Impact of climate change on potential distribution of Quercus suber in the conditions of North Africa

  • A. Benabou Mohammed V University in Rabat
  • S. Moukrim Mohammed V University in Rabat
  • S. Lahssini National School of Forest Engineers
  • A. El Aboudi Mohammed V University in Rabat
  • K. Menzou Quartier Administratif Chellah
  • M. Elmalki Quartier Administratif Chellah
  • M. El Madihi Mohammed V University in Rabat
  • L. Rhazi Mohammed V University in Rabat
Keywords: Cork oak; habitat suitability; MaxEnt; modelling species distribution; Morocco

Abstract

Climate change, which is expected to continue in the future, is increasingly becoming a major concern affecting many components of the biodiversity and human society. Understanding its impacts on forest ecosystems is essential for undertaking long-term management and conservation strategies. This study was focused on modeling the potential distribution of Quercus suber in the Maamora Forest, the world’s largest lowland cork oak forest, under actual and future climate conditions and identifying the environmental factors associated with this distribution. Maximum Entropy approach was used to train a Species Distribution Model and future predictions were based on different greenhouse gas emission scenarios (Representative Concentration Pathway RCPs). The results showed that the trained model was highly reliable and reflected the actual and future distributions of Maamora’s cork oak. It showed that the precipitation of the coldest and wettest quarter and the annual temperature range are the environmental factors that provide the most useful information for Q. suber distribution in the study area. The computed results of cork oak’s habitat suitability showed that predicted suitable areas are site-specific and seem to be highly dependent on climate change. The predicted changes are significant and expected to vary (decline of habitat suitability) in the future under the different emissions pathways. It indicates that climate change may reduce the suitable area for Q. suber under all the climate scenarios and the severity of projected impacts is closely linked to the magnitude of the climate change. The percent variation in habitat suitability indicates negative values for all the scenarios, ranging –23% to –100%. These regressions are projected to be more important under pessimist scenario RCP8.5. Given these results, we recommend including the future climate scenarios in the existing management strategies and highlight the usefulness of the produced predictive suitability maps under actual and future climate for the protection of this sensitive forest and its key species – cork oak, as well as for other forest species.

References

Aafi, A., El Kadmiri, A. A., Benabid, A., & Rochdi, M. (2005). Richesse et diversité floristique de la suberaie de la Mamora (Maroc) [Richness and floristic diversity of the cork oak forest of Mamora (Morocco)]. Acta Botanica Malacitana, 30, 127–138.

Achhal, A., Akabli, O., Barbero, M., Benabid, A., M’hirit, A., Peyre, C., Quezel, P., & Rivas-Martinez, S. (1979). A propos de la valeur bioclimatique et dynamique de quelques essences forestières au Maroc [About the bioclimatic and dynamic value of some forest species in Morocco]. Ecologia Mediterranea, 5, 211–249.

Allan, R. P., Cassou, C., Chen, D., Cherchi, A., Connors, L., Doblas-Reyes, F. J., Douville, H., Driouech, F., Edwards, T. L., Fischer, E., Flato, G. M., Forster, P., AchutaRao, K. M., Adhikary, B., Aldrian, E., & Armour, K. (2021). Summary for Policymakers. In : Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.

Araújo, M. B., Pearson, R. G., Thuiller, W., & Erhard, M. (2005). Validation of species-climate impact models under climate change. Global Change Biology, 11(9), 1504–1513.

Austin, M. (2007). Species distribution models and ecological theory: A critical assessment and some possible new approaches. Ecological Modelling, 200, 1–19.

Avtaeva, T. A., Sukhodolskaya, R. A., & Brygadyrenko, V. V. (2021a). Modeling the bioclimating range of Pterostichus melanarius (Coleoptera, Carabidae) in conditions of global climate change. Biosystems Diversity, 29(2), 140–150.

Avtaeva, T., Petrovičová, K., Langraf, V., & Brygadyrenko, V. (2021b). Potential bioclimatic ranges of crop pests Zabrus tenebrioides and Harpalus rufipes during climate change conditions. Diversity, 13, 559.

Benabid, A. (1982). Bref aperçu sur la zonation altitudinale de la végétation climacique du Maroc. Ecologia Mediterranea, 8(1), 301–315.

Benabid, A. (2000). Flore et écosystèmes du Maroc : Evaluation et préservation de la biodiversité [Flora and ecosystems of Morocco: Assessment and preservation of biodiversity]. Ibis Press & Kalila Wa Dimna, Paris, Rabat.

Benabou, A., Moukrim, S., Laaribya, S., Aafi, A., Chkhichekh, A., Maadidi, T. E., & El Aboudi, A. (2022). Mapping ecosystem services of forest stands: Case study of Maamora, Morocco. Geography, Environment, Sustainability, 15(1), 141–149.

Boudy, P. (1950). Economie forestière Nord-africaine-Tome 2 : Monographies et traitements des essences forestières [North African forestry economy – Volume 2: Monographs and treatments of forest species]. Edition Larose, Paris.

Bugalho, M. N., Caldeira, M. C., Pereira, J. S., Aronson, J., & Pausas, J. G. (2011). Mediterranean cork oak savannas require human use to sustain biodiversity and ecosystem services. Frontiers in Ecology and the Environment, 9(5), 278–286.

Carrión, J. S., Parra, I., Navarro, C., & Munuera, M. (2000). Past distribution and ecology of the cork oak (Quercus suber) in the Iberian Peninsula: A pollen-analytical approach. Diversity and Distributions, 6(1), 29–44.

Di Nuzzo, L., Vallese, C., Benesperi, R., Giordani, P., Chiarucci, A., Di Cecco, V., Di Martino, L., Di Musciano, M., Gheza, G., Lelli, C., Spitale, D., & Nascimbene, J. (2021). Contrasting multitaxon responses to climate change in Mediterranean mountains. Scientific Reports, 11(1), 4438.

Driouech, F., Déqué, M., & Sánchez-Gómez, E. (2010). Weather regimes – Moroccan precipitation link in a regional climate change simulation. Global and Planetary Change, 72(1), 1–10.

Elith, J., & Graham, C. H. (2009). Do they? How do they? Why do they differ? On finding reasons for differing performances of species distribution models. Ecography, 32(1), 66–77.

Elith, J., Graham, C. H., Anderson, R. P., Dudík, M., Ferrier, S., Guisan, A., Hijmans, R. J., Huettmann, F., Leathwick, J. R., Lehmann, A., Li, J., Lohmann, L. G., A. Loiselle, B., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J. McC. M., Peterson, A. T., Phillips, S. J., Richardson, K., Scachetti-Pereira, R., Soberon, J., Williams, S., Wisz, M. S., Zimmermann, N. E. (2006). Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29(2), 129–151.

Fennane, M., & Ibn Tattou, M. (2012). Statistiques et commentaires sur l’inventaire actuel de la flore vasculaire du Maroc [Statistics and comments on the current inventory of the vascular flora of Morocco]. Bulletin de l’Institut Scientifique, Rabat, section Sciences de la Vie, 34(1), 1–9.

Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315.

Franklin, J. (2009). Mapping species distributions: Spatial inference and prediction. Cambridge University Press, Cambridge.

Guisan, A., Thuiller, W., & Zimmermann, N. E. (2017). Habitat suitability and distribution models with applications in R. Cambridge University Press, Cambridge.

Guisan, A., & Zimmermann, N. E. (2000). Predictive habitat distribution models in ecology. Ecological Modelling, 135(2), 147–186.

Hallegatte, S., Fay, M., Bangalore, M., Kane, T., & Bonzanigo, L. (2015). Shock waves: Managing the impacts of climate change on poverty. World Bank Publications, Washington.

Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29–36.

Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978.

Hughes, L. (2000). Biological consequences of global warming: Is the signal already apparent? Trends in Ecology and Evolution, 15(2), 56–61.

Knutti, R., Abramowitz, G., Eyring, V., Gleckler, P. J., Hewitson, B., & Mearns, L. (2010). Good practice guidance paper on assessing and combining multi model climate projections. In: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., & Midgley, P. M. (Éds.). Meeting Report of the IPCC Expert meeting on assessing and combining multi model climate projections. IPCC Working Group I Technical Support Unit, University of Bern. Bern. Pp. 1–11.

Kriegler, E., O’Neill, B. C., Hallegatte, S., Kram, T., Lempert, R. J., Moss, R. H., & Wilbanks, T. (2012). The need for and use of socio-economic scenarios for climate change analysis: A new approach based on shared socio-economic pathways. Global Environmental Change, 22(4), 807–822.

Lahssini, S., Lahlaoi, H., Alaoui, H. M., Bagaram, M., & Ponette, Q. (2015). Predicting cork oak suitability in Maamora forest using random forest algorithm. Journal of Geographic Information System, 7(2), 202.

Li, G., Huang, J., Guo, H., & Du, S. (2020). Projecting species loss and turnover under climate change for 111 Chinese tree species. Forest Ecology and Management, 477, 118488.

McCarty, J. P. (2001). Ecological consequences of recent climate change. Conservation Biology, 15(2), 320–331.

Merow, C., Smith, M. J., & Silander, J. A. (2013). A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography, 36(10), 1058–1069.

Millar, C. I., Stephenson, N. L., & Stephens, S. L. (2007). Climate change and forests of the future: Managing in the face of uncertainty. Ecological Applications, 17(8), 2145–2151.

Miller, R. G. (1974). The jackknife – a review. Biometrika, 61(1), 1–15.

Moukrim, S., Lahssini, S., Mharzi-Alaoui, H., Rifai, N., Arahou, M., & Rhazi, L. (2018). Modélisation de la distribution spatiale des espèces endémiques pour leur conservation : Cas de l’Argania spinosa (L.) Skeels [Modeling the spatial distribution of endemic species for their conservation: the case of Argania spinosa (L.) Skeels]. Revue d’Ecologie (Terre et Vie), 73(2), 153–166.

Moukrim, S., Lahssini, S., Rhazi, M., Alaoui, H. M., Benabou, A., Wahby, I., El Madihi, M., Arahou, M., & Rhazi, L. (2019a). Climate change impacts on potential distribution of multipurpose agro-forestry species: Argania spinosa (L.) Skeels as case study. Agroforestry Systems, 93(4), 1209–1219.

Moukrim, S., Lahssini, S., Naggar, M., Lahlaoi, H., Rifai, N., Arahou, M., & Rhazi, L. (2019b). Local community involvement in forest rangeland management: Case study of compensation on forest area closed to grazing in Morocco. The Rangeland Journal, 41(1), 43–53.

Moukrim, S., Lahssini, S., Rifai, N., Menzou, K., Mharzi-Alaoui, H., Labbaci, A., Rhazi, M., Wahby, I. W., El Madihi, M., & Rhazi, L. (2020). Modélisation de la distribution potentielle de Cedrus atlantica Manetti au Maroc et impacts du changement climatique [Modelling the potential distribution of Cedrus atlantica Manetti in Morocco and impacts of climate change]. Bois & Forêts des Tropiques, 344, 3–16.

Natividade, J. V. (1956). Subériculture, édition française de l’ouvrage portugais “Subericultura” [Subericulture, French edition of the Portuguese book “Subericultura”]. Ecole Nationale des Eaux et Forêts, Nancy France.

Nolan, C., Overpeck, J. T., Allen, J. R. M., Anderson, P. M., Betancourt, J. L., Binney, H. A., Brewer, S., Bush, M. B., Chase, B. M., Cheddadi, R., Djamali, M., Dodson, J., Edwards, M. E., Gosling, W. D., Haberle, S., Hotchkiss, S. C., Huntley, B., Ivory, S. J., Kershaw, A. P., Djamali, M., Dodson, J., Edwards, M. E., Gosling, W. D., Haberle, S., Hotchkiss, S. C., Huntley, B., Ivory, S. J., Kershaw, A. P., Kim, S. H., Latorre, C., Leydet, M., Lézine, A. M., Liu, K. B., Liu, Y., Lozhkin, A. V., McGlone, M. S., Marchant, R. A., Momohara, A., Moreno, P. I., Müller, S., Otto-Bliesner, B. L., Shen, C., Stevenson, J., Takahara, H., Tarasov, P. E., Tipton, J., Vincens, A., Weng, C., Xu, Q., Zheng, Z., & Jackson, S. T. (2018). Past and future global transformation of terrestrial ecosystems under climate change. Science, 361(6405), 920–923.

Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231–259.

Phillips, S. J., & Dudík, M. (2008). Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography, 31(2), 161–175.

Pielke Jr, R., Burgess, M. G., & Ritchie, J. (2022). Plausible 2005–2050 emissions scenarios project between 2 °C and 3 °C of warming by 2100. Environmental Research Letters, 17(2), 024027.

Rifai, N., Moukrim, S., Khattabi, A., Lahssini, S., Alaoui, H. M., & Rhazi, L. (2020). Prédiction de l’aire potentielle de répartition du genévrier thurifère (Juniperus thurifera) au Maroc [Prediction of the potential distribution area of the Spanish juniper (Juniperus thurifera) in Morocco]. Revue Marocaine des Sciences Agronomiques et Vétérinaires, 8(2), 141–150.

Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, B., & Midgley, M. B. (2013). Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge.

Vessella, F., & Schirone, B. (2013). Predicting potential distribution of Quercus suber in Italy based on ecological niche models: Conservation insights and reforestation involvements. Forest Ecology and Management, 304, 150–161.

Weigel, A. P., Knutti, R., Liniger, M. A., & Appenzeller, C. (2010). Risks of model weighting in multimodel climate projections. Journal of Climate, 23(15), 4175–4191.

Published
2022-09-09
Section
Articles

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