DOI: 10.5061/dryad.4xgxd25g4
title: Data from: Trends in plant cover derived from vegetation-plot data using ordinal zero-augmented beta regression

description: Questions. Plant cover values in vegetation-plot data are bounded between
 0 and 1, and cover is typically recorded in discrete classes with
 non-equal intervals. Consequently, cover data are skewed and
 heteroskedastic, which hampers the application of conventional regression
 methods. Recently developed ordinal beta regression models consider these
 statistical difficulties. Our primary question is if we can detect species
 trends in vegetation-plot time series data with this modelling approach. A
 second question is whether trends in cover have additional value compared
 to trends in occurrence, which are easier to assess for practitioners.
 Location. The Netherlands, Western Europe. Methods. We used
 vegetation-plot data collected from 10.000 fixed plots which were surveyed
 once every four years during 1999-2022. We used the ordinal zero-augmented
 beta regression (OZAB) model, a hierarchical model consisting of a
 logistic regression for presence and an ordinal beta regression for cover.
 We adapted the OZAB model for longitudinal data and produced estimates of
 cover and occurrence for each four-year period. Thereafter we assessed
 trends in cover and in occurrence across all periods. Results. We found
 evidence of a trend in cover in 318 out of the 721 species (44%) with
 sufficient data. Most species showed similar directional trends in
 occurrence and percent cover. No trend in occurrence was detected for 64
 species that had evidence of a trend in cover. Declining species had
 stronger relative changes in cover than in occurrence. Conclusions. Our
 model enables researchers to detect trends in cover using longitudinal
 vegetation-plot data. Cover trends often corroborated trends in
 occurrence, but we also regularly found trends in cover even in the
 absence of evidence for trends in occurrence. Our approach thus
 contributes to a more complete picture of (changes in) vegetation
 composition based on large monitoring datasets.
description: The national vegetation monitoring scheme consists of more than
 10.000 fixed plots in the Netherlands. The program monitors all major
 terrestrial habitat types except urban areas. Fieldwork is organised on
 the level of provinces and conducted by professional field workers. These
 field workers selected the plots and collected vegetation data, using
 field guidelines to ensure proper selection of plot location and
 standardisation of data collection at the national level. All vascular
 plants were visually recorded using the extended Braun-Blanquet cover
 scale (Van der Maarel, 2007). This data package contains all observations
 of the species <em>Acer pseudoplantanus</em>,
 <em>Senecio inaequidens</em> and <em>Caltha
 palustris</em> from the period 1999 - 2022 recorded in this
 monitoring scheme.
description: All data tables are colon-separated text files with extension
 '.csv'. 
description: # Data from: Trends in plant cover derived from vegetation-plot data using
 ordinal zero-augmented beta regression All data files with the extension
 '.csv' are colon-separated text files. Visits table: one row per
 visit * Site_id: key variable identifying location * Visit_id: key
 variable identifying a location-date combination * Period: four-year
 visiting period Observations table: one row per observation (species seen
 at a specific time at a specific place) * Site_id: key variable
 identifying location * Visit_id: key variable identifying a location-date
 combination * Species_id: key variable identifying species * Cover: plant
 cover percentage (calculated as described in the publication) *
 Cover_class: plant cover class (as documented in the field) Species table:
 one row per species * Species_id: key variable identifying species *
 Scientific_name: scientific name