Functional Data Analysis in Ecosystem Research: The Decline of Oweekeno Lake Sockeye Salmon and Wannock River Flow

  title={Functional Data Analysis in Ecosystem Research: The Decline of Oweekeno Lake Sockeye Salmon and Wannock River Flow},
  author={Laurie M. Ainsworth and Richard D. Routledge and Jiguo Cao},
  journal={Journal of Agricultural, Biological, and Environmental Statistics},
Functional regression is a natural tool for exploring the potential impact of the physical environment (continuously monitored) on biological processes (often only assessed annually). This paper explores the potential use of functional regression analysis and the closely related functional principal component analysis for studying the relationship between river flow (continuously monitored) and salmon abundance (measured annually). The specific example involves a depressed sockeye salmon… 
Climate effects on growth, phenology, and survival of sockeye salmon (Oncorhynchus nerka): a synthesis of the current state of knowledge and future research directions
It is revealed that associations between temperature and growth, phenology, or survival have been uncovered for all the life stages of sockeye salmon, whereas relationships with other climate-related variables have been sparse.
Modelling Animal Activity as Curves: An Approach Using Wavelet-Based Functional Data Analysis
Temporal activity patterns in animals emerge from complex interactions between choices made by organisms as responses to biotic interactions and challenges posed by external factors. Temporal
Gray whale densities during a seismic survey off Sakhalin Island, Russia
Findings should be interpreted with caution, given the low number of positive densities, due to success of the primary mitigation measure, which was to conduct the seismic survey as early in the feeding season as possible when few gray whales would be present.
Estimating Truncated Functional Linear Models With a Nested Group Bridge Approach
Abstract We study a scalar-on-function truncated linear regression model which assumes that the functional predictor does not influence the response when the time passes a certain cutoff point. We
Comparing two mean humidity curves using functiona t-tests: Turkey Case
Abstract: The goal of thisstudy is to show the usefulness of functional t tests and rainbow plots as aguideline. Meteorological data like humidity is used for this aim. In thisstudy, functional
Robust estimation and variable selection for function‐on‐scalar regression
Function‐on‐scalar regression is commonly used to model the dynamic behaviour of a set of scalar predictors of interest on the functional response. In this article, we develop a robust variable
Estimation of Sparse Functional Additive Models with Adaptive Group LASSO
This work proposes using the adaptive group LASSO method to select relevant components and smoothing splines and, thus, obtain a smoother estimate of those relevant components, to address the lack of fit in conventional functional linear regression models.
Deep Learning with Functional Inputs
The model is shown to perform well in a number of contexts including prediction of new data and recovery of the true underlying functional weights; these results were confirmed through real applications and simulation studies.
This paper develops new methods for providing instantaneous in-game win probabilities for the National Rugby League. Besides the score differential, betting odds and real-time features extracted from


Factors influencing the early marine ecology of juvenile sockeye salmon (O. nerka) in Rivers Inlet, British Columbia
Evidence is provided suggesting that a crucial, population-limiting window may exist in the early marine phase, as the newly smolted juvenile sockeye salmon emerge into Rivers Inlet and nearby waters, which is a key contributor to reduced returns.
Form of Random Variation in Salmon Smolt-to-Adult Relations and Its Influence on Production Estimates
Estimates of the production of adult salmon can be biased by assuming an incorrect form of random noise term in the descriptive model. Many authors of theoretical studies of stock–recruitment
Smolt-to-AduIt Survival Patterns of Sockeye Salmon (Oncorhynchus nerka): Effects of Smolt Length and Geographic Latitude when Entering the Sea
Variations in smolt-to-adult survival (SAS) of sockeye salmon relative to smolt length and age and latitude of the nursery lake outlet were explored for six stocks in Canada, Russia, and Alaska and 12 Alaskan populations.
Regulation of estuarine primary production by watershed rainfall and river flow
Enhanced phytoplankton production and algal blooms, symptoms of eutrophication, are frequently caused by elevated nutrient loading, usually a s nitrogen, to coastal waters. This nitrogen is derived
The Rivers Inlet Sockeye Salmon
The Rivers Inlet sockeye catch has averaged about 1 million fish per year, over 45 years. These are from smolts produced in a cold, deep lake, only 30 square miles in extent, and most of it heavily
Dynamics of marine ecosystems: Biological-physical interactions in the ocean
  • Mann
  • Environmental Science
    Reviews in Fish Biology and Fisheries
  • 2004
If you want to bone up on the basics of biologic oceanography, are contemplating teaching a course in that subject or want to better understand talks given by oceanographic modelers, Dynamics of
Dynamics of marine ecosystems:biological-physical interactions in the oceans
Contents. Preface to Third Edition. Preface to Second Edition. Preface to First Edition. 1 Marine Ecology Comes of Age. Part A: Processes on a Scale of less than 1 Kilometer. 2 Biology and Boundary
This work considers a regression setting where the response is a scalar and the predictor is a random function defined on a compact set of R, and studies an estimator based on a B-splines expansion of the functional coefficient which generalizes ridge regression.
Functional Data Analysis with R and MATLAB
Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of
Functional linear regression analysis for longitudinal data
We propose nonparametric methods for functional linear regression which are designed for sparse longitudinal data, where both the predictor and response are functions of a covariate such as time.