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<p>Climate change threatens food security and crop yield, negatively affecting the coffee industry in the Philippines for the last decade. Herein, species distribution modeling was implemented to map the potentially suitable habitats for cultivating the three topmost coffee crops (<i>Coffea arabica</i>, <i>C. liberica</i>, and <i>C. canephora</i>) in the Philippines under current and future scenarios. After scanning the literature, field records and occurrence points from local reports yielded a final 45 occurrence points for the three <i>Coffea</i> spp. Using the software ArcGIS and MaxEnt, the AUC values for all models yielded moderate values (0.693–0.825), indicating the reliability and robustness of the prediction. After employing the test for multicollinearity, among the four bioclimatic and two topographical environmental predictors, LULC has the most percent contribution for <i>C. arabica</i>. At the same time, soil types are the most important covariate for <i>C. liberica</i> and <i>C. canephora.</i> With the exemption of <i>C. canephora</i>, the predictive maps revealed a general decrease in habitat suitability for the optimistic (SSP 126) and pessimistic (SSP 585) future climatic scenarios of all <i>Coffea</i> species. Models in this study can be used as a scientific basis to propose mitigating and monitoring strategies to counter the adverse effects of climate change on the ecological and economic value of the ailing coffee industry of the country.</p>

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Decreasing suitable coffee cultivation areas under climate change in the Philippines

  • 期刊论文

  • 发表日期：

    2025年5月24日

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  • Jeffer Troy Cabangbang-Jaranilla,
  • Teresa Elika Joy Lacuesta-Jalotjot,
  • Francisco Geronimo-Isidro III,
  • Nicole Andrea Gabayno-Laguatan,
  • Jazpher John Figueroa-Jimenez,
  • James Eduard Limbo-Dizon,
  • Don Enrico Buebos-Esteve,
  • Nikki Heherson A. Dagamac

摘要

Climate change threatens food security and crop yield, negatively affecting the coffee industry in the Philippines for the last decade. Herein, species distribution modeling was implemented to map the potentially suitable habitats for cultivating the three topmost coffee crops (Coffea arabica, C. liberica, and C. canephora) in the Philippines under current and future scenarios. After scanning the literature, field records and occurrence points from local reports yielded a final 45 occurrence points for the three Coffea spp. Using the software ArcGIS and MaxEnt, the AUC values for all models yielded moderate values (0.693–0.825), indicating the reliability and robustness of the prediction. After employing the test for multicollinearity, among the four bioclimatic and two topographical environmental predictors, LULC has the most percent contribution for C. arabica. At the same time, soil types are the most important covariate for C. liberica and C. canephora. With the exemption of C. canephora, the predictive maps revealed a general decrease in habitat suitability for the optimistic (SSP 126) and pessimistic (SSP 585) future climatic scenarios of all Coffea species. Models in this study can be used as a scientific basis to propose mitigating and monitoring strategies to counter the adverse effects of climate change on the ecological and economic value of the ailing coffee industry of the country.