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Activity Number: 361 - Multivariate Ecological Data: Uncovering the Story in the Noise to Inform Species Management and Conservation
Type: Invited
Date/Time: Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #316663
Title: The impacts of sampling design in estimating fish species abundance in fresh water lakes
Author(s): Erin M Schliep* and Joshua S North
Companies: University of Missouri and University of Missouri
Keywords: Bayesian hierarchical models; Joint species distribution models; Climate
Abstract:

The underlying motivation for joint species distribution models (JSDMs) is to investigate the distribution of multiple species as a function of the environment while accounting for dependence between species. The data used to inform JSDMs are collected through a variety of opportunistic sampling protocols, including various gear types (e.g., fish nets, traps), survey times and spatial extents (referred to as sampling effort), and often contain varying degrees of imperfect detection. While some methods exist that account for sampling designs in species distribution models, the effects are assumed to be the same across all species and constant in time. Relaxing these assumptions, we develop statistical methods to investigate the effects of time-varying and species-specific sampling designs in JSDMs. This work is supported by the USGS and motivated by an application to fresh water fish, where different gear types are used at different spatial locations at different times with the aim to learn environmental drivers of abundance.


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