Skip to main content
Log in

Modelling the potential impact of climate change on Carapa procera DC. in Benin and Burkina Faso (West Africa)

  • Original Article
  • Published:
Modeling Earth Systems and Environment Aims and scope Submit manuscript

Abstract

Carapa procera plays an important socio-cultural and economic role for local people. The species is threatened by several factors including climate changes. This study explored the current and future distribution of the species in Benin and Burkina Faso. The maximum entropy (Maxent) software was used which combined the occurrence data of the species with a set of environmental layers. The future distribution of the species was assessed using the shared socioeconomic pathways (SSP) 245 and 585 for 2061–2080 and 2081–2100 periods. Globally, the models performed well, with mean AUC and TSS values of 0.90 and 0.67, respectively, suggesting good performance of the models. A set of five (05) variables drives the distribution of the species with rainfall and isothermality as the most important. For the current distribution, the findings showed that the highly suitable areas were mainly located in Guinea Congolian, and Sudanian zones respectively in Benin and Burkina Faso. The model indicated similar future patterns regardless of the general circulation models (GCMs) and shared socioeconomic pathways (SSPs). The MIROC6 model predicted that the species could lose around 10% of its currently suitable areas, whereas the CNRM model predicted that it would lose 8%. The WAPOK complex was identified to harbor the species in the natural habitats. Our study provides good insight into the current and future distribution of C. procera which can be decisive for the species management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

Data will be made available upon request.

References

  • Allouche O, Tsoar A, Kadmon RJ (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43(6):1223–1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x

    Article  Google Scholar 

  • Amissah L, Mohren GMJ, Bongers F, Hawthorne WD, Poorter L (2014) Rainfall and temperature affect tree species distribution in Ghana. J Trop Ecol 30(5):435–446. https://doi.org/10.1017/S026646741400025X

    Article  Google Scholar 

  • Atato A, Wala K, Batawila K, Lamien N, Akpagana K (2011) Edible wild fruit highly consumed during food shortage period in Togo: state of knowledge and conservation status. J Life Sci 5(12):1046–1057

    Google Scholar 

  • Atwoli L, Muhia J, Merali Z (2022) Mental health and climate change in Africa. Bjpsych Int 19(4):86–89. https://doi.org/10.1192/bji.2022.14

    Article  Google Scholar 

  • Baltzer JL, Davies SJ (2012) Rainfall seasonality and pest pressure as determinants of tropical tree species’ distributions. Ecol Evol 2(11):2682–2694. https://doi.org/10.1002/ece3.383

    Article  Google Scholar 

  • Belem B, Nacoulma BMI, Gbangou R, Kambou S, Hansen HH, Gausset Q, Lund S, Raebild A, Lompo D, Ouédraogo M, Theilade I, Boussim IJ (2007) Use of non wood forest products by local people bordering the “Parc National Kaboré Tambi”, Burkina Faso. J Transdiscipl Environ Stud 6(1):1–21

    Google Scholar 

  • Chaudhary A, Mooers AO (2018) Terrestrial vertebrate biodiversity loss under future global land use change scenarios. Sustainability 10(8):2764

    Article  Google Scholar 

  • Coulibaly M, Idohou R, Akohoue F, Peterson AT, Sawadogo M, Achigan-Dako EG (2022) Coupling genetic structure analysis and ecological-niche modeling in Kersting’s groundnut in West Africa. Sci Rep 12(1):5590

    Article  CAS  Google Scholar 

  • Dembélé U, Lykke AM, Koné Y, Témé B, Kouyaté AM (2015) Use-value and importance of socio-cultural knowledge on Carapa procera trees in the Sudanian zone in Mali. J Ethnobiol Ethnomed 11:14. https://doi.org/10.1186/1746-4269-11-14

    Article  Google Scholar 

  • Dembélé U, Diallo AA, Lykke AM, Koné Y, Témé B, Kouyaté AM (2019) Local perceptions and traditional methods for Carapa procera oil production in Mali. Flora eEt Vegetatio Sudano-Sambesica 22:16–22

    Article  Google Scholar 

  • Djenontin TS, Wotto VD, Avlessi F, Lozano P, Sohounhloué DKC, Pioch D (2012) Composition of Azadirachta indica and Carapa procera (Meliaceae) seed oils and cakes obtained after oil extraction. Ind Crops Prod 38:39–45. https://doi.org/10.1016/j.indcrop.2012.01.005

    Article  CAS  Google Scholar 

  • Fithian W, Elith J, Hastie T, Keith DA (2015) Bias correction in species distribution models: pooling survey and collection data for multiple species. Methods Ecol Evol 6(4):424–438. https://doi.org/10.1111/2041-210X.12242

    Article  Google Scholar 

  • Fontes J, Guinko S (1995) Vegetation and land use’s of Burkina Faso. Explanatory note. Ministry of French Cooperation, Toulouse

    Google Scholar 

  • Gaoue O, Sack L, Ticktin T (2011) Human impacts on leaf economics in heterogeneous landscapes: the effect of harvesting non-timber forest products from African mahogany across habitats and climates. J Appl Ecol 48(4):844–852

    Article  Google Scholar 

  • Gonzalez P, Tucker CJ, Sy H (2012) Tree density and species decline in the African Sahel attributable to climate. J Arid Environ 78:55–64. https://doi.org/10.1016/j.jaridenv.2011.11.001

    Article  Google Scholar 

  • Guèye M, Kenfack D, Forget PM (2010) Importance socioculturelle, potentialités économiques et thérapeutiques du Carapa (Meliaceae) au Sénégal. In: van der Burgt X, van der Maesen J, Onana JM (eds) Systématique et conservation des plantes africaines. Royal Botanical Gardens, Kew, pp 359–367

    Google Scholar 

  • Hamed MM, Nashwan MS, Shahid S (2022) Inter-comparison of historical simulation and future projections of rainfall and temperature by CMIP5 and CMIP6 GCMs over Egypt. Int J Climatol 42(8):4316–4332. https://doi.org/10.1002/joc.7468

    Article  Google Scholar 

  • Hausfather ZJ (2020) CMIP6: the next generation of climate models explained. Carbon Brief, p 8

  • Idohou R, Assogbadjo AE, Kakaï RG, Peterson AT (2017) Spatio-temporal dynamic of suitable areas for species conservation in West Africa: eight economically important wild palms under present and future climates. Agrofor Syst 91(3):527–540. https://doi.org/10.1007/s10457-016-9955-6

    Article  Google Scholar 

  • Jurisch K, Hahn K, Wittig R, Bernhardt-Römermann M (2012) Population structure of woody plants in relation to land use in a semi-arid Savanna, West Africa. Biotropica 44(6):744–751. https://doi.org/10.1111/j.1744-7429.2012.00864.x

    Article  Google Scholar 

  • Lankoandé B, Ouédraogo A, Boussim JI, Lykke AM (2015) Phenotypic traits of Carapa procera fruits from riparian forests of Burkina Faso, West Africa. J Hortic for 7(6):160–167

    Article  Google Scholar 

  • Lankoandé B, Ouédraogo A, Boussim JI, Lykke AM (2017) Identification of determining traits of seed production in Carapa procera and Pentadesma butyracea, two native oil trees from riparian forests in Burkina Faso, West Africa. Biomass Bioenergy 102:37–43. https://doi.org/10.1016/j.biombioe.2017.04.002

    Article  Google Scholar 

  • Lankoandé B, Ouattara B, Bayen P, Ouédraogo A (2021) Assessing fruit production and harvesting effects on Carapa procera DC. population, a threatened oil tree in Burkina Faso, West Africa. Environ Chall 4:100196. https://doi.org/10.1016/j.envc.2021.100196

    Article  Google Scholar 

  • Mahama A, Chama MA, Oppong Bekoe E, Asare GA, Obeng-Kyeremeh R, Amoah D, Adjei S (2022) Assessment of toxicity and anti-plasmodial activities of chloroform fractions of Carapa procera and Alchornea cordifolia in murine models. Front Pharmacol 13:1077380

    Article  CAS  Google Scholar 

  • Malhi GS, Kaur M, Kaushik P (2021) Impact of climate change on agriculture and its mitigation strategies: a review. Sustainability. https://doi.org/10.3390/su13031318

    Article  Google Scholar 

  • Molina-Montenegro MA, Naya DE (2012) Latitudinal patterns in phenotypic plasticity and fitness-related traits: assessing the climatic variability hypothesis (CVH) with an invasive plant species. PLoS ONE. https://doi.org/10.1371/journal.pone.0047620

    Article  Google Scholar 

  • Moreno-Amat E, Mateo RG, Nieto-Lugilde D, Morueta-Holme N, Svenning J-C, García-Amorena I (2015) Impact of model complexity on cross-temporal transferability in Maxent species distribution models: an assessment using paleobotanical data. Ecol Model 312:308–317. https://doi.org/10.1016/j.ecolmodel.2015.05.035

    Article  Google Scholar 

  • Nacoulma BMI, Schumann K, Traoré S, Bernhardt-Römermann M, Hahn K, Wittig R, Thiombiano A (2011) Impacts of land-use on West African savanna vegetation: a comparison between protected and communal area in Burkina Faso. Biodivers Conserv 20(14):3341–3362. https://doi.org/10.1007/s10531-011-0114-0

    Article  Google Scholar 

  • Naimi B (2017) Package ‘usdm’. Uncertainty analysis for species distribution models. Wien. www.cran.r-project.org

  • Newbold T, Hudson LN, Hill SLL, Contu S, Lysenko I, Senior RA, Börger L, Bennett DJ, Choimes A, Collen B, Day J, De Palma A, Díaz S, Echeverria-Londoño S, Edgar MJ, Feldman A, Garon M, Harrison MLK, Alhusseini T, Ingram DJ, Itescu Y, Kattge J, Kemp V, Kirkpatrick L, Kleyer M, Correia DLP, Martin CD, Meiri S, Novosolov M, Pan Y, Phillips HRP, Purves DW, Robinson A, Simpson J, Tuck SL, Weiher E, White HJ, Ewers RM, Mace GM, Scharlemann JPW, Purvis A (2015) Global effects of land use on local terrestrial biodiversity. Nature 520(7545):45–50. https://doi.org/10.1038/nature14324

    Article  CAS  Google Scholar 

  • O’Donnell MS, Ignizio DA (2012) Bioclimatic predictors for supporting ecological applications in the conterminous United States. US Geol Surv Data Ser 691(10):4–9

    Google Scholar 

  • Orwa C, Mutua A, Kindt R, Jamnadass R, Simons A (2009) Agroforestree Database: a tree reference and selection guide. Agroforestree Database: a tree reference selection guide. Version 4

  • Ouédraogo M, Ouédraogo D, Thiombiano T, Hien M, Lykke AM (2013) Dépendance économique aux produits forestiers non ligneux: cas des ménages riverains des forêts de Boulon et de Koflandé, au Sud-Ouest du Burkina Faso. J Agric Environ Int Dev JAEID 107(1):45–72

    Google Scholar 

  • Paul J, Criado AR (2020) The art of writing literature review: what do we know and what do we need to know? Int Bus Rev 29(4):101717. https://doi.org/10.1016/j.ibusrev.2020.101717

    Article  Google Scholar 

  • Peterson AT, Soberón J, Pearson RG, Anderson RP, Martínez-Meyer E, Nakamura M, Araújo MB (2012) Ecological Niches and geographic distributions (MPB-49). Princeton University Press, Princeton

    Google Scholar 

  • Pham TM, Dang GTH, Le ATK, Luu AT (2023) Predicting the potential geographic distribution of Camellia sinensis var. shan under multiple climate change scenarios in Van Chan District Vietnam. Model Earth Syst Environ 9(2):1843–1857

    Article  Google Scholar 

  • Phillips SJ (2006) A brief tutorial on maxent. At&t Res 190(4):231–259

    Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190(3–4):231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME (2017) Opening the black box: an open-source release of Maxent. Ecography 40(7):887–893. https://doi.org/10.1111/ecog.03049

    Article  Google Scholar 

  • Platts PJ, Omeny PA, Marchant R (2015) AFRICLIM: high-resolution climate projections for ecological applications in Africa. Afr J Ecol 53(1):103–108. https://doi.org/10.1111/aje.12180

    Article  Google Scholar 

  • Rendón-Sandoval FJ, Casas A, Moreno-Calles AI, Torres-García I, García-Frapolli EJS (2020) Traditional agroforestry systems and conservation of native plant diversity of seasonally dry tropical forests. Sustainability 12(11):4600. https://doi.org/10.3390/su12114600

    Article  Google Scholar 

  • Rewicz A, Myśliwy M, Rewicz T, Adamowski W, Kolanowska M (2022) Contradictory effect of climate change on American and European populations of Impatiens capensis Meerb. - is this herb a global threat? Sci Total Environ 850:157959. https://doi.org/10.1016/j.scitotenv.2022.157959

    Article  CAS  Google Scholar 

  • Saupe EE, Barve V, Myers CE, Soberón J, Barve N, Hensz CM, Peterson AT, Owens HL, Lira-Noriega A (2012) Variation in niche and distribution model performance: the need for a priori assessment of key causal factors. Ecol Model 237–238:11–22. https://doi.org/10.1016/j.ecolmodel.2012.04.001

    Article  Google Scholar 

  • Schumann K, Wittig R, Thiombiano A, Becker U, Hahn K (2011) Impact of land-use type and harvesting on population structure of a non-timber forest product-providing tree in a semi-arid savanna, West Africa. Biol Conserv 144(9):2369–2376. https://doi.org/10.1016/j.biocon.2011.06.018

    Article  Google Scholar 

  • Sharma G, Hunsdorfer B, Singh KJTE (2016) Comparative analysis on the socio-ecological and economic potentials of traditional agroforestry systems in the Sikkim Himalaya. Trop Ecol 57(4):751–764

    Google Scholar 

  • Sop TK, Oldeland J, Schmiedel U, Ouédraogo I, Thiombiano A (2010) Population structure of three woody species in four ethnic domains of the Sub-Sahel of Burkina Faso. Land Degrad Dev. https://doi.org/10.1002/ldr.1026

    Article  Google Scholar 

  • Swets JAJS (1988) Measuring the accuracy of diagnostic systems. Science 240(4857):1285–1293. https://doi.org/10.1126/science.3287615

    Article  CAS  Google Scholar 

  • Tatebe H, Ogura T, Nitta T, Komuro Y, Ogochi K, Takemura T, Sudo K, Sekiguchi M, Abe M, Saito F, Chikira M, Watanabe S, Mori M, Hirota N, Kawatani Y, Mochizuki T, Yoshimura K, Takata K, O’Ishi R, Yamazaki D, Suzuki T, Kurogi M, Kataoka T, Watanabe M, Kimoto M (2019) Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6. Geosci Model Dev 12(7):2727–2765. https://doi.org/10.5194/gmd-12-2727-2019

    Article  CAS  Google Scholar 

  • Thiombiano A, Schmidt D, Ouédraogo A, Hahn K, Zizka G (2012) Catalogue de plantes vasculaires du Burkina Faso. Boissiera 65:1–391

    Google Scholar 

  • Tramblay Y, Koutroulis A, Samaniego L, Vicente-Serrano SM, Volaire F, Boone A, Le Page M, Llasat MC, Albergel C, Burak S, Cailleret M, Kalin KC, Davi H, Dupuy J-L, Greve P, Grillakis M, Hanich L, Jarlan L, Martin-StPaul N, Martínez-Vilalta J, Mouillot F, Pulido-Velazquez D, Quintana-Seguí P, Renard D, Turco M, Türkeş M, Trigo R, Vidal J-P, Vilagrosa A, Zribi M, Polcher J (2020) Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth Sci Rev 210:103348. https://doi.org/10.1016/j.earscirev.2020.103348

    Article  Google Scholar 

  • Vignali S, Barras AG, Arlettaz R, Braunisch V (2020) SDMtune: an R package to tune and evaluate species distribution models. Ecol Evol 10(20):11488–11506. https://doi.org/10.1002/ece3.6786

    Article  Google Scholar 

  • Voldoire A, Saint-Martin D, Sénési S, Decharme B, Alias A, Chevallier M, Colin J, Guérémy JF, Michou M, Moine MP, Nabat P, Roehrig R, Salas y Mélia D, Séférian R, Valcke S, Beau I, Belamari S, Berthet S, Cassou C, Cattiaux J, Deshayes J, Douville H, Ethé C, Franchistéguy L, Geoffroy O, Lévy C, Madec G, Meurdesoif Y, Msadek R, Ribes A, Sanchez-Gomez E, Terray L, Waldman R (2019) Evaluation of CMIP6 DECK experiments with CNRM-CM6-1. J Adv Model Earth Syst 11(7):2177–2213. https://doi.org/10.1029/2019MS001683

    Article  Google Scholar 

  • Warren DL, Seifert SN (2011) Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol Appl 21(2):335–342. https://doi.org/10.1890/10-1171.1

    Article  Google Scholar 

  • Weber N, Birnbaum P, Forget P-M, Guèye M, Kenfack D (2010) L’huile de carapa (Carapa spp., Meliaceae) en Afrique de l’Ouest: utilisations et implications dans la conservation des peuplements naturels. Fruits 65:343–354

    Article  Google Scholar 

  • Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, NCEAS Predicting Species Distributions Working Group (2008) Effects of sample size on the performance of species distribution models. Divers Distrib 14(5):763–773. https://doi.org/10.1111/j.1472-4642.2008.00482.x

    Article  Google Scholar 

  • Worth JRP, Williamson GJ, Sakaguchi S, Nevill PG, Jordan GJ (2014) Environmental niche modelling fails to predict Last Glacial Maximum refugia: niche shifts, microrefugia or incorrect palaeoclimate estimates?

Download references

Acknowledgements

The authors express their gratitude to all who contributed to the development of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design of the study. Material preparation, data collection and analysis were performed by [SRFT], [RI] and [GA]. The first draft of the manuscript was written by [GA] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to R. Idohou.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A

Appendix A

S1: Pearson’s correlation analysis, VIF and jackknife among test the 24 bioclimatic variables

Variables

VIF

bio13

2.74

bio14

3.87

bio18

5.29

bio19

2.25

bio2

6.70

bio3

3.23

Elevation

3.20

land_cover

1.08

pet

5.10

Ph

3.36

slope

1.56

soil_type

1.57

Texture

1.88

figure a
figure b

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tietiambou, S.R.F., Idohou, R., Agounde, G. et al. Modelling the potential impact of climate change on Carapa procera DC. in Benin and Burkina Faso (West Africa). Model. Earth Syst. Environ. 10, 3023–3034 (2024). https://doi.org/10.1007/s40808-023-01946-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40808-023-01946-5

Keywords

Navigation