USGS Science⌕ Search
Home/Archive/USGS

USGS · 70271944

Accounting for seasonal patterns in bird availability prevents biased population trend estimates with advancing spring phenology

Emily L. Weiser·James Johnson·Steven M. Matsuoka·Colleen M. Handel
View original source ↗Export metadata ↓

Abstract

Advancing spring phenology has been observed around the world, including changes in the timing of breeding of birds. When singing rates are tied to breeding stage, the rate at which birds are available for detection by surveyors can also show seasonal patterns that may shift with spring phenology. As the timing of peak bird availability changes over years, monitoring programs that do not account for changing availability could incorrectly conclude that there is a change in population size. We used a 20-yr point-count dataset to test for relationships between bird availability and spring vegetation phenology for 27 species in boreal Alaska. Nine of 22 migratory species showed a significant effect of day of spring (DOS) on availability, usually with availability declining over the survey window (late spring and early summer). In contrast, 3 of 5 resident species showed availability increasing over the survey window. We then conducted a simulation study to evaluate how changing spring phenology could affect estimates of population trend under a static survey window. We found that including DOS in the model as a covariate of availability prevented bias in the trend estimates and did not reduce precision. However, when the model ignored the effect of DOS on availability, population trend estimates were often significantly biased when spring phenology was advancing. Our study adds to previous evidence that bird availability is often related to spring phenology, and demonstrates that failing to account for seasonal changes in availability could result in the spurious estimation of a population trend when spring phenology changes over time. In some cases, the bias could be large enough to change species status assessments under IUCN Red List Criteria. Monitoring programs for birds and other taxa with seasonally varying availability could avoid bias by simply measuring and modeling the relationship between DOS and availability.

Explore related subjects

Ornithological ApplicationsArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Emily L. Weiser, James Johnson, Steven M. Matsuoka, Colleen M. Handel. 2025-09-23. Accounting for seasonal patterns in bird availability prevents biased population trend estimates with advancing spring phenology. https://doi.org/10.1093/ornithapp%2Fduaf052

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

KEEP EXPLORING

Related USGS reports

USGS2026

The cost of limited nocturnal roost availability on pre-migratory energy budgets in a central-place foraging shorebird, Numenius hudsonicus (Hudsonian Whimbrel)

Mobile species often travel long distances between the sites they use for different behaviors, such as central-place foragers that make daily commutes between a central roost and foraging sites. For migratory shorebird species that use coastal habitats, the limited availability of suitable nocturnal roost sites can lead individuals to commute long distances to their foraging territories, forcing them to balance the energetic cost of commuting with the need to refuel in between migratory flights. We investigated this potential trade-off in a population of Numenius hudsonicus (Hudsonian Whimbrel) that show wide variation in commute distance between a shared central nocturnal roost and individual foraging territories in coastal South Carolina, USA. We combined high-resolution movement data, behavioral state modeling, and empirical foraging behavior data to assess how increasing commute distances from a central nocturnal roost affect individual daily activity budgets, foraging habitat use, potential net energy gain, and breeding ground departure date. We found that N. hudsonicus that commute farther from their nocturnal roost spend a higher proportion of each day foraging and commuting, and that they delay their departure to the breeding grounds by 3–6 days. Our results indicate that roosting habitat close to foraging areas can reduce the energetic cost of commuting to help shorebirds avoid delays in migratory timing. Thus, protecting, restoring, and creating nocturnal roosting habitat close to foraging areas may enhance successful shorebird migration.

South Carolina↗
USGS2026

Modeling observational uncertainty improves estimation of breeding-season parameters that inform lek-based monitoring for Centrocercus urophasianus (Greater Sage-Grouse)

Counts of males on leks are widely used as abundance indices to monitor populations of lek-breeding species, but they can be influenced by variation in male attendance, inter-lek movement, and mortality. When there is imperfect observability of males on leks, estimates of lek attendance and inter-lek movement are likely to be biased low. We compared traditional multi-state mark–recapture (MSMR) and MSMR models with state uncertainty (MSMR-SU) to determine how accounting for uncertainty in GPS-derived lek attendance improves inference of rates underlying lek-based abundance indices for male Centrocercus urophasianus (Greater Sage-Grouse). We found that modeling observational uncertainty with MSMR-SU models consistently reduced bias in lek attendance and inter-lek movement estimates for adult and yearling males compared to MSMR models. Estimates of daily maximum male lek attendance (adults: 0.79; yearlings: 0.68) and inter-lek movement rates (adults: 0.10; yearlings: 0.07) from MSMR-SU models were higher than daily maximum lek attendance (adults: 0.74; yearlings: 0.55) and inter-lek movement rates (adults: 0.01; yearlings: 0.04) from MSMR models. Consistent with previous studies, adults exhibited higher lek attendance and mortality rates than yearlings. However, unlike earlier studies, inter-lek movement rates were similar between age classes, with adults tending to move earlier in the lekking season than yearlings. Wind speed and precipitation had a weak negative effect on lek attendance. Greater distance to the nearest known lek strongly reduced inter-lek movement. Accounting for lekking-season mortality shifted the estimated date of maximum lek attendance earlier in the season by 8–9 days for adults and 1–3 days for yearlings. Accounting for state uncertainty due to error in state assignment should reduce bias in demographic estimates for use in wildlife conservation and management decisions.

Colorado, Wyoming↗
USGS2026

Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data

Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.

Michigan, Minnesota, Wisconson↗