Assessments of environmental impacts are being subject to greater scie
ntific and legal scrutiny than ever before. The application of traditi
onal statistical decision-making criteria to questions of environmenta
l impacts has become increasingly inadequate as society demands greate
r environmental accountability from economic development. In particula
r, impact assessment has inherited a preoccupation with Type I error r
ates that has pervaded ecological research, even though Type II errors
are often equally severe in impact assessment. Estimation of Type II
error rates and specification of critical effect sizes-or the magnitud
es of impacts considered important-are mutually dependent. Considerati
on of Type II errors, therefore, requires the exact specification of a
n hypothesized impact, which is often difficult. Insistence on low rat
es of Type I error (e.g., alpha = 0.05) typically means that equivalen
t rates of Type II error can be realized only when effect sizes (ES) a
re very large or when very many samples are taken. Rather than adherin
g to a fixed, arbitrary, critical, Type I error rate, I propose a proc
edure by which the critical ES is given primacy. Statistical decision
criteria are then selected according to the relative weighting of the
perceived consequences of Type I or Type II errors. The critical Type
I error rate is set by iteration to some multiple (k) of the estimated
potential for Type II error, and the null hypothesis is rejected if t
hat (variable) Type I probability is not exceeded. The value of k woul
d be determined by the ratio of the consequences (e.g., costs) of Type
II and Type I errors. The procedure focuses attention on the magnitud
es of impacts considered important, and provides for statistical decis
ions based on the a priori consideration of the development and enviro
nmental costs of Type I and Type II errors. It also provides incentive
for development proponents to support rigorous environmental monitori
ng.