Larch caterpillar (Dendrolimus superans) is very common in the Da Hinggan Mountains, Northeast China, affecting fire regime and forest ecosystem change at large spatio-temporal scales. In this study, we used a spatial...Larch caterpillar (Dendrolimus superans) is very common in the Da Hinggan Mountains, Northeast China, affecting fire regime and forest ecosystem change at large spatio-temporal scales. In this study, we used a spatially explicit landscape model, LANDIS, to simulate the changes of fire regime and forest landscape under four larch caterpillar disturbance intensity levels scenarios in Huzhong forest area, northern of Da Hinggan Mountains. The results indicate that larch caterpillar disturbances would decrease fine fuel load and increase coarse fuel load in the 300 simulation years. Larch caterpillar disturbances would decrease fire frequency in the first 200 years, and the disturbances also decrease fire intensity and fire risk in the early and late stage of simulation. Larch caterpillar disturbances would decrease the area percent of larch cohorts and increase the proportion of white birch, and increase the degree of aggregation of white birch as a result of its strong seed dispersal and colonization ability. Disturbances would also decrease the mature and over-mature larch cohorts and increase all cohorts of white birch, especially the mature and over-mature cohorts. Larch caterpillar disturbances will decrease the stability of forest landscape, therefore,some measures preventing in- sect outbreak and ensuring the sustainable management of forest ecosystem should been taken in the study area.展开更多
Issues of scale and aggregation become important when large range of space and time scales is considered in landscape models.However,identifying appropriate levels of aggregation to accurately represent the processes ...Issues of scale and aggregation become important when large range of space and time scales is considered in landscape models.However,identifying appropriate levels of aggregation to accurately represent the processes and components of ecological systems is challenging.A raster-based spatially explicit forest landscape model,LANDIS,was used to study the effects of spatial aggregation on simulated spatial pattern and ecological process in Youhao Forest Bureau of the Small Khingan Mountain in Northeastern China.The model was tested over 500 simulation years with systematically increased levels of spatial aggregation.The results show that spatial aggregation significantly influences the simulation of fire disturbance,species abundance,and spatial pattern.Simulated fire regime was relatively insensitive to grain size between 30.m and 270.m in the region.Spatial aggregation from 300.m to 480.m dramatically decreased fire return interval(FRI) and increased mean fire size.Generally,species abundance and its aggregation index(AI) remained higher level over simulation years at the fine-grained level of spatial aggregation than at coarser grains.In addition,the simulated forest dynamics was more realistic at finer grains.These results suggest that appropriate levels of spatial aggregation for the model should not be larger than 270m.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.31070422,40871245)Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA05050201)
文摘Larch caterpillar (Dendrolimus superans) is very common in the Da Hinggan Mountains, Northeast China, affecting fire regime and forest ecosystem change at large spatio-temporal scales. In this study, we used a spatially explicit landscape model, LANDIS, to simulate the changes of fire regime and forest landscape under four larch caterpillar disturbance intensity levels scenarios in Huzhong forest area, northern of Da Hinggan Mountains. The results indicate that larch caterpillar disturbances would decrease fine fuel load and increase coarse fuel load in the 300 simulation years. Larch caterpillar disturbances would decrease fire frequency in the first 200 years, and the disturbances also decrease fire intensity and fire risk in the early and late stage of simulation. Larch caterpillar disturbances would decrease the area percent of larch cohorts and increase the proportion of white birch, and increase the degree of aggregation of white birch as a result of its strong seed dispersal and colonization ability. Disturbances would also decrease the mature and over-mature larch cohorts and increase all cohorts of white birch, especially the mature and over-mature cohorts. Larch caterpillar disturbances will decrease the stability of forest landscape, therefore,some measures preventing in- sect outbreak and ensuring the sustainable management of forest ecosystem should been taken in the study area.
基金Supported by National Natural Science Foundation of China (No.30870441,40331008)the Project of Chinese Academy of Sciences (No.KSCX2-SW-133)
文摘Issues of scale and aggregation become important when large range of space and time scales is considered in landscape models.However,identifying appropriate levels of aggregation to accurately represent the processes and components of ecological systems is challenging.A raster-based spatially explicit forest landscape model,LANDIS,was used to study the effects of spatial aggregation on simulated spatial pattern and ecological process in Youhao Forest Bureau of the Small Khingan Mountain in Northeastern China.The model was tested over 500 simulation years with systematically increased levels of spatial aggregation.The results show that spatial aggregation significantly influences the simulation of fire disturbance,species abundance,and spatial pattern.Simulated fire regime was relatively insensitive to grain size between 30.m and 270.m in the region.Spatial aggregation from 300.m to 480.m dramatically decreased fire return interval(FRI) and increased mean fire size.Generally,species abundance and its aggregation index(AI) remained higher level over simulation years at the fine-grained level of spatial aggregation than at coarser grains.In addition,the simulated forest dynamics was more realistic at finer grains.These results suggest that appropriate levels of spatial aggregation for the model should not be larger than 270m.
