A HYBRID OPTIMIZATION APPROACH TO THE ESTIMATION OF DISTRIBUTED PARAMETERS IN TWO-DIMENSIONAL CONFINED AQUIFERS1

ABSTRACT: In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.     

Conservation and Management for Multiple Species: Integrating Field Research and Modeling into Management Decisions

Multiple-species reserves aim at supporting viable populations of selected species. Population viability analysis (PVA) is a group of methods for predicting such measures as extinction risk based on species-specific data. These methods include models that simulate the dynamics of a population or a metapopulation. A PVA model for the California gnatcatcher in Orange County was developed with landscape (GIS) data on the habitat characteristics and requirements and demographic data on population dynamics of the species. The potential applications of this model include sensitivity analysis that provides guidance for planning fieldwork, designing reserves, evaluating management options, and assessing human impact. The method can be extended to multiple species by combining habitat suitability maps for selected species with weights based on the threat faced by each species, and the contribution of habitat patches to the persistence of each species. These applications and extensions, together with the ability of the model to combine habitat and demographic data, make PVA a powerful tool for the design, conservation, and management of multiple species reserves.     

The Effects of Population Density on Juvenile Growth Rate in White-Tailed Deer

Animal body size is driven by habitat quality, food availability, and nutrition. Adult size can relate to birth weight, to length of the ontogenetic growth period, and/or to the rate of growth. Data requirements are high for studying these growth mechanisms, but large datasets exist for some game species. In North America, large harvest datasets exist for white-tailed deer (Odocoileus virginianus), but such data are collected under a variety of conditions and are generally dismissed for ecological research beyond local population and habitat management. We contend that such data are useful for studying the ecology of white-tailed deer growth and body size when analyzed at ordinal scale. In this paper, we test the response of growth rate to food availability by fitting a logarithmic equation that estimates growth rate only to harvest data from Fort Hood, Texas, and track changes in growth rate over time. Results of this ordinal scale model are compared to previously published models that include additional parameters, such as birth weight and adult weight. It is shown that body size responds to food availability by variation in growth rate. Models that estimate multiple parameters may not work with harvest data because they are prone to error, which renders estimates from complex models too variable to detect interannual changes in growth rate that this ordinal scale model captures. This model can be applied to harvest data, from which inferences about factors that influence animal growth and body size (e.g., habitat quality and nutritional availability) can be drawn.     

Estimation of Mussel Population Response to Hydrologic Alteration in a Southeastern U.S. Stream

The southeastern United States has experienced severe, recurrent drought, rapid human population growth, and increasing agricultural irrigation during recent decades, resulting in greater demand for the water resources. During the same time period, freshwater mussels (Unioniformes) in the region have experienced substantial population declines. Consequently, there is growing interest in determining how mussel population declines are related to activities associated with water resource development. Determining the causes of mussel population declines requires, in part, an understanding of the factors influencing mussel population dynamics. We developed Pradel reverse-time, tag-recapture models to estimate survival, recruitment, and population growth rates for three federally endangered mussel species in the Apalachicola–Chattahoochee–Flint River Basin, Georgia. The models were parameterized using mussel tag-recapture data collected over five consecutive years from Sawhatchee Creek, located in southwestern Georgia. Model estimates indicated that mussel survival was strongly and negatively related to high flows during the summer, whereas recruitment was strongly and positively related to flows during the spring and summer. Using these models, we simulated mussel population dynamics under historic (1940–1969) and current (1980–2008) flow regimes and under increasing levels of water use to evaluate the relative effectiveness of alternative minimum flow regulations. The simulations indicated that the probability of simulated mussel population extinction was at least 8 times greater under current hydrologic regimes. In addition, simulations of mussel extinction under varying levels of water use indicated that the relative risk of extinction increased with increased water use across a range of minimum flow regulations. The simulation results also indicated that our estimates of the effects of water use on mussel extinction were influenced by the assumptions about the dynamics of the system, highlighting the need for further study of mussel population dynamics.     

Assessment of the use of selected rodents in ecological monitoring

Rodents can be useful in detecting environmental impacts because they are easy to study (easy to capture and handle), they can occur in densities adequate for statistical analysis, and they are ecologically important. In this study the usefulness of rodent populations for ecological monitoring was investigated by examining the effect of variation on the possibility of detecting differences among populations of rodents on 10 trapping grids. The effects of sampling frequencies and dispersal on detecting differences in population parameters among grids was also investigated, as was the possibility of inferring population parameters from correlations with habitat data. Statistically significant differences as small as 4.3Peromyscus maniculatus/ha were detected between grids. Of 10 populations, this comprised 12% of the highest-density population and 44% of the lowest-density population. Smaller and more differences among grids were found by examining only animals surviving from previous months. Dispersal confounds detection of direct impacts to populations, especially during the breeding season. Infrequent sampling fails to detect impacts that occur between sampling periods and will indicate impacts when observed changes result from natural variation. Correlations between population parameters and habitat variables exist but should only be used in predicting, not measuring, impacts. It is concluded that some rodent populations can be used in ecological monitoring. However, intensive sampling is required to account for variation and dispersal.     

DYNAMIC MODELING OF STREAM QUALITY BY INVARIANT IMBEDDING1

ABSTRACT. The estimator equations obtained using invariant imbedding is used to estimate the parameters in river or stream pollution. By using these equations, the parameters can be estimated directly from differential equations representing the pollution model and from measured noisy data such as BOD and DO. Another advantage of this approach is that a sequential estimation scheme is obtained. By using this sequential scheme, only current data are needed to estimate current or future values of the unknown parameters. Consequently, a large amount of computer time and computer memory can be saved. Furthermore, not only the parameters but also the concentrations of pollutants can be estimated. Thus, it also forms an effective forecasting technique. The classical least squares criterion is used in the estimation. Several examples are solved to illustrate the technique. (KEY WORDS: dynamic modeling; water pollution; invariant imbedding; forecasting; least squares criterion; estimation)     

Strategic Environmental Assessment of Plans and Programs: A Methodology for Estimating Effects on Biodiversity

We developed a methodology for biodiversity evaluations within the process of Strategic Environmental Assessment and we applied it to the estimation of the effect of two Regional Plans of Development on all bird species inhabiting the Castilla y León region (northwestern Spain). The methodology is based on the evaluation of the effects of main development actions on the habitat requirements of species. From these evaluations, and from data on the current distribution and population size (number of individuals) of each species, we estimated the most likely pattern of distribution and population size after the full implementation of the plans for each species. The impacts of the plans were quantified as the differences between the pre- and postproject patterns after codifying them to compensate for differences in the quality of the information available among species. Overall, we conclude that the proposed methodology fulfills the requirements for its use within the SEA process as it allows for the assessment of cumulative impacts on every species, highlighting the development directions and the habitat types with major impacts, and ascertaining whether impacts affect species with either low or high conservation and/or economic value. Generalization of the proposed methodology to other regions or species will require wildlife-habitat models adequate for SEA analyses, so that we also propose guidelines for the development and validation of these models.     

Endangered species: Deciding which species to save

Many species face extinction because preservation organizations do not have the resources to mount all of the interventions that are needed. Decision analysis provides techniques that can help managers of these organizations to make judgments about which species they will attempt to rescue. A formal analysis of the choices available to the US Fish and Wildlife Services' endangered species program with regard toIsotria medeoloides illustrates how the difficulties of making preservation decisions can be lessened.I. medeoloides is perhaps the rarest orchid in the United States. Little is known of the species' biology and less about effective management. Yet unless a preservation effort is mounted, the species will continue to be threatened by habitat destruction and botanical collecting. The analysis employs formal probabalistic techniques to weigh the utility of possible intervention strategies, that is, their likelihood of achieving different amounts of increase in the longevity of the species, and to balance these gains against their costs. If similar decision analyses are performed on other endangered species, the technique can be used to choose among them, as well as among strategies for individual species.     

Random forest models to estimate bankfull and low flow channel widths and depths across the conterminous United States

Channel dimensions (width and depth) at varying flows influence a host of instream ecological processes, as well as habitat and biotic features; they are a major consideration in stream habitat restoration and instream flow assessments. Models of widths and depths are often used to assess climate change vulnerability, develop endangered species recovery plans, and model water quality. However, development and application of such models require specific skillsets and resources. To facilitate acquisition of such estimates, we created a dataset of modeled channel dimensions for perennial stream segments across the conterminous United States. We used random forest models to predict wetted width, thalweg depth, bankfull width, and bankfull depth from several thousand field measurements of the National Rivers and Streams Assessment. Observed channel widths varied from <5 to >2000 m and depths varied from <2 to >125 m. Metrics of watershed area, runoff, slope, land use, and more were used as model predictors. The models had high pseudo R² values (0.70–0.91) and median absolute errors within ±6% to ±21% of the interquartile range of measured values across 10 stream orders. Predicted channel dimensions can be joined to 1.1 million stream segments of the 1:100 K resolution National Hydrography Dataset Plus (version 2.1). These predictions, combined with a rapidly growing body of nationally available data, will further enhance our ability to study and protect aquatic resources.     

Model-Based Selection of Areas for the Restoration of Acrocephalus paludicola Habitats in NE Germany

The global Aquatic Warbler (Acrocephalus paludicola, Vieillot, 1817) population has suffered a major decline due to the large-scale destruction of its natural habitat (fen mires). The species is at risk of extinction, especially in NE Germany/NW Poland. In this study, we developed habitat suitability models based on satellite and environmental data to identify potential areas for habitat restoration on which further surveys and planning should be focused. To create a reliable model, we used all Aquatic Warbler presences in the study area since 1990 as well as additional potentially suitable habitats identified in the field. We combined the presence/absence regression tree algorithm Cubist with the presence-only algorithm Maxent since both commonly outperform other algorithms. To integrate the separate model results, we present a new way to create a metamodel using the initial model results as variables. Additionally, a histogram approach was applied to further reduce the final search area to the most promising sites. Accuracy increased when using both remote sensing and environmental data. It was highest for the integrated metamodel (Cohen’s Kappa of 0.4, P < 0.001). The final result of this study supports the selection of the most promising sites for Aquatic Warbler habitat restoration.     

Putting the “Ecology” into Environmental Flows: Ecological Dynamics and Demographic Modelling

There have been significant diversions of water from rivers and streams around the world; natural flow regimes have been perturbed by dams, barriers and excessive extractions. Many aspects of the ecological 'health' of riverine systems have declined due to changes in water flows, which has stimulated the development of thinking about the maintenance and restoration of these systems, which we refer to as environmental flow methodologies (EFMs). Most existing EFMs cannot deliver information on the population viability of species because they: (1) use habitat suitability as a proxy for population status; (2) use historical time series (usually of short duration) to forecast future conditions and flow sequences; (3) cannot, or do not, handle extreme flow events associated with climate variability; and (4) assume process stationarity for flow sequences, which means the past sequences are treated as good indicators of the future. These assumptions undermine the capacity of EFMs to properly represent risks associated with different flow management options; assumption (4) is untenable given most climate-change predictions. We discuss these concerns and advocate the use of demographic modelling as a more appropriate tool for linking population dynamics to flow regime change. A 'meta-species' approach to demographic modelling is discussed as a useful step from habitat based models towards modelling strategies grounded in ecological theory when limited data are available on flow-demographic relationships. Data requirements of demographic models will undoubtedly expose gaps in existing knowledge, but, in so doing, will strengthen future efforts to link changes in river flows with their ecological consequences.     

Using Wildlife as Receptor Species: A Landscape Approach to Ecological Risk Assessment

To assist risk assessors at the Department of Energy’s Savannah River Site (SRS), a Geographic Information System (GIS) application was developed to provide relevant information about specific receptor species of resident wildlife that can be used for ecological risk assessment. Information was obtained from an extensive literature review of publications and reports on vertebrate- and contaminant-related research since 1954 and linked to a GIS. Although this GIS is a useful tool for risk assessors because the data quality is high, it does not describe the species’ site-wide spatial distribution or life history, which may be crucial when developing a risk assessment. Specific receptor species on the SRS were modeled to provide an estimate of an overall distribution (probability of being in an area). Each model is a stand-alone tool consisting of algorithms independent of the GIS data layers to which it is applied and therefore is dynamic and will respond to changes such as habitat disturbances and natural succession. This paper describes this modeling process and demonstrates how these resource selection models can then be used to produce spatially explicit exposure estimates. This approach is a template for other large federal facilities to establish a framework for site-specific risk assessments that use wildlife species as endpoints.Current address: Biology Department, University of South Dakota, Vermillion, SD 57069     

A Strategy for Prioritizing Threats and Recovery Actions for At-Risk Species

Ensuring the persistence of at-risk species depends on implementing conservation actions that ameliorate threats. We developed and implemented a method to quantify the relative importance of threats and to prioritize recovery actions based on their potential to affect risk to Mojave desert tortoises (Gopherus agassizii). We used assessments of threat importance and elasticities of demographic rates from population matrix models to estimate the relative contributions of threats to overall increase in risk to the population. We found that urbanization, human access, military operations, disease, and illegal use of off highway vehicles are the most serious threats to the desert tortoise range-wide. These results suggest that, overall, recovery actions that decrease habitat loss, predation, and crushing will be most effective for recovery; specifically, we found that habitat restoration, topic-specific environmental education, and land acquisition are most likely to result in the greatest decrease in risk to the desert tortoise across its range. In addition, we have developed an application that manages the conceptual model and all supporting information and calculates threat severity and potential effectiveness of recovery actions. Our analytical approach provides an objective process for quantifying threats, prioritizing recovery actions, and developing monitoring metrics for those actions for adaptive management of any at-risk species.     

Landscape-scale spatial population dynamics in human-impacted stream systems

The movement of individuals among populations can be critical in preventing local and landscape-scale species extinctions in systems exposed to human perturbation. Current understanding of spatial population dynamics in streams is largely limited to the reach scale and is therefore inadequate to address species response to spatially extensive perturbation. Using model simulations, I examined species response to perturbation in a drainage composed of multiple, hierarchically arranged stream-patches connected by in-stream and overland pathways of dispersal. Patch extinction probability, the proportion of initially occupied patches extinct after 25 years, was highly sensitive to the extent of species occupancy and perturbation within the drainage, longitudinal species distribution, perturbation decay rate and the covariance pattern of stochastic effects on colonization and extinction probabilities. Results of these simulations underscore the importance of identifying and preserving source populations and dispersal routes for stream species in human-impacted landscapes. They also highlight the vulnerability of headwater specialist taxa to anthropogenic perturbation, and the strong positive effect on species resilience of habitat rehabilitation when recolonization is possible. Efforts to conserve and manage stream species may be greatly improved by accounting for landscape-scale spatial population dynamics.     

Resampling methods for evaluating classification accuracy of wildlife habitat models

Predictive models of wildlife-habitat relationships often have been developed without being tested The apparent classification accuracy of such models can be optimistically biased and misleading. Data resampling methods exist that yield a more realistic estimate of model classification accuracy These methods are simple and require no new sample data. We illustrate these methods (cross-validation, jackknife resampling, and bootstrap resampling) with computer simulation to demonstrate the increase in precision of the estimate. The bootstrap method is then applied to field data as a technique for model comparison We recommend that biologists use some resampling procedure to evaluate wildlife habitat models prior to field evaluation.     

Prioritizing Wildlife Taxa for Biological Diversity Conservation at the Local Scale

/ We identified and ranked 108 resident and migratory wildlife taxa on John F. Kennedy Space Center (KSC) that were vulnerable to local, regional, or global extinction. We ranked taxa based on their vulnerability to extinction, their potential role for maintaining faunal integrity, and the relevance of KSC for maintaining their populations in the United States and Florida. Several taxa, not listed by agencies, were vulnerable to regional or global extinction. Many taxa not vulnerable to global extinction were vulnerable to local and regional extinction. Top predators were vulnerable to extinction because of small population size, isolation from other populations, and road mortality. Many taxa were dependent on habitat conditions at different geographic locations so that conservation required greater collaboration among land owners, managers, and researchers at local, regional, and global scales.KEY WORDS: Biological diversity; Endangered species; Conservation     

MEASUREMENT OF HYDRAULIC CONDUCTIVITY AND DIFFUSIVITY FOR PREDICTING THE PROCESS OF SOIL WATER INFILTRATION FROM A TRICKLE SOURCE1

ABSTRACT: Two soil water functions, hydraulic conductivity K(θ) and diffusivity D(θ), were estimated by two methods In one method D(θ) was estimated according to Bruce and Klute (1956), and K(θ) was calculated from D(θ) and the retention curve. In the second, K(θ) was obtained by field estimation, with D(θ) being calculated from K(θ) and the retention curve. The criterion of reliability for both methods was agreement between experimental and predicted distribution of soil water content. The prediction was made using the functions K(θ) and D(θ) as soil water parameters in both methods. Theoretical and experimental agreement was generally good. The first method, however, was found to be best for high soil water content and the second for low soil water content. In addition, the water content at the end of the monotonic increase of function D(θ) (estimated according to Bruce and Klute 1956) was found to be about the upper limit of field soil water content. It can be used as a boundary condition in the numerical solution of a cylindrical model of infiltration from a trickle source. It was concluded that the best agreement between theory and experiment can be found when the combined values of D(θ) and K(θ) from both methods of estimation are used.     

Valuing freshwater salmon habitat on the west coast of Canada

Changes in land use can potentially reduce the quality of fish habitat and affect the economic value of commercial and sport fisheries that rely on the affected stocks. Parks and protected areas that restrict land-use activities provide benefits, such as ecosystem services, in addition to recreation and preservation of wildlife. Placing values on these other benefits of protected areas poses a major challenge for land-use planning. In this paper, we present a framework for valuing benefits for fisheries from protecting areas from degradation, using the example of the Strait of Georgia coho salmon fishery in southern British Columbia, Canada. Our study improves upon previous methods used to value fish habitat in two major respects. First, we use a bioeconomic model of the coho fishery to derive estimates of value that are consistent with economic theory. Second, we estimate the value of changing the quality of fish habitat by using empirical analyses to link fish population dynamics with indices of land use in surrounding watersheds. In our example, we estimated that the value of protecting habitat ecosystem services is C$0.93 to C$2.63 per ha of drainage basin or about C$1322 to C$7010 per km of salmon stream length (C$1.00=US$0.71). Sensitivity analyses suggest that these values are relatively robust to different assumptions, and if anything, are likely to be minimum estimates. Thus, when comparing alternative uses of land, managers should consider ecosystem services from maintaining habitat for productive fish populations along with other benefits of protected areas.     

Should Habitat Trading Be Based on Mitigation Ratios Derived from Landscape Indices? A Model-Based Analysis of Compensatory Restoration Options for the Red-Cockaded Woodpecker

Many species of conservation concern are spatially structured and require dispersal to be persistent. For such species, altering the distribution of suitable habitats on the landscape can affect population dynamics in ways that are difficult to predict from simple models. We argue that for such species, individual-based and spatially explicit population models (SEPMs) should be used to determine appropriate levels of off-site restoration to compensate for on-site loss of ecologic resources. Such approaches are necessary when interactions between biologic processes occur at different spatial scales (i.e., local [recruitment] and landscape [migration]). The sites of restoration and habitat loss may be linked to each other, but, more importantly, they may be linked to other resources in the landscape by regional biologic processes, primarily migration. The common management approach for determining appropriate levels of off-site restoration is to derive mitigation ratios based on best professional judgment or pre-existing data. Mitigation ratios assume that the ecologic benefits at the site of restoration are independent of the ecologic costs at the site of habitat loss. Using an SEPM for endangered red-cockaded woodpeckers, we show that the spatial configuration of habitat restoration can simultaneously influence both the rate of recruitment within breeding groups and the rate of migration among groups, implying that simple mitigation ratios may be inadequate.