Scoring of each indicator based on an internal criterion-scoring scheme applied on the output of the trend and pressure model functions.
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Output tibble from the
Output tibble from the IND~pressure modeling functions.
Data frame or tibble with pressure names (named 'press') in
first column and corresponding pressure types in second column (named 'press_type').
Needed for the spie chart! (see for an example
Internal tibble of (sub)criteria and respective scores
Significance level on which scoring is built; default is 0.05.
Among the 16 common indicator selection criteria summarized in Otto et al. (2018) five criteria relate to the indicators' performances and require time series for their evaluation, i.e.
Crit. 8: Development reflects ecosystem change caused by variation in manageable pressure(s)
Crit. 9: Sensitive or responsive to pressures
Crit. 10: Robust, i.e. responses in a predictive fashion, and statistically sound
Crit. 11: Links to management measures (responsiveness and specificity)
Crit. 12: Relates where appropriate to other indicators but is not redundant (not scored)
In this function, the scoring scheme for these criteria as proposed by Otto et al. (2018) serves as basis for the quantification of the IND performance. Sensitivity (criterion 9) and robustness (criterion 10) are specified into more detailed sub-criteria to allow for quantification based on statistical models and rated individually for every potential pressure that might affect the IND directly or indirectly. In the case of non-significant relationships between a IND and a specific pressures, sub-crit. 9.1 and all following pressure-specific sub-crit. in criteria 9 and 10 are scored zero for this pressure.
The template tibble
crit_scores_tmpl contains all relevant informations and
serves as basis for the scoring in this function. See for more details
View(crit_scores_tmpl). The scoring scheme can
easily be adapted to any kind of state indicator and management scheme by modifying
the scores, the weighting of scores or by removing or adding (sub)criteria in the
crit_scores_tmpl template. The
condition variable can also be modified
but needs to follow the same syntax.
The function returns a nested tibble with the following elements depending on the criteria rated
A vector of the indicator names.
A vector of IND-specific scores for criterion 8 (trend indication) and/or C11 (management application).
A list-column of IND-specific data frames containing pressure-specific scores for the sub-criteria 9.1-9.2, 10.1-10.4.
The tibble can easily be unnested by using the
That is, each element of the data frame in the list-column
its own row in the tibble.
Otto, S.A., Kadin, M., Casini, M., Torres, M.A., Blenckner, T. (2018) A quantitative framework for selecting and validating food web indicators. Ecological Indicators, 84: 619-631, doi: https://doi.org/10.1016/j.ecolind.2017.05.045
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# Using the Baltic Sea demo data in this package scores_tbl <- scoring(trend_tbl = model_trend_ex, mod_tbl = all_results_ex, press_type = press_type_ex) summary_sc(scores_tbl) ## Not run: # To see the criterion template and change it potentially View(crit_scores_tmpl) # E.g. exclude the trend criterion crit_scores_tmpl_new <- crit_scores_tmpl[crit_scores_tmpl$crit_id > 1, ] # Now the trend tibble is not needed anymore scores_tbl <- scoring(mod_tbl = all_results_ex, press_type = press_type_ex, crit_scores = crit_scores_tmpl_new) ## End(Not run)
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