Fig 1.
Study area with location of monitored roads and protected areas.
Reprinted from Brasilia Environmental Institute (IBRAM) under a CC BY license, with permission from the head of the management of environmental information of IBRAM, original copyright 2016.
Table 1.
List of explanatory variables and their range values related to the animal, road, weather and land cover used to explain variations in carcass persistence.
Fig 2.
Survival curves from Kaplan-Meier models and corresponding 95% confidence intervals for global data, and body mass classes.
Table 2.
Summary of the top Akaike’s Information Criterion models (ΔAICc<2.0) of the mixed Cox proportional hazard function for persistence data with 3-km buffer radius.
All models included site as random effect. LogLik: maximum likelihood value; R2: variance explained by the model; ΔAICc: Akaike’s Information Criterion rank; w: AIC model weights.
Table 3.
Model-averaged coefficients (β), respective confidence intervals from unconditional standard errors (95% LCI and 95% UCI), estimates of the hazards ratio (eβ), and importance value of the top mixed Cox models (ΔAICc<2.0) to 3-km buffer.
Variables are ordered according to their importance.
Table 4.
Estimates of total roadkills corrected for biases introduced by carcass persistence and survey method.
f–detectability (%), s–estimated median carcass persistence time (days), p–probability of a carcass being detected after one day. N'–mortality estimate with correction for detectability and carcass persistence (roadkills/day/km). C’–mortality estimates without correction for detectability and carcass persistence (roadkills/day/km). Confidence intervals are provided when available.