Simulating the effects of climate change on the distribution of an invasive plant, using a high resolution, local scale, mechanistic approach: challenges and insights. (10th January 2013)

• Record Type: Journal Article
• Authors: Fennell, Mark; Murphy, James E.; Gallagher, Tommy; Osborne, Bruce
• Is Part Of: Global change biology. Volume 19:Number 4(2013:Apr.)
• Page Start: 1262
• Page End: 1274
• Publication Date: 2013-01-10
• Subjects: Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.12102
• Languages: English
• ISSNs: 1354-1013

Abstract

<abstract abstract-type="main" id="gcb12102-abs-0001"> <title>Abstract</title> <p>The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (<italic>Gunnera tinctoria</italic>) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate‐induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread‐rate and intensity of <italic>G. tinctoria</italic> invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters.</p> </abstract>