DOI: 10.5061/dryad.8pk0p2npj
title: Detections of feral cats on Matuwa between 2018 and 2021

description: Feral cats are difficult to manage and harder to monitor. We analysed the
 cost and the efficacy of monitoring the pre- and post-bait abundance of
 feral cats via camera-traps or track counts using four years of data from
 the Matuwa Indigenous Protected Area. Additionally, we report on the
 recovery of the feral cat population and the efficacy of subsequent
 Eradicat® aerial baiting programs following 12 months of intensive feral
 cat control in 2019. Significantly fewer cats were captured in 2020 (n =
 8) compared to 2019 (n = 126). Pre-baiting surveys for 2020 and 2021
 suggested that the population of feral cats on Matuwa was very low, at 5.5
 and 4.4 cats/100 km, respectively, which is well below our target
 threshold of 10 cats/100 km. Post-baiting surveys then recorded 3.6 and
 3.0 cats/100 km, respectively, which still equates to a 35% and 32%
 reduction in cat activity. Track counts recorded significantly more feral
 cats than camera traps, and were cheaper to implement. We recommend that
 at least two methods of monitoring cats be implemented to prevent
 erroneous conclusions.
description: Two camera-trap arrays of 120 cameras and 130 cameras
 respectively were used to monitor feral cat activity on Matuwa pre- and
 post-management between 2018 and 2021. We also used track counts which
 collect data that reflects that activity of feral cats on unsealed roads
 and is referred to as the track activity index (TAI). Approximately two
 weeks pre- and post-baiting, two teams of experienced observers ran a
 single TAI transect at least 50 km in length each day for four consecutive
 days. Count data from camera-traps and TAI data were analysed via negative
 binomial mixed-effects models with a parameter for zero-inflation in the R
 (V4.0.2) package glmmTMB, with monitoring method (dispersed camera-traps,
 grid camera-traps, or track count), survey (pre- or post-management and
 post-trapping), and year as factorial fixed effects, while year and
 TAI-transect name or camera ID were used as random effects. The proportion
 of camera-traps or TAI-transects that recorded zero cats was considerable
 with 65% of TAI transects, 99% of cameras spread across the landscape, and
 99.8% of cameras in the grid recording zero cats.
description: The coordinates of the camera locations have not been included.
 Prior to re-use of this data please contact the authors or Tarlka Matuwa
 Piarku Aboriginal Corporation as this data is from an Indigenous Protected
 Area. We express gratitude to all the people who
 contributed to the management of Matuwa: Tarlka Matuwa Piarku Aboriginal
 Corporation, the Matuwa and Kurrara Kurrara Rangers, the Matuwa Homestead
 Caretakers, the DBCA Goldfields Regional Staff, and numerous
 volunteers.
description: # Detections of feral cats on Matuwa between 2018 and 2021 Dataset DOI:
 [10.5061/dryad.8pk0p2npj](10.5061/dryad.8pk0p2npj) ## Description of the
 data and file structure The purpose of this data was to measure the cost
 and the efficacy of monitoring the pre- and post-bait abundance of feral
 cats via camera-traps or track counts. *Camera-Trap Monitoring* Two
 camera-trap arrays were used to monitor feral cat activity on Matuwa pre-
 and post-baiting. In 2018–2020, 120 camera-traps (Reconyx Hyperfire PC900
 Professional camera; Reconyx, WI, U.S.A.) were installed using a
 stratified-random design based on the 20 most common geological types in
 the Wiluna region. The cameras were placed between 30 m and 200 m away
 from an ungazetted track. Camera-traps were, on average, 2.80 km from
 their nearest neighbour (min = 1.0 km, max = 5.9 km). Data from 70 of
 these cameras that were placed in an aerial baited site in 2018 and 2019
 were used in subsequent analysis. In 2020 and 2021, the entirety of Matuwa
 was aerial baited, and data from all 120 cameras were used. In 2020–2021,
 a grid of 130 camera-traps with cameras spaced 1 km apart was installed on
 Bullimore sandplain in the south of Matuwa. All cameras were mounted on a
 30 cm high plastic sand peg, in a horizontal position, facing south, in a
 space with at least 3 m of open ground in front of the camera. Two
 olfactory lures (Canines-a-plenty and Catastrophic from Outfoxed Pest
 Control, Victoria, Australia) were placed on two natural sticks
 approximately 30 cm tall and 1 m apart, 3 m from the front of the camera,
 and refreshed at least 10 days before and after management. Herbaceous
 vegetation immediately in front of the camera was removed. Camera-traps
 captured three photos per trigger, with no quiet period. Timed photos were
 taken at 23:00 h to monitor the operation of the camera.   We used data
 from the first 10 days after camera-traps and lures were set, pre- and
 post-baiting. Photos were stored in the Colorado Parks and Wildlife Photo
 Warehouse database (CPW) and viewed by at least two observers to confirm
 species identification. A histogram of time intervals between consecutive
 photos revealed that 99.6% of photos were captured either &lt;5 min apart
 or &gt;60 min apart. To minimise temporal autocorrelation, we grouped
 consecutive photos that were &lt;5 min apart to create independent records
 for subsequent analysis.  *Track Counts* Track counts collect data that
 reflects the activity of feral cats on unsealed roads, referred to as the
 track activity index (TAI). Approximately two weeks pre- and post-baiting,
 two teams of experienced observers ran a single TAI transect at least 50
 km in length each day for four consecutive days. Teams alternated
 transects each day to reduce observer bias. TAI-transects occur on sandy
 4WD tracks, which are initially cleared by towing a heavy iron drag behind
 a 4WD vehicle. Observers, driving all-terrain vehicles (ATVs) at a speed
 of 10–15 km/h, then inspect the transect for cat tracks, and clear new
 signs of animal activity by towing a chain iron drag. Cat tracks that
 occur within 1 km radius of one another on a daily survey are aggregated
 into one cat detection to minimise spatial autocorrelation. A histogram of
 distances between consecutive cat tracks revealed that 92.3% of tracks
 were &lt;1 km apart and usually caused by cats that travelled along roads,
 leaving a continuous set of prints. The single 50 km transect is split at
 disused wells and intersections, with any observations recorded within 1
 km of the well or intersection being discarded. The number of cats
 observed on each TAI-transect is scaled against the total length of the
 TAI-transect within each day and then averaged across sequential survey
 days.  ### Files and variables #### File: Camera_vs_TAI_2018-2021.xlsx
 **Description:** Data analysed to compare the cost and efficacy of
 monitoring feral cats via camera traps or the track activity index. #####
 Variables * method: Fine scale method differentiating camera layout
 patterns, categorical * Method: Coarse scale method listing only cameras
 vs TAI, categorical * survey: survey period defined as pre-bait or
 post-bait period, categorical * Survey: Label for graphing variables,
 categorical * Year: Year, integer * Treatment: Method used to apply
 management technique, aerial baiting or ground based baiting, categorical
 * Day: Number of days since beginning of the survey period, integer *
 LocationName: Name of transect or camera site, categorical * Landsystem:
 Rangeland landsystem types used to describe a distinct combination of
 geology, drainage, elevation, slope, and vegetation, categorical *
 LS_COMBO: Similar landsystem types were combined to reduce diversity in
 the covariate, categorical * Geology: Geology present at a given camera
 site as per Geological survey of Western Australia, categorical *
 DistanceBoundary: Distance between a camera trap and the boundary of the
 proprty in meters * DistanceTrack: Distance between a camera trap and the
 nearest unsealed track in meters * Scaled_cat_detections: Number of cats
 detected using track activity index on a given transect if scaled to 100km
 transect * Integer: Integer of the number of cats detected using track
 activity index on a given transect if scaled to 100km transect