Using an extensive dataset on Hawaiian arthropods, I am applying the maximum entropy theory of ecology (METE) to identify communities out of statistical steady state and test hypotheses about how evolutionary history constrains community structure. METE predicts species abundance and individual metabolic rates by maximizing statistical randomness while constraining the observed number of species, individuals and total metabolic rate of a community. METE is thus neutral conditional on incorporation of specific information and therefore, like other neutral theories, provides a powerful null model. Unlike other neutral theories, new information related to biological mechanism can be easily incorporated to test their importance.
The arthropod communities are arrayed across a chronosequence of substrate ages, ranging from 300 to 4 million years. Communities that deviate from METE are from the youngest and oldest sites. I hypothesize that young communities are constrained by ecological opportunity, both in the form of limited dispersal and limited ability of colonists to persist in potentially novel environments. As communities age, in situ adaptation and diversification along with continued immigration, may allow them to approach statistical steady state, and thus be better predicted by METE. Conversely, if in situ diversification, a process likely to be non-neutral, dominates community assembly, historical contingencies may drive communities away from METE predictions and into alternate ecological, but not statistical, stable states.