Data used in: Assessing the resilience and viability of communities in a changing environment
Data files
Sep 07, 2023 version files 252.63 KB
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bird_data_processed.csv
169.43 KB
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bird_data_raw.zip
81.40 KB
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README.md
1.80 KB
Abstract
In order to assess community resilience, we propose to analyse how variation in overall abundance of individuals affect the number of species. We define community senstivity as the ratio between rate of change in log expected number of individuals in the community and the rate of change in the log expected number of species. Second, we define community resistance as the proportional reduction in expected number of individuals that the community can sustain before expecting to lose one species. To illustrate these concepts we use four datasets of bird communities in European deciduous forests.
We estimated the total variance of the species abundance distribution in order to calculate the community sensitivity and resistance. We found large differences in species heterogeneity and species-specific response to environmental fluctuations, the two major components of the total variance.
The datasets are collected from various previously published sources, see references below and in the paper. The code for importing and analysing the raw data as done in the paper can be found here: https://doi.org/10.5281/zenodo.8252471, but we also provide better-structured datasets for easier applications to others.
https://doi.org/10.5061/dryad.5dv41nsc2
All population estimates are based on nest search or mapping of territorial individuals within a specific area.
Description of data and file structure
The data is structured into ‘Raw’ and ‘Processed’ data and R-code to process the data.
The raw data is in different formats, some extracted from tables in puplications:
- Ammarnäs: https://doi.org/10.34080/os.v14.20236
- Birdsong Valley: https://doi.org/10.34080/os.v4.23023
- Budal: https://doi.org/10.1111/j.1474-919X.2004.00338.x
- Eastern Wood: https://doi.org/10.1002/9780470999592.app2
Some contains additional years of abundance.
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The processed data contains four columns:
- location: one of four locations: Ammarnäs, Budal, Birdsong Valley and Eastern Wood
- year: of sensus
- species:
- abundance:
The raw data contains four datasets:
- bird_ammarnas.csv: three columns: Year, Species, Abundance
- bird_sussex.txt: three columns: Species, Year, Abundance
- Birdsong Valley.xlsx:
two sheets: “Data”: five columns (unnamed): Species, Year, Abundance, Location, Reference.
“Info”: location and description - Budalen_pr_2018_revised.xlsx:
- one sheet: “Data”: data in wide format, Norwegian abbreviated names, but corresponding scientific names are found in the R-code “data_from_raw_to_processed.R”.
Code/Software
The code for importing and analysing the raw data as done in the paper can be found here: https://doi.org/10.5281/zenodo.8252471.
The code for processing the raw data to one single dataset can be found in the R-code “data_from_raw_to_processed.R”.
The data consists of population estimates based on nest search or mapping of territorial individuals within a specific area.
For the locations we have:
| Location | Position | Meters above sea level | Study area (size) | Time span |
| Ammarnäs | 65°58'-65°59'N, 15°58'-16°8E | 540 - 720 m.a.s.l. | 0.420 km2 | 1964-1999 |
| Budal | 62°45'N, 10°30'E | 800 m.a.s.l. | 0.3 km2 | 1967-2018 |
| Birdsong Valley | 55°43'N, 13°18'E | 0.13 km2 | 1953-1992 | |
| Eastern Wood | 51°30'N, -0°38'E | 0.16 km2 | 1950-1979 |