Physiological and morphological response to short-term starvation and re-feeding in sub-yearling siberian sturgeon (Acipenser baerii Brandt, 1896): effects of compensatory growth

In this study, the capacity of Siberian sturgeon, Acipenser baerii with mean weight 19.3±0.4 g to face short-term starvation and subsequent re-feeding was assessed for a 40-day period. To investigate, the effect of compensatory growth on some physiological response (plasma cortisol, thyroid hormones, glucose, protein, cholesterol and triglyceride) and morphological (total body weight and length, condition factor, hepato-somatic index, vicero-somatic index and digestive-somatic index) in Siberian sturgeon four different feeding regimes were established. Control group fed four times daily to apparent satiation; SRF1: 2 days starvation and 8 days refeeding; SRF2: 4 days starvation and 16 days refeeding; SRF3: 8 days starvation and 32 days refeeding were experienced. At the end of experiment, blood samples were collected to analyze biochemical parameters. Plasma cortisol and thyroxin (T_4) hormones levels were not significantly different between control and food deprived groups at the end of experiment (P>0.05) but plasma tri-iodothyronin (T_3) levels were lower in the starved groups compared to control animals, but this decreases only in S1 group was significant (P0.05). Moreover, at the measured morphometric indices were not observed significantly different between the control and starved groups (P>0.05). The results suggest that Siberian sturgeon has the physiologic and metabolic adjustment ability to shortterm starvation and return to basal level after re-feeding

The effect of short-term starvation on some physiological and morphological parameters in juvenile Siberian sturgeon, Acipenser baerii (Actinopterygii: Acipenseriformes: Acipenseridae)

Background. Fish may experience periods of food deprivation or starvation in nature and under culture conditions. Because of the wild  stock reduction of some sturgeon species, Siberian sturgeon, Acipenser baerii Brandt, 1869, has been used as a biological model of physiological and nutritional studies since the 1980s. There are no published records on the physiological responses of Siberian sturgeon to starvation. Hence, in this study the effect of short-term starvation (0, 2, 4, and 8 days) on plasma thyroid hormones (T3 and T4), total protein levels, and hepato-somatic- (HSI), viscero-somatic- (VSI), and digestive-somatic (DSI) indices in juvenile Siberian sturgeon was investigated. Materials and methods. The experiment was conducted at the International Sturgeon Research Institute of Rasht (Iran) in October 2009, using a semi-natural environment (natural photoperiod and natural water temperature fluctuations). After a period of adaptation (10 days on a formulated diet), 180 juvenile Siberian sturgeon individuals (mean weight ± standard error at start of experiment: 19.32 ± 0.43, n = 15) were randomly distributed among twelve circular, 500-L, fibreglass tanks with a flow-through system. In this trial, control (C) was fed a formulated diet to apparent satiation four times daily throughout the experiment. The other three groups were deprived of feed for 2- (2S), 4- (4S), and 8 (8S) days, respectively. At the end of the starvation periods, blood samples were collected to analyze biochemical and physiological parameters. Results. Plasma T3, T4, and total protein levels did not significantly vary between the fed and the starved fish. In comparison to the starved groups, after 8 days of starvation, plasma total protein in group 8S (3.43 ± 0.20) was markedly higher than in 2S (2.67 ± 0.07) and 4S (2.37 ± 0.12) groups. In the presently reported study, a decrease in the measured morphometric indices was observed with an increase in the length of the starvation period. Conclusion. The results suggest that Siberian sturgeon has metabolic adjustment ability to short periods of starvation due to reduced basal metabolism rate and energy reserves utilization during starvation

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76,086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the conceptual model HBV against streamflow records for each of 9053 small to medium-sized (<50,000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1). Our results highlight large differences in estimation accuracy, and hence, the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite- and reanalysis-based P estimates

Remote Sensing of Drought: Vegetation, Soil Moisture, and Data Assimilation

Application of remote sensing is emerging for operational drought monitoring and early warning as it offers opportunities for assessing drought from different perspectives. This chapter provides an overview of the advances in monitoring different types of drought using satellite remote sensing observations with an example on agricultural drought assessment over the continental U.S. While the main constraint in remote sensing of drought is attributed to limited duration of records, this can be overcome by merging the remote-sensing observations with model simulations through data assimilation. The application of data assimilation as a promising approach is described for drought monitoring over the Pacific Northwest US