The LTAR Grazing Land Common Experiment at Archbold Biological Station-University of Florida.

The Archbold Biological Station-University of Florida (ABS-UF) Long-term Agroecosystem Research (LTAR) site lies in the heart of south-central Florida, representing subtropical humid grazing lands in North America and globally. Beef producers in this region face challenges due to climate variability, limited nutritive value of forages, poor soils, public concerns about water quality and greenhouse gas emissions, management trade-offs, economic uncertainty, and increasing urban encroachment. The ABS-UF Common Experiment, co-designed with stakeholders, will assess innovative management systems in comparison to prevailing management systems on key indicators of sustainability. Innovative management systems being tested are alternative fire (frequency and spatial extent) and grazing practices (stocking rate and system). The common experiment framework was implemented across a management intensity gradient spanning from native rangeland to cultivated pastures, including embedded wetlands. Issues that have arisen to date include difficulties in implementing prescribed fire and reduced productivity in cultivated pastures associated with innovative management, which led to an adjustment of the experimental treatment. A stakeholder advisory council will codesign future alternative treatments and guide experimental changes in this long-term experiment. Stakeholder engagement efforts revealed research priorities centered on financial strength, carbon (C) and greenhouse gas emissions, and water quality. Stakeholders are also interested in testing emerging technology such as the utility of virtual fencing. Results from ABS-UF provide a unique perspective from subtropical humid grazing lands for continental-scale cross-site synthesis on sustainable agroecosystems across LTAR.

Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales.

Understanding the relationship between water and production within and across agroecosystems is essential for addressing several agricultural challenges of the 21st century: providing food, fuel, and fiber to a growing human population, reducing the environmental impacts of agricultural production, and adapting food systems to climate change. Of all human activities, agriculture has the highest demand for water globally. Therefore, increasing water use efficiency (WUE), or producing 'more crop per drop', has been a long-term goal of agricultural management, engineering, and crop breeding. WUE is a widely used term applied across a diverse array of spatial scales, spanning from the leaf to the globe, and over temporal scales ranging from seconds to months to years. The measurement, interpretation, and complexity of WUE varies enormously across these spatial and temporal scales, challenging comparisons within and across diverse agroecosystems. The goals of this review are to evaluate common indicators of WUE in agricultural production and assess tradeoffs when applying these indicators within and across agroecosystems amidst a changing climate. We examine three questions: (1) what are the uses and limitations of common WUE indicators, (2) how can WUE indicators be applied within and across agroecosystems, and (3) how can WUE indicators help adapt agriculture to climate change? Addressing these agricultural challenges will require land managers, producers, policy makers, researchers, and consumers to evaluate costs and benefits of practices and innovations of water use in agricultural production. Clearly defining and interpreting WUE in the most scale-appropriate way is crucial for advancing agroecosystem sustainability.

Permafrost thaw with warming reduces microbial metabolic capacities in subsurface soils.

Microorganisms are major constituents of the total biomass in permafrost regions, whose underlain soils are frozen for at least two consecutive years. To understand potential microbial responses to climate change, here we examined microbial community compositions and functional capacities across four soil depths in an Alaska tundra site. We showed that a 5-year warming treatment increased soil thaw depth by 25.7% (p = .011) within the deep organic layer (15-25 cm). Concurrently, warming reduced 37% of bacterial abundance and 64% of fungal abundances in the deep organic layer, while it did not affect microbial abundance in other soil layers (i.e., 0-5, 5-15, and 45-55 cm). Warming treatment altered fungal community composition and microbial functional structure (p < .050), but not bacterial community composition. Using a functional gene array, we found that the relative abundances of a variety of carbon (C)-decomposing, iron-reducing, and sulphate-reducing genes in the deep organic layer were decreased, which was not observed by the shotgun sequencing-based metagenomics analysis of those samples. To explain the reduced metabolic capacities, we found that warming treatment elicited higher deterministic environmental filtering, which could be linked to water-saturated time, soil moisture, and soil thaw duration. In contrast, plant factors showed little influence on microbial communities in subsurface soils below 15 cm, despite a 25.2% higher (p < .05) aboveground plant biomass by warming treatment. Collectively, we demonstrate that microbial metabolic capacities in subsurface soils are reduced, probably arising from enhanced thaw by warming.

Seasonal variation in the canopy color of temperate evergreen conifer forests.

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Winter warming in Alaska accelerates lignin decomposition contributed by Proteobacteria.

BACKGROUND: In a warmer world, microbial decomposition of previously frozen organic carbon (C) is one of the most likely positive climate feedbacks of permafrost regions to the atmosphere. However, mechanistic understanding of microbial mediation on chemically recalcitrant C instability is limited; thus, it is crucial to identify and evaluate active decomposers of chemically recalcitrant C, which is essential for predicting C-cycle feedbacks and their relative strength of influence on climate change. Using stable isotope probing of the active layer of Arctic tundra soils after depleting soil labile C through a 975-day laboratory incubation, the identity of microbial decomposers of lignin and, their responses to warming were revealed. RESULTS: The ß-Proteobacteria genus Burkholderia accounted for 95.1% of total abundance of potential lignin decomposers. Consistently, Burkholderia isolated from our tundra soils could grow with lignin as the sole C source. A 2.2 °C increase of warming considerably increased total abundance and functional capacities of all potential lignin decomposers. In addition to Burkholderia, α-Proteobacteria capable of lignin decomposition (e.g. Bradyrhizobium and Methylobacterium genera) were stimulated by warming by 82-fold. Those community changes collectively doubled the priming effect, i.e., decomposition of existing C after fresh C input to soil. Consequently, warming aggravates soil C instability, as verified by microbially enabled climate-C modeling. CONCLUSIONS: Our findings are alarming, which demonstrate that accelerated C decomposition under warming conditions will make tundra soils a larger biospheric C source than anticipated. Video Abstract.

Accounting for two-billion tons of stabilized soil carbon.

The pedosphere is the largest terrestrial reservoir of organic carbon, yet soil-carbon variability and its representation in Earth system models is a large source of uncertainty for carbon-cycle science and climate projections. Much of this uncertainty is attributed to local and regional-scale variability, and predicting this variation can be challenging if variable selection is based solely on a priori assumptions due to the scale-dependent nature of environmental determinants. Data mining can optimize predictive modeling by allowing machine-learning algorithms to learn from and discover complex patterns in large datasets that may have otherwise gone unnoticed, thus increasing the potential for knowledge discovery. In this analysis, we identify important, regional-scale determinants for top- and subsoil-carbon stabilization in production forestland across the southeastern US. Specifically, we apply recursive feature elimination to a large suite of socio-environmental data to strategically select a parsimonious, yet highly predictive covariate set. This is achieved by recursively considering smaller and smaller covariate sets-or features-by first training the estimator on the full set to obtain feature importance. The least important features are pruned, and the procedure is recursively repeated until a desired number of covariates is identified. We show that although carbon ranges from 0.3 to 8.2 kg m-2 in the topsoil (0 to 20 cm), and from 0.4 to 17.6 kg m-2 in the subsoil (20 to 100 cm), this variability is predictably distributed with precipitation, soil moisture, nitrogen and sand content, gamma ray emissions, mean annual minimum temperature, and elevation. From our spatial predictions, we estimate that 2.6 Pg of soil carbon is currently stabilized in the upper 100 cm of production forestland, which covers 34.7 million ha in the southeastern US.

Tundra microbial community taxa and traits predict decomposition parameters of stable, old soil organic carbon.

The susceptibility of soil organic carbon (SOC) in tundra to microbial decomposition under warmer climate scenarios potentially threatens a massive positive feedback to climate change, but the underlying mechanisms of stable SOC decomposition remain elusive. Herein, Alaskan tundra soils from three depths (a fibric O horizon with litter and course roots, an O horizon with decomposing litter and roots, and a mineral-organic mix, laying just above the permafrost) were incubated. Resulting respiration data were assimilated into a 3-pool model to derive decomposition kinetic parameters for fast, slow, and passive SOC pools. Bacterial, archaeal, and fungal taxa and microbial functional genes were profiled throughout the 3-year incubation. Correlation analyses and a Random Forest approach revealed associations between model parameters and microbial community profiles, taxa, and traits. There were more associations between the microbial community data and the SOC decomposition parameters of slow and passive SOC pools than those of the fast SOC pool. Also, microbial community profiles were better predictors of model parameters in deeper soils, which had higher mineral contents and relatively greater quantities of old SOC than in surface soils. Overall, our analyses revealed the functional potential of microbial communities to decompose tundra SOC through a suite of specialized genes and taxa. These results portray divergent strategies by which microbial communities access SOC pools across varying depths, lending mechanistic insights into the vulnerability of what is considered stable SOC in tundra regions.

Long-Term Warming in Alaska Enlarges the Diazotrophic Community in Deep Soils.

Tundra ecosystems are typically carbon (C) rich but nitrogen (N) limited. Since biological N2 fixation is the major source of biologically available N, the soil N2-fixing (i.e., diazotrophic) community serves as an essential N supplier to the tundra ecosystem. Recent climate warming has induced deeper permafrost thaw and adversely affected C sequestration, which is modulated by N availability. Therefore, it is crucial to examine the responses of diazotrophic communities to warming across the depths of tundra soils. Herein, we carried out one of the deepest sequencing efforts of nitrogenase gene (nifH) to investigate how 5 years of experimental winter warming affects Alaskan soil diazotrophic community composition and abundance spanning both the organic and mineral layers. Although soil depth had a stronger influence on diazotrophic community composition than warming, warming significantly (P < 0.05) enhanced diazotrophic abundance by 86.3% and aboveground plant biomass by 25.2%. Diazotrophic composition in the middle and lower organic layers, detected by nifH sequencing and a microarray-based tool (GeoChip), was markedly altered, with an increase of α-diversity. Changes in diazotrophic abundance and composition significantly correlated with soil moisture, soil thaw duration, and plant biomass, as shown by structural equation modeling analyses. Therefore, more abundant diazotrophic communities induced by warming may potentially serve as an important mechanism for supplementing biologically available N in this tundra ecosystem.IMPORTANCE With the likelihood that changes in global climate will adversely affect the soil C reservoir in the northern circumpolar permafrost zone, an understanding of the potential role of diazotrophic communities in enhancing biological N2 fixation, which constrains both plant production and microbial decomposition in tundra soils, is important in elucidating the responses of soil microbial communities to global climate change. A recent study showed that the composition of the diazotrophic community in a tundra soil exhibited no change under a short-term (1.5-year) winter warming experiment. However, it remains crucial to examine whether the lack of diazotrophic community responses to warming is persistent over a longer time period as a possibly important mechanism in stabilizing tundra soil C. Through a detailed characterization of the effects of winter warming on diazotrophic communities, we showed that a long-term (5-year) winter warming substantially enhanced diazotrophic abundance and altered community composition, though soil depth had a stronger influence on diazotrophic community composition than warming. These changes were best explained by changes in soil moisture, soil thaw duration, and plant biomass. These results provide crucial insights into the potential factors that may impact future C and N availability in tundra regions.

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming.

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon-climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming. Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.

Nonlinear CO2 flux response to 7 years of experimentally induced permafrost thaw.

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss. Using data from 7 years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO2 flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (Reco ), gross primary productivity (GPP), and net summer CO2 storage (NEE). Over 7 years Reco , GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, Reco , GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated microsites and suppressed Reco , GPP, and NEE. However Reco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher Reco in deeply thawed areas during summer months was balanced by GPP. Summer CO2 flux across treatments fit a single quadratic relationship that captured the functional response of CO2 flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO2 flux: plant growth and water table dynamics. Nonsummer Reco models estimated that the area was an annual CO2 source during all years of observation. Nonsummer CO2 loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO2 source.

Circumpolar assessment of permafrost C quality and its vulnerability over time using long-term incubation data.

High-latitude ecosystems store approximately 1700 Pg of soil carbon (C), which is twice as much C as is currently contained in the atmosphere. Permafrost thaw and subsequent microbial decomposition of permafrost organic matter could add large amounts of C to the atmosphere, thereby influencing the global C cycle. The rates at which C is being released from the permafrost zone at different soil depths and across different physiographic regions are poorly understood but crucial in understanding future changes in permafrost C storage with climate change. We assessed the inherent decomposability of C from the permafrost zone by assembling a database of long-term (>1 year) aerobic soil incubations from 121 individual samples from 23 high-latitude ecosystems located across the northern circumpolar permafrost zone. Using a three-pool (i.e., fast, slow and passive) decomposition model, we estimated pool sizes for C fractions with different turnover times and their inherent decomposition rates using a reference temperature of 5 °C. Fast cycling C accounted for less than 5% of all C in both organic and mineral soils whereas the pool size of slow cycling C increased with C : N. Turnover time at 5 °C of fast cycling C typically was below 1 year, between 5 and 15 years for slow turning over C, and more than 500 years for passive C. We project that between 20 and 90% of the organic C could potentially be mineralized to CO2 within 50 incubation years at a constant temperature of 5 °C, with vulnerability to loss increasing in soils with higher C : N. These results demonstrate the variation in the vulnerability of C stored in permafrost soils based on inherent differences in organic matter decomposability, and point toward C : N as an index of decomposability that has the potential to be used to scale permafrost C loss across landscapes.

Observed increase in local cooling effect of deforestation at higher latitudes.

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models.