<abstract xmlns="http://www.w3.org/1999/xhtml">Incursions of <italic>Mimosa pigra</italic> L., a super-invasive plant, were detected in Hoa Vang district, Da Nang city, Vietnam. This invasive species posed threats to the local agricultural and natural areas, especially to Ba Na - Nui Chua Nature Reserve located in the district. In this study, a habitat model was developed to predict potential areas for the upcoming occurrences of the plant. Detected locations of the species were analyzed in association with seven environmental layers (15 m spatial resolution), which characterized the habitat conditions facilitating the plant incursion, to calculate a multivariate statistic, Mahalanobis distance (<italic>D2</italic>). Mimosa occurrences were divided into subsets of modelling (for model construction) and validating data (for selecting the best model from replicate runs). The model performance was tested using a null model of 1,000 random points and indicated a significant relationship between <italic>D2</italic> values and mimosa occurrence. The <italic>D2</italic> model performed markedly better than the random model. The null model in combination with the entire dataset of mimosa locations was also used to identify the threshold <italic>D2</italic> value. Using that threshold value, 99.5% of existing mimosa locations were detected and 20.3% of the study area was determined as high-risk areas for mimosa occurrence. These identified high risk areas would make an important contribution to the local alien invasive species management. Given the potential threats to these species from illegal harvesting, that information may serve as an important benchmark for future habitat and population assessments. The spatial modelling techniques in this study can easily be applied to other species and areas.</abstract>

Incursions of Mimosa pigra L., a super-invasive plant, were detected in Hoa Vang district, Da Nang city, Vietnam. This invasive species posed threats to the local agricultural and natural areas, especially to Ba Na - Nui Chua Nature Reserve located in the district. In this study, a habitat model was developed to predict potential areas for the upcoming occurrences of the plant. Detected locations of the species were analyzed in association with seven environmental layers (15 m spatial resolution), which characterized the habitat conditions facilitating the plant incursion, to calculate a multivariate statistic, Mahalanobis distance (D2). Mimosa occurrences were divided into subsets of modelling (for model construction) and validating data (for selecting the best model from replicate runs). The model performance was tested using a null model of 1,000 random points and indicated a significant relationship between D2 values and mimosa occurrence. The D2 model performed markedly better than the random model. The null model in combination with the entire dataset of mimosa locations was also used to identify the threshold D2 value. Using that threshold value, 99.5% of existing mimosa locations were detected and 20.3% of the study area was determined as high-risk areas for mimosa occurrence. These identified high risk areas would make an important contribution to the local alien invasive species management. Given the potential threats to these species from illegal harvesting, that information may serve as an important benchmark for future habitat and population assessments. The spatial modelling techniques in this study can easily be applied to other species and areas.

GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, <italic>Mimosa pigra</italic> L.

The University of Da Nang - University of Science and Technology

Forestry Studies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant,  L.

Incursions of Mimosa pigra L., a super-invasive plant, were detected in Hoa Vang district, Da Nang city, Vietnam. This invasive species posed threats to the...

GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L.

Online veröffentlicht: 21. Nov. 2019

Seitenbereich: 31 - 43

Eingereicht: 18. Apr. 2019

Akzeptiert: 06. Sept. 2019

DOI: https://doi.org/10.2478/fsmu-2019-0003

Schlüsselwörter
GIS, habitat modelling, Mahalanobis distance, predictive model

© 2019 Thai Son Le et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L.

Online veröffentlicht: 21. Nov. 2019

Seitenbereich: 31 - 43

Eingereicht: 18. Apr. 2019

Akzeptiert: 06. Sept. 2019

DOI: https://doi.org/10.2478/fsmu-2019-0003

SchlüsselwörterGIS, habitat modelling, Mahalanobis distance, predictive model

© 2019 Thai Son Le et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
GIS, habitat modelling, Mahalanobis distance, predictive model