Spatial patterning reflects invasion velocity for exotic plant species

Background/Question/Methods

 

Multiple mechanisms have been identified as explanations for the success of exotic invasive plant species. Less attention has been paid, however, to studying how these mechanisms affect the rate of spatial spread through invaded ranges. Identification of ongoing rates of invasive spread is an important step within the prioritization of nature conservation and restoration efforts. One potential limitation to the study of invasive species spread is the availability of timeseries data at the ecosystem scale. Although the availability of recent Earth Observation data is rapidly increasing (e.g. through Google Earth), these data become increasingly scarce when going further back in time, or when focusing on more remote regions of the globe. Here we present a novel method that enables the inference of invasive species spread from a single ‘snapshot’ (e.g. a satellite image or aerial photograph) in time. The method is derived using an analytical model of invasive species spread. The method is then applied using a more detailed stochastic, individual-based plant competition model. Predictions obtained with the method are tested with high resolution timeseries data documenting invasive species spread in California.  

 

Results/Conclusions

 

Our analyses suggest that the rate of invasive spread of an exotic plant species is reflected in two diagnostic attributes of the plant community distribution pattern. The first attribute is that invasive spread is reflected by the average frontrunner position of the invading species being closer to a so-called optimal vegetation boundary than the native plant species. For a given dispersal strategy, the distance between the invader’s average frontrunner position and the optimal vegetation boundary decreases with increasing rates of spread. The second attribute is that for a given distance of the invader to the optimal vegetation boundary, the steepness of the invader’s density gradient through space reflects the invasion strategy, and hence invasion velocity. More specifically, steeper density profiles correlate with more rapidly invading species that have a wider dispersal kernel. Our results suggest that single snapshots in time enable the identification of hotspots and coldspots of invasive species expansion. The novel method proposed could thus serve as a rapid assessment tool to prioritize invasive species management, to be tested in future empirical studies.