Ribonet al. 2003; Grelle et al. 2005), although many
species are Red-listed as vulnerable, endangered or
critically endangered based on range, or population
estimates (Ribon et al. 2003). Brooks and Balmford
(1996) compare losses of birds projected using a
species–area model with those listed by the IUCN
as ‘threatened’ and find congruence, i.e. they argue
that the predictions are basically correct, but that
there is a substantial lag between the habitat
loss/fragmentation process and global extinction
of the species. There is, moreover, evidence of
local extirpation within the existing range for
bird species. Thus, within the Viçosa region
(a 120 km^2 area in southeastern Brazil) over the
last 70 years, it appears that at least 28 bird species
have become locally extinct, with 43 ‘critically
endangered’, and 25 ‘vulnerable’: in total 61% of
the original avifauna has been significantly reduced
in incidence (Ribon et al. 2003). Nectarivorous
species were least at risk, next came omnivores and
carnivores, with frugivores and insectivores in
greatest jeopardy.
Assuming relaxation to be underway in these
fragmented systems, the next problem is to esti-
mate the lag time between fragmentation and even-
tual species losses. Brooks et al. (1999) attempt this
for tropical forest birds in an area of fragmented
upland forest in Kenya. They base their analyses on
island theory, assuming zvalues (slope of the SAR)
pre-isolation of 0.15, and post-isolation of 0.25 (i.e.
for the new ISAR), and that the rate of decline in
species is approximately exponential. This postu-
lates that fragments will lose approximately half
the species that will eventually be lost every x
years: this they termed the ‘half-life’. The difficulty
is finding systems with ‘before’ and ‘after’ data.
The system they chose for the test is the Kakamega
forest, where forest fragmentation occurred over
60 years ago (but where the time frame is not per-
fectly specified). Their analyses of five fragments
suggests a half-life varying in relation to fragment
area from 23 (100 ha) to 80 (8600 ha) years, and of
approximately 50 years for a 1000 ha fragment. As
might be anticipated from island theory, relaxation
times were suggested to be scale dependent in rela-
tion to both range in area (‘grain size’) and degree
of isolation (cf. Box 10.2).
One important caveat to this study is, however,
that the historical data for the Kakamega area were
derived from general collecting/observations from
the Kakamega area, with values assigned to the
fragments on the basis of the assumption of
z0.15 (slope of SAR) for their pre-isolation states.
Hence, the figures derived for relaxation times
should be seen as still of the nature of first approx-
imations. Moreover, the relaxation times per frag-
ment do not tell us overall species losses from the
system. In practice, the data reviewed by Brooks et al.
(1999) suggest that some loses have occurred, with
10 of an estimated 73 Kakamega species not having
been recorded from these forests in recent years. Of
those species counted as lost at least one is thought
to have been trapped to extinction for the caged-bird
trade; three others were at their eastern range limits
within the study area, so their loss from this area
might be related to other processes and may not
be indicative of their risk of global extinction. In
practice, a single study system, of five fragments,
based on relatively poorly specified empirical data,
is a rather limited basis for building predictive mod-
els, and there are surprisingly few other such studies
with which to compare the values obtained.
Box 10.2 appraises the use of species–area models
in predicting regional species extinctions as a func-
tion of regional habitat loss, arguing that although
there is a crude relationship between habitat loss
and species loss, there is no logical connection
between such models and island theory. It should
also be recognized that even where species–area
analyses are linked phenomenologically to island
theory (i.e. they are being applied to systems of
fragments using parameters derived from other
such systems, which also vary over similar ranges
of area and isolation), they provide only a coarse,
stochastic simulation of the impacts of fragmenta-
tion. The actual drivers of extinction may be
structured, and in some instances avoidable by
appropriate management. For instance, hunting
and collection of birds and mammals may each be
important drivers of the decline of particular
species (Peres 2001; Ribon et al. 2003). With respect
to the Atlantic forest system, conservation action
has likely already been and will continue to be
crucial to staving off the final extinction of highlyRELAXATION AND TURNOVER—THE EVIDENCE 271