Zooplankton Biodiversity Patterns Across a Novel Water Storage Complex in the NJ Pinelands

The study involves the collection of zooplankton samples from Whitesbog, which is an inactive cranberry bog complex that is used as water storage for cranberry harvest during the fall season. Whitesbog is novel because very little human activity occurs in the surrounding area that could degrade water quality, but the complex itself is not natural. The water found in the upstream parts of the bog is highly acidic, which likely creates a gradient of ecological dystrophy in the zooplankton community. In this study, we investigate patterns of density and biodiversity across the complex and question whether these patterns are driven by physical-chemical conditions. Zooplankton density for different species varies between sites, with some sites changing more than others over time. Water temperature was the best predictor of zooplankton density, but it is unclear with present data whether this is a non-linear or linear response gradient. Turbidity and water temperature are the best predictors of zooplankton biodiversity, but the environmental variables we measured were insufficient to explain much of the observed differences between sites. Further testing is needed

Correlation Matrices of Cyanobacterial Bloom Predictors Varies Between Lakes

Under anthropogenically-altered conditions, cyanobacteria may form harmful algal blooms (cHABs) that can be toxic and disrupt ecosystem function. Developing tools to predict cHABs is an increasingly important task, but such tools have been difficult to develop. In our study, we contribute to the development of a predictive model for cHAB formation in the waters of southern New Jersey by statistically screening water quality data from five polymictic reservoirs that were sampled weekly from June through September 2019. The correlation structure of water quality variables differed between the reservoirs in a way that suggests that the mean correlation coefficient is elevated for reservoirs experiencing a cHAB. Some water quality variables are unlikely to be useful for predictive modeling, but among those that do have utility, those measurements were obtained under natural field conditions, semi-controlled conditions in the field, and controlled conditions in the lab. The number of principal components (PC axes) required to describe variation in the water quality data differed between reservoirs in a way that suggests reservoirs experiencing cHABs have less complex covariance structures. Collectively, these results indicate that predictive modeling of cHAB formation should be possible

Predicting Seasonal and Spatial Onset of cHABs in Polymictic Reservoirs

Cyanobacterial Harmful Algal Blooms (cHABS) are a naturally occurring but increasingly common phenomenon due to anthropogenic activities and climate change. cHABs reduce water quality by forming unsightly surface scums and sometimes producing algal matts on the surface of water bodies, reduce water quality, and in high densities can produce cyanotoxins that can harm humans, pets, and wildlife. Ecological forecasting of cHABs has proved elusive in part because the in-situ fluorometric methods currently employed for detecting cyanobacteria cells are subject to varied interference as water quality and the biotic community changes. In this study we seek to develop an ecological forecasting capability that overcomes both temporally and spatially derived in-situ fluorometric interferences. We obtained water samples at 26 polymictic reservoirs over a two-day period and at five polymictic reservoirs weekly during the summer of 2019. Collected water samples are being used for quantitative analysis of cyanobacterial cell densities by means of qPCR. We plan a data reduction technique (e.g. PCA, VIF screening, elastic-net regression as appropriate) followed by multivariate predictive model (e.g. multiple regression, ordination, discriminant analysis as appropriate)

Environmental Predictors of Zooplankton Biodiversity Across a Series of Polymictic Reservoirs

Zooplankton are an important part of lentic food webs because they connect photoautotrophic plankton to higher trophic levels. Past studies in 2016 and 2017 determined that zooplankton biodiversity is different across a polymictic reservoir series in Salem County NJ. In the study presented here, we confirmed a similar zooplankton biodiversity pattern in 2018 and we determine which physicochemical variables were good predictors of zooplankton biodiversity. Our results indicate that there are many physicochemical variables that are reliable predictors of zooplankton biodiversity across this polymictic reservoir series. Additional predictor variables are being developed to help us understand which environmental variables are most influential on zooplankton biodiversity and the influence of human land-use

Dietary and Physical Activity Factors Related to Eating Disorder Symptoms Among Middle School Youth

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95371/1/j.1746-1561.2012.00742.x.pd

School Programs and Characteristics and Their Influence on Student BMI: Findings from Healthy Passages

Background: Little is known about the contribution of school contextual factors to individual student body mass index (BMI). We set out to determine if school characteristics/resources: (1) are associated with student BMI; (2) explain racial/ethnic disparities in student BMI; and (3) explain school-level differences in student BMI. Methods: Using gender-stratified multi-level modeling strategies we examined the association of school characteristics/resources and individual BMI in 4,387 5th graders in the Healthy Passages Longitudinal Study of Adolescent Health. Additionally, we examined the association of race/ethnicity and individual BMI as well as the between-school variance in BMI before and after adding individual and school characteristics to test for attenuation. Results: The school-level median household income, but not physical activity or nutrition resources, was inversely associated with female BMI (β = −0.12, CI: −0.21,−0.02). Neither school demographics nor physical activity/nutrition resources were predictive of individual BMI in males. In Black females, school characteristics attenuated the association of race/ethnicity and BMI. Individual student characteristics—not school characteristics/resources-reduced the between-school variation in BMI in males by nearly one-third and eliminated it in females. Conclusions: In this cohort of 5th graders, school SES was inversely associated with female BMI while school characteristics and resources largely explained Black/White disparities in female weight status. Between-school differences in average student weight status were largely explained by the composition of the student body not by school characteristics or programming

Biobanking and consenting to research: a qualitative thematic analysis of young people’s perspectives in the North East of England

Background: Biobanking biospecimens and consent are common practice in paediatric research. We need to explore children and young people’s (CYP) knowledge and perspectives around the use of and consent to biobanking. This will ensure meaningful informed consent can be obtained and improve current consent procedures. Methods: We designed a survey, in co-production with CYP, collecting demographic data, views on biobanking, and consent using three scenarios: 1) prospective consent, 2) deferred consent, and 3) reconsent and assent at age of capacity. The survey was disseminated via the Young Person’s Advisory Group North England (YPAGne) and participating CYP’s secondary schools. Data were analysed using a qualitative thematic approach by three independent reviewers (including CYP) to identify common themes. Data triangulation occurred independently by a fourth reviewer. Results: One hundred two CYP completed the survey. Most were between 16–18 years (63.7%, N = 65) and female (66.7%, N = 68). 72.3% had no prior knowledge of biobanking (N = 73). Acceptability of prospective consent for biobanking was high (91.2%, N = 93) with common themes: ‘altruism’, ‘potential benefits outweigh individual risk’, 'frugality', and ‘(in)convenience’. Deferred consent was also deemed acceptable in the large majority (84.3%, N = 86), with common themes: ‘altruism’, ‘body integrity’ and ‘sample frugality’. 76.5% preferred to reconsent when cognitively mature enough to give assent (N = 78), even if parental consent was previously in place. 79.2% wanted to be informed if their biobanked biospecimen is reused (N = 80). Conclusion: Prospective and deferred consent acceptability for biobanking is high among CYP in the UK. Altruism, frugality, body integrity, and privacy are the most important themes. Clear communication and justification are paramount to obtain consent. Any CYP with capacity should be part of the consenting procedure, if possible

Using matrix population models to inform biological control management of the wheat stem sawfly, Cephus cinctus

Demographic models are a powerful means of identifying vulnerable life stages of pest species and assessing the potential effectiveness of various management approaches in reducing pest population growth and spread. In a biological control context, such models can be used to focus foreign exploration or conservation efforts on enemies that attack life stages identified to have the greatest impact, and determine target levels of predation or parasitism that would be necessary to suppress population growth. In this study, we constructed a matrix population model to assess the potential effectiveness of biological controls against the wheat stem sawfly, Cephus cinctus, a major pest of wheat in North America. We calculated the sensitivity of C. cinctus population growth to changes in stage-specific survivorship, to identify the stage at which parasitoid attack would have the largest impact on pest population growth. We also calculated the stage-specific rate of mortality needed to reduce C. cinctus population growth rate to zero, to set targets for conservation biological control approaches. Our model indicates that C. cinctus populations are growing (λ = 1.022), and are predicted to triple in a year in the absence of added control measures. The winter larval stage had the highest elasticities, suggesting this stage is the weakest link in the pest life-cycle, in part reflecting the much longer average duration of the winter compared with the summer larval stage (45 versus 5 weeks). Parasitism levels by native Bracon spp. parasitoids necessary to suppress C. cinctus population growth were the same for summer and overwintering stages (68%). These target parasitism levels far exceeded those typically observed in the field, and conservation measures employed to date suggest that single actions do not bolster parasitism to target thresholds. Thus multiple conservation measures (e.g. reduced tillage, increased cutting height and the provisioning of floral resources) will likely need to be complemented by other management approaches (e.g., host plant resistance), to suppress C. cinctus populations. Our results reinforce previous work demonstrating the utility of matrix models for evaluating the potential efficacy of biological control agents, and further illustrates how they can be used to evaluate, and set targets for, conservation management approaches using specific natural enemies

Ecological Thresholds and Environmental Indicators of the Density of Zooplankton Exports from a Polymictic Reservoir Series

Zooplankton export from a reservoir is an important indicator of resources in the lotic system below the reservoir and is quantified via count density (DZE), community composition (CCZE), and biomass (BZE). In the study presented here, we monitored DZE weekly between May and August over three years (2017-2019) at a series of four connected reservoirs in Southern New Jersey. Multiple regression indicated that year-to-year differences in DZE were not significant, but DZE did vary over the course of the season and between reservoirs. The best predictor of seasonal variation in DZE was conductivity (a persistent indicator of anthropogenic nutrient pollution). Conductivity was also the best predictor of differences in DZE between reservoirs, with the residual spatial variation between reservoirs being best explained by Colored Dissolved Organic Matter (CDOM). We detected a state-shift in DZE characterized by low week-to-week variation in DZE early in the season at two of the four reservoirs we monitored. Conductivity is the most reliable predictor of DZE both over the course of the growing season and between polymictic reservoirs, but other factors (chlorophyll and nutrient pulses) are more likely to be the causative factors driving variation in DZE