Overabundant deer and invasive plants drive widespread regeneration debt in eastern United States national parks.

Advanced regeneration, in the form of tree seedlings and saplings, is critical for ensuring the long-term viability and resilience of forest ecosystems in the eastern United States. Lack of regeneration and/or compositional mismatch between regeneration and canopy layers, called regeneration debt, can lead to shifts in forest composition, structure, and, in extreme cases, forest loss. In this study, we examined status and trends in regeneration across 39 national parks from Virginia to Maine, spanning 12 years to apply the regeneration debt concept. We further refined the concept by adding new metrics and classifying results into easily interpreted categories adapted from the literature: imminent failure, probable failure, insecure, and secure. We then used model selection to determine the potential drivers most influencing patterns of regeneration debt. Status and trends indicated widespread regeneration debt in eastern national parks, with 27 of 39 parks classified as imminent or probable failure. Deer browse impact was consistently the strongest predictor of regeneration abundance. The most pervasive component of regeneration debt observed across parks was a sapling bottleneck, characterized by critically low sapling density of native canopy species and significant declines in native canopy sapling basal area or density for most parks. Regeneration mismatches also threaten forest resilience in many parks, where native canopy seedlings and saplings were outnumbered by native subcanopy species, particularly species that are less palatable deer browse. The devastating impact of emerald ash borer eliminating ash as a native canopy tree also drove regeneration mismatches in many parks that contain abundant ash regeneration, demonstrating the vulnerability of forests that lack diverse understories to invasive pests and pathogens. These findings underscore the critical importance of an integrated forest management approach that promotes an abundant and diverse regeneration layer. In most cases, this can only be achieved through long-term (i.e., multidecadal) management of white-tailed deer and invasive plants. Small-scale disturbances that increase structural complexity may also promote regeneration where stress from deer and invasive plants is minimal. Without immediate and sustained management intervention, the forest loss we are already observing may become a widespread pattern in eastern national parks and the broader region.

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators.

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service's Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year(-1) for all indicators and is appropriate for detecting a 1 % trend·year(-1) in most indicators.