Population Dynamics and Management of the Northwest Atlantic Harp Seal (Phoca groenlandica)

1983 ◽  
Vol 40 (7) ◽  
pp. 919-932 ◽  
Author(s):  
Derek A. Roff ◽  
W. Don Bowen
Keyword(s):  
Population Dynamics ◽  
Mortality Rate ◽  
Population Size ◽  
Washington Dc ◽  
Natural Mortality ◽  
Total Catch ◽  
Vital Rates ◽  
Index Method ◽  
Phoca Groenlandica ◽  
Potential Sources

Previous methods of estimating population size and natural mortality rate in harp seals (Phoca groenlandica) are reviewed. Excepting the method of Beddington and Williams (Marine Mammal Comm., Washington, DC., Rep. MMC 79-03, 1980) all previous methods rely heavily upon the survival index method of estimating pup production. We describe the mathematical rationale underlying this method and indicate potential sources of bias. Beddington and Williams' analysis produces a combination of vital rates for 1952 that would not enable a population to persist in the absence of hunting. This suggests that the method may not be able to estimate these parameters accurately. This conclusion is supported by several unpublished analyses. We present an alternative method of analysis that is based on the concept of maximum likelihood. We estimate the rate of natural mortality and trend in 1 + population size from 1967 to 1980, using mark–recapture estimates of pup production in the late 1970s and the observed ratio of the survival of adjacent cohorts in the late 1960s and early 1970s to constrain population trajectories from a simulation model. From this analysis we conclude that the population is increasing and that the present total catch may be substantially smaller than the replacement yield.

Understanding historical summer flounder (Paralichthys dentatus) abundance patterns through the incorporation of oceanography-dependent vital rates in Bayesian hierarchical models

2019 ◽  
Vol 76 (8) ◽  
pp. 1275-1294 ◽  
Author(s):  
Cecilia A. O’Leary ◽  
Timothy J. Miller ◽  
James T. Thorson ◽  
Janet A. Nye
Keyword(s):  
Population Dynamics ◽  
Gulf Stream ◽  
Stock Assessment ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Natural Mortality ◽  
Vital Rates ◽  
Summer Flounder ◽  
Paralichthys Dentatus ◽  
Abundance Patterns

Climate can impact fish population dynamics through changes in productivity and shifts in distribution, and both responses have been observed for many fish species. However, few studies have incorporated climate into population dynamics or stock assessment models. This study aimed to uncover how past variations in population vital rates and fishing pressure account for observed abundance variation in summer flounder (Paralichthys dentatus). The influences of the Gulf Stream Index, an index of climate variability in the Northwest Atlantic, on abundance were explored through natural mortality and stock–recruitment relationships in age-structured hierarchical Bayesian models. Posterior predictive loss and deviance information criterion indicated that out of tested models, the best estimates of summer flounder abundances resulted from the climate-dependent natural mortality model that included log-quadratic responses to the Gulf Stream Index. This climate-linked population model demonstrates the role of climate responses in observed abundance patterns and emphasizes the complexities of environmental effects on populations beyond simple correlations. This approach highlights the importance of modeling the combined effect of fishing and climate simultaneously to understand population dynamics.

Integrating catch-at-age and multiyear tagging data: a combined Brownie and Petersen estimation approach in a fishery context

2006 ◽  
Vol 63 (3) ◽  
pp. 534-548 ◽  
Author(s):  
Tom Polacheck ◽  
J Paige Eveson ◽  
Geoff M Laslett ◽  
Kenneth H Pollock ◽  
William S Hearn
Keyword(s):  
Mortality Rate ◽  
Population Size ◽  
Stock Assessment ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Catch Data ◽  
Coefficients Of Variation ◽  
Southern Bluefin Tuna ◽  
Catch Rates ◽  
Comprehensive Framework

A comprehensive framework for modelling data from multiyear tagging experiments in a fishery context is presented that incorporates catch data into the traditional Brownie tag–recapture model. Incorporation of catch data not only allows for improved estimation of natural and fishing mortality rates, but also for direct estimation of population size at the time of tagging. These are the primary quantities required to be estimated in stock assessments — having an approach for directly estimating them that does not require catch rates provides a potentially powerful alternative for augmenting traditional stock assessment methods. Simulations are used to demonstrate the value of directly incorporating catch data in the model. Results from the range of scenarios considered suggest that in addition to providing a precise estimate of population size (coefficients of variation ranging from ~15% to 30%), including catch data can decrease biases in the mortality rate estimates (natural mortality especially) and improve precision of fishing mortality rate estimates (by as much as 60% at age 1). The model is applied to southern bluefin tuna (Thunnus maccoyii) tag–recapture and catch data collected in the 1990s to provide estimates of natural mortality, fishing mortality, and abundance for five cohorts of fish.

An Application of Computers to the Estimation of Exploited Populations

1969 ◽  
Vol 26 (1) ◽  
pp. 179-189
Author(s):  
K. Radway Allen
Keyword(s):  
Mortality Rate ◽  
Age Distribution ◽  
The Other ◽  
Population Estimates ◽  
Distribution Data ◽  
Natural Mortality ◽  
Computer Programme ◽  
Total Catch ◽  
The Third

This paper describes a computer programme for the estimation of the size of exploited populations by methods described in Allen (1966, J. Fish. Res. Bd. Canada 23: 1553–1574). Although these methods were originally developed for use on whale populations, they are applicable to any other populations where suitable data are available. The essential data are the total catch, the catch for a known amount of effort, and the age distribution of the catch, all for a series of years. An estimate of natural mortality rate is also required but population estimates may be obtained for up to 10 values of this parameter in a single computer run.The entire programme incorporates six subroutines, as well as the main controlling programme. One subroutine reads in the catch and effort data, a second reads in the age distribution data for each year and, if necessary, converts it according to a predetermined transformation from age expressed in terms of whale ear-plug laminations to age in years. The third subroutine estimates the rate of recruitment as the proportion of newly recruited animals in the catch for each year, using the method of Allen (1966). The other three subroutines derive population estimates, using the "q," modified DeLury, and actual and expected catch methods (Allen, 1966). As many sets of data as desired may be processed in a single computer run.

Predicting the effects of climate change on bird population dynamics

2019 ◽  
pp. 74-90
Author(s):  
Bernt-Erik Sæther ◽  
Steinar Engen ◽  
Marlène Gamelon ◽  
Vidar Grøtan
Keyword(s):  
Climate Change ◽  
Population Dynamics ◽  
Population Size ◽  
Environmental Stochasticity ◽  
Population Estimates ◽  
Parameter Estimates ◽  
Vital Rates ◽  
Statistical Sense ◽  
High Level ◽  
Avian Populations

Climate variation strongly influences fluctuations in size of avian populations. In this chapter, we show that it is difficult to predict how the abundance of birds will respond to climate change. A major reason for this is that most available time series of fluctuations in population size are in a statistical sense short, thus often resulting in large uncertainties in parameter estimates. We therefore argue that reliable population predictions must be based on models that capture how climate change will affect vital rates as well as including other processes (e.g. density-dependences) known to affect the population dynamics of the species in question. Our survey of examples of such forecast studies show that reliable predictions necessarily contain a high level of uncertainty. A major reason for this is that avian population dynamics are strongly influenced by environmental stochasticity, which is for most species, irrespective of their life history, the most important driver of fluctuations in population size. Credible population predictions must therefore assess the effects of such uncertainties as well as biases in population estimates.

A Generalization of the Murphy Catch Equation

1970 ◽  
Vol 27 (4) ◽  
pp. 821-825 ◽  
Author(s):  
Patrick K. Tomlinson
Keyword(s):  
Mortality Rate ◽  
Population Size ◽  
Generalized Equation ◽  
Time Interval ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Time Intervals

Given catches, by time intervals, from a known cohort of fish with known natural mortality rate and known fishing mortality rate for either the first or last time interval, the population size at the beginning of each interval and the fishing mortality rate during each interval may be estimated using a generalized Murphy catch equation. The generalized equation is constructed from the ratio of catches in successive intervals and depends on the assumption of simple exponential mortality within the intervals. The intervals may vary in length and have zero catches. The estimates may be badly biased depending on the nature of the catch sequence and the independent estimates of natural mortality and fishing mortality used to start the procedure.

scholarly journals A study of brown-marbled grouper (Epinephelus fuscoguttatus) population dynamics in Takabonerate National Park Waters, South Sulawesi, Indonesia

2021 ◽  
Vol 22 (10) ◽  
Author(s):  
FATMA FATMA ◽  
ACHMAR MALLAWA ◽  
NAJAMUDDIN NAJAMUDDIN ◽  
MUKTI ZAINUDDIN ◽  
FACHRIE REZKA AYYUB
Keyword(s):  
Growth Rate ◽  
Population Dynamics ◽  
Mortality Rate ◽  
National Park ◽  
Size Structure ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
South Sulawesi ◽  
Exploitation Rate ◽  
Epinephelus Fuscoguttatus

Abstract. Fatma, Mallawa A, Najamuddin, Zainuddin M, Fachrie R. 2021. A study of brown-marbled grouper (Epinephelus fuscoguttatus) population dynamics in Takabonerate National Park Waters, South Sulawesi, Indonesia. Biodiversitas 22: 4298-4307. Understanding aspects of the population dynamics of groupers such as the brown-marbled grouper can provide valuable insights into how to manage grouper stocks effectively. Conducted from February 2020 to February 2021 in Takabonerate National Park waters, Selayar Islands District, South Sulawesi, Indonesia, this study sought to elucidate the size structure and cohorts, population growth rate, total mortality rate, fishing mortality rate, natural mortality rate, exploitation rate and yield per recruit (Y/R) of the brown-marbled grouper. Grouper samples were caught using several fishing gears (i.e., hand line fishing, spearfishing, and trapping) with a total catch of 1042 specimens. The sampled specimens exhibited significant size structure and were classified into five age-specific cohorts. The growth rate coefficient was 0.46/year, with the brown-marbled grouper population tending to exhibit slow growth (K < 0.5/year). The estimated asymptotic length was 109.0 cm. The fishing mortality was higher than the natural mortality, with an exploitation rate of 0.65, indicating that brown-marbled groupers in the waters of Takabonerate National Park have been subjected to extensive and intensive fishing, as also indicated by an estimated Y/R lower than the optimum Y/R rate.

scholarly journals POPULATION DYNAMICS OF TUNA (EUTHYNNUS AFFINIS, CANTOR 1849) IN WESTERN WATERS OF SOUTH SULAWESI

2020 ◽  
Vol 8 (8) ◽  
pp. 164-172
Author(s):  
Budiman Yunus ◽  
Suwarni ◽  
Basse Siang Parawansa
Keyword(s):  
Population Dynamics ◽  
Mortality Rate ◽  
Age Groups ◽  
Total Mortality ◽  
Assessment Tools ◽  
Natural Mortality ◽  
Age Group ◽  
Fishing Mortality ◽  
Growth Coefficient ◽  
South Sulawesi

This study aims to determine the population dynamics of tuna including age group, growth, mortality, exploitation rate and yield per recruitment. It was conducted from June to August in West Waters of South Sulawesi. By method of age group using Bhattacharya method with FAO-ICLARM Fish Stock Assessment Tools II (FISAT II) program, growth using Von Bertalanffy’s equation, natural mortality (M) using Pauly’s empirical equation, total mortality (Z) using Beverton and Holt’s equations, fishing mortality (F) by the formula Z = F + M, exploitation (E) using Baverton and Holt’s equations and yield per recruitment (Y/R’) using Baverton and Holt’s equations. The results of research of tuna observed were 737 includes 355 male tunas and 382 female tunas. The estimation of total length ranging from 215 mm to 429 mm. Male tunas are classified into 4 (four) of age groups with a length of 236.67, 272.8, 326.04 and 375.53 mm, respectively. Asymptote length (L∞) = 455.00 mm, growth coefficient (K) = 0.33 and theoretical age (t0) of -0.2377 per year. Total mortality rate (Z) = 1.12 per year. Natural mortality (M) = 0.41 per year, fishing mortality (F) = 0.71, exploitation (E) = 0.63 and yield per recruitment (Y/R’) = 0.0691, while male tunas are classified into 5 (five) of age groups with a length of 235.73, 272.86, 326.89, 360.89 and 408.89 mm, respectively. Asymptote length (L∞) = 453.50 mm, growth coefficient (K) = 0.42 and theoretical age (t0) of -0.1853 per year. Total mortality rate (Z) = 1.35 per year. Natural mortality (M) = 0.48 per year, fishing mortality (F) = 0.87, exploitation (E) = 0.64 and yield per recruitment (Y/R’) = 0.0784. Thus, it can be concluded that tuna in West Waters of South Sulawesi have declined and thought occur overfishing.

scholarly journals Demographic effects of interacting species: exploring stable coexistence under increased climatic variability in a semiarid shrub community

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ana I. García-Cervigón ◽  
Pedro F. Quintana-Ascencio ◽  
Adrián Escudero ◽  
Merari E. Ferrer-Cervantes ◽  
Ana M. Sánchez ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Species Coexistence ◽  
Climatic Factors ◽  
Demographic Data ◽  
Climatic Variability ◽  
Biotic Interactions ◽  
Vital Rates ◽  
Climatic Fluctuations ◽  
Demographic Models ◽  
Shrub Community

AbstractPopulation persistence is strongly determined by climatic variability. Changes in the patterns of climatic events linked to global warming may alter population dynamics, but their effects may be strongly modulated by biotic interactions. Plant populations interact with each other in such a way that responses to climate of a single population may impact the dynamics of the whole community. In this study, we assess how climate variability affects persistence and coexistence of two dominant plant species in a semiarid shrub community on gypsum soils. We use 9 years of demographic data to parameterize demographic models and to simulate population dynamics under different climatic and ecological scenarios. We observe that populations of both coexisting species may respond to common climatic fluctuations both similarly and in idiosyncratic ways, depending on the yearly combination of climatic factors. Biotic interactions (both within and among species) modulate some of their vital rates, but their effects on population dynamics highly depend on climatic fluctuations. Our results indicate that increased levels of climatic variability may alter interspecific relationships. These alterations might potentially affect species coexistence, disrupting competitive hierarchies and ultimately leading to abrupt changes in community composition.

scholarly journals Vital rates of two small populations of brown bears in Canada and range‐wide relationship between population size and trend

2021 ◽  
Vol 11 (7) ◽  
pp. 3422-3434
Author(s):  
Michelle L. McLellan ◽  
Bruce N. McLellan ◽  
Rahel Sollmann ◽  
Heiko U. Wittmer
Keyword(s):  
Population Size ◽  
Small Populations ◽  
Vital Rates ◽  
Brown Bears

scholarly journals Within- and among-population variation in vital rates and population dynamics in a variable environment

2016 ◽  
Vol 26 (7) ◽  
pp. 2086-2102 ◽  
Author(s):  
Simone Vincenzi ◽  
Marc Mangel ◽  
Dusˇan Jesensˇek ◽  
John C. Garza ◽  
Alain J. Crivelli
Keyword(s):  
Population Dynamics ◽  
Population Variation ◽  
Vital Rates ◽  
Variable Environment
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