庐山不同森林植被类型土壤碳库管理指数评价

土壤碳库管理指数(CPMI)是表征土壤碳库变化的一个重要量化指标,能够反映土壤的碳库变化和碳库质量。选取庐山8种森林植被类型土壤为研究对象,对其土壤有机碳库特征及碳库管理指数进行系统研究。结论表明:(1)土壤有机碳(SOC)主要分布于0~20 cm土层中,随着土层深度增加,不同森林植被类型下SOC含量急剧下降;在0~60 cm土层中,不同森林植被类型下SOC含量的平均值排序为:马尾松林常绿阔叶林灌丛针阔混交林常绿-落叶混交林黄山松林落叶阔叶林竹林。(2)不同森林植被类型下活性有机碳(ASOC)含量为0.24~0.57 g·kg–1,总有机碳(TOC)含量为9.72~14.74 g·kg–1,土壤碳库指数(CPI)为1.63~2.48,碳库活度(A)为0.019~0.062,碳库活度指数(AI)为0.388~1.265。不同森林植被类型下ASOC含量排序:落叶阔叶林黄山松林常绿-落叶阔叶混交林灌丛针阔混交林常绿阔叶林竹林马尾松林;不同森林植被类型下ASOC/TOC(%)排序:落叶阔叶林黄山松林常绿-落叶阔叶混交林竹林灌丛针阔混交林常绿阔叶林马尾松林;不同森林植被类型下CPMI排序为:落叶阔叶林黄山松林常绿-落叶阔叶混交林灌丛针阔混交林常绿阔叶林竹林马尾松林。     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用。以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特征。结果表明,（1）研究区2000—2018年植被覆盖趋向改善,NDVI呈现增加趋势,增速为0.11/10a,2008年以后植被增长较为明显;NDVI在2018年中高等级（0.6—0.8）面积比2000年中高等级面积明显增加;中高等级集中于榆林市东部黄土丘陵区,中低等级（0.2—0.4）集中于榆林市西北部的风沙区,植被覆盖呈现东部高西北低的空间分布特征。（2）人口密度和气温因子较好地解释植被NDVI空间分异性,是影响NDVI空间分异性的主要因子,GDP、土地利用类型和坡度是次级影响因子,其他因子对NDVI空间分异存在间接影响;坡向、降水和土壤类型因子与其他自然、人文因素对植被空间分布影响存在显著性差异。（3）自然、人文因子对榆林市NDVI的影响存在交互作用,因子之间的交互...     

秦岭火地塘森林水质的季节性变化特征

在秦岭火地塘林区选择2个闭合小流域及2个支沟集水区,对流域出口径流及支沟集水区溪流水pH值及水化学成分进行了8 a的测试,采用机理分析方法,就森林水质的季节性变化特征进行了研究.结果表明,林区径流pH值在7.1～8.4之间,冬、春季较高,夏、秋季较低,总体上水呈弱碱性;NO-3浓度春季和初夏较高,NH 4冬季和初春较高,PO3-4冬季与夏季较高;K 浓度春、秋季较高,Na 浓度则9月最大,8月最小;Ca2 浓度以6月和10月较高,年内变化范围19.4～44.3 mg·L-1,Mg2 则3月较高,年内变化范围2.18～5.25 mg·L-1;Cd浓度随季节的变化以1～4月较高,Pb浓度12、1月较高,但Cd、Pb均以秋季较低,年内变化范围分别为0.019～0.326 5 μg稬-1和0.217～3.886 μh稬-1;Mn浓度5、12月较高,Fe浓度春季较高,Zn则以3、8月较高.林区径流水质属Ⅰ类,相对而言,水质随季节的变化以秋季较好,冬、春季较差.     

GIS支持下的秦岭植被景观梯度分析

秦岭植被景观类型丰富,具有过渡性和复杂性特点,植被垂直分带明显. 在分析了大尺度秦岭植被景观空间水平分布格局的基础上,利用基于GIS梯度分析方法,分析秦岭的植被与海拔梯度的关系,得到秦岭不同植被景观类型的斑块数、分布范围、植被分布的海拨高度平均值和标准差,并以太白山为例,对太白山植物种进行了梯度分析. 结果表明,随着海拔高度的增加,太白山依次出现7种植被景观类型:温带草丛→温带落叶灌丛→温带落叶阔叶林→亚热带针叶林→亚热带和热带山地针叶林→草甸→高寒草甸等植被类型,植物种亦发生相应的变化.      

Changes in forest biomass carbon stock in the Pearl River Delta between 1989 and 2003

Forest ecosystems play a significant role in maintaining climate stability at the regional and global scales as an important carbon sink.Regional forest carbon storage and its dynamic changes in the Pearl River Delta have been estimated using the continuous biomass expansion factor(BEF)method based on field measurements of forests plots in different age classes and forest inventory data of three periods(1989–1993,1994–1998,1999–2003).The results show that regional carbon storage increased by 16.76%,from 48....     

Natural recovery of different areas of a deserted quarry in South China

A quarry is a surface mining operated place, which produces enormous quantities of gravel, limestone, and other materials for industrial and construction applications. Restoration and revegetation of deserted quarries are becoming increasingly important. Three areas of a typical quarry in South China: terrace for crushed materials (terrace), spoiled mound, and remaining side slope, were investigated, to compare the existing plant species and to study the relationship between environmental factors and revegetation. The plant species composition of these three areas was found to differ significantly after eight years of natural recovery. The typical plant communities found over them were composed of gramineous herbs, fems, and shrubs. Soil organic matter, soil moisture, and soil bulk density were considered to be the major determining factors for vegetation succession. There existed abiotic and biotic thresholds during quarrying restoration. Suggestions had been presented that could have accelerated the process of natural recovery in quarries.     

Negative effects of nitrogen deposition on Swiss butterflies

Nitrogen (N) deposition from agriculture and combustion of fossil fuels is a major threat to plant diversity, but its effects on organisms at higher trophic levels are unclear. We investigated how N deposition may affect species richness and abundance (number of individuals per species) in butterflies. We reviewed the peer-reviewed literature on variables used to explain spatial variation in butterfly species richness and found that vegetation variables appeared to be as important as climate and habitat variables in explaining butterfly species richness. It thus seemed likely that increased N deposition could indirectly affect butterfly communities via its influence on plant communities. To test this prediction, we analyzed data from the Swiss biodiversity monitoring program for vascular plants and butterflies in 383 study sites of 1 km² that are evenly distributed throughout Switzerland. The area has a modeled N deposition gradient of 2–44 kg N ha⁻¹ year⁻¹. We used traditional linear models and structural equation models to infer the drivers of the spatial variation in butterfly species richness across Switzerland. High N deposition was consistently linked to low butterfly diversity, suggesting a net loss of butterfly diversity through increased N deposition. We hypothesize that at low elevations, N deposition may contribute to a reduction in butterfly species richness via microclimatic cooling due to increased plant biomass. At higher elevations, negative effects of N deposition on butterfly species richness may also be mediated by reduced plant species richness. In most butterfly species, abundance was negatively related to N deposition, but the strongest negative effects were found for species of conservation concern. We conclude that in addition to factors such as intensified agriculture, habitat fragmentation, and climate change, N deposition is likely to play a key role in negatively affecting butterfly diversity and abundance.     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.     

Role of the Forest Entomofauna in Successional Processes

Participation of the entomofauna in the succession of forest biogeocenoses is analyzed. In stable ecosystems, insects serve as a mechanism providing for long-term ecological stability. In unstable ecosystems, their activities are essentially negative and cause ecosystem degradation.__________Translated from Ekologiya, No. 3, 2005, pp. 227–230.Original Russian Text Copyright © 2005 by Yanovskii.