DOI: 10.5061/dryad.n02v6wx0m
title: Data from: Assessing the co-occurrence of European pine marten (Martes martes) with humans and domestic cats on a Mediterranean island

description: Anthropogenic activities often lead to changes in the distribution and
 behaviour of wild species. The mere presence of humans and free-roaming
 domestic cats (Felis catus) can affect wildlife communities; however,
 responses to these disturbances might not be ubiquitous and may vary with
 local conditions. We investigated European pine martens' (Martes
 martes) distribution on Elba Island, Italy, where the species is the only
 wild carnivore. In this system, pine martens act as the top predator, and
 human presence is mostly driven by seasonal tourism. We evaluated 1. pine
 marten’s occurrence in relation to vegetation type and elevation and the
 potential effects of proximity to settlements, 2. whether pine marten’s
 distribution was associated with the co-occurrence of humans and domestic
 cats, and, if so, 3. whether these co-occurrence patterns were associated
 with proximity to anthropogenic infrastructures. Additionally, we explored
 similarities in activity patterns between pine marten and the other two
 species. We collected camera-trap data at 77 locations throughout Elba
 Island in February-July 2020. Using single-season multi-state occupancy
 models, we found evidence that pine martens’ occupancy was generally high
 across all vegetation types and elevation, and proximity to settlements
 was only weakly associated with the species occurrence. Contrary to
 expectations, we found no evidence of an association between pine martens’
 distribution and the presence of either humans or free-roaming domestic
 cats on Elba Island. Opposing activity patterns might have facilitated
 pine martens' co-existence with humans, with pine martens being
 active at ground level almost exclusively during nighttime. On the
 contrary, cats and pine martens showed similar activity patterns, and
 further studies are needed to define the co-existence mechanisms. These
 findings have important management implications and suggest that response
 to direct and indirect anthropogenic pressures can be highly
 context-dependent and mediated by the availability of resources and
 competition mechanisms.
description: By Camera Trapping.  It has been processed
 using R and multispecies occupancy models (Rota et al.
 2016)  
description: # Data, R Code, and Output Supporting: **Assessing the co-occurrence of
 European pine marten (Martes martes) with humans and domestic cats on a
 Mediterranean island** This README file was generated on February 8, 2024
 by Fabiola Iannarilli. ## General Information ### 1. Title Data, R Code,
 and Output Supporting: Assessing the co-occurrence of European pine marten
 (*Martes martes*) with humans and domestic cats on a Mediterranean island
 ### 2. Author Information * **Emiliano Manzo** * *Institution:* Fondazione
 Ethoikos, Convento dell’Osservanza s.n.c. * *Address:* Radicondoli, Siena,
 Italy * *Email:* emiliano.manzo [at] ethoikos.it * **Fabiola Iannarilli**
 * *Institution:* Max Planck Institute of Animal Behavior, Department of
 Migration * *Address:* Konstanz, Germany * *Email:* fiannarilli [at]
 ab.mpg.de * **Paola Bartolommei** * *Institution:* Fondazione Ethoikos,
 Convento dell’Osservanza s.n.c. * *Address:* Radicondoli, Siena, Italy *
 **Andrea Bonacchi** * *Institution:* Fondazione Ethoikos, Convento
 dell’Osservanza s.n.c. * *Address:* Radicondoli, Siena, Italy * **Filippo
 Dell'Agnello** * *Institution:* Fondazione Ethoikos, Convento
 dell’Osservanza s.n.c. * *Address:* Radicondoli, Siena, Italy * **Stefania
 Gasperini** * *Institution:* Fondazione Ethoikos, Convento dell’Osservanza
 s.n.c. * *Address:* Radicondoli, Siena, Italy * **Roberto Cozzolino** *
 *Institution:* Fondazione Ethoikos, Convento dell’Osservanza s.n.c. *
 *Address:* Radicondoli, Siena, Italy ### 3. Date of data collection
 February 2020 - July 2020 ### 4. Geographic location of data collection
 Elba Island, Italy ### 5. Information about funding sources The project is
 funded by Fondazione Ethoikos. ## Sharing/Access Information ### 1. Links
 to publications Manzo E.*, Iannarilli F.*, Bartolommei P., Bonacchi A.,
 Dell’Agnello F., Gasperini S., Cozzolino R. Assessing the co-occurrence of
 European pine marten (*Martes martes*) with humans and domestic cats on a
 Mediterranean island. ### 2. Recommended citation Manzo E.*, Iannarilli
 F*., Bartolommei P., Bonacchi A., Dell’Agnello F., Gasperini S., Cozzolino
 R. (2024). Data, R Code, and Output Supporting: Assessing the
 co-occurrence of European pine marten (*Martes martes*) with humans and
 domestic cats on a Mediterranean island. ## Data & File Overview ###
 File List The compressed folder
 'Manzo_Iannarilli_et_al_2024_data_and_code' contains data, R
 scripts, and relative output files (figures and htmls files) to reproduce
 figures and results reported in Manzo et al. (submitted). We recommend
 users to unzip the folder in the desired working directory and use the R
 user interface RStudio (RStudio Team 2024) to reproduce the analysis.
 Clicking the 'Manzo_Iannarilli_et_al_2024_data_and_code.Rproj'
 file will directly open the RStudio interface and will allow users to
 navigate through the different R scripts and select the code to reproduce
 the analysis. More information on how to use a project in RStudio are
 available at: [Using
 Projects](https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects). #### 1. The subfolder 'data' contains: * **Detection_History_Cats.csv, Detection_History_Human.csv, Detection_History_Martes.csv:** These files contain detection/nondetection data of domestic cats (*Felis catus*), humans (hiking and biking), and pine martens *Martes martes*, respectively. Each file consists of 30 columns (named from o1 to o30) - each representing a day of sampling - and 78 rows - one row for each of the 77 sampled sites, plus the header). 1s and 0s represent detection and nondetection of a certain species at a certain site during a specific day of sampling. * **DB_Elba_Activity.csv:** This file contains information to calculate the activity patterns of the three species mentioned above. Each row represents an independent detection event. * Column 1: sp_binomial: scientific name of the species detected. * Column 2: deployment_name: identifier for the location sampled. * Column 3: photo_time: time of the day of the detection event (HH:MM:SS). * Column 4: photo_datetime: date and time of the day of the detection event (YYYY-MM-DD HH:MM:SS). * Column 5: longitude: longitude of the sampled site where the detection event occurred. * Column 6: latitude: latitude of the sampled site where the detection event occurred. * **Covarites.csv:** This file contains information to calculate the activity patterns of the three species mentioned above. Each row represents an independent detection event. * Column 1: Camera_ID: identifier for the location sampled (same as deployment_name in *DB_Elba_Activity.csv*). * Column 2: Start_Date: first day of sampling at a certain location. * Column 3: Retrieval_Date: last day of sampling (either retrieval or camera inactive) at a certain location. * Column 4: Latitude: latitude of the sampled site where the detection event occurred. * Column 5: Longitude: longitude of the sampled site where the detection event occurred. * Column 6: Feature Type: class of dominant vegetation at the location sampled. * Column 7: Road_distance_m: Euclidean distance of the location sampled from the closest paved road. * Column 8: Settl_distance_m: Euclidean distance of the location sampled from the closest human settlement. * **subfolder 'Data for mapping'** contains files to map the predicted estimates of occupancy for the three species: * subfolder 'Grid 1km': shapefile of a 1x1 km grid overlapping Elba Island. * subfolder 'Italy_municipalities_ISTAT_2023': shapefile reporting Elba Island (for map background). * Database_Centroids: latitude and longitude, distance to roads and settlements, and dominant vegetation type for all the 1x1 km cell contained in 'Grid 1 km" shapefile. #### 2. The subfolder 'figures' contains figures included in Manzo et al. (submitted). The figures were created running the code reported in the R scripts files contained in the main folder. Each figure is in a .png format and labeled based on its reference in the manuscript. #### 3. The subfolder 'htmls' contains the html outputs (including plots stored in the associated folder 'figures') associated with the R scripts included in the main folder. For a description of the content of each file, please refer to the description of the associated R script labeled using a similar name. #### 4. The subfolder 'custom\_functions' contains the R script 'single\_activity.R' which contains code to organize the data in independent events and calculate activity patterns based on KDEs. #### 5. Martes\_martes\_Elba\_cooccurrence.R R script containing code to calculate cooccurrence. #### 6. Martes\_martes\_Elba\_activity.R R script containing code to calculate activity patterns. ## References * Manzo E.*, Iannarilli F.*, Bartolommei P., Bonacchi A., Dell’Agnello F., Gasperini S., Cozzolino R. Assessing the co-occurrence of European pine marten (*Martes martes*) with humans and domestic cats on a Mediterranean island. * RStudio Team (2024). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA. [URL](http://www.rstudio.com/) ## Version changes Dec-2024: Added the corrected version of the R script where all variable names were updated to English to match the centroid CSV.