Citizen science data reveal altitudinal movement and seasonal ecosystem use by hummingbirds in the Andes Mountains

Ensuring connectivity is crucial to protect landscapes but it requires knowledge about how animals use ecosystems throughout the year. However, animal movements remain largely unknown in biodiversity hotspots, even for species that fulfill key ecological roles, as is the case of hummingbirds in the Andes. In the complex topography of mountain slopes, movement of these avian pollinators may occur either between habitat patches with asynchronous plant blooms or across ecosystems that are located within same elevation bands or along altitudinal gradients. Here, we used two decades (2000-2020) of records from citizen science data and boosted regression trees to predict monthly distributions for 55 hummingbird species in the Andes. We identified shifts in altitudinal distribution between contiguous months and calculated changes in the proportion of predicted distributions occupied by ecosystem types. Our findings reveal substantial altitudinal movement and differences in the proportion of ec..., , , # Citizen science data reveal altitudinal movement and seasonal ecosystem use by hummingbirds in the Andes Mountains

[https://doi.org/10.5061/dryad.w3r2280xs](https://doi.org/10.5061/dryad.w3r2280xs)

The zip file includes R code and dataset that were used to generate results for this publication.

Note that the dataset does not include eBird Basic Data (EBD) and Sampling Event Dataset (SED), which were downloaded from eBird ([ebird.org](https://ebird.org/home)) on 2021-09-01 with this date as last edition date.

Download of other data available from its original source (see manuscript methods): ground elevation layer (Amatulli et al., 2018), climatic covariates retrieved from the ERA5 monthly averaged data in the Copernicus Climate Data Store (0.25ºx0.25º grid, Hersbach et al., 2018), transformed land covers from the Copernicus Climate Change Service (ESA CCI Land cover, 2019), South America Ecosystems layer (The Nature Conservancy, 2008), GMBA Mountain inventory (https://ilias.unibe....