Identifying pathways for managing multiple disturbances to limit plant invasions

June 5, 2014
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(This article was first published on Statistical Modeling, Causal Inference, and Social Science » R, and kindly contributed to R-bloggers)

Andrew Tanentzap, William Lee, Adrian Monks, Kate Ladley, Peter Johnson, Geoffrey Rogers, Joy Comrie, Dean Clarke, and Ella Hayman write:

We tested a multivariate hypothesis about the causal mechanisms underlying plant invasions in an ephemeral wetland in South Island, New Zealand to inform management of this biodiverse but globally imperilled habitat. . . . We found that invasion by non-native plants was lowest in sites where the physical disturbance caused by flooding was both intense and frequent. . . . only species adapted to the dominant disturbance regimes at a site may become successful invaders.

Their keywords are:

causal networks; community dynamics; functional traits, invasive species, kettlehole; megafauna; rabbits; restoration; turf plants

But here’s the part that I like best:

We fitted all our models within a hierarchical Bayesian framework using . . . STAN v.1.3 (Stan Development Team 2012) from R v.2.15 (R Development Core Team 2012).

The post Identifying pathways for managing multiple disturbances to limit plant invasions appeared first on Statistical Modeling, Causal Inference, and Social Science.

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