• Energy Research

Climate warming has significantly advanced plant spring phenology in temperate and boreal biomes in the northern hemisphere. However, the response of subtropical forest phenology to climate change remains largely unclear. This study aimed to determine the spatiotemporal patterns of spring photosynthetic phenology in subtropical forests in China over the period 2002-2017 and explore its underlying mechanism in response to the changes of different climate variables. We applied four methods to extract the start of the photosynthetic period (SOP) from a solar–induced chlorophyll fluorescence (SIF) data set during the period 2002 to 2017, and determined correlations between SOP and environmental factors using partial correlation analyses. Overall, the SOP was advanced by 6.8 days. Furthermore, we found that the SIF-based SOP is highly correlated with the flux data–based photosynthetic onset dates, demonstrating that SIF can be a useful index in characterizing the photosynthetic phenology in subtropical forests. Interestingly, based on partial correlation analysation temperature dominated the SOP in the northern subtropical forest, but the importance of precipitation increased with decreasing latitudes, and the primary climatic control of SOP in southern monsoon evergreen forests is precipitation. These results suggested that the predicted increase in temperature and shift in precipitation regimes under ongoing climate change might potentially largely affect the photosynthetic phenology, and thus affect the carbon and water cycles in subtropical forests.

AbstractArctic and subarctic ecosystems are experiencing substantial changes in hydrology, vegetation, permafrost conditions, and carbon cycling, in response to climatic change and other anthropogenic drivers, and these changes are likely to continue over this century. The total magnitude of these changes results from multiple interactions among these drivers. Field measurements can address the overall responses to different changing drivers, but are less capable of quantifying the interactions among them. Currently, a comprehensive assessment of the drivers of ecosystem changes, and the magnitude of their direct and indirect impacts on subarctic ecosystems, is missing. The Torneträsk area, in the Swedish subarctic, has an unrivalled history of environmental observation over 100 years, and is one of the most studied sites in the Arctic. In this study, we summarize and rank the drivers of ecosystem change in the Torneträsk area, and propose research priorities identified, by expert assessment, to improve predictions of ecosystem changes. The research priorities identified include understanding impacts on ecosystems brought on by altered frequency and intensity of winter warming events, evapotranspiration rates, rainfall, duration of snow cover and lake-ice, changed soil moisture, and droughts. This case study can help us understand the ongoing ecosystem changes occurring in the Torneträsk area, and contribute to improve predictions of future ecosystem changes at a larger scale. This understanding will provide the basis for the future mitigation and adaptation plans needed in a changing climate.

Climate change substantially affects plant phenology, resulting in earlier vegetation onset across temperate and boreal regions. Phenological shifts caused by warming may alter species interactions across trophic levels because of species-specific responses, and influence the reproductive success of dioecious species if the phenological sensitivity to warming (S T ) differs between genders. We used twigs collected from male and female gingko trees at three elevations on Tianmu Mountain in eastern China. The twigs were cultivated in climate chambers to determine the effects of three temperatures (10, 15, and 20 °C) and two photoperiods (8 and 16 h). We observed slightly earlier leaf unfolding dates in male twigs (1 day), and a higher heat requirement (growing degree hours) for leaf unfolding in female (14,334 ± 588 °C) compared to male twigs (13,874 ± 551 °C). Similar responses to temperature (S T = 3.7 days °C −1 ), photoperiod and elevation were observed across genders. The long photoperiod treatment shortened the time to leaf unfolding by 9.1 days, but temperature and photoperiod effects on leaf unfolding differed significantly depending on the elevation of the donor trees. Specifically, S T was higher (4.17 days °C −1 ) and the photoperiod effect on S T was larger (decreased by 1.15 days °C −1 ) at the lowest elevation than at the higher elevations (S T = 3.26 days °C −1 ; decreased by 0.48 days °C −1 ). This may be related to environment-induced local adaptations and self-protection mechanisms of trees at high elevations to avoid frost damage. Our results indicate that the photoperiod and genetic adaptations to local environments influenced the warming-induced phenological responses in ginkgo, but these responses were generally similar between the genders. For a given species, individuals in different climates may exhibit different phenological responses to higher temperatures, with individuals in warmer regions likely becoming increasingly limited by the photoperiod as the climate warms further.

AbstractLakes are important natural resources and carbon gas emitters and are undergoing rapid changes worldwide in response to climate change and human activities. A detailed global characterization of lakes and their long-term dynamics does not exist, which is however crucial for evaluating the associated impacts on water availability and carbon emissions. Here, we map 3.4 million lakes on a global scale, including their explicit maximum extents and probability-weighted area changes over the past four decades. From the beginning period (1984–1999) to the end (2010–2019), the lake area increased across all six continents analyzed, with a net change of +46,278 km2, and 56% of the expansion was attributed to reservoirs. Interestingly, although small lakes (<1 km2) accounted for just 15% of the global lake area, they dominated the variability in total lake size in half of the global inland lake regions. The identified lake area increase over time led to higher lacustrine carbon emissions, mostly attributed to small lakes. Our findings illustrate the emerging roles of small lakes in regulating not only local inland water variability, but also the global trends of surface water extent and carbon emissions.

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.

AbstractAutumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003–2017 based on a global, fine‐resolution solar‐induced chlorophyll fluorescence (SIF) dataset (GOSIF) using four fitting methods, and then explored the temporal–spatial variations of APTD and its underlying mechanisms using partial correlation analysis and machine learning methods. We further predicted the APTD shifts under future climate warming conditions by applying process‐based and machine learning‐based models. We found that the APTD was significantly delayed, with an average rate of 7.7 days per decade, in subtropical China during 2003–2017. Both partial correlation analysis and machine learning methods revealed that soil moisture was the primary driver responsible for the APTD changes in southern subtropical monsoon evergreen forest (SEF) and middle subtropical evergreen forest (MEF), whereas solar radiation controlled the APTD variations in the northern evergreen‐broadleaf deciduous mixed forest (NMF). Combining the effects of temperature, soil moisture and radiation, we found a significantly delayed trend in APTD during the 2030–2100 period, but the trend amplitude (0.8 days per decade) was much weaker than that over 2003–2017. In addition, we found that machine learning methods outperformed process‐based models in projecting APTD. Our findings generate from different methods highlight that soil moisture is one of the key players in determining autumn photosynthetic phenological processes in subtropical forests. To comprehensively understand autumn phenological processes, in‐situ manipulative experiments are urgently needed to quantify the contributions of different environmental and physiological factors in regulating plants' response to ongoing climate change.

Abstract Over the past half century, the Yangtze Plain of China has experienced rapid economic development. Lake reclamation (i.e., conversion of natural lake/wetland areas to agricultural/urban land or aquaculture, thereby reducing the area of natural waters) in particular has greatly contributed to meeting the increasing demands for food and urban development. However, until now, a comprehensive quantification and understanding of historical anthropogenic lacustrine exploitation in this region has been lacking, prohibiting assessment of the impacts of these activities. We used Landsat observations from 1973 to 2018 to track reclamation-induced changes in 112 large lakes (97.8% of the total lake area) in the Yangtze Plain. We show that 41.6% (6056.9 km2) of the total lake area has been reclaimed since the 1970s. The expansion of agricultural and built-up lands dominated the reclamation activities in the 1970s, while the increase of aquaculture zones has prevailed since the mid-1980s. Reclamation activities were closely connected to government policies and major socio-economic events and had strong impacts on lake hydrology, flood risk mitigation capacity, and water quality as revealed by satellite and in situ observations. This new quantitative understanding of anthropogenic reclamation and its associated impacts on Yangtze Plain freshwater lakes can underpin the development of strategies to reduce the impacts of lake reclamation on environmental quality. The study has also demonstrated the unique strength of using long-term series satellite images in tracking historical environmental changes in a substantial region of the world, and the methods used here are potentially extendable to other inland and coastal areas to understand similar human-environment interaction problems.

AbstractOver the past decades, global warming has led to a lengthening of the time window during which temperatures remain favorable for carbon assimilation and tree growth, resulting in a lengthening of the green season. The extent to which forest green seasons have tracked the lengthening of this favorable period under climate warming, however, has not been quantified to date. Here, we used remote sensing data and long‐term ground observations of leaf‐out and coloration for six dominant species of European trees at 1773 sites, for a total of 6060 species–site combinations, during 1980–2016 and found that actual green season extensions (GS: 3.1 ± 0.1 day decade−1) lag four times behind extensions of the potential thermal season (TS: 12.6 ± 0.1 day decade−1). Similar but less pronounced differences were obtained using satellite‐derived vegetation phenology observations, that is, a lengthening of 4.4 ± 0.13 and 7.5 ± 0.13 day decade−1 for GS and TS, respectively. This difference was mainly driven by the larger advance in the onset of the thermal season compared to the actual advance of leaf‐out dates (spring mismatch: 7.2 ± 0.1 day decade−1), but to a less extent caused by a phenological mismatch between GS and TS in autumn (2.4 ± 0.1 day decade−1). Our results showed that forest trees do not linearly track the new thermal window extension, indicating more complex interactions between winter and spring temperatures and photoperiod and a justification of demonstrating that using more sophisticated models that include the influence of chilling and photoperiod is needed to accurately predict spring phenological changes under warmer climate. They urge caution if such mechanisms are omitted to predict, for example, how vegetative health and growth, species distribution and crop yields will change in the future.