Modelling the monitoring and management of cryptic threatened lizard species in mauritius

The use of conservation translocations as a tool for restoration of biodiversity is becoming common practice in the conservation of threatened species. Despite this increase in use, guidance for translocations of reptiles, especially for prey species, is very limited. The cryptic nature of many reptile species further impedes efforts to effectively plan translocations and monitor released populations. This limited information leads to high uncertainty in estimated demographic parameters, which are often used to assess the outcome of translocations and then adaptively manage populations. An incomplete understanding of population dynamics further limits the ability to respond to stochastic events such as extreme weather events or environmental disasters.

Capture-recapture methods are commonly employed to monitor species where individuals can be uniquely identified. The statistical approaches applied to this survey data enable the estimation of demographic parameters such as population size, survival probability and probability of new entrants to a population. However, when working with translocated populations of threatened species, initial population sizes can be very small, leading to high uncertainty in estimated parameters.

In this thesis, I apply statistical methods to increase understanding of threatened reptile population dynamics following conservation management actions. I develop a bespoke capture-recapture model to improve the accuracy of estimates of demographic parameters for translocated populations. I compare the estimates of this model to a standard capture-recapture model (Jolly-Seber/JS model) using a simulation study, and case study of a reintroduced threatened gecko (the lesser night gecko, Nactus coindemirensis), in Mauritius. I further examine the demographics of cryptic reptile populations (Bojer's skink, Gongylomorphus bojerii and lesser night gecko) following an environmental disaster in Mauritius, the MV Wakashio oil spill in 2020, using the bespoke capture-recapture model developed for the reintroduced population affected. Finally, I describe the planning process, translocation and initial monitoring for a reintroduction of lesser night gecko to Round Island, Mauritius, combining existing knowledge with expert elicited recommendations to optimise decisions in an ecosystem where native predators were present.

I demonstrate that the use of standard JS models can lead to overestimates in initial population size of translocated populations where detection probability is below 0.3. The use of the modified JS model developed prevents this overestimation by accounting for translocated individuals, in addition to reducing overall uncertainty in parameter estimates. Results from the analysis of the Bojer's skink and lesser night gecko populations following the MV Wakashio oil spill indicated limited variation in survival or body condition that could be attributed to the oil spill, due to delays in surveys during the Covid-19 pandemic. Expert recommendations and published literature led to the use of soft-release enclosures for translocation of lesser night geckos to Round Island and highlighted the risks of predation and dispersal. Predator removal, carried out prior to the release, led to population suppression by an estimated 67-75%, assessed using geometric removal models accounting for time-varying detection probability using covariates of survey effort. The analysis of monitoring data from the first seven months after release estimated a monthly survival probability between 0.75-0.92, and by the end of the study juveniles were present in all enclosures.

The findings presented in this thesis emphasize the need for suitable modelling of translocated populations of cryptic species in order to obtain more robust estimates of demographic parameters, better informing management actions and ultimately increasing the likelihood of translocation success. I demonstrate the need for thorough baseline surveys of populations with high risk of extinction, to allow better management following random stochastic events. Further, I highlight the requirement of continued monitoring of translocated populations to allow for accurate measures of success. The evidence I present provides guidance on collection and analysis of monitoring data on cryptic reptile species following conservation management actions.