Isotopic niche partitioning and individual specialization in an Arctic raptor guild
Data files
May 10, 2022 version files 548.77 KB
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CAM_MASTER_FULL.csv
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CAM_MASTER_SIA.csv
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README.rtf
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SIA_GYRF_CAM.csv
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SIA_NESTS.csv
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SIA_PREY.csv
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SIA_RAPTORS.csv
Abstract
Intra- and inter-specific resource partitioning within predator communities is a fundamental component of trophic ecology, and one proposed mechanism for how populations partition resources is through individual niche variation. The Niche Variation Hypothesis (NVH) predicts that inter-individual trait variation leads to functional trade-offs in foraging efficiency, resulting in populations composed of individual dietary specialists. The degree to which niche specialization persists within a population is plastic and responsive to fluctuating resource availability. We quantified niche overlap and tested the NVH within an Arctic raptor guild, focusing on three species that employ different foraging strategies: golden eagles (generalists); gyrfalcons (facultative specialists); and rough-legged hawks (specialists). Tundra ecosystems exhibit cyclic populations of arvicoline rodents (lemmings and voles), providing a unique system in which to examine predator diet in response to interannual fluctuations in resource availability. Using blood δ13C and δ15N values from 189 raptor nestlings on Alaska’s Seward Peninsula (2014–2019), we calculated isotopic niche width and used Bayesian stable isotope mixing models (BSIMMs) to characterize individual specialization and test the NVH. Nest-level specialization estimated from stable isotopes was strongly correlated with indices of specialization based on camera trap data. We observed a high degree of isotopic niche overlap between the three species and gyrfalcons displayed a positive relationship between individual specialization and population niche width on an interannual basis consistent with the NVH. Our findings suggest plasticity in niche specialization may reduce intra- and inter-specific resource competition under dynamic ecological conditions.
Methods
This dataset contains the following files:
"CAM_MASTER_FULL.csv": Raw dietary data from Gyrfalcon feeding observations from nest cameras from 2014-2019.
"CAM_MASTER_SIA.csv": Subset of CAM_MASTER_FULL.csv which only includes camera prey observations contemporaneous with stable isotope data (e.g., select nests from 2016-2019).
"SIA_GYRF_CAM.csv": Stable isotope data from red blood cells for individual Gyrfalcons from 2016-2019, for the subset of the study which had contemporaneous camera and stable isotope data.
"SIA_Nests.csv": Mean stable isotope values for each raptor nest included in this study.
"SIA_Prey.csv": Stable isotope values for each prey specimen measured in this study and incorporated into prey categories.
"SIA_RAPTORS.csv": Stable isotope data from red blood cells for individual raptors; 2016-2019.
Further methodological details can be found in the article to which this dataset is supplement (https://doi.org/10.1007/s00442-022-05154-3).
Usage notes
Further details on this dataset and how it was used can be found in the attached RMarkdown document (JAE-2020-00518.Rmd).
*note*: the "RData" data folder contains a .RData object containing output from the Bayesian Stable Isotope Mixing Models we ran for this analysis. Due to the computational intensity of these mixing models, we included the code we used to generate said models, then import them into the RMarkdown document via a separate .RData file (CH3_MODELS.RData).
*note*: Some plots were generated using a package we wrote: "SIAplotR". A tar.gz file for this package is included so figures can be recreated exactly as they appear in the manuscript using the RMarkdown file.