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Abstract. The flow of carbon through terrestrial ecosystems and the response toclimate are critical but highly uncertain processes in the global carboncycle. However, with a rapidly expanding array of in situ and satellitedata, there is an opportunity to improve our mechanistic understanding ofthe carbon (C) cycle's response to land use and climate change. Uncertaintyin temperature limitation on productivity poses a significant challenge topredicting the response of ecosystem carbon fluxes to a changing climate.Here we diagnose and quantitatively resolve environmental limitations onthe growing-season onset of gross primary production (GPP) using nearly 2 decades of meteorological and C flux data (2000–2018) at a subalpineevergreen forest in Colorado, USA. We implement the CARbonDAta-MOdel fraMework (CARDAMOM) model–datafusion network to resolve the temperature sensitivity of spring GPP. Tocapture a GPP temperature limitation – a critical component of the integratedsensitivity of GPP to temperature – we introduced a cold-temperature scalingfunction in CARDAMOM to regulate photosynthetic productivity. We found thatGPP was gradually inhibited at temperatures below 6.0 ∘C (±2.6 ∘C) and completely inhibited below −7.1 ∘C(±1.1 ∘C). The addition of this scaling factor improvedthe model's ability to replicate spring GPP at interannual and decadal timescales (r=0.88), relative to the nominal CARDAMOM configuration (r=0.47), and improved spring GPP model predictability outside of the dataassimilation training period (r=0.88). While cold-temperaturelimitation has an important influence on spring GPP, it does not have asignificant impact on integrated growing-season GPP, revealing that otherenvironmental controls, such as precipitation, play a more important role inannual productivity. This study highlights growing-season onset temperatureas a key limiting factor for spring growth in winter-dormant evergreenforests, which is critical in understanding future responses to climatechange.
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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.
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- Award ID(s):
- 1926090
- PAR ID:
- 10480572
- Publisher / Repository:
- Global Change Biology
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 29
- Issue:
- 19
- ISSN:
- 1354-1013
- Page Range / eLocation ID:
- 5652 to 5665
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/gcb.16867
