Inferring the Evolutionary Model of Community-Structuring Traits with Convolutional Kitchen Sinks.

When communities are assembled through processes such as filtering or limiting similarity acting on phylogenetically conserved traits, the evolutionary signature of those traits may be reflected in patterns of community membership. We show how the model of trait evolution underlying community-structuring traits can be inferred from community membership data using both a variation of a traditional eco-phylogenetic metric-the mean pairwise phylogenetic distance (MPD) between taxa-and a recent machine learning tool, Convolutional Kitchen Sinks (CKS). Both methods perform well across a range of phylogenetically informative evolutionary models, but CKS outperforms MPD as tree size increases. We demonstrate CKS by inferring the evolutionary history of freeze tolerance in angiosperms. Our analysis is consistent with a late burst model, suggesting freeze tolerance evolved recently. We suggest that multiple data types that are ordered on phylogenies, such as trait values, species interactions, or community presence/absence, are good candidates for CKS modeling because the generative models produce structured differences between neighboring points that CKS is well-suited for. We introduce the R package kitchen to perform CKS for generic application of the technique.

Optical Variation and Molecular Transformation of Brown Carbon During Oxidation by NO3• in the Aqueous Phase.

The NO3•-driven nighttime aging of brown carbon (BrC) is known to greatly impact its atmospheric radiative forcing. However, the impact of oxidation by NO3• on the optical properties of BrC in atmospheric waters as well as the associated reaction mechanism remain unclear. In this work, we found that the optical variation of BrC proxies under environmentally relevant NO3• exposure depends strongly on their sources, with enhanced light absorptivity for biomass-burning BrC but bleaching for urban aerosols and humic substances. High-resolution mass spectrometry using FT-ICR MS shows that oxidation by NO3• leads to the formation of light-absorbing species (e.g., nitrated organics) for biomass-burning BrC while destroying electron donors (e.g., phenols) within charge transfer complexes in urban aerosols and humic substances, as evidenced by transient absorption spectroscopy and NaBH4 reduction experiments as well. Moreover, we found that the measured rate constants between NO3• with real BrCs (k = (1.8 ± 0.6) × 107 MC-1s-1, expressed as moles of carbon) are much higher than those of individual model organic carbon (OC), suggesting the reaction with OCs may be a previously ill-quantified important sink of NO3• in atmospheric waters. This work provides insights into the kinetics and molecular transformation of BrC during the oxidation by NO3•, facilitating further evaluation of BrC's climatic effects and atmospheric NO3• levels.

Microbial Sources and Sinks of Nitrous Oxide during Organic Waste Composting.

Composting is widely used for organic waste management and is also a major source of nitrous oxide (N2O) emission. New insight into microbial sources and sinks is essential for process regulation to reduce N2O emission from composting. This study used genome-resolved metagenomics to decipher the genomic structures and physiological behaviors of individual bacteria for N2O sources and sinks during composting. Results showed that several nosZ-lacking denitrifiers in feedstocks drove N2O emission at the beginning of the composting. Such emission became negligible at the thermophilic stage, as high temperatures inhibited all denitrifiers for N2O production except for those containing nirK. The nosZ-lacking denitrifiers were notably enriched to increase N2O production at the cooling stage. Nevertheless, organic biodegradation limited energy availability for chemotaxis and flagellar assembly to restrain nirKS-containing denitrifiers for nitrate reduction toward N2O sources but insignificantly interrupt norBC- and nosZ-containing bacteria (particularly nosZ-containing nondenitrifiers) for N2O sinks by capturing N2O and nitric oxide (NO) for energy production, thereby reducing N2O emission at the mature stage. Furthermore, nosZII-type bacteria included all nosZ-containing nondenitrifiers and dominated N2O sinks. Thus, targeted strategies can be developed to restrict the physiological behaviors of nirKS-containing denitrifiers and expand the taxonomic distribution of nosZ for effective N2O mitigation in composting.

When can a population spreading across sink habitats persist?

We consider populations with time-varying growth rates living in sinks. Each population, when isolated, would become extinct. Dispersal-induced growth (DIG) occurs when the populations are able to persist and grow exponentially when dispersal among the populations is present. We provide a mathematical analysis of this surprising phenomenon, in the context of a deterministic model with periodic variation of growth rates and non-symmetric migration which are assumed to be piecewise continuous. We also consider a stochastic model with random variation of growth rates and migration. This work extends existing results of the literature on the DIG effects obtained for periodic continuous growth rates and time independent symmetric migration.

On the Reliability of Wireless Sensor Networks with Multiple Sinks.

The convergence of heterogeneous wireless sensor networks provides many benefits, including increased coverage, flexible load balancing capabilities, more efficient use of network resources, and the provision of additional data by different types of sensors, thus leading to improved customer service based on more complete information. However, despite these advances, the challenge of ensuring reliability and survivability remains due to low-cost sensor requirements and the inherent unreliability of the wireless environment. Integrating different sensor networks and unifying protocols naturally leads to the creation of a network with multiple sinks, necessitating the exploration of new approaches to rational reliability assurance. The failure of some sensors does not necessarily lead to a shutdown of the network, since other sensors can duplicate information and deliver data to sinks via an increased number of alternative routes. In this paper, the reliability indicator is defined as the probability that sinks can collect data from a given number of sensors. In this context, a dedicated reliability metric is introduced and examined for its effectiveness. This metric is computed using an algorithm rooted in the modified factoring method. Furthermore, we introduce a heuristic algorithm designed for optimal sink placement in wireless sensor networks to achieve the highest level of network reliability.

Different preferences for inorganic carbon influence CO2 flux under Cyanobacteria or Chlorophyta dominance days.

Algae play critical roles in the carbon dioxide (CO2) exchange between the water bodies and the atmosphere. However, the effects of prokaryotic and eukaryotic algae on carbon utilization, CO2 flux, and the underlying mechanisms remain poorly understood. Therefore, this study investigated the differences in carbon preferences and CO2 fluxes under different algal dominance days. Our research revealed that dissolved inorganic carbon (DIC) concentration fluctuations had a limited effect on the relative abundance of algae. However, shifts in dominant algal phyla induced changes in DIC, with Cyanobacteria preferring HCO3- and Chlorophyta preferring CO2. Analysis of the water chemistry balance indicated that the growth of Chlorophyta had a 15.59 times greater effect on CO2 sinks compared with that of Cyanobacteria. During the Cyanobacteria dominance days, the lower DIC concentration did not result in a reduction in CO2 emissions. However, increases in the dissolved organic carbon concentration provided a favorable environment for Cyanobacteria, which promoted CO2 emissions. The CCM model indicated that the growth of Chlorophyta resulted in CO2 uptake rates at least 3.57 times higher and CO2 leakage rates up to 0.97 times lower compared to Cyanobacteria, accelerating CO2 transport into the cell. Overall, CO2 sink was stronger on Chlorophyta dominance days than on Cyanobacteria dominance days. This study emphasized the influence of algal phyla on CO2 fluxes, revealing the significant CO2 sink associated with Chlorophyta. Further research should investigate how to manipulate environmental factors to favor Chlorophyta growth and effectively reduce CO2 emissions.

Dissolved organic matter (DOM) is independently stratified in thermally stratified water bodies.

Thermal stratification often occurs in deep-water bodies, including oceans, lakes, and reservoirs. Dissolved organic matter (DOM) plays a critical role in regulating the dynamics of aquatic food webs and water quality in aquatic ecosystems. In the past, thermal stratification boundaries have been sometimes used exclusively to analyze the vertical distribution of DOM in thermally stratified water bodies. However, the validity of this practice has been challenged. Currently, there is limited understanding of the formation mechanism and stratification of the vertical distribution of DOM in thermally stratified water bodies, which hinders the analysis of the interactions between DOM and vertical aquatic ecological factors. To address this gap, we conducted a comprehensive study to extensively collect the vertical distribution of DOM in thermally stratified water bodies and identify the primary factors influencing this distribution. We found that DOM was independently stratified in thermally stratified water bodies (including two cases in unstratified water bodies), and that the formation mechanisms and statuses of DOM stratification were different from those of thermal stratification. The boundaries and numbers of DOM stratification were generally inconsistent with those of thermal stratification. Therefore, it is more accurate to divide DOM into different layers according to its own vertical profile, and analyze DOM characteristics of each layer based on its own stratification instead of thermal stratification. This study sheds light on the relationship between DOM and thermal stratification and provides a novel approach for analyzing DOM vertical distribution characteristics and their impact on aquatic ecosystems. This finding also holds significant implications for the design and implementation of environmental management programs aimed at preserving the health and functionality of aquatic ecosystems.

Carbon sinks/sources' spatiotemporal heterogeneity and their spatial response to economic-social factors in relatively developed regions: A case of China's coastal area.

With the global climate change, carbon reduction in economically active regions has gradually become a focus of attention and its underlying drivers were essential for understanding alterations in ecosystems in response to human behavior. However, the exploration of Carbon Sinks/Sources Patterns (CSSP) in an Economic-Social context was lacking. Distinguished from traditional Net Ecosystem Productivity (NEP) estimation methods, we optimized model parameters, adjusted estimation logic, and revealed CSSP more reasonably. Moreover, spatial econometric model was used to reveal the spatial effects mechanism of Economic-Social Development on CSSP. Over the past 20 years, we revealed that: (a) The pattern of NEP exhibited distinct spatial heterogeneity, with higher sinks observed in the north and offshore regions. It demonstrated regular cyclic fluctuations, averaging a 3-4-year cycle, featuring a gradual ascent followed by a rapid descent; (b) The Carbon Sequestration Capacity (CSC) of vegetation significantly increased. Based on the carbon sink properties, the study area was distinctly divided into three clusters; (c) CSSP have been profoundly affected by economic-social factors. Economic growth and industrial structure optimization contributed to the enhancement of CSC, but population aggregation and urban expansion had negative impacts. The direct effect of innovation capacity and the spatial spillover effect of industrial structure optimization were negative. Overall, exploring CSSP against the backdrop of economic-social factors not only provides a new perspective for understanding the regularities of change and the underlying mechanisms driven by human factors but also offers valuable insights for achieving sustainable development and green growth in other coastal regions globally.

Avoiding emissions versus creating sinks-Effectiveness and attractiveness to climate finance.

The perception of greater impact via new sinks, as opposed to through avoided emissions, has already led some large investors to focus on sink-related projects. This is a flawed perception when applied universally and carries a risk that effective routes to mitigation through avoiding emissions are side-lined. In reality, both emissions avoidance and emissions removal are needed, and both can be a cost-effective means of delivering mitigation.

Response of macrophyte litter decomposition in global blue carbon ecosystems to climate change.

Blue carbon ecosystems (BCEs) are important nature-based solutions for climate change-mitigation. However, current debates question the reliability and contribution of BCEs under future climatic-scenarios. The answer to this question depends on ecosystem processes driving carbon-sequestration and -storage, such as primary production and decomposition, and their future rates. We performed a global meta-analysis on litter decomposition rate constants (k) in BCEs and predicted changes in carbon release from 309 studies. The relationships between k and climatic factors were examined by extracting remote-sensing data on air temperature, sea-surface temperature, and precipitation aligning to the decomposition time of each experiment. We constructed global numerical models of litter decomposition to forecast k and carbon release under different scenarios. The current k averages at 27 ± 3 × 10-2 day-1 for macroalgae were higher than for seagrasses (1.7 ± 0.2 × 10-2 day-1 ), mangroves (1.6 ± 0.1 × 10-2 day-1 ) and tidal marshes (5.9 ± 0.5 × 10-3 day-1 ). Macrophyte k increased with both air temperature and precipitation in intertidal BCEs and with sea surface temperature for subtidal seagrasses. Above a temperature threshold for vascular plant litter at ~25°C and ~20°C for macroalgae, k drastically increased with increasing temperature. However, the direct effect of high temperatures on k are obscured by other factors in field experiments compared with laboratory experiments. We defined "fundamental" and "realized" temperature response to explain this effect. Based on relationships for realized temperature response, we predict that proportions of decomposed litter will increase by 0.9%-5% and 4.7%-28.8% by 2100 under low- (2°C) and high-warming conditions (4°C) compared to 2020, respectively. Net litter carbon sinks in BCEs will increase due to higher increase in litter C production than in decomposition by 2100 compared to 2020 under RCP 8.5. We highlight that BCEs will play an increasingly important role in future climate change-mitigation. Our findings can be leveraged for blue carbon accounting under future climate change scenarios.

Cloth-Air Partitioning of Neutral Per- and Polyfluoroalkyl Substances (PFAS) in North Carolina Homes during the Indoor PFAS Assessment (IPA) Campaign.

Partitioning of per- and polyfluoroalkyl substances (PFAS) to indoor materials, including clothing, may prolong the residence time of PFAS indoors and contribute to exposure. During the Indoor PFAS Assessment (IPA) Campaign, we measured concentrations of nine neutral PFAS in air and cotton cloth in 11 homes in North Carolina, for up to 9 months. Fluorotelomer alcohols (i.e., 6:2 FTOH, 8:2 FTOH, and 10:2 FTOH) are the dominant target species in indoor air, with concentrations ranging from 1.8 to 49 ng m-3, 1.2 to 53 ng m-3, and 0.21 to 5.7 ng m-3, respectively. In cloth, perfluorooctane sulfonamidoethanols (i.e., MeFOSE and EtFOSE) accumulated most significantly over time, reaching concentrations of up to 0.26 ng cm-2 and 0.24 ng cm-2, respectively. From paired measurements of neutral PFAS in air and suspended cloth, we derived cloth-air partition coefficients (Kca) for 6:2, 8:2, and 10:2 FTOH; ethylperfluorooctane sulfonamide (EtFOSA); MeFOSE; and EtFOSE. Mean log(Kca) values range from 4.7 to 6.6 and are positively correlated with the octanol-air partition coefficient. We investigated the effect of the cloth storage method on PFAS accumulation and the influence of home characteristics on air concentrations. Temperature had the overall greatest effect. This study provides valuable insights into PFAS distribution, fate, and exposure indoors.

Regional Sources and Sinks of Atmospheric Particulate Selenium in the United States Based on Seasonality Profiles.

Selenium (Se) is an essential nutrient for humans and enters our food chain through bioavailable Se in soil. Atmospheric deposition is a major source of Se to soils, driving the need to investigate the sources and sinks of atmospheric Se. Here, we used Se concentrations from PM2.5 data at 82 sites from 1988 to 2010 from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network in the US to identify the sources and sinks of particulate Se. We identified 6 distinct seasonal profiles of atmospheric Se, grouped by geographical location: West, Southwest, Midwest, Southeast, Northeast, and North Northeast. Across most of the regions, coal combustion is the largest Se source, with a terrestrial source dominating in the West. We also found evidence for gas-to-particle partitioning in the wintertime in the Northeast. Wet deposition is an important sink of particulate Se, as determined by Se/PM2.5 ratios. The Se concentrations from the IMPROVE network compare well to modeled output from a global chemistry-climate model, SOCOL-AER, except in the Southeast US. Our analysis constrains the sources and sinks of atmospheric Se, thereby improving the predictions of Se distribution under climate change.

Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks.

The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.

Assessment of suitable areas for afforestation and its carbon sink value in fragile ecological areas of northern China.

Afforestation and reforestation are pivotal in mitigating land degradation and bolstering the carbon sink capacity of terrestrial ecosystems. However, the potential economic ramifications of afforestation and reforestation in the context of climate change remain largely unexplored. In this study, we employed an interdisciplinary methodology to establish a framework for assessing future forest potential and carbon sequestration in the Eastern Loess Plateau region of China. Our findings indicate that an estimated 17,392.99 km2 of land suitable for afforestation still existed within the region, exhibiting a propensity to aggregate around existing forests rather than being dispersed randomly. Notably, 4385.36 km2 was prioritized for afforestation initiatives. Projections suggest a significant enhancement of the forest carbon sink within the study area by 2050, ranging from 36.93 Mt to 105.38 Mt. The corresponding economic value for this enhancement is estimated to vary between US$3.25 billion and US$17.68 billion. Of significance is the observed polarization of the region's carbon sink capacity over time, with half of the total carbon sinks concentrated within 10% of the districts. Additionally, approximately 26% of the counties are expected to transition from carbon sinks to carbon sources. These findings underscore the substantial impact of climate change on forest distribution and suggest a targeted approach to combat forest degradation by circumventing ineffective afforestation activities.

How does heterogeneous environmental regulation affect net carbon emissions: Spatial and threshold analysis for China.

The Chinese government has made great efforts in air pollutant reduction and carried out strict regulation policies. Since numerous air pollutants and CO2 tend to have the same root, source, and process, recent studies argue that environmental regulation may also contribute to reducing carbon emissions. To investigate how various types of environmental regulations affect carbon emissions reduction, this paper constructs the spatial Durbin model and panel threshold model based on provincial panel data in China during 2003-2019. The main findings are as follows: First, China's net carbon emissions show a decreasing trend from east to west, displaying significant spatial agglomeration characteristics. Then, formal and informal environmental regulations have inverted U-shaped impacts on net carbon emissions. The "green paradox" and "reverse emission reduction" effects come into play at different stages. Finally, the threshold model reveals that with the improvement of regional technological innovation levels, the carbon-reducing effect of environmental regulation will increasingly come to the fore. These research findings are conducive to providing theoretical guidance for government to formulate and implement environmental regulation policies rationally.

Multi-scenario simulation of carbon budget balance in arid and semi-arid regions.

The carbon budget has emerged as a central focus in global carbon cycle research. The limited understanding of carbon budget balance dynamics has led to an increasing imbalance between ecological and socio-economic benefits. Building upon a comprehensive analysis of carbon storage and emission in Lanzhou from 2000 to 2020, this study develops a novel deep learning model (CNN-LSTM) to simulate carbon budget under various scenarios from 2030 to 2050. Additionally, scientifically grounded recommendations for carbon compensation are provided. The results demonstrate several key findings: (1) The deep learning model exhibits outstanding performance, with an average overall accuracy exceeding 0.93. The coupled model outperforms individual models, underscoring the significance and necessity of incorporating both temporal and spatial features in land use simulation. (2) Under the ecological protection redline scenario from 2030 to 2050, a noteworthy augmentation in carbon storage and a proficient constraint on carbon emissions are observed. This substantiates the effectiveness of ecological protection interventions. (3) Carbon compensation payment areas are predominantly concentrated in built-up land, with the extent of these areas expanding over time. (4) The disparities in carbon balance effects of forest were more conspicuous than that of built-up land across diverse temporal and scenarios.

The political economy of net-zero transitions: Policy drivers, barriers, and justice benefits to decarbonization in eight carbon-neutral countries.

This study examines the political economy of decarbonization in eight countries over the period 2000 to 2021/2022 that have already achieved a national net-zero transition. These countries are Bhutan, Suriname, Panama, Guyana, Comoros, Gabon, Madagascar, and Niue. It utilizes an analytical method of a rich, interdisciplinary and systematized literature review integrated with thematic analysis. For each of these countries, the study examines the drivers and political motivation behind net-zero progress, including the timeline of events; the barriers and challenges that had to be overcome; and the benefits of decarbonization and its impacts on equity and justice. The main objectives of the study are to broaden the evidence base on low-carbon transitions beyond often and even overstudied countries that are Western, Educated, Industrialized, Rich, Democracies, or WEIRD countries, and to offer new empirical data on the strategy of energy policies in the real world, examining the first eight countries to achieve net-zero success in the modern era. It finds that all eight countries used a similar mix of nine policy interventions involving land use, renewable energy, and waste management. Common barriers included vulnerability to the effects of extreme climate events either in the form of natural disasters (i.e. landslides and floodings) or ecosystems degradation (i.e. ocean acidification, coastal erosion and forests loss). Despite these barriers, achieving net-zero emissions positively impacted marginalized communities by providing a more equitable distribution of climate benefits, mitigating adverse health effects and reducing social inequalities, particularly in low-income areas.

Spatial distribution of microplastics in a large watershed: a case study of the Ottawa River watershed.

River water was sampled at 105 locations in the Ottawa River watershed and analysed for microplastics. Sampling techniques were standardised and replicated at each sample location to give an indication of the spatial extent of microplastics at the watershed scale. Microplastic concentrations remained largely uniform, with no clear accumulation of microplastics towards the lower reaches of the watershed. An ANCOVA analysis determined that the only significant relationships to microplastic concentration were distance downstream on the main channel and tributaries and an increase of microplastic concentrations at boat launch locations. However, these relationships were not strong (R2 value of 0.15) and suggest a more complex interaction of microplastics in large watersheds. It is recommended that further research on microplastic pollution in rivers needs to also focus on temporal factors in addition to considering sinks as an important element in the distribution of microplastics at the watershed scale.

Adding Tree Rings to North America's National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO2.

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and-ultimately-the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

Symposium review: Understanding the role of the rumen microbiome in enteric methane mitigation and productivity in dairy cows.

Ruminants are one of the largest sources of global CH4 emissions. This enteric CH4 is exclusively produced by methanogenic archaea as a natural product during microbial fermentation in the reticulorumen. As CH4 formation leads to a gross energy loss for the ruminant host and is also an environmental issue, several CH4 mitigation approaches have been investigated, but results have been inconsistent, which may be partially attributed to a lack of understanding of the mechanistic basis of methanogenesis and the effect of inhibitors on individual methanogenic lineages and other fermenting microbes in the rumen. Methanogenic archaea are obligatory anaerobes that can reduce CO2, methanol, or methylamines or cleave acetate to form CH4. Although methanogens work toward a common goal of generating energy through the formation of CH4, individual methanogenic lineages differ in their physiological and metabolic capabilities, which can differentially affect H2 transactions and CH4 formation. Using advanced omic approaches, recent research has revealed that less abundant methanol-utilizing Methanosphaera and methylamine- and methanol-utilizing Methanomassiliicoccales lineages are positively correlated with CH4 emissions and may have a greater share in overall CH4 production compared with more abundant CO2-reducing methanogens than previously thought. These data imply that the diversity as well as the abundance of methanogens is important in CH4 formation, and that this diversity is influenced by H2 availability and interactions within and between H2-producing microbes in the rumen. These complex interactions between microbes and H2 are further influenced by variations in dietary, host, and environmental conditions. This review discusses critical knowledge gaps underlying methanogen diversity and its link to CH4 formation, formation of specific bacteria-archaeal cohorts, and how H2 production and utilization are regulated between these cohorts during normal and inhibited methanogenesis. Addressing these knowledge gaps has the potential to lead to the development of novel strategies or to complement existing strategies to effectively reduce CH4 formation while also improving productivity in dairy cows.