Biodiversity Science ›› 2018, Vol. 26 ›› Issue (9): 931-940.doi: 10.17520/biods.2018059

• Original Papers • Previous Article     Next Article

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

Hongfei Zhuang1, 2, Yinbo Zhang3, Wei Wang1, 4, *(), Yueheng Ren1, Fangzheng Liu1, Jinhong Du1, Yue Zhou1   

  1. 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
  • Received:2018-02-13 Accepted:2018-05-15 Online:2019-01-05
  • Wang Wei E-mail:wang.wei@craes.org.cn
  • About author:

    # Co-first authors

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 area under ROC curve (AUC value) for Three Parallel Rivers, Yunnan Province and China were 0.936, 0.887, and 0.930 respectively and OR values were 0.18, 0.15, and 0.20, indicating that MaxEnt model for all three spatial scales could successfully predict the distribution of M. insignis. 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 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 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.

Key words: MaxEnt model, spatial scale, Manglietia insignis, minimum convex polygon, hotspots, common species

Table 1

Scale setting of the study areas and the distribution status of Manglietia insignis"

尺度
Scale
覆盖范围
Cover range
红色木莲分布现状
Distribution status of Manglietia insignis
三江并流
Three Parallel
Rivers
泸水县、兰坪白族普米族自治县、玉龙纳西族自治县、福贡县、维西傈僳族自治县、德钦县、贡山独龙族怒族自治县和香格里拉市8个行
政县, 约4.5万km2
Including Lushui County, Lanping Bai Pumi Autonomous County, Yulong Naxi Autonomous County, Fugong County, Weixi County, Deqin County, Gongshan County, and Shangri-La City, about 45,000 km2
泸水县、福贡县、德钦县和贡山独龙族怒族自治县有其分布记录
Lushui County, Fugong County, Deqin County, and Gongshan County with distribution records
云南省
Yunnan Province
包含昆明市、玉溪市和迪庆藏族自治州等16个州市, 约39万km2
Containing 16 cities, such as Kunming, Yuxi, and Dêqên Tibetan Autonomous Prefecture, about 390,000 km2
临沧市、普洱市和玉溪市等12个州市有其分布
记录
Twelve cities including Lincang City, Puer City, and Yuxi with distribution records
全国
Country
包含省、自治区、直辖市及特别行政区在内的34个省级行政区域, 约
960万km2
Containing 34 provincial administrative regions, including provinces, autonomous regions, municipalities, and special administrative regions, about 9,600,000 km2
湖北、湖南、福建、广西、四川、贵州、云南和西藏8省有其分布记录
Hubei, Hunan, Fujian, Guangxi, Sichuan, Guizhou, Yunnan, Tibet with distribution records

Fig. 1

Modeling areas of three spatial scales and distribution sites of Manglietia insignis"

Fig. 2

Receiver operating characteristic curve of three spatial scales and area under the curve (AUC)"

Fig. 3

Potential suitable distributions and its centroids of Manglietia insignis under three spatial scales"

Fig. 4

Optimized hot spot analysis of probability distribution of Manglietia insignis under three spatial scales"

Table 2

Contribution of environmental variables for Manglietia insignis under Three Parallel Rivers scale (TPRS), Yunnan Province scale (YPS), and country scale (CS)"

尺度
Scale
变量
Variable
环境因子贡献率
Contribution (%)
尺度
Scale
变量
Variable
环境因子贡献率
Contribution (%)
三江并流尺度
TPRS
b1 3.4 b15 13.7
b2 9.8 alt 2.9
b4 6.2 slo 10.1
b15 11 asp 3.5
alt 39.4* 全国尺度
CS
b1 5.9
slo 8.1 b2 24.8*
asp 22.1* b7 21.7*
云南省尺度
YPS
b1 5.1 b12 11.4
b2 8.9 b18 14.1
b4 18.8 alt 7.1
b12 35.5* slo 10.4
b14 1.6 asp 4.7

Fig. 5

Results of Jackknife evaluation of the environmental variables with respect to regularized training gain for Three Parallel Rivers scale (A), Yunnan Province scale (B), and country scale (C)"

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