State Key Laboratory of Urban and Regional Ecology

Abstract Our understanding and quantification of global soil nitrous oxide (N 2 O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO 2 concentration, on global soil N 2 O emissions for the period 1861–2016 using a standard simulation protocol with seven process‐based terrestrial biosphere models. Results suggest global soil N 2 O emissions have increased from 6.3 ± 1.1 Tg N 2 O‐N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N 2 O‐N/year in the recent decade (2007–2016). Cropland soil emissions increased from 0.3 Tg N 2 O‐N/year to 3.3 Tg N 2 O‐N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N 2 O emissions since the 1970s. However, US cropland N 2 O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N 2 O emissions appear to have decreased by 14%. Soil N 2 O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N 2 O‐N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO 2 concentration reduced soil N 2 O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N 2 O emissions, this study recommends several critical strategies for improving the process‐based simulations.

Abstract Excessive ammonia (NH 3 ) emitted from nitrogen (N) fertilizer applications in global croplands plays an important role in atmospheric aerosol production, resulting in visibility reduction and regional haze. However, large uncertainty exists in the estimates of NH 3 emissions from global and regional croplands, which utilize different data and methods. In this study, we have coupled a process‐based Dynamic Land Ecosystem Model (DLEM) with the bidirectional NH 3 exchange module in the Community Multiscale Air‐Quality (CMAQ) model (DLEM‐Bi‐NH 3 ) to quantify NH 3 emissions at the global and regional scale, and crop‐specific NH 3 emissions globally at a spatial resolution of 0.5° × 0.5° during 1961–2010. Results indicate that global NH 3 emissions from N fertilizer use have increased from 1.9 ± 0.03 to 16.7 ± 0.5 Tg N/year between 1961 and 2010. The annual increase of NH 3 emissions shows large spatial variations across the global land surface. Southern Asia, including China and India, has accounted for more than 50% of total global NH 3 emissions since the 1980s, followed by North America and Europe. Rice cultivation has been the largest contributor to total global NH 3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH 3 emissions in context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010. This study provides a robust estimate on global and regional NH 3 emissions over the past 50 years, which offers a reference for assessing air quality consequences of future nitrogen enrichment as well as nitrogen use efficiency improvement.

Amazon droughts have impacted regional ecosystem functioning as well as global carbon cycling. The severe dry-season droughts in 2005 and 2010, driven by Atlantic sea surface temperature (SST) anomaly, have been widely investigated in terms of drought severity and impacts on ecosystems. Although the influence of Pacific SST anomaly on wet-season precipitation has been well recognized, it remains uncertain to what extent the droughts driven by Pacific SST anomaly could affect forest greenness and photosynthesis in the Amazon. Here, we examined the monthly and annual dynamics of forest greenness and photosynthetic capacity when Amazon ecosystems experienced an extreme drought in 2015/2016 driven by a strong El Niño event. We found that the drought during August 2015-July 2016 was one of the two most severe meteorological droughts since 1901. Due to the enhanced solar radiation during this drought, overall forest greenness showed a small increase, and 21.6% of forests even greened up (greenness index anomaly ≥1 standard deviation). In contrast, solar-induced chlorophyll fluorescence (SIF), an indicator of vegetation photosynthetic capacity, showed a significant decrease. Responses of forest greenness and photosynthesis decoupled during this drought, indicating that forest photosynthesis could still be suppressed regardless of the variation in canopy greenness. If future El Niño frequency increases as projected by earth system models, droughts would result in persistent reduction in Amazon forest productivity, substantial changes in tree composition, and considerable carbon emissions from Amazon.

Arsenic (As) is a pervasive and ubiquitous environmental toxin that has created worldwide human health problems. However, there are few studies about how organisms detoxify As. Cyanobacteria are capable of both photolithotrophic growth in the light and heterotrophic growth in the dark and are ubiquitous in soils, aquatic systems, and wetlands. In this study, we investigated As biotransformation in three cyanobacterial species (Microcystis sp. PCC7806, Nostoc sp. PCC7120, and Synechocystis sp. PCC6803). Each accumulated large amounts of As, up to 0.39 g kg(-1) dry weight, 0.45 g kg(-1) dry weight, and 0.38 g kg(-1) dry weight when treated with 100 μM sodium arsenite for 14 d, respectively. Inorganic arsenate and arsenite were the predominant species, with arsenate making up >80% of total As; methylated arsenicals were detected following exposure to higher As concentrations. When treated with arsenate for 6 weeks, cells of each cyanobacterium produced volatile arsenicals. The genes encoding the As(III) S-adenosylmethionine methyltransferase (ArsM) were cloned from these three cyanobacteria. When expressed in an As-hypersensitive strain of Escherichia coli, each conferred resistance to arsenite. Two of the ArsM homologs (SsArsM from Synechocystis sp. PCC6803 and NsArsM from Nostoc sp. PCC7120) were purified and were shown to methylate arsenite in vitro with trimethylarsine as the end product. Given that ArsM homologs are widespread in cyanobacteria, we propose that they play an important role in As biogeochemistry.

Abstract Balancing crop production and greenhouse gas (GHG) emissions from agriculture soil requires a better understanding and quantification of crop GHG emissions intensity, a measure of GHG emissions per unit crop production. Here we conduct a state‐of‐the‐art estimate of the spatial‐temporal variability of GHG emissions intensities for wheat, maize, and rice in China from 1949 to 2012 using an improved agricultural ecosystem model (Dynamic Land Ecosystem Model‐Agriculture Version 2.0) and meta‐analysis covering 172 field‐GHG emissions experiments. The results show that the GHG emissions intensities of these croplands from 1949 to 2012, on average, were 0.10–1.31 kg CO 2 ‐eq/kg, with a significant increase rate of 1.84–3.58 × 10 –3 kg CO 2 ‐eq kg −1 year −1 . Nitrogen fertilizer was the dominant factor contributing to the increase in GHG emissions intensity in northern China and increased its impact in southern China in the 2000s. Increasing GHG emissions intensity implies that excessive fertilizer failed to markedly stimulate crop yield increase in China but still exacerbated soil GHG emissions. This study found that overfertilization of more than 60% was mainly located in the winter wheat–summer maize rotation systems in the North China Plain, the winter wheat–rice rotation systems in the middle and lower reaches of the Yangtze River and southwest China, and most of the double rice systems in the South. Our simulations suggest that roughly a one‐third reduction in the current N fertilizer application level over these “overfertilization” regions would not significantly influence crop yield but decrease soil GHG emissions by 29.60%–32.50% and GHG emissions intensity by 0.13–0.25 kg CO 2 ‐eq/kg. This reduction is about 29% and 5% of total agricultural soil GHG emissions in China and the world, respectively. This study suggests that improving nitrogen use efficiency would be an effective strategy to mitigate GHG emissions and sustain China's food security.

Enhanced pollutant removal by FeOOH/RGO hydrogels relying on π–π and π–Fe interactions.

Understanding the spatial growth of cities is crucial for proactive planning and sustainable urbanization. The largest and most densely inhabited megapolis of Pakistan, Karachi, has experienced massive spatial growth not only in the core areas of the city, but also in the city’s suburbs and outskirts over the past decades. In this study, the land use/land cover (LULC) in Karachi was classified using Landsat data and the random forest algorithm from the Google Earth Engine cloud platform for the years 1990, 2000, 2010, and 2020. Land use/land cover classification maps as well as an urban sprawl matrix technique were used to analyze the geographical patterns and trends of urban sprawl. Six urban classes, namely, the primary urban core, secondary urban core, sub-urban fringe, scatter settlement, urban open space, and non-urban area, were determined for the exploration of urban landscape changes. Future scenarios of LULC for 2030 were predicted using a CA–Markov model. The study found that the built-up area had expanded in a considerably unpredictable manner, primarily at the expense of agricultural land. The increase in mangroves and grassland and shrub land proved the effectiveness of afforestation programs in improving vegetation coverage in the study area. The investigation of urban landscape alteration revealed that the primary urban core expanded from the core districts, namely, the Central, South, and East districts, and a new urban secondary core emerged in Malir in 2020. The CA–Markov model showed that the total urban built-up area could potentially increase from 584.78 km2 in 2020 to 652.59 km2 in 2030. The integrated method combining remote sensing, GIS, and an urban sprawl matrix has proven invaluable for the investigation of urban sprawl in a rapidly growing city.

Abstract. Excessive anthropogenic nitrogen (N) inputs to the biosphere have disrupted the global nitrogen cycle. To better quantify the spatial and temporal patterns of anthropogenic N inputs, assess their impacts on the biogeochemical cycles of the planet and the living organisms, and improve nitrogen use efficiency (NUE) for sustainable development, we have developed a comprehensive and synthetic dataset for reconstructing the History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere. The HaNi dataset takes advantage of different data sources in a spatiotemporally consistent way to generate a set of high-resolution gridded N input products from the preindustrial period to the present (1860–2019). The HaNi dataset includes annual rates of synthetic N fertilizer, manure application/deposition, and atmospheric N deposition on cropland, pasture, and rangeland at a spatial resolution of 5 arcmin × 5 arcmin. Specifically, the N inputs are categorized, according to the N forms and land uses, into 10 types: (1) NH4+-N fertilizer applied to cropland, (2) NO3--N fertilizer applied to cropland, (3) NH4+-N fertilizer applied to pasture, (4) NO3--N fertilizer applied to pasture, (5) manure N application on cropland, (6) manure N application on pasture, (7) manure N deposition on pasture, (8) manure N deposition on rangeland, (9) NHx-N deposition, and (10) NOy-N deposition. The total anthropogenic N (TN) inputs to global terrestrial ecosystems increased from 29.05 Tg N yr−1 in the 1860s to 267.23 Tg N yr−1 in the 2010s, with the dominant N source changing from atmospheric N deposition (before the 1900s) to manure N (in the 1910s–2000s) and then to synthetic fertilizer in the 2010s. The proportion of synthetic NH4+-N in fertilizer input increased from 64 % in the 1960s to 90 % in the 2010s, while synthetic NO3--N fertilizer decreased from 36 % in the 1960s to 10 % in the 2010s. Hotspots of TN inputs shifted from Europe and North America to East and South Asia during the 1960s–2010s. Such spatial and temporal dynamics captured by the HaNi dataset are expected to facilitate a comprehensive assessment of the coupled human–Earth system and address a variety of social welfare issues, such as the climate–biosphere feedback, air pollution, water quality, and biodiversity. The data are available at https://doi.org/10.1594/PANGAEA.942069 (Tian et al., 2022).

UNLABELLED: Anaerobic ammonium oxidation with nitrite reduction to dinitrogen (termed anammox) has been reported to be an important process for removing fixed nitrogen (N) in marine ecosystems and in some agricultural and wetland soils. However, its importance in upland forest soils has never been quantified. In this study, we evaluated the occurrence of anammox activity in two temperate forest soils collected from northeastern China. With (15)N-labeled NO3 (-) incubation, we found that the combined potential of the N2 production rates of anammox and codenitrification ranged from 0.01 ± 0.01 to 1.2 ± 0.18 nmol N per gram of soil per hour, contributing 0.5% to 14.4% of the total N2 production along the soil profile. Denitrification was the main pathway of N2 production and accounted for 85.6% to 99.5% of the total N2 production. Further labeling experiments with (15)NH4 (+) and (15)NO2 (-) indicated that codenitrification was present in the mixed forest soil. Codenitrification and anammox accounted for 2% to 12% and 1% to 7% of the total N2 production, respectively. Two anammox species, "Candidatus Brocadia fulgida" and "Candidatus Jettenia asiatica," were detected in this study but in very low abundance (as indicated by the hzsB gene). Our results demonstrated that the anammox process occurs in forest soils, but the contribution to N2 loss might be low in these ecosystems. More research is necessary to determine the activities of different N2 releasing pathways in different forest soils. IMPORTANCE: In this study, we examined the anammox activity in temperate upland forest soils using the (15)N isotope technique. We found that the anammox process contributed little to the N2 production rate in the studied forest soil. Two anammox organisms, "Candidatus Brocadia fulgida" and "Candidatus Jettenia asiatica," were detected. In addition, we found that codenitrification was another N2 production pathway in forest soils. Our results could contribute to the understanding of soil gaseous N losses and microbial controls in forest soils.

ABSTRACT Introduction: Phosphorus (P) is an essential element in food production. P consumption is increasing over the years due to increasing population and increasing demand for agricultural yields. Managing the agricultural P through the understanding of bioavailability, transport, and runoff will maximize the soil productivity and minimize the environmental effects. Efficient management in agriculture, governance, and lack of integrated international governance need to be addressed to overcome the P scarcity issue. Results and Discussions: This article is focusing one such efficient management of P resource addressing the major portion of phosphorus which is unnoticed in agricultural residues, manures, and other sources. Increasing cost of phosphate fertilizer, a scarcity of high-quality phosphate rock (PR), and increasing surface water pollution are driving a need to accelerate the recovery and reuse of phosphorus (P) from various waste sectors. Options to recover P occur all along the open P cycle from mining to households to oceans. However, P recovery as a regional and global strategy toward P sustainability and future food, bio energy, and water security are in its infancy because of a number of technological, socioeconomic, and institutional constraints. Resolving these constraints requires concerted collaboration between relevant stakeholders and an integrated approach combining successful business models with socioeconomic and institutional changes.

Abstract The application of manure and mineral nitrogen (N) fertilizer, and livestock excreta deposition are the main drivers of nitrous oxide (N 2 O) emissions in agricultural systems. However, the magnitude and spatiotemporal variations of N 2 O emissions due to different management practices (excreta deposition and manure/fertilizer application) from grassland ecosystems remain unclear. In this study, we used the Dynamic Land Ecosystem Model to simulate the spatiotemporal variation in global N 2 O emissions and their attribution to different sources from both intensively managed ( pasturelands ) and extensively managed ( rangelands ) grasslands during 1961–2014. Over the study period, pasturelands and rangelands experienced a significant increase in N 2 O emissions from 1.74 Tg N 2 O‐N in 1961 to 3.11 Tg N 2 O‐N in 2014 ( p < 0.05). Globally, pasturelands and rangelands were responsible for 54% (2.2 Tg N 2 O‐N) of the total agricultural N 2 O emissions (4.1 Tg N 2 O‐N) in 2006. Natural and anthropogenic sources contributed 26% (0.64 Tg N 2 O‐N/year) and 74% (1.78 Tg N 2 O‐N/year) of the net emissions, respectively. Across different biomes, pasturelands (i.e., C3 and C4) were the single largest contributor to N 2 O fluxes, accounting for 86% of the net global emissions from grasslands. Among different sources, livestock excreta deposition contributed 54% of the net emissions, followed by manure N (13%) and mineral N (7%) application. Regionally, southern Asia contributed 38% of the total emissions, followed by Europe (29%) and North America (16%). Our modeling study demonstrates that livestock excreta deposition and manure/fertilizer application have dramatically altered the N cycle in pasturelands, with a substantial impact on the climate system.

Abstract Carbon fluxes at the land‐atmosphere interface are strongly influenced by weather and climate conditions. Yet what is usually known as “climate extremes” does not always translate into very high or low carbon fluxes or so‐called “carbon extremes.” To reveal the patterns of how climate extremes influence terrestrial carbon fluxes, we analyzed the interannual variations in ecosystem carbon fluxes simulated by the Terrestrial Biosphere Models (TBMs) in the Inter‐Sectoral Impact Model Intercomparison Project. At the global level, TBMs simulated reduced ecosystem net primary productivity (NPP; 18.5 ± 9.3 g C m −2 yr −1 ), but enhanced heterotrophic respiration (Rh; 7 ± 4.6 g C m −2 yr −1 ) during extremely hot events. TBMs also simulated reduced NPP (60.9 ± 24.4 g C m −2 yr −1 ) and reduced Rh (16.5 ± 11.4 g C m −2 yr −1 ) during extreme dry events. Influences of precipitation extremes on terrestrial carbon uptake were larger in the arid/semiarid zones than other regions. During hot extremes, ecosystems in the low latitudes experienced a larger reduction in carbon uptake. However, a large fraction of carbon extremes did not occur in concert with either temperature or precipitation extremes. Rather these carbon extremes are likely to be caused by the interactive effects of the concurrent temperature and precipitation anomalies. The interactive effects showed considerable spatial variations with the largest effects on NPP in South America and Africa. Additionally, TBMs simulated a stronger sensitivity of ecosystem productivity to precipitation than satellite estimates. This study provides new insights into the complex ecosystem responses to climate extremes, especially the emergent properties of carbon dynamics resulting from compound climate extremes.

Arbuscular mycorrhizal (AM) symbiosis, established between AM fungi (AMF) and roots of higher plants, occurs in most terrestrial ecosystems. It has been well demonstrated that AM symbiosis can improve plant performance under various environmental stresses, including drought stress. However, the molecular basis for the direct involvement of AMF in plant drought tolerance has not yet been established. Most recently, we cloned two functional aquaporin genes, GintAQPF1 and GintAQPF2, from AM fungus Glomus intraradices. By heterologous gene expression in yeast, aquaporin localization, activities and water permeability were examined. Gene expressions during symbiosis in expose to drought stress were also analyzed. Our data strongly supported potential water transport via AMF to host plants. As a complement, here we adopted the monoxenic culture system for AMF, in which carrot roots transformed by Ri-T DNA were cultured with Glomus intraradices in two-compartment Petri dishes, to verify the aquaporin gene functions in assisting AMF survival under polyethylene glycol (PEG) treatment. Our results showed that 25% PEG significantly upregulated the expression of two aquaporin genes, which was in line with the gene functions examined in yeast. We therefore concluded that the aquaporins function similarly in AMF as in yeast subjected to osmotic stress. The study provided further evidence to the direct involvement of AMF in improving plant water relations under drought stresses.

Changes in the land use/cover alter the Earth system processes and affect the provision of ecosystem services, posing a challenge to achieve sustainable development. In the past few decades, the Yellow River (YR) basin faced enormous social and environmental sustainability challenges associated with environmental degradation, soil erosion, vegetation restoration, and economic development, which makes it important to understand the long-term land use/cover dynamics of this region. Here, using three decades of Landsat imagery (17,080 images) and incorporating physiography data, we developed an effective annual land use/cover mapping framework and provided a set of 90 m resolution continuous annual land use/cover maps of the YR basin from 1986 to 2018 based on the Google Earth Engine and the Classification and Regression Trees algorithm. The independent random sampling validations based on the field surveys (640 points) and Google Earth (3456 points) indicated that the overall accuracy of these maps is 78.3% and 80.0%, respectively. The analysis of the land system of the YR basin showed that this region presents complex temporal and spatial changes, and the main change patterns include no change or little change, cropland loss and urban expansion, grassland restoration, increase in orchard and terrace, and increase in forest during the entire study period. The major land use/cover change has occurred in the transitions from forests, grasslands, and croplands to the class of orchard and terrace (19.8% of all change area), which not only increase the greenness but also raised the income, suggesting that YR progress towards sustainable development goals for livelihood security, economic growth, and ecological protection. Based on these data and analysis, we can further understand the role of the land system in the mutual feedback between society and the environment, and provide support for ecological conservation, high-quality development, and the formulation of sustainable management policies in this basin, highlighting the importance of continuous land use/cover information for understanding the interactions between the human and natural systems.

) of YH decreased from 2.51 to 1.31, which meant YH had an obvious maturity effect. These results highlighted the potential application of YH in composting kitchen waste.

This study demonstrates that rare earth oxide nanoparticles can enhance soil microbial antibiotic resistance by inducing the enrichment and spread of antibiotic resistance genes in soil microbial communities.

The assessment of ecological environmental quality (EEQ) has provided an important knowledge base for protecting human health and realizing sustainable development. Previous studies have often used only principal component analysis (PCA) to perform the EEQ evaluation by determining the remote sensing based ecological index (RSEI) in a single year, and the assessment results are not comparable between years. Thus, a comparable and accurate method needs to be found and applied. In this paper, we applied the PCA combined with a random forest algorithm (a machine learning algorithm) to quantify the EEQ of Beijing, China, in 2014 and 2020 and analysed the relationship between the RSEI and four ecological indicators (greenness, wetness, dryness and heat). The results suggested that the RSEI and the ecological indicators of Beijing all changed substantially from 2014 to 2020, and the method of combining PCA and random forest was suitable for calculating the time-series data of RSEI in the study period. Specifically, the RSEI in Beijing increased slightly from 0.31 to 0.33 overall, the greenness of Beijing increased drastically (26.09%), the wetness decreased by 10.00%, and the dryness and heat increased by 8.62% and 2.00%, respectively. The Pearson correlation coefficient test showed that both the greenness and wetness had positive effects on the RSEI, while the dryness and heat had negative effects. Of the four ecological indicators in Beijing, the greenness contributed greatly as the main positive factor, and dryness was the most negative factor during the six years. This paper developed an improved framework for continuous EEQ monitoring, and these results provide a scientific basis for the sustainable development and ecological environmental monitoring of Beijing and other megacities.

Abstract. Production and application to soils of manure excreta from livestock farming significantly perturb the global nutrient balance and result in significant greenhouse gas emissions that warm the earth's climate. Despite much attention paid to synthetic nitrogen (N) fertilizer and manure N applications to croplands, spatially explicit, continuous time-series datasets of manure and fertilizer N inputs on pastures and rangelands are lacking. We developed three global gridded datasets at a resolution of 0.5∘ × 0.5∘ for the period 1860–2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer and N manure application rates), by combining annual and 5 arcmin spatial data on pastures and rangelands with country-level statistics on livestock manure, mineral and chemical fertilizers, and land use information for cropland and permanent meadows and pastures. Based on the new data products, we estimated that total N inputs, the sum of manure N deposition, manure N application and fertilizer N application to pastures and rangelands, increased globally from 15 to 101 Tg N yr−1 during 1860–2016. In particular during the period 2000–2016, livestock manure N deposition accounted for 83 % of the total N inputs, whereas manure and fertilizer N application accounted 9 % and 8 %, respectively. At the regional scale, hotspots of manure N deposition remained largely similar during the period 1860–2016 (i.e., southern Asia, Africa and South America); however, hotspots of manure and fertilizer N application shifted from Europe to southern Asia in the early 21st century. The new three global datasets contribute to the filling of the previous data gaps of global and regional N inputs in pastures and rangelands, improving the abilities of ecosystem and earth system models to investigate the global impacts of N enrichment due to agriculture, in terms of associated greenhouse gas emissions and environmental sustainability issues. Datasets are available at https://doi.org/10.1594/PANGAEA.892940.

The influence of the human gut microbiota on the bioaccessibility and bioavailability of trace elements in vegetables has barely been studied. An in vitro digestion model combining the physiologically based extraction test (PBET) and the Simulator of Human Intestinal Microbial Ecosystem (SHIME) was applied. Results showed that the gut microbiota increased the bioaccessibility of iron (Fe) in ten test vegetables by 1.3-1.8 times, but reduced the bioaccessibility of manganese (Mn), copper (Cu), and zinc (Zn) in vegetables in the colon phase by 3.7% to 89.6%, 24.8% to 100.0%, and 59.9% to 100.0%, respectively. Using the Caco-2 cell model to simulate the human absorption process, the bioavailable contents and the bioavailability of the trace elements were further determined. Swamp cabbage was the best source of Fe and Cu; spinach and lettuce provided the highest amounts of bioavailable Mn and Zn, respectively. Referring to the daily reference intakes of trace elements, the obtained data provide a scientific basis for both reasonable ingestion of vegetables in diets and diversification of diets.

Abstract The biogeochemical processes of carbon (C), nitrogen (N), and phosphorous (P) are fully coupled in the Earth system, which shape the structure, functioning, and dynamics of terrestrial ecosystems. However, the representation of P cycle in terrestrial biosphere models (TBMs) is still in an early stage. Here we incorporated P processes and C‐N‐P interactions into the C‐N coupled Dynamic Land Ecosystem Model (DLEM‐CNP), which had a major feature of the ability in simulating the N and P colimitation on vegetation C assimilation. DLEM‐CNP was intensively calibrated and validated against daily or annual observations from four eddy covariance flux sites, two Hawaiian sites along a chronosequence of soils, and other 13 tropical forest sites. The results indicate that DLEM‐CNP significantly improved simulations of forest gross and net primary production ( R 2 : 0.36–0.97, RMSE:1.1–1.49 g C m −2 year −1 for daily GPP at eddy covariance flux sites; R 2 = 0.92, RMSE = 176.7 g C m −2 year −1 for annual NPP across 13 tropical forest sites). The simulations were also consistent with field observations in terms of biomass, leaf N:P ratio and plant response to fertilizer addition. A sensitivity analysis suggests that simulated results are reasonably robust against uncertainties in model parameter estimates and the model was very sensitive to parameters of P uptake. These results suggest that incorporating P processes and N‐P interaction into terrestrial biosphere models is of critical importance for accurately estimating C dynamics in tropical forests, particularly those P‐limited ones.