Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models
Niku, J., Hui, F. K. C., Taskinen, S., & Warton, D. I. (2021). Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models. Environmetrics, 32(6), Article e2683. https://doi.org/10.1002/env.2683
© 2021 The Authors. Environmetrics published by John Wiley & Sons Ltd.
In ecological community studies it is often of interest to study the effect of species related trait variables on abundances or presence-absences. Specifically, the interest may lay in the interactions between environmental and trait variables. An increasingly popular approach for studying such interactions is to use the so-called fourth-corner model, which explicitly posits a regression model where the mean response of each species is a function of interactions between covariate and trait predictors (among other terms). On the other hand, many of the fourth-corner models currently applied in the literature are too simplistic to properly account for variation in environmental and trait response and any residual covariation between species. To overcome this problem, we propose a fourth-corner latent variable model which combines the following three features: latent variables to capture the correlation between species, fourth-corner terms to account for environment-trait interactions, and species-specific random slopes for modeling excess heterogeneity between species in their environmental response. We perform an extensive numerical study comparing a variety of fourth-corner models available in the literature which account for the aforementioned sources of variation to varying degrees. Simulation results demonstrate that the proposed fourth-corner latent variable models performed well when testing for the fourth-corner (interaction) coefficients, across both Type I error and power. By comparison, some models that do not full account for all relevant sources of variation suffer from inflated Type I error leading to potentially misleading inference. The proposed method is illustrated by an example on ground beetle data. ...
PublisherJohn Wiley & Sons
Publication in research information system
MetadataShow full item record
Additional information about fundingAustralian Research Council; KoneenSäätiö; Maj ja Tor Nesslingin Säätiö;Suomen Kulttuurirahasto
Showing items with similar title or keywords.
gllvm : Fast analysis of multivariate abundance data with generalized linear latent variable models in R Niku, Jenni; Hui, Francis K.C.; Taskinen, Sara; Warton, David I. (Wiley, 2019)1.There has been rapid development in tools for multivariate analysis based on fully specified statistical models or “joint models”. One approach attracting a lot of attention is generalized linear latent variable models ...
Hui, Francis K. C.; Warton, David I.; Ormerod, John T.; Haapaniemi, Viivi; Taskinen, Sara (American Statistical Association, 2017)Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal ...
Niku, Jenni; Brooks, Wesley; Herliansyah, Riki; Hui, Francis K. C.; Taskinen, Sara; Warton, David I. (Public Library of Science, 2019)Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, ...
Fitting Generalized Linear Latent Variable Models using the method of Extended Variational Approximation Korhonen, Pekka (2020)Yhteisöekologian alalla tutkijat ovat usein kiinnostuneita yhden tai useamman kasvi- tai eläinlajin välisistä esiintyvyyssuhteista eri mittauspaikoilla tai ekosysteemeissä. Tämänkaltaiset tutkimuskysymykset johtavat ...
From clear lakes to murky waters : tracing the functional response of high-latitude lake communities to concurrent ‘greening’ and ‘browning’ Hayden, B.; Harrod, C.; Thomas, S. M.; Eloranta, Antti; Myllykangas, J.-P.; Siwertsson, A.; Præbel, K.; Knudsen, R.; Amundsen, P.-A.; Kahilainen, K. K. (Wiley-Blackwell Publishing Ltd., 2019)Climate change and the intensification of land use practices are causing widespread eutrophication of subarctic lakes. The implications of this rapid change for lake ecosystem function remain poorly understood. To assess ...