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Scientia Silvae Sinicae ›› 2019, Vol. 55 ›› Issue (10): 138-151.doi: 10.11707/j.1001-7488.20191014

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Dynamics of Spatial Point Patterns of Different Forest Types Blocks and Associations among the Blocks in Liangshui Nature Reserve

Lingbo Dong1,Hezhi Wang2,Zhaogang Liu1,*   

  1. 1. Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education School of Forestry, Northeast Forestry University Harbin 150040
    2. Academy of Inventory and Planning, State Forestry and Grassland Administration Beijing 100714
  • Received:2018-02-28 Online:2019-10-25 Published:2019-11-26
  • Contact: Zhaogang Liu
  • Supported by:
    国家自然科学基金项目(31700562);国家重点研发计划课题(2017YFC0504103)

Abstract:

Objective: The objective of this paper was to carry out quantitative analysis of the dynamics of spatial point pattern and its associations with different forest type blocks in Liangshui Nature Reserve during the last forty years (1974-2009), which provided some insights for ecological and environmental protection within this region. Method: The datasets were obtained from four different forest resource inventories carried out in 1974, 1989, 1999, and 2009, respectively. The spatial point pattern and its associations with six different types of natural forest, namely Pinus koraiensis (PK), mixed Picea asperata-Abies fabric (PA), mixed Populus davidiana-Betula platyphylla (PB), mixed coniferous (CF), mixed coniferous-broadleaved (CB), and mixed broadleaved (BF), were calculated using the O-ring statistics within Programita (2010 version) software.Result: Results showed that the areas of different forest types changed significantly during the periods from 1974 to 2009, with areas of PK and PA remaining unchanged, while the areas of other lands (e.g., non-forest land, Larix gmelinii plantations and Pinus koraiensis plantations) and PB both decreased significantly, and most of them were converted into the CF, CB and BF. The O-ring statistics indicated that all the six forest types displayed evident pattern of random distribution within different periods (approximately 92.74%), mainly due to harvesting at early period and complex ecological habitats in this region. The spatial associations among the different forest types were predominated by non-correlations (approximately 71.29%), and the percentages decreased significantly with the increases of recovery time, while the percentages of spatial negative association increased significantly with the increases of recovery time, however the percentages of positive spatial association always remained stable, with an average of about 6.56%. The development patterns of spatial associations among 15 different forest types were divided into three categories. CategoryⅠindicated the spatial associations between two alternative type blocks would be converted from early non-correlations at entire scale to the later non-correlations at small scale and positive correlations at large scale (only including PK & PA), while the spatial associations between two alternative type blocks for categoryⅡusually transferred from the early non-correlations to the later negative-correlations or fluctuated between non- and negative-correlations at entire scale, including PK & CB, PK & BF, PA & PB, PA & BF, PB & CB, PB & BF, CF & CB, CF & BF and CB & BF. The spatial associations between two alternative type blocks of category Ⅲ were all non-significant (namely non-correlations) at all scales during the entire periods. This group included 5 pairs:PK & PB, PK & CF, PA & CF, PA & CB, and PB & CF. Objective: The structures of the forest types in this region have been significantly improved during the last 60 years (i.e., stop deforestation in 1952), however the status of the landscape structures within Liangshui Nature Reserve still remains in the recovery phase, the spatial patterns of different forest types distributed randomly for all periods, and the spatial associations of the different forest types within this region are still relatively weak and unstable. Thus, implementing more rigid and effective conservation of the forest resources in this region is still indispensable.

Key words: nature reserve, forest types blocks, spatial patterns, spatial associations, O-ring statistics

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