The influence of domestic dogs on the spatial and temporal distribution of tayra
Data files
Sep 17, 2024 version files 41.39 KB
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Activitypattern2.csv
9.93 KB
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occu_dog.csv
3.65 KB
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occu_tayra.csv
3.67 KB
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README.md
3.14 KB
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varocc.csv
14.52 KB
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varsite.csv
6.48 KB
Abstract
The domestic dog (Canis familiaris) is an exotic species known to have impacts on native fauna and it may induce spatial and temporal segregation in other species as a mechanism to reduce agonistic interactions. The tayra (Eira barbara), a medium-sized, widely distributed mustelid, is one of the species that can be affected. To test this hypothesis, between 2020 and 2022, we installed camera traps in an agricultural landscape composed of a protected area, agro-livestock areas, an urban area, and several rural households. We calculated the activity patterns, their overlapping coefficients and generated models to explain the species’s occupancy and verify possible interferences. We obtained 32 records of tayras and 100 of domestic dogs. In only 8 of 73 sampling points, the two species occurred concomitantly. Activity overlap was 68%; however, at the points where both species occurred, the overlap was 43%. Tayra showed to be positively associated with forest areas, and negatively with agricultural exploitation areas. Dogs predominantly occupied agricultural areas and were negatively related to forest areas. In addition to dog interference, which seems to affect tayra's use of the landscape, environmental conditions are also essential in describing the occupancy of the subordinate species. It is possible that their scansorial habit is important to avoid agonistic events.
README: The influence of domestic dogs on the spatial and temporal distribution of tayra
https://doi.org/10.5061/dryad.zgmsbccn3
Description of the data and file structure
We obtained records of tayras and dogs using 40 camera traps between December 2020 and August 2022, totalling a sampling effort of 43,665 cameras per day. The camera traps were systematically arranged at 73 sampling points approximately 30-40 centimeters from the ground, with approximately 2 kilometers between the points. We programmed the traps to work continuously, 24 hours a day for at least 60 consecutive days.
The photographic records were extracted as information on the location of species activity, their presence and absence histories and the temporal variations that interfere with detection and the spatial variations that interfere with occupation.
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Files and variables
File: Activitypattern2.csv
Description: The spreadsheet contains the dates and locations where the species were recorded and the h values, which are formulas that convert time data into radians, that is, circular data.
Variables
- Species;Date;Local;Ponto;Time;hdec;hday:
File: occu_dog.csv
Description: Matrix of presence and absence of domestic dogs, where each occasion is a grouping of 5 consecutive days. Each line represents a sample point and each column an occasion.
Variables
- Name;1;2;3;4;5;6;7;8;9;10;11;12;13;14;15;16;17;18;19;20;21:
- 0 = absence
- 1 = presence
File: varocc.csv
Description: Matrix containing the climatic covariates that affect the detection of species. The average temperatures (t) and precipitation (p) were grouped for 5-day occasions. Each line represents a sample point and each column an occasion.
Variables
- t1;t2;t3;t4;t5;t6;t7;t8;t9;t10;t11;t12;t13;t14;t15;t16;t17;t18;t19;t20;t21;p1;p2;p3;p4;p5;p6;p7;p8;p9;p10;p11;p12;p13;p14;p15;p16;p17;p18;p19;p20;p21:
File: occu_tayra.csv
Description: Matrix of presence and absence of tayra where each occasion is a grouping of 5 consecutive days. Each line represents a sample point and each column an occasion.
- Name;1;2;3;4;5;6;7;8;9;10;11;12;13;14;15;16;17;18;19;20;21:
- 0 = absence
- 1 = presence
File: varsite.csv
Description: Environmental covariates that affect the occupation of species. Land use percentages were extracted from land use and land cover maps at different scales. The data were normalized. Land use percentages were extracted from land use and land cover maps at different scales. The data were normalized. Land use percentages were extracted from land use and land cover maps at different scales. The data were normalized. Each line represents a sample point and each column shows the percentages of the coverage types at each sample point,.
Variables
- Agriculture_200;Temporary_200;Agriculture_500;Forest_800;Pasture_800;Perennial_1000;Forest_1000;Temporary_1000;Agriculture_200ms;Temporary_200ms;Agriculture_500ms;Forest_800ms;Pasture_800ms;Perennial_1000ms;Forest_1000ms;Temporary_1000ms: