Contrasting responses of peak vegetation growth to asymmetric warming: Evidences from FLUXNET and satellite observations

Uncovering the role of solar radiation and water stress factors in constraining decadal intra-site spring phenology variability in diverse ecosystems across the Northern Hemisphere

The spring phenology has advanced significantly over recent decades with climate change, impacting large-scale biogeochemical cycles, climate feedback, and other essential ecosystem processes. Although numerous prognostic models have been developed for spring phenology, regional analyses of the optimality (OPT) strategy model that incorporate environmental variables beyond temperature and photoperiod remain lacking. We investigated the roles of solar radiation (SR) and three water stress factors (precipitation (P), soil moisture, and vapor pressure deficit (VPD)) on spring phenology from 1982 to 2015 using the OPT model with Global Inventory Modeling and Mapping Studies NDVI3g dataset and environmental data from TerraClimate, CRU_TS, and Global Land Data Assimilation System across the Northern Hemisphere (> 30°N). Our results show that SR and water stress factors significantly impacted intrasite decadal spring phenology variability, with water stress factors dominant in grassland ecosystems while SR dominated in the rest of the ecosystem types. Enhanced models incorporating SR (OPT-S) and VPD (OPT-VPD) outperformed the original OPT model, likely due to improved representation of the adaptive strategy of spring phenology to optimize photosynthetic carbon gain while minimizing frost risk. Our research enhances the understanding of the key environmental drivers influencing decadal spring phenology variation in the Northern Hemisphere and contributes to more accurate forecasts of ecological responses to global environmental change.

Ecological dichotomies of solar energy expansion: resilience in arid regions versus fragility in humid ecosystems

The deployment of Utility-Scale Solar Energy (USSE) systems is increasingly recognized as a cornerstone strategy in mitigating climate change. However, the environmental ramifications of such extensive developments remain the subject of considerable debate, with marked regional variability in their ecological effects, particularly across different biomes. As such, there is a pressing need for comprehensive, systems-level investigations to evaluate the multifaceted environmental impacts of USSE in both arid and humid ecosystems. Here, we undertake an exhaustive assessment utilizing a high-resolution (10 m) dataset of photovoltaic (PV) station distributions across China, complemented by Landsat-derived NDVI remote sensing data from 2019 to 2023. This approach facilitates the quantification of the dynamic effects of PV infrastructure development on vegetation greenness (NDVImean and NDVImax), and allows for the assessment of scale-dependent ecological responses across two contrasting regions: the arid zone of Ningxia and the humid zone of Anhui. Our results indicate that in the arid region, the construction of PV facilities has a negligible effect on vegetation greenness, with inter-annual variations in NDVImean remaining consistently below 0.05, and no discernible change in NDVImax. In contrast, PV development in the humid region led to a dramatic deterioration in vegetation greenness, with NDVImean declining sharply from 0.42 to below 0.20-representing a reduction of over 50%, particularly during the growing season (April to October). Furthermore, the relationship between the scale of PV installations and their ecological impact in the humid region was characterized by a pronounced non-linearity, with large-scale PV plants (spanning >10,000 pixels) causing near-total vegetation collapse, driving NDVI toward near-zero. Collectively, these findings suggest that the sparse vegetation and enhanced microclimatic regulation characteristic of arid ecosystems provide greater resilience to external disturbances, whereas the high-biomass vegetation typical of humid regions is significantly more vulnerable to perturbations. Based on these insights, we advocate for the strategic prioritization of arid regions with greater ecological adaptability for future USSE development, alongside the incorporation of ecological restoration measures and the optimization of facility scale to mitigate potential environmental disturbances. Our study emphasizes the need for a synergistic approach to optimize both energy transition and ecological conservation in the context of regional variability, offering a solid scientific basis for the national-scale planning and site selection of photovoltaic energy projects.

Vegetation Types Shift Physiological and Phenological Controls on Carbon Sink Strength in a Coastal Zone

The carbon sink function performed by the different vegetation types along the environmental gradient in coastal zones plays a vital role in mitigating climate change. However, inadequate understanding of its spatiotemporal variations across different vegetation types and associated regulatory mechanisms hampers determining its potential shifts in a changing climate. Here, we present long-term (2011-2022) eddy covariance measurements of the net ecosystem exchange (NEE) of CO2 at three sites with different vegetation types (tidal wetland, nontidal wetland, and cropland) in a coastal zone to examine the role of vegetation type on annual carbon sink strength. We found that the three study sites are stable carbon sinks and are influenced by their distinct physiological and phenological factors. The annual NEE of the tidal wetland, nontidal wetland, and cropland were determined predominantly by the seasonal peaks of net CO2 uptake, release, and duration of CO2 uptake period. Furthermore, the changes in annual NEE were sensitive to climatic variables, as spring mean air temperature reduced the carbon sink strength in the tidal wetland, maximum daily precipitation in summer reduced it in the nontidal wetland, and summer mean global radiation elicited the same effect in the cropland. Finally, a worldwide database of the three vegetation types was compiled, using which we further validated the global consistency of the biological controls. Overall, these results emphasize the importance of considering the underlying mechanisms by which vegetation types influence NEE for the accurate forecasting of carbon sink dynamics across different coastal vegetation types under climate change.

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.

Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture

Alpine grassland is among the world's most vulnerable ecosystems, characterized by a high sensitivity to climate change (CC) and human activities (HA). Quantifying the relative contributions of CC and HA to grassland change plays a crucial role in safeguarding grassland ecological security and devising sustainable grassland management strategies. Although there were adequate studies focusing on the separate impacts of CC and HA on alpine ecosystem, insufficient attention has been given to investigating the effects of extreme temperatures and soil moisture. In this study, the spatiotemporal variations of alpine grassland were analyzed based on MODIS NDVI during the growing season from 2000 to 2020 in Naqu, using partial least squares regression and residual analysis methods to analyze the importance of climate factors and the impacts of CC and HA on grassland change. The results show that the NDVI during the growing season in Naqu exhibited an increasing trend of 0.0046/10a. At the biome scale, the most significant and rapid increase was observed in alpine desert and alpine desert grassland. Extreme temperature and soil moisture (SM) exerted a more significant importance on alpine grassland at whole scale. SM always showed a significant importance at biome and grid scale. The contributions of CC and HA to the change during the growing season were calculated as 0.0032/10a and 0.0015/10a, respectively, accounting for 68.05 % and 31.05 %. CC dominated the increase in NDVI during the growing season; HA contributed positively to NDVI in most areas of Naqu. The results are expected to enhance our understanding of grassland variations under CC and HA and provide a scientific basis for future ecological conservation in alpine regions.