Shoot Biomass Assessments of the Marine Phanerogam Zostera marina for Two Methods of Data Gathering

1544

and processing sufficient data to test a robust statistical

method, could be an extremely time consuming endeavor.

For that reason some authors use aggregated data or data

at a shoot level instead of data at a leaf level (non-ag-

gregated) to test differences of some measurements in

time and space [13]. Moreover, data gathering for eel-

grass assessments methods could be time consuming and

destructive. For example at a leaf level, each leaf in a

shoot should be counted, measured (length and width)

and weighted implying a enormous time of sample proc-

essing and for biomass (for example) a bigger error in

weighting each leaf separately.

On the other hand, aggregated data, could be easier to

obtain and present less error, but could not be used in

some models that require individual measurements, as

Equation (1).

We have demonstrated in this work, that for biomass

assessments a several-variables version of the allometric

Equation (1), Equation (2) where leaf dry weights are

aggregated at a shoot level gives the same results as the

assessments found for the fitting of Equation (1). We

found that parameters fitted for both models were statis-

tically the same with p = 0.11 for

and p = 0.50 for

.

The determination coefficients for both fittings were

also statistically the same (p > 0.05). Moreover Lin [19]

Concordance Correlation Coefficient of reproducibility

(ˆ

) attained exactly the same value for both fits (0.92),

and The AIC shows that both models deserve considera-

tion for statistical inference. Figure 4 shows that pro-

jected values of mean shoot biomass per month are al-

most identical and in a good correspondence with ob-

served values, therefore we consider that Equations (1)

and (2) can be used indistinctly for shoot biomass as-

sessments. Nevertheless, the fitting of Equation (1) gives

us the advantages of a smaller estimation error, but with

the disadvantage of bigger time consuming in data proc-

essing. Whereas in the fitting of Equation (2) processing

data is much less time consuming but have a slight

higher estimation error and a better disposition of residu-

als. Moreover, since the time of processing material in

aggregated form is much less time consuming, bigger

samples can be taken if necessary. In any case, regardless

of the type of data (aggregated or non-aggregated), the

allometric relationship between leaf or shoot dry weight

and leaf length is consistent for Zostera marina. In con-

clusion, for shoot weight assessments, we proposed

model of Equation (2) for large samples and faster data

processing and model of Equation (1) if data at leaf level

is required for other endeavors.

5. Acknowledgements

The authors thank Jose Maria Dominguez and Francisco

Ponce for the art work.

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