| Mangrove ecosystem is formed through long terms of succession between marine andterrestrial ecosystems. It is a special forest ecosystem which has stable system structure andhigh productivity. Mangroves play an important role in protecting coastlines, creating land withsilt, purifying sea water, maintaining biodiversity. The object of mangrove healthy managementis to maintain complete, stable continuous system function and high productivity. Therefore, itis urgent work for mangrove protection and recovery to evaluate ecosystem health, adjustlandscape pattern and optimizate forest spatial structure.This paper taked Zhangjiangkou Estuary Mangrove National Natural Reserve, lacated inYunxiao County, Fujian Province, as the subject, and analyzed dynamic the changes oflandscape pattern and driving force in mangrove wetland based on three temporal differenthigh-resolution sensing images in2003,2008and2013. Every ojbcetive wood was located andthe stand description factors were surveyed in typical mangrove communities selected fromdifferent tidal zones. The characteristic of forest stand spatial structure was researched basedon GIS technology and mangrove ecosystem health was evaluated using PSR chain andanalytic hierarchy process. According to analysis results, optimation layout of mangrovelandscape structure was put forward on landscape level. The mangrove forest spaceoptimization models of selecting cutting and replanting were built based on forest stand spatialstructure comprehension index on the forest stand scale and applied the models to simulatemanagement in research area. Sustainable management measures were put forward to eliminateor weake influence of mangrove ecosystem health from outside pressure. The results showedthat:（1）Mangrove landscape informations were extracted accurately based on high-resolutionremote sensing images of SPOT5and PLEIADES. The auxiliary informations built embankment line, calculated by Band1/Band2,(Band4-Band3)/(Band4+Band3), Band3/Band2,were added to decision tree rules. The results showed that overall accuracy of three imageswere separately97.24%,92.90%,97.86%and their Kappa coefficients were0.97,0.91,0.97.Compared with supervise classification without auxiliary informations, the overall accuraciesraised separately16.91%,7.90%and12.21%.（2）Mangrove areas increased from47.69hm2to64.24hm2during the last ten years.Centre of mass of mangrove moved slightly to northeast. Spartina areas increased42.72hm2and encroached on mangrove of13.38hm2with the trend of rapidly increasing after falling.Artificial shrimp pond areas almost twice increased from148.69hm2to254.84hm2. Themangrove ecosystem was degradated gradually during a large amount of natural wetlands weretransformed to artificial wetlands and2.11hm2of mangrove were eliminated. The analysis ofmangrove wetland landscape pattern index showed that landscape diversity and fragmentationdegree increased continuously, all types of pacthes developed to equilibrium, and continuityand integrity of landscape appeared worse. The main factors of dynamic change of mangrovewetland landscape were impoundment for farming, bank maintenance and spartina invasion.The change of mangrove wetland landscape was predicted by Markov model in future, theproportion of natural wetland would be dropped significantly and mangrove ecosystem wouldbe further degradated if there are no measures to control the sharp increasement of spartina andartificial shrimp ponds.（3）The forest stand spatial structure unit made up objective wood and adjacentcompetited wood was devided using Thiessen polygon method. It will reduce a great deal ofwork of field survey to query the serial numbers of adjacent woods using secondarydevelopment program of GIS and calculate forest stand spatial structure indexes withapplication of VBA program. The difference of mingling degree among different tidal forestwas obvious and they were high tidal zone, middle tidal zone and low tidal zone in the order ofmingling degree, moreover, the low tidal forest was nearly pure stand. （4）Tree species composition was simple and diversity was low. The level of speciesisolation was low, which was weak mingling. In mangrove forests, the intraspecificcompetition is fiercer than the interspecific competition, and they were Aegiceras corniculatum,Kandelia candel, Avicennia marina and Bruguiera gymnorrhiza in the order of competitionindex. There was a small difference among the average neighbor-hood comparisons ofinvestigation forest stands. The difference of diameter at breast height was not obvious inspecies and the growth conditions of different trees were balanced. There were a littledifference among mangrove trees and the average healthy indexes were no significantdifference. The distribution frequency of uniform angle index was a little difference amongdifferent tidal mangrove trees, the overall distribution patterns were even distribution mainlyand inclined to be randomly slightly. The distribution frequency of aggregation index wassignificant difference among different species. The aggregation distribution was predominantin Aegiceras corniculatum and Kandelia candel, there were same distribution frequency ofaggregation, random and even in Avicennia marina, and the random distribution frequency ofBruguiera gymnorrhiza was higher than the others’.（5）There were significant difference among different species’height structure, the heightand under-branch height of Kandelia candel and Bruguiera gymnorrhiza were higher thanAvicennia marina’s and Aegiceras corniculatum’s. The diameter at breast heights were small,concentrated in3to7cm. There was a little difference among diameters of crown in differentspecies, Avicennia marina’s was largest and Aegiceras corniculatum’s was smallest.（6）The ecosystem health of mangrove was evaluated by PSR model and AHP method.The results showed comprehension healthy index was0.66, in healthy level.（7）Suitable forest land was divided to the habitat condition of mangrove. Mangrovelandscape structure was optimized from directions of Spartina treatment and layout ofprotective forests. After optimation, mangrove area ratio increased by6.92%, spartina arearatio reduced4.50%. Mangrove’s centre of mass moved1323m to southeast. （8）Applied gray correlation analysis method to research the relationship between forestspatial structure comprehension index and it’s factors, and it showed that aggregationindex(0.80), compitition index(0.80), uniform angle index (0.74), health index(0.73), minglingdegree(0.71), neighbor-hood comparison(0.67). The mangrove forest space optimizationmodels of selecting cutting and replanting were built based on GIS technology, according toforest stand spatial structure comprehension index as objective function, setting six indicesstand structure as constraints. Applying the two optimization models to guide forestmanagement, the spatial structure could be improved significantly which made spatial structureof mangrove stands transforming to ideal spatial structure.Overall, this study led to the following innovations:(1)The decision tree method withauxiliary informations built embankment line, calculated by Band1/Band2,(Band4-Band3)/(Band4+Band3), Band3/Band2, could greatly increase accuracy of mangrovewetland classification compared with traditional supervise classification method;(2)Forestspatial structure analysis method was applied to mangrove ecosystem. The forest spatialstructure unit was divided by Thiessen polygon method and serial numbers of adjacent woodwere found using GIS program, and the forest spatial structure indexes of mingling degree,neighbor-hood comparison, compitition index, health index, uniform angle index andaggregation index were calculated by VBA program.(3)Built mangrove forest spaceoptimization models of selecting cutting and replanting were built based on GIS technology. |
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