Modeling Fish Population and Biomass on the Everglades Landscape (ALFISH)

Fact Sheet ◽  
2002 ◽  
Author(s):  
Donald L. DeAngelis ◽  
Louis J. Gross ◽  
Holly Gaff ◽  
Rene Salinas
Keyword(s):  
Fish Population

Watershed Impacts on the Fish Population in the Clearwater River, ID

2002 ◽  
Author(s):  
A. N. Papanicolaou ◽  
N. Evaggelopoulos ◽  
A. Bdour
Keyword(s):  
Fish Population ◽  
Clearwater River

Individual variability and spatial heterogeneity in fish population models

1994 ◽  
Vol 4 (1) ◽  
pp. 91-123 ◽  
Author(s):  
Jeffrey A. Tyler ◽  
Kenneth A. Rose
Keyword(s):  
Spatial Heterogeneity ◽  
Fish Population ◽  
Individual Variability ◽  
Population Models

Bias in Using an Age–Length Key to Estimate Age-Frequency Distributions

1978 ◽  
Vol 35 (2) ◽  
pp. 184-189 ◽  
Author(s):  
S. J. Westrheim ◽  
W. E. Ricker
Keyword(s):  
Frequency Distribution ◽  
Age Distribution ◽  
Length Distribution ◽  
Fish Population ◽  
Systematic Bias ◽  
Parental Age ◽  
Frequency Distributions ◽  
Class Strength ◽  
Key Words Age ◽  
Age Frequency Distribution

Consider two representative samples of fish taken in different years from the same fish population, this being a population in which year-class strength varies. For the "parental" sample the length and age of the fish are determined and are used to construct an "age–length key," the fractions of the fish in each (short) length interval that are of each age. For the "filial" sample only the length is measured, and the parental age–length key is used to compute the corresponding age distribution. Trials show that the age–length key will reproduce the age-frequency distribution of the filial sample without systematic bias only if there is no overlap in length between successive ages. Where there is much overlap, the age–length key will compute from the filial length-frequency distribution approximately the parental age distribution. Additional bias arises if the rate of growth if a year-class is affected by its abundance, or if the survival rate in the population changes. The length of the fish present in any given part of a population's range can vary with environmental factors such as depth of the water; nevertheless, a sample taken in any part of that range can be used to compute age from the length distribution of a sample taken at the same time in any other part of the range, without systematic bias. But this of course is not likely to be true of samples taken from different populations of the species. Key words: age–length key, bias, Pacific ocean perch, Sebastes alutus

scholarly journals Toward linking ocean models to fish population dynamics

2010 ◽  
Vol 84 (1-2) ◽  
pp. 85-88 ◽  
Author(s):  
Lawrence J. Buckley ◽  
Lauren B. Buckley
Keyword(s):  
Population Dynamics ◽  
Fish Population ◽  
Fish Population Dynamics ◽  
Ocean Models

Contrasting Trophic Level Interactions in Lake St. George and Haynes Lake (Ontario, Canada)

1991 ◽  
Vol 48 (3) ◽  
pp. 356-363 ◽  
Author(s):  
Nathalie Lafontaine ◽  
Donald J. McQueen
Keyword(s):  
Chlorophyll A ◽  
Trophic Level ◽  
Fish Population ◽  
Pelagic Fish ◽  
Strongly Correlated ◽  
Total Zooplankton ◽  
Clear Water ◽  
Southern Ontario ◽  
Water Lake ◽  
Pelagic Communities

Two small, adjacent kettle lakes in southern Ontario were sampled during spring and summer 1987. The data comprised weekly samples of zooplankton and water chemistry, monthly diel assessments of the densities of pelagic fish and zooplankton found at 1-m depth intervals in the water column, and an annual mark and recapture assessment of the entire fish population. The two lakes had very different community structures. Haynes Lake was characterized by high piscivore numbers, few planktivores, a relatively large assemblage of large bodied zooplankton, low chlorophyll a concentrations, and clear water. Lake St. George had a lower piscivore to planktivore ratio, smaller zooplankton, more chlorophyll a, and murkier water. Comparisons of trophic level biomasses for the two lakes suggested that in both communities, the relationships between piscivores and planktivores and between planktivores and zooplankton were strongly correlated with predator abundances. In the more oligotrophy community (Haynes Lake) this influence extended weakly to the phytoplankton, but in the more eutrophic system, little of the variability in chlorophyll a with respect to total phosphorus could be explained by total zooplankton (or Daphnia) abundance. This suggests that for freshwater pelagic communities, top-down effects may be stronger in more oligotrophic systems.

Lack of relationship between simulated fish population responses and their life history traits: inadequate models, incorrect analysis, or site-specific factors?

2005 ◽  
Vol 62 (4) ◽  
pp. 886-902 ◽  
Author(s):  
Kenneth A Rose
Keyword(s):  
Life History ◽  
Life History Traits ◽  
Lake Trout ◽  
Fish Population ◽  
Population Models ◽  
Site Specific ◽  
Density Dependent ◽  
Population Responses ◽  
Adult Growth ◽  
Specific Factors

Relationships between fish population responses to changes in their vital rates and commonly available life history traits would be a powerful screening tool to guide management about species vulnerability, to focus future data collection on species and life stages of concern, and to aid in designing effective habitat enhancements. As an extension of previous analyses by others, I analyzed the responses to changes in fecundity and yearling survival of age-structured matrix and individual-based population models of 17 populations comprising 10 species. Simulations of the matrix models showed that the magnitude of population responses, but not the relative order of species sensitivity, depended on the state (sustainable or undergoing excessive removals) of the population. Matrix and individual-based models predicted population responses that appeared to be unrelated to their species-level life history traits when responses were plotted on a three-end-point life history surface. Density-dependent adult growth was added to the lake trout (Salvelinus namaycush) matrix model, and simulations demonstrated the potential importance to predicted responses of density-dependent processes outside the usual spawner–recruit relationship. Four reasons for the lack of relationship between population responses and life history traits related to inadequate population models, incorrect analysis, inappropriate life history model, and important site-specific factors are discussed.

River health assessment in a large river: Bioindicators of fish population

2013 ◽  
Vol 26 ◽  
pp. 24-32 ◽  
Author(s):  
Y.T. Jia ◽  
Y.F. Chen
Keyword(s):  
Health Assessment ◽  
Fish Population ◽  
Large River ◽  
River Health
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