What can Joint Species Distribution Models tell us about beta diversity?

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http://urn.fi/URN:NBN:fi:hulib-202106303255
Title: What can Joint Species Distribution Models tell us about beta diversity?
Author: Serra Dominguez, Lluis
Contributor: University of Helsinki, Faculty of Biological and Environmental Sciences
Publisher: Helsingin yliopisto
Date: 2021
Language: eng
URI: http://urn.fi/URN:NBN:fi:hulib-202106303255
http://hdl.handle.net/10138/332005
Thesis level: master's thesis
Degree program: Ekologian ja evoluutiobiologian maisteriohjelma
Master's Programme in Ecology and Evolutionary Biology
Magisterprogrammet i ekologi och evolutionsbiologi
Specialisation: ei opintosuuntaa
no specialization
ingen studieinriktning
Abstract: Beta diversity (total dissimilarity) can be partitioned into two components: dissimilarity attributed to turnover and nestedness-resultant dissimilarity. Turnover refers to the variation in species identities among sites and implies the replacement of some species by others. In contrast, nestedness occurs when species-poor sites have a subset of the biota present in species-richer sites. Although disentangling the relative contribution of these two antithetic components from beta diversity can characterize species assemblages, the dissimilarity indices do not provide information on the processes generating the patterns. Conversely, Hierarchical Modelling of Species Communities (HMSC), which unifies many of the recent advantages of Joint Species Distribution Models, has proved to be the one of the best performing frameworks for unravelling the underlying mechanisms structuring ecological communities. The aim of this research is to explore the relationship between the outputs of the HMSC model and the dissimilarity indices in different communities with a wide range of parameterizations. As the observed patterns measured by the beta-diversity indices result from the underlying processes which HMSC attempts to capture, I hypothesized that both frameworks are at least partially linked to each other. To achieve this aim, I simulated the community data by following the structure of the HMSC model. For simplicity, only one environmental covariate was considered, which was scaled to 0 mean. The intercept of the HMSC model accounted for the baseline occurrence probability of the species, while the slope modeled the species responses to the environmental covariate. The HMSC-intercept and the HMSC-slope, which represent the species multivariate niches, were summarized in terms of center and spread. Simultaneously, the beta diversity indices (total, turnover and nestedness dissimilarity) were calculated from the community data. Finally, the outputs of both frameworks were related in terms of linear modelling and variation partitioning. As hypothesized, the results of this study suggest that outputs of the HMSC model are able to explain most of the variation in the beta-diversity indices, indicating that both frameworks are strongly related. By plotting the species niches (intercept and slope coefficients of the HMSC model) it is possible to determine the main axes of niche variation producing the nestedness and turnover patterns. While nestedness is generated by a shared response of the species to the environmental covariate(s), turnover is produced by variation in the species responses. Finally, the total dissimilarity index is driven by species rarity. In conclusion, the most comprehensive evaluation of the structure of ecological communities and the processes determining the diversity patterns can be achieved by combining the outputs of beta-diversity indices and the HMSC model.
Subject: HMSC
joint species distribution models
beta diversity
nestedness
turnover
dissimilarity


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