10.5061/DRYAD.6HDR7SQX4
Barajas Barbosa, Martha Paola
0000-0002-9040-0766
University of Göttingen
Weigelt, Patrick
University of Göttingen
Borregaard, Michael
University of Copenhagen
Keppel, Gunnar
0000-0001-7092-6149
University of South Australia
Kreft, Holger
University of Göttingen
Data from: Environmental heterogeneity dynamics drive plant diversity on
oceanic islands
Dryad
dataset
2020
general dynamic model
island ontogeny
oceanic islands
insular endemism
Deutsche Forschungsgemeinschaft
https://ror.org/018mejw64
152112243
2021-05-27T00:00:00Z
2021-03-25T00:00:00Z
en
https://doi.org/10.1111/jbi.13925
607428001 bytes
7
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Aim: The General Dynamic Model (GDM) links island biogeographical
processes to island geological history. A key premise of the GDM implies
that environmental factors shaping the ecology and evolution of insular
biota follow a hump-shaped trend over the island’s life span and drive
dynamics in carrying capacity, species diversity and endemism. An
important component of the GDM is environmental heterogeneity (EH), but
its effects on insular diversity remain poorly understood. Here, we first
quantified EH, tested whether EH follows the expected hump-shaped trend
along island ontogeny and evaluated how EH relates to plant diversity.
Location: 135 oceanic islands of volcanic origin. Taxon: Vascular plants.
Methods: We calculated 20 alternative EH metrics for focusing on
topographic and climatic components of EH, and comparing whole-island
metrics (e.g., range) and moving-window metrics (e.g., roughness). Using
linear mixed-effects models, we evaluated the trends of EH with island age
and the EH-plant diversity relationship expected based on the GDM.
Results: Our analysis revealed some EH components to be collinear, e.g.,
elevation and temperature heterogeneity, but also underlined that EH
metrics capture different aspects of EH, e.g., climatic gradients vs.
climatic complexity. EH generally followed a hump-shaped trend with island
age with an early peak in island ontogeny. Among the EH components,
climatic heterogeneity had the strongest effect on plant species richness
and elevation heterogeneity on endemism. Including EH into previous
analytical models to test the GDM improved their predictive power. Main
conclusions: The EH metrics compared here captured various attributes of
the environment that influence insular plant diversity. In line with the
GDM, our results strongly support the hump-shaped relationship between EH
and island age, suggesting that islands become highly heterogeneous early
in their ontogeny. Finally, the contribution of EH to GDM-based models of
species richness and endemism suggests that EH is a main driver of the
diversity of oceanic island biotas.
Data analysed and produced in this study 1. Number of native and
single-island endemic species, age, area and archipelago information per
island were obtained from the Global Inventory of Floras and Traits
(GIFT). The GIFT database provides information of distributions and
floristic status (native, endemic, alien) of plant species based on a wide
range of regional floristic databases, floras and checklists (Weigelt et
al., 2020) 2. Information of environmental components: 1.1. Elevation was
downloaded from URL:
https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/.
Heat load index, was derived from elevation data using the Spatial Analyst
extension and the Geomorphometry & Gradient Metrics toolbox (Evans
et al., 2014) in ESRI ArcGIS version 10.4. URL:
https://github.com/jeffreyevans/GradientMetrics. 1.2 Precipitation and
temperature were downloaded from URL: http://chelsa-climate.org/ 1.3.
Heterogeneity rasters were produced using the Spatial Analyst extension
and the Geomorphometry & Gradient Metrics toolbox (Evans et al.,
2014) in ESRI ArcGIS version 10.4. 3. The code created in R software is
also available. With the code EH metrics can be calculated and statistical
anylsis can be reproduced.