|Aim The relationship between species number and area is of fundamental impor-
tance in macroecology and conservation science, yet the implications of different
means of quantitative depiction of the relationship remain contentious. We set out
(1) to establish the variation in form of the relationship between two distinct
methods applied to the same habitat island datasets, (2) to explore the relevance of
several key dataset properties for variation in the parameters of these relationships,
and (3) to assess the implications for application of the resulting models.
Methods Through literature search we compiled 97 habitat island datasets. For
each we analysed the form of the island species–area relationship (ISAR) and
several versions of species accumulation curve (SAC), giving priority to a
randomized form (Ran-SAC). Having established the validity of the power model,
we compared the slopes (z-values) between the ISAR and the SAC for each dataset.
We used boosted regression tree and simulation analyses to investigate the effect of
nestedness and other variables in driving observed differences in z-values between
ISARs and SACs.
Results The Ran-SAC was steeper than the ISAR in 77% of datasets. The differ-
ences were primarily driven by the degree of nestedness, although other v ariables
(e.g. the number of islands in a dataset) were also important. The ISAR was often
a poor predictor of archipelago species richness.
Main conclusions Slopes of the ISAR and SAC for the same data set can vary
substantially, revealing their non-equivalence, with implications for applications of
species–area curve parameters in conservation science. For example, the ISAR was
a poor predictor of archipelagic r ichness in datasets with a low degree of
nestedness. Caution should be employed when using the ISAR for the purposes of
extrapolation and prediction in habitat island systems.|