Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling. Issue 9 (15th April 2018) - Benoit, David; Jackson, Donald A.; Ridgway, Mark S.
Abstract: Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses. Abstract : In this paper, we explore the implications of imperfect detection or the inability to detect all species in a given survey, on estimates of diversity and community structure. Through multispecies occupancy modelling, we demonstrated that detectability is highly variable, both among species and habitats. This variability in detection was shown to produce underestimations of species richness at the site level and summarized differences in community structure, represented through correspondence analyses.