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Amano, T., Ripperger, J. A., & Albrecht, U. (2020). Changing the light schedule in late pregnancy alters birth timing in mice. Theriogenology, in press.
Abstract: In rats, birth timing is affected by changes in the light schedule until the middle of the pregnancy period. This phenomenon can be used to control birth timing in the animal industry and/or clinical fields. However, changes in the light schedule until the middle of the pregnancy period can damage the fetus by affecting the development of the major organs. Thus, we compared birth timing in mice kept under a 12-h light/12-h darkness schedule (L/D) throughout pregnancy with that of mice kept under a light schedule that changed from L/D to constant light (L/L) or constant darkness (D/D) from day 17.5 of pregnancy, the latter phase of the pregnancy period. On average, the pregnancy period was longer in D/D mice (19.9 days) than L/L or L/D mice (19.5 and 19.3 days, respectively, P < 0.05), confirming that light schedule affects birth timing. The average number of newborns was the same in L/L, L/D, and D/D mice (7.5, 7.8, and 7.9, respectively), but the average newborn weight of L/L mice (1.3 g) was lower than that of L/D and D/D mice (both 1.4 g, P < 0.05), indicating that constant light has detrimental effects on fetus growth. However, the percentage of dead newborns was the same between L/L, L/D, and D/D mice (11.1, 10.6, and 3.6%, respectively). The serum progesterone level on day 18.5 of pregnancy in L/D mice was 42.8 ng/ml, lower (P < 0.05) than that of D/D mice (65.3 ng/ml), suggesting that light schedule affects luteolysis. The average pregnancy period of mice lacking a circadian clock kept under D/D conditions from day 17.5 of pregnancy (KO D/D) (20.3 days) was delayed compared with wild-type (WT) D/D mice (P < 0.05). However, the average number of newborns, percentage of births with dead pups, and weight per newborn of KO D/D mice (7.6, 3.6%, and 1.4 g, respectively) were the same as WT mice kept under D/D conditions. A direct effect of the circadian clock on the mechanism(s) regulating birth timing was questionable, as the lighter average weight per KO fetus (0.6 g) versus WT fetus (0.7 g) on day 17.5 of pregnancy might have caused the delay in birth. The range of birth timing in KO D/D mice was the same as that of WT D/D mice, indicating that the circadian clock does not concentrate births at one time.
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Baekelandt, S., Milla, S., Cornet, V., Flamion, E., Ledore, Y., Redivo, B., et al. (2020). Seasonal simulated photoperiods influence melatonin release and immune markers of pike perch Sander lucioperca. Sci Rep, 10(1), 2650.
Abstract: Melatonin is considered as the time-keeping hormone acting on important physiological functions of teleosts. While the influence of melatonin on reproduction and development is well described, its potential role on immune functions has little been considered. In order to better define an immune modulation by the melatonin hormone, we hypothesized that natural variations of photoperiod and subsequent changes in melatonin release profile may act on immune status of pikeperch. Therefore, we investigated during 70 days the effects of two photoperiod regimes simulating the fall and spring in western Europe, on pikeperch physiological and immune responses. Samples were collected at 04:00 and 15:00 at days 1, 37 and 70. Growth, plasma melatonin levels, innate immune markers and expression of immune-relevant genes in head kidney tissue were assessed. While growth and stress level were not affected by the seasonal simulated photoperiods, nocturnal levels of plasma melatonin were photoperiod-dependent. Innate immune markers, including lysozyme, complement, peroxidase and phagocytic activities, were stimulated by the fall-simulated photoperiod and a significant correlation was made with plasma melatonin. In addition to bring the first evidence of changes in fish immunocompetence related to photoperiod, our results provide an additional indication supporting the immunomodulatory action of melatonin in teleosts.
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Lieske, D. J., Tranquilla, L. M. F., Ronconi, R. A., & Abbott, S. (2020). “Seas of risk”: Assessing the threats to colonial-nesting seabirds in Eastern Canada. Marine Policy, 115, 103863.
Abstract: This study presents the results of the first broad-scale, spatial cumulative impact analysis (SCIA) conducted for colonial-nesting seabirds at-sea in eastern Canada. Species distribution models, based on at-sea tracking data for thirteen species/groups of seabirds (n = 520 individuals), were applied to over 5000 species-specific colonies to map relative abundance patterns across the entire region. This information was combined with distributional data for a number of key anthropogenic threats to quantify exposure to fisheries, light and ship-source oil pollution, and marine traffic. As a final step, information about species-specific sensitivity to each threat was integrated to compute region-wide cumulative risk.
The data products permit the visualization of the interaction between species and threats, and confirm that large portions of the coastal zones of Nova Scotia and Newfoundland, as well as the Grand Banks shelf break, constitute areas where breeding seabirds experience the highest potential impact. The cumulative risk maps revealed that species which were either widespread throughout coastal areas (e.g., gulls), or capable of foraging long distance (Leach's Storm-Petrel), were most at risk. Cumulative risk maps help identify appropriate and potentially effective management and conservation actions, and are of value to federal regulators responsible for managing cumulative effects as part of the new Canadian Impact Assessment Act. They also can assist marine planners achieve the Aichi marine conservation targets as specified by the Convention on Biodiversity. By filling a knowledge gap for a large potion of the northwest Atlantic, these results help to counter the “shifting baselines syndrome”.
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Zheng, Q., Weng, Q., & Wang, K. (2020). Correcting the Pixel Blooming Effect (PiBE) of DMSP-OLS nighttime light imagery. Remote Sensing of Environment, 240, 111707.
Abstract: In the last two decades, the advance in nighttime light (NTL) remote sensing has fueled a surge in extensive research towards mapping human footprints. Nevertheless, the full potential of NTL data is largely constrained by the blooming effect. In this study, we propose a new concept, the Pixel Blooming Effect (PiBE), to delineate the mutual influence of lights from a pixel and its neighbors, and an integrated framework to eliminate the PiBE in radiance calibrated DMSP-OLS datasets (DMSPgrc). First, lights from isolated gas flaring sources and a Gaussian model were used to model how the PiBE functions on each pixel through point spread function (PSF). Second, a two-stage deblurring approach (TSDA) was developed to deconvolve DMSPgrc images with Tikhonov regularization to correct the PiBE and reconstruct PiBE-free images. Third, the proposed framework was assessed by synthetic data and VIIRS imagery and by testing the resulting image with two applications. We found that high impervious surface fraction pixels (ISF > 0.6) were impacted by the highest absolute magnitude of PiBE, whereas NTL pattern of low ISF pixels (ISF < 0.2) was more sensitive to the PiBE. By using TSDA the PiBE in DMSPgrc images was effectively corrected which enhanced data variation and suppressed pseudo lights from non-built-up pixels in urban areas. The reconstructed image had the highest similarity to reference data from synthetic image (SSIM = 0.759) and VIIRS image (r = 0.79). TSDA showed an acceptable performance for linear objects (width > 1.5 km) and circular objects (radius > 0.5 km), and for NTL data with different noise levels (<0.6σ). In summary, the proposed framework offers a new opportunity to improve the quality of DMSP-OLS images and subsequently will be conducive to NTL-based applications, such as mapping urban extent, estimating socioeconomic variables, and exploring eco-impact of artificial lights.
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Yeh, C., Perez, A., Driscoll, A., Azzari, G., Tang, Z., Lobell, D., et al. (2020). Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. Nat Commun, 11(1), 2583.
Abstract: Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery. Models can explain 70% of the variation in ground-measured village wealth in countries where the model was not trained, outperforming previous benchmarks from high-resolution imagery, and comparison with independent wealth measurements from censuses suggests that errors in satellite estimates are comparable to errors in existing ground data. Satellite-based estimates can also explain up to 50% of the variation in district-aggregated changes in wealth over time, with daytime imagery particularly useful in this task. We demonstrate the utility of satellite-based estimates for research and policy, and demonstrate their scalability by creating a wealth map for Africa's most populous country.
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