Sampling harmful benthic dinoflagellates: Comparison of artificial and natural substrate methods

This study compared two collection methods for Gambierdiscus and other benthic harmful algal bloom (BHAB) dinoflagellates, an artificial substrate method and the traditional macrophyte substrate method. Specifically, we report the results of a series of field experiments in tropical environments designed to address the correlation of benthic dinoflagellate abundance on artificial substrate and those on adjacent macrophytes. The data indicated abundance of BHAB dinoflagellates associated with new, artificial substrate was directly related to the overall abundance of BHAB cells on macrophytes in the surrounding environment. There was no difference in sample variability among the natural and artificial substrates. BHAB dinoflagellate abundance on artificial substrates reached equilibrium with the surrounding population within 24 h. Calculating cell abundance normalized to surface area of artificial substrate, rather than to the wet weight of macrophytes, eliminates complications related to the mass of different macrophyte species, problems of macrophyte preference by BHAB dinoflagellates and allows data to be compared across studies. The protocols outlined in this study are the first steps to a standardized sampling method for BHAB dinoflagellates that can support a cell-based monitoring program for ciguatera fish poisoning. While this study is primarily concerned with the ciguatera-associated genus Gambierdiscus, we also include data on the abundance of benthic Prorocentrum and Ostreopsis cells.     

Validation of the detection of Pseudo-nitzschia spp. using specific RNA probes tested in a microarray format: Calibration of signal based on variability of RNA content with environmental conditions

Harmful algal blooms (HAB) occur worldwide and cause health problems and economic damage to fisheries and tourism. Monitoring for toxic algae is therefore essential but is based primarily on light microscopy, which is time consuming and can be limited by insufficient morphological characters such that more time is needed to examine critical features with electron microscopy. Monitoring with molecular tools is done in only a few places world-wide. EU FP7 MIDTAL (Microarray Detection of Toxic Algae) used SSU and LSU rRNA genes as targets on microarrays to identify toxic species. In order to comply with current monitoring requirements to report cell numbers as the relevant threshold measurement to trigger closure of fisheries, it was necessary to calibrate our microarray to convert the hybridisation signal obtained to cell numbers. Calibration curves for two species of Pseudo-nitzschia for use with the MIDTAL microarray are presented to obtain cell numbers following hybridisation. It complements work presented by Barra et al. (2012b. Environ. Sci. Pollut. Res. doi: 10.1007/s11356-012-1330-1v) for two other Pseudo-nitzschia spp., Dittami and Edvardsen (2012a. J. Phycol. 48, 1050) for Pseudochatonella, Blanco et al. (2013. Harmful Algae 24, 80) for Heterosigma, McCoy et al. (2013. FEMS. doi: 10.1111/1574-6941.12277) for Prymnesium spp., Karlodinium veneficum, and cf. Chatonella spp. and Taylor et al. (2014. Harmful Algae, in press) for Alexandrium.     

River Restoration in Victoria, Australia: Change is in the Wind, and None too Soon

Stream restoration has become a multibillion dollar industry worldwide, yet there are few clear success stories and the scientific basis for effective stream restoration remains uncertain. We compiled data on completed river restoration projects from four management authorities in Victoria, Australia, to examine how the available data could inform the science of restoration ecology in rivers, and thus improve future restoration efforts. We found that existing data sources are limited and much historical information has been lost through industry restructuring and poor data archiving. Examining records for 2,247 restoration projects, we found that riparian management projects were the most common, followed by bank stabilization and in‐stream habitat improvement. Only 14% of the project records indicated that some form of monitoring was carried out. It is evident that overall there is little scientific guidance and little or no monitoring and evaluation of the projects for which we had information. However, recent advances with mandatory, statewide reporting and an increased emphasis on project design and monitoring strongly suggest that the design, implementation, monitoring, and reporting of stream restoration projects have improved in recent years and will continue to do so.     

Distribution and Recent Reduction of Gelidium Beds in Toyama Bay, Japan

The distribution and recent reduction of Gelidium beds, i.e. mat-like beds dominated by the agarophyte G. elegans Kützing in Toyama Bay (Sea of Japan), in which 95% of the coastline is protected artificially, are reported. Gelidium beds were common in shallow waters (usually < 10 m deep); most of the large beds (> 1 ha) were restricted to the inner coasts of the bay. In calm and eutrophic areas, however, G. elegans was heavily colonized by epiphytes. In the last decade, two beds were buried in situ and beds in their vicinity were damaged by the stagnation of coastal water and/or sedimentation by silts which accompanied land reclamation. At the other two beds monitored since 1988, Gelidium declined a few times but most prominently in 1998, when episodic long summer rain was recorded. This is the first report, not only on the current status of Gelidium beds other than for the central Pacific Coast of Honshu in Japan, but also concerning reduction of the beds caused by both anthropogenic and natural events.     

Spotlight surveys for white-tailed deer: Monitoring panacea or exercise in futility?

Many monitoring programs for white-tailed deer (Odocoileus virginianus) on both private and public lands across the United States have long relied on the use of road-based spotlight surveys for monitoring population size and trends. Research has suggested spotlight surveys are ineffective and that road-based surveys for deer are biased because of highly variable detection rates. To evaluate variability in detection rates relative to the assumption that repeated surveys along roads will provide reliable trend data for use in calculating deer density estimates, we collected 5 years of thermal-imager and spotlight survey data using a multiple-observer, closed-capture approach. Using a Huggin's closed capture model, data bootstrapping, and variance components analyses, our results suggest that density estimates for white-tailed deer generated from data collected during road-based spotlight surveys are likely not reflective of the standing deer population. Detection probabilities during individual spotlight surveys ranged from 0.00 to 0.80 (median = 0.45) across all surveys, and differed by observer, survey, management unit, and survey transect replicate. Mean spotlight detection probability (0.41) and process standard deviation (0.12) estimates indicated considerable variability across surveys, observers, transects, and years, which precludes the generation of a correction factor or use of spotlight data to evaluate long-term trends at any scale. Although recommended by many state, federal, and non-governmental agencies, our results suggest that the benefit of spotlight survey data for monitoring deer populations is limited and likely represents a waste of resources with no appreciable management information gained. © 2012 The Wildlife Society.     

Circadian Rhythm of Blood Pressure Challenges Office Values as the “Gold Standard” in the Diagnosis of Gestational Hypertension

Despite poor sensitivity and specificity, office blood pressure (BP) determinations are still the “gold standard” for diagnosing gestational hypertension. This prospective blind study evaluates the prognostic value of office values as compared with ambulatory monitoring in pregnancy. We analyzed 2175 BP series systematically sampled from 355 non-preeclamptic pregnant women for 48 h every 4 wks from the first hospital visit until delivery. Women were divided for comparative purposes into three groups: “detected” gestational hypertension, defined on the basis of casual clinical BP>140/90 mm Hg after 20 wks of gestation and hyperbaric index (area of BP excess above the upper limit of a time-specified tolerance interval adjusted for the circadian pattern of the reference population) consistently above the threshold for diagnosing hypertension in pregnancy; “undetected” gestational hypertension, women with office BP<140/90 mm Hg but hyperbaric index consistently above the threshold for diagnosis; and normotension, women with both office values and hyperbaric index below the respective thresholds for diagnosis. Small and insignificant differences in the 24 h mean BP between “detected” and “undetected” gestational hypertension is observed in all trimesters, in contrast with highly significant differences between these two groups and normotensive pregnancies. Normotensive women are characterized by highly significant lesser incidence by 60% in preterm delivery, 70% in intrauterine growth retardation, and 50% in delivery by cesarean section (P<0.001) compared with women with “detected” and “undetected” gestational hypertension (P>0.715). In pregnancy, the hyperbaric index is markedly superior to office BP measurements for diagnosis of what should be truly considered gestational hypertension, and for prediction of the outcome of pregnancy.     

A weight of evidence approach for selecting exposure biomarkers for biomonitoring

Context: It is known that there are usually several biomarkers and/or medium combinations that can be applied to answer a specific exposure question. To help determine an appropriate combination for the specific question, we have developed a weight-of-evidence Framework that provides a relative appropriateness score for competing combinations.

Methods: The Framework is based on an expert assessor’s evaluation of the relevance and suitability of the biomarker and medium for the question based on a set of criteria. We provide a computer based modeling tool to guide the researcher through the process.

Results: We present an example with six biomarkers of benzene exposure in one matrix; the six are either the most commonly used biomarkers and/or have recent widespread usage. The example clearly demonstrates the usefulness of the Framework for scoring the choices, as well as the transparency of the method that provides the basis for discussion.

Conclusions: The Framework provides for the first time a method to transparently document the rationale behind selecting, from among a set of alternatives, the most scientifically supportable exposure biomarker to address a specific biomonitoring question, thus providing a reproducible account of expert opinions on the suitability of a biomarker.