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).
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.
±
0 4 8 16 24 32
Kilometers Study plots
Elevation 50 - 301m 301m - 769m 769m - 1330m 1330m - 2003m 2003m - 3311m Study area
Map of Taiwan Tropic of Cancer
FIG. 2. Study area and 100 survey plots.
FIG. 3. Histogram of annual rainfall in study plots.
FIG. 4. Histogram of average altitude in study plots.
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.
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:
∑
Species percentage is percentage of either naturalized or native
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).
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):
∑
Landscape fragmentation is comprised of two parameters: edge density and patch density. Edge density was total patch perimeter
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).
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…
Analyses
FIG. 5. Flow chart of data management.
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.
TABLE 3. An example of standardize sampling plots when counting species richness.
Plot A Plot B Plot C Plot D
Species 1 Yes Yes
Species 2 Yes Yes
Four sampling plots
A~D and the occurrence
of species 1~5
Species 3 Yes Yes
Species 4 Yes Yes Yes
Species 5 Yes 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 A+B+C+D 5
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.