Biodiversity Science ›› 2013, Vol. 21 ›› Issue (5): 554-563.doi: 10.3724/SP.J.1003.2013.10049

• Orginal Article • Previous Article     Next Article

Influence of geographical distance and topographic difference on β diversity in two large-scale forest dynamics plots

Pin Lu1, 2, Yi Jin2, Jianhua Chen1, Minghong Li1, *, Mingjian Yu2, *()   

  1. 1 Institute of Ecology, Zhejiang Normal University, Jinhua, Zhejiang 321004
    2 College of Life Sciences, Zhejiang University, Hangzhou 310058
  • Received:2013-02-24 Accepted:2013-04-26 Online:2013-10-08
  • Li Minghong,Yu Mingjian E-mail:fishmj202@sohu.com

β diversity quantifies the extent of community compositional shift in a heterogeneous environment. To understand how β diversity is influenced by geographical distance and topographic variation in continuous space, we compared β diversity in two large-scale forest dynamics plots (FDPs). One of these is a 24 ha plot exhibiting complex topography in a subtropical evergreen broad-leaved forest at Gutianshan (GTS), China. The other is a 50 ha plot of comparatively simple topography present in a lowland tropical moist forest on Barro Colorado Island (BCI) in Panama. We investigated the influence of geographical distance and topographic difference on β diversity at four levels of grain. We adopted the 1-Chao-Jaccard index as a measure of β diversity, and performed tests such as Mantel and Partial Mantel tests to disentangle the effects of geographical distance, topographic variation and five topographical variables on β diversity. The results showed that in both plots β diversity was grain size dependent, decreasing as grain size increased. In both plots β diversity was significantly affected by geographical distance and topographic difference. Furthermore, the influence of geographical distance on β diversity showed a monotonic increase in both FDPs with increase in grain size. The effect of topography on β diversity was consistently larger in GTS than in BCI, and was manifested in GTS mainly through altitude and convexity at each grain size. Our results suggest the importance of both niche and dispersal processes in shaping β diversity patterns.

Key words: β diversity, subtropical evergreen broad-leaved forest, Gutianshan, tropical forest, Barro Colorado Island, topography, niche process, dispersal process

Table 1

Background information about the Gutianshan plot and the Barro Colorado Island (BCI) plot"

样地
Plot
大小
Size
经度
Longitude
纬度
Latitude
海拔
Elevation (m)
坡度
Slope
GTS 400 m (SN)×600 m (WE) 118°07.010′-118°07.400′ E 29°15.101′-29°15.344′ N 446.3-714.9 12.8°-62.0°
BCI 500 m (SN)×1,000 m (WE) 79°51.31'-79°51.318' W 9°9.075'-9°9.345' N 121.2-159.2 0.2°-19.4°

Fig. 1

Relationship between community similarity and distance at different grain sizes. a, b, c and d represent grain sizes of 10 m, 20 m, 40 m and 50 m, respectively. Black line indicates Gutianshan plot; Grey line indicates BCI plot."

Fig. 2

The Mantel-test derived correlation coefficients bet- ween beta diversity and geographical distance at each grain size in the Gutianshan (GTS) plot and Barro Colorado Island (BCI) plot. GTS and BCI, Topography uncontrolled; gts and bci, Topography controlled."

Fig. 3

The Mantel-test derived correlation coefficients bet- ween beta diversity and topographic difference at each grain size in the Gutianshan (GTS) plot and Barro Colorado Island (BCI) plot (* P<0.05, ** P<0.01, *** P<0.001). GTS and BCI, Geographical distance uncontrolled; gts and bci, Geographical distance controlled."

Fig. 4

The Partial Mantel-test derived correlation coefficients between beta diversity and each topographic variables (elevation, convexity, slope, EW aspect and SN aspect) at each grain sizes in the GTS plot and BCI plot (* P<0.05, ** P<0.01, *** P<0.001). a, Elevation; b, Slope; c, Convexity; d, Aspect 1 (East-West); e, Aspect 2 (North-South)."

Fig. 5

The third-degree polynomial regressions fitting the relationship between community similarity and geographical distance and topographic difference. a, BCI plot; b, GTS plot; 1, 2, 3 and 4 represent grain sizes 10 m, 20 m, 40 m, and 50 m respectively. Grey line indicate observe values. Black line represents geographical distance fitting, the adjusted R2 from 10 m to 50 m grain size in GTS were 0.0211, 0.0351, 0.0710 and 0.0680, respectively, and in BCI were 0.0104, 0.0219, 0.0601 and 0.0875, respectively. Circles represent topography fitting, the adjusted R2 from 10 m to 50 m grain size in GTS were 0.0596, 0.1127, 0.1067 and 0.0821 respectively, and in BCI were 0.0083, 0.0010, 0.0212 and 0.0279 respectively. Dots represent the geographic distance and topography joint fitting, the adjusted R2 from 10 m to 50 m grain size in GTS were 0.0667, 0.1211, 0.1478 and 0.1303, respectively, and in BCI were 0.0126, 0.0219, 0.0584 and 0.0890, respectively. P<0.001 for all the above fitting results."

Appendix I

World map showing the locations of the GTS plot and BCI plot"

Appendix II

Topographical map of the GTS plot"

Appendix III

Topographical map of the BCI plot"

Appendix IV

Linear regression fitting of the logged community similarity with geographical distance. a, BCI plot; b, Gutianshan plot; 1, 2, 3 and 4 represent grain size 10 m, 20 m, 40 m and 50 m respectively. BCI decay rate: -2.994×10-5/m, -1.295×10-4/m, -1.081×10-4/m and -1.073×10-4/m ; GTS decay rate: -1.152×10-4/m, -3.207×10-4/m, -2.345×10-4/m and -1.742×10-4/m ."

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