Long-range Dependence Characteristics of Forest Biological Disasters in China against the Background of Climate Change

Benyang Wang, Shiqing Chen and Shixiao Yu

Asian Agricultural Research, 2017, vol. 09, issue 04

Abstract: Forest biological disasters (FBD) seriously impact energy flow and material cycling in forest ecosystems, while the underlying causes of FBD are complex. These disasters involve large areas and cause tremendous losses. As a result, the occurrence of FBDs in China (CFBD)threatens the country’s ability to realize its strategic target of increasing both forested area (40 million ha) and forest volume (1.3 billion m3) from 2005 to 2020. Collectively, China has officially named this effort to increase forest area and volume the “Two Increases” as national goals related to forestry. Based on Hurst index analysis from fractal theory, we analyzed the time series of the occurrence area and related data of FBDs from 1950 to 2007 to quantitatively determine the patterns of the macro occurrence of FBDs in China. Results indicates that, the time series of (CFBD) areas is fractal (self-affinity fractal dimension D=1.3548), the fluctuation of (CFBD) areas is positively correlated (auto-correlation coefficient C=0.2170), and the occurrence of the time series of (CFBD) is long-range dependent (Hurst index H=0.6416), showing considerably strong trend of increases in FBDC area. Three different methods were further carried out on the original time series, and its two surrogate series generated by function surrogate in library tseries, and function SurrogateData in library in WaveletCo on software R, so as to analyze the reliability of Hurst indexes. The results showed that the Hurst indices calculated using different estimation methods were greater than 0.5, ranging from 0.64 to 0.97, which indicated that the change of occurrence area data of FBDs was positively autocorrelated. The long-range dependence in forest biological disasters in China is obvious, and the spatial extent of FBDs tended to increase during this study period indicating this trend should be expected to persistent and worsen in the future.

Keywords: Agribusiness (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:ags:asagre:262787

DOI: 10.22004/ag.econ.262787

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