Caterpillars Count! A Citizen Science Project for Monitoring Foliage Arthropod Abundance and Phenology

'Caterpillars Count!' is a citizen science project that allows participants to collect data on the seasonal timing, or phenology, of foliage arthropods that are important food resources for forest birds. This project has the potential to address questions about the impacts of climate change on birds over biogeographic scales. Here, we provide a description of the project’s two survey protocols, evaluate the impact of survey methodology on results, compare findings made by citizen scientist participants versus trained scientists, and identify the minimum levels of sampling frequency and intensity needed to accurately capture phenological dynamics. We find that beat sheet surveys and visual surveys yield similar relative and absolute density estimates of different arthropod groups, with beat sheet surveys recording a higher frequency of beetles and visual surveys recording a higher frequency of flies. Citizen scientists generated density estimates within 6% of estimates obtained by trained scientists regardless of survey method. However, patterns of phenology were more consistent between citizen scientists and trained scientists when using beat sheet surveys than visual surveys. By subsampling our survey data, we found that conducting 30 foliage surveys on a weekly basis led to 95% of peak caterpillar date estimates to fall within one week of the “true” peak. We demonstrate the utility of 'Caterpillars Count!' for generating a valuable dataset for ecological research, and call for future studies to evaluate how training and resource materials impact data quality and participant learning gains

Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals

The value of citizen science for ecological monitoring of mammals

Citizen science approaches are of great interest for their potential to efficiently and sustainably monitor wildlife populations on both public and private lands. Here we present two studies that worked with volunteers to set camera traps for ecological surveys. The photographs recorded by these citizen scientists were archived and verified using the eMammal software platform, providing a professional grade, vouchered database of biodiversity records. Motivated by managers’ concern with perceived high bear activity, our first example enlisted the help of homeowners in a short-term study to compare black bear activity inside a National Historic Site with surrounding private land. We found similar levels of bear activity inside and outside the NHS, and regional comparisons suggest the bear population is typical. Participants benefited from knowing their local bear population was normal and managers refocused bear management given this new information. Our second example is a continuous survey of wildlife using the grounds of a nature education center that actively manages habitat to maintain a grassland prairie. Center staff incorporated the camera traps into educational programs, involving visitors with camera setup and picture review. Over two years and 5,968 camera-nights this survey has collected 41,393 detections of 14 wildlife species. Detection rates and occupancy were higher in open habitats compared to forest, suggesting that the maintenance of prairie habitat is beneficial to some species. Over 500 volunteers of all ages participated in this project over two years. Some of the greatest benefits have been to high school students, exemplified by a student with autism who increased his communication and comfort level with others through field work with the cameras. These examples show how, with the right tools, training and survey design protocols, citizen science can be used to answer a variety of applied management questions while connecting participants with their secretive mammal neighbors

Conversion from Red to Blue Photoluminescence in Alcohol Dispersions of Alkyl-Capped Silicon Nanoparticles: Insight into the Origins of Visible Photoluminescence in Colloidal Nanocrystalline Silicon

Visibly emissive silicon nanoparticles (Si NPs) were obtained via annealing of (HSiO_1.5)_<i>n</i> polymer, followed by chemical etching. The hydride-terminated Si NPs (H-Si NPs) were surface-functionalized via thermal hydrosilylation with 1-decene and were dispersed in straight chain alcohols varying in carbon chain length (C1–C10). The initial red photoluminescence (PL) (λ_max,em ∼580 nm) observed from hexane dispersions of the decane-terminated Si NPs (dec-Si NPs) became weaker upon exposure to alcohols smaller than a minimum chain length, commensurate with appearance of strong, blue PL (λ_max,em ∼450 nm). A suite of spectroscopic and microscopic techniques was employed to study and correlate the change in Si NP PL with composition and/or size changes to the Si NPs. The results of these studies support that the conversion from red to blue PL originates from dangling bond defect passivation by small alcohol molecules, resulting in an enhanced blue/red PL ratio. The dangling bond defect (Si^•) is supported by reactivity studies of H-Si NPs with the stable radical (2,2,6,6-tetramethylpiperidin-1-yl)­oxy (TEMPO) and with <i>n</i>-alkanes. We discuss these experimental results in light of current hypotheses about the origins of Si NP visible light emission, which we demonstrate is markedly influenced by the Si NP surface chemistry. An energy level diagram is proposed to account for the spectral and dynamic features observed, in which the role of surface states is highlighted