These files are used to run the R scripts related to the calculation and visualization of RRMSE (Supplementary material S8 and S9) for the total number of roadkills, as well as for carcass location, carcass persistence, and carcass observation bias probabilities. The data files contain simulated values of the total number of roadkills Nitd for each site i, month t, and day d, along with the results of Bayesian analysis based on previously simulated datasets.
Due to the inability to rename the files, the differences between the concepts in the file names and the scientific article are as follows:p1 = pL (Carcass Location Probability)p2 = pP (Average Carcass Persistence Probability in D-day period)p3[1] = pOw (Carcass observation probability by walking survey method)p3[2] = pOc (Carcass observation probability by cycling survey method)p3[3] = pOd (Carcass observation probability by driving survey method)SE p1 = SE pL (Standard Error Carcass Location Probability)SE p2 = SE pP (Standard Error Carcass Persistence Probability)SD N = SD lambda (Variability in daily roadkill abundance)SD p2 = SD pPd (Variability in daily carcass persistence probability)nsites = number of transectslizards = Reptiles G1Snakes = Reptiles G2small_birds_and_bats = Birds/Bats G1medium_and_large_birds = Birds G2small_mammals = Mammals G1Lagomorphs = Mammals G2hedhehogs = Mammals G3medium_and_large_carnivores = Mammals G4ungulates = Mammals G5

This file contains a processed sample of simulated data and the results from their analysis.The structure of the contents is described below.
1. SimulationsFor each functional group, the dataset includes 5 simulations per simulation scenario.Included in the section "simulated_parameters_real_values":- Nitd: Total number of daily roadkills at site i, month t, day d.- NitD: Total number of roadkills during the maximum number of days a carcass remains visible in the survey area at site i and month t.- NtD: Total number of roadkills across all survey sites combined in month t.
Additionally, this section includes the true probability values of detection biases:- pL: Carcass location bias- pP: Carcass persistence bias- pOwalking: Carcass observation bias for walking surveys- pOcycling: Carcass observation bias for cycling surveys- pOdriving: Carcass observation bias for driving surveys
2. Bayesian Parameter EstimationIncluded in the section "Bayesian_parameter_estimation":- Posterior estimates for the following parameters: - totalN (NtD): Estimated total number of roadkills - pL - pP - pOwalking - pOcycling - pOdriving
Each parameter includes:- Posterior mean- R̂ (R-hat) convergence diagnostic- Full posterior distribution

This file contains a processed sample of simulated data and the results from their analysis.The structure of the contents is described below.
1. SimulationsFor each functional group, the dataset includes 5 simulations per simulation scenario.Included in the section "simulated_parameters_real_values":- Nitd: Total number of daily roadkills at site i, month t, day d.- NitD: Total number of roadkills during the maximum number of days a carcass remains visible in the survey area at site i and month t.- NtD: Total number of roadkills across all survey sites combined in month t.
Additionally, this section includes the true probability values of detection biases:- pL: Carcass location bias- pP: Carcass persistence bias- pOwalking: Carcass observation bias for walking surveys- pOcycling: Carcass observation bias for cycling surveys- pOdriving: Carcass observation bias for driving surveys
2. Bayesian Parameter EstimationIncluded in the section "Bayesian_parameter_estimation":- Posterior estimates for the following parameters: - totalN (NtD): Estimated total number of roadkills - pL - pP - pOwalking - pOcycling - pOdriving
Each parameter includes:- Posterior mean- R̂ (R-hat) convergence diagnostic- Full posterior distribution

These files are used to run the R scripts related to the calculation and visualization of RRMSE (Supplementary material S8 and S9) for the total number of roadkills, as well as for carcass location, carcass persistence, and carcass observation bias probabilities. The data files contain simulated values of the total number of roadkills Nitd for each site i, month t, and day d, along with the results of Bayesian analysis based on previously simulated datasets.
Due to the inability to rename the files, the differences between the concepts in the file names and the scientific article are as follows:p1 = pL (Carcass Location Probability)p2 = pP (Average Carcass Persistence Probability in D-day period)p3[1] = pOw (Carcass observation probability by walking survey method)p3[2] = pOc (Carcass observation probability by cycling survey method)p3[3] = pOd (Carcass observation probability by driving survey method)SE p1 = SE pL (Standard Error Carcass Location Probability)SE p2 = SE pP (Standard Error Carcass Persistence Probability)SD N = SD lambda (Variability in daily roadkill abundance)SD p2 = SD pPd (Variability in daily carcass persistence probability)nsites = number of transectslizards = Reptiles G1Snakes = Reptiles G2small_birds_and_bats = Birds/Bats G1medium_and_large_birds = Birds G2small_mammals = Mammals G1Lagomorphs = Mammals G2hedhehogs = Mammals G3medium_and_large_carnivores = Mammals G4ungulates = Mammals G5

These data files are outputs from IBM simulations of:
Bond M, Lee DE, Paniw M. Extinction risks and mitigation for a megaherbivore, the giraffe, in a human-influenced landscape under climate change
The metadata is described in https://github.com/MariaPaniw/Masai_giraffe_ibm

These data files are outputs from IBM simulations of:
Bond M, Lee DE, Paniw M. Extinction risks and mitigation for a megaherbivore, the giraffe, in a human-influenced landscape under climate change
The metadata is described in https://github.com/MariaPaniw/Masai_giraffe_ibm

TASMAX for 21 GCMs to be used for project in https://github.com/MariaPaniw/IBM_meerkat.

TASMAX for 21 GCMs to be used for project in https://github.com/MariaPaniw/IBM_meerkat.