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Modeling potential habitats and predicting habitat connectivity for Leucanthemum vulgare Lam. in northwestern rangelands of Iran

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Abstract

Invasive plants can alter the function and structure of ecosystems resulting in social, economic, and ecological damage. Effective methods to reduce the dominance of invasive plants are needed. The present study was aimed at modeling the invasive species Leucanthemum vulgare Lam. in the rangelands of the Namin region in northwest Iran, as well as predicting the habitat connectivity of this species to detect areas with high habitat connectivity. Modeling of potential habitats was performed using logistic regression (LR) and maximum entropy (MaxEnt); the ensemble map which resulted from these was used to predict habitat connectivity using the electrical circuit method. Topography (elevation, slope, and aspect), climate (precipitation and temperature), and soil (acidity, electrical conductivity, soil texture, calcium, magnesium, sodium, phosphorus, potassium, organic carbon, organic matter, saturation percentage, and total neutralizing value) were used in this study. The presence and absence points of the L. vulgare were recorded using a stratified-random sampling method by means of a global positioning system. Soil samples were collected at a depth of 0 to 30 cm where L. vulgare was present and also where it was absent. According to the results, in LR, the variables of temperature, phosphorus, organic matter, and sand and in the MaxEnt, the variables of sand, total neutralizing value (TNV), and silt were the most influential factors on the distribution of L. vulgare. The appraisal of the MaxEnt performance and the precision of the model prediction were 0.97. The Kappa indices for the predicted map obtained from the LR and MaxEnt models were 0.80 and 0.73, respectively. The models’ evaluation indicated that both models were able to predict the distribution of L. vulgare habitats with a high level of accuracy; however, LR was more reliable. According to the LR prediction, 9.91% (10,556.25 ha) of the Namin region was attacked by L. vulgare. Connectivity assessment showed that the current density spread of L. vulgare continued from the northeast of the Namin region toward the southeast. On the other hand, the higher current density spread was demonstrated in the eastern region (rangelands adjacent to Fandoghlu forests), and other rangelands which are more threatened by the invasion of L. vulgare. Identifying sites exposed to invasive species can help implement programs to prevent invasive species from invading areas where management and prevention should be implanted to prevent and/or reduce the spread.

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Data availability

The datasets generated during and/or analyzed in the current study are available from the corresponding author on reasonable request.

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Funding

The research was the PhD thesis of the first author under the supervision and advisory of the co-authors, and it was funded by the University of Mohaghegh Ardabili, Iran, under the terms of Student Grant.

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Authors and Affiliations

  1. Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

    Sahar Samadi Khanghah, Mehdi Moameri, Ardavan Ghorbani & Raoof Mostafazadeh

  2. School of Environmental Sciences, University of Guelph, Guelph, Canada

    Asim Biswas

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  1. Sahar Samadi Khanghah
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  2. Mehdi Moameri
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  3. Ardavan Ghorbani
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  4. Raoof Mostafazadeh
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Contributions

S. Samadi Khanghah (first author), original researcher, introduction, author, methodologist, statistical analyst, writing-review and editing (35%); M. Moameri (second author), original researcher, methodologist, statistical analyst, discussion author, writing-review and editing (30%); A. Ghorbani (third author), methodologist, statistical analyst (20%); R. Mostafazadeh (fourth author), assistant researcher, statistical analyst, writing-review and editing (10%); A. Biswas (fifth author), assistant researcher, writing-review and editing (5%). All authors have read and agreed to the published version of the manuscript.

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Correspondence to Mehdi Moameri.

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Khanghah, S.S., Moameri, M., Ghorbani, A. et al. Modeling potential habitats and predicting habitat connectivity for Leucanthemum vulgare Lam. in northwestern rangelands of Iran. Environ Monit Assess 194, 109 (2022). https://doi.org/10.1007/s10661-021-09716-5

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