Insect Diapause

Our highly seasonal world restricts insect activity to brief portions of the year. This feature necessitates a sophisticated interpretation of seasonal changes and enactment of mechanisms for bringing development to a halt and then reinitiating it when the inimical season is past. The dormant state of diapause serves to bridge the unfavourable seasons, and its timing provides a powerful mechanism for synchronizing insect development. This book explores how seasonal signals are monitored and used by insects to enact specific molecular pathways that generate the diapause phenotype. The broad perspective offered here scales from the ecological to the molecular and thus provides a comprehensive view of this exciting and vibrant research field, offering insights on topics ranging from pest management, evolution, speciation, climate change and disease transmission, to human health, as well as analogies with other forms of invertebrate dormancy and mammalian hibernation.

Global Mean Sea Level. Time Trends and Persistence with Long Range Dependent Data

Global mean sea level data are examined in this work by looking at the presence of time trends in the context of long memory or long range dependent processes. By looking at both seasonal signals retained and seasonal signals removed data from 1992 to 2020, the results show that the two series display significant time trend coefficients and high levels of persistence.

Tracing δ18O and δ2H in Source Waters and Recharge Pathways of a Fractured-Basalt and Interbedded-Sediment Aquifer, Columbia River Flood Basalt Province

The heterogeneity and anisotropy of fractured-rock aquifers, such as those in the Columbia River Basalt Province, present challenges for determining groundwater recharge. The entrance of recharge to the fractured-basalt and interbedded-sediment aquifer in the Palouse region of north-central Idaho is not well understood because of successive basalt flows that act as restrictive barriers. It was hypothesized that a primary recharge zone exists along the basin’s eastern margin at a mountain-front interface where eroded sediments form a more conductive zone for recharge. Potential source waters and groundwater were analyzed for δ18O and δ2H to discriminate recharge sources and pathways. Snowpack values ranged from −22 to −12‰ for δ18O and from −160 to −90‰ for δ2H and produced spring-time snowmelt ranging from −16.5 to −12‰ for δ18O and from −120 to −90‰ for δ2H. With the transition of snowmelt to spring-time ephemeral creeks, the isotope values compressed to −16 and −14‰ for δ18O and −110 and −105‰ for δ2H. A greater range of values was present for a perennial creek (−18 to −13.5‰ for δ18O and −125 to −98‰ for δ2H) and groundwater (−17.5 to −13‰ for δ18O and −132 to −105‰ for δ2H), which reflect a mixing of seasonal signals and the varying influence of vapor sources and sublimation/evaporation. Inverse modeling and the evaluation of matrix characteristics indicate conductive pathways associated with paleochannels and deeper pathways along the mountain-front interface. Depleted isotope signals indicate quicker infiltration and recharge pathways that were separate from, or had limited mixing with, more evaporated water that infiltrated after greater time/travel at the surface.

Geocenter Variations Assessment using Frequency Analysis and Allan Variance Method

The objective of this work is to characterize the signals and noises of Geocenter variations time series obtained from different space geodesy techniques as Global Positioning System (GPS), Doppler Orbitography and Radiopositioning Integrated on Satellite (DORIS), and Satellite Laser Ranging (SLR). The proposed methodology is based on the estimation of periodic signals by performing frequency analysis using FAMOUS software (Frequency Analysis Mapping On Unusual Sampling) and evaluation of level and type of noises by Allan variance technique and Three Corned Hat (TCH) method. The available data concern 13 years (from 1993 to 2006) of weekly series of Geocenter residuals components and scale factor variations, according to ITRF2000. The results estimated are more accurate according to GPS and SLR of about 2-8 mm than DORIS of about 8-42 mm, for Geocenter. Better RMS of scale factor was obtained of about 0.1ppb (0.6mm) for GPS technique than SLR and DORIS with 0.6 and 0.9 ppb (3.6 and 5.4mm), respectively. The estimated seasonal signals amplitudes are in the range of few milimeters per technique with centimetre level for Z Geocenter component of DORIS. The Geocenter motion derived from SLR technique is more accurate and close to the geodynamic models. The noise analysis shows a dominant white noise in the SLR and DORIS Geocenter solutions at a level of 0.6-1 mm and 10-40 mm, respectively. However, the GPS solution is characterized by a flicker noise at millimetre level, relating to mismodeling systematic errors.

BOMB-PRODUCED RADIOCARBON ACROSS THE SOUTH PACIFIC GYRE—A NEW RECORD FROM AMERICAN SAMOA WITH UTILITY FOR FISHERIES SCIENCE

ABSTRACT Coral skeletal structures can provide a robust record of nuclear bomb produced 14C with valuable insight into air-sea exchange processes and water movement with applications to fisheries science. To expand these records in the South Pacific, a coral core from Tutuila Island, American Samoa was dated with density band counting covering a 59-yr period (1953–2012). Seasonal signals in elemental ratios (Sr/Ca and Ba/Ca) and stable carbon (δ13C) values across the coral core corroborated the well-defined annual band structure and highlighted an ocean climate shift from the 1997–1998 El Niño. The American Samoa coral 14C measurements were consistent with other regional records but included some notable differences across the South Pacific Gyre (SPG) at Fiji, Rarotonga, and Easter Island that can be attributed to decadal ocean climate cycles, surface residence times and proximity to the South Equatorial Current. An analysis of the post-peak 14C decline associated with each coral record indicated 14C levels are beginning to merge for the SPG. This observation, coupled with otolith measurements from American Samoa, reinforces the perspective that bomb 14C dating can be performed on fishes and other marine organisms of the region using the post-peak 14C decline to properly inform fisheries management in the South Pacific.

Characteristics of inherent coupling structure of model climates

This work proposes a framework to examine interactions of climate modes that are identified as leading EOF modes; their coupling structure is unveiled through correlation analysis and helps constructing a regression model, whose performance is compared across GCMs, thereby providing a quantitative overview of model performances in simulating mode-interaction. As demonstration surface temperature is analyzed for five CMIP5 PiControl simulations. Along with the seasonal land and ocean modes, four interannual modes are identified: Tropical Mode (TM) associated with the Hadley circulation, Tropical Pacific Mode (TPM) characterizing a zonal temperature contrast between the eastern tropical Pacific and the Atlantic-Indian ocean, and two annular modes: Arctic Mode (AM) and Ant-arctic Mode (AAM). All GCMs converge on the following: 1) TM strongly couples with seasonal signals of the previous year; 2) TPM leads TM by 1 year, thus a weaker zonal temperature contrast in the tropics contributes to warming in the entire tropical band one year later; 3) AM weakly couples to TM at a one-year lead, suggesting a colder north pole may contribute to colder tropics. In addition, all GCMs do not support a linear coupling between AAM and TM. The above-learned coupling structure is incorporated to construct an optimum regression model that demonstrates considerable predictive power. The proposed approach may both serve as a useful tool for dynamical analysis and lend insight into GCM differences. Its merit is demonstrated by the finding that different representations of the mean seasonal cycle in GCMs may account for the GCM-dependence of relative contributions of seasonal and inter-annual modes to TM variability.

Seasonal Signals Observed in Non-Contact Long-Term Road Texture Measurements

Texture is required on road pavements for safe vehicle braking and manoeuvres. This paper provides a unique analysis of long-term texture obtained using traffic speed condition survey (TRACS) data from 14 sites, located along a north to south transect spanning the longest highway in the UK. A total of 19 years of sensor measured texture depth (SMTD) data have been analyzed using spatial filtering techniques and compared with meteorological and traffic datasets. The results for hot rolled asphalt (HRA) surfaces reveal that changes to SMTD follow a linearly increasing trend with time. The “rate of change” is influenced by the order of magnitude of annual average daily traffic (AADT), when factored for the percentage of heavy goods vehicles. This linear trend is disrupted by environmental parameters, such as rainfall events and seasonal conditioning. In the summer, this signal is evident as a transient peak in the “rate of change” of texture greater than 0.04 mm, and in the winter as a reduction. The transient changes in texture corresponded to above average rainfall occurring in the week prior to SMTD measurement. The signal observed demonstrates an inverse pattern to the classically understood seasonal variation of skid resistance in the UK, where values are low in the summer and high in the winter. The findings demonstrate for the first time that texture measurements experience a seasonal signal, and provide compelling evidence pointing toward surface processes (such as polishing and the wetting and drying of surface contaminants) causing changes to texture that are affecting seasonal variation in skid resistance.

Changes in Air Pollution Following the COVID-19 Epidemic in Northern China: The Role of Meteorology

COVID-19 has a tremendous impact on both human life and the environment due to the unprecedented large-scale shutdown of economic activities at the beginning of 2020. While it was widely expected to see a dramatic reduction in air pollution, reality appears to be much more complex due to the joint influences of emissions and meteorology in dictating air pollution. By analyzing ample meteorological and environmental observational data, this study attempts to evaluate the contribution of an economic lockdown or at a well-below normal level across China to air pollution during the COVID-19 pandemic in the Beijing-Tianjin-Hebei region. Besides the unprecedented emission reductions that helped to improve air quality, multiple other factors came into play, such as high humidity and low wind speed that are favorable for haze formation. After separating long-term trends, seasonal signals, holiday effects, and meteorological contributions concerning climatology, we estimated that the relative contributions of human activities to changes in particulate matter with a diameter of less than 2.5 μm and nitrogen dioxide during the epidemic were −17.13 μg/m3 and −0.03 μg/m3, respectively, with negative quantities denoting reductions to air pollution. Furthermore, comparing the changes in PM2.5 and NO2 concentrations after lockdown revealed that for short-term control measures, meteorological factors mainly affected pollutant particles.

Detection of SST fronts from high-resolution model and its preliminary results in the South China Sea

A frontal detection algorithm is developed with the capability of detecting significant frontal segments of sea surface temperature (SST) in the high resolution South China Sea Operational Forecasting System (SCSOFS). In order to effectively obtain frontal information, a gradient-based Canny edge detection algorithm is improved with post-processing designed for high resolution numerical model, aiming at extracting primary ocean fronts, meanwhile ensuring the balance of frontal continuity and positioning accuracy. Metrics of frontal probability and strength are used to measure the robustness of the results in terms of mean state and seasonal variability of frontal activities in the South China Sea (SCS). Most fronts are found in the nearshore and forming a strip shape extending from the Taiwan Strait to the coast of Vietnam. The SCSOFS is found to reproduce strong seasonal signals dominating the variability of the frontal strength and occurrence probability in the SCS. We implement the algorithm on the daily-averaged SST derived from two other SST analyses for inter-comparison in the SCS.