DOI: 10.5061/dryad.q573n5tv4
title: Data from: Habitat selection and outdoor recreation explain human-carnivore conflict

description: Human-wildlife conflict occurs anywhere humans and wildlife overlap with
 significant socio-ecological consequences. As participation in outdoor
 recreation grows, so too does the potential for conflict between people
 and wildlife. This work investigates how outdoor recreation affects the
 movement behavior of a large carnivore and demonstrates the potential for
 human activity to lead to habituation in mountain lions (Puma concolor).
 Despite evidence of habituation, we found that human-tolerant individuals
 are not more likely to engage in conflict. Instead, mountain lion attacks
 on people, and other conflict events, are best explained by an overlap in
 high-quality mountain lion habitat and concentrated human presence. This
 work offers a mechanistic understanding of human-wildlife conflict and
 demonstrates behavioral pathways that contribute to human-wildlife
 coexistence.
description: # Data from: Habitat selection and outdoor recreation explain
 human-carnivore conflict Dataset DOI:
 [10.5061/dryad.q573n5tv4](10.5061/dryad.q573n5tv4) ## Description of the
 data and file structure The dataset provided can be used to reproduce
 results associated with the manuscript titled "Habitat selection and
 outdoor recreation explain human-carnivore conflict" by Morgan et al.
 2025 (in review). These data consist of .csv files originally analyzed
 using R (version 3.6.0). All GPS movement data were collected by the Santa
 Cruz Puma Project within California's Santa Cruz Mountains, USA,
 between 2018 and 2023. GPS data have been stripped of location information
 due to the sensitive nature of mountain lion space use within the study
 area. Human outdoor recreation data were derived from Strava Metro data
 collected from 2018–2023. Recreation data represent on-trail recreation
 intensity at multiple unique spatial and temporal scales around each used
 and available GPS location. Further details on how recreation intensity
 was calculated can be found in the manuscript. Human-mountain lion
 conflict data are based on 23 confirmed mountain lion attacks on people
 occurring in California between 1986 and 2024. Additional types of
 human-mountain lion conflict, such as depredations, nuisance reports,
 potential conflict, and sightings, are included and were compiled by
 California Department of Fish and Wildlife from 2018–2024. Together these
 data can be used to model mountain lion behavioral response to outdoor
 recreation activity and to better understand the drivers of human-mountain
 lion conflict. ### Files and variables #### File:
 1_morgan_et_al_issa_steps.csv **Description:** This file contains all core
 data for fitting integrated step selection analyses (iSSA), including
 columns for pumaID, stepID, movement characteristics, and standardized
 habitat covariates. This file should be merged with the appropriate
 recreation file based on the recreation scale of interest. Files should be
 merged based on “unique_pt_id” column.  ##### Variables * unique_pt_id:
 unique identifier of each GPS relocation. Includes both used and available
 points. * pumaID: individual mountain lion identifier * sex: male/female *
 case: used locations = 1, available locations = 0 * stepID: unique step
 identifier, each consisting of 1 used location and 20 available locations
 * start_time_UTC: date and time at start of step, timezone = UTC *
 end_time_UTC: date and time at end of step, timezone = UTC * year:
 calendar year of movement step * sl_km: step length in kilometers *
 sl_log_km: natural log of step length in kilometers * ta_rad: turning
 angle in radians; Note: this column contains 'NA' values (not
 applicable) for locations that do not have have a valid relocation
 immediately prior and therefore no turning angle could be calculated.  *
 hd_150_end_std: standardized housing density at end of step *
 slope_end_std: standardized slope at end of step * cover_end_std:
 standardized % cover at end of step * dist_urban_end_std: standardized
 distance to nearest urban edge at end of step * dist_trail_end_std:
 standardized distance to nearest trail at end of step #### File:
 2_morgan_et_al_issa_recreation.zip **Description:** This folder contains
 outdoor recreation intensity data for all spatial and temporal scales
 tested. Each file is named according to the temporal scale at which
 recreation was calculated. Within each file there are columns named based
 on the spatial scale tested. For example, the file
 “rec_dat_01hr_AVG365da.csv” refers to the mean hourly recreation intensity
 based on the previous 365 days of trail use data. Within this file, the
 column “avg_rec_all_30_end” refers to the recreation intensity within 30 m
 of the end of each step. Merging this file with
 1_morgan_et_al_issa_steps.csv will provide data necessary for fitting top
 performing iSSA model. * rec_dat_12mo.csv - cumulative recreation
 intensity based on previous 12 months of trail use * rec_dat_30da.csv -
 cumulative recreation intensity based on previous 30 days of trail use *
 rec_dat_01da.csv - cumulative recreation intensity based on previous 1 day
 of trail use * rec_dat_24hr.csv - cumulative recreation intensity based on
 previous 24 hours of trail use * rec_dat_04hr.csv - cumulative recreation
 intensity based on previous 4 hours of trail use * rec_dat_01hr.csv -
 cumulative recreation intensity based on previous 1 hour of trail use *
 rec_dat_04hr_AVG07da.csv - average recreation intensity over previous 4
 hours based on previous 7 days of trail use * rec_dat_04hr_AVG30da.csv -
 average recreation intensity over previous 4 hours based on previous 30
 days of trail use * rec_dat_04hr_AVG90da.csv - average recreation
 intensity over previous 4 hours based on previous 90 days of trail use *
 rec_dat_04hr_AVG180da.csv - average recreation intensity over previous 4
 hours based on previous 180 days of trail use *
 rec_dat_04hr_AVG365da.csv - average recreation intensity over previous 4
 hours based on previous 365 days of trail use * rec_dat_01hr_AVG07da.csv -
 average recreation intensity over previous 1 hour based on previous 7 days
 of trail use * rec_dat_01hr_AVG30da.csv - average recreation intensity
 over previous 1 hour based on previous 30 days of trail use *
 rec_dat_01hr_AVG90da.csv - average recreation intensity over previous 1
 hour based on previous 90 days of trail use * rec_dat_01hr_AVG180da.csv -
 average recreation intensity over previous 1 hour based on previous 180
 days of trail use * rec_dat_01hr_AVG365da.csv - average recreation
 intensity over previous 1 hour based on previous 365 days of trail use
 #### File: 3_morgan_et_al_CA_conflict.csv **Description:** This file
 contains human-mountain lion conflict data across the state of California
 and was used to fit generalized linear models predicting the drivers of
 conflict. Attack and non-attack locations are defined in the “case_attack”
 column, while wildlife incident report events are defined in the
 “case_wir” column. Recreation intensity for each cell is defined by
 “rec_std”, while “rsf_fix_std”, “rsf_min_std”, “rsf_max_std” refer to the
 predicted relative probability of mountain lion space use based on
 population-level fixed effects, as well random effect estimates
 representing shy and bold individuals in our top fitting iSSA model. #####
 Variables * cell_id: unique identifier for each used and available
 location across CA * case_attack: attack locations = 1, available
 locations = 0 * case_wir: locations with wildlife incident report = 1,
 available locations = 1 * rec_std: standardized estimate of recreation
 intensity * rsf_fix_std: predicted relative probability of mountain lion
 use based on fixed effects in top performing iSSA model * rsf_min_std:
 predicted relative probability of mountain lion use based on lowest
 observed levels of human tolerance. Derived from individual-level random
 effects extracted from top performing iSSA model.  *
 rsf_max_std: predicted relative probability of mountain lion use based on
 highest observed levels of human tolerance. Derived from individual-level
 random effects extracted from top performing iSSA model.  ## Code/software
 All models were run using R (version 3.6.0).  iSSA models were fit using
 the function 'fitTMB' in the *glmmTMB* R package. Generalized
 linear models were fit using the function 'glm' in the *stats* R
 package. ## Access information Data related to mountain lion attacks on
 people were derived from California Department of Fish and Wildlife: *
 [https://wildlife.ca.gov/Conservation/Mammals/Mountain-Lion/Attacks](https://wildlife.ca.gov/Conservation/Mammals/Mountain-Lion/Attacks) California statewide recreation intensity estimates were derived from Strava's global heatmap: * [https://www.strava.com/maps/global-heatmap](https://www.strava.com/maps/global-heatmap)