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J A M E S P. G I B B S
equal 10, with count variances comparable to the average value calculated for
each group based on the literature survey (table 7.2). Trends in the population
index were assumed to be linear, α and β were set at 0.05, and tests of significance were two-sided. Within this framework, sampling requirements to
detect overall changes in population indices of 10 percent, 25 percent, and 50
percent for each group were estimated.
This analysis (table 7.3) indicated that infrequent monitoring (for example, once or twice per year) on a small number of sites or plots (10 or less)
would reliably detect strong population trends (that is, a 50 percent change
over 10 years) in most groups. Even for highly variable groups frequent monitoring (three to five times per year) of a small number of plots (30 or less)
would permit detection of a trend of this magnitude. However, more intensive
monitoring is needed to detect weaker trends of 25 percent and 10 percent,
but nevertheless is still at a logistically feasible level (100 or fewer plots) for animal ecologists to undertake for most groups. The sampling requirements
become more modest if significance levels are relaxed. For example, setting α
= β = 0.10 reduced the sampling requirements in table 7.3 by, on average, 20
percent The main utility of these results (table 7.3) is to provide a reference for
animal ecologists to consult when planning monitoring activities or assessing
the effectiveness of existing programs. Note that stringent α and β levels (0.05)
were used to generate these results. Less stringent levels may well be more
appropriate in a monitoring context (Gibbs et al. 1998). Sampling recommendations using other combinations of α and β are provided over the Internet at http://www.im.nbs.gov/powcase/powcase.html.
A caveat is that these recommendations are based on the assumption that
trends in populations are fixed and linear. This is appropriate in certain situations, such as declining endangered species or increasing introduced species,
whose populations often follow deterministic trends. However, most populations monitored follow an irregular trajectory. Furthermore, trends in a particular local population probably represent a random sample of a spatially variable, regional population trend. The simulation software described (table 7.1)
can accommodate random trend variation among plots or sites if estimates of
its magnitude are available.
SETTING OBJECTIVES FOR A MONITORING PROGRAM
It is important to emphasize that conclusions drawn from these analyses are
contingent on the initial statement of a monitoring program’s objectives.
Power estimates are influenced by many factors controlled by researchers, such
J A M E S P. G I B B S
equal 10, with count variances comparable to the average value calculated for
each group based on the literature survey (table 7.2). Trends in the population
index were assumed to be linear, α and β were set at 0.05, and tests of significance were two-sided. Within this framework, sampling requirements to
detect overall changes in population indices of 10 percent, 25 percent, and 50
percent for each group were estimated.
This analysis (table 7.3) indicated that infrequent monitoring (for example, once or twice per year) on a small number of sites or plots (10 or less)
would reliably detect strong population trends (that is, a 50 percent change
over 10 years) in most groups. Even for highly variable groups frequent monitoring (three to five times per year) of a small number of plots (30 or less)
would permit detection of a trend of this magnitude. However, more intensive
monitoring is needed to detect weaker trends of 25 percent and 10 percent,
but nevertheless is still at a logistically feasible level (100 or fewer plots) for animal ecologists to undertake for most groups. The sampling requirements
become more modest if significance levels are relaxed. For example, setting α
= β = 0.10 reduced the sampling requirements in table 7.3 by, on average, 20
percent The main utility of these results (table 7.3) is to provide a reference for
animal ecologists to consult when planning monitoring activities or assessing
the effectiveness of existing programs. Note that stringent α and β levels (0.05)
were used to generate these results. Less stringent levels may well be more
appropriate in a monitoring context (Gibbs et al. 1998). Sampling recommendations using other combinations of α and β are provided over the Internet at http://www.im.nbs.gov/powcase/powcase.html.
A caveat is that these recommendations are based on the assumption that
trends in populations are fixed and linear. This is appropriate in certain situations, such as declining endangered species or increasing introduced species,
whose populations often follow deterministic trends. However, most populations monitored follow an irregular trajectory. Furthermore, trends in a particular local population probably represent a random sample of a spatially variable, regional population trend. The simulation software described (table 7.1)
can accommodate random trend variation among plots or sites if estimates of
its magnitude are available.
SETTING OBJECTIVES FOR A MONITORING PROGRAM
It is important to emphasize that conclusions drawn from these analyses are
contingent on the initial statement of a monitoring program’s objectives.
Power estimates are influenced by many factors controlled by researchers, such