Use of Descriptors of Ecosystem Functioning for Monitoring a National Park Network: A Remote Sensing Approach

Baseline assessments and monitoring of protected areas are essential for making management decisions, evaluating the effectiveness of management practices, and tracking the effects of global changes. For these purposes, the analysis of functional attributes of ecosystems (i.e., different aspects of the exchange of matter and energy) has advantages over the traditional use of structural attributes, like a quicker response to disturbances and the fact that they are easily monitored through remote sensing. In this study, we described the spatiotemporal patterns of different aspects of the ecosystem functioning of the Spanish national parks and their response to environmental changes between 1982 and 2006. To do so, we used the NOAA/AVHRR-GIMMS dataset of the Normalized Difference Vegetation Index (NDVI), a linear estimator of the fraction of photosynthetic active radiation intercepted by vegetation, which is the main control of carbon gains. Nearly all parks have significantly changed during the last 25 years: The radiation interception has increased, the contrast between the growing and nongrowing seasons has diminished, and the dates of maximum and minimum interception have advanced. Some parks concentrated more changes than others and the degree of change varied depending on their different environmental conditions, management, and conservation histories. Our approach identified reference conditions and temporal changes for different aspects of ecosystem functioning, which can be used for management purposes of protected areas in response to global changes.     

Social Learning Through Evaluation: A Case Study of Overcoming Constraints for Management of Dryland Salinity

Conventional approaches to evaluation of environmental programs have tended to limit themselves to restricted measures of program effectiveness. This paper shows how a social learning approach can be incorporated into evaluating public environmental programs. A social learning approach is particularly suited to complex environmental challenges which are inherently difficult to understand, predict, and manage, thus complicating the evaluation process. The paper presents an Australian case study of dryland salinity management where there are major knowledge barriers impeding conventional management techniques. The research presented in this paper focused on evaluating a public demonstration program to track its impact through its design, implementation, and monitoring phases. The paper shows that, by incorporating social learning principles and practices, program evaluation can promote collective action, critical reflection, and increased knowledge to underpin improved environmental management.     

Species-specific and context-dependant disruption of temporal population fluctuations resulting from hypereutrophication events

This study quantifies the disruption of zooplankton population fluctuations in relation to two magnitudes of fire retardant contamination events using artificial ponds as model systems. Population time series were analysed using redundancy analysis where time was modelled with a principal coordinate of neighborhood matrices approach that identified relevant scales of fluctuation frequencies. Analyses of temporal coherence provided insight whether population fluctuations correlated with system intrinsic or extrinsic forces. Responses to stress were species-specific and context-dependant. Contamination changed temporal structure in some species. These alterations were associated with an increased intrinsic control of dynamics. In some cases the magnitude of impact was unrelated to contamination severity. Some populations were less tolerant of pollution in the low relative to the high concentration treatment. Results suggest that population-level monitoring of degraded sites may be suboptimal because disparate population responses complicate the selection of specific sentinel organisms to monitor stress.     

Substance-related environmental monitoring

Background  Due to the requirements of the EU Water Framework Directive and other legal regulations (e.g., national laws like the German Federal Soil Protection Act), but also due to the implementation of the new EU chemicals management system REACH, environmental monitoring will gain increasing importance for the surveillance of environmental quality as well as for the assessment of chemicals. Against this background, the Work Group on ‘Environmental Monitoring’ of the Division of ‘Environmental Chemistry and Ecotoxicology’ within the German Chemical Society has compiled a position paper on substance-related environmental monitoring. Scope  Core elements of this position paper are the definitions of important terms like monitoring, exposure monitoring, effect monitoring, and integrated monitoring. Moreover, temporal and spatial aspects (monitoring of spatial distributions, trend monitoring, and retrospective monitoring) and their applications are discussed. The main focus of this position paper is the coverage of aspects which have to be observed for the preparation and implementation of a monitoring program. Essential is the clear specification of the targets of the monitoring which determine the development of the monitoring concept and its realization, e.g., if environmental media (compartments) or organisms are most appropriate as samples for the aim of the study. Of course, also the properties of the target substances are important (e.g., lipophilicity/bioaccumulation as pre-requisite for an exposure monitoring with organisms). Finally, the monitoring phases of sample planning, sampling, storage and transport of samples, selection of analytical methods, quality assurance measures as well as reporting are discussed. Perspectives  An important issue for the future is to link the quantification of chemicals in environmental compartments (exposure and pollution monitoring) more closely to the study of biological effects (effect monitoring) than has been the case up to now. Furthermore, by inclusion of a spatial differentiation, a comprehensive evaluation of the state of an ecosystem can be obtained and the relevance of the results improved. Practical examples of monitoring studies which illustrate various aspects covered in this position paper will be presented in a series of publications by members of the Work Group in the following issues of this journal.

基于神经网络的城市夜间环境监控与预测

因夜间天空亮度分布具有非线性变化特点,故引入神经网络算法,建立基于时间序列的夜天空亮度预测模型,夜天空亮度预测模型可为城市光污染防治提供评价依据.文章对神经网络的原理进行了论述,建立了基于时间序列预测模型.以测试数据为训练样本集,基于MATLAB(矩阵实验室,Matrix Laboratory的简称),采用改进的BP算法(误差反向传播算法)对网络进行学习训练,并对存在的误差进行了分析.基于时间序列BP神经网络的夜天空预测模型,当隐含层神经元数目为5,训练函数为L-M优化算法(trainlm)时,最大绝对误差可达到0.003 6 cd/m2,最大相对误差达到2.361 4%.结果表明,模型的运行结果与试验数据比较吻合,输出与目标矢量之间相关性也较好.     

细菌在近海污染监测及评价中的应用研究

通过对天津渤海湾的三个河流入海口(青静黄排水河、独流减河和海河),不同季节实地采集的水样中微生物数量及理化因子如温度、盐度、溶解氧(DO)、化学需氧量(COD)、无机氮等的研究,发现细菌指标与理化指标对污染指示结果有一定的相似性,都指示青静黄排水河河口污染较严重.利用SPSS软件的相关性分析方法对实验结果进行分析,发现水环境中细菌指标与理化因子具有一定的相关性.其中异养菌数与COD呈显著正相关性(P<0.05),与DO呈负相关性(P=0.051);大肠菌群数与理化因子DO呈极显著负相关关系(P<0.01),与COD呈正相关关系(P=0.061),与NO3-N,盐度呈负相关性(P>0.05).其他细菌指标与各理化因子也存在一定的相关性,但不明显.     

Estimating pesticide runoff in small streams

Surface runoff is one of the most important pathways for pesticides to enter surface waters. Mathematical models are employed to characterize its spatio-temporal variability within landscapes, but they must be simple owing to the limited availability and low resolution of data at this scale. This study aimed to validate a simplified spatially-explicit model that is developed for the regional scale to calculate the runoff potential (RP). The RP is a generic indicator of the magnitude of pesticide inputs into streams via runoff. The underlying runoff model considers key environmental factors affecting runoff (precipitation, topography, land use, and soil characteristics), but predicts losses of a generic substance instead of any one pesticide. We predicted and evaluated RP for 20 small streams. RP input data were extracted from governmental databases. Pesticide measurements from a triennial study were used for validation. Measured pesticide concentrations were standardized by the applied mass per catchment and the water solubility of the relevant compounds. The maximum standardized concentration per site and year (runoff loss, R_Loss) provided a generalized measure of observed pesticide inputs into the streams. Average RP explained 75% (p < 0.001) of the variance in R_Loss. Our results imply that the generic indicator can give an adequate estimate of runoff inputs into small streams, wherever data of similar resolution are available. Therefore, we suggest RP for a first quick and cost-effective location of potential runoff hot spots at the landscape level.     

Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.     

Pilot survey of a broad range of priority pollutants in sediment and fish from the Ebro river basin (NE Spain)

Priority organic pollutants were investigated in sediments and fish collected along the Ebro river basin (NE Spain) to evaluate their occurrence, transport and bioavailability. Sediments were collected in 18 sites and two species of fish were captured in nine sites according to the availability in each area. The sampling sites covered industrial, urban and agricultural areas. Four methods were used to detect 20 organochlorine compounds (OCs), 8 polycyclic aromatic hydrocarbons, 3 organotin compounds, 2 alkylphenols and 40 polybrominated diphenyl ethers (PBDEs) from purified extracts. The contamination pattern was site specific and no downstream increase in concentration of pollutants was observed but rather a generalized low level diffuse pollution. Target compounds were detected in sediments at 0.01 to 2331 microg/kg dry weight, and only OCs and PBDEs were accumulated in benthopelagic fish. Toxicological assessment was performed according to predicted environmental levels and revealed sites where adverse effects could occur.     

Biological effect monitoring in dab (<Emphasis Type="Italic">Limanda limanda</Emphasis>) using gene transcript of CYP1A1 or EROD—a comparison

BACKGROUND, AIM, AND SCOPE: Gene expression analyses with real-time (RT)-polymerase chain reaction (PCR) gains importance in marine monitoring. This new technique has to be compared to the classical approaches like the well known biomarker ethoxyresorufin-O-deethylase (EROD) to test their suitability for monitoring programmes. The goal of the present study is to compare EROD activity and CYP1A1 mRNA expression in the important monitoring fish species dab (Limanda limanda) and to answer the question of whether these parameters reflect the polycyclic aromatic hydrocarbon (PAH) contamination of the fish. Further on, glyceraldehyd-3-phosphate dehydrogenase (GAPDH) was investigated as a potential housekeeping gene. MATERIALS AND METHODS: Female dab were caught in the summer of 2004 in the North Sea and in the Baltic. EROD activity was determined in liver samples by a kinetic fluorimetric assay according to a standard protocol. The gene expression of CYP1A (cytochrome P450 1A) and GAPDH were determined by means of RT-PCR. Results were compared to gonado somatic index and to the concentration of PAH metabolite 1OHPyr (1-hydroxypyrene) analysed in the bile fluids of the fish, respectively. RESULTS: Dab from all stations showed a considerable individual variation in the levels of both CYP1A mRNA and EROD. Highest mean values for CYP1A mRNA and EROD were detected in the northern part of the sampling area. In contrast, the PAH metabolite 1OHPyr was found at the highest concentration in fish caught near the German coast. CYP1A mRNA and EROD showed only a minor but significant correlation (r = 0.32, p < 0.05, n = 123). 1OHPyr in bile correlated significantly (p < 0.05) with the amount of GAPDH mRNA content in the liver. DISCUSSION: The significant but low correlation of CYP1A mRNA and EROD activity on an individual basis illustrates that these two parameters are apparently not closely linked. However, maximum EROD values correspond with maximum CYP1A mRNA concentrations when station means are regarded. Because EROD and CYP1A mRNA in dab follow different physiological principles, their application will lead to related but not identical monitoring results. This should be taken into account when future marine monitoring programmes are designed. The results also indicate that PAH are not the crucial factor for CYP1A and EROD levels in dab from the off-shore areas in the North Sea. This is remarkable because the PAH metabolism is known to be CYP1A-dependent and the widely used biomarker EROD has been recommended for monitoring PAH-related effects in fish from the North Sea. Due to a correlation between GAPDH and 1OHPyr, GAPDH was not suitable as housekeeping gene for dab. CONCLUSIONS: Neither the results from EROD nor from CYP1A1 mRNA measurements in dab reflected their exposure to PAH as measured by the PAH metabolite 1OHPyr. Thus, the question arises of whether EROD or CYP1A mRNA is a suitable biomarker at all to indicate PAH exposure in dab from the open North Sea. RECOMMENDATIONS AND PERSPECTIVES: For future biological effect monitoring, it is advisable to measure more and predominately independent parameters by RT-PCR and to incorporate more components of the detoxification system.