Using Song Dialects to Assess the Migration Strategy of the Golden-crowned Sparrow

Most techniques used to study migration of wild birds require capture for banding or for attachment and/or recovery of tags or transmitters. We took advantage of the fact that the Golden-crowned Sparrow (Zonotrichia atricapilla) sings in winter, combined with published data on the distribution of its distinct song dialects in the breeding range, to assess its migration strategy and migratory connectivity by means of these dialects. Using recordings of the Golden-crowned Sparrow’s song across much of its winter range, we categorized these birds by song type to identify their likely origin in some subset of the breeding range. This method allows examination of migration without the need to capture birds. Our results fit best with a pattern of chain migration, with the northernmost breeders wintering in the northernmost part of the winter range, and the southerly breeders wintering farther south. The results suggest strong migratory connectivity between segments of the breeding and winter ranges, though our small sample size makes it difficult to draw firm conclusions on connectivity.

Quantifying effects of snow depth on caribou winter range selection and movement in Arctic Alaska

Background Caribou and reindeer across the Arctic spend more than two thirds of their lives moving in snow. Yet snow-specific mechanisms driving their winter ecology and potentially influencing herd health and movement patterns are not well known. Integrative research coupling snow and wildlife sciences using observations, models, and wildlife tracking technologies can help fill this knowledge void. Methods Here, we quantified the effects of snow depth on caribou winter range selection and movement. We used location data of Central Arctic Herd (CAH) caribou in Arctic Alaska collected from 2014 to 2020 and spatially distributed and temporally evolving snow depth data produced by SnowModel. These landscape-scale (90 m), daily snow depth data reproduced the observed spatial snow-depth variability across typical areal extents occupied by a wintering caribou during a 24-h period. Results We found that fall snow depths encountered by the herd north of the Brooks Range exerted a strong influence on selection of two distinct winter range locations. In winters with relatively shallow fall snow depth (2016/17, 2018/19, and 2019/20), the majority of the CAH wintered on the tundra north of the Brooks Range mountains. In contrast, during the winters with relatively deep fall snow depth (2014/15, 2015/16, and 2017/18), the majority of the CAH caribou wintered in the mountainous boreal forest south of the Brooks Range. Long-term (19 winters; 2001–2020) monitoring of CAH caribou winter distributions confirmed this relationship. Additionally, snow depth affected movement and selection differently within these two habitats: in the mountainous boreal forest, caribou avoided areas with deeper snow, but when on the tundra, snow depth did not trigger significant deep-snow avoidance. In both wintering habitats, CAH caribou selected areas with higher lichen abundance, and they moved significantly slower when encountering deeper snow. Conclusions In general, our findings indicate that regional-scale selection of winter range is influenced by snow depth at or prior to fall migration. During winter, daily decision-making within the winter range is driven largely by snow depth. This integrative approach of coupling snow and wildlife observations with snow-evolution and caribou-movement modeling to quantify the multi-facetted effects of snow on wildlife ecology is applicable to caribou and reindeer herds throughout the Arctic.

Noninvasive genetic surveys before and after a megafire detect displacement of migratory mule deer

Due to climate change and past logging and fire suppression, the western US are experiencing increasingly large and frequent wildfires. Understanding how wildlife respond to these mega-fires is becoming increasingly relevant to protect and manage these populations. However, the lack of predictability inherent in such events makes studies difficult to plan. We took advantage of a large high-severity wildfire that burned adjacent to an ongoing study of mule deer (Odocoileus hemionus) on their summer range upslope of the fire to investigate their displacement onto our study area both immediately and upon their return to summer range the following year. We used spatial capture-recapture models in conjunction with noninvasive fecal DNA sampling to estimate density and non-spatial Pradel robust-design models to estimate apparent survival and recruitment rates. Compared to density before the fire, we observed an increase in deer density and an increase in per-capita recruitment rates one month after the fire. These findings suggest that the immediate response of at least some deer was to flee the fire upslope onto the study area rather than to downslope toward their winter range. These changes did not carry over into the following year, however, suggesting that deer formerly using the burned area as summer range may have returned there despite the high severity of the fire, or may have chosen new areas for their summer range. This suggests that, at least in the short term, the fire did not negatively affect the deer population.

Predicting multi-predator risk to elk (Cervus canadensis) using scats: Are migrant elk exposed to different predation risk?

There is evidence that prey can perceive the risk of predation and alter their behaviour in response, resulting in changes in spatial distribution and potential fitness consequences. Previous approaches to mapping predation risk quantify predator space use to estimate potential predator-prey encounters, yet this approach does not account for successful predator attacks resulting in prey mortality. An exception is a prey kill-site, which reflects an encounter resulting in mortality, but obtaining these data can be expensive and requires time to accumulate adequate sample sizes. We illustrate an alternative approach using predator scat locations and their contents to quantify spatial predation risk for elk (Cervus canadensis) from multiple predators in Alberta, Canada. We combined predictions of scat-based resource selection functions for bears (Ursus arctos/U. americanus), cougars (Puma concolor), coyotes (Canis latrans), and wolves (C. lupus) based on scat-detection dog surveys with predictions for the probability that a predator-specific scat in a location contained elk. We evaluated our approach by comparing predictions to a predation risk model developed from elk kill sites and applied it to describing spatial patterns in predation risk that were consistent with changes in the distribution of elk over the past decade. We found a strong correlation between risk predicted by kill sites and risk predicted by our approach (r = 0.98, P < 0.001). There was a spatial pattern to predation risk, where elk that migrated east of their winter range were exposed to highest risk from cougars, non-migratory elk were exposed to high risk from wolves and bears, and risk to elk that migrated west of their winter range into protected areas was high only from bears. The patterns in predator risk were consistent with changes in the migratory tactics in this population. The scat-based approach we present permits broad-scale inferences on predation risk for prey.

Predicting multi-predator risk to elk (Cervus canadensis) using scats: Are migrant elk exposed to different predation risk?

There is evidence that prey can perceive the risk of predation and alter their behaviour in response, resulting in changes in spatial distribution and potential fitness consequences. Previous approaches to mapping predation risk quantify predator space use to estimate potential predator-prey encounters, yet this approach does not account for successful predator attacks resulting in prey mortality. An exception is a prey kill-site, which reflects an encounter resulting in mortality, but obtaining these data can be expensive and requires time to accumulate adequate sample sizes. We illustrate an alternative approach using predator scat locations and their contents to quantify spatial predation risk for elk (Cervus canadensis) from multiple predators in Alberta, Canada. We combined predictions of scat-based resource selection functions for bears (Ursus arctos/U. americanus), cougars (Puma concolor), coyotes (Canis latrans), and wolves (C. lupus) based on scat-detection dog surveys with predictions for the probability that a predator-specific scat in a location contained elk. We evaluated our approach by comparing predictions to a predation risk model developed from elk kill sites and applied it to describing spatial patterns in predation risk that were consistent with changes in the distribution of elk over the past decade. We found a strong correlation between risk predicted by kill sites and risk predicted by our approach (r = 0.98, P < 0.001). There was a spatial pattern to predation risk, where elk that migrated east of their winter range were exposed to highest risk from cougars, non-migratory elk were exposed to high risk from wolves and bears, and risk to elk that migrated west of their winter range into protected areas was high only from bears. The patterns in predator risk were consistent with changes in the migratory tactics in this population. The scat-based approach we present permits broad-scale inferences on predation risk for prey.

Integrating tracking and resight data enables unbiased inferences about migratory connectivity and winter range survival from archival tags

Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. We show that integrating geolocator recovery data and mark–resight data enables unbiased estimates of both migratory connectivity between breeding and nonbreeding populations and region-specific survival probabilities for wintering locations. Using simulations, we first demonstrate that an integrated Bayesian model returns unbiased estimates of transition probabilities between seasonal ranges. We also used simulations to determine how different sampling designs influence the estimability of transition probabilities. We then parameterized the model with tracking data and mark–resight data from declining Painted Bunting (Passerina ciris) populations breeding in the eastern United States, hypothesized to be threatened by the illegal pet trade in parts of their Caribbean, nonbreeding range. Consistent with this hypothesis, we found that male buntings wintering in Cuba were 20% less likely to return to the breeding grounds than birds wintering elsewhere in their range. Improving inferences from archival tags through proper data collection and further development of integrated models will advance our understanding of the full annual cycle ecology of migratory species.

Monitoring through Community Science: Anna’s Hummingbird Winter Range Expansion into Idaho

Increased urbanization and supplementary feeding are implicated in driving the expansion of the range of the Anna’s Hummingbird (Calypte anna). In many areas this range expansion has been well described, but the recent expansion of the northeastern limit of the nonbreeding distribution, in winter in Idaho, has not yet been summarized. Using data from the Idaho Bird Records Committee database and www.eBird.org from 1976 through 2020, we collated records for Idaho and supplemented them with data from a community-science program of monitoring by homeowners. Our additional effort to solicit records from the community shows that database records and feeder observations alone underestimate the number of individuals present in the state. Through banding and color-marking of 58 individual hummingbirds at private residences, we documented six instances of Anna’s Hummingbirds returning to a site in successive winters, found a roughly even sex ratio, and found a ratio of adults to juveniles of about 3:1. Anna’s Hummingbird may now be a sparse year-round resident in parts of Idaho.

288 Forage mineral and nutrient element concentrations on sheep winter range

Supplementation strategies and nutritional management of ewes during critical production periods of breeding and gestation is an important consideration, particularly when ewes are on winter range. Clinical and subclinical trace mineral deficiencies at these times limit ewe productivity in these extensive environments. The objectives of this study were to (1) quantify mineral element concentrations of common forages on winter range, and (2) evaluate producer supplementation strategies using a survey. We hypothesized that mineral element concentrations in winter forages were inadequate to meet ewe requirements during critical production stages and shrub species would contain higher levels of macro- and micro-mineral element concentrations than grass species. Forage samples were collected from 25 ranches across Wyoming winter range and were compiled by species and analyzed for nutrient and mineral element composition; however, data presented herein represents the first year of data collection (12 of 25 ranches). Nutrient and mineral element concentration results indicated an effect in CP, Ca, P, K, Mg, S, Na, Zn, Cu, Se, Mn, and Mo concentrations between grass and shrub species (P &lt; 0.05). Specifically, Mg and Mo concentrations were higher in grasses while the other mineral element concentrations were higher in shrubs. No effect was observed for Fe and Co concentrations between grass and shrub species (P = 0.37 and P = 0.29). Survey results revealed that 80% of ranches had more than 1000 sheep, and 47% of respondents utilized winter range for 131 to 170 day periods throughout production year. While on winter range the majority of producers (47%) supplement with a protein source. Additionally, 58% do not supplement white salt, while 47% supplement a complete trace mineral mix.