Preprint Article Version 1 This version is not peer-reviewed

The Spatially Differentiated Trends Between Forest Pest Control Efficiency and Pest-induded Losses in China

Version 1 : Received: 26 October 2018 / Approved: 2 November 2018 / Online: 2 November 2018 (09:32:22 CET)

A peer-reviewed article of this Preprint also exists.

Cai, Q.; Cai, Y.; Wen, Y. Spatially Differentiated Trends between Forest Pest-Induced Losses and Measures for Their Control in China. Sustainability 2019, 11, 73. Cai, Q.; Cai, Y.; Wen, Y. Spatially Differentiated Trends between Forest Pest-Induced Losses and Measures for Their Control in China. Sustainability 2019, 11, 73.

Journal reference: Sustainability 2018, 11, 73
DOI: 10.3390/su11010073

Abstract

China historically exhibits spatial differentiation from population distribution to ecological or economic development, and the forest pest control work is an epitome of this tendency. In recent times, global warming, man-made monoculture tree plantations, increasing human population density and intensified international trade aggravate forest pest outbreaks. Although Chinese government has complied with the internationally recommended practices, few stones remain unturned due to existing differential regional imbalance of forest pest distribution and control abilities. Evidence shows that the high-income provinces in the south have taken advantage of economic and technological superiority, resulting in the adoption of more efficient pest-control measures. To the contrary, in economically underdeveloped provinces of the northwest, a paucity of financial support has led to serious threats of pest damage that almost mirrored the demarcations of the Hu Huanyong Line. In this paper, we propose introducing public-private partnership (PPP) model into forest pest control and combining the national strategies to enact regional prevention measures in order to break the current spatially differentiated trends in China.

Subject Areas

forest pest; control effeciency; pest-induced losses; spatially differentiated

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