Disturbance macroecology: a comparative study of community structure metrics in a high‐severity disturbance regime

Abstract

2020.Disturbance macroecology: a comparative study of community structure metrics in a high-severity disturbance regime.Abstract. Macroecological studies have established widespread patterns of species diversity and abundance in ecosystems but have generally restricted their scope to relatively steady-state systems. As a result, how macroecological metrics are expected to scale in ecosystems that experience natural disturbance regimes is unknown. We examine macroecological patterns in a fire-dependent forest of Bishop pine (Pinus muricata). We target two different-aged stands in a stand-replacing fire regime: a mature stand with a diverse understory and with no history of major disturbance for at least 40 yr, and one disturbed by a stand-replacing fire 17 yr prior to measurement. We compare properties of these stands with macroecological predictions from the Maximum Entropy Theory of Ecology (METE), an information entropy-based theory that has proven highly successful in predicting macroecological metrics in multiple ecosystems and taxa. Ecological patterns in the mature stand more closely match METE predictions than do data from the more recently disturbed, mid-seral stage stand. This suggests METE's predictions are more robust in latesuccessional, slowly changing, or steady-state systems than those in rapid flux with respect to species composition, abundances, and organisms' sizes. Our findings highlight the need for a macroecological theory that incorporates natural disturbance, perturbations, and ecological dynamics into its predictive capabilities, because most natural systems are not in a steady state.

Shifting Macroecological Patterns and Static Theory Failure in a Stressed Alpine Plant Community

“…1, the general pattern of deviation from METE in this study is in the direction of even further deviation from power law behavior, with the slope decreasing more rapidly with scale than METE predicts. This is in contrast with results from another study (Newman et al 2020) that compared the SAR in two nearby Bishop pine forests: one that had recently burned and was undergoing post fire succession, and a mature forest that had not burned in many decades. The mature forest SAR was accurately predicted by Eq.…”

“…This contrasts with evidence from another study suggesting that disturbance results in a lognormal distribution (Kempton & Taylor 1974). It also contrasts with evidence from the Bishop pine study (Newman et al 2020), which shows a rank-log(abundance) curve that bows in the opposite direction (that is, a concave curve) from the SADs in Fig. 3.…”

“…Our analysis showed that the species-area relationship and the species-abundance distribution increasingly deviated from the predictions of METE over a period of six years from 2014 to 2019, in conformity with previous speculation (Newman et al 2020;Harte and Newman 2014;Harte 2011) that increasing theory failure over time will be observed in ecosystems undergoing change. Our results suggest that the goodness of fit of ecological models may contain useful information on the state of the system that can be applied to forecasting and generalizing ecological models to more dynamic systems.…”

“…There is accumulating evidence from multi-site comparisons that ecosystems undergoing change in response to either anthropogenic or natural disturbance regimes do exhibit macroecological patterns that differ from those observed in relatively undisturbed sites in similar types of ecosystems (Newman et al 2020;Rominger et al 2015;Supp et al 2012;Harte 2011;Carey et al 2006;Kempton & Taylor 1974). These studies also reveal a weakness of the Maximum Entropy Theory of Ecology (METE), which is based on an inference procedure derived from information theory (Harte 2011).…”

“…METE predicts patterns of distribution, abundance, and energetics using instantaneous values of a community's state variables: total area, total abundance, total species richness, and total system metabolism. Numerous examples exist of the success of METE for systems in which the state variables are relatively static, as well as its failures in disturbed ecosystems in which state variables are changing in response to disturbance (Newman et al 2020;Harte et al 2017;Xiao et al 2015;Harte et al 2013;White et al 2012;Harte et al 2009;Harte et al 2008).…”