Please wait a minute...
Journal of Integrative Agriculture  2012, Vol. 12 Issue (4): 593-599    DOI: 10.1016/S1671-2927(00)8579
PHYSIOLOGY & BIOCHEMISTRY · TILLAGE · CULTIVATION Advanced Online Publication | Current Issue | Archive | Adv Search |
Modeling the Potential Geographic Distribution of Black Pepper (Piper nigrum) in Asia Using GIS Tools
 HAO Chao-yun, FAN Rui, Milton Cezar Ribeiro, TAN Le-he, WU Hua-song, YANG Jian-feng, ZHENG Wei-quan , YU Huan
1.Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences/Key Laboratory of Genetic Resources Utilization of Spice and Beverage Crops, Ministry of Agriculture/Hainan Provincial Key Laboratory of Genetic Improvement and Quality Regulation for Tropical Spice and Beverage Crops, Wanning 571533, P.R.China
2.Ecological Departament, University of Sao Paulo, Sao Paulo 05513-970, S.P.Brazil
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  Known as the “king of spices”, black pepper (Piper nigrum), a perennial crop of the tropics, is economically the most important and the most widely used spice crop in the world. To understand its suitable bioclimatic distribution, maximum entropy based on ecological niche modeling was used to model the bioclimatic niches of the species in its Asian range. Based on known occurrences, bioclimatic areas with higher probabilities are mainly located in the eastern and western coasts of the Indian Peninsula, the east of Sumatra Island, some areas in the Malay Archipelago, and the southeast coastal areas of China. Some undocumented places were also predicted as suitable areas. According to the jackknife procedure, the minimum temperature of the coldest month, the mean monthly temperature range, and the precipitation of the wettest month were identified as highly effective factors in the distribution of black pepper and could possibly account for the crop’s distribution pattern. Such climatic requirements inhibited this species from dispersing and gaining a larger geographical range.

Abstract  Known as the “king of spices”, black pepper (Piper nigrum), a perennial crop of the tropics, is economically the most important and the most widely used spice crop in the world. To understand its suitable bioclimatic distribution, maximum entropy based on ecological niche modeling was used to model the bioclimatic niches of the species in its Asian range. Based on known occurrences, bioclimatic areas with higher probabilities are mainly located in the eastern and western coasts of the Indian Peninsula, the east of Sumatra Island, some areas in the Malay Archipelago, and the southeast coastal areas of China. Some undocumented places were also predicted as suitable areas. According to the jackknife procedure, the minimum temperature of the coldest month, the mean monthly temperature range, and the precipitation of the wettest month were identified as highly effective factors in the distribution of black pepper and could possibly account for the crop’s distribution pattern. Such climatic requirements inhibited this species from dispersing and gaining a larger geographical range.
Keywords:  Piper ngirum      ENM      bioclimatic distribution      Maxent  
Received: 26 January 2011   Accepted:
Fund: 

This research was founded by Chinese Special Scientific Research Fund for Public Welfare Industry (Agriculture, 200903024) and the Natural Science Foundation of Hainan Province, China (310071).

Corresponding Authors:  Correspondence WU Hua-song, Tel: +86-898-62556925, E-mail: 13807622912@163.com     E-mail:  13807622912@163.com

Cite this article: 

HAO Chao-yun, FAN Rui, Milton Cezar Ribeiro, TAN Le-he, WU Hua-song, YANG Jian-feng, ZHENG Wei-quan , YU Huan . 2012. Modeling the Potential Geographic Distribution of Black Pepper (Piper nigrum) in Asia Using GIS Tools. Journal of Integrative Agriculture, 12(4): 593-599.

[1]Anderson R P, Lew D, Peterson A T. 2003. Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecological Modelling, 162, 211-232.

[2]Anderson R P, Martínez-Meyer E. 2004. Modeling species’ geographic distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador. Biological Conservation, 116, 167-179.

[3]Elith J, Graham H C, Anderson P R, Dudik M, Ferrier S, Guisan A, Hijmans J R, Huettmann F, Leathwick R, Lehmann A, et al. 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129-151.

[4]Fielding A H, Bell J F. 1997. A review of methods for the assessment of prediction errors in conservation p r e s e n c e / a b s e n c e m o d e l s . E n v i r o n m e n t a l Conservation, 24, 38-49.

[5]Food and Agriculture Organization of the United Nations. 2009. FAOSTAT. [2011-1-10]. http://faostat.fao.org/site/ 567/default.aspx# ancor

[6]Giovanelli J G R, Haddad C B F, Alexandrino J. 2008. Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil. Biological Invasions, 10, 585-590.

[7]Graham C H, Hijmans R J. 2006. A comparison of methods for mapping species ranges and species richness. Global Ecology and Biogeography, 15, 578-587.

[8]Grinnell J. 1917. The niche-relationships of the California thrasher. The Auk, 34, 427-433.

[9]Guisan A, Thuiller W. 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8, 993-1009.

[10]Hijmans R J, Cameron S E, Parra J L, Jones P G, Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978.

[11]Howard R A. 1973. Notes on the piperaceae of lesser antilles. Journal of the Arnold Arboretum, 54, 377-411.

[12]Hutchinson G E. 1957. Concluding remarks. Coldspring Harbor Symposia Quantitative Biology, 22, 415-427.

[13]Indian Institute of Spices Research. 2008. Black pepper (Extension Pamphlet). Niseema Printers and Publishers, Kochi. pp. 1-3.

[14]James F C, Mc Culloch C E. 2002. Predicting species presence and abundance. In: Scott J M, Heglund P J, Morrison M L, Haufler J B, Raphael M G, Wall W A, Samson F B, eds., Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Washington, D.C. pp. 461-465.

[15]Krishtalka L, Humphrey P S. 2000. Can natural history museums capture the future? Bioscience, 50, 611-617.

[16]Li Z G, Liu A Q, Wu H S, Tan L H, Long Y Z, Gou Y F, Sun S W, Sang L W. 2010. Influence of temperature, light and plant growth regulators on germination of black pepper (Piper nigrum L.) seeds. African Journal of Biotechnology, 9, 1345-1358.

[17]Mathew P J, Mathew P M, Kumar V. 2006. Multivariate analysis in fifty cultivars/landraces of ‘black pepper’ (Piper nigrum L.) occurring in Kerala, India. Revista Brasileira de Plantas Medicinais, 8, 180-185.

[18]Nair R R, Gupta S D. 2003. Somatic embryogenesis and plant regeneration in black pepper (Piper nigrum L.). The Journal of Horticultural Science and Biotechnology, 78, 416-421.

[19]Navickene H M D, Alecio A C, Kato M J, Bolzani V S, Young M C M, Cavalheiro A J, Furlan M. 2000. Antifungal amides from Piper hispidum and Piper tuberculatum. Phytochemistry, 55, 621-626.

[20]Parthasarathy U, Saji K V, Jayarajan K, Parthasarathy V A. 2006. Biodiversity of piper in south India-application of GIS and cluster analysis. Current Science, 91, 652-658.

[21]Peterson A T. 2003. Predicting the geography of species’ invasions via ecological niche modeling. Quarterly Review Biology, 78, 419-433.

[22]Peterson A T, Papes M, Eaton M. 2007. Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent. Ecography, 30, 550-560.

[23]Peterson T A, Papes M, Soberón J. 2008. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecological Modelling, 213, 63-72.

[24]Phillips S J. 2008. Transferability, sample selection bias and background data in presence-only modeling: a response to Peterson et al. (2007). Ecography, 31, 272-278.

[25]Phillips S J, Anderson R P, Schapire R E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-259.

[26]Ravindran P N. 2000. Black pepper: Piper nigrum. Harwood academic publishers, New Jersey. pp. 1-10.

[27]Ravindran P N, Nirmal Babu K. 1994. Genetic resources of black pepper. In: Chadha K L, Rethinum P, eds., Advances in Horticulture. vol. 9. Malhotra Publishing House, New Delhi. pp. 99-120.

[28]Scott I M, Jensen H R, Philogene B J R, Arnason J T. 2008. A review of Piper spp. (Piperaceae) phytochemistry, insecticidal activity and mode of action. Phytochemistry Reviews, 7, 65-75.

[29]Soberón J, Peterson A T. 2005. Interpretation of models of fundamental ecological niches and species distributional areas. Biodiversity Informatics, 2, 1-10.

[30]Solano E, Feria T P. 2007. Ecological niche modeling and geographic distribution of the genus Polianthes L. (Agavaceae) in Mexico: using niche modeling to improve assessments of risk status. Biodiversity and Conservation, 16, 1885-1900.

[31]Srinivasan K. 2007. Black pepper and its pungent principlepiperine: A review of diverse physiological effects. Critical Reviews in Food Science and Nutrition, 47, 735-748.

[32]Stockwell D R B, Peterson A T. 2002. Effects of sample size on accuracy of species distribution models. Ecological Modelling, 148, 1-13.

[33]Thorn J S, Nijman V, Smith D, Nekaris K A I. 2009. Ecological niche modeling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions, 15, 289-298.

[34]Umit A, Ilhan Kadir, Akgun K O. 2009. Antifungal activity of aqueous extracts of spices against bean rust (Uromyces appendiculatus). Allelopathy Journal, 24, 973-1046.

[35]Wang Y S, Xie B Y, Wan F H, Xiao Q M, Dai L Y. 2007. Potential geographic distribution of Radopholus similis in China. Scientia Agricultura Sinica, 40, 2502-2506. (in Chinese)
[1] XIAN Xiao-qing, ZHAO Hao-xiang, GUO Jian-yang, ZHANG Gui-fen, LIU Hui, LIU Wan-xue, WAN Fang-hao. Estimation of the potential geographical distribution of a new potato pest (Schrankia costaestrigalis) in China under climate change[J]. >Journal of Integrative Agriculture, 2023, 22(8): 2441-2455.
[2] PAN Song, PENG De-liang, LI Ying-mei, CHEN Zhi-jie, ZHAI Ying-yan, LIU Chen, HONG Bo. Potential global distribution of the guava root-knot nematode Meloidogyne enterolobii under different climate change scenarios using MaxEnt ecological niche modeling[J]. >Journal of Integrative Agriculture, 2023, 22(7): 2138-2150.
[3] Jing Wan, QI Guo-jun, MA Jun, Yonglin Ren, WANG Rui, Simon MCKIRDY.
Predicting the potential geographic distribution of Bactrocera bryoniae and Bactrocera neohumeralis (Diptera: Tephritidae) in China using MaxEnt ecological niche modeling
[J]. >Journal of Integrative Agriculture, 2020, 19(8): 2072-2082.
[4] CUI Bei, ZHAO Qian-jun, HUANG Wen-jiang, SONG Xiao-yu, YE Hui-chun, ZHOU Xian-feng. Leaf chlorophyll content retrieval of wheat by simulated RapidEye, Sentinel-2 and EnMAP data[J]. >Journal of Integrative Agriculture, 2019, 18(6): 1230-1245.
[5] LIU Zhao-fei, YAO Zhi-jun, YU Cheng-qun , ZHONG Zhi-ming. Assessing Crop Water Demand and Deficit for the Growth of Spring Highland Barley in Tibet, China[J]. >Journal of Integrative Agriculture, 2013, 12(3): 541-551.
No Suggested Reading articles found!