Scoring of each indicator based on an internal criterion-scoring scheme applied on the output of the trend and pressure model functions.
scoring( trend_tbl = NULL, mod_tbl, press_type = NULL, crit_scores = INDperform::crit_scores_tmpl, sign_level = 0.05 )
| trend_tbl | Output tibble from the |
|---|---|
| mod_tbl | Output tibble from the IND~pressure modeling functions. |
| press_type | 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 |
| crit_scores | Internal tibble of (sub)criteria and respective scores
named |
| sign_level | Significance level on which scoring is built; default is 0.05. |
The function returns a nested tibble with the following elements depending on the criteria rated
indA vector of the indicator names.
C8 and/or C11A vector of IND-specific scores for criterion 8 (trend indication) and/or C11 (management application).
press_spec_scA 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 unnest function.
That is, each element of the data frame in the list-column press_spec_sc becomes
its own row in the tibble.
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
crit_scores_tmpl or 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.
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
unnest to make each element of the data frame in the
list-column press_spec_sc its own row and nest for the
inverse operation
Other score-based IND performance functions:
clust_sc(),
dist_sc_group(),
dist_sc(),
expect_resp(),
plot_clust_sc(),
plot_spiechart(),
summary_sc()
Other IND~pressure modeling functions:
find_id(),
ind_init(),
model_gamm(),
model_gam(),
plot_diagnostics(),
plot_model(),
select_model(),
test_interaction()
# 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)#> $overview #> ind nr_sign_press C8 C9 C10 C11 C8_in% C9_in% C10_in% C11_in% #> 1 TZA 2 0 5.0 2.0 2 0 83 33 100 #> 2 MS 2 0 4.0 2.5 1 0 67 42 50 #> 3 rCC 1 0 6.0 4.0 2 0 100 67 100 #> 4 Cops 0 0 0.0 0.0 0 0 0 0 0 #> 5 Micro 2 1 5.0 4.0 1 100 83 67 50 #> 6 rZPPP 1 0 4.0 5.0 2 0 67 83 100 #> 7 Sprat 1 1 2.0 1.0 2 100 33 17 100 #> 8 Herring 0 1 0.0 0.0 0 100 0 0 0 #> 9 Stickle 0 1 0.0 0.0 0 100 0 0 0 #> 10 Cod 2 1 5.5 1.5 2 100 92 25 100 #> 11 SPF 1 1 5.0 4.0 2 100 83 67 100 #> 12 LPF 1 1 5.0 5.0 2 100 83 83 100 #> #> $subcriteria_per_press #> ind press press_type C9_1 C9_2 C10_1 C10_2 C10_3 C10_4 C9 C10 C9_in% #> 1 TZA Fsprat Fishing 3 3 1 0 0 0 6 1 100 #> 2 TZA Fher Fishing 1 3 1 1 1 0 4 3 67 #> 3 MS Swin Climate 2 2 1 0 1 1 4 3 67 #> 4 MS Fher Fishing 1 3 1 1 0 0 4 2 67 #> 5 rCC Tsum Climate 3 3 1 1 1 1 6 4 100 #> 6 Micro Tsum Climate 2 3 1 1 2 1 5 5 83 #> 7 Micro Fsprat Fishing 2 3 1 0 2 0 5 3 83 #> 8 rZPPP Tsum Climate 1 3 1 1 2 1 4 5 67 #> 9 Sprat Fher Fishing 2 0 1 0 0 0 2 1 33 #> 10 Cod Fher Fishing 3 3 1 0 0 0 6 1 100 #> 11 Cod Fcod Fishing 2 3 1 0 1 0 5 2 83 #> 12 SPF Pwin Eutrophication 2 3 1 1 1 1 5 4 83 #> 13 LPF Fcod Fishing 2 3 1 1 2 1 5 5 83 #> C10_in% #> 1 17 #> 2 50 #> 3 50 #> 4 33 #> 5 67 #> 6 83 #> 7 50 #> 8 83 #> 9 17 #> 10 17 #> 11 33 #> 12 67 #> 13 83 #> #> $scores_matrix #> C8 C11 Fcod_C10 Fcod_C9 Fher_C10 Fher_C9 Fsprat_C10 Fsprat_C9 Nwin_C10 #> TZA 0 2 0 0 3 4 1 6 0 #> MS 0 1 0 0 2 4 0 0 0 #> rCC 0 2 0 0 0 0 0 0 0 #> Cops 0 0 0 0 0 0 0 0 0 #> Micro 1 1 0 0 0 0 3 5 0 #> rZPPP 0 2 0 0 0 0 0 0 0 #> Sprat 1 2 0 0 1 2 0 0 0 #> Herring 1 0 0 0 0 0 0 0 0 #> Stickle 1 0 0 0 0 0 0 0 0 #> Cod 1 2 2 5 1 6 0 0 0 #> SPF 1 2 0 0 0 0 0 0 0 #> LPF 1 2 5 5 0 0 0 0 0 #> Nwin_C9 Pwin_C10 Pwin_C9 Swin_C10 Swin_C9 Tsum_C10 Tsum_C9 #> TZA 0 0 0 0 0 0 0 #> MS 0 0 0 3 4 0 0 #> rCC 0 0 0 0 0 4 6 #> Cops 0 0 0 0 0 0 0 #> Micro 0 0 0 0 0 5 5 #> rZPPP 0 0 0 0 0 5 4 #> Sprat 0 0 0 0 0 0 0 #> Herring 0 0 0 0 0 0 0 #> Stickle 0 0 0 0 0 0 0 #> Cod 0 0 0 0 0 0 0 #> SPF 0 4 5 0 0 0 0 #> LPF 0 0 0 0 0 0 0 #>if (FALSE) { # To see the criterion template and change it potentially View(crit_scores_tmpl) # E.g. exclude the trend criterion crit_scores_tmpl_new <- crit_scores_tmpl[crit_scores_tmpl$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) }