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臺灣北部人爲活動與環境因子對外來植物多樣性之影響

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(1) . National Taiwan Normal University Department of Life Science Master Thesis. The effects of anthropogenic activities and environmental factors on naturalized flora in the Northern Taiwan. Author: Hao-Ting Sun Advisor: Dr. Shan-Huah Wu Dr. Teng-Chiu Lin. August 2009    .

(2)  . Abstract. To approach the effects of anthropogenic activities and environmental factors on local native and naturalized plant communities, this study was conducted in the Northern Taiwan. A total of 2,242 quadrats in 1m2 of 100 plots in 1km2 were sampled according to designated habitat types. Selected anthropogenic and environmental factors were obtained, and biodiversity indices were applied on the field data for further analyses. According to the results, habitat types with higher anthropogenic activities (e.g. roadside, cemetery, crop field) were highly invaded. Plant invasions were facilitated by anthropogenic activities (including both diversity and intensity) as well as environmental factors. Significantly positive relationships were found between anthropogenic activities (e.g. landscape heterogeneity, exploitation intensity, and agriculture factor) and the biodiversity and dominance of naturalized species. On the other hand, exploitation intensity was negatively correlated to native biodiversity. Propagule pressure and disturbances created by anthropogenic activities may be the major mechanism facilitating biodiversity and dominance of naturalized species. I   .

(3)  . Environmental factors including elevation-temperature and precipitation factors were negatively correlated to naturalized biodiversity but positively correlated to native biodiversity. Native—exotic richness relationships were also examined under different plot characteristics at same spatial scale. Negative relationships (more native less exotic) were found at plots with lower anthropogenic activities, while positive relationships (more native more exotic) were found at plots with higher anthropogenic activities. The mechanisms related to the native—exotic relationship transformation may be biotic resistance in negative relationships and abiotic factors including landscape heterogeneity in positive relationships. This result demonstrated the new evidence of how anthropogenic activities affect plant invasions and also made the current discussions in native—exotic richness relationships more comprehensive. These results can provide valuable direction in the management of naturalized plants.. Keywords: anthropogenic activities, biodiversity, environmental factors, naturalized plants, landscape heterogeneity, native—exotic richness relationships, Northern Taiwan, plant invasion II   .

(4)  . Contents Abstract .......................................................................................................................... I Contents ....................................................................................................................... III Figures..........................................................................................................................IV Tables ............................................................................................................................ V I. Introduction .......................................................................................................... 1 II. Materials and methods ................................................................................ 7 Terminology .......................................................................................................... 7 Study area ............................................................................................................. 8 Sampling design ................................................................................................. 11 Biodiversity and dominance of native and naturalized plants ...................... 12 Shannon diversity index (SHDI) ............................................................... 12 Species percentage ..................................................................................... 12 Frequency ................................................................................................... 13 Cover percentage........................................................................................ 13 Environmental factors ....................................................................................... 13 Anthropogenic activities .................................................................................... 14 Landscape heterogeneity ........................................................................... 14 Landscape fragmentation.......................................................................... 14 Land use type percentage .......................................................................... 15 Analyses .............................................................................................................. 17 III. Results ......................................................................................................... 21 Summary of the plant invasions in the Northern Taiwan .............................. 21 Biodiversity of habitat types ............................................................................. 24 Grouping ............................................................................................................. 30 The effects of factors .......................................................................................... 34 Native—exotic richness relationships .............................................................. 42 IV. Discussion.................................................................................................... 53 Plant invasions in different habitat types ........................................................ 53 The effects of anthropogenic and environmental factors on native and naturalized biodiversity ..................................................................................... 56 Native—exotic richness relationships .............................................................. 60 Conclusion .......................................................................................................... 65 V. References ........................................................................................................... 66 Appendix ..................................................................................................................... 71 III   .

(5)  . Figures.  . FIG. 1. Conceptual diagram of native-exotic richness relationships (NERR) analysis. ........................................................................................................................................ 4 FIG. 2. Study area and 100 survey plots. ..................................................................... 9 FIG. 3. Histogram of annual rainfall in study plots. .................................................. 10 FIG. 4. Histogram of average altitude in study plots ................................................. 10 FIG. 5. Flow chart of data management. .................................................................... 17 FIG. 6. The relationships between native richness and naturalized richness in 1km2 scale.............................................................................................................................. 27 FIG. 7. The relationships between the cover of native and naturalized species in 1km2 scale.............................................................................................................................. 28 FIG. 8. Scatter plot of landscape heterogeneity and naturalized species richness ..... 36 FIG. 9. Scatter plot of exploitation intensity and naturalized species richness.......... 37 FIG. 10. Scatter plot of agriculture factor and naturalized species richness .............. 38 FIG. 11. Scatter plot of elevation and naturalized species richness ........................... 39 FIG. 12. Scatter plot of annual rainfall and naturalized species richness .................. 40 FIG. 13. Cluster analysis of plots according to their anthropogenic activities. ......... 44 FIG. 14. Cluster analysis of plots according to their environmental factors.............. 47 FIG. 15. Cluster analysis of plots according to both of the anthropogenic and environmental factors................................................................................................... 50. IV   .

(6)  . Tables TABLE 1. Processes and their importance that may result in positive or negative native—exotic richness relationships (NERR) .............................................................. 5 TABLE 2. Naturalness discrimination ....................................................................... 16 TABLE 3. An example of standardize sampling plots when counting species richness ...................................................................................................................................... 19 TABLE 4. Dominant naturalized plants of different habitat types ............................ 23 TABLE 5. Numerical summary of six different habitats. .......................................... 25 TABLE 6. Correlation coefficients of native—exotic richness relationships in different habitat types at fine scale (1m2). ................................................................... 29 TABLE 7. Correlation coefficients of native—exotic richness relationships in different habitat types at broad scale (1km2). .............................................................. 29 TABLE 8. Groups of factor analysis on anthropogenic activities ............................. 31 TABLE 9. Groups of factor analysis on environmental factors ................................ 33 TABLE 10. Correlation analysis of factors and biodiversity indices of native and naturalized plants ......................................................................................................... 35 TABLE 11. Coefficient between groups of factors.................................................... 41 TABLE 12. Native—exotic richness relationships before cluster analysis ............... 42 TABLE 13. Native—exotic richness relationships of groups with different anthropogenic activity groups ...................................................................................... 45 TABLE 14. Native—exotic richness relationships of groups with different environmental factor groups. ....................................................................................... 48 TABLE 15. Native—exotic richness relationships of groups with different anthropogenic and environmental factors. ................................................................... 51 TABLE 16. The difference of cover percentage in two integrated plot groups ......... 52. V   .

(7)  . I. Introduction Anthropogenic activities have been related to plant invasions and different mechanisms have been revealed, e.g. increasing propagule pressure (Lonsdale 1999), disturbing native community (Sher and Hyatt 1999), and creating habitat fragmentation (Deutschewitz et al. 2003). Human mediated propagule pressure (the number and frequency of individuals released into a region to which they are not native), which has been acknowledged as one of the important determinants of plant invasion (Williamson 1996, Lockwood et al. 2005), might derived from human activities, such as horticulture/agriculture introduction cargo, local transportation, and tourism (Lonsdale 1999). They are often indirectly assessed by population density or percentage of human residence, industrial or agriculture area (Chytry et al. 2008). Many anthropogenic activities have the potential to disturb native plant community, e.g. agricultural activities, roads and buildings construction, and recreational activities (Hill et al. 2005). These disturbances cause by anthropogenic activities (anthropogenic disturbances, here after) may promote invasion via decreasing competition intensity that exotic species received or increasing the resource availability of exotic species. The latter mechanism known as fluctuating resource hypothesis (Davis et al. 2000). Habitat fragmentation has been shown to facilitate plant invasions by reducing native richness, promote generalist species, and increasing edge effects (Harrison and Bruna 1999, Alpert et al. 2000). Patch and edge density are often utilized to evaluate habitat 1   .

(8)  . fragmentation (Deutschewitz et al. 2003). Landscape heterogeneity resulted from various kind of anthropogenic activities has also been related to plant invasions in many cases (Deutschewitz et al. 2003, Kumar et al. 2006). It has been shown that higher habitat heterogeneity may support higher naturalized species richness as well as native species richness (Deutschewitz et al. 2003). The mechanisms were correlated to the propagule pressure, dispersal, resource availability, and fragmentation (Kumar et al. 2006). Beside landscape heterogeneity, type of land uses may be correlated to different levels of plant invasions as well (Hobbs and Humphries 1995, Austrheim et al. 1999). Environmental factors have been shown to be influential on successful plant invasions in terms of the invasibility (Rejmánek et al. 2005). They usually include elevation, temperature, and precipitation (Thuiller et al. 2006, Chytry et al. 2008, Pauchard et al. 2009). The relationships between altitude and invasion were one of the most often addressed links (Pauchard et al. 2009). Studies have revealed that the diversity of naturalized plants is often higher in lower elevations, probably due to the warm weather (Pauchard and Alaback 2004, Harrison et al. 2006, MacDougall et al. 2006). Harsh environments and lower anthropogenic activities at higher elevation probably represented habitat limitations for naturalized species. Habitats with rich precipitation and warm temperature are often more prone to invasions (Dukes and Mooney 1999, Pino et al. 2005). 2   .

(9)  . However, these studies are often conducted in relatively xeric environments; situation may be different in mesic regions. Since the native communities are often affected by anthropogenic activities and environmental factors, the relationships between native and naturalized richness may be influenced as well (Stadler et al. 2000, Deutschewitz et al. 2003). Native—exotic richness relationships (NERR) have been discussed widely across different spatial scales, and the varies assumptions regarding the susceptibility of invasions have been proposed (Levine and D'Antonio 1999). Negative NERR (Fig. 1a) are often addressed in studies with relatively fine scales (< 10m2) indicating a resistance performed by native species to plant invasions (Kennedy et al. 2002). One the contrary, positive NERR (Fig. 1b) are often demonstrated in studies with relative broad scales (> 1km2); implying the same species-area relationships performed by native and exotic plants (Stohlgren et al. 2003). One of the explanation is that competitive exclusion operates at fine scale but masked by other covarying factors (e.g. climate, habitat heterogeneity, substrate…) at broad scale (e. g. Shea and Chesson 2002). These processes may have different importance at different spatial scale. At fine scale, biotic resistance mainly operated and negative NERR demonstrated. At broad scale spatial variances become dominant and positive NERR demonstrated. The results from most studies were operated by several processes. Many factors operate the mechanisms of NERR (Table 1). However, no studies focus on the discussion about NERR at the same spatial 3   .

(10)  . scale yet. Here I further propose that native—exotic relationships may change at different anthropogenic factors or environmental factors even at same spatial scale.. b. a. FIG. 1. Conceptual diagram of native-exotic richness relationships (NERR) analysis. (a) Negative NERR, indicate rich native community can resist exotic plant invasion. (b) Positive NERR, areas with more native richness also harbor more exotic species.. 4   .

(11)  . TABLE 1. Processes and their importance that may result in positive or negative native—exotic richness relationships (NERR) at different spatial scales. Adapted from Fridley et al. (2007).. Process. Fine-scale importance. Broad-scale importance. Negative NERR 1) Statistical artifact. High. Low. 2) Eltonian biotic resistance. High. Low. 3) Invasional meltdown. High. High. Low. High. Low. High. Low. High. High. High. High. Low. Positive NERR 4) Neutral processes + spatial variance in community immigration rates 5) Neutral processes + spatial variance in disturbance rates 6) Niche processes: spatial environmental heterogeneity 7) Niche processes: biotic acceptance + non-equilibrium conditions 8) Facilitation (generalist). Notes: Neutral processes describe species with identical behaviors where properties of the habitat determine NERRs, while niche processes mandate that species respond differently to the environment.. 5   .

(12)  . Taiwan, with an average population density of 636 population per km2, is second only to Bangladesh in countries which area larger than 10,000 km2 (“List of countries and dependencies by population density”, 2009); Thus received high anthropogenic activities. Although attentions have been paid to plant invasions recently, the effects of anthropogenic activities and environmental factors on plant invasion remains unclear. The main purpose of this study is to understand the effects of these factors on plant invasion and four main questions were addressed: (1) How is the invasion status in different habitat type? (2) How do anthropogenic activities affect native and naturalized species? (3) How do environmental factors affect native and naturalized species? (4) Does the native—exotic richness relationships change (e.g. from negative to positive) with different site characteristics at same spatial scale?. 6   .

(13)  . II. Materials and methods Terminology Terms used in this study are defined as following: Disturbance means removal of competing vegetation (Hobbs 1991). Exotic plants means plant taxa in a given area whose presence there is due to intentional or accidental introductions as a result of human activity (Richardson et al. 2000). Invasibility means overall susceptibility of sites to invasion (Williamson 1996). Landscape heterogeneity is a structural property of landscapes that can be defined by the complexity and variability of ecological systems’ properties in space (Kumar et al. 2006). Naturalized plants are exotic plants that reproduce consistently (cf. casual alien plants) and sustain population over many life cycles without direct intervention by humans (or in spite of human intervention); they often recruit offspring freely, usually close to adult plants, and do not necessarily invade natural, seminatural or human-made ecosystems (Richardson et al. 2000). Propagule pressure means number of propagules arriving at a site (Williamson 1996).. 7   .

(14)  . Study area This study was conducted in the Northern Taiwan, Ranging from latitude 24°30' N to 25°28' N, longitude 120°86' E to 122°00' E (Fig. 2). Annual average temperature is about 22 degrees Celsius. In the warmest month, July, the average monthly temperature is about 28 degrees Celsius. In the coldest month, January, the monthly temperature is about 15 degrees Celsius. There are more than 2,000 millimeters of rainfall every year with no dry seasons (MacDonald 2009). Average annual rainfall of study plots are 3031 ± 935 mm (mean ± SD)(Fig. 3). And the maximum is 5386 mm; the minimum is 1559 mm. Average elevation are 308 ± 387 m (mean ± SD)(Fig. 4). And the maximum is 1887 m; the minimum is 0 m.. 8   .

(15)  . Study area. Tropic of Cancer. Map of Taiwan. ±. Study plots Elevation 50 - 301m 301m - 769m 769m - 1330m 1330m - 2003m 2003m - 3311m. FIG. 2.. 0 4 8. Study area and 100 survey plots.. 9   . 16. 24. 32 Kilometers.

(16)  . FIG. 3. Histogram of annual rainfall in study plots.. FIG. 4. Histogram of average altitude in study plots. 10   .

(17)  . Sampling design A total of 2,242 quadrats in 1m2 of 100 plots in 1km2 were sampled in the study area. The plots in 1km2 were randomly selected in the study area (Fig. 2). In each plot, six different land use types, including roadside, forest, crop field (Any types of the agriculture land use), abandoned field (Plant habitats abandoned after human exploitation), riparian, and cemetery, were classified. For each land use type in a particular plot, species and coverage of ten quadrats in 1m2 were collected. However, the number of quadrats were adjusted according to the field situation if necessary.. 11   .

(18)  . Biodiversity and dominance of native and naturalized plants Although the biodiversity and dominance of naturalized plants are considered as correlated (Stohlgren et al. 2002, Stohlgren et al. 2006). It is useful to separate them, for relevant analyses, since they may be influenced by different factors (Lundholm and Larson 2004). Both of biodiversity and dominance indices, which adapted from Brown and Peet (2003), were utilized to present the relationships between species and anthropogenic/environmental factors in this study. The biodiversity indices including richness and Shannon diversity index (SHDI), which is an often used biodiversity index. The dominance indices were species percentage, frequency, and cover percentage. Shannon diversity index (SHDI) This index changes with richness and individual numbers (or species cover). The computing formula is as following: m. SHDI = −∑ ( Pi × log Pi ) i =1. m=Total species richness Pi=The relative cover of each species Species percentage. Species percentage is percentage of either naturalized or native 12   .

(19)  . species number to total species number: number of naturalized or native species divided by total species number. In this study, the species percentage computed using species number values after standardization. Frequency. Frequency means the frequency of plots with naturalized (or native) species presented. In this study, this index was applied and examined whether this can appropriately reflect invasion status. Cover percentage. This parameter was used as a substitute of biomass (Lundholm and Larson 2004). In this study, relative cover of each naturalized (or native) species within each plot was recorded. Environmental factors. Environmental factors included temperature, precipitation, and elevation. The values of standard deviations were evaluated in order to present the spatial heterogeneity within each plot. Further factor analysis was performed to simplify variables and examines the relationships between environmental factors and species biodiversity (or species dominance). 13   .

(20)  . Anthropogenic activities. Three categories of anthropogenic activities were classified in this study, including landscape heterogeneity, landscape fragmentation, and different land use types. These factors were obtained using ArcGIS 9.3and FRAGSTATS(McGarigal et al. 2002). GIS as a useful tool in landscape studies, had been used widely (Deutschewitz et al. 2003, Gilbert and Lechowicz 2005, Chytry et al. 2008). Landscape heterogeneity. Two indicators were used to present landscape heterogeneity: land use richness and landscape SHDI. Orthophotograph in ArcGIS were used to distinguish different land use types. The formula of landscape SHDI is as following (Uuemaa et al. 2005): m. SHDI = −∑ ( Pi × log Pi) i =1. m=Total patch richness Pi=The relative area of each patch. Landscape fragmentation. Landscape fragmentation is comprised of two parameters: edge density and patch density. Edge density was total patch perimeter 14   .

(21)  . divided by area, and patch density means total patch numbers divided by area (Hargis et al. 1998).. Land use type percentage. Four indices were used to present land use type percentage, including built-up area percentage, crop field percentage, road length, and naturalness. Built-up area and crop field percentage were employed to present the effect of specific land use types due to their prevalence. Total road length and naturalness (Hsu 1994) were quantified as well for each plot. Naturalness represents the levels of nature status of each plant community (Table 2).. 15   .

(22)  . TABLE 2. Naturalness discrimination. Adapted from Hsu (1984). Naturalness level. Naturalness discrimination.. Naturalness 5. Primary or secondary forest.. Naturalness 4. Succession restricted to grassland due to local restrictions.. Naturalness 3. Forest plantation, grass land, and bamboo forest.. Naturalness 2. Human agriculture.. Naturalness 1. Non-vegetation zone caused by natural. Including river, rock, exposed area…. Naturalness 0. Non-vegetation zone due to anthropogenic activities. Including urban, road, airport…. 16   .

(23)  . Analyses. FIG. 5. Flow chart of data management.. 17   .

(24)  . Two spatial scales were employed in our study: fine scale (1m2) and broad scale (1km2), all analyses were performed at broad scales except the analyses of native—exotic richness relationships at both broad and fine scales. Since the land use type numbers were varied between plots, total quadrat numbers were uneven for all plots, standardization was applied to reduce the sample size effect (Williams et al. 2009). By performing standardization of the data, the average species numbers of ten quadrats per plot were calculated for all possible combination of extracted ten quadrats (Table 3) (Colwell et al. 2004). Nonparametric analyses were applied to the converted data afterwards. The importance value index for the herbaceous species was determined as the sum of the relative frequency and relative dominance (Curtis and Cottam 1962). Relative frequency = (frequency of the species/total frequency of all species) x 100. Relative dominance = (coverage of the species/total coverage of all species) x 100.. 18   .

(25)  . TABLE 3. An example of standardize sampling plots when counting species richness. Plot A. Plot B. Species 1 Species 2. Plot C. Plot D. Yes. Yes. Yes. Yes Four sampling plots. Species 3. Yes. Yes A~D and the occurrence. Species 4. Yes. Species 5. Yes Yes. Yes. of species 1~5. Yes. Count mean richness (estimated richness) for different sampling square numbers. One plot. Richness Two plots Richness Three plots Richness Four plots Richness. A. 3. A+B. 4. A+B+C. 5. B. 2. A+C. 5. A+B+D. 5. C. 2. A+D. 4. A+C+D. 5. D. 4. B+C. 3. B+C+D. 5. B+D. 5. C+D. 5. A+B+C+D. 5. Mean richness. 4.4. 4.3. 5. 19   . 5.

(26)  . Factor analyses were performed for site characteristics including anthropogenic activities and environmental factors to simplify variables (SPSS 15, 2006). Most factors in this study were not normally distributed; therefore, Spearman’s rank correlations were used to examine the relationships between variables. In order to examine native—exotic richness relationships under different site characteristics, TwoStep Cluster Analyses were utilized for grouping plots. Since the groups of cluster analysis have similar characteristics, it allowed us to reduce the complexities to approach native—exotic relationships under different site characteristics at same spatial scale.. 20   .

(27)  . III. Results Summary of the plant invasions in the Northern Taiwan. A total of 475 native plants and 139 naturalized plant species were recorded. Richness of native species was higher than that of naturalized species before and after standardization. Average native species numbers per plot before and after standardization were 31.34 ± 13.79 (mean ± SD) and 20.54 ± 8.76 (mean ± SD) respectively. On the other hand, average naturalized species numbers per plot before and after standardization were 13.56 ± 6.09 (mean ± SD) and 9.25 ± 3.47 (mean ± SD) accordingly. The mean cover of native plants is 51.26%, while that of naturalized plants is 48.74%.. 21   .

(28)  . According to the importance value index (IVI), the most dominant species were Bidens pilosa var. radiata Sch. Bip., Paspalum conjugatum Bergius, Ageratum houstonianum Mill., Ageratum conyzoides L., and Ipomoea cairica (L.) Sweet. Most. habitat types accommodated a single most dominant species: Bidens pilosa var. radiata Sch. Bip. (Table 4). The species composition of. forest was different from that of other habitat types. There were five naturalized species have importance value index higher than 10. The most dominant naturalized plant in forest is Setaria palmifolia (J. Konig) Stapf., followed by Ageratum houstonianum Mill., Bidens pilosa var. radiata Sch. Bip., Elephantopus mollis Kunth, and Impatiens walleriana Hook. f... 22   .

(29)  . TABLE 4. Rank 1 2 3 4 5 6 7. Rank 1 2 3 4 5 6 7. Rank 1 2 3 4 5 6 7. Dominant naturalized plants of different habitat types. Cemetery. Bidens pilosa Paspalum conjugatum Ipomoea cairica Wedelia trilobata Spermacoce latifolia Conyza sumatrensis Chamaesyce hirta. Roadside Bidens pilosa Ageratum houstonianum Paspalum conjugatum Ageratum conyzoides Ipomoea cairica Setaria palmifolia Panicum maximum. Abandoned field Bidens pilosa Paspalum conjugatum Ipomoea cairica Ageratum houstonianum Paspalum dilatatum Ageratum conyzoides Conyza sumatrensis. IVI 77.1 6.8 6.8 6.2 5.5 4.7 4.4. Crop field Bidens pilosa Ageratum conyzoides Paspalum conjugatum Ageratum houstonianum Spermacoce latifolia Alternanthera sessilis Alternanthera philoxeroides. IVI 65.9 8.7 8.2 7.0 5.7 5.5 5.5. Forest Setaria palmifolia Ageratum houstonianum Bidens pilosa Elephantopus mollis Impatiens walleriana Lantana camara Ageratum conyzoides. IVI 52.0 14.3 8.5 6.8 6.2 4.9 4.9. Riparian Bidens pilosa Pennisetum purpureum Paspalum conjugatum Wedelia trilobata Conyza sumatrensis Rumex crispus Paspalum dilatatum. 23   . IVI 48.8 15.5 13.6 10.4 9.0 8.2 7.0. IVI 35.3 25.2 15.8 13.2 11.7 9.9 9.4. IVI 70.0 11.6 10.3 9.1 7.6 7.5 6.8.

(30)  . Biodiversity of habitat types. Species numbers of native species were higher than those of naturalized species in all habitat types; however, different patterns of plant invasions were found among habitat types (Table 5). Roadside habitats have the largest number of naturalized plants, followed by abandoned field (79), crop field (75), cemetery (62), riparian (43), and forest (28). However, cemetery was the most infested habitat according to the percentage of naturalized species to all plants (45%), followed by abandoned field (38%), crop field (34%), riparian (30%), roadside (25%), and forest (10%).. 24   .

(31)  . TABLE 5. Numerical summary of six different habitats. Frequency: percentage of plots contain naturalized species (%), Cover: average percentage of naturalized cover (%), Richness: naturalized species number/total species number (%). Number of plots. Native. Naturalized. Habitat types. Frequency (%). Cover (%). Richness (%). sampled. richness. richness. Roadside. 936. 322. 110. 94. 54. 25. Crop field. 441. 147. 75. 97. 58. 34. Abandoned field. 332. 127. 79. 98. 51. 38. Forest. 223. 253. 28. 30. 11. 10. Riparian. 190. 98. 43. 90. 47. 30. Cemetery. 120. 77. 62. 99. 74. 45. 25   .

(32)  . Forests harbored significantly more native species, while riparian, abandoned field and cemetery had similar richness of native species and naturalized species (Fig. 6). As for cover, forest has significantly higher native species cover, while crop fields have generally higher naturalized species cover than native species (Fig. 7). The native—exotic richness relationships were different at fine and broad scales. At fine scale, crop field, abandoned field, and cemetery have significantly positive native—exotic relationships (Table 6). At broad scale, roadside, crop field, abandoned field and riparian have significantly positive native—exotic relationships (Table 7).. 26   .

(33)  . FIG. 6. The relationships between native richness and naturalized richness in 1km2 scale.. 27   .

(34)  . FIG. 7. The relationships between the cover of native and naturalized species in 1km2 scale.. 28   .

(35)  . TABLE 6. Correlation coefficients of native—exotic richness relationships in different habitat types at fine scale (1m2). N: sample size. Habitat. Correlation coefficients. P value. N. Roadside Crop field Abandoned field Forest Riparian Cemetery. 0.05 0.12* 0.14* 0.02 0.11 0.19*. 0.17 0.01 0.01 0.73 0.11 0.04. 936 441 332 223 190 120. *Correlation is significant at the 0.05 level (2-tailed).. TABLE 7. Correlation coefficients of native—exotic richness relationships in different habitat types at broad scale (1km2). N: sample size. Land use types. Correlation coefficients. P value. N. Roadside Crop field Abandoned field Forest Riparian Cemetery. 0.32* 0.38* 0.63* 0.19 0.72* 0.1. 0.01 0.01 0.01 0.34 0.01 0.76. 94 45 34 28 19 12. *Correlation is significant at the 0.05 level (2-tailed).. 29   .

(36)  . Grouping. According to factor analysis, three groups of anthropogenic factors can be categorized (Table 8), and they were named landscape heterogeneity, exploitation intensity, and agriculture groups. Landscape heterogeneity group contained factors, such as land use richness, land use SHDI, edge density, and patch density (38.10% of total variance). Exploitation intensity group, which included built-up area percentage, naturalness, and road length factor, explained 30.65% of total variance. Agriculture group explained 13.86% of total variance, and it mainly comprised of crop field percentage, also edge density and patch density.. 30   .

(37)  . TABLE 8. Groups of factor analysis on anthropogenic activities. Landscape Exploitation Agriculture Variables. loading. loading. loading. Communalities. Land use richness. 0.88. -0.17. -0.20. 0.84. Land use SHDI. 0.87. 0.21. 0.10. 0.81. Edge density. 0.71. -0.05. 0.61. 0.88. Patch density. 0.71. -0.10. 0.54. 0.81. Built-up area percentage. -0.21. 0.90. -0.21. 0.89. Crop field percentage. -0.02. 0.20. 0.89. 0.84. Naturalness. -0.07. -0.87. -0.18. 0.80. Road length. 0.07. 0.83. 0.21. 0.73. Eigen value. 3.05. 2.45. 1.11. Total variance explained. 38.10%. 30.65%. 13.86%. Cumulative variance explained. 38.10%. 68.75%. 82.61%. 31   .

(38)  . Environmental factors were classified into two groups (Table 9): elevation-temperature and precipitation. Elevation-temperature group contained both of elevation and temperature variables and explained 57.28% of total variance. Precipitation group were mainly correlated with annual average rainfall and rainfall standard deviation, and explained 26.18% total variance.. 32   .

(39)  . TABLE 9. Groups of factor analysis on environmental factors.. Variables. Elevation-temperature. Precipitation. group loading. group loading. Annual average temperature. Communalities. -0.91. -0.05. 0.83. Temperature standard deviation. 0.91. 0.13. 0.84. Average elevation. 0.92. 0.00. 0.85. Elevation standard deviation. 0.91. 0.12. 0.84. Annual average rainfall. 0.11. 0.91. 0.83. Rainfall standard deviation. 0.04. 0.90. 0.81. Eigenvalue. 3.44. 1.57. 5.01. Total variance explained. 57.28%. 26.18%. Cumulative variance explained. 57.28%. 83.46%. 33   .

(40)  . The effects of factors. Biodiversity and dominance of naturalized species were positively correlated with anthropogenic factors and negatively correlated with environmental factors (Table 10). On the contrary, biodiversity and dominance of native species were negatively correlated with anthropogenic factors and positively correlated with environmental factors. Among anthropogenic activity factors, only exploitation intensity was correlated with native diversity. The higher correlation coefficients were also appeared when examined relationships between exploitation intensity and native richness, or between elevation and native richness.. 34   .

(41)  . TABLE 10. Correlation analysis of factors and biodiversity indices of native and naturalized plants. Landscape: landscape heterogeneity factor, Exploitation: exploitation intensity factor, Elevation: elevation-temperature factor. Species %: species percentage, frequency %: frequency percentage, cover %: cover percentage. Values demonstrate Spearman correlation coefficients. Landscape. Exploitation Agriculture Elevation Precipitation. Exotic richness. 0.29*. 0.26*. 0.26*. -0.31*. -0.16. Native richness. -0.13. -0.48*. -0.01. 0.51*. 0.33*. Exotic SHDI. 0.28*. 0.23*. 0.22*. -0.20*. -0.21*. Native SHDI. 0.05. -0.24*. 0.09. 0.26*. 0.21*. Exotic species %. 0.25*. 0.53*. 0.15. -0.60*. -0.36*. Native species %. -0.25*. -0.53*. -0.15. 0.60*. 0.36*. Exotic frequency %. 0.30*. 0.23*. 0.12. -0.34*. -0.32*. Native frequency %. -0.17. -0.22*. -0.17. 0.29*. 0.33*. Exotic cover %. 0.25*. 0.28*. 0.19. -0.35*. -0.29*. Native cover %. -0.25*. -0.28*. -0.19. 0.35*. 0.29*. *Correlation is significant at the 0.05 level (2-tailed).. 35   .

(42)  . Naturalized species richness slightly increased with increasing landscape heterogeneity (Fig. 8), exploitation intensity (Fig. 9), and agriculture factor (Fig. 10). Environmental variables, elevation and annual rainfall, had negative correlation with naturalized species richness (Fig. 11 & 12).. FIG. 8. Scatter plot of landscape heterogeneity and naturalized species richness. Correlation coefficient = 0.29, p < 0.05.. 36   .

(43)  . FIG. 9. Scatter plot of exploitation intensity and naturalized species richness. Correlation coefficient = 0.26, p < 0.05.. 37   .

(44)  . FIG. 10. Scatter plot of agriculture factor and naturalized species richness. Correlation coefficient = 0.26, p < 0.05.. 38   .

(45)  . FIG. 11. Scatter plot of elevation and naturalized species richness. Correlation coefficient = -0.24, p < 0.05.. 39   .

(46)  . FIG. 12. Scatter plot of annual rainfall and naturalized species richness. Correlation coefficient = -0.21, p < 0.05.. 40   .

(47)  . Significant correlation was found between groups of factors (Table 11). Elevation-temperature and exploitation intensity were highly and negatively correlated. Precipitation and exploitation intensity were slightly and negatively correlated.. TABLE 11. Coefficient between groups of factors. Landscape: landscape heterogeneity factor, Exploitation: exploitation intensity factor, Elevation: elevation-temperature factor. Values demonstrate Spearman correlation coefficients. Landscape Exploitation Agriculture Landscape Exploitation. 1. Precipitation. 0.16. 0.05. -0.09. -0.13. 1. 0.09. -0.73*. -0.22*. 1. -0.11. -0.11. 1. 0.12. Agriculture Elevation Precipitation. 1. *Correlation is significant at the 0.05 level (2-tailed).. 41   . Elevation.

(48)  . Native—exotic richness relationships. Before cluster analysis, native species richness and naturalized species richness was not correlated (Table 12).. TABLE 12. Native—exotic richness relationships before cluster analysis. Native indices. Correlation coefficient of corresponding naturalized indices. Richness 1m. -0.03. Richness 1km. -0.01. *Correlation is significant at the 0.05 level (2-tailed).. According to cluster analysis, the plots were separated into four groups (Fig. 13), and these groups were characterized with different anthropogenic factors. These four groups included high exploitation group, high heterogeneity group, low anthropogenic activity group, and high agriculture group. They were highly associated with high exploitation intensity, high landscape heterogeneity, low anthropogenic activities, and high agriculture activities respectively.. 42   .

(49)  . Native—exotic relationships moved from negative to positive along with increasing anthropogenic activities at fine scale (Table 13). Low anthropogenic activity group demonstrated negative native—exotic richness relationship, while positive relationships were found for higher anthropogenic activity groups, including high agriculture group and high landscape heterogeneity group. However, similar trend was not found at broader scale.. 43   .

(50)  . 3. Landscape heterogeneity. 2.5. Indicies after standardization. 2. Exploitation intensity. 1.5. Agriculture. 1 0.5 0 ‐0.5 ‐1 ‐1.5 ‐2. High High Low High exploitation heterogeneity anthropogenic agriculture N=15 N=33 activities N=18 N=34 FIG. 13. Cluster analysis of plots according to their anthropogenic activities. The values in Y-axis had been standardized in factor analysis. Error bars indicate means ± standard deviation.. 44   .

(51)  . TABLE 13. Native—exotic richness relationships of groups with different anthropogenic activity groups. Correlation coefficients of native vs. naturalized plants including native richness 1m2 vs. naturalized richness 1m2, and native richness 1km2 vs. naturalized richness 1km2 at different groups were shown. Naturalized indices High. High. Low. High. exploitation. heterogeneity. anthropogenic. agriculture. group. group. activities. group. Native indices. group. Richness 1m2. -0.05. 0.11*. -0.23*. 0.10*. Richness 1km2. 0.34. 0.32. -0.18. 0.24. *Correlation is significant at the 0.05 level (2-tailed).. 45   .

(52)  . According to cluster analysis, the plots were separated into three groups (Fig. 14), and these groups were characterized with different environmental factors. These three groups include low elevation and precipitation group, high precipitation group, and high elevation group. They were highly associated with low elevation and precipitation, high precipitation, and high elevation respectively. Native—exotic relationships moved from negative to positive along with decreasing precipitation at fine scale (Table 14). High precipitation group demonstrated negative native—exotic richness relationship, while positive relationship was found in low elevation and precipitation group. Positive native—exotic relationship was also found at broad scale in low elevation and precipitation group.. 46   .

(53)  .  . Indices after standardization. 2.5 2 1.5. Elevation-temperature Precipitation. 1 0.5 0 ‐0.5 ‐1 ‐1.5. Low elevation & High precipitation precipitation group group N=34 N=42. High elevation group N=24. FIG. 14. Cluster analysis of plots according to their environmental factors. The values in Y-axis had been standardized in factor analysis. Error bars indicate means ± standard deviation.. 47   .

(54)  . TABLE 14. Native—exotic richness relationships of groups with different environmental factor groups. Correlation coefficients of native vs. naturalized plants including native richness 1m2 vs. naturalized richness 1m2, and native richness 1km2 vs. naturalized richness 1km2 at different groups were shown. Naturalized indices. Native indices. Low elevation &. High. High. precipitation. precipitation. elevation. group. group. group. Richness 1m2. 0.10*. -0.09*. -0.08. Richness 1km2. 0.36*. -0.18. -0.03. *Correlation is significant at the 0.05 level (2-tailed).. 48   .

(55)  . Two groups of plots were categorized (Fig. 15) by employing both of the anthropogenic and environmental factors, integrated high anthropogenic activities with low elevation group and integrated low anthropogenic activities with high elevation group. Native—exotic relationships moved from negative to positive along with increasing anthropogenic activities and decreasing elevation at fine scale (Table 15). Integrated low anthropogenic activities with high elevation group demonstrated negative native—exotic richness relationship, while positive relationship was found in integrated high anthropogenic activities with low elevation group. Positive native—exotic relationship was also found at broad scale in integrated high anthropogenic activities with low elevation group.. 49   .

(56)  . 2.5. 2. Landscape heterogeneity Exploitation intensity Agriculture. Indicies after standardization. 1.5. Elevation-temperature Precipitation. 1. 0.5. 0. ‐0.5. ‐1. ‐1.5. Integrated high anthropogenic activities N=60. Integrated low anthropogenic activities N=40. FIG. 15. Cluster analysis of plots according to both of the anthropogenic and environmental factors. The values in Y-axis had been standardized in factor analysis. Error bars indicate means ± standard deviation..        . 50   .

(57)  . TABLE 15. Native—exotic richness relationships of groups with different anthropogenic and environmental factors. Correlation coefficients of native vs. naturalized plants including native richness 1m2 vs. naturalized richness 1m2, and native richness 1km2 vs. naturalized richness 1km2 at different groups were shown.. Naturalized indices. Native indices. Integrated. Integrated. high anthropogenic. low anthropogenic. activities with low. activities with high. elevation group. elevation group. Richness 1m2. 0.09*. -0.18*. Richness 1km2. 0.36*. -0.18. *Correlation is significant at the 0.05 level (2-tailed).. 51   .

(58)  . Integrated high anthropogenic activities group had higher naturalized species cover percentage than integrated low anthropogenic activities group, but native species cover percentage and total cover percentage were higher in integrated low anthropogenic activities group than high anthropogenic activities group (Table 16).. TABLE 16. The difference of cover percentage in two integrated plot groups. The average total cover percentage, average native cover percentage, average naturalized cover percentage at integrated high anthropogenic activities with low elevation group and integrated low anthropogenic activities with high elevation group. Using ANOVA to examine the significant level between two groups. Demonstrate average ± standard error. * indicates the significant differences at 0.05 significant level. Total cover. Native cover. Naturalized cover. High anthropogenic activities. 89.1 ± 2.5. 40.3 ± 2.9. 48.8 ± 2.5. Low anthropogenic activities. 98.4 ± 3.1. 60.5 ± 3.6. 38 ± 3. 0.02*. <0.01*. <0.01*. P values. 52   .

(59)  . IV. Discussion Plant invasions in different habitat types. Habitat types received relatively higher anthropogenic activities are more vulnerable to plant invasions (Table 5). Propagule pressure may be the main mechanism promoting plant invasions in habitats with relatively high anthropogenic activities (Lockwood et al. 2005). For example, achenes of Bidens pilosa L. var. radiata may adhere to clothing and disperse with human activities. Besides, resource availability after disturbance may facilitate plant invasions as well (Davis et al. 2000). Highest naturalized species frequency, cover, and species percentage found in the cemetery habitats may be this case, since it usually has annual disturbances, including uprooting, prescribed fire, tramping, and herbicide application, during the memorial month in April. Although anthropogenic activities may facilitate plant invasions, natural disturbances may also induce invasions. Riparian habitat, which suffers from frequent natural disturbances, is the case (Table 5; Hood and Naiman 2000). Anthropogenic disturbances may introduce exotic species to riparian zones, and natural disturbances may 53   .

(60)  . facilitate their spread (Hood and Naiman 2000). On the other hand, the low invasion in forest habitat may partly due to it generally received relatively lower anthropogenic activities, since forests were still retained natural plant community comparable to abandoned field, crop field, or cemetery. Lower anthropogenic activities may correlate to lower propagule pressure and lower anthropogenic disturbance (Alston and Richardson 2006), which may result in decreased plant invasions. Beside natural or anthropogenic disturbances, environmental factors, such as light intensity may function as well. Forest was the only low light availability environment in this study, but the dominant naturalized plants in other habit types (e.g. Bidens pilosa var. radiata) are often the species adapt to open canopy with full sunlight (Table 4). Even if these species enters forest, they may have less competition advantage due to environment intolerance (Williamson 1996). But we have to be cautious, once the propagule pressure from surrounding habitats are large enough, even the species with poor adaptation can also invade forest (Rejmánek 1989). For example, Bidens pilosa var. radiata was the third dominant species in 54   .

(61)  . forest (Table 4), this demonstrated that the environmental intolerant naturalized species can still invade once the propagule pressure is large enough. Fewer exotic plants have good adaptation to forest (e.g. Setaria palmifolia and Elephantopus mollis), and these species have. relatively fewer propagule pressure than species which have good adaptation to open canopy with full sunlight (e.g. Bidens pilosa var. radiata and Ipomoea cairica); plant invasions may have time lag. (Banasiak and Meiners 2009) in this case. There were also studies indicate that plant invasion were serious in forest with higher anthropogenic disturbance (Vitousek 1990, Meyer and Florence 1996); But in this study, we did not distinguish between forests that received higher or lower anthropogenic activity thus we cannot examine the effects of different anthropogenic activities on plant invasion in forest. In Taiwan, the invasion process in forest still needs to be further addressed. According to the native—exotic richness relationships at different habitats (Table 6 and Table 7), no negative relationships were demonstrated. This means no habitats demonstrated biotic resistance. These results may suggest that even the lowest invaded habitat 55   .

(62)  . type—forest, should aware of further invasion in the future.  . The effects of anthropogenic and environmental factors on native and naturalized biodiversity. The positive correlations between anthropogenic factors and naturalized biodiversity and dominance (Table 10), implied the facilitative effects of anthropogenic activities on plant invasions. Among anthropogenic factors, landscape heterogeneity as well as habitat fragmentation are both associated with plant invasion, they may influence habitat diversity, propagule pressure, dispersal, and resource availability (Deutschewitz et al. 2003, Kumar et al. 2006); for example, habitat diversity may support higher naturalized species richness. These may explain the increased plant invasion with higher landscape heterogeneity in this study. The negative effects of anthropogenic activities on native communities (Table 10) are probably due to habitat destruction (Vitousek et al. 1997). Exploitation intensity is the anthropogenic factor that can reflect habitat destruction since it mainly comprised the built-up area percentage (Table 8). This is also the only factor 56   .

(63)  . significantly detrimental to native species richness (Table 10). Propagule pressure may be elevated by anthropogenic activities and result in plant invasions afterwards (Lockwood et al. 2005). Although propagule pressure cannot be measured directly, factors used in this study including landscape heterogeneity, fragmentation, built-up area percentage, and road length can all be the proxy measures of propagule pressure (Chytry et al. 2008) and these were positively correlated to naturalized species richness (Table 8 and Table 10). Furthermore, anthropogenic disturbance (e.g. habitat destruction) may also enhance plant invasion, since naturalized species richness percentage were positively correlated to exploitation intensity (Table 8 and Table 10). The results of elevation-temperature factor on biodiversity (Table 10) were mainly affected by anthropogenic activities. According to Hsieh (2002), highest native plant richness situated at low elevation in Taiwan. However, the highest native richness appeared at higher elevation in this study, this result can be attributed to lower anthropogenic activities at higher elevation (Table 11). Lower anthropogenic activities cause less habitat destruction to 57   .

(64)  . native community. The results demonstrated that naturalized species richness decrease with increasing elevation (Table 10), which is consistent with previous studies (Stohlgren et al. 2002, Pauchard and Alaback 2004, Becker et al. 2005, Daehler 2005, McDougall et al. 2005). This may be relevant to four main factors previous studies proposed (Pauchard et al. 2009): (1) adaptation of naturalized plants to abiotic conditions, (2) disturbances especially anthropogenic disturbances, (3) biotic resistance of native community, (4) propagule pressure of naturalized plants. In this study, the results can mainly be attributed to (2) disturbance and (4) propagule pressure, these factors are highest at lowland where anthropogenic activities are high (Table 11). Also, the results can be attributed to poor adaptation of naturalized plants at higher elevation. Naturalized plants may have poor adaptation at higher elevation because they have higher chance to be transported to lowland and adapted to there (Becker et al. 2005). After exotic plants adapted to lowland, they became less adapted to higher elevation and may result in lower invasion at higher elevation. Also, most naturalized plants in Taiwan comes from tropical zones (Wu et al. 2004); fewer naturalized plants comes from temperate 58   .

(65)  . zones. Which suggest that fewer species have good adaptation at higher elevation comparable to lower elevation. We did not think abiotic conditions be harsh enough to constraint naturalized species (McDougall et al. 2005) in this study because the highest elevation only reaches 2000m (Fig. 4) where are no snow and still have long growing seasons. The results of precipitation factor on biodiversity (Table 10) were not consistent with most previous studies (e.g. Dukes and Mooney 1999). Most previous studies situated in arid or semi-arid zones, and demonstrated that areas with higher precipitation were more invaded. Nevertheless, there were also explanation about wet terrestrial habitats and its invasibility (Rejmánek et al. 2005): “Wet terrestrial habitats do not provide resources – mainly light – for invaders because of fast growth and high competitiveness of resident species.” This explanation based on the fact that net primary production increase with precipitation (e.g. Williams et al. 2005), but according to the study in Hawaii (Schuur and Matson 2001, Austin 2002), net primary production had no observed increase with precipitation when annual rainfall higher than 2000mm. Even more, primary production 59   .

(66)  . may be lower at highest rainfall. In this study, average annual precipitation higher than 3000 mm (Fig. 3) where increase in precipitation cannot increase primary production any further. The explanation about precipitation—productivity does not fit in this study. Instead, reasonable explanation is that characteristics of naturalized plants had poor adaptation to highest rainfall area in Taiwan. Poor adaptation of naturalized plants to extremely wet habitats may lower the plant invasions in Taiwan but this hypothesis needs to be further examined.. Native—exotic richness relationships. The negative native—exotic richness relationships in lower anthropogenic activities group at fine scale (Table 13 and Table 15) may be explained by biotic resistance: the diversity of native community can provide resistance to exotic plant invasion (e.g. Levine and D'Antonio 1999). Biotic resistance is the most possible process among three processes contributed to negative native—exotic richness relationships (Table 1) because (1) the negative relationships were consistently appeared in plot groups with lower anthropogenic activities which may not simply due to statistical artifact (2) the plant 60   .

(67)  . invasions were lowest in plot groups with lower anthropogenic groups where invasional meltdown was not possible to take place. The positive relationships were much more complicated to explain. First, biotic resistance disappeared at higher anthropogenic activities. Second, some abiotic factors affected both native and naturalized plants at higher anthropogenic activities (may simultaneously have higher landscape heterogeneity). Although landscape heterogeneity provides more habitat diversity and can comprise more species richness (Kumar et al. 2006), this is not the case in this study because landscape heterogeneity only had positive relationships with naturalized plants but had no relationships with native plants (Table 10). There was no evidence that landscape heterogeneity favors both native and naturalized plants. No directly effects of landscape heterogeneity can explain positive relationships. Here, I propose two compatible hypotheses that may operate indirectly to result in positive relationships. First one is propagule pressure. Different landscape heterogeneity may have different propagule pressure (higher heterogeneity may have higher disturbance and enhance immigration rate, Fridley et al. 2007), and 61   .

(68)  . result in the same directional change of native and naturalized plants. But the magnitudes of landscape heterogeneity and propagule pressure are not exactly equals. Propagule pressure affected by many factors including plant distribution, distance to river, plantation, anthropogenic activities facilitate dispersal, and habitat destruction …(Lonsdale 1999, Chytry et al. 2008). Landscape heterogeneity only reflects part of propagule pressure; this is why positive relationships occur at higher landscape heterogeneity and no evidence that landscape heterogeneity can favor both native and exotic plants. The second explanation is the unsaturated native communities. The niche saturation effect (Moore et al. 2001, Gilbert and Lechowicz 2005, Fridley et al. 2007, Stohlgren et al. 2008) proposed that when niche is saturated then no empty niche exists and immigration is difficult. In the contrary, sites with higher landscape heterogeneity are harder to be fully occupied (unsaturated) by relatively constrained species pool (Fridley et al. 2007). If the niche is unsaturated, native species and naturalized species are easily to immigrant and richness may increase simultaneously. Some evidence in this study can support this hypothesis (Table 16). Integrated high 62   .

(69)  . anthropogenic activities with low elevation group have lower total cover percentage and native cover percentage than integrated low anthropogenic activities with high elevation group. Indicate the plant community is less saturated at higher anthropogenic activities. These two explanations: propagule pressure and unsaturated communities may be the cause of positive native—exotic relationships at sites with higher landscape heterogeneity. The results of native—exotic richness relationships at different environmental groups (Table 14) suggest that higher precipitation may help native community to limit exotic plant invasion. And may imply that biotic resistance was not the reason why plots with higher elevation were less invaded. Anthropogenic activities may still be the most important determinant on plant invasion at higher elevation in this study. The results of native—exotic richness relationships at different spatial scale were consistent with previous studies (Richardson and Pysek 2006): positively relationships mainly at broad scale and negative relationships at fine scale (Table 14 and Table 15). The explanation should be careful as Fridey et al. (2007) concluded: 63   .

(70)  . “natively rich ecosystems are likely to be hotspots for exotic species, but the reduction of local species richness can further accelerate the invasion of these and other vulnerable habitats.” The mechanisms affect native—exotic richness relationships at different plot characteristics and different spatial scales are similar: “biotic” or “abiotic”. Negative relationships result from biotic resistance; positive relationships result from abiotic factor (e.g. landscape heterogeneity). Also, disappear of negative relationships may suggest the disappearance of biotic resistance and may promote further plant invasion.. 64   .

(71)  . Conclusion. In summary of all the results and discussions, the most important process of plant invasion comes from anthropogenic activities which lead to increase propagule pressure. Also, anthropogenic activities cause disturbance to native community which decrease native biodiversity and dominance. This made biotic resistance disappear and resource availability increase. In this case, the relative dominance of naturalized species increased considerably. This can explain that some habitats (e.g. cemetery and plots with high exploitation intensity) were seriously invaded. The areas where contain many different habitat types inevitably cause habitat destruction to native species, so the heterogeneity cannot enhance native diversity. But the area with higher landscape heterogeneity will be much unlikely to be saturated and have open opportunity for native and naturalized species to immigrant. This may interact with propagule pressure to result in positive native—exotic richness relationships. Environmental factors have relatively smaller effects than anthropogenic activities, but the effects were still significant. The processes may be relevant to adaptation and competition. 65   .

(72)  . V. References Alpert, P., E. Bone, and C. Holzapfel. 2000. Invasiveness, invasibility and the role of environmental stress in the spread of non-native plants. Perspectives in Plant Ecology, Evolution and Systematics 3:52-66. Alston, K. P. and D. M. Richardson. 2006. The roles of habitat features, disturbance, and distance from putative source populations in structuring alien plant invasions at the urban/wildland interface on the Cape Peninsula, South Africa. Biological Conservation 132:183-198. Austin, A. T. 2002. Differential effects of preciptation on production and decomposition along a rainfall gradient in hawaii. Ecology 83:328-338. Austrheim, G., E. Gunilla, A. Olsson, and E. Grontvedt. 1999. Land-use impact on plant communities in semi-natural sub-alpine grasslands of Budalen, central Norway. Biological Conservation 87:369-379. Banasiak, S. and S. Meiners. 2009. Long term dynamics of Rosa multiflora in a successional system. Biological Invasions 11:215-224. Becker, T., H. Dietz, R. Billeter, H. Buschmann, and P. J. Edwards. 2005. Altitudinal distribution of alien plant species in the Swiss Alps. Perspectives in Plant Ecology, Evolution and Systematics 7:173-183. Brown, R. L. and R. K. Peet. 2003. Diversity and invasibility of southern appalachian plant communities. Ecology 84:32-39. Chytry, M., V. Jarosik, P. Pysek, O. Hajek, I. Knollova, L. Tichy, and J. Danihelka. 2008. Separating habit invasibility by alien plants from the actual level of invasion. Ecology 89:1541-1553. Colwell, R. K., C. X. Mao, and J. Chang. 2004. Interpolating, extrapolating ,and comparing incidence-based species accumulation curves. Ecology 85:2717-2727. Curtis, J. T. and G. Cottam. 1962. Plant ecology workbook: laboratory field and. reference manual. Burgess Publishing Co., Minneapolis. Daehler, C. C. 2005. Upper-montane plant invasions in the Hawaiian Islands: Patterns and opportunities. Perspectives in Plant Ecology, Evolution and Systematics 7:203-216. Davis, M. A., J. P. Grime, and K. Thompson. 2000. Fluctuating Resources in Plant Communities: A General Theory of Invasibility. The Journal of Ecology 88:528-534. Deutschewitz, K., A. Lausch, I. Kühn, and S. Klotz. 2003. Native and alien plant species richness in relation to spatial heterogeneity on a regional scale in Germany. Global Ecology & Biogeography 12:299-311. 66   .

(73)  . Dukes, J. S. and H. A. Mooney. 1999. Does global change increase the success of biological invaders? Trends in Ecology & Evolution 14:135-139. Fridley, J. D., J. J. Stachowicz, S. Naeem, D. F. Sax, E. W. Seabloom, M. D. Smith, T. J. Stohlgren, D. Tilman, and B. V. Holle. 2007. The invasion paradox : reconciling pattern and process in species invasions. Ecology 88:3-17. Gilbert, B. and M. J. Lechowicz. 2005. Invasibility and abiotic gradients :the. positive correlation between native and exotic plant diversity. Ecology 86:1848-1855. Hargis, C. D., J. A. Bissonette, and J. L. David. 1998. The behavior of landscape. metrics commonly used in the study of habitat fragmentation. Landscape Ecology 13:167-186. Harrison, S. and E. Bruna. 1999. Habitat fragmentation and large-scale conservation: what do we know for sure? Ecography 22:225-232. Harrison, S., J. B. Grace, K. F. Davies, H. D. Safford, and J. H. Viers. 2006. Invasion in a diversity hotspot: exotic cover and native richness in the California serpentine flora. Ecology 87:695-703. Hill, S. J., P. J. Tung, and M. R. Leishman. 2005. Relationships between anthropogenic disturbance, soil properties and plant invasion in endangered Cumberland Plain Woodland, Australia. Austral Ecology 30:775-788. Hobbs, R. J. 1991. Disturbance a precursor to weed invasion in native vegetation.. Plant Protection Quarterly 6:99-104. Hobbs, R. J. and S. E. Humphries. 1995. An Integrated Approach to the Ecology and Management of Plant Invasions. Conservation Biology 9:761-770. Hood, W. G. and R. J. Naiman. 2000. Vulnerability of riparian zones to invasion by exotic vascular plants. Plant Ecology 148:105-114. Hsu, K.-S., T.-T. Lin, Y.-F. Chen, and S.-Y. Lu. 1984. Taroko National Park plant ecology resources report. Construction and Planning Agency Ministry of the Interior. Kennedy, T. A., S. Naeem, K. M. Howe, J. M. H. Knops, D. Tilman, and P. Reich. 2002. Biodiversity as a barrier to ecological invasion. Nature 417:636-638. Kumar, S., T. J. Stohlgren, and G. W. Chong. 2006. Spatial heterogeneity. influences native and nonnative plant species richness. Ecology 87:3186-3199. Levine, J. M. and C. M. D'Antonio. 1999. Elton revisited: a review of evidence. linking diversity and invasibility. Oikos 87:15-26. 67   .

(74)  . List of countries and dependencies by population density. (2009, July 26). In Wikipedia, the free encyclopedia. Retrieved July 28, 2009, from http://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_po pulation_density Lockwood, J. L., P. Cassey, and T. Blackburn. 2005. The role of propagule pressure in explaining species invasions. Trends in Ecology & Evolution 20:223-228. Lonsdale, W. M. 1999. Global Patterns of Plant Invasions and the Concept of. Invasibility. Ecology 80:1522-1536. Lundholm, J. T. and D. W. Larson. 2004. Dominance As An Overlooked Measure of Invader Success. Biological Invasions 6:505-510. MacDonald, J. E. (2009). Taiwan. Grolier Multimedia Encyclopedia. Retrieved July 28, 2009, from Grolier Online http://gme.grolier.com/cgi-bin/article?assetid=0283210-0 MacDougall, A. S., J. Boucher, R. Turkington, G. E. Bradfield, and V. D. Pillar. 2006. Patterns of plant invasion along an environmental stress gradient. Journal of Vegetation Science 17:47-56. McDougall, K. L., J. W. Morgan, N. G. Walsh, and R. J. Williams. 2005. Plant invasions in treeless vegetation of the Australian Alps. Perspectives in Plant Ecology, Evolution and Systematics 7:159-171. McGarigal, K., S. A. Cushman, M. C. Neel, and E. Ene. 2002. FRAGSTATS: spatial pattern analysis program for categorical maps. University of Massachusetts, Amherst. McIntyre, S. and R. Hobbs. 1999. A Framework for Conceptualizing Human Effects on Landscapes and Its Relevance to Management and Research Models. Conservation Biology 13:1282-1292. Meyer, J.-Y. and J. Florence. 1996. Tahiti's native flora endangered by the invasion of Miconia calvescens DC. (Melastomataceae). Journal of Biogeography 23:775-781. Moore, J. L., N. Mouquet, J. H. Lawton, and M. Loreau. 2001. Coexistence, saturation and invasion resistance in simulated plant assemblages. Oikos 94:303-314. Pauchard, A. and P. B. Alaback. 2004. Influence of Elevation, Land Use, and. Landscape Context on Patterns of Alien Plant Invasions along Roadsides in Protected Areas of South-Central Chile. Conservation Biology 18:238-248. Pauchard, A., C. Kueffer, H. Dietz, C. C. Daehler, J. Alexander, P. J. Edwards, J.. R. Arevalo, L. A. Cavieres, A. Guisan, S. Haider, G. Jakobs, K. 68   .

(75)  . McDougall, C. I. Millar, B. J. Naylor, C. G. Parks, L. J. Rew, and T. Seipel. 2009. Ain't no mountain high enough: plant invasions reaching new elevations. Frontiers in Ecology and the Environment 7. Pino, J., X. Font, J. Carb, M. Jov, and L. Pallares. 2005. Large-scale correlates of alien plant invasion in Catalonia (NE of Spain). Biological Conservation 122:339-350. Rejmánek, M. 1989. Invasibility of plant communities. Pages 369-388 in J. A.. Drake, H. A. Mooney, F. di Castri, R. H. Groves, F. J. Kuruger, M. Rejmánek, and M. Willams, editors. Biological invasions: a global perspective. John Wiley & Sons, Chichester. Rejmánek, M., D. M. Richardson, and P. Pysek. 2005. Plant invasions and invasibility of plant communities. Pages 332-355 in E. v. d. Maarel, editor. Vegetation ecology. Blackwell, Oxford. Richardson, D. M. and P. Pysek. 2006. Plant invasions: merging the concepts of species invasiveness and community invasibility. Progress in Physical Geography 30:409-431. Richardson, D. M., P. Pysek, M. Rejmanek, M. G. Barbour, F. D. Panetta, and C. J. West. 2000. Naturalization and Invasion of Alien Plants: Concepts and Definitions. Diversity and Distributions 6:93-107. Schuur, E. and P. Matson. 2001. Net primary productivity and nutrient cycling across a mesic to wet precipitation gradient in Hawaiian montane forest. Oecologia 128:431-442. Shea, K. and P. Chesson. 2002. Community ecology theory as a framework for biological invasions. Trends in Ecology & Evolution 17:170-176. Sher, A. A. and L. A. Hyatt. 1999. The disturbed resource-flux invasion matrix: a new framework for patterns of plant invasion. Biological Invasions 1:107-114. Smith, R. L. and T. M. Smith. 2002. Elements of ecology. Fifth edition edition.. Benjamin Cummings, San Francisco. SPSS for Windows, Rel. 15.0.0. 2006. Chicago: SPSS Inc Stadler, J., A. Trefflich, S. Klotz, and R. Brandl. 2000. Exotic plant species invade diversity hot spots: the alien flora of northwestern Kenya. Ecography 23:169-176. Stohlgren, T. J., D. T. Barnett, C. S. Jarnevich, C. Flather, and J. Kartesz. 2008. The myth of plant species saturation. Ecology Letters 11:313-322. Stohlgren, T. J., D. T. Barnett, and J. T. Kartesz. 2003. The rich get richer: patterns of plant invasions in the United States. Frontiers in Ecology and the Environment 1:11-14. 69   .

(76)  . Stohlgren, T. J., G. W. Chong, L. D. Schell, K. A. Rimar, Y. Otsuki, M. Lee, M. A. Kalkhan, and C. A. Villa. 2002. Assessing Vulnerability to Invasion by Nonnative Plant Species at Multiple Spatial Scales. Environmental Management 29:566-577. Stohlgren, T. j., C. Jarnevich, G. W. Chong, and P. H. Evangelista. 2006. Scale and plant invasions: a theory of biotic acceptance. Preslia 78:405-426. Thuiller, W., D. M. Richardson, M. Rouget, S. Proches, and J. R. U. Wilson. 2006. Interactions between environment, species traits, and human uses describe patterns of plant invasions. Ecology 87:1755-1769. Uuemaa, E., J. Roosaare, and U. Mander. 2005. Scale dependence of landscape metrics and their indicatory value for nutrient and organic matter losses from catchments. Ecological Indicators 5:350-369. Vitousek, P. M. 1990. Biological invasions and ecosystem processes: towards an integration of population biology and ecosystem studies. Oikos 57:7-13. Vitousek, P. M., H. A. Mooney, J. Lubchenco, and J. M. Melillo. 1997. Human Domination of Earth's Ecosystems. Science 277:494-499. Williams, J. W., E. W. Seabloom, D. Slayback, D. M. Stoms, and J. H. Viers. 2005. Anthropogenic impacts upon plant species richness and net primary productivity in California. Ecology Letters 8:127-137. Williams, M. R., B. B. Lamont, and J. D. Henstridge. 2009. Species-area functions revisited. Journal of Biogeography. doi:10.1111/j.1365-2699.2009.02110.x Williamson, M. 1996. Biological invasions. Chapman and Hall, London. Wu, S.-H., C.-F. Hsieh, S.-M. Chaw, and M. Rejmánek. 2004. Plant invasions in Taiwan: Insights from the flora of casual and naturalized alien species. Diversity & Distributions 10:349-362.. 70   .

(77)  . Appendix Terminology Disturbance. Definition Removal of competing vegetation.. Reference (Hobbs 1991). Plant taxa in a given area whose presence there is due to intentional or (Richardson et Exotic plants accidental introduction as a result of human activity.. al. 2000). Fragmentation caused by humans has been represented as a simple typology of landscape classification into (1) habitat that is reduced to Habitat. fragments or patches and (2) nonhabitat, which is extensive enough to (McIntyre and. fragmentation form the landscape matrix.. Hobbs 1999) (Williamson. Invasibility. Overall susceptibility of sites to invasion.. 1996). Invasion, spread into areas away from sites of introduction, requires that introduced plants also overcome barriers to dispersal within the new region and can cope with the abiotic environment and biota in the (Richardson et Invasion. general area.. al. 2000). Landscapes are ecological systems that exist at the scale of kilometers and comprise recognizable elements, such as forest patches, fields and (Forman and Landscape. hedgerows, human settlements, and natural ecosystems.. Gordon 1986). Spatial heterogeneity of vegetation patterns (i.e., landscape heterogeneity) is a structural property of landscapes that can be Landscape. defined by the complexity and variability of ecological systems’. heterogeneity properties in space.. (Kumar et al. 2006). Alien plants that reproduce consistently (cf. casual alien plants ) and sustain populations over many life cycles without direct intervention by humans (or in spite of human intervention); they often recruit Naturalized. offspring freely, usually close to adult plants, and do not necessarily. (Richardson et. plants. invade natural, seminatural or human-made ecosystems.. al. 2000). The rate at which radiant energy is converted by photosynthesis to Primary. organic compounds is referred to as primary productivity because it is (Smith and. productivity. the first and basic form of energy storage.. Propagule pressure. Smith 2002) (Williamson. Number of propagules arriving at a site.. 1996) (Smith and. Richness. Number of species.. Smith 2002). 71   .

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