DOI: 10.5061/dryad.s1rn8pk85
title: Autogenic regulation and resilience in tropical dry forest

description: 1. Engineering resilience, a forest’s ability to maintain its properties
 in the event of disturbance, comprises two components: resistance and
 recovery. In human-dominated landscapes, forest resilience depends mostly
 on recovery. Forest recovery largely depends on autogenic regulation,
 which entails a negative feedback loop between rates of change of forest
 state variables and state variables themselves. Hence community dynamics
 changes in response to deviations from forest equilibrium state. Based on
 the premise that autogenic regulation is a key aspect of the recovery
 process, here we tested the hypothesis that combined old-growth forest
 (OGF) and secondary forest (SF) dynamics should show autogenic regulation
 in state variables, and thus convergence towards OGF-based reference
 points, indicating forest resilience. 2. We integrated dynamic data for
 OGF (11-year monitoring) and SF (16-year monitoring) to analyse three key
 state variables (basal area, tree density, species richness), their annual
 rates of change, and their underlying demographic processes (recruitment,
 growth, mortality). We examined autogenic regulation through generalized
 linear mixed-effects models (GLMMs) to quantify functional relationships
 between rates of change of state variables (and underlying demographic
 processes), and their respective state variables. 3. State variables in
 OGF decreased moderately over time, against our prediction of OGF
 constancy. In turn, the three state variables analysed showed negative
 relationships with their respective rates of change, which allows the
 return of SF to OGF values after disturbance. In all cases, recruitment
 decreased with increasing values in state variables, while mortality
 increased. 4. The observed negative relationships between state variables,
 their rates of change and their underlying demographic processes support
 our hypothesis of integrated OGF and SF dynamics showing autogenic
 regulation for state variables. Competition seems to be a major driver of
 autogenic regulation given its dependence on a resource availability that
 declines as forest structure develops. 5. Synthesis. Based on a
 straightforward and comprehensive approach to quantify the extent to which
 tropical forest dynamics is self-regulated, this study highlights the role
 of autogenic regulation in tropical dry forest as a basic component of its
 resilience. This approach is potentially valuable for a generalised
 assessment of engineering resilience of forests worldwide.
description: Data comes from 28 tropical dry forest plots of secondary forest
 (SF) and old-growth forest (OGF). SF plots were established in 2003 and
 OGF plots were established in 2008. Within these plots, woody stems
 meeting inclusion criteria (see Supplementary Material Figure S1) were
 tagged and identified to species. Diameter at breast height and survival
 were recorded annually for all tagged individuals. Plant
 diameter, survival and taxonomical identity were used to estimate basal
 area, tree density and species richness (state variables of the study) at
 plot level for all plots on a yearly basis. We used
 survival information to describe the ongoing demographic process
 (recruitment, growth, mortality) per individual and annual period.
 Further, for each individual and period, we computed the difference in
 state variable values. Then, we estimated the contribution of each
 demographic process towards each of the three state variables by grouping
 individuals going through the same demographic process in each year, and
 then adding their changes in state variable values.
 This database contains information on state variable values,
 annual changes, and contributions per demographic process on a plot-year
 resolution.
description: For some plot-year datapoints, tree density's sum of
 recruitment and mortality do not add up to the net change of the state
 variable. This is because we used a stratified sampling: trees shifting
 from a size category to another change their scaling factor, although they
 do not undergo recruitment or mortality. Therefore, their tree density
 value might differ from one year to the next one. These differences are
 negligible and were not accounted for in the analysis.