TY - JOUR
T1 - Model-based ordination of pin-point cover data
T2 - Effect of management on dry heathland
AU - Damgaard, Christian
AU - Hansen, Rikke Reisner
AU - Hui, Francis K.C.
N1 - Publisher Copyright:
© 2020
PY - 2020/11
Y1 - 2020/11
N2 - Recently, there has been an increasing interest in model-based approaches for the statistical modelling of the joint distribution of multi-species abundances. The Dirichlet-multinomial distribution has been proposed as a suitable candidate distribution for the joint species distribution of pin-point plant cover data and is here applied in a model-based ordination framework. Unlike most model-based ordination methods, both fixed and random effects are in our proposed model structured as p-dimensional vectors and added to the latent variables before multiplying with the species-specific coefficients. This changes the interpretation of the parameters, so that the fixed and random effects now measure the relative displacement of the vegetation by the fixed and random factors in the p-dimensional latent variable space. This parameterization allows statistical inference of the effect of fixed and random factors in vector space, and makes it easier for practitioners to perform inferences on species composition in a multivariate setting. The method was applied on plant pin-point cover data from dry heathlands that had received different management treatments (burned, grazed, harvested, unmanaged), and it was found that treatment have a significant effect on heathland vegetation both when considering plant functional groups or when the taxonomic resolution was at the species level.
AB - Recently, there has been an increasing interest in model-based approaches for the statistical modelling of the joint distribution of multi-species abundances. The Dirichlet-multinomial distribution has been proposed as a suitable candidate distribution for the joint species distribution of pin-point plant cover data and is here applied in a model-based ordination framework. Unlike most model-based ordination methods, both fixed and random effects are in our proposed model structured as p-dimensional vectors and added to the latent variables before multiplying with the species-specific coefficients. This changes the interpretation of the parameters, so that the fixed and random effects now measure the relative displacement of the vegetation by the fixed and random factors in the p-dimensional latent variable space. This parameterization allows statistical inference of the effect of fixed and random factors in vector space, and makes it easier for practitioners to perform inferences on species composition in a multivariate setting. The method was applied on plant pin-point cover data from dry heathlands that had received different management treatments (burned, grazed, harvested, unmanaged), and it was found that treatment have a significant effect on heathland vegetation both when considering plant functional groups or when the taxonomic resolution was at the species level.
KW - Management of dry heathlands
KW - Model-based ordination
KW - Plant pin-point cover data
KW - Statistical inferences on fixed and random effects
UR - http://www.scopus.com/inward/record.url?scp=85091228691&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2020.101155
DO - 10.1016/j.ecoinf.2020.101155
M3 - Article
SN - 1574-9541
VL - 60
JO - Ecological Informatics
JF - Ecological Informatics
M1 - 101155
ER -