Age and spatial distribution of the world's oldest trees

Extremely old trees have important roles in providing insights about historical climatic events and supporting cultural values, yet there has been limited work on their global distribution and conservation. We extracted information on 197,855 tree cores from 4854 sites and combined it with other tree age (e.g., the OLDLIST) data from a further 156 sites to determine the age of the world's oldest trees and quantify the factors influencing their global distribution. We found that extremely old trees >1000 years were rare. Among 30 individual trees that exceeded 2000 years old, 27 occurred in high mountains. We modeled maximum tree age with climatic, soil topographic, and anthropogenic variables, and our regression models demonstrated that elevation, human population density, soil carbon content, and mean annual temperature were key determinants of the distribution of the world's oldest trees. Specifically, our model predicted that many of the oldest trees will occur in high-elevation, cold, and arid mountains with limited human disturbance. This pattern was markedly different from that of the tallest trees, which were more likely to occur in relatively more mesic and productive locations. Global warming and expansion of human activities may induce rapid population declines of extremely old trees. New strategies, including targeted establishment of conservation reserves in remote regions, especially those in western parts of China and the United States, are required to protect these trees.     

Learning habitat models for the diatom community in Lake Prespa

Habitat suitability modelling studies the influence of abiotic factors on the abundance or diversity of a given taxonomic group of organisms. In this work, we investigate the effect of the environmental conditions of Lake Prespa (Republic of Macedonia) on diatom communities. The data contain measurements of physical and chemical properties of the environment as well as the relative abundances of 116 diatom taxa. In addition, we create a separate dataset that contains information only about the top 10 most abundant diatoms. We use two machine learning techniques to model the data: regression trees and multi-target regression trees. We learn a regression tree for each taxon separately (from the top 10 most abundant) to identify the environmental conditions that influence the abundance of the given diatom taxon. We learn two multi-target regression trees: one for modelling the complete community and the other for the top 10 most abundant diatoms. The multi-target regression trees approach is able to detect the conditions that affect the structure of a diatom community (as compared to other approaches that can model only a single target variable). We interpret and compare the obtained models. The models present knowledge about the influence of metallic ions and nutrients on the structure of the diatom community, which is consistent with, but further extends existing expert knowledge.     

Hierarchical Bayesian scaling of soil properties across urban, agricultural, and desert ecosystems.

Ecologists increasingly use plot-scale data to inform research and policy related to regional and global environmental change. For soil chemistry research, scaling from the plot to the region is especially difficult due to high spatial variability at all scales. We used a hierarchical Bayesian model of plot-scale soil nutrient pools to predict storage of soil organic carbon (oC), inorganic carbon (iC), total nitrogen (N), and available phosphorus (avP) in a 7962-km2 area including the Phoenix, Arizona, USA, metropolitan area and its desert and agricultural surroundings. The Bayesian approach was compared to a traditional approach that multiplied mean values for urban mesic residential, urban xeric residential, nonresidential urban, agricultural, and desert areas by the aerial coverage of each land-use type. Both approaches suggest that oC, N, and avP are correlated with each other and are higher (in g/m2) in mesic residential and agricultural areas than in deserts or xeric residential areas. In addition to traditional biophysical variables, cultural variables related to impervious surface cover, tree cover, and turfgrass cover were significant in regression models predicting the regional distribution of soil properties. We estimate that 1140 Gg of oC have accumulated in human-dominated soils of this region, but a significant portion of this new C has a very short mean residence time in mesic yards and agricultural soils. For N, we estimate that 130 Gg have accumulated in soils, which explains a significant portion of "missing N" observed in the regional N budget. Predictions for iC differed between the approaches because the Bayesian approach predicted iC as a function of elevation while the traditional approach employed only land use. We suggest that Bayesian scaling enables models that are flexible enough to accommodate the diverse factors controlling soil chemistry in desert, urban, and agricultural ecosystems and, thus, may represent an important tool for ecological scaling that spans land-use types. Urban planners and city managers attempting to reduce C emissions and N pollution should consider ways that landscape choices and impervious surface cover affect city-wide soil C, N, and P storage.     

A sustainable extension package for rural and urban communities: An undertaking in western Sri Lanka

The biggest challenge of agricultural extension in urban communities is how to reach the appropriate target group, because the majority of people are engaged in agricultural production as well as homestead development in a part-time or restricted-time basis, and have different interests. Therefore, an agricultural extension research package, initiated in late 1990, is being tested, with special reference to the horticultural interests of the population in the Western Province. It has three modules: first, dealing with rehabilitation of already existing fruit trees (rambutan, mango) for long-term economic benefits; second, strengthening the income-generating activities at the homestead level, namely leafy vegetable cultivation, value-added products from fruits and vegetables, cultivation of vegetables in pots and hanging baskets, in situ budding, and post-harvest management techniques in fruits, vegetables and flowers; third, the improvement of soil fertility and waste management—particularly soil conservation, compost making, and landscaping techniques. The package integrates traditional and modern extension methods, and at present is still undergoing the implementation process (currently 15% complete). Moreover, it includes a mechanism enabling the mixing of indigenous knowledge and exogenous knowledge by viewing the target group as the subject of the extension process.     

人工封闭对城市土壤功能的影响研究进展

随着全球城市化的快速发展,城市生态系统研究已受到人们的广泛关注。土壤作为城市生态系统的一个重要组成单位与功能载体,其功能与质量已受到城市化的冲击和影响。由人类活动（如房屋建筑、道路建设等）引起的土壤封闭是城市土壤的一个重要特征。与自然土壤封闭相比,人工封闭土壤严重地阻碍了城市土壤与外界环境的物质能量交换,限制了土壤功能的实现,成为导致土壤质量退化的重要因素。研究人工封闭对城市土壤功能的影响有利于更全面认识城市化的生态环境效应。本文介绍了城市土壤人工封闭的概念、主要特点及其与传统自然土壤封闭的异同;综述了人工封闭对城市土壤水分运动、土壤与环境间气体与能量交换、生物多样性与行为以及粮食安全影响等方面取得的研究进展。目前城市封闭土壤研究仍处于起步阶段,仅在个别城市开展过相关研究,且主要围绕人工封闭对城市环境与土壤的表观影响,对封闭后土壤性质的变化及其机制研究仍很缺乏。未来仍需在更多城市开展系统调查以获取基础数据,需着重研究城市封闭土壤中污染物的赋存、迁移、转化,封闭后土壤碳氮固持能力的变化,以及土壤微生物性质的变化,同时要创新研究方式和研究方法,为加强城市生态系统研究、实现城市可持续发展提供科学依据。     

Consistent effects of nitrogen fertilization on soil bacterial communities in contrasting systems

Ecosystems worldwide are receiving increasing amounts of reactive nitrogen (N) through anthropogenic activities. Although the effects of increased N inputs on plant communities have been reasonably well studied, few comparable studies have examined impacts on whole soil bacterial communities, though they play critical roles in ecosystem functioning. We sampled soils from two long-term ecological research (LTER) experimental N gradients, both of which have been amended with NH4NO3; a grassland at Cedar Creek (27 years of N additions) and an agricultural field at Kellogg Biological Station (8 years of N additions). By examining shifts in bacterial communities across these contrasting ecosystem types, we could test competing hypotheses about the direct and indirect factors that might drive bacterial responses to elevated N inputs. Bacterial community structure was highly responsive to N additions. We observed predictable and consistent changes in the structure of the bacterial communities across both ecosystem types. Our results suggest that bacterial communities across these gradients are more structured by N and/or soil carbon availability than by shifts in the plant community or soil pH associated with the elevated nitrogen inputs. In contrast to the pronounced shifts in bacterial community composition and in direct contrast to the patterns often observed in plant communities, increases in N availability did not have consistent effects on the richness and diversity of soil bacterial communities.     

Resilience of Southwestern Amazon Forests to Anthropogenic Edge Effects

Abstract:  Anthropogenic edge effects can compromise the conservation value of mature tropical forests. To date most edge-effect research in Amazonia has concentrated on forests in relatively seasonal locations or with poor soils in the east of the basin. We present the first evaluation from the relatively richer soils of far western Amazonia on the extent to which mature forest biomass, diversity, and composition are affected by edges. In a southwestern Amazonian landscape we surveyed woody plant diversity, species composition, and biomass in 88 × 0.1 ha samples of unflooded forest that spanned a wide range in soil properties and included samples as close as 50 m and as distant as >10 km from anthropogenic edges. We applied Mantel tests, multiple regression on distance matrices, and other multivariate techniques to identify anthropogenic effects before and after accounting for soil factors and spatial autocorrelation. The distance to the nearest edge, access point, and the geographical center of the nearest community ("anthropogenic-distance effects") all had no detectable effect on tree biomass or species diversity. Anthropogenic-distance effects on tree species composition were also below the limits of detection and were negligible in comparison with natural environmental and spatial factors. Analysis of the data set's capacity to detect anthropogenic effects confirmed that the forests were not severely affected by edges, although because our study had few plots within 100 m of forest edges, our confidence in patterns in the immediate vicinity of edges is limited. It therefore appears that the conservation value of most "edge" forests in this region has not yet been compromised substantially. We caution that because this is one case study it should not be overinterpreted, but one explanation for our findings may be that western Amazonian tree species are naturally faster growing and more disturbance adapted than those farther east.     

Pollution indices and sources appointment of heavy metal pollution of agricultural soils near the thermal power plant

Alluvial soils of valleys of the Danube and Mlave rivers represent priority development areas with favorable conditions for life, agriculture and tourism in eastern Serbia. Operation of the thermal power plant Kostolac results in the emission of potentially toxic pollutants into the air, water and land. The goals were to determine the soil pollution with inorganic pollutants using different pollution indices, to identify of the sources of pollutants by means of principal component analysis and the loading of each factor for individual element assessed by multi-linear regression analyses. Chemical characteristics of the studied area resulted in division of the area into four impact zones upon the distance from main pollutants (power plant blocks and ash disposal dumps). There was no established soil pollution with potentially toxic elements in bulk of the agricultural territory. Two principal components (PC1 and PC2) explained about 73% of variance. Three studied elements (As, Cu and Pb) showed anthropogenic origin of their most concentrations in soil, while other elements (Cd, Co, Cr, Ni and Zn) were of a natural (geological) origin. Single pollution index showed moderate pollution level by Ni. Integrated Nemerow pollution index showed low to no pollution levels, indicating slight ecological risk. There were no established limitations for agricultural production in the studied area, except for the only spot polluted by As due to the great flooding event in the studied year.

     

我国几种典型树种非甲烷烃类的排放特征

采用封闭式采样法和带有预浓缩及程序升温装置的熔融毛细管柱气相色谱仪，对我国的松、柏、杨、槐等几种典型树种排放非甲烷烃类（ＮＭＨＣ）的组成和排放速率进行了定性和定量测定，初步确定了不同树种和的特征物种和排放规律，结果表明，针叶树种和阔叶树种排放的ＮＭＨＣ组成差别很大，各树种的排放规律除了与自身的结构和生理活动等在内在因素有关外，还在不同程度上受到外界因素（主要是温度和光强）的影响，一般温度越高，光强     

氮肥对旱地土壤甲烷氧化能力的影响

甲烷是重要的温室气体之一，对全球变暖的贡献率是20％。大气中甲烷浓度的迅速增加与甲烷的源和汇的不平衡有关。土壤中存在甲烷氧化菌，在一定条件下可以氧化大气中的甲烷。不过土壤对甲烷的氧化能力受一些农业生产活动的影响。氮肥的施用对土壤甲烷氧化有一定的影响。长期定位施肥实验的结果表明氮肥对土壤甲烷氧化的影响主要来源于铵态氮而不是硝态氮，因为氨对甲烷氧化有着竞争性抑制作用。此外，长期施用氮肥还改变了土壤微生物的区系及其活性，从而降低甲烷的氧化速率。氮肥施用的短期效应则与土壤的耕作管理历史、土壤性质、氮肥施用量等因素有关。有机肥对土壤甲烷氧化的影响比化肥要低得多，其物理化学性质及施用方法的不同都会影响到土壤对甲烷的氧化。     

免耕和秸秆覆盖对农田土壤温室气体排放的影响

农业土壤是重要的温室气体排放源,各种农业措施对温室气体排放产生重要的影响。免耕和秸秆覆盖作为两种重要的保护性耕作措施正在被越来越广泛的应用,但是其对土壤温室气体排放的影响还不明确,结果存在分歧。通过对免耕和秸秆覆盖措施下农田三种主要的温室气体（CO2、CH4和N2O）排放的相关研究进行对比分析,探讨两种保护性农业措施对温室气体排放的影响。研究表明,免耕减少土壤干扰,增加团聚体的稳定性,有利于难分解碳的形成,减少土壤CO2排放;与常规耕作相比,免耕有利于CH4氧化,增强甲烷氧化菌活性,降低CH4排放;免耕对N2O排放的影响与气候类型和土壤性质有密切的相关关系,在干燥的气候条件下,免耕增加通气条件差的土壤的N2O排放,对通气好的土壤影响不大。而在湿润的气候条件下,不同的土壤性质结论不一致。秸秆覆盖增加土壤CO2排放,并随着秸秆覆盖量的增加而增大;秸秆覆盖对CH4排放的影响有很大的不确定性,与覆盖方式和覆盖秸秆性质有密切联系;大部分研究认为秸秆覆盖增加N2O排放,但也有研究认为秸秆覆盖对N2O排放无影响或降低N2O排放量,秸秆覆盖对N2O排放机理复杂,需要进一步研究。通过综述发现随着保护性农业措施的推广,大量的研究集中在其对作物产量、土壤水分利用率、土壤性质等方面的研究;而保护性农业措施对温室气体排放的研究相对较少,特别是对三种温室气体的综合影响研究并不多见。因此,需结合不同土地类型,开展不同气候类型下免耕和秸秆覆盖对三种主要温室气体排放影响的综合研究,预测增温潜势,为不同气候带保护性农业措施下温室气体排放提供基础数据,并为制定合理的耕作和秸秆覆盖措施提供理论支持。运用同位素示踪等新技术明确秸秆覆盖对温室气体排放的直接和间接贡献率,结合不同研究区?     

辽西大凌河流域土地利用变化及驱动力分析

从政策、流域综合治理、经济发展和技术进步、农民认知态度等4方面对影响大凌河流域土地利用变化的驱动力进行了分析。同时运用农户问卷调查和驱动力分析结果,选取影响耕地变化的社会经济和人口因子,运用主成分分析和多元迭代回归分析确定影响耕地变化的主要因子,并拟合出耕地变化的最优度模型。研究结果表明:在1987—2002年期间,农田和未利用荒地面积在不断减小,而林地、果园、草地在不断增加,但1995年后变化边际度大大减小;主成分分析表明影响土地利用变化主要影响因子是农业人口(A-POP)、总人口(T-POP)、农村经济收入(TIRE)、农林牧渔收入(IAFAF)和第三产业总产值(GTI);多元迭代回归分析表明耕地面积变化的最优回归模型中主变量是农业人口(A-POP)、总人口(T-POP)、农村经济收入(TIRE),这些变量能够解释95.1%的耕地变化。     

Predicting Extinction Risk of Brazilian Atlantic Forest Angiosperms

Understanding how plant life history affects species vulnerability to anthropogenic disturbances and environmental change is a major ecological challenge. We examined how vegetation type, growth form, and geographic range size relate to extinction risk throughout the Brazilian Atlantic Forest domain. We used a database containing species‐level information of 6,929 angiosperms within 112 families and a molecular‐based working phylogeny. We used decision trees, standard regression, and phylogenetic regression to explore the relationships between species attributes and extinction risk. We found a significant phylogenetic signal in extinction risk. Vegetation type, growth form, and geographic range size were related to species extinction risk, but the effect of growth form was not evident after phylogeny was controlled for. Species restricted to either rocky outcrops or scrub vegetation on sandy coastal plains exhibited the highest extinction risk among vegetation types, a finding that supports the hypothesis that species adapted to resource‐limited environments are more vulnerable to extinction. Among growth forms, epiphytes were associated with the highest extinction risk in non‐phylogenetic regression models, followed by trees, whereas shrubs and climbers were associated with lower extinction risk. However, the higher extinction risk of epiphytes was not significant after correcting for phylogenetic relatedness. Our findings provide new indicators of extinction risk and insights into the mechanisms governing plant vulnerability to extinction in a highly diverse flora where human disturbances are both frequent and widespread. Predicción del Riesgo de Extinción de Angiospermas del Bosque Atlántico Brasileño     

密云水库流域植被覆盖度变化对输沙量的影响

封闭流域中,泥沙的产生是多种因素相互作用,相互制约的结果,而在这些众多的环境影响因素中,植被是土壤侵蚀中最重要的环境控制因子,目前,植被覆盖度变化对输沙量的影响一直是区域生态环境研究中比较热门的话题。文章使用遥感(Remote Sensing(RS))、地理信息系统(Geographic Information System(GIS))与统计分析相结合的方法评价了密云水库流域内2个子流域出口处2002年至2005年植被覆盖度变化对输沙量的影响。密云水库流域多为山地,其降雨具有明显的季节性。本文的主要目的在于分析2002年至2005年植被覆盖度变化对流域输沙量的影响,并分析了植被覆盖度变化对气候改变及人类活动的综合影响,结果表明:在密云水库流域内,输沙量是降雨情况和人为因素引起的地表植被覆盖度变化情况的综合反映,人口增长、经济发展和城市化是密云水库流域内引起土地利用变化和地表植被覆盖度变化的主要驱动力。并且,输沙量可以被看作是一个很好的指标来定量分离出生物生理和人为的影响,并从中能够找出在流域生态系统中获得显著结果关键的临界点。研究结果对制定流域的合理开发和管理计划将有所帮助。     

天龙山珍稀植物丽豆(Calophaca sinica)分布区植物群落物种多样性与土壤因子的关系

采用样方法对太原天龙山珍稀濒危植物丽豆(Calophaca sinica)野生种群的生境和群落特征进行调查,应用TWINSPAN分类分析群落多样性.据TWINSPAN分类,将丽豆分布区的植物群落划分为14个群丛类型,丽豆在群落中具有明显的生态优势,并对群落的结构起一定决定作用.研究结果表明,丽豆分布区植物群落的物种多样性指数变化受自然环境、群落特征和人为干扰的综合影响,光照充足、人为干扰小的群丛类型的物种多样性较为丰富,在以丽豆为建群种或优势种的群丛中多样性指数较高,均匀度指数也较大.在丽豆分布区的9个土壤因子之间有6对因子存在显著和极显著的相关性;多样性指数与土壤因子回归分析表明,锌(Zn)与8个群落物种多样性指数之间有显著或极显著的相关性,钾(K)、磷(P)与6个多样性指数之间显著相关,其他土壤因子与多样性指数的相关性均不显著.     

Factors affecting HCH and DDT in soils around watersheds of Beijing reservoirs,China

The factors that influence the dynamics of hexachlorocyclohexane (HCH) and dichlorodiphenyltrichloroethane (DDT) in soils around the watersheds of Beijing reservoirs were examined. Compared with other studies on HCH and DDT in soils and established reference values, the concentrations of HCH and DDT in soils around our study area were relatively low. The relationships between HCH and DDT concentrations and land use, soil texture, and soil properties were discussed. HCH and DDT concentrations were higher in arable soils than those in uncultivated fallow soils. Although land use was the most important factor affecting HCH and DDT residues, additional factors such as soil texture and soil total organic carbon were also involved in pesticide retention in soils. The results indicated that the historical agricultural applications of HCH and DDT were the major source of their residues. Atmospheric deposition, as well as long-distance transportation and inputs from surrounding weathered agricultural soils may also serve as important sources of HCH and DDT residues in the watersheds.     

Coastal flood management in rural planning unit through land-use planning: Kaikhali, West Bengal, India

The Indian subcontinent is highly prone to the detrimental impacts of hazards viz. cyclones, floods and storm surges. Of late, these events have become extreme in nature and intensity. While occurrence and severity of the events is being linked to the phenomenon of climate change, their devastating potentialities are also getting triggered due to lack of resilience and coping capacity of the human community. That in turn depends on distribution of activities over the land i.e. land use pattern, affecting the socio -economic conditions directly. A coastal village often lacks infrastructural support, administrative attention and planning standards compared to a coastal city, thereby making it more vulnerable to disasters like flood. In a coastal city it is easy to govern and manage livelihood as land use depends highly on anthropogenic decisions. While in a coastal village, activities would highly depend on its natural characteristics viz. coastal geomorphology, soil, vegetation cover i.e. governance of livelihood by the eco-system. Hence, managing disaster through in-situ pro-active or developmental measures in a rural planning unit though imperative, is a challenging task. This paper focuses on spatial planning techniques for Restoration of ecological buffers and livelihood enhancement that would sustainably combat the impact of flood at village level in a coastal area. Geographic Information System (GIS) and Remote Sensing (RS) techniques have been used extensively in this study as application tools.     

Detecting Rare Species with Random or Subjective Sampling: a Case Study of Red-Listed Saproxylic Beetles in Boreal Sweden

Abstract:  Efficient sampling design in field studies is important for economical and statistical reasons. We compared two ways to distribute sampling effort over an area, either randomly or subjectively. We searched for red-listed saproxylic (wood-living) beetles in 30 spruce stands in boreal Sweden by sifting wood from dead trees. We randomly selected positions within each stand with a geographic positioning system and sampled the nearest dead tree (random sample). In the same stand we also sampled dead trees that, based on literature, were likely to host such species (subjective sampling). The subjective sampling (two to five samples per stand, depending on stand size) was compared with the higher, random sampling effort (fixed level of 12 samples/stand). Subjective sampling was significantly more efficient. Red-listed species were found in 36% of the subjective samples and in 16% of the random samples. Nevertheless, the larger random effort resulted in a comparable number of red-listed species per stand and in 13 detected species in total (vs. 12 species with subjective sampling). Random sampling was less efficient, but provided an unbiased alternative more suitable for statistical purposes, as needed in, for example, monitoring programs. Moreover, new species-specific knowledge can be gained through random searches.     

湿地碳循环研究综述

湿地由于其巨大的碳库储存能力而成为碳循环研究的热点之一.从湿地CO_2/CH_4释放时空格局,CO_2/CH_4释放影响因子,碳"源""汇"评估及人类活动影响四个方而综述了国内外湿地碳循环方面的研究工作.认为当前对湿地碳排放过程各种潜在的影响因素比较清楚,但碳排放过程各种影响因子之间存在的交互作用有待于进一步深入研究.在进行不同湿地类型碳循环研究的同时,应加强包括微生物、植物根系等地下碳动态研究,加强碳、氮耦合研究.在评估人类活动对湿地碳循环的影响过程中,要综合考虑植被碳库、土壤碳库及土壤碳排的变化.另外,无论从认识不同湿地类型碳过程特征及机理的角度,还是从减少全球或区域碳收支估测不确定性的角度来看,加强数据缺乏地区的湿地类型的碳平衡及相关碳过程的研究都具有重要意义.     

城市绿地土壤呼吸时空变异及其影响因素

2012年7月-2012年12月,采用LI—COR-8100测定了柳树、圆柏和杏树3种北京绿化树木的土壤呼吸速率,并分析了生物因子和非生物因子对土壤呼吸的影响。结果表明：3个树种的土壤呼吸速率平均值为：柳树3．53μmol／（m2·s）,圆柏2．68μmol（m2·s）,杏树2．38μmol／（m2·s）;3种树木土壤呼吸速率呈现相似的月动态,与温度呈极显著指数相关,而与土壤水分相关性不显著。8月柳树和圆柏的土壤呼吸显著高于杏树;9月柳树的土壤呼吸显著高于圆柏和杏树;10—11月3种树木之间差异性不显著。8—9月土壤呼吸速率和温度、树木胸径、总碳、总氮、有机碳及硝态氮显著相关,而与碳氮比、叶面积指数呈极显著负相关。逐步回归分析表明,8—9月间3种树木的土壤呼吸主要受到树木胸径和叶面积指数的影响,模型解释率为42．0％（p=0．001）。