Data from: Spatial consistency in drivers of population dynamics of a declining migratory bird
Data files
Oct 31, 2022 version files 580.81 MB
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DIN_IPMData.rds
82.47 KB
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EDM_IPMData.rds
45.47 KB
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KAT_IPMData.rds
20.30 KB
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NAG_IPMData.rds
39.88 KB
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NWA_IPMData.rds
24.55 KB
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OKE_IPMData.rds
18.82 KB
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README.md
5.42 KB
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SPI-IPM_DIN.rds
75.70 MB
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SPI-IPM_EDM.rds
124.39 MB
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SPI-IPM_KAT.rds
73.76 MB
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SPI-IPM_NAG.rds
75.55 MB
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SPI-IPM_NWA.rds
66.66 MB
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SPI-IPM_OKE.rds
87.78 MB
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SPI-IPM_TEI.rds
76.72 MB
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TEI_IPMData.rds
13.64 KB
Mar 29, 2023 version files 842.33 MB
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DIN_IPMData.rds
82.47 KB
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EDM_IPMData.rds
45.47 KB
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EnvData.rds
11 KB
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KAT_IPMData.rds
20.30 KB
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NAG_IPMData.rds
39.88 KB
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NWA_IPMData.rds
24.55 KB
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OKE_IPMData.rds
18.82 KB
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README.md
7.04 KB
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SPI-Indep_DIN.rds
33.67 MB
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SPI-Indep_EDM.rds
55.95 MB
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SPI-Indep_KAT.rds
33.16 MB
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SPI-Indep_NAG.rds
34.13 MB
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SPI-Indep_NWA.rds
30.15 MB
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SPI-Indep_OKE.rds
39.61 MB
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SPI-Indep_TEI.rds
34.83 MB
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SPI-IPM_DIN.rds
75.70 MB
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SPI-IPM_EDM.rds
124.39 MB
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SPI-IPM_KAT.rds
73.76 MB
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SPI-IPM_NAG.rds
75.55 MB
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SPI-IPM_NWA.rds
66.66 MB
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SPI-IPM_OKE.rds
87.78 MB
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SPI-IPM_TEI.rds
76.72 MB
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TEI_IPMData.rds
13.64 KB
Abstract
1. Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets.
2. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modeling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain.
3. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34–64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structures to changes in short- and long-term population growth rates using transient life table response experiments (LTREs).
4. Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or non-breeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period.
5. We show that both short- and longer-term population changes of British-breeding pied flycatchers are likely linked to factors acting during migration and in non-breeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.
Methods
Data collection protocols are described in the paper, and further references provided therein. Raw data were harmonised and converted to a standard format by SPI-Birds (https://spibirds.org/) and then collated into the input data provided here using code deposited on https://github.com/SPI-Birds/SPI-IPM. Details on this step of data processing will be added to https://spi-birds.github.io/SPI-IPM/. The MCMC sample data files are the outputs of the integrated population models fitted in the study. Please refer to the published article and material deposited on the associated GitHub repository for more details.
Usage notes
Data is provided as .rds files. Files can be read directly into the software "R" using the "readRDS" function.