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Likely year-round presence of beaked whales in the Bay of Biscay

HYDROBIOLOGIA 2022年第10期849卷 2225-2239页

作者： Robbins, J. R. Bell, E. Potts, J. Babey, L. Marley, S. A. Univ Portsmouth Inst Marine Sci Ferry Rd Portsmouth PO4 9LY Hants England Brittany Ctr ORCA Wharf Rd Portsmouth PO2 8RU Hants England Scotlands Rural Coll SRUC Craibstone Estate Aberdeen AB21 9YA Scotland

Beaked whales are cryptic and difficult to study species, often distributed in deep offshore waters and only briefly visible at the surface. A diverse range of cetacean species has been documented in the Bay of Biscay, including several species of beaked whales. However, little is known about how persistent their presence is. Citizen science data collected during ferry-based surveys between 2006 and 2018 were analysed to investigate how encounter rates varied across space and time, and their drivers for beaked whale species. Approximately 244,400 km were surveyed, and there were 419 encounters with beaked whales recorded including Cuvier's beaked whales, (n = 260), Northern bottlenose whales (n = 19), Sowerby's beaked whales (n = 13), and True's beaked whales (n = 1). generalized additive models revealed that encounters were generally more frequent in the southern bay, on northern facing slopes, with all species except Sowerby's showing a preference for both deep waters and shallow shelf waters. Animals were recorded in each of the eight surveyed months, suggesting that beaked whales may be present year-round, with increased encounter rates in summer months. This study is the first to indicate that beaked whales may persist in this area throughout the year, which is key information for appropriate management.

关键词： Beaked whales Conservation Bay of Biscay Seasonality generalized additive models

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Variation in the distribution of yellowfin sole Limanda aspera larvae in warm and cold years in the eastern Bering Sea

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FISHERIES OCEANOGRAPHY 2022年第1期31卷 108-122页

作者： Porter, Steven M. NOAA Natl Marine Fisheries Serv Recruitment Proc Program Resource Assessment & Conservat Engn DivAlaska F 7600 Sand Point Way NE Seattle WA 98115 USA

Multiyear periods of relatively cold temperatures (2007-2013) and warm temperatures (2001-2005 and 2014-2018) altered the eastern Bering Sea ecosystem, affecting ocean currents and wind patterns, plankton community, and spatial distribution of fishes. Yellowfin sole Limanda aspera larvae were collected from the inner domain (<= 50 m depth) of the eastern Bering Sea among four warm years (2002, 2004, 2005, 2016), an average year (2006), and three cold years (2007, 2010, 2012). Spatial distribution and density of larvae among those years was analyzed using generalized additive models that included timing of sea-ice retreat, areal coverage of water <= 0 degrees C, and water temperature as covariates. Analyses indicated a combination of temperature effects on the location and timing of spawning, and on egg and larval survival, may explain the variation in larval density and distribution among years. During warm years, higher density and wider spatial distribution of larvae may be due to earlier spawning, an expansion of the spawning area, and higher egg and larvae survival due to favorable temperatures. Larval distribution contracted shoreward, and density was lower during cold conditions and was likely due to fish spawning closer to shore to remain in preferred temperatures, later spawning, and increased mortality. Predicted drift trajectories from spawning areas showed that larvae would reach nursery grounds in most years. Years when the drift period was longer than the pelagic phase of the larvae occurred during both warm and cold conditions indicating that settlement outside of nursery areas could happen during either temperature condition.

关键词： Bering Sea climate change fish larvae flatfish generalized additive models spatial distribution yellowfin sole

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INTENSITY ESTIMATION ON GEOMETRIC NETWORKS WITH PENALIZED SPLINES

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ANNALS OF APPLIED STATISTICS 2022年第2期16卷 843-865页

作者： Schneble, Marc Kauermann, Goeran Ludwig Maximilians Univ Munchen Dept Stat Munich Germany

In the past decades the growing amount of network data lead to many novel statistical models. In this paper we consider so-called geometric networks. Typical examples are road networks or other infrastructure networks. Nevertheless, the neurons or the blood vessels in a human body can also be interpreted as a geometric network embedded in a three-dimensional space. A network-specific metric, rather than the Euclidean metric, is usually used in all these applications, making the analyses of network data challenging. We consider network-based point processes, and our task is to estimate the intensity (or density) of the process which allows us to detect high- and low-intensity regions of the underlying stochastic processes. Available routines that tackle this problem are commonly based on kernel smoothing methods. This paper uses penalized spline smoothing and extends this toward smooth intensity estimation on geometric networks. Furthermore, our approach easily allows incorporating covariates, enabling us to respect the network geometry in a regression model framework. Several data examples and a simulation study show that penalized spline-based intensity estimation on geometric networks is a numerically stable and efficient tool. Furthermore, it also allows estimating linear and smooth covariate effects, distinguishing our approach from already existing methodologies.

关键词： Intensity estimation of stochastic point processes generalized additive models geometric networks penalized splines poisson regression with offset spats tat package

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Wetland hydropattern and vegetation greenness predict avian populations in Palo Verde, Costa Rica

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ECOLOGICAL APPLICATIONS 2022年第2期32卷 1-17页

作者： Barchiesi, Stefano Alonso, Alice Pazmino-Hernandez, Marco Serrano-Sandi, Juan M. Munoz-Carpena, Rafael Angelini, Christine Univ Florida Sch Nat Resources & Environm Black Hall Gainesville FL 32611 USA Catholic Univ Louvain Earth & Life Inst Environm Sci Croix Sud 2 B-1348 Louvain La Neuve Walloon Brabant Belgium Univ Florida Agr & Biol Engn Dept Frazier Rogers Hall Gainesville FL 32611 USA Org Trop Studies Palo Verde Biol Res Stn Parque Nacl Palo Verde Bagaces 50401 Guanacaste Costa Rica Univ Florida Engn Sch Sustainable Infrastruct & Environm Dept Environm Engn Sci Weil Hall Gainesville FL 32611 USA

Many wetlands around the world that occur at the base of watersheds are under threat from land-use change, hydrological alteration, nutrient pollution, and invasive species. A relevant measure of whether the ecological character of these ecosystems has changed is the species diversity of wetland-dependent waterbirds, especially those of conservation value. Here, we evaluate the potential mechanisms controlling variability over time and space in avian species diversity of the wetlands in the Palo Verde National Park, a Ramsar Site of international importance in Costa Rica. To do so, we assessed the relative importance of several key wetland condition metrics (i.e., surface water depth, wetland extent, and vegetation greenness), and temporal fluctuations in these metrics, in predicting the abundance of five waterbirds of high conservation value as well as overall waterbird diversity over a 9-yr period. generalized additive models revealed that mean NDVI, an indicator of vegetation greenness, combined with a metric used to evaluate temporal fluctuations in the wetland extent best predicted four of the five waterbird species of high conservation value as well as overall waterbird species richness and diversity. Black-bellied Whistling-ducks, which account for over one-half of all waterbird individuals, and all waterbird species together were better predicted by including surface water depth along with wetland extent and its fluctuations. Our calibrated species distribution model confidently quantified monthly averages of the predicted total waterbird abundances in seven of the 10 sub-wetlands making up the Ramsar Site and confirmed that the biophysical diversity of this entire wetland system is important to supporting waterbird populations both as a seasonal refuge and more permanently. This work further suggests that optimizing the timing and location of ongoing efforts to reduce invasive vegetation cover may be key to avian conservation by increasing waterbird habitat

关键词： biodiversity conservation dry tropics ecological character environmental monitoring generalized additive models normalized difference vegetation index Ramsar Convention remote sensing species distribution models waterbirds wetland extent

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Particulate Matter Component Analyses in Relation to Public Health in Canada

Particulate Matter Component Analyses in Relation to Public ...

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作者： Jarvis, Shannon Trent University (Canada)

学位级别：M.S., Master of Science/Master of Surgery

This thesis explores the shot-term relationship between exposure to ambient air pollution and human health through metrics such as mortality and hospitalization in Canada. We begin by detailing the organization and interpolation of air pollution data from its partially quality-controlled source form. Analyses of seasonal, regional and temporal trends of all major components of PM2.5, was performed, showing a seasonal variation across most regions and validating the dataset. A one-pollutant statistical generalized additive Model was applied to the data, estimating the health risk associated with exposure to thirteen different components of PM2.5. The selected components were based on those that compromised the majority of the mass and included: sulphate, nitrate, zinc, silicon, iron, nickel, vanadium, potassium, organic carbon, organic matter, elemental carbon, total carbon. Trends based on annual estimates of the association for PM2.5, and its constituents,were compared, showing that carbonaceous compounds, sulphate and nitrate had similar estimates of association. Many estimates, as is common in population ecologic epidemiology, had association estimates statistically indistinguishable from zero,but with clear features of interest, including evident differences between cold and warm season associations in Canada's temperate climate. A method to model two correlated pollutants (in this case, PM2.5 and O3) was developed using thin plate splines. In this approach, the location of the response surface (after accounting for the temperature, a smooth function of time and day of week) that corresponds to the average pollutant concentration and the average plus one unit was used as the estimate of the joint contribution of pollutants due to a unit increase. The estimates from the thin plate spline (TPS) approach were compared to the single pollutant models, with large increases and decreases in PM2.5 and O3 being captured in the TPS estimates. However, this approach indica

关键词： Air pollution Environmental epidemiology generalized additive models Human health Multivariate models Thin plate splines

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Analysis of the effect of meteorological factors on hemorrhagic fever with renal syndrome in Taizhou City, China, 2008-2020

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BMC PUBLIC HEALTH 2022年第1期22卷 1-9页

作者： Zhang, Rong Zhang, Ning Sun, Wanwan Lin, Haijiang Liu, Ying Zhang, Tao Tao, Mingyong Sun, Jimin Ling, Feng Wang, Zhen Zhejiang Prov Ctr Dis Control & Prevent Key Lab Vaccine Prevent & Control Infect Dis Zhej Hangzhou 310051 Zhejiang Peoples R China Puyan St Community Hlth Serv Ctr Binjiang Dist Hangzhou 310013 Zhejiang Peoples R China Taizhou City Ctr Dis Control & Prevent Taizhou 318000 Zhejiang Peoples R China Ningbo Univ Sch Med Ningbo 315000 Zhejiang Peoples R China

Background Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area. Methods Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS. Results The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 celcius, weekly highest temperature at 18 celciusrelative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09-1.82), 1.32 (95% CI: 1.05-1.66), 2.18 (95% CI: 1.16-4.07), and 1.91 (95% CI: 1.16-2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation. Conclusion Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.

关键词： Hemorrhagic fever with renal syndrome Distributed lag non-linear generalized additive models Lag effect Interactive effect

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Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change

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ANNALS OF BOTANY 2022年第7期129卷 787-794页

作者： Collette, Justin C. Sommerville, Karen D. Lyons, Mitchell B. Offord, Catherine A. Errington, Graeme Newby, Zoe-Joy von Richter, Lotte Emery, Nathan J. Australian Inst Bot Sci Australian Bot Garden Australian PlantBank Mt Annan NSW 2567 Australia Sch Biol Earth & Environm Sci Ctr Ecosyst Sci Sydney NSW 2052 Australia

Background and Aims Seed germination is strongly influenced by environmental temperatures. With global temperatures predicted to rise, the timing of germination for thousands of plant species could change, leading to potential decreases in fitness and ecosystem-wide impacts. The thermogradient plate (TGP) is a powerful but underutilized research tool that tests germination under a broad range of constant and alternating temperatures, giving researchers the ability to predict germination characteristics using current and future climates. Previously, limitations surrounding experimental design and data analysis methods have discouraged its use in seed biology research. Methods Here, we have developed a freely available R script that uses TGP data to analyse seed germination responses to temperature. We illustrate this analysis framework using three example species: Wollemia nobilis, Callitris baileyi and Alectryon subdentatus. The script generates >40 germination indices including germination rates and final germination across each cell of the TGP. These indices are then used to populate generalized additive models and predict germination under current and future monthly maximum and minimum temperatures anywhere on the globe. Key Results In our study species, modelled data were highly correlated with observed data, allowing confident predictions of monthly germination patterns for current and future climates. Wollemia nobilis germinated across a broad range of temperatures and was relatively unaffected by predicted future temperatures. In contrast, C. baileyi and A. subdentatus showed strong seasonal temperature responses, and the timing for peak germination was predicted to shift seasonally under future temperatures. Conclusions Our experimental workflow is a leap forward in the analysis of TGP experiments, increasing its many potential benefits, thereby improving research predictions and providing substantial information to inform management and conservation of plan

关键词： Alectryon subdentatus Callitris baileyi climate change generalized additive models germination niche seed testing temperature Wollemia nobilis

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COVID-19, social distancing and guests' preferences: impact on peer-to-peer accommodation pricing

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CURRENT ISSUES IN TOURISM 2022年第16期25卷 2571-2577页

作者： Hidalgo, Alberto Riccaboni, Massimo Rungi, Armando Velazquez, Francisco J. IMT Sch Adv Studies Lucca Italy Univ Complutense Madrid Dept Appl & Struct Econ & Hist Madrid Spain

This paper investigates how guests' preferences in peer-to-peer (P2P) accommodations changed during the COVID-19 summer season. Specifically, we test the importance of attributes that better allow for preserving the social distancing. To this end, we adopt a semi-parametric hedonic pricing model. We take the city of Madrid as a compelling case study of an important tourist destination severely hit by the crisis. We show that guests' marginal willingness to pay for social distancing characteristics has changed from August 2019 to August 2020. In particular, we find that whereas listings with kitchen amenities increase 15.2 percentage points their premium price in August 2020 with respect to the previous year, the marginal willingness to pay for size-related characteristics decreased by 2.7 percentage points. Results are robust to sample and time composition. This study provides meaningful findings of a shift in guests' tastes towards social distancing attributes on P2P accommodations.

关键词： COVID-19 pandemic consumer behaviour peer-to-peer accommodation hedonic modelling generalized additive models

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Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego

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JOURNAL OF TRANSPORT GEOGRAPHY 2022年第0期104卷

作者： Zhang, Zhaolin Zhai, Guocong Xie, Kun Xiao, Feng Southwestern Univ Finance & Econ Fac Business Adm Sch Business Adm Chengdu 610031 Peoples R China Old Dominion Univ ODU Dept Civil & Environm Engn 129C Kaufman Hall Norfolk VA 23529 USA

The emergence of ridesharing services might complement or substitute public transit systems, leading to intricate relationships between the two services. However, limited studies focused on the nonlinear effects of ridesharing use frequency on public transit usage. Therefore, this paper investigated such nonlinear effects using the hier-archical negative binomial generalized additive model (HNBGAM), with the latest publicly available National Household Travel Survey (NHTS) dataset. The negative binomial and hierarchical negative binomial generalized linear models were also developed for comparison with the HNBGAM. The NHTS data involved travel infor-mation of 928 ridesharing users within 98 census tracts in San Diego. Two-level hierarchy (individual and census tract level) was constructed in the HNBGAM. In addition, the smooth function of the HNBGAM could help identify the nonlinear effects of ridesharing use frequencies on public transit usage. Demographic factors (age, gender, race, household size, etc.) and built environment factors (e.g., population density, worker density, percentage of rental houses, and house unit density) were also considered in the modeling process. The findings revealed a negligible impact on public transit usage for occasional ridesharing use (from one to eleven times per month), a complementary effect for regular ridesharing use (from eleven to thirty-two times per month), and a substitution effect for active ridesharing use (more than thirty-two times per month). Understanding such nonlinear relationships could help policymakers make more informed decisions to avoid the over-substitution of public transit usage and better complement the public transport system.

关键词： Spatial dependence Multilevel generalized additive models Nonlinear effects Ridesharing use frequency

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A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants

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INTERNATIONAL JOURNAL OF FORECASTING 2022年第1期38卷 321-338页

作者： Posch, Konstantin Truden, Christian Hungerlaender, Philipp Pilz, Juergen Alpen Adria Univ Klagenfurt Dept Math Klagenfurt Austria Alpen Adria Univ Klagenfurt Dept Stat Klagenfurt Austria

Accurate demand forecasting is one of the key aspects for successfully managing restaurants and staff canteens. In particular, properly predicting future sales of menu items allows for a precise ordering of food stock. From an environmental point of view, this ensures a low level of pre-consumer food waste, while from the managerial point of view, this is critical to the profitability of the restaurant. Hence, we are interested in predicting future values of the daily sold quantities of given menu items. The corresponding time series show multiple strong seasonalities, trend changes, data gaps, and outliers. We propose a forecasting approach that is solely based on the data retrieved from point-of-sale systems and allows for a straightforward human interpretation. Therefore, we propose two generalized additive models for predicting future sales. In an extensive evaluation, we consider two data sets consisting of multiple time series collected at a casual restaurant and a large staff canteen and covering a period of 20 months. We show that the proposed models fit the features of the considered restaurant data. Moreover, we compare the predictive performance of our method against the performance of other well-established forecasting approaches. (c) 2021 The Author(s). Published by Elsevier B.V. on behalf of International Institute of Forecasters. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Sales prediction Time series generalized additive models Bayesian methods Shrinkage priors

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