(guest post by Juliette Franzman, recent UC Berkeley graduate) – read her paper in Ecosphere!

Macroecological models often rely on the assumption that the system under study is static or changing slowly enough to be considered static. However, most real systems, especially those under some kind of stress, change over time as they respond to disturbance. Although these static models may fail when applied to dynamic systems, the results can still offer interesting insight into the macroecological patterns of the systems.

The Maximum Entropy Theory of Ecology (METE) is an example of a macroecological model with static assumptions. Cross-site studies have shown that METE performs well in undisturbed sites while it often times fails for disturbed sites. However, there have not been any studies of METE theory performance on a single site that moves from an undisturbed to disturbed state under cumulative stress over time. In our paper we examine such a site.

As an undergraduate at UC Berkeley, I joined the Undergraduate Research Apprentice Program (URAP) for five semesters as an apprentice to Professor John Harte’s work on METE. I initially worked on solving numerical equations related to the dynamic extension of METE (DynaMETE), but later worked on studying an application of METE on a dataset collected by Professor Benjamin Blonder’s team.

This dataset covers six years of census data collected from an alpine plant community on Mount Baldy in western Colorado. This system exhibits signs of demographic decline in the form of increasing mortality and decreasing recruitment. Additionally, snowmelt data from the Rocky Mountain Biological Laboratory (RMBL) provide a quantitative measure of drought during the study period (2014-2019). Together, these points provide evidence that the system is under environmental stress.

Our results showed that the macroecological patterns of the system deviate over time from the METE predictions. The observed and METE predicted species-area relationship (SAR) increasingly disagree over time and the observed and METE predicted species-abundance distribution (SAD) show agreement in the first year with consistent disagreement in the following years.

We additionally examined the correlation between METE theory performance over time with the following measures of stress: number of individuals, species richness, recruitment, mortality, and net loss. We were able to find meaningful correlation between the stress factors and the SAR error but not so much for the SAD error. Recruitment, number of individuals, and species richness negatively correlated with the SAR error as expected because these values tend to be lower in stressed and disturbed systems. Mortality and net loss positively correlated with the SAR error again as expected because these values tend to be higher in stressed and disturbed systems. We found that the SAR error had the strongest correlation (r = .97) with the net loss.

Our results showed that snapshot measurements of macroecological patterns can provide insight into the dynamic state of a system. This can help extend static theory to dynamic domains and identify macroecological patterns caused by different stressors. Under disturbance state variables such as the number of individuals and species richness can no longer reasonably be assumed to be static, and thus combining METE with mechanistic time-dependent state variables may more realistically capture shifting macroecological patterns. There are also variations in the way that METE fails for disturbed systems, so cataloguing the macroecological patterns caused by different stressors may help better predict ecosystem response under increasing natural and anthropogenic disturbances.