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An Empirical Method for Characterizing Standing Crops of Aquatic Vegetation 1

Daniel E. Canfieldjr, Mark V. Hoyer, Carlos M. Duarte

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Abstract

where N = number of sampling stations; t = Student's t at a given probability level; S = standard deviation, X = estimated true population mean; d = permissible error of the final mean. Thus, the number of sampling stations necessary to characterize the mean macrophyte standing crop changes proportionally to the square of the coeffi­ cient of variation and to the inverse of the square of the permissible error (Figure 1). Because the coefficient of variation associated with the mean macrophyte standing crop is often> 50 %, the number of sampling stations necessary to estimate the mean macrophyte standing crop, especially with a permissible error of 10 % as is often re- ABSTRACT 10% Data from 55 Florida lakes were used to demonstrate that the maximum measured standing crop of emergent, floating-leaved, and submersed plants can be used to pro­ vide a simple characterization of macrophyte standing crops in the littoral zones of lakes. The maximum standing crop was strongly related to the mean standing crop of emergent (R2 = 0.83), floating-leaved (R2 = 0.64), and submersed (R2 = 0.85) macrophytes, and there was also a strong relationship (R2 = 0.79) when data from all plant types were combined. Our best-fit regression equations were In EB = 1.07 In MEB - 1.19, In FB = 1.28 In MFB - 2.73, In SB = 1.20 In MSB - 1.98, and In TMB = 1.20 In MTMB - 2.11 where EB, FB, SB, and TMB are the average standing crops (g dry wt m- 2 ) of emergent, float­ ing-leaved, submersed, and total macrophytes respectively, and MEB, MFB, MSB, and MTMB are the maximum standing crops measured for the different groups. Stand­ ard errors of estimates for the average standing crops of the different plant types in individual lakes were of similar magnitude to the errors of estimates obtained for the <JJ mean-maximum standing crop regression equations. ~ These analyses suggest that the maximum standing crop ~ of aquatic macrophytes can provide useful information to ~ characterize macrophyte standing crop in the littoral zone ­ of lakes. ~ E

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where N = number of sampling stations; t = Student's t at a given probability level; S = standard deviation, X = estimated true population mean; d = permissible error of the final mean. Thus, the number of sampling stations necessary to characterize the mean macrophyte standing crop changes proportionally to the square of the coeffi­ cient of variation and to the inverse of the square of the permissible error (Figure 1). Because the coefficient of variation associated with the mean macrophyte standing crop is often> 50 %, the number of sampling stations necessary to estimate the mean macrophyte standing crop, especially with a permissible error of 10 % as is often re- ABSTRACT 10% Data from 55 Florida lakes were used to demonstrate that the maximum measured standing crop of emergent, floating-leaved, and submersed plants can be used to pro­ vide a simple characterization of macrophyte standing crops in the littoral zones of lakes. The maximum standing crop was strongly related to the mean standing crop of emergent (R2 = 0.83), floating-leaved (R2 = 0.64), and submersed (R2 = 0.85) macrophytes, and there was also a strong relationship (R2 = 0.79) when data from all plant types were combined. Our best-fit regression equations were In EB = 1.07 In MEB - 1.19, In FB = 1.28 In MFB - 2.73, In SB = 1.20 In MSB - 1.98, and In TMB = 1.20 In MTMB - 2.11 where EB, FB, SB, and TMB are the average standing crops (g dry wt m- 2 ) of emergent, float­ ing-leaved, submersed, and total macrophytes respectively, and MEB, MFB, MSB, and MTMB are the maximum standing crops measured for the different groups. Stand­ ard errors of estimates for the average standing crops of the different plant types in individual lakes were of similar magnitude to the errors of estimates obtained for the <JJ mean-maximum standing crop regression equations. ~ These analyses suggest that the maximum standing crop ~ of aquatic macrophytes can provide useful information to ~ characterize macrophyte standing crop in the littoral zone ­ of lakes. ~ E

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Available abstract

where N = number of sampling stations; t = Student's t at a given probability level; S = standard deviation, X = estimated true population mean; d = permissible error of the final mean. Thus, the number of sampling stations necessary to characterize the mean macrophyte standing crop changes proportionally to the square of the coeffi­ cient of variation and to the inverse of the square of the permissible error (Figure 1). Because the coefficient of variation associated with the mean macrophyte standing crop is often> 50 %, the number of sampling stations necessary to estimate the mean macrophyte standing crop, especially with a permissible error of 10 % as is often re- ABSTRACT 10% Data from 55 Florida lakes were used to demonstrate that the maximum measured standing crop of emergent, floating-leaved, and submersed plants can be used to pro­ vide a simple characterization of macrophyte standing crops in the littoral zones of lakes. The maximum standing crop was strongly related to the mean standing crop of emergent (R2 = 0.83), floating-leaved (R2 = 0.64), and submersed (R2 = 0.85) macrophytes, and there was also a strong relationship (R2 = 0.79) when data from all plant types were combined. Our best-fit regression equations were In EB = 1.07 In MEB - 1.19, In FB = 1.28 In MFB - 2.73, In SB = 1.20 In MSB - 1.98, and In TMB = 1.20 In MTMB - 2.11 where EB, FB, SB, and TMB are the average standing crops (g dry wt m- 2 ) of emergent, float­ ing-leaved, submersed, and total macrophytes respectively, and MEB, MFB, MSB, and MTMB are the maximum standing crops measured for the different groups. Stand­ ard errors of estimates for the average standing crops of the different plant types in individual lakes were of similar magnitude to the errors of estimates obtained for the <JJ mean-maximum standing crop regression equations. ~ These analyses suggest that the maximum standing crop ~ of aquatic macrophytes can provide useful information to ~ characterize macrophyte standing crop in the littoral zone ­ of lakes. ~ E

Key concepts: Standing crop, Macrophyte, Mathematics, Mean squared error, Sampling (signal processing), Crop, Statistics, Population

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