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Frost is one of the most frequent, intense, and influential agrometeorological disasters that occurs frequently in Northeast China. The study of the spatiotemporal changes of ground frost is of great significance for farmers and policymakers in Northeast China, as it can inform decisions related to crop selection, planting schedules, and the development of regional climate adaptation plans. In this study, the spatiotemporal changes of frost indices (last spring frost (LSF), first fall frost (FFF), and frost-free period (FFP)) in Northeast China were analyzed from 1961 to 2020. Then, we investigated the mutation characteristics of the frost indices and their correlation with geographical factors. The results revealed that (1) the LSF, FFF, and FFP in Northeast China were concentrated at 120–140 DOY, 260–280 DOY, and 110–170 days, respectively. The spatial distribution of frost indices exhibited significant spatial heterogeneity. (2) The LSF, FFF, and FFP showed significant trends of advancement, delay, and extension, with trends of −1.94 days/10 a, 1.72 days/10 a, and 4.21 days/10 a, respectively. (3) More than 80% of the LSF, FFF, and FFP of the sites showed trends of advancement, delay, and extension, with greater variability in the central part of Heilongjiang Province. (4) The FFF and FFP experienced an abrupt change in the late 1990s. (5) The correlation between latitude and LSF, FFF, and FFP was the strongest, with correlation coefficients of 0.77, −0.79, and −0.78, respectively. This study provides a comprehensive understanding of the changing characteristics of ground frost indices that impact agricultural production in Northeast China against the backdrop of climate change. The findings hold significant scientific value in guiding the adaptation of agricultural production layouts in Northeast China to the evolving climatic conditions. [ABSTRACT FROM AUTHOR]

Accurately quantifying the relative effects of climate change and human activities on soil carbon, nitrogen, and phosphorus in alpine grasslands and their feedback is an important aspect of global change, and high-precision models are the key to solving this scientific problem with high quality. Therefore, nine models, the random forest model (RFM), generalized boosted regression model (GBRM), multiple linear regression model (MLRM), support vector machine model (SVMM), recursive regression tree model (RRTM), artificial neural network model (ANNM), generalized linear regression model (GLMR), conditional inference tree model (CITM), and eXtreme gradient boosting model (eXGBM), were used for modeling soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), the ratio of SOC to TN (C:N), the ratio of SOC to TP (C:P), and the ratio of TN to TP (N:P) at depths of 0-10, 10-20, and 20-30 cm under non-grazing and free-grazing scenarios in the Xizang grasslands. Annual radiation (ARad), annual precipitation (AP), and annual temperature (AT) were used as independent variables under non-grazing scenarios, whereas ARad, AP, AT, and growing season maximum normalized difference vegetation index (NDVImax) were used as independent variables under free-grazing scenarios. Overall, the RFM and GBRM were more accurate than the other seven models. However, the tree numbers of the GBRM were much larger than those of the RFM, indicating that the GBRM may have a greater model complexity and lower running speed. Therefore, the RFM had the best performance among the nine models in modeling SOC, TN, TP, C:N, C:P, and N:P in the Xizang grasslands. The RFM established in this study can not only help scientists save time and money on massive sampling and analysis, but can also be used to construct a database of SOC, TN, and TP, and their ratios, and further scientific research related to ecological and environmental issues (e.g., examining whether soil systems intensified global warming over the past few decades by exploring whether climate change and human activities altered soil organic carbon) in the grasslands of Xizang Plateau. [ABSTRACT FROM AUTHOR]

Land surface phenology plays a crucial role in accurately parameterizing interactions between land ecosystems and the atmosphere. Changes in autumn phenology directly impact the length of vegetation growing season and year-to-year changes in carbon uptake. Previous studies have often focused solely on the end of growing season when characterizing autumn phenology, neglecting the onset and duration of autumn. Here, we extracted the annual autumn phenological metrics, i.e., the start of brown-down phase (SOB), the end of brown-down phase (EOB), and the length of brown-down phase (LOB), for temperate China from 1982 to 2018 based on our self-developed global LSP dataset. We conducted a comparative analysis of SOB, EOB, and LOB in the field of their spatial distribution, temporal trends, and performance on various categories of vegetated regions (i.e., forests, grasslands, croplands, and vegetated areas in urban lands (V_Urban)). The results showed a significant negative correlation between the timing of autumn phenological metrics and latitude in temperate China. Between 1982 and 2018, there were significant positive increasing trends in EOB and LOB in V_Urban, as well as in LOB in forests in temperate China. However, the annual mean SOB, EOB, and LOB did not show significant trends across the entire study area. At the local pixel scale, SOB, EOB, and LOB exhibited a combination of advanced and delayed trends within various vegetated categories. The trends of the same phenological metric were not uniform across these diverse vegetated regions. For instance, the majority of pixels with significant trends in SOB exhibited delayed trends in forests and croplands, while displaying advanced trends in grasslands and V_Urban. In this study, employing three metrics (SOB, EOB, and LOB) to describe autumn phenology enhances our understanding of the impacts of global climate change on ecosystems, offering a more comprehensive and detailed perspective. In the future, satellite-based monitoring and phenological modeling should contemplate incorporating additional potential phenological metrics. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite‐derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p <.05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges. [ABSTRACT FROM AUTHOR]

This study used a multilevel mediation model to test the theory that former early childhood education (ECE) attendees' 5th grade achievement is mediated by the aggregate school-wide achievement of their elementary school. Aggregate school-wide achievement was defined as the percentage of 5th graders in a school who were at/above academic proficiency in reading or math. Research questions were: (a) Do ECE program participants have better achievement at 5th grade compared with their matched peers who did not participate in an ECE program?; and (b) Is the association between ECE attendance and 5th grade academic performance mediated by school-wide achievement? Results indicated that children who attended prekindergarten (pre-K) and child care outperformed their matched peers who had not attended ECE programs; conversely, those children who did not attend ECE actually outperformed their Head Start counterparts. Mediation analyses indicated that aggregate school-wide achievement at 5th grade partially mediated the association between former ECE attendance and 5th grade performance; however, these mediated effects were small. Overall, the size of the total effects of ECE and the 5th grade academic outcomes were consistent with prior studies. This research confirms the long-term effects of pre-K and child care until 5th grade.

Understanding the spatiotemporal variation in vegetation phenology of freshwater marshes and its response to climate change is significant to evaluate the global carbon cycling. Based on the climate and satellite‐derived vegetation index data, this work investigated the temporal and spatial variation of spring phenology and its response to climatic change in freshwater marshes of the Tibetan Plateau. We found that the start date of vegetation growing season (SOS) showed a significant advancing trend of 3.4 d decade−1 from 2001 to 2019 in freshwater marshes of the Tibetan Plateau. The increase of spring daytime and nighttime temperatures could advance the vegetation SOS over the marshes of the Tibetan Plateau. However, the effects of day maximum and night minimum temperature on freshwater marsh SOS were divergent at different altitudes: the advancing effect of warming night‐time and daytime temperature on the SOS was more significant in the regions below and above 4000 m, respectively. [ABSTRACT FROM AUTHOR]