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Contribution of ocean variability to climate-catch models of Pacific sardine

DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY 2019年 159卷 103-111页

作者： Martinez-Rincon, Raul O. Saldivar-Lucio, Romeo Morales, Mark Lluch-Cota, Salvador E. Lluch-Cota, Daniel B. Salvadeo, Christian Ponce-Diaz, German CONACYT Ctr Invest Biol Noroeste Ave Inst Politecn Nacl 195 La Paz Mexico CONACYT Ctr Invest Cient & Educ Super Ensenada CI Unidad La Paz 334 Miraflores La Paz Baja California Mexico Univ Calif Santa Cruz Dept Ecol & Evolutionary Biol 115 McAllister Way Santa Cruz CA 95060 USA Ctr Invest Biol Noroeste Ave Inst Politecn Nacl 195 La Paz Mexico Univ Autonoma Baja California Sur CONACYT La Paz Mexico IPN Ctr Interdisciplinario Ciencias Marinas IPN CICIM Ave Inst Politecn Nacl S-N La Paz Mexico

Small-pelagic fishes are economically and ecologically important as they make up a large proportion of wild caught fisheries and provide an important link between planktonic organisms and higher trophic level organisms such as piscivorous fishes, squid, seabirds and marine mammals. In the California Current Ecosystem (CCE), the distribution and abundance of Pacific sardine (Sardinops sagax) is influenced by both natural climate variability and exploitation. This study uses generalized additive models to evaluate the effects of environmental forcing at multiple spatial scales (i.e. local, regional and basin) on sardine catch recorded at British Columbia (CAN), California (USA) and Bahia Magdalena (MEX). We find that the Pacific Circulation Index, sea surface temperature, upwelling strength, and primary productivity were the most influential factors explaining variability of sardine catch in the northeastern Pacific Ocean. Our CCE-wide analysis shows that regional scale environmental variability best explained catch rates of the Pacific sardine for California and Bahia Magdalena while basin-scale environmental variability did so for catch rates for British Columbia.

关键词： Sardinops sagax generalized additive models Climate-catch models Climate variability California current

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Extending the hybrid methodology for orbit propagation by fitting techniques

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NEUROCOMPUTING 2019年 354卷 49-60页

作者： Perez, Ivan San-Martin, Montserrat Lopez, Rosario Vergara, Eliseo R. Wittig, Alexander Felix San-Juan, Juan Univ La Rioja Sci Comp Grp GRUCACI San Jose de Calasanz 31 Logrono 26004 Spain Univ Granada Sci Comp Grp GRUCACI Santander 1 Melilla 52005 Spain Univ La Rioja Sci Comp Grp GRUCACI Madre de Dios 53 Logrono 26006 Spain European Space Agcy Adv Concepts Team Keplerlaan 1 NL-2200 AG Noordwijk Netherlands Univ Southampton Southampton SO17 1BJ Hants England

The hybrid methodology for orbit propagation is a technique that allows improving the accuracy of any propagator for predicting the future trajectory of a satellite or space-debris object in orbit around the Earth. It is based on modeling the error of the base propagator to be enhanced. Both statistical time-series forecasting methods and machine-learning techniques can be used for that purpose. The standard procedure for developing a hybrid orbit propagator requires some initial control data, that is, a set of precise ephemerides corresponding to either real observations or accurately computed pseudo-observations, from which to model the base-propagator error dynamics. It also needs tuning the time-series forecaster from those control data. We propose an improvement to the hybrid methodology for orbit propagation, based on fitting new hybrid propagators from others previously developed for nearby initial conditions, which avoids the need for both the control data and the tuning process, and achieves comparable results. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Artificial satellite theory Orbit propagator Hybrid propagation methodology Time series forecasting Holt-Winters generalized additive models

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Phytoplankton response to climate changes and anthropogenic activities recorded by sedimentary pigments in a shallow eutrophied lake

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SCIENCE OF THE TOTAL ENVIRONMENT 2019年 647卷 1398-1409页

作者： Zhang, Hanxiao Huo, Shouliang Yeager, Kevin M. He, Zhuoshi Xi, Beidou Li, Xiaochuang Ma, Chunzi Wu, Fengchang Chinese Res Inst Environm Sci State Key Lab Environm Criteria & Risk Assessment Beijing 100012 Peoples R China Univ Kentucky Dept Earth & Environm Sci Lexington KY 40506 USA

Studies that address the potential effects of climate and anthropogenic activities on lacustrine phytoplankton succession are scarce in the shallow lakes. In the present work, the succession of phytoplankton community inferred from sedimentary pigments has been investigated;the impacts of climate and anthropogenic activities on the succession have been evaluated by the generalized additive models (GAMs) in a shallow eutrophied lake, Lake Chaohu, located eastern China. The results show that phytoplankton succession can be divided into two periods: pre-1960s and post 1960s. The mean values of beta beta Car and Chl a increased after the 1960s at both sites sampled, from 0.013 to 0.359, and 0.013 to 1.382 mu g g(-1), respectively (site C4), and from 0.015 to 0.530, and 0.010 to 0.921 mu g g(-1), respectively (site C14), reflecting significant increases of primary productivity since the 1960s. The percentage of diatoms and dinoflagellates preserved in sediments decreased from similar to 90% to similar to 15% since the 1960s, while cyanobacteria and green algae increased from similar to 5% to similar to 35%, respectively, reflecting the shift of the lake phytoplankton community. This succession was related to construction of the Chaohu Dam in 1963, increasing discharges of anthropogenic N and P into the Lake, and a generally warming environment as reflected by increasing average air temperatures. The results of GAMs showed aquatic total phosphorus (TP) concentration is the dominant contributor to phytoplankton community change, explaining 42.74%, 40.27%, 40.77% and 72.28% of the variance of total algae, cyanobacteria, green algae, and diatoms and dinoflagellates, respectively. The positive impacts of increasing TP concentrations on abundances of total algae, cyanobacteria, and green algae were observed during periods of relatively high TP concentrations since the mid-1970s. The positive responses of total algae, cyanobacteria, green algae and diatoms and dinoflagellates t

关键词： Algae succession Anthropogenic activities Climate change generalized additive models Phytoplankton pigments

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Scale effects on the performance of niche-based models of freshwater fish distributions

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ECOLOGICAL MODELLING 2019年 405卷 33-42页

作者： Kaercher, Oskar Frank, Karin Walz, Ariane Markovic, Danijela Osnabruck Univ Appl Sci Fac Business Management & Social Sci Caprivistr 30A D-49076 Osnabruck Germany Univ Potsdam Inst Earth & Environm Sci Karl Liebknecht Str 24-25 D-14476 Potsdam Germany UFZ Helmholtz Ctr Environm Res Ltd Dept Ecol Modelling Permoserstr 15 D-04318 Leipzig Germany Univ Osnabruck Inst Environm Syst Res Barbarastr 12 D-49076 Osnabruck Germany iDiv German Ctr Integrat Biodivers Res Halle Jena Deutsch Pl 5e D-04103 Leipzig Germany

Niche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species' distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grain-size by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable.

关键词： Catchment order Conservation planning Danube generalized additive models Species distribution modelling

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Synthetically lagged models

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STATISTICS & PROBABILITY LETTERS 2019年 144卷 37-43页

作者： Burr, Wesley S. Shin, Hwashin H. Takahara, Glen Trent Univ Growski Coll Dept Math 1600 West Bank Dr Peterborough ON K9L0G2 Canada Hlth Canada EHRSB Populat Studies Div Ottawa ON Canada Queens Univ Dept Math & Stat Jeffrey Hall48 Univ Ave Kingston ON K7L 3N6 Canada

Epidemiologic studies often report health risk due to short-term air pollution exposure through examination of lagged association, expressing manifestation of population health effects over time. We develop a new approach to the problem of lagged manifestation of air pollution exposure: synthetically lagged models. This approach also generalizes to other lagged time series regression models. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Air pollution generalized additive models Lag Phase Multitaper spectrum estimation

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generalized Linear models for Flexible Parametric Modeling of the Hazard Function

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MEDICAL DECISION MAKING 2019年第7期39卷 867-878页

作者： Kearns, Benjamin Stevenson, Matt Triantafyllopoulos, Kostas Manca, Andrea Univ Sheffield Sheffield S Yorkshire England Univ York York N Yorkshire England

Background. Parametric modeling of survival data is important, and reimbursement decisions may depend on the selected distribution. Accurate predictions require sufficiently flexible models to describe adequately the temporal evolution of the hazard function. A rich class of models is available among the framework of generalized linear models (GLMs) and its extensions, but these models are rarely applied to survival data. This article describes the theoretical properties of these more flexible models and compares their performance to standard survival models in a reproducible case study. Methods. We describe how survival data may be analyzed with GLMs and their extensions: fractional polynomials, spline models, generalized additive models, generalized linear mixed (frailty) models, and dynamic survival models. For each, we provide a comparison of the strengths and limitations of these approaches. For the case study, we compare within-sample fit, the plausibility of extrapolations, and extrapolation performance based on data splitting. Results. Viewing standard survival models as GLMs shows that many impose a restrictive assumption of linearity. For the case study, GLMs provided better within-sample fit and more plausible extrapolations. However, they did not improve extrapolation performance. We also provide guidance to aid in choosing between the different approaches based on GLMs and their extensions. Conclusions. The use of GLMs for parametric survival analysis can outperform standard parametric survival models, although the improvements were modest in our case study. This approach is currently seldom used. We provide guidance on both implementing these models and choosing between them. The reproducible case study will help to increase uptake of these models.

关键词： survival analysis time to event generalized additive models dynamic survival models generalized linear mixed models splines fractional polynomials frailty models

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Nonlinear regression models for heterogeneous data with massive outliers

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JOURNAL OF APPLIED STATISTICS 2019年第8期46卷 1456-1477页

作者： Jung, Yoonsuh Korea Univ Dept Stat Seoul South Korea

The income or expenditure-related data sets are often nonlinear, heteroscedastic, skewed even after the transformation, and contain numerous outliers. We propose a class of robust nonlinear models that treat outlying observations effectively without removing them. For this purpose, case-specific parameters and a related penalty are employed to detect and modify the outliers systematically. We show how the existing nonlinear models such as smoothing splines and generalized additive models can be robustified by the case-specific parameters. Next, we extend the proposed methods to the heterogeneous models by incorporating unequal weights. The details of estimating the weights are provided. Two real data sets and simulated data sets show the potential of the proposed methods when the nature of the data is nonlinear with outlying observations.

关键词： Case-specific parameters generalized additive models heteroscedasticity nonlinear regression outliers robust regression

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Modeling the Spatial Distribution of Swordfish (Xiphias gladius) Using Fishery and Remote Sensing Data: Approach and Resolution

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REMOTE SENSING 2020年第6期12卷

作者： Su, Nan-Jay Chang, Chia-Hao Hu, Ya-Ting Chiang, Wei-Chuan Tseng, Chen-Te Natl Taiwan Ocean Univ Dept Environm Biol & Fisheries Sci Keelung 20224 Taiwan Natl Taiwan Ocean Univ Ctr Excellence Oceans Keelung 20224 Taiwan Council Agr Fisheries Res Inst Keelung 20246 Taiwan Council Agr Eastern Marine Biol Res Ctr Fisheries Res Inst Taitung 96143 Taiwan

Swordfish, Xiphias gladius (Linnaeus, 1758), is a commercially important species that is widely distributed throughout three oceans. This species inhabits oceanic waters with preferred environmental ranges and migrates vertically to the surface layer for feeding. However, the spatial distribution pattern and habitat preferences of swordfish have been rarely studied in the Pacific Ocean due to the wide geographic range of this species. This study examined the spatial distribution and preferred ranges of environmental variables for swordfish using two approaches, generalized additive models and habitat suitability index methods, with different spatio-temporal data resolution scales. Results indicated that sea surface temperature is the most important factor determining swordfish spatial distribution. Habitat spatial pattern and preferred environmental ranges, estimated using various modeling approaches, were robust relative to the spatio-temporal data resolution scales. The models were validated by examining the consistency between predictions and untrained actual observations, which all predicted a high relative density of swordfish in the tropical waters of the central Pacific Ocean, with no obvious seasonal movement. Results from this study, based on fishery and remote sensing data with wide spatial coverage, could benefit the conservation and management of fisheries for highly migratory species such as swordfish and tuna.

关键词： spatial pattern habitat selection generalized additive models habitat suitability index scale effect data resolution

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System failure estimation based on field data and semi-parametric modeling

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ENGINEERING FAILURE ANALYSIS 2019年 101卷 473-484页

作者： Valis, David Pokora, Ondrej Kolacek, Jan Univ Def Brno Brno Czech Republic Masaryk Univ Brno Czech Republic

A top-priority task nowadays is to ensure quality, safety, and dependability of technical systems. As present systems are highly reliable, it is relatively unlikely for hard failure to occur frequently. One of the ways to avoid failures is by monitoring the conditions and degradation of the system using diagnostic signals. In this article, modern and nontrivial semiparametric approaches to analyze the statistically relevant set of field data are used. In particular, the generalized additive models (GAM) are applied. GAM reflect the current trends in statistics as they include both linear and spline-based modeling. We applied GAM to successfully obtain an appropriate description of the variability of the analyzed field data. The analyzed data come as diagnostic signals from an observed vehicle fleet. Based on the diagnostic signals and applied GAM, we present outcomes from investigating, studying and modeling the technical condition, degradation and failure occurrence of the observed system.

关键词： Oil field data Functional data analysis generalized additive models Ornstein-Uhlenbeck process First hitting time Residual useful life

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Freshwater species distributions along thermal gradients

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ECOLOGY AND EVOLUTION 2019年第1期9卷 111-124页

作者： Kaercher, Oskar Hering, Daniel Frank, Karin Markovic, Danijela Osnabruck Univ Appl Sci Fac Business Management & Social Sci Osnabruck Germany Univ Duisburg Essen Fac Biol Aquat Ecol Essen Germany UFZ Helmholtz Ctr Environm Res Ltd Dept Ecol Modelling Leipzig Germany Univ Osnabruck Inst Environm Syst Res Osnabruck Germany iDiv German Ctr Integrat Biodivers Res Halle Jena Leipzig Germany

The distribution of a species along a thermal gradient is commonly approximated by a unimodal response curve, with a characteristic single optimum near the temperature where a species is most likely to be found, and a decreasing probability of occurrence away from the optimum. We aimed at identifying thermal response curves (TRCs) of European freshwater species and evaluating the potential impact of climate warming across species, taxonomic groups, and latitude. We first applied generalized additive models using catchment-scale global data on distribution ranges of 577 freshwater species native to Europe and four different temperature variables (the current annual mean air/water temperature and the maximum air/water temperature of the warmest month) to describe species TRCs. We then classified TRCs into one of eight curve types and identified spatial patterns in thermal responses. Finally, we integrated empirical TRCs and the projected geographic distribution of climate warming to evaluate the effect of rising temperatures on species' distributions. For the different temperature variables, 390-463 of 577 species (67.6%-80.2%) were characterized by a unimodal TRC. The number of species with a unimodal TRC decreased from central toward northern and southern Europe. Warming tolerance (WT = maximum temperature of occurrence-preferred temperature) was higher at higher latitudes. Preferred temperature of many species is already exceeded. Rising temperatures will affect most Mediterranean species. We demonstrated that freshwater species' occurrence probabilities are most frequently unimodal. The impact of the global climate warming on species distributions is species and latitude dependent. Among the studied taxonomic groups, rising temperatures will be most detrimental to fish. Our findings support the efforts of catchment-based freshwater management and conservation in the face of global warming.

关键词： climate change European freshwater generalized additive models preferred temperature safety margin thermal response warming tolerance

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