Ecological and intrinsic drivers of foraging parameters of Eurasian lynx across Europe

The estimation of foraging parameters is fundamental for understanding predator ecology. Predation and feeding can vary with multiple factors, such as prey availability, presence of kleptoparasites, and human disturbance. However, our knowledge is mostly limited to local scales, which prevents studying effects of environmental factors across larger ecological gradients. Here, we compared inter-kill intervals and handling times of Eurasian lynx (Lynx lynx) across a large latitudinal gradient from subarctic to the Mediterranean ecosystems using a standardised dataset of predicted adult ungulate kills from 107 GPS-collared lynx from nine distinct populations in Europe. We analysed variations in these two foraging parameters in relation to proxies reflecting prey availability, scavengers’ presence, and human disturbance, to improve our understanding of lynx predation at a continental scale. We found that inter-kill intervals and handling times varied between populations, social status and i..., We used GPS and kill-sites data from nine populations across Europe. Data were collected through the EUROLYNX network, a collaborative bottom-up platform of lynx researchers across Europe for sharing data and expertise (Heurich et al, 2021). We first developed a predictive model to classify GPS location clusters into adult ungulate kills or other (non-kill and/or small prey kill), following Oliveira et al. (2022) - see Appendix S2 for more details. The dataset used for this part of the analyses is entitled \"dataset_GLC_classification\". 
Secondly, we used these predicted GPS location clusters to calculate inter-kill intervals and handling times. For each parameter, we extracted environmental covariates trelated to prey availability, human disturbance, and scavengers presence. We provide two datasets, one for inter-kill intervals (\"inter_kill\"), and another for handling times (\"feeding_t\"). 
For more details, please see the README document (\"README_dataset_randomforest_classification.txt\"..., , # Data for the Eurasian lynx GLCs' characteristics for classification with random forest algorithm

This README file describes the provided dataset for the random forest classification analysis, and variation of foraging parameters (handling time and inter-kill interval).

**Description of the data and file structure**

* According to our paper, this dataset contains the information required to run the random forest models. It includes the type of cluster (class), animal social status (social_status), and cluster characteristics (latitude, cluster duration, number of cluster locations, fidelity, maximum foray, average cluster distance, maximum cluster radius, and night proportion fixed and automatic). All these parameters were extracted from GPS location clusters, using the GPSeqClus R package ([https://doi.org/10.1111/2041-210X.13572](https://doi.org/10.1111/2041-210X.13572)).
* Format(s): .csv
* Size(s): 138 KB
* Dimensions: 3435 rows x 11 columns
* Variables:

*class - Type of clus...