pinecone/core-2020-05-10-deduplication huggingface dataset:
Scallop dredging has profound, long-term impacts on maerl habitats

Maerl beds are mixed sediments built by a surface layer of slow-growing, unattached coralline algae that are of international conservation significance because they create areas of high biodiversity. They are patchily distributed throughout Europe (to ∼ 30 m depth around the British Isles and to ∼ 120 m depth in the Mediterranean) and many are affected by towed demersal fishing. We report the effects of Newhaven scallop dredges on a previously unfished maerl bed compared with the effects on similar grounds that have been fished commercially in the Clyde Sea area, Scotland. Sediment cores were taken to assess the population density of live maerl thalli prior to scallop dredging on marked test and control plots. These plots were then monitored biannually over a four-year period. Live maerl thalli were sparsely distributed at the impacted site, and experimental dredging had no discernible effect on their numbers. The previously unfished ground had dense populations of live maerl and scallops (both Aequipecten opercularis and Pecten maximus). While counts of live maerl remained high on the control plot, scallop dredging led to a >70% reduction with no sign of recovery over the subsequent four years. The vulnerability of maerl and associated benthos (e.g., the delicate bivalve, Limaria hians) is discussed in relation to towed demersal fishing practices. © 2000 International Council for the Exploration of the Sea
Comparative analysis of Calanus finmarchicus demography at locations around the Northeast Atlantic

Standardized time-series sampling was carried out throughout 1997 at seven locations around the Northeast Atlantic to investigate regional variations in the seasonal demography of Calanus finmarchicus. Sites ranged from an inshore location in the North Sea, where C. finmarchicus formed only a small component of the zooplankton (<10 mgC m-2 during spring and early summer), to the shelf south of Iceland, and Weathership M in the Norwegian Sea, where the species dominated the zooplankton (>2000 mgC m-2 during spring and summer). The internal consistency of the demographic time-series from each site was investigated by three partial models of life-cycle processes. In general, the demography of late copepodites could be accounted for by a relatively simple forecast model of stage development and diapause. However, there was a large discrepancy between nowcast estimates of egg production based on female abundance, temperature, and chlorophyll, and hindcast simulations of the egg production required to account for the observed abundance of early copepodite stages. The results point to a gap in our understanding of seasonal variations in rates of egg production and/or survival of nauplii. Overall, the population sampled at Weathership M appeared to be reasonably self-contained, but all other sites were reliant on invasion of overwintered stock in spring. At least two generations were observed at all but one site, but the extent to which these were generated by discrete bursts of egg production varied between sites and seemed to be partly dependent on the proximity to an overwintering location
Modelling the Northeast Atlantic circulation : implications for the spring invasion of shelf regions by Calanus finmarchicus

The appearance in spring of the copepod Calanus finmarchicus in continental shelf waters of the northeastern Atlantic has been hypothesized to be mainly attributable to invasion from across the continental slope rather than in situ overwintering. This paper describes the application of a hydrodynamic circulation model and a particle-tracking model to Northeast Atlantic waters in order to assess the influence of the flow field and ascent migration parameters on the spring invasion of C. finmarchicus. For hydrodynamic modelling, the Hamburg Shelf-Ocean Model (HAMSOM) was applied to the North Atlantic and Nordic Seas and forced with daily mean atmospheric data. Simulated flow fields from HAMSOM serve as forcing functions for a particle-tracking model of the same region. The robustness of the simulated shelf invasion in three target boxes of the Northeast Atlantic Shelf was assessed by means of a sensitivity analysis with respect to variations in four key migration parameters: overwintering depth, ascent rate, ascent timing, and depth during residence in upper layers. The invasion of the northern North Sea and Norwegian Shelf waters is more sensitive to ascent migration parameters than invasion of the Faroese Shelf. The main reason for enhanced sensitivity of the North Sea invasion is the time and space-dependent flow structure in the Faroe-Shetland Channel. Dense aggregations of overwintering C. finmarchicus are found in the Channel, but because of the complex flow field only a proportion of the overwintering stock has the capacity to reach the North Sea
In situ target strength studies on Atlantic redfish (Sebastes spp.)

In situ acoustic target strength (TS) experiments were conducted on Atlantic redfish (Sebastes spp.) in Newfoundland waters (1996–1998) using deep-tow dual beam and hull-mounted split beam echosounders (38 kHz). The dual and split beam mean TSs did not differ. The deep-tow system was deployed at various depths over several aggregations. Calibration corrections were made for depths from 5–70 m (<1 dB). The TS declined at ranges <50 m from the top of the fish shoal suggesting avoidance behaviour. It was biased upward at ranges >200 m and a number of fish per sampled volume >0.04. After being controlled for variations related to range, reverberation volume and fish density the TS did not differ with respect to depth, distance from bottom, fish sex ratio, condition factor or weight. The mean length was the dominant influence on the mean TS. Pooled ex situ experimental data and controlled in situ data – which did not differ – indicated a length-based regression (weighted by s.e.−1) in standard format: TS=20 log [length (cm)] −68.7 (r2=0.49)
Spatial pattern and patchiness during ontogeny: post-settled Gadus morhua from coastal Newfoundland

Expand+ICES Journal of Marine Science: Journal du Conseilicesjms.oxfordjournals.orgICES J. Mar. Sci. (2003) 60 (1): 38-51. doi: 10.1006/jmsc.2002.1315 \ud
Spatial pattern and patchiness during ontogeny: post-settled Gadus morhua from coastal Newfoundland \ud
David A. Methven⇓, D. C. Schneider and George A. Rose+ Author Affiliations\ud
Fisheries Conservation, Fisheries and Marine Institute, Memorial University of Newfoundland St John's, Newfoundland, Canada, A1C 5R3\ud
Ocean Sciences Centre, Memorial University of Newfoundland St John's, Newfoundland, Canada, A1B 3X9\ud
Fisheries Conservation, Fisheries and Marine Institute, Memorial University of Newfoundland St John's, Newfoundland, Canada, A1C 5R3\ud
+ Author Notes\ud
↵Present address: Department of Biology, University of New Brunswick, PO Box 5050, Saint John, New Brunswick, Canada E2L 4L5; e-mail: dmethven@unbsj.ca\ud
Correspondence to D. A. Methven\ud
Received May 23, 2001. \ud
Accepted August 20, 2002. \ud
Abstract\ud
We tested the hypothesis that patchiness increases after settlement to the bottom in a marine broadcast spawner, the Atlantic cod Gadus morhua. Patchiness P=1+1/k was estimated from the dispersion parameter k of the negative binomial distribution. Estimates were based on length frequency distributions of fish from 18–330 mm that were seined from shallow nursery areas (<10 m depth) during autumn. Patchiness was highest for small cod (<24 mm) in the process of settling to benthic or epibenthic habitats. Settling cod were only collected from coastal sites located in deep fjords where adults overwinter and spawn. Patchiness was lowest for fish newly settled to benthic habitats (c. 50 mm SL) and increased thereafter with length to 200 mm SL. Our analyses suggest that patchiness in G. morhua > 200 mm depends on a shifting balance between establishment of home ranges (tending to reduce patchiness) and schooling behaviour (tending to increase patchiness). Patchiness generally increased for G. morhua between 25–200 mm SL when examined at different spatial (major bays along the northeast coast of Newfoundland) and temporal (years) scales suggesting processes responsible for these patterns may be consistent among the bays and years examined. Our results show that more is learned about the distribution of fish by examining the zeroth, first, and second moments (presence/absence, mean abundance and patchiness) than by examining only one measure. We hypothesize that patchiness continues to increase for larger juvenile and adult G. morhua that were not examined in this study. We propose that patchiness may then decrease for the very largest cod, “mother fish” that may not undergo extensive annual spawning migrations
Linkages: A Tool for the Construction of Multivariate Distributions with Given Nonoverlapping Multivariate Marginals

AbstractOne of the most useful tools for handling multivariate distributions with givenunivariatemarginals is the copula function. Using it, any multivariate distribution function can be represented in a way that emphasizes the separate roles of the marginals and of the dependence structure. The goal of the present paper is to introduce an analogous tool, called the linkage function, that can be used for the study of multivariate distributions with givenmultivariatemarginals by emphasizing the separate roles of the dependence structurebetweenthe given multivariate marginals, and the dependence structurewithineach of the nonoverlapping marginals. Preservation of some setwise positive dependence properties, from the linkage functionLto the joint distributionFand vice versa, are studied. When two different distribution functions are associated with the same linkage function (that is, have the same setwise dependence structure) we show that strong stochastic dominance order among the corresponding multivariate marginal distributions implies an overall stochastic dominance between the two underlying distribution functions
On Edgeworth Expansion and Moving Block Bootstrap for StudentizedM-Estimators in Multiple Linear Regression Models

AbstractThis paper considers the multiple linear regression modelYi=xi′β+εi,i=i, …, n, wherexi's are knownp×1 vectors,βis ap×1 vector of parameters, andε1,ε2, … are stationary, strongly mixing random variables. Letβndenote anM-estimator ofβcorresponding to some score functionψ. Under some conditions onψ,xi's andεi's, a two-term Edgeworth expansion for Studentized multivariateM-estimator is proved. Furthermore, it is shown that the moving block bootstrap is second-order correct for some suitable bootstrap analog of Studentizedβn
A Measure of Association for Bivariate Frailty Distributions

AbstractA general formula is derived for the variance of Kendall's coefficient of concordance for absolutely continuous bivariate distributions generated by frailties. The formula is specialized to the case of Gumbel's Type II distribution of extreme values, which arises when the frailty has a positive stable distribution. A new diagnostic is suggested for the goodness of fit of a bivariate frailty distribution, based on the value of Kendall's tau for a truncated sample. It is shown that as a function of the proportion of the sample truncated, this truncated tau characterizes the original frailty distribution. The methods are applied to some cable insulation failure data
Bivariate Dependence Properties of Order Statistics

AbstractIfX1, …,Xnare random variables we denote byX(1)⩽X(2)⩽…⩽X(n)their respective order statistics. In the case where the random variables are independent and identically distributed, one may demonstrate very strong notions of dependence between any two order statisticsX(i)andX(j). If in particular the random variables are independent with a common density or mass function, thenX(i)andX(j)areTP2dependent for anyiandj. In this paper we consider the situation in which the random variablesX1, …,Xnare independent but otherwise arbitrarily distributed. We show that for anyi<jandtfixed,P[X(j)>t∣X(i)>s] is an increasing function ofs. This is a stronger form of dependence betweenX(i)andX(j)than that of association, but we also show that among the hierarchy of notions of bivariate dependence this is the strongest possible under these circumstances. It is also shown that in this situation,P[X(j)>t∣X(i)>s] is a decreasing function ofi=1, …,nfor any fixeds<t. We give various applications of these results in reliability theory, counting processes, and estimation of conditional probabilities. We also consider the situation whereX1, …,Xnrepresent a random sample of sizendrawn without replacement from a linearly ordered finite population. In this case it is shown thatX(i)andX(j)areTP2dependent for anyiandj, and the implications are discussed
On Joint Estimation of Regression and Overdispersion Parameters in Generalized Linear Models for Longitudinal Data

AbstractLiang and Zeger introduced a class of estimating equations that gives consistent estimates of regression parameters and of their variances in the class of generalized linear models for longitudinal data. When the response variable in such models is subject to overdispersion, the oerdispersion parameter does not only influence the marginal variance, it may also influence the mean of the response variable. In such cases, the overdispersion parameter plays a significant role in the estimation of the regression parameters. This raises the necessity for a joint estimation of the regression, as well as overdispersion parameters, in order to describe the marginal expectation of the outcome variable as a function of the covariates. To correct for the effect of overdispersion, we, therefore, exploit a general class of joint estimating equations for the regression and overdispersion parameters. This is done, first, under the working assumption that the observations for a subject are independent and then under the general condition that the observations are correlated. In the former case, both score and quasi-score estimating equations are developed. The score equations are obtained from the marginal likelihood of the data, and the quasi-score equations are derived by exploiting the first two moments of the marginal distribution. This quasi-score equations approach requires a weight matrix, usually referred to as the pseudo-covariance weight matrix, which we construct under the assumption that the observations for a subject (or in a cluster) are independent. In the later case when observations are correlated, quasi-score estimating equations are developed in the manner similar to that of the independence case but the pseudo-covariance weight matrix is constructed from a suitable working covariance matrix of the longitudinal observations, the joint distribution of the observations being unknown. Asymptotic theory is provided for the general class of joint estimators for the regression and overdispersion parameters. The asymptotic distributional results are also applied to develop suitable chi-square test for testing for the regression of the overdispersed data
On the Rate of Approximations for Maximum Likelihood Tests in Change-Point Models

AbstractWe study the asymptotics of maximum-likelihood ratio-type statistics for testing a sequence of observations for no change in parameters against a possible change while some nuisance parameters remain constant over time. We obtain extreme value as well as Gaussian-type approximations for the likelihood ratio. We get necessary and sufficient conditions for the weak convergence of supremum andLp-functionals of the likelihood ration process. We also approximate the maximum likelihood ratio with Ornstein-Uhlenbeck processes and obtain bounds for the rate of approximation. We show that the Ornstein-Uhlenbeck approach is superior to the extreme value limit in case of moderate sample sizes
WBF Property and Stochastical Monotonicity of the Markov Process Associated to Schur-Constant Survivial Functions

AbstractWe concentrate attention on non-negative absolutely continuous random variables with aSchur-constantjoint survival function. Such a property defines a special case of exchangeability, corresponding to a multivariateno agingcondition, in a Bayesian set-up. In the longitudinal observation of our random variables, the pair (Number of failures,Total time on test) is a Markov process which has a central role. Our main result result shows that such a process isstochastically increasingif and only if the variables areWBF(Weakened By Failure)
Penalized Likelihood-type Estimators for Generalized Nonparametric Regression

AbstractWe consider the asymptotic analysis of penalized likelihood type estimators for generalized nonparametric regression problems in which the target parameter is a vector-valued function defined in terms of the conditional distribution of a response given a set of covariates. A variety of examples including ones related to generalized linear models and robust smoothing are covered by the theory. Linear approximations to the estimator are constructed using Taylor expansions in Hilbert spaces. An application which is treated is upper bounds on rates of convergence for the penalized likelihood-type estimators
Identification of Refined ARMA Echelon Form Models for Multivariate Time Series

AbstractIn the present article, we are interested in the identification of canonical ARMA echelon form models represented in a “refined” form. An identification procedure for such models is given by Tsay (J. Time Ser. Anal.10(1989), 357-372). This procedure is based on the theory of canonical analysis. We propose an alternative procedure which does not rely on this theory. We show initially that an examination of the linear dependency structure of the rows of the Hankel matrix of correlations, with originkin Z (i.e., with correlation at lagkin position (1, 1)), allows us not only to identify the Kronecker indicesn1, …, nd, whenk=1, but also to determine the autoregressive ordersp1, …, pd, as well as the moving average ordersq1, …, qdof the ARMA echelon form model by settingk>1 andk<1, respectively. Successive test procedures for the identification of the structural parametersni,pi, andqiare then presented. We show, under the corresponding null hypotheses, that the test statistics employed asymptotically follow chi-square distributions. Furthermore, under the alternative hypothesis, these statistics are unbounded in probability and are of the formNδ{1+op(1)}, whereδis a positive constant andNdenotes the number of observations. Finally, the behaviour of the proposed identification procedure is illustrated with a simulated series from a given ARMA model
A Bayesian Decision Theory Approach to Classification Problems

AbstractWe address the classification problem where an item is declared to be from populationπjif certain of its characteristicsvare assumed to be sampled from the distribution with pdf fj(v∣θj), wherej=1, 2, …, m. We first solve the two population classification problem and then extend the results to the generalmpopulation classification problem. Usually only the form of the pdf's is known. To use the classical classification rule the parameters,θj, must be replaced by their estimates. In this paper we allow the parameters of the underlying distributions to be generated from prior distributions. With this added structure, we obtain Bayes rules based on predictive distributions and these are completely determined. Using the first-order expansion of the predictive density, where the coefficients of powers ofn−1remain uniformly bounded innwhen integrated, we obtain an asymptotic bound for the Bayes risk
Nonparametric Approach for Non-Gaussian Vector Stationary Processes

AbstractSuppose that {z(t)} is a non-Gaussian vector stationary process with spectral density matrixf(λ). In this paper we consider the testing problemH:∫π−πK{f(λ)}dλ=cagainstA:∫π−πK{f(λ)}dλ≠c, whereK{·} is an appropriate function andcis a given constant. For this problem we propose a testTnbased on ∫π−πK{f(λ)}dλ=c, wheref(λ) is a nonparametric spectral estimator off(λ), and we define an efficacy ofTnunder a sequence of nonparametric contiguous alternatives. The efficacy usually depnds on the fourth-order cumulant spectraf4Zofz(t). If it does not depend onf4Z, we say thatTnis non-Gaussian robust. We will give sufficient conditions forTnto be non-Gaussian robust. Since our test setting is very wide we can apply the result to many problems in time series. We discuss interrelation analysis of the components of {z(t)} and eigenvalue analysis off(λ). The essential point of our approach is that we do not assume the parametric form off(λ). Also some numerical studies are given and they confirm the theoretical results
Extreme Value Asymptotics for Multivariate Renewal Processes

AbstractFor a sequence of partial sums ofd-dimensional independent identically distributed random vectors a corresponding multivariate renewal process is defined componentwise. Via strong invariance together with an extreme value limit theorem for Rayleigh processes, a number of weak asymptotic results are established for thed-dimensional renewal process. Similar theorems for the estimated version of this process are also derived. These results are suggested to serve as simultaneous asymptotic testing devices for detecting changes in the multivariate setting
Some Asymptotic Formulae for Gaussian Distributions

AbstractThis paper considers asymptotic expansions of certain expectations which appear in the theory of large deviation for Gaussian random vectors with values in a separable real Hilbert space. A typical application is to calculation of the “tails” of distributions of smooth functionals,p(r)=P{Φ(r−1ξ)⩾0},r→∞, e.g., the probability that a centered Gaussian random vector hits the exterior of a large sphere surrounding the origin. The method provides asymptotic formulae for the probability itself and not for its logarithm in a situation, where it is natural to expect thatp(r)=c′rD exp{−c″r2}. Calculations are based on a combination of the method of characteristic functionals with the Laplace method used to find asymptotics of integrals containing a fast decaying function with “small” support
A Multivariate CLT for Local Dependence withn−1/2 log nRate and Applications to Multivariate Graph Related Statistics

AbstractThis paper concerns the rate of convergence in the central limit theorem for certain local dependence structures. The main goal of the paper is to obtain estimates of the rate in the multidimensional case. Certain one-dimensional results are also improved by using some more flexible characteristics of dependence. Assuming the summands are bounded, we obtain rates close to those for independent variables. As an application we study the rate of the normal approximation of certain graph related statistics which arise in testing equality of several multivariate distribution
Stochastic Orders for Spacings of Heterogeneous Exponential Random Variables

AbstractWe obtain some new results on normalized spacings of independent exponential random variables with possibly different scale parameters. It is shown that the density functions of the individual normalized spacings in this case are mixtures of exponential distributions and, as a result, they are log-convex (and, hence, DFR). G. Pledger and F. Proschan (Optimizing Methods in Statistics(J. S. Rustagi, Ed.), pp. 89–113, Academic Press, New York, 1971), have shown, with the help of a counterexample, that in a sample of size 3 the survival function of the last spacing is not Schur convex. We show that, however, this is true for the second spacing for all sample sizes. G. Pledger and F. Proschan (ibid.) also prove that the spacings are stochastically larger when the scale parameters are unequal than when they are all equal. We strengthen this result from stochastic ordering to likelihood ratio ordering. Some new results on dispersive ordering between the normalized spacings have also been obtained