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Data from: Global fern and lycophyte richness explained: how regional and local factors shape plot richness

<p>Aim<br> To disentangle the influence of environmental factors at different spatial grains (regional and local) on fern and lycophyte species richness and ask how regional and plot-level richness are related to each other.<br> Location<br> Global.<br> Time Period<br> Present.<br> Major Taxa studied<br> Ferns and lycophytes.<br> Methods<br> We explored fern and lycophyte species richness at two spatial grains, regional (hexagonal grid cells of 7666 km2) and plot-level (300–500 m2), in relation to environmental data at regional and local grains (the 7666-km2 hexagonal grid cells and 4-km2 square grid cells, respectively). For the regional grain, we obtained species richness data for 1243 spatial units and used them together with climatic, and topographical predictors to model global fern richness. For the plot-level grain, we collated a global dataset of nearly 83,000 vegetation plots with surface area in the range 300–500 m2 in which all fern and lycophyte species had been counted. We used structural equation modelling to identify which regional and local factors have the biggest effect on plot-level fern and lycophyte species richness worldwide. We investigate how plot-level richness is related to modelled regional richness at the plot's location.<br> Results<br> Plot-level fern and lycophyte species richness was best explained by models allowing a link between regional environment and plot-level richness. A link between regional richness and plot-level richness was essential, as models without it were rejected, while models without the regional environment - plot-level richness link were still valid but had a worse goodness-of-fit value. Plot-level richness showed a hump-shaped relationship with regional richness.<br> Main Conclusions<br> Both regional environment and regional fern and lycophyte species richness each are important determinants of plot-level richness, and the inclusion of one does not substitute the inclusion of the other. Plot-level richness increases with regional richness until a saturation point is reached, after which plot-level richness decreases despite increasing regional richness, possibly reflecting species interactions.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
12
Access
12
Reuse readiness
0
Engagement
4

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Dataset details

Repository
dryad
Published
November 17, 2020
License
cc-zero
DOI
10.5061/dryad.hmgqnk9c3

Scored with release 0.9.0

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