Data from: Projected impacts of climate change on interactions between plants and avian frugivores across the Americas
Data files
Abstract
Aim:
Frugivorous birds provide crucial seed-dispersal functions in terrestrial ecosystems. However, the impact of climate change on plant–avian frugivore interactions remains unclear due to past methodological limitations. In this study, we address this by mapping these interactions across the Americas and projecting shifts in interaction diversity under future climate scenarios.
Location:
North, South, and Central America.
Time Period:
Present (1980–2010) and future (2070–2100).
Major Taxa Studied:
Frugivorous birds and fleshy-fruited plants.
Methods:
Using a trait-matching framework, we estimated interaction probabilities between frugivorous birds (n = 629 species) and fleshy-fruited plants (n = 3,283 species) at the ecoregion level. To estimate climate impacts, we modelled how interaction probabilities will change under future scenarios based on the overlap between avian climate niches and ecoregion climates. From these probabilities, we calculated plant–frugivore interaction diversity as the effective number of avian partners for a given plant species in an ecoregion. We then used simulations to examine how avian dietary flexibility and dispersal may buffer future diversity of plant–frugivore interactions.
Results:
Under future climate scenarios, our models projected a decline in interaction diversity across most ecoregions, especially in tropical and subtropical biomes. Simulations indicated that interaction rewiring through dietary flexibility and dispersal could partially mitigate losses of interaction diversity, particularly in tropical forests.
Main conclusions:
Our results suggest that the diversity of plant–frugivore interactions in the Americas will decline in response to climate change, potentially undermining the stability of seed-dispersal functions. We also show that the resilience of this function depends on the capacity of frugivorous birds to modify their geographic ranges or dietary preferences. However, the extent to which avian dispersal and adaptation will regulate future species interactions remains unknown, highlighting the importance of maintaining high plant–frugivore interaction diversity in current assemblages to buffer ecosystems against future climatic changes, especially in the tropics.
https://doi.org/10.5061/dryad.h44j0zpvs
Description of the data and file structure
Files and variables
File: Data.zip
Description:
NOTE: column names referred to in []
Climate data:
avian_niche_hypervolumes: hypervolumes summarizing the climatic niche of each frugivorous bird species used in this study (n = 539). Climatic niche hypervolumes were generated from average monthly precipitation (10 g/m2) and temperature (°C) for processed eBird occurrence records at a 1 km resolution and at the month and year of the occurrence (see Methods or Code/1.2_PreProcessing.R). Climate data was sourced from CHELSA.
Ecoregion_Hypervolumes: hypervolumes summarizing current climate for all ecoregions used in this study (n = 277). Hypervolumes were generated from average monthly temperature and precipitation layers (1 km resolution, 1980–2010) extracted across ecoregion polygon boundaries (see Methods or Code/1.2_PreProcessing.R). Climate data was sourced from CHELSA.
Future_Ecoregion_Hypervolumes: hypervolumes summarizing future climate for all ecoregions used in this study (n = 277). Hypervolumes were generated from average monthly temperature and precipitation layers (1 km resolution; time frame: 2070-2100) extracted across ecoregion polygon boundaries. An RCP 7.0 emissions scenario was applied across 4 climate models (CM1: GFDL-ESM4, CM2: IPSL-CM6A, CM3: MPI-ESM1, CM4: MRI-ESM2) (see Methods or Code/1.2_PreProcessing.R). Climate data was sourced from CHELSA.
Ecoregion communities:
BIRD_RM_COMMS.csv: a table outlining which bird species [Species] occur in which ecoregions [Ecoregion], as determined through intersecting BirdLife bird range maps with ecoregion polygons (see Methods or Code/1.2_PreProcessing.R).
FUT_BIRD_COMMS_DISP.csv: a table outlining which bird species [Species] occur in which ecoregions [Ecoregion] under a future dispersal scenario, as determined through intersecting BirdLife bird range maps with ecoregion polygons and including species with a dispersal zone larger than the distance between prospective source and destination ecoregions (see Methods or Code/1.2_PreProcessing.R).
PLANT_RM_COMMS.csv: a table outlining which plant species [Species] occur in which ecoregions [Ecoregion], as determined through intersecting BIEN plant range maps with ecoregion polygons (see Methods or Code/1.2_PreProcessing.R).
Bird and plant data:
CombinedPlantTRAITS.csv: a table of fruit length measurements (mm) [fruit_length] for all plant species [Species] used in this study (n = 3283). Plant trait data were sourced from Dehling et al. (2016), Kissling et al. (2019), and Sinnott-Armstrong et al. (2018).
McFadden_BIRDTRAITS.csv: a table of gape width measurements (mm) [Gape_width] for all frugivorous bird species [Species] (n = 2231). Bird trait data were sourced from McFadden et al. (2022).
DispDistances.csv: a table of dispersal distances (m) [DispPred] for all bird species [Species] used in the main analysis and supplementary analyses. These dispersal distance values were predicted using a linear mixed model trained on a known dispersal distance dataset (see Methods).
GenLengths.csv: a table of generation lengths [GenLength] for all bird species [Species] (n = 11,244). This table is used when estimating bird species dispersal zones. Generation length data were sourced from Bird et al. (2020). Units = years.
RangeSizes.csv: a table of range sizes [Range_Size] for all bird species [Species1] (n = 11,010). This table is used for Figure S1. Range size data were sourced from Tobias et al. (2022). Units = km2.
birdRM_combined.shp, birdRM_combined.shx, birdRM_combined.dbf: shapefile showing cleaned and unionized bird range map data sourced from BirdLife.
plantRM_combined.shp, plantRM_combined.shx, plantRM_combined.dbf: shapefile showing cleaned and unionized plant range map data sourced from BIEN.
Ecoregion data:
ecoregion_codes.csv: a table of ecoregion names [Ecoregion] and accompanying codes [Code] used throughout the analysis.
Realms_codes.csv: a table of ecoregion name [Ecoregion] with accompanying realm code [REALM]. The realm codes refer to the following biogeographic realms: NT = Neotropic, Narc = Nearctic, PA = Palearctic, IM = Indomalaya, AT = Afrotropic, OC = Oceania, AA = Australasia, AN = Antarctic. These classifications are derived from the WWF Terrestrial ecoregion dataset. This table is used in future avian community assembly under a dispersal scenario (see Methods or Code/1.2_PreProcessing.R).
ECOBIOMES.csv: a table of all ecoregions [Ecoregion] with accompanying codes [Code], biome name [Biome] with accompanying biome code [BiomeCode2], realm code [REALM] and realm group [Realm_group]. The realm codes refer to the following biogeographic realms: NT = Neotropic, Narc = Nearctic. The realm group variable refers to whether a biome occurs in both the Nearctic and Neotropics or solely in either the Nearctic or Neotropics. These classifications are derived from the WWF Terrestrial ecoregion dataset.
ecoregions_combined.shp: cleaned and unionized ecoregion polygon data sourced from WWF.
Code/software
File: Code.zip
PIPELINE.R: This is the main holder script from which all sub-scripts can be run to replicate the main analysis/results presented in the manuscript. The main stages of the analysis (2.1_TraitMatching.R, 2.2_ClimaticSuitability.R, 2.3_IntDiversityProjections) are run for all 4 scenarios.
1.1_Functions_Packages.R: This script creates all directory paths and loads all functions and packages required throughout the analysis.
1.2_PreProcessing.R: The assembly of ecoregion communities (both present and future) occurs in this script. Avian climatic niche estimates are generated in this script. Ecoregion climate hypervolumes (present and future) are generated in this script.
1.3_LoadData.R: This script defines environment parameters for a given analysis and loads in all datasets required throughout the analysis.
2.1_TraitMatching.R: Interaction probabilities, as derived from the level of trait correspondence between a co-occurring pair of bird and plant, are calculated in this script across all ecoregion communities under a given scenario.
2.2_ClimaticSuitability.R: The climatic suitability weighting on interaction probabilities, as derived through comparing avian climatic niches with present and future ecoregion climate, is implemented in this script across all ecoregion communities under a given scenario.
2.3_IntDiversityProjections.R: Shift in interaction diversity is calculated in this script from weighted interaction probabilities across all ecoregion communities under a given scenario.
3.1_Outputs.R: All figures presented in the manuscript and supplementary materials are generated in this script including trait maps, interaction diversity map and maps of projected climate impacts on interaction diversity with forest biome boxplots.
Access information
Other publicly accessible locations of the data:
- https://www.worldwildlife.org/publications/terrestrial-ecoregions-of-the-world
- https://bien.nceas.ucsb.edu/bien/
- https://www.birdlife.org/
- https://ebird.org/home
- https://chelsa-climate.org/
Data was derived from the following sources:
- McFadden, I. R., Fritz, S. A., Zimmermann, N. E., Pellissier, L., Kissling, W. D., Tobias, J. A., Schleuning, M., & Graham, C. H. (2022). Global plant-frugivore trait matching is shaped by climate and biogeographic history. Ecology Letters, 25(3), 686–696. https://doi.org/10.1111/ele.13890
- Dehling, D. M., Jordano, P., Schaefer, H. M., Böhning-Gaese, K., & Schleuning, M. (2016). Morphology predicts species’ functional roles and their degree of specialization in plant–frugivore interactions. Proceedings of the Royal Society B: Biological Sciences, 283(1823), 20152444. https://doi.org/10.1098/rspb.2015.2444
- Kissling, W. D., Balslev, H., Baker, W. J., Dransfield, J., Göldel, B., Lim, J. Y., Onstein, R. E., & Svenning, J.-C. (2019). PalmTraits 1.0, a species-level functional trait database of palms worldwide. Scientific Data, 6(1), 178. https://doi.org/10.1038/s41597-019-0189-0
- Sinnott-Armstrong, M. A., Downie, A. E., Federman, S., Valido, A., Jordano, P., & Donoghue, M. J. (2018). Global geographic patterns in the colours and sizes of animal-dispersed fruits. Global Ecology and Biogeography, 27(11), 1339–1351. https://doi.org/10.1111/geb.12801
- Bird, J. P., Martin, R., Akçakaya, H. R., Gilroy, J., Burfield, I. J., Garnett, S. T., Symes, A., Taylor, J., Şekercioğlu, Ç. H., & Butchart, S. H. M. (2020). Generation lengths of the world’s birds and their implications for extinction risk. Conservation Biology, 34(5), 1252–1261. https://doi.org/10.1111/cobi.13486
- Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang, J., Sayol, F., Neate-Clegg, M. H. C., Alioravainen, N., Weeks, T. L., Barber, R. A., Walkden, P. A., MacGregor, H. E. A., Jones, S. E. I., Vincent, C., Phillips, A. G., Marples, N. M., Montaño-Centellas, F. A., Leandro-Silva, V., Claramunt, S., … Schleuning, M. (2022). AVONET: morphological, ecological and geographical data for all birds. In Ecology Letters (Vol. 25, Issue 3, pp. 581–597). John Wiley and Sons Inc. https://doi.org/10.1111/ele.13898
