16
1 Introduction to the Concepts and Use of ERA Acute
Transparency is therefore needed when presenting results, and as with all other
models, users need to verify both data coverage and applicability before entering
data into the model. It is recommended that VEC data from the different levels
(A.1, A.2 and A.3) are not mixed in the same analysis, e.g. by using presence/no
presence data for one VEC and fraction of populations for another VEC, as the
calculated results reflect the VEC cell value directly. Different data types should
be separated when showing results. Many options are possible for the VEC “unit”,
the parameter that defines the seasonal and geographical distribution (denoted N in
calculations), and the ERA Acute industry guideline (NOROG 2020) will advise on
data use for standardized applications of the ERA Acute methodology, including
setting the analysis scale. The model implementation software handles differences
in data set levels but uses the VEC distribution parameter-value transparently and
directly. Users must therefore still apply scientific caution when using data sets from
different sources, especially when comparing and interpreting results, as is the case
for all models.
Comparing results between compartments can be particularly challenging in
models like ERA Acute, because the impact calculations are based on compartmentspecific modes of action and ERA Acute therefore uses compartment-specific functions behind the calculations of lethality and exposure. In e.g. the surface compartment, laboratory-controlled experiments cannot be used to determine the quantitative
relationship between dose and response. For some mechanisms, such as smothering
or oiling on feathers, a dose-response relationship may not even be clear, although we
intuitively understand that a large spill may have a higher impact than a smaller spill.
Different approaches have therefore been used in the model development, utilizing
as far as possible the knowledge available of impact mechanisms, impact magnitudes after known oil spills and various theoretical approaches. Since the units of
the VEC distribution parameter-values and therefore also the endpoints are different,
the numerical results in compartments cannot be compared directly, but users may
compare for example results as relative to a maximum or in severity categories carefully defined for each compartment. Relative differences in risks within a single
compartment may be compared directly between cases. Comparisons are relevant
e.g. in SIMA analyses. Keeping the integrity of each compartment is important, both
when it comes to the possibility for the analyst to interpret results clearly and for the
use of the different endpoints in practical applications. Weighting the result-levels
between the four compartments has so far not been part of the methodology development. Also, under different regulatory frameworks there may be different requirements regarding weighting between VECs and/or compartments, or to which degree
stakeholders are involved in the assessment process or whether the management
process includes stakeholder value scoring of VECs (e.g. Bock et al. 2018).
ERA Acute uses a series of input parameters that are entered into the model
at various stages. The ERA Acute methodology has been tested with respect to
sensitivity towards important input parameters, using statistical and deterministic
testing methods as part of the uncertainty handling (Chap. 4). The model is flexible
in design by allowing the user to change some of these parameters if other values
are more relevant regionally. However, within a region, it is recommended that the
1 Introduction to the Concepts and Use of ERA Acute
Transparency is therefore needed when presenting results, and as with all other
models, users need to verify both data coverage and applicability before entering
data into the model. It is recommended that VEC data from the different levels
(A.1, A.2 and A.3) are not mixed in the same analysis, e.g. by using presence/no
presence data for one VEC and fraction of populations for another VEC, as the
calculated results reflect the VEC cell value directly. Different data types should
be separated when showing results. Many options are possible for the VEC “unit”,
the parameter that defines the seasonal and geographical distribution (denoted N in
calculations), and the ERA Acute industry guideline (NOROG 2020) will advise on
data use for standardized applications of the ERA Acute methodology, including
setting the analysis scale. The model implementation software handles differences
in data set levels but uses the VEC distribution parameter-value transparently and
directly. Users must therefore still apply scientific caution when using data sets from
different sources, especially when comparing and interpreting results, as is the case
for all models.
Comparing results between compartments can be particularly challenging in
models like ERA Acute, because the impact calculations are based on compartmentspecific modes of action and ERA Acute therefore uses compartment-specific functions behind the calculations of lethality and exposure. In e.g. the surface compartment, laboratory-controlled experiments cannot be used to determine the quantitative
relationship between dose and response. For some mechanisms, such as smothering
or oiling on feathers, a dose-response relationship may not even be clear, although we
intuitively understand that a large spill may have a higher impact than a smaller spill.
Different approaches have therefore been used in the model development, utilizing
as far as possible the knowledge available of impact mechanisms, impact magnitudes after known oil spills and various theoretical approaches. Since the units of
the VEC distribution parameter-values and therefore also the endpoints are different,
the numerical results in compartments cannot be compared directly, but users may
compare for example results as relative to a maximum or in severity categories carefully defined for each compartment. Relative differences in risks within a single
compartment may be compared directly between cases. Comparisons are relevant
e.g. in SIMA analyses. Keeping the integrity of each compartment is important, both
when it comes to the possibility for the analyst to interpret results clearly and for the
use of the different endpoints in practical applications. Weighting the result-levels
between the four compartments has so far not been part of the methodology development. Also, under different regulatory frameworks there may be different requirements regarding weighting between VECs and/or compartments, or to which degree
stakeholders are involved in the assessment process or whether the management
process includes stakeholder value scoring of VECs (e.g. Bock et al. 2018).
ERA Acute uses a series of input parameters that are entered into the model
at various stages. The ERA Acute methodology has been tested with respect to
sensitivity towards important input parameters, using statistical and deterministic
testing methods as part of the uncertainty handling (Chap. 4). The model is flexible
in design by allowing the user to change some of these parameters if other values
are more relevant regionally. However, within a region, it is recommended that the