Optimizing passive acoustic sampling of bats in forests

Passive acoustic methods are increasingly used in biodiversity research and monitoring programs because they are cost-effective and permit the collection of large datasets. However, the accuracy of the results depends on the bioacoustic characteristics of the focal taxa and their habitat use. In particular, this applies to bats which exhibit distinct activity patterns in three-dimensionally structured habitats such as forests. We assessed the performance of 21 acoustic sampling schemes with three temporal sampling patterns and seven sampling designs. Acoustic sampling was performed in 32 forest plots, each containing three microhabitats: forest ground, canopy, and forest gap. We compared bat activity, species richness, and sampling effort using species accumulation curves fitted with the clench equation. In addition, we estimated the sampling costs to undertake the best sampling schemes. We recorded a total of 145,433 echolocation call sequences of 16 bat species. Our results indicated that to generate the best outcome, it was necessary to sample all three microhabitats of a given forest location simultaneously throughout the entire night. Sampling only the forest gaps and the forest ground simultaneously was the second best choice and proved to be a viable alternative when the number of available detectors is limited. When assessing bat species richness at the 1-km(2) scale, the implementation of these sampling schemes at three to four forest locations yielded highest labor cost-benefit ratios but increasing equipment costs. Our study illustrates that multiple passive acoustic sampling schemes require testing based on the target taxa and habitat complexity and should be performed with reference to cost-benefit ratios. Choosing a standardized and replicated sampling scheme is particularly important to optimize the level of precision in inventories, especially when rare or elusive species are expected

Auto-generation of passive scalable macromodels for microwave components using scattered sequential sampling

This paper presents a method for automatic construction of stable and passive scalable macromodels for parameterized frequency responses. The method requires very little prior knowledge to build the scalable macromodels thereby considerably reducing the burden on the designers. The proposed method uses an efficient scattered sequential sampling strategy with as few expensive simulations as possible to generate accurate macromodels for the system using state-of-the-art scalable macromodeling methods. The scalable macromodels can be used as a replacement model for the actual simulator in overall design processes. Pertinent numerical results validate the proposed sequential sampling strategy

Scalable macromodelling of microwave system responses using sequential sampling with path-simplexes

A scattered sequential sampling algorithm for the automatic construction of stable and passive scalable macromodels of parameterised system responses with a well-conditioned refinement strategy using path-simplexes is proposed. The method is tailored towards the local scalable macromodelling schemes on scattered grids. A pertinent numerical example validates the proposed approach

Calibration of polyurethane foam (PUF) disk passive air samplers for quantitative measurement of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs): Factors influencing sampling rates.

PUF disk passive air samplers are increasingly employed for monitoring of POPs in ambient air. In order to utilize them as quantitative sampling devices, a calibration experiment was conducted. Time integrated indoor air concentrations of PCBs and PBDEs were obtained from a low volume air sampler operated over a 50d period alongside the PUF disk samplers in the same office microenvironment. Passive sampling rates for the fully-sheltered sampler design employed in our research were determined for the 51 PCB and 7 PBDE congeners detected in all calibration samples. These values varied from .57 to 1.55m(3)d(-1) for individual PCBs and from 1.1 to 1.9m(3)d(-1) for PBDEs. These values are appreciably lower than those reported elsewhere for different PUF disk sampler designs (e.g. partially sheltered) employed under different conditions (e.g. in outdoor air), and derived using different calibration experiment configurations. This suggests that sampling rates derived for a specific sampler configuration deployed under specific environmental conditions, should not be extrapolated to different sampler configurations. Furthermore, our observation of variable congener-specific sampling rates (consistent with other studies), implies that more research is required in order to understand fully the factors that influence sampling rates. Analysis of wipe samples taken from the inside of the sampler housing, revealed evidence that the housing surface scavenges particle bound PBDEs

Sampling and analysis of chlorpyrifos airborne residue emitted under treated field conditions

Ambient air sampling on 12-hour daytime before and immediately after chlorpyrifos application using mist-blower (Solo 412) was done by passive air sampling (cotton gauze, cellulose filter and PUF) and active sampling (PUF plug and quartz filter cartridges). During spray application, sampling was also done in the air at operator breathing zone through active samplers. Samples were analysed by gas chromatography with micro electron-capture detection (GC-ʮECD) with full method validation under laboratory conditions. In the study, pre-spray measurements showed no detection of chlorpyrifos level both in active and passive air samplings. In post-spray measurements, PUF passive samplers recorded the highest level of residue detection in both post-spray sampling events in comparison to cellulose and cotton gauze. In active sampling, chlorpyrifos was detected only on PUF plug samples revealing the fact that chlorpyrifos are partitioned in the air as vapour rather than particles. The highest measured concentrations were recorded during spraying period, and then sharply declined in the post-spray periods with the passage of time. Paired comparison of performance between passive and active sampling methods in terms of residue uptake showed that passive sampling showed better performance than active sampling in this study

NORMAN interlaboratory study (ILS) on passive sampling of emerging pollutants;

Passive samplers can play a valuable role in monitoring water quality within a legislative framework such as the European Union’s Water Framework Directive (WFD). The time-integrated data from these devices can be used to complement chemical monitoring of priority and emerging contaminants which are difficult to analyse by spot or bottle sampling methods, and to improve risk assessment of chemical pollution. In order to increase the acceptance of passive sampling technology amongst end users and to gain further information about the robustness of the calibration and analytical steps, several inter-laboratory field studies have recently been performed in Europe. Such trials are essential to further validate this sampling method and to increase the confidence of the technological approach for end users. An inter-laboratory study on the use of passive samplers for the monitoring of emerging pollutants was organised in 2011 by the NORMAN association (Network of reference laboratories for monitoring emerging environmental pollutants; www.norman-network.net ) together with the European DG Joint Research Centre to support the Common Implementation Strategy of the WFD. Thirty academic, commercial and regulatory laboratories participated in the passive sampler comparison exercise and each was allowed to select their own sampler design. All the different devices were exposed at a single sampling site to treated waste water from a large municipal treatment plant. In addition, the organisers deployed in parallel for each target analyte class multiple samplers of a single type which were subsequently distributed to the participants for analysis. This allowed an evaluation of the contribution of the different analytical laboratory procedures to the data variability. The results obtained allow an evaluation of the potential of different passive sampling methods for monitoring selected emerging organic contaminants (pharmaceuticals, polar pesticides, steroid hormones, fluorinated surfactants, triclosan, bisphenol A and brominated flame retardants). In most cases, between laboratory variation of results from passive samplers was roughly a factor 5 larger than within laboratory variability. Similar results obtained for different passive samplers analysed by individual laboratories and also low within laboratory variability of sampler analysis indicate that the passive sampling process is causing less variability than the analysis. This points at difficulties that laboratories experienced with analysis in complex environmental matrices. Where a direct comparison was possible (not in case of brominated flame retardants) analysis of composite water samples provided results that were within the concentration range obtained by passive samplers. However, in the future a significant improvement of the overall precision of passive sampling is needed. The results will be used to inform EU Member States about the potential application of passive sampling methods for monitoring organic chemicals within the framework of the WFD.JRC.H.1 - Water Resource