【作者】 王静；

【导师】 冯江；

【作者基本信息】 东北师范大学 ， 环境科学， 2009， 博士

【摘要】 论文在长白山西南麓罗通山自然保护区,采用声学调查法监测马铁菊头蝠(Rhinolophus ferrumequinum)活动,基于3S技术、地统计学方法和加权秩神经网络模型分别在景观尺度、森林立地尺度和微生境尺度研究马铁菊头蝠生境选择,采用GIS栅格法在多空间尺度下预测马铁菊头蝠潜在空间分布,获得以下研究结果:1.用声学采样法分季节评估马铁菊头蝠在不同生境的活动。从相对开阔到相对复杂的生境,马铁菊头蝠总体活动频次有逐渐增加的趋势,在池塘、针叶林、复杂阔叶林、开阔阔叶林、山脊、草地、森林边缘7种生境活动具有显著季节差异(p < 0.05)。除了盛夏,在初夏、初秋和深秋,马铁菊头蝠活动均受到温湿度的影响(p < 0.05)。2.景观尺度下,用Logistic回归模型研究高程、小溪邻近度、林间小路长度、河道长度、斑块丰富度和边缘密度对马铁菊头蝠生境选择的影响,应用ΔAIC_c和Akaike权重(w)选择最优模型。共构建了包含景观变量的31个模型,林间小路长度、高程和小溪邻近度是预测马铁菊头蝠出现的最优变量。其中,林间小路长度在马铁菊头蝠出现和不出现地点具有显著差异(F = 4.787,p = 0.034)。3.森林立地尺度下,研究森林类型、林分郁闭度、林龄、林分平均树高和坡向对马铁菊头蝠生境选择的影响,共构建31个Logistic回归模型。其中,林分郁闭度、坡向和森林类型是马铁菊头蝠生境选择的最优预测变量,其中森分郁闭度贡献率最高(0.989),其次是坡向(0.633)和森林类型(0.596);树高(0.424)和林龄(0.37)具有较低的贡献率。只有林分郁闭度在马铁菊头蝠出现和不出现地点具有显著差异(U = 40.0,p = 0.032)。在马铁菊头蝠出现的52个地点中,18个地点坡向朝南,没有坡向朝北和西北的地点,表明向阳坡对于马铁菊头蝠捕食具有重要影响。4.微生境尺度下,在75个样地分季节测量对马铁菊头蝠活动具有重要影响的昆虫丰富度、植被结构和温湿度,记录月相。夏季总体昆虫丰富度显著高于秋季(F = 504.054,p < 0.001)。深秋,落叶使得树冠郁闭度显著低于初夏、盛夏和初秋(F = 17.03,p < 0.001)。Poisson广义线性模型结果表明,马铁菊头蝠微生境选择模式存在季节变化。初夏,总体昆虫丰富度、灌木高度和密度是重要影响因素;盛夏,灌木高度和密度是重要影响因素;初秋,总体昆虫丰富度和温度是重要影响因素;深秋,总体昆虫丰富度是重要影响因素。这表明食物丰度高的季节,植被覆盖比食物资源重要,而在食物丰度低的季节,食物资源比植被覆盖更重要,揭示马铁菊头蝠在食物和植被覆盖重要性间进行季节权衡。5.采用粪便分析法分析马铁菊头蝠的食性。马铁菊头蝠食物主要以鳞翅目和鞘翅目为主,各昆虫体积百分比随季节变化。初夏和盛夏以鳞翅目体积百分比最高,分别为73.97%和51.15%;初秋和深秋鞘翅目体积百分比最高,分别为42.03%和54.03%。6.运用GIS栅格计算法创建马铁菊头蝠分布可能性图,在景观和立地尺度下预测马铁菊头蝠潜在分布区,用留一交叉验证检验模型精度。景观尺度下的预测模型精度为62.5%;森林立地尺度下预测模型精度为69 %。论文的主要创新点:1.运用遥感和GIS技术,在不同尺度下预测蝙蝠潜在空间分布,为野生动物保护和管理提供新思路和方法;2.将加权秩神经网络模型应用于遥感数据处理,大大提高遥感数据处理精度,并将其应用于动物生境选择研究,具有一定的开创性;3.在国际范围内率先开展马铁菊头蝠微生境选择研究,阐明马铁菊头蝠活动与微尺度生态因子关系,在细尺度下揭示马铁菊头蝠生境选择机制。根据对马铁菊头蝠多尺度生境选择和空间分布预测结果,提出马铁菊头蝠种群与生境保护管理的主要建议:在距离小溪较近的地点和向阳坡种植具有大树冠的阔叶林;增加干扰,采用择伐的方式为其提供边缘生境,同时增加林窗昆虫丰富度;保护灌木层,为马铁菊头蝠提供保护覆盖。更多还原

【Abstract】 We studied habitat selection by greater horseshoe bats (Rhinolophus ferrumequinum) from the scale of landscape, forest stand and microhabitat in Luotong Mountain natural reserve in southwest of Changbai Mountain, and form a set of quantitative methods for animal habitat selection and spatial distribution prediction from landscape, forest stand and microhabitat scale. Combined remote sensing and Geographical Information System (GIS) technique, we predicted the potential spatial distribution from multiple spatial scales. The main conclusions were as follows:1. We assessed the seasonal activity of greater horseshoe bats in different habitats using acoustic survey. From relatively open habitat to relatively clutter habitat, there was an increase trend in the activity of greater horseshoe bats. The use frequency of different habitat was as follows: mixed woodland > cluttered broadleaved woodland > forest edge > pond > trail > oak woodland > stream > open broadleaved woodland > ridge line > rock > coniferous woodland > grassland > resident sites. We didn’t detect any bats in farmland and treeline habitat. There were significant seasonal differences (p < 0.05) in pond, coniferous forest, cluttered broadleaved forest, open broadleaved forest, ridge, grassland and forest edge. There were high level activity of greater horseshoe bats in cluttered forest and trail in early summer, late summer, early autumn and late autumn, respectively. Except in late summer, the activity of greater horseshoe bats was affected by temperature and humidity in early summer, late autumn and late autumn, respectively (p < 0.05).2. In landscape scale, we used logistic regression model to study the effects of elevation, distance from the nearest stream, the length of terrestrial flyway, the length of riparian flyway, patch richness and edge density on habitat selection by greater horseshoe bats. We usedΔAICc and Akaike weight to assess and select the model with the lowestΔAICc. We constructed 31 habitat models including the variables in landscape scale. The model with the lowestΔAIC_c showed that elevation and distance from the neareast stream were the best predictors of the presence of greater horseshoe bats. In all the landscape variables, only the length of terrestrial flyway was significantly different in the presence sites and the absence sites (F = 4.787, p = 0.034).3. In forest stand scale, we studied the effects of forest type, forest cover, forest age, tree height and aspect on habitat selection by greater horseshoe bats, and constructed 31 habitat models including the variables in forest stand scale. Forest cover, aspect and forest type were the best predictor of habitat selection by greater horseshoe bats. The importance of forest cover was the highest (0.989), then aspect (0.633) and forest type (0.596), and the importance of height (0.424) and age (0.37) was low. In all the forest stand variables, only forest cover was significantly different in the presence sites and the absence sites (U = 40.0, p = 0.032). At the 52 presence sites of greater horseshoe bats, the aspect was south facing at 18 sites. There were no sites where the aspect was north or northwest. The results showed that eutropic aspect was important for foraging greater horseshoe bats.4. In microhabitat scale, we measured insect prey availability, vegetation structure, temperature and humidity data in different seasons in 75 sampling sites. These variables were extremely important to the activity of greater horseshoe bats. In trapped insects, total insect abundance in summer were higher than that in autumn (F = 504.054, p < 0.001). In late autumn, defoliation made the canopy cover lower than that in early summer, late summer and early autumn (F = 17.03, p < 0.001). We used Poisson Generalized Linear Model (GLM) to study the relationship between the activity of greater horseshoe bats and microhabitat variables, and found that the factors influencing habitat selection of greater horseshoe bats varied with seasons. In early summer, total insect abundance, shrub height and shrub density were the best predictors of habitat selection by greater horseshoe bats, thereinto insect resources were more important than shrub height and shrub density; in late summer, shrub height and density were the best predictors of habitat selection by greater horseshoe bats; in early autumn, total insect abundance and temperature were the best predictors of habitat selection by greater horseshoe bats; in late autumn, total insect abundance was the best predictor of habitat selection by greater horseshoe bats. This indicated that vegetation cover was more important than food when food resources were seasonally abundant, whereas food was more important than cover when food resources were seasonally scarce. These results revealed that there was a trade-off between the importance of food and cover for greater horseshoe bats.5. Fecal analysis was used to analyze the diet of greater horseshoe bats. Moths in the order Lepidoptera were the dominant component in the diet of greater horseshoe bats followed by Coleoptera. The percentage by volume of these insect groups changed with seasons. The volume percentage of order Lepidoptera was the highest in early summer (73.97 %) and late summer (51.15); the volume percentage of order Coleoptera was the highest in early autumn (42.03 %) and late autumn (54.03 %). Compared with other seasons, the volume percentage of order Hymenoptera has been improved (15.53 %) in early autumn, and the volume percentage of family Coccinellidae has been improved (12.2 %) in late autumn.6. GIS raster calculator was used to create the possibility map of distribution to predict the potential distribution area of greater horseshoe bat in multiple spatial scales. In landscape scale, we used elevation and distance from the nearest stream to create the potential distribution map. The results of leave-one-out cross-validation showed that the accuracy of the model in landscape scale was 62.5 %. Forest cover, aspect and forest type were used to create the potential distribution map in forest stand scale, and the accuracy of the model was 69 %.更多还原