Moisture-driven divergence in mineral-associated soil carbon persistence.

Mineral stabilization of soil organic matter is an important regulator of the global carbon (C) cycle. However, the vulnerability of mineral-stabilized organic matter (OM) to climate change is currently unknown. We examined soil profiles from 34 sites across the conterminous USA to investigate how the abundance and persistence of mineral-associated organic C varied with climate at the continental scale. Using a novel combination of radiocarbon and molecular composition measurements, we show that the relationship between the abundance and persistence of mineral-associated organic matter (MAOM) appears to be driven by moisture availability. In wetter climates where precipitation exceeds evapotranspiration, excess moisture leads to deeper and more prolonged periods of wetness, creating conditions which favor greater root abundance and also allow for greater diffusion and interaction of inputs with MAOM. In these humid soils, mineral-associated soil organic C concentration and persistence are strongly linked, whereas this relationship is absent in drier climates. In arid soils, root abundance is lower, and interaction of inputs with mineral surfaces is limited by shallower and briefer periods of moisture, resulting in a disconnect between concentration and persistence. Data suggest a tipping point in the cycling of mineral-associated C at a climate threshold where precipitation equals evaporation. As climate patterns shift, our findings emphasize that divergence in the mechanisms of OM persistence associated with historical climate legacies need to be considered in process-based models.

Recent decline in tropical temperature sensitivity of atmospheric CO2 growth rate variability.

A two-fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability ( Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ ) till early 2000s has been reported, which suggests a drought-induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations, we show that Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ has significantly declined in the last two decades, to the level during the 1960s. The Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline begs the question of whether the sensitivity of ecosystem carbon cycle to temperature variations at local scale has largely decreased. With state-of-the-art dynamic global vegetation models, we further find that the recent Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline is barely attributed to ecosystem carbon cycle response to temperature fluctuations at local scale, which instead results from a decrease in spatial coherence in tropical temperature variability and land use change. Our results suggest that the recently reported loss of rainforest resilience has not shown marked influence on the temperature sensitivity of ecosystem carbon cycle. Nevertheless, the increasing extent of land use change as well as more frequent and intensive drought events are likely to modulate the responses of ecosystem carbon cycle to temperature variations in the future. Therefore, our study highlights the priority to continuously monitor the temperature sensitivity of CGR variability and improve Earth system model representation on land use change, in order to predict the carbon-climate feedback.

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

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.

Increased atmospheric CO2 and the transit time of carbon in terrestrial ecosystems.

The response of terrestrial ecosystems to increased atmospheric CO2 concentrations is controversial and not yet fully understood, with previous large-scale forest manipulation experiments exhibiting contrasting responses. Although there is consensus that increased CO2 has a relevant effect on instantaneous processes such as photosynthesis and transpiration, there are large uncertainties regarding the fate of extra assimilated carbon in ecosystems. Filling this research gap is challenging because tracing the movement of new carbon across ecosystem compartments involves the study of multiple processes occurring over a wide range of timescales, from hours to millennia. We posit that a comprehensive quantification of the effect of increased CO2 must answer two interconnected questions: How much and for how long is newly assimilated carbon stored in ecosystems? Therefore, we propose that the transit time distribution of carbon is the key concept needed to effectively address these questions. Here, we show how the transit time distribution of carbon can be used to assess the fate of newly assimilated carbon and the timescales at which it is cycled in ecosystems. We use as an example a transit time distribution obtained from a tropical forest and show that most of the 60% of fixed carbon is respired in less than 1 year; therefore, we infer that under increased CO2 , most of the new carbon would follow a similar fate unless increased CO2 would cause changes in the rates at which carbon is cycled and transferred among ecosystem compartments. We call for a more frequent adoption of the transit time concept in studies seeking to quantify the ecosystem response to increased CO2 .

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I-Harnessing theory.

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question-How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

Integrating plant physiology and community ecology across scales through trait-based models to predict drought mortality.

Forests are a critical carbon sink and widespread tree mortality resulting from climate-induced drought stress has the potential to alter forests from a carbon sink to a source, causing a positive feedback on climate change. Process-based vegetation models aim to represent the current understanding of the underlying mechanisms governing plant physiological and ecological responses to climate. Yet model accuracy varies across scales, and regional-scale model predictive skill is frequently poor when compared with observations of drought-driven mortality. I propose a framework that leverages differences in model predictive skill across spatial scales, mismatches between model predictions and observations, and differences in the mechanisms included and absent across models to advance the understanding of the physiological and ecological processes driving observed patterns drought-driven mortality.

Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence.

Understanding the controls on the amount and persistence of soil organic carbon (C) is essential for predicting its sensitivity to global change. The response may depend on whether C is unprotected, isolated within aggregates, or protected from decomposition by mineral associations. Here, we present a global synthesis of the relative influence of environmental factors on soil organic C partitioning among pools, abundance in each pool (mg C g-1  soil), and persistence (as approximated by radiocarbon abundance) in relatively unprotected particulate and protected mineral-bound pools. We show that C within particulate and mineral-associated pools consistently differed from one another in degree of persistence and relationship to environmental factors. Soil depth was the best predictor of C abundance and persistence, though it accounted for more variance in persistence. Persistence of all C pools decreased with increasing mean annual temperature (MAT) throughout the soil profile, whereas persistence increased with increasing wetness index (MAP/PET) in subsurface soils (30-176 cm). The relationship of C abundance (mg C g-1  soil) to climate varied among pools and with depth. Mineral-associated C in surface soils (<30 cm) increased more strongly with increasing wetness index than the free particulate C, but both pools showed attenuated responses to the wetness index at depth. Overall, these relationships suggest a strong influence of climate on soil C properties, and a potential loss of soil C from protected pools in areas with decreasing wetness. Relative persistence and abundance of C pools varied significantly among land cover types and soil parent material lithologies. This variability in each pool's relationship to environmental factors suggests that not all soil organic C is equally vulnerable to global change. Therefore, projections of future soil organic C based on patterns and responses of bulk soil organic C may be misleading.

Radiocarbon signature reveals that most springtails depend on carbon from living plants.

Terrestrial carbon cycling is largely mediated by soil food webs. Identifying the carbon source for soil animals has been desired to distinguish their roles in carbon cycling, but it is challenging for small invertebrates at low trophic levels because of methodological limitations. Here, we combined radiocarbon (14C) analysis with stable isotope analyses (13C and 15N) to understand feeding habits of soil microarthropods, especially focusing on springtail (Collembola). Most Collembola species exhibited lower Δ14C values than litter regardless of their δ13C and δ15N signatures, indicating their dependence on young carbon. In contrast with general patterns across all taxonomic groups, we found a significant negative correlation between δ15N and Δ14C values among the edaphic Collembola. This means that the species with higher δ15N values depend on C from more recent photosynthate, which suggests that soil-dwelling species generally feed on mycorrhizae to obtain root-derived C. Many predatory taxa exhibited higher Δ14C values than Collembola but lower than litter, indicating non-negligible effects of collembolan feeding habits on the soil food web. Our study demonstrated the usefulness of radiocarbon analysis, which can untangle the confounding factors that change collembolan δ15N values, clarify animal feeding habits and define the roles of organisms in soil food webs.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.

Structure and parameter uncertainty in centennial projections of forest community structure and carbon cycling.

Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of forest function, and whether models can reproduce multi-decadal succession patterns is an indication of our ability to predict forest responses to future change. We test the ability of a vegetation model to simulate C cycling and community composition during 100 years of forest regrowth following stand-replacing disturbance, asking (a) Which processes and parameters are most important to accurately model Upper Midwest forest succession? (b) What is the relative importance of model structure versus parameter values to these predictions? We ran ensembles of the Ecosystem Demography model v2.2 with different representations of processes important to competition for light. We compared the magnitude of structural and parameter uncertainty and assessed which sub-model-parameter combinations best reproduced observed C fluxes and community composition. On average, our simulations underestimated observed net primary productivity (NPP) and leaf area index (LAI) after 100 years and predicted complete dominance by a single plant functional type (PFT). Out of 4,000 simulations, only nine fell within the observed range of both NPP and LAI, but these predicted unrealistically complete dominance by either early hardwood or pine PFTs. A different set of seven simulations were ecologically plausible but under-predicted observed NPP and LAI. Parameter uncertainty was large; NPP and LAI ranged from ~0% to >200% of their mean value, and any PFT could become dominant. The two parameters that contributed most to uncertainty in predicted NPP were plant-soil water conductance and growth respiration, both unobservable empirical coefficients. We conclude that (a) parameter uncertainty is more important than structural uncertainty, at least for ED-2.2 in Upper Midwest forests and (b) simulating both productivity and plant community composition accurately without physically unrealistic parameters remains challenging for demographic vegetation models.

Satellite-based estimates reveal widespread forest degradation in the Amazon.

Anthropogenic and natural forest disturbance cause ecological damage and carbon emissions. Forest disturbance in the Amazon occurs in the form of deforestation (conversion of forest to non-forest land covers), degradation from the extraction of forest resources, and destruction from natural events. The crucial role of the Amazon rainforest in the hydrologic cycle has even led to the speculation of a disturbance "tipping point" leading to a collapse of the tropical ecosystem. Here we use time series analysis of Landsat data to map deforestation, degradation, and natural disturbance in the Amazon Ecoregion from 1995 to 2017. The map was used to stratify the study area for selection of sample units that were assigned reference labels based on their land cover and disturbance history. An unbiased statistical estimator was applied to the sample of reference observations to obtain estimates of area and uncertainty at biennial time intervals. We show that degradation and natural disturbance, largely during periods of severe drought, have affected as much of the forest area in the Amazon Ecoregion as deforestation from 1995 to 2017. Consequently, an estimated 17% (1,036,800 ± 24,800 km2 , 95% confidence interval) of the original forest area has been disturbed as of 2017. Our results suggest that the area of disturbed forest in the Amazon is 44%-60% more than previously realized, indicating an unaccounted for source of carbon emissions and pervasive damage to forest ecosystems.

Edge effects enhance carbon uptake and its vulnerability to climate change in temperate broadleaf forests.

Forest fragmentation is a ubiquitous, ongoing global phenomenon with profound impacts on the growing conditions of the world's remaining forest. The temperate broadleaf forest makes a large contribution to the global terrestrial carbon sink but is also the most heavily fragmented forest biome in the world. We use field measurements and geospatial analyses to characterize carbon dynamics in temperate broadleaf forest fragments. We show that forest growth and biomass increase by 89 ± 17% and 64 ± 12%, respectively, from the forest interior to edge, but ecosystem edge enhancements are not currently captured by models or approaches to quantifying regional C balance. To the extent that the findings from our research represent the forest of southern New England in the United States, we provide a preliminary estimate that edge growth enhancement could increase estimates of the region's carbon uptake and storage by 13 ± 3% and 10 ± 1%, respectively. However, we also find that forest growth near the edge declines three times faster than that in the interior in response to heat stress during the growing season. Using climate projections, we show that future heat stress could reduce the forest edge growth enhancement by one-third by the end of the century. These findings contrast studies of edge effects in the world's other major forest biomes and indicate that the strength of the temperate broadleaf forest carbon sink and its capacity to mitigate anthropogenic carbon emissions may be stronger, but also more sensitive to climate change than previous estimates suggest.

Pathways of mineral-associated soil organic matter formation: Integrating the role of plant carbon source, chemistry, and point of entry.

To predict the behavior of the terrestrial carbon cycle, it is critical to understand the source, formation pathway, and chemical composition of soil organic matter (SOM). There is emerging consensus that slow-cycling SOM generally consists of relatively low molecular weight organic carbon substrates that enter the mineral soil as dissolved organic matter and associate with mineral surfaces (referred to as "mineral-associated OM," or MAOM). However, much debate and contradictory evidence persist around: (a) whether the organic C substrates within the MAOM pool primarily originate from aboveground vs. belowground plant sources and (b) whether C substrates directly sorb to mineral surfaces or undergo microbial transformation prior to their incorporation into MAOM. Here, we attempt to reconcile disparate views on the formation of MAOM by proposing a spatially explicit set of processes that link plant C source with MAOM formation pathway. Specifically, because belowground vs. aboveground sources of plant C enter spatially distinct regions of the mineral soil, we propose that fine-scale differences in microbial abundance should determine the probability of substrate-microbe vs. substrate-mineral interaction. Thus, formation of MAOM in areas of high microbial density (e.g., the rhizosphere and other microbial hotspots) should primarily occur through an in vivo microbial turnover pathway and favor C substrates that are first biosynthesized with high microbial carbon-use efficiency prior to incorporation in the MAOM pool. In contrast, in areas of low microbial density (e.g., certain regions of the bulk soil), MAOM formation should primarily occur through the direct sorption of intact or partially oxidized plant compounds to uncolonized mineral surfaces, minimizing the importance of carbon-use efficiency, and favoring C substrates with strong "sorptive affinity." Through this framework, we thus describe how the primacy of biotic vs. abiotic controls on MAOM dynamics is not mutually exclusive, but rather spatially dictated. Such an understanding may be integral to more accurately modeling soil organic matter dynamics across different spatial scales.

Differential declines in Alaskan boreal forest vitality related to climate and competition.

Rapid warming and changes in water availability at high latitudes alter resource abundance, tree competition, and disturbance regimes. While these changes are expected to disrupt the functioning of boreal forests, their ultimate implications for forest composition are uncertain. In particular, recent site-level studies of the Alaskan boreal forest have reported both increases and decreases in productivity over the past few decades. Here, we test the idea that variations in Alaskan forest growth and mortality rates are contingent on species composition. Using forest inventory measurements and climate data from plots located throughout interior and south-central Alaska, we show significant growth and mortality responses associated with competition, midsummer vapor pressure deficit, and increased growing season length. The governing climate and competition processes differed substantially across species. Surprisingly, the most dramatic climate response occurred in the drought tolerant angiosperm species, trembling aspen, and linked high midsummer vapor pressure deficits to decreased growth and increased insect-related mortality. Given that species composition in the Alaskan and western Canadian boreal forests is projected to shift toward early-successional angiosperm species due to fire regime, these results underscore the potential for a reduction in boreal productivity stemming from increases in midsummer evaporative demand.

Long-term litter decomposition controlled by manganese redox cycling.

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of litter was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn(2+) provided by fresh plant litter to produce oxidative Mn(3+) species at sites of active decay, with Mn eventually accumulating as insoluble Mn(3+/4+) oxides. Formation of reactive Mn(3+) species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn(3+)-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn(3+) species in the litter layer. This observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant-soil system may have a profound impact on litter decomposition rates.

The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax ) on global gross primary production.

The maximum photosynthetic carboxylation rate (Vcmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr-1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes.

Constraining future terrestrial carbon cycle projections using observation-based water and carbon flux estimates.

The terrestrial biosphere is currently acting as a sink for about a third of the total anthropogenic CO2  emissions. However, the future fate of this sink in the coming decades is very uncertain, as current earth system models (ESMs) simulate diverging responses of the terrestrial carbon cycle to upcoming climate change. Here, we use observation-based constraints of water and carbon fluxes to reduce uncertainties in the projected terrestrial carbon cycle response derived from simulations of ESMs conducted as part of the 5th phase of the Coupled Model Intercomparison Project (CMIP5). We find in the ESMs a clear linear relationship between present-day evapotranspiration (ET) and gross primary productivity (GPP), as well as between these present-day fluxes and projected changes in GPP, thus providing an emergent constraint on projected GPP. Constraining the ESMs based on their ability to simulate present-day ET and GPP leads to a substantial decrease in the projected GPP and to a ca. 50% reduction in the associated model spread in GPP by the end of the century. Given the strong correlation between projected changes in GPP and in NBP in the ESMs, applying the constraints on net biome productivity (NBP) reduces the model spread in the projected land sink by more than 30% by 2100. Moreover, the projected decline in the land sink is at least doubled in the constrained ensembles and the probability that the terrestrial biosphere is turned into a net carbon source by the end of the century is strongly increased. This indicates that the decline in the future land carbon uptake might be stronger than previously thought, which would have important implications for the rate of increase in the atmospheric CO2 concentration and for future climate change.

Photoautotrophic microorganisms as a carbon source for temperate soil invertebrates.

We tested experimentally if photoautotrophic microorganisms are a carbon source for invertebrates in temperate soils. We exposed forest or arable soils to a (13)CO2-enriched atmosphere and quantified (13)C assimilation by three common animal groups: earthworms (Oligochaeta), springtails (Hexapoda) and slugs (Gastropoda). Endogeic earthworms (Allolobophora chlorotica) and hemiedaphic springtails (Ceratophysella denticulata) were highly (13)C enriched when incubated under light, deriving up to 3.0 and 17.0%, respectively, of their body carbon from the microbial source in 7 days. Earthworms assimilated more (13)C in undisturbed soil than when the microbial material was mixed into the soil, presumably reflecting selective surface grazing. By contrast, neither adult nor newly hatched terrestrial slugs (Deroceras reticulatum) grazed on algal mats. Non-photosynthetic (13)CO2 fixation in the dark was negligible. We conclude from these preliminary laboratory experiments that, in addition to litter and root-derived carbon from vascular plants, photoautotrophic soil surface microorganisms (cyanobacteria, algae) may be an ecologically important carbon input route for temperate soil animals that are traditionally assigned to the decomposer channel in soil food web models and carbon cycling studies.

Lignin decomposition is sustained under fluctuating redox conditions in humid tropical forest soils.

Lignin mineralization represents a critical flux in the terrestrial carbon (C) cycle, yet little is known about mechanisms and environmental factors controlling lignin breakdown in mineral soils. Hypoxia is thought to suppress lignin decomposition, yet potential effects of oxygen (O2 ) variability in surface soils have not been explored. Here, we tested the impact of redox fluctuations on lignin breakdown in humid tropical forest soils during ten-week laboratory incubations. We used synthetic lignins labeled with 13 C in either of two positions (aromatic methoxyl or propyl side chain Cß ) to provide highly sensitive and specific measures of lignin mineralization seldom employed in soils. Four-day redox fluctuations increased the percent contribution of methoxyl C to soil respiration relative to static aerobic conditions, and cumulative methoxyl-C mineralization was statistically equivalent under static aerobic and fluctuating redox conditions despite lower soil respiration in the latter treatment. Contributions of the less labile lignin Cß to soil respiration were equivalent in the static aerobic and fluctuating redox treatments during periods of O2 exposure, and tended to decline during periods of O2 limitation, resulting in lower cumulative Cß mineralization in the fluctuating treatment relative to the static aerobic treatment. However, cumulative mineralization of both the Cß - and methoxyl-labeled lignins nearly doubled in the fluctuating treatment relative to the static aerobic treatment when total lignin mineralization was normalized to total O2 exposure. Oxygen fluctuations are thought to be suboptimal for canonical lignin-degrading microorganisms. However, O2 fluctuations drove substantial Fe reduction and oxidation, and reactive oxygen species generated during abiotic Fe oxidation might explain the elevated contribution of lignin to C mineralization. Iron redox cycling provides a potential mechanism for lignin depletion in soil organic matter. Couplings between soil moisture, redox fluctuations, and lignin breakdown provide a potential link between climate variability and the biochemical composition of soil organic matter.

Wood Formation Modeling - A Research Review and Future Perspectives.

Wood formation has received considerable attention across various research fields as a key process to model. Historical and contemporary models of wood formation from various disciplines have encapsulated hypotheses such as the influence of external (e.g., climatic) or internal (e.g., hormonal) factors on the successive stages of wood cell differentiation. This review covers 17 wood formation models from three different disciplines, the earliest from 1968 and the latest from 2020. The described processes, as well as their external and internal drivers and their level of complexity, are discussed. This work is the first systematic cataloging, characterization, and process-focused review of wood formation models. Remaining open questions concerning wood formation processes are identified, and relate to: (1) the extent of hormonal influence on the final tree ring structure; (2) the mechanism underlying the transition from earlywood to latewood in extratropical regions; and (3) the extent to which carbon plays a role as "active" driver or "passive" substrate for growth. We conclude by arguing that wood formation models remain to be fully exploited, with the potential to contribute to studies concerning individual tree carbon sequestration-storage dynamics and regional to global carbon sequestration dynamics in terrestrial vegetation models.