Annual Net Primary Production Research Articles

A comparative study on the spatio-temporal patterns and drivers of net primary productivity in three basins across different climate gradients in China

The comparative study on terrestrial net primary productivity in regions across climate gradients may help to better understand ecosystem response to climate change, yet is relatively understudied. Therefore, in this study, we compared the spatio-temporal patterns of net primary productivity during 2010-2019 and identify the different controls in three basins with typical climates in China: the Heihe River Basin with arid and semi-arid climate, Weihe River Basin with semi-arid and semi-humid climate, and Lower Yangtze River Basin with humid climate. Results indicated that the net primary productivity followed the order: Lower Yangtze River Basin (480.3 g C m−2 yr−1) > Weihe River Basin (346.7 g C m−2 yr−1) > Heihe River Basin (98.1 g C m−2 yr−1). The vegetation in the Heihe River Basin had severel hydrothermal limitation as the greatest importance of temperature and precipitation to the net primary productivity. In contrast, land cover type instead of climate became the most important variable on net primary productivity in the Weihe River Basin, and topography and land cover type were critical controls in the Lower Yangtze River Basin. In addition, the annual net primary productivity in all three areas exhibited an increasing trend during 2010-2019. However, the increase of net primary productivity in the Heihe River Basin was primarily driven by the increase of both temperature and precipitation due to the warming and humification in the northwestern of China. In contrast, the increase of temperature (especially spring warming) dominated the increase of net primary productivity in the Weihe River Basin and Lower Yangtze River Basin, due to the relatively sufficient precipitation. Furthermore, monthly net primary productivity exhibited a unimodal curve throughout the year. However, the increasing trend nearly stopped in June and July in the Lower Yangtze River Basin. This is possibly due to the light deficiency with abundant precipitation for plant photosynthesis in the natural ecosystem like forest and shrubland, and the rotation from wheat harvesting to rice planting in the cropland in these months.

Exploring the relationship between sea ice and phytoplankton growth in the Weddell Gyre using satellite and Argo float data

Abstract. Some of the highest rates of primary production across the Southern Ocean occur in the seasonal ice zone (SIZ), making this a prominent area of importance for both local ecosystems and the global carbon cycle. There, the annual advance and retreat of ice impacts light and nutrient availability, as well as the circulation and stratification, thereby imposing a dominant control on phytoplankton growth. In this study, the drivers of variability in phytoplankton growth between 2002–2020 in the Weddell Gyre SIZ were assessed using satellite net primary production (NPP) products alongside chlorophyll-a and particulate organic carbon (POC) data from autonomous biogeochemical floats. Although the highest daily rates of NPP are consistently observed in the continental shelf region (water depths shallower than 2000 m), the open-ocean region's larger size and longer ice-free season mean that it dominates biological carbon uptake within the Weddell Gyre, accounting for 93 %–96 % of the basin's total annual NPP. Variability in the summer maximum ice-free area is the strongest predictor of inter-annual variability in total NPP across the Weddell Gyre, with greater ice-free area resulting in greater annual NPP, explaining nearly half of the variance (R2=42 %). In the shelf region, the return of sea ice cover controls the end of the productive season. In the open ocean, however, both satellite NPP and float data show that a decline in NPP occurs before the end of the ice-free season (∼ 80 to 130 d after sea ice retreat). Evidence of concurrent increases in float-observed chlorophyll-a and POC suggest that later in the summer season additional factors such as micro-nutrient availability or top-down controls (e.g. grazing) could be limiting NPP. These results indicate that in a warmer and more ice-free Weddell Gyre, notwithstanding compensating changes in nutrient supply, NPP is likely to be enhanced only up to a certain limit of ice-free days.

Shrub Age and Water Dynamics Influence Primary Production, Carbon, and Nitrogen Stocks in a Coastal Environment

Drivers of shrub primary production and associated landscape impacts of encroachment are well known in drylands but have not been thoroughly studied in mesic and coastal habitats. The native, nitrogen-fixing shrub, Morella cerifera, has expanded into coastal grassland along the US Atlantic coast due to warming temperatures, but impacts on ecosystem function are not well known. Annual net primary production (ANPP) of Morella cerifera and key environmental drivers were measured long-term (1990 – 2007) across a chronosequence of shrub age on a mid-Atlantic barrier island. Soil and groundwater nutrients were compared with un-encroached grassland soil to evaluate impacts of vegetation on nutrient dynamics. Shrub ANPP declined with age at the same rate among all thickets, but there was variability from year to year. When climate variables were included in models, shrub age, precipitation, and freshwater table depth were consistent predictors of ANPP. Water table depth decreased over time, reducing ANPP. This may be due to rising sea-level, as well as to feedbacks with shrub age and evapotranspiration. Soil N and C increased with shrub age and were higher than adjacent grassland sites; however, there was a significant loss of N and C to groundwater. Our results demonstrate that drivers influencing the encroachment of shrubs in this coastal system (i.e., warming temperature) are not as important in predicting shrub primary production. Rather, interactions between shrub age and hydrological properties impact ANPP, contributing to coastal carbon storage.

Climate change causes spatial shifts in the productivity of agricultural long-term field experiments

Long-term field experiments (LTE) are highly valuable infrastructures in agricultural- and soil sciences for understanding the long-term impacts of climate and management practices. While they are designed to run under constant conditions, climate change is expected to affect site conditions considerably. This needs to be quantified when interpreting experimental results and when redesigning the experimental setup. One way to achieve this is by utilizing vegetation growth and carbon dynamics, specifically the Net Primary Productivity (NPP), as a spatially explicit indicator. NPP facilitates the assessment and interpretation of yield performance in LTEs under future climatic conditions. Our study estimated the changes in NPP for 271 LTE sites in Germany, comparing a baseline (2000–2020) with two scenarios (2081–2100) that were based on the Shared Socioeconomic Pathways (SSPs) (SSP245) and SSP585) by the Intergovernmental Panel on Climate Change (IPCC). We used the NASA-CASA biogeochemical model to calculate NPP in baseline and IPCC scenarios using Germany as a test case. LTEs were grouped by land use (crop types) and soil information (soil type, texture), drawing on the geodata infrastructure “BonaRes Repository”. The total annual terrestrial NPP for the baseline was calculated as 202.4 Mt C (sum of forests, grasslands, and arable lands) in Germany, while total NPP was up to 56.0 Mt C for different land use types. For both scenarios, NPP was projected to increase in LTEs located in southern Germany, indicating increased crop productivity, while a decrease was projected for the central Germany. The decrease in NPP of numerous LTEs in central Germany was estimated to extend to the LTEs in the eastern part corresponding to the worst-case scenario SSP585. Explicitly, the use of the multi-model ensemble mean as the climate driver in modelling may overestimate projected NPP by reducing inter-annual variability, highlighting the importance of methodological choices for accurate future projections. Besides, the results indicated that poor soils are projected to experience a further decline in productivity, primarily attributed to escalating water scarcity. Conversely, soils with high quality are likely to witness enhanced productivity, largely driven by the extension of the growing seasons. The outcomes of this study provide a basis for considering the future conditions of German LTEs and facilitate distinguishing between the effects of climate change and the impact of agricultural management on productivity at the regional level. These outputs enable planning and developing research strategies for selecting future LTE sites and redesigning existing or newly planned experiments. Moreover, the integrated modelling framework presented here highlights the potential of LTE data for large-scale modelling studies of ecosystem functions.

Increased leaf area index and efficiency drive enhanced production under elevated atmospheric [CO2 ] in a pine-dominated stand showing no progressive nitrogen limitation.

Enhancement of net primary production (NPP) in forests as atmospheric [CO2 ] increases is likely limited by the availability of other growth resources. The Duke Free Air CO2 Enrichment (FACE) experiment was located on a moderate-fertility site in the southeastern US, in a loblolly pine (Pinus taeda L.) plantation with broadleaved species growing mostly in mid-canopy and understory. Duke FACE ran from 1994 to 2010 and combined elevated [CO2 ] (eCO2 ) with nitrogen (N) additions. We assessed the spatial and temporal variation of NPP response using a dataset that includes previously unpublished data from 6 years of the replicated CO2  × N experiment and extends to 2 years beyond the termination of enrichment. Averaged over time (1997-2010), NPP of pine and broadleaved species were 38% and 52% higher under eCO2 compared to ambient conditions. Furthermore, there was no evidence of a decline in enhancement over time in any plot regardless of its native site quality. The relation between spatial variation in the response and native site quality was suggested but inconclusive. Nitrogen amendments under eCO2 , in turn, resulted in an additional 11% increase in pine NPP. For pine, the eCO2 -induced increase in NPP was similar above- and belowground and was driven by both increased leaf area index (L) and production efficiency (PE = NPP/L). For broadleaved species, coarse-root biomass production was more than200% higher under eCO2 and accounted for the entire production response, driven by increased PE. Notably, the fraction of annual NPP retained in total living biomass was higher under eCO2 , reflecting a slight shift in allocation fraction to woody mass and a lower mortality rate. Our findings also imply that tree growth may not have been only N-limited, but perhaps constrained by the availability of other nutrients. The observed sustained NPP enhancement, even without N-additions, demonstrates no progressive N limitation.

Decadal forest mensuration cycle significantly underestimates net primary production in dense young beech stands

The early development of naturally regenerated forest stands is highly dynamic and includes rapid shifts in productivity and mortality. To characterise the growth dynamics in the initial decades, we assessed aboveground biomass stocks (Sab),aboveground biomass productivity (DPab), and aboveground biomass mortality (DMab) in five naturally regenerated European beech stands located in the Inner Western Carpathians. We developed allometric models for aboveground biomass compartments based on a sample of 262 trees. We also established five circular sampling plots within each stand and, for 15 years, carried out annual measurements of stem diameter at the base and height for all trees within the sampling plots. We then utilised the allometric models to calculate annual biomass accumulation in aboveground biomass compartments on an area basis. Our findings show that, despite the declining contribution of foliage to the total aboveground stock, about a quarter of annual net primary production in young beech stands enters the dead biomass pool due to leaf fall and tree mortality. The growth dynamics and biomass allocation patterns of young beech forests necessitate the development of specific allometric models to describe their growth and carbon capture processes.

Vertical stratification of phytoplankton biomass in a deep estuary site: implications for satellite-based net primary productivity

The accuracy of satellite estimates for water column net primary productivity (NPP) are contingent upon the reliability of surface phytoplankton biomass, specifically chlorophyll a (Chl.a) and carbon (Cphyt), as indicators of euphotic biomass and photosynthetic rate. We assessed patterns in water column biomass at a deep estuary site (~40 m) in the Firth of Thames, Hauraki Gulf, New Zealand, using ten years (2005-2015) of in situ sampling (40 seasonal voyages and moored instrumentation). Seasonal biomass stratification coincided with physical and chemical stratification and exhibited a reasonable predictability based on surface Chl.a measures from mooring timeseries. High Chl.a (but not Cphyt) accumulated from late-spring (Nov.) in the lower portion of the water column, under nutrient deficient, clear surface water with deep euphotic zone conditions, peaking in mid-summer (Jan.) and ending by early autumn (Mar.). Satellite (MODIS-Aqua) NPP (2002-2018), was estimated with and without correction for deep biomass in two vertically generalized production models (Chl.a-VGPM and Cphyt-CbPM). Mean annual NPP (220-161 g C m-2 y-1, VGPM and CbPM respectively) increased 5-18% after accounting for euphotic zone deep biomass with a mid-summer maxim (Jan.: 30-33%). Interannual anomalies in biomass and NPP (about -10% to 10%) were an order of magnitude greater than small decreasing trends (<< 1% y-1). We discuss the impacts of observational factors on biomass and NPP estimation. We offer contextual insights into seasonal patterns by considering previous observations of biomass trends and nutrient enrichment in the Firth of Thames region. We propose future directions in accounting for deep biomass variations from shallow coastal areas to deeper continental shelf waters.

Interannual Variations in Terrestrial Net Ecosystem Productivity and Climate Attribution in the Southern Hilly Region of China.

The vegetation ecosystem in the southern hilly region of China (SHRC) plays a crucial role in the country's carbon reservoir. Clarifying the dynamics of net primary productivity (NPP) in this area and its response to climate factors in the context of climate change is important for national forest ecology, management, and carbon neutrality efforts. This study, based on remote sensing and meteorological data spanning the period 2001 to 2021, aims to unveil the spatiotemporal patterns of vegetation productivity and climate factors in the southern hilly region, explore interannual variation characteristics of vegetation productivity with altitude, and investigate the response characteristics of NPP to various climate factors. The results indicate that from 2001 to 2021, the annual average NPP in the southern hilly region had a significant increasing trend of 2.13 ± 0.78 g m-2 a-1. The trend of NPP varies significantly with altitude. Despite a general substantial upward trend in vegetation NPP, regions at lower elevations exhibit a faster rate of increase, suggesting a diminishing difference in the NPP of different elevation ranges. The overall rise in average temperature has positive implications for the southern hilly region, while the impact of precipitation on vegetation NPP demonstrates noticeable spatial heterogeneity. Regions in which vegetation NPP is significantly negatively correlated with precipitation are mainly concentrated in the southern areas of Guangdong, Fujian, and Jiangxi provinces. In contrast, other regions further away from the southeastern coast tend to exhibit a positive correlation. Over the past two decades, there has been an asymmetry in the diurnal temperature variation in the SHRC, with the nighttime warming rate being 1.8 times that of the daytime warming rate. The positive impact of daytime warming on NPP of vegetation is more pronounced than the impact of nighttime temperature changes. Understanding the spatiotemporal patterns of NPP in the SHRC and the characteristics of its response to climate factors contributes to enhancing our ability to protect and manage vegetation resources amidst the challenges of global climate change.

Multi-source data-driven estimation of urban net primary productivity: A case study of Wuhan

Amidst urban expansion, numerous ecological challenges have surfaced, notably the swift alterations in the net primary productivity (NPP), presenting complexities in discerning their scale and spatial distribution. Leveraging meteorological data, multi-modal remote sensing datasets, field sampling data, and a digital elevation model (DEM), this research amalgamates field assessments, model simulations, and cutting-edge remote sensing techniques to craft a city-scale NPP estimation model for vegetation rooted in the Carnegie-Ames-Stanford Approach (CASA). This improved CASA model facilitated the computation of monthly NPP for Wuhan over 2017–2020. Our analysis divulged NPP spatiotemporal trends and distribution nuances in Wuhan, and assessed meteorological influences on the same. Salient conclusions encompass: (1) Wuhan's annual NPP maximum between 984.40 and 1310.51 gC/(m2 a), averaging from 316.78 to 430.32 gC/(m2 a), and culminating in totals from 170.15 to 231.60 × 1010 gC/a. (2) Monthly NPP trajectories in Wuhan exhibited a unimodal pattern: ascending from January to June, peaking in July–August, and tapering off through September-December, with a spatial distribution characterized by lower NPP values centrally and higher values peripherally. (3) Regionally, temperature markedly influenced NPP over precipitation. This research underpins urban ecological planning, offering empirical insights and strategic guidance for fostering a sustainable coexistence between humans and their environment, and charting future urban development paradigms.

A High-Resolution Simulation of Forest Ecosystem Carbon Budget Change with Complex Terrain

Forest ecosystems represent important carbon sinks within terrestrial ecosystems. Simulating carbon budgets in forest ecosystems located within complex terrains forms the foundation for understanding global carbon cycle dynamics. In this study, employing the FORCCHN model and utilizing mountain climate data as forcing parameters, the impact of the terrain factors of the Changbai Mountain Nature Reserve on carbon budget change in 1998–2017 was studied. The dynamics and distribution patterns of carbon fluxes at different slope aspects and elevations were discussed. Findings demonstrated that between 1998 and 2017, the per-unit area gross primary production (GPP), net primary production (NPP), and net ecosystem production (NEP) for the Changbai Mountain Reserve were 839.35, 462.03, and 192.72 gC m −2 a −1 , respectively. The carbon fluxes varied significantly with elevation: the GPP of the north, south, and west and the NPP of the east, south, and west decreased, and the NEP of the south and west increased. The total amount in GPP and NPP of the Changbai Mountain Nature Reserve fluctuated slightly year by year, but the carbon sequestration capacity decreased from year to year. The reserve had an average annual total GPP, NPP, and NEP of 1.62, 0.89, and 0.37 TgC a −1 , respectively. The north was the strongest carbon sink in the study area, contributing 35.98%, 35.88%, and 36.80% to the total amount of GPP, NPP, and NEP, respectively. This study emphasized the significance of precise mountain meteorological data to accurately quantify the carbon fluxes of mountain forest ecosystems.

Soil Organic Carbon Lateral Movement Processes Integrated Into a Terrestrial Ecosystem Model

AbstractLateral movement of soil organic carbon (SOC) induced by soil erosion and runoff changes spatial distributions of SOC, and further changes the land‐atmosphere CO2 exchange and terrestrial carbon budget. However, current ecosystem models do not or only poorly integrate the process of SOC lateral movement and cannot simulate the impacts of soil erosion on the carbon cycle. This study integrated SOC erosion and deposition processes into a process‐based ecosystem model (i.e., Integrated BIosphere Simulator (IBIS)), and separately simulated the lateral movements of dissolved organic carbon (DOC) and particulate organic carbon (POC). The model was evaluated in three river basins in Northeast China that are dominated by cropland, forest, and grassland. The results showed that the model reproduced well the production, erosion, and deposition of DOC and POC. The annual SOC lateral movement (1.34–7.22 g C m−2 yr−1) induced by erosion in the three tested basins was 0.27%–1.45% of the annual net primary production. The model developed in this study has great implications for simulating the lateral movements of SOC in terrestrial ecosystems, which can improve model performance in projecting the terrestrial carbon budget.

Assessing net primary production in the northwestern Barents Sea using in situ, remote sensing and modelling approaches

The northwestern Barents Sea (NW-BS) is a highly productive region within the transitional zones of an Atlantic to Arctic-dominated marine ecosystem. The steep latitudinal gradients in sea ice concentration, Atlantic and Arctic Water, offer an opportunity to test hypotheses on physical drivers of spatial and temporal variability of net primary production (NPP). However, quantifying NPP in such a large ocean region can be challenged by the lack of in situ measurements with high spatial and temporal resolution, and gaps in remote sensing estimates due to the presence of clouds and sea ice, and assumptions regarding the depth distribution of alga biomass. Without reliable data to evaluate models, filling these gaps with numerical models is limited by the model representation of the physical environment and its assumptions about the relationships between NPP and its main limiting factors. Hence, within the framework of the Nansen Legacy Project, we combined in situ measurements, remote sensing, and model simulations to constrain the estimates of phytoplankton NPP in the NW-BS. The region was subdivided into Atlantic, Subarctic, and Arctic subregions on the basis of different phytoplankton phenology. In 2004 there was a significant regime change in the Atlantic subregion that resulted in a step-increase in NPP in tandem with a step-decrease in sea ice concentration. Contrary to results from other Arctic seas, this study does not find any long term trends in NPP despite changes in the physical environment. Mixing was the main driver of simulated annual NPP in the Atlantic subregion, while light and nutrients drove annual NPP in the Subarctic and Arctic subregions. The multi-source estimate of annual NPP ranged 79–118gCm−2yr−1 in the Atlantic, 74–82gCm−2yr−1 in the Subarctic, and 19–47gCm−2yr−1 in the Arctic. The total NPP in the NW-BS region was estimated between 15 and 48TgCyr−1, which is 15–50% of the total NPP needed to sustain three of the most harvested fish species north of 62°N (roughly 90TgCyr−1). This research shows the importance of continuing to strive for better regional estimates of NPP.

Value of Biodiversity on Patagonian Rangeland: Estimation via a Hedonic Price Index

Plant diversity has long been linked to an increase in ecosystem productivity and function, but concrete examples in which ecosystem services are linked to diversity at the scale at which management decisions are taken are rare. We specifically tested for a correlation between plant diversity and provisioning ecosystem services estimated via the potential to produce meat and wool. We also tested whether higher levels of plant diversity conferred higher levels of ecosystem resistance to global change drivers, measured as the ability to sustain productivity across time. This was achieved by analyzing the interactive effects of a range of environmental variables on annual net primary production in a network of long-term biodiversity plots in Southern Patagonia. We found evidence of a positive correlation between plant diversity and plant productivity, which we relate to the ability to produce wool and meat from livestock. We also found evidence of a link between ecosystem resistance and diversity, though the effect was modest. The instrumental (economic) valuation presented doesn't account for the full range of values that rangeland in southern Patagonia generates. Nevertheless, these calculations do provide a starting point for broadening the discussion around the importance and value of natural capital in southern Patagonia. The results are consistent with theory and suggest that plant diversity has instrumental and monetary value as well as insurance value that may increase the resistance of rangeland ecosystems to global change drivers.

The role of climatic factor timing on grassland net primary productivity in Altay, Xinjiang

Grassland, as highly vulnerable ecosystem, requires a comprehensive understanding of its dynamics and response patterns to climate factors in response to climate change challenges. While previous research has primarily centered on the influence of interannual climate variability on grassland Net Primary Productivity (NPP), knowledge of the impacts of seasonal or monthly climate variations on annual net primary productivity (ANPP) remains limited. This study investigated the climatic drivers of grassland NPP dynamics in Xinjiang's Altay region from 2000 to 2022 using the Carnegie-Ames-Stanford approach (CASA) model and the random forest regression model. The study examined the significance and patterns of precipitation, solar radiation, temperature, soil moisture, and snowmelt water on NPP at three temporal scales. The results revealed the following key findings: (1) Grassland NPP declined significantly from 2000 to 2009 but showed a gradual increase from 2009 to 2022. Spatially, higher values were observed in the northern region and lower values were observed in the southern region. (2) Precipitation was the primary influential climate factor affecting grassland NPP, followed by solar radiation, temperature, soil moisture, and snowmelt water. In determining the significance of climate factor timing on ANPP, June played a critical role particularly for precipitation, temperature, and soil moisture, while August was essential for solar radiation. Moreover, the importance of snowmelt water had a bimodal distribution, with peaks in April and October. (3) Grassland NPP exhibited diverse nonlinear response dynamics and spatial heterogeneity to various climate factors at different temporal scales. These findings highlight the importance of considering both the magnitude and the local conditions, as well as the timing of climate variations when studying grassland dynamic responses to climate change and predicting future impacts. These insights enhance the comprehension of the intricate dynamics of grassland ecosystems and enhance predictions of their responses to future climate change.

Characteristics of carbon sources and sinks and their relationships with climate factors during the desertification reversal process in Yulin, China

Research on carbon sources/sinks in desert ecosystems is of great importance to understand the carbon cycle and its response to climate change. Net primary productivity (NPP) and net ecosystem productivity (NEP) are the two most important indictors for quantitatively evaluating carbon storage and can be used to indicate the response of terrestrial ecosystems to climate change. In this study, we used remote sensing data, meteorological data and vegetation type data to estimate the NPP and NEP using CASA model and soil respiration model from 2000 to 2020 in the region of Yulin, which is a typical desertification reversal region in the Mu Us Sandy Land. The spatial and temporal features of the NPP and NEP and their relationships with temperature and precipitation were determined. The results showed that both the annual NPP and NEP showed an increasing trend from 2000 to 2020 in the region of Yulin, where the terrestrial ecosystem acted as a carbon source until 2001 but turned into a sink thereafter. The carbon storage showed an increasing trend with a rate of 0.50 Tg C·a−1 from 2000 to 2020. Both the mean annual NPP and the total NEP increased from the west to the east of the region in spatial distribution. The total NEP indicated that the area with a carbon sink accounted for 89.22% of the total area, showing a carbon accumulation of 103.0 Tg C, and the carbon source area accounted for 10.78% of the total area with a carbon emission of 4.40 Tg C. The net carbon sequestration was 99.44 Tg C in the region of Yulin during the period from 2000 to 2020. Temperature had no significant effects on NPP and NEP for most areas of the region, while precipitation had a positive effect on the increasing NPP in 75.3% of areas and NEP in 30.07% of areas of the region. These results indicated that it is of utmost significance to protect terrestrial ecosystems from degradation, and ecological restoration projects are essential in combating desertification, which would be helpful for soil water conservation and could effectively increase carbon storage in desert ecosystems.

Spatial–Temporal Variation Characteristics and Driving Factors of Net Primary Production in the Yellow River Basin over Multiple Time Scales

Vegetation net primary productivity (NPP) serves as a crucial and intuitive indicator for assessing ecosystem health. However, the nonlinear dynamics and influencing factors operating at various time scales are not yet fully understood. Here, the ensemble empirical mode decomposition (EEMD) method was used to analyze the spatiotemporal patterns of NPP and its association with hydrothermal factors and anthropogenic activities across different temporal scales for the Yellow River Basin (YRB) from 2000 to 2020. The results indicate that: (1) the annual average NPP was 236.37 g C/m2 in the YRB and increased at rates of 4.64 g C/m2/a1 (R2 = 0.86, p < 0.01) during 2000 to 2020. Spatially, nonlinear analysis indicates that 72.77% of the study area exhibits a predominantly increasing trend in NPP, while 25.17% exhibits a reversing trend. (2) On a 3-year time scale, warming has resulted in an increase in NPP in the majority of areas of the study area (69.49%). As the time scale widens, the response of vegetation to climate change becomes more prominent; especially under the long-term trend, the percentage areas of the correlation between vegetation and precipitation and temperature increased with significance, reaching 48.21% and 11.57%, respectively. (3) Through comprehensive time analysis and multivariate regression analysis, it was confirmed that both human activities and climate factors had comparable impacts on vegetation growth. Among different vegetation types, climate was still the main factor affecting grassland NPP, and only 15.74% of grassland was affected by human activities. For shrubland, forest, and farmland, human activity was a dominating factor for vegetation NPP change. There are still few studies on vegetation change using nonlinear methods in the Yellow River Basin, and most studies have not considered the effect of time scale on vegetation evolution. The findings highlight the significance of multi-time scale analysis in understanding the vegetation dynamics and providing scientific guidance for future vegetation restoration and conservation efforts.

Regional Contribution and Attribution of the Interannual Variation of Net Primary Production in the Yellow River Basin, China

Net primary production (NPP) serves as a crucial indicator of the ecosystem’s capacity to capture atmospheric CO2. Gaining insights into the dynamics of NPP and its driving mechanisms is pivotal for optimizing ecosystem carbon sink resource management. Since the implementation of the Grain-for-Green Program (GFGP) in 1999, the Yellow River Basin (YRB) has been one of the most significant areas for ecological restoration in China. However, our knowledge regarding the interannual variability (IAV) of NPP and the underlying driving forces in this region remains incomplete. In this study, we utilized a light use efficiency model to assess the spatiotemporal dynamics, IAV, and driving factors of NPP in the YRB during the period from 1999 to 2018. Our findings revealed that the average annual NPP in the YRB approximated 189.81 Tg C. Over the study duration, NPP significantly increased in 79.63% of the basin with an overall increasing rate of 6.76 g C m−2 yr−1. The most prominent increase was observed in the key GFGP implementation area, predominantly in the semi-humid region. Notably, the middle altitude region (1–1.5 km), semi-humid region, and grassland emerged as the primary contributors to the basin’s total vegetation carbon sequestration. However, it is worth emphasizing that there was substantial IAV in the temporal trends of NPP, with the semi-humid region being the most influential contributor (62.66%) to the overall NPP IAV in the YRB. Further analysis of the driving mechanisms unveiled precipitation as the primary driver of NPP IAV in the YRB with a contribution of 62.9%, followed by temperature (23.07%) and radiation (14.03%). Overall, this study deepened our understanding of the IAV and driving mechanisms of NPP in the YRB under ecological restoration, and provided scientific support for optimizing the management of regional carbon sequestration resources.

Spatiotemporal variations of leaf senescence velocity on the Tibetan Plateau grasslands

Leaf senescence plays a pivotal role in the regulation of carbon and nutrient cycles within terrestrial ecosystems. However, our understanding of leaf senescence velocity (LSV) remains comparatively limited when compared to the end of the growing season (EOS). In this study, we extracted the LSV in Tibet Plateau (TP) over the period 2001–2018 based on the satellite-derived normalized difference greenness index (NDGI), then we evaluated the influences of climate drivers on the spatio-temporal variations of LSV. Lastly, we explored the implications of LSV on vegetation growth by analyzing the correlation between LSV and the start of growing season (SOS) and the annual net primary production (NPP). Our findings revealed that the multi-year averaged LSV ranged from 30 to 70% mon-1 and displayed a discernible spatial gradient, declining from west to east, and the spatial pattern of LSV was mainly controlled by radiation. Trend tests and partial correlation analyses unveiled a temporal decrease in LSV within the central TP region, attributed to rising temperatures, while an increase was observed in the southwestern TP due to water deficits. We also found that LSV had a strong impact on current-year net NPP and following-year SOS. This suggests that LSV may play a significant role in regulating carbon exchange during the current year and influencing the onset of spring green-up in the subsequent year. By emphasizing the continuous nature of leaf senescence, our study provides fresh insights into the intricate interactions between vegetation growth and climate change, contributing to the existing body of knowledge in this field.

Temporal and Spatial Evolution, Prediction, and Driving-Factor Analysis of Net Primary Productivity of Vegetation at City Scale: A Case Study from Yangzhou City, China

Net primary productivity (NPP) is an important index with which to evaluate the safety and quality of regional carbon sinks. Based on the improved CASA model, climate data, social data, remote-sensing ecological data, and other multi-source data types, this article took a Chinese city, Yangzhou, as the research object, used Theil–Sen medium-trend analysis and the Hurst index to analyze its spatial–temporal-evolution characteristics and future change trends, and used geographical detectors to analyze the impact of climate, social, ecological, and other factors on the change in NPP in the study area, with the intention of providing a theoretical exploration and practical basis for achieving the “dual carbon” goals in the region. The results showed that the annual average NPP levels of the vegetation in Yangzhou in the five sampling years were 445.343 gc/m2·a, 447.788 gc/m2·a, 427.763 gc/m2·a, 398.687 gc/m2·a, and 420.168 gc/m2·a, respectively, exhibiting a trend that first decreases and then increases, with a slight overall decrease from 2000 to 2020. The area in which the vegetation in Yangzhou had the higher grades of NPP increased by 203,874 km², and an increase of 321,769 km² in the lower levels was observed. The NPP level of vegetation showed polarization, with relatively high levels in the surrounding farmland and mountain–forest areas and relatively low levels in densely populated urban areas. The ranking was highest in Baoying and lowest in Gaoyou. From the average NPP of all the land types in the study area, the following trend was exhibited: forest land > farmland > bare soil > impermeable surface > water. The future change in vegetation NPP in Yangzhou City will mainly follow the trend of the past 20 years, with a slow decrease. The NDVI (q = 0.728) and LUCC (q = 0.5601) were the leading driving factors of vegetation NPP change in Yangzhou City, and the interaction effect of double driving factors was greater than that of single driving factors.

Synechococcus nitrogen gene loss in iron-limited ocean regions

Synechococcus are the most abundant cyanobacteria in high latitude regions and are responsible for an estimated 17% of annual marine net primary productivity. Despite their biogeochemical importance, Synechococcus populations have been unevenly sampled across the ocean, with most studies focused on low-latitude strains. In particular, the near absence of Synechococcus genomes from high-latitude, High Nutrient Low Chlorophyll (HNLC) regions leaves a gap in our knowledge of picocyanobacterial adaptations to iron limitation and their influence on carbon, nitrogen, and iron cycles. We examined Synechococcus populations from the subarctic North Pacific, a well-characterized HNLC region, with quantitative metagenomics. Assembly with short and long reads produced two near complete Synechococcus metagenome-assembled genomes (MAGs). Quantitative metagenome-derived abundances of these populations matched well with flow cytometry counts, and the Synechococcus MAGs were estimated to comprise >99% of the Synechococcus at Station P. Whereas the Station P Synechococcus MAGs contained multiple genes for adaptation to iron limitation, both genomes lacked genes for uptake and assimilation of nitrate and nitrite, suggesting a dependence on ammonium, urea, and other forms of recycled nitrogen leading to reduced iron requirements. A global analysis of Synechococcus nitrate reductase abundance in the TARA Oceans dataset found nitrate assimilation genes are also lower in other HNLC regions. We propose that nitrate and nitrite assimilation gene loss in Synechococcus may represent an adaptation to severe iron limitation in high-latitude regions where ammonium availability is higher. Our findings have implications for models that quantify the contribution of cyanobacteria to primary production and subsequent carbon export.