Geoscience Reference
In-Depth Information
Lesson:
To do a valid PVA, you must have data to build a realistic popula-
tion model.
• The model ignores spatial variation, which increases population viability.
As suggested by Stacey and Taper (1992), immigration can occasionally rescue
a population from extinction.
Lesson:
If the population is widely distributed geographically, incorporate
spatial variation.
• The model uses estimates of temporal variation that are at best poor
guesses. This statement assumes that the modeler understood the difference
between process variation and sampling variation. Often, sampling variation is
assumed to substitute for process variation; as a result, the estimates of persis-
tence are too pessimistic. Sampling variation has nothing to do with popula-
tion persistence. Estimates of population parameters must not be treated as if
they are the true parameter value.
Lesson:
Obtain reliable estimates of temporal variation and don't confuse
sampling variation and temporal variation.
• The model uses demographic variation as a substitute for temporal varia-
tion in the process and ignores true temporal variation.
Lesson:
Incorporate both demographic and temporal variation into the
PVA.
• The model ignores life-long individual heterogeneity that increases popu-
lation viability and assumes that all individuals endure the same identical sur-
vival and reproduction parameters. Such a naive assumption results in popula-
tion viability being underestimated.
Lesson:
Individual heterogeneity must be incorporated into a PVA model if
you don't want to underestimate viability.
• The model assumes that current conditions are not changing; that is, the
stochastic processes included in the model are assumed constant for the indef-
inite future. Loss of habitat and other environmental changes that affect these
stochastic processes are ignored. Thus, as discussed by Caswell (1989), the
model probably is not useful in forecasting (i.e., predicting what will happen)
but is useful in projecting (i.e., predicting what will happen if conditions do
not change).
