Temperature loggers decrease costs of determining bird nest survival

Sutti, Flavio; Strong, Allan M.

doi:10.1002/wsb.473

Cited by 10 publications

(18 citation statements)

References 14 publications

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“…We found and monitored nests using established protocols (Martin & Geupel 1993) from early April to mid-August during 2015−2017. We used iButton ® (Thermocron) temperature loggers in most nests (wren, n = 729 of 888 nests [82%]; sparrow, n = 92 of 116 nests [79%]), because temperature data provided precise nest completion dates and times (Sutti & Strong 2014) and allowed us to check nests less frequently (every 7 d) than is typically suggested for passerines (2−4 d; Martin & Geupel 1993) to reduce disturbance to vegetation and nesting birds. We determined completion dates by comparing temperatures in nests with ambient temperatures recorded by a control logger in a nearby abandoned sparrow nest or a wren dummy nest (nest and ambient temperatures differed until a nest failed or fledged).…”

Section: Field Methods and Habitat Measurementsmentioning

confidence: 99%

Tide and habitat features affect salt marsh songbird nest survival in northeast Florida, USA

Cox¹,

Schwarzer²,

Tornwall³

et al. 2020

Endang. Species. Res.

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Tidal salt marshes face numerous pressures that threaten their ecological integrity, and many salt marsh vertebrates have exhibited declines concomitant with the degradation of salt marsh habitats. We studied nest survival of MacGillivray's seaside sparrow Ammospiza maritima macgillivraii and Worthington's marsh wren Cistothorus palustris griseus in smooth cordgrass Spartina alterniflora and black needlerush Juncus roemerianus dominated salt marshes in northeast Florida, USA, during 2015−2017 to understand why both species have undergone range contractions. We evaluated the effects of tides, habitat features, and weather on nest survival. The probability of a nest surviving from laying to fledging young was low for both species (seaside sparrow: 0.03, 95% CI: 0.00, 0.10; marsh wren: 0.10, 95% CI: 0.04, 0.18), suggesting that nest survival may limit population growth. The most substantial threat to marsh wren and seaside sparrow nest survival was from greater than normal high tides. However, there was limited evidence of direct nest loss due to flooding. An analysis of only fledged and depredated nests suggests that higher tides influenced nest survival by increasing nest predation, substantially so for marsh wrens. Other factors negatively associated with marsh wren nest survival, albeit less strongly, included precipitation and the amount of black needlerush at and within 50 m of the nest. The effect of tide height on nest survival suggests that salt marsh birds in northeast Florida are vulnerable to continued sea-level rise, which is exacerbated by upland development that will hinder marsh migration. Monitoring and protecting northeast Florida's high-elevation, cordgrass-dominated marshes should be a priority.

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Section: Field Methods and Habitat Measurementsmentioning

confidence: 99%

Tide and habitat features affect salt marsh songbird nest survival in northeast Florida, USA

Cox¹,

Schwarzer²,

Tornwall³

et al. 2020

Endang. Species. Res.

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“…4). Potential increases in statistical power from data loggers thus come mainly from increased logistical flexibility resulting from needing fewer nest checks and having more time to locate additional nests (Sutti and Strong 2014). If revisit time is fixed by other constraints, then our results suggest that data loggers could be most beneficial for studies with few nests and long revisit intervals, such as for species that abandon frequently disturbed nests.…”

Section: Discussionmentioning

confidence: 99%

“…Investigators in previous studies have examined the possible effects of using iButton brand data loggers on nest survival (Hartman and Oring 2006, Schneider and McWilliams 2007, Jacobson et al. 2011, Sutti and Strong 2014), but not the possible effects on the precision of DSR estimates. Collectively, the results of these studies suggest that these data loggers do not affect nest success, but the applicability across guilds and taxa is limited by the small number of species where there is statistical power to draw meaningful conclusions.…”

Section: Figmentioning

confidence: 99%

“…Collectively, the results of these studies suggest that these data loggers do not affect nest success, but the applicability across guilds and taxa is limited by the small number of species where there is statistical power to draw meaningful conclusions. Furthermore, Jacobson et al (2011) and Sutti and Strong (2014) were the only investigators to evaluate the impacts of miniature data loggers on nest fates of songbirds, and neither addressed potential differences between species that accept and reject eggs of brood parasites, such as Brown-headed Cowbirds (Molothrus ater). We were unable to locate any previous studies where differences in nest survival between nest parasite acceptor and nest rejecter species were examined when iButtons or similar thermal data-loggers were used.…”

Section: Introductionmentioning

confidence: 99%

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Miniature temperature data loggers increase precision and reduce bias when estimating the daily survival rate for bird nests

Stephenson

Schulte

Klaver

et al. 2021

J of Field Ornithology

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Demographic studies of many bird species are challenging because their nests are cryptic, resulting in few nests being found. To maximize statistical power, methods are needed that minimize disturbance while yielding as much information per nest as possible. One way to meet these objectives is to use miniature thermal data loggers to precisely date nest fates. Our objectives, therefore, were to (1) examine the possible effect of thermal data loggers on nest success through hatching by grass-and shrub-nesting songbirds that differed in their parasite egg-accepting and -rejecting behavior, (2) examine the effect of using daily temperature data versus less frequent nest-visit data on statistical power, bias, and precision when estimating the daily survival rate (DSR) for nests, and (3) compare these two approaches using a simulation study and field data. We monitored the survival of nests located in agricultural landscapes and used a binomial logistic regression with main effects for data-loggers and parasite-accepting or -rejecting status and their interaction. We also compared maximum likelihood-derived DSR for differences in estimated rates, precision, and sample sizes with both data collected in the field and simulated with varying sample sizes and visit frequencies. We found no evidence that thermal data loggers had any effect on hatching rates either for all species or for parasite egg-accepting and -rejecting species, separately. Both our simulation and analysis of real nest data indicated that use of data loggers increased the statistical power from each nest studied by increasing effective sample sizes and precision of DSR estimates compared to in-person visits. We also found a negative bias in DSR estimates with longer visit intervals, which use of data-loggers removed. Both the results of simulated-and field-data analyses suggest that future studies of nest survival can be improved by automated nest monitoring by removing a source of bias and providing more time to find additional nests.

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“…Piecewise regression is therefore a quick and easy method that can be used to identify breakpoints that may be indicative of mortality. This approach can also be extended to monitor nest success with temperature loggers (Hartman & Oring, 2006; Sutti & Strong, 2014; Zangmeister et al, 2009). As part of a study of trumpeter swan movement ecology, we evaluated whether we could detect mortality using piecewise regression of Overall Dynamic Body Acceleration (ODBA) and temperature data (Figure 5; Wolfson, unpublished data).…”

Section: Example Applicationsmentioning

confidence: 99%

Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

Wolfson

Fieberg

Andersen

2021

Preprint

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Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal’s location, movement characteristics, external environmental conditions, and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide five example applications highlighting a variety of taxonomic species, data streams, timescales, and biological phenomena. These examples include a short-term behavioral response (flee and return) by a trumpeter swan (Cygnus buccinator) immediately following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose (Alces alces); a physiological response (spike in heart-rate) in a black bear (Ursus americanus) to a stressful stimulus (presence of a drone); a mortality event of a trumpeter swan signaled by changes in collar temperature and Overall Dynamic Body Acceleration; and an unsupervised method for identifying the onset, return, duration, and staging use of sandhill crane (Antigone canadensis) migration. We implement analyses using the mcp package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criterion and cross-validation measures. This approach uses simple modeling approaches that are accessible to a wide audience and is a straightforward means of assessing a variety of biologically relevant changes in animal behavior.

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Temperature loggers decrease costs of determining bird nest survival

Cited by 10 publications

References 14 publications

Tide and habitat features affect salt marsh songbird nest survival in northeast Florida, USA

Tide and habitat features affect salt marsh songbird nest survival in northeast Florida, USA

Miniature temperature data loggers increase precision and reduce bias when estimating the daily survival rate for bird nests

Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

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