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Emily L. Weiser

Publications and source records attributed to Emily L. Weiser.

At least 19 recordsLinked to original sources
USGS2025

Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds

Animal-borne trackers are commonly used to study bird movements, including in long-distance migrants such as shorebirds. Selecting a tracker and attachment method can be daunting, and methodological advancements often have been made by trial and error and conveyed by word of mouth. We synthesized tracking outcomes across 2745 dorsally mounted trackers on 37 shorebird species around the world. We evaluated how attachment method, power source, data retrieval method, relative tracker mass, and biological traits affected success, where success was defined as whether or not each tag deployment reached its expected tracking duration (i.e. all aspects succeeded for the intended duration of the study: attachment, tracking, data acquisition, and bird survival). We conducted separate analyses for tag deployments with remote data retrieval (‘remote-upload tag deployments') and those that archived data and had to be recovered (‘archival tag deployments'). Among remote-upload tag deployments, those that were a lighter mass relative to the bird, were beyond their first year of production, transmitted data via satellite, or were attached with a leg-loop harness were most often successful at reaching their expected tracking duration. Archival tag deployments were most successful when applied at breeding areas, or when applied to males in any season. Remote-upload tag deployments with solar power, satellite data retrieval, or leg-loop harnesses continued tracking for longer than those with battery power, other types of data retrieval, or glue attachments. However, the majority of tag deployments failed to reach their expected tracking duration (71% of remote-upload, 83% of archival), which could have been due to tracker failure, attachment failure, or bird mortality. Our findings highlight that many tag deployments may fail to meet the goals of a study if tracking duration is crucial. Using our results, we provide guidelines for selecting a tracker and attachment to improve success at meeting study goals.

Journal of Avian Biology↗
USGS2025

Land cover, elevation, and precipitation predict distribution and hotspots of three bird species of concern in boreal Alaska

The boreal forest biome is an important breeding area for migratory birds and is undergoing rapid changes, including drying of wetlands, changes to vegetation composition, and human development. Many boreal bird populations are declining, but information is often lacking on how these species associate with habitat characteristics and thus how they may respond to changing conditions. We used a large point-count dataset to describe habitat associations and hotspots for three boreal species of concern in Alaska, USA: Tringa flavipes (Lesser Yellowlegs), Contopus cooperi (Olive-sided Flycatcher), and Euphagus carolinus (Rusty Blackbird). We used an N-mixture model to evaluate covariates of abundance and two components of detection (availability and perceptibility). We then used the estimated relationships with covariates to predict density of each species across the Northwestern Interior Forest (Bird Conservation Region 4) in Alaska, including identifying hotspots where density was predicted to be in the top 10% of all locations. T. flavipes and E. carolinus were associated with wetlands and mean values of June precipitation; T. flavipes were also associated with low elevation and recent fire; and C. cooperi was associated with needleleaf forest and moderate elevation. Hotspots for T. flavipes and E. carolinus usually overlapped, while hotspots for C. cooperi almost never overlapped with those of the other two species. Following ground-truthing, these predicted distributions could be used to indicate areas of high importance for species of conservation concern and thus inform management decisions and mitigation measures. Our results could also help identify areas that are likely to be important for these species in the future, given the rapid changes now occurring across the boreal biome in response to climate warming and drying.

Alaska↗
USGS2025

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

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.

Alaska↗
USGS2025

Reducing bias in shorebird nest survival rates across a large Arctic landscape

Reproductive success is a key demographic parameter that can have profound impacts on a species' population trend. Indeed, poor reproductive success has been suggested as a contributing factor to the declines observed in many species of birds, including Arctic-breeding shorebirds. However, the available information on Arctic-breeding shorebird nest survival is restricted to a limited number of non-random locations where proximity to human settlements and traditional invasive monitoring techniques may artificially alter nest predation rates and, thus, bias results. To accurately assess reproductive success, unbiased estimates are needed. In this study, we monitored 96 shorebird nests (six species) at 41 randomly selected sites across a large Arctic landscape (1219 km 2 area of the Arctic National Wildlife Refuge) using minimally invasive techniques (i.e. single nest visits, temperature loggers and cameras) in 2019 and 2022. Overall, daily survival was 0.975 (95% CI: 0.955–0.987), which translates to a 53% (95% CI: 32–72%) probability of a shorebird nest surviving the median (25 days) incubation period for the studied species. Camera footage indicated Arctic Foxes Vulpes lagopus were the primary nest predator (85% of identified predation events), but Parasitic Jaegers Stercorarius parasiticus and Sandhill Cranes Grus canadensis also contributed to nest loss. In both years, greater nest failure occurred in the northwest and northcentral regions of our study area, potentially the result of greater shorebird abundance and density-dependent predation rates. Nest survival rates obtained in this study were the same as those obtained in a previous large geographical study that monitored shorebird nests across numerous small, non-randomly selected, high-density shorebird field sites that employed intensive human monitoring techniques. However, site-specific and annual differences in predator and shorebird species and densities make direct comparisons to previous studies difficult. Continued monitoring using methods that minimize bias and are consistent across time are needed to accurately measure true changes in nest survival rates that may occur under a changing climate and with increased human development.

Alaska↗
USGS2024

Geese migrating over the Pacific Ocean select altitudes coinciding with offshore wind turbine blades

Renewable energy facilities are a key part of mitigating climate change, but can pose threats to wild birds and bats, most often through collisions with infrastructure. Understanding collision risk and the factors affecting it can help minimize impacts on wild populations. For wind turbines, flight altitude is a major factor influencing collision risk, and altitude-selection analyses can evaluate when and why animals fly at certain altitudes under certain conditions. We used GPS tags to track Pacific Flyway geese (Pacific greater white-fronted goose, tule greater white-fronted goose and lesser snow goose) on transoceanic migrations between Alaska and the Pacific Coast of the contiguous United States, an area where offshore windfarm development is beginning. We evaluated how geographic and environmental covariates affected (1) whether birds were at rest on the water versus in flight (binomial model) and (2) altitude selection when in flight (similar to a step-selection framework). We then used a Monte Carlo simulation to predict the probability of flying at each altitude under various conditions, considering both the fly/rest decision and altitude selection. In both spring and fall, geese showed strong selection for altitudes within the expected rotor-swept zone (20–200 m asl), with 56% of locations expected to be within the rotor-swept zone under mean daylight conditions and 28% at night. This indicates a high possibility that migrating geese may be at risk of collision when passing through windfarms. Although there was some variation across subspecies, geese were most likely to be within the rotor-swept zone with little wind or light tailwinds, low clouds, little to no precipitation and moderate to cool air temperatures. Geese were unlikely to be in the rotor-swept zone at night, when most individuals were at rest on the water. Synthesis and applications . These results could be used to inform windfarm management, including decisions to shut down turbines when collision risk is high. The altitude-selection framework we demonstrate could facilitate further study of other bird species to develop a holistic view of how windfarms in this area could affect the migratory bird community as a whole.

Journal of Applied Ecology↗
USGS2022

Optimizing surveys of fall-staging geese using aerial imagery and automated counting

Ocular aerial surveys allow efficient coverage of large areas and can be used to monitor abundance and distribution of wild populations. However, uncertainty around resulting population estimates can be large due to difficulty in visually identifying and counting animals from aircraft, as well as logistical challenges in estimating detection probabilities. Photographic aerial surveys can mitigate these challenges and can allow flight at higher altitudes to minimize disturbance of birds and improve safety for surveyors. We evaluated a photographic aerial survey that incorporated a systematic sampling design with automated photo capture and processing for fall-staging geese at Izembek Lagoon, Alaska, in 2017–2019. Ocular aerial surveys have been completed at Izembek Lagoon for >40 years. For the new photo survey, we used a commercial system to automatically trigger cameras at preset points. We then applied a machine-learning algorithm trained to automatically identify and count geese in our photos, manually corrected those counts, and quantified the algorithm's accuracy. We translated corrected counts into density and extrapolated mean density across the entire lagoon to estimate total population size for Pacific brant ( Branta bernicla ) and cackling geese ( B. hutchinsii ). The automated algorithm undercounted geese, but successfully identified the small subset of photos containing geese. Manual correction was therefore needed only for photos automatically identified as containing geese, allowing substantial reduction of workload. Manually-corrected, photo-based estimates of Pacific brant and cackling goose population sizes were larger and more precise than ocular estimates in all 3 years. To reduce costs with little penalty for variance around population estimates, the photographic survey design could be optimized by reducing the number of transects to ~67% of the current number while still manually correcting all photos in which the automated algorithm detected geese. Further years of both ocular and photo surveys would be needed to calibrate the photo estimates against the >40-year timeseries of the ocular survey, after which the photo series could successfully guide management of Pacific brant. As technologies continue to advance, we expect photographic surveys with automated counting to be easily implemented and advantageous to many monitoring programs.

Alaska↗
USGS2021

Fully accounting for nest age reduces bias when quantifying nest survival

Accurately measuring nest survival is challenging because nests must be discovered to be monitored, but nests are typically not found on the first day of the nesting interval. Studies of nest survival therefore often monitor a sample that overrepresents older nests. To account for this sampling bias, a daily survival rate (DSR) is estimated and then used to calculate nest survival to the end of the interval. However, estimates of DSR (and thus nest survival) can still be biased if DSR changes with nest age and nests are not found at age 0. Including nest age as a covariate of DSR and carefully considering the method of estimating nest survival can prevent such biases, but many published studies have not fully accounted for changes in DSR with nest age. I used a simulation study to quantify biases in estimates of nest survival resulting from changes in DSR with nest age under a variety of scenarios. I tested four methods of estimating nest survival from the simulated datasets and evaluated the bias and variance of each estimate. Nest survival estimates were often strongly biased when DSR varied with age but DSR was assumed to be constant, as well as when the model included age as a covariate but calculated nest survival from DSR at the mean monitored nest age (the method typically used in previous studies). In contrast, biases were usually avoided when nest survival was calculated as the product of age-specific estimates of DSR across the full nesting interval. However, the unbiased estimates often showed large variance, especially when few nests were found at young ages. Future field studies can maximize the accuracy and precision of nest survival estimates by aiming to find nests at young ages, including age as a covariate in the DSR model, and calculating nest survival as the product of age-specific estimates of DSR when DSR changes with nest age.

Ornithological Applications↗
USGS2021

TrendPowerTool: A lookup tool for estimating the statistical power of a monitoring program to detect population trends

A simulation-based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web-based lookup app, called TrendPowerTool ( https://www.usgs.gov/apps/TrendPowerTool/ ), to provide guidance for ecological monitoring programs when resources are not available for a simulation-based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user-specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user-friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.

Conservation Science and Practice↗
USGS2020

Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska

Authorization of lease sales for oil development in the 1002 Area of the Arctic National Wildlife Refuge has highlighted gaps in information about biological communities in the area. The U.S. Fish and Wildlife Service, which is planning a study to evaluate spatial variation in the nest survival of tundra-breeding shorebirds to identify hotspots with high nest survival, sought advice from the U.S. Geological Survey on how to predict which sampling designs might be successful in achieving the study goals. I used previously obtained data on nest survival from Alaska’s North Slope to develop a simulation study that explored the statistical consequences of various sampling designs in the context of expected ranges of values of biological parameters. Of all sampling parameters, the number of nests per plot had the strongest influence on the ability to detect hotspots, followed by number of years of monitoring and the age at which nests were found. The benefit of sampling 98 plots instead of 68 was relatively small. Ages of nests cannot be predicted a priori, so I developed a field reference chart to identify when further nest-searching would be useful for a given plot. This simulation study used the best available information, but values of biological parameters will become better defined following subsequent data collection in the 1002 Area. Data from upcoming field seasons could be used to refine this analysis and improve estimation of the expected results of the field study, thus maximizing the likelihood that data from the 1002 Area nest survival study will meet the monitoring goals.

Alaska↗
USGS2020

Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain

Conservation status and management priorities are often informed by population trends. Trend estimates can be derived from population surveys or models, but both methods are associated with sources of uncertainty. Many Arctic-breeding shorebirds are thought to be declining based on migration and/or overwintering population surveys, but data are lacking to estimate the trends of some shorebird species. In addition, for most species, little is known about the stage(s) at which population bottlenecks occur, such as breeding vs. nonbreeding periods. We used previously published and unpublished estimates of vital rates to develop the first large-scale population models for 6 species of Arctic-breeding shorebirds in North America, including separate estimates for 3 subspecies of Dunlin. We used the models to estimate population trends and identify life stages at which population growth may be limited. Our model for the arcticola subspecies of Dunlin agreed with previously published information that the subspecies is severely declining. Our results also linked the decline to the subspecies’ low annual survival rate, thus potentially implicating factors during the nonbreeding period in the East Asian-Australasian Flyway. However, our trend estimates for all species showed high uncertainty, highlighting the need for more accurate and precise estimates of vital rates. Of the vital rates, annual survival had the strongest influence on population trend in all taxa. Improving the accuracy, precision, and spatial and temporal coverage of estimates of vital rates, especially annual survival, would improve demographic model-based estimates of population trends and help direct management to regions or seasons where birds are subject to higher mortality.

The Condor↗
USGS2020

Evidence for a growing population of eastern migratory monarch butterflies is currently insufficient

The eastern migratory population of monarch butterflies has experienced a multi-decadal decline, but a recent increase in abundance (to 6.05 ha in winter 2018) has led some observers to question whether the population has reversed its long-standing decline and embarked on a trajectory of increasing abundance. We examined this possibility through changepoint analyses, first assessing whether a change in trajectory existed and whether that change was sufficient to alter our estimated risk for the population. We found evidence of a change in trajectory in 2014, but insufficient statistical support for a significantly increasing population since that time (β = 0.285, 95% CI = -0.127, 0.697). If the population estimate for winter 2019 is ≥4.0 ha, we will then be able to credibly assert the population has been increasing since 2014. However, given estimated levels of time series variability, presumed habitat capacity and no recent change in status or trend, there was a 13.5% probability of observing a population estimate as large or larger than was reported for winter 2018. Despite insufficient evidence for an increasing population, near-term risk of quasi-extinction by 2023 has declined (mean risk declining from 43% to 20%) because of higher abundance estimates since 2014. Our analyses highlight the incredible difficulty in drawing robust conclusions from annual changes in abundance over a short time series, especially for an insect that commonly exhibits considerable year-to-year variation. Thus, we urge caution when drawing conclusions regarding species status and trends for any species for which limited data are available.

Frontiers in Ecology and Evolution↗
USGS2020

Challenges for leveraging citizen science to support statistically robust monitoring programs

Large samples and long time series are often needed for effective broad-scale monitoring of status and trends in wild populations. Obtaining those sample sizes can be more feasible when volunteers contribute to the dataset, but volunteer-selected sites are not always representative of a population. Previous work to account for biased site selection has relied on knowledge of covariates to explain differences between site types, but such knowledge is often unavailable. For cases where relevant covariates have not been defined, we used a simulation study to identify the consequences of including non-probabilistically selected sites (NP sites) in addition to sites selected from a probability-based design (P sites), test modeling frameworks that might correct for biases, and evaluate whether those frameworks could allow NP sites to reduce the sampling requirement for P sites and potentially reduce costs of monitoring. We informed the simulation with pilot data from surveys of monarch butterflies and their obligate larval host plant, milkweed. We found strong biases in NP sites versus P sites in density and trends of monarchs and milkweed. Modeling frameworks that accounted for site type with a group effect or that strongly downweighted NP sites successfully produced unbiased estimates. However, sampling more NP sites typically did not improve accuracy or precision, and adding NP sites sometimes required also adding P sites to prevent biases. Further work on novel modeling frameworks would be useful to allow citizen-science data to contribute useful information to conservation.

Biological Conservation↗
USGS2019

Is the timing, pace and success of the monarch migration associated with sun angle?

A basic question concerning the monarch butterfly’s fall migration is which monarchs succeed in reaching overwintering sites in Mexico, which fail—and why. We document the timing and pace of the fall migration, ask whether the sun’s position in the sky is associated with the pace of the migration, and whether timing affects success in completing the migration. Using data from the Monarch Watch tagging program, we explore whether the fall monarch migration is associated with the daily maximum vertical angle of the sun above the horizon (Sun Angle at Solar Noon, SASN) or whether other processes are more likely to explain the pace of the migration. From 1998 to 2015, more than 1.38 million monarchs were tagged and 13,824 (1%) were recovered in Mexico. The pace of migration was relatively slow early in the migration but increased in late September and declined again later in October as the migrating monarchs approached lower latitudes. This slow-fast-slow pacing in the fall migration is consistent with monarchs reaching latitudes with the same SASN, day after day, as they move south to their overwintering sites. The observed pacing pattern and overall movement rates are also consistent with monarchs migrating at a pace determined by interactions among SASN, temperature, and daylength. The results suggest monarchs successfully reaching the Monarch Butterfly Biosphere Reserve (MBBR) migrate within a “migration window” with an SASN of about 57° at the leading edge of the migration and 46° at the trailing edge. Migrants reaching locations along the migration route with SASN outside this migration window may be considered early or late migrants. We noted several years with low overwintering abundance of monarchs, 2004 and 2011–2014, with high percentages of late migrants. This observation suggests a possible effect of migration timing on population size. The migration window defined by SASN might serve as a framework against which to establish the influence of environmental factors on the size, geographic distribution, and timing of past and future fall migrations.

Frontiers in Ecology and Evolution↗
USGS2019

Balancing sampling intensity against spatial coverage for a community science monitoring programme

Community science is an increasingly integral part of biodiversity research and monitoring, often achieving broad spatial and temporal coverage but lower sampling intensity than studies conducted by professional scientists. When designing a community‐science monitoring programme, careful assessment of sampling designs that could be both feasible and successful at meeting programme goals is essential. Monarch butterflies ( Danaus plexippus ) are the focus of several successful community‐science projects in the U.S., but broader coverage is needed to monitor breeding areas and explain population declines observed in overwintering areas. The U.S. Monarch Conservation Science Partnership's Integrated Monarch Monitoring Program (IMMP) will representatively monitor monarchs and milkweed across North America. We performed a simulation‐based power analysis to predict trade‐offs between sampling breadth (number of sites and years) and sampling intensity (number of visits or subplots per site and year) for the IMMP. We evaluated whether each sampling design would produce sufficient statistical power to detect population trends and differences among land‐use sectors in densities of milkweed, monarch eggs, and adult monarchs. Sampling breadth had much stronger effects than sampling intensity on statistical power for all three monitoring targets. Depending on land‐use sector, monitoring 400–800 sites over 10–15 years would detect trends in densities of milkweed and adult monarchs, but no scenarios were successful for monarch eggs. Sampling 400–800 sites would also detect small (for adult monarchs) to large (for milkweed) differences among land‐use sectors in density of all three monitoring targets within the first 2–5 years. As more data become available from the IMMP, the sampling goals can be updated. Synthesis and applications . Careful sample design is an essential step in developing a successful monitoring programme. For monarchs and milkweed, we found that sampling breadth (number of sites and years) had a much stronger effect on statistical power than sampling intensity (number of visits or subsamples per site), suggesting field protocols could be tailored to maximize recruitment and retention of volunteers by minimizing the effort required to monitor each site. Many long‐term monitoring programmes might similarly benefit from evaluating the statistical trade‐offs between sampling breadth and intensity in their sampling designs.

Journal of Applied Ecology↗
USGS2019

Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates

Responses to climate change can vary across functional groups and trophic levels, leading to a temporal decoupling of trophic interactions or ‘phenological mismatches.’ Despite a growing number of single-species studies that identified phenological mismatches as a nearly universal consequence of climate change, we have a limited understanding of the spatial variation in the intensity of this phenomenon nor what influences this variation. In this study, we tested for geographic patterns in phenological mismatches between six species of shorebirds and their invertebrate prey at ten sites spread across ~13º latitude and ~84º longitude in the Arctic over three years. At each site, we quantified the phenological mismatch between shorebirds and their invertebrate prey at: 1) an individual nest level, as the difference in days between the seasonal peak in food and the peak demand by chicks, and 2) a population level, as the overlapped area under fitted curves for total daily biomass of invertebrates and dates of the peak demand by chicks. We tested whether the intensity of past climatic change observed at each site corresponded with the extent of phenological mismatch and used Structural Equation Modeling to test for causal relationships among: 1) environmental factors, including geographic location and current climatic conditions, 2) the timing of invertebrate emergence and the breeding phenology of shorebirds, and 3) the phenological mismatch between the two trophic levels. The extent of phenological mismatch varied more among different sites than among different species within each site. A greater extent of phenological mismatch at both the individual-nest and population-levels coincided with changes in the timing of snowmelt as well as the potential dissociation of long-term snow phenology from changes in temperature. The timing of snowmelt also affected the shape of the food and demand curves, which determined the extent of phenological mismatch at the population level. Finally, we found larger mismatches at more easterly longitudes, which may be affecting the population dynamics of shorebirds, as two of our study species show regional population declines in only the eastern part of their range. This suggests that phenological mismatches may be resulting in demographic consequences for arctic-nesting birds.

Alaska↗
USGS2019

The integrated monarch monitoring program: From design to implementation

Steep declines in North American monarch butterfly ( Danaus plexippus ) populations have prompted continent-wide conservation efforts. While monarch monitoring efforts have existed for years, we lack a comprehensive approach to monitoring population vital rates integrated with habitat quality to inform adaptive management and effective conservation strategies. Building a geographically and ecologically representative dataset of monarchs and their habitat will improve these efforts. These data will help track long-term changes in the distribution and abundance of monarchs and their habitats, refine population and habitat models, and illuminate how conservation activities affect monarchs and their habitats. The Monarch Conservation Science Partnership developed the Integrated Monarch Monitoring Program (IMMP) to profile breeding habitats and their use by monarchs in North America. A spatially balanced random sampling framework guides site selection, while also allowing opportunistic inclusion of sites chosen by participants, such as conservation areas. The IMMP weaves new protocols together with those from existing monitoring programs to improve data compatibility for assessing milkweed (Asclepias spp.) density, nectar resources, monarch reproduction and survival, and adult monarch habitat use. Participants may select a protocol subset according to interests or local monitoring objectives, thereby maximizing contributions. Conservation partners, including public and private land managers, academic researchers, and citizen scientists contribute data to a national dataset available for analyses at multiple scales. We describe the program and its development, implementation elements that make the program robust and feasible, participation to date, and how IMMP data can advance research and conservation for monarchs, pollinators, and their habitats.

North America↗
USGS2019

Weak effects of geolocators on small birds: a meta‐analysis controlled for phylogeny and publication bias

Currently, the deployment of tracking devices is one of the most frequently used approaches to study movement ecology of birds. Recent miniaturisation of light‐level geolocators enabled studying small bird species whose migratory patterns were widely unknown. However, geolocators may reduce vital rates in tagged birds and may bias obtained movement data. There is a need for a thorough assessment of the potential tag effects on small birds, as previous meta‐analyses did not evaluate unpublished data and impact of multiple life‐history traits, focused mainly on large species and the number of published studies tagging small birds has increased substantially. We quantitatively reviewed 549 records extracted from 74 published and 48 unpublished studies on over 7,800 tagged and 17,800 control individuals to examine the effects of geolocator tagging on small bird species (body mass <100 g). We calculated the effect of tagging on apparent survival, condition, phenology and breeding performance and identified the most important predictors of the magnitude of effect sizes. Even though the effects were not statistically significant in phylogenetically controlled models, we found a weak negative impact of geolocators on apparent survival. The negative effect on apparent survival was stronger with increasing relative load of the device and with geolocators attached using elastic harnesses. Moreover, tagging effects were stronger in smaller species. In conclusion, we found a weak effect on apparent survival of tagged birds and managed to pinpoint key aspects and drivers of tagging effects. We provide recommendations for establishing matched control group for proper effect size assessment in future studies and outline various aspects of tagging that need further investigation. Finally, our results encourage further use of geolocators on small bird species but the ethical aspects and scientific benefits should always be considered.

Journal of Animal Ecology↗