CMStatistics 2022: Start Registration
View Submission - CMStatistics
B0305
Title: Flexible species distributions modelling for spatiotemporal opportunistic surveys data Authors:  Jafet Belmont - University of Glasgow (United Kingdom) [presenting]
Claire Miller - University of Glasgow (United Kingdom)
Marian Scott - University of Glasgow (United Kingdom)
Craig Wilkie - University of Glasgow (United Kingdom)
Abstract: Biodiversity monitoring programs have become essential to describe, predict and map species distributions across large geographic and temporal scales. Unfortunately, collecting species occurrence data in such large-scale studies can be difficult. Thus, citizen science projects, involving volunteers who help to collect data and monitor sites, offer a cost-effective solution to investigate species distributions at large spatial and temporal scales. However, analysing data from these opportunistic recording schemes is challenging because of uneven sampling efforts and species imperfect detection. Over the last decade, the increasing awareness of accounting for species imperfect detection in ecological studies has led to the development of different species distribution models. Particularly, dynamic occupancy models have proven to be a powerful tool for estimating temporal changes in species occurrences while correcting for imperfect detection and varying sampling effort. Thus, we discuss some of the challenges involved with occupancy models and opportunistic recording schemes, and propose a multiple-species flexible dynamic model that enables non-linear effects to be estimated. We applied this model to investigate how dragonflies' population dynamics are affected by temperature levels in waterbodies across the UK and to account for seasonal patterns in species' life cycles.