Data from: Trends in plant cover derived from vegetation-plot data using ordinal zero-augmented beta regression
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https://datadryad.org/dataset/doi:10.5061/dryad.4xgxd25g4
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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.
提供机构:
Dryad
创建时间:
2024-06-14



