GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra 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 local agricultural and natural areas, especially to Ba Na - Nui Chua Nature Reserve located in the district. In this study, a habitat model was...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Sciendo
2019-06-01
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| Series: | Metsanduslikud Uurimused |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/fsmu-2019-0003 |
| _version_ | 1818307536272490496 |
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| author | Le Thai Son Thoa Pham Thi Kim Tuan Nguyen Van |
| author_facet | Le Thai Son Thoa Pham Thi Kim Tuan Nguyen Van |
| author_sort | Le Thai Son |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T06:59:56Z |
| format | Article |
| id | doaj.art-debdeafaa926425dab446a1d8b050ab8 |
| institution | Directory Open Access Journal |
| issn | 1736-8723 |
| language | English |
| last_indexed | 2024-12-13T06:59:56Z |
| publishDate | 2019-06-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Metsanduslikud Uurimused |
| spelling | doaj.art-debdeafaa926425dab446a1d8b050ab82022-12-21T23:55:58ZengSciendoMetsanduslikud Uurimused1736-87232019-06-01701314310.2478/fsmu-2019-0003GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L.Le Thai Son0Thoa Pham Thi Kim1Tuan Nguyen Van2Vietnam National University of Forestry, Xuan Mai Town, Chuong My District, Hanoi, VietnamThe University of Da Nang - University of Science and Technology, Da Nang, VietnamDepartment of Silviculture Foundation, Silviculture Research Institute, Vietnam Academy of Forest Sciences, Hanoi, VietnamIncursions 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.https://doi.org/10.2478/fsmu-2019-0003gishabitat modellingmahalanobis distancepredictive model |
| spellingShingle | Le Thai Son Thoa Pham Thi Kim Tuan Nguyen Van GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. Metsanduslikud Uurimused gis habitat modelling mahalanobis distance predictive model |
| title | GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. |
| title_full | GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. |
| title_fullStr | GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. |
| title_full_unstemmed | GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. |
| title_short | GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L. |
| title_sort | gis based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant mimosa pigra l |
| topic | gis habitat modelling mahalanobis distance predictive model |
| url | https://doi.org/10.2478/fsmu-2019-0003 |
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