Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling
Abstract
:1. Introduction
2. Materials and Methods
2.1. Location of Weed Survey
2.2. Procedure of Weed Survey
2.3. Determination of Relative Density and Abundance of Parthenium Weed
2.4. Environmental and Bioclimatic Data
2.5. Current and Future Projections of Parthenium
3. Results
3.1. Location and Distribution of Parthenium Weed Infestation
3.2. Density, Frequency, and Abundance of Parthenium Weed
3.3. Maxent Model Validation
3.4. Variable Importance
3.5. Potential Habitat Suitability of Parthenium Weed under Current Climatic Conditions
3.6. Distribution of Suitable Habitats of Parthenium Weed under Future Climate Change Scenarios
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Districts | Upazila | Distribution of Parthenium Weed | ||||
---|---|---|---|---|---|---|
Sporadic | Low | Medium | High | Very High | ||
Jashore | Sarsha | ■ | ||||
Jikargacha | ■ | |||||
Chougacha | ■ | |||||
Sadar | ■ | |||||
Keshabpur | ■ | |||||
Manirampur | ■ | |||||
Abhaynagar | ■ | |||||
Bagherpara | ■ | |||||
Jhenaidah | Sadar | ■ | ||||
Maheshpur | ■ | |||||
Kaliganj | ■ | |||||
Kotchandpur | ■ | |||||
Shailkupa | ■ | |||||
Harinakunda | ■ | |||||
Chuadanga | Alamdanga | ■ | ||||
Sadar | ■ | |||||
Damurhuda | ■ | |||||
Jibannagar | ■ | |||||
Meherpur | Gangni | ■ | ||||
Sadar | ■ | |||||
Mujibnagar | ■ | |||||
Khustia | Bheramara | ■ | ||||
Daulatpur | ■ | |||||
Khoksa | ■ | |||||
Kumarkhali | ■ | |||||
Sadar | ■ | |||||
Mirpur | ■ |
References
- Adkins, S.; Shabbir, A. Biology, Ecology and Management of the Invasive Parthenium Weed (Parthenium hysterophorus L.). Pest Manag. Sci. 2014, 70, 1023–1029. [Google Scholar] [CrossRef] [PubMed]
- Masum, S.M.; Hasanuzzaman, M.; Ali, M.H. Threats of Parthenium hysterophorus on Agro-Ecosystems and Its Management: A Review. Int. J. Agric. Crop Sci. 2013, 6, 684. [Google Scholar]
- Mao, R.; Shabbir, A.; Adkins, S. Parthenium hysterophorus: A Tale of Global Invasion over Two Centuries, Spread and Prevention Measures. J. Environ. Manag. 2021, 279, 111751. [Google Scholar] [CrossRef]
- Kohli, R.K.; Batish, D.R.; Singh, H.P.; Dogra, K.S. Status, Invasiveness and Environmental Threats of Three Tropical American Invasive Weeds (Parthenium hysterophorus L., Ageratum conyzoides L., Lantana camara L.) in India. Biol. Invasions 2006, 8, 1501–1510. [Google Scholar] [CrossRef]
- Kumar, S. Current Spread, Impact and Management of Parthenium Weed in India. Int. Parthenium News 2012, 5. [Google Scholar]
- Annapurna, C.; Singh, J.S. Variation of Parthenium hysterophorus in Response to Soil Quality: Implications for Invasiveness. Weed Res. 2003, 43, 190–198. [Google Scholar] [CrossRef]
- Tefera, T. Allelopathic Effects of Parthenium hysterophorus Extracts on Seed Germination and Seedling Growth of Eragrostis Tef. J. Agron. Crop Sci. 2002, 188, 306–310. [Google Scholar] [CrossRef]
- Wiesner, M.; Tessema, T.; Hoffmann, A.; Wilfried, P.; Büttner, C.; Mewis, I.; Ulrichs, C. Impact of the Pan-Tropical Weed Parthenium hysterophorus L. on Human Health in Ethiopia; Institute of Horticultural Science, Urban Horticulture: Berlin, Germany, 2007. [Google Scholar]
- Lakshmi, C.; Srinivas, C.R. Seminar-Parthenium: A Wide Angle View. Indian J. Dermatol. Venereol. Leprol. 2007, 73, 296–306. [Google Scholar] [PubMed]
- Islam, A. Nitrogen Exploitation Capacity of Parthenium Weed and Its Inhibitory Effects on Growth and Development of Rice. M.S. Thesis, Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh, 2010. [Google Scholar]
- Adkins, S.W.; Sowerby, M.S. Allelopathic Potential of the Weed, Parthenium hysterophorus L., in Australia. Plant Prot. Q. 1996, 11, 20–23. [Google Scholar]
- Bajwa, A.A.; Chauhan, B.S.; Farooq, M.; Shabbir, A.; Adkins, S.W. What Do We Really Know about Alien Plant Invasion? A Review of the Invasion Mechanism of One of the World’s Worst Weeds. Planta 2016, 244, 39–57. [Google Scholar] [CrossRef]
- Oudhia, P. Medicinal Herbs and Insects of Chhattisgarh India. Insect Environ. 2000, 6, 138. [Google Scholar]
- Gnanavel, I. Parthenium hysterophorus L.: A Major Threat to Natural and Agro Eco-Systems in India. Sci. Int. 2013, 1, 124–131. [Google Scholar] [CrossRef] [Green Version]
- Navie, S.C.; McFadyen, R.E.; Panetta, F.D.; Adkins, S.W. The Effect of CO2 Enrichment on the Growth of a C3 Weed (Parthenium hysterophorus L.) and Its Competitive Interaction with a C4 Grass (Cenchrus ciliaris L.). Plant Prot. Q. 2005, 20, 61–66. [Google Scholar]
- Bradley, B.A.; Blumenthal, D.M.; Wilcove, D.S.; Ziska, L.H. Predicting Plant Invasions in an Era of Global Change. Trends Ecol. Evol. 2010, 25, 310–318. [Google Scholar] [CrossRef]
- Maszura, C.M.; Karim, S.M.R.; Norhafizah, M.Z.; Kayat, F.; Arifullah, M. Distribution, Density, and Abundance of Parthenium Weed (Parthenium hysterophorus L.) at Kuala Muda, Malaysia. Int. J. Agron. 2018, 2018, 1046214. [Google Scholar] [CrossRef] [Green Version]
- Elith, J.; Phillips, S.J.; Hastie, T.; Dudík, M.; Chee, Y.E.; Yates, C.J. A Statistical Explanation of MaxEnt for Ecologists. Divers. Distrib. 2011, 17, 43–57. [Google Scholar] [CrossRef]
- Phillips, S.J.; Dudik, M. Modeling of Species Distributions with Maxent: New Extensions and a Comprehensive Evaluation. Ecography 2008, 31, 161–175. [Google Scholar] [CrossRef]
- Abdelaal, M.; Fois, M.; Fenu, G.; Bacchetta, G. Using MaxEnt Modeling to Predict the Potential Distribution of the Endemic Plant Rosa Arabica Crép. in Egypt. Ecol. Inform. 2019, 50, 68–75. [Google Scholar] [CrossRef]
- Chhogyel, N.; Kumar, L.; Bajgai, Y. Invasion Status and Impacts of Parthenium Weed (Parthenium hysterophorus) in West-Central Region of Bhutan. Biol. Invasions 2021, 23, 2763–2779. [Google Scholar] [CrossRef]
- Fareen, A.G.E.; Mahmood, T.; Bodlah, I.; Rashid, A.; Khalid, A.; Mahmood, S. Modeling Potential Distribution of Newly Recorded Ant, Brachyponera Nigrita Using Maxent under Climate Change in Pothwar Region, Pakistan. PLoS ONE 2022, 17, e0262451. [Google Scholar]
- McConnachie, A.J.; Strathie, L.W.; Mersie, W.; Gebrehiwot, L.; Zewdie, K.; Abdurehim, A.; Abrha, B.; Araya, T.; Asaregew, F.; Assefa, F.; et al. Current and Potential Geographical Distribution of the Invasive Plant Parthenium hysterophorus (Asteraceae) in Eastern and Southern Africa. Weed Res. 2011, 51, 71–84. [Google Scholar] [CrossRef]
- Zhou, Y.; Zhang, Z.; Zhu, B.; Cheng, X.; Yang, L.; Gao, M.; Kong, R. Maxent Modeling Based on CMIP6 Models to Project Potential Suitable Zones for Cunninghamia Lanceolata in China. Forests 2021, 12, 752. [Google Scholar] [CrossRef]
- Merow, C.; Silander, J.A., Jr. A Comparison of Maxlike and Maxent for Modelling Species Distributions. Methods Ecol. Evol. 2014, 5, 215–225. [Google Scholar] [CrossRef]
- Phillips, S.J.; Anderson, R.P.; Dudik, M.; Schapire, R.E.; Blair, M.E. Opening the Black Box: An Open-Source Release of Maxent. Ecography 2017, 40, 887–893. [Google Scholar] [CrossRef]
- Rahman, M.; Lateh, H. Climate Change in Bangladesh: A Spatio-Temporal Analysis and Simulation of Recent Temperature and Rainfall Data Using GIS and Time Series Analysis Model. Theor. Appl. Climatol. 2017, 128, 27–41. [Google Scholar] [CrossRef]
- Akter, A.; Zuberi, M.I. Invasive Alien Species in Northern Bangladesh: Identification, Inventory and Impacts. Int. J. Biodivers. Conserv. 2009, 1, 129–134. [Google Scholar]
- Karim, S.M.R. Parthenium Agacha: Bangladesher Janno Maraktok Humki (Parthenium Weed: A Dangerous Threat for Bangladesh). Krishi Projukti Barta 2009, 3, 21–23. [Google Scholar]
- Adkins, S.; Parthenium Weed Poses Danger to Crops. Dhaka Mirror 2009. Available online: https://www.dhakamirror.com/environment/parthenium-weed-poses-danger-to-crops/#more-10210 (accessed on 1 December 2021).
- Karim, S.M.R.; Forzwa, R. Allelopathic effects of parthenium weed on the seed germination and seedling growth of field crops. In Proceedings of the Abstracts, Annual Botanical Conference 2009, Chattogram, Bangladesh, 9–10 January 2010; pp. 38–39. [Google Scholar]
- Khan, H.; Marwat, K.B.; Hassan, G.; Khan, M.A.; Hashim, S. Distribution of Parthenium Weed in Peshawar Valley, Khyber Pakhtunkhwa-Pakistan. Pak. J. Bot. 2014, 46, 81–90. [Google Scholar]
- Mahajan, M.; Fatima, S. Frequency, Abundance, and Density of Plant Species by List Count Quadrat Method. Int. J. Multidiscip. Res. 2017, 3, 1–8. [Google Scholar]
- Knox, J.; Jaggi, D.; Paul, M.S. Population Dynamics of Parthenium hysterophorus (Asteraceae) and Its Biological Suppression through Cassia Occidentalis (Caesalpiniaceae). Turk. J. Bot. 2011, 35, 111–119. [Google Scholar] [CrossRef]
- Nkoa, R.; Owen, M.D.K.; Swanton, C.J. Weed Abundance, Distribution, Diversity, and Community Analyses. Weed Sci. 2015, 63, 64–90. [Google Scholar] [CrossRef] [Green Version]
- Fick, S.E.; Hijmans, R.J. WorldClim 2: New 1-Km Spatial Resolution Climate Surfaces for Global Land Areas. Int. J. Climatol. 2017, 37, 4302–4315. [Google Scholar] [CrossRef]
- IPCC. IPCC Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Core Writing Team, Pachauri, R.K., Meyer, L.A., Eds.; IPCC: Geneva, Switzerland, 2014; p. 151. [Google Scholar]
- Rodríguez-Medina, K.; Yañez-Arenas, C.; Peterson, A.T.; Ávila, J.E.; Herrera-Silveira, J. Evaluating the Capacity of Species Distribution Modeling to Predict the Geographic Distribution of the Mangrove Community in Mexico. PLoS ONE 2020, 15, e0237701. [Google Scholar] [CrossRef] [PubMed]
- Uzma, A.; Peterson, A.T.; Chaudhry, M.N.; Irfan, A.; Zafeer, S.; Ahmad, S.R.; Hassan, A. Ecological Niche Model Comparison under Different Climate Scenarios: A Case Study of Olea spp. in Asia. Ecosphere 2017, 8, e01825. [Google Scholar]
- Naimi, B.; Hamm, N.A.S.; Groen, T.A.; Skidmore, A.K.; Toxopeus, A.G. Where Is Positional Uncertainty a Problem for Species Distribution Modelling? Ecography 2014, 37, 191–203. [Google Scholar] [CrossRef]
- R Foundation for Statistical Computing. R Core Team R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022. [Google Scholar]
- Kass, J.M.; Muscarella, R.; Galante, P.J.; Bohl, C.L.; Pinilla-Buitrago, G.E.; Boria, R.A.; Soley-Guardia, M.; Anderson, R.P. ENMeval 2.0: Redesigned for Customizable and Reproducible Modeling of Species’ Niches and Distributions. Methods Ecol. Evol. 2021, 12, 1602–1608. [Google Scholar] [CrossRef]
- Kass, J.M.; Anderson, R.P.; Espinosa-Lucas, A.; Juárez-Jaimes, V.; Martínez-Salas, E.; Botello, F.; Tavera, G.; Flores-Martínez, J.J.; Sánchez-Cordero, V. Biotic Predictors with Phenological Information Improve Range Estimates for Migrating Monarch Butterflies in Mexico. Ecography 2020, 43, 341–352. [Google Scholar] [CrossRef] [Green Version]
- Radosavljevic, A.; Anderson, R.P. Making Better Maxent Models of Species Distributions: Complexity, Overfitting and Evaluation. J. Biogeogr. 2014, 41, 629–643. [Google Scholar] [CrossRef]
- Ahmed, N. Wild Flowers of Bangladesh; The University Press Limited (UPL): Dhaka, Bangladesh, 1997. [Google Scholar]
- McFadyen, C.R. Biological Control against Parthenium Weed in Australia. Crop Prot. 1992, 11, 400–407. [Google Scholar] [CrossRef]
- Phillips, S.J.; Anderson, R.P.; Schapire, R.E. Maximum Entropy Modeling of Species Geographic Distributions. Ecol. Model. 2006, 190, 231–259. [Google Scholar] [CrossRef] [Green Version]
- Merow, C.; Smith, M.J.; Silander, J.A., Jr. A Practical Guide to MaxEnt for Modeling Species’ Distributions: What It Does, and Why Inputs and Settings Matter. Ecography 2013, 36, 1058–1069. [Google Scholar] [CrossRef]
- Purohit, S.; Rawat, N. MaxEnt Modeling to Predict the Current and Future Distribution of Clerodendrum Infortunatum L. under Climate Change Scenarios in Dehradun District, India. Modeling Earth Syst. Environ. 2021, 8, 2051–2063. [Google Scholar] [CrossRef]
- Thiney, U.; Banterng, P.; Gonkhamdee, S.; Katawatin, R. Distributions of Alien Invasive Weeds under Climate Change Scenarios in Mountainous Bhutan. Agronomy 2019, 9, 442. [Google Scholar] [CrossRef] [Green Version]
SL | Code | Name | Unit | Source |
---|---|---|---|---|
1 | Bio1 | Annual mean temperature | °C | WorldClim |
2 | Bio2 | Mean diurnal range (Mean of monthly (max temp–in temp)) | °C | |
3 | Bio3 | Isothermality (Bio2/Bio7) (×100) | ||
4 | Bio4 | Temperature seasonality (Standard deviation × 100) | °C | |
5 | Bio5 | Max temperature of warmest month | °C | |
6 | Bio6 | Min temperature of coldest month | °C | |
7 | Bio7 | Temperature annual range (Bio5–Bio6) | °C | |
8 | Bio8 | Mean temperature of wettest quarter | °C | |
9 | Bio9 | Mean temperature of driest quarter | °C | |
10 | Bio10 | Mean temperature of warmest quarter | °C | |
11 | Bio11 | Mean temperature of coldest quarter | °C | |
12 | Bio12 | Annual precipitation | mm | |
13 | Bio13 | Precipitation of wettest month | mm | |
14 | Bio14 | Precipitation of driest month | mm | |
15 | Bio15 | Precipitation seasonality (Coefficient of variation) | 1 | |
16 | Bio16 | Precipitation of wettest quarter | mm | |
17 | Bio17 | Precipitation of driest quarter | mm | |
18 | Bio18 | Precipitation of warmest quarter | mm | |
19 | Bio19 | Precipitation of coldest quarter | mm | |
20 | ALT | Elevation | m | |
21 | SLO | Slope | % | Derived from ALT |
22 | ASP | Aspect | ° |
No | Upazila | District | OS | AS | QP | F | A | R | SC |
---|---|---|---|---|---|---|---|---|---|
1 | Sarsha | Jashore | 75.9 | 94.7 | 8 | 0.8 | 29.7 | 33.51 | H |
2 | Jhikargacha | 60.2 | 62.5 | 8 | 0.8 | 25.4 | 28.68 | H | |
3 | Chougacha | 61.4 | 67.4 | 8 | 0.8 | 20.0 | 23.74 | H | |
4 | Sadar | 54.3 | 67.7 | 7 | 0.7 | 19.1 | 27.79 | H | |
5 | Keshabpur | 59.6 | 64.9 | 6 | 0.6 | 8.8 | 18.17 | M | |
6 | Manirampur | 41.5 | 42.7 | 3 | 0.3 | 4.0 | 2.81 | L | |
7 | Abhaynagar | 65.5 | 67.0 | 3 | 0.3 | 5.0 | 2.24 | L | |
8 | Bagherpara | 53.0 | 60.9 | 7 | 0.7 | 11.3 | 12.97 | M | |
9 | Sadar | Jhenaidah | 50.3 | 65.4 | 8 | 0.8 | 18.9 | 27.09 | H |
10 | Maheshpur | 56.6 | 77.8 | 8 | 0.8 | 26.5 | 27.25 | H | |
11 | Kaliganj | 44.9 | 47.5 | 4 | 0.4 | 6.5 | 5.47 | M | |
12 | Kotchandpur | 63 | 67.2 | 4 | 0.4 | 10.5 | 6.25 | M | |
13 | Shailkupa | 41.5 | 42.7 | 3 | 0.3 | 4.0 | 2.81 | L | |
14 | Harinakunda | 51.8 | 56.2 | 5 | 0.5 | 8.8 | 7.83 | M | |
15 | Alamdanga | Chuadanga | 65.5 | 67.0 | 3 | 0.3 | 5.0 | 2.24 | L |
16 | Sadar | 55.6 | 61.6 | 7 | 0.7 | 8.6 | 9.74 | M | |
17 | Damurhuda | 53.8 | 67.4 | 7 | 0.7 | 19.4 | 29.82 | H | |
18 | Jibannagar | 39.8 | 49.8 | 5 | 0.5 | 20.0 | 28.08 | H | |
19 | Gangni | Meherpur | 83.1 | 83.5 | 3 | 0.3 | 1.3 | 0.48 | T |
20 | Sadar | 41.5 | 53.2 | 7 | 0.7 | 16.7 | 26.99 | H | |
21 | Mujibnagar | 46.4 | 60 | 8 | 0.8 | 17.0 | 27.67 | H | |
22 | Bheramara | Khustia | 49.2 | 64 | 7 | 0.7 | 21.1 | 25.13 | H |
23 | Daulatpur | 65.5 | 67.0 | 3 | 0.3 | 5.0 | 2.24 | L | |
24 | Khoksa | 49.2 | 64 | 7 | 0.7 | 21.1 | 25.13 | H | |
25 | Kumarkhali | 49.7 | 55.4 | 5 | 0.5 | 11.4 | 10.29 | M | |
26 | Sadar | 39 | 41.2 | 4 | 0.4 | 5.5 | 5.34 | M | |
27 | Mirpur | 65.5 | 67.0 | 3 | 0.3 | 5.0 | 0.24 | T |
RM | Feature Combinations | AUC Train | CBI Train | OR.10p | AICc | ∆AICc | Number of Coefficients |
---|---|---|---|---|---|---|---|
3 | LQHP | 0.90 | 0.95 | 0.11 | 821.38 | 14.88 | 11 |
Variable | VIF | PC | PI |
---|---|---|---|
Temperature seasonality (Bio15) | 3.60 | 54.4 | 41.4 |
Annual mean temperature (Bio1) | 8.84 | 13.9 | 19.4 |
Precipitation of driest month (Bio14) | 7.22 | 11.3 | 18.1 |
Precipitation of wettest quarter (Bio16) | 4.17 | 10.5 | 0.1 |
Temperature annual range (Bio7) | 3.80 | 2.8 | 2.9 |
Min temperature of coldest month (Bio6) | 7.48 | 2.2 | 4 |
Elevation (ALT) | 3.61 | 2 | 9.9 |
Aspect (ASP) | 1.00 | 1.4 | 1.5 |
Slope (SLP) | 1.03 | 0.8 | 1.3 |
Precipitation of driest quarter (Bio17) | 5.34 | 0.6 | 1 |
Mean temperature of warmest quarter (Bio10) | 2.08 | 0.2 | 0.3 |
Class | Probability Class | Current | HE2.6 | HE8.5 | MI2.6 | MI8.5 |
---|---|---|---|---|---|---|
Unsuitable | 0.0–0.10 | 455.82 | 665.30 | 786.90 | 366.38 | 473.87 |
(+209.47) | (+331.08) | (−89.44) | (+18.04) | |||
Low | 0.11–0.30 | 1409.05 | 1424.74 | 863.00 | 808.09 | 1412.19 |
(+15.69) | (−546.05) | (−600.97) | (+3.14) | |||
Medium | 0.31–0.70 | 5278.45 | 4982.68 | 5462.04 | 5893.54 | 5345.92 |
(−295.78) | (+183.58) | (+615.09) | (+67.47) | |||
High | 0.71–1.0 | 809.66 | 877.13 | 837.90 | 881.83 | 717.86 |
(+67.47) | (+28.24) | (+72.18) | (−91.79) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Masum, S.M.; Halim, A.; Mandal, M.S.H.; Asaduzzaman, M.; Adkins, S. Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling. Agronomy 2022, 12, 1592. https://doi.org/10.3390/agronomy12071592
Masum SM, Halim A, Mandal MSH, Asaduzzaman M, Adkins S. Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling. Agronomy. 2022; 12(7):1592. https://doi.org/10.3390/agronomy12071592
Chicago/Turabian StyleMasum, Sheikh Muhammad, Abdul Halim, Mohammad Shamim Hasan Mandal, Md Asaduzzaman, and Steve Adkins. 2022. "Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling" Agronomy 12, no. 7: 1592. https://doi.org/10.3390/agronomy12071592