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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Ecology of the naturalisation and geographic distribution of the non-indigenous seed plant species of New Zealand.

Gatehouse, Hazel A. W. January 2008 (has links)
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.
2

Determinants of the introduction, naturalisation, and spread of Trifolium species in New Zealand

Gravuer, Kelly January 2004 (has links)
Two conceptual approaches which offer promise for improved understanding of biological invasions are conceptualizing the invasion process as a series of distinct stages and explicitly incorporating human actions into analyses. This study explores the utility of these approaches for understanding the invasion of Trifolium (true clover) species in New Zealand. From the published literature, I collected a range of Trifolium species attributes, including aspects of global transport and use by humans, opportunistic association with humans in New Zealand, native range attributes, habitat characteristics, and biological traits. I also searched historical records to estimate the extent to which each species had been planted in New Zealand, a search facilitated by the enormous importance of Trifolium in New Zealand’s pastoral agriculture system. Regression analysis and structural equation modelling were then used to relate these variables to success at each invasion stage. Fifty-four of the 228 species in the genus Trifolium were intentionally introduced to New Zealand. Species introduced for commercial agriculture were characterised by a large number of economic uses and presence in Britain, while species introduced for horticulture or experimental agriculture were characterised by a large native range area. Nine of these 54 intentionally introduced species subsequently naturalised in New Zealand. The species that successfully naturalised were those that had been planted extensively by humans and that were well-matched to the New Zealand climate. A further 16 species (from the pool of 174 species that were never intentionally introduced) arrived and naturalised in New Zealand without any recorded intentional aid of humans. Several attributes appeared to assist species in unintentional introduction-naturalisation, including a good match to the New Zealand climate, a large native range area, presence in human-influenced habitats, a widespread distribution in Britain, and self-pollination capability. The 25 total naturalised species varied greatly in their current distributions and in the rates at which they had spread to achieve those distributions. Species that had spread quickly and are currently more widespread had been frequent contaminants in the pasture seed supply and have a long flowering period in New Zealand. Other biological traits and native range attributes played supporting roles in the spread process. Attributes facilitating success clearly varied among invasion stages. Humans played a dominant role at all stages of this invasion, although biological traits had increasing importance as a species moved through the invasion sequence. My findings suggest that incorporation of human actions and the stage-based framework provide valuable insight into the invasion process. I discuss potential avenues by which these approaches might be integrated into predictive invasion models.
3

Determinants of the introduction, naturalisation, and spread of Trifolium species in New Zealand

Gravuer, Kelly January 2004 (has links)
Two conceptual approaches which offer promise for improved understanding of biological invasions are conceptualizing the invasion process as a series of distinct stages and explicitly incorporating human actions into analyses. This study explores the utility of these approaches for understanding the invasion of Trifolium (true clover) species in New Zealand. From the published literature, I collected a range of Trifolium species attributes, including aspects of global transport and use by humans, opportunistic association with humans in New Zealand, native range attributes, habitat characteristics, and biological traits. I also searched historical records to estimate the extent to which each species had been planted in New Zealand, a search facilitated by the enormous importance of Trifolium in New Zealand's pastoral agriculture system. Regression analysis and structural equation modelling were then used to relate these variables to success at each invasion stage. Fifty-four of the 228 species in the genus Trifolium were intentionally introduced to New Zealand. Species introduced for commercial agriculture were characterised by a large number of economic uses and presence in Britain, while species introduced for horticulture or experimental agriculture were characterised by a large native range area. Nine of these 54 intentionally introduced species subsequently naturalised in New Zealand. The species that successfully naturalised were those that had been planted extensively by humans and that were well-matched to the New Zealand climate. A further 16 species (from the pool of 174 species that were never intentionally introduced) arrived and naturalised in New Zealand without any recorded intentional aid of humans. Several attributes appeared to assist species in unintentional introduction-naturalisation, including a good match to the New Zealand climate, a large native range area, presence in human-influenced habitats, a widespread distribution in Britain, and self-pollination capability. The 25 total naturalised species varied greatly in their current distributions and in the rates at which they had spread to achieve those distributions. Species that had spread quickly and are currently more widespread had been frequent contaminants in the pasture seed supply and have a long flowering period in New Zealand. Other biological traits and native range attributes played supporting roles in the spread process. Attributes facilitating success clearly varied among invasion stages. Humans played a dominant role at all stages of this invasion, although biological traits had increasing importance as a species moved through the invasion sequence. My findings suggest that incorporation of human actions and the stage-based framework provide valuable insight into the invasion process. I discuss potential avenues by which these approaches might be integrated into predictive invasion models.

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