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P.J. Heglund

Publications and source records attributed to P.J. Heglund.

11 recordsLinked to original sources
USGS2011

Climate change, uncertainty, and natural resource management

Climate change and its associated uncertainties are of concern to natural resource managers. Although aspects of climate change may be novel (e.g., system change and nonstationarity), natural resource managers have long dealt with uncertainties and have developed corresponding approaches to decision-making. Adaptive resource management is an application of structured decision-making for recurrent decision problems with uncertainty, focusing on management objectives, and the reduction of uncertainty over time. We identified 4 types of uncertainty that characterize problems in natural resource management. We examined ways in which climate change is expected to exacerbate these uncertainties, as well as potential approaches to dealing with them. As a case study, we examined North American waterfowl harvest management and considered problems anticipated to result from climate change and potential solutions. Despite challenges expected to accompany the use of adaptive resource management to address problems associated with climate change, we conclude that adaptive resource management approaches will be the methods of choice for managers trying to deal with the uncertainties of climate change. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗
USGS2011

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.

Aquatic Botany↗
USGS2008

Long-term change in limnology and invertebrates in Alaskan boreal wetlands

Climate change is more pronounced at high northern latitudes, and may be affecting the physical, chemical, and biological attributes of the abundant wetlands in boreal forests. On the Yukon Flats, located in the boreal forest of northeast Alaska, wetlands originally sampled during 1985-1989 were re-sampled for water chemistry and macroinvertebrates in summer 2001-2003. Wetlands sampled lost on average 19% surface water area between these periods. Total nitrogen and most metal cations (Na, Mg, and Ca, but not K) increased between these periods, whereas total phosphorus and chlorophyll a (Chl a) declined. These changes were greater in wetlands that had experienced more drying (decreased surface area). Compared with 1985-1989, densities of cladocerans, copepods, and ostracods in both June and August were much higher in 2002-2003, whereas densities of amphipods, gastropods, and chironomid larvae were generally lower. In comparisons among wetlands in 2002-2003 only, amphipod biomass was lower in wetlands with lower Chl a, which might help explain the decline of amphipods since the late 1980s when Chl a was higher. The decline in Chl a corresponded to greatly increased zooplankton density in June, suggesting a shift in carbon flow from scrapers and deposit-feeders to water-column grazers. Declines in benthic and epibenthic deposit-feeding invertebrates suggest important food web effects of climate change in otherwise pristine wetlands of the boreal forest. ?? 2008 Springer Science+Business Media B.V.

Hydrobiologia↗
USGS2008

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

Environmental and Ecological Statistics↗
USGS2006

Comparative ecology of the Flammulated Owl and Northern Saw-whet Owl during fall migration

We compared the migration ecology of two owl species that exhibit different migration strategies: the Flammulated Owl (Otus flammeolus) and the Northern Saw-whet Owl (Aegolius acadicus). During fall 1999-2004, we captured 117 Flammulated Owls and 1433 Northern Saw-whet Owls in the southern Boise Mountains of southwestern Idaho. These owl species exhibited contrasting seasonal timing and body condition. Flammulated Owl captures peaked in mid-September and Northern Saw-whet Owl captures peaked in early to mid-October. Flammulated Owls displayed greater body condition than Northern Saw-whet Owls and increasing condition scores during the season, whereas Northern Saw-whet Owls had no apparent seasonal condition patterns. Based on seasonal timing of captures, both species showed unimodal movement patterns characteristic of fall migrants. However, in 1999 both species' capture rates were at least double those in other years of this study. Flammulated Owls' earlier arrival and departure, coupled with superior body condition, were consistent among years and typical of a long-distance migration strategy. In contrast, the Northern Saw-whet Owls' later arrival, more lengthy passage, and variable body condition were more characteristic of a short-distance migrant strategy. Furthermore, Northern Saw-whet Owls' body condition was significantly lower during the irruptive year than during nonirruptive years, supporting the notion that population density affects their migratory condition. ?? 2006 The Raptor Research Foundation, Inc.

Journal of Raptor Research↗
USGS2001

Modeling avian detection probabilities as a function of habitat using double-observer point count data

Point counts are a controversial sampling method for bird populations because the counts are not censuses, and the proportion of birds missed during counting generally is not estimated. We applied a double-observer approach to estimate detection rates of birds from point counts in Maryland, USA, and test whether detection rates differed between point counts conducted in field habitats as opposed to wooded habitats. We conducted 2 analyses. The first analysis was based on 4 clusters of counts (routes) surveyed by a single pair of observers. A series of models was developed with differing assumptions about sources of variation in detection probabilities and fit using program SURVIV. The most appropriate model was selected using Akaike's Information Criterion. The second analysis was based on 13 routes (7 woods and 6 field routes) surveyed by various observers in which average detection rates were estimated by route and compared using a t-test. In both analyses, little evidence existed for variation in detection probabilities in relation to habitat. Double-observer methods provide a reasonable means of estimating detection probabilities and testing critical assumptions needed for analysis of point counts.

Book chapter↗
USGS2000

A double-observer approach for estimating detection probability and abundance from point counts

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

The Auk↗
USGS2000

Sensitivity of species habitat-relationship model performance to factors of scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service's Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area <0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of Spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 - minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 - percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy.

Idaho↗
USGS1999

Obtaining environmental measures to facilitate vertebrate habitat modeling

Published literature generally lacks habitat information needed to adequately model the habitats of most wildlife species at large scales (>1:100,000). We searched in primary and secondary literature for occurrence of several potentially useful habitat measures for 20 species of interest to the Idaho Department of Fish and Game. We found adequate information for modeling only the habitats of certain game species and species of special interest. We suggest that many more researchers could collect simple habitat information regarding vegetation composition and structure, topographic features, soils, temperature, and distance to special landscape features such that current research expenses would not be increased significantly. We recommend that habitat data be consistently reported in peer-reviewed literature or deposited into a central data repository. This will not only help fill the gaps in our current knowledge of wildlife but also place it in a format that is readily accessible by the scientific community.

Wildlife Society Bulletin↗
USGS1994

Use of boreal forested wetlands by Pacific loons ( Gavia pacifica Lawrence) and horned grebes ( Podiceps auritus L.): Relations with limnological characteristics

Our objective was to determine if the occurrence and abundance of Pacific loons ( Gavia pacifica Lawrence) and horned grebes ( Podiceps auritus L.) on 123 wetlands of Yukon Flats National Wildlife Refuge in east central Alaska were related to the limnological characteristics of those wetlands. Aquatic bird-wetland use surveys were conducted in conjunction with limnological sampling from May through September 1985–87 and May through August 1989. Results from logistic regression analysis demonstrated a significant association between the probability of wetland use by Pacific loons and shoreline length, water color, calcium and total phosphorus. Wetland use by horned grebes was related to shoreline length, pH, and chlorophyll. Aquatic bird abundance was then used as a Poisson response variable and modeled as a function of wetland limnological characteristics. Our results indicate that Pacific loon abundance was adequately modeled by linear and quadratic functions of shoreline length, color, pH, calcium and total phosphorus. Horned grebe abundance could not be modeled with this approach. The statistical techniques known collectively as generalized linear models provided a framework for the development of models for aquatic bird use of wetlands. Our results, however, indicate that while this approach shows promise, a better understanding of how to model aquatic bird abundance is needed. We then identify problems in model development and suggest avenues for future research.

Alaska↗