Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov ), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson ), which are formed concomitantly with soot (Pugmire ). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark ). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The rocket combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles (SpaceX, Hanwha) therefore also need larger fuels loads to achieve the same launched/transferred mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer ; Sheaffer ), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.
A NASA sponsored study conducted at John Hopkins University Applied Physics Lab culminated in a community-inspired heliospheric mission concept called the Interstellar Probe (ISP). The ISP’s science goals include understanding our habitable astrosphere by investigating its interactions with the interstellar medium, and determining the structure, composition, and variability of its constituents. A suite of instruments were proposed to achieve these and other science objectives. The instruments include a Lyman-a spectrograph for velocity-resolved measurements of neutral H atoms. The capability to address key components of the ISP’s science objectives by utilizing high spectral resolution Lyman-a measurements are described in this presentation. These findings have been submitted as a community White Paper to the recent Heliophysics decadal survey.
Vegetation acts as a critical link between the geosphere, biosphere, and atmosphere, regulating the flux of water to the atmosphere via transpiration (E) and the input of carbon from the atmosphere to plants and soil via photosynthetic carbon assimilation (A). The rate of A is known to be seasonally dynamic, however, few studies have investigated how the ratio between E and A, known as the water use efficiency (WUE), changes with phenology. WUE directly impacts regional to global carbon and water cycles and lack of knowledge regarding the dynamics of WUE remains among the largest uncertainties in current earth system model (ESM) projections of carbon and water exchange in temperate forests. Here we attempt to reduce this knowledge gap by studying these dynamics across a range of eight deciduous tree species common to temperate forests of North America. Using gas exchange and spectroscopic measurements, we investigated seasonal patterns in leaf level physiological, biochemical, and anatomical properties, including the seasonal progress of WUE and foliar capacity for carbon assimilation, which corollate with seasonal leaf phenology. We incorporate these findings into a modeling framework that contains the same representation of A, E, and canopy scaling found in ESMs to explore the impact of parameterization, which tracks phenological status, on model forecasts. Our results indicate that both photosynthetic capacity and WUE are seasonally dynamic processes which are not synchronized. WUE increased from a minimum at leaf out toward a more conservative behavior at the mid-summer growth peak. This pattern was explained by a decreased stomatal aperture and a decrease in cuticular leakage with leaf aging. We also observed a seasonal increase in maximum carboxylation capacity, with maximum rates of A and modeled tree net primary productivity (NPP) occurring later toward the end of the summer. This change was primarily driven by an increase in foliar nitrogen content, and a shift in the ratio of Vcmax to Jmax between expanding and mature leaves. By applying our revised parameterization, which captures seasonal dynamics of gas exchange, into our model framework we aim to improve the process representation of leaf function in a temperate forest, and more faithfully represent dynamics of NPP and E in the early and late growth season.
We present evidence of damping of equatorial noise due to Finite-Larmor-radius (FLR) effect in the inner Van Allen belt. Detail observation of the FLR phenomenon in the inner belt region has not been reported until now. Waves primarily damped by the FLR mechanism can influence the energy dependent proton density structure. We analyze a typical case recorded by the Van Allen probe that involves FLR damping of equatorial noise, which was propagating radially towards the Earth, at L-shell ~1.7. As a result of this damping, protons in the energy range of ~18 – 21 MeV at L-shell ~1.7 – 2 get energized. This kind of wave-particle interaction should be included in the future models of the inner Van Allen belt. This phenomenon may also account for the unknown proton loss mechanism reported in Selesnick and Albert (2019).
A cloud event in the altitude range of 53-65 km was observed with lidars over Yanqing (40.5°N, 116°E) and Pingquan (41°N, 118.7°E) on 30 October 2018. Clouds with a multilayer structure first occurred within the line view of lidar at dawn (03:40-06:00LT). They were faint and tenuous, and the maximum volume backscatter coefficient (VBSC) was 1.4×10-10m-1sr-1. At twilight, clouds with multilayer structures were reobserved via lidars, but they became much thicker, with a maximum VBSC of 11.2×10-10m-1sr-1. The structure of the cloud layers varied with time, and they faded completely at approximately ~00:30 LT (+1 day). Measurements from SABER/TIMED were utilized for analysis, and it was found that before the onset of cloud event, a temperature anomaly occurred in the mesosphere over Beijing, and water vapor was also very abundant. The frost point temperature profile of water vapor was estimated, and lidar measurements showed that the atmospheric temperature was close to the frost point of water vapor in the vicinity of the stratopause when the mesosphere was undergoing a low-temperature phase. It was a rare mesospheric cloud event observed with lidars at rather low latitudes, and the clouds probably resulted from the nucleation of saturated water vapor due to the occurrence of a temperature anomaly in the mesosphere.
[This presentation is published at https://doi.org/10.1111/1440-1703.12317] Dead organic matter (DOM), which consists of leaf litter, fine woody debris (FWD; < 3 cm diameter), downed coarse woody debris (CWDlog), and standing or suspended coarse woody debris (CWDsnag), plays a crucial role in forest carbon cycling. However, the contributions of each DOM type on stand-scale carbon storage (necromass) and stand-scale CO2 efflux (Rstand) estimates are not well understood. In addition, there is little knowledge of the effect of each DOM type on the accuracy of stand-scale estimates of total necromass and Rstand. This study investigated characteristics of necromass and Rstand from DOM in a subtropical forest in Okinawa island, Japan, to quantify the effect of each DOM type on total necromass, total Rstand, and estimate error of total necromass and Rstand. The CWDsnag accounted for the highest proportion (54%) of total necromass (1499.7 g C m–2), followed by CWDlog (24%), FWD (11%), and leaf litter (11%). Leaf litter accounted for the highest proportion (37%) of total Rstand (340.6 g C m–2 yr–1), followed by CWDsnag (25%), CWDlog (20%), and FWD (17%). The CWDsnag was distributed locally with 173% of the coefficient of variation for necromass, which was approximately two times higher than those of leaf litter and FWD (72–73%). Our spatial analysis revealed, for accurate estimates of CWDsnag and CWDlog necromass, sampling areas of ≥ 28750 m2 and ≥ 2058‒42875 m2 were required, respectively, under the condition of 95% confidence level and 0.1 of accepted error. In summary, CWD considerably contributed to stand-scale carbon storage and efflux in this subtropical forest, resulting in a major source of errors in the stand-scale estimates. In forests where frequent tree death is likely to occur, necromass and Rstand of CWD are not negligible in considering the carbon cycling as in this study, and therefore need to be estimated accurately.
Graphene or graphene-based nanomaterials have emerged as novel scaffolds for developing robust bio-catalytic systems and a fast-developing promising contender for bioremediation. The interaction of bacteria and graphene is such an elusive issue that its implication in environmental biotechnology is unclear. The complexity and recalcitrant nature of the dyes make the conventional techniques inadequate and remain a challenge for industrial effluent treatment. Many scientists have developed hybrid processes and hybrid materials to enhance the treatment processes to satisfy increasingly stringent laws and criteria related to effluent discharge. The current study explicitly focuses on immobilization and growth of dye-degrading marine bacterial isolates on graphene oxide and their application in methylene blue dye degradation. The synergistic effects of adsorption and biodegradation achieved a unique clean-up performance that the counterpart-free bacteria could not fulfill. Further, toxicity analysis of intermediates also confirmed the non-toxic nature of the intermediates formed after synergistic treatment. This work has the potential to lead to zero effluent treatment processes.
Moisture recycling via evapotranspiration (ET) is often invoked as a mechanism for the high deuterium excess signals observed in continental precipitation (dP). However, a global-scale analysis of precipitation monitoring station isotope data shows that metrics of ET contributions to precipitation (van der Ent et al., 2014) explain little dp variability on seasonal timescales. This occurs despite the fact that ET contributions increase by ~50% in continental locations such as the Eurasian interior from wet to dry seasons. To explain this apparent paradox, we hypothesize that the effects of ET on dP are dampened during dry seasons due to contributions from isotopically-evolved residual water storage that act to lower the d-excess of ET fluxes (dET), in combination with changes in transpiration fraction (T/ET). To test this hypothesis, we develop a parsimonious two-season (wet, dry) model for dET incorporating residual water storage and ET partitioning effects. We find that in environments with limited water storage, such as shallow-rooted grasslands, dry season dET is lower than wet season dET despite lower relative humidity. As global average ratios of annual water storage to precipitation are relatively low (Guntner et al., 2007), these dynamics may be widespread over continents. In environments where water storage is not limiting, such as groundwater-dependent ecosystems, dry season dET is still likely lower; however, this effect arises instead due to higher seasonal T/ET when energy-driven plant water use is enhanced and surface evaporation is relatively limited by water availability. Together, these analyses also indicate multiple mechanisms by which dET may be lower than dp during the same season, challenging the view that moisture recycling feedback increases the dp in continental interiors. This work demonstrates the potential complexity of seasonal dp dynamics and cautions against simple interpretations of dP as a process tracer for moisture recycling. References: Guntner et al., 2007. Water Resour. Res., 43, W05416. van der Ent et al., 2014. Earth Syst. Dynam., 5, 471–489.
Though Venus’s atmospheric conditions and composition have been directly measured, the composition of the Venus lower atmosphere near the surface is generally still poorly known. It was extrapolated from observational data at other altitudes by assuming the constancy of elemental composition without condensation (Krasnopolsky 2007). Both in-situ measurement and remote-sensing observations reveals the most abundant components that exceed the mixing ratio of 10-4 to be CO2, N2, and SO2 (Bezard & de Bergh 2007, JGR 112, E04S07). Water and formation of photochemical H2SO4 — and condensation of cloud-forming H2SO4 — is only important at higher altitudes (Krasnopolsky 2012, Icarus 191, 25). In this work, the balancing of chemical-gravitational-thermal diffusive potentials for the ternary mixture of CO2, N2, and SO2, which represent the neutral Venusian lower atmosphere near the surface, is addressed to obtain the composition grading and to evaluate the tendency toward supercritical density-driven separation of CO2 and N2 (Lebonnois & Schubert 2017, Nat. Geosci. 10, 473). Even though dynamic atmospheric systems, including advective mixing, are more realistic, the static cases evaluated in this work provide stationary states where every dynamic process would eventually proceed to. Hence, our modeling is of a limiting case of the systems of interest, which could help explain some indications of compositional grading. The CRYOCHEM equation of state, which has been successfully applied in describing phase equilibria of Titan’s atmosphere and the surface liquid (Tan & Kargel 2018, Fluid Phase Equilib. 458, 153), as well as that involving solid phases on Pluto’s surface (Tan & Kargel 2018, MNRAS, 474, 4254), is used in this work on the supercritical Venus’s lower atmosphere. In the absence of direct measurement of composition of the lower atmosphere, as well as no lab evidence of CO2 and N2 separation under Venusian surface conditions (Lebonnois et al. 2020, Icarus 338, 113550), the results from this study may at least introduce some new concepts that would entail some tendency for molecular fractionation.
Solid-vapor phase equilibria describe the volatile ices on Pluto’s surface (Tan & Kargel 2018, MNRAS 474, 4254). A simple model of the atmosphere with three components N2/CH4/CO may have solved the long-standing puzzle of the existence of CH4-rich ice in addition to the expected N2-rich ice. An isobaric treatment using CRYOCHEM equation of state naturally results in one solid phase of either ice, which is in equilibrium with the atmosphere, depending on the local temperature variations of Pluto’s surface. CH4-rich ice forms at higher temperatures, while N2-rich ice forms at lower temperatures. A temperature also exists on Pluto where three phases coexist, including vapor in equilibrium with two ices, and where the ices can switch from one type to the other upon cooling or warming. Our model relies on fundamental physics-based thermodynamics, and it explains New Horizons observations of the distributions of these ices, as presented by Bertrand et al. (Nat. Commun. 2020, 11, 1), without invoking a vertically distributed atmospheric CH4 that has not been verified with observation. As observed by New Horizons, Pluto’s surface has valley networks and channels, perhaps resulting from either fluvial (Moore et al. 2016, Science 351, 1284) or glacial (Howard et al. 2017, Icarus 287, 287; Umurhan et al. 2017, Icarus 287, 301) mechanisms, or both, at the present or in the past. Considering the present freezing condition on the surface, if the mechanisms are still in action, they must occur under the surface. Therefore, it is of great interest to know the phase equilibria involving the ices and liquid at conditions that may exist underground. Similar to the treatment of the surface ices, this work also applies CRYOCHEM to describe the phase equilibria that progress through depth as the temperature and pressure increase. The fate of the ices can be determined by examining the resulting phase diagrams at conditions at different depths, specifically the appearance of a liquid phase.
Concerns about water security often inform climate risk-related decisions made by environmentally focused investors (Porritt, 2001; Stern, 2006). Yet, potential liabilities for damage caused by extreme flood and drought events linked to global warming present risks that are not always reflected in share prices (Krosinsky et al., 2012). Considering the highly destructive nature of such events, we query whether companies, or specific sectors, could and should be held at least partially liable for their emission-releasing business activities. Recent articles (Rayer & Millar, 2018; Rayer et al., 2020) estimate that under a hypothetical climate liability regime, North Atlantic hurricane seasons might increasingly generate 1-2% losses on market capitalizations (or share prices) for the top seven carbon-emitting, publicly listed companies. In this paper, we extend the concept of the climate liability regime to estimate the impact of global flood- and drought-related damages on the share prices of nine fossil-fuel firms (including the seven mentioned by Rayer et al. (2020)). Following Rayer et al. (2020), we use incremental climate impacts and historical corporate emissions to estimate that climate change-related global flood and drought damages for the period of 2012 to 2016 amount to approximately 2-3% of the top nine carbon-emitting companies’ market capitalizations. We also include a discussion of moral responsibility and the proportion of obligations between producers and users. Quantifying impacts from extreme weather events increases salience and serves as an example of how science can identify and address the important business questions, pertinent to both investors and companies, that arise from a changing climate. References Krosinsky, C., Robins, N., & Viederman, S. (2012). Evolutions in sustainable investing. John Wiley & Sons. Porritt, J. (2001). The world in context. HRH The Prince of Wales’ Business and the Environment Programme, Cambridge. Rayer, Q. G., & Millar, R. J. (2018). Investing in Extreme Weather Conditions. Citywire Wealth Manager®, (429) 36. Rayer, Q., Pfleiderer, P., & Haustein, K. (2020). Global Warming and Extreme Weather Investment Risks. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-38858-4_3 Stern, N. (2006). Stern Review executive summary. London.
The spatiotemporal patterns of precipitation are critical for understanding the underlying mechanism of many hydrological and climate phenomena. Over the last decade, applications of the complex network theory as a data-driven technique has contributed significantly to study the intricate relationship between many variable in a compact way. In our work, we conduct a study to compare an extreme precipitation pattern in Ganga River Basin, by constructing the networks using two nonlinear methods - event synchronization (ES) and edit distance (ED). Event synchronization has been frequently used to measure the synchronicity between the climate extremes like extreme precipitation by calculating the number of synchronized events between two events like time series. Edit distance measures the similarity/dissimilarity between the events by reducing the number of operations required to convert one segment to another, that consider the events’ occurrence and amplitude. Here, we compare the extreme precipitation patterns obtained from both network construction methods based on different network’s characteristics. We used degree to understand network topology and identify important nodes in the networks. We also attempted to quantify the impact of precipitation seasonality and topography on extreme events. The study outcomes suggested that the degree is decreased in the southwest to the northwest direction and the timing of peak precipitation influences it. We also found an inverse relationship between elevation and timing of peak precipitation exists and the lower elevation greatly influences the connectivity of the stations. The study highlights that Edit distance better captures the network’s topology without getting affected by artificial boundaries.
An accurate estimation of the shale permeability is essential to understand heterogeneous organic-rich shale reservoir rocks and predict the complexity of pore fluid transport in the rocks. However, predicting the matrix permeability by traditional models is still challenging because they require information often measured from core measurements. First, Kozeny’s equation (Kozeny, 1927) uses porosity and specific surface area of solid grains. However, it is difficult to characterize the specific surface area values or grain sizes from the logs. Second, Herron’s method (Herron, 1987) has been used for predicting permeability based on the mineral contents provided by well log data in conventional sandstone reservoirs. However, the predictive accuracy is low due to the different pore network structures of the shales. In this study, we estimate shale matrix permeability by a combined exploratory data analysis (EDA) and nonlinear regression estimation from the wireline logs. First, we conduct a bivariate correlation analysis for permeability and rock properties in core measurements. According to the correlation and Shapley value sensitivity test, we find that permeability change has a significant effect on the variation in porosity. Also, we investigate a nonlinear behavior between porosity and permeability. Second, we derive a nonlinear polylogarithmic estimation function of porosity to permeability, comparing it to the multivariate linear regression of porosity and clay volume fraction. As a result, a cubic logarithmic function of porosity significantly improves the fitting performance of the permeability values, better than the traditional methods. Moreover, we generate the permeability logs from the calibrated porosity logs, and they imply better shale permeability prediction as well. Since we can invert the porosity distribution from seismic data, this approach can provide a more accurate permeability estimation and reliable fluid flow modeling for shale and mudrock.
The tandem rise in satellite-based observations and computing power has changed the way we (can) see rivers across the Earth’s surface. Global datasets of river and river network characteristics at unprecedented resolutions are becoming common enough that the sheer amount of available information presents problems itself. Fully exploiting this new knowledge requires linking these geospatial datasets to each other within the context of a river network. In order to cope with this wealth of information, we are developing Veins of the Earth (VotE), a flexible system designed to synthesize knowledge about rivers and their networks into an adaptable and readily-usable form. VotE is not itself a dataset, but rather a database of relationships linking existing datasets that allows for rapid comparison and exports of river networks at arbitrary resolutions. VotE’s underlying river network (and drainage basins) is extracted from MERIT-Hydro. We link within VotE a newly-compiled dam dataset, streamflow gages from the GRDC, and published global river network datasets characterizing river widths, slopes, and intermittency. We highlight VotE’s utility with a demonstration of how vector-based river networks can be exported at any requested resolution, a global comparison of river widths from three independent datasets, and an example of computing watershed characteristics by coupling VotE to Google Earth Engine. Future efforts will focus on including real-time datasets such as SWOT river discharges and ReaLSAT reservoir areas.
Seismic noise correlation is one of the most used tools to know the earth's structure in the last decade. In this study, we used autocorrelation to determine the presence of underground mines by extracting the normal seismic response in transmission between the ground surface and the cavity roof. The experiments are carried out in the urban environment of the Mexico City western zone, where a high risk of mines collapse subsists. For this, we use ambient noise recorded for 30 min in vertical 4.5 Hz geophone arrays. We obtain zero offset sections of power spectra density from the stacking of autocorrelations in 4 s time windows. The results are compared with GPR, ERT, and seismic refraction studies. We observe that surface cavities such as drainpipe systems are present at frequencies greater than 30 Hz. Between 10 and 30 Hz, the seismic response is produced by resonances associated with cavities that can be delimited laterally by spectral maxima and whose presence agrees with discontinuities on radargrams. The mine roof depth is related to half-wavelength and the compression wave velocity of the surface layer determined by seismic refraction. The autocorrelation method does not determine the shape or vertical extent of the cavity, which is well resolved by the high resistivity values of the ERT method. However, low spectral amplitudes are observed on saturated materials where the electromagnetic wave is noisy and low resistivity values are resolved.
Despite extensive research into the transport and fate of oceanic microplastics (MP, <5mm in size), there is comparatively little focus on river systems considered to be pathways for these contaminants. The Savannah River, forming the border between Georgia and South Carolina, provides a unique location to study MP pollution along a variably industrialized river system terminating in the Atlantic Ocean. We investigated spatial variations in MP concentrations along the Savannah River to better understand their transport and deposition in rural to highly developed fluvial systems. Samples of riverbank sediment and suspended particles captured by a <80μm plankton net were collected along a 115 km reach of the river extending from just below the Strom Thurmond Dam to 25km downstream of Augusta, GA. Laboratory MP separation followed NOAA guidelines with a heavy liquid float-sink separation technique and wet peroxide oxidation treatment. Visually identified MPs were counted and photographed using a stereomicroscope; a subset of particles from each sample were examined using a Horiba XploRa Plus confocal microscope system. Average MP concentrations were measured at 3.1 (range: 1.5-4.6) particles/cubic meter in water and 16.8 (range: 6.2-27.4) particles/kg sediment and primarily composed of polyester fibers and polypropylene pellets. Comparison of MP concentrations between sediment samples from the upper bank and water margin suggests that MP particle deposition is dependent on river stage. Preliminary results further indicate that there is no observable relationship between increasing drainage area and MP concentration, suggesting that concentration may be dependent on localized anthropogenic sources rather than cumulative upstream contributions. Measured concentrations of MP in bank sediment in the upper reaches of the Savannah River are an order-of magnitude less than published concentrations at the river’s mouth collected over the same sampled cross-sectional area, suggesting tidal action exerts a significant control on MP pollution in coastal and near coastal areas. Future work will focus on quantifying the predicted role of tidally dominated systems in concentrating microplastics around river mouths and identifying river reaches with highly concentrated MP particles for targeted remediation.
UCSC GEOPATHS is an NSF-supported initiative to improve undergraduate success in the geosciences, driven by a desire to broaden academic engagement. One component of the program is a funded undergraduate summer program that provides authentic, professional experiences – across all employment sectors – to increase commitment in the geoscience pipeline. Many hydrologic basins rely on groundwater to supply domestic, municipal, and agricultural demand, but resources are increasingly stressed by rising demand, changes in land use, and a shifting climate. Consequences of groundwater overdraft include drying surface water systems, land subsidence, and seawater intrusion. Managed aquifer recharge (MAR) can help improve groundwater resources by increasing infiltration of excess surface water. We are part of a research team assessing hydrologic conditions during MAR on an active vineyard in Central California, through diversion of high flows from an adjacent river, a strategy known as “flood-MAR.” Our team collected soil samples from the upper 100 cm below ground surface at 24 locations across the 785-acre field site. We analyzed samples for soil texture at 10-cm spacing using a particle size analyzer based on laser light scattering. Preliminary analysis of fractions of sand, silt, and clay-sized particles indicate some lateral continuity from site to site. The northern part of the field area appears to be finer grained, on average, consistent with regional soil maps, but there is also considerable variability with depth. These data will be used to assess variations in expected infiltration rates by combining soil texture (to estimate infiltration capacity) and potential flood and saturation depths (to bracket vertical head gradients). Studies of this kind are helpful for assessing the efficacy of flood-MAR as a strategy to improve groundwater supplies and quality.
Climate-induced episodes of extensive tree mortality worldwide are leading to abrupt changes in forest carbon stocks. A severe frost in early February 2011 triggered widespread tree mortality in the lowland tropical dry forest (TDF) of northwestern Mexico. The studied landscape in southern Sonora is composed by a patchy matrix dominated by mature, secondary (originated in abandoned fields), and active agricultural fields. In this forest, we used allometric equations to assessed frost-induced changes in aboveground biomass (AGB) stocks in mature and secondary tropical dry forests. For AGB estimations we used 48 1-ha plots (24 plots per forest type) distributed within four distant subareas in our 83 230 ha study area. On each plot, we recorded all live/dead individuals, and a total of 11 205 woody plants were registered, of which 7 137 (with at least a stem DBH > 2.5 cm) were likely present before the frost, and the remaining smaller ones were considered as new recruits regenerated from seeds (4,068 individuals). From those plants present before the frost, 26 842 and 8 059 were live and dead stems, and 1 222 were dead individuals. All registered live and dead stems accounted for a total of 273.4 Mg of AGB in our study plots (4.8 ha). From this amount, 57.3 Mg was necromass (dead stems). Interestingly, only two out of a total of 74 registered species contributed with ca. 80% of this necromass. These highly sensitive species are the tree legumes Lysioma divaricatum and Acacia cochliacantha. On average, AGB in the studied mature and secondary TDF was 64.3 and 49.6 Mg ha-1, respectively. The corresponding necromass for these forests was 10.9 and 13 Mg ha, respectively. The 2011 frost induced a greater change from live biomass to necromass in secondary than mature forests, 26.2% and 16.9%, respectively, which can be explained by the higher abundance of individuals from sensitive species in secondary forests. Our results suggest that climate-induced shifts in carbon stocks are linked to previous land-use changes in tropical dry forests. Restoration plans of these degraded lands should consider the vulnerability of tropical dry forest species to climate extremes.