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Landslides influence the global carbon (C) cycle by facilitating transfer of terrestrial C in biomass and soils to offshore depocenters and redistributing C within the landscape, affecting the terrestrial C reservoir itself. How landslides affect terrestrial C stocks is rarely quantified, so we derive a model that couples stochastic landslides with terrestrial C dynamics, calibrated to temperate rainforests in southeast Alaska, United States. Modeled landslides episodically transfer C from scars to deposits and destroy living biomass. After a landslide, total C stocks on the scar recover, while those on the deposit either increase (in the case of living biomass) or decrease while remaining higher than if no landslide had occurred (in the case of dead biomass and soil C). Specifically, modeling landslides in a 29.9 km2 watershed at the observed rate of 0.004 landslides km−2 yr−1 decreases average living biomass C density by 0.9 tC ha−1 (a relative amount of 0.4%), increases dead biomass C by 0.3 tC ha−1 (0.6%), and increases soil C by 3.4 tC ha−1 (0.8%) relative to a base case with no landslides. The net effect is a small increase in total terrestrial C stocks of 2.8 tC ha−1 (0.4%). The size of this boost increases with landslide frequency, reaching 6.5% at a frequency of 0.1 landslides km−2 yr−1. If similar dynamics occur in other landslide‐prone regions of the globe, landslides should be a net C sink and a natural buffer against increasing atmospheric CO2 levels, which are forecast to increase landslide‐triggering precipitation events. Plain Language Summary: Landslides are a natural process, often triggered by rainfall, that removes soil and forest cover from steep slopes and deposits them in valleys. Those soils and vegetation contain large amounts of carbon that has been removed from the atmosphere by photosynthesis. Landslides and carbon are therefore related, but it has not previously been determined whether the net effect of landslides is to release carbon back to or sequester additional carbon from the atmosphere. Our work, focused on temperate rainforests in southeast Alaska, indicates that landslides sequester additional carbon from the atmosphere by burying existing carbon in deposits and providing space for new carbon to accumulate on landslide scars. The amount of additional carbon sequestration increases as landslides occur more frequently. As climate change leads to more extreme rainfall events in forested parts of the world, such as southeast Alaska, more landslides are expected to occur. Therefore, increased landsliding may partially offset some of the elevated atmospheric carbon dioxide levels that drive landslide‐triggering extreme weather events in the first place, in a newly identified feedback loop. Key Points: Coupled landslide‐carbon model shows landslides boost C stocks by sequestering C in deposits and creating space for new C to accumulateSize of the boost increases with landslide frequency, from ∼1% at an areal frequency of ∼10−4 yr−1 to ∼6.5% by a frequency of 10−3 yr−1Landslides in temperate rainforests are likely a net C sink with respect to the atmosphere and a buffer against increasing atmospheric CO2 levels [ABSTRACT FROM AUTHOR]

Climate drivers are increasingly creating conditions conducive to higher frequency fires. In the coniferous boreal forest, the world's largest terrestrial biome, fires are historically common but relatively infrequent. Post-fire, regenerating forests are generally resistant to burning (strong fire self-regulation), favoring millennial coniferous resilience. However, short intervals between fires are associated with rapid, threshold-like losses of resilience and changes to broadleaf or shrub communities, impacting carbon content, habitat, and other ecosystem services. Fires burning the same location 2 + times comprise approximately 4% of all Alaskan boreal fire events since 1984, and the fraction of short-interval events (< 20 years between fires) is increasing with time. While there is strong resistance to burning for the first decade after a fire, from 10 to 20 years post-fire resistance appears to decline. Reburning is biased towards coniferous forests and in areas with seasonally variable precipitation, and that proportion appears to be increasing with time, suggesting continued forest shifts as changing climatic drivers overwhelm the resistance of early postfire landscapes to reburning. As area burned in large fire years of ~ 15 years ago begin to mature, there is potential for more widespread shifts, which should be evaluated closely to understand finer grained patterns within this regional trend. [ABSTRACT FROM AUTHOR]

Climate drivers are increasingly creating conditions conducive to higher frequency fires. In the coniferous boreal forest, the world's largest terrestrial biome, fires are historically common but relatively infrequent. Post-fire, regenerating forests are generally resistant to burning (strong fire self-regulation), favoring millennial coniferous resilience. However, short intervals between fires are associated with rapid, threshold-like losses of resilience and changes to broadleaf or shrub communities, impacting carbon content, habitat, and other ecosystem services. Fires burning the same location 2 + times comprise approximately 4% of all Alaskan boreal fire events since 1984, and the fraction of short-interval events (< 20 years between fires) is increasing with time. While there is strong resistance to burning for the first decade after a fire, from 10 to 20 years post-fire resistance appears to decline. Reburning is biased towards coniferous forests and in areas with seasonally variable precipitation, and that proportion appears to be increasing with time, suggesting continued forest shifts as changing climatic drivers overwhelm the resistance of early postfire landscapes to reburning. As area burned in large fire years of ~ 15 years ago begin to mature, there is potential for more widespread shifts, which should be evaluated closely to understand finer grained patterns within this regional trend. [ABSTRACT FROM AUTHOR]

The study of community succession is one of the oldest pursuits in ecology. Challenges remain in terms of evaluating the predictability of succession and the reliability of the chronosequence methods typically used to study community development. The research of William S. Cooper in Glacier Bay National Park is an early and well-known example of successional ecology that provides a long-term observational data set to test hypotheses derived from space-for-time substitutions. It also provides a unique opportunity to explore the importance of historical contingencies and as an example of a revitalized historical study system. We test the textbook successional trajectory in Glacier Bay and evaluate long-term plant community development via primary succession through extensive fieldwork, remote sensing, dendrochronological methods, and newly discovered data that fills in data gaps (1940s to late 1980s) in continuous measurement over 100+ years. To date, Cooper’s quadrats do not support the classic facilitation model of succession in which a sequence of species interacts to form predictable successional trajectories. Rather, stochastic early community assembly and subsequent inhibition have dominated; most species arrived shortly after deglaciation and have remained stable for 50+ years. Chronosequence studies assuming prior composition are thus questionable, as no predictable species sequence or timeline was observed. This underscores the significance of assumptions about early conditions in chronosequences and the need to defend such assumptions. Furthermore, this work brings a classic study system in ecology up to date via a plot size expansion, new baseline biogeochemical data, and spatial mapping for future researchers for its second century of observation. [ABSTRACT FROM AUTHOR]

Context: Predicting ecosystem resilience is a challenge, especially as climate change alters disturbance regimes and conditions for recovery. Recent research has highlighted the importance of spatially-explicit disturbance and resilience processes to long-term ecosystem dynamics. "Neoecological" approaches characterize resilience mechanisms at relatively fine spatio-temporal resolutions, but results are difficult to extrapolate across broad temporal scales or climatic ranges. Paleoecological methodologies can consider the effects of climates that differ from today. However, they are often limited to coarse-grained spatio-temporal resolutions.Methods: In this synthesis, we describe implicit and explicit examples of studies that incorporate both neo- and paleoecological approaches. We propose ways to build on the strengths of both approaches in an explicit and proactive fashion.Results: Linking the two approaches is a powerful way to surpass their respective limitations. Aligning spatial scales is critical: Paleoecological sampling design should incorporate knowledge of the spatial characteristics of the disturbance process, and neoecological studies benefit from a longer-term context to their conclusions. In some cases, modeling can incorporate non-spatial data from paleoecological records or emerging spatial paleo-data networks with mechanistic disturbance/recovery processes that operate at fine spatiotemporal scales.Conclusions: Linking these two complementary approaches is a powerful way to build a complete understanding of ecosystem disturbance and resilience. [ABSTRACT FROM AUTHOR]