Forest productivity recovery or collapse? Model‐data integration insights on drought‐induced tipping points

Abstract

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate–plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model‐data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012–2015 California drought. Our study area is a mid‐montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011–2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012–2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping‐point collapse to recovery. We present novel process‐driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states—showing that the full extent of GPP response takes several years to arise. Thus, long‐term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.

Resolving the Carbon‐Climate Feedback Potential of Wetland CO2 and CH4 Fluxes in Alaska

“…This derivation assumes linear responses of carbon cycling to climate (Equations 14–16). While the linear sensitivities presented here provide a first‐order estimate of flux sensitivity to contemporary climate variability, larger and/or sustained climate perturbations can potentially induce non‐linear responses such as (a) non‐linear functional responses to climate, for example, heterotrophic temperature and moisture sensitivities or vegetation functional responses (Norton et al., 2023), (b) cumulative legacy effects, and their propagation across the terrestrial carbon cycle states (e.g., productivity increases and subsequently lagged growth of soil organic C states), and (c) long‐term processes unrepresented in the model‐data integration analysis, for example, shrub expansion, permafrost thaw or nutrient cycling, and/or (d) a shift of ecosystem states beyond a climate threshold or tipping point (Au et al., 2023; Luo et al., 2011). Characterizing the longer‐term sensitivities of cumulative CH 4 and CO 2 fluxes to sustained climate change is therefore a key step toward establishing whether (a) contemporary linear responses are the predominant contribution to CH 4 and CO 2 fluxes to climate sensitivity, or (ii) lagged and/or non‐linear process responses to climate change will amount to prominent climate sensitivity terms.…”

Declining coupling between vegetation and drought over the past three decades

“…The next challenge is to reveal specific plant water use strategies (Brodribb et al., 2020) and understand the deep soil water uptake process (Werner et al., 2021) as response time increases over time. It is also critical to apply other robust methods to quantify vegetation's sensitivity to droughts, such as regression slope methods (Rao et al., 2022) and tipping point theory (Au et al., 2023).…”

Drought sensitivity in mesic forests heightens their vulnerability to climate change

“…A tree’s age, genotype, functional traits, and mechanisms of acclimation ( 64 , 66 , 67 ) are all important determinants of growth responses to drought, which can decouple the relationship between RWI and mortality. Importantly, our predictions of vulnerability might understate the risk of mortality at dry-range edges if there are thresholds in the relationship between tree growth and mortality ( 68 ). For example, trees likely require a minimum amount of growth to survive ( 68 ); therefore, the same percentage growth decline could be more harmful for slow-growing trees located at their dry-range edge than for trees growing in mesic areas ( 10 ).…”

“…Importantly, our predictions of vulnerability might understate the risk of mortality at dry-range edges if there are thresholds in the relationship between tree growth and mortality ( 68 ). For example, trees likely require a minimum amount of growth to survive ( 68 ); therefore, the same percentage growth decline could be more harmful for slow-growing trees located at their dry-range edge than for trees growing in mesic areas ( 10 ). Future research that characterizes these nonlinear responses to drought could improve predictions of climate impacts ( 42 , 43 ).…”