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Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia.

Wakie TT, Evangelista PH, Jarnevich CS, Laituri M - PLoS ONE (2014)

Bottom Line: Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95).Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora.Our methods can also be replicated for managing invasive species in other East African countries.

View Article: PubMed Central - PubMed

Affiliation: Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, United States of America; Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, United States of America.

ABSTRACT
We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

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Related in: MedlinePlus

Prosopis juliflora reflectance.Box plots of P. juliflora EVI and NDVI reflectance values. Note that NDVI and EVI values for the other months were dropped from the final model due to cross-correlations.
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pone-0112854-g002: Prosopis juliflora reflectance.Box plots of P. juliflora EVI and NDVI reflectance values. Note that NDVI and EVI values for the other months were dropped from the final model due to cross-correlations.

Mentions: The remote sensing and topographic predictors with the highest percent contribution for mapping current distributions were November EVI (43.5%), April NDVI (15.7%), elevation (12.8%), and slope (6.6%; Table 1). The NDVI and EVI values for P. juliflora showed similar trends with higher values recorded in September, and lower values recorded in March (Figure 2). The NDVI values were always higher than the EVI values. Visual inspection of the current P. juliflora distribution map shows that infestation is dominant in the Gabi, Awsi, and Hari administrative zones, respectively (Figure 3). According to the model, the northern most administrative area, Kilbet, is the least invaded. The banks of Awash River are heavily invaded by P. juliflora (Figure 3). Area calculations of model results show that the current predicted distribution of P. juliflora invasion covers 3,605 km2 of the Afar region. The remote sensing and topo-climatic predictors correlated well with the P. juliflora occurrence data, with both having high Kappa and AUC values. Kappa and AUC values based on the independent data for the current model were 0.85 and 0.94, respectively (Table 3).


Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia.

Wakie TT, Evangelista PH, Jarnevich CS, Laituri M - PLoS ONE (2014)

Prosopis juliflora reflectance.Box plots of P. juliflora EVI and NDVI reflectance values. Note that NDVI and EVI values for the other months were dropped from the final model due to cross-correlations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231090&req=5

pone-0112854-g002: Prosopis juliflora reflectance.Box plots of P. juliflora EVI and NDVI reflectance values. Note that NDVI and EVI values for the other months were dropped from the final model due to cross-correlations.
Mentions: The remote sensing and topographic predictors with the highest percent contribution for mapping current distributions were November EVI (43.5%), April NDVI (15.7%), elevation (12.8%), and slope (6.6%; Table 1). The NDVI and EVI values for P. juliflora showed similar trends with higher values recorded in September, and lower values recorded in March (Figure 2). The NDVI values were always higher than the EVI values. Visual inspection of the current P. juliflora distribution map shows that infestation is dominant in the Gabi, Awsi, and Hari administrative zones, respectively (Figure 3). According to the model, the northern most administrative area, Kilbet, is the least invaded. The banks of Awash River are heavily invaded by P. juliflora (Figure 3). Area calculations of model results show that the current predicted distribution of P. juliflora invasion covers 3,605 km2 of the Afar region. The remote sensing and topo-climatic predictors correlated well with the P. juliflora occurrence data, with both having high Kappa and AUC values. Kappa and AUC values based on the independent data for the current model were 0.85 and 0.94, respectively (Table 3).

Bottom Line: Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95).Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora.Our methods can also be replicated for managing invasive species in other East African countries.

View Article: PubMed Central - PubMed

Affiliation: Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, United States of America; Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, United States of America.

ABSTRACT
We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

Show MeSH
Related in: MedlinePlus