Roland L. Redmond

Classifying and mapping wildfire severity : A comparison of methods

This study evaluates six different approaches to classifying and mapping fire severity using multi-temporal Landsat Thematic Mapper data. The six approaches tested include: two based on temporal image differencing and ratioing between pre-fire and post-fire images, two based on principal component analysis of pre- and post-fire imagery, and two based on artificial neural networks, one using just postfire imagery and the other both pre- and post-fire imagery. Our results demonstrated the potential value for any of these methods to provide quantitative fire severity maps, but one of the image differencing methods (ND4/7) provided a flexible, robust, and analytically simple approach that could be applied anywhere in the Continental U.S. Based on the results of this test, the ND4/7 was implemented operationally to classify and map fire severity over 1.2 million hectares burned in the Northern Rocky Mountains and Northern Great Plains during the 2000 fire season, as well as the 2001 fire season (Gmelin and Brewer, 2002). Approximately the same procedure was adopted in 2001 by the USDA Forest Service, Remote Sensing Applications Center to produce Burned Area Reflectance Classifications for national-level support of Burned Area Emergency Rehabilitation activities (Orlemann, 2002).

Estimation and Mapping of Misclassification Probabilities for Thematic Land Cover Maps

There is abundant evidence that thematic map accuracy may vary across a landscape in a manner that is only partially related to land cover type. Spatial variation in accuracy may be attributable to factors such as terrain, landscape complexity, and land use patterns. There may be serious consequences in the construction and application of thematic maps when the pattern and degree of spatial variation of map accuracy is not understood. Classification error matrices, the usual summary of thematic map accuracy, are not a natural tool for analyzing spatial variation in accuracy. This article presents a method of mapping spatially based estimates of map accuracy. We formulate a concept of misclassification probability and present a method of estimating misclassification probabilities at training observation locations. Misclassification probability estimates are then interpolated from the training locations to a lattice of points via Kriging. The last step uses the lattice to construct a contour accuracy map. We illustrate the method by constructing an accuracy map for a full Landsat Thematic Mapper scene covering a portion of central Idaho and western Montana, and a finer resolution accuracy map for a small area within that scene. The method is found to provide valuable information on the spatial distribution and variation of map accuracy for both decision-makers and GIS analysts.

LINKING DEMOGRAPHIC EFFECTS OF HABITAT FRAGMENTATION ACROSS LANDSCAPES TO CONTINENTAL SOURCE–SINK DYNAMICS

Forest fragmentation may cause increased brood parasitism and nest pre- dation of breeding birds. In North America, nest parasitism and predation are expected to increase closer to forest edges because the brood-parasitic Brown-headed Cowbird (Mol- othrus ater) and generalist nest predators often enter the forest from adjoining developed (largely agricultural) habitats. Yet the abundance of brood parasites and nest predators at the patch scale may be strongly constrained by the total area of developed habitat at landscape scales. The scale and extent of landscape effects are unclear, however, because past studies were mostly conducted within local landscapes rather than across independent landscapes. We report replicated studies from 30 independent landscapes across 17 states of the United States that show that nest parasitism is strongly affected by fragmentation at a 20 km radius scale, equivalent to the maximum foraging range of cowbirds. Nest predation is influenced by both edge and landscape effects, and increases with fragmentation at a 10 km radius scale. Predation is additive to parasitism mortality, and the two together yield decreased population growth potential with increasing forest fragmentation at a 10 km radius scale for 20 of 22 bird species. Mapping of population growth potential across continental landscapes displays broad impacts of fragmentation on population viability and allows geographic prioritization for conservation.

An Automated Technique for Delineating and Characterizing Valley-Bottom Settings

Accurate delineation and characterization of valley-bottom settings is crucial to the assessment of the biological and geomorphological components of riverine systems; yet, to date, most valley-bottom mapping endeavors have been done manually. To improve this situation, we developed automated techniques in a Geographic Information System (GIS) for delineating and characterizing valley-bottom settings in river basins ranging in size from approximately 1,000–10,000 km2. All procedures were developed with ARC/INFO GIS software and fully automated in Arc Macro Language (AML). The GRID module is required for valley-bottom delineation and slope calculations; whereas characterization (i.e., measuring the width of the valley-bottom zone) requires Coordinate Geometry (COGO) in the ARCEDIT module. The process requires three inputs: a polygon coverage of the analysis area; an arc coverage of its hydrography, and a grid representing its digital elevation. The AML is designed to operate within a wide range of computer memory/disk space options, and it allows users to customize several procedures to match the scale and complexity of a given analysis area with available computer hardware.

Natal philopatry and breeding area fidelity of long-billed curlews (Numenius americanus): Patterns and evolutionary consequences

SummaryLong-billed curlews (Numenius americanus) appear unique among scolopacid shorebirds so far studied in possessing a significant sex bias in natal philopatry. We resighted 9 curlews at least attempting to breed that were color-banded as chicks; 8 of these were males. Male curlews also cooperate extensively with neighbors in mobbing potential chick predators. This mutualistic behavior may have evolved through kin selection among philopatric males. If so, we would expect such an evolutionary consequence to lead to a similar sex bias in breeding area fidelity. Yet our resightings of colorbanded adults over 4 consecutive years indicate that males and females were equally likely to return to previous nesting territories. Excessive disturbance such as capture and nest loss within a single breeding season was correlated with the likelihood of breeding dispersal by females but not males. This suggests potentially stronger breeding area fidelity of males.

Migration of Bristle-Thighed Curlews on Laysan Island: Timing, Behavior and Estimated Flight Range

Bristle-thighed Curlews (Numenius tahitiensis) fly at least 4,000 km non-stop from staging grounds in western Alaska to the northern edge of the winter range at Laysan Island in the Northwestern Hawaiian Islands. Adults migrate from Laysan in early May and return in July and August. Juveniles, which arrive in late August and early September, largely migrate unaccompanied by adults. Compared with other shorebirds, Bristle-thighed Curlews migrate in small flocks and show no diurnal pattern in timing of departures. Subadults do not fatten adequately for migration but often accompany departing adults briefly and then return to the island. Fat content in adults at the start of spring migration is high, averaging 42%. Our findings indicate that curlews wintering in the Central and South Pacific overfly Hawaii during spring and autumn, undertaking non-stop flights of >6,000 km. In the absence of tailwinds, only two of the four flight range models that we tested (Summers and Waltner 1979, Davidson 1984) provide reasonable estimates of the migratory performance of Bristle-thighed Curlews (i.e., non-stop flights from Alaska to Laysan and beyond). Within the range of altitudes at which they migrate, curlews probably seek out tailwinds that facilitate long-distance, non-stop flights.

Toward estimation of map accuracy without a probability test sample

The time and effort required of probability sampling for accuracy assessment of large-scale land cover maps often means that probability test samples are not collected. Yet, map usefulness is substantially reduced without reliable accuracy estimates. In this article, we introduce a method of estimating the accuracy of a classified map that does not utilize a test sample in the usual sense, but instead estimates the probability of correct classification for each map unit using only the classification rule and the map unit covariates. We argue that the method is an improvement over conventional estimators, though it does not eliminate the need for probability sampling. The method also provides a new and simple method of constructing accuracy maps. We illustrate some of problems associated with accuracy assessment of broad-scale land cover maps, and our method, with a set of nine Landsat Thematic Mapper satellite image-based land cover maps from Montana and Wyoming, USA.

Mapping Patterns of Human Use and Potential Resource Conflicts on Public Lands

Focusing on a 2.2 million hectare area surrounding the Lolo National Forest in western Montana, USA, we illustrate a GIS method for predicting patterns of human use on public lands and highlighting potential for impacts on fish and wildlife species. Data inputs include human population count (derived from the 1990 Census), roads and trails, and the predicted distributions of bull trout (Salvelinus confluentus) and 41 terrestrial vertebrates of special concern. Because results highlight areas where conflicts between humans and resources may occur, they are of potential use to land managers. This approach can be applied wherever data are available, and inputs can be varied according to the topics of interest.

Conservation problems and research needs for Bristle-thighed Curlews Numenius tahitiensis on their wintering grounds

The Bristle-thighed Curlew Numenius tahitiensis is a rare shorebird that breeds in western Alaska and winters on oceanic islands in the tropical and subtropical Pacific Ocean. Before human colonization, the islands on which curlews winter were devoid of terrestrial predators, allowing curlews to evolve a rapid moult during which about 50% of adults become flightless. Especially when flightless, these birds are vulnerable to harvest by humans and to predation by introduced mammals such as dogs and cats. On atolls where they are harvested by humans, curlews tend to occur only on uninhabited islets. Consequently, human encroachment in Oceania has probably reduced Bristle-thighed Curlew numbers and altered winter distribution of the species. Future studies should (1) identify concentrations of wintering curlews, focusing in the Tuamotu Archipelago; (2) determine whether migratory stopover sites exist in the central Pacific between Hawaii and the southern end of the wintering grounds; and (3) establish a monitoring programme to assess population trends in several parts of the winter range. A comprehensive plan is needed to provide for the existence of predator-free islands throughout key portions of the winter range.

Application of Ecological Classification and Predictive Vegetation Modeling to Broad-Level Assessments of Ecosystem Health

The Little Missouri National Grasslands (LMNG) of western North Dakota support the largest permitted cattle grazing use within all lands administered by the USDA, Forest Service, as well as critical habitat for many wildlife species. This fact, coupled with the need to revise current planning direction for range allotments of the LMNG, necessitated that a broad-level characterization of ecosystem integrity and resource conditions be conducted across all lands within the study area (approximately 800,000 hectares) in a rapid and cost-effective manner. The approach taken in this study was based on ecological classifications, which effectively utilized existing field plot data collected for a variety of previous inventory objectives, and their continuous spatial projection across the LMNG by maps of both existing and potential vegetation. These two map themes represent current and reference conditions (existing vs. potential vegetation); their intersection allowed us to assign various ecological status ratings (i.e., ecosystem integrity and resource condition) based on the degree of departure between current and reference conditions. In this paper, we present a brief review of methodologies used in the development of ecological classifications, and also illustrate their application to assessments of rangeland health through selected maps of ecological status ratings for the LMNG.