A Global, Cross-System Meta-Analysis of Polychlorinated Biphenyl Biomagnification.

Studies evaluating the mechanisms underpinning the biomagnification of polychlorinated biphenyls (PCBs), a globally prevalent group of regulated persistent organic pollutants, commonly couple chemical and stable isotope analyses to identify bioaccumulation pathways. Due to analytical costs constraining the scope, sample size, and range of congeners analyzed, and variation in methodologies preventing cross-study syntheses, how PCBs biomagnify at food web, regional, and global scales remains uncertain. To overcome these constraints, we compiled diet (stable isotopes) data and lipid-normalized concentrations of sum total PCB (PCBST), seven indicator PCB congeners, and their sum (PCB∑7). Our analyses revealed that the number of congeners analyzed, region, and class most strongly predicted PCBST, while similarly, region, class, and feeding location best predicted PCB∑7 and all seven congeners. We also discovered that PCBST, PCB∑7, and the seven indicator congeners all occur in higher concentrations in freshwater than marine ecosystems but are more likely to biomagnify in the latter. Moreover, although the seven congeners vary in their propensity to biomagnify, their trophic magnification factors are all generally greater in the Atlantic than the Pacific. Thus, novel insights regarding PCB biomagnification across taxonomic, food webs, regional, and global scales can be gleaned by leveraging existing data to overcome analytical constraints.

Automated data-intensive forecasting of plant phenology throughout the United States.

Phenology, the timing of cyclical and seasonal natural phenomena such as flowering and leaf out, is an integral part of ecological systems with impacts on human activities like environmental management, tourism, and agriculture. As a result, there are numerous potential applications for actionable predictions of when phenological events will occur. However, despite the availability of phenological data with large spatial, temporal, and taxonomic extents, and numerous phenology models, there have been no automated species-level forecasts of plant phenology. This is due in part to the challenges of building a system that integrates large volumes of climate observations and forecasts, uses that data to fit models and make predictions for large numbers of species, and consistently disseminates the results of these forecasts in interpretable ways. Here, we describe a new near-term phenology-forecasting system that makes predictions for the timing of budburst, flowers, ripe fruit, and fall colors for 78 species across the United States up to 6 months in advance and is updated every four days. We use the lessons learned in developing this system to provide guidance developing large-scale near-term ecological forecast systems more generally, to help advance the use of automated forecasting in ecology.

Estimating flowering transition dates from status-based phenological observations: a test of methods.

The scale of phenological research has expanded due to the digitization of herbarium specimens and volunteer based contributions. These data are status-based, representing the presence or absence of a specific phenophase. Modelling the progress of plant dormancy to growth and reproduction and back to dormancy requires estimating the transition dates from these status-based observations. There are several methods available for this ranging from statistical moments using the day of year to newly introduced methods using concepts from other fields. Comparing the proficiency of different estimators is difficult since true transition dates are rarely known. Here I use a recently released dataset of in-situ flowering observations of the perennial forb Echinacea angustifolia. In this dataset, due to high sampling frequency and unique physiology, the transition dates of onset, peak, and end of flowering are known to within 3 days. I used a Monte Carlo analysis to test eight different estimators across two scales using a range of sample sizes and proportion of flowering presence observations. I evaluated the estimators accuracy in predicting the onset, peak, and end of flowering at the population level, and predicting onset and end of flowering for individual plants. Overall, a method using a Weibull distribution performed the best for population level onset and end estimates, but other estimators may be more appropriate when there is a large amount of absence observations relative to presence observations. For individual estimates a method using the midway point between the first flower presence and most prior flower absence, within 7 days, is the best option as long as the restriction does not limit the final sample size. Otherwise, the Weibull method is adequate for individual estimates as well. These methods allow practitioners to effectively utilize the large amount of status-based phenological observations currently available.

Comparison of large-scale citizen science data and long-term study data for phenology modeling.

Large-scale observational data from citizen science efforts are becoming increasingly common in ecology, and researchers often choose between these and data from intensive local-scale studies for their analyses. This choice has potential trade-offs related to spatial scale, observer variance, and interannual variability. Here we explored this issue with phenology by comparing models built using data from the large-scale, citizen science USA National Phenology Network (USA-NPN) effort with models built using data from more intensive studies at Long Term Ecological Research (LTER) sites. We built statistical and process based phenology models for species common to each data set. From these models, we compared parameter estimates, estimates of phenological events, and out-of-sample errors between models derived from both USA-NPN and LTER data. We found that model parameter estimates for the same species were most similar between the two data sets when using simple models, but parameter estimates varied widely as model complexity increased. Despite this, estimates for the date of phenological events and out-of-sample errors were similar, regardless of the model chosen. Predictions for USA-NPN data had the lowest error when using models built from the USA-NPN data, while LTER predictions were best made using LTER-derived models, confirming that models perform best when applied at the same scale they were built. This difference in the cross-scale model comparison is likely due to variation in phenological requirements within species. Models using the USA-NPN data set can integrate parameters over a large spatial scale while those using an LTER data set can only estimate parameters for a single location. Accordingly, the choice of data set depends on the research question. Inferences about species-specific phenological requirements are best made with LTER data, and if USA-NPN or similar data are all that is available, then analyses should be limited to simple models. Large-scale predictive modeling is best done with the larger-scale USA-NPN data, which has high spatial representation and a large regional species pool. LTER data sets, on the other hand, have high site fidelity and thus characterize inter-annual variability extremely well. Future research aimed at forecasting phenology events for particular species over larger scales should develop models that integrate the strengths of both data sets.

Forecasting biodiversity in breeding birds using best practices.

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and "naive" forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the "naive" model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

Aqueous foam films stabilized by sodium naphthenates.

Stratification of a foam liquid film drawn from aqueous solutions of sodium naphthenate at relatively high concentration is likely due to a lamellar liquid crystal-like structure within the film. Film stratification, resulting in stepwise thinning, has been observed in foam films formed from systems containing either moderate to high concentrations of surfactant or in films formed from solutions containing solid particles. At moderate surfactant concentrations, film stratification is likely due to layers of ordered spherical micelles as postulated in Wasan and Nikolov's model of film stratification. At high surfactant concentrations, stepwise thinning of the films and occurrence of domains of uniform color within the film suggest a lamellar liquid crystal-like structure within the film, potentially up to hundred or more oriented layers. The LLC-like structure inside the film can occur at concentrations below the lower limit of the LLC existence as a bulk phase.

Stepwise thickening in aqueous foam films stabilized by sodium naphthenates.

During drainage of a foam film formed from an aqueous sodium naphthenate solution, a transient, local, stepwise thickening process was observed. Film stratification is related to the stepwise thinning drainage process where individual layers of material are drained from a film. The process typically involves the appearance of a sequence of small, uniformly thick spots that eventually expand to the size of the film. The appearance and growth of each spot represents a discrete decrease in the thickness of the film. The size of each decrease or step typically corresponds to the size of one or more lamella layers of the stratified film. Stepwise thinning was observed in a foam film formed from an aqueous sodium naphthenate solution, as frequently reported for a variety of systems. However, during the drainage process, a transient stepwise thickening process was also observed. Bright spots began to appear and grow, indicate a discrete increase in the thickness of a portion of the film. This local, stepwise thickening process appeared to be an alternate and temporary drainage process directly related to the expansion of the stepwise thinning spots.

Disjoining pressure isotherms of water-in-bitumen emulsion films.

In the oil sands industry, undesirable water-in-oil emulsions are often formed during the bitumen recovery process where water is used to liberate bitumen from sand grains. Nearly all of the water is removed except for a small percentage (approximately 1 to 2%), which remains in the solvent-diluted bitumen as micrometer-sized droplets. Knowledge of the colloidal forces that stabilized these water droplets would help to increase our understanding of how these emulsions are stabilized. In this study, the thin liquid film-pressure balance technique has been used to measure isotherms of disjoining pressure in water/toluene-diluted bitumen/water films at five different toluene-bitumen mass ratios. Even though a broad range of mass ratios was studied, only two isotherms are obtained, indicating a possible change in the molecular orientation of surfactant molecules at the bitumen/water interfaces. At low toluene-bitumen mass ratios, the film stability appears to be due to a strong, short-range steric repulsion created by a surfactant bilayer. Similar isotherms were obtained for water/toluene-diluted asphaltene/water films, indicating that the surface active material at the interface probably originated from the asphaltene fraction of the bitumen. However, unlike the bitumen films, films of toluene-diluted asphaltenes often formed very rigid interfaces similar to the "protective skin" described by other researcher.