89657583
Sources of variation in stomach contents of predators of Atlantic herring in the Northwest Atlantic during 1973–2014
Spatial and temporal variation in stomach-contents data is often unquantified or combined in such a way (e.g. averaged among years) that true signal in diets may be lost. Using a delta approach, this paper fits generalized additive mixed models (GAMMs) to the amount of Atlantic herring (Clupea harengus) identified in predator stomachs using only data from stomachs in which herring occurred, and to the probability that a stomach contained herring. Both the amount of herring in stomachs and the probability of a stomach containing herring varied seasonally, spatially, and among years. Of the random effects in each GAMM, the effect of predator species had the largest variance. An index of herring abundance derived from the stomach-contents data was generally consistent with recent herring stock assessments. The temporal and spatial variation in the stomach-contents data suggested that the effect of averaging or combining stomach-contents data among years, seasons, or areas may lead to falsely precise or biased estimates from multispecies assessments or in estimates of consumption, and may restrain the relevance of static foodweb models.
83944251
Seasonal Variation in Guild Structure of the Puget Sound Demersal Fish Community
Identification of food web linkages is a major aim in ecology because it provides basic information on trophic flows and the potential for interspecific interactions. In addition, policy and restoration measures mandated to conform to ecosystem-based management principals can benefit from information on temporal and spatial variability in community-level interactions. Here, we analyzed guild structure of the demersal fish assemblage in Puget Sound, WA, a temperate estuarine system on the US west coast. Using diet information from 2,401 stomachs collected across three seasons (fall, winter, and summer), we identified guild membership for 21 fish species, examined seasonal guild switching, and tested for seasonal shifts in predation and for differences in the degree of diet overlap at the assemblage level. We accounted for ontogenetic variation in diet by dividing species into large (L) and small (S) size classes when appropriate. Using cluster analysis and a permutation approach, we identified seven significant guilds that were typified by predation on benthic invertebrates, pelagic invertebrates, and piscivory. Of the 18 species with more than one season of diet information, six switched guilds (Pacific sanddab L, sturgeon poacher, Pacific tomcod S, speckled sanddab, rex sole, and rock sole S). At the assemblage level, we tested for seasonal differences in prey use between seasons by performing an analysis of similarities based on Bray–Curtis diet similarities and found no significant difference. However, diet overlap was significantly higher in the summer than the fall and winter (with summer > fall > winter) indicating that diets within the assemblage converged in the summer. These results indicate that analyses of guild structure and diet overlap can reveal seasonal variation in community trophic structure and highlight intra-annual food web variation in the Puget Sound demersal fish community.
16043510
The foraging ecology of larval and juvenile fishes
Knowledge of the foraging ecology of fishes is fundamental both to understanding the processes that function at the individual, population and community levels, and for the management and conservation of their populations and habitats. Furthermore, the factors that influence the acquisition and assimilation of food can have significant consequences for the condition, growth, survival and recruitment of fishes. The majority of marine and freshwater fish species are planktivorous at the onset of exogenous nutrition and have a limited ability to detect, capture, ingest and digest prey. Improvements in vision, development of fins and associated improvements in swimming performance, increases in gape size and development of the alimentary tract during ontogeny often lead to shifts in diet composition. Prey size, morphology, behaviour and abundance can all influence the prey selection of larval and juvenile fishes. Differences in feeding behaviour between fish species, individuals or during ontogeny can also be important, as can inter- and intraspecific interactions (competition, predation risk). Temporal (diel, seasonal, annual) and spatial (microhabitat, mesohabitat, macrohabitat, regional) variations in prey availability can have important implications for the prey selection, diet composition, growth, survival, condition and, ultimately, recruitment success of fishes. For fish populations to persist, habitat must be available in sufficient quality and quantity for the range of activities undertaken during all periods of development. Habitats that enhance the diversity, size ranges and abundance of zooplankton should ensure that sufficient food resources are available to larval and juvenile fishes.
53636475
Fish gut content analysis: robust measures of diet composition
Trophic studies are fundamental components of our understanding of biology and ecology, from observing individual organisms to modelling ecosystem function. When measuring ﬁsh gut contents, we rely on collecting samples that represent snapshots in time. Many limitations in extrapolating from these snapshots are well understood. However, there seems to be a widespread belief that when quantifying the composition of gut contents, more detail always provides more information. We highlight some fundamental problems with the apparently more quantitative
approaches (i.e. ‘bulk’ methods measuring biomass or volume of each prey type)
and suggest that frequency of occurrence (%F) provides the most robust and interpretable measure of diet composition. The additional information provided by bulk
methods contains unquantiﬁable and potentially signiﬁcant error from a variety of
sources. In our experience, the contents of most guts cannot be unambiguously
separated into prey categories for quantiﬁcation because of the presence of unidentiﬁable and inseparable partially digested material. Even where separation is possible, the composition of a gut at one point in time is affected by many
unquantiﬁable factors unrelated to the actual composition of the diet. Consequently, bulk methods provide ambiguous interpretations from superﬁcially quantitative models. Where research questions require more detail, these problems mean
there is little alternative to time-consuming approaches like prey reconstruction.
However, for the descriptions of dietary composition presented in many studies, %
F provides robust data that overcome many of the limitations of the more
detailed approaches and provides considerable logistical and economic beneﬁts.
86303760
Evaluating the effect of predation mortality on forage species population dynamics in the Northeast US continental shelf ecosystem using multispecies virtual population analysis
Tyrrell, M. C., Link, J. S., Moustahfid, H., and Overholtz, W. J. 2008. Evaluating the effect of predation mortality on forage species population dynamics in the Northeast US continental shelf ecosystem using multispecies virtual population analysis. - ICES Journal of Marine Science, 65: 1689-1700.An expanded version of multispecies virtual population analysis (MSVPA) is used to analyse the effects of predation by 14 key predators on Atlantic herring and Atlantic mackerel in the Northwest Atlantic ecosystem for the period 1982-2002. For herring, MSVPA produced greater abundance estimates than single-species assessments, especially for the youngest age classes. The average rate of predation mortality for herring aged 0 and 1 was also higher than the standard total natural mortality rate (0.2) for the 21-year time frame (0.84-3.2). The same was true for mackerel in this MSVPA (0.37-1.6). Consumptive removals of herring and mackerel generally increased over time. From 1999 to 2001, the biomass removed by predators exceeded each species' commercial landings. The sum of consumption and landings notably exceeded the multispecies maximum sustainable yield for herring for the years 1995-2002 and for mackerel for the period 1999-2002. We highlight the importance of accounting for predation on forage species in the context of changes to the fish community that have taken place in the Northwest Atlantic over the past few decades.
82104704
MULTISPECIES AND SINGLE-SPECIES MODELS OF FISH POPULATION DYNAMICS: COMPARING PARAMETER ESTIMATES
Population features inferred from single- species, age-structured models are compared to those in- ferred from a multispecies, age-structured model that in- cludes predator-prey interactions among three commercially harvested fish species—walleye pollock, Atka mackerel, and Pacific cod—on the Aleutian Shelf, Alaska. The multispecies framework treats the single-species models and data as a spe- cial case of the multispecies model and data. The same data from fisheries and surveys are used to estimate model param- eters for both single-species and multispecies configurations of the model. Additionally, data from stomach samples and predator rations are used to estimate the parameters of the multispecies model. One form of the feeding functional re- sponse, predator pre-emption, was selected using AIC from seven alternative models for how the predation rate changes with the densities of prey and possibly other predators. Dif- ferences in estimated population dynamics and productivity between the multispecies and single-species models were ob- served. The multispecies model estimated lower mackerel pop- ulation sizes from 1964-2003 than the single-species model, while the spawning biomass of pollock was estimated to have declined more than three times faster since 1964 by the multi- species model. The variances around the estimates of spawning biomass were smaller for mackerel and larger for pollock in the multispecies model compared to the single-species model.
83602630
ASSESSING UNCERTAINTY IN A MULTISPECIES AGE-STRUCTURED ASSESSMENT FRAMEWORK: THE EFFECTS OF DATA LIMITATIONS AND MODEL ASSUMPTIONS
Performance of a multispecies age-structured assessment (MSASA) model in the Gulf of Alaska (GOA) relative to changes in data and model assumptions was examined through simulation exercises. Species included arrowtooth flounder (Atheresthes stomias), Pacific cod (Gadus macrocephalus), walleye pollock (Theragra chalcogramma), Pacific halibut (Hippoglossus stenolepis), and Steller sea lion (Eumetopias jubatus). Age-specific predation mortality was estimated as a flexible function of predator and prey abundances and fitted to diet data. Simulated data sets were constructed by applying random error to estimates of catch, survey, and diet data from an operating model, whose structure was identical to that of the estimating model. Simulations explored the effects of data variability, mismatched assumptions regarding model structure, and lack of diet data on model performance. Model misspecification and uninformative diet data had the greatest influence on model performance. Given the current emphasis on the development of ecosystem-based models and management, prioritizing the rigorous sampling of diet data would best facilitate the development of predation models useful to management agencies.
86233213
An ecosystem model of food web and fisheries interactions in the Baltic Sea
Because fisheries operate within a complex array of species interactions, scientists increasingly recommend multispecies approaches to fisheries management. We created a food web model for the Baltic Sea proper, using the Ecopath with Ecosim software, to evaluate interactions between fisheries and the food web from 1974 to 2000. The model was based largely on values generated by multispecies virtual population analysis (MSVPA). Ecosim outputs closely reproduced MSVPA biomass estimates and catch data for sprat (Sprattus sprattus), herring (Clupea harengus), and cod (Gadus morhua), but only after making adjustments to cod recruitment, to vulnerability to predation of specific species, and to foraging times. Among the necessary adjustments were divergent trophic relationships between cod and clupeids: cod exhibited top-down control on sprat biomass, but had little influence on herring. Fishing, the chief source of mortality for cod and herring, and cod reproduction, as driven by oceanographic conditions as well as unexplained variability, were also key structuring forces. The model generated many hypotheses about relationships between key biota in the Baltic Sea food web and may ultimately provide a basis for estimating community responses to management actions.
84246702
An Ecosystem Approach for Assessment Advice and Biological Reference Points for the Gulf of Maine-Georges Bank Atlantic Herring Complex
Abstract The biomass of Atlantic herring Clupea harengus in the Gulf of Maine–Georges Bank (GOM–GB) region declined sharply in the mid- to late 1970s, when fishery harvests ranged from 300 to 400 kilo–metric tons (kt) per year. During this same period, the consumption of Atlantic herring by fish and marine mammal predators was very large. Consumption has greatly exceeded landings from 1985 to the present. Previous research showed that four groups of predators (demersal fishes, marine mammals, large pelagic fishes, and seabirds) together annually consumed over 200 kt of Atlantic herring during the 1970s and over 300 kt during the late 1990s and early 2000s. Our analyses indicate that Atlantic herring predation mortality rates are related to the abundance of both Atlantic herring and predators. Predation mortality rates were relatively low during the 1960s, when Atlantic herring were abundant, but increased in the late 1970s and early 1980s, when Atlantic herring declined. Predation mortality rates declined...
84383338
The advantage of explicitly incorporating predation mortality into age-structured stock assessment models: an application for Atlantic mackerel
Moustahfid, H., Link, J. S., Overholtz, W. J., and Tyrrell, M. C. 2009. The advantage of explicitly incorporating predation mortality into age-structured stock assessment models: an application for Atlantic mackerel. - ICES Journal of Marine Science, 66: 445-454.An age-structured assessment programme (ASAP) that explicitly incorporates predation mortality was applied to Atlantic mackerel (Scomber scombrus) in the Northwest Atlantic. Predatory removals were modelled in the same manner as fishing mortality, with a comparable set of time-series, to produce estimates of predation mortality at age and for each year. Results from the analysis showed that incorporating predation into a mackerel stock assessment model notably altered model outputs. When excluding explicitly modelled rates of predation, the model underestimated the magnitude and uncertainty in spawning-stock biomass (SSB) and recruitment. Further, the rates of predation mortality varied across time and were higher for younger fish. Predation mortality was higher than fishing mortality for fish aged 1 year, approximately equal for 2-year-olds, and lower for older fish (3 years and older). Biological reference points for Atlantic mackerel differed considerably when predation mortality was included. For example, SSB MSY was more than twice as high in the model where predation was incorporated than in the fisheries-only model. Although there are several caveats to the predation model outputs, chief of which is that the estimates are conservative because some mackerel predators were excluded, the results demonstrate the feasibility of executing such an approach with an extant tool. The approach presented here ultimately has the advantage of detecting, and upon detection parsing out, the impact of predators relative to fisheries and has the potential to provide useful information to those interested in small pelagic fish and their associated fisheries.
83569117
When “data” are not data: the pitfalls of post hoc analyses that use stock assessment model output
The practice of treating stock assessment model output as data in subsequent modeling efforts is becoming more common, aided in part by the growing availability of online repositories of assessment...
134024019
Seasonal trends and phenology shifts in sea surface temperature on the North American northeastern continental shelf
The northeastern North American continental shelf from Cape Hatteras to the Scotian Shelf is a region of globally extreme positive trends in sea surface temperature (SST). Here, a 33-year (1982–2014) time series of daily satellite SST data was used to quantify and map spatial patterns in SST trends and phenology over this shelf. Strongest trends are over the Scotian Shelf (>0.6°C decade –1 ) and Gulf of Maine (>0.4°C decade –1 ) with weaker trends over the inner Mid-Atlantic Bight (~0.3°C decade –1 ). Winter (January–April) trends are relatively weak, and even negative in some areas; early summer (May–June) trends are positive everywhere, and later summer (July–September) trends are strongest (~1.0°C decade –1 ). These seasonal differences shift the phenology of many metrics of the SST cycle. The yearday on which specific temperature thresholds (8° and 12°C) are reached in spring trends earlier, most strongly over the Scotian Shelf and Gulf of Maine (~ –0.5 days year –1 ). Three metrics defining the warmest summer period show significant trends towards earlier summer starts, later summer ends and longer summer duration over the entire study region. Trends in start and end dates are strongest (~1 day year –1 ) over the Gulf of Maine and Scotian Shelf. Trends in increased summer duration are >2.0 days year –1 in parts of the Gulf of Maine. Regression analyses show that phenology trends have regionally varying links to the North Atlantic Oscillation, to local spring and summer atmospheric pressure and air temperature and to Gulf Stream position. For effective monitoring and management of dynamically heterogeneous shelf regions, the results highlight the need to quantify spatial and seasonal differences in SST trends as well as trends in SST phenology, each of which likely has implications for the ecological functioning of the shelf
85211957
Using fish stomachs as samplers of the benthos: integrating long-term and broad scales
Sampling benthic organisms in a synoptic manner is difficult, particularly at the scale of large marine ecosystems. Several known omnivorous and benthivorous fishes were evaluated as pos- sible samplers of the benthic community on the scale of the US northeast continental shelf ecosystem, collected from the early 1970s to 2001. Frequency of occurrence of organisms in the diet across time was examined as an index of relative abundance. Other prey and sampling caveats were accounted for by considering only those predators that met criteria such as adequate sample size, appropriate diet compositions, asymptotic stomach-prey curves, and relative constancy of all major prey groups comprising the diet. The geographic distribution of a suite of benthic organisms found in the stom- achs of predators was also examined. The benthic organisms focused on were ophiuroids, echinoids, holothuroideans, asteroids, octopods, stomatopods, cumaceans, pagurids, aphroditids, anthozoans, hydrozoans and caprellids. Of these 12 prey groups, only 3 showed a decline over time based on evi- dence from multiple predator stomachs. Most benthic organisms exhibited non-negative trends in an index of relative abundance, and 2 showed an increase over the time-series. Additionally, many of the organisms were widely distributed, with some concentrated more on Georges Bank and others more in the Gulf of Maine. Only 1 of 9 organisms showed a shift in distribution compared to studies from 50 yr earlier. I conclude that at broad spatial and temporal scales, the routine and systematic sampling of fish stomachs can be a useful indirect method for inferring information about benthic communities on continental shelves.
56113401
Dynamic trophic linkages in a large estuarine system — support for supply-driven dietary changes using delta generalized additive mixed models
Trophic dynamics within aquatic systems are a predominant regulator of fish production and an important consideration for implementing ecosystem approaches to fisheries management. We analyzed 10 years of fish diet data from Chesapeake Bay, USA, to (1) evaluate the effects of environmental variables on trophic interactions of 12 common predatory fishes, (2) infer dynamics of four key prey groups (mysids, bay anchovy, bivalves, and polychaetes), and (3) evaluate whether interannual dietary trends were coherent among predators and regulated by prey availability. Based on delta generalized additive mixed models (delta-GAMMs), predator length was the most important covariate in modeling prey consumption. When latitude, temperature, and depth effects were statistically significant, the effects of each variable were largely similar across predators for a given prey. Annual patterns of mysid and bivalve consumption each showed a single, dramatic peak shared by multiple predators with varied feeding preferences a...
53397363
Considering Other Consumers: Fisheries, Predators, and Atlantic Herring in the Gulf of Maine
After decades of overexploitation and severe depletion, Atlantic herring stocks in waters of the northeastern United States have recovered. Fishery managers now consider the herring resource to be underexploited. Nevertheless, some fishery managers and sustainable fishery advocates in New England have expressed concern that the fishery management plan may not adequately consider the importance of herring as prey for marine mammals, seabirds, and piscivorous fish. Several studies suggest that consumption by these predators is significant, yet trophic interactions are not explicitly considered in stock assessment models. Instead, as in most fisheries stock assessments, predation is subsumed within the natural mortality rate, and no empirical estimates of herring consumption are used in the models. The goal of the present study was to assess the consumption of herring by marine mammals and to compare this level of consumption with estimates of natural mortality derived from herring stock assessment models. Using the most recent estimates of abundance and the best available data on diet, we estimated total annual consumption of herring by eight marine mammal species in the Gulf of Maine. Our results indicate that marine mammals consume 93,802–189,898 metric tons (mt; 1 metric ton = 1000 kg) of herring annually. In addition, piscivorous fish and seabirds are important predators of herring. We estimate that the consumption of herring by these upper trophic level predators may have exceeded the estimate of natural mortality used in stock assessment models by more than fourfold in 1991. We suggest that fisheries management must move beyond a single-species approach to one that includes formal consideration of trophic relationships. INTRODUCTION Fishery managers face the dual responsibility of obtaining the optimum yield from fisheries while simultaneously protecting certain other species (Gerber et al. 1999). The bycatch of protected species such as sea turtles and marine mammals is well recognized (Crowder and Murawski 1998, National Research Council 1999), but the ecological role of commercially important fish species as prey of protected species has received less attention in the management process (Overholtz et al. 2000). Most commercial fisheries in the United States are managed on a single-species basis, but trophic interactions occur within a complex, multispecies environment. Managing the extraction of natural resources to account for larger ecosystem dynamics is a challenging task for both terrestrial and aquatic natural resource managers. Whether concerned with fish or forests, managers seek to obtain optimum benefits from resource extraction while considering biological and ecological processes such as reproduction, regeneration, predation, and competition. In some systems, however, the data required to adequately understand ecosystem processes may be difficult to obtain or unavailable. Yet, despite this difficulty, federal legislation may mandate that resources are managed to protect additional species and habitats. In the Gulf of Maine, Atlantic herring (Clupea harengus) is both a commercially valuable species and an important prey species for a large number of marine mammals, seabirds, and piscivorous fish (Caddy and Iles 1973, Overholtz et al. 1991, 2000, NEFMC 1999). The herring resource in the Gulf of Maine is currently considered to be underexploited by the New England Fishery Management Council. In 2001, the ex-vessel Efforts to model ecosystem bioenergetics are underway in many resource sectors. Approaches such as Ecopath offer a method for scientists to understand ecosystem processes such as feeding interactions or nutrient flow in the context of various harvest regimes.
83993415
Standardizing catch and effort data: a review of recent approaches
The primary indices of abundance for many of the world's most valuable species (e.g. tunas) and vulnerable species (e.g. sharks) are based on catch and effort data collected from commercial and recreational fishers. These indices can, however, be misleading because changes over time in catch rates can occur because of factors other than changes in abundance. Catch-effort standardization is used to attempt to remove the impact of these factors. This paper reviews the current state of the art in the methods for standardizing catch and effort data. It outlines the major estimation approaches being applied, the methods for dealing with zero observations, how to identify and select appropriate explanatory variables, and how standardized catch rate data can be used when conducting stock assessments.
14088956
Thin plate regression splines
I discuss the production of low rank smoothers for "d" ≥ 1 dimensional data, which can be fitted by regression or penalized regression methods. The smoothers are constructed by a simple transformation and truncation of the basis that arises from the solution of the thin plate spline smoothing problem and are optimal in the sense that the truncation is designed to result in the minimum possible perturbation of the thin plate spline smoothing problem given the dimension of the basis used to construct the smoother. By making use of Lanczos iteration the basis change and truncation are computationally efficient. The smoothers allow the use of approximate thin plate spline models with large data sets, avoid the problems that are associated with 'knot placement' that usually complicate modelling with regression splines or penalized regression splines, provide a sensible way of modelling interaction terms in generalized additive models, provide low rank approximations to generalized smoothing spline models, appropriate for use with large data sets, provide a means for incorporating smooth functions of more than one variable into non-linear models and improve the computational efficiency of penalized likelihood models incorporating thin plate splines. Given that the approach produces spline-like models with a sparse basis, it also provides a natural way of incorporating unpenalized spline-like terms in linear and generalized linear models, and these can be treated just like any other model terms from the point of view of model selection, inference and diagnostics. Copyright 2003 Royal Statistical Society.
88513115
Fitting Linear Mixed-Effects Models Using lme4
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.
84329114
Developing Model-Based Indices of Lake Whitefish Abundance Using Commercial Fishery Catch and Effort Data in Lakes Huron, Michigan, and Superior
Abstract Fishery catch per effort (CPE) is often used to assess relative fish abundance, and in many Great Lakes and other freshwater applications the CPE index is based on either an average or the ratio of summed aggregate catch to summed aggregate effort. In particular, assessments used to estimate the abundance of lake whitefish Coregonus clupeaformis and recommend harvest quotas in 1836 Treaty-ceded waters of Lakes Huron, Michigan, and Superior assume that commercial CPE from gill-net and trap-net fisheries is proportional to abundance; however, CPE may change due to factors other than abundance, leading to violations of this assumption. To account for sources of CPE variation that are not attributable to abundance, general linear mixed models (GLMMs) were developed for each management unit and least-squares means (LSMs) for each year were used as the index of abundance. The effect of using the GLMM method for standardization was evaluated by examining the temporal trends in the proportional differenc...
122265839
Generalized Additive Models: An Introduction With R
also includes some topics one may not expect to find in a text on robust statistics, such as sequential M estimates and L estimates, multivariate admissibility and shrinkage, and goodness-of-fit tests. These are topics of special interest to the authors and to which they have made significant research contributions. The presentation of the theoretical material in the text is well organized and easy to follow. Chapters 1, 2, 3, and 6 provide a fairly good introduction to the theory of robust statistics. In particular, the discussion of statistical functionals and differentiability, along with the accompanying examples, offers a clear and accessible account of these challenging topics. There are some minor shortcomings in the theoretical presentation. The definition of a linear functional, which is used extensively in Chapter 1, is presumed to be known. The proof given on page 17 that shows that a Fréchet differentiable functional is also Gâteaux differentiable presumes the Gâteaux derivative is a linear functional, but this is the key to the proof. The definitions given for the maximum bias and the asymptotic maximum bias on pages 33 and 35, respectively, are redundant. On page 46, the breakdown point of an M estimate of location is given as 1/2 whenever the corresponding ψ function is odd and bounded, but the condition that the ψ function should also be monotonic is omitted. Expressions for the breakdown points of redescending M estimates of location are more complicated; see Huber (1984). There are some minor typographical errors, none of which should confuse a student reader except perhaps the one appearing on page 48 [where E(IF(x; X̃,P ))2 should read E(IF(x; X̃,P )2)]. The methodological and computational parts of the book are less extensive than the theoretical part and, consequently, are not as clearly written. The methods tend to lack sufficient motivation or explanation. For example, an illustration of robust regression with MM estimates, computed using R, is given at the end of Chapter 4. Within the chapter, though, the only mention of MM estimates is a one line general definition. No motivation or discussion of properties of MM estimates is given. In particular, the text does not note that they are high breakdown point estimates introduced to improve upon the poor normal efficiency of the S estimates of regression. Rather, on page 110, one finds the statement that the S estimates “combine the high breakdown point. . . with a fairly good efficiency at the normal model.” Aside from the use of R, the text does not discuss computational algorithms for robust methods. The examples using R are not always sufficiently documented and are sometimes simply presented as R commands with their corresponding outputs. As an example, the illustrations of robust regression using M and MM estimates in Chapter 4 do not indicate which M estimate or MM estimate is being computed (i.e., what the default is) or how the estimates are tuned. Nevertheless, the authors should be commended for assembling a ready reference of various R commands that are applicable to robust statistics. The book is intended to be a graduate level text. In the American system, it would not be appropriate for a Master’s level course in statistics or for a course that emphasizes methodology and applications, especially one that has students from other disciplines. Ideally, the text is more appropriate for a Ph.D. level research course in robust statistics, either as the primary text or as a secondary resource. The book tends to be overly ambitious for its size in trying to cover robust topics from in-depth theory to applications and illustrations with R programs. This results in a rather terse style, and so the text reads for the most part like lecture notes. This could be an advantage if used as a primary text in that it allows instructors to give their own motivation, explanations, and emphasis to the various topics. Provided an instructor does so, the book would provide a good basis for a research level course on robust statistics. At the very least, for those with an interest in robust statistics, this text is worth having in one’s personal library. If I were teaching a graduate course in robust statistics, I would seriously consider this text. It has the unfortunate timing, however, of being published at the same time as the long awaited text by Maronna, Martin, and Yohai (2006). Although less theoretical, this latter text tends to be more comprehensive and more contemporary in its coverage of robust statistics.
55942350
Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
Representation of generalized additive models (GAM's) using penalized regression splines allows GAM's to be employed in a straightforward manner using penalized regression methods. Not only is inference facilitated by this approach, but it is also possible to integrate model selection in the form of smoothing parameter selection into model fitting in a computationally efficient manner using well founded criteria such as generalized cross-validation. The current fitting and smoothing parameter selection methods for such models are usually effective, but do not provide the level of numerical stability to which users of linear regression packages, for example, are accustomed. In particular the existing methods cannot deal adequately with numerical rank deficiency of the GAM fitting problem, and it is not straightforward to produce methods that can do so, given that the degree of rank deficiency can be smoothing parameter dependent. In addition, models with the potential flexibility of GAM's can also present practical fitting difficulties as a result of indeterminacy in the model likelihood: Data with many zeros fitted by a model with a log link are a good example. In this article it is proposed that GAM's with a ridge penalty provide a practical solution in such circumstances, and a multiple smoothing parameter selection method suitable for use in the presence of such a penalty is developed. The method is based on the pivoted QR decomposition and the singular value decomposition, so that with or without a ridge penalty it has good error propagation properties and is capable of detecting and coping elegantly with numerical rank deficiency. The method also allows mixtures of user specified and estimated smoothing parameters and the setting of lower bounds on smoothing parameters. In terms of computational efficiency, the method compares well with existing methods. A simulation study compares the method to existing methods, including treating GAM's as mixed models.
17511583
Fast stable direct fitting and smoothness selection for generalized additive models
Existing computationally efficient methods for penalized likelihood generalized additive model fitting employ iterative smoothness selection on working linear models (or working mixed models). Such schemes fail to converge for a non-negligible proportion of models, with failure being particularly frequent in the presence of concurvity. If smoothness selection is performed by optimizing 'whole model' criteria these problems disappear, but until now attempts to do this have employed finite-difference-based optimization schemes which are computationally inefficient and can suffer from false convergence. The paper develops the first computationally efficient method for direct generalized additive model smoothness selection. It is highly stable, but by careful structuring achieves a computational efficiency that leads, in simulations, to lower mean computation times than the schemes that are based on working model smoothness selection. The method also offers a reliable way of fitting generalized additive mixed models. Copyright (c) 2008 Royal Statistical Society.
85628867
Evaluating the sensitivity of a trophic mass- balance model (Ecopath) to imprecise data inputs
Ecopath with Ecosim has become the most widely adopted modelling framework to facilitate a more holistic, ecosystem-based approach to fisheries management. I evaluated the sensitivity of Ecopath predictions to uncertainty in input data and determined the extent to which they were improved via the mass-balance constraint. I used nine published Ecopath models as operational models, added error to input variables, and then determined how well Ecopath could uncover the true model structure. I focused on Ecopath's ability to precisely estimate biomass and ecotrophic efficiency (the proportion of a group's total mortality explicitly represented in the model by predation and fishing). Ecopath error predictions were approximately as precise as the input variables, except in cases of tightly linked cycles of food web connections when errors become greatly amplified. The process of model balancing had little effect on the magnitude of prediction errors. Moreover, accurate information about the source of imprecise d...
4298474
Predator size - prey size relationships of marine fish predators: interspecific variation and effects of ontogeny and body size on trophic-niche breadth
We utilized a long-term data base collected over a broad geographic range to examine predator size - prey size relationships for 18 species of marine fish predators from continental shelf waters off the northeast US coast. Regression analysis was used to illustrate interspecific variation in ontogenetic patterns of prey size use, gape allometries, and ratio-based trophic niche breadths. Size- based feeding strategies were assessed through comparison of frequency distributions of relative prey sizes eaten and were related to general predator feeding tactics and gape morphology. The results demonstrated that the range of prey sizes eaten expanded with increasing predator body size for each of the marine predators examined, leading to asymmetric predator size - prey size distribu- tions. Absolute maximum prey size and slopes of maximum prey size versus predator size varied widely among predator taxa. Distinct size-based feeding strategies were evident, as diets of some predators were dominated by prey that were 10 to 20% of predator size, whereas other predators frequently consumed prey >50% of predator size. Gape sizes and allometric relationships with body size were also diverse among predators and often were closely associated with maximum prey sizes. Ratio-based trophic-niche breadths generally did not expand with predator ontogeny and tended to narrow for the largest predators, which may be common for animal taxa.