Pyrolysis of modern wetland sediment: extracting climate records from fens in the Uinta Mountains and Fish Lake Plateau,Utah, USA

Rock‐Eval pyrolysis provides a quick, relatively inexpensive means of characterizing organic‐rich strata, and has been used for decades to understand global petroleum systems. Although designed to characterize ancient kerogens, pyrolysis is increasingly being used to understand Holocene systems as well. The ability of this technique to distinguish between types of preserved organic matter is useful in characterizing climatic evolution, particularly in systems sensitive to climatic fluctuation such as isolated fens and bogs. Cores collected from the Tokewanna and Garden Basin Cattail fens in central/eastern Utah exhibit variability of organic source, with the mixture of terrestrial and algal sources varying through time, as shown through the hydrogen index (HI) and oxygen index pyrolysis parameters. A sediment core was collected at each fen, and 176 samples were taken from the cores at 6‐cm intervals. Total organic carbon (TOC) for all samples ranges from 1.3 to 44.2%, with an average of 18.2% TOC. Samples range from 84 to 687 HI, equivalent to Type I (lacustrine algal) to Type III (terrestrial) organic material (OM). Variability in HI response represents mixing of the two OM sources, and the relative amount of aqueous organic input can be estimated through time based on age‐calibrated HI curves at the two sites. The balance of organic input serves as an accurate, high‐resolution proxy for climate, and calibration with palynological data near both sites confirms patterns shown by pyrolysis, showing the utility of this method in quickly, affordably and accurately characterizing Holocene sediments for use in understanding palaeoclimate.     

Coronal images from the 1984 solar eclipse

We present digitized photographs of the white-light solar corona taken during the total solar eclipse of 22–23 November, 1984, on both calibrated black-and-white film and on color film. Conditions on site in Hula, Papua New Guinea, were exceptionally clear. The color image was used to produce an isophotal map of the inner corona, from which a flattening coefficient of 0.23 was measured. The black-and-white image was enhanced through a digital radial filter. Our images are the best processed images available from the 1984 eclipse and so provide important data for synoptic observations.     

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPI_JJA), Sep.–Nov. (SPI_SON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available.     

Political orientation and climate concern shape visual attention to climate change

Despite the scientific consensus, there is widespread public controversy about climate change. Previous explanations focused on interpretations hampered by political bias or insufficient knowledge of climate facts. We propose that public views of climate change may also be related to an attentional bias at a more basic level of cognitive processing. We hypothesized that selective visual attention towards or away from climate-related information would be associated with climate concern. To test prioritization of climate-related stimuli under conditions of limited attention, we asked participants to identify climate-related and neutral words within a rapid stream of stimuli. Undergraduate students attended to climate-related words more readily than neutral words. This attentional prioritization correlated with self-rated climate concern. We then examined this relationship in a more diverse community sample. Principal component analysis of survey data in the community sample revealed a component indexing a relationship between climate concern and political orientation. That component was correlated with the degree of selective inattention to climate-related words. Our findings suggest that climate-related communications may be most effective if tailored in a manner accounting for how attentional priorities differ between audiences—particularly those with different political orientations.     

Collating Historic Weather Observations for the East Asian Region:Challenges,Solutions,and Reanalyses

正1.Introduction Historic instrumental weather observations,made on land or at sea from as early as the 17th century(e.g.,Camuffo et al.,2010),are integral to extending our understanding of the decadal and centennial variations of Earth’s climate and for comparison with paleo-proxy data.The potential of such data is shown to best effect when used in dynamical 4D global     

ENSO and Sea Surface Temperature Anomalies in Association with Canadian Wheat Yield Variability

Interannual variations of spring wheat yields in Canadian agricultural regions are analyzed, together with the associated sea surface temperature (SST) anomalies in the northern hemisphere tropics and extratropics, from 1961 to 2015. The cubic trend is calculated and used to represent the trend related to advances in agricultural technology over this time period. The correlations between Canadian wheat yields at regional scales and the tropical El Niño–Southern Oscillation (ENSO) variability are not robust at any stage of the evolution of ENSO. Based on the power spectrum and cross-spectrum analysis, the most prominent yield variance is found in the Canadian Prairies, with a significant power peak of 4.5 years but does not co-vary significantly with interannual ENSO variability. ENSO weakly affects temperature and precipitation anomalies in the Canadian Prairie Region in summer—two important agroclimatic conditions for crop growth—and hence insignificantly impacts wheat yields. This indicates that there would be little benefit to including tropical ENSO indices in the operational wheat yield forecasting system. For Canadian wheat yield forecasting, attention should be paid to the preceding winter and spring SST anomalies in the northern extratropics. The SST anomalies associated with yields in the Canadian Prairie region and Central Region are generally stronger than those associated with yields in the Canadian Pacific Coast Region and eastern Maritime Region. In association with the Prairie Region and Central Region yields, SST shows pronounced anomalies in the mid-high latitudes of the North Pacific from winter to summer. The non-linearity of the SST anomalies associated with the Canadian yields is also clearly evident. Stronger (weaker) SST anomalies in the extratropical North Pacific correspond to low wheat yields in the Prairie (Central) Region, while weaker (stronger) SST anomalies correspond to high yields in the Prairie (Central) Region.     

Population Shrinkage in Resource-dependent Cities in China: Processes,Patterns and Drivers

Resource-dependent cities(RCs)are a vulnerable group of urban settlements that often face population shrinkage;however,population changes in RCs in China are not well understood.This study offers new insight into this matter through a robust analysis that features a longer time scale,a larger sample of RCs,and a finer unit of analysis.It finds new evidence that problems of population shrinkage in RCs are more serious than previous literature has suggested.Approximately 30%of the studied units have experienced either long-term or short-term population shrinkage,and many more are experiencing a slowing down of population growth.Problems are especially common among three types of RCs:the resource-depleted RCs,the forestry-based RCs,and RCs in Northeast China.These results underscore transition policy inadequacies in addressing population loss,and call for a more comprehensive and diversified population policy that tackles the multifaceted factors that contribute to population shrinkage,including lack of industrial support,maladjustment to market oriented reformation,poor urban environment and natural population decline.     

The Influence of Salinity on the Uptake, Distribution, and Excretion of Metals by the Smooth Cordgrass, Spartina alterniflora (Loisel.), Grown in Sediment Contaminated by Multiple Metals

The effect of salinity on the concentration of metals in Spartina alterniflora tissues and excreted salts and the distribution of metals between these compartments was tested in a greenhouse experiment. S. alterniflora stems were planted in pots of dredge sediment that was amended with a suite of six metals (Cd, Cr, Cu, Ni, Pb, and Zn). The overlying water of individual pots was maintained at treatment salinities of 0, 15, or 30 practical salinity units. The proportion of total metal distributed to the tissues and excreted salt of S. alterniflora was not significantly influenced by salinity for any of the metals. The concentration of Pb in root and leaf tissues and in excreted salt was influenced by salinity, as was the concentration of Zn in root tissue and excreted salt. Contrary to expectations, the concentration of Pb and Zn in excreted salts decreased as salinity increased. Although the influence of salinity on the concentration of Pb and Zn in S. alterniflora tissue has not been previously reported, the influence of salinity on the tissue concentrations of Pb agrees with previous research on dicots.