USGS Science⌕ Search

USGS · 5224859

Estimation and correction of visibility bias in aerial surveys of wintering ducks

Abstract

Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1?100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36?42%, and associated standard errors increased 38?55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A.T. Pearse, P.D. Gerard, S.J. Dinsmore, R.M. Kaminski, K. J. Reinecke. 2008. Estimation and correction of visibility bias in aerial surveys of wintering ducks. https://pubs.usgs.gov/publication/5224859

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Duck nesting response to experimental management of upland habitats in California

Habitat loss and limited upland nesting cover likely constrain waterfowl productivity in intensively managed wetland landscapes in California, USA. We evaluated whether experimental manipulations of upland habitats, including the seeding of native plants, dense nesting cover, or cereal grains, could enhance nesting vegetation and improve duck nest density and nest survival in a Mediterranean climate. During 2008 to 2013, we used a before-after-control-impact (BACI) experimental design within 15 upland grassland fields (each 12–28 ha in size) at a state wildlife area to evaluate habitat management treatment effects on nest site vegetation, vegetation structure, and reproductive performance of mallard ( Anas platyrhynchos ) and gadwall ( Mareca strepera ). The BACI design allowed vegetation and duck nesting responses in treated fields to be compared to untreated control fields both before and after treatment implementation. Prior to treatment implementation, all study fields consisted of upland grasslands dominated primarily by non-native annual grasses typical of Mediterranean-climate ecosystems in California. Relative to control fields, we observed only limited improvement to duck nest success in fields seeded with cereal grains and dense nesting cover, whereas fields seeded with native plants showed persistently lower duck nest survival. Vegetation composition after treatment application shifted rapidly from plants that were purposefully seeded to non-native grasses (e.g., Italian ryegrass [ Lolium multiflorum ]) by the second and third years after treatment. Vegetation structural metrics (i.e., visual obstruction height, lateral density, and canopy density) also showed limited or no improvement attributable to the experimental treatments. Across nearly all treatment and control fields, duck nest densities increased during the first several years following treatment implementation but later declined towards pre-treatment levels by the fourth year after treatment. However, mallard nest densities increased much more markedly in native fields than in control fields in the early post-treatment years but declined again in later post-treatment years, suggesting limited long-term benefit. Clutch size, nest initiation date, and egg hatching success were not affected by treatments. Our results indicate that vegetation management and direct seeding had limited short-term and no measurable long-term benefits to the vegetation's structure, duck nesting densities, or duck nest survival, and upland habitat conditions showed little sustained improvement during later breeding seasons (years 2–4 post-treatment). Upland restoration efforts in agricultural landscapes may need more continued, multi-year habitat management to improve nesting conditions for waterfowl over the long-term.

California↗

Beginning with a single step: A social theory of change for managing chronic wasting disease

Emerging wildlife diseases, like chronic wasting disease (CWD), not only lead to changing dynamics within the ecology of the susceptible species but also to changes within interrelated social and management systems. Chronic wasting disease has proven challenging to manage partially because the best management practices (BMP) available have conflicted with historical cervid management paradigms. In support of CWD management decisions, we conducted an expert elicitation investigation of potential intervention strategies that experts believed would positively affect CWD management. The most prioritized intervention was “understanding audiences, outreach, and engagement with public.” Using the most prioritized intervention theme, we continued the expert elicitation process to develop a social theory of change that describes the expected results of implementing the intervention theme. The results chain describes a process of conducting social science investigation to gather evidence and understand the situation and use the gathered evidence to support the selection of appropriate behavior change strategies and pathways prior to implementing a desired CWD management action. The produced social theory of change provides CWD managing organizations with a framework for evaluating efforts to engage with the public about the actions they are taking and working to increase support or participation.

Journal of Wildlife Management↗

White light reduces flight height of birds in low-density migration corridor

Artificial light at night (ALAN) has been shown to influence the behavior of migratory birds, yet how different light spectra modulate these effects remains unclear. We conducted a field experiment for 31 nights at a remote site in northern Colorado, USA, using 2 800-W light-emitting diode (LED) floodlights with white, red, amber, and blue lighting treatments during fall migration in 2023 and 2024. Using a vertical-looking radar system, we quantified avian in-flight responses in migration traffic rate, flight height, and flight direction between paired control periods with no light and periods with lighting treatments. Although we found no effects of our treatments on migration traffic rate and weak effects on flight direction, we found that broad-spectrum white light with emissions across a 400–600 nm spectrum reduced mean avian flight height by an estimated 22.57 m (±10.53 SE) compared to dark periods, and this response was stronger than red and blue lighting treatments. Our ability to detect behavior changes from a point source in a rural, low-density migration system supports the notion that the effects of artificial light at night on bird behavior may be more pervasive than is often recognized, and that this varies by ALAN spectra. Beyond providing insight into avian orientation and in-flight behavior, our results have implications for future research, the conservation management of artificial light at night, and lighting designs that minimize effects on migratory birds.

Colorado↗