Skip to main content
SpringerLink
Log in

Habitat suitability of Opuntia ficus-indica (L.) MILL. (CACTACEAE): a comparative temporal evaluation using diverse bio-climatic earth system models and ensemble machine learning approach

  • Research
  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

A comprehensive evaluation of the habitat suitability across the India was conducted for the introduced species Opuntia ficus-indica. This assessment utilized a newly developed model called BioClimInd, takes into account five Earth System Models (ESMs). These ESMs consider two different emission scenarios known as Representative Concentration Pathways (RCP), specifically RCP 4.5 and RCP 8.5. Additionally, the assessment considered two future time frames: 2040–2079 (60) and 2060–2099 (80). Current study provided the threshold limit of different climatic variables in annual, quarter and monthly time slots like temperature annual range (26–30 °C), mean temperature of the driest quarter (25–28 °C); mean temperature of the coldest month (22–25 °C); minimum temperature of coldest month (13–17 °C); precipitation of the wettest month (250–500 mm); potential evapotranspiration Thronthwaite (1740–1800 mm). Predictive climatic habitat suitability posits that the introduction of this exotic species is deemed unsuitable in the Northern as well as the entirety of the cooler eastern areas of the country. The states of Rajasthan and Gujarat exhibit the highest degree of habitat suitability for this particular species. Niche hypervolumes and climatic variables affecting fundamental and realized niches were also assessed. This study proposes using multi-climatic exploration to evaluate habitats for introduced species to reduce modeling uncertainties.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Data availability

The data that support the findings of this study specifically geo-coordinates of the species are available on request from the corresponding author, [Manish Mathur]. The data are not publicly available due to avoid the duplication of the work within the same geographical area.

References

  • Ab Lah, N. Z., Yusop, Z., Hashim, M., Salim, J. M., Numata, S. (2021). Predicting the habitat suitability of Melaleuca cajuputi based on the MaxEnt species distribution model. Forest, 12(11), https://doi.org/10.3390/f12111449

  • Acharya, P., Biradar, C., Louhaichi, M., Ghosh, S., Hassan, S., Moyo, H., & Sarkar, A. (2019). Finding a suitable niche for cultivating cactus pear (Opuntia ficus-indica) as an integrated crop in resilient dryland agroecosystems of India. Sustainability, 11, 5897. https://doi.org/10.3390/su11215897

    Article  Google Scholar 

  • Ahmad, R., Khuroo, A. A., Hamid, M., Charle, B., & Rashid, I. (2019). Predicting invasion potential and niche dynamics of Parthenium hysterophorus (Congress grass) in India under projected climate changes. Biodiversity Conservation. https://doi.org/10.1007/s10531-019-01775-y

    Article  Google Scholar 

  • Araujo, M. B. (2007). New, M. ensemble forecasting of species distributions. Trends in Ecology and Evolution, 22, 42–47.

    Article  PubMed  Google Scholar 

  • Baker, D. J., Maclean, I. M. D., Goodall, M., & Gaston, K. J. (2021). Species distribution modelling is needed to support ecological impact assessments. Journal of Applied Ecology, 58, 21–26.

    Article  Google Scholar 

  • Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., & Kristjánsson, J. E. (2013). The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate. Geoscience Model Development, 6, 687–720. https://doi.org/10.5194/gmd-6-687-2013

    Article  ADS  Google Scholar 

  • Booth, T. H. (2017). Assessing species climatic requirements beyond the realized niche: Some lessons mainly from tree species distribution modelling. Climate Change, 145, 259–271.

    Article  ADS  Google Scholar 

  • Breiner, F., Guisan, A., Bergamini, A., & Nobis, M. (2015). Overcoming limitations of modelling rare species by using ensembles of small models. Methods in Ecological Evolution, 6, 1210–1218.

    Article  Google Scholar 

  • Cao, Z., Zhang, L., Zhang, X., & Guo, Z. (2021). Predicting the potential distribution of Hylomecon japonica in China under current and future climate change based on maxent model. Sustainability, 13, 11253. https://doi.org/10.3390/su132011253

    Article  Google Scholar 

  • Cavalcante, A. M. B., Fernades, P. H. C., & da Silva, E. M. (2020). Opuntia ficus-indica (L.) Mill. And climate change: an analysis in the light of species distribution modelling in the Caatinga biome. Brazilian Journal of Meteorology. https://doi.org/10.1590/0102-7786353001

    Article  Google Scholar 

  • Changjun, G., Yanli, T., Linshan, L., Bo, W., Yili, Z., Haibin, Y., Xilong, W., Zhuoga, Y., Binghua, Z., & Bochao, C. (2021). Predicting the potential global distribution of Ageratina adenophora under current and future climate change scenarios. Ecology and Evolution, 1, 22. https://doi.org/10.1002/ece3.7974

    Article  Google Scholar 

  • Coban, H.O., Orucu, O.K., Arslan. E.S. (2020). MaxEnt modelling for predicting the current and future potential geographical distribution of Quercus libani Olivier. Sustainability, 2671, https://doi.org/10.3390/su12072671

  • Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., & Totterdell, I. J. (2000). Acceleration of global warming due to carboncycle feedbacks in a coupled climate model. Nature, 408, 184–187.

    Article  ADS  PubMed  CAS  Google Scholar 

  • Erauskin-Extramiana, M., Arrizabalaga, H., Cabre, A., Coelho, R., Rosa, D., Ibaibarriaga, L., & Chust, G. (2020). Are shifts in species distribution triggered by cli–mate change? A swordfish case study. Deep Sea Research Part II: Tropical Studies in Oceanography, 175, 104666.

    Article  Google Scholar 

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

    Article  ADS  Google Scholar 

  • Gajender, Yadav, R. K., Dagar, J. C., Lal, K., & Singh, G. (2013). Growth and fruit characteristics of edible cactus (Opuntia ficus-indica) under sat stress environment. Journal of Soil Salinity and Water Quality, 5(2), 136–142.

    Google Scholar 

  • Gajender, Singh, G., Dagar, J. C., Lal, K., & Yadav, R. K. (2014). Performance of edible cactus (Opuntia ficus -indica) in saline environments. Indian Journal of Agricultural Sciences, 84(4), 509–513.

    Article  Google Scholar 

  • GBIF.org (27 June 2023) GBIF Occurrence Download https://doi.org/10.15468/dl.dbe5g8

  • Goncalves-Oliveira, R.C., Rodrigues, H.B., Benko-Iseppon, A.M. (2022). Range distribution of the invasive alien species Calotropis procera in South America dry environments under climatic change scenarios. Journal of Arid Environment, 205. 10. 1016/j. jaridenv. 2022. 104819

  • Hajima, T. (2015). Evaluation of historical leaf area index change in the MIRCO-ESM. Journal of the Remote Sensing Society of Japan, 35(1), 24–30.

    Google Scholar 

  • Hempel, S., Frieler, K., Warszawski, L., Schewe, J., & Piontek, F. (2013). A trend-preserving bias correction -The ISI-MIP approach. Earth System Dynamics, 4, 219–236. https://doi.org/10.5194/esd-4-219-2013

    Article  ADS  Google Scholar 

  • Inglese, P., Scalenghe, R. (2009). Cactus pear (Opuntia ficus‐indica L. (Mill)). In Manual of methods for soil and land evaluation; Constantini, E.A.C., Ed.; Science Publisher: Enfield, NH, USA. pp. 275–285.

  • Jijon, J.D., Gaudry, K.H., Constante, J., Valencia, C. (2021). Augmenting the spatial resolution of climate-change temperature projections for city planners and local decision makers. Environmental Research Letters, 16, https://doi.org/10.1088/1748-9326/abf7f2

  • Jung, J. B., Park, G. E., Kim, H. J., Huh, J. H., & Um, Y. (2023). Predicting the habitat suitability for Angelica gigas medicinal herb using an ensemble species distribution model. Forests, 14, 592. https://doi.org/10.3390/f14030592

    Article  Google Scholar 

  • Kass, J. M., Vilela, B., Aiello-Lammens, M. E., Muscarella, R., Merow, C., & Anderson, R. P. (2018). Wallace: A flexible platform for reproducible modelling of species niches and distributions built for community expansion. Methods in Ecology and Evolution, 9, 1151–1156. https://doi.org/10.1111/2041-210X.12945

    Article  Google Scholar 

  • Kauthale, V., Kadao, S., Aware, M. (2021). Introduction of cactus pear (Opuntia ficus indica) as a source of fodder in dry areas of Rajasthan and Gujarat. BAIF Development Research Foundation, Central Research Station, Urulikanchan, Pune, India. Page 40. ISBN : 978–81–952265–5–9

  • Khan, A.M., Li, Q., Saqib, Z., Khan, N., Habib, T., Khalid, N., Majeed, M., Tariq, A. (2022). MaxEnt modeling and impact of climate change on habitat suitability variations of economically important chilgoza pine (Pinus gerardiana Wall.) in South Asia. Forests, 13, 715 .3390/f130507150

  • Khan, S., & Verma, S. (2022). Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata. Frontiers in Forest and Global Change, 5, 977691. https://doi.org/10.3389/gc.2022.977691

    Article  Google Scholar 

  • Khandelwal, V., Mohamed, M. B. N. M., Shukla, A. K., Mangalassery, S., & Dayal, D. (2019). Establishment and performance of cactus (Opuntia ficus-indica) accessions at initial stages under shed net in semi-arid region of Rajasthan. International Journal of Current Microbiology and Applied Sciences, 8(10), 1983–1988.

    Article  Google Scholar 

  • Kogo, B. K., Kumar, L., Koech, R., & Langat, P. (2019). Modelling impacts of climate change on maize (Zea mays L.) growth and productivity: A review of models, outputs and limitations. Journal of Geoscience and Environment Protection, 7, 76–95.

    Article  Google Scholar 

  • Kumar, S., & Stohlgren, T. J. (2009). MaxEnt modelling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology Nature and Environment, 1, 94–98.

    Google Scholar 

  • Kumar, S., Louhaichi, M., Dana Ram, P., Tirumala, K. K., Ahmad, S., Rai, A. K., Sarker, A., Hassan, S., Liguori, G., Kumar, P. G., Govindasamy, P., Prasad, M., Hulgathur, G., & Kumar, P. K. (2021). Cactus pear (Opuntia ficus-indica) productivity, proximal composition and soil parameters as affected by planting time and agronomic management in a semi-arid region of India. Agronomy, 11, 1647. https://doi.org/10.3390/agronomy11081647

    Article  CAS  Google Scholar 

  • Kumar, S., Palsaniya, D. R., Kumar, T. K., Misra, A. K., Ahmad, S., Rai, A. K., Sarkar, A., Louhaichi, M., Hassan, S., Liguori, G., Ghosh, P. K., Govindasamy, P., Mahawer, S. K., & Bhargavi, H. A. (2022). Survival, morphological variability, and performance of Opuntia ficus-indica in a semi-arid region of India. Archives of Agronomy and Soil Sciences. https://doi.org/10.1080/03650340.2022.2031998

    Article  Google Scholar 

  • Le Houérou, H. N. (1996). The role of cacti (Opuntia spp.) in erosion control, land reclamation, rehabilitation agricole and agricultural development in the Mediterranean Basin. Journal of Arid Environment, 33, 135–159.

    Article  ADS  Google Scholar 

  • Le Houérou, H. N. (2002). Cacti (Opuntia spp.) as a fodder crop for marginal lands in the Mediterranean Basin. Acta Horticulture, 581, 21–46.

    Article  Google Scholar 

  • Le Houérou, H,N. (1989). An assessment of the economic feasibility of fodder shrubs plantation (with particular reference to Africa). In The Biology and Utilization of Shrubs; McKell, C.M., Ed.; Academic Press: New York, USA. 603–630.

  • Louhaichi, M., Park, A. G., Mata-Gonzalez, R., Johnson, D. E., & Mohawesh, Y. M. A. (2015). A preliminary model of Opuntia ficus-indica (L.) Miller suitability for Jordan. Acta Horticulture, 1067, 267–273.

    Article  Google Scholar 

  • Louhaichi, M., Hassan, S., Kumar, S., Palsaniya, D.R., Misra, A.K., Ahmed, S., Naorem, A., Patel, S. (2021). Promoting cactus (Opuntia ficus-indica) as drought resilient feed resource under different agro-ecological production system across India: 1–26 https://mel.cgiar.org/reporting/download/hash/3d9958fc21c2a7d935fed84424ba711e

  • Mathur, P., & Mathur, M. (2023a). Machine learning ensemble species distribution modeling of an endangered arid land tree Tecomella undulata : A global appraisal. Arabian Journal of Geosciences, 16, 131.

    Article  Google Scholar 

  • Mathur, M., & Mathur, P. (2023b). Predictive ecological niche modelling of an important bio-control agent: Trichoderma harzianum (Rifai) using the MaxEnt machine learning tools with climatic and non-climatic predictors. Biocontrol Science and Technology. https://doi.org/10.1080/09583157.2023.2245985

    Article  Google Scholar 

  • Mathur, M., & Mathur, P. (2023c). Prediction of global distribution of Ganoderma lucidum (Leys.) Karsten: a machine learning maxent analysis for a commercially important plant fungus. Indian Journal of Ecology, 50(2), 289–305. https://doi.org/10.55362/IJE/2023/3893

    Article  Google Scholar 

  • Mathur, M., Mathur, P. (2023d). Global distribution modelling of Macrophomina phaseolina (Tassi) Goid: A Comparative Assessment Using Ensemble Machine Learning Tools. Australasian Plant Pathology, 52(3): https://doi.org/10.1007/s13313-023-00927-7.

  • Mathur, M., Mathur, P., & Purohit, H. (2023). Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables. Ecological Processes, 12, 8. https://doi.org/10.1186/s13717-023-00423-2

    Article  Google Scholar 

  • Meghwal, P. R., Kumar, A., & Kumar, S. (2018). Performance of cactus pear at two geographical locations in Indian arid zone. Indian Journal of Horticulture, 75(1), 157–160.

    Article  Google Scholar 

  • Morales-Barbero, J., & Vega-Álvarez, J. (2019). Input matters matter: Bioclimatic consistency to map more reliable species distribution models. Methods in Ecology and Evolution, 10, 212–224.

    Article  Google Scholar 

  • Nimbkar, N. (2017). Research on Opuntia species at the Nimbkar Agricultural Research Institute (NARI) Maharashtra, India. In: Cactus Pear (Opuntia ficus- indica) in India. Suresh, K., Devi, D., Shamsudheen, M., Deepesh, M. and Om Prakash, Y. 2017. ICAR-Central Arid Zone Research Institute, Jodhpur, Regional Research Station, Kukma-Bhuj, Gujarat. P 19–21.

  • Noce, S., Caporaso, L., & Santini, M. (2020). A new global dataset of bioclimatic indicators. Scientific Data, 7, 398. https://doi.org/10.1038/s41597-020-00726-5

    Article  PubMed  PubMed Central  Google Scholar 

  • Nunez-Penichet, C., Cobos, M. E., & Soberon, J. (2021). Non-overlapping climatic niches and biogeographic barriers explain disjunct distributions of continental Urania moths. Frontiers in Biogeography, 13(2), e52142.

    Article  Google Scholar 

  • Obiakara, M. C., & Fourcade, Y. (2018). Climatic niche and potential distribution of Tithonia diversifolia (Hemsl.) A. gray in Africa. PLoS One, 13(9), e0202421. https://doi.org/10.1371/journal.pone.020242

    Article  PubMed  PubMed Central  Google Scholar 

  • Osorio-Olvera, L, Lira-Noriega, A., Soberon, J., Townsend, P. A., Falcon. M., Contrears-Diaz, R.G., Martinez-Meyer, E., Barve, V., Barve, N. (2020). Ntbox: an R package with graphical user interface for modeling and evaluating multidimensional ecological niches. Methods in Ecology and Evaluation 11, 1199–1206 https://doi.org/10.1111/2041-210X.13452. https://github.com/luismurao/ntbox

  • Pimienta-Barrios, E., Zando, J., Yepez, E., Pimienta-Barrios, E., & Nobel, P. S. (2000). Seasonal variation of net CO2 uptake for cactus pear (Opuntia ficus-indica) and pitayo (Stenocereus queretaroensis) in a semi-arid environment. Journal of Arid Environment, 44, 73–83.

    Article  ADS  Google Scholar 

  • Pradhan, P. (2016). Strengthening Maxent modelling through screening of redundant explanatory bioclimatic variables with variance inflation factor analysis. Researcher, 8(5), 29–34.

    Google Scholar 

  • Purwaningsih, A., & Hidayat, R. (2016). Performance of decadal prediction in couple model intercomparisson project phase 5 (CMIP5) on projecting climate in tropical areas. Procardia of Environmental Sciences, 33, 128–139.

    Article  Google Scholar 

  • Rajamanickam, V., Babel, H., Montano-Herrera, L., Ehsani, A., Stiefel, F., Haider, S., Presser, B., & Knapp, B. (2021). About model validation in bioprocessing. Processes, 9, 961. https://doi.org/10.3390/pr9060961

    Article  Google Scholar 

  • Rajpoot, R., Adhikari, D., Verma, S., Saikia, P., Kumar, A., Grant, K.R., Dyanandan, A., Kumar, A., Khare, P.K., Khan, M.L. (2020). Climate models predict a divergent future for the medicinal tree Boswellia serrate Roxb. In India. Global Ecological Conservation, 23, https://doi.org/10.1016/j.gecco.2020.e01040

  • Schmitt, S., Pouteau, R., Justeau, D., de Boissieu, F., & Brinbaum, P. (2017). SSDM: An R package to predict distribution of species richness and composition based on stacked species distribution models. Methods in Ecology and Evaluation. https://doi.org/10.1111/2041-210X.12841

    Article  Google Scholar 

  • Soni, M. L., Yadava, N. D., Kumar, S., & Roy, M. M. (2015). Evaluation for growth and yield performance of prickly pear cactus (Opuntia ficus-indica (L.) Mill) accessions in hot arid region of Bikaner, India. Range Management and Agroforestry, 36(1), 19–25.

    Google Scholar 

  • Tesfay, Y. B., & Kreyling, J. (2021). The invasive Opuntia ficus-indica homogenizes native plant species compositions in the highlands of Eritrea. Biological Invasion, 23, 433–442. https://doi.org/10.1007/s10530-020-02373-8(0123456789(),-volV)(01234567

    Article  Google Scholar 

  • Wang, N., Zhang, H., & Nobel, P. S. (1998). Carbon flow and carbohydrate metabolism during sink-to-source transition for developing cladodes of Opuntia ficus-indica. Journal of Experimental Botany, 49, 1835–1843.

    Article  CAS  Google Scholar 

  • Wani, Z. A., Ridwan, Q., Khan, S., Pant, S., Siddiqui, S., Moustafa, M., Ahmad, A. E., & Yassin, H. M. (2022). Changing climatic scenarios anticipate dwindling of suitable habitats for endemic species of Himalaya- Prediction of ensemble modelling using Aconitum heterophyllum as a model plant. Sustainability, 14, 8491. https://doi.org/10.3390/su14148491

    Article  Google Scholar 

  • Winter, K., Garcia, M., & Holtum, J. A. M. (2008). On the nature of facultative and constitutive CAM: Environmental and developmental control of CAM expression during early growth of Clusia, Kalanchoe¨, and Opuntia. Journal of Experimental Botany, 59, 1829–1840.

    Article  PubMed  CAS  Google Scholar 

  • Xu, D., Zhou, Z., Wang, R., Ye, M., & Pu, B. (2019). Modeling the distribution of Zanthoxylum armatum in China with MaxEnt modeling. Global Ecology and Conservation. https://doi.org/10.1016/j.gecco.2019.e00691

    Article  Google Scholar 

  • Xu, F., Wang, B., He, C., Liu, D. L., Feng, P., Yao, N., Zhang, R., Xu, S., Xue, J., & Feng, H. (2021). Optimizing sowing date and planting density can mitigate the impacts of future climate on maize yield: A case study in the Guanzhong plain of China. Agronomy, 11, 1452. https://doi.org/10.3390/agronomy11081452

    Article  CAS  Google Scholar 

  • Yigini, Y., & Panagos, P. (2016). Assessment of soil organic carbon stocks under future climate and land cover changes in Europe. Science of Total Environment, 557, 838–850.

    Article  ADS  Google Scholar 

  • Zhang, Y., Wang, Y., & Niu, H. (2017). Spatio-temporal variations in the areas suitable for the cultivation of rice and maize in China under future climate scenarios. Science of Total Environment, 601, 518–531.

    Article  ADS  Google Scholar 

  • Zhang, Y., Clauzel, C., Li, J., Xue, Y., Zhang, Y., Wu, G., & Li, D. (2019). Identifying refugia and corridors under climate change conditions for the Sichuan snub-nosed monkey (Rhinopithecus roxellana) in Hubei Province, China. Ecology and Evolution, 9(4), 1680–1690.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

Senior author thankful to the Director, ICAR-CAZRI for giving approval to him for attending training on R-Programming. Miss Preet Mathur (Jodhpur Institute of Engineering and Technology, Jodhpur, India) thankful to their Director for extending their academic help.

Author information

Authors and Affiliations

  1. ICAR-Central Arid Zone Research Institute, 342 003, Jodhpur, India

    Manish Mathur

  2. Jodhpur Institute of Engineering and Technology, Computer Science Department, Jodhpur, India

    Preet Mathur

Authors
  1. Manish Mathur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Preet Mathur
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Dr. Manish Mathur conceptualized the theme and interpretation of output of various machine learning techniques. Miss Preet Mathur prepared various types of language codes in python, Java and in R scripts and convert the various file format for SSDM R packages.

Corresponding author

Correspondence to Preet Mathur.

Ethics declarations

All authors have read, understood, and have complied as applicable.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 187 KB)

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

Mathur, M., Mathur, P. Habitat suitability of Opuntia ficus-indica (L.) MILL. (CACTACEAE): a comparative temporal evaluation using diverse bio-climatic earth system models and ensemble machine learning approach. Environ Monit Assess 196, 232 (2024). https://doi.org/10.1007/s10661-024-12406-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-024-12406-7

Keywords

Search

Navigation