Resource selection by New York City deer reveals the effective interface between wildlife, zoonotic hazards, and humans
Data files
Sep 27, 2023 version files 89.54 MB
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All_M1_FineScale.csv
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allcoef_boots_females.csv
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allcoef_boots_males.csv
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AllDeer_MultiScale_RSS.rds
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females_breed2019.rds
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females_breed2020.rds
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females_postbreed2020.rds
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females_postbreed2021.rds
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females_prebreed2020.rds
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LCarea_in_HR.csv
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males_breed2016.rds
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males_breed2017.rds
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males_breed2018.rds
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males_breed2019.rds
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males_postbreed2017.rds
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males_postbreed2018.rds
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males_postbreed2019.rds
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males_postbreed2020.rds
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males_prebreed2018.rds
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males_prebreed2019.rds
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males_prebreed2020.rds
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README.md
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VanAcker_et_al_2023_DeerMovementAnalysis.R
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VanAcker_SI_NY_USA.qml
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VanAcker_SI_NY_USA.tfw
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VanAcker_SI_NY_USA.tif
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VanAcker_SI_NY_USA.tif.aux.xml
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VanAcker_SI_NY_USA.tif.vat.cpg
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VanAcker_SI_NY_USA.tif.vat.dbf
Abstract
Although the role of host movement in shaping infectious disease dynamics is widely acknowledged, methodological separation between animal movement and disease ecology has prevented researchers from leveraging empirical insights from movement data to advance landscape scale understanding of infectious disease risk. To address this knowledge gap, we examine how movement behavior and resource utilization by white-tailed deer (Odocoileus virginianus) determines blacklegged tick (Ixodes scapularis) distribution, which depend on deer for dispersal in a highly fragmented New York City borough. Multi-scale hierarchical resource selection analysis and movement modeling provide insight into how deer’s movements contribute to the risk landscape for human exposure to the Lyme disease vector–I. scapularis. We find deer select highly vegetated and accessible residential properties which support blacklegged tick survival. We conclude the distribution of tick-borne disease risk results from individual resource selection by deer across spatial scales in response to habitat fragmentation and anthropogenic disturbances.
README: Title of Dataset:
VanAcker, M.C., DeNicola, V.L., DeNicola, A.J., Aucoin, S.G., Simon, R., Toal, K.L., Diuk-Wasser, M.A., Cagnacci, F. Resource selection by New York City deer reveals the effective interface between wildlife, zoonotic hazards, and humans. Ecology Letters
Description of the data and file structure
The files named 'males_seasonyear.rds' or 'females_seasonyear.rds' can be used for the manuscript's integrated step selection analysis (iSSA). Each .rds file is divided by deer sex, season, and year. These files are already in the form needed to use the “amt” package for iSSA models. All data files used for iSSA have GPS locations, turn angles, step lengths, and the landcover type extracted for each observed and random location. The file ‘AllDeer_MultiScale_RSS.rds’ is used to produce the summarized AIC results from the second order resource selection functions and can be used to produce Figure S7 from the supplemental material file.
The file ‘LCarea_in_HR.csv’ is used to produce Figure 2 and includes the area of each landcover type contained within individual deer’s home range. ‘All_M1_FineScale.csv’ contains the resulting coefficient estimates for all individual deer model #1 runs which used the fine thematic resolution spatial layer. This can be used to produce Figure 3. The files ‘allcoef_boots_males.csv’ and ‘allcoef_boots_females.csv’ are used to produce Figure 4 movement covariate plots for males and females across urban and natural habitat types. The files entitled 'VanAcker_SI_NY_USA' contain the .tif spatial file used in fine thematic scale models and include accompanying style files used for the Figure 1 map symbology.
Data description for male and female .rds files
Column | Term | Definition | Unit |
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A | id | Unique IDs for white-tailed deer male and female individuals | |
B | burst_ | Sequential integers denoting the track subsets with constant sampling rate | |
C | x1_ | Starting step easting coordinate | EPSG 32618: WGS 84 / UTM Zone 18N |
D | x2_ | Ending step easting coordinate | EPSG 32618: WGS 84 / UTM Zone 18N |
E | y1_ | Starting step northing coordinate | EPSG 32618: WGS 84 / UTM Zone 18N |
F | y2_ | Ending step northing coordinate | EPSG 32618: WGS 84 / UTM Zone 18N |
G | sl_ | Step length | meters; CRS unit from EPSG 32618 |
H | direction_p | Absolute direction | radians |
I | ta_ | Turning angle | degrees |
J | t1_ | Step start time | UTC timestamp |
K | t2_ | Step end time | UTC timestamp |
L | dt_ | Time difference between steps | hours |
M | step_id_ | Sequential integer grouping observed and available steps | |
N | case_ | Observed step = 'TRUE' or available step = 'FALSE' | |
O | tod_end_ | Time of day at end step | day or night |
P | landuse_start | Landuse type at start step | 1 (Water/Wetland/Herb), <br>2 (Low Development), <br>3 (Med-Hi Development), <br>4 (Forest), <br>5 (High Vegetation Block), <br>6 (Low Vegetation Block) |
Q | landuse_end | Landuse type at end step | 1 (Water/Wetland/Herb), <br>2 (Low Development), <br>3 (Med-Hi Development), <br>4 (Forest), <br>5 (High Vegetation Block), <br>6 (Low Vegetation Block) |
R | landuseC_start | Categorical landuse type at start step | Water/Wetland/Herb, <br>LowDev = Low Development, <br>MedHiDev = Med-Hi Development, <br>Forest, <br>Block1 = High Vegetation Block, <br>Block2 = Low Vegetation Block |
S | landuseC_end | Categorical landuse type at end step | Water/Wetland/Herb, <br>LowDev = Low Development, <br>MedHiDev = Med-Hi Development, <br>Forest, <br>Block1 = High Vegetation Block, <br>Block2 = Low Vegetation Block |
T | cos_ta_ | Cosine of the turning angle | |
U | log_sl_ | Natural log of the step length |
Data description for ‘AllDeer_MultiScale_RSS.rds’ file
Column | Term | Definition | Unit |
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A | id | Unique IDs for white-tailed deer male and female individuals | |
B | scale | Buffer scale surrounding each used or available location for which the total area of developed land was estimated | meters |
C | AIC | Akaike Information Criteria of multi-scale logistic regression models examining the effect of development on location use for deer | |
D | nobs | Number of used and available locations used in model | |
E | min_aic | Lowest model AIC score grouped by id | |
F | delta_aic | AIC score difference between each model and the best (or lowest) AIC by id | |
G | relative_aic | Delta AIC score divided by the maximum delta AIC score grouped by id |
Data description for 'LCarea_in_HR.csv' file
Column | Term | Definition | Unit |
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A | id | Unique IDs for white-tailed deer male and female individuals | |
B | simp | Simpson's diversity index of habitat within home range | Diversity index (D) |
C | lc_category | Categorical landuse type | Water/Wetland/Herb, <br>LowDev = Low Development, <br>MedHiDev = Med-Hi Development, <br>Forest, <br>Block1 = High Vegetation Block, <br>Block2 = Low Vegetation Block |
D | lc_area_ha | Landuse area within deer homerange | hectares |
Data description for ‘All_M1_FineScale.csv’ file
Column | Term | Definition |
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A | term | Coefficient term from iSSA model #1 |
B | estimate | Beta coefficient estimate |
C | conf.low | Lower limit of 95% confidence interval |
D | conf.high | Upper limit of 95% confidence interval |
E | ID | Unique IDs for white-tailed deer male and female individuals |
F | Breed_year | Year of breeding season data |
G | sex | Deer sex |
Data description for 'allcoef_boots_ .csv' files
Column | Term | Definition |
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A | key | Coefficient term |
B | lq | 2.5% Lower quantile |
C | mean | Average beta coefficient from bootstrap |
D | uq | 97.5% Upper quantile |
E | inv_se | Inverse variance of beta coefficient |
F | id | Unique IDs for white-tailed deer male and female individuals |
G | sex | Deer sex |
H | season | Season of data collection |
I | year | Year of data collection |
Sharing/Access information
Comments and requests should be addressed to Meredith VanAcker: VanAckerM@si.edu. All material is free of use, but please notify me of its use and cite the dataset and the matching paper if appropriate.
Data was derived from the following sources:
The male white-tailed deer movement data was collected as part of New York City's Deer Impact Management Plan.
The spatial file was derived from the following open-sourced datasets:
NYC Tax PLUTO data
NLCD 2016 Landcover Layer
These were integrated with non-open-sourced data to develop the final spatial layer.
Code/Software
The code is written in R and used version 4.0.5. The data to be imported at the beginning of the script is listed in order of its use for each code section. Sections A and B can be run with any individual season-sex-year files. Section C should be run only with female deer files. Section D should be run only with files labeled ‘breed’ for male and female deer. All exporting of datafiles or figures have been hashed out. The spatial file can be mapped using QGIS.