Search

A grid-based, spatially-explicit Regional Organism Exchange (ROE) model is presented as a framework for integrating aquatic ecosystems and fish population processes at the landscape level. Active fish movements across a grid cell boundary were predicted, based on environmental tolerance ranges. The model was designed to be easily modified for any aquatic system, migratory life-stage, or trophic community. ROE was specifically developed to understand how large-scale physical patterns (i.e., tidal and freshwater intrusions) and landscape biological processes (i.e., primary production and foraging behavior) control migration of stenohaline fishes in the estuarine lagoon of Laguna de Terminos, Mexico. A migration response matrix for temperature, salinity, food availability, birth, and mortality was used to control cell-to-cell population movements. Internal cell processes included logistic population growth, trophic interactions, and ecosystem feedback parameters. Output data maps from the ROE model showed how population spatial distributions were linked to spatial and temporal patterns of water quality. However, the most significant parameter affecting long-term population stability was birth rate; an internal cell variable. It was concluded that the simulation of large, density-dependent, spatial processes such as migration can be understood with a grid-based mechanistic ROE model because its rule-based design for movement allowed organisms to respond to ecological processes and adjust to changing environmental conditions.

A spatial model of long term habitat succession at a degrading Louisiana wetland was constructed based upon simulating exchanges across irregularly shaped polygons. Polygons represented the natural morphology which is indicative of the natural landscape. The PBS model was partially successful in simulating spatial habitat changes over a 28-year period when more than 1000 ha of wetland loss occurred (r2=.56). General landscape trends did, however, emerge from the model development. Areas of high annual water level fluctuations, and high primary productivity were less likely to change from wetlands to open water and were most likely to recover if altered. We discuss the potential for predictive improvement and for integration with polygon-based geographic information systems, and conclude that a PBS model demonstrates the need for spatially explicit landscape management.

Water management infrastructure and operations have fragmented the greater Everglades into separate, impounded basins, altering flows and hydropatterns in these internationally recognized wetlands. A significant area of this managed system has experienced anthropogenic eutrophication. This combination of altered hydrology and water quality has interacted to degrade vegetative habitats and other ecological characteristics of the Everglades. As part of a massive plan to “restore” the Everglades, simulation models are being applied to better understand the system’s hydrologic and ecological dynamics, evaluating options for restoration plans. One such tool is the Everglades Landscape Model (ELM), a process-based, spatially explicit simulation of ecosystem dynamics across a heterogeneous, 10,000 km region. The model development has proceeded in tandem with advances in Everglades research, improving its algorithms and calibration to best capture dynamics of key landscape attributes. The first spatial application of the model was in an intensively studied subregion along an anthropogenic nutrient gradient. The model captured the spatiotemporal dynamics of hydrology, surface and ground water phosphorus, periphyton biomass and community type, macrophyte biomass and habitat type, and peat accumulation. Refinements to the model have improved its hydrologic and ecological performance, with good calibrations of long term hydrologic and surface water quality dynamics across most of the Everglades landscape. Using this updated version, we evaluated phosphorus loading throughout the Everglades system under two base scenarios. The 1995 base case assumed current management operations, with phosphorus inflow concentrations fixed at their long term, historical average. The 2050 base case assumed future modifications in water management, with all managed inflows to the Everglades having reduced phosphorus concentrations (due to filtering by constructed wetlands). In an example “indicator” subregion that currently is highly eutrophic, the 31-yr simulations predicted that desirable periphyton and macrophyte communities were maintained under the 2050 base case, whereas in the 1995 base case, periphyton biomass and production decreased to negligible levels and macrophytes became extremely dense. The negative periphyton response in the 1995 base case was due to high phosphorus loads and rapid macrophyte growth that shaded this algal community. Along an existing 11 km eutrophication gradient, the model indicated that the 2050 base case had ecologically significant reductions in phosphorus accumulation compared to the 1995 base case. Indicator regions (in Everglades National Park) distant from phosphorus inflow points also exhibited reductions in phosphorus accumulation under the 2050 base case, albeit to a lesser extent due to its distance from phosphorus inflows. The ELM fills a critical information need in Everglades management, and has become an accepted tool in evaluating scenarios of potential restoration of the natural system. Refinements to the model will enable us to evaluate the full suite of ecological responses to management scenarios throughout the greater Everglades.

Periphyton is a key component of the Everglades ecosystems. It is a major primary producer, providing food and habitat for a variety of organisms, contributing material to the surface soil, and regulating water chemistry. Periphyton is sensitive to the phosphorus (P) supply and P enrichment has caused dramatic changes in the native Everglades periphyton assemblages. Periphyton also affects P availability by removing P from the water column and depositing a refractory portion into sediment. A quantitative understanding of the response of periphyton assemblages to P supply and its effects on P cycling could provide critical supports to decision making in the conservation and restoration of the Everglades. We constructed a model to examine the interaction between periphyton and P dynamics. The model contains two differential equations: P uptake and periphyton growth are assumed to follow the Monod equation and are limited by a modified logistic equation. Equilibrium and stability analyses suggest that P loading is the driving force and determines the system behavior. The position and number of steady states and the stability also depend upon the rate of sloughing, through which periphyton deposits refractory P into sediment. Multiple equilibria may exist, with two stable equilibria separated by an unstable equilibrium. Due to nonlinear interplay of periphyton and P in this model, catastrophe and hysteresis are likely to occur.

Tree islands are a feature of many large, flat wetlands. They develop in these wetlands around some point of formation. Points of formation can include topographic highs in the bedrock, blocks of floating peat and depressions in the bedrock. Their point of formation can even be the result of human activities. The flora and fauna of tree islands are not unique, but are a subset of those in surrounding areas. This chapter summarizes what we know about the origin, development and human use of tree islands. Tree islands are important to the Everglades because: 1) they are a major spatial feature of the landscape and provide much of its biocomplexity. 2) they enable many terrestrial plant and animal species to live in the Everglades ecosystem. 3) they are essential for many groups of wetland animals and birds during part of their life cycle, especially for nesting. 4) they concentrate nutrients and may play an important role in the overall nutrient dynamics of the Everglades ecosystem, and 5) they preserve important archaeological and cultural features of South Florida.

This book provides basic information about the geology, ecology, and human use of tree islands. This information is needed to develop sound environmental policy and water management for the preservation and restoration of tree islands in the Everglades, and it provides a sound basis for tree island management and protection in the Everglades and other wetlands with tree islands throughout the world. This chapter provides a context for the rest of the book and a framework for understanding the current status of tree islands, including a consideration of their location and significance in the Everglade’s landscape, theories about their origin and development, historic trends in their abundance and restoration goals for them within the Comprehensive Everglades Restoration Plan (CERP).

The Florida Everglades, a vast wetland dotted with diverse tree islands, is a uniquely difficult wetland to manage because of competing urban, agricultural and environmental water demands. Tree islands in certain sections of the Everglades have experienced altered hydroperiod due to water management practices that has, at times, caused tree island vegetation to die. This study uses the Everglades Landscape Vegetation Model (ELVM) to investigate whether an observed trend in tree island loss is reversible, and if tree islands can be used as performance measures or ecological indicators for the success of Everglades restoration actions. The ELVM was developed and designed to be a tool to understand the spatial and temporal interactions among vegetation, water, fire and nutrients. Simulation results from this model suggest that hydroperiod is a major factor contributing to tree island development and stability in the Everglades. Simulations of the ELVM indicated that tree island water depths greater than 30 cm and hydroperiods longer than 150 days were decreasing tree island survival rates. According to the model, about 60% of tree islands lost in the Water Conservation Area 2A (WCA-2A) in the last few decades can be recovered by restoring the natural hydrological regimes. As a result, tree island health could be used as a performance measure to evaluate the effects of various hydrological restoration alternatives in the Everglades.

Models are usually developed for one of two purposes: to better understand ecological systems or to evaluate the influence of an altered condition to make a decision or set policy. A spatial model can loosely be defined as one that has either one or more state variables that are a function of space or can be related to other space-dependent variables. The information-richness of spatial data and models comes from their simultaneous depiction of temporal and spatial patterns. This richness is easily grasped by only the most powerful of all computers, the mind. For example, the mind can immediately compare a temperature map of today with the map from the day before and quickly develop a spatial trend analysis for areas of change. Put three maps together and the mind computer may even venture to predict areas cooling down or warming up. It does this easily, with no thought of the spatial distribution of weather stations, kriging techniques, data collection errors, the influence of scale, or knowledge of meteorological models, yet these things and more are all factors that contribute to the spatial uncertainty of this mental model. These uncertainties become extremely important when one tries to formalize and quantify this spatial modeling process for prediction.

/ Freshwater inflow is one of the most influential landscape processes affecting community structure and function in lagoons, estuaries, and deltas of the world; nevertheless there are few reviews of coastal impacts associated with altered freshwater inputs. A conceptual model of the possible influences of freshwater inflows on biogeochemical and trophic interactions was used to structure this review, evaluate dominant effects, and discuss tools for coastal management. Studies in the Gulf of Mexico were used to exemplify problems commonly encountered by coastal zone managers and scientists around the world. Landscape alteration, impacting the timing and volume of freshwater inflow, was found to be the most common stress on estuarine systems. Poorly planned upstream landscape alterations can impact wetland and open-water salinity patterns, nutrients, sediment fertility, bottom topography, dissolved oxygen, and concentrations of xenobiotics. These, in turn, influence productivity, structure, and behavior of coastal plant and animal populations. Common biogeochemical impacts include excessive stratification, eutrophication, sediment deprivation, hypoxia, and contamination. Common biological impacts include reduction in livable habitats, promotion of "exotic" species, and decreased diversity. New multiobjective statistical models and dynamic landscape simulations, used to conduct policy-relevant experiments and integrate a wide variety of coastal data for freshwater inflow management, assume that optimum estuarine productivity and diversity is found somewhere between the stress associated with altered freshwater flow and the subsidy associated with natural flow. These models attempt to maximize the area of spatial overlap where favorable dynamic substrates, such as salinity, coincide with favorable fixed substrates, such as bottom topography. Based upon this principle of spatial overlap, a statistical performance model demonstrates how population vitality measurements (growth, survival, and reproduction) can be used to define sediment, freshwater, and nutrient loading limits. Similarly, a spatially articulate landscape simulation model demonstrates how cumulative impacts and ecosystem processes can be predicted as a function of changes in freshwater, sediment, and nutrient inflows.KEY WORDS: Resource management; Landscape impacts; Freshwater discharge; Coastal, ecosystem models; Coastal wetlands

We used enclosures to quantify wetland-water column nutrient exchanges in a dwarf red mangrove, (Rhizophora mangle L.) system near Taylor River, an important hydraulic linkage between the southern Everglades and eastern Florida Bay, Florida, USA. Circular enclosures were constructed around small (2.5–4 m diam) mangrove islands (n=3) and sampled quarterly from August 1996 to May 1998 to quantify net exchanges of carbon, nitrogen, and phosphorus. The dwarf mangrove wetland was a net nitrifying environment with consistent uptake of ammonium (6.6–31.4 μmol m−2 h−1) and release of nitrite +nitrate (7.1–139.5 μmol m−2 h−1) to the water column. Significant flux of soluble reactive phosphorus was rarely detected in this nutrient-poor, P-limited environment. We did observe recurrent uptake of total phosphorus and nitrogen (2.1–8.3 and 98–502 μmol m−2 h−1, respectively), as well as dissolved organic carbon (1.8–6.9 μmol m−2 h−1) from the water column. Total organic carbon flux shifted unexplainably from uptake, during Year 1, to export, during Year 2. The use of unvegetated (control) enclosures during the second year allowed us to distinguish the influence of mangrove vegetation from soil-water column processes on these fluxes. Nutrient fluxes in control chambers typically paralleled the direction (uptake or release) of mangrove enclosure fluxes, but not the magnitude. In several instances, nutrient fluxes were more than twofold greater in the absence of mangroves, suggesting an influence of the vegetation on wetland-water column processes. Our findings characterize wetland nutrient exchanges, in a mangrove forest type that has received such little attention in the past, and serve as baseline data for a system undergoing hydrologic restoration.

The complex interaction of a daily temporally fixed sampling design with seasonal, tidal, and diurnal cycles can result in serious aliasing and reduced usefulness of estuarine data. The choice of appropriate sampling windows for data grouping and analysis of tidally influenced data is complex and must take into account both solar and lunar influences and their interactions in order to represent actual estuarine conditions. A fixed modulus for grouping or time-series analysis introduces errors. Grouping data by calendar month can be misleading since calendar months may have as many as three or as few as one spring tide. Daily measurements of salinity and water clarity at a fixed time of day were analyzed to illustrate the effects of aliasing. Although the length of synodical (lunar) months is also variable, a seasonally adjusted grouping variable based on solar and synodical month (MO-DAY), created to partially correct for aliasing, was found to be an efficient way to remove short-term cycles for the identification of long-term trends, episodic events, and spatial patterns.

Turner, M.G., Costanza, R. and Sklar, F.H., 1989. Methods to evaluate the performance of spatial simulation models. EcoL Modelling, 48: 1-18. Quantitative methods are necessary to compare spatial patterns and evaluate the performance of spatial simulation models. We present and review several approaches to the analysis and comparison of spatial patterns. The methods are readily applicable to digital data that are in matrix (i.e., grid cell or raster) format, and include: (a) indices of particular aspects of spatial pattern, including fractal dimension, contagion, and interface; (b) spatial predictability; and (c) a variable resolution approach for measuring the degree of fit between two patterns. Because these methods measure different aspects of spatial patterns, they may be differentially suited to particular modeling and analysis objectives. In this paper, we describe the methods, apply each method to a sample data set, then evaluate the information provided and appropriate situations for its use.

Core and floating “scoop” samples were taken monthly for two years in a Louisiana hardwood swamp for the characterization and identification of the benthic habitats far removed from waterways and bayous. Most backswamp macroinvertebrates have physiological and behavorial adaptations to withstand both desiccation and anoxia. The most ubiquitous taxa included amphipods, oligochaetes, diptera larvae, isopods, and fingernail clams. The biomass and density of backswamp benthic communities were some of the highest recorded for any “unpolluted” freshwater or estuarine soft-bottom habitat. The average number of invertebrates living in the sediments (5,690/m2) was significantly less than the numbers living in the floating mats ofLemna spp. (10,508/m2). The biomass distribution was just the opposite. There was a significantly greater invertebrate biomass in the sediments (8.4 g AFDW/m2) than in the floating vegetation (4.2 g AFDW/m2). Diversity (H) was relatively low, averaging only 1.8 in the floating vegetation and 1.4 in the sediments. Seasonal changes in density, biomass, and diversity were bimodal with peaks occuring during spring and fall, and were a function of the seasonality of wetland flooding and temperature.

To adequately model many ecological systems and management problems, spatial dynamics need to be treated explicitly. A dynamic spatial simulation model composed of interacting cells was designed to project habitat changes as a function of marsh type, hydrology, subsidence, and sediment transport for a generalized coastal wetland area. The model with nine interacting cells was developed to test mathematical formulations and computer algorithms, and to help explain model structure and behavior. Each cell in the model is classified and assigned a habitat parameter ‘signature’ corresponding to a multidimensional niche space. Large-scale habitat changes (‘succession’) occur in the model when water and material fluxes between cells produce storages corresponding to the signature of a new habitat. After some time lag to reflect successional changes, the cell parameters are changed to reflect the new habitat signature. In this manner the model can be used to project the impact of natural and man-made changes (i.e., levees, canals) to the system on the spatial distribution and productivity of the various habitats.

Large quantities of the organophosphate Guthion®, used to control insect infestations on large Louisiana plantations, can potentially enter surrounding wetland habitats and impact commercially important crayfish populations. The adsorption of Guthion to plant oils and organic sediments means that its impact on crayfish will include, and possibly be dominated by, its oral rather than dermal toxicity. Guthion was tested for acute and chronic oral toxicity with the red swamp crayfish Procambarus clarkii . The 48 h LD 50 of Guthion for adult crayfish was 1·9 mg kg −1 crayfish and was substantially higher than published dermal toxicity values. Chronic effects, tested at 25 μg kg −1 of crayfish food for 8 months, had no effect on growth rates. However, the rate of senescence increased for those crayfish fed Guthion-contaminated food. Treated crayfish began to die 2–3 months before their control counterparts. This was a life-span reduction of 15–20% for the males and 7–10% for the females. It is recommended that the establishment of runoff standards for organophosphates be based on the response of ecologically significant aquatic invertebrates to chronic contamination, both in the water and on food substances.

Due to large reserves of second-growth cypress ( Taxodium distichum and T. distichum var. nutans ) in the southeastern United States, logging of cypress is once again becoming attractive. This increased activity has led to the question of whether adequate natural regeneration will be established after logging. Four logged cypress stands in the Barataria Basin region of Louisiana were sampled to determine vegetation characteristics and survival and growth of baldcypress seedlings and stump sprouts. Coppice regeneration was prolific during the first year after cutting, however, most of the sprouts died in the following years. In addition, even though observations were made during a particularly dry year, no seedling establishment occurred.

Eighty-seven mathematical models of freshwater wetlands and shallow water bodies were classified by wetland type, location, and degree of nonlinearity, and rated by three new indices: articulation; accuracy; and effectiveness. Articulation measures the size and complexity of the model in the three modes of components, space, and time. Accuracy combines measures of goodness-of-fit in each mode. Effectiveness measures explanatory power as a combination of articulation and accuracy. For the models reviewed accuracy was seen to fall with increasing articulation, probably as a result of increasing complexity and cost. Effectiveness, however, rose to a maximum at intermediate articulation and then fell, reflecting the fact that highly accurate models tended to be low in articulation (they said much about little), while highly articulate models tended to be low in accuracy (they said little about much). These methods for ranking models may prove useful for further analysis and the results of this analysis may provide a useful guide to model builders concerned with maximizing the effectiveness of their models using limited resources.

Measurements of tree growth, leaf litter production, aquatic respiration, decomposition rates, benthic invertebrates and floating communities of plants and animals were taken from an impounded cypress-tupelo swamp of the Upper Barataria Basin. A dynamic computer simulation model was designed to identify the significant associations among the aquatic components as a function of environmental forcing functions (i.e. temperature, surplus precipitation, water flow, extent of dry season), and biological parameters (i.e. growth rates, predator-prey relations, assimilation efficiences). It was also developed to predict the response of an impounded swamp habitat to various management options, especially manipulation of the hydrologic regimes. Swamp impoundments, for example, were found to increase their annual energy exports by 43% when spoil banks were removed. Results indicate the sensitivity of swamp ecosystem response to changes in hydrology and the options for management of swamp ecosystems.

A spatial simulation model was constructed to help understand the historical changes in the Atchafalaya/Terrebonne marsh/estuarine complex in south Louisiana and to project impacts of proposed human modifications. The model consists of almost 3,000 interconnected cells each representing 1 km 2. Each cell in the model contains a dynamic, nonlinear, simulation model. Variables include water volume and flow, sediment and salt concentrations, organic standing crop, and productivity. The balance between sediment deposition and erosion as influenced by these variables in this rapidly subsiding area is particularly critical to habitat succession and the productivity of the area. Primary input data for the model were detailed, digitized habitat maps prepared by the U.S. Fish and Wildlife Service for 1956 and 1978. In addition, long time series of field measurements are available for some variables. The data base assembled for the model includes annual changes in environmental forcing functions, such as river discharge, and human modifications, such as canals and levees. At present, we are in the preliminary stages of running and calibrating the model. Our current results mimic the spatial seasonal patterns of sediment, salinity and water flow reasonably well. Starting with the 1956 initial conditions the model correctly predicts the habitat type in 1978 of 68% of the almost 3000 cells. Changes in salinity zones were accurately predicted but the model predicts higher land loss rates in the fresh zone than those actually observed and does not do well at predicting the growth of the Atchafalaya delta. The former problem may have to do with the prevalence of floating marsh in the fresh zone, which the model does not adequately consider at present. This paper discusses: (1) the structure of the model; (2) the spatial data base necessary to run the model; (3) some preliminary results concerning the temporal and spatial distributions of some of the state variables; and (4) future directions for the model. In general, this approach seems to be applicable to modeling spatial ecosystem dynamics, but the size and computational complexity of the model makes calibration and verification difficult.

A spatial simulation model was constructed to help understand the historical changes in the Atchafalaya/Terrebonne marsh/estuarine complex in south Louisiana and to project impacts of proposed human modifications. The model consists of 2,479 interconnected “lcells,” each representing 1 square km. Each cell in the model contains a dynamic, nonlinear, simulation model that has evolved out of the modelling work mentioned in the previous chapter. Variables include water volume and flow, relative elevation, sediment, nutrient, and salt concentrations, organic standing crop, and productivity. The model produces weekly maps of all the state variables and habitat types. Habitat succession occurs in a cell in the model when physical conditions change sufficiently, so that the new conditions better match the “signature” of another habitat. In this chapter we: 1) summarize the history of the Louisiana coastal land loss problem and suggested solutions; 2) briefly discuss the model's structure, data base, and degree of fit with historical data; 3) discuss the uses and implications of the model, particularly as regards the estimation of the impacts of canals and levees on coastal marsh systems; and 4) outline the potential interface between the model and management agencies to provide solutions to pressing coastal management problems.

We have developed a General Ecosystem Model (GEM) that is designed to simulate a variety of ecosystem types using a fixed model structure. Driven largely by hydrologic algorithms for upland, wetland and shallow-water habitats, the model captures the response of macrophyte and algal communities to simulated levels of nutrients, water, and environmental inputs. It explicitly incorporates ecological processes that determine water levels, plant production, nutrient cycling associated with organic matter decomposition, consumer dynamics, and fire. While the model may be used to simulate ecosystem dynamics for a single homogenous habitat, our primary objective is to replicate it as a “unit” model in heterogeneous, grid-based dynamic spatial models using different parameter sets for each habitat. Thus, we constrained the process (i.e., computational) complexity, yet targeted a level of disaggregation that would effectively capture the feedbacks among important ecosystem processes. A basic version was used to simulate the response of sedge and hardwood communities to varying hydrologic regimes and associated water quality. Sensitivity analyses provided examples of the model dynamics, showing the varying response of macrophyte production to different nutrient requirements, with subsequent changes in the sediment water nutrient concentrations and total water head. Changes in the macrophyte canopy structure resulted in differences in transpiration, and thus the total water levels and macrophyte production. The GEM's modular design facilitates understanding the model structure and objectives, inviting variants of the basic version for other research goals. Importantly, we hope that the generic nature of the model will help alleviate the “reinventing-the-wheel” syndrome of model development, and we are implementing it in a variety of systems to help understand their basic dynamics.