Abstract

AbstractDetection probability (p) in plants is imperfect in natural conditions due to several factors. This imperfect detectability is rarely accounted for in the estimation of demographic parameters, such as survival probabilities (S) or transition rates between different life states or size classes (ψ), which may result in inaccurate quantitative information about plant populations. In this study, we used previously collected data of five plant species belonging to different families with contrasting life forms and habitats (Flaveria chlorifolia, Mammillaria hernandezii, Neobuxbaumia macrocephala, Govenia lagenophora, and Castilleja tenuiflora), data simulations, multi‐state models (a demographic tool that explicitly accounts for p), and direct estimation of survival and transition rates (i.e., assuming perfect detection) to identify in which species, states, or demographic parameters the bias caused by ignoring our imperfect detectability is more severe. Detection was imperfect (p < 1) for all our study species. In general, ignoring detection probabilities yielded underestimated survival and transition rates in all five species. Biases caused by assuming perfect detection were also large and significant, mainly in inconspicuous life states and size classes, such as seedlings and dry individuals. In contrast, considering detection probabilities resulted in fewer underestimated survival and transition rates, with smaller and mostly nonsignificant biases. Intriguingly, some transitions were overestimated even when accounting for detection probabilities. Our findings highlight the importance of considering that detection of most plant species is imperfect in the field, even in species that are apparently conspicuous, to avoid incorrect inferences about plant populations.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.