Variability Of Primary Production Research Articles

Tropical ocean teleconnections with gross primary productivity of monsoon-Asia

The intricate oceanic climate interactions with terrestrial primary production of Asian ecosystems exert crucial social-economical-environmental repercussions. Yet, a holistic understanding of tropical sea surface temperature (SST) anomalies associated with the gross primary productivity (GPP) variations of monsoon-Asia remains constrained. This study provides a statistical framework demonstrating how SST perturbations in the tropics influence GPP fluctuations in monsoon-Asia by modulating hydrothermal conditions of different climate system components. Observation evidence explicitly illustrated the characteristic anomalous SST signatures of positive and negative GPP anomalies in South and Southeast Asia during June–August. The SST anomalies of the central-eastern tropical Pacific showed a robust negative impact on the GPP variability of South-Asia. The GPP alterations in maritime-Southeast-Asia exhibited strong connections with SST anomalies of the western Pacific (positive) and eastern equatorial Pacific (negative). The oceanic signals in the GPP variability of South-Asia and maritime-Southeast-Asia mirrored canonical El Niño and La Niña patterns. The detected SST–GPP link is feasible through large-scale atmospheric circulation variability and the consequent regional modulation of heat and moisture fluxes. The anomalous strengthening (weakening) of Walker cell enhances (reduces) water availability to plants for photosynthesis during the La Niña (El Niño) phase of the ENSO cycle and thus elevates (lowers) GPP in South-Asia and Maritime-southeast-Asia. In contrast, the enhanced GPP anomaly in mainland-Southeast-Asia depicts signs of canonical La Niña and Indian Ocean subtropical dipole (IOSD) teleconnections. The positive impact of IOSD was through the modulation of the Mascarene High and the consequent impact on the monsoon. Meanwhile, decreased GPP bears the imprint of El Niño Modoki and warm tropical Indian Ocean SSTs. The atmospheric teleconnections demonstrated the delayed impact of El Niño Modoki on GPP variability through the Indian Ocean capacitor effect. Our findings could be instrumental in forecasting the probable effects on vegetation growth in monsoon-Asia associated with high-frequency tropical oceanic changes.

Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPPmax) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p < 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPPspr) had a significantly increasing trend (p < 0.01), and the earlier SOS had obvious positive effects on GPPspr. Summer GPP (GPPsum) was significantly and negatively correlated to POS (p < 0.05). In addition, GPPmax had a significant and positive correlation with GPPsum and GPPann (p < 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming.

Dynamics of Carbon and Water Fluxes over Cropland and Agroforest Ecosystems on the Southern Chinese Loess Plateau

Studies on the spatiotemporal dynamics in ecosystem carbon and water exchanges are essential in predicting the effects of climate change on regional carbon and energy budgets. Using the eddy covariance technique, carbon and water fluxes were observed in a typical winter wheat ecosystem (WWE) and an agroforest ecosystem (AFE) in the southern Loess Plateau from 2004 to 2010. The seasonal and inter-annual variability in gross primary productivity (GPP), net ecosystem exchange (NEE), evapotranspiration (ET), and water use efficiency (WUE) were examined and the main influencing factors were identified using the Pearson correlation. The results indicate that the seasonal GPP and NEE showed a bimodal distribution in WWE, while this was unimodal in AFE. The sinusoidal function did well in the characterization of seasonal ET dynamics for both ecosystems, with the determination coefficients being 0.85 and 0.94, respectively. In WWE and AFE, the annual mean GPP were 724.33 and 723.08 g C m−2 a−1, respectively, and the corresponding ET were 392.22 and 410.02 mm a−1. However, the difference in NEE between the two ecosystems was obvious, NEE were −446.28 and −549.08 g C m−2 a−1, respectively, showing a stronger carbon sink in AFE. There were strong coupling relationships between the GPP and ET of both ecosystems; the overall slopes were 1.71 and 1.69, respectively. The seasonal trend of WUE was bimodal in WWE, with peak values of 3.94 and 3.65 g C kg−1 H2O, occurring in November and April, respectively. However, the monthly WUE in AFE had one single peak of 4.07 g C kg−1 H2O in January. Photosynthetically active radiation (PAR) and soil temperature (Ts) were most positively correlated with GPP, net radiation (Rn) and Ts were the major factors influencing ET, while vapor pressure deficit (VPD) and soil water content (SWC) were the major influencing factors for WUE. These results provide observational support for regional carbon neutrality simulations.

Local depositional and diagenetic conditions control the positive δ34S excursion during the Ordovician-Silurian transition: Evidence from the Wufeng-Longmaxi formations in Sichuan Basin

The Ordovician-Silurian (OS) transition was characterized by significant changes in global climate, marine redox conditions, and biological evolution, which include global seawater euxinia, the onset of the Hirnantian glaciation, and large-scale extinctions. During this time, the marine sulfur cycle was disrupted, and the pyrite sulfur isotope (δ34Spy) showed a large positive excursion. This excursion is closely tied to the Hirnantian glaciation, with δ34Spy increasing at the start of and decreasing at the end of the glaciation. Although it is thought that variations in marine sulfate concentration and primary productivity are responsible for the positive excursion in δ34Spy, contemporary marine sediment δ34Spy data suggest that sedimentary processes can also lead to significant fluctuations in δ34Spy. To assess the impact of local changes in sedimentary conditions on this positive δ34Spy excursion event, we conducted detailed depositional and geochemical analyses of sedimentary pyrite found in black shales from the Wufeng-Longmaxi formations in the Weiyuan area of the Sichuan Basin, China. These sedimentary pyrites include three types: framboidal, euhedral, and laminated pyrite. Bulk sample sulfur isotope analyses revealed that δ34Spy values vary from −16.2‰ to 15.8‰ (mean = −3.8‰, n = 22). In situ analyses of δ34Spy show that different pyrite crystals exhibit a range of intragranular δ34Spy values that are likely indicators of diagenesis. Variations in bulk sample δ34Spy are strongly and negatively correlated with the proportion of framboidal pyrite, i.e., lower levels of framboidal pyrite content resulted in a higher bulk sample δ34Spy value, suggesting diagenetic alteration controls on δ34Spy. In addition, the δ34Spy excursion in the Wufeng-Longmaxi formations also appears to be compatible with lithological changes related to sedimentation rate. The δ34Spy values from the Guanyinqiao Bed, which consists of calcareous shales, are higher than those from black shales with a relatively low sedimentation rate. Our results suggest that the positive δ34Spy excursion during the OS transition during the Hirnantian glaciation is controlled not only by diagenetic alterations but also by local sedimentation rate.

Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia

The Hetao Irrigation District in Inner Mongolia, a vital grain-producing region in northern China, faces growing environmental challenges. Studying net primary productivity (NPP) is essential for understanding spatiotemporal vegetation shifts and guiding locally adapted restoration and management efforts. Utilizing MOD17A3/NPP data, this study applies the Theil–Sen median trend, Mann–Kendall significance, and the Hurst index to scrutinize the spatiotemporal distribution patterns of NPP from 2001 to 2021 and forecast future changes in the area. The findings reveal cyclic temporal trends, forming a “∧” shape with initial increases followed by decreases, notably during the July to August period each year. The multi-year average NPP exhibits a slight upward fluctuation trend, averaging 172.40 gCm−2a−1. Peaks occur approximately every three years, reaching the highest average in 2012 at 218.96 gCm−2a−1. Spatially, NPP distribution stays consistent over the years, influenced by various land cover types, especially cropland, shaping the spatial patterns. Monthly and yearly NPP trends over the 21 years indicate a significant decrease in May and June, with other months mostly showing a non-significant increase. The Hurst index for monthly and yearly NPP changes over 21 years shows relatively high weak anti-persistence. In summary, over the past 21 years, the NPP trend in the study area has not significantly improved and is expected to decline in the future. This study offers data support and a scientific foundation for refining the carbon cycle model, quantifying vegetation carbon sequestration capacity, addressing climate change policies, and striving for carbon peak and neutrality in the Hetao Irrigation District.

Spatiotemporal variation and response of gross primary productivity to climate factors in forests in Qiannan state from 2000 to 2020

Accurate estimation of terrestrial gross primary productivity (GPP) is essential for quantifying the carbon exchange between the atmosphere and biosphere. Light use efficiency (LUE) models are widely used to estimate GPP at different spatial scales. However, difficulties in properly determining the maximum LUE (LUEmax) and downregulation of LUEmax into actual LUE result in uncertainties in the LUE-estimated GPP. The recently developed P model, a new LUE model, captures the adaptability of vegetation to the environment and simplifies parameterization. Site-level studies have proven the superior performance of the P model over LUE models. As a representative karst region with significant changes in forest cover in Southwest China, Qiannan is useful for exploring the spatiotemporal variation in forest GPP and its response to climate change for formulating forest management policies to address climate changes, e.g., global warming. Based on remote sensing and meteorological data, this study estimated the forest ecosystem GPP in Qiannan from 2000–2020 via the P model. This study explored the spatiotemporal changes in GPP in the study region over the past 20 years, used the Hurst index to predict future development trends from a time series perspective, and used partial correlation analysis to analyse the spatiotemporal GPP changes over the past 20 years in response to three factors: temperature, precipitation, and vapor pressure deficit (VPD). Our results showed that (1) the total amount of GPP and average GPP in Qiannan over the past 21 years (2000–2020) were 1.9 × 104 ± 2.0 × 103 MgC ha−1 year−1 and 1238.9 ± 107.9 gC m−2 year−1, respectively. The forest GPP generally increased at a rate of 6.1 gC m−2 year−1 from 2000 to 2020 in Qiannan, and this increase mainly occurred in the nongrowing season. (2) From 2000 to 2020, the forest GPP in Qiannan was higher in the southeast and lower in the northwest, indicating significant spatial heterogeneity. In the future, more than 70% of regional forest GPP will experience a weak increase in nonsustainability. (3) In Qiannan, forest GPP was positively correlated with both temperature and precipitation, with partial correlation coefficients of 0.10 and 0.11, respectively. However, the positive response of GPP to precipitation was approximately 70.47%, while that to temperature was 64.05%. Precipitation had a stronger restrictive effect on GPP than did temperature in this region, and GPP exhibited a negative correlation with VPD. The results showed that an increase in VPD inhibits GPP to some extent. Under rapid global change, the P model GPP provides new GPP data for global ecology studies, and the comparison of various stress factors allows for improvement of the GPP model in the future. The results of this study will aid in understanding the dynamic processes of terrestrial carbon. These findings are helpful for estimating and predicting the carbon budget of forest ecosystems in karst regions, clarifying the regional carbon absorption capacity, clarifying the main factors limiting vegetation growth in these regions, promoting sustainable regional forestry development and serving the “dual carbon goal.” This work has important guiding significance for policy formulation to mitigate climate change.

Variability of Primary Productivity as an Initial Link in Carbon Flux Under the Influence of Hydrological Conditions in the Baltic Sea

Investigating variability in phytoplankton primary productivity as a key component of the “biological pump” is critical to quantifying flux in the marine environment. We hypothesized that under certain hydrological conditions, changes in phytoplankton productivity are greater with changes in photosynthetic efficiency (the ratio of primary production (P P ) to the rate of electron transport in the phytoplankton photosystem, P P /ETR) than with changes in chlorophyll content. This study showed that increase of P P during sharp changes in hydrological parameters in the temporary frontal South-East Baltic (SEB) is achieved by increasing the efficiency of photosynthesis, i.e., the degree of use of light energy captured by chlorophyll a (Chl a). In the Gulf of Finland (GF), an increase in P P followed an increase in salinity from the Neva mouth to the sea and controls chlorophyll contents with low variability in photosynthetic efficiency. For SEB and GF, measurements of parameters of phytoplankton productivity and chlorophyll a content in late autumn (November) are carried out. The first stage of carbon flow (in biological pump), expressed in terms of primary production, was higher in the SEB than in the GF

Two-decade satellite observations reveal variability in size-fractionated phytoplankton primary production in the South China Sea

Understanding variations in marine phytoplankton primary production (PP) is crucial for assessing the response of the marine environment to climate change and for quantifying the ocean carbon cycle. However, the spatiotemporal variability of size-fractionated PP in the South China Sea (SCS) remains ambiguous. Our study investigated the monthly, seasonal, and inter-annual variability of size-fractionated PP in the SCS using satellite observations from 2002 to 2022. There were noticeable seasonal and monthly variations in size-fractionated PP, with notably high PP values appearing during the cold season. The disparities in distribution and the distinct fluctuation patterns between size-fractionated PP suggest that total PP alone is not a comprehensive indicator of marine ecosystem health. Over the past two decades in the SCS, there were more pronounced decreases in total, pico-, and nano-PP, whereas micro-PP displayed no significant trend. The most pronounced decline occurred in the northern SCS, contrasted by increases in coastal areas. These size-fractionated PP anomalies showed strong correlations with climate change indices, highlighting the impact of environmental factors on these anomalies, such as sea surface temperature, mixed layer depth, and wind speed. Our findings emphasize the importance considering size-fractionated PP to gain a more nuanced understanding of the ocean carbon cycle and the marine ecosystem's response to climate changes.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain.Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits.Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %–69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %–50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau.Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

Relative abundance and biometry of Bolivina ordinaria on the northern continental slope of the Pelotas basin during the late Quaternary

This study examines the variations in relative abundance, test size, and biomass of the species Bolivina ordinaria (Foraminifera) over the last 112 ka BP on the northern slope of the Pelotas Basin, Southern Brazil. The analyses were based on 651 individuals from 42 samples distributed along the cores SIS-249 (Marine Isotope Stage 5 to 3) and SIS-188 (Marine Isotope Stage 3 to 1). Bolivina ordinaria was the most abundant species of the Bolivinitidae family in these cores, particularly during warmer periods (MIS 1 and 5). Nine other species of this family were identified: B. compacta, B. doniezi, B. lowmani, Bolivina sp., B.striatula, Brizalina sp., Brizalina spinescens, Brizalina subaenariensis, and Brizalina subspinescens. Larger test lengths were observed during MIS 3 in the both cores. The summed biomass was higher during MIS 5 in the SIS-249 core and lower during MIS 3 in the SIS-188 core. The fluctuations observed in the relative abundance and summed biomass of B. ordinaria are consistent with the oscillations in total organic carbon flow, and the variations in primary productivity between the interglacial and glacial periods. The results suggest that this infaunal species is favored by the regular supply of refractory organic matter during warmer periods but faces increased competition from shallow infaunal and epifaunal species during glacial periods, when the flow of labile organic matter increases.

Seasonal variation of net ecosystem carbon exchange and gross primary production over a Loess Plateau semi-arid grassland of northwest China

Grassland ecosystems store approximately one-third of the global terrestrial carbon stocks, which play a crucial role in regulating the carbon cycle on regional and global scales, but the current scientific understanding of the variation in net carbon dioxide exchange (NEE) on grassland ecosystems is still limited. Based on the eddy covariance technique, this study investigated the seasonal variation of ecosystem respiration (Reco) and gross primary production (GPP) from 2018 to 2020 in a semi-arid grassland on the Loess Plateau in northwest China. The results indicated that the annual cumulative average NEE value was − 0.778 kg C/m2, the growing season cumulative value accounted for approximately 83.81%, which suggested that the semiarid grassland showed a notable soil carbon sink. The correlation analysis revealed that soil temperature (Ts) (RReco = 0.71, RGPP = 0.61) and soil water content (SWC) (RReco = 0.47, RGPP = 0.44) were the two main driving factors in modulating the variation of daily average GPP and Reco (P < 0.01). Therefore, the monthly average of GPP and Reco increased with the increase in Ts (RGPP = 0.716, P < 0.01; RReco = 0.586, P < 0.05), resulting in an increase in the carbon sequestration capacity of the grass ecosystem. This study also showed that soil moisture has a promoting effect on the response of Reco and GPP to Ts, and the correlation among GPP, Reco, and Ts was much stronger under wet conditions. For instance, the coefficient of determination of Reco and GPP with Ts under wet conditions in 2018 increased by 0.248 and 0.286, respectively, compared to those under droughty conditions. Additionally, the temperature sensitivity of Reco (Q10) increased by 46.13% compared to dry conditions. In addition, carbon exchange models should consider the synergistic effect of Ts and SWC as one of the main driving factors for theoretical interpretation or modeling. Under the potential scenario of future global warming and the frequent extreme weather events, our findings have important implications for predicting future CO2 exchange and establishing an optimal ecological model of carbon flux exchange.

Contrasting variations of ecosystem gross primary productivity during flash droughts caused by competing water demand and supply

Flash drought events (FDEs) are projected to increase frequently in a warming world, significantly impacting ecosystem productivity and the global carbon cycle. The development of FDEs, induced by anomalies in different environmental variables, may cause different responses to the ecosystem’s gross primary productivity (GPP). However, the GPP variations and underlying mechanisms during the FDEs have rarely been quantified. This study collected long-term (>10 years) high-quality flux observations from the FLUXNET 2015 dataset to investigate GPP variations and their driving mechanisms during FDEs. Results showed that all vegetation types have two contrasting GPP variations during FDEs. One variation is a decreasing then increasing standardized GPP anomaly (V-shape response). The other shows an increase followed by decreasing standardized GPP anomaly (inverted V-shape response). The V-shape GPP response to FDEs was induced by increased soil water content deficit at the onset stage of FDEs. In contrast, the inverted V-shape GPP response to FDEs was induced by increased net radiation at the onset of FDEs. Such results indicated competing moisture supply and atmospheric moisture demand at the onset of FDEs, controlling the two contrasting ecosystem’s carbon responses with its development. Moreover, the contribution of water use efficiency to the magnitude of the V-shape GPP response (64.5 ± 22.4%) is greater than that to the inverted V-shape GPP response (47.6 ± 18.7%). This study identified the two contrasting types of GPP variations during FDEs and their driving mechanisms across multiple ecosystem types which can improve our ability to predict the future effects of more frequent FDEs on ecosystem productivity.

Using phenology to unravel differential soil water use and productivity in a semiarid savanna

AbstractSavannas are water‐limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna‐wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, &lt;0–30 cm and deep, &gt;30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components.

Distinct Contributions of Climate Change and Anthropogenic Activities to Evapotranspiration and Gross Primary Production Variations over Mainland China

In recent decades, China has experienced substantial climate change and significant vegetation greenness due to the extensive implementation of artificial ecological restoration programs. However, the quantitative contributions of climatic and anthropogenic drivers to the national variations in associated evapotranspiration (ET) and gross primary productivity (GPP) over China at different climate zoning sub-regions remain unclear. Based on the analysis of climate factor and vegetation disturbance trends created by anthropogenic activities, this study constructed a remote sensing-based ecological model consisting of Penman–Monteith–Leuning (PML) and light use efficiency (LUE) components. The proposed model simulated the spatiotemporal changes in ET and GPP between 1999 and 2018 over China. The contributions of climatic factors and anthropogenic activities to ET and GPP variations were quantitatively calculated by ridge regression. The results show that (1) both interannual ET and GPP markedly increased, by 1.32 mm yr−1 and 8.01 g C m−2 yr−1, respectively; (2) vegetation changes due to anthropogenic disturbance made the dominant contribution to GPP variations over China, while the dominant factor influencing ET changes differed by sub-region due to the joint effects of vegetation and climate; (3) temperature and precipitation positively affected ET, while wind speed, humidity, and solar radiation negatively contributed to ET in most parts of Mainland China. These findings may provide a workable, scientific reference for further ecological restoration decision-making processes in China.

How does vegetation change under the warm–wet tendency across Xinjiang, China?

Recently, the warm–wet tendency in northwestern China has become a hot research topic. How does vegetation change under this tendency, and what are the impacts of climate change on vegetation? To address these questions, the dynamic variations in vegetation and their relationships with five climate factors (i.e., Pre: precipitation, Tmp: temperature, SM: root zone soil moisture, Vap: vapor pressure, and Pet: potential evapotranspiration) across Xinjiang are comprehensively analyzed during the period of 1982–2021. The spatiotemporal variations in vegetation are analyzed using the normalized difference vegetation index (NDVI) and leaf area index (LAI), employing the Mann–Kendall (M−K) and empirical orthogonal function (EOF) approaches. The key findings indicate that a significant greening trend is observed, with a value of 0.00226 m2m-2year−1 according to the annual LAI. For the seasonal variations, the vegetation had the largest increasing trend in summer (JJA: June, July, August) compared with the other seasons, with significant values of 0.000876 year−1 and 0.00382 m2m-2year−1 for the NDVI and LAI, respectively (p < 0.05). The spring (MAM: March, April, May) and the growing season (GS) also have significant increasing trends based on the LAI. Spatially, approximately 40 % of the areas have an increasing trend, indicating greening variations, which are mainly distributed in the mountainous area of northwestern Xinjiang. The EOF results also suggest that the vegetation in the mountainous area of northwestern Xinjiang has a greening trend. The vegetation is significantly positively correlated with the five climate factors, which illustrates their positive influence on the vegetation. Our study helps to better understand the long-term vegetation variations under the warm–wet tendency, which provides an important scientific basis for net primary production (NPP) variations and the carbon cycle in Xinjiang.

Sea otter recovery buffers century-scale declines in California kelp forests

The status of kelp forests and their vulnerability to climate change are of global significance. As the foundation for productive and extensive ecosystems, understanding long-term kelp forest trends is critical to coastal ecosystem management, climate resiliency, and restoration programs. In this study, we curate historical US government kelp canopy inventories, develop methods to compare them with contemporary surveys, and use a machine learning framework to evaluate and rank the drivers of change for California kelp forests over the last century. Historical surveys documented Macrocystis and Nereocystis kelp forests covered approximately 120.4 km2 in 1910–1912, which is only slightly above surveys in 2014–2016 (112.0 km2). These statewide comparisons, however, mask dramatic regional changes with increases in Central California (+57.6%, +19.7 km2) and losses along the Northern (-63.0%, -8.1 km2), and Southern (-52.1%, -18.3 km2) mainland coastlines. Random Forest models rank sea otter (Enhydra lutris nereis) population density as the primary driver of kelp changes, with benthic substrate, extreme heat, and high annual variation in primary productivity also significant. This century-scale perspective identifies dramatically different outcomes for California’s kelp forests, providing a blueprint for nature-based solutions that enhance coastal resilience to climate change.

Spatio-temporal Variation in Net Primary Productivity of Different Vegetation Types and Its Influencing Factors Exploration in Southwest China

Studying the spatiotemporal variation in vegetation net primary productivity (NPP) and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data, combined with in situ meteorological data, land use data, and vegetation type data, this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale, from 2000 to 2021, vegetation NPP, NPPPre (vegetation NPP exclusively under the influence of climate change), and NPPRes (vegetation NPP exclusively under the influence of human activities) in southwest China showed a fluctuating upward trend. Among different vegetation types, NPP, NPPPre, and NPPRes exhibited an upward trend, except for a minor decline in NPPRes of tree vegetation at a rate of -0.183 g·(m2·a)-1. Among them, NPP, NPPPre, and NPPRes of economic vegetation showed the most significant upward rates, 5.96, 3.09, and 2.94 g·(m2·a)-1, respectively. On the spatial scale, the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan, while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north," and the average value of the correlation coefficient increased in the ascending order of arbor vegetation (0.101), shrub vegetation (0.105), herb vegetation (0.110), and economic vegetation (0.114). The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP, while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China, with an increasing percentage of 30.91%. Different types of vegetation had different requirements for different climatic factors, but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21.03-28.49℃, and the warmth index was 106.46-167.2, the NPP of different vegetation types peaked. Under natural succession, the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected, while the herb vegetation community with low stability was highly affected by climate. In contrast, the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions.

Critical influencing factors on vegetation productivity in sandy land of the Northwestern Liaoning Province,China

To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwes-tern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact.

Spatial and temporal variation of net primary productivity of herbaceous marshes and its climatic drivers in China.

Herbaceous marshes are widely distributed in China and are vital to regional ecological security and sustainable development. Vegetation net primary productivity (NPP) is a vital indicator of vegetation growth. Climatic change can significantly affect NPP, but variations in NPP of herbaceous marsh and their responses to climate change in China remain unclear. Using meteorological data and MODIS NPP data during 2000-2020, this study analyzed the spatial and temporal variations of NPP and their responses to climate change in Chinese herbaceous marshes. We found that the annual NPP of herbaceous marshes in China increased significantly at a rate of 3.34 g C/m2/a from 2000 to 2020, with an average value of 336.60 g C/m2. The increased annual total precipitation enhanced the national average NPP, whereas annual mean temperature had no significant effect on the national average NPP. Regionally, precipitation had a significant positive effect on the NPP in temperate semi-arid and arid and temperate semi-humid and humid marsh regions. For the first time, we discovered asymmetry effects of daytime and nighttime temperatures on NPP in herbaceous marshes of China. In temperate humid and semi-humid marsh regions, increased summer daytime temperature decreased the NPP while increased summer nighttime temperature increased the NPP. In the Tibetan Plateau, increased autumn daytime temperature, as well as summer daytime and nighttime temperatures could increase the NPP of herbaceous marshes. This study highlights the different influences of seasonal climate change on the NPP of herbaceous marshes in China and indicates that the differential effects of daytime and nighttime temperatures should be considering in simulating the NPP of herbaceous marshes in terrestrial ecosystem models, especially under the background of global asymmetric diurnal warming.

Assessing Phytoplankton Primary Productivity Variability in the Changjiang Estuary, East China Sea From Coupled Fast Repetition Rate (FRR) Fluorometry and Chlorophyll‐a Measurements

AbstractPhytoplankton primary productivity (PP) varies significantly over environmental gradients, particularly in physically‐dynamic systems such as estuaries and coastal seas. During summer, runoff peaks in the Changjiang River driving large environmental gradients in both the Changjiang estuary and adjacent East China Sea (ECS), likely driving significant variability in PP. As satellite models of PP often underperform in coastal waters, we aimed to develop a novel approach for assessing net PP variability in such a dynamic environment. Parallel in situ measurements of Fast Repetition Rate (FRR) fluorometry and carbon (C) uptake rates were conducted for the first time in this region during two summer cruises in 2019 and 2021. A series of 13C‐incubations (n = 31) were performed, with measured PP ranging from ∼6 to 1,700 mgC m−3 d−1. Net PP values were significantly correlated with salinity (r = 0.45), phytoplankton chlorophyll a (Chl‐a, r = 0.88), Photosystem II (PSII) functional absorption cross‐section (σPSII, r = −0.76) and maximum PSII quantum yield (Fv/Fm, r = 0.59). Stepwise regression analysis showed that Chl‐a and σPSII were the strongest predictors of net PP. A generalized additive model (GAM) was also used to estimate net PP considering nonlinear effects of Chl‐a and σPSII. We demonstrate that GAM outperforms linear modeling approaches in estimating net PP in this study, as evidenced by a lower root mean square error (∼140 vs. 250 mgC m−3 d−1). Our novel approach provides a valuable tool to examine carbon cycling dynamics in this important region.