Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration.

Many forest species are adapted to long-interval, high-severity fires, but the intervals between severe fires are decreasing with changes in climate, land use, and biological invasions. Although the effects of changing fire regimes on some important recovery processes have previously been considered, the consequences for the dispersal of propagules (plant seeds and fungal spores) in forest communities have not. We characterize three mechanisms by which changing fire regimes disrupt propagule dispersal in mesic temperate, boreal, and high-elevation forests: reduced abundance and altered spatial distributions of propagule source populations, less effective dispersal of propagules by wind, and altered behavior of animal dispersers and propagule predators. We consider how disruptions to propagule dispersal may interact with other factors that are also influenced by fire regime change, potentially increasing risk of forest conversion. Finally, we highlight urgent research topics regarding how dispersal limitation may shape twenty-first century forest recovery after stand-replacing fire.

Subalpine forests that historically burned every 100–300 yr are expected to burn more frequently as climate warms, perhaps before trees reach reproductive maturity or produce a serotinous seedbank. Tree regeneration after short‐interval (100 yr) P. contorta forest in Grand Teton National Park (Wyoming, USA). We asked how propagule pressure varied with time since last fire, how seed delivery into burned forest varied with age and structure of live forest edges, what variables explained seed delivery into burned forest, and how spatial patterns of delivery across the burned area could vary with alternate patterns of surrounding live forest age. Seeds were collected in traps along 100‐m transects (n = 18) extending from live forest edges of varying age (18, 30, and >100 yr) into areas of recent (2‐yr) high‐severity fire, and along transects in live forests to measure propagule pressure. Propagule pressure was low in 18‐yr‐old stands (~8 seeds/m²) and similarly greater in 30‐ and 100‐yr‐old stands (~32 seeds/m²). Mean dispersal distance was lowest from 18‐yr‐old edges and greatest from >100‐yr‐old edges. Seed delivery into burned forest declined with increasing distance and increased with height of trees at live forest edges, and was consistently higher for P. contorta than for other conifers. Empirical dispersal kernels revealed that seed delivery from 18‐yr‐old edges was very low (≤2.4 seeds/m²) and concentrated within 10 m of the live edge, whereas seed delivery from >100‐yr‐old edges was >4.9 seeds/m² out to 80 m. When extrapolated throughout the burned landscape, estimated seed delivery was low (70% of areas that burned in short‐interval fire (<30 yr). As fire frequency increases, immaturity risk will be compounded in short‐interval fires because seed dispersal from surrounding young trees is limited.

The ability to estimate and model future vegetation dynamics is a central focus of contemporary ecology and is essential for understanding future ecological trajectories. It is therefore critical to understand when the influence of initial post‐disturbance regeneration versus stochastic processes dominates long‐term post‐disturbance ecological processes. Often, conclusions about post‐disturbance dynamics are based upon initial regeneration in the years immediately after disturbances. However, the degree to which initial post‐disturbance regeneration indicates longer‐term trends is likely to be contingent on the types, intensities, and combinations of disturbances, as well as pre‐disturbance ecosystem structure and composition. Our relatively limited understanding of why initial post‐disturbance regeneration is sometimes a poor predictor of future ecosystem trajectories represents a critical gap in post‐disturbance ecological forecasting. We studied the composition and density of regeneration of tree species following wind blowdown in 1997, wildfire in 2002, and compounded disturbances by blowdown and wildfire in subalpine forests of Colorado. We examined regeneration of Picea engelmannii, Abies lasiocarpa, Pinus contorta, and Populus tremuloides in 180 permanent plots across 12 sites (classified by pre‐disturbance age and composition) in 2003, 2010, and 2015. At sites that were blown down but not burned, regeneration was dense and dominated by Picea and Abies. At these sites, regeneration observed from 2003 to 2005 (hereafter initial regeneration) was also highly predictive of regeneration 5–10 yr later. In contrast, at sites that were burned and sites that were blown down and burned, regeneration was less dense and dominated by a mix of species. At these sites, initial regeneration was a poor predictor of longer‐term trends as species dominance and overall density fluctuated over the 13‐yr period. These findings call into question our ability to confidently predict ecosystem trajectories based upon observations made in the years immediately after large, severe disturbances such as wildfires and compounded disturbances. As compounded disturbances become more common under climatically driven changes in disturbance regimes, post‐disturbance ecosystem trajectories may become increasingly stochastic and unpredictable.

Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a crucial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data and Random Forest (RF) models, to develop 30-m maps of the presence (i.e., any occurrence) and severity (i.e., cumulative percent basal area mortality) of beetle-caused tree mortality 1997–2019 in subalpine forests throughout the Southern Rocky Mountains, USA. Using resultant maps, we also quantified spatial patterns of cumulative tree mortality throughout the region, an important yet poorly understood concept in beetle-affected forests. RF models using LTS products to predict presence and severity performed well, with 80.3% correctly classified (Kappa = 0.61) and R² = 0.68 (RMSE = 17.3), respectively. We found that ≥10,256 km² of subalpine forest area (39.5% of the study area) was affected by bark beetles and 19.3% of the study area experienced ≥70% tree mortality over the twenty-three year period. Variograms indicated that severity was autocorrelated at scales < 250 km. Interestingly, cumulative patch-size distributions showed that areas with a near-total loss of the overstory canopy (i.e., ≥90% mortality) were relatively small (<0.24 km²) and isolated throughout the study area. Our findings help to inform an understanding of the variable effects of bark beetle outbreaks across complex forested regions and provide insight into patterns of disturbance legacies, landscape connectivity, and susceptibility to future disturbance.

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.