Data from: Geography of roadkills within the Tropical Andes biodiversity hotspot: poorly known vertebrates are part of the toll
Data files
Feb 25, 2021 version files 119.38 KB
-
Data_S1_Amphibians.csv
-
Data_S2_Reptiles.csv
-
Data_S3_Birds.csv
-
Data_S4_Mammals_without_opossum.csv
-
Data_S5_Opossum.csv
-
Data_S6_Spatial_analysis_and_land_cover.xlsx
-
Data_S7_AllRoadkills.csv
-
Data_S8_Roadkills_without_1st_day.csv
-
Data_S9_Roadkills_48h.csv
-
Readme.docx
Abstract
We explore the effect of roads in animal mortality within the Biodiversity Hotspot with the highest number of endemic species of vertebrates on Earth, the Tropical Andes. Our objectives were to know which species are killed on roads in this particularly biodiversity-rich area and how landscape composition and configuration influences roadkills. We systematically looked for roadkills along roads that border three protected areas in the Ecuadorian Andes. To evaluate our hypotheses, we used correlation, logistic regression and GIS analyses. We surveyed a total of 7128 km and observed a roadkill rate of 6.24 (95% CI = 5.35–7.14) individuals per 100 km/day. Roadkills included poorly known endemic and endangered vertebrates; among them, one undescribed snake species of the genus Atractus. Most roadkills were by pastures, the dominant vegetation by roads in our study area. Roadkills were more likely to occur near bridges and were more frequent at greater distances from natural vegetation, towns and rivers. We conclude that pastures and bridges may be functioning as ecological traps for small and poorly known vertebrates. Mitigation measures could include increasing road permeability to wildlife by constructing culverts in critical points where mortality is high, and the adaptation of areas beneath bridges for them to function effectively as wildlife underpasses. These measures should be complemented with fences to exclude vertebrates from roads in areas near wildlife passages and along pastures. We encourage the development of similar studies in biodiversity-rich areas to inform mitigation measures that can be adapted to local conditions.
Usage notes
Data S1 to S5, column headings correspond to:
Roadkill: 1, when data corresponds to roadkill, 0 when data corresponds to random point
rivers: distance to nearest river (meters)
towns: distance to nearest town (meters)
bridge: distance to nearest bridge (meters)
remnant_vegetation: distance to nearest patch of remnant vegetation (meters)
percent_rem_veg: percentage of forest cover within a 100m radius of roadkill or random point
Data S6_spatial analysis and land cover; columns correspond to:
Code: code of roadkill
mmddyy: date (month, day, year)
Road_segment: segment of road where roadkill was found
Class: vertebrate Class
Order: vertebrate Order
Family: vertebrate Family
Species: binomial latin name
UTM zone: zone of UTM coordinates (dataset includes UTM 17M and 18M).
XCoordinate: UTM X coordinate
YCoordinate: UTM Y coordinate
Time: time when roadkill was detected
Altitude: altitude in meters above sea level
Land_cover: land cover class at both sides of the road of roadkill site. Shrubs (S), Forest (F), Urban (U), Cropland (C), Pastures (P). A single land cover character indicates the same land cover type at both sides of road.