Global fern and lycophyte richness explained: How regional and local factors shape plot richness
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In: Journal of Biogeography, Vol. 47, No. 1, 01.01.2020, p. 59-71.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Global fern and lycophyte richness explained: How regional and local factors shape plot richness
AU - Weigand, Anna
AU - Abrahamczyk, Stefan
AU - Aubin, Isabelle
AU - Bita-Nicolae, Claudia
AU - Bruelheide, Helge
AU - I. Carvajal-Hernández, Cesar
AU - Cicuzza, Daniele
AU - Nascimento da Costa, Lucas Erickson
AU - Csiky, János
AU - Dengler, Jürgen
AU - Gasper, André Luís de
AU - Guerin, Greg R.
AU - Haider, Sylvia
AU - Hernández-Rojas, Adriana
AU - Jandt, Ute
AU - Reyes-Chávez, Johan
AU - Karger, Dirk N.
AU - Khine, Phyo Kay
AU - Kluge, Jürgen
AU - Krömer, Thorsten
AU - Lehnert, Marcus
AU - Lenoir, Jonathan
AU - Moulatlet, Gabriel M.
AU - Aros-Mualin, Daniela
AU - Noben, Sarah
AU - Olivares, Ingrid
AU - G. Quintanilla, Luis
AU - Reich, Peter B.
AU - Salazar, Laura
AU - Silva-Mijangos, Libertad
AU - Tuomisto, Hanna
AU - Weigelt, Patrick
AU - Zuquim, Gabriela
AU - Kreft, Holger
AU - Kessler, Michael
N1 - Publisher Copyright: © 2019 John Wiley & Sons Ltd
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Aim: To disentangle the influence of environmental factors at different spatial grains (regional and local) on fern and lycophyte species richness and to ask how regional and plot-level richness are related to each other. Location: Global. Taxon: Ferns and lycophytes. Methods: We explored fern and lycophyte species richness at two spatial grains, regional (hexagonal grid cells of 7,666 km2) and plot level (300–500 m2), in relation to environmental data at regional and local grains (the 7,666 km2 hexagonal grid cells and 4 km2 square grid cells, respectively). For the regional grain, we obtained species richness data for 1,243 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 a 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. Results: Plot-level fern and lycophyte species richness were 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. Main conclusions: 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.
AB - Aim: To disentangle the influence of environmental factors at different spatial grains (regional and local) on fern and lycophyte species richness and to ask how regional and plot-level richness are related to each other. Location: Global. Taxon: Ferns and lycophytes. Methods: We explored fern and lycophyte species richness at two spatial grains, regional (hexagonal grid cells of 7,666 km2) and plot level (300–500 m2), in relation to environmental data at regional and local grains (the 7,666 km2 hexagonal grid cells and 4 km2 square grid cells, respectively). For the regional grain, we obtained species richness data for 1,243 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 a 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. Results: Plot-level fern and lycophyte species richness were 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. Main conclusions: 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.
KW - Biology
KW - big data
KW - macroecology
KW - pteridophytes
KW - regional-local richness relationship
KW - saturation curves
KW - structural equation modelling
UR - http://www.scopus.com/inward/record.url?scp=85077896250&partnerID=8YFLogxK
U2 - 10.1111/jbi.13782
DO - 10.1111/jbi.13782
M3 - Journal articles
AN - SCOPUS:85077896250
VL - 47
SP - 59
EP - 71
JO - Journal of Biogeography
JF - Journal of Biogeography
SN - 0305-0270
IS - 1
ER -