DOI: 10.5061/dryad.5c793
title: Data from: Hunting-mediated predator facilitation and superadditive mortality in a European ungulate

description: Predator-prey theory predicts that in the presence of multiple types of
 predators using a common prey, predator facilitation may result as a
 consequence of contrasting prey defense mechanisms, where reducing the
 risk from one predator increases the risk from the other. While predator
 facilitation is well established in natural predator-prey systems, little
 attention has been paid to situations where human hunters compete with
 natural predators for the same prey. Here, we investigate hunting-mediated
 predator facilitation in a hunter-predator-prey system. We found that
 hunter avoidance by roe deer (Capreolus capreolus) exposed them to
 increase predation risk by Eurasian lynx (Lynx lynx). Lynx responded by
 increasing their activity and predation on deer, providing evidence that
 superadditive hunting mortality may be occurring through predator
 facilitation. Our results reveal a new pathway through which human
 hunters, in their role as top predators, may affect species interactions
 at lower trophic levels and thus drive ecosystem processes.
description: deer_allDataThis table contains the roe deer steps associated with habitat variables and temporal variables that were used to build the step selection function (SSF) named the all data model in Gehr et al. 2017 (Ecology and Evolution). The table is divided into used (actual) lynx steps and random steps in a ratio of 1:10 (column "use"). The random steps match to their corresponding location id in the used steps (column “loc_id”). Swisstopo in the column headers refers to the source of the environmental variables. Cover swisstopo is a dummy variable for open/cover. Edge_dist_swisstopo refers to the distance to the closest forest edge. Slope_sq and altitude_sq are the squared slope and altitude variables. Aspect_swisstopoS is the southern exposition. Dist2 refers to the step length. Pred_risk_search refers to the chronic predation risk which was derived from a lynx habitat model for active/searching lynx. The 6 temporal variables are time harmonics of a Fourier transform for time of day (tsin, tcos; period of 24) and day of year (ytsin, ytcos, ytsin2, ytcos2; period of 365). All habitat variables were measured at the end of a step. All continuous variables in this table are mean centered and standardized to a SD=1. For information on the raw data or for R-code used to run the models please contact the data owner.deer_nohuntingThis table contains the roe deer steps associated with habitat variables and temporal variables that were used to build the step selection function (SSF) named the no hunting model in Gehr et al. 2017 – Ecology and Evolution. This table differs from the all data table in that all locations during the 10 week hunting season were removed. The table is divided into used (actual) lynx steps and random steps in a ratio of 1:10 (column "use"). The random steps match to their corresponding location id in the used steps (column “loc_id”). Swisstopo in the column headers refers to the source of the environmental variables. Cover swisstopo is a dummy variable for open/cover. Edge_dist_swisstopo refers to the distance to the closest forest edge. Slope_sq and altitude_sq are the squared slope and altitude variables. Aspect_swisstopoS is the southern exposition. Dist2 refers to the step length. Pred_risk_search refers to the chronic predation risk which was derived from a lynx habitat model for active/searching lynx. The 6 temporal variables are time harmonics of a Fourier transform for time of day (tsin, tcos; period of 24) and day of year (ytsin, ytcos, ytsin2, ytcos2; period of 365). All habitat variables were measured at the end of a step. All continuous variables in this table are mean centered and standardized to a SD=1. For information on the raw data or for R-code used to run the models please contact the data owner.lynx_allDataThis table contains the GPS locations of lynx associated with habitat variables and temporal variables that were used to build a logistic regression modelling the proportion of time lynx spend active. The data in this table refers to the all data model in Gehr et al. 2017 (Ecology and Evolution). The data was restricted to locations between the beginning of astronomical twilight in the morning (sun angle &lt; 18 degrees below the horizon) and the end of astronomical twilight in the evening (sun angle &gt; 18 degrees below the horizon). Hence, to repeat the model in Gehr et al. 2017 (Ecology and Evolution) the data with sun angle &lt;= -18 degrees have to be removed. For the model used to create Figure S4 in the Appendix S1 the complementary dataset has to be used. The table is divided into locations assigned to an active or inactive behavioral state (column “active” is a dummy variable - 1=active/0=inactive). Swisstopo in the column headers refers to the source of the environmental variables. Cover swisstopo is a dummy variable for open/cover. Edge_dist_swisstopo refers to the distance to the closest forest edge. Slope_sq and altitude_sq are the squared slope and altitude variables. Aspect_swisstopoS is the southern exposition. Cover_edge refers to an interaction term between cover_swisstopo and edge_dist_swisstopo. House_road_dist_small refers to an interaction between house_density and road_dist_small. The 6 temporal variables are time harmonics of a Fourier transform for time of day (tsin, tcos; period of 24) and day of year (ytsin, ytcos, ytsin2, ytcos2; period of 365). All habitat variables were measured at the end of a step. All continuous variables in this table are mean centered and standardized to a SD=1. For information on the raw data or for R-code used to run the models please contact the data owner.lynx_nohuntingThis table contains the GPS locations of lynx associated with habitat variables and temporal variables that were used to build a logistic regression modelling the proportion of time lynx spend active. The data in this table refers to the no hunting model in Gehr et al. 2017 (Ecology and Evolution). This table differs from the all data table in that all locations during the 10 week hunting season were removed. The data was restricted to locations between the beginning of astronomical twilight in the morning (sun angle &lt; 18 degrees below the horizon) and the end of astronomical twilight in the evening (sun angle &gt; 18 degrees below the horizon). Hence, to repeat the model in Gehr et al. 2017 (Ecology and Evolution) the data with sun angle &lt;= -18 degrees have to be removed. For the model used to create Figure S4 in the Appendix S1 the complementary dataset has to be used. The table is divided into locations assigned to an active or inactive behavioral state (column “active” is a dummy variable - 1=active/0=inactive). Swisstopo in the column headers refers to the source of the environmental variables. Cover swisstopo is a dummy variable for open/cover. Edge_dist_swisstopo refers to the distance to the closest forest edge. Slope_sq and altitude_sq are the squared slope and altitude variables. Aspect_swisstopoS is the southern exposition. Cover_edge refers to an interaction term between cover_swisstopo and edge_dist_swisstopo. House_road_dist_small refers to an interaction between house_density and road_dist_small. The 6 temporal variables are time harmonics of a Fourier transform for time of day (tsin, tcos; period of 24) and day of year (ytsin, ytcos, ytsin2, ytcos2; period of 365). All habitat variables were measured at the end of a step. All continuous variables in this table are mean centered and standardized to a SD=1. For information on the raw data or for R-code used to run the models please contact the data owner.mortality_systematicSearchThis table contains the deer mortality data used to build the general additive models (GAM) for the systematic search data in Gehr et al. 2017 (Ecology and Evolution) showing hunting induced predator facilitation in lynx. Column “count” refers to the number of kills found per Julian day (column “Julian”) during systematic cluster searches between 2011-2015. The column “rm” refers to the moving average (rolling mean) of counts over a window size of 31 days (i.e. one month). The column “n_lynx” refers to the number of lynx monitored for the systematic cluster searches per month. The column “rm_weighted” refers to the ratio between rm and n_lynx and was used to correct for temporal variation in lynx prey remain monitoring, and hence for the variation in detection probability. For the all data model all data was used whereas for the no hunting model the data for the hunting season was excluded (Julian days 244-319).mortality_publicReporting_lynxThis table contains the deer mortality data used to build the general additive models (GAM) for the public reporting data in Gehr et al. 2017 (Ecology and Evolution) showing hunting induced predator facilitation in lynx. Column “count” refers to the number of kills reported per Julian day (column “Julian”) for the years 1990-2010. The column “rm” refers to the moving average (rolling mean) of counts over a window size of 31 days (i.e. one month). The column “ratio_raw” refers to the ratio between the moving average of reported lynx kills (“rm” in this table) and the moving average of reported natural mortalities (“rm” in the table “mortality_publicReporting_natural.txt”) used to account for reporting bias in the public reporting dataset. For the all data model all data was used whereas for the no hunting model the data for the hunting season was excluded (Julian days 244-319).mortality_publicReporting_naturalThis table contains the natural mortality data for deer used to correct for reporting bias in the number of reported lynx kills in the public reporting data in Gehr et al. 2017 (Ecology and Evolution; see “mortality_publicReporting_lynx.txt”). Column “count” refers to the number of kills reported per Julian day (column “Julian”) for the years 1990-2010. The column “rm” refers to the moving average (rolling mean) of counts of reported natural mortalities over a window size of 31 days (i.e. one month). The column “rm” was used to calculate the ratio between the moving average of reported lynx kills (“rm” in the table “mortality_publicReporting_lynx.txt”) and the moving average of reported natural mortalities (“ratio_raw” in the table “mortality_publicReporting_lynx.txt”) used to account for reporting bias in the public reporting dataset.