Investigation of the invasion dynamics of Asparagus asparagoides at the habitat level using spatial analytical techniques

Investigation of the invasion dynamics of Asparagus asparagoides at the habitat level using spatial analytical techniques

Siderov, K 2005, Investigation of the invasion dynamics of Asparagus asparagoides at the habitat level using spatial analytical techniques, PhD Thesis, School of Mathematical and Geospatial Sciences, RMIT University.

Document type:	Thesis
Collection:	Theses

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Title	Investigation of the invasion dynamics of Asparagus asparagoides at the habitat level using spatial analytical techniques
Author(s)	Siderov, K
Year	2005
Abstract	This thesis reports on research that examines the early stage invasion process of Asparagus asparagoides (L.) W. Wight (bridal creeper), primarily a bird-dispersed weed, in a remnant vegetation patch. The study site is on Phillip Island, approximately 100 kilometres south east of Melbourne, Victoria. Asparagus asparagoides invasion of the remnant vegetation reserve is a relatively recent phenomenon. Landscape elements that affect bird dispersal and vegetation types that affect seedling establishment may be important factors that limit or enhance the spread of A. asparagoides. A systematic sampling strategy was adopted and data collected for a variety of landscape and vegetative variables including cover and abundance of A. asparagoides and the data were presented in a Geographic Information System (GIS). Preliminary results show that the distribution of A. asparagoides within a remnant vegetation patch is not random. It appears to have entered the reserve from two boundaries, spreading toward the centre, which to date remains sparsely colonised despite the capacity of this weed to spread rapidly over long distances by birds. A number of other outcomes are noted. Asparagus asparagoides establishment is prevented in pasture where sheep and cattle graze, and paddocks subjected to tillage practices. The exclusion of grazing in fenced off vegetation in pastures demonstrates rapid weed establishment and colonisation several hundred metres from main infestation. Field observation and visual inspection of temporal progress of invasion (using above ground weed density with tuber appearance to infer age) appear to suggest that invasion into remnant is associated with the track network. This age/density assumption is strengthened when spatial distribution is examined using a data set where low-density values for A. asparagoides are removed and compared with a data set using all A. asparagoides density values. The mapping of A. asparagoides in fenced off farm remnants suggests that velocity of spread at 191m/yr is a considerable underestimate. Subsequent analysis shows that the spatial distribution of A. asparagoides is not completely spatially random while intensity surface analysis highlights regions of low and high intensity located near track network. Mapping a density surface within GIS provided confirmatory evidence for the establishment of satellite clusters along the track network. The change in the intensity surface observed using the two data sets (lowdensity values and all density values) is also consistent with an expanding invasion occurring between two time periods. Spatial point pattern analysis using K-function statistics shows that xxii the clustering observed using GIS appears to be occurring at two scales or distances (130m- 160m and 195m-205m). The association between tracks and the invasion process observed in the initial stages of the study is examined. There is a change in density as a function of distance from a track where the density of A. asparagoides appears to reduce the further away from the track a site is and this relationship holds regardless of track width. The final stages of the study look at the development of a predictive model. Visual exploration of the data through mapping in a GIS and field observation made during data collection provide the starting point for the development of logistic models to estimate the probability of A. asparagoides presence. Finally the best overall logistic model is applied to a second independent site to determine the general applicability of the model. A number of variables that impact on the presence of A. asparagoides, particularly during the initial stages of the invasion process, are identified. While all the identified variables and the overall model are statistically significant, the model is found to correctly predict presence/absence in only 67% of cases overall. The model however could be expected to correctly predict the presence of A. asparagoides in 74% of cases and has a false positive rate of 40%. The model is applied at a second independent site and found to have an overall percent correct rate of 80% and correctly predicted A. asparagoides presence in 94% of cases. The variables identified as influential in the early stage of invasion are relatively easy to acquire by simple field survey that does not require specialist skills. When considering the model as a tool for the management of remnant vegetation communities, high false positive rates may lead to limited resources being spent on searching sites where there is no weed. However, a high false negative rate would have a larger impact on the management of the weed since the undetected infestations would form sources for new propagules. The model performs well from this point of view in that it provided low false negative rates at both sites. The value of the predictive model is its ability to provide managers with information regarding specific areas to target for weed eradication and management can use the model to assess the effectiveness of any control measures by going back to obtain new cover density data, then using the model to examine the changes over time. The model also provides a starting point for the development of a generic model of A. asparagoides invasion at sites outside of Phillip Island and could also provide the starting point for developing models that could be used for other bird-dispersed fleshy-fruited weed species.
Degree	PhD Thesis
Institution	RMIT University
School, Department or Centre	School of Mathematical and Geospatial Sciences
Keyword(s)	Noxious weeds - Victoria

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