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Marco A Molina-Montenegro, Alejandro del Pozo, Ernesto Gianoli, Ecophysiological basis of the Jack-and-Master strategy: Taraxacum officinale (dandelion) as an example of a successful invader, Journal of Plant Ecology, Volume 11, Issue 1, February 2018, Pages 147–157, https://doi.org/10.1093/jpe/rtw121
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Abstract
Successful invasive plants are often assumed to display significant levels of phenotypic plasticity. Three possible strategies by which phenotypic plasticity may allow invasive plant species to thrive in changing environments have been suggested: (i) via plasticity in morphological or physiological traits, invasive plants are able to maintain a higher fitness than native plants in a range of environments, including stressful or low-resource habitats: a ‘Jack-of-all-trades’ strategy; (ii) phenotypic plasticity allows the invader to better exploit resources available in low stress or favorable habitats, showing higher fitness than native ones: a ‘Master-of-some’ strategy and (iii) a combination of these abilities, the ‘Jack-and-Master’ strategy.
We evaluated these strategies in the successful invader Taraxacum officinale in a controlled experiment mimicking natural environmental gradients. We set up three environmental gradients consisting of factorial arrays of two levels of temperature/light, temperature/water and light/water, respectively. We compared several ecophysiological traits, as well as the reaction norm in fitness-related traits, in both T. officinale and the closely related native Hypochaeris thrincioides subjected to these environmental scenarios.
Overall, T. officinale showed significantly greater accumulation of biomass and higher survival than the native H. thrincioides, with this difference being more pronounced toward both ends of each gradient. T. officinale also showed significantly higher plasticity than its native counterpart in several ecophysiological traits. Therefore, T. officinale exhibits a Jack-and-Master strategy as it is able to maintain higher biomass and survival in unfavorable conditions, as well as to increase fitness when conditions are favorable. We suggest that this strategy is partly based on ecophysiological responses to the environment, and that it may contribute to explaining the successful invasion of T. officinale across different habitats.
INTRODUCTION
Invasion biologists have long sought to identify species traits that could be reliable predictors of the ability to colonize new environments. Elton (1958) hypothesized that species able to establish in uncolonized ground possessed traits that allowed them to use resources or tolerate stresses in ways that native or non-invasive species could not. Biological invasion processes have been considered suitable systems to assess the importance of such ‘key traits’ in establishment success worldwide (Godoy et al. 2011; Molina-Montenegro et al. 2012a; Rejmánek and Richardson 1996). Phenotypic plasticity has been largely seen as a key feature explaining why some exotic plant species are successful in the colonized habitats (Daehler 2003; Davidson et al. 2011; Funk 2008; Maron et al. 2004; Molina-Montenegro et al. 2011; Richards et al. 2006; Sexton et al. 2002; Skálová et al. 2012; Williams et al. 1995). As plasticity may allow species to show adaptive phenotypes in a broad range of environments, it is likely to influence their ecological distribution and thus their potential for invasion (Alpert 2000; Daehler 2003; Hulme 2008; Molina-Montenegro et al. 2013b). Nevertheless, several recent studies have shown that invasive plant species do not necessarily have greater plasticity than their native counterparts (Dawson et al. 2012; Godoy et al. 2011; Palacio-López and Gianoli 2011).
High plasticity may be advantageous to cope with spatio-temporal fluctuations of resources in different environments (Gianoli 2004; Godoy et al. 2011; Williams et al. 1995; Willis and Hulme 2002). Because physiological performance may be impaired in low-resource environments (Davis et al. 2000), phenotypic plasticity can help maintain plant fitness under such stressful conditions (fitness homeostasis); on the other hand, phenotypic plasticity may contribute to better capitalize temporal pulses of high resource availability experienced by plants (Sultan 2001). Richards et al. (2006) summarized these concepts in three possible strategies by which invasive plant species can thrive in changing environments: (i) via plasticity in morphological or physiological traits, invasive plants are able to maintain a higher fitness than native plants in a range of environments, including stressful or low-resource habitats: a ‘Jack-of-all-trades’ strategy; (ii) phenotypic plasticity allows the invader to better exploit resources available in low stress or favorable habitats, showing higher fitness than natives: a ‘Master-of-some’ strategy and (iii) a combination of these abilities, the ‘Jack-and-Master’ strategy.
Taraxacum officinale (dandelion) is a perennial herb native to Europe that is considered an aggressive invasive species worldwide (Holm et al. 1997). In its native range, T. officinale is present in alpine environments, mostly restricted to disturbed sites (Quiroz et al. 2009). In contrast, in Chile, this alien species grows abundantly in zones with different disturbance levels (Cavieres et al. 2005; Quiroz et al. 2011) and has spread along a ~4000 km latitudinal gradient (Molina-Montenegro and Naya 2012) and up to mountain-tops in Central Chile Andes (Molina-Montenegro and Cavieres 2010). T. officinale has shown high tolerance to abiotic stress and efficient use of resources due to high plasticity in morphological and physiological traits (Molina-Montenegro et al. 2010, 2011, 2012b). Thus, when it experiences favorable abiotic conditions T. officinale shows enhanced abundance, physiological performance, biomass accumulation, survival and seed production (Cavieres et al. 2005, 2008; Molina-Montenegro et al. 2011, 2012b, 2013b), suggesting a Master-of-some strategy. On the other hand, it has been reported that under unfavorable abiotic conditions T. officinale exhibits better physiological performance, growth and survival than a native counterpart (Molina-Montenegro et al. 2012a, 2013b), suggesting a Jack-of-all-trades strategy. These strategies may partly account for the negative effects of T. officinale on native plant species in high-mountain communities (Muñoz and Cavieres 2008; Molina-Montenegro et al. 2012b). Therefore, it may be conceived that the invasion success of T. officinale partly results from the deployment of both strategies, the aforementioned Jack-and-Master (Richards et al. 2006).
As indicated above, T. officinale in Chile is not restricted to disturbed environments where resource availability is high, it is also found growing within native communities in high-mountain sites where environmental conditions are stressful (Molina-Montenegro and Cavieres 2010; Molina-Montenegro et al. 2012b). We undertook an experimental approach to test for a Jack-and-Master strategy in T. officinale, including a comparison with a phylogenetically close and ecologically related native species. We set up three environmental gradients consisting of factorial arrays of two levels of temperature/light, temperature/water and light/water, respectively. To evaluate the Jack-and-Master hypothesis, we compared several morphological and physiological traits, as well as the reaction norm in fitness-related traits, in both T. officinale and the closely related native Hypochaeris thrincioides subjected to these environmental scenarios, which were arranged in terms of their stressfulness.
MATERIALS AND METHODS
Seed collection and growth conditions
Seeds of the invasive Taraxacum officinale and the native Hypochaeris thrincioides were collected in the Andes of central Chile at 2800 m.a.s.l. A few seeds per individual (four to five) were collected from a relatively large number of maternal plants (over 50). We selected these plant species because both are members of the family Asteraceae, tribe Cichorieae and co-occur at the same altitudinal level (2300 to 2800), showing a similar morphology with showy yellow heads and leaves in rosettes at the soil surface (Matthei 1995). A field study has shown that T. officinale negatively affects H. thrincioides via competition for pollinators (Muñoz and Cavieres 2008). In addition, T. officinale and H. thrincioides showed comparable levels of ecophysiological traits and tolerance to herbivory (Molina-Montenegro et al. 2013b, 2012b). Nevertheless, T. officinale showed greater distribution, abundance and competitive ability than H. thrincioides, suggesting that this invasive species would deploy different strategies to colonize and spread compared with the native species. Thus, these two plant species constitute a suitable system to test the hypothesis of a Jack-and-Master strategy.
Seeds from different maternal plants in both T. officinale and H. thrincioides were pooled and germinated in glasshouse conditions. Individuals of both species were generated from this initial seed pool and were grown in a glasshouse at Universidad de Concepción, central Chile. During six months, plants were irrigated every two days with 50 ml of tap water until they produced seeds, which were used to obtain new experimental plants. Seeds were germinated in a room at 28 ± 3°C on wet filter paper in Petri dishes and planted in 300 ml plastic pots filled with potting soil (peat-perlite-sand; 2:1:1). One week after appearance of the first true leaf, seedlings were transferred to controlled conditions (growth chambers in CEAZA facilities, La Serena, Chile). All plants were supplemented with Phostrogen (Solaris N-P-K; 14:10:27) using 0.2 g l−1 once every 15 days. Experimental treatments lasted for three months and consisted of combinations of temperature, light intensity and water availability, as described below.
Gradients and abiotic scenarios
We experimentally generated three abiotic gradients, each with four stress levels ranging from unfavorable (S1) to favorable scenarios (S4). The first abiotic gradient resulted from a factorial combination of two temperatures (5 and 25°C; cold and warm) and two light intensities (1000 and 2000 µmol m−2 s−1; adequate and excessive). The scenarios were 2000 µmol m−2 s−1 + 5°C (scenario 1, S1), 1000 µmol m−2 s−1 + 5°C (scenario 2, S2), 2000 µmol m−2 s−1 + 25°C (scenario 3, S3) and 1000 µmol m−2 s−1 + 25°C (scenario 4, S4). In this gradient, all individuals of both species were irrigated with 50 ml of tap water every three days. The second abiotic gradient arose from a factorial combination of two watering regimes (irrigation every 3 and 7 days with 50 ml of tap water; regular watering and water shortage) and two light intensities (1000 and 2000 µmol m−2 s−1). The scenarios were 2000 µmol m−2 s−1 + 7d (S1), 1000 µmol m−2 s−1 + 7d (S2), 2000 µmol m−2 s−1 + 3d (S3) and 1000 µmol m−2 s−1 + 3d (S4). In this gradient, all individuals of both species were maintained at 25°C. The third abiotic gradient resulted from a factorial combination of two watering regimes (irrigation every 3 and 7 days with 50 ml of tap water) and two temperatures (5 and 25°C). The scenarios were 7d + 25°C (S1), 7d + 5°C (S2), 3d + 5°C (S3) and 3d + 25°C (S4). In this gradient, all individuals of both species were grown under 1000 µmol of light intensity. In all cases, 25 individuals from each plant species were subjected to each of the abiotic scenarios along the favorable–unfavorable axis (Table 1). The combinations of abiotic conditions that gave rise to the experimental gradients (temperature: 5 and 25°C; light: 2000 and 1000 µmol m−2 s−1; water supply every 3 and 7 days) are likely to be experienced by both plant species in their distribution range (Molina-Montenegro and Cavieres 2010; Molina-Montenegro et al. 2010, 2011, 2012b, 2013b; Molina-Montenegro and Naya 2012). The unfavorable–favorable hierarchy of scenarios was defined based on previous experience with manipulative experiments conducted with the study species and considering the altitudinal and latitudinal ranges of distribution in Chile.
Temperature and light . | Water and light . | Water and temperature . | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | ||||||
F . | P . | F . | P . | . | F . | P . | F . | P . | . | F . | P . | F . | P . | . | |
Origin (O) | 21.12 | <0.001 | 29.23 | <0.001 | 76.78 | 0.033 | 86.9 | < 0.01 | 69.64 | 0.046 | 73.77 | 0.039 | |||
Scenario (S) | 123.43 | 0.031 | 138.65 | 0.022 | 265.78 | <0.001 | 295.67 | <0.001 | 142.23 | <0.001 | 165.88 | <0.001 | |||
O × S | 5.31 | 0.055 | 8.02 | 0.032 | J & M | 4.56 | 0.097 | 12.45 | 0.012 | M | 21.23 | 0.040 | 34.55 | 0.035 | J & M |
Temperature and light . | Water and light . | Water and temperature . | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | ||||||
F . | P . | F . | P . | . | F . | P . | F . | P . | . | F . | P . | F . | P . | . | |
Origin (O) | 21.12 | <0.001 | 29.23 | <0.001 | 76.78 | 0.033 | 86.9 | < 0.01 | 69.64 | 0.046 | 73.77 | 0.039 | |||
Scenario (S) | 123.43 | 0.031 | 138.65 | 0.022 | 265.78 | <0.001 | 295.67 | <0.001 | 142.23 | <0.001 | 165.88 | <0.001 | |||
O × S | 5.31 | 0.055 | 8.02 | 0.032 | J & M | 4.56 | 0.097 | 12.45 | 0.012 | M | 21.23 | 0.040 | 34.55 | 0.035 | J & M |
Analyses were performed separately for each environmental gradient, considering origin (O; native vs. invasive) as main factor and abiotic scenario (S) as covariate. For each environmental gradient, we considered four scenarios ranging from unfavorable (S1) to favorable (S4) abiotic conditions. The temperature was 5 or 25 ºC, light was 2000 or 1000 µmol m-2 s-1 and water was irrigation every 7 or 3 days. Temperature–light gradient: 2000 + 5 (S1), 1000 + 5 (S2), 2000 + 25 (S3) and 1000 + 25 (S4). Water–light gradient: 2000 + 7 (S1), 1000 + 7 (S2), 2000 + 3 (S3) and 1000 + 3 (S4). Temperature–water gradient: 7 + 25 (S1), 7 + 5 (S2), 3 + 5 (S3) and 3 + 25 (S4); see text for more details. Strategies deployed: Jack-of-all-trades (J), Master-of-Some (M), Jack-and-Master (J&M). Scenario S3 to S1: Jack-of-all-Trades strategy and Scenario S2 to S4: Master-of-Some strategy. Significant P values (<0.05) are highlighted in bold.
Temperature and light . | Water and light . | Water and temperature . | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | ||||||
F . | P . | F . | P . | . | F . | P . | F . | P . | . | F . | P . | F . | P . | . | |
Origin (O) | 21.12 | <0.001 | 29.23 | <0.001 | 76.78 | 0.033 | 86.9 | < 0.01 | 69.64 | 0.046 | 73.77 | 0.039 | |||
Scenario (S) | 123.43 | 0.031 | 138.65 | 0.022 | 265.78 | <0.001 | 295.67 | <0.001 | 142.23 | <0.001 | 165.88 | <0.001 | |||
O × S | 5.31 | 0.055 | 8.02 | 0.032 | J & M | 4.56 | 0.097 | 12.45 | 0.012 | M | 21.23 | 0.040 | 34.55 | 0.035 | J & M |
Temperature and light . | Water and light . | Water and temperature . | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | S3 to S1 . | S2 to S4 . | Strategy . | ||||||
F . | P . | F . | P . | . | F . | P . | F . | P . | . | F . | P . | F . | P . | . | |
Origin (O) | 21.12 | <0.001 | 29.23 | <0.001 | 76.78 | 0.033 | 86.9 | < 0.01 | 69.64 | 0.046 | 73.77 | 0.039 | |||
Scenario (S) | 123.43 | 0.031 | 138.65 | 0.022 | 265.78 | <0.001 | 295.67 | <0.001 | 142.23 | <0.001 | 165.88 | <0.001 | |||
O × S | 5.31 | 0.055 | 8.02 | 0.032 | J & M | 4.56 | 0.097 | 12.45 | 0.012 | M | 21.23 | 0.040 | 34.55 | 0.035 | J & M |
Analyses were performed separately for each environmental gradient, considering origin (O; native vs. invasive) as main factor and abiotic scenario (S) as covariate. For each environmental gradient, we considered four scenarios ranging from unfavorable (S1) to favorable (S4) abiotic conditions. The temperature was 5 or 25 ºC, light was 2000 or 1000 µmol m-2 s-1 and water was irrigation every 7 or 3 days. Temperature–light gradient: 2000 + 5 (S1), 1000 + 5 (S2), 2000 + 25 (S3) and 1000 + 25 (S4). Water–light gradient: 2000 + 7 (S1), 1000 + 7 (S2), 2000 + 3 (S3) and 1000 + 3 (S4). Temperature–water gradient: 7 + 25 (S1), 7 + 5 (S2), 3 + 5 (S3) and 3 + 25 (S4); see text for more details. Strategies deployed: Jack-of-all-trades (J), Master-of-Some (M), Jack-and-Master (J&M). Scenario S3 to S1: Jack-of-all-Trades strategy and Scenario S2 to S4: Master-of-Some strategy. Significant P values (<0.05) are highlighted in bold.
Ecophysiological and fitness-related traits
Pot positions were randomized within the growth chamber or growth room every three days. Inter-pot distances were sufficient to prevent mutual shading. After three months we recorded the following ecophysiological traits for T. officinale and H. thrincioides individuals: maximum photosynthesis (Amax; maximum rate at which leaves are able to fix carbon during photosynthesis), instantaneous water use efficiency (WUE; ratio of the rate of carbon assimilation [photosynthesis] to the rate of water loss [transpiration]), non-photochemical quenching (NPQ; mechanism employed by plants to dissipate excess energy as heat) and foliar angles. An infra-red gas analyzer (IRGA, CIRAS1, PP-Systems, Hoddesdon, UK), operating in open mode and fitted with a Parkinson leaf cuvette (2.5 cm2), was used to measure gas exchange traits at constant concentration of CO2 (360 ppm). We measured maximum photosynthetic rate (Amax, µmol m−2s−1) and transpiration rate (mmol m−2s−1) on 12 adult individuals of both species between 12:00 and 15:00 h, during two consecutive days. Amax is a good predictor of relative growth rate across species (Poorter and Garnier 2007). From gas exchange values, WUE was calculated as the ratio between photosynthesis and transpiration rate (Nobel 2005). WUE reflects the water cost of carbon gain and therefore its impact on fitness may be independent of that of Amax (Heschel et al. 2002); significant water losses may curtail plant vigor, and water-stressed plants cannot convert efficiently assimilated carbon into biomass. At the end of the experiment, using a pulse-amplitude modulated fluorimeter (PAM-2000, Walz, Germany) we measured NPQ as an estimate of energy dissipation. NPQ helps regulate and protect photosystem II in environments where light energy absorption exceeds the capacity for light utilization in photosynthesis (Nobel 2005). One fully developed leaf from the same individuals used for gas exchange measurements (n = 12 plants per species in each abiotic scenario) was dark-adapted for 30 min to obtain open PSII centers. Leaf detachment from the plant was carefully avoided, thus allowing the recording of each parameter necessary for NPQ calculation (details in Molina-Montenegro et al. 2013a). Foliar angles were measured in two mature leaves of 12 individuals of each species at midday and averaged per individual, using a protractor with a plumb line attached to the midpoint of the flat side (see Molina-Montenegro et al. 2012b). Changes in foliar angle have been interpreted as a mechanism to avoid photoinhibition by reducing the incident solar radiation (Molina-Montenegro and Cavieres 2010). Importantly, total foliar area of T. officinale and H. thrincioides individuals from the study site were 1125 ± 114 cm2 and 803 ± 89 cm2, respectively (n = 15 individuals per species). Thus, any advantage in ecophysiological performance in T. officinale determined at the leaf scale could be maintained or even increased at the whole-plant scale. At the end of the experiment, we recorded as fitness-related traits the survival percentage (for each group of 25 plants) and total dry biomass (including fallen leaves and belowground biomass) of plants oven-dried at 70°C for 72 h.
Because plasticity in a trait is defined as the property of a genotype, experiments should be conducted ideally with clonal replicates. Since such clonal replicates are not available for many species, it is common to study reaction norms at the species level using random grouping (Gianoli and Valladares 2012; Pigliucci 2001), as we did here.
Statistical analyses
The comparison of reaction norms in fitness-related traits (biomass and survival) as well as ecophysiological traits (Amax, NPQ, foliar angles and WUE) allowed us to identify the different strategies shown by T. officinale. In order to compare the reaction norms between the native and invasive species, we conducted an analysis of covariance (ANCOVA) separately for each of three environmental gradients, considering native vs. invasive origin as main factor, ecophysiological or fitness trait as dependent variable, and abiotic scenario as covariate. A statistically significant factor-by-covariate interaction indicated differences in plasticity between the native and the invasive species. To adequately test the Jack-and-Master strategy, this analysis was separately conducted along average to unfavorable (S3 to S1) and average to favorable (S2 to S4) subsets of conditions. Hence, if the decrease in fitness of T. officinale was lower than that of H. thrincioides in the first gradient (unfavorable setting: S3 to S1), it could be suggested the occurrence of a Jack-of-all-trades strategy. On the other hand, if T. officinale had a steeper fitness increase compared to H. thrincioides in the second gradient (favorable setting: S2 to S4), we could suggest a Master-of-some strategy. Finally, if both patterns were verified, a Jack-and-Master strategy could be inferred (Richards et al. 2006). For all analyses, the assumptions of normality and homogeneity of variances were tested using the Shapiro–Wilks and Bartlett tests, respectively (Zar 1999).
In the case of survival data (number of plants alive after 3 months, with initial n = 25), because we had no replication within each experimental group, the Jack-of-all-trades and the Master-of-some strategies were evaluated only once, pooling data from the three environmental gradients. This was done by comparing (T. officinale vs. H. thrincioides) the difference in survival between the S3 and S1 scenarios (Jack), and between the S2 and S4 scenarios (Master), for each of the three environmental gradients. A t-test for dependent samples (n = 3) was used to compare these differences in survival between the native and the invasive species across the experimental gradients.
RESULTS
Temperature and light gradient
Total plant biomass was significantly higher in the invader T. officinale—compared to the native H. thrincioides—throughout the S3 to S1 scenarios (unfavorable setting; Fig. 1A, Table 1). Specifically, although the accumulation of biomass decreased with less favorable scenarios in both species, the decrease was lesser in T. officinale (Fig. 1A, Table 1), thus suggesting a Jack-of-all-trades strategy. Plant biomass was also different between species across the S2 to S4 scenarios (favorable setting; Fig. 1A, Table 1). Particularly, although the accumulation of biomass increased with more favorable scenarios in both species, the increase was of greater magnitude in T. officinale (Fig. 1A, Table 1), thus indicating a Master-of-some strategy. Therefore, considering patterns of biomass accumulation in both experimental gradients, T. officinale showed a Jack-and-Master strategy. Concerning plant survival, we found that the survival percentage was higher in T. officinale than in H. thrincioides, considering both the S3 to S1 scenarios, where this difference increased under the most unfavorable scenario (S3 = 8%, S2 = 8%, and S1 = 12%, Fig. 1B), and the S2 to S4 scenarios, where this difference increased toward more favorable abiotic conditions (S2 = 8%, S3 = 8%, and S4 = 20%, Fig. 1B). Consequently, survival patterns were also consistent with a Jack-and-Master strategy in the invasive dandelion. Regarding ecophysiological traits, T. officinale showed significantly higher maximum photosynthesis (Amax) and WUE under the average to unfavorable abiotic gradient (S3 to S1; Table 2). With increasingly stressful conditions, T. officinale showed a significantly less steep increase in NPQ and foliar angles than the native H. thrincioides (Table 2). Under the average to favorable scenario (S2 to S4), T. officinale showed significantly higher Amax and WUE than the native counterpart (Table 2), and both NPQ and foliar angles were significantly lower than in H. thrincioides (Table 2). Therefore, the patterns of expression of all ecophysiological traits studied were also consistent with a Jack-and-Master strategy in the invasive species.

biomass accumulation (mg) and survival (%) in the invasive Taraxacum officinale (open circles) and in the closely related native Hypochaeris thrincioides (closed circles) exposed to three different environmental gradients, each with four stress levels ranging from unfavorable (S1) to favorable scenarios (S4). The first abiotic gradient resulted from a factorial combination of two temperatures (5 and 25°C; cold and warm) and two light intensities (1000 and 2000 µmol m−2 s−1; adequate and excessive). The scenarios were 2000 µmol m−2 s−1 + 5°C (scenario 1, S1), 1000 µmol m−2 s−1 + 5°C (scenario 2, S2), 2000 µmol m−2 s−1 + 25°C (scenario 3, S3) and 1000 µmol m−2 s−1 + 25°C (scenario 4, S4). The second abiotic gradient arose from a factorial combination of two watering regimes (irrigation every 3 and 7 days with 50 ml of tap water; regular watering and water shortage) and two light intensities (1000 and 2000 µmol m−2 s−1). The scenarios were 2000 µmol m−2 s−1 + 7d (S1), 1000 µmol m−2 s-1 + 7d (S2), 2000 µmol m−2 s−1 + 3d (S3) and 1000 µmol m−2 s−1 + 3d (S4). The third abiotic gradient resulted from a factorial combination of two watering regimes (irrigation every 3 and 7 days with 50 ml of tap water) and two temperatures (5 and 25°C). The scenarios were 7d + 25°C (S1), 7d + 5°C (S2), 3 + 5°(S3) and 3d + 25°C (S4).
analysis of covariance (ANCOVA) of ecophysiological traits: maximum photosynthesis rate (Amax; in µmol m−2s−1), non-photochemical quenching (NPQ), angles of leaves and water use efficiency (WUE; in µmol m−2s−1/mmol m−2s−1)
. | Temperature and light . | . | Water and light . | . | Temperature and water . | . | |||
---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . |
Trait . | P value . | P value . | Strategy . | P value . | P value . | Strategy . | P value . | P value . | Strategy . |
A max | |||||||||
Origin (O) | <0.001 | 0.032 | 0.023 | <0.001 | <0.001 | <0.001 | |||
Scenario (S) | 0.025 | 0.622 | 0.036 | <0.001 | 0.002 | <0.001 | |||
O × S | 0.018 | 0.047 | J&M | 0.031 | <0.001 | J&M | <0.001 | <0.001 | J&M |
NPQ | |||||||||
Origin (O) | 0.021 | 0.042 | <0.001 | 0.048 | 0.043 | 0.002 | |||
Scenario (S) | 0.015 | 0.054 | 0.003 | 0.081 | 0.066 | <0.001 | |||
O × S | 0.020 | 0.043 | J&M | <0.001 | 0.062 | J | 0.081 | <0.001 | M |
Leaf angle | |||||||||
Origin (O) | 0.015 | 0.056 | 0.002 | 0.052 | 0.043 | 0.046 | |||
Scenario (S) | 0.564 | 0.042 | 0.054 | 0.091 | 0.976 | 0.091 | |||
O × S | 0.031 | 0.045 | J&M | 0.043 | 0.069 | J | 0.077 | 0.076 | --- |
WUE | |||||||||
Origin (O) | <0.001 | 0.035 | <0.001 | 0.032 | 0.036 | 0.052 | |||
Scenario (S) | 0.043 | 0.041 | 0.003 | 0.055 | 0.044 | 0.128 | |||
O × S | 0.021 | 0.040 | J&M | 0.002 | 0.041 | J&M | 0.037 | 0.767 | J |
. | Temperature and light . | . | Water and light . | . | Temperature and water . | . | |||
---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . |
Trait . | P value . | P value . | Strategy . | P value . | P value . | Strategy . | P value . | P value . | Strategy . |
A max | |||||||||
Origin (O) | <0.001 | 0.032 | 0.023 | <0.001 | <0.001 | <0.001 | |||
Scenario (S) | 0.025 | 0.622 | 0.036 | <0.001 | 0.002 | <0.001 | |||
O × S | 0.018 | 0.047 | J&M | 0.031 | <0.001 | J&M | <0.001 | <0.001 | J&M |
NPQ | |||||||||
Origin (O) | 0.021 | 0.042 | <0.001 | 0.048 | 0.043 | 0.002 | |||
Scenario (S) | 0.015 | 0.054 | 0.003 | 0.081 | 0.066 | <0.001 | |||
O × S | 0.020 | 0.043 | J&M | <0.001 | 0.062 | J | 0.081 | <0.001 | M |
Leaf angle | |||||||||
Origin (O) | 0.015 | 0.056 | 0.002 | 0.052 | 0.043 | 0.046 | |||
Scenario (S) | 0.564 | 0.042 | 0.054 | 0.091 | 0.976 | 0.091 | |||
O × S | 0.031 | 0.045 | J&M | 0.043 | 0.069 | J | 0.077 | 0.076 | --- |
WUE | |||||||||
Origin (O) | <0.001 | 0.035 | <0.001 | 0.032 | 0.036 | 0.052 | |||
Scenario (S) | 0.043 | 0.041 | 0.003 | 0.055 | 0.044 | 0.128 | |||
O × S | 0.021 | 0.040 | J&M | 0.002 | 0.041 | J&M | 0.037 | 0.767 | J |
Analyses were performed separately for each environmental gradient, considering origin (O; native vs. invasive) as main factor and abiotic scenario (S) as covariate. For each environmental gradient, we considered four abiotic scenarios ranging from unfavorable (S1) to favorable (S4) abiotic conditions. Temperature was 5 or 25°C, light was 2000 or 1000 µmol m−2 s−1 and water was irrigation every 7 or 3 days. Temperature–light gradient: 2000 + 5 (S1), 1000 + 5 (S2), 2000 + 25 (S3) and 1000 + 25 (S4). Water–light gradient: 2000 + 7 (S1), 1000 + 7 (S2), 2000 + 3 (S3) and 1000 + 3 (S4). Temperature–water gradient: 7 + 25 (S1), 7 + 5 (S2), 3 + 5 (S3) and 3 + 25 (S4); see text for more details. Strategies deployed: Jack-of-all-trades (J), Master-of-Some (M), Jack-and-Master (J&M) or none (–). Scenario S3 to S1: Jack-of-all-Trades strategy and scenario S2 to S4: Master-of-Some strategy.
analysis of covariance (ANCOVA) of ecophysiological traits: maximum photosynthesis rate (Amax; in µmol m−2s−1), non-photochemical quenching (NPQ), angles of leaves and water use efficiency (WUE; in µmol m−2s−1/mmol m−2s−1)
. | Temperature and light . | . | Water and light . | . | Temperature and water . | . | |||
---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . |
Trait . | P value . | P value . | Strategy . | P value . | P value . | Strategy . | P value . | P value . | Strategy . |
A max | |||||||||
Origin (O) | <0.001 | 0.032 | 0.023 | <0.001 | <0.001 | <0.001 | |||
Scenario (S) | 0.025 | 0.622 | 0.036 | <0.001 | 0.002 | <0.001 | |||
O × S | 0.018 | 0.047 | J&M | 0.031 | <0.001 | J&M | <0.001 | <0.001 | J&M |
NPQ | |||||||||
Origin (O) | 0.021 | 0.042 | <0.001 | 0.048 | 0.043 | 0.002 | |||
Scenario (S) | 0.015 | 0.054 | 0.003 | 0.081 | 0.066 | <0.001 | |||
O × S | 0.020 | 0.043 | J&M | <0.001 | 0.062 | J | 0.081 | <0.001 | M |
Leaf angle | |||||||||
Origin (O) | 0.015 | 0.056 | 0.002 | 0.052 | 0.043 | 0.046 | |||
Scenario (S) | 0.564 | 0.042 | 0.054 | 0.091 | 0.976 | 0.091 | |||
O × S | 0.031 | 0.045 | J&M | 0.043 | 0.069 | J | 0.077 | 0.076 | --- |
WUE | |||||||||
Origin (O) | <0.001 | 0.035 | <0.001 | 0.032 | 0.036 | 0.052 | |||
Scenario (S) | 0.043 | 0.041 | 0.003 | 0.055 | 0.044 | 0.128 | |||
O × S | 0.021 | 0.040 | J&M | 0.002 | 0.041 | J&M | 0.037 | 0.767 | J |
. | Temperature and light . | . | Water and light . | . | Temperature and water . | . | |||
---|---|---|---|---|---|---|---|---|---|
. | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . | S3 to S1 . | S2 to S4 . | . |
Trait . | P value . | P value . | Strategy . | P value . | P value . | Strategy . | P value . | P value . | Strategy . |
A max | |||||||||
Origin (O) | <0.001 | 0.032 | 0.023 | <0.001 | <0.001 | <0.001 | |||
Scenario (S) | 0.025 | 0.622 | 0.036 | <0.001 | 0.002 | <0.001 | |||
O × S | 0.018 | 0.047 | J&M | 0.031 | <0.001 | J&M | <0.001 | <0.001 | J&M |
NPQ | |||||||||
Origin (O) | 0.021 | 0.042 | <0.001 | 0.048 | 0.043 | 0.002 | |||
Scenario (S) | 0.015 | 0.054 | 0.003 | 0.081 | 0.066 | <0.001 | |||
O × S | 0.020 | 0.043 | J&M | <0.001 | 0.062 | J | 0.081 | <0.001 | M |
Leaf angle | |||||||||
Origin (O) | 0.015 | 0.056 | 0.002 | 0.052 | 0.043 | 0.046 | |||
Scenario (S) | 0.564 | 0.042 | 0.054 | 0.091 | 0.976 | 0.091 | |||
O × S | 0.031 | 0.045 | J&M | 0.043 | 0.069 | J | 0.077 | 0.076 | --- |
WUE | |||||||||
Origin (O) | <0.001 | 0.035 | <0.001 | 0.032 | 0.036 | 0.052 | |||
Scenario (S) | 0.043 | 0.041 | 0.003 | 0.055 | 0.044 | 0.128 | |||
O × S | 0.021 | 0.040 | J&M | 0.002 | 0.041 | J&M | 0.037 | 0.767 | J |
Analyses were performed separately for each environmental gradient, considering origin (O; native vs. invasive) as main factor and abiotic scenario (S) as covariate. For each environmental gradient, we considered four abiotic scenarios ranging from unfavorable (S1) to favorable (S4) abiotic conditions. Temperature was 5 or 25°C, light was 2000 or 1000 µmol m−2 s−1 and water was irrigation every 7 or 3 days. Temperature–light gradient: 2000 + 5 (S1), 1000 + 5 (S2), 2000 + 25 (S3) and 1000 + 25 (S4). Water–light gradient: 2000 + 7 (S1), 1000 + 7 (S2), 2000 + 3 (S3) and 1000 + 3 (S4). Temperature–water gradient: 7 + 25 (S1), 7 + 5 (S2), 3 + 5 (S3) and 3 + 25 (S4); see text for more details. Strategies deployed: Jack-of-all-trades (J), Master-of-Some (M), Jack-and-Master (J&M) or none (–). Scenario S3 to S1: Jack-of-all-Trades strategy and scenario S2 to S4: Master-of-Some strategy.
Water and light gradient
Greater plant biomass was found in T. officinale throughout the S3 to S1 scenarios (unfavorable setting; Fig. 1C, Table 1). However, the accumulation of biomass decreased with less favorable scenarios similarly in both species, i.e. the Jack-of-all-trades strategy was not found (Fig. 1C, Table 1). Plant biomass was also greater in the invasive dandelion across the S2 to S4 scenarios (favorable setting; Fig. 1C, Table 1). In this case, although the accumulation of biomass increased toward more favorable scenarios in both species, the increase was greater in T. officinale (Fig. 1C), indicating a Master-of-some strategy. Overall, survival percentage was higher in T. officinale than in H. thrincioides across the S3 to S1 scenarios, where this difference was increased toward the most unfavorable scenario (S3 = 0%, S8 = 8%, and S1 = 8%, Fig. 1D), and throughout the S2 to S4 scenarios, where this difference was higher in the most favorable abiotic condition (S2 = 8%, S3 = 0%, and S4 = 16%, Fig. 1D). Thus, plant survival patterns suggested a Jack-and-Master strategy in T. officinale. Regarding ecophysiological traits, T. officinale showed significantly higher Amax and WUE, as compared to H. thrincioides, when grown both under stressful conditions (S3 to S1) and under more favorable conditions (S2 to S4), suggesting that the expression of these ecophysiological traits in the invasive species are consistent with a Jack-and-Master strategy (Table 2). On the other hand, T. officinale showed a significantly less steep increase in NPQ and foliar angles (Table 2) than the native H. thrincioides under stressful conditions (S3 to S1), but neither NPQ nor foliar angles differed between the invasive dandelion and its native counterpart under more favorable conditions (S2 to S4), suggesting that for these ecophysiological traits the invader displays a Jack-of-all-trades strategy (Table 2).
Water and temperature gradient
Total plant biomass was significantly higher in T. officinale throughout the unfavorable and favorable scenarios (Fig. 1E, Table 1). Specifically, the decrease in biomass with less favorable scenarios was of lesser magnitude and the biomass increase toward more favorable scenarios was greater in T. officinale (Fig. 1E, Table 1), suggesting a Jack-and-Master strategy. Overall, survival percentage was higher in T. officinale considering the S1 to S3 scenarios, where this difference increased under the most unfavorable scenario (S3 = 4%, S2 = 8%, and S1 = 12%, Fig. 1F), and considering the S2 to S4 scenarios, where this difference increased toward more favorable abiotic conditions (S2 = 8%, S3 = 4%, and S4 = 20%, Fig. 1F). Consequently, survival patterns were also consistent with a Jack-and-Master strategy in the invasive species. Regarding ecophysiological traits, with the exception of foliar angles, the ANCOVA was significant for the interaction (origin × scenario) of all ecophysiological traits measured (Table 2). Specifically, following the criteria used for the preceding cases, it was concluded that variation in Amax, NPQ and WUE corresponded to Jack-and-Master, Master-of-some and Jack-of-all-trades strategies, respectively (Table 2).
Fitness variation in T. officinale across environmental gradients
The fitness losses in the unfavorable settings (Jack-of-all-trades strategy), measured as the differences in seedling survival between the S3 and S1 scenarios, were lower for T. officinale compared to the native H. thrincioides (P = 0.054, t-test for dependent samples, n = 3 environmental gradients; Fig. 1). Fitness gains in the favorable settings (Master-of-some strategy), measured as the differences in seedling survival between the S2 and S4 scenarios, were higher for T. officinale compared to H. thrincioides (P = 0.015, t-test for dependent samples, n = 3; Fig. 1). Therefore, overall survival patterns supported the hypothesis that T. officinale would show a Jack-and-Master strategy.
Summarizing, as compared to H. thrincioides, T. officinale showed a Jack-and-Master strategy in fitness-related traits across environmental gradients, and this could be based on ecophysiological responses. Thus, fitness patterns under unfavorable conditions in this invasive species could be explained by a lesser decrease in Amax and increased WUE, NPQ and leaf angles in all three gradients (Table 2, Fig. 2). On the other hand, fitness patterns under favorable conditions could be explained by a higher increase in Amax and lesser decrease in WUE (all three gradients), as well as a lesser increase in NPQ in the water + temperature gradient (Table 2, Fig. 2).

maximum photosynthesis rate (Amax; in µmol m−2s−1), non-photochemical quenching (NPQ), angles of leaves, and water use efficiency (WUE; in µmol m−2s−1/mmol m−2s−1) in the invasive Taraxacum officinale (closed circles) and in the closely related native Hypochaeris thrincioides (open circles) exposed to three different environmental gradients, each with four stress levels ranging from unfavorable (S1) to favorable scenarios (S4; see Figure 1 for more details).
DISCUSSION
Invasive plant species represent a major threat to biodiversity and cause significant economic costs (Pimentel et al. 2005; Ricciardi et al. 2011). The establishment and spread of invasive plants outside their native range depends on both biotic and abiotic factors, such as propagule pressure, abiotic characteristics of the invaded ecosystem, traits of the invaders and the interactions between the invasive species and the native community (Richardson and Pysek 2006). The identification of mechanisms underlying successful invasions is a key issue in invasion ecology studies (Daehler 2003; Davis et al. 2000; Rejmánek and Richardson 1996; Richards et al. 2006; Seastedt and Pysek 2011). In this regard, Hulme (2008) indicated that rather than simply quantifying greater phenotypic plasticity in invasive species, research questions should be aimed at better understanding its role in the geographic distribution, successful colonization and higher local abundance of invasive species in the introduced range. We may add that integrated measures of ecophysiological and fitness-related traits, rather than particular differences in individual traits across an environmental gradient, are essential to link plasticity with invasion. Baker’s (1965) ideal weed, by maintaining fitness in resource-poor environments and maximizing fitness in favorable conditions, embodied both the Jack-of-all-trades and Master-of-some strategies, which presumably explain successful plant invasions (McAlpine et al. 2008; Mozdzer and Megonigal 2012; Pichancourt and van Klinken 2012).
Here, we have shown that the invasive T. officinale exhibits this Jack-and-Master strategy due to its ability to both maintain higher biomass accumulation and survival in unfavorable conditions and increase its fitness when conditions are favorable, compared with the closely related native H. thrincioides. We suggest that this combination of strategies in fitness-related traits, resulting from ecophysiological responses, contribute significantly to the invasiveness of this species across changing environments (Molina-Montenegro and Naya 2012; Molina-Montenegro et al. 2013b). Phenotypic plasticity has long been suggested to facilitate biological invasions across changing environments by enabling a robust ecophysiological performance (Hulme 2008; Molina-Montenegro et al. 2013b). Understanding how and why certain strategies or biological traits promote invasiveness is of paramount importance for invasive species management, and for this reason several studies have addressed differences among native vs. invasive or native vs. non-native taxa (van Kleunen et al. 2010; Palacio-López and Gianoli 2011). The higher ecophysiological performance and fitness shown by T. officinale—compared to H. thrincioides—suggests that a Jack-and-Master strategy could help explain the establishment and invasion success of T. officinale. Nonetheless, this finding cannot be extrapolated to other successful invasive species without appropriate experimental evaluation. Comparisons among several native and invasive taxa would shed light on the generality of the Jack-and-Master strategy as the mechanisms underlying successful invasion processes. Furthermore, although we carefully chose the study species pair taking into account phylogeny, ecological niche, growth habit and biology in general, we cannot rule out that a factor other than species origin (invasive/native) may also partly explain the observed results. A single pairwise comparison, however adequate, has obvious limitations concerning the generality of the conclusions that can be drawn.
There are few reported examples of a Jack-and-Master strategy in the invasion literature. It has even been suggested that such invaders may reflect a relatively rare strategy in nature (Mozdzer and Megonigal 2012). Nevertheless, the dearth of published cases may be due to the difficulties in correctly assessing Jack-and-Master invaders. Thus, for a rigorous test of whether invasive species show this strategy, it would be required: (i) ecologically and taxonomically related species pairs in order to minimize phylogenetic biases (Palacio-López and Gianoli 2011), (ii) the use of F2 plants for each species, as it has been shown that maternal effects can influence phenotype and fitness responses (Gianoli 2002), (iii) information on both phenotypic plasticity in ecophysiological traits and fitness-related traits and (iv) the use of several conditions/scenarios and abiotic gradients to enhance the realism and generality of the outcome (Richards et al. 2006). Moreover, comparisons of performance and fitness of the invader species against that of the dominant native species in the community prior to invasion are very informative and valuable, and thus could constitute a fifth requisite, but this is not always feasible. Not surprisingly, it is hard to find many rigorous cases of Jack-and-Master invaders. Although two recent articles have claimed to demonstrate the importance of Jack-and-Master phenotypic plasticity in plant invasions (Mozdzer and Megonigal 2012; Pichancourt and van Klinken 2012), these studies show some limitations. Mozdzer and Megonigal (2012) did not include a stressful scenario, only average and enriched environments. In addition, they did not consider a fitness response variable, and the occurrence of a Jack-and-Master strategy is claimed but not supported by statistical analyses. Pichancourt and van Klinken (2012) did not include a clear gradient of stress, and all procedures were made on an invasive species, with no comparison with a native counterpart. In addition, phenotypic plasticity was not assessed by an experimental approach, but only inferred from field data. Thus, to our knowledge, our study is the first one meeting the requirements to demonstrate empirically the Jack-and-Master strategy in an invasive plant. Moreover, we provide a mechanistic basis for the fitness patterns observed in T. officinale (see Fig. 3).

graphical model describing the effects of different environmental conditions on an invasive plant species (e.g. Taraxacum officinale) and on a closely related native species. It is shown that plasticity in ecophysiological traits may explain how the invasive species maintains a relatively constant fitness in unfavorable conditions (‘Jack-of-all-trades’ strategy) and enhances its performance in favorable conditions (‘Master-of-some’ strategy). It is suggested that the combined strategies (‘Jack-and-Master’) could help explain T. officinale invasion and spread along changing environments.
Studies that address species’ traits that favor invasion highlight the importance of ecophysiological, morphological, life history and fitness traits (van Kleunen et al. 2010; Molina-Montenegro et al. 2012a; Rejmánek and Richardson 1996). However, few studies addressing the importance of traits associated with invasion success measure plant traits in more than one environment, as is recommended (Berg and Ellers 2010; Burns 2004; Leicht-Young et al. 2007; Williams et al. 2008). By using a suitable plant model and a rigorous experimental protocol, we could identify the strategy that presumably explains the invasion success of T. officinale, an aggressive invasive plant that is distributed worldwide (Holm et al. 1997), particularly in changing environments (Molina-Montenegro and Naya 2012; Molina-Montenegro et al. 2013b). Specifically, in this study we demonstrated that at least in five out of six abiotic scenarios (combination of two fitness-traits × three abiotic gradients), T. officinale lost less fitness with increased environmental stress and/or gained more fitness when environmental conditions were more favorable.
Although greater biomass accumulation and survival under experimental conditions can be useful predictors of invasion success, several other plant features may influence colonization and expansion. Previous studies have shown that T. officinale is more tolerant to simulated herbivory (Molina-Montenegro et al. 2013b) and has greater competitive ability (Molina-Montenegro et al. 2012b) than the native Hypochaeris spp., and has higher WUE than its native congener T. ceratophorum (Brock et al. 2005). Taken together, this evidence and the results herein reported—obtained in a realistic combination of climatic scenarios—strongly suggest a superior capacity of exploitation of resource availability and a greater climatic tolerance in the invasive dandelion, which would facilitate colonization of new habitats through the combined Jack-and-Master strategy. To provide a better understanding of this strategy, we provide a graphical model that shows how plasticity in ecophysiological traits may maintain fitness under unfavorable conditions and improve resource use efficiency under favorable conditions, compared to a native species. Both strategies may contribute to invasion success in changing environments (Fig. 3).
Considering that climate is changing globally, the understanding of the strategies underlying invasion success in changing environments has become an issue of paramount importance for invasion ecologists. We are still far from a comprehensive understanding of the strategy used by successful plant invaders to spread across changing environments worldwide. Nonetheless, we herein provide a piece of evidence in a suitable system showing the occurrence of the Jack-and-Master strategy in a successful invasive plant.
ACKNOWLEDGEMENTS
Thanks to Graciela Valencia, Alexis Estay, Leticia González, Claudia Bavestrello and Rodrigo Álvarez for their assistance with experimental procedures. We thank Luis J. Corcuera and two anonymous reviewers for helpful comments on earlier versions of this manuscript. No specific permits were required for seed collection in the localities sampled in this study and all populations are not privately owned or protected in any way. Additionally, we declare that the field studies did not involve endangered or protected species.