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Optimized hot spot analysis for probability of species distribution under different spatial scales based on MaxEnt model: Manglietia insignis case

ZHUANG Hongfei1,2 ZHANG Yinbo3 WANG Wei1,4 REN Yueheng1 LIU Fangzheng1 DU Jinhong1 ZHOU Yue1

(1.State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012)
(2.Institute of Loess Plateau, Shanxi University, Taiyuan 030006)
(3.School of Environmental and Resource Sciences, Shanxi University, Taiyuan 030006)
(4.Collaborative Innovation Center for Biodiversity and Conservation in the Three Parallel Rivers Region of China, Dali, Yunnan 671003)

【Abstract】Whether a maximum entropy (MaxEnt) model constructed at one spatial scale is representative of species distributions at other scales is an important issue in the application and development of these models. Using distribution data for Manglietia insignis, we used the minimum convex polygon (MCP) method to model species distribution for three spatial scales—Three Parallel Rivers, Yunnan Province and China—with a 20 km buffer outside the distribution region. We built the MaxEnt model for Three Parallel Rivers, Yunnan Province and China using 19, 67, and 88 presence-only records respectively and combined these with data on environmental factors at the point locations. We estimated the prediction accuracy of the MaxEnt model using receiver operating characteristic (ROC) curve and omission rate (OR). Next, we used ArcGIS to analyze distribution trends for habitat suitability and potential hotspots. We identified the location of geometric centroid of potentially suitable areas using Zonal and used the Jackknife method to test the dominant environmental factors affecting the distribution of M. insignis. We found that the areas under ROC curve (AUC value) for Three Parallel Rivers, Yunnan Province and China were 0.936, 0.887, and 0.930 respectively and the OR values were 0.18, 0.15, and 0.20, indicating that Max Ent model for all three spatial scales could successfully predict the distribution of M. insignis. The distribution trends of potential habitat suitability and habitat hotspots were consistent between different scales and were concentrated in the river basins of Dulong River, Nujiang River and Lancang River, with no significant zonal transfer for the location of geometric centroid. Different environmental factors affected the geographical distribution of M. insignis at the three spatial scales, suggesting scale dependence in the distribution patterns of M. insignis. In summary, this study indicates that the MaxEnt model of M. insignis performs stably and successfully for different spatial scales. In addition, the consistency of results across spatial scales became more obvious for hotspots, indicating that the hotspot analysis greatly reduced the effect of spatial scale for the MaxEnt model. Thus, we propose integrating MaxEnt model and hotspot analysis to simulate the geographical distributions of species.

【Keywords】 MaxEnt model; spatial scale; Manglietia insignis; minimum convex polygon; hotspots; common species;


【Funds】 National Key Research and Development Plan (2016YFC0503304)

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    [1]. (1) Shang Zhonghui (2016) Prediction uncertainty analysis based on Maxent’s spatial distribution? Angelica is taken as an example. Master’s thesis, Shaanxi Normal University, Xi’an. [^Back]


    Ahmed SE, McInerny G, O’Hara K, Harper R, Salido L, Emmott S, Joppa LN (2015) Scientists and software-surveying the species distribution modelling community. Diversity and Distributions, 21, 258–267.

    Barbosa FG, Schneck F (2015) Characteristics of the top-cited papers in species distribution predictive models. Ecological Modelling, 313, 77–83.

    Catherineh G, Jane E, Robertj H, Antoine G, Townsend PA, Bettea L (2008) The influence of spatial errors in species occurrence data used in distribution models. Journal of Applied Ecology, 45, 239–247.

    Chai Y, Zhu H, Meng GT, Shi JP, Yang GB (2011) Population structure and distribution pattern of dominant tree species in ancient tea tree community in Ailao Mountains of Yunnan Province, China. Forest Research, 24, 277–284 (in Chinese with English abstract).

    Chen F, Wang JM, Sun BG, Chen XM, Yang ZX, Duan ZY (2012) Relationships of plant species distribution in different strata of Pinus yunnanensis forest with landform and climatic factors. Chinese Journal of Ecology, 31, 1070–1076 (in Chinese with English abstract).

    Chen XM, Lei YC, Zhang XQ, Jia HY (2012) Effects of sample sizes on accuracy and stability of maximum entropy model in predicting species distribution. Scientia Silvae Sinicae, 48 (1), 53–59 (in Chinese with English abstract).

    Dong XF (2017) Effect of topographic factors on the distribution of Manglietia insignis. Journal of Anhui Agricultural Sciences, 45 (10), 162–163 (in Chinese with English abstract).

    Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17, 43–57.

    Escalante T, Rodríguez-Tapia G, Linaje M, Illoldi-Rangel P, González-López R (2013) Identification of areas of endemism from species distribution models: Threshold selection and Nearctic mammals. Transaction Image Processing, 16, 5–17.

    Getis A, Ord JK (1992) The analysis of spatial association by use of distance statistics. Geographical Analysis, 24, 189–206.

    Hu X, Wu FC, Guo W, Liu N (2014) Identification of potential cultivation region for Santalum album in China by the MaxEnt ecologic niche model. Scientia Silvae Sinicae, 50 (5), 27–33 (in Chinese with English abstract).

    Jiang ZG (1996) Hoarding behavior of animal and its ecological functions. Chinese Journal of Zoology, (3), 47–49 (in Chinese).

    Kunming Institute of Botany, Chinese Academy of Sciences (2006) Flora of Yunnan. Science Press, Beijing (in Chinese).

    Levin SA (1992) The problem of pattern and scale in ecology: The Robert H. MacArthur Award lecture. Ecology, 73, 1943–1967.

    Li HJ, Zhang ZB (2001) Relationship between animals and plant regeneration by seed. II. Seed predation, dispersal and burial by animals and relationship between animals and seedling establishment. Biodiversity Science, 9, 25–37 (in Chinese with English abstract).

    Lin YP, Deng D, Lin WC, Lemmens R, Crossman ND, Henle K, Schmeller DS (2015) Uncertainty analysis of crowd-sourced and professionally collected field data used in species distribution models of Taiwanese moths. Biological Conservation, 181, 102–110.

    Manhães AP, Loyola R, Mazzochini GG, Ganade G, Oliveira-Filho AT, Carvalho AR (2018) Low-cost strategies for protecting ecosystem services and biodiversity. Biological Conservation, 217, 187–194.

    Morales NS, Fernández IC, Bacagonzález V (2017) MaxEnt’s parameter configuration and small samples: Are we paying attention to recommendations? A systematic review. PeerJ, 5, e3093.

    Myers N (1990) The biodiversity challenge: Expanded hot-spots analysis. Environmentalist, 10, 243–256.

    Nüchel J, Bøcher PK, Xiao W, Zhu AX, Svenning JC (2018) Snub-nosed monkeys (Rhinopithecus): Potential distribution and its implication for conservation. Biodiversity and Conservation, 27, 1517–1538.

    Ord JK, Getis A (1995) Local spatial autocorrelation statistics: Distributional issues and an application. Geographical Analysis, 27, 286–306.

    Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231–259.

    Phillips SJ, Dudík M, Schapire RE (2004) A Maximum Entropy Approach to Species Distribution Modeling. p. 83. Association for Computing Machinery, Banff.

    Raes N, Roos MC, Slik JWF, van Loon EE, ter Steege H (2009) Botanical richness and endemicity patterns of Borneo derived from species distribution models. Ecography, 32, 180–192.

    Raes N, Steege HT (2007) A null-model for significance testing of presence-only species distribution models. Ecography, 30, 727–736.

    Scott JM, Csuti B, Jacobi JD, Estes JE (1987) Species richness. BioScience, 37, 782–788.

    Sierra R, Campos F, Chamberlin J (2002) Assessing biodiversity conservation priorities: Ecosystem risk and representativeness in continental Ecuador. Landscape and Urban Planning, 59, 95–110.

    Song W, Kim E, Lee D, Lee M, Jeon SW (2013) The sensitivity of species distribution modeling to scale differences. Ecological Modelling, 248, 113–118.

    Tang JH, Cheng YX, Luo LZ, Zhang L, Jiang XF (2017) MaxEnt-based prediction of overwintering areas of Loxostege sticticalis in China under different climate change scenarios. Acta Ecologica Sinica, 37, 4852–4863 (in Chinese with English abstract).

    Tang ZY, Fang JY (2004) A review on the elevational patterns of plant species diversity. Biodiversity Science, 12, 20–28. (in Chinese with English abstract)

    VazÚL, Cunha HF, Nabout JC (2015) Trends and biases in global scientific literature about ecological niche models. Brazilian Journal of Biology, 75 (4), S17–S24.

    Wang HL (2017) Protection and utilization of wild animals and plants in Lanping County. Journal of Green Science and Technology, (3), 90–91. (in Chinese)

    Wiegand T, Gunatilleke S, Gunatilleke N (2007) Species associations in a heterogeneous Sri Lankan dipterocarp forest. The American Naturalist, 170, E77.

    Yang GB (2011) Ecological quality assessment of Yunling Nature Reserve in Lanping County of Yunnan Province. Journal of West China Forestry Science, 40 (4), 48–53 (in Chinese with English abstract).

    Yang GB (2013) Lanping Yunling Nature Reserve. Yunnan Science and Technology Press, Kunming (in Chinese).

    Zhang L (2015a) Application of MaxEnt model in predicting the potential distribution of species. Bulletin of Biology, 50 (11), 9–12 (in Chinese).

    Zhang L (2015b) Prediction of potential distribution area of Euphorbia dentata in China based on MaxEnt model. Journal of Biosafety, 24, 194–200 (in Chinese with English abstract).

    Zhao SQ, Fang JY, Lei GC (2000) Global 200: An approach to setting large-scale biodiversity conservation priorities. Chinese Biodiversity, 8, 435–440 (in Chinese with English abstract).

    Zhu GP, Qiao HJ (2016) Effect of the MaxEnt model’s complexity on the prediction of species potential distributions. Biodiversity Science, 24, 1189–1196 (in Chinese with English abstract).

This Article



Vol 26, No. 09, Pages 931-940

September 2018


Article Outline


  • 1 Materials and methods
  • 2 Results
  • 3 Discussion
  • Supplementary Material
  • Footnote