Geology topics

J.E. Howell

Publications and source records attributed to J.E. Howell.

3 recordsLinked to original sources

USGS2010

Building hierarchical models of avian distributions for the State of Georgia

To predict the distributions of breeding birds in the state of Georgia, USA, we built hierarchical models consisting of 4 levels of nested mapping units of decreasing area: 90,000 ha, 3,600 ha, 144 ha, and 5.76 ha. We used the Partners in Flight database of point counts to generate presence and absence data at locations across the state of Georgia for 9 avian species: Acadian flycatcher (Empidonax virescens), brownheaded nuthatch (Sitta pusilla), Carolina wren (Thryothorus ludovicianus), indigo bunting (Passerina cyanea), northern cardinal (Cardinalis cardinalis), prairie warbler (Dendroica discolor), yellow-billed cuckoo (Coccyxus americanus), white-eyed vireo (Vireo griseus), and wood thrush (Hylocichla mustelina). At each location, we estimated hierarchical-level-specific habitat measurements using the Georgia GAP Analysis18 class land cover and other Geographic Information System sources. We created candidate, species-specific occupancy models based on previously reported relationships, and fit these using Markov chain Monte Carlo procedures implemented in OpenBugs. We then created a confidence model set for each species based on Akaike's Information Criterion. We found hierarchical habitat relationships for all species. Three-fold cross-validation estimates of model accuracy indicated an average overall correct classification rate of 60.5%. Comparisons with existing Georgia GAP Analysis models indicated that our models were more accurate overall. Our results provide guidance to wildlife scientists and managers seeking predict avian occurrence as a function of local and landscape-level habitat attributes.

Journal of Wildlife Management↗

USGS2009

Conservation of northern bobwhite on private lands in Georgia, USA under uncertainty about landscape-level habitat effects

Large-scale habitat enhancement programs for birds are becoming more widespread, however, most lack monitoring to resolve uncertainties and enhance program impact over time. Georgia?s Bobwhite Quail Initiative (BQI) is a competitive, proposal-based system that provides incentives to landowners to establish habitat for northern bobwhites (Colinus virginianus). Using data from monitoring conducted in the program?s first years (1999?2001), we developed alternative hierarchical models to predict bobwhite abundance in response to program habitat modifications on local and regional scales. Effects of habitat and habitat management on bobwhite population response varied among geographical scales, but high measurement variability rendered the specific nature of these scaled effects equivocal. Under some models, BQI had positive impact at both local farm scales (1, 9 km2), particularly when practice acres were clustered, whereas other credible models indicated that bird response did not depend on spatial arrangement of practices. Thus, uncertainty about landscape-level effects of management presents a challenge to program managers who must decide which proposals to accept. We demonstrate that optimal selection decisions can be made despite this uncertainty and that uncertainty can be reduced over time, with consequent improvement in management efficacy. However, such an adaptive approach to BQI program implementation would require the reestablishment of monitoring of bobwhite abundance, an effort for which funding was discontinued in 2002. For landscape-level conservation programs generally, our approach demonstrates the value in assessing multiple scales of impact of habitat modification programs, and it reveals the utility of addressing management uncertainty through multiple decision models and system monitoring.

Landscape Ecology↗

USGS2008

Sources of variation in detection of wading birds from aerial surveys in the Florida Everglades

We conducted dual-observer trials to estimate detection probabilities (probability that a group that is present and available is detected) for fixed-wing aerial surveys of wading birds in the Everglades system, Florida. Detection probability ranged from <0.2 to similar to 0.75 and varied according to species, group size, observer, and the observer's position in the aircraft (front or rear seat). Aerial-survey simulations indicated that incomplete detection can have a substantial effect oil assessment of population trends, particularly river relatively short intervals (<= 3 years) and small annual changes in population size (<= 3%). We conclude that detection bias is an important consideration for interpreting observations from aerial surveys of wading birds, potentially limiting the use of these data for comparative purposes and trend analyses. We recommend that workers conducting aerial surveys for wading birds endeavor to reduce observer and other controllable sources of detection bias and account for uncontrollable sources through incorporation of dual-observer or other calibratior methods as part of survey design (e.g., using double sampling).

The Auk↗