Climate, litter quality and radiation duration jointly regulate the net effect of UV radiation on litter decomposition.

Photodegradation via ultraviolet (UV) radiation is an important factor driving plant litter decomposition. Despite increasing attention to the role of UV photodegradation in litter decomposition, the specific impact of UV radiation on the plant litter decomposition stage within biogeochemical cycles remains unclear at regional and global scales. To clarify the variation rules of magnitude of UV effect on plant litter decomposition and their regulatory factors, we conducted a meta-analysis based on 54 published papers. Our results indicated that UV significantly promoted the mass loss of litter by facilitating decay of carbonaceous fractions and release of nitrogen and phosphorus. The promotion effect varied linearly or non-linearly with the time that litter exposed to UV, and with climatic factors. The UV effect on litter decomposition decreased first than increased on precipitation and temperature gradients, reaching its minimum in the area with a precipitation of 400-600 mm, and a temperature of 15-20 °C. This trend might be attributed to a potential equilibrium between the photofacilitation and photo-inhibition effects of UV under this condition. This variation in UV effect on precipitation gradient was in agreement with the fact that UV photodegradation effect was weakest in grassland ecosystems compared to that in forest and desert ecosystems. In addition, initial litter quality significantly influenced the magnitude of UV effect, but had no influence on the correlation between UV effect and climate gradient. Litter with lower initial nitrogen and lignin content shown a greater photodegradation effect, whereas those with higher hemicellulose and cellulose content had a greater photodegradation effect. Our study provides a comprehensive understanding of photodegradation effect on plant litter decomposition, indicates potentially substantial impacts of global enhancements of litter decomposition by UV, and highlights the necessity to quantify the contribution of photochemical minerallization pathway and microbial degradation pathway in litter decomposition.

Algal-bacterial shortcut nitrogen removal model with seasonal light variations.

The algal-bacterial shortcut nitrogen removal (ABSNR) process can be used to treat high ammonia strength wastewaters without external aeration. However, prior algal-bacterial SNR studies have been conducted under fixed light/dark periods that were not representative of natural light conditions. In this study, laboratory-scale photo-sequencing batch reactors (PSBRs) were used to treat anaerobic digester sidestream under varying light intensities that mimicked summer and winter conditions in Tampa, FL, USA. A dynamic mathematical model was developed for the ABSNR process, which was calibrated and validated using data sets from the laboratory PSBRs. The model elucidated the dynamics of algal and bacterial biomass growth under natural illumination conditions as well as transformation processes for nitrogen species, oxygen, organic and inorganic carbon. A full-scale PSBR with a 1.2 m depth, a 6-day hydraulic retention time (HRT) and a 10-day solids retention time (SRT) was simulated for treatment of anaerobic digester sidestream. The full-scale PSBR could achieve >90% ammonia removal, significantly reducing the nitrogen load to the mainstream wastewater treatment plant (WWTP). The dynamic simulation showed that ABSNR process can help wastewater treatment facilities meet stringent nitrogen removal standards with low energy inputs.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States.

BACKGROUND: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. METHODS: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. RESULTS: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. CONCLUSIONS: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

RSV Disease Burden in Primary Care in Italy: A Multi-Region Pediatric Study, Winter Season 2022-2023.

INTRODUCTION: Human respiratory syncytial virus (RSV) is one of the most frequent causes of respiratory infections in children under 5 years of age, but its socioeconomic impact and burden in primary care settings is still little studied. METHODS: During the 2022/2023 winter season, 55 pediatricians from five Italian regions participated in our community-based study. They collected a nasal swab for RSV molecular test from 650 patients under the age of 5 with acute respiratory infections (ARIs) and performed a baseline questionnaire. The clinical and socioeconomic burden of RSV disease in primary care was evaluated by two follow-up questionnaires completed by the parents of positive children on Days 14 and 30. RESULTS: RSV laboratory-confirmed cases were 37.8% of the total recruited ARI cases, with RSV subtype B accounting for the majority (65.4%) of RSV-positive swabs. RSV-positive children were younger than RSV-negative ones (median 12.5 vs. 16.5 months). The mean duration of symptoms for all children infected by RSV was 11.47 ± 6.27 days. We did not observe substantial differences in clinical severity between the two RSV subtypes, but RSV-A positive patients required more additional pediatric examinations than RSV-B cases. The socioeconomic impact of RSV infection was considerable, causing 53% of children to be absent from school, 46% of parents to lose working days, and 25% of families to incur extra costs. CONCLUSIONS: Our findings describe a baseline of the RSV disease burden in primary care in Italy before the introduction of upcoming immunization strategies.

Comparative Analysis of Clinical Outcomes Using Propensity Score Matching: Coronavirus Disease 2019 vs. Seasonal Influenza in Korea.

BACKGROUND: The advent of the omicron variant and the formulation of diverse therapeutic strategies marked a new epoch in the realm of coronavirus disease 2019 (COVID-19). Studies have compared the clinical outcomes between COVID-19 and seasonal influenza, but such studies were conducted during the early stages of the pandemic when effective treatment strategies had not yet been developed, which limits the generalizability of the findings. Therefore, an updated evaluation of the comparative analysis of clinical outcomes between COVID-19 and seasonal influenza is requisite. METHODS: This study used data from the severe acute respiratory infection surveillance system of South Korea. We extracted data for influenza patients who were infected between 2018 and 2019 and COVID-19 patients who were infected in 2021 (pre-omicron period) and 2022 (omicron period). Comparisons of outcomes were conducted among the pre-omicron, omicron, and influenza cohorts utilizing propensity score matching. The adjusted covariates in the propensity score matching included age, sex, smoking, and comorbidities. RESULTS: The study incorporated 1,227 patients in the pre-omicron cohort, 1,948 patients in the omicron cohort, and 920 patients in the influenza cohort. Following propensity score matching, 491 patients were included in each respective group. Clinical presentations exhibited similarities between the pre-omicron and omicron cohorts; however, COVID-19 patients demonstrated a higher prevalence of dyspnea and pulmonary infiltrates compared to their influenza counterparts. Both COVID-19 groups exhibited higher in-hospital mortality and longer hospital length of stay than the influenza group. The omicron group showed no significant improvement in clinical outcomes compared to the pre-omicron group. CONCLUSION: The omicron group did not demonstrate better clinical outcomes than the pre-omicron group, and exhibited significant disease severity compared to the influenza group. Considering the likely persistence of COVID-19 infections, it is imperative to sustain comprehensive studies and ongoing policy support for the virus to enhance the prognosis for individuals affected by COVID-19.

Evaluating Pilot Implementation of 'PenCS Flu Topbar' App in Medical Practices to Improve National Immunisation Program-Funded Seasonal Influenza Vaccination in Central Queensland, Australia.

BACKGROUND: The 'PenCS Flu Topbar' app was deployed in Central Queensland (CQ), Australia, medical practices through a pilot programme in March 2021. METHODS: We evaluated the app's user experience and examined whether the introduction of 'PenCS Flu Topbar' in medical practices could improve the coverage of NIP-funded influenza vaccinations. We conducted a mixed-method study including a qualitative analysis of in-depth interviews with key end-users and a quantitative analysis of influenza vaccine administrative data. RESULTS: 'PenCS Flu Topbar' app users reported positive experiences identifying patients eligible for NIP-funded seasonal influenza vaccination. A total of 3606 NIP-funded influenza vaccinations was administered in the eight intervention practices, 14% higher than the eight control practices. NIP-funded vaccination coverage within practices was significantly higher in the intervention practices (31.2%) than in the control practices (27.3%) (absolute difference: 3.9%; 95% CI: 2.9%-5.0%; p < 0.001). The coverage was substantially higher in Aboriginal and Torres Strait Islander people aged more than 6 months, pregnant women and children aged 6 months to less than 5 years for the practices where the app was introduced when compared to control practices: incidence rate ratio (IRR) 2.4 (95% CI: 1.8-3.2), IRR 2.7 (95% CI: 1.8-4.2) and IRR 2.3 (1.8-2.9) times higher, respectively. CONCLUSIONS: Our evaluation indicated that the 'PenCS Flu Topbar' app is useful for identifying the patients eligible for NIP-funded influenza vaccination and is likely to increase NIP-funded influenza vaccine coverage in the eligible populations. Future impact evaluation including a greater number of practices and a wider geographical area is essential.

Ecological baselines in the Eastern Mediterranean Sea shifted long before the availability of observational time series.

Native biodiversity loss and invasions by nonindigenous species (NIS) have massively altered ecosystems worldwide, but trajectories of taxonomic and functional reorganization remain poorly understood due to the scarcity of long-term data. Where ecological time series are available, their temporal coverage is often shorter than the history of anthropogenic changes, posing the risk of drawing misleading conclusions on systems' current states and future development. Focusing on the Eastern Mediterranean Sea, a region affected by massive biological invasions and the largest climate change-driven collapse of native marine biodiversity ever documented, we followed the taxonomic and functional evolution of an emerging "novel ecosystem", using a unique dataset on shelled mollusks sampled in 2005-2022 on the Israeli shelf. To quantify the alteration of observed assemblages relative to historical times, we also analyzed decades- to centuries-old ecological baselines reconstructed from radiometrically dated death assemblages, time-averaged accumulations of shells on the seafloor that constitute natural archives of past community states. Against expectations, we found no major loss of native biodiversity in the past two decades, suggesting that its collapse had occurred even earlier than 2005. Instead, assemblage taxonomic and functional richness increased, reflecting the diversification of NIS whose trait structure was, and has remained, different from the native one. The comparison with the death assemblage, however, revealed that modern assemblages are taxonomically and functionally much impoverished compared to historical communities. This implies that NIS did not compensate for the functional loss of native taxa, and that even the most complete observational dataset available for the region represents a shifted baseline that does not reflect the actual magnitude of anthropogenic changes. While highlighting the great value of observational time series, our results call for the integration of multiple information sources on past ecosystem states to better understand patterns of biodiversity loss in the Anthropocene.

Poor durability of the neutralizing response against XBB sublineages after a bivalent mRNA COVID-19 booster dose in persons with HIV.

We estimated the dynamics of the neutralizing response against XBB sublineages and T cell response in persons with HIV (PWH) with previous AIDS and/or CD4 < 200/mm3 receiving the bivalent original strain/BA.4-5 booster dose in fall 2022. Samples were collected before the shot (Day 0), 15 days, 3, and 6 months after. PWH were stratified by immunization status: hybrid immunity (HI; vaccination plus COVID-19) versus nonhybrid immunity (nHI; vaccination only). Fifteen days after the booster, 16% and 30% of PWH were nonresponders in terms of anti-XBB.1.16 or anti-EG.5.1 nAbs, respectively. Three months after, a significant waning of anti-XBB.1.16, EG.5.1 and -XBB.1 nAbs was observed both in HI and nHI but nAbs in HI were higher than in nHI. Six months after both HI and nHI individuals displayed low mean levels of anti-XBB.1.16 and EG.5.1 nAbs. Regarding T cell response, IFN-γ values were stable over time and similar in HI and nHI. Our data showed that in PWH, during the prevalent circulation of the XBB.1.16, EG.5.1, and other XBB sublineages, a mRNA bivalent vaccine might not confer broad protection against them. With a view to the 2023/2024 vaccination campaign, the use of the monovalent XBB.1.5 mRNA vaccine should be urgently warranted in PWH to provide adequate protection.

Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits.

Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012-2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha-1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (-25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.

High stocking rates effects in continuous season long grazing reduces the contribution of microbial necromass to soil organic carbon in a semi-arid grassland in Inner Mongolia.

Livestock grazing strongly influences the accumulation of soil organic carbon (SOC) in grasslands. However, whether the changes occurring in SOC content under different intensities of continuous summer long grazing are associated with the changes in microbially-derived necromass C remains unclear. Here, we established a sheep grazing experiment in northern China in 2004 with four different stocking rates. Soil samples were collected after 17 years of grazing and analyzed for physical, chemical, and microbial characteristics. Grazing decreased SOC and microbial necromass carbon (MNC). Notably, grazing also diminished contributions of MNC to SOC. MNC declined with decreasing plant carbon inputs with degradation of the soil environment. Direct reductions in microbial necromass C, which indirectly reduced SOC, resulted from reduced in plant C inputs and microbial abundance and diversity. Our study highlights the key role of stocking rate in governing microbial necromass C and SOC and the complex relationships these variables.

Multi-hazard assessment of climate-related hazards for European coastal cities.

The assessment of risk posed by climate change in coastal cities encompasses multiple climate-related hazards. Sea-level rise, coastal flooding and coastal erosion are important hazards, but they are not the only ones. The varying availability and quality of data across cities hinders the ability to conduct holistic and standardized multi-hazard assessments. Indeed, there are far fewer studies on multiple hazards than on single hazards. Also, the comparability of existing methodologies becomes challenging, making it difficult to establish a cohesive understanding of the overall vulnerability and resilience of coastal cities. The use of indicators allows for a standardized and systematic evaluation of baseline hazards across different cities. The methodology developed in this work establishes a framework to assess a wide variety of climate-related hazards across diverse coastal cities, including sea-level rise, coastal flooding, coastal erosion, heavy rainfall, land flooding, droughts, extreme temperatures, heatwaves, cold spells, strong winds and landslides. Indicators are produced and results are compared and mapped for ten European coastal cities. The indicators are meticulously designed to be applicable across different geographical contexts in Europe. In this manner, the proposed approach allows interventions to be prioritized based on the severity and urgency of the specific risks faced by each city.

Seasonal variation of asymptomatic viral and bacterial nasopharyngeal carriage in rural Senegal.

BACKGROUND: The surveillance of respiratory pathogens in rural areas of West Africa has, to date, largely been focussed on symptoms. In this prospective study conducted prior to the COVID-19 pandemic, we aimed to assess the asymptomatic prevalence of respiratory pathogen carriage in a group of individuals living in a rural area of Senegalese. METHODS: Longitudinal follow up was performed through monthly nasopharyngeal swabbing during the dry season and weekly swabbing during the rainy season. We enrolled 15 individuals from the village of Ndiop. A total of 368 nasopharyngeal swabs were collected over a one-year period. We investigated the prevalence of 18 respiratory viruses and eight respiratory bacteria in different age groups using singleplex and multiplex PCR. RESULTS: In total, 19.56% of the samples (72/368) were positive for respiratory viruses and 13.60% of the samples (50/368) were positive for respiratory bacteria. Coronaviruses (19/72, 26.39%), adenoviruses (17/72, 23.61%), rhinoviruses (14/72, 19.44%), Streptococcus pneumoniae (17/50, 34%), and Moraxella catarrhalis (15/50, 30%) were the most frequently detected viruses. Interestingly, the carriage of respiratory pathogens was shown to be more frequent during the rainy season, as pluviometry was shown to be positively associated with the occurrence of respiratory viruses such as influenza (P = .0078, r2 =.523) and RSV (P = .0055, r2 =.554). CONCLUSIONS: Our results show a non-negligible circulation of respiratory pathogens in a rural area in Senegal (West Africa) with an underestimated proportion of asymptomatic individuals. This study highlights the fact that the circulation of viruses and bacteria in the community has been overlooked.

Perinatal photoperiod associations with bipolar disorder and depression: A systematic literature review and cross-sectional analysis of the UK Biobank database.

Season-of-birth associations with psychiatric disorders point to environmental (co-)aetiological factors such as natural photoperiod that, if clarified, may allow interventions toward prevention. We systematically reviewed the literature concerning season-of-birth and bipolar disorder and depression and explored associations between the perinatal natural photoperiod and these outcomes in a cross-sectional analysis of the UK Biobank database. We used mean daily photoperiod and relative photoperiod range (relative to the mean) in the 3rd trimester and, separately, in the first 3 months post birth as metrics. From review, increased risk of depression with late spring birth is compatible with increased odds of probable single episode-, probable recurrent-, and diagnosed depression (OR 2.85 95 %CI 1.6-5.08, OR 2.20 95 %CI 1.57-3.1, and OR 1.48 95 %CI 1.11-1.97, respectively) with increasing 3rd trimester relative photoperiod range for participants who experienced relatively non-extreme daily photoperiods. Risk of bipolar disorder with winter-spring birth contrasted with no consistent patterns of perinatal photoperiod metric associations with bipolar disorder in the UK Biobank. As natural photoperiod varies by both time-of-year and latitude, perinatal natural photoperiods (and a hypothesized mechanism of action via the circadian timing system and/or serotonergic circuitry associated with the dorsal raphe nucleus) may reconcile inconsistencies in season-of-birth associations. Further studies are warranted.

Predicting Quercus gilva distribution dynamics and its response to climate change induced by GHGs emission through MaxEnt modeling.

Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species.

Significant shifts in latitudinal optima of North American birds.

Changes in climate can alter environmental conditions faster than most species can adapt. A prediction under a warming climate is that species will shift their distributions poleward through time. While many studies focus on range shifts, latitudinal shifts in species' optima can occur without detectable changes in their range. We quantified shifts in latitudinal optima for 209 North American bird species over the last 55 y. The latitudinal optimum (m) for each species in each year was estimated using a bespoke flexible non-linear zero-inflated model of abundance vs. latitude, and the annual shift in m through time was quantified. One-third (70) of the bird species showed a significant shift in their optimum. Overall, mean peak abundances of North American birds have shifted northward, on average, at a rate of 1.5 km per year (±0.58 SE), corresponding to a total distance moved of 82.5 km (±31.9 SE) over the last 55 y. Stronger poleward shifts at the continental scale were linked to key species' traits, including thermal optimum, habitat specialization, and territoriality. Shifts in the western region were larger and less variable than in the eastern region, and they were linked to species' thermal optimum, habitat density preference, and habitat specialization. Individual species' latitudinal shifts were most strongly linked to their estimated thermal optimum, clearly indicating a climate-driven response. Displacement of species from their historically optimal realized niches can have dramatic ecological consequences. Effective conservation must consider within-range abundance shifts. Areas currently deemed "optimal" are unlikely to remain so.

Spatiotemporal atmospheric in-situ carbon dioxide data over the Indian sites-data perspective.

In the current study, atmospheric carbon dioxide (CO2) data covering multiple locations in the Indian subcontinent are reported. This data was collected using a dedicated ground-based in-situ network established as part of the Geosphere-Biosphere Programme (CAP-IGBP) of the Climate and Atmospheric Processes of the Indian Space Research Organisation (ISRO). Data are collected over Ponmudi, Ooty, Sriharikota, Gadanki, Shadnagar, Nagpur, and Dehradun during 2014-2015, 2017-2020, 2012, 2011-2015, 2014-2017, 2017 and 2008-2011, respectively. The atmospheric CO2 generated as part of the CAP-IGBP network would enhance the understanding of CO2 variability in different time scales ranging from diurnal, seasonal, and annual over the Indian region. Data available under this network may be interesting to other research communities for modeling studies and spatiotemporal variability of atmospheric CO2 across the study locations. The work also evaluated the CO2 observations against the Model for Interdisciplinary Research on Climate version 4 atmospheric chemistry-transport model (MIROC4-ACTM) concentrations.

Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes.

Previous studies have primarily focused on the influence of temperature and precipitation on phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth can effect on vegetation phenology. In this research, we conducted an analysis of the start (SOS) and end (EOS) of the growing seasons in the northern region of China above 30°N from 1982 to 2014, focusing on two-season vegetation phenology. We examined the response of vegetation phenology of different vegetation types to preseason climatic factors, including relative humidity (RH), shortwave radiation (SR), maximum temperature (Tmax), and minimum temperature (Tmin). Our findings reveal that the optimal preseason influencing vegetation phenology length fell within the range of 0-60 days in most areas. Specifically, SOS exhibited a significant negative correlation with Tmax and Tmin in 44.15% and 42.25% of the areas, respectively, while EOS displayed a significant negative correlation with SR in 49.03% of the areas. Additionally, we identified that RH emerged as the dominant climatic factor influencing the phenology of savanna (SA), whereas temperature strongly controlled the SOS of deciduous needleleaf forest (DNF) and deciduous broadleaf forest (DBF). Meanwhile, the EOS of DNF was primarily influenced by Tmax. In conclusion, this study provides valuable insights into how various vegetation types adapt to climate change, offering a scientific basis for implementing effective vegetation adaptation measures.