The resulting modeling challenge is to effectively estimate and communicate to decision makers and stakeholders the risks and uncertainties
associated with using models to estimate effects on measures associated
with specific endpoints. Those measures may include, as an example, some
combination of population-level effects, effects on commercial and recreational fisheries, and effects on entire ecosystems. Each of these categories
of effects, however, must be framed in terms of specific endpoints and
associated measures useful for decision makers and stakeholders. For any
given 316(b) assessment, the choice of a tractable set of species, of endpoints and associated measures, of models and methods of analysis, and of
how to present and interpret results all involve value-laden judgments
similar to those made for human-health outcomes. Such choices are
unavoidable in risk assessments. These choices are the bridge connecting
scientific understanding with value-laden policy perspectives. Because of
the relative lack of experience in characterizing and valuing ecological
outcomes, 316(b) decisions cannot fall back on an accepted and narrowly
defined set of risk management protocols. Furthermore, the scientific
understanding of the ecological world is inherently complex, dynamic, and
uncertain.
52
Webb Van Winkle and John Kadvany
Informationcollection,
modeldevel opm ent,
and cal ibration
Information collection,
model development,
and calibration
Devel opi ng
deci sionmode ls
orcriteria
Developing
decision models
or criteria
Deci sionmaking
Decisionmaking
Screening, low info
requirements
More rigorous
science,
modest stakes
Harder science,
higher stakes
Basic to modest
data or modeling
Modest to significant
data or modeling
Extensive data and
modelingefforts
Simpler rules or
criteria, easier choices
Some challenging
measurement, uncertainty,
value, or stakeholder issues
Multiple measurement,
uncertainty, value,
stakeholder issues
Decision stakes and complexity
Figure 3.1. Resource management decisions involve three major activities that vary
as the decision stakes and complexity of the assessment increase.
associated with using models to estimate effects on measures associated
with specific endpoints. Those measures may include, as an example, some
combination of population-level effects, effects on commercial and recreational fisheries, and effects on entire ecosystems. Each of these categories
of effects, however, must be framed in terms of specific endpoints and
associated measures useful for decision makers and stakeholders. For any
given 316(b) assessment, the choice of a tractable set of species, of endpoints and associated measures, of models and methods of analysis, and of
how to present and interpret results all involve value-laden judgments
similar to those made for human-health outcomes. Such choices are
unavoidable in risk assessments. These choices are the bridge connecting
scientific understanding with value-laden policy perspectives. Because of
the relative lack of experience in characterizing and valuing ecological
outcomes, 316(b) decisions cannot fall back on an accepted and narrowly
defined set of risk management protocols. Furthermore, the scientific
understanding of the ecological world is inherently complex, dynamic, and
uncertain.
52
Webb Van Winkle and John Kadvany
Informationcollection,
modeldevel opm ent,
and cal ibration
Information collection,
model development,
and calibration
Devel opi ng
deci sionmode ls
orcriteria
Developing
decision models
or criteria
Deci sionmaking
Decisionmaking
Screening, low info
requirements
More rigorous
science,
modest stakes
Harder science,
higher stakes
Basic to modest
data or modeling
Modest to significant
data or modeling
Extensive data and
modelingefforts
Simpler rules or
criteria, easier choices
Some challenging
measurement, uncertainty,
value, or stakeholder issues
Multiple measurement,
uncertainty, value,
stakeholder issues
Decision stakes and complexity
Figure 3.1. Resource management decisions involve three major activities that vary
as the decision stakes and complexity of the assessment increase.