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AbstractElevated carbon-dioxide concentration [eCO2] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO2. It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO2. To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO2, APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO2] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO2].

Land use changes from cropland to orchards in Eastern China have raised serious concerns about the regional nitrogen (N) cycle and greenhouse gas balance. We measured soil nitrous oxide (N2O) emissions and methane (CH4) uptake using manual static chambers in an apple orchard. The primary aims were to assess the effect of N fertilizer application on gas fluxes and quantify the site-specific N2O emission factor (EFd). Field experiments were arranged in a randomized block design with three N input rates (0, 800 and 2600/2000 kg N ha−1 year−1). We found that orchard soils were a negligible CH4 sink (−1.1 to −0.4 kg C ha−1 year−1). Annual N2O emissions responded positively to N input rates, ranging from 34.1 to 60.3 kg N ha−1 year−1. EFd ranged from 1.00% to 1.65% with a mean of 1.34%. The extremely large background emissions of N2O (34.1–34.3 kg N ha−1 year−1) most likely originated from nitrate accumulation in the soil profile because of historical overuse of N fertilizer. We conclude that (1) site-specific EFd is suitable for assessing regional direct N2O emissions from upland orchards; and (2) conventional fertilization regimes must be avoided, and reduced N input rates are recommended in the study region.

Neurobasis chinensis is widely distributed in eastern tropical Asia. Its only congener in China, the N. anderssoni, has not been observed for decades. To protect N. chinensis, it is necessary to understand the ecological properties of its habitats and specie’s range shift under climate change. In the present study, we modeled its potential distribution under one historical, current, and four future scenarios. We evaluated the importance of the factors that shape its distribution and habitats and predicted the historical and current core spatial distributions and their shifting in the future. Two historical core distribution areas were identified: the inland region of the Bay of Bengal and south-central Vietnam. The current potential distribution includes south China, Vietnam, Laos, Thailand, Myanmar, Luzon of Philippines, Malaysia, southwest and northeast India, Sri Lanka, Indonesia (Java, Sumatera), Bangladesh, Nepal, Bhutan, and foothills of the Himalayas, in total, ca. 3.59 × 106 km2. Only one core distribution remained, concentrated in south-central Vietnam. In a warming future, the core distribution, high suitable habitats, and even the whole range of N. chinensis will expand and shift northwards. Currently, N. chinensis mainly resides in forest ecosystems below 1200 m above sea level (preferred 500 m to 1200 m a.s.l.). Annual precipitation, mean temperature of driest quarter, and seasonality of precipitation are important factors shaping the species distribution. Our study provides systematic information on habitats and geographical distribution, which is useful for the conservation of N. chinensis.

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

Abstract Exploring the spatiotemporal variation characteristics of vegetation in the confluent area of water systems in western Jinan and its response mechanism to climatic factors is of great significance for the scientific evaluation of the benefits of the water system connectivity project and eco-environmental protection and can provide a reference for ecotourism development in the Jixi wetland park. Based on the Landsat series of images and meteorological data, this study used ENVI to interpret the normalized difference vegetation index (NDVI) of the confluent area from 2010 to 2021 and the spatiotemporal change characteristics and trends of NDVI were quantitatively analysed. The response of the growing-season NDVI (GSN) to climate factors and its time-lag effect were explored. The results showed that the overall change in the interannual NDVI in the confluent area from 2010 to 2021 was stable. The GSN in the confluent area was significantly positively correlated with precipitation, average temperature, and relative humidity in 37.64%, 25.52%, and 20.87% of the area respectively, and significantly negatively correlated with sunshine hours in 15.32% of the area. There was a time-lag effect on the response of the GSN to climate factors; the response to precipitation and sunshine hours lagged by one month, and the response to average temperature and relative humidity was longer.

In the context of climate change and rural revitalization, numerous solar photovoltaic (PV) panels are being installed on village roofs and lands, impacting the enjoyment of the new rural landscape characterized by PV panels. However, the visual acceptance of PV panels in rural areas of China is not yet fully understood. This study aims to identify and correlate three key influential factors that contribute to the acceptance and appreciation of PV panels in China’s rural settings. A quasi-experiment was conducted, incorporating diverse landscapes into six rural settings, each containing both the original landscape and PV panels. The findings demonstrated that the original rural landscape was significantly more scenic than PV panels, and factors contributing to the appreciation of traditional landscapes, such as nostalgia, played a vital role in rejecting PV panels. Conversely, renewable energy-related factors, such as economic stakes and moral desirability, were found to contribute to the acceptance of PV panels. This study contributes to the strategic planning and design of solar PV panels in rural landscapes, taking into consideration social acceptance and local contexts.

Lake Biwa, Japan represents a crucial example of the complex climatic and anthropogenic drivers influencing lake ecological transformations, vital to informing Sustainable Development Goals globally. This study utilizes 2002–2022 Landsat, MODIS and in situ Lake Biwa monitoring data to analyze surface layer spatiotemporal dynamics across interrelated vegetation, water quality and meteorological indicators—encompassing Normalized Difference Vegetation Index (NDVI), nitrogen (N), phosphorus (P), chlorophyll-a (Chl) and water temperature (W-TEM). Upward NDVI raster trends were found over 20 years alongside prevalent N, P and Chl declines—although some increases did occur spatially in P and Chl—while W-TEM mostly rose lakewide. Southwest–northeast gradients typified distributions. Further attribution analyses revealed W-TEM as the primary N, P and Chl driver, while agricultural expansion and urbanization mediated crucial N and P changes. Moreover, wind speed (WS), Crop, W-TEM, minimum temperature (TMMN), Chl and N constituted top NDVI raster influence factors respectively. These novel integrated models quantifying Lake Biwa ecological responses to multifaceted environmental change provide new perspectives to inform sustainable management of Lake Biwa itself and critical freshwater resources worldwide.