Attributes of reliable long-term landscape-scale studies: Malpractice insurance for landscape ecologists

Monitoring long-term change in forested landscapes is an intimidating challenge with considerable practical, methodological, and theoretical limitations. Current field approaches used to assess vegetation change at the plot-to-stand scales and nationwide forest monitoring programs may not be appropriate at landscape scales. We emphasize that few vegetation monitoring programs (and, thus, study design models) are designed to detect spatial and temporal trends at landscape scales. Based primarily on advice from many sources, and trial and error, we identify 14 attributes of a reliable long-term landscape monitoring program: malpractice insurance for landscape ecologists. The attributes are to: secure long-term funding and commitment; develop flexible goals; refine objectives; pay adequate attention to information management; take an experimental approach to sampling design; obtain peer-review and statistical review of research proposals and publications; avoid bias in selection of long-term plot locations; insure adequate spatial replication; insure adequate temporal replication; synthesize retrospective, experimental, and related studies; blend theoretical and empirical models with the means to validate both; obtain periodic research program evaluation; integrate and synthesize with larger and smaller scale research, inventory, and monitoring programs; and develop an extensive outreach program. Using these 14 attributes as a guide, we describe one approach to assess the potential effect of global change on the vegetation of the Front Range of the Colorado Rockies. This self-evaluation helps identify strengthes and weaknesses in our program, and may serve the same role for other landscape ecologists in other programs.     

Establishing a standard Sonoran Reference Plant and its application in monitoring industrial and urban pollution throughout the Sonoran Desert

Using analyses from honey mesquite (Prosopis glandulosa) leaves from nearly pristine locations in Arizona, an inorganic plant concentration standard is proposed for use as a Sonoran Reference Plant (SRP). Such a standard can be used as a monitoring device for different anthropogenic pollution sources throughout the Sonoran Desert. To test the application of the SRP, honey mesquite leaves were collected at different sites in southern Arizona and their chemical fingerprints compared to SRP. Sources of element origin were identified through factor analysis and correlation matrices. A terrestrial factor was found in leaves from all sites. Anthropogenic factors varied for different sites. Mesquite leaves accumulated significant amounts of elements originating from copper smelters (As, Sb) and urban pollution (La, Sm, Ce, V). These pollutants are small-sized and have been linked to human lung diseases. Mesquite is a deciduous tree; the yearly comparison of mesquite leaf element concentration spectra to the SRP standard can be used to determine seasonal improvement or deterioration of environmental quality in a particular area.     

Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.     

Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

High frequency monitoring of the coastal marine environment using the MAREL buoy

The MAREL Iroise data buoy provides physico-chemical measurements acquired in surface marine water in continuous and autonomous mode. The water is pumped 1.5 m from below the surface through a sampling pipe and flows through the measuring cell located in the floating structure. Technological innovations implemented inside the measuring cell atop the buoy allow a continuous cleaning of the sensor, while injection of chloride ions into the circuit prevents biological fouling. Specific sensors for temperature, salinity, oxygen and fluorescence investigated in this paper have been evaluated to guarantee measurement precision over a 3 month period. A bi-directional link under Internet TCP-IP protocols is used for data, alarms and remote-control transmissions with the land-based data centre. Herein, we present a 29 month record for 4 parameters measured using a MAREL buoy moored in a coastal environment (Iroise Sea, Brest, France). The accuracy of the data provided by the buoy is assessed by comparison with measurements of sea water weekly sampled at the same site as part of SOMLIT (Service d'Observation du Milieu LIToral), the French network for monitoring of the coastal environment. Some particular events (impact of intensive fresh water discharges, dynamics of a fast phytoplankton bloom) are also presented, demonstrating the worth of monitoring a highly variable environment with a high frequency continuous reliable system.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Benchmarking for best practice environmental management

Benchmarking of environmental performance to demonstrate theachievement of best practice environmental management is acomponent of a new form of licensing of industrialdischarges in Western Australia. The paper describes theapproaches to benchmarking for the critical environmentalissues for an alumina refinery and wastewater treatmentplant. It also describes the lessons learnt from thebenchmarking process on appropriate methods, the benefitsand difficulties in the benchmarking process, and changesthat would assist benchmarking for best practiceenvironmental management.     

Bioindicator organisms: Heavy metal pollution evaluation in the Ionian Sea (Mediterranean Sea—Italy)

Trace metal concentrations of mercury, cadmium, lead and chromium in Patella caerulea, and Mullus barbatus were investigated to provide information on pollution of Ionian Sea, since these metals have the highest toxic potential. High chromium levels (0.47–0.97 g g^–1 ww) were registered in limpet samples collected from two station near the Gulf of Taranto, while elevated concentration of mercury (0.31–1.50 g g^–1 ww) were found in mullet specimens from Sicily. The metal concentrations recorded at the clean stations may be considered as useful background levels to which to refer for comparison within the Mediterranean area. On the contrary, the high levels of chromium and mercury found respectively in the areas near the Gulf of Taranto and at Capo Passero being of concern in terms of environmental health need frequent monitoring.     

Monitoring of Butter and Ghee (Clarified Butter Fat) for Pesticidal Contamination from Cotton Belt of Haryana, India

Butter (45) and ghee (55) samples were collected from rural and urban areas of cotton growing belt of Haryana and analysed for detecting the residues of organochlorine, synthetic pyrethroid and organophosphate insecticides. The estimation was carried out by using multi residue analytical technique employing GC-ECD and GC-NPD systems equipped with capillary columns. Butter samples were comparatively more contaminated (97%) than ghee (94%), showing more contamination with organochlorine insecticides from urban samples. About 11% samples of butter showed endosulfan residues above MRL value and 2% samples had residues of synthetic pyrethroids and organophosphates each above their respective MRL values. In ghee, residues of HCH & DDT both and of endosulfan exceeded the MRL values in 5 and 20% samples, respectively. Among organophosphates, only chlorpyriphos was detected with 9% samples showing its residue above MRL value. Irrespective of contamination levels, residues above the MRL values were more in ghee. More extensive study covering other agricultural regions/zones of Haryana has been suggested to know the overall scenario of contamination of milk products.