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Data from : Historical legacies and ecological determinants of grass naturalizations worldwide

<p>The global distribution of exotic species is the result of abiotic, biotic and dispersal<br> filtering processes that shape the movement and success of species outside their native<br> range. In this study we aim to understand how these filtering processes drive the fluxes<br> of grass species among regions, the factors that influence which species establish outside<br> of their native range, and where they do so.</p> <p><br> We used national and subnational checklists of native and introduced grass species<br> to determine the extent to which each region was a source or recipient of exotic grass<br> species. We asked how species traits may distinguish those grass species that have naturalized<br> outside their native range from those that have not, and how environmental<br> conditions are related to the distribution of exotic grass species.</p> <p><br> We found that exotic grass establishment is shaped by an array of factors including<br> characteristics of regions, traits of species and their interactions. Regions with a longer<br> history of human occupation and larger numbers of native grass species were generally<br> the most important sources of exotic species. Global flows of species were mostly<br> driven by a climate match between the native and exotic ranges, but were also highly<br> asymmetric, with regions with recent human arrival being the major hosts of exotic<br> grass species. Tall, annual and C4 grass species exhibited particularly high probabilities<br> of establishment outside their native range.</p> <p><br> Despite the idiosyncrasy and stochasticity characteristic of exotic species establishment,<br> this biogeographical analysis revealed important generalities across this large<br> plant group. Our results suggest that grass species that have co-occurred with humans<br> for a longer time may be better adapted to living in anthropogenic landscapes, explaining<br> the global asymmetry in species introductions.</p>

ShareScore

36/100

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
8

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