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Data and code for implementing time-to-detection occupancy model

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DataONE2024-08-01 更新2025-04-26 收录
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Camera traps have been widely employed in wildlife research, offering significant potential for monitoring species interactions at ephemeral resources. However, raw data obtained from camera traps often face limitations due to observation censoring, where resource consumption by dominant animals may obscure potential resource use by less dominant animals. We extended time-to-detection occupancy modelling to quantify interspecific consumptive competition and redundancy of ecosystem functions through consumption between two species, while accounting for observation censoring. By treating resource use by rival species as censored data, we estimated the proportion of resources potentially used in the absence of rival species, and calculated the loss caused by the rival species, which is defined as 'Competition Intensity Index'. We also defined the Unique Functional Contribution, which represents the net functional loss when a species is removed, calculated by excluding the contribution pote..., , , ## Description of the data and file structure The following files are stored in this data repository. * Case_1_data.RData: Data of Case 1 study * Case_2_data.RData: Data of Case 1 study * Case_1_sample_code.R: R code to implement the analysis * Case_1_stan.stan: Stan code for the TTD occupancy model * Case_2_sample_code.R: R code to implement the analysis * Case_2_Stan.stan: Stan code for the TTD occupancy model and the Gompertz regression model The Case 1 and Case 2 prefixes correspond to the case studies presented in Nakashima et al. (2024) ([https://onlinelibrary.wiley.com/doi/10.1002/ece3.70031](https://onlinelibrary.wiley.com/doi/10.1002/ece3.70031)). These files contain the data and Stan code for conducting TTD (Time-To-Detection) analyses, along with the R code to execute them. ### Case 1  Case_1_data.RData contains a list object called data_list. To view the data, download the file and save it to your working directory, then run the following code: ``` load(\"Case_1_data....
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2024-08-02
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