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Competitive inhibition of temperate forest tree recruits by herbs is likely important on sites with high fertility owing to faster height growth and consequent pre‐emption of light. We explored the site conditions and stand structure under which herbaceous growth has an impact on tree regeneration.

Plot data from 610 forest sites were collected from five areas across the southern Appalachian Mountains.

Several plant guilds were distinguished based on various biological traits. Deterministic models of forest understorey were validated through recursive path analysis. The numerical analyses were performed both on all plots and on a subset of 150 plots free of evergreen shrubs.

In general, total herb cover increased with soil fertility, but in sites without evergreen shrubs no relationship emerged. Total herb cover varied inversely with woody stem density (saplings excluded), but the slope was much less steep in the absence of evergreen shrubs. Tree sapling density displayed a left‐tailed, asymmetric response with respect to total herb cover, but a symmetric unimodal response against tall herb cover. The shape of the distribution of tree stems by diameter class shifted from unimodal under a very sparse herbaceous layer to negative exponential in stands with mid to high herb cover. This was due to the suppressive impact of evergreen shrubs on understorey vegetation, which led to a positive covariance between total herb cover and tree sapling density. These two understorey variables became unrelated in the path model built on the subset without evergreen shrubs, but a similar model involving tall herbs revealed a direct negative effect of tall herb cover on tree sapling density.

Our results provide evidence of tree recruits exclusion by tall herbs on fertile sites but not on acidic sites, where herb interference is much reduced by the suppressive effect of evergreen shrubs and trees on herbaceous layer vegetation.

Natural regeneration is increasingly recognized as a potentially cost‐effective strategy to reach ambitious forest landscape restoration targets, but rates of recovery are notoriously variable. We asked how well initial habitat conditions after cessation of agriculture predict forest recovery after nearly a decade. We aimed to provide land managers with general rules of thumb to assess when it is necessary to invest resources in active restoration, such as tree planting, to accelerate forest recovery.

Coto Brus County, Puntarenas, Costa Rica.

We compiled data on initial vegetation structure, soil nutrients, prior land‐use history and surrounding forest cover at 13 sites. After 8.5 years, we measured vegetation indicators commonly used to assess forest recovery, namely amount of canopy closure and number and diversity of woody recruits.

Two variables, grass cover and canopy closure, measured 1.5 years after site abandonment, explained 47–87% of five of the six response variables after 8.5 years; recovery was faster in sites with lower grass cover and higher canopy closure initially. Waiting an additional year to measure initial vegetation variables did not improve model fit. Time since the original forest was cleared explained 62% of change in canopy cover, whereas percentage of surrounding forest cover, length of pasture use and soil variables explained minimal additional variation.

Our results suggest that two easily measurable vegetation variables can provide guidance to land managers and policy makers about where to invest scarce restoration resources to facilitate forest recovery.