Environmental Engineering Reference
In-Depth Information
150
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0
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Age
Fig. 2.15
Addax are critically endangered by hunting, so there is no
suggestion that management options could aim for sustainable use in the
near future, but information on growth can still be helpful in order to assess
the condition of managed populations. The graph fits a von Bertalanffy
growth curve to age and weight data for addax, comparing a semi-captive
population in Bou-Hedma National Park, Tunisia (filled points), with addax
from St Louis Zoo (open points). The Tunisian population is part of a
programme to reintroduce addax to the northern part of their historic range.
Source:
St. Louis Zoo, CMS/FFEM and Tunisian Direction Général des Fôrets
unpublished data. Photo © Tim Wacher.
not a strict function of time as it is in age-structured models, and we therefore need
to estimate these transition probabilities.
The simplest analytical approach is to use
known fates
, tagging a sample of
individuals and monitoring them over time to observe directly the proportions of
each class that change state in each time unit. While this works well for plants and
other sessile species (e.g. Van der Voort and McGraw 2006), for most animals, less
than certain re-observation from year to year will necessitate a mark-recapture
approach. In this case, an extension of open population survival analysis known as
multi-strata modelling
can be used (Nichols
et al
. 1992; Williams
et al
. 2002). This
can provide estimates of the rates at which individuals move from one state to
another (the probability of growth from one size class to the next in this case), while
controlling for survival and detection rates. The approach requires the size class of
each individual to be recorded on capture or re-observation, but otherwise the same
assumptions and considerations apply as those discussed in Section 2.4.2.2. A final
possibility when size and age are closely correlated is to derive transition rates from
a
growth curve and rates of survival
(Box 2.17), although this is a data-hungry
approach, requiring both age-specific survival rates and estimates of age-specific size
in order to plot the growth curve.
