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Invasive species (sensuRichardson et al. 2000; Pyšek et al. 2004) are characterized by remarkable dynamics of spread that allow them to colonize large areas in regions where they are not native. A primary question in invasion biology is: what will the rate of spread of an organism be after the initial establishment at a single location (Hastings 1996)? The issue of invasion dynamics also has a practical aspect: rate of spread has been long recognized as one of the parameters that we need to know if an alien weed is to be controlled, as alien taxa that exhibit high rates of spread are likely to become widely distributed and troublesome (Forcella 1985). Unfortunately, as the crucial aspect of recognizing an invasive species is the invasion itself (observable only after the event), plant invasions are mostly studied post hoc (Fuller & Boorman 1977; Pyšek & Prach 1993; Delisle et al. 2003) and studies rarely describe the whole process of invasion from its beginning (but see Robinson 1965; Richardson & Brown 1986; Lonsdale 1993).
The present study dealt with one of the most noxious European invaders, Heracleum mantegazzianum Sommier et Levier (Apiaceae) (Tiley, Dodd & Wade 1996), and analysed the dynamics of its invasion at the local scale by using aerial photographs. This invasion was captured since its very beginning, which made it possible to ask questions that can rarely be answered in invasion biology. (i) What is more important in determining the outcome of the invasion, its duration or the rate of spread? (ii) What are the spatial extent and dynamics of the invasion by the species? (iii) How do some parameters of the species’ population dynamics change over 40 years of invasion?
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On average, 7·0% of the landscape was covered by Heracleum in the localities studied at the later stage of invasion, ranging from 0·8 to 18·9% (Table 3). Of the land-use types, treeless areas were most suitable for Heracleum invasion; their mean contribution to the total cover of Heracleum in a site was 83·4%, while that of forested landscape and settlement areas were 15·1% and 1·5%, respectively. On average 10·1% of the total cover of treeless areas, 7·7% of urban areas and 3·0% of forests and scrub were invaded by Heracleum (Table 3).
Table 3. Characteristics of invasion in particular sites and its extent shown for land-use types. Invaded area relates to the year in which the largest area covered by Heracleum was recorded (indicated in the Year column). Relative invaded area is the percentage of the 60-ha landscape sector that was covered by Heracleum in that year. Contribution to the invaded area is the proportion of invaded area accounted for by each land-use type. Flowering intensity is expressed as the proportion of invaded area covered by flowering plants in the year when the largest invaded area was recorded; proportion of land-use invaded is the percentage of the land-use area that was covered by Heracleum in that year
|Locality||Invaded area (m2)||Relative invaded area (%)||Flowering intensity (%)||Beginning of invasion||Year||Contribution to the invaded area (%)||Proportion of land-use type invaded (%)|
|Arnoltov|| 47 170|| 7·9||57·7||1973||2000|| 9·3|| 90·5||0·2||1·9||11·7|| 1·5|
|Dvorečky|| 24 817|| 4·1||68·1||1973||1996||27·8|| 71·6||0·6||1·9|| 7·8|| 1·1|
|Krásná Lípa II|| 9 454|| 1·6||43·9||1987||1996||15·6|| 83·1||1·3||0·8|| 2·1|| 0·0|
|Lískovec|| 8 174|| 1·4||47·3||1987||1996|| 0·7|| 99·2||0·1||0·0|| 1·9|| 0·0|
|Litrbachy|| 4 711|| 0·8||42·2||1973||1996||17·2|| 82·7||0·0||0·9|| 0·8|| 0·0|
|Potok|| 39 774|| 6·6||52·7||1962||1996||50·7|| 49·0||0·3||4·6||12·4|| 1·6|
|Prameny|| 55 575|| 9·3||69·2||1973||1996|| 8·0|| 86·7||5·3||8·9|| 9·4|| 7·7|
|Rájov|| 5 198|| 0·9||39·3||1996||1996|| 0·0||100·0||0·0||0·0|| 1·0|| 0·0|
|Žitný I||113 236||18·9||52·5||1957||1987||10·1|| 86·0||3·9||5·8||24·9||32·7|
|Žitný II||111 351||18.6||54·2||1962||1991||12·0|| 84·9||3·1||5·1||28·8||32·2|
|Mean|| || 7·0|| || || ||15·1|| 83·4||1·5||3·0||10·1|| 7·7|
The percentage of invaded area contributed by linear stands significantly decreased as the invasion continued (effect of the percentage of linear stands = 46·36–0·88 residence time; F1,22 = 14·49, P < 0·001, r2 = 0·397). The contribution of linear stands to total invaded area varied significantly among sites (deletion test for the same contribution of all sites: F12,22 = 10·53, P < 0·001), with significant effects at sites Žitný I, Žitný II and Litrbachy (Fig. 2).
Figure 2. Changes in the importance of linear stands (defined as the proportion of the total invaded area accounted for by stands up to 20 m from the axis of a linear habitat) for Heracleum invasion. Fitted lines show significant slopes for Žitný I (percentage of linear stands = 65·57–1·38 residence time), Žitný II and Litrbachy (common slope: percentage of linear stands =−4·78 + 1·72 residence time). Overall significance of the minimal adequate model: F4,19 = 41·56, P < 0·001, R2 = 89·7%. The enlarged white point (site Arnoltov) is an outlier not included in the analysis. Black squares, Prameny; white squares, Žitný I; black triangles, Potok; crosses, Arnoltov; black circles, Litrbachy; white circles, Krásná Lípa II; dash, Žitný II. Fitted lines: large dashes, Žitný I; small dashes, Žitný II and Litrbachy.
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rate of spread
Mean rate of areal spread was 1261 ± 1052 m2 year−1 (mean ± SD, n= 10). These values, calculated as the ratio between the highest recorded value of invaded area at a locality and the residence time needed to achieve this area, ranged from 139 to 3275 m2 year−1 (Table 1). When evaluated statistically, mean rate of areal spread, expressed as the estimated time of 50% of the total invaded area (t50), ranged between 17 and 31 years, and differed significantly among sites, being faster at Žitný I and Arnoltov than at Prameny and Lískovec (Fig. 3).
Figure 3. Mean rates of spread (with 95% confidence intervals) expressed as t50, the estimated time to 50% of the total area invaded. Means at individual sites, ranked in ascending order, whose confidence intervals do not overlap, are significantly different. 1, Prameny; 2, Lískovec; 3, Žitný II; 4, Dvorečky; 5, Potok; 6, Litrbachy; 7, Žitný I; 8, Arnoltov.
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Mean rate of linear spread, expressed as the maximum distance the population reached from the primary invasion focus divided by the residence time, was 10·8 ± 7·2 m year−1 (mean ± SD, n= 9) and ranged from 3·8 to 26·7 m year−1 (Table 1).
relationship between invaded area, rate of spread and residence time
Significant pairwise relationships between invaded area, rate of spread and residence time were found. The rate of spread positively affected invaded area and was its strongest pairwise predictor (invaded area = 255·8 + 37·8 rate of spread; F1,7 = 138·90, P < 0·001, r2 = 0·952). At the same time, the invaded area was significantly lower in sites where invasion started later (invaded area =−111 626 + 4113 residence time; F1,7 = 11·94, P < 0·05, r2 = 0·631). Residence time also exerted a positive effect on the rate of spread (rate of spread =−2348 + 92·84 residence time; F1,7 = 6·52, P < 0·05).
Multiple regression relating the invaded area to both rate of spread and residence time yielded the following relationship:
- invaded area = −37 097 + 1166 residence time + 31·74 rate of spread
The regression was highly significant (F2,6 = 134·9, P < 0·001), explaining 97·8% of the variance. Both explanatory variables, i.e. residence time (F1,7 = 7·23, P < 0·05, r2 = 0·026) and the rate of spread (F1,7 = 95·92, P < 0·001, r2 = 0·348), were significant.
Based on the significance of the two terms in the multiple regression, it was evident that both residence time and rate of spread contributed to invaded area. The direct effect of residence time on invaded area was less than half (0·22) its indirect effect (0·57). The direct effect of the rate of spread on invaded area (0·82) was nearly four times larger than the direct effect of residence time (0·22), but the combined direct and indirect effect of residence time was only slightly less (0·79) than the effect of the rate of spread (0·82) (Table 4).
Table 4. Path and effect coefficients of the path model of invaded area as a function of the residence time and the rate of spread. Path coefficients a1, b1 and b2 represent direct effects; a1 is the regression slope for the standardized variables rate of spread and residence time; b1 and b2 are standardized regression slopes from multiple regression of invaded area as a function of residence time and the rate of spread. Indirect effects are calculated as a product of path coefficients along the links between causal variables and the response variable through other causal variables. Effect coefficients are the sum of direct and indirect effects
| a 1, effect of residence time on the rate of spread (direct)||0·69|
| b 1, effect of rate of spread on invaded area (direct)||0·82|
| b 2, effect of residence time on invaded area (direct)||0·22|
| a 1 b 1, effect of residence time on invaded area (indirect)||0·57|
| b 2 + a1b1, residence time effect on invaded area (total)||0·79|
| b 1, rate of spread effect on invaded area (total)||0·82|
changes in population characteristics during invasion
Flowering intensity varied between 30% and 70% over time and did not exhibit any significant trend over the 40 years of invasion. The number of isolated Heracleum patches initially decreased from the beginning of the invasion; this trend reversed after c. 20 years when the number of patches started to increase. Patch size was largest at the intermediate course of invasion (Fig. 4). Both patterns were consistent over sites (deletion test for patch number, effect of varying quadratic terms, F6,9 = 1·74, NS; linear terms, F6,15 = 1·17, NS; intercepts, F6,21 = 0·79, NS; deletion test for patch size, effect of varying quadratic terms, F6,10 = 2·23, NS; linear terms, F6,16 = 2·64, NS; intercepts, F6,22 = 2·37, NS).
Figure 4. Trends in the number and size of Heracleum patches (defined as an isolated area of minimum size 3 m2 covered by Heracleum plants) in the course of invasion. Patch number = 127 − 12·34 residence time + 0·37 (residence time)2. F2,21 = 9·77, P < 0·01, R2 = 48·2%; the enlarged white point (site Žitný I) is an outlier not included in the regression. Ln(patch size) = 3·84 + 0·26 (residence time) − 0·0057 (residence time)2. F2,22 = 3·84, P < 0·05, R2 = 25·9%.
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The rate of linear spread found for Heracleum in our study (average 10·8 m year−1, site maximum 26·7 m year−1) is of the same order as values reported for some of the world's most dramatic invasions (for a review of rates of spread see Pyšek & Hulme 2005). Comparing the value of areal spread recorded in the present study (1261 m2 year−1, site maximum 3275 m2 year−1) with data from the literature is difficult because the values must be related to the size of the monitored area and different source population sizes, which differ among studies (Pyšek & Hulme 2005).
By selecting the study sites post hoc using knowledge of present-day infestation, we could select areas where it could be assumed populations had not spread outside the study plots. The majority of study sites were located in isolated open areas within otherwise mostly forested landscape, and invading populations were located in the central parts of these areas. It can therefore be assumed that the invaded area recorded at a site resulted from the foci identified on the earliest photographs. The penetration of invading plants from outside analysed plots cannot be completely excluded, but the data indicate that if this occurred it was of minor importance. Such occurrence would make the estimated values of spread more conservative. On the other hand, the maximum values found at the Žitný I and II sites (Table 1) represent a good estimate of invasion potential because they are located in a large open area of former pastures and meadows, surrounding an abandoned village, with low representation of forest and scrub patches that could represent physical constraints to the invasion. In these two sites, Heracleum invaded 18·6% and 18·9% of the available areas over 40 years (Table 3 and Fig. 1). Field research has confirmed and previous study (Pyšek & Pyšek 1995) has demonstrated that forests indeed represent barriers to invasion by Heracleum. Heracleum invades forest margins but only very rarely are solitary plants found in forest interior.
An absence of correlation between linear and areal measures of spread (Table 3; F1,7 = 0·57, P= 0·47) indicates that Heracleum populations do not spread as an advancing front but that long-distance dispersal (within the scale involved in the study) plays an important role in the invasion process (Higgins & Richardson 1999; Hulme 2003).
The analyses presented make several assumptions. (i) Photographs were taken when Heracleum was flowering or fruiting and plants are easy to distinguish, so that the invaded area could have been identified and measured. The largest invaded area recorded in a site over the study period was used, rather than the most recent value recorded, because in two sites (Table 1) the total invaded area decreased slightly between the most recent dates. This was probably the result of occasional unsuccessful small-scale control efforts and/or photograph quality varying between samples. (ii) Samples were regularly distributed over the 40 years of invasion, allowing us to measure the rate of invasion. (iii) Monitoring had started before the onset of invasion, so it was possible to determine the start with reasonable precision given the intervals between monitoring dates.
These data allowed us to explore the relative role of the two determinants of invaded area. Both the residence time and rate of spread significantly contributed to the invaded, area with the direct effect of the latter being much larger than that of the former. However, as the residence time also had a significant effect on the rate of spread (the invasion proceeded faster in sites where Heracleum was introduced earlier), the total effects of the residence time and rate of spread were of comparable importance. If the invaded area was determined only by the year a site was invaded, the rate of invasion would be the same in each locality and the species would have spread regardless of specific site conditions. As the year of invasion was determined mainly by dispersal opportunities, the current pattern of Heracleum occurrence in the study area would be primarily determined by the fact that the species’ propagules reached the sites at different times. However, the significant differences in the rate of invasion among sites indicate that, despite Heracleum being an extremely successful invader (Moravcováet al. 2005) and the study region being climatically suitable (Pyšek 1991; Pyšek et al. 1998), there are constraints to invasion that vary among sites. That the sites are not equally suited for colonization by Heracleum is determined by variation in environmental conditions such as soil nutrients and moisture, character of resident vegetation and site history (Rouget & Richardson 2003; Rickey & Anderson 2004; Barney, DiTommaso & Weston 2005). These features affect the species’ population biology and ecology and act in concert with landscape determinants of invasion. The importance of environmental heterogeneity in influencing invasions has been highlighted (Davis, Grime & Thompson 2000). As environments differ in their spatial and temporal patterns of resource supply, the opportunities they provide for recruitment and spread differ (Higgins & Richardson 1996).
Distribution of invasive species has been reported to depend on the rate of spread in a study of alien weeds in Australia (Forcella 1985). The present results suggest that the residence time is of the same importance.
Inferring population characteristics from aerial photographs is limited by the quality of the photographs; however, some robust patterns over the 40 years of invasion could be identified. The proportion of plants that flowered did not change over time. This indicates that the study region is climatically suitable for this species of Caucasian origin, unlike warmer parts of the Czech Republic where the warm January temperatures are probably suboptimal (Pyšek et al. 1998). A stable proportion of flowering plants was also recorded by sampling permanent plots in the field (J. Pergl et al., unpublished data).
The spatial structure of Heracleum populations changed during the course of invasion. The number of isolated patches decreased in the initial 10–15 years and at the same time their mean size increased. This suggests that during the process of establishment at a site there is a period of enlargement of individual patches that merge with each other, and hence their total number decreases. After 20–25 years, patch number started to increase, indicating colonization of more distance places within a site. At the same time patch size started to decrease, suggesting dynamic spread associated with forming a large number of small colonizing patches.
Linear landscape features such as paths, roads and streams provide good possibilities for dispersal by humans and water, and proved to be important drivers of invasion. At the beginning, a large proportion of Heracleum stands was associated with these habitats, but their importance gradually decreased as invasion proceeded and populations invaded more distant places. The pattern found at the local scale is mimicked at the geographical scale of the Czech Republic. Heracleum was reported to spread first along large rivers, acting as migration corridors, and only later invaded landscapes distant from water streams (Pyšek 1991, 1994).
Aerial photographs are used for detecting invasive plant species because estimates of invaded area make it possible to monitor their spread over time (Higgins & Richardson 1999; McCormick 1999; Stow et al. 2000; Higgins, Richardson & Cowling 2001). Examples where this method has been applied for the study of alien plant invasions include Tamarix ramosissima (Robinson 1965), Rhododendron ponticum (Fuller & Boorman 1977), Pinus radiata (Richardson & Brown 1986), Pinus halepensis (Rouget et al. 2001) and Ammophila arenaria (Buell, Pickart & Stuart 1995). The cost of repeated coverage to detect changes must be borne in mind but, given the costs associated with the impact of alien plants (Zavaleta, Hobbs & Mooney 2001), the benefits prevail if repeated monitoring is followed by the design of an appropriate control strategy (Bakker & Wilson 2004; Paynter & Flanagan 2004; Perry, Galatowitsch & Rosen 2004; Taylor & Hastings 2004). It should be noted that the examples mentioned above are invasions by a different life form, not present in the invaded community before; this makes their detection by aerial photographs easier. The potential to study invasions by herbaceous plants at such large scales is in general very limited; Heracleum is an exception to this rule.
On earlier sampling dates, the photographs of our study area were taken for military purposes and kept classified. From the 1990s, sampling was initiated by the Protected Landscape Area authorities for the purpose of monitoring the extent of Heracleum invasion. Although infestation maps were created they have not been used efficiently in practice up to now, and the control efforts remain largely unsystematic and the selection of stands for control is quite random. The present study has shown that aerial photography is appropriate for monitoring the distribution of Heracleum and the method benefits from the invader having a very different appearance from native dominants (Rouget et al. 2003). The results of our study could facilitate the development of a control strategy that could not have been devised without this information (Wadsworth et al. 2000). There are four important aspects that can be incorporated directly into an appropriate control strategy. (i) Heracleum is easily detected from aerial photographs taken not only at flowering but also at early fruiting time, which extends the potential sampling period until late August. A detailed inspection of photographs allows detection of even single plants. These should be targeted for immediate removal to prevent further spread. As demonstrated by Moody & Mack (1988), effectiveness of control measures is greatly improved by concentrating on satellite isolated populations instead of on large expanding stands. Unlike in other herb species that are less easy to recognize, the control programmes could profit from the level of recording detail that can be achieved in monitoring Heracleum.
(ii) Linear landscape structures such as paths, roads and streams play an important role at the beginning of Heracleum invasion. The role of these linear corridors in the spread of alien plants has been documented (Thébaud & Debussche 1991; Pyšek & Prach 1993; Planty-Tabacchi et al. 1996; Hood & Naiman 2000) but the present study highlights that they should be targeted in the early stages of invasions, when control measures can be applied more efficiently than later on. Therefore the utmost attention should be paid to the occurrence of Heracleum along these corridors in sections of landscape where the invasion starts.
(iii) By employing longitudinal data, the present study allowed us to measure the actual rate of spread. Its strong effect on the extent of invaded area indicates that the species is not limited much by local site conditions. This should be taken as a warning that the entire area, including habitats currently less prone to the invasion, must be included in control programmes. On the other hand, knowing how fast the invader is able to spread locally and which of the habitats are particularly prone to the invasion makes it possible to identify localities that are at highest risk of immediate infestation.
(iv) Results of the present study can be applied to predict the occurrence of Heracleum in unsampled sites (N. Nehrbass et al., unpublished). A clear indication of where invasion is most likely to occur in the future would be the most valuable message for managers (Hulme 2003).