Functional diversity in agricultural landscapes: evidence of long-term clustering and multi-scale effects of land use on avian communities
Data files
Jan 26, 2026 version files 9.95 GB
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commun_dfix_ran.csv
902.98 KB
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commun_dfix.csv
455.01 KB
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Dfix_hv.list.RData
3.34 GB
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Dfix_ran_hv.list.RData
6.57 GB
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Dfix_ran.RData
554.41 KB
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Dfix.RData
35.26 MB
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FuncDiv_script.R
74.72 KB
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README.md
12.47 KB
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traits_dfix_ran.csv
4.35 KB
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traits_dfix.csv
4.36 KB
Abstract
Dataset DOI: 10.5061/dryad.bzkh189r4
Description of the data and file structure
Bird data included in these datasets were derived from the Long-term Monitoring Program of Breeding Birds of Lombardy using data collected between 2007 and 2021 (for details, see Bani et al., 2009, https://doi.org/10.1080/08927014.2009.9522509; Tirozzi et al., 2021, https://doi.org/10.3390/ani11123426). Species traits were compiled using information from Pearman et al. 2014, https://doi.org/10.1111/geb.12127; Wilman et al. 2014, https://doi.org/10.1890/13-1917.1; Storchová & Hořák 2018, https://doi.org/10.1111/geb.12709; Tobias et al. 2022, https://doi.org/10.1111/ele.13898).
For further details see the associated article.
Files and variables
File: Dfix.RData
Description: The dfix dataset covers a 15-years sampling period (2007-2021) and includes fixed point counts with at least five years of repeated samplings. R workspace containing the following objects:
- commun = dataframe of the avian community matrix (observation IDs in rows, species EURING codes in columns, where E = EURING, and the five-digit number identifies the unique code assigned to each species. EURING is the coordinating organisation for European bird ringing schemes. Species are codified using standardised codes; for further details and for correspondence between codes and species names visit https://euring.org/data-and-codes/euring-codes). Bird abundances are reported as the number of breeding pairs (see the associated article for details)
- dat = dataframe of survey data:
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- WGS84_long: longitude of the observation (WGS 84 Datum, EPSG 4326)
- WGS84_lat: latitude of the observation (WGS 84 Datum, EPSG 4326)
- site: point count ID identifying spatially distinct point counts
- Group: primary sampling unit ID grouping point counts that fall within the same sampling unit
- Year: year of sampling
- dat_FD = dataframe resulting from the analyses, containing the output data from section 1 of the R script FuncDiv_script.R
- tbl_site = dataframe of no. of surveys per each site (rows) and year (columns)
- traits.sel2 = species x traits matrix. A detailed explanation of the traits is provided in the Supporting Information S14 of the associated article and in the READMI for the file "traits_dfix.csv"
- alpha_perm_trend = simulated functional richness under random expectation given species richness. These data were produced using the HPC Leonardo https://leonardo-supercomputer.cineca.eu/
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- the other columns (sim.x) represent each of the 1000 simulated values, where x is the index of the corresponding simulation
- div_perm_trend = simulated functional divergence under random expectation given species richness. These data were produced using the HPC Leonardo https://leonardo-supercomputer.cineca.eu/
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- the other columns (sim.x) represent each of the 1000 simulated values, where x is the index of the corresponding simulation
- eve_perm_trend = simulated functional evenness under random expectation given species richness. These data were produced using the HPC Leonardo https://leonardo-supercomputer.cineca.eu/
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- the other columns (sim.x) represent each of the 1000 simulated values, where x is the index of the corresponding simulation
- lab_CWM_plot = dataframe to be used for generating Fig. 4.
- ori: original name of the trait derived from the model output
- trait_title: title for each subplot
- trait_group: traits to be used for assigning colours in the plot
File: Dfix_ran.RData
Description: The dfix_ran dataset covers a 15-years sampling period (2007-2021) and includes both fixed and non-permanent point counts. R workspace containing the following objects:
- commun: dataframe of the avian community matrix (observation IDs in rows, species EURING codes in columns, where E = EURING, and the five-digit number identifies the unique code assigned to each species. EURING is the coordinating organisation for European bird ringing schemes. Species are codified using standardised codes; for further details and for correspondence between codes and species names visit https://euring.org/data-and-codes/euring-codes). Bird abundances are reported as the number of breeding pairs (see the associated article for details)
- traits.sel2 = species x traits matrix. A detailed explanation of the traits is provided in the Supporting Information S14 of the associated article and in the READMI for the file "traits_dfix.csv"
- dat_FD = dataframe resulting from the analyses described in the R script FuncDiv_script.R, containing the output data and the variables required to perform land-use models.
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- SES_rich: standardised effect size for functional richness (numeric)
- SES_div: standardised effect size for functional divergence (numeric)
- SES_eve: standardised effect size for fucntional evenness (numeric)
- fric_obs: observed functional richness (numeric)
- fdiv_obs: observed functional divergence (numeric)
- feve_obs: observed functional evenness (numeric)
- p.lower.rich_01: presence/absence of functional clustering for functional richness. 0 if absent, 1 if present
- p.lower.div_01: presence/absence of functional clustering for functional divergence. 0 if absent, 1 if present
- p.lower.eve_01: presence/absence of functional clustering for functional evenness. 0 if absent, 1 if present
- WGS84_lat: latitude of the observation (WGS 84 Datum, EPSG 4326)
- WGS84_long: longitude of the observation (WGS 84 Datum, EPSG 4326)
- Year: year of sampling
- Land-use variables were calculated as percentage of cover within a specified buffer around the point count. Below, the explanation of abbreviations and acronyms:
- built: built-up areas
- orch: orchards
- woodycrops: timber plantations
- fk: hedgerows' density
- meadows: meadows
- evo_shurbs: shrubs
- forest: forests
- water_wet: water bodies and wetlands
- arable: arable land
- rice: rice fields
- b100: 100-m buffer radius
- b500: 500-m buffer radius
- b2000: 2000-m buffer radius
File: Dfix_hv.list.RData
Description: Dfix_hv.list.RData: R workspace containing the list of hypervolumes for each observation in the dataset Dfix. Names of the hypervolumes correspond to the observation IDs.
File: Dfix_ran_hv.list.RData
Description: Dfix_ran_hv.list.RData: R workspace containing the list of hypervolumes for each observation in the dataset Dfix_ran. Names of the hypervolumes correspond to the observation IDs.
File: FuncDiv_script.R
Description: R script to run the analyses. All instructions and explanations are contained within the script.
File: commun_dfix.csv
Description: Community matrix for the dfix dataset. The dfix dataset covers a 15-years sampling period (2007-2021) and includes fixed point counts with at least five years of repeated samplings.
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- All the other columns represent the EURING code for avian species (E = EURING, the five-digit number identifies the unique code assigned to each species. EURING is the coordinating organisation for European bird ringing schemes. Species are codified using standardised codes; for further details and for correspondence between codes and species names visit https://euring.org/data-and-codes/euring-codes). Bird abundances are reported as the number of breeding pairs (see the associated article for details)
File: commun_dfix_ran.csv
Description: Community matrix for the dfix_ran dataset. The The dfix_ran dataset covers a 15-years sampling period (2007-2021) and includes both fixed and non-permanent point counts.
- ID: observation ID; a unique code for each observation collected at a specific site in a specific year
- All the other columns represent the EURING code for avian species (E = EURING, the five-digit number identifies the unique code assigned to each species. EURING is the coordinating organisation for European bird ringing schemes. Species are codified using standardised codes; for further details and for correspondence between codes and species names visit https://euring.org/data-and-codes/euring-codes). Bird abundances are reported as the number of breeding pairs (see the associated article for details)
File: traits_dfix.csv
Description: Species x traits matrix for the dfix dataset. For further information on traits see Supporting Information S14 in the associated article.
- Euring: EURING code for avian species (E = EURING, the five-digit number identifies the unique code assigned to each species. EURING is the coordinating organisation for European bird ringing schemes. Species are codified using standardised codes; for further details and for correspondence between codes and species names visit https://euring.org/data-and-codes/euring-codes)
- Weight: mean weight in breeding season, unsexed (g) (numerical trait)
- Clutch: mean clutch size, i.e. number of eggs (numerical trait)
- Broods: mean number of broods per breeding season (numerical trait)
- HWI: Hand-Wing Index, i.e. the Kipps' distance corrected fro wing size (numerical trait)
- Hab: main habitat where the species lives; categorical trait with six levels
- Diet: main source of foods on which the species feeds on; categorical trait with five levels
- Nest: nesting habits in relation to types of location where birds build their nests; categorical trait with five levels
- FB_Sa: foraging behaviour "sally"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FB_Fg: foraging behaviour "foliage glean"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FB_Pp: foraging behaviour "pursuit/pounce"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FB_Gpdop: foraging behaviour "graze/pick-peck-stab/dig/overturn object/probe"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Ca: foraging substrate "canopy"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Sh: foraging substrate "shrub.low.high"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Ve: foraging substrate "vegetation"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Ai: foraging substrate "air"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Wa: foraging substrate "water"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
- FS_Gm: foraging substrate "ground/mud"; categorical binary trait; 0 if the characteristic is absent, 1 if it is present
File: traits_dfix_ran.csv
Description: Species x traits matrix for the dfix_ran dataset. For the content of the dataset, refer to the file "traits_dfix.csv". For further information on traits see Supporting Information S14 in the associated article.
Code/software
Analyses were run using R version 4.3.2 (R Core Team, 2023, https://www.R-project.org/) and the HPC Leonardo (https://leonardo-supercomputer.cineca.eu/)
