DDF(dry dipterocarp forest)is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products.So,people would like to come to use these products fo...DDF(dry dipterocarp forest)is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products.So,people would like to come to use these products for daily uses in this forest type.The main aim of this study is to evaluate significant biophysical factors for DDF distribution using factor analysis and to model DDF distribution using ENFA(ecological niche factor analysis).In this study,13 watersheds of Ping Basin in northern Thailand were selected as the study site based on availability of forest inventory data in 2007 from DNP(Department of National Parks,Wildlife and Plant Conservation).Basic biophysical data for data analysis included forest inventory data(179 DDF plots),10 climatic data,three topographic data,and one soil data.For identification and evaluation of biophysical factors for DDF distribution using factor analysis,the first three factors,namely DDF-1,DDF-2 and DDF-3,had been extracted with 95.35%of total variance.These three components were used to predict DDF distribution based on HS(habitat suitability)with ENFA.In practice,the results were validated with AVI(absolute validation index)and CVI(contrast validation index)with validated forest inventory dataset.This evaluation shows that DDF-2 model is the best HS data consisting of four physical factors(mean annually temperature,mean monthly maximum temperature,mean monthly minimum temperature,and elevation),which is able to effectively used for habitat suitability for DDF distribution prediction.It was found that habitat suitability for DDF distribution can be classified into four classes including high suitable habitat,moderate suitable habitat,low suitable habitat,and unsuitable habitat.As a result,DDF distributions with high suitable habitat are highly related with DDF forest inventory plots of DNP.Thus,the obtained output can be further used for DDF rehabilitation according to climate and topographic factors.展开更多
The rapid pace of development of GIS （geographical information system） has assisted in identification of conservation priority sites by delineating species distribution using models on habitat suitability. Gaur, Bos...The rapid pace of development of GIS （geographical information system） has assisted in identification of conservation priority sites by delineating species distribution using models on habitat suitability. Gaur, Bos gaurus, is categorized as ＂Vulnerable＂ in the IUCN Red List of Threatened Species, 2009. The study has used ENFA （ecological niche factor analysis） to understand the distribution status of Gaur in TATR （Tadoba-Andhari Tiger Reserve）, Central India. TATR was sampled using stratified random sampling strategy. A total of 21 continuous variables were used, categorised under 4 environmental descriptors categories viz. habitat, anthropogenic, topographic and hydrological variables. All the variables were tested for the correlation and one of the variable among strongly correlated （r 〉 0.7） variables was discarded to avoid redundancy. A total of 14 variables were retained. The model resulted in marginality of 0.56 and specialization of 2.608. Presence of Gaur showed the positive association with canopy density classes （〈 30% ＆ 40-60%） and open forest. However, it was negatively associated with elevation, non-forest, riparian forest, scrub and teak forest. The study has delineated the areas where appropriate habitat conditions exist to sustain Gaur populations vital for planning strategies for conservation of this megaherbivore species in tropical forests.展开更多
Introduction:Huemul(Hippocamelus bisulcus Molina)is the most threatened flag species of Southern Patagonia,where conservation efforts were not effective to avoid the retraction of its distribution area.Habitat quality...Introduction:Huemul(Hippocamelus bisulcus Molina)is the most threatened flag species of Southern Patagonia,where conservation efforts were not effective to avoid the retraction of its distribution area.Habitat quality modeling can assist to design better management strategies for regional conservation planning.The objective was to elaborate one habitat suitability map for huemul,defining the environmental characteristics at landscape level,and determining the distribution of the suitable habitat inside the current natural reserve network.Methods:We used a database of 453 records and explored 40 potential explanatory variables(climate,topographic,and landscape variables including human-related ones)to develop one habitat suitability map using the Environmental Niche Factor Analysis(ENFA)for Santa Cruz province(Argentina).We combined the outputs in a GIS project using different shapes,including the current natural reserve network.Results:We defined the potential habitat for huemul,where forest edges and ecotone zones(e.g.,mainly alpine environments)were the most important environmental variables,as well as some forest types(e.g.,Nothofagus pumilio).Habitat losses were found in the extreme potential distribution areas(northern and southern areas),probably related to the increasing ranch activities.The current natural reserve network maintains approximately half of the huemul potential habitat in Santa Cruz province,where National Parks presented the similar conservation importance than the Provincial natural reserves.Conclusions:Habitat suitability model for huemul can be used as a decision support system for new management strategies at different landscape levels to improve the current conservation efforts.展开更多
With the aim of solving the detection problems for current complex event detection models in detecting a related event for a complex event from the high proportion disordered RFID event stream due to its big uncertain...With the aim of solving the detection problems for current complex event detection models in detecting a related event for a complex event from the high proportion disordered RFID event stream due to its big uncertainty arrival,an efficient complex event detection model based on Extended Nondeterministic Finite Automaton(ENFA)is proposed in this paper.The achievement of the paper rests on the fact that an efficient complex event detection model based on ENFA is presented to successfully realize the detection of a related event for a complex event from the high proportion disordered RFID event stream.Specially,in our model,we successfully use a new ENFA-based complex event detection model instead of an NFA-based complex event detection model to realize the detection of the related events for a complex event from the high proportion disordered RFID event stream by expanding the traditional NFA-based detection model,which can effectively address the problems above.The experimental results show that the proposed model in this paper outperforms some general models in saving detection time,memory consumption,detection latency and improving detection throughput for detecting a related event of a complex event from the high proportion out-of-order RFID event stream.展开更多
文摘DDF(dry dipterocarp forest)is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products.So,people would like to come to use these products for daily uses in this forest type.The main aim of this study is to evaluate significant biophysical factors for DDF distribution using factor analysis and to model DDF distribution using ENFA(ecological niche factor analysis).In this study,13 watersheds of Ping Basin in northern Thailand were selected as the study site based on availability of forest inventory data in 2007 from DNP(Department of National Parks,Wildlife and Plant Conservation).Basic biophysical data for data analysis included forest inventory data(179 DDF plots),10 climatic data,three topographic data,and one soil data.For identification and evaluation of biophysical factors for DDF distribution using factor analysis,the first three factors,namely DDF-1,DDF-2 and DDF-3,had been extracted with 95.35%of total variance.These three components were used to predict DDF distribution based on HS(habitat suitability)with ENFA.In practice,the results were validated with AVI(absolute validation index)and CVI(contrast validation index)with validated forest inventory dataset.This evaluation shows that DDF-2 model is the best HS data consisting of four physical factors(mean annually temperature,mean monthly maximum temperature,mean monthly minimum temperature,and elevation),which is able to effectively used for habitat suitability for DDF distribution prediction.It was found that habitat suitability for DDF distribution can be classified into four classes including high suitable habitat,moderate suitable habitat,low suitable habitat,and unsuitable habitat.As a result,DDF distributions with high suitable habitat are highly related with DDF forest inventory plots of DNP.Thus,the obtained output can be further used for DDF rehabilitation according to climate and topographic factors.
文摘The rapid pace of development of GIS （geographical information system） has assisted in identification of conservation priority sites by delineating species distribution using models on habitat suitability. Gaur, Bos gaurus, is categorized as ＂Vulnerable＂ in the IUCN Red List of Threatened Species, 2009. The study has used ENFA （ecological niche factor analysis） to understand the distribution status of Gaur in TATR （Tadoba-Andhari Tiger Reserve）, Central India. TATR was sampled using stratified random sampling strategy. A total of 21 continuous variables were used, categorised under 4 environmental descriptors categories viz. habitat, anthropogenic, topographic and hydrological variables. All the variables were tested for the correlation and one of the variable among strongly correlated （r 〉 0.7） variables was discarded to avoid redundancy. A total of 14 variables were retained. The model resulted in marginality of 0.56 and specialization of 2.608. Presence of Gaur showed the positive association with canopy density classes （〈 30% ＆ 40-60%） and open forest. However, it was negatively associated with elevation, non-forest, riparian forest, scrub and teak forest. The study has delineated the areas where appropriate habitat conditions exist to sustain Gaur populations vital for planning strategies for conservation of this megaherbivore species in tropical forests.
基金This research was supported by the financial support of the“Operationalisation of Ecosystem Services and Natural Capital:From concepts to real-world applications(OpenNESS)”project financed under the European Commission’s Seventh Framework Programme(project number 308428).
文摘Introduction:Huemul(Hippocamelus bisulcus Molina)is the most threatened flag species of Southern Patagonia,where conservation efforts were not effective to avoid the retraction of its distribution area.Habitat quality modeling can assist to design better management strategies for regional conservation planning.The objective was to elaborate one habitat suitability map for huemul,defining the environmental characteristics at landscape level,and determining the distribution of the suitable habitat inside the current natural reserve network.Methods:We used a database of 453 records and explored 40 potential explanatory variables(climate,topographic,and landscape variables including human-related ones)to develop one habitat suitability map using the Environmental Niche Factor Analysis(ENFA)for Santa Cruz province(Argentina).We combined the outputs in a GIS project using different shapes,including the current natural reserve network.Results:We defined the potential habitat for huemul,where forest edges and ecotone zones(e.g.,mainly alpine environments)were the most important environmental variables,as well as some forest types(e.g.,Nothofagus pumilio).Habitat losses were found in the extreme potential distribution areas(northern and southern areas),probably related to the increasing ranch activities.The current natural reserve network maintains approximately half of the huemul potential habitat in Santa Cruz province,where National Parks presented the similar conservation importance than the Provincial natural reserves.Conclusions:Habitat suitability model for huemul can be used as a decision support system for new management strategies at different landscape levels to improve the current conservation efforts.
基金the National Natural Science Foundation of China(No.61502110)and(No.61602187)and(No.61601189)the Guangdong Science and Technology Projects(No.2016A020209007)and(No.2016A020210088)the Guangzhou Science and Technology Projects(N0.201707010482)。
文摘With the aim of solving the detection problems for current complex event detection models in detecting a related event for a complex event from the high proportion disordered RFID event stream due to its big uncertainty arrival,an efficient complex event detection model based on Extended Nondeterministic Finite Automaton(ENFA)is proposed in this paper.The achievement of the paper rests on the fact that an efficient complex event detection model based on ENFA is presented to successfully realize the detection of a related event for a complex event from the high proportion disordered RFID event stream.Specially,in our model,we successfully use a new ENFA-based complex event detection model instead of an NFA-based complex event detection model to realize the detection of the related events for a complex event from the high proportion disordered RFID event stream by expanding the traditional NFA-based detection model,which can effectively address the problems above.The experimental results show that the proposed model in this paper outperforms some general models in saving detection time,memory consumption,detection latency and improving detection throughput for detecting a related event of a complex event from the high proportion out-of-order RFID event stream.
