Fall survival of American woodcock in the western Great Lakes Region

John G. Bruggink; Eileen J. Oppelt; Kevin Doherty; David E. Andersen; Jed Meunier; R. Scott Lutz

doi:10.1002/jwmg.547

Home/Archive/USGS

USGS · 70168465

Fall survival of American woodcock in the western Great Lakes Region

John G. Bruggink·Eileen J. Oppelt·Kevin Doherty·David E. Andersen·Jed Meunier·R. Scott Lutz

View original source ↗Export metadata ↓

Abstract

We estimated fall (10 Sep–8 Nov) survival rates, cause-specific mortality rates, and determined the magnitude and sources of mortality of 1,035 radio-marked American woodcock ( Scolopax minor ) in Michigan, Minnesota, and Wisconsin during 2001–2004. In all 3 states, we radio-marked woodcock on paired study areas; 1 of which was open to hunting and expected to receive moderate to high hunter use and the other of which was either closed to hunting (Michigan and Minnesota) or was relatively inaccessible to hunters (Wisconsin). We used Program MARK to estimate fall survival rates, to evaluate a set of candidate models to examine the effects of hunting and several covariates (sex, age, year, state) on survival, and to examine the relationship between survival rates and kill rates due to hunting. Hunting accounted for 70% of the 86 woodcock deaths in the hunted areas, followed by predation (20%) and various other sources of mortality (10%). Woodcock deaths that occurred in the non-hunted and lightly hunted areas ( n  = 50) were caused by predators (46%), hunting (32%), and various other sources (22%). Based on small-sample corrected Akaike's Information Criterion values, variation in fall survival of woodcock was best explained by treatment (i.e., hunted vs. non-hunted), year, and period (pre-hunting season intervals vs. hunting season intervals). The average fall survival estimate from our best model for woodcock in the non-hunted areas (0.893, 95% CI = 0.864–0.923) was greater than the average for the hunted areas (0.820, 95% CI = 0.786–0.854 [this estimate includes data from the lightly hunted area in Wisconsin]), and the average treatment effect (i.e., greater survival rates in non-hunted areas) was 0.074 (95% CI = 0.018–0.129). The kill rate due to hunting was 0.120 (95% CI = 0.090–0.151) when data were pooled among states and years. We detected a negative relationship between hunting kill rates and survival in our hunted areas, which suggests that hunting mortality was at least partially additive during fall. Our results illustrate the influence of hunting relative to other sources of mortality in Michigan, Minnesota, and Wisconsin, and indicate that managers may be able to influence fall survival rates by manipulating hunting regulations or access on public land.

Explore related subjects

Journal of Wildlife Management Article

Source-reported bounding extent: 45.12392881616326° to 46.27483447871401° latitude; -93.75869750976562° to -87.6104736328125° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

John G. Bruggink, Eileen J. Oppelt, Kevin Doherty, David E. Andersen, Jed Meunier, R. Scott Lutz. 2013-04-08. Fall survival of American woodcock in the western Great Lakes Region. https://doi.org/10.1002/jwmg.547

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

KEEP EXPLORING

Related USGS reports

USGS2026

Validating antler- and movement-based estimates of caribou reproduction using video camera collars

Wildlife agencies invest substantial resources in monitoring ungulate reproductive rates given ongoing concerns about population trends and their implications for management. For barren-ground caribou ( Rangifer tarandus ) in the North American Arctic, data on parturition and neonate survival have traditionally been collected using visual observations of antler retention and calf presence from small, fixed-wing aircraft. However, these surveys are weather-dependent, expensive, and dangerous, motivating the development of movement-based approaches that infer reproductive events from global positioning system (GPS) location data. We had the unique opportunity to use video camera collars to validate both antler- and movement-based methods for estimating reproduction in barren-ground caribou, using data from the Porcupine (2018–2023) and Western Arctic (2021, 2023) herds in Alaska, USA, and Yukon, Canada. For the movement-based approaches, we assessed individual-based and population-based methods, which both inferred parturition following a sharp decline in movement and inferred calf loss following a sharp increase in movement. We investigated these approaches using rarified 1-, 2-, 4-, and 8-hour fix intervals. Based on video collar observations, we found that antler retention at the onset of the calving period was highly accurate for predicting parturition (96% accuracy) but became unreliable as calving progressed, as approximately 80% of parturient females shed their antlers during the calving period. In contrast, both movement methods performed marginally for estimating caribou parturition (~70% accuracy), with estimates from the individual-based method exhibiting greater bias than those from the population-based method. The individual-based method also poorly predicted neonate survival (≤49% accuracy for detecting parturition and calf fate for the Porcupine Herd). Video data revealed that inaccuracies with the movement methods often occurred when caribou bedded during storms, rested after traversing mountainous terrain, lost a calf shortly after birth, or increased movement to evade insects. These results have important implications for management agencies using antler- and movement-based methods to estimate caribou reproduction, particularly when informing assessments of population decline or recovery. Our results demonstrate the utility of video collar data for validating reproductive monitoring approaches and provide insights into how these approaches can be improved.

Alaska, Yukon↗

USGS2026

Ringtail (Bassariscus astutus) survival in southwestern Oregon

The effective conservation and management of small carnivore populations requires understanding species’ life-history traits and identifying important vital rates that drive population trajectories. However, many of these species are rare or elusive and of state or federal conservation concern, and demographic information is often lacking and difficult to obtain. At the northern limit of their range in Oregon, USA, ringtail ( Bassariscus astutus ) occupy mid-elevation forests and are a species of conservation concern because of their limited distribution and suspected low density. We initiated a radio-telemetry study in 2020 to estimate monthly and annual survival of ringtail in southwest Oregon. We monitored 26 ringtail from November 2020 to October 2022 and estimated survival rates using a known-fate framework and Program MARK. Model-averaged monthly survival estimates ranged from lows of 0.963 (SE = 0.022, 95% CI = 0.887–0.988) in spring (Feb–May) of 2021 to highs of 0.980 (SE = 0.018, 95% CI = 0.889–0.997) in summer (Jun–Oct) of 2022. Model-averaged estimates of annual survival were 0.695 (SE = 0.176, 95% CI = 0.310–0.920) during 2020–2021 and 0.728 (SE = 0.168, 95% CI = 0.336–0.934) during 2021–2022. Predation was the leading cause of mortality, but notably, no mortalities could be attributed to avian predation. Survival rates were much higher within forested landscapes in Oregon than for populations in the southwestern United States, which may have implications for regional conservation and management strategies.

Oregon↗

USGS2026

Linking distribution and return-on-investment models to optimize woody management for prairie grouse in Nebraska

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area-based surveys for greater prairie-chicken ( T. cupido ) and sharp-tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario-based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero-inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return-on-investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3-year period, median estimated annual populations were 142,380 for greater prairie-chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp-tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie-chicken (range of 95% CIs = 7–14%) and 6% for sharp-tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp-tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence-based, quantitative approaches for prioritizing conservation actions on working lands. Scenario-based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.

Nebraska↗