DOI: 10.5061/dryad.z08kprrkr
title: Livestock guardian dogs establish a landscape of fear for wild predators: implications for the role of guardian dogs in reducing human-wildlife conflict and supporting biodiversity conservation

description: Livestock guardian dogs (LGDs) are increasingly used to protect livestock
 from predators, but their effects on the distribution and behaviour of
 wild predators are mostly unknown. A key question is whether LGDs exclude
 predators from grazing land, or if predators continue to use areas with
 LGDs but modify their behaviour in ways that reduce impacts on livestock.
 We studied effects of LGDs (Maremma sheepdogs) on distribution and
 behaviour of red foxes Vulpes vulpes in north-eastern Victoria, Australia.
 We mapped the activity of LGDs across the study areas using GPS tracking
 and measured fox activity using remote cameras. We also measured
 risk-sensitive foraging in foxes to test if they reduced feeding time at
 sites regularly used by LGDs. Foxes occurred throughout areas occupied by
 LGDs, but their probability of detection was negatively related to
 probability of LGD presence. Foxes extracted fewer food items from
 experimental food stations in proportion to the intensity of local
 activity of LGDs. This indicates that though foxes overlapped with LGDs,
 they responded to risk of encountering LGDs by allocating less time to
 foraging.  While LGDs do not necessarily exclude wild predators
 from areas used for livestock production, they can have strong effects on
 predator behaviour. Reduction in time allocated to foraging in areas
 regularly used by LGDs could lead to suppression of hunting behaviour and
 therefore a reduction in attacks on livestock. The flexible response of
 predators to LGDs should facilitate coexistence of wild predators with
 livestock farming, by allowing predators to continue to use areas occupied
 by livestock while still preventing attacks on those livestock. Our
 results therefore strengthen the case for use of LGDs in the conservation
 of predators threatened by conflict with farming. Suppression of hunting
 behaviour should also mean that prey species experience reduced rates of
 predation on farmland with LGDs. This effect could be valuable for
 conservation of threatened species of prey.
description: For detailed description of the methods, please see our paper:
 'Livestock guardian dogs establish a landscape of fear for wild
 predators: implications for the role of guardian dogs in reducing
 human-wildlife conflict and suppporting biodiversity conservation',
 published in Ecological Solutions and Evidence.  Data
 was collected on four properties in north-east Victoria, Australia; two
 were used as experimental sites (Heatherlie and Riversdale) and two were
 used as controls (Mullenmeah and Wagonbark). The experimental sites ran
 Maremma sheepdogs, guarding sheep, and the control sites ran livestock
 without livestock guardian dogs. Each experimental site was paired with
 its own control site (Riversdale and Wagonbark, 10 km apart; Heatherlie
 and Mullameah, 45 km apart) due to the fox surveys and experiments taking
 place in different seasons for each pair of properties; fox activity and
 behaviour is seasonally highly variable. GPS tracking
 collars of two types (Lotek, Havelock North, New Zealand; and Telemetry
 Solutions, Concord, USA) were fitted on all LGDs between July 2017 and
 March 2018, the two types being interspersed across properties. One collar
 failed at Heatherlie and could not be replaced due to the dog’s shyness.
 Collars took a location every 30 minutes and were fitted a minimum of four
 weeks before collection of data on foxes. Only locations with a HDOP
 (horizontal dilution of precision) &lt;10 (Lotek collars) or &lt;4
 (Telemetry Solution collars) were retained for analysis. HDOP values were
 chosen as those that offered the best balance between filtering out
 inaccurate locations and data retention, based on a pilot study of
 stationary GPS collars. A mean (± SE) of 3.0% ± 0.4%
 locations was deleted from the datasets collected by the Lotek collars,
 resulting in a mean (± SE) HDOP of 2.0 ± 0.05 of the retained sample of
 locations. A mean (± SE) of 2.4%± 0.8% was deleted from the datasets
 collected by the Telemetry Solution collars, resulting in a mean (± SE)
 HDOP of 1.2 ± 0.09 in the retained sample.  Forty-eight
 Reconyx PC800 HyperFire Professional IR cameras (Reconyx, Holmen, WI, USA)
 were distributed over each pair of trial and control properties for a
 6-week survey (2,016 trap nights). Cameras were set to take three images
 in rapid succession when triggered, with a minimum one-minute delay
 between consecutive triggers to reduce repeat triggers by the same
 individual. On Riversdale and Wagonbark, this survey ran in August and
 September 2017; on Heatherlie and Mullameah it ran in December 2017 and
 January 2018. Half of the 48 cameras were allocated to the control site
 and were evenly distributed over the chosen area in a grid pattern. The
 remaining 24 cameras were distributed over each trial site, according to
 the intensity of use of different areas by the Maremmas (see
 below).  A minimum of four weeks of data from the GPS
 tracking collars were used to calculate a fixed kernel home range (Worton
 1989) for each dog group by pooling the locations of all members. We used
 an <em>ad hoc</em> smoothing parameter designed to prevent
 under- or over-smoothing, which involved choosing the smallest increment
 of the reference bandwidth (Href) that resulted in a 95% home-range
 polygon that was as contiguous as possible (Jacques<em> et
 al.</em> 2009; Kie<em> et al.</em> 2010). The package
 ‘adehabitat HR’ (version 0.4.19) in R statistical software (Calenge 2006;
 R Core Team 2013) was used for all home range calculations. The 10%, 50%,
 90%, 95% and 99% isopleths were extracted from this home range
 calculation, and the area covered by each incremental isopleth was
 determined. The 24 cameras were distributed in order to equalise camera
 density for each incremental area, with a higher density in the 10% and
 50% isopleth areas to maintain a minimum of two cameras per isopleth
 zone. Experimental fox feeding trials exploited the
 propensity of foxes to dig for food items and were designed to yield a
 measurement equivalent to a giving-up density (GUD). At each site we dug a
 30-cm deep hole approximately 2 m in front of the camera and filled it in
 while placing a chicken neck at each 5-cm depth interval, the top chicken
 neck being buried just below the surface. Chicken necks were chosen based
 on a pilot study that showed they are favoured by wild foxes. The cameras
 monitoring the foraging behaviour of foxes at trial sites were set to take
 three images in rapid succession at each trigger, with no delay between
 consecutive triggers. When analysing the data in the
 paper, two measures of Maremma presence were calculated for each camera
 site. The first was the probability of Maremma occurrence based on home
 range calculations. We obtained this probability from a long-term
 (eight-month) home range calculation of each dog group on each property
 using the Brownian bridge approach of the kernel method (Bullard 1991;
 Horne<em> et al.</em> 2007). Locations at the control sites
 were allocated a value of zero. To enable statistical analysis with these
 values, they were transformed with the following formula:
 (log10(<em>probability value</em>+1))*10000. The second
 measure was the number of days on which Maremmas were detected at each
 camera site during the survey. As Maremmas were rarely detected on camera
 (N=9), we identified all instances in which a GPS collar from a Maremma
 logged a location within 30 m of a camera, and added these to the camera
 detection data (N=76) to calculate ‘days of Maremma detection’. This
 measure proved to have a greater effect in all models used in our analysis
 than ‘probability of Maremma occurrence’, so only ‘days of Maremma
 detection’ was used as an indicator of Maremma presence. At Mullameah, all
 camera locations that fell within 300 m of their wild dog exclusion fence
 were excluded from analysis because of poison baiting along the fence just
 prior to the research. At Riversdale and Heatherlie all camera locations
 beyond the 95% isopleth were excluded due to continuing lethal fox control
 on the edge and outside the experimental properties.
 The uploaded data includes: For
 each trial/control site combination; the results from the wildlife survey,
 the two measures of Maremma presence at each camera site (as above) and
 the covariates for each camera site used in the analysis in the
 paper For each trial/control site combination; the
 results from the fox feeding trial, with the covariates for each camera
 site as used in the analysis in the paper. 
description: # Livestock guardian dogs establish a landscape of fear for wild
 predators: implications for the role of guardian dogs in reducing
 human-wildlife conflict and supporting biodiversity conservation
 The data contains four
 excel files. Two files contain the results of a 6-week wildlife survey on
 each of two trial/control site pairs (Riversdale/Wagonbark and
 Heatherlie/Mullenmeah). The wildlife survey results are a record of which
 species was recorded, with an associated date, time, the camera location
 it was recorded at, the camera number, the property and whether this was
 an experimental or control site. These files also contain a separate
 worksheet with the Maremma detections, as measured by their GPS tracking
 collars, that fall within 30m of the camera sites during the survey
 period. Last, they contain a third worksheet with the covariates for each
 camera site, as used in the analysis in the paper. This includes the
 isopleth that the camera site falls into, as calculated from the long term
 Maremma home range (see paper), the two measures of Maremma presence (see
 paper for details) and the distance from the nearest cover for each camera
 site. The other two files contain the results of the experimental fox
 feeding trial from the paper, for each trial/control site pair. This
 includes the basic information for each entry about which property, which
 camera site and time of the year the entry is for, in addition to whether
 or not a fox was detected and the number of food items it took, and
 whether another species had already dug at the site before a fox turned
 up. It also includes the covariates for each camera site, similar as
 above, with one additional covariate which is the livestock type that is
 present in the paddock where the camera site is located. These were the
 data that were used for the analysis as described in the paper. ##
 Description of the data and file structure Most of the data should be
 self-explanatory with the description above, and reading the paper. In the
 files for Riversdale and Heatherlie containing the results from the
 experimental fox feeding trial, the column 'no. lures taken by a
 fox' contains 'NA' in the cases where a fox was never
 detected during the time of the trial, and could therefore not have taken
 any lures. It also contains 'NA' in the cases where another
 animal has dug at the site before a fox appeared. When another animal had
 dug at the site earlier, that site had to be excluded from analysis to
 avoid confounding results. In those same files, the column 'days of
 Maremma detection' contain no data for a number of the entries. Days
 of Maremma detection was only calculated for those entries that could be
 used in the analysis (as per the paper); it was only included for those
 sites where a fox had been detected, that had not been dug up by another
 animal prior to a fox appearing, that fell within the 95% isopleth area of
 Maremma use and, for Mullameah, that did not fall within 300m of the wild
 dog exclusion fence. ## Sharing/Access information NA, data only available
 through Dryad or by contacting the corresponding author on the paper. ##
 Code/Software Only standard packages were used to analyse data in R, and
 the software 'Presence', which is all freely available online.