Corresponding author: Reham F. El-Barougy ( email@example.com )
Academic editor: Brad Murray
© 2017 Reham F. El-Barougy, Marc W. Cadotte, Abdel-Hameed A. Khedr, Reham M. Nada, J. Scott Maclvor.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: El-Barougy RF, Cadotte MW, Khedr A-HA, Nada RM, Maclvor SJ (2017) Heterogeneity in patterns of survival of the invasive species Ipomoea carnea in urban habitats along the Egyptian Nile Delta. NeoBiota 33: 1-17. https://doi.org/10.3897/neobiota.33.9968
Plant traits are critical for understanding invasion success of introduced species, yet attempts to identify universal traits that explain invasion success and impact have been unsuccessful because environment-trait-fitness relationships are complex, potentially context dependent, and variation in traits is often unaccounted for. As introduced species encounter novel environments, their traits and trait variability can determine their ability to grow and reproduce, yet invasion biologists do not often have an understanding of how novel environments might shape traits. To uncover which combination of traits are most effective for predicting invasion success, we studied three different urban habitat types along the Nile Delta in Egypt invaded by the Pink Morning Glory, Ipomoea carnea Jacq. (Family: Convolvulaceae). Over two years, we measured ten plant traits at monthly intervals along an invasion gradient in each habitat. No single trait sufficiently explained survival probability and that traits linked to invasion success were better predicted by the characteristics of the invaded habitat. While the measured traits did influence survival of I. carnea, the importance of specific traits was contingent on the local environment, meaning that local trait-environment interactions need to be understood in order to predict invasion.
Invasion success, Exotic species, Survival probability, Morning Glory, Disturbed habitat
Biological invasion is a significant threat to biodiversity and often leads to habitat degradation (
At a more basic level, we often lack a basic understanding of how size and life history traits contribute to the successful growth and reproduction of most species and especially non-native species. The attributes that are associated with successful species is undoubtedly correlated with local environmental conditions (
A number of studies have shown that invasion success can be linked to specific traits and the degree to which they promote survival in novel environments. These include for example, traits linked with reproduction and dispersal, leaf traits that are believed to reflect competitive strategies, overall resource allocation into growth, and seedling growth patterns (
While the search for the attributes that influence species performance and especially invasion would undoubtedly lead to advancing general theory, it is often underappreciated just how sensitive trait-performance relationships can be to local environmental conditions. The appreciation of the importance of intraspecific trait variation has greatly increased in community ecology (
This study investigates the aboveground and belowground plant attributes, and especially those that reflect resource allocation, that influence the survivorship of the invasive pink morning glory, Ipomoea carnea Jaq. (Family: Convolvulaceae), in three unique urbanized habitats that it invades in the Nile Delta region in Egypt. Ipomoea carnea is an annual vine that is native to Central and South America, but occurs worldwide in many habitats, including the Nile Delta where it is invasive (
The study area is bound by the main tributaries of the Nile Delta in Egypt, from the Rosetta branch at the west to the Damietta Governorate at the east, the Mediterranean Sea to the north and the Menoufia Governorate to the South. The area of the Nile Delta is about 22,000km2 and it comprises about 63% of Egypt’s productive agricultural area (
Nine permanent stands in Damietta Governorate were established in each of three different urban habitats where the invasive I. carnea occurred: wastelands, roadsides (both with dry-sandy soil) and canal banks (with clay-organic soil) (
Ten randomly distributed quadrats (1 × 1 m) were laid down in each stand. The number of I. carnea ramets in each quadrat was counted and used to estimate I. carnea density per stand (ramets/ m2). Ten ramets (1 per m2 plot) were randomly selected and marked using flagging tape to monitor the monthly variation in each of the plant traits. The height from the ground (cm), average diameter (cm), leaf area (cm2), number of flowering ramets, number of non-flowering ramets, number of leaves, flowers and fruits of the canopy for each permanent marked ramet were estimated monthly.
Three randomly selected ramets were harvested from each stand and their roots, stems and leaves were separated and weighted to determine their fresh weights. The roots, stems and leaves were oven dried at 60°C for three days to determine the dry weight. Mean fresh and dry weights of the roots, stems and leaves of the ramets of each habitat were determined (gm ramet-1) and multiplied by the number of ramets (m-2) in each stand to give their standing crop (gm-2) in each habitat (
In each stand, a composite soil sample was collected from beneath invaded and non-invaded canopies from each habitat, each 50 cm deep. These were air dried and passed through a 2 mm sieve to separate gravel and debris. Soil water extracts at 1:5 were prepared for the determination of soil reaction (pH) using a Benchtop pH Meter (Mettler-Toledo).
There were 14 different variables used in generalized multivariable modelling (Table
List of measured variables from which the average values were taken from 10 plants per stand in each of the three urban habitats (Canal banks, Wastelands and Roadsides).
|Total surviving and dead ramets||-||y|
|Number of all leaves||-||NL|
|Number of flowering ramets||-||Flr|
|Number of non-flowering ramets||-||NFlr|
|Number of flowers||-||Fl|
|Soil pH under canopy (invaded areas)||-||PhU|
|Soil pH outside canopy (non-invaded areas)||-||PhO|
For each urban habitat, we assessed the observed survival probability based on the ratio between the observed number of surviving ramets and total ramets (including surviving and dead ramets), while the fitted survival probability was assessed from each multivariable model as fitted values. We tested the difference between the observed and fitted survival probability values for all multivariable models to confirm that the difference between observed and fitted values from the best model was very low. Further, for each modelled trait, we assessed which trait values tended to have higher or lower survival probabilities. All analyses were completed using R v.3.2.2 (
We modelled the probabilities of survival as a function of the plant traits and environmental variables in different habitats and to do this we used odds ratio to predict the upper and lower limit of the ratio of the probability of success (survival) and the probability of failure (death) for each modelled variable. Odds ratios were also used to test for possible associations between different environmental variables. If the OR is equal to 1, there is no association. If the OR is (> 1and <1), then there is a possible statistical association between them (Morris et al. 1988,
There was a highly significant effect of habitat on survival probability of I. carnea with lower survival probability in wastelands and roadsides compared to canal banks which showed a remarkably highly survival probability. For adult ramet mortality, wasteland and roadside had the highest, while canal banks had the lowest (Fig.
a Comparison between the mean of observed survival probability at habitat level b–d the relationship between fitted survival probabilities from the three top models and survival probabilities from the actual observed data in canal banks, roadsides and wastelands respectively.
Comparing the mean plant trait values and abiotic variables in different habitats, forty generalized linear models were constructed (Suppl. material
For the abiotic variables, there was a positive significant interaction between the binomial response variable and sampling time in canal bank, while this interaction showed a negative significant effect in road side habitats. Additionally, being in soil with high pH (>7) values resulted in lower I. carnea survival in wasteland habitat (Table
Comparison of the top multivariable models from the stratified generalized linear models. The confidence interval (CI) with upper (U) and lower limit (L) and odds ratios (OR) for the modelled coefficients in the three habitats: canal banks (CB), roadsides (RS), waste lands (WL). (-) represents a variable that is excluded in the given top model.
|Variables||Coefficients||CI (U,L)||Odds ratio (OR)||P-value|
|Month||0.79||-||-0.145||0.577, 1.025||-||-0.24, -0.05||2.2||-||0.86||0.00||-||0.003|
|Leaf biomass||-0.03||-0.001||-||-0.032, -0.018||-0.002, -2.9×10-4||-||0.97||0.99||-||0.00||0.02||-|
|# Flowering ramets||0.46||-||0.13||0.276, 0.730||-||0.05,0.21||1.58||-||1.13||0.00||-||0.000|
|# Flowers||0.13||-||-||0.055, 0.190||-||-||1.14||-||-||0.00||-||-|
|# Non-flowering ramets||0.09||-||0.05||-3.2×10-4, 0.200||-||0.001,0.11||1.09||-||1.05||0.05||-||0.05|
|Root biomass||0.02||-0.001||-||-8.5×10-5, 0.030||-0.002, -1.7×10-6||-||1.01||0.99||0.02||0.05||-|
|Number of leaves||-||0.013||-||-||-0.002, 2.8×10-2||-||-||1.01||-||0.10||-|
|Soil PH (under canopy)||-||-0.79||0.95||-||-1.52,-7.3×102||-0.24,2.12||-||0.45||2.6||-||0.03||0.11|
All of the I. carnea biomass traits differed significantly between habitats. Higher values of leaf biomass had a strongly significant negative effect on the survival rate in canal bank and wasteland. Additionally, higher root biomass decreased survival rate in wasteland but increased survival in canal bank. Other traits that significantly increased survival probability included the number of leaves in wasteland habitat, higher values of flowering ramets and non-flowering ramets in road sides, and the number of flowers in canal banks. Although declining stem diameter led to a significant reduction in survival rate in wasteland habitats, smaller stems were positively correlated with survival rate in roadside habitats (Table
Furthermore, when we tested the difference between the observed survival probability from actual data and fitted survival probability from the three top models in different habitats, we found that the difference was very low compared to other models (Fig.
The odds ratio and confidence interval for modelled variables were interpreted as the ratio of the probability of success (survival) over the probability of failure (mortality). For each top model, we used odds ratios as a measure of statistical significance of the association between each modelled traits and survival probability. Accordingly, all odds ratios were (>1 and <1) (Table
The relationship between survival probability and predictors from the top model for Canal bank habitat.
The relationship between survival probability and predictors from the top model for wasteland habitat.
In our study we showed that plant attributes associated with the survival of the invasive species I. carnea differed by urban habitat type. Confirming recent calls for the inclusion of intraspecific variation in ecological studies, we showed that growth and biomass allocation traits were indeed important for predicting species performance, but that the important traits differed among the habitats analyzed. Our results showed that using morphological plant traits provides a simple approach to understand invasive species survival in novel habitats. The critical conclusion is that while the measured traits did influence survival of I. carnea, the importance of specific traits was contingent on the local environment, meaning that local trait-environment interactions need to be understood in order to predict and plan for invasive species.
Our study showed a clear selection of traits in different habitats (Table
However, it should be noted that size-based traits were the best predictors for invader survival, which is in some ways not surprising. It is well known that larger plants have higher survival probabilities and greater reproduction (
Traits linked to invader colonization in new environments are those most likely to predict invasion success. Trait-environment relationships were also consistent with general patterns observed along large ecological gradients (
From the top models, our study showed a significant relationship between leaf traits and different habitats. For example, there was a positive significant effect of the number of leaves on the survival probability of I. carnea in wastelands, whereas survival probability decreased significantly with increasing leaf biomass in canal banks and wastelands habitat.
It should be noted that the three habitat types were spatially segregated and thus the analyses would be pseudo replicated if included in single statistical models (
This study concluded that trait-environment interactions are critical predictors of invader species survival and subsequent success in novel urban habitats. As invasive plant species continue to pose significant threat to natural areas, understanding how they interact in novel, urban habitats is often a first step to understand the dynamics of invasive species in more pristine and protected habitats. Our approach was able to predict the local abundance of I. carnea across a large ecological gradient. Also it can help to assess monitoring of invasive species in native Egyptian ecosystems. We gain a better insight on the rapid growth and adaptability of I. carnea from dry to aquatic habitats which may indicate that this plant is capable of rooting within a few days (
The authors sincerely thank Sohee Kang (Professor of biostatistics, Department of Math and computer science, Toronto University, Scarborough) for her help in stats analysis that greatly improved our manuscript. MWC was supported by the TD Professor of Urban Forest Conservation and Biology chair, Canada Foundation for Innovation, the Ontario Research Fund, and Natural Sciences and Engineering Research Council of Canada (#386151).