|dc.description.abstract||The naturalisation and subsequent spread of non-indigenous plant species (NIPS) is a major problem for most regions of the world. Managing plant invasions requires greater understanding of factors that determine initial naturalisation and distribution of wild NIPS. By the year 2000, 2252 NIPS were recorded as wild (1773 fully naturalised and 479 casual) in New Zealand. From published literature and electronic herbaria records, I recorded year of discovery of wild populations, and regional distribution of these wild NIPS. I also recorded species related attributes hypothesised to affect naturalisation and/or distribution, including global trade, human activities, native range and biological data; and regional attributes hypothesised to affect distribution, including human population densities, land use/cover, and environmental data.
I used interval-censored time-to-event analyses to estimate year of naturalisation from discovery records, then analysed the importance of historical, human activity, biogeographical and biological attributes in determining patterns of naturalisation.
Typically, NIPS that naturalised earlier were herbaceous, utilitarian species that were also accidentally introduced and/or distributed, with a wide native range that included Eurasia, naturalised elsewhere, with a native congener in New Zealand.
In the year 2000, 28% of wild NIPS occupied only one region, 18% occupied two regions, decreasing incrementally to 2.5 % for nine regions, but with 13.5% occupying all ten regions. I used generalised linear models (GLMs) with binomial distribution to determine predictors of whether a wild NIPS occupied ten regions or not, and GLMs with Poisson distribution for wild NIPS occupying 0 – 9 regions. As expected, the dominant effect was that species discovered earlier occupied more regions. Utilitarian wild NIPS that were also accidentally introduced and/or distributed, and wild NIPS with a native congener tended to be more widely distributed, but results for other attributes varied between datasets.
Although numbers of wild NIPS recorded in regions of New Zealand were sometimes similar, composition of wild NIPS was often very different. I used nonmetric multidimensional scaling (NMDS) to determine dissimilarity in composition between regions. Then, after reducing correlation between predictor variables using principal
components analyses (PCAs), I tested the importance of regional variables in determining the regional composition of wild NIPS using metaMDS. The density of human populations best explained the dissimilarity in composition, but temperature gradients and water availability gradients were also important. In the year 2000 more than 1100 (60%) of the 1773 fully naturalised NIPS in mainland New Zealand had each been recorded in Northland/Auckland and Canterbury, and at the other end of the scale, Southland and Westland each had fewer than 500 (30%). I used GLMs to analyse the importance of people and environment in determining the numbers of wild NIPS in each region. Because I conducted multiple tests on the same dataset I used sequential Bonferroni procedures to adjust the critical P-value. Only human population density was important in explaining the numbers of NIPS in the regions. Overall, humans were the dominant drivers in determining the patterns of naturalisation and spread, although environment helps determine the composition of NIPS in regions. Incorporating human associated factors into studies of wild NIPS helps improve the understanding of the stages in the naturalisation and spread process.||en