Skip to main content
Dryad logo

Sensory pollutants alter bird phenology and fitness across a continent

Citation

Francis, Clinton et al. (2020), Sensory pollutants alter bird phenology and fitness across a continent, Dryad, Dataset, https://doi.org/10.5061/dryad.dbrv15dzc

Abstract

Expansion of anthropogenic noise and night-lighting across our planet is of increasing conservation concern Despite growing knowledge of physiological and behavioural responses to these stimuli from single-species and local-scale studies, whether these pollutants affect fitness is less clear, as is how and why species vary in their sensitivity to these anthropic stressors. Here, we leverage a large citizen science dataset paired with high-resolution noise and light data from across the contiguous United States to assess how these stimuli affect reproductive success in 142 bird species. We find responses to both sensory pollutants linked to the functional traits and habitat affiliations of species. For example, overall nest success was negatively correlated with noise among birds in closed environments. Species-specific changes in reproductive timing and hatching success in response to noise exposure were explained by vocalization frequency, nesting location and diet. Additionally, increased light-gathering ability of species’ eyes was associated with stronger advancements in reproductive timing in response to light exposure, potentially creating phenological mismatches. Unexpectedly, better light-gathering ability was linked to reduced clutch failure and increased overall nest success in response to light exposure, raising important questions about how responses to sensory pollutants counteract or exacerbate responses to other aspects of global change, such as climate warming. These findings demonstrate that anthropogenic noise and light can substantially affect breeding bird phenology and fitness, and underscore the need to consider sensory pollutants alongside traditional dimensions of the environment that typically inform biodiversity conservation.

Methods

Nest records were obtained from the Cornell Lab of Ornithology's NestWatch Program. From 186,705 nest records from 2000-2014, we maximized nest record precision and plausibility by removing nest records: 1) with imprecise or implausible locations, 2) with identical coordinates in the same year, 3) implausible (e.g., negative clutch size) or unlikely (e.g., clutch sizes exceeding reported maximum for a given species, those monitored outside of the reported breeding season for a given species). The resulting dataset consisted of 58,506 nest records from 142 species.

Analyses of this dataset with spatially-explicit mixed-effect models generated a second dataset consisting of effect sizes and standard error estimates for the effects of noise or light on 27 individual species for the following response variables: clutch initiation (i.e., day first egg was laid), clutch size, clutch failure, partial hatch failure (i.e., whether any eggs in the nest failed to hatch) and overall nest success (i.e., whether a nest fledged at least one chick or not). These data were paired with several species traits:

1) Peak vocal frequency, which reflects the frequency at which a vocalization has the highest amplitude.

2) The ratio of the eye corneal diameter and transverse diameter, which reflects an eye's light gathering ability. Direct measurements were obtained for 16 of 27 species. Values for the remaining 11 species were imputed using the phylopars function in the R package Rphylopars using a larger database of 77 North American bird species and trait information reflective of morphology and ecology.

3) Diet, categorized as plant-based or animal-based. Omnivorous species were grouped with animal-based. 

4) Whether a bird species nested in a cavity or not.

Included in this dataset are summary statistics regarding species-specific exposure to noise and light. Specifically, mean, standard deviation, minimum and maximum noise and light exposure values for nests in the dataset.

Usage Notes

Four data files and associated ReadMe files are included:

1) "Senzaki_etal_NestWatchDataset.csv" - Full NestWatch database.

2) "Senzaki_etal_SpeciesMatrixForImputation.csv" - Database used for imputation of eye geometries.

3) "Senzaki_traits&responses.csv" - Database including species-specific responses to noise and light, species traits, and summary information for species exposure to noise and light.

Phylogeny:

"Jetz_ConsensusPhy.tre" - One consensus phylogeny from Jetz et al. (2012) Nature 491: 444-448, which was used with database 2 and 3.

Associated Code:

Three R scripts are provided:

1. "Senzaki_etal_NestWatch_SampleCode.R" - Example spatially-explicit mixed-effect models are provided for both multi-species models and single-species models.

2. "Senzaki_etal_NestWatch_Imputation.R" - Imputation of corneal:transverse data. Code used for data imputation is supplied.

3. "Senzaki_etal_NestWatch_TraitsAndResponses.R" - Analysis of relationships between responses to noise or light and traits. Code for the phylogenetic generalized least squares (PGLS) analyses is provided.

Funding

National Science Foundation, Award: 1414171

National Science Foundation, Award: 1556177

National Science Foundation, Award: 1556192

National Science Foundation, Award: 1812280

Earth Sciences Division

National Aeronautics and Space Administration, Award: NNX17AG36G

Japanese Society for the Promotion of Sciences, Award: 17J00646