showing satisfactory results in the vegetation periods and annual sums, but worse agreement in autumn and spring time. A regional assessment study was done in the federal state of Brandenburg (Germany) to test the applicability and multi-criteria evaluation capabilities of the approach on the landscape and catchments scale using forest data, daily river discharge and regional water balance.     

Spatial cross-correlation of undisturbed,natural shortleaf pine stands in northern Georgia

In this study a cross-correlation statistic is used to analyse the spatial relationship among stand characteristics of natural, undisturbed shortleaf pine stands sampled during 1961–72 and 1972–82 in northern Georgia. Stand characteristics included stand age, site index, tree density, hardwood competition, and mortality. In each time period, the spatial cross-correlation statistic was used to construct cross-correlograms and cumulative cross-correlograms for all significant pairwise combination of stand characteristics. Both the cross-correlograms and cumulative cross-correlograms identified small-scale clustering and weak directional gradients for different stand characteristics in each time period. The cumulative cross-correlograms, which are based on inverse distance weighting were more sensitive in detecting small-scale clustering than the cross-correlograms based on a 0–1 weighting. Further analysis suggested that the significant cross-correlation observed among basal area growth and other stand characteristics were due, in a large part, on a subset of sample plots located in the northern part of the state, rather than regional or broad-scale variation as first thought. The ability to analyse the spatial relationship between two or more response surfaces should provide valuable insight in the development of ecosystem level models and assist decision makers in formulating pertinent policy on intelligent multiresource management.     

Climate, canopy conductance and leaf area development controls on evapotranspiration in a boreal coniferous forest over a 10-year period: A united model assessment

The aim of this work was to test a process-based model (hydrological model combined with forest growth model) on the simulation of seasonal variability of evapotranspiration (ET) in an even-aged boreal Scots pine (Pinus sylvestris L.) stand over a 10 year period (1999-2008). The water flux components (including canopy transpiration (E_t) and evaporation from canopy (E_c) and ground surface (E_g) were estimated in order to output the long-term stand water budget considering the interaction between climate variations and stand development. For validation, half-hourly data on eddy water vapor fluxes were measured during the 10 growing seasons (May-September). The model predicted well the seasonal course of ET compared to the measured values, but slightly underestimated the water fluxes both in non-drought and drought (2000, 2003 and 2006) years. The prediction accuracy was, on average, higher in drought years. The simulated ET over the 10 years explained, on average, 58% of the daily variations and 84% of the monthly amount of ET. Water amount from E_t contributed most to the ET, with the fractions of E_t, E_c and E_g being, on average, 67, 11 and 23% over the 10-year period, respectively. Regardless of weather conditions, the daily ET was strongly dependent on air temperature (T_a) and vapor pressure deficit (D_a), but less dependent on soil moisture (W_s). On cloudy and rainy days, there was a non-linear relationship between the ET and solar radiation (R_o). During drought years, the model predicted lower daily canopy stomatal conductance (g_cs) compared with non-drought years, leading to a lower level of E_t. The modeled daily g_cs responded well to D_a and W_s. In the model simulation, the annual LAI increased by 35% between 1999 and 2008. The ratio of E_c: ET correlated strongly with LAI. Furthermore, LAI reduced the proportion of E_g as a result of the increased share of E_c and E_t and radiation interception. Although the increase of LAI affected positively E_t, the contribution of E_t in ET was not significantly correlated with LAI. To conclude, although the model predicted reasonably well the seasonal course of ET, the calculation time steps of different processes in the model should be homogenized in the future to increase the prediction accuracy.     

Neighborhood effects on seed dispersal by frugivores: testing theory with a mistletoe-marsupial system in Patagonia

The outcome of the dispersal process in zoochorous plants is largely determined by the behavior of frugivorous animals. Recent simulation studies have found that fruit removal rates and mean dispersal distances are strongly affected by fruiting plant neighborhoods. We empirically tested the effects of conspecific fruiting plant neighborhoods, crop sizes, and plant accessibility on fruit removal rates and seed dispersal distances of a mistletoe species exclusively dispersed by an arboreal marsupial in Northern Patagonia. Moreover, in this study, we overcome technical limitations in the empirical estimation of seed dispersal by using a novel 15N stable isotope enrichment technique together with Bayesian mixing models that allowed us to identify dispersed seeds from focal plants without the need of extensive genotyping. We found that, as predicted by theory, plants in denser neighborhoods had greater fruit removal and shorter mean dispersal distances than more isolated plants. Furthermore, the probability of dispersing seeds farther away decreased with neighborhood density. Larger crop sizes resulted in larger fruit removal rates and smaller probabilities of longer distance dispersal. The interplay between frugivore behavioral decisions and the spatial distribution of plants could have important consequences for plant spatial dynamics.     

ANAFORE: A stand-scale process-based forest model that includes wood tissue development and labile carbon storage in trees

A stand-scale forest model has been developed that dynamically simulates, besides carbon (C) and water (H₂O) fluxes, wood tissue development from physiological principles. The forest stand is described as consisting of trees of different size cohorts (for example, dominant, co-dominant and suppressed trees), either of the same or of different species (deciduous or coniferous). Half-hourly C and H₂O fluxes are modeled at the leaf, tree and stand level. In addition to total growth and yield, the model simulates the daily evolution of tracheid or vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition and density are calculated. Simulation of the labile C stored in the living tissues allows for simulation of trans-seasonal and trans-yearly effects, and improved simulations of long-term effects of environmental stresses on growth. A sensitivity analysis was performed to indicate the main parameters influencing simulated stem growth and wood quality at the tree and stand level. Case studies were performed for a temperate pine forest to illustrate the main model functioning and, more in particular, the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for simultaneous analyses of wood quality development and forest ecosystem functioning.     

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.