A Continental-Scale Connectivity Analysis to Predict Current and Future Colonization Trends of Biofuel Plant’s Pests for Sub-Saharan African Countries
Biofuel production in Sub-Saharan Africa is an important part of local low-income countries. Among many plant species, <i>Jatropha curcas</i> gained popularity in this area, as it can be grown even where crops of agricultural interest cannot. A natural African pest of <i>J. curcas&...
Guardado en:
Autores principales: | , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/6331e166ee3e4d38bb1ea3d7420a3fa8 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: | Biofuel production in Sub-Saharan Africa is an important part of local low-income countries. Among many plant species, <i>Jatropha curcas</i> gained popularity in this area, as it can be grown even where crops of agricultural interest cannot. A natural African pest of <i>J. curcas</i> is the <i>Aphthona cookei</i> species group, for which future climatic suitability is predicted to favor areas of co-occurrence. In this research, we identify the possible climatic corridors in which the colonization of <i>J. curcas</i> crops may occur through a circuit theory-based landscape connectivity software at a country scale. Additionally, we use the standardized connectivity change index to predict possible variations in future scenarios. Starting from ecological niche models calibrated on current and 2050 conditions (two different RCP scenarios), we found several countries currently showing high connectivity. Ghana, Zambia and Ivory Coast host both high connectivity and a high number of <i>J. curcas</i> cultivations, which is also predicted to increase in the future. On the other side, Burundi and Rwanda reported a future increase of connectivity, possibly acting as “connectivity bridges” among neighboring countries. Considering the economic relevance of the topic analyzed, our spatially explicit predictions can support stakeholders and policymakers at a country scale in informed territorial management. |
---|