Evaluation of a Regional Monitoring Program’s Statistical Power to Detect Temporal Trends in Forest Health Indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year^?1 for all indicators and is appropriate for detecting a 1 % trend·year^?1 in most indicators.     

Validation of an electronic device for measuring driving exposure

OBJECTIVE: This study sought to evaluate an on-board diagnostic system (CarChip) for collecting driving exposure data in older drivers. METHODS: Drivers (N = 20) aged 60 to 86 years from Winnipeg and surrounding communities participated. Information on driving exposure was obtained via the CarChip and global positioning system (GPS) technology on a driving course, and obtained via the CarChip and surveys over a week of driving. Velocities and distances were measured over the road course to validate the accuracy of the CarChip compared to GPS for those parameters. RESULTS: The results show that the CarChip does provide valid distance measurements and slightly lower maximum velocities than GPS measures. From the results obtained in this study, it was determined that retrospective self-reports of weekly driving distances are inaccurate. CONCLUSIONS: Therefore, an on-board diagnostic system (OBDII) electronic device like the CarChip can provide valid and detailed information about driving exposure that would be useful for studies of crash rates or driving behavior.     

Heavy metal (Cu, Zn, Cd and Pb) contamination of vegetables in urban India: a case study in Varanasi

The contributions of heavy metals in selected vegetables through atmospheric deposition were quantified in an urban area of India. Deposition rate of Zn was recorded maximum followed by Cu, Cd and Pb. The concentrations of Zn and Cu were highest in Brassica oleracea, Cd in Abelmoschus esculentus and B. oleracea, while Pb was highest in Beta vulgaris. Heavy metal pollution index showed that B. oleracea was maximally contaminated with heavy metals followed by A. esculentus and then B. vulgaris. The results of washing showed that atmospheric deposition has contributed to the increased levels of heavy metals in vegetables. Both Cu and Cd posed health risk to local population via test vegetables consumption, whereas Pb posed the same only through B. oleracea. The study concludes that atmospheric depositions can elevate the levels of heavy metals in vegetables during marketing having potential health hazards to consumers.     

Longitudinal monitoring of neutral and adaptive genomic diversity in a reintroduction

Restoration programs in the form of ex-situ breeding combined with reintroductions are becoming critical to counteract demographic declines and species losses. Such programs are increasingly using genetic management to improve conservation outcomes. However, the lack of long-term monitoring of genetic indicators following reintroduction prevents assessments of the trajectory and persistence of reintroduced populations. We carried out an extensive monitoring program in the wild for a threatened small-bodied fish (southern pygmy perch, Nannoperca australis) to assess the long-term genomic effects of its captive breeding and reintroduction. The species was rescued prior to its extirpation from the terminal lakes of Australia's Murray-Darling Basin, and then used for genetically informed captive breeding and reintroductions. Subsequent annual or biannual monitoring of abundance, fitness, and occupancy over a period of 11 years, combined with postreintroduction genetic sampling, revealed survival and recruitment of reintroduced fish. Genomic analyses based on data from the original wild rescued, captive born, and reintroduced cohorts revealed low inbreeding and strong maintenance of neutral and candidate adaptive genomic diversity across multiple generations. An increasing trend in the effective population size of the reintroduced population was consistent with field monitoring data in demonstrating successful re-establishment of the species. This provides a rare empirical example that the adaptive potential of a locally extinct population can be maintained during genetically informed ex-situ conservation breeding and reintroduction into the wild. Strategies to improve biodiversity restoration via ex-situ conservation should include genetic-based captive breeding and longitudinal monitoring of standing genomic variation in reintroduced populations.