The Department of Earth System Science (ESS) focuses on how the atmosphere, land, and oceans interact as a system, and how the Earth will change over a human lifetime.
Projecting climate change is a generalization problem: We extrapolate the recent past using physical models across past, present, and future climates. Current climate models require representations of processes that occur at scales smaller than model grid size, which have been the main source of model projection uncertainty. Recent machine learning (ML) algorithms hold promise to improve such process representations but tend to extrapolate poorly to climate regimes that they were not trained on. To get the best of the physical and statistical worlds, we propose a framework, termed climate-invariant ML, incorporating knowledge of climate processes into ML algorithms, and show that it can maintain high offline accuracy across a wide range of climate conditions and configurations in three distinct atmospheric models. Our results suggest that explicitly incorporating physical knowledge into data-driven models of Earth system processes can improve their consistency, data efficiency, and generalizability across climate regimes.
Determining the key elements of interconnected infrastructure and complex systems is paramount to ensure system functionality and integrity. This work quantifies the dominance of the networks' nodes in their respective neighborhoods, introducing a centrality metric, DomiRank, that integrates local and global topological information via a tunable parameter. We present an analytical formula and an efficient parallelizable algorithm for DomiRank centrality, making it applicable to massive networks. From the networks' structure and function perspective, nodes with high values of DomiRank highlight fragile neighborhoods whose integrity and functionality are highly dependent on those dominant nodes. Underscoring this relation between dominance and fragility, we show that DomiRank systematically outperforms other centrality metrics in generating targeted attacks that effectively compromise network structure and disrupt its functionality for synthetic and real-world topologies. Moreover, we show that DomiRank-based attacks inflict more enduring damage in the network, hindering its ability to rebound and, thus, impairing system resilience. DomiRank centrality capitalizes on the competition mechanism embedded in its definition to expose the fragility of networks, paving the way to design strategies to mitigate vulnerability and enhance the resilience of critical infrastructures.
Models estimating decomposition rates of dead wood across space and time are mainly based on studies carried out in temperate zones where microbes are dominant drivers of decomposition. However, most dead wood biomass is found in tropical ecosystems, where termites are also important wood consumers. Given the dependence of microbial decomposition on moisture with termite decomposition thought to be more resilient to dry conditions, the relative importance of these decomposition agents is expected to shift along gradients in precipitation that affect wood moisture. Here, we investigated the relative roles of microbes and termites in wood decomposition across precipitation gradients in space, time and with a simulated drought experiment in tropical Australia. We deployed mesh bags with non-native pine wood blocks, allowing termite access to half the bags. Bags were collected every 6 months (end of wet and dry seasons) over a 4-year period across five sites along a rainfall gradient (ranging from savanna to wet sclerophyll to rainforest) and within a simulated drought experiment at the wettest site. We expected microbial decomposition to proceed faster in wet conditions with greater relative influence of termites in dry conditions. Consistent with expectations, microbial-mediated wood decomposition was slowest in dry savanna sites, dry seasons and simulated drought conditions. Wood blocks discovered by termites decomposed 16–36% faster than blocks undiscovered by termites regardless of precipitation levels. Concurrently, termites were 10 times more likely to discover wood in dry savanna compared with wet rainforest sites, compensating for slow microbial decomposition in savannas. For wood discovered by termites, seasonality and drought did not significantly affect decomposition rates. Taken together, we found that spatial and seasonal variation in precipitation is important in shaping wood decomposition rates as driven by termites and microbes, although these different gradients do not equally impact decomposition agents. As we better understand how climate change will affect precipitation regimes across the tropics, our results can improve predictions of how wood decomposition agents will shift with potential for altering carbon fluxes. Read the free Plain Language Summary for this article on the Journal blog.
Changes in substrate quality driven by climate, land use, or other forms of global change may represent a strong selective force on microbial communities. Invasion of new taxa into a community through dispersal, evolution, or recolonization could impact the outcome of this environmental selection. Here, we simulated substrate change with a trait-based model of microbial litter decomposition (DEMENTpy) to assess the legacy effects of past substrate quality and the impact of selection by a new substrate on community decomposition activity. Simulations were run with different levels of invasion, including invasion from communities long-adapted to the new substrate. Legacy effects were evident with substrate change for native communities differing in composition. Protein was the only substrate that exerted a strong enough selective force to affect community composition. Legacy effects disappeared when invaders came from substrates similar to the new substrate. Together, our simulations demonstrate that substrate quality changes associated with global change can lead to legacy effects on substrate degradation. In decomposing plant litter, such legacy effects can occur if substrate inputs shift to higher protein content and if invasion is low.
Decadal and multidecadal changes in the meridional overturning circulation may originate from either the subpolar North Atlantic or the Southern Hemisphere. New records of carbon and oxygen isotopes from an eastern Martinique Island (Lesser Antilles) coral reveal irregular, decadal, double-step events of low ∆14C and enhanced vertical mixing, high δ18O and high δ13C values starting in 1885. Comparison of the new and published ∆14C records indicates that the last event (1956-1969) coincides with a widespread, double-step ∆14C low of South Atlantic origin from 32°N to 18°S, associated with a major slowdown of the Caribbean Current transport between 1963 and 1969. This event and the past Martinique ∆14C lows are attributed to pulses of northward advection of low ∆14C Sub-Antarctic Mode Waters into the tropical Atlantic. They are coeval with changes of the tropical freshwater budget and likely driven by meridional overturning circulation changes since ~1880.
The soil environment contains the largest pool of carbon on Earth, with controls on soil carbon residency and flux being an emergent property of microbial metabolism. Despite the fact that microbial interactions have metabolic implications, the contribution of interactions are often overlooked regarding the carbon cycle. Here, we hypothesize that microbial interactions are intrinsically coupled to carbon cycling through eco-evolutionary principles. Interactions drive phenotypic responses that result in allocation pattern shifts and changes in carbon use efficiency. These changes promote alterations in resource availability and community structure, thereby creating selective pressures that contribute to diffuse evolutionary mechanisms. The outcomes then feed back into microbial metabolic operations with consequences for carbon turnover, continuing a feedback loop of microbial interactions, evolutionary processes, and the carbon cycle.
Woody biomass is a large carbon store in terrestrial ecosystems. In calculating biomass, tree stems are assumed to be solid structures. However, decomposer agents such as microbes and insects target stem heartwood, causing internal wood decay which is poorly quantified. We investigated internal stem damage across five sites in tropical Australia along a precipitation gradient. We estimated the amount of internal aboveground biomass damaged in living trees and measured four potential stem damage predictors: wood density, stem diameter, annual precipitation, and termite pressure (measured as termite damage in downed deadwood). Stem damage increased with increasing diameter, wood density, and termite pressure and decreased with increasing precipitation. High wood density stems sustained less damage in wet sites and more damage in dry sites, likely a result of shifting decomposer communities and their differing responses to changes in tree species and wood traits across sites. Incorporating stem damage reduced aboveground biomass estimates by > 30% in Australian savannas, compared to only 3% in rainforests. Accurate estimates of carbon storage across woody plant communities are critical for understanding the global carbon budget. Future biomass estimates should consider stem damage in concert with the effects of changes in decomposer communities and abiotic conditions.
Hybrid fuel cell/gas turbine systems provide an efficient means of producing electricity from fossil fuels with ultra low emissions. However, there are many significant challenges involved in integrating the fuel cell with the gas turbine and other components of this type of system. The fuel cell and the gas turbine must maintain efficient operation and electricity production while protecting equipment during perturbations that may occur when the system is connected to the utility grid or in stand-alone mode. This paper presents recent dynamic simulation results from two laboratories focused on developing tools to aid in the design and dynamic analyses of hybrid fuel cell systems. The simulation results present the response of a carbonate fuel cell/gas turbine, or molten carbonate fuel cell/gas turbine, (MCFC/GT) hybrid system to a load demand perturbation. Initial results suggest that creative control strategies will be needed to ensure a flexible system with wide turndown and robust dynamic operation. Paper No. GT2004-53653,
External cycling regenerating nitrogen oxides (NOx ≡ NO + NO2) from their oxidative reservoir, NOz, is proposed to reshape the temporal-spatial distribution of NOx and consequently hydroxyl radical (OH), the most important oxidant in the atmosphere. Here we verify the in situ external cycling of NOx in various environments with nitrous acid (HONO) as an intermediate based on synthesized field evidence collected onboard aircraft platform at daytime. External cycling helps to reconcile stubborn underestimation on observed ratios of HONO/NO2 and NO2/NOz by current chemical model schemes and rationalize atypical diurnal concentration profiles of HONO and NO2 lacking noontime valleys specially observed in low-NOx atmospheres. Perturbation on the budget of HONO and NOx by external cycling is also found to increase as NOx concentration decreases. Consequently, model underestimation of OH observations by up to 41% in low NOx atmospheres is attributed to the omission of external cycling in models.