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

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 potentially substituted by the other
species. We also considered resource degradation and computed the quantity
of resources acquired by each species. This established framework was
applied to predation data on bird nests by alien squirrels and other
predators (Case 1) as well as scavenging on mammalian carcasses by two
carnivores (Case 2). In Case 1, the introduction of squirrels
significantly affected the breeding success of birds. Although nests were
being preyed upon by native crows also, our model estimated that Unique
Functional Contribution by the squirrels was 0.47. This means that, by
eradicating the squirrels, the reproductive success of the birds could
potentially increase by as much as 47 %. In Case 2, the Competition
Intensity Index for foxes was 0.17, while that for raccoon dogs was 0.46,
suggesting an asymmetric effect of resource competition between the two
species. The frequency distribution of wet mass available to the two
species differed significantly. This approach will enable a more robust
construction of resource-consumer interaction networks.