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Afforestation and land use changes that sequester carbon from the atmosphere in the form of woody biomass have turned southern China into one of the largest carbon sinks globally, which contributes to mitigating climate change. However, forest growth saturation and available land that can be forested limit the longevity of this carbon sink, and while a plethora of studies have quantified vegetation changes over the last decades, the remaining carbon sink potential of this area is currently unknown. Here, we train a model with multiple predictors characterizing the heterogeneous landscapes of southern China and predict the biomass carbon carrying capacity of the region for 2002–2017. We compare observed and predicted biomass carbon density and find that during about two decades of afforestation, 2.34 PgC have been sequestered between 2002 and 2017, and a total of 5.32 Pg carbon can potentially still be sequestrated. This means that the region has reached 73% of its aboveground biomass carbon carrying capacity in 2017, which is 12% more than in 2002, equal to a decrease of 0.77% per year. We identify potential afforestation areas that can still sequester 2.39 PgC, while old and new forests have reached 87% of their potential with 1.85 PgC remaining. Our work locates areas where vegetation has not yet reached its full potential but also shows that afforestation is not a long‐term solution for climate change mitigation. Plain Language Summary Forests sequester carbon dioxide from the atmosphere in the form of vegetation biomass, and tree planting initiatives are thus suggested as a promising measure against climate change. China has recently planted millions of trees, which sequester large amounts of carbon, but this carbon sink is not infinite. We quantify the amount of carbon that can still be sequestered in the forests of southern China. We find that 73% of the limits have been reached in 2017, which is 12% more than in 2002, when the tree planting initiatives started. This illustrates that planting trees is only a short term solution and only a reduction of CO2 emissions helps to mitigate climate change in the long term. Key Points We estimate the aboveground forest biomass of southern China to be 15.22 PgC in 2017 and the carrying capacity is 20.54 PgC Afforestation starting in 2002 has consumed 2.34 PgC, but 5.32 PgC of potential carbon sinks are left Afforestation approaches the carbon sink limits quickly and is not a long term measure to achieve carbon neutrality

Allosteric communication among domains in modular proteins consisting of flexibly linked domains with complimentary roles remains poorly understood. To understand how complementary domains communicate, we have studied human Pin1, a representative modular protein with two domains mutually tethered by a flexible linker: a WW domain for substrate recognition and a peptidyl-prolyl isomerase (PPIase) domain. Previous studies of Pin1 showed that physical contact between the domains causes dynamic allostery by reducing conformation dynamics in the catalytic domain, which compensates for the entropy costs of substrate binding to the catalytic site and thus increases catalytic activity. In this study, the S138A mutant PPIase domain, a mutation that mimics the structural impact of the interdomain contact, was demonstrated to display dynamic allostery by rigidification of the α2-α3 loop that harbors the key catalytic residue C113. The reduced dynamics of the α2-α3 loop stabilizes the C113–H59 hydrogen bond in the hydrogen-bonding network of the catalytic site. The stabilized hydrogen bond between C113 and H59 retards initiation of isomerization, which explains the reduced isomerization rate by ~20% caused by the S138A mutation. These results provide new insight into the interdomain allosteric communication of Pin1.

Enoyl-CoA carboxylases/reductases (ECRs) are some of the most efficient CO2-fixing enzymes described to date. However, the molecular mechanisms underlying the extraordinary catalytic activity of ECRs on the level of the protein assembly remain elusive. Here we used a combination of ambient-temperature X-ray free electron laser (XFEL) and cryogenic synchrotron experiments to study the structural organization of the ECR from Kitasatospora setae. The K. setae ECR is a homotetramer that differentiates into a pair of dimers of open- and closed-form subunits in the catalytically active state. Using molecular dynamics simulations and structure-based mutagenesis, we show that catalysis is synchronized in the K. setae ECR across the pair of dimers. This conformational coupling of catalytic domains is conferred by individual amino acids to achieve high CO2-fixation rates. Our results provide unprecedented insights into the dynamic organization and synchronized inter- and intrasubunit communications of this remarkably efficient CO2-fixing enzyme during catalysis.

Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton’s equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10–46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10–34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

Dynamic soil response and dynamic soil-structure interaction (DSSI) play an important role on the seismic response and distress of all engineering structures. The role of soil response and DSSI can be either beneficial or detrimental depending on the relationship between the dynamic characteristics of: (a) the seismic excitation(s) at the seismic bedrock (or at the rock-outcrop), (b) the soil layer(s) – if any, and (c) the overlying structure. On the other hand, the seismic response of a retaining wall is another DSSI problem, where the term \"structure\" is used to describe the retaining wall, while the term \"soil\" includes, apart from the retained soil layer(s), the soil layer(s) of the wall foundation. In urban environments the need for deep excavations usually requires the construction of temporal or even permanent retaining walls close to pre-existing structures, a fact that will probably have an impact on the dynamic soil response and/or the prevailing DSSI pattern. This positive or negative impact depends on the circumstances, while in the worst-case scenario this interaction may lead to single or double resonance phenomena. Under this perspective, the current study examines numerically the complex phenomenon of dynamic wall-soil-structure interaction (DWSSI). Additionally, an effective mitigation measure is examined, consisting of expanded polystyrene (EPS) blocks behind the retaining wall. This soft inclusion may offer a \"frequency tuning\" of the system that can potentially reduce the detrimental effects of DWSSI on the structure and/or the wall.

To regulate regional water resources, it is essential to identify the relationships among the elements that influence water conservation. Taking the Beijing‐Tianjin‐Hebei urban agglomeration as the study area, the authors applied a new method in combination with a geodetector model and spatial elastic coefficient trajectory model to reveal factors controlling water conservation and to identify relationships among the elements driving water conservation, in which the water conservation capacity and its spatial distribution were achieved using an Integrated Valuation of Ecosystem Services and Tradeoffs model. The authors selected precipitation, potential evapotranspiration, temperature, land use, maximum burial depth of soil, plant‐available water content, soil‐saturated hydraulic conductivity, percentage slope, gross domestic product, and population as the spatial driving factors, which measured the influence on the distribution of water conservation capacity on the whole region, plateaus, mountains, and plains, respectively. On the basis of previous research results, the authors selected precipitation, potential evapotranspiration, and land use as time‐driven factors. The results indicated that the strong water conservation capacity was reflected primarily in the Yanshan and Taihang Mountains and the eastern coastal areas. The water conservation capacity of the entire region, mountains, plateaus, and plains was affected mainly by the soil‐saturated hydraulic conductivity, plant‐available water content, precipitation, and precipitation, respectively. Each driving factor exhibited a clearly interactive influence on the spatial distribution of water conservation in terms of space and time. Key Points The authors calculated water conservation capacity of Beijing‐Tianjin‐Hebei urban agglomeration according to the InVEST model In terms of space, the authors used a geodetector model to explore the driving factors' interactions in relation to water conservation capacity In terms of time, a spatial elastic coefficient trajectory model was used to explore the interactions

Higher‐order multi‐protein complexes such as RNA polymerase II (Pol II) complexes with transcription initiation factors are often not amenable to X‐ray structure determination. Here, we show that protein cross‐linking coupled to mass spectrometry (MS) has now sufficiently advanced as a tool to extend the Pol II structure to a 15‐subunit, 670 kDa complex of Pol II with the initiation factor TFIIF at peptide resolution. The N‐terminal regions of TFIIF subunits Tfg1 and Tfg2 form a dimerization domain that binds the Pol II lobe on the Rpb2 side of the active centre cleft near downstream DNA. The C‐terminal winged helix (WH) domains of Tfg1 and Tfg2 are mobile, but the Tfg2 WH domain can reside at the Pol II protrusion near the predicted path of upstream DNA in the initiation complex. The linkers between the dimerization domain and the WH domains in Tfg1 and Tfg2 are located to the jaws and protrusion, respectively. The results suggest how TFIIF suppresses non‐specific DNA binding and how it helps to recruit promoter DNA and to set the transcription start site. This work establishes cross‐linking/MS as an integrated structure analysis tool for large multi‐protein complexes.

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite‐derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above‐ground biomass. The adjusted simulation significantly reduced the above‐ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation‐constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon. Plain Language Summary The Western United States is dominated by natural lands that play a critical role for carbon balance (e.g., trees, soils), water quality, and timber reserves. This region is also particularly vulnerable to tree death from drought, insect attack, and wildfires, thus requiring constant monitoring to assess its health. Traditional carbon monitoring techniques are usually not possible within mountainous terrain, thus we used satellite observations of leaf area and forest biomass to improve modeled simulations of the Western United States. When we accounted for observations of trees our modeled estimates showed reduced amounts of biomass and relatively small amounts of atmospheric CO2 transfer from the atmosphere to the land (the land absorbs carbon from the atmosphere through photosynthesis). Our best estimate of carbon absorbed by the land was much less than other modeled estimates. This suggests our method better accounted for the current conditions of the trees including death from fire, insect attack, and drought. Our modeled estimate of biomass and carbon balance across the Western United States can be improved further by considering more observations of the land surface related to soil moisture and soil carbon. Key Points Assimilating observations of biomass and leaf area reduces simulated biomass and projects a weak land carbon sink across the Western United States Our estimate of carbon exchange contrasts with an independent FLUXCOM estimate that shows a significant carbon sink in the Western United States Water cycle observations should be used to complement biomass observations to improve the spatial pattern of modeled carbon fluxes

Indigenous Peoples in Northwestern North America have always worked with predictable cycles of day and night, tides, moon phases, seasons, and species growth and reproduction, including such phenological indicators as the blooming of flowers and the songs of birds. Negotiating variability has been constant in people's lives. Long‐term monitoring and detailed knowledge of other lifeforms and landscapes of people's home territories have assisted in responding and adapting to change. Aspects of cultural knowledge and practice that have helped Indigenous Peoples navigate nature's cycles at different scales of time and space include kin ties and social relationships, experiential learning, language, storytelling and timing of ceremonies such as “First Foods” celebrations. Working with ecological processes, Indigenous Peoples have been able to maintain optimal conditions for preferred species, reducing variability and uncertainty through taking care of productive habitats, leaving ecosystems intact, and allowing other species to change in their own cycles. Since the onset of colonization, however, Indigenous Peoples' lifeways have been changed drastically, culminating with the current impacts of global climate change and biodiversity loss. This paper, based on contributions of numerous Indigenous Knowledge holders from across Northwestern North America, outlines some of the key ways in which Indigenous Peoples have embraced predictability and change in their environments and lifeways, and addresses the particular threat of climate change: its recognition, ways of adapting to it, and, ultimately, how it might be reversed through developing more careful, respectful relationships with and responsibilities for the other‐than‐human world. Plain Language Summary Indigenous Peoples of Northwestern North America have, for millennia, lived within seasonal cycles, using the life cycles of plants, birds, and other local species as indicators for harvesting. Their own calendars also mark the times of year when they can normally access and process the foods, materials, and medicines they rely upon and interact with. Indigenous Peoples have long held respectful, interdependent relationships with the plants and animals of their homelands, and have developed many different ways of tending and caring for these species, as well as creating adaptive practices, enabling them to respond to unanticipated shocks and events such as floods or unexpected loss of fish. The arrival of European colonizers caused many changes to Indigenous Peoples' lifeways, resulting in overall resource depletion and, most recently, drastic declines in biodiversity tied with global climate change, industrialization, and colonization. However, Indigenous Peoples' knowledge, practices, and strategies remain critically important, and are absolutely vital in identifying, alleviating, and reversing the impacts of these combined threats. Equally crucial are ethical ways of working together for the benefit of all. Key Points Indigenous Knowledge has guided Peoples of Northwestern North America in optimizing their seasonal activities in synchrony with biological species The breadth and variety of Indigenous Knowledge prepared people for interannual variation, and helped them face the impacts with resilience Currently, with biodiversity loss and climate change threatening protective systems, Indigenous Knowledge is as critically important as ever

Recent advances in satellite observations of solar‐induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf‐level to canopy‐level is usually not well‐represented. Here, we incorporate the simulation of far‐red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf‐level fluorescence yield was simulated by a parametric simplification of the Soil Canopy‐Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf‐level to top‐of‐canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (R2 > 0.91, root‐mean‐square error <0.19 W⋅m−2⋅sr−1⋅μm−1), and captured the day‐to‐day variation of tower‐measured SIF at temperate forest sites (R2 > 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite‐observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations. Plain Language Summary During photosynthesis, plants emit faint light referred to as solar‐induced chlorophyll fluorescence (SIF). Global observations of SIF by satellites provide a new opportunity to evaluate and constrain the simulation of terrestrial photosynthesis by models, which is highly uncertain. To achieve this, accurate simulation of observed SIF is required. As a light signal, SIF experiences complicated scattering and re‐absorption (radiative transfer) before it reaches the sensor. The radiative transfer of SIF is usually not well‐represented in the few studies that incorporated SIF into global models. Here, we incorporate simulation of SIF into one of those models with the radiative transfer processes taken into account. Simulated SIF generally captured the spatial and seasonal patterns of observed SIF, and whether the radiative transfer processes were properly considered had a considerable impact on simulated SIF. By better representing the processes involved in SIF simulation, our model allows more reasonable comparisons between simulated and observed SIF toward constraining and evaluating the simulation of terrestrial photosynthesis. Key Points Simulation of nadir solar‐induced chlorophyll fluorescence (SIF) at 740 nm is incorporated in Community Land Model version 5 (CLM5) with canopy scattering, clumping, and bidirectional effect taken into account CLM5 SIF simulation generally captured the spatial and seasonal patterns of observed SIF The radiative transfer processes had considerable impact on SIF simulations