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Abstract Forested landscapes have the potential to help offset global carbon emissions. However, current global models do not, nor are they intended to, capture the fine‐scale variability of the distributions of carbon in aboveground or belowground stocks or their simultaneous variability. Regional investigations are necessary to resolve patterns in carbon that can guide policy and planning, but regional maps that quantify multiple carbon pools are scarce. We quantified the spatial relationships of aboveground and belowground carbon stocks to understand their simultaneous variability across the forested area of the perhumid ecoregion of the Pacific Coastal Temperate Rainforest. Further, we identified topo‐climatic contexts associated with unique patterns in both aboveground and belowground carbon stocks by conducting an overlay analysis across the entire ecoregion. We utilized previously published estimates of carbon stocks based on extensive governmental data and machine learning techniques to model simultaneous spatial relationships of aboveground and belowground carbon stocks and generate a map for a high carbon region. We employed Pearson's correlations as well as ANOVA and Tukey honestly significant difference (HSD) tests for comparisons of topography and climate. Approximately 25% (2.6 million ha) of the area across the perhumid ecoregion had similar trends in aboveground and belowground stocks (convergence). Likewise, 20% of the ecoregion had opposite trends of aboveground and belowground stocks (divergence), and 56% of the ecoregion experienced no relationship (moderate conditions) between aboveground and belowground stocks. Convergence areas consist of carbon hotspots associated with 1.3 million ha and 794 Mg C ha⁻¹on average, or carbon cold spots associated with 1.2 million ha and 224 Mg C ha⁻¹. Areas with convergence, divergence, and moderate carbon stocks all had unique associations with slope, elevation, aspect, mean annual precipitation, and annual mean temperature. High levels of aboveground carbon were associated with steeper slopes, while high levels of belowground carbon were associated with high levels of precipitation. The interactions between slope, precipitation, and temperature correspond with carbon convergence and divergence, likely due to water accumulation which impacts the decomposition of organic matter in soil. These data are critical to regional planning and carbon policy and inform expectations for future carbon storage as the climate changes. 

Abstract Given that terrestrial ecosystems globally are facing the loss of biodiversity from land use conversion, invasive species, and climate change, effective management requires a better understanding of the drivers and correlates of biodiversity. Increasingly, biodiversity is co‐managed with aboveground carbon storage because high biodiversity in animal species is observed to correlate with high aboveground carbon storage. Most previous investigations into the relationship of biodiversity and carbon co‐management do not focus on the biodiversity of the species rich plant kingdom, which may have tradeoffs with carbon storage. To examine the relationships of plant species richness with aboveground tree biomass carbon storage, we used a series of generalized linear models with understory plant species richness and diversity data from the USDA Forest Service Forest Inventory and Analysis dataset and high‐resolution modeled carbon maps for the Tongass National Forest. Functional trait data from the TRY database was used to understand the potential mechanisms that drive the response of understory plants. Understory species richness and community weighted mean leaf dry matter content decreased along an increasing gradient of tree biomass carbon storage, but understory diversity, community weighted mean specific leaf area, and plant height at maturity did not. Leaf dry matter content had little variance at the community level. The decline of understory plant species richness but not diversity to increases in aboveground biomass carbon storage suggests that rare species are excluded in aboveground biomass carbon dense areas. These decreases in understory species richness reflect a tradeoff between the understory plant community and aboveground carbon storage. The mechanisms that are associated with observed plant communities along a gradient of biomass carbon storage in this forest suggest that slower‐growing plant strategies are less effective in the presence of high biomass carbon dense trees in the overstory. 

Spatially explicit global estimates of forest carbon storage are typically coarsely scaled. While useful, these estimates do not account for the variability and distribution of carbon at management scales. We asked how climate, topography, and disturbance regimes interact across and within geopolitical boundaries to influence tree biomass carbon, using the perhumid region of the Pacific Coastal Temperate Rainforest, an infrequently disturbed carbon dense landscape, as a test case. We leveraged permanent sample plots in southeast Alaska and coastal British Columbia and used multiple quantile regression forests and generalized linear models to estimate tree biomass carbon stocks and the effects of topography, climate, and disturbance regimes. We estimate tree biomass carbon stocks are either 211 (SD = 163) Mg C ha⁻¹or 218 (SD = 169) Mg C ha⁻¹. Natural disturbance regimes had no correlation with tree biomass but logging decreased tree biomass carbon and the effect diminished with increasing time since logging. Despite accounting for 0.3% of global forest area, this forest stores between 0.63% and 1.07% of global aboveground forest carbon as aboveground live tree biomass. The disparate impact of logging and natural disturbance regimes on tree biomass carbon suggests a mismatch between current forest management and disturbance history. 

1. Amplified by warming temperatures and drought, recent outbreaks of native bark beetles (Curculionidae: Scolytinae) have caused extensive tree mortality throughout Europe and North America. Despite their ubiquitous nature and important effects on ecosystems, forest recovery following such disturbances is poorly understood, particularly across regions with varying abiotic conditions and outbreak effects. 2. To better understand post-outbreak recovery across a topographically complex region, we synthesized data from 16 field studies spanning subalpine forests in the Southern Rocky Mountains, USA. From 1997 to 2019, these forests were heavily affected by outbreaks of three native bark beetle species (Dendroctonus ponderosae, Dendroctonus rufipennis and Dryocoetes confusus). We compared pre- and post-outbreak forest conditions and developed region-wide predictive maps of post-outbreak (1) live basal areas, (2) juvenile densities and (3) height growth rates for the most abundant tree species – aspen (Populus tremuloides), Engelmann spruce (Picea engelmannii), lodgepole pine (Pinus contorta) and subalpine fir (Abies lasiocarpa). 3. Beetle-caused tree mortality reduced the average diameter of live trees by 28.4% (5.6 cm), and species dominance was altered on 27.8% of field plots with shifts away from pine and spruce. However, most plots (82.1%) were likely to recover towards pre-outbreak tree densities without additional regeneration. Region-wide maps indicated that fir and aspen, non-host species for bark beetle species with the most severe effects (i.e. Dendroctonus spp.), will benefit from outbreaks through increased compositional dominance. After accounting for individual size, height growth for all conifer species was more rapid in sites with low winter precipitation, high winter temperatures and severe outbreaks. 4. Synthesis. In subalpine forests of the US Rocky Mountains, recent bark beetle outbreaks have reduced tree size and altered species composition. While eventual recovery of the pre-outbreak forest structure is likely in most places, changes in species composition may persist for decades. Still, forest communities following bark beetle outbreaks are widely variable due to differences in pre-outbreak conditions, outbreak severity and abiotic gradients. This regional variability has critical implications for ecosystem services and susceptibility to future disturbances.