Data from: Plant diversity in oceanic archipelagos: realistic patterns emulated by an agent‐based computer simulation
Although islands as natural laboratories have held the attention of scientists for centuries, they continue to offer new study questions, especially in the context of the current biodiversity crisis. To date, habitat diversity on islands and spatial configuration of archipelagos have received less a...
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Zusammenfassung: | Although islands as natural laboratories have held the attention of
scientists for centuries, they continue to offer new study questions,
especially in the context of the current biodiversity crisis. To date,
habitat diversity on islands and spatial configuration of archipelagos
have received less attention than classical island area and isolation.
Moreover, in the field where experiments are impossible, correlative
methods have dominated, despite the call for more mechanistic approaches.
We developed an agent‐based computer simulation to study the effect of
habitat diversity and archipelago configuration on plant species richness
and composition in five archipelagos worldwide (Hawaii, Galapagos, Canary
Islands, Cape Verde and Azores) and compared simulated diversity patterns
to the empirical data. Habitat diversity proved to be an important factor
to achieve realistic simulation results in all five archipelagos, whereas
spatial structure of archipelagos was important in more elongated
archipelagos. In most cases, simulation results correlate stronger with
spermatophyte than with pteridophyte data, which we suggest can be
attributed to the different dispersal and evolution rates of the two
species groups. Correlation strength between simulated and observed
diversity also varied among archipelagos, suggesting that geological and
biogeographic histories of archipelagos have affected the species richness
and composition on the islands. Our study demonstrates that a relatively
simple computer simulation involving just a few essential processes can
largely emulate patterns of archipelagic species richness and composition
and serve as a powerful additional method to complement empirical
approaches. |
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DOI: | 10.5061/dryad.668ds1f |