DOI: 10.5061/dryad.pc866t1rz
title: Intraguild interactions and abiotic conditions mediate occupancy of mammalian carnivores: co-occurrence of coyotes-fishers-martens

description: The widespread eradication of large carnivores and subsequent expansion of
 top mesopredators have the potential to impact species and community
 interactions with ecosystem-wide implications. An example of these trophic
 dynamics is the widespread establishment of coyotes following the
 extirpation of wolves and mountain lions in eastern North America. Here,
 we examined the occupancy of three carnivores in northern New York
 considering both environmental/habitat factors and interspecific
 interactions. We estimated the co-occurrence of coyotes, fishers, and
 martens from a landscape-scale winter camera trap survey repeatedly
 annually for three years. Martens occurred independently of both coyotes
 and fishers, while fishers and coyotes displayed positive intraguild
 interactions that were constant across the landscape. Both marten and
 fisher first-order occupancy was driven by a combination of biotic and
 abiotic factors, with both species displaying positive associations with
 forest cover but antithetical responses to average snow depth. The
 integral and antithetical role of snow depth in driving the occurrence of
 martens (positive) and fishers (negative) in the landscape indicates that
 future climatic warming could reduce the availability of current spatial
 refuges for martens created by severe winter conditions. Climate-driven
 alterations to established competitive interactions and co-existence
 patterns between marten and fishers have critical implications for the
 species' survival and conservation. We provide correlational evidence
 consistent with the potential for positive top-down effects of dominant
 mesocarnivores on subordinate species, with fisher occupancy increasing
 conditional on the presence of coyotes across the landscape. These
 findings align with the hypothesis that under certain conditions, coyotes
 may facilitate certain subordinate carnivores. The evidence produced here
 is consistent with hypotheses on the dynamic nature of trophic niches. We
 demonstrate the need to consider the interplay between climate, habitat,
 and interspecific interactions to understand wildlife occupancy patterns
 and inform wildlife management in a rapidly changing world.
description: We conducted camera trap surveys for carnivores from
 January-March 2016-2018 throughout the Adirondack and Tug Hill regions of
 northern New York State (Figure S1). The study area is an approximately
 32,000 km<sup>2</sup> region dominated by contiguous mature
 stands of deciduous, mixed, and coniferous forests along an elevational
 gradient ranging from 24 – 1448m. We used a stratified random sampling
 design to select 15-km<sup>2</sup> sample units and a
 standardized methodology across all surveys which included the same 195
 sample units in each of the three years (except for 13 sites that were not
 sampled in 2017). At each site, a camera trap was deployed randomly within
 the 15 km<sup>2</sup> grid.  Camera traps were secured to
 trees approximately 1.0-1.5 m above ground. A bait station was placed on a
 tree opposite the camera trap and secured to the tree using wire mesh. The
 bait used varied and included beaver (<em>Castor
 canadensis</em>), moose (<em>Alces alces</em>),
 white-tailed deer (<em>Odocoileus virginianus</em>), muskrat
 (<em>Ondatra zibethicus</em>), raccoon (<em>Procyon
 lotor</em>), beef (<em>Bos taurus</em>), and chicken
 (<em>Gallus domesticus</em>). At all sites, skunk-based call
 lures were applied. Cameras were deployed for 3 weeks (21 days) at each
 location after which cameras were retrieved. Cameras and bait were checked
 halfway through 3 weeks of sampling (generally day 10 or 11) with
 batteries and bait replaced and replenished as necessary. Detection
 records were created for each of the species sampled over the recording
 period. We used a weekly occasion length, with only one detection of each
 species being possible per weekly period to ensure independence of
 detections. 
description: # Intraguild interactions and abiotic conditions mediate occupancy of
 mammalian carnivores: co-occurrence of coyotes-fishers-martens
 [https://doi.org/10.5061/dryad.pc866t1rz](https://doi.org/10.5061/dryad.pc866t1rz) The data stems from a large-scale camera trapping project conducted for 3-weeks annually at approximately 195 sites over 3 years in the Adirondacks and Tug Hill region of New York State, USA. The target species were fisher, marten, and coyote. Camera traps were secured to trees approximately 1.0-1.5 m above ground. A bait station was placed on a tree opposite the camera trap and secured to the tree using wire mesh. The bait used varied and included beaver, moose, white-tailed deer, muskrat, raccoon, cow, and chicken. ## Description of the data and file structure ## The data folder This folder has ten files. **1. 7dayoccDetectionscoyoteNZ.csv** This file contains detection/non-detection data for coyotes between the years of 2016-2018 in New York state. 0 is not detected, and 1 is detected. Each row is a site, each column is a weekly occasion, and each cell is a detection/non-detection record. **2. 7dayoccDetectionsfisherNZ** This file contains detection/non-detection data for fishers between the years of 2016-2018 in New York state. 0 is not detected, and 1 is detected. Each row is a site, each column is a weekly occasion, and each cell is a detection/non-detection record. **3. 7dayoccDetectionsmartenNZ** This file contains detection/non-detection data for American marten between the years of 2016-2018 in New York state. 0 is not detected, and 1 is detected. Each row is a site, each column is a weekly occasion, and each cell is a detection/non-detection record. **4. NZ.3yrcamsite.6km.buffer.alllandscapecovariates.csv** This file contains all of the summarized spatial covariate data at a 6km scale used in the analysis. Each row is a different 6km 2 pixel in New York State, each column is a covariate, and each cell is a value. The acronyms used in this dataset are WSI = Winter Severity Index, ADK = Adirondacks, TH = Tug Hill, FID = Field ID, and NZ = Northern Zone). The landscape covariates used in the analysis are: | **Column name / covariate** | **Description** | **Source** | | :-------------------------- | :------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Deciduous | Proportion of a 6 km2 buffer around the detector made up of deciduous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Coniferous | Proportion of a 6 km2 buffer around the detector made up of coniferous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Mixed | Proportion of a 6 km2 buffer around the detector made up of mixed forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Pasture | Proportion of a 6 km2 buffer around the detector made up of pasture | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Cultivated.Crops | Proportion of a 6 km2 buffer around the detector made up of cultivated crops | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | RoadDen | Mean number of km of road per km2 in each 6 km2 buffer | calculated from primary and secondary roads raster provided by the NYSDEC, hosted on GitHub | | snowdepth | Mean daily snow depth(m) of the 6 km2 buffer around each detector across the sampling period | National Operational Hydrologic Remote Sensing Centre, 2004. Snow data assimilation system (SNODAS) products ([https://doi.org/10.7265/N5TB14TC](https://doi.org/10.7265/N5TB14TC)). | | forest.edge | Edge density of combined class of all forest in each 6 km2 buffer around detectors | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | min\_temp | The mean daily minimum temperature over the sampling period at each detector (degree C). | PRISM Climate data, Oregon State University ([http://prism.oregonstate.edu](http://prism.oregonstate.edu)).  | | GPP | The amount of carbon captured by plants (kg C MJ-1) in at the detectors | MODIS Land Satellite, 2017 ([https://lpdaac.usgs.gov/products/mod17a2hv006/](https://lpdaac.usgs.gov/products/mod17a2hv006/)) | **5. NZ.3yrcamsite.20km.buffer.alllandscapecovariates.csv** This file contains all of the summarized spatial covariate data at a 20km scale used in the analysis. Each row is a different 20km 2 pixel in New York State, each column is a covariate, and each cell is a value. The acronyms used in this dataset are WSI = Winter Severity Index, ADK = Adirondacks, TH = Tug Hill, FID = Field ID, and NZ = Northern Zone). The landscape covariates used in the analysis are: | **Column name / covariate** | **Description** | **Source** | | :-------------------------- | :-------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Deciduous | Proportion of a 20 km2 buffer around the detector made up of deciduous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Coniferous | Proportion of a 20 km2 buffer around the detector made up of coniferous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Mixed | Proportion of a 20 km2 buffer around the detector made up of mixed forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Pasture | Proportion of a 20 km2 buffer around the detector made up of pasture | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Cultivated.Crops | Proportion of a 20 km2 buffer around the detector made up of cultivated crops | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | RoadDen | Mean number of km of road per km2 in each 20 km2 buffer | calculated from primary and secondary roads raster provided by the NYSDEC, hosted on GitHub | | snowdepth | Mean daily snow depth(m) of the 20 km2 buffer around each detector across the sampling period | National Operational Hydrologic Remote Sensing Centre, 2004. Snow data assimilation system (SNODAS) products ([https://doi.org/10.7265/N5TB14TC](https://doi.org/10.7265/N5TB14TC)). | | forest.edge | Edge density of combined class of all forest in each 20 km2 buffer around detectors | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | min\_temp | The mean daily minimum temperature over the sampling period at each detector (degree C). | PRISM Climate data, Oregon State University ([http://prism.oregonstate.edu](http://prism.oregonstate.edu)).  | | GPP | The amount of carbon captured by plants (kg C MJ-1) in at the detectors | MODIS Land Satellite, 2017 ([https://lpdaac.usgs.gov/products/mod17a2hv006/](https://lpdaac.usgs.gov/products/mod17a2hv006/)) | **6. NZ.3yrcamsite.15km.buffer.alllandscapecovariates.csv** This file contains all of the summarized spatial covariate data at a 15km scale used in the analysis. Each row is a different 15km 2 pixel in New York State, each column is a covariate, and each cell is a value. The acronyms used in this dataset are WSI = Winter Severity Index, ADK = Adirondacks, TH = Tug Hill, FID = Field ID, and NZ = Northern Zone). The landscape covariates used in the analysis are: | **Column name / covariate** | **Description** | **Source** | | :-------------------------- | :-------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Deciduous | Proportion of a 15 km2 buffer around the detector made up of deciduous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Coniferous | Proportion of a 15 km2 buffer around the detector made up of coniferous forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Mixed | Proportion of a 15 km2 buffer around the detector made up of mixed forest | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Pasture | Proportion of a 15 km2 buffer around the detector made up of pasture | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | Cultivated.Crops | Proportion of a 15 km2 buffer around the detector made up of cultivated crops | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | RoadDen | Mean number of km of road per km2 in each 15 km2 buffer | calculated from primary and secondary roads raster provided by the NYSDEC, hosted on the github | | snowdepth | Mean daily snow depth(m) of the 15 km2 buffer around each detector across the sampling period | National Operational Hydrologic Remote Sensing Centre, 2004. Snow data assimilation system (SNODAS) products ([https://doi.org/10.7265/N5TB14TC](https://doi.org/10.7265/N5TB14TC)). | | forest.edge | Edge density of combined class of all forest in each 15 km2 buffer around detectors | NLCD, 2019 ([https://www.mrlc.gov/data/nlcd-2019-land-cover-conus](https://www.mrlc.gov/data/nlcd-2019-land-cover-conus)) | | min\_temp | The mean daily minimum temperature over the sampling period at each detector (degree C). | PRISM Climate data, Oregon State University ([http://prism.oregonstate.edu](http://prism.oregonstate.edu)).  | | GPP | The amount of carbon captured by plants (kg C MJ-1) in at the detectors | MODIS Land Satellite, 2017 ([https://lpdaac.usgs.gov/products/mod17a2hv006/](https://lpdaac.usgs.gov/products/mod17a2hv006/)) | **7. NZ7daycameras.csv** This file contains observation-level covariate data detailing the camera used on each date. Each row is a different site in New York State, each column is an occasion, and each cell is a value. The acronyms used in this dataset are ADK = Adirondacks, TH = Tug Hill, and NZ = Northern Zone). **8. NZ7dayoccbait.csv** This file contains observation-level covariate data detailing the bait used on each date. Each row is a different site in New York State, each column is an occasion, and each cell is a value. The acronyms used in this dataset are ADK = Adirondacks, TH = Tug Hill, and NZ = Northern Zone). **9. NZAvgTempByOcc.csv** This file contains observation-level covariate data detailing the mean temperature on each occasion at each site. Each row is a different site in New York State, each column is an occasion, and each cell is a value. The temperatures are in degrees C. The acronyms used in this dataset are ADK = Adirondacks, TH = Tug Hill, Occ = Occasion, and NZ = Northern Zone). **10. NZAvgTempByOcc.csv** This file contains observation-level covariate data detailing the ordinal date on the first day of each occasion at each site. Each row is a different site in New York State, each column is an occasion, and each cell is a value. The acronyms used in this dataset are ADK = Adirondacks, TH = Tug Hill, Occ = Occasion, and NZ = Northern Zone). ## Description of software and packages required All analysis was conducted in R, and code to fully reproduce the analysis is provided. The packages required to run this analysis in R include 'unmarked', 'aiCcmodavg', and 'MuMIn'.