Change in habitat suitability of the invasive Snowflake coral (Carijoa riisei) during climate change: An ensemble modelling approach

Nisin K.M.N., Mohamed; K.R., Sreenath; Paul Sreeram, Miriam

doi:10.1016/j.ecoinf.2023.102145

Cited by 5 publications

(1 citation statement)

References 85 publications

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“…Based on the performance of the Ensemble Species Distribution Model, the ensemble model was regarded as suitable in predicting environmental suitability for the anthrax outbreaks in Zimbabwe under different climate scenarios as it had ROC > 0.7, TSS and Kappa > 0.6. The employment of multiple metrics for model validation is a standard practice that ensures the reliability of the model results and helps uncover errors and inconsistencies from different angles [54][55][56][57][58]. For instance, [54] clearly demonstrated how TSS can overcome some of the weaknesses associated with Kappa statistic while preserving the positive aspects of the evaluation technique.…”

Section: Model Validationmentioning

confidence: 99%

Modelling climate change impacts on the spatial distribution of anthrax in Zimbabwe

John,

Shekede,

Gwitira

et al. 2024

BMC Public Health

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Background In Zimbabwe, anthrax is endemic with outbreaks being reported almost annually in livestock, wildlife, and humans over the past 40 years. Accurate modelling of its spatial distribution is key in formulating effective control strategies. In this study, an Ensemble Species Distribution Model was used to model the current and future distribution of anthrax occurrence in Zimbabwe. Methods Bioclimatic variables derived from the Beijing Climate Centre Climate System Model were used to model the disease. Collinearity testing was conducted on the 19 bioclimatic variables and elevation to remove redundancy. Variables that had no collinearity were used for anthrax habitat suitability modelling. Two future climate change scenarios for different Representative Concentration Pathways (RCP), RCP4.5 and RCP8.5 were used. Model evaluation was done using true skill, Kappa statistics and receiver operating characteristics. Results The results showed that under current bioclimatic conditions, eastern and western districts of Zimbabwe were modelled as highly suitable, central districts moderately suitable and southern parts marginally suitable for anthrax occurrence. Future predictions demonstrated that the suitable (8%) and highly suitable (7%) areas for anthrax occurrence would increase under RCP4.5 scenario. In contrast, a respective decrease (11%) and marginal increase (0.6%) of suitable and highly suitable areas for anthrax occurrence were predicted under the RCP8.5 scenario. The percentage contribution of the predictors varied for the different scenarios; Bio6 and Bio18 for the current scenario, Bio2, Bio4 and Bio9 for the RCP4.5 and Bio3 and Bio15 for the RCP8.5 scenarios. Conclusions The study revealed that areas currently suitable for anthrax should be targeted for surveillance and prevention. The predicted future anthrax distribution can be used to guide and prioritise surveillance and control activities and optimise allocation of limited resources. In the marginally to moderately suitable areas, effective disease surveillance systems and awareness need to be put in place for early detection of outbreaks. Targeted vaccinations and other control measures including collaborative ‘One Health’ strategies need to be implemented in the predicted highly suitable areas. In the southern part where a high decrease in suitability was predicted, continued monitoring would be necessary to detect incursions early.

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Section: Model Validationmentioning

confidence: 99%

Modelling climate change impacts on the spatial distribution of anthrax in Zimbabwe

John,

Shekede,

Gwitira

et al. 2024

BMC Public Health

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Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes

Liu,

Xu,

Zheng

et al. 2024

Ecology and Evolution

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The great gerbil (Rhombomys opimus) is a gregarious rodent in Central Asia and is one of the major pests found in desert forest and grassland areas. The distribution changes and migration routes of R. opimus in Central Asia under climate change remain unexplored. This study employed multi‐model ensemble, correlation analysis, jackknife method, and minimum cumulative resistance (MCR) model to simulate the potential habitat of R. opimus under current and future (2030 and 2050) climate scenarios and estimate its possible migration routes. The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. Under future climate scenarios, northern Xinjiang and southeastern Kazakhstan will remain the core areas of R. opimus distribution. However, the optimal habitat region will expand relative to the current one. This expansion will increase with the rising CO2 emission levels and over time, potentially enlarging the suitable area by up to 39.49 × 104 km2. In terms of spatial distribution, the suitable habitat for R. opimus is shifting toward higher latitudes and elevations. For specific migration routes, R. opimus tends to favor paths through farmland and grassland. This study can provide guidance for managing and controlling R. opimus under future climate change scenarios.

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An Empirical Evaluation of Ensemble Strategies in Habitat Suitability Modeling

El Alaoui,

Idri

2024

SN COMPUT. SCI.

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Change in habitat suitability of the invasive Snowflake coral (Carijoa riisei) during climate change: An ensemble modelling approach

Cited by 5 publications

References 85 publications

Modelling climate change impacts on the spatial distribution of anthrax in Zimbabwe

Modelling climate change impacts on the spatial distribution of anthrax in Zimbabwe

Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes

An Empirical Evaluation of Ensemble Strategies in Habitat Suitability Modeling

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