Data from: Fox control and fire influence the occurrence of invasive predators and threatened native prey
Data files
Nov 01, 2023 version files 990.75 KB
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gams.R
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plot_gams.R
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raw_data_gams_pa.csv
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README.md
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sw-vic-occurrence-phd.Rproj
Abstract
It can be challenging to distinguish management impacts from other population drivers, including 'natural' processes and co-occurring threats. However, disentangling processes is important, particularly when management may have unintended consequences, such as mesopredator release. We explored the effects of long-term, broadscale poison-baiting programs on the distribution of red foxes Vulpes vulpes (targeted invasive predator), feral cats Felis catus (unmanaged invasive competitor) and two of their threatened native prey in two fire-affected regions of south-eastern Australia. We synthesised data from 3,667 camera-trap deployments at 1,232 sites (172,052 trap-nights), combining experimental manipulation of foxes and fire with space-for-time approaches. Fox control effectiveness––in terms of decreased probability of fox occurrence and increased probability of prey occurrence––depended on the duration and intensity of the poison-baiting program. The effects of fox control on prey occurrence also varied between the two native prey species: fox control was strongly beneficial to the long-nosed potoroo Potorous tridactylus but had no measurable effect on southern brown bandicoot Isoodon obesulus occurrence. Feral cat occupancy tended to be higher in landscapes with long-term fox control, although we found no effect of fox-bait density on fine-scale cat occurrence. Time since fire (0–80 years) was associated with the occurrence of each study species, but its association with invasive predators also differed among vegetation types. Invasive predators and altered fire regimes are key, often overlapping, biodiversity threats. Our work highlights the importance of fine-scale monitoring and consideration of multiple drivers in distribution models to develop effective, tailored conservation strategies.
README: Data from: Fox control and fire influence the occurrence of invasive predators and threatened native prey
https://doi.org/10.5061/dryad.msbcc2g4p
This repository contains data and code to reproduce GAM results from the Biological Invasions manuscript 'Fox control and fire influence the occurrence of invasive predators and threatened native prey'. Additional code and data can be found on GitHub (https://github.com/matt-w-rees/sw-vic-occurrence-phd). Here we provide an R-project file ('sw-vic-occurrence-phd.Rproj'), as well as a raw data csv file ('raw_data_gams_pa.csv'), and two R scripts: one to fit the models ('gams.R') and another to plot the results ('plot_gams.R').
The following variables are contained in the columns of the raw data file ('raw_data_gams_pa.csv'):
# region - Glenelg or Otway Ranges
# block - forest block. Glenelg = distinct forests\, Otways = focal areas (Otway Ark data) + north / south (matts cat grids / zoi's surveys)
# data_source - dataset owner: Matt Rees (phd surveys)\, Glenelg Ark camera-trap dataset 2013-19\, Otway Ark dataset 2016-18
# station - unique ID for camera-trap site
# longitude - coordiantes for location of cam-trap site
# latitude - coordiantes for location of cam-trap site
# year - year of survey
# station_year - unique deployment: camera trap site x year
# date_start - start date of cam-trap survey (yyyy-mm-dd)
# date_end - end date of camera-trap survey (yyyy-mm-dd)
# survey_duration - total survey duration (days)
# fox - red fox: detected at least once (1) or not (0)
# cat - feral cat: detected at least once (1) or not (0)
# bandicoot_sb - bandicoot southern brown: detected at least once (1) or not (0)
# potoroo_ln - long-nosed potoroo: detected at least once (1) or not (0)
# XGROUPNAME - vegetation type: Ecological Vegetation Class group (DEWLP)
# EFG_NAME - vegetation type: Ecological Fire Group (https://www.ffm.vic.gov.au/__data/assets/pdf_file/0008/21113/Report-84-REDUCED-SIZE-Growth-Stages-and-Tolerable-Fire-Intervals-For-Victorias-Native-Vegetation-Data-Se.pdf)
# treatment - non-treatment / treatment (control / impact) sites in regards to fox control (i.e.\, blocks without fox control but were eventually subject to fox-baiting considered 'treatment')
# foxbaits - number of 1080 fox-off poison-baits within a 2.3 km radius around each cam-trap (average fox dmax in Hradsky et al 2017 Sci Reports)
# elevation - metres above sea level based of Vicmap digital elevation model layer: 10m resolution (https://www.land.vic.gov.au/maps-and-spatial/spatial-data/vicmap-catalogue/vicmap-elevation)
# ruggedness - topographic ruggedness index made using QGIS plugin based off above^ elevation layer: median value within 30 m radius of cam-trap
# wetness - topographic wetness index: median value within 30 m radius of cam-trap (https://data.gov.au/dataset/ds-dap-csiro%3A5588/details?q=)
# rain_diff_percent_06months - deviation in rainfall (%) from the long-term average (closest weather station) in the last 6 months (from start of survey duration)
# rain_diff_percent_12months - deviation in rainfall (%) from the long-term average (closest weather station) in the last 12 months (from start of survey duration)
# rain_diff_percent_18months - deviation in rainfall (%) from the long-term average (closest weather station) in the last 18 months (from start of survey duration)
# rain_diff_percent_24months - deviation in rainfall (%) from the long-term average (closest weather station) in the last 24 months (from start of survey duration)
# tsf - time since last fire (year)
# n_fires - number of fires since 1939 bushfires
# dist_nnv - distance to nearest area of non-native vegatation (greater than 30 ha): derived from inverted extent of DELWP native vegetation extent layer
Methods
We compiled data from multiple smaller-scale camera-trap studies, each designed to experimentally assess mammal responses to fox control. Overall, we collated 5,449 and 2,202 independent detections of foxes and cats, respectively (separated by at least 30 minutes) from 172,052 camera-trap nights. We collated camera-trap data across two regions in south-west Victoria, Australia: the Glenelg region and Otway Ranges. In broad sections of each region, government land managers conduct ongoing targeted lethal fox control for biodiversity conservation. All camera-trap deployments consisted of a Reconyx (Holmen, Wisconsin) brand camera-trap (white or infrared flash), attached to a tree or a metal picket, facing a lure. Analyses were conducted in R version 4.1.3. We modelled species occupancy probabilities using occupancy-detection and generalised additive models.