Terrestrial Carbon Dynamics Research Articles

The increasing rate of net carbon uptake in Eurasia has been declining since the early 2000s

The analysis of terrestrial ecosystem carbon dynamics, based on scarce carbon flux observations or carbon flux products simulated by reanalysis meteorological data, has great uncertainties. A more accurate understanding of carbon dynamics in Eurasia was achieved by using a carbon flux dataset (CFD) from meteorological stations with quasi-observational characteristics. The growth of net carbon uptake of ecosystems over Eurasia has been decreasing since the early 2000s. The net ecosystem productivity (NEP) increased significantly with the growth rate of 8.7 × 10−3 g C m−2d−1 yr−1 in spring, summer, and autumn (SSA) during 2003–2011 (p < 0.05), which was correlated with the enhanced vegetation index (EVI) and land surface water index (LSWI). This growth was mostly in dry subhumid and humid regions. However, the change in Eurasian NEP was not significant after 2011. Additionally, about 79 % of the stations in Eurasia were in net carbon uptake in SSA, and net carbon emission stations were mainly located in southwestern Eurasia. The intensity of net carbon uptake was highest in the forest, with a mean carbon uptake of 1.73 ± 0.76 g C m−2d−1 in SSA during 2003–2018, and almost all stations demonstrated carbon uptake. During 2011–2018, the number of stations experiencing reduced NEP exceeded those with increased NEP, and this ratio was higher compared to 2003–2011, mainly due to the decrease in EVI and LSWI. The rate of NEP decline at stations with reduced NEP was 5.2 × 10−3 g C m−2d−1 yr−1 faster during 2011–2018 than in the previous period (p < 0.01). Most of the decreases in NEP during 2011–2018 occurred in cropland, grassland and urban land. The spatio-temporal dynamic analysis of Eurasian NEP could provide references for effective carbon management.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit.

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Terrestrial carbon dynamics and economic valuation of ecosystem service for land use management in the Mediterranean region

Land use change is a significant cause of land degradation, resulting in the removal of carbon and its transfer to the hydrosphere or atmosphere, which can have a detrimental impact on essential ecosystem functions and services. In contrast, rural landscapes offer both ecological and economic benefits to people due to their carbon storage properties. This benefit is often evaluated within the framework of Ecosystem Services (ES). The rural landscapes offer unique structures and ecosystem services. The aim of this study is to provide an economic quantification of carbon storage and sequestration in rural landscapes as an ecosystem service and to introduce carbon-based rural landscape management. The study enables the integration of carbon-based strategies and policies by generating quantitative outputs for landscape plans that have not yet been included in the spatial planning hierarchy. The Upper Seyhan Basin (USB), located on the Eastern Mediterranean coast of Turkiye, was modelled using spatiotemporal and economic valuation approaches to assess terrestrial carbon storage and sequestration in this context. The study modelled and mapped the four main terrestrial carbon storage components in the rural landscape: (i) above-ground biomass, (ii) below-ground biomass, (iii) Soil Organic Carbon (SOC), and (iv) dead organic matter carbon. The future land cover of 2055 was modelled using the Multilayer Perceptron (MLP)-Markov Chain (MC) algorithm based on the “Business-As-Usual” (BAU) scenario to determine future carbon sequestration. The Social Cost of Carbon (SCC) was estimated for Turkiye using the Regional Integrated Model of Climate and Economy (RICE) to economically model carbon services. In the final stage of the study, modelling outputs, including carbon storage pools/sinks, projected land cover dynamics, and SCC components, were used within the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to map the carbon dynamics of the rural landscape at the regional level. This paper demonstrates the role of geospatial modelling and proposes a new planning and design logic that considers carbon-based inputs and global climate change in an appropriate format for land management by bridging the interface between earth sciences and spatial planning. The study results indicate that, the rural landscape in the study area provided an ecosystem service of 70,266 TgC carbon in 2014 with a storage value of USD 222,853,170. For the 2014–2025 projection, an estimated 1.042 TgC of carbon sequestration was valued at USD 6,234,137. The 2014–2055 projection estimated 3.185 TgC of carbon sequestration valued at USD 58,745,265.

Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods

Temperature sensitivity (Q10) of ecosystem respiration (Re) is a critical parameter for predicting global terrestrial carbon dynamics and its response to climate warming. However, the determination of Q10 has been controversial. In this study, we scrutinized the underpinnings of three mainstream methods to reveal their relationships in estimating Q10 for Re in the Heihe River Basin, northwest China. Specifically, these methods are Q10 estimated from the long-term method (Q10_long), short-term method (Q10_short), and the low-frequency (Q10_lf) and high-frequency (Q10_hf) signals decomposed by the singular spectrum analysis (SSA) method. We found that: 1) Q10_lf and Q10_long are affected by the confounding effects caused by non-temperature factors, and are 1.8 ± 0.3 and 1.7 ± 0.3, respectively. 2) The high-frequency signals of the SSA method and short-term method have consistent roles in removing the confounding effects. Both Q10_short and Q10_hf reflect the actual response of respiration to temperature. 3) Overall, Q10_long has a larger variability (1.7 ± 0.3) across different biomes, whereas Q10_short and Q10_hf show convergence (1.4 ± 0.2 and 1.3 ± 0.1, respectively). These results highlight the fact that Q10 can be overestimated by the long-term method, whereas the short-term method and high-frequency signals decomposed by the SSA method can obtain closer and convergent values after removing the confounding effects driven by non-temperature factors. Therefore, it is recommended to use the Q10 value estimated by the short-term method or high-frequency signals decomposed by the SSA method to predict carbon dynamics and its response to global warming in Earth system models.

Terrestrial carbon dynamics in an era of increasing wildfire

Terrestrial carbon dynamics in an era of increasing wildfire

Flexible Foliar Stoichiometry Reduces the Magnitude of the Global Land Carbon Sink

AbstractIncreased plant growth under elevated carbon dioxide (CO2) slows the pace of climate warming and underlies projections of terrestrial carbon (C) and climate dynamics. However, this important ecosystem service may be diminished by concurrent changes to vegetation carbon‐to‐nitrogen (C:N) ratios. Despite clear observational evidence of increasing foliar C:N under elevated CO2, our understanding of potential ecological consequences of foliar stoichiometric flexibility is incomplete. Here, we illustrate that when we incorporated CO2‐driven increases in foliar stoichiometry into the Community Land Model the projected land C sink decreased two‐fold by the end of the century compared to simulations with fixed foliar chemistry. Further, CO2‐driven increases in foliar C:N profoundly altered Earth's hydrologic cycle, reducing evapotranspiration and increasing runoff, and reduced belowground N cycling rates. These findings underscore the urgency of further research to examine both the direct and indirect effects of changing foliar stoichiometry on soil N cycling and plant productivity.

Legacy Effect of Long-Term Elevated CO2 and Warming on Soil Properties Controls Soil Organic Matter Decomposition

Plant litter quality is one of the key factors that control soil organic matter (SOM) decomposition. Under climate change, although significant change in litter quality has been intensively reported, the effect of litter quality change on SOM decomposition is poorly understood. This limits our ability to model the dynamics of soil carbon under climate change. To determine the effect of litter quality and soil property change on SOM decomposition, we performed a controlled, reciprocal transplant and litter decomposition experiments. The soils and plant litters were collected from a long-term field experiment, where four treatments were designed, including: (1) the control without warming at ambient CO2; (2) elevated atmospheric CO2 up to 500 ppm (C); (3) warming plant canopy by 2 °C (T); (4) elevated CO2 plus warming (CT). We found that elevated CO2 and warming altered the litter quality significantly in terms of macronutrients’ content and their stoichiometry. Elevated CO2 decreased the concentration of N in rice and wheat straw, while warming decreased the concentration of N and K in wheat straw. However, the change in plant litter quality did not lead to a shift in SOM decomposition. On the contrary, the legacy effect of long-term elevated CO2 and warming on soil properties dominated the decomposition rate of SOM. Elevated atmospheric CO2 suppressed SOM decomposition mainly by increasing phosphorous availability and lowering the soil C/N, fungi/bacteria ratio, and N-acetyl-glucosaminidase activity, while warming or elevated CO2 plus warming had no effect on SOM decomposition. Our results demonstrated that the changes in soil property other than litter quality control the decomposition of SOM under climate change, and soil property change in respond to climate change should be considered in model developing to predict terrestrial soil carbon dynamics under elevated atmospheric CO2 and warming.

Harnessing Novel Soil Bacteria for Beneficial Interactions with Soybean.

It is claimed that one g of soil holds ten billion bacteria representing thousands of distinct species. These bacteria play key roles in the regulation of terrestrial carbon dynamics, nutrient cycles, and plant productivity. Despite the overwhelming diversity of bacteria, most bacterial species remain largely unknown. Here, we used an oligotrophic medium to isolate novel soil bacteria for positive interaction with soybean. Strictly 22 species of bacteria from the soybean rhizosphere were selected. These isolates encompass ten genera (Kosakonia, Microbacterium, Mycobacterium, Methylobacterium, Monashia, Novosphingobium, Pandoraea, Anthrobacter, Stenotrophomonas, and Rhizobium) and have potential as novel species. Furthermore, the novel bacterial species exhibited plant growth-promoting traits in vitro and enhanced soybean growth under drought stress in a greenhouse experiment. We also reported the draft genome sequences of Kosakonia sp. strain SOY2 and Agrobacterium sp. strain SOY23. Along with our analysis of 169 publicly available genomes for the genera reported here, we demonstrated that these bacteria have a repertoire of genes encoding plant growth-promoting proteins and secondary metabolite biosynthetic gene clusters that directly affect plant growth. Taken together, our findings allow the identification novel soil bacteria, paving the way for their application in crop production.

Leaf economics fundamentals explained by optimality principles.

The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics.

Satellite-Detected Contrasting Responses of Canopy Structure and Leaf Physiology to Drought

Disentangling drought impacts on plant photosynthesis is crucial for projecting future terrestrial carbon dynamics. We examined the separate responses of canopy structure and leaf physiology to an extreme summer drought that occurred in 2011 over Southwest China, where the weather was humid and radiation was the main growth-limiting factor. Canopy structure and leaf physiology were, respectively, represented by near-infrared reflectance of vegetation (NIRv) derived from MODIS data and leaf scale fluorescence yield (Φ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">_f</i> ) derived from both Continuous SIF (CSIF) and global OCO-2 SIF (GOSIF). We detected contrasting responses of canopy structure and leaf physiology to drought with a 14.0% increase in NIRv, compared with 12.6 or 19.3% decreases in Φ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">_f</i> from CSIF and GOSIF, respectively. The increase in structure resulted in a slight carbon change, due to water deficit-induced physiological constraints. The net ecosystem effect was a 7.5% (CSIF), 1.2% (GOSIF) and -2.96% (EC-LUE GPP) change in photosynthesis. Our study improves understanding of complex vegetation responses of plant photosynthesis to drought and may contribute to the reconciliation of contrasting observed directions in plant responses to drought in cloudy regions via remote sensing.

Drivers of community assembly change during succession in wood-decomposing beetle communities.

The patterns of successional change of decomposer communities is unique in that resource availability predictably decreases as decomposition proceeds. Saproxylic (i.e. deadwood-dependent) beetles are a highly diverse and functionally important decomposer group, and their community composition is affected by both deadwood characteristics and other environmental factors. Understanding how communities change with faunal succession through the decomposition process is important as this process influences terrestrial carbon dynamics. Here, we evaluate how beta-diversity of saproxylic beetle communities change with succession, as well as the effects of different major drivers of beta-diversity, such as deadwood tree species, spatial distance between locations, climate and forest structure. We studied spatial beta-diversity (i.e. dissimilarity of species composition between deadwood logs in the same year) of saproxylic beetle communities over 8 years of wood decomposition. Our study included 379 experimental deadwood logs comprising 13 different tree species in 30 forest stands in Germany. We hypothesized that the effects of tree species dissimilarity, measured by phylogenetic distance, and climate on beta-diversity decrease over time, while the effects of spatial distance between logs and forest structure increase. Observed beta-diversity of saproxylic beetle communities increased over time, whereas standardized effects sizes (SES; based on null models) of beta-diversity decreased indicating higher beta-diversity than expected during early years. Beta-diversity increased with increasing phylogenetic distance between tree species and spatial distance among regions, and to a lesser extent with spatial distance within regions and differences in climate and forest structure. Whereas effects of space, climate and forest structure were constant over time, the effect of phylogenetic distance decreased. Our results show that the strength of the different drivers of saproxylic beetle community beta-diversity changes along deadwood succession. Beta-diversity of early decay communities was strongly associated with differences among tree species. Although this effect decreased over time, beta-diversity remained high throughout succession. Possible explanations for this pattern include differences in decomposition rates and fungal communities between logs or the priority effect of early successional communities. Our results suggest that saproxylic beetle diversity can be enhanced by promoting forests with diverse tree communities and structures.

A decline in atmospheric CO2 levels under negative emissions may enhance carbon retention in the terrestrial biosphere

Negative emissions are a key mitigation measure in emission scenarios consistent with Paris agreement targets. The terrestrial biosphere is a carbon sink that regulates atmospheric carbon dioxide (CO2) concentration and climate, but its role under negative emissions is highly uncertain. Here, we investigate the reversibility of the terrestrial carbon cycle to idealized CO2 ramp-up and ramp-down forcing using an ensemble of CMIP6 Earth system models. We find a strong lag in the response of the terrestrial carbon cycle to CO2 forcing. The terrestrial biosphere retains more carbon after CO2 removal starts, even at equivalent CO2 levels. This lagged response is greatest at high latitudes due to long carbon residence time and enhanced vegetation productivity. However, in the pan-Arctic region, terrestrial carbon dynamics under negative emissions are highly dependent on permafrost processes. We suggest that irreversible carbon emissions may occur in permafrost even after achieving net-zero emissions, which offsets ~30% of enhanced land C retention and could hinder climate mitigation.

Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water.

Elevated atmospheric CO2 (eCO2 ) influences the carbon assimilation rate and stomatal conductance of plants, thereby affecting the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO2 in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO2 effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO2 effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO2 concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO2 effects. The eCO2 effect on gross primary productivity (GPP) emerges at relatively low CO2 increase (∆[CO2 ] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO2 effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO2 increase (∆[CO2 ] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO2 is detectable earlier for variables related to the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO2 effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.

Global systematic review with meta-analysis shows that warming effects on terrestrial plant biomass allocation are influenced by precipitation and mycorrhizal association

Biomass allocation in plants is fundamental for understanding and predicting terrestrial carbon storage. Yet, our knowledge regarding warming effects on root: shoot ratio (R/S) remains limited. Here, we present a meta-analysis encompassing more than 300 studies and including angiosperms and gymnosperms as well as different biomes (cropland, desert, forest, grassland, tundra, and wetland). The meta-analysis shows that average warming of 2.50 °C (median = 2 °C) significantly increases biomass allocation to roots with a mean increase of 8.1% in R/S. Two factors associate significantly with this response to warming: mean annual precipitation and the type of mycorrhizal fungi associated with plants. Warming-induced allocation to roots is greater in drier habitats when compared to shoots (+15.1% in R/S), while lower in wetter habitats (+4.9% in R/S). This R/S pattern is more frequent in plants associated with arbuscular mycorrhizal fungi, compared to ectomycorrhizal fungi. These results show that precipitation variability and mycorrhizal association can affect terrestrial carbon dynamics by influencing biomass allocation strategies in a warmer world, suggesting that climate change could influence belowground C sequestration.

The effects of varying drought-heat signatures on terrestrial carbon dynamics and vegetation composition

Abstract. The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, the differential impacts of climate extremes on the terrestrial biosphere and anthropogenic CO2 sink remain poorly understood. In this study, we analyse the effects of six hypothetical climate scenarios with differing drought-heat signatures, sampled from a long stationary climate model simulation, on vegetation distribution and land carbon dynamics, as modelled by a dynamic global vegetation model (LPX-Bern v1.4). The six forcing scenarios consist of a Control scenario representing a natural climate, a Noextremes scenario featuring few droughts and heatwaves, a Nocompound scenario which allows univariate hot or dry extremes but no co-occurring extremes, a Hot scenario with frequent heatwaves, a Dry scenario with frequent droughts, and a Hotdry scenario featuring frequent concurrent hot and dry extremes. We find that a climate with no extreme events increases tree coverage by up to 10 % compared to the Control scenario and also increases ecosystem productivity as well as the terrestrial carbon pools. A climate with many heatwaves leads to an overall increase in tree coverage primarily in higher latitudes, while the ecosystem productivity remains similar to the Control scenario. In the Dry and even more so in the Hotdry scenario, tree cover and ecosystem productivity are reduced by up to −4 % compared to the Control scenario. Regionally, this value can be much larger, for example up to −80 % in mid-western USA or up to −50 % in mid-Eurasia for Hotdry tree ecosystem productivity. Depending on the vegetation type, the effects of the Hotdry scenario are stronger than the effects of the Hot and Dry scenarios combined, illustrating the importance of correctly simulating compound extremes for future impact assessment. Overall, our study illustrates how factorial model experiments can be employed to disentangle the effects of single and compound extremes.

How does the Net primary productivity respond to the extreme climate under elevation constraints in mountainous areas of Yunnan, China?

Mountain ecosystems regulate global terrestrial carbon dynamics and are sensitive to changes of extreme climate. To discuss extreme climate’s impact on productivity of vegetation by using the elevation change as a binding force can provide a new reference for carbon sink management of ecosystem in alpine regions. The CASA model and Rclimdex1.0 were used to calculate NPP and 16 climate extremes indices, respectively, from 1982 to 2019 in Yunnan. The response characteristics of regional NPP to climate extremes were calculated using unary regression analysis, correlation analysis, geographic detector, and relative importance analysis. The results are as follows: (1) The turning point of NPP for various vegetation types appeared in the late 1980s in Yunnan. (2) The correlation between extreme precipitation index and NPP is more dependent on elevation than on extreme temperature indices. (3) Extreme climate indices are more sensitive in middle and high-elevation areas. As a result, NPP of alpine vegetation increased by more than 10% after the turning point compared with that before the turning point. (4) In the elevation range Ⅰ-IV (76–4000 m), the proportion of double-factor increase on NPP was more than 30%, while in the range of 4000–5000 m, the proportion of double-factor increase on NPP was <10%. (5) The primary controlling factors of NPP in the elevation Ⅰ﹣III (76–3000 m) were R25mm, R10mm, and R10mm, respectively. The primary controlling factors of NPP increasing in the elevation IV﹣Ⅵ (4000–6000 m) were SU25, TR20, and FD0, respectively. This study provides new insights into the impact of extreme climate on regional NPP from the perspective of elevation, emphasizing the management of ecological environment in high-elevation regions which are sensitive to climate response.

Controlling factors of soil organic carbon and nitrogen in lucerne grasslands in a semiarid environment

Lucerne (Medicago sativa L.) is one of the most successfully introduced species for revegetation on the Loess Plateau of China and provides important ecosystem services. However, the driving mechanism of soil organic carbon (SOC) and total nitrogen (TN) in lucerne grasslands remains unclear. This study explored the controlling factors of SOC and TN in lucerne grasslands in the semiarid Loess Plateau. A total of 112 quadrats were employed in 28 lucerne fields. Vegetation characteristics, topographic factors, and soil properties at a 0–20 cm depth were measured in each quadrat. The SOC and TN contents increased with altitude and showed positive correlations with species richness, aboveground biomass of native plants, soil moisture, soil inorganic nitrogen, total soil phosphorus (P), and C:P and N:P ratios. Variations in SOC and TN contents were mainly attributed to soil resources, followed by the interaction of topography, vegetation and soil. Soil P, soil moisture, altitude, and native plant species were the main factors controlling SOC and TN contents in these lucerne grasslands. Results suggest that specific abiotic (soil P and moisture) and biotic (plant species diversity) factors controlled SOC and TN in semiarid lucerne grasslands. These factors should be included in SOC and TN evaluation models to predict the future terrestrial ecosystem carbon and nitrogen dynamics.

Terrestrial ecosystem response to flash droughts over India

Rapid onset droughts, termed as “flash droughts”, cause short-term but serious threats to terrestrial ecosystems and influence carbon dynamics due to insufficient warning. To date, how the regional terrestrial carbon dynamics respond to flash droughts in India remains unknown. Since, India is highly dependent on its cropland and vegetation, identifying the influence of flash droughts on terrestrial ecosystem is important. Here we use MODIS remote sensing satellite sensor based gross primary productivity (GPP) and remote sensing-based soil moisture data to compute the response of ecosystems to flash droughts in India. From the investigation, it was observed that GPP responds to more than 95% of the flash droughts across India, with the highest response frequency occurring over Ganga basin and southern India while the lowest response across northeastern India. The discrepancies in the response frequencies are mainly attributed to different vegetation resilience conditions across different parts of the country. Moreover, the mean response time is about 10 to 19 days averaged over India, with the lowest and highest response time over Indus-Ganga basins and northeastern Indian river basins (including the Brahmaputra, Minor rivers draining into Myanmar basin (MRMB), and Barak basins), respectively. Severe reduction in water use efficiency (WUE) was observed for the Ganga river basin and some parts of southern India, which highlighted the non-resilient nature of ecosystem towards rapid soil moisture variations. The study facilitates the identification of flash drought hotspots in the country including the Indus basin, Southern river basins (Cauveri, EFRPCP, and EFRSCB basins), some parts of the Ganga basin, and the ability of an ecosystem to withstand such drastic conditions. These findings highlight the need to adopt essential drought mitigation measures to safeguard the sustainability of ecosystems.

Quantifying the role of moss in terrestrial ecosystem carbon dynamics in northern high latitudes

Abstract. Mosses are ubiquitous in northern terrestrial ecosystems, and play an important role in regional carbon, water and energy cycling. Current global land surface models that do not consider mosses may bias the quantification of regional carbon dynamics. Here we incorporate mosses as a new plant functional type into the process-based Terrestrial Ecosystem Model (TEM 5.0), to develop a new model (TEM_Moss). The new model explicitly quantifies the interactions between vascular plants and mosses and their competition for energy, water, and nutrients. Compared to the estimates using TEM 5.0, the new model estimates that the regional terrestrial soils currently store 132.7 Pg more C and will store 157.5 and 179.1 Pg more C under the RCP8.5 and RCP2.6 scenarios, respectively, by the end of the 21st century. Ensemble regional simulations forced with different parameters for the 21st century with TEM_Moss predict that the region will accumulate 161.1±142.1 Pg C under the RCP2.6 scenario and 186.7±166.1 Pg C under the RCP8.5 scenario over the century. Our study highlights the necessity of coupling moss into Earth system models to adequately quantify terrestrial carbon–climate feedbacks in the Arctic.

Enhanced drought resistance of vegetation growth in cities due to urban heat, CO2 domes and O3 troughs

Sustained increase in atmospheric CO2 is strongly coupled with rising temperature and persistent droughts. While elevated CO2 promotes photosynthesis and growth of vegetation, drier and warmer climate can potentially negate this benefit, complicating the prediction of future terrestrial carbon dynamics. Manipulative studies such as free air CO2 enrichment (FACE) experiments have been useful for studying the joint effect of global change factors on vegetation growth; however, their results do not easily transfer to natural ecosystems partly due to their short-duration nature and limited consideration of climatic gradients and potential confounding factors, such as O3. Urban environments serve as a useful small-scale analogy of future climate at least in reference to CO2 and temperature enhancements. Here, we develop a data-driven approach using urban environments as test beds for revealing the joint effect of changing temperature and CO2 on vegetation response to drought. Using 75 urban-rural paired plots from three climate zones over the conterminous United States (CONUS), we find vegetation in urban areas exhibits a much stronger resistance to drought than in rural areas. Statistical analysis suggests the drought resistance enhancement of urban vegetation across CONUS is attributed to rising temperature (with a partial correlation coefficient of 0.36) and CO2 (with a partial correlation coefficient of 0.31) and reduced O3 concentration (with a partial correlation coefficient of −0.12) in cities. The controlling factor(s) responsible for urban-rural differences in drought resistance of vegetation vary across climate regions, such as surface O3 gradients in the arid climate, and surface CO2 and O3 gradients in the temperate and continental climates. Thus, our study provides new observational insights on the impacts of competing factors on vegetation growth at a large scale, and ultimately, helps reduce uncertainties in understanding terrestrial carbon dynamics.