S. Sfenthourakis et al., Testing for nestedness in the terrestrial isopods and snails of Kyklades islands (Aegean archipelago, Greece), ECOGRAPHY, 22(4), 1999, pp. 384-395
Most insular communities exhibit nestedness, with the species assemblages o
f the more depauperate islands constituting subsets of those of the richer.
Several methods for the estimation and evaluation of nestedness have been
developed during the last fifteen years. In this paper we use two of the mo
re recent and elaborate methods, namely the "temperature" method of Atmar a
nd Patterson and the "departures" method of Lomolino. in order to investiga
te patterns of nestedness in the distribution of two well studied and speci
ose animal groups, terrestrial isopods and land snails, in the Kyklades arc
hipelago (Aegean Sea, Greece) that lies between two continental legions. Si
gnificant nestedness is present in both species assemblages and, surprising
ly, each method gives almost identical levels of nestedness for the two ani
mal groups. Isolation has been found to be more important in producing nest
edness in both groups than area, which does not seem to be an important exp
lanatory factor. However, the role of isolation in this case is better unde
rstood under an historical perspective, taking into account the complex pal
aeogeography of the region and the differential departmentalisation of dist
inct island groups. Additionally, certain metrics of habitat diversity that
were included in the analysis were the best explanatory factors of nestedn
ess, indicating a more complex causal pattern that also involves extinction
. Since the two methods used are based on different assumptions and have di
fferent scopes, their results do not converge. The "temperature" method fin
ds the maximum possible nestedness in an island sorting which does not nece
ssarily lead to plausible biogeographical explanations, while the "departur
es" method, although more useful in detecting causality, fails to fully eva
luate levels of nestedness. Nevertheless, both methods are valuable tools i
n the exploration of interesting distributional patterns, when this effort
is accompanied by a good understanding of historical. ecological and idiosy
ncratic properties of each particular data set.