Methodology for measuring forestry ecological security based on ecology-industry symbiosis: a research framework
基于生态-产业共生关系的林业生态安全测度方法构想

Some weaknesses of researches on measuring forestry ecological security (FES) are found both in China and abroad, such as pre-warning lag owing to confining the visual field to ecology only, subjectivity in establishing evaluation indicators system and in weighting, difficulty in complementing each other's advantages between indicators system and characteristic indexes, lack of objective criterion for FES, and so on, by studying the connotational constitution of FES and comparing the existing measuring methods. To overcome these weaknesses, a new methodology for measuring FES need to be researched based on ecology-industry symbiosis. Firstly, methods for building FES pressure-state-impact-response structural model and structural equation model (SEM) are researched, in order to provide theoretical basis as well as structured and quantificational methods for establishing evaluation indicators system and for weighting. Then, the two characteristic indexes that are ecology-industry symbiotic degree and mature level which indicate respectively the nature and extent of FES changing trend are derived from exploring the organic link between indicators system and characteristic indexes. Thereby the quantificational methods for ascertaining FES threshold and bottom-line are presented, so that FES degree can be divided into 3 security intervals, 6 security levels and 4 pre-warning levels in accordance with the bicharacteristic judgment matrix. Finally, the overall framework of the methodology for measuring FES based on ecology-industry symbiosis is established according to the above researches, which includes means-ends tree and technology roadmap. There are following technological advantages of FES measure and pre-warning information provided through the methodology according to its building-up mechanism: weak subjectivity, good predictability, explicit eco-economy meaning of characteristic indexes, convenient cause tracing, etc, which are helpful to FES supervisory control.