Geology topics

Richard L. Schroeder

Publications and source records attributed to Richard L. Schroeder.

16 recordsLinked to original sources

USGS2004

Writing refuge management goals and objectives: a handbook

Goals and objectives are the unifying elements of successful refuge management. They identify and focus management priorities, provide a context for resolving issues, guide specific projects, provide rationale for decisions, and offer a defensible link among management actions, refuge purpose(s), Service policy, and the National Wildlife Refuge System (Refuge System) mission. Pursuant to Refuge Planning Policy (602 FW 1, 3, 4), this handbook offers guidance on how to write goals and objectives for national wildlife refuges and provides counsel on their development. While the handbook specifically addresses biology and visitor services, you can also utilize this guidance when developing goals and objectives for other refuge programs. Several assumptions are basic to this handbook. The handbook focuses on the mechanics of writing sound goals and objectives. Detailed guidance on what information to consider, collect, interpret, and synthesize into goals and objectives is beyond the scope of this handbook. It views a vision statement as the synthesis of a refuge’s purpose(s), the Refuge System mission and goals, and other biological, legal, and social concerns in which the refuge has a role. It also assumes a familiarity with the hierarchical nature of planning and where, within a planning process, the writing of goals and objectives occurs. This guidance applies to conceptual management plans, comprehensive conservation plans (CCPs), step-down management plans (e.g., habitat management, visitor services, fire management), or any other planning document incorporating goals and objectives, including strategic documents developed under the Government Performance and Results Act. We intend this guidance for use by an internal audience tasked with writing refuge goals and objectives, primarily refuge managers, biologists, visitor services specialists, planners, and other members of refuge planning teams. Still, it recognizes that we should write goals and objectives so that interested members of the public can understand them, to the extent this does not jeopardize the technical accuracy or reduce the inclusion of necessary information. The terminology and definitions used in this handbook are widely accepted in the planning field and are not inconsistent with more recent application in strategic planning. Perhaps most important, the handbook presumes all goals and objectives must further the specific purpose(s) of the refuge and the broader mission of the Refuge System, as well as be consistent with Refuge Planning Policy and any other relevant Service policy and directives.

Report↗

USGS1999

Estimating effects of limiting factors with regression quantiles

In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e.g., 90-95th) were greater than if effects were estimated by changes in the means from standard linear model procedures. Estimating a range of regression quantiles (e.g., 5-95th) provides a comprehensive description of biological response patterns for exploratory and inferential analyses in observational studies of limiting factors, especially when sampling large spatial and temporal scales.

Ecology↗

USGS1992

Assessment of habitat of wildlife communities on the Snake River, Jackson, Wyoming

The composition of the wildlife community in western riparian habitats is influenced by the horizontal and vertical distribution of vegetation, the physical complexity of the channel, and barriers to movement along the corridor. Based on information from the literature and a workshop, a model was developed to evaluate the wildlife community along the Snake River near Jackson, Wyoming. The model compares conditions of the current or future years with conditions in 1956, before constructions of levees along the river. Conditions in 1956 are assumed to approximate the desirable distribution of plant cover types and the associated wildlife community and are used as a standard of comparison in the model. The model may be applied with remotely sensed data and is compatible with a geographic information systems analysis. In addition to comparing existing or future conditions with conditions in 1956, the model evaluated floodplain and channel complexity and assesses anthropogenic disturbance and its potential effect on the quality of wildlife habitat and movements of wildlife in the riparian corridor.

Wyoming↗

USGS1992

Wildlife species richness in shelterbelts: test of a habitat model

Shelterbelts are human-made habitats consisting of rows of shrubs and trees planted either in fields or on the windward side of farmstead dwellings. Shelterbelts provide wooded habitat for a large variety of birds and other wildlife. A model to predict wildlife species richness in shelterbelts (Schroeder 1986) was published as part of the U.S. Fish and Wildlife Service Habitat Suitability Index (HSI) model series (Schamberger et al. 1982). HSI models have been used extensively by wildlife managers and land use planners to assess habitat quality. Several HSI models have become the focus of a test program that includes analysis of field data for corroboration, refutation, or modification of model hypotheses. Previous tests of HSI models focused either on single species (e.g., Cook and Irwin 1985, Morton et al. 1989, Schroeder 1990) or examined portions of HSI models, such as the relationship between cavity abundance and tree diameter (Allen and Corn 1990). The shelterbelt model, however, assesses habitat value at the community level. The effects of habitat characteristics, area, and perimeter on diversity and abundance of bird and mammal species in shelterbelts were first studied by Yahner (1983a, b). Johnson and Beck (1988) confirmed the importance of shelterbelts to wildlife and identified area, perimeter, and diversity and complexity of vegetation as key measurements of habitat quality. The shelterbelt model incorporates both specific habitat variables and larger scale parameters, such as area and configuration, to predict wildlife species richness. This shift in perspective comes at a time of increasing interest in conservation and planning beyond the species levels (e.g., Graul and Miller 1984, Hutto et al. 1987, Schroeder 1987: 26). We report results of a 3-year study of spatial and vegetative parameters and their relationship to breeding bird species richness (BSR) in 34 Kansas shelterbelts. Our objectives were to test the hypothesis presented in the original shelterbelt model (Schroeder 1986) that species richness can be predicted by shelterbelt characteristics and to investigate alternative models for predicting BSR in shelterbelts.

Kansas↗

USGS1990

Tests of a habitat suitability model for black-capped chickadees

The black-capped chickadee ( Parus atricapillus ) Habitat Suitability Index (HSI) model provides a quantitative rating of the capability of a habitat to support breeding, based on measures related to food and nest site availability. The model assumption that tree canopy volume can be predicted from measures of tree height and canopy closure was tested using data from foliage volume studies conducted in the riparian cottonwood habitat along the South Platte River in Colorado. Least absolute deviations (LAD) regression showed that canopy cover and over story tree height yielded volume predictions significantly lower than volume estimated by more direct methods. Revisions to these model relations resulted in improved predictions of foliage volume. The relation between the HSI and estimates of black-capped chickadee population densities was examined using LAD regression for both the original model and the model with the foliage volume revisions. Residuals from these models were compared to residuals from both a zero slope model and an ideal model. The fit model for the original HSI differed significantly from the ideal model, whereas the fit model for the original HSI did not differ significantly from the ideal model. However, both the fit model for the original HSI and the fit model for the revised HSI did not differ significantly from a model with a zero slope. Although further testing of the revised model is needed, its use is recommended for more realistic estimates of tree canopy volume and habitat suitability.

Report↗

USGS1987

Community models for wildlife impact assessment: a review of concepts and approaches

The first two sections of this paper are concerned with defining and bounding communities, and describing those attributes of the community that are quantifiable and suitable for wildlife impact assessment purposes. Prior to the development or use of a community model, it is important to have a clear understanding of the concept of a community and a knowledge of the types of community attributes that can serve as outputs for the development of models. Clearly defined, unambiguous model outputs are essential for three reasons: (1) to ensure that the measured community attributes relate to the wildlife resource objectives of the study; (2) to allow testing of the outputs in experimental studies, to determine accuracy, and to allow for improvements based on such testing; and (3) to enable others to clearly understand the community attribute that has been measured. The third section of this paper described input variables that may be used to predict various community attributes. These input variables do not include direct measures of wildlife populations. Most impact assessments involve projects that result in drastic changes in habitat, such as changes in land use, vegetation, or available area. Therefore, the model input variables described in this section deal primarily with habitat related features. Several existing community models are described in the fourth section of this paper. A general description of each model is provided, including the nature of the input variables and the model output. The logic and assumptions of each model are discussed, along with data requirements needed to use the model. The fifth section provides guidance on the selection and development of community models. Identification of the community attribute that is of concern will determine the type of model most suitable for a particular application. This section provides guidelines on selected an existing model, as well as a discussion of the major steps to be followed in modifying an existing model or developing a new model. Considerations associated with the use of community models with the Habitat Evaluation Procedures are also discussed. The final section of the paper summarizes major findings of interest to field biologists and provides recommendations concerning the implementation of selected concepts in wildlife community analyses.

Report↗

USGS1986

Habitat Suitability Index Models: Wildlife species richness in shelterbelts

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for evaluating potential species richness in shelterbelts. The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1985

Habitat Suitability Index Models: Eastern wild turkey

A review and synthesis of existing information were used to develop a Habitat Suitability Index (HSI) model for the eastern wild turkey (Meleagris gallopavo sylvestris). The model consolidates habitat use information into a framework appropriate for field application, and is scaled to produce an index between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). HSI models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1984

Habitat Suitability Index Models: Black brant

A review and synthesis of existing information were used to develop a habitat suitability index model for wintering habitat of the black brant (Branta bernicla nigracans). The model consolidates habitat use information into a framework appropriate for field application and is scaled to produce an index value between 0.0 (unsuitable habitat) to 1.0 (optimum habitat). Habitat suitability index (HSI) models are designed to be used with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1983

Habitat Suitability Index Models: Black-capped chickadee

A review and synthesis of existing information was used to develop a habitat model for the black-capped chickadee (Parus atricapillus). The model is scaled to produce an index of habitat suitability between 0 (unsuitable habitat) and 1 (optimally suitable habitat) for areas of the continental United States. Habitat suitability indexes are designed for use with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1983

Habitat Suitability Index Models: Downy woodpecker

A review and synthesis of existing information was used to develop a habitat model for the downy woodpecker (Picoides eubescens). The model is scaled to produce an index of habitat suitability between 0 (unsuitable habitat) and 1 (optimally suitable habitat) for areas of the continental United States. Habitat suitability indexes are designed for use with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1983

Habitat Suitability Index Models: Pileated woodpecker

A review and synthesis of existing information was used to develop a habitat model for the pileated woodpecker (Dryocopus pileatus). The model is scaled to produce an index of habitat suitability between 0 (unsuitable habitat) and 1 (optimally suitable habitat) for areas of the continental United States. Habitat suitability indexes are designed for use.with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.

FWS/OBS↗

USGS1982

Habitat models for land-use planning: assumptions and strategies for development

Wildlife managers have long recognized that management goals must be constrained by the availability and suitability of habitat. This recognition, combined with ever increasing land development pressures, has resulted in environmental legislation emphasizing systematic approaches to collection and analysis of habitat information. Wildlife planners have responded with a variety of approached to the development of models that quantify habitat requirements. The use of habitat models in wildlife management is certainly not a new concept. Early models attempted to relate habitat quality and quantity as defined by various life requisites (Trippensee 1948). Conceptually, these early approaches are identical to many contemporary efforts directed at modeling habitat. This paper has two objectives related to contemporary habitat modeling approaches. The first objective is to characterize the assumptions and limitations inherent to operational habitat models. Various approaches to habitat modeling, some of which will be discussed at this conference, are described in their own terminology-which tends to obscure the fact that they have common ideals and are subject to the same sets of limitations. The second objective of this paper is to describe a strategy for development of habitat models consistent with these potential limitations. There seems to be two divergent perspectives on operational habitat models. The first is an ideal perspective, which views operational habitat models with skepticism because the current state of habitat knowledge is limited. The second is a pragmatic perspective, which recognizes that available habitat information, no matter how incomplete, can be used to improve the credibility of a land-use decision. The strategy outlined in this paper is directed toward the latter perspective but may help to bridge the gap between the pragmatic and ideal.

Book↗

USGS1982

Habitat Suitability Index Models: Yellow warbler

Habitat preferences of the yellow warbler (Dendroica petechia) are described in this publication. It is one of a series of Habitat Suitability Index (HSI) models and was developed through an analysis of available information on the species-habitat requirements of the species. Habitat use information is presented in a review of the literature, followed by the development of an HSI model, designed for use in impact assessment and habitat management activities.

FWS/OBS↗

USGS1982

Habitat Suitability Index Models: Pine warbler

Habitat preferences of the pine warbler (Dendroica pinus) are described in this publication, which is one of a series of Habitat Suitability Index (HSI) models. Habitat use information is presented in a synthesis of the literature on the species-habitat requirements of the pine warbler, followed by the development of the HSI model. The model is presented in three formats: graphic, word, and mathematical, and is designed to provide information for use in impact assessment and habitat management activities.

FWS/OBS↗

USGS1982

Habitat Suitability Index Models: Eastern meadowlark

Habitat preferences of the eastern meadowlark (Sturnella magna) are described in this publication, which is one of a series of Habitat Suitability Index (HSI) models. Habitat use information is presented in a synthesis of the literature on the species-habitat requirements of the eastern meadowlark, followed by the development of the HSI model. The model is presented in three formats: graphic, word, and mathematical, and is designed to provide information for use in impact assessment and habitat management activities.

FWS/OBS↗