Generalized Additive Models

The environmental processes associated with the climatic oscillations that drive variability in swordfish catch rates are largely unexplored. This study used generalized additive models fitted to longline fishery data to investigate relationships between environmental variables and catch rates to understand the processes influencing swordfish distributions in the Indian Ocean. The catch rates and distribution of swordfish in the Indian Ocean were sensitive to climatic and environmental variation. The environmental effects differ between the northwest and southwest Indian Ocean. The predicted relative abundance reveals a notable increase along the western coast of the northwest Indian Ocean during nominal Indian Ocean Dipole and negative Southern Indian Ocean Dipole (IOSD) events, and is related to the changes in net primary production and shallow mixed layer depth. The predicted relative abundances also show that the distribution of lower sea surface temperature and sea surface height deviation surrounding Madagascar increased during negative IOSD events in the southwest Indian Ocean.

(released open access: https://pubs.asha.org/doi/10.1044/2019_JSLHR-S-CSMC7-18-0208)
This study examines the temporal organization of vocalic anticipation in German children from 3 to 7 years of age and adults. The main objective was to test for non-linear processes in vocalic anticipation, which may result from the interaction between lingual gestural goals for individual vowels, and those for their neighbours over time.
The technique of ultrasound imaging was employed to record tongue movement at five time points throughout short utterances of the form V1#CV2. Vocalic anticipation was examined with Generalized Additive Modeling, an analytical approach allowing for the estimation of both linear and non-linear influences on anticipatory processes.
Adults and children exhibited non-linear patterns of vocalic anticipation over time with the degree and extent of vocalic anticipation varying as a function of the individual consonants and vowels assembled. However, noticeable developmental discrepancies were found with vocalic anticipation being present earlier in children's utterances at 3-4-5 years of age in comparison to adults and to some extent 7-year-old children.
A developmental transition towards more contextually-specified coarticulatory organizations seems to occur from kindergarten to primary school to adulthood. In adults, non-linear anticipatory patterns over time suggest a strong differentiation between the gestural goals for consecutive segments. In children, this differentiation is not yet mature: variations in the temporal overlap of lingual gestures for consecutive segments are present but vowels show greater prominence over time and seem activated more in-phase with those of previous segments relative to adults.

Spatial data exists practically everywhere, including the oil and gas industry. Several factors drive the distribution of the location of oil and gas wells: performance of existing wells, available acreage, need for operators to maintain a certain amount of production and to stay competitive. Some of the important parameters to consider in the design of a completion job for an unconventional oil and gas well are the length of lateral (and by extension perforated interval), number of stages, total pounds of proppants, total volume of fluid pumped, injection pressure and injection rate. In big data analytics and building of a regression model to capture the effects of these parameters on oil production, the practice has been to analyze wells in similar formations or similar basins, even when these wells are miles apart. Due to the presence of spatial autocorrelation and non-stationarity in such data, the recommended practice should be to take these spatial dependencies into account by using geographically weighted regression (GWR). In this paper, we present an application of GWR in location-based regression modeling to capture the effect of these completion parameters on the first six months of oil production in 5700 wells in the Bakken and Three Forks formation in North Dakota. GWR builds different models for every location, leading to a spatial distribution of variable coefficients. This model is well suited to capture both local and global variations in our dependent variable. We also compare the results obtained with that of three other models: multiple regression model, artificial neural network model and universal kriging. Just like the use of kriging, GWR model resulted in a much-improved prediction of oil production as captured by the goodness-of-fit diagnostics (R squared, AIC, and RMSPE), compared to the other two non-location-based models. We recommend the use of the GWR model in the prediction of oil or gas production when spatial non-stationarity exists.

Rastrelliger kanagurta is among the pelagic fish of commercial value caught in the archipelagic waters of Spermonde, Indonesia. The dynamic oceanographic pattern in this area influences the distribution of this pelagic fish. Understanding the relationship between the distribution of fish and environmental factors is important in exploring fisheries resources. This study used Rastrelliger kanagurta fishing-catch data during the high-catch season in the second quarter, which was from April to June (2008 and 2009), and satellite data of chlorophyll-a (chl-a), and sea surface temperature (SST) from MODIS-Aqua. The study aimed to identify the relationship between fish distribution with chl-a and SST constructed using the Generalized Additive Model (GAM), detect the potential fishing grounds, and determine the impact of climate change on fish distribution based on temperature projection of IPCC-AR5-RCPs. The distribution of Rastrelliger kanagurta was significantly associated (p < 0.0001) with the preferred range of chl-a at 0.30–0.40 mg/m 3 and SST at 30.00–31.00 °C. The potential fishing ground maps showed that areas with high potential catch were located near the coast to offshore (3–20 M), with acceptable level of map accuracy at 83.34%; with kappa value at 0.70. Increased temperature of 1.80 °C resulted in movement of potential fishing grounds to the southern part of Makassar Straits leading to the archipelagic waters of Spermonde. In contrast, increased temperature of 2.60 °C and 3.30 °C resulted in lesser potential fishing grounds area which shifted further to the south. The results of this study indicated applicability of remote sensing in contributing to optimal fishing effort and decision making for long-term management of Rastrelliger kanagurta resources.

RESUMO Previsões de curto prazo da geração eólica constituem informações fundamentais para a integração segura e econômica de parques eólicos à um sistema elétrico de potência. No presente trabalho apresenta-se um modelo aditivo generalizado para previsão dos quantis da geração eólica (regressão quantílica), a partir dos quais se obtém uma previsão da densidade de probabilidade da produção de um parque eólico. A metodologia foi implementada no programa computacional VENTOS. Para ilustrar a aplicação da metodologia e as funcionalidades do programa apresentam-se os resultados de um experimento computacional com dados reais de um parque eólico localizado na Galícia, Espanha. ABSTRACT Short-term wind power forecasts are fundamental information for the safe and economic integration of wind farms into an electric power system. In this work we present a generalized additive model to predict the wind power quantiles (quantile regression) from which we obtain a prediction of the wind power probability density function in a wind farm. The methodology was implemented in the VENTOS computational program. In order to illustrate the application of the methodology as well as the functionalities of the program this work presents the results achieved by a computational experiment based on real data from a wind farm located in Galicia, Spain.

Bilingualism has been linked to structural adaptations of subcortical brain regions that are important nodes in controlling of multiple languages. However, research on the location and extent of these adaptations has yielded variable patterns. Existing literature on bilingualism-induced brain adaptations has so far largely overseen evidence from other domains that experience-based structural neuroplasticity often triggers non-linear adaptations which follow expansion-renormalisation trajectories. Here we use generalised additive mixed models (GAMMs) to investigate the non-linear effects of quantified bilingual experiences on the basal ganglia and thalamus in a sample of bilinguals with wide range of bilingual experiences. Our results revealed that volumes of bilateral caudate nuclei and accumbens were positively related to bilingual experiences in a non-linear pattern, with increases followed by decreases, in the most experienced bilinguals, suggesting a return to baseline volume at higher levels of bilingual experience. Moreover, volumes of putamen and thalamus were positively linearly predicted by bilingual experiences. The results offer the first direct evidence that bilingualism, similarly to other cognitively demanding skills, leads to dynamic subcortical structural adaptations which can be nonlinear, in line with expansion-renormalisation models of experience-dependent neuroplasticity.

1. Palaeoecological records of species richness spanning time intervals over which climate variables have shifted relative to one another can help reduce issues of colinearity that might affect our understanding of patterns of species richness.

Small-scale fisheries (SSFs) constitute a substantial component of European fisheries and have a high socioeconomic importance, especially for remote insular areas. Traps produce catches of high quality and value, associated with limited bycatch and low habitat impact. Long-standing trap SSFs in both the Mediterranean and the Atlantic showcase the potential of such SSFs to support remote fishing communities; however, trap SSFs remain relatively understudied. Here, we investigate the spatial and temporal dynamics of a Greek trap SSF targeting Plesionika narval (Fabricius, 1787) in the eastern Mediterranean, by means of Generalized Additive Models fitted on fishers' logbook data from 2005 to 2014. The dynamics of both catch per unit effort (CPUE) and profits suggest a pronounced seasonality for this fishery, while there are also signs of local overexploitation in the traditional fishing grounds. Additionally, small vessels (\ 12 m) report higher CPUEs than larger vessels. Our results point to management measures that could improve the sustainability of this valuable SSF, such as changes in the spatial and temporal allocation of fishing effort, and in fleet composition. The insights gained from this study are relevant to other localized trap SSFs and illustrate().,-volV) (0123456789().,-volV)

1. Our understanding of a biological population can be greatly enhanced by modelling their distribution in space and as a function of environmental covariates. Such models can be used to investigate the relationships between distribution and environmental covariates as well as reliably estimate abundances and create maps of animal/ plant distribution. 2. Density surface models consist of a spatial model of the abundance of a biological population which has been corrected for uncertain detection via distance sampling methods. 3. We review recent developments in the field and consider the likely directions of future research before focussing on a popular approach based on generalized additive models. In particular, we consider spatial modelling techniques that may be advantageous to applied ecologists such as quantification of uncertainty in a two-stage model and smoothing in areas with complex boundaries. 4. The methods discussed are available in an R package developed by the authors (dsm) and are largely implemented in the popular Windows software Distance.

Long-term studies are necessary to gain insight into the influence of external climate forcing on zooplankton dynamics. Using monthly time series (1993–2010) collected in the Cantabrian Sea (southern Bay of Biscay), we studied long-term trends and seasonal cycles of zooplankton abundance and biomass along a coastal-ocean gradient. We also analysed changes in environmental variables such as sea surface temperature (SST) and chlorophyll a concentration. Zooplankton abundance and biomass increased during the study period, with greater increases in biomass towards the coast and for larger size classes. These results contrast with the decrease in biomass and size expected under global warming, which is shown in the region by the rise in summer SST, suggesting the operation of other processes. Indeed, winter mixing and coastal upwelling were key drivers of zooplankton dynamics in spring and autumn, respectively. In these seasons, zooplankton inter-annual increases were stronger. Including these hydrographic processes in future models of zooplankton dynamics for the Bay of Biscay and other temperate areas will improve their accuracy. Our results highlight the importance of disentangling the main mechanisms behind long-term changes in zooplankton, especially within the context of climate change.

Background: Pneumonia is a common cause of childhood hospitalization. Both host and pathogen factors are associated with environmental conditions, but the associations between childhood pneumonia and meteorological variables are unclear. This study investigated the short-term associations between childhood pneumonia admissions and meteorological variables.
Methods: A retrospective time-series analysis was conducted using distributed lagged nonlinear models. Daily pneumonia admissions among children <15-year-old in Hong Kong during 2004–2011 were regressed on daily meteorological variables with air pollutants, influenza admissions, seasonal trend, and long-term trend adjusted. Analyses were stratified by age group.
Results: There were 34,303 admissions during 2004–2011. Temperature had a u-shaped association with childhood pneumonia admissions with minimum morbidity temperature at 25°C and with a long lagged effect up to 45 days. The cumulative relative risk (cum RR [95% confidence interval]) (vs. 25°C; lag 0–45 days) at 30°C was 1.41 (1.11, 1.79) and was 1.58 (1.21, 2.06) at 12°C. Relative humidity (RH) showed a u-shaped association with minimum risk at 65% and lagged effect up to 45 days. The cum RR (vs. 65%; lag 0–45 days) at 53% was 1.26 (1.04, 1.54) and was 2.22 (1.78, 2.77) at 94%. Children 5- to 14-year- olds were highly sensitive to temperature and RH while admissions among children <5-year-old were only associated with high RH. Conclusions: Childhood pneumonia admissions were very strongly associated with both high and low temperature and RH for children
5–14-year-olds. Efforts to reduce exposure of children to extreme temperatures and RH may have the potential to reduce the burden of pediatric pneumonia.

Satellite-linked dive recorders were attached to 53 harbor seal pups in Prince William Sound (PWS) and at Tugidak Island, Alaska, during 1997-1999. We used generalized additive models and bootstrap techniques to describe pup diving behavior during their first year of life. Pups increased their ability to dive during the first 3-6 mo, as indicated by increases in proportion of time in the water (time wet) and maximum dive depth achieved by a pup each day (max-depth) values. Time wet and/or max-depth later decreased, suggesting a seasonal component to diving behavior. Monthly time wet varied from an overall minimum of 0.68 at tagging in July to a maximum of 0.89 in November. Pups spent half of their time wet swimming in water <25 m deep, the shallowest 30% of the available water column. They spent only 5% of their time swimming in the deepest 30% of the available water column, at depths >60-70 m. This strongly suggests they were not feeding on or near bottom during their first year. Average maxdepths and deepest actual dives were similar for PWS and Tugidak pups. PWS pups dove deeper sooner and spent less time wet than Tugidak pups during the first few months after tagging, probably as a result of regional bathymetric differences. Diving behavior and body condition suggest that food availability was not 1 Current address: 73-

Studies have shown that environmental variables significantly affect variation in stock abundance of marine populations. The northern Gulf of California (NGC) is a highly productive region of interest due to its fish resources and diversity. Conservation of the marine species inhabiting the region is of public interest. Our study analysed the influence of physical environmental factors on several commercial marine species, using catch per unit effort (CPUE) as a proxy for abundance. Generalized additive models were used to test the significance of selected environmental variables on stock abundance. Deseasonalized cross-correlation analysis was used to examine time-lagged correlations between CPUE and abiotic variables to identify response timings. The results suggest that for most commercial species the sea surface temperature and the long-term climate Pacific Decadal Oscillation index are the predominant predictors for species abundance, followed by the Colorado River discharge. The Multivariate ENSO Index and the Pacific-North American pattern indices also showed specific effects on certain species. The NGC is a highly dynamic region, where species respond to environmental changes according to the characteristics of their life histories.

Keywords: physical environmental variables; abundance of commercial marine species; northern Gulf of California; Colorado River discharge; sea surface temperature.

Efectos de la variabilidad ambiental en la abundancia de especies marinas comerciales en el norte del golfo de California.

Resumen: Diversas investigaciones han demostrado que las variables ambientales influyen significativamente en la varia-ción en la abundancia de las poblaciones marinas. El norte del golfo de California (NGC) es una región altamente productiva de interés por sus recursos pesqueros y biodiversidad. La conservación de las especies marinas en la región es de interés público. Nuestro estudio analizó la influencia de los factores ambientales físicos sobre varias especies marinas comerciales, usando la captura por unidad de esfuerzo (CPUE) como proxy de la abundancia. Se usaron modelos de aditivos generalizados para probar que variables ambientales influyen significativamente sobre la abundancia del stock. Se utilizó un análisis de correlación cruzada desestacionalizado para examinar correlaciones con retraso entre la CPUE y las variables abióticas para identificar tiempos de respuesta. Los resultados sugieren que para la mayoría de las especies comerciales, la temperatura superficial del mar y el índice de la Oscilación Decadal del Pacífico son los predictores predominantes de la abundancia de especies, seguidos de la descarga del río Colorado. El índice multivariado ENOS y el índice del Patrón del Pacífico de Améri-ca del Norte mostraron efectos en algunas especies. El NGC es una región altamente dinámica, donde las especies responden a los cambios ambientales de acuerdo con las características de sus historias de vida.

Palabras clave: variables ambientales físicas; especies marinas comerciales; norte del golfo de California; descarga del río Colorado; temperatura superficial del mar.

Citation/Como citar este artículo: Ruiz-Barreiro T.M., Arreguín-Sánchez F., González-Baheza A., Hernández-Padilla J.C. 2019. Effects of environmental variability on abundance of commercial marine species in the northern Gulf of California. Sci. Mar. 83(3): 000-000.  Editor: V. Stelzenmüller.

Link: http://scimar.icm.csic.es/scimar/index.php/secId/6/IdArt/4545/

The spring phytoplankton bloom plays a key role in the dynamics of temperate and polar seas. Nevertheless, the mechanisms and processes behind these blooms remain a subject of considerable debate. We analyzed the influence of deep mixing during winter on the spring phytoplankton bloom in the Cantabrian Sea (southern Bay of Biscay). To this end, we combined long-term physical and biogeochemical in situ data (1993–2012) and satellite observations (1997–2012). Deeper winter mixing led to higher nitrate and chlorophyll concentrations through the water column during the spring bloom. However, this effect was modified by short-term variability in near-surface stratification in spring. Winter-mixing preconditioning also influenced different spring bloom metrics: deeper and later mixing in winter was followed by later blooms with a larger peak. In these enhanced blooms, nitrate was taken up at faster rates, indicating higher rates of phytoplankton production. Winters with weaker mixing (that led to weaker spring blooms) were associated with warmer surface temperatures. This relationship suggests that the multi-decadal trend toward warmer surface temperatures in the Bay of Biscay may promote a decrease in the magnitude of the spring bloom, which could impact upper trophic levels and also deep carbon export in the future.