| Identifying priority areas for biodiversity conservation is an important way to improve the effectiveness of conservation actions.And,identifying areas with high conservation value according to biogeographical distribution characteristics is the first step to optimizing the protected areas system.The most effective way is to take species as the indicator of conservation planning under the premise of comprehensive species.Nevertheless,the lack of information and low accuracy of species has become a major obstacle to global conservation planning.How to make scientific and rational decisions on regional biodiversity conservation based on limited species quantity or quality information has become a hot research topic.This paper takes the Southeast Himalaya biodiversity priority conservation areas as the target area,and the biogeographical area of the Himalayas as the extended area.Select endangered,endemic and national key protected plants as indicators,and set three scenarios(scenario 1: species in the target area;scenario 2: the extended area is the same species as the target area;scenario 3: all species in the extended area and target area).First,the Maxent model was used to predict the distribution of potential suitable habitat for each species,and then the micro-priority areas in the target area were identified based on the Zonation model.Then,quantify the ecological representativeness,conservation gaps and landscape pattern indices of each scenario micro-priority areas in the target area,and select the optimal scenario planning scheme.Finally,through landscape pattern analysis,identify the potential protection units that can be used as established protected areas in the conservation gaps of the optimal scenario micro-priority areas,and comprehensive protection strategies and suggestions are put forward.The main conclusions are as follows:(1)In the scenarios with relatively complete species data,the AUC values of scenarios 2 and 3 were significantly higher than those of scenario 1,the Maxent model fitting accuracy was higher,and the prediction results were closer to the true distribution of species.The areas with high species richness in the three scenarios were distributed in the middle and lower reaches of the Yarlung Zangbo river,and the species was most abundant in the 4000～4500 m altitude gradient.However,there were some differences.Scenario 1 demonstrated high species richness in the whole Rikaze region except Zhongba county,while scenario 2 and scenario 3 showed less and dispersed species diversity in the high-diversity region of Rikaze region.(2)Scenario 1 micro-priority areas are mainly located in the high mountains and valleys in southeastern Tibet,the original lake basins and valleys in southern Tibet,and the middle section of the Himalayas in southwestern Tibet.The micro-priority areas in scenario 2 and scenario 3 mostly cover Nyingchi in southeast Tibet,the Shannan area,and the eastern part of Rikaze.The distribution range of the micro-priority areas in the three scenarios is different.Compared with scenario 1,the micro-priority areas in scenario 2 and scenario 3 were not distributed from the west to the north of Tingri to the north of Saga.Overall,the distribution of micro-priority areas in scenario 2 and scenario 3 is more clustered.(3)The species similarity between the administrative unit and species richness level of each scenario is generally high,the spatial similarity of species richness is only the best at the level Ⅰ,and the spatial similarity of the micro-priority areas is between the similar and extremely similar levels.From the perspective of ecological representativeness,the ecological representativeness of the micro-priority areas in scenario 1 is higher than that in scenario 2 and scenario 3,but the difference in ecological representativeness among the three is not obvious.From the perspective of conservation gaps and landscape indices,the micro-priority areas in scenario 3 have higher spatial overlap with established protected areas,and the patch distribution is more concentrated and less fragmented.Based on the above indicators,this study selects the scenario 3 micro-priority areas with high prediction accuracy and ecological representativeness of the Maxent model,high matching degree with established protected areas,and low patch fragmentation as the optimal scenario planning scheme.(4)There is a partial spatial mismatch between the optimal scenario micro-priority areas and the established protected areas.The conservation gaps were mainly located in Zayü,northern Mêdog,northern Lhozhag,southern Nagrze,Kamba,Yadong,Kangmar,and central Saga.Aiming at the conservation gaps,an optimization model of protected areas was constructed based on the landscape pattern index,and five patch areas with low patch fragmentation,good landscape connectivity and high aggregation were screened out as potential protected areas.In conclusion,this study suggests that it is feasible to predict the potential habitat of species in the target area based on the species data of the extended area,and to identify the biodiversity micro-priority areas of the target area.It is an important direction to explore biodiversity conservation planning in species deficient areas.This paper identifies high efficiency micro-priority areas,and provides scientific reference and decision support for how to build and optimize high efficiency protected areas systems at the fine scale. |
