Abstract
Prosopis juliflora, one of the most invasive species in arid and semi-arid environments, can sequester considerable amounts of carbon and provide fuel wood for domestic consumption. However, the lack of species-specific allometric models limits efforts to estimate forest biomass and its potential to store carbon. We conducted this study to determine the rate of expansion of this Prosopis in arid environments and develop robust allometric models to precisely predict tree-level biomass and its carbon storage potential. The satellite image analysis showed that Prosopis continues to expand rapidly along riverbanks and accounted for 69% of the available vegetation cover in the study area. The spatial coverage of Prosopis increased by 40% within 5 years from 2016 to 2021 and has been expanding at a rate of 8% per year. The rate of Prosopis expansion calls for the application of new utilization systems like massive charcoal production which may be a great blessing to the region. For such purpose, quantification of the biomass of Prosopis from easily measured variables is essential. Hence, after destructive sampling of 45 individual trees, the relationships between three variables (diameter at stump height, DSH; height, H; and wood density, ρ) and their total biomass of the aboveground parts were used to fit regression models in R software. These models were developed using DSH alone, DSH and height or in a combination of DSH, H and ρ. Although DSH alone explained most of the variations (91%), adding H and ρ as additional independent variables resulted in a much better prediction of biomass estimation with the lowest values of bias. Therefore, the best-selected model for the above-ground biomass (AGB) estimation of the species Prosopis is M9 (\({\text{AGB}}={\text{exp}}(-3.053+0.919\times {\text{ln}} ({\text{DSH}}^{2} \times H \times \rho ))\) which presented the highest adj. R2 value (0.985) and the lowest values of Akaike information criteria. Given narrow diameter ranges, the model can be applied beyond their valid data ranges and to other similar growth forms across the arid regions of Ethiopia.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The dataset supporting the conclusions of this article is included within the article.
References
Abdulahi MM, Ute JA, Regasa T (2017) Prosopis juliflora L.: distribution, impacts and available control methods in Ethiopia. Trop Subtrop Agroecosyst 20:75–89
Abich A, Mucheye T, Tebikew M et al (2019) Species-specific allometric equations for improving aboveground biomass estimates of dry deciduous woodland ecosystems. J For Res 30:1619–1632. https://doi.org/10.1007/S11676-018-0707-5
Andreas J, Markus H, Martin R, Bernhard H (2011) Estimation of aboveground biomass in alpine forests: a semi-empirical approach considering canopy transparency derived from airborne LiDAR data. Sensors 11:278–295. https://doi.org/10.3390/s110100278
Askar NN, Phairuang W et al (2018) Estimating aboveground biomass on private forest using sentinel-2 imagery. J Sens. https://doi.org/10.1155/2018/6745629
Asrat G, Seid A (2017) Allelopathic effect of meskit (Prosopis juliflora (Sw.) DC) aqueous extracts on tropical crops tested under laboratory conditions. Momona Ethiop J Sci 9:32. https://doi.org/10.4314/mejs.v9i1.3
Berhanu A, Tesfaye G (2006) The prosopis dilemma, impacts on dryland biodiversity and some controlling methods. J Drylands 1(2):158–164
Birhane E, Treydte AC, Eshete A et al (2017) Can rangelands gain from bush encroachment? Carbon stocks of communal grazing lands invaded by Prosopis juliflora. J Arid Environ 141:60–67. https://doi.org/10.1016/j.jaridenv.2017.01.003
Bohdan K, Jozef P, Vladimír S (2015) Biomass functions and expansion factors for young trees of European ash and Sycamore maple in the Inner Western Carpathians. Aust J For Sci 131:1–26
Chave J, Réjou-Méchain M, Búrquez A et al (2014) Improved allometric models to estimate the aboveground biomass of tropical trees. Glob Change Biol 20:3177–3190. https://doi.org/10.1111/gcb.12629
Cienciala E, Centeio A, Blazek P et al (2013) Estimation of stem and tree level biomass models for Prosopis juliflora/pallida applicable to multi-stemmed tree species. Trees Struct Funct 27:1061–1070. https://doi.org/10.1007/s00468-013-0857-1
Diédhiou I, Diallo D, Mbengue A et al (2017) Allometric equations and carbon stocks in tree biomass of Jatropha curcas L. in Senegal’s Peanut Basin. Glob Ecol Conserv 9:61–69. https://doi.org/10.1016/j.gecco.2016.11.007
Dimobe K, Mensah S, Goetze D et al (2018) Aboveground biomass partitioning and additive models for Combretum glutinosum and Terminalia laxiflora in West Africa. Biomass Bioenergy 115:151–159. https://doi.org/10.1016/j.biombioe.2018.04.022
Djomo AN, Chimi CD (2017) Tree allometric equations for estimation of above, below and total biomass in a tropical moist forest: case study with application to remote sensing. For Ecol Manag 391:184–193. https://doi.org/10.1016/j.foreco.2017.02.022
Edrisi SA, El-Keblawy A, Abhilash PC (2020) Sustainability analysis of Prosopis juliflora (Sw.) DC based restoration of degraded land in North India. Land. https://doi.org/10.3390/land9020059
Ethiopian Mapping Agency (EMA) (2018) Ethiopian land use land cover classification and coding standard. Addis Ababa
Feyisa K, Beyene S, Megersa B et al (2018) Allometric equations for predicting above-ground biomass of selected woody species to estimate carbon in East African rangelands. Agrofor Syst 92:599–621. https://doi.org/10.1007/S10457-016-9997-9
Gianvenuti A, Farah I, Yasmin N et al (2018) Using Prosopis as an energy source for refugees and host communities in Djibouti, and controlling its rapid spread. Food and Agriculture Organization of the United Nations (FAO), Rome
Gunawardena AR, Fernando TT, Nissanka SP, Dayawansa NDK (2015) Assessment of spatial distribution and estimation of biomass of Prosopis juliflora (Sw.) DC. in Puttlam to mannar region of Sri Lanka using remote sensing and GIS. Trop Agric Res 25:228. https://doi.org/10.4038/tar.v25i2.8144
Guo Z, Fang J, Pan Y, Birdsey R (2010) Inventory-based estimates of forest biomass carbon stocks in China: a comparison of three methods. For Ecol Manag 259:1225–1231. https://doi.org/10.1016/j.foreco.2009.09.047
Haile M, Hishe H, Gebremedhin D (2018) Prosopis juliflora pods mash for biofuel energy production: implication for managing invasive species through utilization. Int J Renew Energy Dev 7:205–212. https://doi.org/10.14710/ijred.7.3.205-212
Huy B, Kralicek K, Poudel KP et al (2016) Allometric equations for estimating tree aboveground biomass in evergreen broadleaf forests of Viet Nam. For Ecol Manag 382:193–205. https://doi.org/10.1016/j.foreco.2016.10.021
Ilukor J, Rettberg S, Treydte A, Birner R (2016) To eradicate or not to eradicate? Recommendations on Prosopis juliflora management in Afar, Ethiopia, from an interdisciplinary perspective. Pastoralism 6:4–11. https://doi.org/10.1186/s13570-016-0061-1
Kapinga K, Syampungani S, Kasubika R et al (2018) Species-specific allometric models for estimation of the above-ground carbon stock in miombo woodlands of Copperbelt Province of Zambia. For Ecol Manag 417:184–196. https://doi.org/10.1016/j.foreco.2018.02.044
Kumar R, Chandrashekar N (2016) Study on fuelwood and carbonization characteristics of Prosopis juliflora. J Indian Acad Wood Sci. https://doi.org/10.1007/s13196-016-0171-9
Kusmana C, Hidayat T, Tiryana T et al (2018) Allometric models for above- and below-ground biomass of Sonneratia spp. Glob Ecol Conserv 15:e00417. https://doi.org/10.1016/j.gecco.2018.e00417
Kyuma RK (2016) Evaluation of Prosopis Juliflora productivity for carbon stocks and animal feeds in selected dry land sites, Magadi Sub-county, Kenya. University of Nairobi, Nairobi
Linders TEW, Schaffner U, Eschen R et al (2019) Direct and indirect effects of invasive species: biodiversity loss is a major mechanism by which an invasive tree affects ecosystem functioning. J Ecol 107:2660–2672. https://doi.org/10.1111/1365-2745.13268
Mehari ZH (2015) The invasion of Prosopis juliflora and Afar pastoral livelihoods in the Middle Awash area of Ethiopia. Ecol Process 4:1–9. https://doi.org/10.1186/s13717-015-0039-8
Meroni M, Ng WT, Rembold F et al (2017) Mapping Prosopis juliflora in West Somaliland with Landsat 8 Satellite Imagery and Ground Information. Land Degrad Dev 28:494–506. https://doi.org/10.1002/ldr.2611
Mongabay (2019) Deforestation statistics for Ethiopia. rainforests.mongabay.com. Accessed 10 Feb 2022
Mugasha WA, Eid T, Bollandsås OM et al (2013) Allometric models for prediction of above- and belowground biomass of trees in the miombo woodlands of Tanzania. For Ecol Manag 310:87–101. https://doi.org/10.1016/j.foreco.2013.08.003
Ng WT, Meroni M, Immitzer M et al (2016) Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland. Int J Appl Earth Obs Geoinf 53:76–89. https://doi.org/10.1016/j.jag.2016.07.019
Ng WT, Rima P, Einzmann K et al (2017) Assessing the potential of sentinel-2 and pléiades data for the detection of prosopis and vachellia spp. in Kenya. Remote Sens. https://doi.org/10.3390/rs9010074
Oduor NM, Githiomi JK (2013) Fuel-wood energy properties of Prosopis juliflora and Prosopis pallida grown in Baringo District, Kenya. Afr J Agric Res 8:2476–2481. https://doi.org/10.5897/AJAR08.221
Pasiecznik NM, Choge SK, Rosenfeld AB, Harris PJC(2007) Underutilised crops for famine and poverty alleviation: a case study on the potential of the multipurpose Prosopis tree. In: 5th international symposium on new crop uses their role a rapidly change world, pp 326–346
Patnaik P, Abbasi T, Abbasi SA (2017) Prosopis (Prosopis juliflora): blessing and bane. Trop Ecol 58:455–483
Picard N, Henry M, Mortier F et al (2012) Using Bayesian model averaging to predict tree aboveground biomass in tropical moist forests. For Sci 58:15–23
Rapinel S, Mony C, Lecoq L et al (2019) Evaluation of Sentinel-2 time-series for mapping floodplain grassland plant communities. Remote Sens Environ 223:115–129. https://doi.org/10.1016/J.RSE.2019.01.018
Ravhuhali KE, Mudau HS, Moyo B et al (2021) Prosopis species—an invasive species and a potential source of browse for livestock in semi-arid areas of South Africa. Sustainability 13:1–13. https://doi.org/10.3390/su13137369
Shackleton RT, Le Maitre DC, Pasiecznik NM, Richardson DM (2014) Prosopis: a global assessment of the biogeography, benefits, impacts and management of one of the world’s worst woody invasive plant taxa. AoB Plants 6:1–18. https://doi.org/10.1093/aobpla/plu027
Shiferaw W, Bekele T, Demissew S, Aynekulu E (2019) Prosopis juliflora invasion and environmental factors on density of soil seed bank in Afar Region, Northeast Ethiopia. J Ecol Environ 43:1–21. https://doi.org/10.1186/s41610-019-0133-4
Shiferaw H, Bewket W, Eckert S (2019b) Performances of machine learning algorithms for mapping fractional cover of an invasive plant species in a dryland ecosystem. Ecol Evol 9:2562–2574. https://doi.org/10.1002/ece3.4919
Shiferaw H, Alamirew T, Dzikiti S et al (2021) Water use of Prosopis juliflora and its impacts on catchment water budget and rural livelihoods in Afar Region, Ethiopia. Sci Rep 11:1–14. https://doi.org/10.1038/s41598-021-81776-6
Sillett SC, Van Pelt R, Carroll AL et al (2019) Allometric equations for Sequoia sempervirens in forests of different ages. For Ecol Manag 433:349–363. https://doi.org/10.1016/j.foreco.2018.11.016
Singh V, Tewari A, Kushwaha SPS, Dadhwal VK (2011) Formulating allometric equations for estimating biomass and carbon stock in small diameter trees. For Ecol Manag 261:1945–1949. https://doi.org/10.1016/j.foreco.2011.02.019
Tilahun SL, Asfaw A (2012) Modeling the expansion of Prosopis juliflora and determining its optimum utilization rate to control the invasion in Afar Regional State of Ethiopia. Int J Appl Math Res 1:726–743. https://doi.org/10.14419/ijamr.v1i4.200
Ubuy MH, Eid T, Bollandsås OM, Birhane E (2018) Aboveground biomass models for trees and shrubs of exclosures in the drylands of Tigray, northern Ethiopia. J Arid Environ 156:9–18. https://doi.org/10.1016/j.jaridenv.2018.05.007
Vidhya R, Vijayasekaran D, Ramakrishnan SS (2017) Mapping invasive plant Prosopis juliflora in arid land using high resolution remote sensing data and biophysical parameters. Indian J Geo-Mar Sci 46:1135–1144
Vinh T, Van, Marchand C, Linh TVK et al (2019) Allometric models to estimate above-ground biomass and carbon stocks in Rhizophora apiculata tropical managed mangrove forests (Southern Viet Nam). For Ecol Manag 434:131–141. https://doi.org/10.1016/j.foreco.2018.12.017
Wakie TT, Evangelista PH, Jarnevich CS, Laituri M (2014) Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia. PLoS One 9:3–11. https://doi.org/10.1371/journal.pone.0112854
Wakie TT, Laituri M, Evangelista PH et al (2021) Allelopathic effect of meskit (Prosopis juliflora (Sw.) DC) aqueous extracts on tropical crops tested under laboratory conditions. Appl Geogr 66:32. https://doi.org/10.4314/mejs.v9i1.3
Walter KJ, Armstrong KV (2014) Benefits, threats and potential of Prosopis in South India. For Trees Livelihoods 23:232–247. https://doi.org/10.1080/14728028.2014.919880
WRB (2014) World reference base for soil resources 2014. Food and Agriculture Organization of the United Nations, Rome
Acknowledgements
This study was supported by the Panafrica Geoinformation Service plc (Prosopis Juliflora energy potential estimation project in Afra region, Ethiopia). We acknowledge Panafrica Geoinformation Service plc for reasonable financial support. During the course of this research, many individuals were involved in biomass sampling; the authors would like to thank the Awash Office of Agriculture and the leaders of the forestry sector for their kind assistance in the field work. Comments from two anonymous referees and editor improved the quality of the original manuscript.
Funding
Funding was provided by Panafrica Geoinformation Service plc (Prosopis Juliflora energy potential estimation project_2019).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor 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.
About this article
Cite this article
Assefa, D., Mekuriaw, A., Tesfaye, M. et al. Mapping of Prosopis juliflora rate of expansion and developing species-specific allometric equations to estimate its aboveground biomass in the dry land of Ethiopia. Model. Earth Syst. Environ. 9, 263–274 (2023). https://doi.org/10.1007/s40808-022-01495-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-022-01495-3