A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

科学的挑战--重视成本效益,清洁波罗的海

波罗的海是世界上受人类活动影响最严重的海洋之一,虽然有减少向波罗的海排放营养物质的国际协议,但迄今为止采取的措施,既没有从根本上减少营养物质的排放,也没有促进环境的改善.部分原因可以归咎为缺少有关物理学、生物地球化学和生态特性之间大尺度关系和相互作用的知识,但是还缺少全流域范围的成本效益分析.错误的决策非常危险,例如,执行的减少排放的方案根本没有效果,或远远达不到成本效益.许多学科的研究者正面临着一个共同的挑战开发一个决策支持系统,作为整个波罗的海成本效益分析法的科学基础.研究项目海洋富营养化的研究(MARE)(http∥www.mare.su.se)正致力于这方面的研究.     

近期和长远时段内北极生态系统结构受到的影响

生物在物种水平上对全球气候变暖和紫外线B(UV-B)辐射增强的反应受到其群落内其他物种以及生态系统内养分循环的调节,所有的这些反应将会导致生态系统结构的变化.根据高纬度地区坏境因子的可能变化而做的控制试验表明,由夏季变暖而引起苔原植被的变化要小于增加施肥而引起的变化,试验涉及的某些环境因子对北极生态系统的结构有非常强烈地影响,但是这些影响因地区而异,观测结果表明,处于最寒冷地区的植物群落和无脊椎动物群落对全球气候变暖和紫外线B辐射的增强反应最为强烈.尽管微生物量和养分储存量相对稳定,北极无脊椎动物群落还是很可能会对全球变暖产生迅速的反应.试验结果显示,加强紫外线B辐射会改变革兰氏阴性细菌和真菌的群落组成结构,但不会对植物群落的组成产生影响.由夏季气温升高而提高的植物生产力将会控制食物网的动态变化,以苔原植被和亚极地森林植物为基础的食物网中的营养流动会明显地影响到几种优势动物种群数量的周期性波动,在某些年分这些动物的种群数量会达到峰值.小型啮齿动物和食叶昆虫如秋毛虫种群数量的周期性变化则会影响苔原和森林苔原植物的组成结构和多样性,同时也会影响到一些专性捕食者和寄生虫的变化.在暖冬,雪表形成冰壳可能会减少旅鼠的植物食物来源,然而较深的雪也可以使它们免受雪地表面上捕食者对它们的捕食.在芬诺斯堪的亚地区,已有证据表明小型啮齿类动物群落结构和种群动态的显著变化会导致专门以小型啮齿类动物为食物的捕食者的数量减少.气候还可能改变昆虫在白桦森林生态系统中的作用,因为暖冬可以增加这些昆虫卵的成活率,并且扩大其分布范围.此外,在夏季困扰驯鹿的昆虫会由于夏季气候的变暖而扩大其分布范围、增加种群数量并且种群更为活跃;同时在另一方面也会对驯鹿不利,即那些昔日驯鹿/北美驯鹿的避难场所--冰川和未融的成片的雪--在这样温暖的夏季则可能会消失.     

近期和长远时段内北极生态系统功能受到的影响

长期以来,就营养物质和碳循环而言,北极生态系统降低了初级生产力；能量,水和温室气体交换的水平已引起了局部和区域性的小幅度降温.大气CO2中的碳沉积在广袤而寒冷的有机土壤中,冰雪覆盖的低矮植被产生高的反射率,都影响了局部气候.然而,北极生态系统功能的许多方面都对气候变化及其产生的生物多样性影响敏感.当前的北极气候导致了低的有机物质分解速率,因此,尽管有机物和元素输入量较低,但北极生态系统还是趋向于积累有机物和元素,土壤中氮和磷等可利用元素结果成为促进碳固定以及生物量和有机物进一步积累的关键性限制因素.气候变暖可能增加特别是土壤中的碳和元素的周转,起初可能导致元素的丢失,但最后会慢慢的恢复.在北极生态系统中,单个物种和物种多样性已经明显地影响了元素的输入和滞留,另一方面,从长远来看,尽管CO2和紫外线增加对植物组织化学、分解和氮固定的影响可能变得重要,但对整个生态系统来说,影响可能很小.碳循环的示踪气体主要形式是CO2和CH4,大多数碳以CO2的形式损失,这些CO2是由植物和土壤生物产生.来自潮湿苔原生态系统以CH4形式释放的碳大约是CO2形式的5％,而且在没有任何其他变化的情况下,对变暖作出响应.冬天过程和植物类型也影响CH4释放和能量在生物圈和大气之间的交换,因为反射率从冬末到夏天存在很大的变化,在冬末,雪反射了入射的大部分光线,在夏天,生态系统吸收了入射的大部分光线,所以在所有的陆地生态系统中,北极生态系统在能量交换方面表现出巨大的季节性变化.植被深刻地影响北极生态系统水和能量交换.在冰雪覆盖期间,反射率从苔原、森林苔原、落叶林、常绿林依次降低.灌木和树增加了雪的深度,反过来又使冬天的土壤温度增加,因此,由气候变化而引起的未来植被方面的变化很可能深远地改变区域的气候.     

Chemical Composition and Acidity of Rain at the Gulf of Iskenderun,North-East Mediterranean

The purpose of the present work was to investigate the chemistry of rain in the Gulf of Iskenderun, North East Mediterranean, Turkey. The Gulf region has a large number of industries. Main industries existing in the region are iron and steel works, fertilizer plants, a cement plant, and several medium and mini size steel mills in addition to the international pipe line terminals. This study aims to apportion the local sources contributing to the overall pollution of the region. To this end a precipitation sampling program was started in January 2000, and over 48 precipitation samples were collected from each of 5 stations located at Iskenderun city center, Iskenderun industrial zone, Payas city center, the campus of Iskenderun Technical College and the campus of Mustafa Kemal University. Samples were analysed for pH, NO₃ ⁺, Cl^-. Ca, Al, Ba, Na, Cd, Co, Cr, Cu, Pb, Li, Mg, Mn, Ni, Zn, Fe, K. Concentrations of metal ions were determined by ICP-AES. NO₃ ^- ions and pH were determined by using NO₃ ^- selective electrode and pH meter, respectively.pH values of the collected samples at the industrial zone and at Payas city center, ranged between 5.02 and 7.38, respectively. NO₃ ^- and metal ions concentrations were highly variable. Concentrations of Ca and Fe ions were higher in the industrial zone and Payas city center. In the other three stations, concentrations of metal ions and NO₃ ^- ion were lower than that of industrial zone and the values of pH ranged between 6 and 7.4. The average pH values at Iskenderun Gulf showed that the precipitation was not acidic, because of the high concentration of Ca. The highest concentrations of Na and Cl ions were recorded in the University campus because the campus is located by the Mediterranean Sea.     

Information Network Topologies for Enhanced Local Adaptive Management

We examined the principal effects of different information network topologies for local adaptive management of natural resources. We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states: one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers lose their capacity to reorganize back to the desired state. An erratum to this article can be found at .     

Mineral contents and proximate composition of Pistacia vera kernels

The mineral contents of Pistacia vera kernels were determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The minimum and maximum values of K, P, Ca, Mg, and S elements ranged from 6,333 to 8,064 mg/kg, 3,630 to 5,228 mg/kg, 1,614 to 3,226 mg/kg, 1,716 to 2,402 mg/kg, and 1,417 to 1,825 mg/kg, respectively. In addition, the mean values of Fe, Zn, Cu, Mn, B, Mo, Cr and Ni elements were determined as 42.48, 20.52, 12.81, 7.48, 11.31, 0.106, 0.511 and 1.67 mg/kg, respectively. Ash levels of kernels were found between 2.28 % (Urfa) and 2.79 % (Halebi). In addition, crude oil and protein contents were determined between 48.8 % (Halebi) to 55.3 % (Siirt) and 23.33 % (Uzun) to 27.16 % (Halebi), respectively.