Remote sensing of the cyanobacteria life cycle: A mesocosm temporal assessment of a Microcystis sp. bloom using coincident unmanned aircraft system (UAS) hyperspectral imagery and ground sampling efforts.

Remote sensing technologies offer a consistent, spatiotemporal approach to assess water quality, which includes the detection, monitoring, and forecasting of cyanobacteria harmful algal blooms. In this study, a series of ex-situ mesoscale experiments were conducted to first develop and then monitor a Microcystis sp. bloom using a hyperspectral sensor mounted on an unmanned aircraft system (UAS) along with coincident ground sampling efforts including laboratory analyses and in-situ field probes. This approach allowed for the simultaneous evaluation of both bloom physiology (algal growth stages/life cycle) and data collection method on the performance of a suite of 41 spectrally-derived water quality algorithms across three water quality indicators (chlorophyll a, phycocyanin and turbidity) in a controlled environment. Results indicated a strong agreement between Lab and Field-based methods for all water quality indicators independent of growth phase, with regression R2-values above 0.73 for mean absolute percentage error (MAPE) and 0.87 for algorithm R2 values. Three of the 41 algorithms evaluated met predetermined performance criteria (MAPE and algorithm R2 values); however, in general, algal growth phase had a substantial impact on algorithm performance, especially those with blue and violet wave bands. This study highlights the importance of co-validating sensor technologies with appropriate ground monitoring methods to gain foundational knowledge before deploying new technologies in large-scale field efforts.

Temperature preference of juvenile lumpfish (Cyclopterus lumpus) originating from the southern and northern parts of Norway.

Fish are ectothermic animals and have body temperatures close to that of the water they inhabit. They can still control their body temperatures by selecting habitats with temperatures that maximize their growth, feed conversion and wellbeing. Lumpfish, Cyclopterus lumpus, is widely distributed in the North Atlantic Ocean and therefore exposed to variable water temperatures. Lumpfish is extensively used as cleanerfish in salmon farming in Norway and exposed to a wide temperature range along the north-south axis of the Norwegian coastline. But, if these temperature ranges correspond to the preference temperatures of lumpfish is not known. If lumpfish has adapted to regional temperatures along the Norwegian coast, differences in preference temperature for fish from different regions should be evident. In a selective breeding perspective, different selection lines for preference temperature would then be useful for further development of lumpfish as a cleanerfish. We subjected lumpfish juveniles weighing 154-426g originated from northern (Group North - GN) and southern (Group South - GS) Norway to a temperature preference test, using an electronic shuttle box system. The system allowed the fish to control the water temperature by moving between two chambers, and thereby choosing its preferred temperature in the range from 5 to 16 °C. We started the temperature at 7.8 ± 1.37 °C for GN and 7.58 ± 1.34 °C for GS, but all the fish except four (two each from GN and GS) chose lower temperatures (5.03-7.6 °C) in the first 18 h and stayed closer to that temperature during the next 30 h. Based on the results, GN and GS lumpfish preferred 6.92 ± 1.8 and 6.2 ± 1.2, respectively, and there was no significant difference between the groups. Neither was there any significant difference in growth rates (SGR) between the two groups. Based on our results, we suggest that lumpfish from any geographical origin along the Norwegian coast can be used anywhere in Norway. It follows that lumpfish from a single selection line could be used at any salmon farm in Norway independent of its location.

Pregnancy outcomes in women with kidney transplant: Metaanalysis and systematic review.

BACKGROUND: Reproductive function in women with end stage renal disease generally improves after kidney transplant. However, pregnancy remains challenging due to the risk of adverse clinical outcomes. METHODS: We searched PubMed/MEDLINE, Elsevier EMBASE, Scopus, BIOSIS Previews, ISI Science Citation Index Expanded, and the Cochrane Central Register of Controlled Trials from date of inception through August 2017 for studies reporting pregnancy with kidney transplant. RESULTS: Of 1343 unique studies, 87 met inclusion criteria, representing 6712 pregnancies in 4174 kidney transplant recipients. Mean maternal age was 29.6 ± 2.4 years. The live-birth rate was 72.9% (95% CI, 70.0-75.6). The rate of other pregnancy outcomes was as follows: induced abortions (12.4%; 95% CI, 10.4-14.7), miscarriages (15.4%; 95% CI, 13.8-17.2), stillbirths (5.1%; 95% CI, 4.0-6.5), ectopic pregnancies (2.4%; 95% CI, 1.5-3.7), preeclampsia (21.5%; 95% CI, 18.5-24.9), gestational diabetes (5.7%; 95% CI, 3.7-8.9), pregnancy induced hypertension (24.1%; 95% CI, 18.1-31.5), cesarean section (62.6, 95% CI 57.6-67.3), and preterm delivery was 43.1% (95% CI, 38.7-47.6). Mean gestational age was 34.9 weeks, and mean birth weight was 2470 g. The 2-3-year interval following kidney transplant had higher neonatal mortality, and lower rates of live births as compared to > 3 year, and < 2-year interval. The rate of spontaneous abortion was higher in women with mean maternal age < 25 years and > 35 years as compared to women aged 25-34 years. CONCLUSION: Although the outcome of live births is favorable, the risks of maternal and fetal complications are high in kidney transplant recipients and should be considered in patient counseling and clinical decision making.

Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations.

We analyzed 37 satellite reflectance algorithms and 321 variants for five satellites for estimating turbidity in a freshwater inland lake in Ohio using coincident real hyperspectral aircraft imagery converted to relative reflectance and dense coincident surface observations. This study is part of an effort to develop simple proxies for turbidity and algal blooms and to evaluate their performance and portability between satellite imagers for regional operational turbidity and algal bloom monitoring. Turbidity algorithms were then applied to synthetic satellite images and compared to in situ measurements of turbidity, chlorophyll-a (Chl-a), total suspended solids (TSS) and phycocyanin as an indicator of cyanobacterial/blue green algal (BGA) abundance. Several turbidity algorithms worked well with real Compact Airborne Spectrographic Imager (CASI) and synthetic WorldView-2, Sentinel-2 and Sentinel-3/MERIS/OLCI imagery. A simple red band algorithm for MODIS imagery and a new fluorescence line height algorithm for Landsat-8 imagery had limited performance with regard to turbidity estimation. Blue-Green Algae/Phycocyanin (BGA/PC) and Chl-a algorithms were the most widely applicable algorithms for turbidity estimation because strong co-variance of turbidity, TSS, Chl-a, and BGA made them mutual proxies in this experiment.

Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne hyperspectral imagery and dense surface observations.

This study evaluated the performances of twenty-nine algorithms that use satellite-based spectral imager data to derive estimates of chlorophyll-a concentrations that, in turn, can be used as an indicator of the general status of algal cell densities and the potential for a harmful algal bloom (HAB). The performance assessment was based on making relative comparisons between two temperate inland lakes: Harsha Lake (7.99 km2) in Southwest Ohio and Taylorsville Lake (11.88 km2) in central Kentucky. Of interest was identifying algorithm-imager combinations that had high correlation with coincident chlorophyll-a surface observations for both lakes, as this suggests portability for regional HAB monitoring. The spectral data utilized to estimate surface water chlorophyll-a concentrations were derived from the airborne Compact Airborne Spectral Imager (CASI) 1500 hyperspectral imager, that was then used to derive synthetic versions of currently operational satellite-based imagers using spatial resampling and spectral binning. The synthetic data mimics the configurations of spectral imagers on current satellites in earth's orbit including, WorldView-2/3, Sentinel-2, Landsat-8, Moderate-resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS). High correlations were found between the direct measurement and the imagery-estimated chlorophyll-a concentrations at both lakes. The results determined that eleven out of the twenty-nine algorithms were considered portable, with r2 values greater than 0.5 for both lakes. Even though the two lakes are different in terms of background water quality, size and shape, with Taylorsville being generally less impaired, larger, but much narrower throughout, the results support the portability of utilizing a suite of certain algorithms across multiple sensors to detect potential algal blooms through the use of chlorophyll-a as a proxy. Furthermore, the strong performance of the Sentinel-2 algorithms is exceptionally promising, due to the recent launch of the second satellite in the constellation, which will provide higher temporal resolution for temperate inland water bodies. Additionally, scripts were written for the open-source statistical software R that automate much of the spectral data processing steps. This allows for the simultaneous consideration of numerous algorithms across multiple imagers over an expedited time frame for the near real-time monitoring required for detecting algal blooms and mitigating their adverse impacts.