Number of initial variables considered, number of covariates in the initial model, and number of covariates in each modeling region’s final model.

Incubation represents a life stage of crucial importance for the optimal development of avian embryos. For most birds, incubation poses a trade-off between investing in self-maintenance and offspring care. Furthermore, incubation is affected by environmental temperatures and, therefore, will be likely impacted by climate change. Despite its relevance and readily available temperature logging methods, avian incubation research is hindered by recognised limitations in available software. In this paper, a new quantitative approach to analyse incubation behaviour is presented. This new approach is embedded in a free R package, incR. The flexibility of the R environment eases the analysis, validation and visualisation of incubation temperature data. The core algorithm in incR is validated here and it is shown that the method extracts accurate metrics of incubation behaviour (e.g. number and duration of incubation bouts). This paper also presents a suggested workflow along with detailed R code to aid the practical implementation of incR.

These data were used to investigate variation in the costs and benefits of nesting at various positions along an intertidal gradient. These data were collected from one laboratory and two field experiments carried out in 2018 and 2019. The focal species, the plainfin midshipman Porichthys notatus, is a marine toadfish that nests in the intertidal and shallow subtidal zones of beaches along the Pacific Coast of North America.

File 1: a_hellmayri_survival.csv

Nest survival data of Anthus hellmayri collected during 2017-2018, 2018-2019, and 2019-2020 breeding seasons in Punta Indio, Buenos Aires, Argentina. Used to estimate daily nest survival rates and include covariates in the models.

File 2: Readme_a_hellmayri_survival.docx

File conainting information about the columns and data

File 3: script_ah.R

Example code to be used in R software. This code leads to the main result of the paper.

Factor by which golden eagle nest density varies from the lowest bin for each modeling regions’ final model.

Number of thinned nest sites is the sample of nest sites used for model development, after we thinned the initial sample to reduce the chance of pseudoreplication. Modeling region size is total size of modeling region, whereas modeling area size is the union of 20-km radius circles around the thinned nest sites. Modeling area percentage of modeling region is the result of dividing the modeling area by modeling region sizes (x 100). Number of sub-regions is the number of discrete sub-regions within each modeling region.

Shew_et_al_2018_Journal_of_Applied_EcologyData package includes: README, text R script, and data files used to analyze daily nest survival of grassland birds in northwestern, Illinois, USA (2011-2014) associated with Conservation Reserve Program management and multi-scale factors.Shew_grassland_bird_nest_survival_data_package.zip

Data and R code associated with a study conducted by the University of Exeter and Ascension Island Government titled "Efficacy of artificial nest shading as a climate change adaptation measure for marine turtles at Ascension Island.

There are three types of files: data, figures and scripts

Data:

File1: Table containing 210Pb dating profiles, CRS ages and 14C dates over the depth of the nests.

File2: Results of the clam analysis carried out for DSE3 nest

File3: Results of the clam analysis carried out for DSE5 nest

File4: Diatom and other siliceous indicators count data for the depths of the nests.

File5: Zscores for Pb, Zn, Cd, N15 and Chla used in Figure 8.

File6: PCA1 for diatoms and the other indicators used in Figure 8.

File7: N15 data obtained in the nests.

File8: Historical data (Christian Vibes annotations, Arctic Institute archives ) for rifles and shotguns that were sold or traded in the west coast of Greenland.

File 9: Table of the metal(loid)s analyzed in the nests.

Scripts:

• CLAM_script: Script used for performing the age-depth modeling for each nest in R, using 210Pb and 14C dates with the function ‘clam’ in the R package ‘clam’ v. 2.5.0.
• PCA code: Script for performing the principal component analysis (PCA) in R to summarize the main patterns of variation over time, PCA-1diatoms and PCA-1indicators from each nest and plotted against time.
• Script bchron

The figures are those included in the manuscript.

Best choice: chose the better new nest, or split between the two new nests; moderate: chose the worse new nest; impaired: remained in starting nest or split between starting and worse new nests (nest destruction from previously published data).Cross tabulation for effect of manipulation on final nest choice.

Telemetry technology and data are commonly used to study behavior and demography of wildlife. Satellite-based, global positioning system (GPS) telemetry allows researchers to remotely collect a high volume of fine-resolution animal location data but may also come with hidden costs. For example, recent studies suggested GPS transmitters attached via backpacks may reduce survival of greater sage-grouse (Centrocercus urophasianus) relative to very high frequency (VHF) telemetry transmitters attached via collars. While some evidence suggests GPS backpacks can reduce survival, no studies examined their effects on sage-grouse breeding behavior and success. We compared survival, breeding behavior, and nest success for sage-grouse hens marked with either VHF collars or GPS backpack transmitters in central Idaho, USA. GPS backpacks reduced spring-summer survival relative to VHF collars, yet GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation rela..., , , # Supporting data for assessing impacts of satellite GPS transmitters on survival, nesting propensity, and nest success of greater sage-grouse

The data files contain data used to conduct the following analyses: 1) multi-state modeling of daily mortality probabilities for hen sage-grouse in program MARK (MultiState.inp), 2) nest survival modeling to estimate daily nest survival probabilities for greater sage grouse in program MARK (NestSurvival.inp), 3) mixed effects logistic regression modeling of nesting propensity for hen sage-grouse (i.e., proportion of females initiating a nest) in program R (nest_propensity.csv), and 4) mixed effects Gaussian regression modeling of timing of nest initiation for hen sage-grouse in program R (NestTiming.R). In addition, analysis scripts, written in R language, are provided for analyses 3 (LogisticReg.R) and 4 (GaussianReg.R) above. These R scripts are self contained and annotated within to explain each piece of code.

Description of the data an...

This dataset consists of two .xlsx files containing data on nest-site and territory characteristics of the Seychelles warbler and nest survival, and the R-script used to analyze the data.

The potential for animals to respond to changing climates has sparked interest in intraspecific variation in avian nest structure since this may influence nest microclimate and protect eggs and offspring from inclement weather. However, there have been relatively few large-scale attempts to examine variation in nests or the determinates of individual variation in nest structure within populations. Using a set of mostly pre-registered analyses, we studied potential predictors of variation in the size of a large sample (803) of blue tit (Cyanistes caeruleus) nests across three breeding seasons at Wytham Woods, UK. Whilst our pre-registered analyses found that individual females built very similar nests across years, there was no evidence in follow-up (post hoc) analyses that their nest size correlated to that of their genetic mother or, in a cross-fostering experiment, to the nest where they were reared. In further pre-registered analyses, spatial environmental variability explained nest size variability at relatively broad spatial scales, and especially strongly at the scale of individual nestboxes. Our study indicates that nest structure is a characteristic of individuals, but is not strongly heritable, indicating that it will not respond rapidly to selection. Explaining the within-individual and within-location repeatability we observed requires further study.

Usage Notes

Final blue tit nest size dataNest sizes recorded by SCG in Wytham Woods, UK 2001-2003. Nest sizes were recorded as fraction of standardised nest box filled. Blue tits were identified using uniquely marked metal rings to give identities. Zone is the woodland compartment in Wytham Woods where the nest is.Final BT nest data LON 2018-2-6.csvBlue tit nest sizes for genetic mother-daughter pairsNest sizes (recorded as fraction of standardised nest box filled) of blue tit daughters and their genetic mothers, as recorded by SCG in Wytham Woods, Oxfordshire, UK in 2001-2003genetic depth2.csvBlue tit nest sizes for foster mother-daughter pairs 2Nest sizes (recorded as fraction of standardised nest box filled) of daughters and their foster mothers, as recorded by SCG in Wytham Woods, UK during 2001-2003 breeding seasons. Rrearing depth2.csvFinal R code used for analysis 2The R code that I wrote to analyse different factors controlling the nest size of blue tits in Wytham Woods, UK during the 2001-2003 breeding seasons using the data files attachedFinal BT nest size analysis code.R

Climate change, including directional shifts in weather averages and extremes and increased inter-annual weather variation, is influencing demograhy and distributions for many bird species. We examined how temperature and precipitation coinciding with multiple nesting seasons affected overall nesting success and productivity for two red-cockaded woodpecker (Dryobates borealis, RCW) populations at the species' northwestern range periphery. We used 26 years of nesting data (1991-2016) from the two RCW populations to determine if inter-annual weather variation has affected nesting pehnology and productivity. We conducted analyses at both broad nesting periods (30 and 60 days before nesting; 40 days overalpping the nesting period up to fledging) and short windows to capture the effects of temperature and precipitation extremes on individual nests. For both RCW populations, warmer early spring temperatures generally advanced nesting and increased clutch size and fledgling number. Howeve...

Animals often eavesdrop on signals intended for others to gather information about their environment. While adult animals have been shown to learn to recognize unfamiliar heterospecific alarm calls through both social and asocial learning, it remains unclear whether and how young animals learn to recognize unfamiliar alarm calls. We show experimentally that nestling Daurian redstarts Phoenicurus auroreus can socially learn to recognize unfamiliar heterospecific alarm signals by associating them with conspecific alarm calls. We trained nestlings by presenting two unfamiliar sounds, one together with conspecific alarm calls (training) and one without (control). Before training, nestlings showed similarly little response to both novel sounds. After training, however, nestlings showed clear anti-predator responses to the training sound, but not to the control sound. These results show that nestling birds can socially learn to associate novel sounds with known alarm calls, even without visua..., , , # Nestling birds learn socially to eavesdrop on heterospecific alarm calls through acoustic association

Dataset DOI: 10.5061/dryad.612jm64fj

Description of the data and file structure

Files and variables

File: Data_alarm.csv

Variables

nestid = nest identity

nesttype = type of nest (natural/box)

recording = video reocording identity

clutchsize = clutch size

group = warbler or rosefinch group

stage = test stage (Pre-training / test day 1 / test day 2)

treatment = playback treatment (warbler / rosefinch)

ifhead = whether nestlings lower the head (0 = no; 1 = yes; NA = not available, as no usable video was recorded due to reasons such as nest predation or severe weather conditions.)

ifbeg = whether nestlings emit begging call (0 = no; 1 = yes; NA = not available, as no usable video was recorded due to reasons such as nest predation or severe weather conditions.)

Code/software

We used one R script (Rcode_alarm.R) to analyze ...,

Restoration of anthropogenically altered habitats has often focused on management for umbrella species—vulnerable species whose conservation is thought to benefit co-occurring species. Woody plant encroachment is a form of habitat alteration occurring in grasslands and shrublands around the globe, driven by anthropogenic shifts in disturbance regimes. One pervasive threat to historically widespread sagebrush communities is conifer expansion, which outcompetes sagebrush and can negatively affect sagebrush-obligate animal species. Degradation and loss of sagebrush plant communities in western North America have been associated with drastic declines in wildlife populations. The imperiled Greater Sage-Grouse is assumed to be an umbrella species for the sagebrush community, so habitat restoration, including removal of encroaching conifers, is commonly targeted toward sage-grouse. How this conservation action affects the demography of species other than age grouse is largely unknown. We quant..., Density To understand how treatment impacted breeding pair density, we used spot-mapping to create territory maps in each year of the study (Chalfoun & Martin, 2007; Ralph et al., 1993). We surveyed all plots 3-5 times throughout the breeding season and mapped every bird seen and heard. The 50m grid of points was used to assist with the accurate identification of bird locations using a GPS unit and visual distance estimation. We paid attention to males that were counter-singing to determine territory boundaries. Using the spot-mapping observations and nest locations, we created a territory map for each species each year of the study. We assumed that every territory held a pair of birds and if a territory overlapped the plot boundary, then it was considered half of a territory. We used the final territory maps to estimate the number of pairs of each species on each plot and divided by plot area to calculate density. Nest success and offspring production To estimate reproductive succe..., , # Impacts of umbrella species management on non-target species

https://doi.org/10.5061/dryad.zgmsbcckx

This dataset consists of species abundances as collected by territory mapping surveys and nest data. Data used to calculate species density, number of offspring produced, and daily nest success between treatments are included.

Description of the data and file structure

The data are set up in CSV format for easy import into R. All data analysis was conducted in R (version 4.3.0) and important packages included nlme and lme4 for modeling and ggplot for plotting.

Territory data includes the year, species (SPP, common names associated with four-letter codes can be found in Table 1), plot, treatment, number of territories in the plot, and plot area in hectares.

Nest data includes a row for each nest found and consists of the year, nest ID (NID), species (SPP, common names associated with four-letter codes can be found in Table 1), plot, tr...

Here, we provide the data and R-scripts used in:

Bård-Jørgen Bårdsen and Jan Ove Bustnes (2022). Multiple stressors: negative effects of nest predation on the viability of a threatened gull in different environmental conditions. Journal of Avian Biology. https://doi.org/10.1111/jav.02953. Bård-Jørgen Bårdsen and Jan Ove Bustnes (2023). Correction to Multiple stressors: negative effects of nest predation on the viability of a threatened gull in different environmental conditions. Journal of Avian Biology. https://doi.org/10.1111/jav.12915.

This study assessed the viability of a population of the lesser black-backed gull (Larus fuscus fuscus) using data collected from 2005-2020 from a nature reserve in Northern Norway. The study merged results from statistical analyses of empirical data with a Leslie model. Here, we provide the underlying data and the R-scripts used to analyse the data and run the model. The data set includes information about reproduction at several stages (laying, hatching and fledgling), nest predation, and individual capture histories (used to estimate apparent survival; see Bårdsen and Bustnes 2022). We discovered a misspecification error in the matrix model in Bårdsen and Bustnes (2022). This error did not change the overall conclusions or the results in the original article's empirical analyses. Here, we present an updated version of our scripts, i.e., scripts used by Bårdsen and Bustnes (2023). In the correction, we also highlight which part of the original article was affected by this mistake. Methods Bårdsen and Bustnes (2022), including the online Supplementary Material (Appendix S1-2), provide a detailed description of the study area and the empirical data. In the downloadable software ('ToBePublished.zip'), we provide data, metadata, and R-scripts for the statistical analyses and the models. Please confer with the 'README.txt' in 'ToBePublished.zip' for more information. We also include the data (without the scripts) from our study area as a downloadable dataset ('Data.zip'; see the included 'README.txt' for details).

Coastal birds that rely on sandy beaches for breeding are vulnerable to catastrophic flooding events resulting from tropical cyclones. The effects of storm surge on annual productivity depend on the propensity and success of renesting attempts post-storm. From 2017-2021, I investigated the effects of storm surge on Least Tern (Sternula antillarum) annual productivity, renesting probability, and nest and chick survival after storms on Mississippi’s Gulf of Mexico Coast. Tropical cyclones made landfall during peak breeding period in three of these years, resulting in complete overwash of all colonies. Observers monitored daily nest survival, productivity (max fledge count/max nest count), and frequency of disturbance from avian predators at each colony. Total annual productivity (fledge count/ nest count across the study area) summed across colonies ranged from 0.00-0.07 in storm years and 0.29-0.66 in non-storm years. Probability of colony re-occupation declined as a function of storm da..., , , # Least Tern Disturbance Observations and Colony Survey Data

This dataset contains multiple raw data files as .csv format, .txt files with Bayesian models written in BUGS code used to estimate Least Tern nest and chick survival, and the R script used to clean, collate, and analyze the data.

Description of the data and file structure

colony.storm.names.update.csv

This file contains beach width (m) measurements and presence or absence of dunes for each Least Tern colony in this manuscript.

ColonySurveys.zip

This file contains three .csv files with raw Least Tern colony survey data. These data were collected weekly to twice per week at all mainland colonies. The first five columns contain information about the survey: Site (site name, typically in reference to the nearest cross street that meets Highway 90), Date, Time, Species, and Survey Type (Exterior if conducted outside of the colony, Interior if surveyed by walking through the colony). Most surveys were conducted b...

The nests of ground-nesting birds rely heavily on camouflage for their survival, and predation risk, often linked to ecological changes from human activity, is a major source of mortality. Numerous ground-nesting bird populations are in decline, so understanding the effects of camouflage on their nesting behaviour is of relevance to their conservation concern. Habitat three-dimensional (3D) geometry together with predator visual abilities, viewing distance, and viewing angle determine whether a nest is either visible, occluded or too far away to detect. While this link is intuitive, few studies have investigated how fine-scale geometry is likely to help defend nests from different predator guilds. We quantified nest visibility based on 3D occlusion, camouflage, and predator visual modelling in northern lapwing, Vanellus vanellus, on different land management regimes. Lapwings selected local backgrounds that had a higher 3D complexity at a spatial scale greater than their entire clutches..., Data Collection Sites All images and 3D scans were collected from two separate locations monitored by the Game and Wildlife Conservation Trust (GWCT); the Avon Valley in Hampshire [50.93105,-1.78462] and Burpham in Sussex [50.87198, -0.51812]. Predation Data Nest predation status was determined using nest temperature loggers (iButtons) and weekly nest checks from the date of discovery to the point of failure or hatching following the methods of Hartman and Oring (Hartman & Oring, 2006). Predated eggshell fragments or disappearance of clutches/eggs prior to egg weight estimated hatch dates were encoded as predation events. Nest and Null Photography and Scanning From March to Mid-June of 2021 and 2022, we photographed 115 lapwing nests and 3D scanned 83. The nests were scanned with an ASUS Zenfone AR using the Matterport Scenes app from a height of 1.2m. Scans and photographs were taken from a height of 1.2 metres at a flat 90o (vertical) angle from the ground. For each nest, an addi..., Running the statistical analyses requires the R code and data frames for 3D and colour measures, stored in the same folder layout as provided for the zip. Simply set the working directory for the R script to the same folder. Example 3D scans and .mspecs are also provided, requiring ImageJ and version 2.2.0 to open. All scripts for our 3D analyses are provided on our GitHub: https://github.com/GeorgeHancock471/3D_RNL_Tools. To open our .mspecs requires the installation of a custom version of "_Load_Multispectral_Image.txt", which allows for RAW UV and human visible spectrum images with different rotations to be combined. Copy and paste the .txt file provided alongside our .mspecs into the plugins/micaToolbox/ folder of ImageJ.

description: In 2008, we initiated the first year of a comprehensive 4-year monitoring project to study the breeding ecology of Kittlitz s murrelets at Agattu Island with the following objectives: 1) describe habitat characteristics of nest sites; 2) quantify breeding chronology; 3) determine chick growth rates, nestling diet and adult nest attendance patterns; 4) measure nest survival rates and overall reproductive success; and 5) collect genetic samples for comparative study of murrelet populations. This progress report for the 2009 season, the second year of the comprehensive study, contains summary data for some but not all of the parameters we measured. Analysis is pending on nest survival models and nest site selection (R. Kaler, USFWS), sex determination and population genetics (V. Friesen, Queen s University), and diet analyses of chicks (R. Kaler, USFWS; J. Piatt and M. Arimitsu, USGS). All data will be incorporated and compared in the final report after the completion of the final season of field data collection.; abstract: In 2008, we initiated the first year of a comprehensive 4-year monitoring project to study the breeding ecology of Kittlitz s murrelets at Agattu Island with the following objectives: 1) describe habitat characteristics of nest sites; 2) quantify breeding chronology; 3) determine chick growth rates, nestling diet and adult nest attendance patterns; 4) measure nest survival rates and overall reproductive success; and 5) collect genetic samples for comparative study of murrelet populations. This progress report for the 2009 season, the second year of the comprehensive study, contains summary data for some but not all of the parameters we measured. Analysis is pending on nest survival models and nest site selection (R. Kaler, USFWS), sex determination and population genetics (V. Friesen, Queen s University), and diet analyses of chicks (R. Kaler, USFWS; J. Piatt and M. Arimitsu, USGS). All data will be incorporated and compared in the final report after the completion of the final season of field data collection.