The effect of growth curve and sampling regime on instantaneous‐growth, removal‐summation, and Hynes/Hamilton estimates of aquatic insect production: A computer simulation 1

Cushman, R. M.; Shugart, H. H.; Hildebrand, S.G.; Elwood, Jerry W.

doi:10.4319/lo.1978.23.1.0184

Cited by 55 publications

(39 citation statements)

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“…Calculation methods such as those based on cohort increment or removal summation, Allen's curve, instantaneous growth, and the size frequency methods have been studied and compared (Waters and Crawford, 1973;Cushman et al, 1978;Wildish and Pier, 1981;Benke, 1984;Giberson and Galloway, 1985;Morin et al, 1987). In general, cohort methods were considered as providing similar and more accurate estimates (although with instantaneous growth estimates could be slightly more biased, Cushman et al, 1978;Morin et al, 1987), whereas size frequency methods have been pointed out to over estimate production (Waters and Crawford, 1973;Cushman et al, 1978;Wildish and Pier, 1981;Benke, 1984).…”

Section: Methodological Comparisonsmentioning

confidence: 99%

“…In general, cohort methods were considered as providing similar and more accurate estimates (although with instantaneous growth estimates could be slightly more biased, Cushman et al, 1978;Morin et al, 1987), whereas size frequency methods have been pointed out to over estimate production (Waters and Crawford, 1973;Cushman et al, 1978;Wildish and Pier, 1981;Benke, 1984). Also, cohort increment summation is often used in secondary production studies (Brey, 1990a,b;Benke, 1993;Sprung, 1994;Mistri et al, 2001;Dolbeth et al, 2003), which justifies its use as a benchmark.…”

Section: Methodological Comparisonsmentioning

confidence: 99%

“…It is a quantitative measure of population function in the ecosystem, being often used to assess environmental stress, rational management of biological resources, energy flow, organic matter cycling and food web interactions (Waters and Crawford, 1973;Cushman et al, 1978;Benke, 1984Benke, , 1993Crisp, 1984;Morin et al, 1987;Tumbiolo and Downing, 1994). Moreover, it may acquire economic importance, when related with fish and shellfish yield (Waters and Crawford, 1973;Crisp, 1984;Brey, 1990a).…”

Section: Introductionmentioning

confidence: 99%

“…For long time, methods based on the recognition of cohorts have been considered to provide accurate evaluation of secondary production (Waters and Crawford, 1973;Cushman et al, 1978;Benke, 1993;Sprung, 1993;Medernach, 1999;Brey, 2001). Whenever cohorts are not recognizable, size frequency and mass specific growth rate methods have been applied (Benke, 1984;Brey, 2001).…”

Section: Introductionmentioning

confidence: 99%

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Annual production of estuarine fauna in different environmental conditions: An evaluation of the estimation methods

Dolbeth

Lillebø

Cardoso

et al. 2005

Journal of Experimental Marine Biology and Ecology

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Secondary production is one of the most comprehensive measurements of ecosystem health. Production of five estuarine species, with different life history and abundance in the ecosystem, was estimated for 2 consecutive years at a Zostera noltii bed and sand-muddy area, with contrasted environmental conditions. Calculations were performed using different estimation methods, commonly cited in secondary production studies. Annual production estimated by cohort increment summation varied between 43.3 and 209.2 g AFDW m À 2 y À 1. All the other methods were compared with the results obtained from this methodology to evaluate each method's performance. In general, satisfactory results were obtained with Brey (2001) [Brey, T., 2001. Population dynamics in benthic invertebrates. A virtual handbook. Version 01.2. http:// www.awi-bremerhaven.de/Benthic/Ecosystem/FoodWeb/Handbook/main.html. Alfred Wegener Institute for Polar and Marine Research, Germany] version 4-04 (deviations that ranged between À 4 to + 10%). The responses of the other empirical methods were more variable, depending on the species characteristics. Therefore, the optimal selection of an empirical method in secondary production studies depends on the species considered and on the quality of the parameters required for the application of the method. Brey (2001) [Brey, T., 2001. Population dynamics in benthic invertebrates. A virtual handbook. Version 01.2. http://www.awi-bremerhaven.de/Benthic/Ecosystem/FoodWeb/Handbook/main.html. Alfred Wegener Institute for Polar and Marine Research, Germany] version 4-04 was considered the best methodology. For the less representative species the simple sum of biomass increments from one sampling date to the next may be an easy and valid option. D

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Section: Methodological Comparisonsmentioning

confidence: 99%

Section: Methodological Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Annual production of estuarine fauna in different environmental conditions: An evaluation of the estimation methods

Dolbeth

Lillebø

Cardoso

et al. 2005

Journal of Experimental Marine Biology and Ecology

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“…They have been extensively compared through simulations, most notably by Cushman et al (1978), Lapchin andNeveu (1980), andMorin et al (1987). These and other authors examined how various estimates were affected by different assumptions on the growth and mortality curves, as well as by sampling effort.…”

Section: Introductionmentioning

confidence: 99%

Effect of different sampling designs and methods on the estimation of secondary production: A simulation

Cusson

Plante

Genest

2006

Limnology & Ocean Methods

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IntroductionIn marine studies, the secondary production of macrobenthic populations can be estimated in a number of ways. Classic techniques can be broadly classified as cohort-and size-based. Prominent in the first group are the Allen-curve, incrementand removal-summation, and instantaneous-growth methods. The second group consists mainly of the size-frequency, massspecific growth rate, and mass-specific mortality rate methods.These estimation techniques, and numerous variants thereof, have been described, e.g., by Benke (1984), Crisp (1984), andRigler andDowning (1984). They have been extensively compared through simulations, most notably by Cushman et al. (1978), Lapchin andNeveu (1980), andMorin et al. (1987). These and other authors examined how various estimates were affected by different assumptions on the growth and mortality curves, as well as by sampling effort. Their hypothetical populations, which were alternately assumed to be synchronous or not, were modeled on freshwater species having a lifespan of 1 year or less.This article revisits the issue and expands on the comparison of the above production estimates, and several of their variants introduced in the literature, using a hypothetical population of mussels characterized by a number of realistic factors. Most prominent among them are the simultaneous presence of different cohorts, quadrat-dependent population density, seasonal growth oscillation, gradual recruit arrival, and random individual variation both in survival and in weight gain.The simulations presented herein are also novel in that several aspects of the sampling design are considered, namely the number of sampling occasions (either regularly spaced or concentrated in the growing season), quadrats sampled per occasion, and use of two different sieves. Following Cushman et al. (1978), the bias and variance of the various estimators are compared to the exact production obtained by summing all individual body-mass gains, rather than to a theoretical Allen curve which may or may not reflect reality. Effect of different sampling designs and methods on the estimation of secondary production: A simulation AbstractThis article reports the results of a simulation study designed to investigate the effect of several sampling design factors on the accuracy and precision of various estimates of secondary production. Whereas most previous studies of this sort were concerned with freshwater fauna (e.g., insects), the hypothetical population used here reflects the characteristics of marine mussels from cold-temperate and subarctic regions. It features the simultaneous presence of different cohorts, gradual recruit arrival, seasonal growth oscillation, and quadratdependent population density, as well as random individual variation both in survival and in weight gain. For this population, the percentage relative bias (PRB) and relative root mean squared error (RRMSE) of 4 classic cohort-based methods, 3 size-based methods, and several variants thereof were computed as a function of sampling frequency...

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Life Cycle, Production and Survival Rates ofPtychoptera paludosa(Diptera: Ptychopteridae)

Wolf¹,

Zwick²

2001

Internat. Rev. Hydrobiol.

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The effect of growth curve and sampling regime on instantaneous‐growth, removal‐summation, and Hynes/Hamilton estimates of aquatic insect production: A computer simulation 1

Cited by 55 publications

References 9 publications

Annual production of estuarine fauna in different environmental conditions: An evaluation of the estimation methods

Annual production of estuarine fauna in different environmental conditions: An evaluation of the estimation methods

Effect of different sampling designs and methods on the estimation of secondary production: A simulation

Life Cycle, Production and Survival Rates ofPtychoptera paludosa(Diptera: Ptychopteridae)

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