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Descripción
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PROJECT DESCRIPTION
Apex predators play a crucial role in maintaining ecosystem functioning and biodiversity, so studying their diet is key to understanding habitat dynamics. In the context of global change, predators must adapt to both natural ecological gradients such as elevation, and human-driven impacts, including climate and land use changes.
Using camera traps, we assessed the diet of Mediterranean golden eagles (Aquila chrysaetos homeyeri) across the Iberian Peninsula.
We reviewed 520,282 images collected over 1365 monitoring days, spanning 50 distinct reproductive events over four breeding seasons (2017-2020).
We analyzed the frequency and biomass of each prey species in relation to elevation and land use, which have recently experienced significant anthropogenic changes, mostly due to climate change and rural abandonment. Elevation emerged as the primary driver of dietary variation, with consistent shifts across land-use categories.
Lagomorphs and Columbiformes dominated their diet at lower elevation, while wild ungulates, passerines, and reptiles increased at higher elevations. Furthermore, prey diversification was greater at higher elevations for all land uses.
Despite lagomorphs remaining the most consumed prey, wild ungulates (mostly roe deer) and reptiles represented a higher proportion than previous studies. Rural abandonment and climate change are reshaping prey communities in the Iberian Peninsula.
Our findings highlight the high adaptability of golden eagles to changes in prey availability, driven by anthropogenic global change.
DATA DESCRIPTION
The dataset is part of the AEQUILIBRIUM+ project data from 2017 to 2020. The publicly available information consists of two types: databases on prey, land use, and territorial information, as well as R scripts to perform the study analysis. The published contents are as follows:
Databases: xlsx format (2 files).
Scripts: .R format (7 files). (2026-02)
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Notas
| METHODOLOGY
Fieldwork and Data Collection:
Between 2017–2020, 50 golden eagle reproductive events were monitored across 42 territories in the Iberian Peninsula. Nest monitoring included identifying breeding platforms in March, retrieving nestlings at 35–45 days old for banding and measurement, and installing motion-activated cameras in the nests. All handling was performed by authorized personnel under regional government permits.
Camera Trap Setup:
Six BROWNING© camera models were used, positioned ~2 meters from nests. Cameras captured 3 photos per activation, with a 5-minute interval between bursts, running continuously until fledging (Aug–Sept) to record prey deliveries with minimal disturbance.
Diet Composition Analysis:
Images were reviewed to identify prey type, age, condition, and portion delivered. Total prey quantity, delivery frequency, and biomass were calculated. Biomass estimates used published species weights, with adjustments for partial carcasses and age classes. Usable biomass was defined as 70–80% of body mass depending on prey size.
Habitat Covariates:
Mean elevation and land use were calculated using Digital Terrain Models (IGN) and CORINE Land Cover 2018. A 36 km² buffer was applied around each nest to simulate home range. Land use types were grouped into six categories, including three mixed formations based on dominant land cover combinations.
Statistical Analysis:
Diet variation was assessed using log-transformed daily frequency and biomass values. Linear Mixed Models (LMMs) analyzed the influence of elevation, land use, and prey taxonomy (class/order), with year nested within territory as a random effect. Visualizations were generated using ggplot2.
FILES
DATABASES AND GEOGRAPHIC INFORMATION LAYERS (xlsx formats)
Content: Dataset with databases (xlsx format).
Formats: xlsx databases, R scripts.
Total files: 9 (2 .xlsx + 7 .R).
DATABASES (2 files)
2 files - xlsx format - DB_MONITOREO- EFT_DB-
7 files - .R format, one for each part of the analysis:
00_Packages_databases_functions
01_Model_averaging
02_Frecuency_analysis
03_Biomass_analysis
04_Triple_interaction_SM
05_Table1
06_Relevel at different elevations
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