Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-26T07:15:58.812Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting the potential suitable habitats of forest spices Piper capense and Aframomum corrorima under climate change in Ethiopia

Published online by Cambridge University Press:  30 March 2022

Tibebu Enkossa ,
Sileshi Nemomissa  and
Debissa Lemessa
Tibebu Enkossa*
Affiliation:
Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia Department of Plant Science, College of Agriculture, Wollega University, Nekemte, Ethiopia
Sileshi Nemomissa
Affiliation:
Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia
Debissa Lemessa
Affiliation:
Department of Plant Biology and Biodiversity Management, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia
*
Author for correspondence: Tibebu Enkossa, Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Continuing climate change may cause shifts in the adaptive ranges of plant species. But this impact is less understood for many species in the tropics. Here, we examined the distribution of the current and future potential suitable habitats of two native forest spices Piper capense and Aframomum corrorima. We have used MaxEnt software to predict the current and future suitable habitats of these species. Two future climate change scenarios, that is, middle (Representative Concentration Pathway [RCP 4.5]) and extreme (RCP 8.5) scenarios for years 2050 and 2070, were used. A total of 60 and 74 occurrence data of P. capense and A. corrorima, respectively, and 22 environmental variables were included. The effects of elevation, solar radiation index (SRI) and topographic position index (TPI) on suitable habitats of these species were tested using linear model in R. Precipitation of the driest quarter, SRI and TPI significantly affect future suitable habitats of P. capense and A. corrorima. Furthermore, there are significant elevational shifts of suitable habitats for both species under future scenarios (P < 0.001). These novel suitable habitats are located in moist Afromontane and Combretum-Terminalia vegetations. Our results suggest that conservation planning for these species should consider climate change factors including assisted migration.

Keywords

climate changeCombretum-Terminalia woodlanddistribution modellingEthiopiamoist Afromontane forestsuitable habitats
Type
Research Article
Information
Journal of Tropical Ecology , Volume 38 , Issue 4 , July 2022 , pp. 219 - 232
Check for updates
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aerts, R, Hundera, K, Berecha, G, Gijbels, P, Baeten, M, Van Mechelen, M, Muys, B and Honnay, O (2011) Semi-forest coffee cultivation and the conservation of Ethiopian Afromontane rainforest fragments. Forest Ecology and Management 261, 1034–1041.CrossRefGoogle Scholar
Agize, M and Zouwen, L (2016) Spice and medicinal plants production and value chain analysis from SouthWest Ethiopia. Journal of Pharmacy and Alternative Medicine. (www.iiste.org) Vol.10. |ISSN 2222-4807(online) ISSN 2222-5668.Google Scholar
Anderegg, WRL, Hicke, JA, Fisher, RA, Allen, CD, Aukema, J, Bentz, B, Hood, S, Lichstein, JW, Macalady, AK, Mcdowell, N, Pan, Y, Raffa, K, Sala, A, Shaw, JD, Stephenson, NL, Tague, C and Zeppel, M (2015) Tree mortality from drought, insects, and their interactions in a changing climate. New Phytologist. doi: 10.1111/nph.13477.CrossRefGoogle Scholar
Antúnez, P, Suárez-mota, ME, Valenzuela-encinas, C and Ruiz-aquino, F (2018) The potential distribution of tree species in three periods of time under a climate change scenario. Forests. doi: 10.3390/f9100628.CrossRefGoogle Scholar
Ardestani, EG, Tarkesh, M, Bassiri, M and Vahabi, MR (2015) Potential habitat modeling for reintroduction of three native plant species in central Iran. Journal of Arid Land 7, 381–390.CrossRefGoogle Scholar
Austin, M (2006) Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecological Modelling 200, 1–19.CrossRefGoogle Scholar
Avril, M (2011) A study case on Timiz (Piper Capense). Home Gardens of Ethiopia.Google Scholar
Bloom, TD, Flower, A and DeChaine, EG (2018) Why georeferencing matters: introducing a practical protocol to prepare species occurrence records for spatial analysis. Ecology and Evolution 8, 765–777.CrossRefGoogle ScholarPubMed
Cao, M, Prince, SD, Small, J and Goetz, SJ (2004) Remotely sensed interannual variations and trends in terrestrial net primary productivity 1981–2000. Ecosystems 7, 233–242.CrossRefGoogle Scholar
Carlin, T, Bufford, J, Hulme, P and Godsoe, W (2021) Global assessment of climatic niche shifts in three Rumex species.CrossRefGoogle Scholar
Catford, JA, Vesk, PA, Richardson, DM and Pyšek, P (2012) Quantifying levels of biological invasion: towards the objective classification of invaded and invasible ecosystems. Global Change Biology 18, 44–62.CrossRefGoogle Scholar
Chen, IC, Hill, JK, Ohlemüller, R, Roy, DB and Thomas, CD (2011) Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026.CrossRefGoogle ScholarPubMed
Chhetri, PK, Gaddis, KD and Cairns, DM (2018) Predicting the suitable habitat of treeline species in the Nepalese Himalayas under climate change. Mountain Research and Development 38, 153–163.CrossRefGoogle Scholar
Choudhury, MR, Deb, P, Singha, H, Chakdar, B and Medhi, M (2016) Predicting the probable distribution and threat of invasive Mimosa diplotricha Suavalle and Mikania micrantha Kunth in a protected tropical grassland. Ecological Engineering 97, 23–31.CrossRefGoogle Scholar
Crimmins, SM, Dobrowski, SZ, Greenberg, JA, Abatzoglou, JT and Mynsberge, AR (2010) Changes in climatic water balance drive downhill shifts in plant species’ optimum elevations. Science 331, 324–327.CrossRefGoogle Scholar
Dagnino, D, Guerrina, M, Minuto, L, Mariotti, MG, Médail, F and Casazza, G (2020) Climate change and the future of endemic flora in the South Western Alps: relationships between niche properties and extinction risk. Regional Environmental Change 20, 121.CrossRefGoogle Scholar
Debebe, E, Dessalegn, T and Melaku, Y (2018) Chemical constituents and antioxidant activities of the fruits extracts of Piper capense . Bulletin of the Chemical Society of Ethiopia 32, 167–174.CrossRefGoogle Scholar
Desalegn, W and Beierkuhnlein, C (2010) Plant species and growth form richness along altitudinal gradients in the southwest Ethiopian highlands. Journal of Vegetation Science 21, 617–626.Google Scholar
EFCCC (2017) Environment, forest and climate change commission of Ethiopia. Ethiopia’s Forest Reference Level Submission to the UNFCCC. Available online: https://redd.unfccc.int/files/ethiopia_frel_3.2_final_modified_submission.pdf (accessed on 18 July 2021).Google Scholar
Elith, J and Leathwick, JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics 40, 677–697.CrossRefGoogle Scholar
Elith, J, Graham, CH, Anderson, RP, Dudik, M, Ferrier, S, Guisan, A, Hijmans, RJ, Huettmann, F, Leathwick, JR, Lehmann, A, Li, J, Lohmann, LG, Loiselle, BA, Manion, G, Moritz, C, Nakamura, M, Nakazawa, Y, Overton, JM, Peterson, AT, Phillips, SJ, Richardson, KS, Scachetti-pereira, R, Schapire, RE, Sobero´n, J, Williams, S, Wisz, MS and Zimmermann, NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151.CrossRefGoogle Scholar
Elith, J, Phillips, SJ, Hastie, T, Dudík, M, Chee, YE and Yates, CJ (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17, 43–57.CrossRefGoogle Scholar
Elsen, PR, Monahan, WB and Merenlender, AM (2020) Topography and human pressure in mountain ranges alter expected species responses to climate change. Nature Communications 11, 1–10.CrossRefGoogle ScholarPubMed
Engels, JMM, Hawkes, JG and Worede, M (1991) Plant Genetic Resources of Ethiopia. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Essl, F, Staudinger, M, Stöhr, O, Schratt-Ehrendorfer, L, Rabitsch, W and Niklfeld, H (2009) Distribution patterns, range size and niche breadth of Austrian endemic plants. Biological Conservation 142, 2547–2558.CrossRefGoogle Scholar
Eyob, S, Martinsen, BK, Tsegaye, A, Appelgren, M and Skrede, G (2008) Antioxidant and antimicrobial activities of extract and essential oil of korarima (Aframomum corrorima (Braun) PCM Jansen). African Journal of Biotechnology 7, 2585–2592.Google Scholar
Fourcade, Y, Engler, JO, Rödder, D and Secondi, J (2014) Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PloS one 9, e97122.CrossRefGoogle ScholarPubMed
Friis, I, Demissew, S and Breugel, PV (2010) Atlas of the Potential Vegetation of Ethiopia. The Royal Danish Academy of Science and Letters, Copenhagen.Google Scholar
Gaston, KJ (1996) Biodiversity-latitudinal gradients. Progress in Physical Geography 20, 466–476.CrossRefGoogle Scholar
Gebrewahid, Y, Abrehe, S, Meresa, E, Eyasu, G, Abay, K, Gebreab, G, Kidanemariam, K, Adissu, G, Abreha, G and Darcha, G (2020) Current and future predicting potential areas of Oxytenanthera abyssinica (A. Richard) using MaxEnt model under climate change in Northern Ethiopia. Ecological Processes. doi: 10.1186/s13717-019-0210-8 CrossRefGoogle Scholar
Getasetegn, M and Tefera, Y (2016) Biological activities and valuable compounds from five medicinal plants. Natural Products Chemistry & Research. doi: 10.4172/2329-6836.1000220.CrossRefGoogle Scholar
Gole, TW, Feyera, S, Kassahun, T and Fite, G (2009) Yayu Coffee Forest Biosphere Reserve Nomination Form. Ethiopian MAB National Committee, Addis Ababa.Google Scholar
González-Moreno, P, Diez, JM, Richardson, DM and Vilà, M (2015) Beyond climate: disturbance niche shifts in invasive species. Global Ecology and Biogeography 24, 360–370.CrossRefGoogle Scholar
Gregory, A, Spence, E, Beier, P and Garding, E (2021) Toward best management practices for ecological corridors. Land 10, 140.CrossRefGoogle Scholar
Hamid, M, Khuroo, AA, Charles, B, Ahmad, R, Singh, C and Aravind, N (2019) Impact of climate change on the distribution range and niche dynamics of Himalayan birch, a typical treeline species in Himalayas. Biodiversity and Conservation 28, 2345–2370.CrossRefGoogle Scholar
Hibistu, T (2020) Korarima (Aframomum corrorima) value chain development in Ethiopia: a review to exploit the investment potential. International Journal of African and Asian Studies. doi: 10.7176/JAAS/66-04.Google Scholar
Hijmans, RJ, Cameron, SE, Parra, JL, Jones, PG and Jarvis, A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965–1978.CrossRefGoogle Scholar
Hylander, K, Nemomissa, S, Delrue, J and Enkosa, W (2013) Effects of coffee management on deforestation rates and forest integrity. Conservation Biology 27, 1031–1040.CrossRefGoogle ScholarPubMed
IPCC (2008) Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies. Geneva: Intergovernmental Panel on Climate Change, 132 pp.Google Scholar
Jansen, PCM (1981) Spices, Condiments and Medicinal Plants in Ethiopia, Their Taxonomy and Agricultural Significance. Wageningen: Pudoc, Centre for Agricultural Publishing and Documentation.Google Scholar
Jensen, MN (2003) Consensus on ecological impacts remains elusive. Science 299, 38. doi: 10.1126/science.299.5603.38.CrossRefGoogle ScholarPubMed
Jezkova, T, Jaeger, JR, Oláh-Hemmings, V, Jones, KB, Lara-Resendiz, RA, Mulcahy, DG and Riddle, BR (2016) Range and niche shifts in response to past climate change in the desert horned lizard Phrynosoma platyrhinos. Ecography 39, 437–448.CrossRefGoogle ScholarPubMed
Kearney, M and Porter, W (2009) Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges. Ecology Letters 12, 334–350.CrossRefGoogle ScholarPubMed
Keating, KA, Gogan, PJ, Vore, JM and Irby, LR (2007) A simple solar radiation index for wildlife habitat studies. The Journal of Wildlife Management 71, 1344–1348.CrossRefGoogle Scholar
Khanum, R, Mumtaz, A and Kumar, S (2013) Predicting impacts of climate change on medicinal asclepiads of Pakistan using Maxent modeling. Acta Oecologica 49, 23–31.CrossRefGoogle Scholar
Kifelew, H (2014) Morphological characterization of two species of Piper, Piper umbellatum and Piper capense in Tepi, Ethiopia. Greener Journal of Plant Breeding and Crop Science 2, 27–33.Google Scholar
Kreyling, J, Wana, D and Beierkuhnlein, C (2010) Climate warming and tropical plant species—consequences of a potential upslope shift of isotherms in southern Ethiopia. Diversity and Distributions 16, 593–605.CrossRefGoogle Scholar
Kumar, P, Verdin, KL and Greenlee, SK (2000) Basin level statistical properties of topographic position index for North America. Advances in Water Resources 23, 571–578.CrossRefGoogle Scholar
Larsen, TH, Brehm, G, Navarrete, H, Franco, P, Gomez, H, Mena, JL, Morales, V, Argollo, J, Blacutt, L and Canhos, V (2011) Range shifts and extinctions driven by climate change in the tropical Andes: synthesis and directions. In Herzog SK, Martinez R, Jorgensen PM and Tiessen H (eds), Climate Change and Biodiversity in the Tropical Andes. São Paulo, Brazil: Inter-American Institute for Global Change Research (IAI) and Scientific Committee on Problems of the Environment (SCOPE). pp. 47–67.Google Scholar
Lock, J (1976) Notes on some East African species of Aframomum (Zingiberaceae). Kew Bulletin   31, 263–271. doi: 10.2307/4109172.CrossRefGoogle Scholar
Loritz, R, Kleidon, A, Jackisch, C, Westhoff, M, Ehret, U, Gupta, H and Zehe, E (2019) A topographic index explaining hydrological similarity by accounting for the joint controls of runoff formation. Hydrology and Earth System Sciences 23, 3807–3821.CrossRefGoogle Scholar
Lucas, PM, González-Suárez, M and Revilla, E (2019) Range area matters, and so does spatial configuration: predicting conservation status in vertebrates. Ecography 42, 1103–1114.CrossRefGoogle Scholar
Madronich, S, Mckenzie, RL, Björn, LO and Caldwell, MM (1998) Changes in biologically active ultraviolet radiation reaching the Earth’s surface. Photochemical & Photobiological Sciences Official Journal of the European Photochemistry Association & the European Society for Photobiology 46, 5–19.Google ScholarPubMed
Millennium Ecosystem Assessment (2005) Ecosystems and Human Well-Being: Synthesis. Island, Washington, DC.Google Scholar
Mukherjee, S, Mukherjee, S, Garg, RD, Bhardwaj, A and Raju, PL (2013) Evaluation of topographic index in relation to terrain roughness and DEM grid spacing. Journal of Earth System Science 122, 869–886.CrossRefGoogle Scholar
Murphey, P C, Guralnick, R P, Glaubitz, R, Neufeld, D and Ryan, J A (2004) Georeferencing of museum collections: a review of problems and automated tools, and the methodology developed by the mountain and plains spatio-temporal database-informatics initiative (Mapstedi). PhyloInformatics 3, 1–29.Google Scholar
Nogués-Bravo, D, Araújo, MB, Romdal, T and Rahbek, C (2008) Scale effects and human impact on the elevational species richness gradients. Nature 453, 216–219.CrossRefGoogle ScholarPubMed
Norris, D (2014) Model thresholds are more important than presence location type: understanding the distribution of lowland tapir (Tapirus terrestris) in a continuous Atlantic forest of southeast Brazil. Tropical Conservation Science 7, 529–547.CrossRefGoogle Scholar
O’Sullivan, KS, Ruiz-Benito, P, Chen, JC and Jump, AS (2021) Onward but not always upward: individualistic elevational shifts of tree species in subtropical montane forests. Ecography 44, 112–123.CrossRefGoogle Scholar
Peng, LP, Cheng, FY, Hu, XG, Mao, JF, Xu, XX, Zhong, Y, Li, SY and Xian, HL (2019) Modeling environmentally suitable areas for the potential introduction and cultivation of the emerging oil crop Paeonia ostii in China. Scientific Reports 9, 1–10.Google Scholar
Perrings, C and Halkos, G (2015) Agriculture and the threat to biodiversity in sub-Saharan Africa. Environmental Research Letters 10, 1–10.CrossRefGoogle Scholar
Phillips, S and Dudik, M (2008) Modelado de distribuciones de especies con MaxEnt: nuevas extensiones y una evaluación exhaustiva. Ecografía 31, 161–175.CrossRefGoogle Scholar
Phillips, SJ, Dudík, M and Schapire, RE (2004) A maximum entropy approach to species distribution modeling. Proceedings of the Twenty-First International Conference on Machine Learnings, pp. 655–662.CrossRefGoogle Scholar
Phillips, SJ, Anderson, RP and Schapire, RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modeling 190, 231–259.CrossRefGoogle Scholar
Purvis, A, Gittleman, JL, Cowlishaw, G and Mace, GM (2000) Predicting extinction risk in declining species. Proceedings of the Royal Society of London. Series B: Biological Sciences 267, 1947–1952.CrossRefGoogle ScholarPubMed
Román-Palacios, C and Wiens, JJ (2020) Recent responses to climate change reveal the drivers of species extinction and survival. Proceedings of the National Academy of Sciences 117, 4211–4217. CrossRefGoogle ScholarPubMed
Serdeczny, O, Adams, S, Baarsch, F, Coumou, D, Robinson, A, Hare, W, Schaeffer, M, Perrette, M and Reinhardt, J (2016) Climate change impacts in Sub-Saharan Africa: from physical changes to their social repercussions. Regional Environmental Change. doi: 10.1007/s10113-015-0910-2.Google Scholar
Shumi, G, Rodrigues, P, Schultner, J, Dorresteijn, I, Hanspach, J, Hylander, K, Senbeta, F and Fischer, J (2019) Conservation value of moist evergreen Afromontane forest sites with different management and history in southwestern Ethiopia. Biological Conservation 232, 117–126.CrossRefGoogle Scholar
Støa, B, Halvorsen, R, Stokland, JN and Gusarov, VI (2019) How much is enough? Influence of number of presence observations on the performance of species distribution models. Sommerfeltia 39, 1–28.CrossRefGoogle Scholar
Swets, JA (1988) Measuring the accuracy of diagnostic systems. Science 240, 1285–1293. doi: 10.1126/science.3287615 PMID: 3287615.CrossRefGoogle ScholarPubMed
Tadese, S, Soromessa, T, Bekele, T and Meles, B (2021) Biosphere reserves in the southwest of Ethiopia. Advances in Agriculture. doi: 10.1155/2021/1585149 CrossRefGoogle Scholar
Team R C (2021) R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Available online: https://www.r-project.org/ (accessed on 1 January 2021).Google Scholar
Teramura, A H (1983) Effects of ultraviolet-B radiation on the growth and yield of crop plants. Physiologia Plantarum 58, 415–427.CrossRefGoogle Scholar
Trew, BT and Maclean, IMD (2021) Vulnerability of global biodiversity hotspots to climate change. Global Ecology Biogeography 30, 768–783.CrossRefGoogle Scholar
van Proosdij, AS, Sosef, MS, Wieringa, JJ and Raes, N (2016) Minimum required number of specimen records to develop accurate species distribution models. Ecography 39, 542–552.CrossRefGoogle Scholar
Weyant, J, Azar, C, Kainuma, M, Kejun, J, Nakicenovic, N, Shukla, PR, Rovere, EL and Yohe, G (2009) Report of 2.6 Versus 2.9 Watts/m2 RCPP Evaluation Panel Geneva. Switzerland: IPCC Secretariat.Google Scholar
Yackulic, CB, Chandler, R, Zipkin, EF, Royle, JA, Nichols, JD, Campbell grant, EH and Veran, S (2013) Presence-only modeling using MAXENT: when can we trust the inferences? Methods in Ecology and Evolution 4, 236–243.CrossRefGoogle Scholar
Yates, CJ, Elith, J, Latimer, AM, Le maitre, D, Midgley, GF, Schurr, FM and West, AG (2010) Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic regions: opportunities and challenges. Austral Ecology 35, 374–391.CrossRefGoogle Scholar
Supplementary material: PDF

Enkossa et al. supplementary material

Enkossa et al. supplementary material

Download Enkossa et al. supplementary material(PDF)
PDF 104.7 KB