Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon

Fisheries and water resource managers are challenged to maintain stable or increasing populations of Chinook salmon in the face of increasing demand on the water resources and habitats that salmon depend on to complete their life cycle. Alternative management plans are often selected using professional opinion or piecemeal observations in place of integrated quantitative information that could reduce uncertainty in the effects of management plans on population dynamics. We developed a stochastic life cycle simulation model for an endangered population of winter-run Chinook salmon in the Sacramento River, California, USA with the goal of providing managers a tool for more effective decision making and demonstrating the utility of life cycle models for resource management. Sensitivity analysis revealed that the input parameters that influenced variation in salmon escapement were dependent on which age class was examined and their interactions with other inputs (egg mortality, Delta survival, ocean survival). Certain parameters (river migration survival, harvest) that were hypothesized to be important drivers of population dynamics were not identified in sensitivity analysis; however, there was a large amount of uncertainty in the value of these inputs and their error distributions. Thus, the model also was useful in identifying future research directions. Simulation of variation in environmental inputs indicated that escapement was significantly influenced by a 10% change in temperature whereas larger changes in other inputs would be required to influence escapement. The model presented provides an effective demonstration of the utility of life cycle simulation models for decision making and provides fisheries and water managers in the Sacramento system with a quantitative tool to compare the impact of different resource use scenarios.     

Models relating individual and population response to contaminants

Even when present at sub‐lethal levels, toxic compounds have an effect on the dynamics of a population, expressed through altered growth and reproduction rates. We explore some of the potential effects of toxicants on populations, using a simple model that considers a generic toxicant and populations of two species, a primary producer, and a consumer living under food‐limited conditions. The toxicant is assumed to affect the consumers only, and it may enter them either directly from the environment or via their food, the latter opening the possibility of biomagnification. The initial response of the consumer to introduction of a toxicant is invariably a decline in its fecundity and density. However, in the longer term, the equilibrium densities of both producer and consumer may increase or decrease, depending on parameter values and ambient toxicant levels. The surprising case of an increased equilibrium in response to the toxicant occurs if, in the absence of toxicant, the consumers held the producers at a very low level, analogous to ‘overfishing’ in fishery studies. If the toxicant enters the consumer via food, multiple, non‐trivial equilibria are possible. The complex, but interpretable, dynamics exhibited by these simple models will be used to guide studies with more realistic models, for whose development this study forms a prelude.     

Modelling and assessment of South African elephant Loxodonta africana population persistence

The use of a quantitative population growth model to investigate the persistence of South African elephant populations is explored. The model provides quantitative assessments of population persistence and confidence intervals for estimated parameters based purely on population size estimates. The analysis supports the view that most of the larger populations in the region are secure. This view is further supported by a lack of density dependent effects in most of the recovering populations and the high population rates of increase observed. This predominantly positive prognosis is in contrast with that emerging from most of the rest of the African continent where the populations are under greater threat because of habitat restriction and direct human conflict. This preliminary assessment of elephant population persistence suggests that “viable” populations may lie between 400 and 6000 individuals. Although not inconsistent with information-greedy genetic and demographic models, the relationship between population growth versus genetic and demographic models should be further investigated. The implementation of a metapopulation management strategy towards these smaller populations is advocated. In addition, as all of the populations included in this analysis have been afforded some degree of protection since the 1920s, continued protection would be a prerequisite for their continued survival.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

An object oriented modelling strategy to depict activity pattern of organisms in heterogeneous environments

The object oriented programming and simulation approach has been used at the Project Center for Ecosystems Research (Kiel) in order to advance ecological theory and in order to integrate empirical ecological field work. In this contribution we present a general scheme, which provides a framework for the development of individual based models. The scheme covers a general layout of the organism – environment interaction; the organization of (quasi‐)parallel activities of individuals (self‐scheduling of objects versus list processing); a concept to coordinate context specific activity alternatives. Basing on these considerations we give different application examples. These examples show the potential of individual based modelling to depict the modification of organismic activity pattern and population dynamics in heterogeneous environments and to study the interaction of different levels of aggregation. The model examples are simulation of a fish school in a changing environment; simulation of a robin population in a beech forest; simulation of plant development.     

Spatial modeling of rat bites and prediction of rat infestation in Peshawar valley using binomial kriging with logistic regression

In this study, we propose to develop a geostatistical computational framework to model the distribution of rat bite infestation of epidemic proportion in Peshawar valley, Pakistan. Two species Rattus norvegicus and Rattus rattus are suspected to spread the infestation. The framework combines strengths of maximum entropy algorithm and binomial kriging with logistic regression to spatially model the distribution of infestation and to determine the individual role of environmental predictors in modeling the distribution trends. Our results demonstrate the significance of a number of social and environmental factors in rat infestations such as (I) high human population density; (II) greater dispersal ability of rodents due to the availability of better connectivity routes such as roads, and (III) temperature and precipitation influencing rodent fecundity and life cycle.     

Evaluation of Ecologically Relevant Bioassays for a Lotic System impacted by a Coal-mine effluent, using Isonychia

Many studies investigating the ecotoxicological impacts of industrial effluents on fresh-water biota utilize standardized test species such as the daphnids, Ceriodaphnia dubia, Daphnia magna, and the fathead minnow, Pimephales promelas. Such species may not be the most predictive or ecologically relevant gauges of the responses of instream benthic macroinvertebrates to certain stressors, such as total dissolved solids. An indigenous species approach should be adopted, using a sensitive benthic collector-filterer following development of practical laboratory bioassays. In the Leading Creek Watershed (southeast Ohio), an aggregated approximately 99% reduction in mean mayfly abundance for all impacted sites was observed below a coal-mine effluent with mean specific conductivity (SC) of 8,109 (7,750-8,750) microS cm(-1). The mayfly, Isonychia, was exposed for 7-days to a simulation of this effluent, in lotic microcosms. Based on lowest observable adverse effect concentrations, Isonychia survival was a more sensitive endpoint to SC (1,562 microS cm(-1)) than were 7-day C. dubia survival and fecundity (3,730 microS cm(-1)). Isonychia molting, a potentially more sensitive endpoint, was also examined. Using traditional test species to assess discharges to surface water alone may not adequately protect benthic macroinvertebrate assemblages in systems impaired by discharges high in SC.     

Evolutionary consequences for ecological risk assessment and management

The human health risk assessment (HRA) paradigm is being used as a basis for developing ecological risk assessment (ERA). The modification of the HRA paradigm to ERA will be most useful in an ecotoxicological sense, to assess the effect of hazards to single indicator species and populations, rather than to ecosystems. However, even for single species and population assessments, there are major differences in HRA and ERA. One such difference derives from the HRA tenet that human impairment at any age is important, and that each individual is important. For ERA, individuals are less important, and it is the population and its survival and interactions that are of concern. One exception is in the case of endangered species where every individual is critical because of its potential impact on survival and genetic diversity of the species. We suggest that ERA must take into account the relative reproductive value of the potentially impacted individuals in assessing hazards. This will involve adding additional steps to evaluate the value of the individual to current population levels, assessing reproductive value, and assessing recovery potential. Although ecologists recognize the importance of these factors, we suggest that they should be integral parts of ecological risk assessment.     

Rabbit Population Landscape-Scale Simulation to Investigate the Relevance of Using Rabbits in Regulatory Environmental Risk Assessment

This paper describes the development and testing of the ALMaSS rabbit model and its baseline, and subsequently its application to the question of lagomorph population vulnerability in environmental risk assessment (ERA). Development and testing following a pattern-oriented modelling protocol resulted in a model able to replicate local and landscape-level rabbit population patterns. We then tested how robust rabbit populations are to an (imaginary) extreme toxic stressor at a landscape level in a variety of landscapes, and to what extremes key uncertain model parameters must be pushed to cause extinctions. This was contrasted with the same (imaginary) toxic stressor applied to the already existing ALMaSS hare model. For EU risk assessment of plant protection products, these results clearly indicate that if the protection goal is population-level impacts, either in abundance and/or distribution, then the hare is a much more vulnerable species than the rabbit under all the conditions tested. Rabbits would only be more vulnerable than hares if the entire population were to be exposed simultaneously, when lower body mass would then be a critical factor. This did not occur even though the toxicant and exposure scenarios tested here were extreme and, in fragmented landscapes at scales used here, will not occur in reality from the use of plant protection products on crop fields. As well as specifically answering the question on rabbit versus hare vulnerability, this study generally illustrates the potential application of models for setting focal species for risk assessments.     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

A Regional Approach to Projecting Land-Use Change and Resulting Ecological Vulnerability

This study explores ecological vulnerability to land-use change in the U.S. Mid-Atlantic Region by spatially extrapolating land and economic development, and overlaying these projections with maps of sensitive ecological resources. As individual extrapolations have a high degree of uncertainty, five methods with different theoretical bases are employed. Confidence in projections is increased for counties targeted by two or more projection methods. A county is considered at risk if it currently supports three or more sensitive resources, and is projected to experience significant growth by the year 2010 by two or more methods. Analysis designated 19 counties and two cities as at risk, highlighting within a large region the priority areas where state and regional efforts would contribute the most to integrating environmental considerations into the process of land development. The study also found that potentially severe ecological effects of future land-use change are not limited to the outskirts of major urban areas. Recreational demands on smaller communities with mountain and coastal resources are also significant, as are initiatives to promote economic development in rural areas of high ecological quality. This approach provides a comprehensive overview of potential regional development, leading to an objective prioritization of high-risk areas. The intent is to inform local planning and decision-making so that regional and cumulative ecological degradation are minimized.     

non-lethal responses of the freshwater snail potamopyrgus antipodarum to dissolved arsenic

Two non-lethal responses, avoidance andimmobility, were observed for thefreshwater gastropod Potamopyrgusantipodarum on exposure to dissolvedarsenic (As) as arsenate (As(V)) orarsenite (As(III)). Two differentpopulations of P. antipodarum, onewith a long history of exposure todissolved As from geothermal fluids andthe other with minimal exposure, werecompared to test for adaptation to As. Both snail populations avoided dissolvedAs(III), the more toxic form, at lowerconcentrations than As(V). As(V), theless toxic form, was avoided by both snailpopulations at much lower concentrationsthan those at which the snails becameimmobile. In contrast, the concentrationsof As(III) which caused avoidance werealmost the same as those which causedimmobility, implying that avoidance may notbe an effective response to protect thesesnails from exposure to As(III). Snailsfrom the exposed population avoided As(V)at about 20% of the concentration thatwas avoided by the snails from theunexposed population. At higherconcentrations of As(V) which causedimmobility, this difference in sensitivitypersisted up to an exposure time of 48 hours. After 96 hours exposure, however,both populations showed similarsensitivity. Snails from the exposedpopulation were more sensitive to As(III),both avoiding the As and becoming immobileat lower concentrations than were observedfor the same responses in the snails fromthe unexposed population. We suggest thatthe differences in sensitivity between thetwo populations could have been the resultof the higher soft body As burden of theexposed snails at the start of thelaboratory experiments.     

Evaluation of Early Life Stage Fall Chinook Salmon Exposed to Hexavalent Chromium from a Contaminated Groundwater Source

We conducted a laboratory evaluation to assess the risk to early life stage (i.e., eyed egg to swim up) fall Chinook salmon (Oncorhynchus tshawytscha) for exposure to hexavalent chromium from a contaminated groundwater source. Local populations of fall Chinook salmon were exposed to Hanford Site source groundwater that was diluted with Columbia River water. Specific endpoints included survival, development rate, and growth. Tissue burdens of fish were also measured to estimate uptake and elimination rates of chromium. Survival, development, and growth of early life stage fall Chinook salmon were not adversely affected by extended exposures (i.e., 98 day) to hexavalent chromium ranging from 0.79 to 260 μg/l. Survival for all treatment levels and controls exceeded 98% at termination of the test. In addition, there were no differences among the mean lengths and weights of fish among all treatment groups. Whole-body concentrations of chromium in early life stage fall Chinook salmon had a typical dose-response pattern; i.e., those subjected to highest exposure concentrations and longest exposure intervals had higher tissue concentrations. Given the spatial extent of chromium concentrations at the Hanford Site, and the dynamics of the groundwater–river water interface, the current cleanup criterion of 10 μg/l chromium appear adequate to protect early life stage fall Chinook salmon. These findings, together with previous research indicate low risk to these populations.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Assessment of chlorine tolerance profile of <Emphasis Type="BoldItalic">Citrobacter</Emphasis> species recovered from wastewater treatment plants in Eastern Cape,South Africa

This present study assessed the chlorine tolerance of some Citrobacter species recovered from secondary effluents from the clarifiers of two wastewater treatment plants in the Eastern Cape, South Africa. The bacterial survival, chlorine lethal dose and inactivation kinetics at lethal doses were examined. Inactivation of the test bacteria (n = 20) at the recommended dose of 0.5 mg/l for 30 min exposure showed a progressive reduction in bacterial population from 4 to 5 log reduction and residuals ranged between 0.12 and 0.46 mg/l. The bactericidal activity of chlorine increased at higher dosages with a substantial reduction in viability of the bacteria and complete inactivation of the bacterial population at a lethal dose of 0.75 and 1.0 mg/l in 30 min. For the inactivation kinetics, bactericidal activity of chlorine increased with time showing a 3.67–5.4 log reduction in 10 min, 4.0–5.6 log reduction in 20 min and above 6.3 log reductions to complete sterilization of bacterial population over 30 min for all the entire test Citrobacter isolates used in this study. Furthermore, there was a strong correlation (R ² > 0.84) between bacteria inactivation and increase in contact time. This study appears to have provided support for laboratory evidence of bacterial tolerance to chlorine disinfection at current recommended dose (0.5 mg/l for 30 min), and chlorine concentration between 0.75 and 1.0 mg/l was found to have a better disinfecting capacity to check tolerance of Citrobacter species.     

How Certain Are Salmon Recovery Forecasts? A Watershed-scale Sensitivity Analysis

Complex relationships between landscape and aquatic habitat conditions and salmon (Oncorhynchus spp.) populations make science-based management decisions both difficult and essential. Due to a paucity of empirical data, models characterizing these relationships are often used to forecast future conditions. We evaluated uncertainties in a suite of models that predict possible future habitat conditions and fish responses in the Lewis River Basin, Washington, USA. We evaluated sensitivities of predictions to uncertainty in model parameters. Results were sensitive to 60% of model parameters but substantially so (|partial regression coefficients| >0.5) to <10%. We also estimated accuracy of several predictions using field surveys. Observations mostly fell within predicted ranges for riparian shade and fine-sediment deposition, but large woody debris estimates matched only half the time. We provide suggestions to modelers for improving model accountability, and describe how managers can incorporate prediction uncertainty into decision-making, thereby improving the odds of successful salmon habitat recovery.     

Probability sampling of stony coral populations in the Florida Keys

Principles of probability survey design were applied to guide large-scale sampling of populations of stony corals and associated benthic taxa in the Florida Keys coral reef ecosystem. The survey employed a two-stage stratified random sampling design that partitioned the 251-km(2) domain by reef habitat types, geographic regions, and management zones. Estimates of the coefficient of variation (ratio of standard error to the mean) for stony coral population density and abundance ranged from 7% to 12% for four of six principal species. These levels of survey precision are among the highest reported for comparable surveys of marine species. Relatively precise estimates were also obtained for octocoral density, sponge frequency of occurrence, and benthic cover of algae and invertebrates. Probabilistic survey design techniques provided a robust framework for estimating population-level metrics and optimizing sampling efficiency.     

A dynamic model of the spatial spread of an infectious disease: the case of fox rabies in Illinois

A spatially explicit computer model is developed to examine the dynamic spread of fox rabies across the state of Illinois and to evaluate possible disease control strategies. The ultimate concern is that the disease will spread from foxes to humans through the pet population. Modeling the population dynamics of rabies in foxes requires comprehensive ecological and biological knowledge of the fox and pathogenesis of the rabies virus. Variables considered including population densities, fox biology, home ranges, dispersal rates, contact rates, and incubation periods, can greatly effect the spread of disease. Accurate reporting of these variables is paramount for realistic construction of a spatial model. The spatial modeling technique utilized is a grid-based approach that combines the relevant geographic condition of the Illinois landscape (typically described in a georeferenced database system) with a nonlinear dynamic model of the phenomena of interest in each cell, interactively connected to the other appropriate cells (usually adjacent ones). The resulting spatial model graphically links data obtained from previous models, fox biology, rabies information and landscape parameters using various hierarchical scales and makes it possible to follow the emergent patterns and facilitates experimental stimulus/result data collection techniques. Results of the model indicate that the disease would likely spread among the native healthy fox population from East to West and would occur in epidemiological waves radiating from the point of introduction; becoming endemic across the State in about 15 years. Findings also include the realization that while current hunting pressures can potentially wipe out the fox in the State, some level of hunting pressure can be effectively utilized to help control the disease. This revised version was published online in July 2006 with corrections to the Cover Date.     

A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-index assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics.     

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.