General Additive Modeling Research Articles

Climate and salinity together control above ground carbon accumulation in the Sundarbans mangrove ecosystem

Mangroves play a crucial role in mitigating climate change through carbon (C) accumulation. Developing robust methods for the estimation of long-term C accumulation is essential for monitoring and reporting carbon financing projects under different global mechanisms. Moreover, understanding the effects of climate and habitat on C accumulation is important for developing mangrove management plans and conservation options. In this study, long-term above ground C accumulation in the three most dominated mangrove tree species, Heritiera fomes, Excoecaria agallocha and Sonneratia apetala, was estimated using a dendrochronological approach in two contrasting (low vs high) salinity zones in the Bangladesh Sundarbans. In addition, how climate and habitat (e.g., regulators and soil resources) influence C accumulation was analyzed. For the first time, we estimated C accumulation in mangrove species over their entire lifetime using stem disc-derived tree-ring data. The C accumulation patterns exhibited similar patterns of variation, increasing from pith to bark in each case. C accumulation was significantly higher in the low salinity zone (LSZ) than in the high salinity zone (HSZ) (p < 0.05). The cumulative C accumulation increased with tree age in each case, and C accumulation was influenced mainly by seasonal precipitation, especially during monsoon. General additive modeling (GAM) revealed that soil salinity had a stronger effect on C accumulation variability in the studied tree species. Other regulatory variables (i.e., siltation and elevation) and soil resources (i.e., P and K) had species-specific influences on C accumulation. Tree-ring data show the potential to yield better biomass and C estimations, which could aid frequent and rapid reporting of C accumulation in mangroves. Moreover, the results also suggest that climate and regulatory variables, especially soil salinity, together impact the C cycles in the Sundarbans.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves.

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Using artificial intelligence to identify the top 50 independent predictors of subjective well-being in a multinational sample of 37,991 older European & Israeli adults

Subjective well-being (SWB) is widely recognized as an important health outcome, but its complexity, myriad predictors, and analytic requirements pose significant challenges to identifying the relative order and impact of SWB determinants. This study involved a representative sample of 37,991 older adults from 17 European countries and Israel. An aggregate index of SWB was developed and compared across countries, and machine-learning algorithms were used to rank-order the strongest 50 (of an initial 94) SWB predictors from 15 categories. General Additive Modeling (GAM) and low-degree polynomials (i.e., splines) were used to determine the independent effect sizes and significance levels for each of these top-50 SWB predictors. Of the 18 countries included in this study, Denmark had the highest mean SWB, while Greece had the lowest. The two top-ranked SWB predictors (loneliness, social activity satisfaction) were social factors, which also had the highest overall group ranking, followed by physical health, demographics, financial status and personality. Self-reported health was the strongest health-related predictor, neuroticism was the strongest personality predictor, and women reported higher SWB than men. SWB decreased with age, and increased with income up to 350,000 euros/year, after which it declined. Social factors were of primary importance for subjective well-being in this research, while childhood experiences and healthcare status exerted the smallest effects. The vast majority of the top 50 SWB predictors were statistically significant, with the notable exceptions of body mass index and most health behaviors, which may impact SWB indirectly through their effects on physical health. Future multivariate modeling is recommended to clarify the mechanisms for these and other observed relationships.

Assessment of light-duty versus heavy-duty diesel on-road mobile source emissions using general additive models applied to traffic volume and air quality data and COVID-19 responses

ABSTRACT Following the outbreak of the COVID-19 pandemic, several papers have examined the effect of the pandemic response on urban air pollution worldwide. This study uses observed traffic volume and near-road air pollution data for black carbon (BC), oxides of nitrogen (NOx), and carbon monoxide (CO) to estimate the emissions contributions of light-duty and heavy-duty diesel vehicles in five cities in the continental United States. Analysis of mobile source impacts in the near-road environment has several health and environmental justice implications. Data from the initial COVID-19 response period, defined as March to May in 2020, were used with data from the same period over the previous two years to develop general additive models (GAMs) to quantify the emissions impact of each vehicle class. The model estimated that light-duty traffic contributes 4–69%, 14–65%, and 21–97% of BC, NOx, and CO near-road levels, respectively. Heavy-duty diesel traffic contributes an estimated 26–46%, 17–63%, and −7–18% of near-road levels of the three pollutants. The estimated mobile source impacts were used to calculate NOx to CO and BC to NOx emission ratios, which were between 0.21–0.32 μg m−3 NOx (μg m−3 CO)−1 and 0.013–0.018 μg m−3 BC (μg m−3 NOx)−1. These ratios can be used to assess existing emission inventories for use in determining air pollution standards. These results agree moderately well with recent National Emissions Inventory estimates and other empirically-derived estimates, showing similar trends among the pollutants. However, a limitation of this study was the recurring presence of an implausible air pollution impact estimate in 41% of the site-pollutant combinations, where a vehicle class was estimated to account for either a negative impact or an impact higher than the total estimated pollutant concentration. The variations seen in the GAM estimates are likely a result of location-specific factors, including fleet composition, external pollution sources, and traffic volumes. Implications: Drastic reductions in traffic and air pollution during the lockdowns of the COVID-19 pandemic present a unique opportunity to assess vehicle emissions. A General Additive Modeling approach is developed to relate traffic levels, observed air pollution, and meteorology to identify the amount vehicle types contribute to near-road levels of traffic-related air pollutants (TRAPs), which is important for future emission regulation and policy, given the significant health and environmental justice implications of vehicle-related pollution along major roadways. The model is used to evaluate emission inventories in the near-road environment, which can be used to refine existing estimates. By developing a locally data-driven method to readily characterize impacts and distinguish between heavy and light duty vehicle effects, local regulations can be used to target policies in major cities around the country, thus addressing local health disbenefits and disparities occurring as a result of exposure to near-road air pollution.

A Temporal Analysis of the Cost of Aesthetic Surgical Procedures Over the Past Decade in Relation to Consumer Price Indices and the Stock Market

Abstract Goals/Purpose As inflation continues to rise, virtually all consumer markets are affected. However, the effect of these increases on aesthetic surgical procedures are not well defined. An important relational understanding of these effects can help aesthetic practices offer fair market prices to benefit both patients and practices alike. The purpose of this study was to quantify temporal changes in pricing for the most common aesthetic surgeries and to make comparisons to various indices of inflation and the stock market. Methods/Technique Annual surgical fees for 18 aesthetic plastic surgery procedures were collected from 2007 to 2020 using the ASAPs and ASPS yearly plastic surgery statistic reports. In addition, annual consumer price indices (CPI) for all items, physicians’ services, and hospital services were collected from the U.S Bureau of Labor Statistics. Finally yearly Dow Jones Industrial (DJI) Averages were collected during the same time frame. Correlation statistics, generalized additive models, and parametric tests were performed to understand the relationships of these surgical costs to other indices. Results/Complications A total of 322 annual measurements were collected for analysis. The cumulative percent change from 2007 to 2020 was highest for rhytidectomy, blepharoplasty, and otoplasty 38.1%, 33.4%, and 30.4%, respectively. Liposuction had the lowest overall cumulative percent change at -10.0%. Kendall correlation test revealed that out of all surgeries, male gynecomastia had the strongest correlation with time, Tau= 0.74, p=0.001. Breast augmentation, blepharoplasty, and abdominoplasty also correlated with time. When comparing the temporal change in prices to the various indices through nonparametric general additive modeling, breast augmentation, blepharoplasty, facelift, and liposuction costs changed at a statistically different rate than the overall CPI of all items, p=0.035, 0.018, 0.012, and &amp;lt;0.001, respectively. In contrast, rates of price changes in rhinoplasty, buttock lift, and breast lift surgery have not differed significantly from that of the CPI. The DJI has grown at rates far greater than the price of any aesthetic surgery procedure and models have been statistically different. Conclusion While over the past decade aesthetic surgery costs have changed, certain procedure costs such as the rhytidectomy have greatly increased, while others have modestly increased, and liposuction has even decreased. Interestingly, the cost for the majority of the most performed aesthetic procedures are not greatly impacted by inflation. This suggests that other forces such as supply and demand may have a greater impact on price changes over the years. Many surgical procedures however were found to have similar rates of price change as the CPI, suggesting that these surgeries and their costs are more vulnerable to inflationary adjustments. Furthermore the price changes of aesthetic surgeries seem to be independent of how the stock market fluctuates and therefore possibly independent of other markets as a whole. This study has several limitations, with the data source as its greatest. The ASPS and ASAPs statistic reports are based on surveys from national members and computational adjustments, which have inherent biases and can vary significantly in any given year. Furthermore the various modeling and statistical analyses performed herein were based on several assumptions and estimates. An understanding of the price trends in aesthetic surgery over time and in relation to consumer price indices and the DJI can help plastic surgery practices and patients better appreciate the economics surrounding aesthetic surgeries.

Assessing the viability of estimating baleen whale abundance from tourist vessels

Many populations of southern hemisphere baleen whales are recovering and are again becoming dominant consumers in the Southern Ocean. Key to understanding the present and future role of baleen whales in Southern Ocean ecosystems is determining their abundance on foraging grounds. Distance sampling is the standard method for estimating baleen whale abundance but requires specific logistic requirements which are rarely achieved in the remote Southern Ocean. We explore the potential use of tourist vessel-based sampling as a cost-effective solution for conducting distance sampling surveys for baleen whales in the Southern Ocean. We used a dataset of tourist vessel locations from the southwest Atlantic sector of the Southern Ocean and published knowledge from Southern Ocean sighting surveys to determine the number of tourist vessel voyages required for robust abundance estimates. Second, we simulated the abundance and distributions of four baleen whale species for the study area and sampled them with both standardized line transect surveys and non-standardized tourist vessel-based surveys, then compared modeled abundance and distributions from each survey to the original simulation. For the southwest Atlantic, we show that 12-22 tourist vessel voyages are likely required to estimate abundance for humpback and fin whales, with relative estimates for blue, sei, Antarctic minke, and southern right whales. Second, we show tourist vessel-based surveys outperformed standardized line transect surveys at reproducing simulated baleen whale abundances and distribution. These analyses suggest tourist vessel-based surveys are a viable method for estimating baleen whale abundance in remote regions. For the southwest Atlantic, the relatively cost-effective nature of tourist vessel-based survey and regularity of tourist vessel voyages could allow for annual and intra-annual estimates of abundance, a fundamental improvement on current methods, which may capture spatiotemporal trends in baleen whale movements on forging grounds. Comparative modeling of sampling methods provided insights into the behavior of general additive model-based abundance modeling, contributing to the development of detailed guidelines of best practices for these approaches. Through successful engagement with tourist company partners, this method has the potential to characterize abundance across a variety of marine species and spaces globally, and deliver high-quality scientific outcomes relevant to management organizations.

Interactive Effects of Nutrients and Salinity on Phytoplankton in Subtropical Plateau Lakes of Contrasting Water Depths

Eutrophication and salinization are serious global environmental problems in freshwater ecosystems, occasionally acting jointly to exert harmful effects on aquatic ecosystems. To elucidate the interactive effects of nutrients and salinity on phytoplankton assemblages, we conducted a four-season study during 2020–2021 of eight lakes from Yunnan Plateau (Southwest China) with a wide range of conductivities (Cond, reflecting degree of salinization), eutrophic states, and water depths and used General Additive Modeling (GAM) of the data. We found that: (1) species number (SN), density (DPhyt), and biomass (BPhyt) of phytoplankton showed stronger seasonal dynamics in shallow lakes than in deep lakes, all being, as expected, higher in the warm season; (2) annual and summer data revealed highly significant positive relationships between SN, DPhyt, and BPhyt with total nitrogen (TN) and total phosphorus (TP), which became weaker at high TP occurring when the N:P ratio was low, indicating N limitation; (3) SN, DPhyt, and BPhyt showed a unimodal relationship with salinity, peaking at 400–1000 μS/cm (Cond); (4) the two dominant taxa (cyanobacteria and chlorophyta) showed different patterns, with chlorophyta generally dominating at low TN and cyanobacteria at high TN and Cond, suggesting the synergistic effect of nitrogen and Cond on cyanobacterial dominance.

Learning to Read Interacts with Children’s Spoken Language Fluency

ABSTRACT Until at least the end of adolescence, children articulate speech differently than adults. While this discrepancy is often attributed to the maturation of the speech motor system, we sought to demonstrate that the development of spoken language fluency is shaped by complex interactions across motor and cognitive domains. In this study, we specifically tested for a relationship between reading proficiency and coarticulatory organization, a fundamental correlate of spoken language fluency, used for both reading aloud and conversational speech. We conducted reading assessments and ultrasound-based kinematic measurements of intersegmental coarticulation in a group of 32 German children. In German, a language which supports rather consistent grapheme-to-phoneme relationships, reading aloud uses similar phoneme to speech motor gesture correspondences as well as coarticulatory mechanisms as conversational speech. Using general additive modeling we found that better readers exhibited lower degrees of intersegmental coarticulation than poorer readers. This study therefore provides evidence that reading proficiency interacts with coarticulatory patterns in beginning readers. It suggests that in addition to maturational factors, interactions between speech motor ability and other co-developing skills must be considered to fully account for spoken language fluency.

Agro-Environmental Determinants of Leptospirosis: A Retrospective Spatiotemporal Analysis (2004-2014) in Mahasarakham Province (Thailand).

Leptospirosis has been recognized as a major public health concern in Thailand following dramatic outbreaks. We analyzed human leptospirosis incidence between 2004 and 2014 in Mahasarakham province, Northeastern Thailand, in order to identify the agronomical and environmental factors likely to explain incidence at the level of 133 sub-districts and 1982 villages of the province. We performed general additive modeling (GAM) in order to take the spatial-temporal epidemiological dynamics into account. The results of GAM analyses showed that the average slope, population size, pig density, cow density and flood cover were significantly associated with leptospirosis occurrence in a district. Our results stress the importance of livestock favoring leptospirosis transmission to humans and suggest that prevention and control of leptospirosis need strong intersectoral collaboration between the public health, the livestock department and local communities. More specifically, such collaboration should integrate leptospirosis surveillance in both public and animal health for a better control of diseases in livestock while promoting public health prevention as encouraged by the One Health approach.

Different response of the taxonomic, phylogenetic and functional diversity of birds to forest fragmentation

Habitat fragmentation is considered as major threat to biodiversity worldwide. Biodiversity can be described as taxonomic, functional and phylogenetic diversity. However, the effect of forest fragmentation on taxonomic, phylogenetic and functional diversity is barely understood. We compare the response of taxonomic (species richness), phylogenetic and functional diversity of birds to forest fragmentation. We hypothesised that with increasing forest patch isolation and/or decreasing patch size the diversity of birds decreases but only if certain thresholds of fragmentation metrics are reached. Specifically, we hypothesized that out of the three diversity components the taxonomic diversity is the most sensitive to forest fragmentation, which means that it starts declining at larger patch size and higher connectivity values than phylogenetic and functional diversity do. We compared the three biodiversity metrics of central European bird species in a large set of forest patches located in an agricultural landscape. General additive modeling and segmented regression were used in analyses. Habitat fragmentation differentially affected studied biodiversity metrics. Bird taxonomic diversity was the most responsive towards changes in fragmentation. We observed an increase in taxonomic diversity with increasing patch area, which then stabilized after reaching certain patch size. Functional diversity turned out to be the least responsive to the fragmentation metrics and forest stand characteristics. It decreased linearly with the decreasing isolation of forest patches. Apart from the habitat fragmentation, bird taxonomic diversity but not phylogenetic diversity was positively associated with forest stand age. The lower share of dominant tree species, the highest taxonomic diversity was. While preserving a whole spectrum of forests (in terms of age, fragmentation and size) is important from the biodiversity perspective, forest bird species might need large, intact, old-growth forests. Since the large and intact forest becomes scarcer, our study underscore their importance for the preservation of forest specialist species.

A hierarchy of environmental covariates control the global biogeography of soil bacterial richness

Soil bacterial communities are central to ecosystem functioning and services, yet spatial variations in their composition and diversity across biomes and climatic regions remain largely unknown. We employ multivariate general additive modeling of recent global soil bacterial datasets to elucidate dependencies of bacterial richness on key soil and climatic attributes. Although results support the well-known association between bacterial richness and soil pH, a hierarchy of novel covariates offers surprising new insights. Defining climatic soil water content explains both, the extent and connectivity of aqueous micro-habitats for bacterial diversity and soil pH, thus providing a better causal attribution. Results show that globally rare and abundant soil bacterial phylotypes exhibit different levels of dependency on environmental attributes. Surprisingly, the strong sensitivity of rare bacteria to certain environmental conditions improves their predictability relative to more abundant phylotypes that are often indifferent to variations in environmental drivers.

Refurbishment of office buildings in New Zealand: identifying priorities for reducing environmental impacts

In recent years, the building sector has highlighted the importance of operational energy and efficient resource management in order to reduce the environmental impacts of buildings. However, differences in building-specific properties (building location, size, construction material, etc.) pose a major challenge in development of generic policy on buildings. The aim of this study was to investigate the relationship between energy and resource management policies, and building-specific characteristics on environmental impacts of refurbished office buildings in New Zealand. Life Cycle Assessment (LCA) was performed for 17 office buildings operating under seven representative climatic conditions found in New Zealand. Each building was assessed under four policy scenarios: (i) business-as-usual, (ii) use of on-site photovoltaic (PV) panels, (iii) electricity supply from a renewable energy grid, and (iv) best practice construction activities adopted at site. The influence of 15 building-specific characteristics in combination with each scenario was evaluated. The study adopted regression analysis, more specifically Kruskal-Wallis and General Additive Modeling (GAM), to support interpretation of the LCA results. All the chosen policies can significantly contribute to climate change mitigation as compared to business-as-usual. However, the Kruskal-Wallis results highlight policies on increasing renewable energy sources supplying national grid electricity can substantially reduce the impacts across most environmental impact categories. Better construction practices should be prioritized over PV installation as use of on-site PV significantly increases the environmental impacts related to use of resources. The GAM results show on-site PV could be installed in low-rise buildings in regions with long sunshine hours. The results also show the strong influence of facade elements and technical equipment in determining the environmental performance of small and large buildings, respectively. In large multi-storied buildings, efficient HVAC and smaller window area are beneficial features, while in small buildings the choice of facade materials with low embodied impacts should be prioritized. In general, the study highlighted the importance of policies on increasing renewable energy supply from national grid electricity to substantially reduce most of the impacts related to buildings. In addition, the study also highlighted the importance of better construction practices and building-specific characteristics to reduce the impacts related to resource use. These findings can support policy makers to prioritize strategies to improve the environmental performance of existing buildings in New Zealand and in regions with similar building construction and climate.

Landscape and flow path-based nutrient loading metrics for evaluation of in-stream water quality in Saginaw Bay, Michigan

Abstract Landscape metrics are often used to model nonpoint source pollution from agricultural and urban surface runoff. By considering topography and the spatial arrangement of land cover, landscape metrics can better account for hydrologic connectivity, loading quantity, and vegetated buffer filtering between nutrient loading sources and streams. For this study we develop a surface runoff nutrient loading metric that considers source (i.e. cropland or developed) loading and buffer filtering along hydrologic transport vectors, or flow paths. We use General Additive Modeling to evaluate the relationship between this metric and in-stream nitrogen (N) and phosphorus (P) concentrations in the Saginaw Bay watershed in Michigan, US and compare the relative predictive power between this metric and other landscape metrics that do not consider hydrologic connectivity. The flow path-based cropland loading metric was a stronger predictor of in-stream NO3 concentrations than alternative metrics. In-stream P concentrations were best predicted by models that included 48-h antecedent precipitation and catchment-wide proportion of developed landcover. Metric maps reveal high nutrient loading areas where only a small proportion of loading reaches streams via surface runoff, highlighting the need to consider nutrient loading via drainage tiles and other subsurface pathways in efforts to quantify nonpoint source loading to surface waters. The flow path-based loading metric is represented spatially as a gridded dataset showing estimates of nutrient loading adjacent to streams, and with higher resolution stream delineation data it could be used by land managers to target locations for precision buffer placement to intercept surface runoff and reduce nutrient loading.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines

BackgroundSeveral studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting.MethodsDengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 – December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated.ResultsAmong the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model.ConclusionThe study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Selective enhancement of orientation tuning before saccades.

Saccadic eye movements cause a rapid sweep of the visual image across the retina and bring the saccade's target into high-acuity foveal vision. Even before saccade onset, visual processing is selectively prioritized at the saccade target. To determine how this presaccadic attention shift exerts its influence on visual selection, we compare the dynamics of perceptual tuning curves before movement onset at the saccade target and in the opposite hemifield. Participants monitored a 30-Hz sequence of randomly oriented gratings for a target orientation. Combining a reverse correlation technique previously used to study orientation tuning in neurons and general additive mixed modeling, we found that perceptual reports were tuned to the target orientation. The gain of orientation tuning increased markedly within the last 100 ms before saccade onset. In addition, we observed finer orientation tuning right before saccade onset. This increase in gain and tuning occurred at the saccade target location and was not observed at the incongruent location in the opposite hemifield. The present findings suggest, therefore, that presaccadic attention exerts its influence on vision in a spatially and feature-selective manner, enhancing performance and sharpening feature tuning at the future gaze location before the eyes start moving.

Use of Wind Fetch and Shoreline Relief to Predict Nearshore Substrate Composition in a North Temperate Lake

AbstractSpawning habitat assessments often focus on substrate composition, but few studies have predicted shoal substrates by using environmental factors. We developed a model for predicting shoal substrates in Belle Lake, Minnesota, using wind fetch and shoreline relief characteristics. Percent composition of four substrate classes (silt, sand, gravel, and rock), water depth estimated at 1 m from shore (shoal slope), effective wind fetch measured using a GIS model, and riparian bank height derived from LIDAR imaging were determined at 50 transects. Classification and regression tree (CART) analysis grouped substrates into categories, and general additive modeling described the effects of three predictor variables on the percent composition of substrate classes. The CART analysis correctly grouped 39 of 50 transects into four categories, and misclassifications primarily resulted from the movement of sand. Effective fetch most influenced silt (low fetch) and rock (high fetch) substrate classes, shoal slope was predictive of rock, and riparian height was useful in distinguishing sand from gravel. These results demonstrate the utility of a single empirical model for determining shoal substrate composition. Fisheries managers can use this technique to determine potential fish spawning locations and identify potential areas for habitat restoration or protection projects.Received December 5, 2016; accepted May 5, 2017 Published online July 19, 2017

"Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction": Correction to Sullivan et al. (2016).

Reports an error in "Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction" by Edith V. Sullivan, Ty Brumback, Susan F. Tapert, Rosemary Fama, Devin Prouty, Sandra A. Brown, Kevin Cummins, Wesley K. Thompson, Ian M. Colrain, Fiona C. Baker, Michael D. De Bellis, Stephen R. Hooper, Duncan B. Clark, Tammy Chung, Bonnie J. Nagel, B. Nolan Nichols, Torsten Rohlfing, Weiwei Chu, Kilian M. Pohl and Adolf Pfefferbaum (Neuropsychology, 2016[May], Vol 30[4], 449-473). A problem with a computation to invert speed scores is noted and explained in this correction. All statements indicating group differences in speed scores, as well as Table 5 and Figure 8A, have been corrected in the online version of this article. (The following abstract of the original article appeared in record 2016-00613-001.) To investigate development of cognitive and motor functions in healthy adolescents and to explore whether hazardous drinking affects the normal developmental course of those functions. Participants were 831 adolescents recruited across 5 United States sites of the National Consortium on Alcohol and NeuroDevelopment in Adolescence 692 met criteria for no/low alcohol exposure, and 139 exceeded drinking thresholds. Cross-sectional, baseline data were collected with computerized and traditional neuropsychological tests assessing 8 functional domains expressed as composite scores. General additive modeling evaluated factors potentially modulating performance (age, sex, ethnicity, socioeconomic status, and pubertal developmental stage). Older no/low-drinking participants achieved better scores than younger ones on 5 accuracy composites (general ability, abstraction, attention, emotion, and balance). Speeded responses for attention, motor speed, and general ability were sensitive to age and pubertal development. The exceeds-threshold group (accounting for age, sex, and other demographic factors) performed significantly below the no/low-drinking group on balance accuracy and on general ability, attention, episodic memory, emotion, and motor speed scores and showed evidence for faster speed at the expense of accuracy. Delay Discounting performance was consistent with poor impulse control in the younger no/low drinkers and in exceeds-threshold drinkers regardless of age. Higher achievement with older age and pubertal stage in general ability, abstraction, attention, emotion, and balance suggests continued functional development through adolescence, possibly supported by concurrently maturing frontal, limbic, and cerebellar brain systems. Determination of whether low scores by the exceeds-threshold group resulted from drinking or from other preexisting factors requires longitudinal study.

Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction.

To investigate development of cognitive and motor functions in healthy adolescents and to explore whether hazardous drinking affects the normal developmental course of those functions. Participants were 831 adolescents recruited across 5 United States sites of the National Consortium on Alcohol and NeuroDevelopment in Adolescence 692 met criteria for no/low alcohol exposure, and 139 exceeded drinking thresholds. Cross-sectional, baseline data were collected with computerized and traditional neuropsychological tests assessing 8 functional domains expressed as composite scores. General additive modeling evaluated factors potentially modulating performance (age, sex, ethnicity, socioeconomic status, and pubertal developmental stage). Older no/low-drinking participants achieved better scores than younger ones on 5 accuracy composites (general ability, abstraction, attention, emotion, and balance). Speeded responses for attention, motor speed, and general ability were sensitive to age and pubertal development. The exceeds-threshold group (accounting for age, sex, and other demographic factors) performed significantly below the no/low-drinking group on balance accuracy and on general ability, attention, episodic memory, emotion, and motor speed scores and showed evidence for faster speed at the expense of accuracy. Delay Discounting performance was consistent with poor impulse control in the younger no/low drinkers and in exceeds-threshold drinkers regardless of age. Higher achievement with older age and pubertal stage in general ability, abstraction, attention, emotion, and balance suggests continued functional development through adolescence, possibly supported by concurrently maturing frontal, limbic, and cerebellar brain systems. Determination of whether low scores by the exceeds-threshold group resulted from drinking or from other preexisting factors requires longitudinal study. (PsycINFO Database Record

Temporal segregation of the Australian and Antarctic blue whale call types (Balaenoptera musculus spp.).

We examined recordings from a 15-month (May 2009–July 2010) continuous acoustic data set collected from a bottom-mounted passive acoustic recorder at a sample frequency of 6kHz off Portland, Victoria, Australia (38°33′01″S, 141°15′13″E) off southern Australia. Analysis revealed that calls from both subspecies were recorded at this site, and general additive modeling revealed that the number of calls varied significantly across seasons. Antarctic blue whales were detected more frequently from July to October 2009 and June to July 2010, corresponding to the suspected breeding season, while Australian blue whales were recorded more frequently from March to June 2010, coinciding with the feeding season. In both subspecies, the number of calls varied with time of day; Antarctic blue whale calls were more prevalent in the night to early morning, while Australian blue whale calls were detected more often from midday to early evening. Using passive acoustic monitoring, we show that each subspecies adopts different seasonal and daily call patterns which may be related to the ecological strategies of these subspecies. This study demonstrates the importance of passive acoustics in enabling us to understand and monitor subtle differences in the behavior and ecology of cryptic sympatric marine mammals.

Money balances in the production function: Nonlinear tests of model stability and measurement issues – two sides of the same coin?

Past empirical attempts to test the role of money in the production function following the Sinai and Stokes (1972) preliminary Cobb–Douglas model specification estimated in 1929–1967, using yearly data, have focused on estimating alternative production function models, such as CES and Translog, and experimenting with alternative specifications of the monetary variable. Most research in the United States on this topic has involved four basic datasets: annual data in the period 1929–1967, nonfinancial quarterly data in the period 1953:1 to 1977:3, annual data in the period 1930–1978 and annual data in the period 1959–1985. The current research uses MARS modeling, general additive modeling, flexible least squares and VAR methods to assess whether there is evidence of nonlinearity and/or model structural change that is impacted by whether a monetary variable has been added to the model specification or a different period is under study. VAR modeling is used with the nonfinancial quarterly dataset to assess whether shocks in the financial sector, as measured by log real M2, can impact the real sector. Since a significant impact is found on log capital, log labor and log real output, the implication is that the real sector is not isolated from the financial sector. One way to think of this is that shocks to the financial sector can have dynamic effects on the real sector.