Accurate assessments of biodiversity are crucial to advising ecosystem-monitoring programs and understanding ecosystem function. Nevertheless, a standard operating procedure to assess biodiversity accurately and consistently has not been established. This is especially true for meiofauna, a diverse community (>20 phyla) of small benthic invertebrates that have fundamental ecological roles. Recent studies show that metabarcoding is a cost-effective and time-effective method to estimate meiofauna biodiversity, in contrast to morphological-based taxonomy. Here, we compare biodiversity assessments of a diverse meiofaunal community derived by applying multiple taxonomic methods based on comparative morphology, molecular phylogenetic analysis, DNA barcoding of individual specimens, and metabarcoding of environmental DNA. We show that biodiversity estimates are strongly biased across taxonomic methods and phyla. Such biases affect understanding of community structures and ecological interpretations. This study supports the urgency of improving aspects of environmental high-throughput sequencing and the value of taxonomists in correctly understanding biodiversity estimates.

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Poisoning from lead fishing tackle has been identified as the leading cause of mortality in adult common loons (Gavia immer). As a K-selected species, adult survival is a critical component in the population demography of loons, but the population-level effects of mortality from ingested lead tackle on loons have not been quantified. We used a long-term dataset on common loon mortality in New Hampshire, USA, to describe the types of lead tackle ingested by loons, investigate methods of ingestion of lead tackle, document the number and rate of adult mortalities resulting from lead tackle, and test for a population-level effect of lead tackle on the loon population in New Hampshire. Nearly half (48.6%) of collected adult mortalities resulted from lead toxicosis from ingested lead fishing tackle, representing an adjusted annual mortality rate of 1.7 AE 0.6% (SD) of the statewide population. Jigs accounted for 52.6% and sinkers for 38.8% of the archived lead tackle objects removed from loons, a higher proportion of jigs than has been reported in previous studies. The timing of lead tackle mortalities and a high incidence of accompanying non-lead associated fishing gear (hooks, fishing line, leaders, swivels, wire), which peaked in July and August, suggest that loons obtain the majority of lead tackle from current fishing activity rather than from a reservoir of lead tackle on lake bottoms. To project the statewide loon population in the absence of lead fishing tackle as a stressor, we constructed a retrospective population model, which re-inserted loons that died from lead tackle into the population, and used linear regression to test for a population-level effect. We defined a populationlevel effect as a difference in the population growth rate (l). We estimated that lead tackle mortality reduced the population growth rate (l) by 1.4% and the statewide population by 43% during the years of the study. This study suggests that replacing lead fishing sinkers and jigs weighing 28.4 g with non-toxic alternatives would result in an immediate benefit to the loon population in New Hampshire. Ó 2017 The Wildlife Society.

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Global climate change is an environmental hazard with significant public health impacts. High-impact weather events including periods of extreme temperature or extreme precipitation are frequently associated with adverse effects on human health. This study evaluates the impact of extreme weather events on injuries across New Hampshire. A set of five daily extreme weather metrics (EWMs) was analyzed: daily maximum temperature ≤32 °F (0 °C), daily maximum temperature ≥90 °F (32 °C), daily maximum temperature ≥95 °F (35 °C), daily precipitation ≥1″, and daily precipitation ≥2″. Exposure to these EWMs was defined by linking the population within 10 miles of nine weather stations distributed across the state. Injuries were defined as hospitalizations categorized as: all-cause injury, vehicle accidents, accidental falls, accidents due to natural and environmental causes (including excessive heat, excessive cold, exposure due to weather conditions, lightning, and storms and floods), accidental drowning, and carbon monoxide poisoning. The associations between all injury categories and all EWMs as well as daily maximum temperature and daily precipitation were explored. A quasi-Poisson regression model was used to evaluate the relationship between the four strongest exposure–outcome pairs linking maximum temperature to all-cause injury-, vehicle accident-, accidental fall-, and heat-related hospital visits. Results indicate that daily maximum temperature (>90 °F) was most strongly associated with heat-related hospital visits and was also associated with all-cause injury-related hospital visits. Future work should include further analysis of cold weather metrics and incorporate these findings into public health planning and response efforts.