Origins and scales of hypoxia on the Louisiana shelf: Importance of seasonal plankton dynamics and river nutrients and discharge

Management plans for the Mississippi River Basin call for reductions in nutrient concentrations up to 40% or more to reduce hypoxia in the Gulf of Mexico (GOM), while at the same time the government is considering new farm subsidies to promote development of biofuels from corn. Thus there are possibilities of both increasing and decreasing river nutrients depending on national priorities. River flow rates which also influence the extent of hypoxia on the shelf may be altered by global climate change. We have therefore developed a series of simulations to forecast ecosystem response to alterations in nutrient loading and river flow. We simulate ecosystem response and hypoxia events using a linked model consisting of multiple phytoplankton groups competing for nitrogen, phosphorus and light, zooplankton grazing that is influenced by prey edibility and stoichiometry, sub-pycnocline water-column metabolism that is influenced by sinking fecal pellets and algal cells, and multi-element sediment diagenesis. This model formulation depicts four areas of increasing salinity moving westward away from the Mississippi River point of discharge, where the surface mixed layer, four bottom layers and underlying sediments are represented in each area. The model supports the contention that a 40% decrease in river nutrient will substantially reduce the duration and areal extent of hypoxia on the shelf. But it also suggests that in low and middle salinity areas the hypoxia response is saturated with respect to nutrients, and that in high salinity regions small increases in nutrient and river flow will have disproportionally large effects on GOM hypoxia. The model simulations also suggest that river discharge is a stronger factor influencing hypoxia than river nutrients in the Mississippi River plume. Finally, the model simulations suggest that primary production in the low salinity regions is light limited while primary production in the higher salinity zones is phosphate limited during the May to October period when hypoxia is prevalent in the Mississippi River plume.     

Modeling individual and population dynamics in a consumer–resource system: Behavior under food limitation and crowding and the effect on population cycling in Daphnia

In population modeling, a considerable level of complexity is often required to provide trustworthy results, comparable with field observations. By assuring sufficient detail at the individual level while preserving the potential to explore the consequences at higher levels, individual-based modeling may thus provide a useful tool to investigate dynamics at different levels of organization. Still, population dynamics resulting from such models are often at odds with observations from the field. This may be partly caused by a lack of focus on the individual dynamics under conditions of food stress and starvation. I developed a physiologically structured, individual-based simulation model to investigate life history of Daphnia and its effect on population dynamics in response to the productivity of the system. In verifying model behavior with available literature data on life history and physiology, I paid special attention to the dynamics of food intake and the verification of individual level results under conditions of food limitation and starvation. I show that the maximum filtering rates under low food levels used in the current model are much closer to measured filtering rates than the ones used in other models. Being consistent with results on physiology and life history from experiments at a wide range of food availability (including starvation), the model generates low amplitude or high amplitude population density cycles depending on the productivity of the system, as observed in field and experimental populations of Daphnia and with the minimum population densities being one to two orders of magnitude lower in the high amplitude than in the low amplitude cycles. To generate results which are not only qualitatively but also quantitatively comparable to experimental and field observations, however, a crowding effect on the filtering response has to be incorporated in the model.     

气温变化对西南山区流域森林水文效应影响的模拟

为了揭示气温变化对西南山区流域森林水文效应的影响,用生物物理/动态植被模型SSiB4/TRIFFID与流域地形指数水文模型TOPMODEL的耦合模型SSiB4T/TRIFFID模拟了西南山区长江上游梭磨河流域森林水文效应对气温变化的响应,分析了气温变化对植被不同演替阶段的流域总径流和总蒸发以及冠层截流蒸发、植被蒸腾和土壤蒸发的影响。结果表明,（1）梭磨河流域森林（常绿针叶林）蒸腾与草和灌木差异小,森林蒸腾潜热比草和灌木仅高1~4 W.m-2,森林冠层截留蒸发高于草和灌木,但土壤蒸发明显低于草和灌木覆盖,森林覆盖流域总蒸发低于草和灌木覆盖甚至低于裸土蒸发,因此增加了流域总径流量,但森林增加径流的作用随土壤蒸发的减小而减小。（2）气温减小1℃将通过减小森林冠层截留蒸发和蒸腾而使森林增加流域总径流量的作用增加;相反,气温增加将增加森林冠层截留蒸发和蒸腾而使森林增加总径流量的作用减小。（3）当温度增加4℃,由于森林总蒸发较草和灌木明显增加,对于较高的土壤蒸发,森林增加总径流量的作用已不明显;对于较低的土壤蒸发,森林减小了流域总径流量。     

Population dynamics models based on cumulative density dependent feedback: A link to the logistic growth curve and a test for symmetry using aphid data

Density dependent feedback, based on cumulative population size, has been advocated to explain and mathematically characterize “boom and bust” population dynamics. Such feedback results in a bell-shaped population trajectory of the population density. Here, we note that this trajectory is mathematically described by the logistic probability density function. Consequently, the cumulative population follows a time trajectory that has the same shape as the cumulative logistic function. Thus, the Pearl–Verhulst logistic equation, widely used as a phenomenological model for density dependent population growth, can be interpreted as a model for cumulative rather than instantaneous population. We extend the cumulative density dependent differential equation model to allow skew in the bell-shaped population trajectory and present a simple statistical test for skewness. Model properties are exemplified by fitting population trajectories of the soybean aphid, Aphis glycines. The linkage between the mechanistic underpinnings of the logistic probability density function and cumulative distribution function models could open up new avenues for analyzing population data.     

The fire frequency analysis branch of the pyrostatistics tree: sampling decisions and censoring in fire interval data

Statistical characterization of past fire regimes is important for both the ecology and management of fire-prone ecosystems. Survival analysis—or fire frequency analysis as it is often called in the fire literature—has increasingly been used over the last few decades to examine fire interval distributions. These distributions can be generated from a variety of sources (e.g., tree rings and stand age patterns), and analysis typically involves fitting the Weibull model. Given the widespread use of fire frequency analysis and the increasing availability of mapped fire history data, our goal has been to review and to examine some of the issues faced in applying these methods in a spatially explicit context. In particular, through a case study on the massive Cedar Fire in 2003 in southern California, we examine sensitivities of parameter estimates to the spatial resolution of sampling, point- and area-based methods for assigning sample values, current age surfaces versus historical intervals in generating distributions, and the inclusion of censored (i.e., incomplete) observations. Weibull parameter estimates were found to be roughly consistent with previous fire frequency analyses for shrublands (i.e., median age at burning of ~30–50 years and relatively low age dependency). Results indicate, however, that the inclusion or omission of censored observations can have a substantial effect on parameter estimates, far more than other decisions about specifics of sampling.

Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach

Ticks act as vectors of pathogens that can be harmful to animals and/or humans. Epidemiological models can be useful tools to investigate the potential effects of control strategies on diseases such as tick-borne diseases. The modelling of tick population dynamics is a prerequisite to simulating tick-borne diseases and the corresponding spread of the pathogen. We have developed a dynamic model to simulate changes in tick density at different stages (egg, larva, nymph and adult) under the influence of temperature. We have focused on the tick Ixodes ricinus, which is widespread in Europe. The main processes governing the biological cycles of ticks were taken into account: egg laying, hatching, development, host (small, mainly rodents, or large, like deer and cattle, mammals) questing, feeding and mortality. This model was first applied to a homogeneous habitat, where simulations showed the ability of the model to reproduce the general patterns of tick population dynamics. We considered thereafter a multi-habitat model, where three different habitats (woodland, ecotone and meadow) were connected through host migration. Based on this second application, it appears that migration from woodland, via the ecotone, is necessary to sustain the presence of ticks in the meadow. Woodland can therefore be considered as a source of ticks for the meadow, which in turn can be regarded as a sink. The influence of woodland on surrounding tick densities increases in line with the area of this habitat before reaching a plateau. A sensitivity analysis to parameter values was carried out and demonstrated that demographic parameters (sex ratio, development, mortality during feeding and questing, host finding) played a crucial role in the determination of questing nymph densities. This type of modelling approach provides insight into the influence of spatial heterogeneity on tick population dynamics.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.     

Using a fisheries ecosystem model with a water quality model to explore trophic and habitat impacts on a fisheries stock: A case study of the blue crab population in the Chesapeake Bay

Recent calls for the development of ecosystem-based fisheries management compel the development of resource management tools and linkages between existing fisheries management tools and other resource tools to enable assessment and management of multiple impacts on fisheries resources. In this paper, we describe the use of the Chesapeake Bay Fisheries Ecosystem Model (CBFEM), developed using the Ecopath with Ecosim (EwE) software, and the Chesapeake Bay Water Quality Model (WQM) to demonstrate how linkages between available modeling tools can be used to inform ecosystem-based natural resource management. The CBFEM was developed to provide strategic ecosystem information in support of fisheries management. The WQM was developed to assess impacts on water quality. The CBFEM was indirectly coupled with the WQM to assess the effects of water quality and submerged aquatic vegetation (SAV) on blue crabs. The output from two WQM scenarios (1985-1994), a baseline scenario representing actual nutrient inputs and another with reduced inputs based on a tributary management strategy, was incorporated into the CBFEM. The results suggested that blue crab biomass could be enhanced under management strategies (reduced nutrient input) when the effective search rate of blue crab young-of-the-year's (YOY's) predators or the vulnerability of blue crab YOY to its predators was adjusted by SAV. Such model linkages are important for incorporating physical and biological components of ecosystems in order to explore ecosystem-based fisheries management options.