Lars H. Holbech, Francis Gbogbo, Timothy Khan Aikins. 2018: Abundance and prey capture success of Common Terns (Sterna hirundo) and Pied Kingfishers (Ceryle rudis) in relation to water clarity in south-east coastal Ghana. Avian Research, 9(1): 25. DOI: 10.1186/s40657-018-0116-7
Citation: Lars H. Holbech, Francis Gbogbo, Timothy Khan Aikins. 2018: Abundance and prey capture success of Common Terns (Sterna hirundo) and Pied Kingfishers (Ceryle rudis) in relation to water clarity in south-east coastal Ghana. Avian Research, 9(1): 25. DOI: 10.1186/s40657-018-0116-7

Abundance and prey capture success of Common Terns (Sterna hirundo) and Pied Kingfishers (Ceryle rudis) in relation to water clarity in south-east coastal Ghana

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  • Corresponding author:

    l.holbech@gmail.com

  • Received Date: 12 Nov 2017
  • Accepted Date: 05 Jul 2018
  • Available Online: 24 Apr 2022
  • Publish Date: 15 Jul 2018
  • Background 

    Water clarity may negatively influence rate of plunge diving and prey capture success of piscivorous plunge-diving birds, and therefore has implications for their conservation in polluted urban wetlands. We studied the relationship between water clarity and the abundance and prey capture success of Pied Kingfishers (Ceryle rudis) and Common Terns (Sterna hirundo) in two polluted coastal waters of south-east Ghana—the Weija Lake and Densu Delta Ramsar Site.

    Methods 

    On each wetland, data on abundance and prey capture success of plunge-divers were collected in four spatio-temporal quadrats of 100 m?×?100 m and analysed with concurrent measurements of water quality parameters using GLM regression with Pearson's correlation coefficients.

    Results 

    Mean prey capture success of Pied Kingfishers (34.7?±?13.1%) and Common Terns (35.3?±?11.0%) were similar but the two species responded differently to water clarity. The abundance of Common Terns was significantly higher in less transparent/more turbid water while that of Pied Kingfishers showed no significant relationship with turbidity and transparency. In contrast, the prey capture success of Common Terns was neither related to transparency nor turbidity, as opposed to that of Pied Kingfishers which was significantly higher in more turbid/less transparent waters. Correlations between capture success and bird abundance, as well as capture attempts were insignificant, suggesting that increased fish abundance associated with cloudy water may not necessarily promote higher abundance and capture success of foraging birds. Thus, when foraging in less transparent water, capture success may depend more on predator avoidance by fish prey than lower prey detectability of foraging birds.

    Conclusion 

    Within a gradient of 15-51 cm transparency studied, lower water clarity did not constrain prey capture success of Common Terns and Pied Kingfishers. Further studies on the foraging ecology of plunge-divers in coastal Ghana are however required to make firm conclusions on the relationship between water clarity and foraging birds and fish prey abundances, as well as capture success.

  • Phenotypic flexibility allows individual organisms to match phenotypes to environmental or ecological demands (Piersma and Drent 2003; Nussey et al. 2005; Swanson et al. 2014). Flexibility of physiological phenotypes within individuals can be expected when environmental demands vary over time as a result of ontogeny, shifting environmental regimes (e.g., winter cold or food shortage), or behavioral decisions (e.g., to reproduce or migrate) (Diamond and Hammond 1992). Food is an important factor affecting animals' energy metabolism; food resource and quality, as well as animals' assimilative capacity, have a major effect on metabolic rate (Brzęk and Konarzewski 2001; Killpack and Karasov 2012).

    The life history of many animals includes extended periods of food scarcity (Hiebert 1991; Foster 1997). In birds, different strategies for coping with food shortage have been described, including torpor (Ruf and Geiser 2014), food hoarding (Garamszegi and Eens 2004), and seasonal migration (Pierce and McWilliams 2004). Winter acclimatization and seasonal migration in small birds living in cold climates produce a phenotype characterized by up-regulation of metabolic rate to meet enhanced thermoregulatory demands (Swanson 2010). Decreased food availability, shortened day length for foraging, and increased energy demands due to decreased ambient temperature, indicate that winter is an energetically challenging time for homoeothermic animals (Doucette and Geiser 2008; Liknes and Swanson 2011; Swanson et al. 2014). Although residency and migration are different life-history strategies, they are unified by the common physiological necessity for elevated aerobic capacity and endurance in response to elevated energy expenditure during certain periods of the annual cycle (Dawson et al. 1983; Swanson 2010). It has been demonstrated that a bird's body mass and composition (Kelly and Weathers 2002), energy balance (Liang et al. 2015), basal metabolic rate (BMR) (AL-Mansour 2004; McKechnie and Wolf 2004; Gutiérrez et al. 2011), and reproduction (Perrins 1965; Robb et al. 2008) are all affected by food restriction. Such changes include changes in both physiology and metabolism (Marjoniemi 2000). In laboratory animals, food and calorie restriction have been found to have many beneficial effects (Harper et al. 2006). However, such beneficial effects are at least partially lost when studying wild, or wild-derived, animals. Very few studies have focused on calorie restriction in birds (Ottinger et al. 2005). For example, adaptive and active decreases in energy expenditure in response to food shortage can be pronounced; for example some trochilifromes and galliformes can reduce their metabolic rate by 30‒40% in thermoneutral conditions, eventually entering torpor (Hainsworth et al. 1977; Prinzinger and Siedle 1988). Liang et al. (2015) found when food is limited, birds consume energy reserves, reducing body mass, body fat and organ mass in order to maintain essential metabolic functions. They also reduce energy consumption by reducing their basal metabolic thermogenesis. Birds also use food as a cue for the onset of breeding and food availability can constrain females' ability to produce eggs (Perrins 1965; Boutin 1990). In addition, food restriction may attenuate mitochondrial bioenergetics and oxidative stress in the striped hamster (Cricetulus barabensis) (Zhang et al. 2016). Therefore, substantial efforts have been made to examine the effects of food restriction on animal survival, adaptation, and reproductive success (Prinzinger and Siedle 1988; Robb et al. 2008).

    BMR (basal metabolic rate) in small birds is an example of a flexible trait that can be seasonally modulated through adjustments at several levels of organization (McKechnie 2008; Swanson 2010). At the organ level, changes in the mass of metabolically active organs can influence BMR (Daan et al. 1990; Williams and Tieleman 2000; Liu and Li 2006; Zheng et al. 2008a, 2014a). Internal organs (i.e., the liver, kidney, heart, and digestive tract) represent less than 10% of body mass, but contribute more than 60% of energy expenditure (Clapham 2012). At the biochemical level, variation in cellular catabolic enzyme activities and/or capacity for metabolic substrate transport in the liver and muscle is often measured by examining variation in state-4 respiration (reflecting oxidative phosphorylation capacity), the activity of citrate synthase (CS; a key regulatory enzyme of the Krebs cycle) or cytochrome c oxidase (COX; a key regulatory enzyme of oxidative phosphorylation) (Vézina and Williams 2005; Swanson 2010). In addition to these morphological and physiological adjustments, molecular regulation might also contribute to variation in thermogenesis in birds (Bicudo et al. 2001; Dridi et al. 2004). Uncoupling proteins (UCPs), located in the inner membrane of mitochondria, have the potential to dissipate free energy as heat by uncoupling oxidative phosphorylation (Ricquier and Bouillaud 2000). UCP1, the first uncoupling protein, is expressed exclusively in brown adipose tissue (BAT), which is critical for protection against the cold in rodents (Cannon and Nedergaard 2004), and has been implicated in regulating both thermogenesis and energy balance (Ricquier and Bouillaud 2000). In recent years, uncoupling protein gene homologues have been cloned and sequenced from chicken skeletal muscle, avian uncoupling protein (avUCP) (Raimbault et al. 2001; Rey et al. 2010; Teulier et al. 2010) and hummingbird (HmUCP) (Vianna et al. 2001), and are thought to play a key role in facultative thermogenesis in birds in response to cold, mainly through non-shivering thermogenesis (NST). However, recent evidence suggests that the primary role of avUCP is regulating oxidative balance rather than thermoregulation (Talbot et al. 2004; Mozo et al. 2005; Teulier et al. 2010).

    The Chinese Bulbul (Pycnonotus sinensis) is a small passerine with a wide geographical range that includes vast areas of central, southern, and eastern China, as well as other parts of eastern and southern Asia, including regions with cold winters (MacKinnon and Phillipps 2000). It is common in Zhejiang Province and has recently spread to central China. Within its natural range, the Chinese Bulbul prefers scrub lands, bamboo and coniferous forest, but also lives around villages on deforested plains and hills (Zheng and Zhang 2002). The Chinese Bulbul is omnivorous, feeding mainly on arthropods (e.g., insects and spiders) and mollusks (e.g., snails and slugs) in spring and summer and plant foods (e.g., buds, fruits and seeds) in autumn and winter (Peng et al. 2008). Elevated winter BMR in bulbuls is associated with elevated nutritional and exercise organ mass and heightened respiratory enzyme activity in the liver and muscle (Zhang et al. 2008; Zheng et al. 2008a, b, 2010). Decreased BMR in bulbuls is associated with decreased nutritional and exercise organ mass during periods of food shortage (Liang et al. 2015). With global warming, Chinese Bulbuls have recently spread to northern China—a region with less food in winter, but a similar average temperature to the pre-global warming temperature in southern China (Zheng et al. 2010). Bulbuls are non-migratory and must therefore have greater capacity to adjust their energetic expenditure and thermogenesis in response to seasonal changes in temperature and food availability than migratory birds. It is therefore of interest to examine the features underlying this flexibility.

    In this study, we used an integrative approach to measure changes in thermogenic properties of Chinese Bulbuls during food restriction at different levels of biological organization from the physiological to molecular, including BMR, nutritional and exercise organ mass, mitochondrial state-4 respiration and COX activity in the liver and muscle, and avUCP mRNA expression in muscle. More specifically, we test the hypothesis that bulbuls adjust to food restriction by decreasing their body mass and the mass of various internal organs, and by reducing their BMR, state-4 respiration, COX activity and avUCP mRNA content.

    This study was carried out in Wenzhou City, Zhejiang Province (27°29ʹN, 120°51ʹE, 14 m in elevation), China. The climate is warm-temperate with an average annual rainfall of 1500 mm spread across all months with slightly more precipitation during spring and summer. Mean daily temperatures range from 28‒39 ℃ in July to 3‒8 ℃ in January (Zheng et al. 2008b, 2014a).

    Adult Chinese Bulbuls were captured by mist nets in Wenzhou City in October 2012, then transported to the laboratory and maintained in individual enclosures (60 cm × 60 cm × 30 cm) at 25 ± 1 ℃ on a 12:12-h light-dark photoperiod with lights on at 06:00 a.m. Food (commercial bulbul pellets: 20% crude protein, 6% crude fat, 4% crude fiber, 1% calcium; Xietong Bioengineering, Jiangsu, China) and water were supplied ad libitum (Zheng et al. 2013a). Chinese Bulbuls showed significant seasonal variation in body mass; birds were 21% heavier in winter than summer (Zheng et al. 2014a). Birds were kept under these conditions for 2 weeks, then randomly assigned to one of two groups; a control group (n = 12), which had access to food ad libitum, and a food restriction group (FR) (n = 10), which was provided with one-half of the usual quantity of food for 12 days (Karasov et al. 2004). All experimental procedures were approved by the Wenzhou City Animal Care and Use Committee.

    Oxygen consumption was measured using an open-circuit respirometry system (S-3A/I, AEI technologies, Pittsburgh, PA, USA) (Zheng et al. 2014a; Wu et al. 2015). The metabolic chambers were 1.5 L in volume and contained a perch for birds to stand on (Smit and McKechnie 2010). Individual birds were allowed to rest in a metabolic chamber which was housed in a temperature-controlled cabinet capable of regulating temperature to ± 0.5 ℃ (Artificial Climatic Engine BIC-300, Shanghai, China). Air was scrubbed of H2O and CO2 by passing it through a silica gel/soda lime/silica column, before and after passing through the metabolic chamber. The fractional concentrations of oxygen in excurrent gas were measured from the metabolic chamber with an oxygen sensor (AEI Technologies N-22 M, USA). The pump was located downstream of the metabolic chamber and air was pulled through the chamber at 300 mL/min by the pump during metabolic rate measurements. This maintained a fractional concentration of O2 in the respirometry chamber of about 20%, calibrated to ± 1% accuracy with a general purpose thermal mass flow-meter (TSI 4100 Series, USA) (McNab 2006). Oxygen consumption rates were measured at 25 ± 0.5 ℃, which is within the thermal neutral zone of the Chinese Bulbul (Zheng et al. 2008b, 2014a). Baseline O2 concentrations were obtained before and after each test (Li et al. 2010; Wu et al. 2015). All gas exchange measurements were obtained during the rest-phase of birds' circadian cycles (between 20:00 and 04:00) in dark chambers. Food was removed 4 h before each test to create post-absorptive conditions. Measurement of oxygen consumption commenced when birds were observed perching calmly in the chamber and continued for 1 h. Each animal was generally in the metabolic chamber for at least 2 h. From these data, we calculated 5 min running means of steady-state oxygen consumption over the entire test period using equation 2 of Hill (1972) and considered the lowest 5 min mean oxygen consumption recorded over the test period as the resting metabolic rate (Wu et al. 2015). Metabolic rates were expressed as mL O2/h and corrected to STPD conditions. Body mass was measured to the nearest 0.1 g before and after experiments; mean body mass was used in calculations.

    Birds were killed by decapitation after metabolic measurements were completed and their pectoral muscle, brain, heart, lungs, liver, kidneys, gizzard, small intestine, and rectum removed and weighed to ± 0.1 mg. Sub-samples of liver and muscle were used for preparation of mitochondria (Zheng et al. 2008a, 2014b). Internal organs, including the remaining portions of the liver and muscle, were dried to a constant mass over 2 d at 65 ℃ and weighed to ± 0.1 mg (Williams and Tieleman 2000; Zhang et al. 2008). The remainder of the carcass was then weighed to determine its wet mass, then dried in an oven at 65 ℃ to a constant mass and then reweighed (to ± 0.1 mg) to determine its dry mass (Liu and Li 2006; Zheng et al. 2008a). Total fat was extracted from the dried carcasses by ether extraction in a Soxtec 2050 Soxhlet apparatus (FOSS Instrument, Germany). Body and liver fat content was calculated according to Dawson et al. (1983) and Wu et al. (2014) as follows:

    Bodyfatcontent(%)=(totalfatofcarcass/wetcarcassmass)×100%Liverfatcontent(%)=(totalfatofliver/wetlivermass)×100%
    (1)

    Liver and pectoral muscle sub-samples were cleaned of any adhering tissue, blotted dry, and weighed before being placed in ice-cold sucrose-buffered medium. Both liver and pectoral muscle samples were then coarsely chopped with scissors, after which liver samples were rinsed and resuspended in 5 vol of ice-cold medium (250 mmol/L sucrose, 5 mmol/L Tris/HCl, 1 mmol/L MgCl2 and 0.5 mmol/L EDTA, pH 7.4, 4 ℃) (Rasmussen et al. 2004). Pectoral muscle samples were treated with proteinase for 5‒10 min, then resuspended in 10 vol of ice-cold medium (100 mmol/L KCl, 50 mmol/L Tris/HCl, 5 mmol/L MgSO4 and 1 mmol/L EDTA, pH 7.4, 4 ℃). Liver and muscle preparations were then homogenized in a Teflon/glass homogenizer. Homogenates were centrifuged at 600g for 10 min at 4 ℃ in an Eppendorf centrifuge after which the resultant pellets of nuclei and cell debris was discarded. The supernatants were then centrifuged at 12, 000g for 10 min at 4 ℃. The resultant pellets were suspended, respun at 12, 000g, resuspended, and the final pellets (2:1, w/v for liver and 4:1 for muscle) placed in ice-cold medium (Zheng et al. 2013b; Zhou et al. 2016). The protein content of mitochondria was determined by the Folin phenol method with bovine serum albumin as standard (Lowry et al. 1951).

    We measured mitochondrial state-4 respiration in liver and pectoral muscle at 30 ℃ in 1.96 mL of respiration medium (225 mmol/L sucrose, 50 mmol/L Tris/HCl, 5 mmol/L MgCl2, 1 mmol/L EDTA and 5 mmol/L KH2PO4, pH 7.4) with a Clark electrode (Hansatech Instruments LTD., England, DW-1), essentially as described by Estabrook (1967). State-4 respiration and cytochrome c oxidase (COX) activity were measured in both muscle and liver tissue. State-4 respiration was measured over a 1 h period under substrate dependent conditions, with succinate as the substrate (Zheng et al. 2013b, 2014a). COX activity was measured polarographically at 30 ℃ using a Clark electrode as described in Sundin et al. (1987). We express state-4 respiration and COX activity measurements as mass-specific [µmol O2/(min g tissue)], measurements (Wiesinger et al. 1989; Zheng et al. 2013b, 2014b).

    Avian uncoupling protein (avUCP) mRNA expression was determined in pectoral muscle by quantitative Real-time PCR (RT-qPCR). Total RNA was isolated from bulbul pectorals muscle as described by Chomczynski and Sacchi (1987) using the E.Z.N.A Total RNA Extraction Kit (R6834-02, Omega). The integrity of the RNA obtained was tested using agarose electrophoresis and the RNA concentration was estimated with a Micro-Ultraviolet Spectrophotometer (NanoDrop 2000c, Thermo Scientific). A Reverse Transcription System (A3500, Promega) was used to manufacture cDNA samples with total RNA as the template. A 10 μL RT mixture of each sample (1 μg total RNA) was prepared using 2 μL of 10× Buffer, 4 μL of MgCl2 (25 mmol/L), 2 μL dNTP Mixture (10 mmol/L), 0.5 μL Recombinant RNasin® Ribonuclease Inhibitor, 15 U of AMV Reverse Transcriptase (High Conc.), 0.5 μL of Oligo (dT) (15 Primer) and nuclease-free water to a final volume of 20 μL. Specific primers were designed based on the cDNA sequence of the Chinese Bulbul listed in GenBank (Accession No. JQ353836). The avUCP primers were 5ʹ-CTCTGGGGACGGGAATGT-3ʹ (forward) and 5ʹ-AGGAAGGACGGGACGAAG-3ʹ (reverse). The reference primer β-actin was made essentially as described by Rey et al. (2008). The reaction began with an initial denaturation for 5 min at 95 ℃ followed by 40 cycles of denaturation at 94 ℃ for 30 s, annealing at 60 ℃ for 15 s, and extension at 72 ℃ for 30 s.

    Data were analyzed using SPSS (version 19.0). The normality of all variables was examined with the Kolmogorov-Smirnov test and non-normally distributed data were log10 transformed. The significance of between-group differences were evaluated with an independent sample t test. In order to correct for the effect of body mass, analysis of covariance (ANCOVA) was used to analyze between-group differences in organ mass, using body mass minus wet organ mass as a covariate for the organ in question to avoid part-whole correlations (Christians 1999). Partial and residual correlations were used to evaluate the relationship between BMR and dry organ mass, and least-squares linear regression to evaluate the relationships between log BMR and log body mass, log state-4 respiration, log COX and log avUCP. p values < 0.05 were considered statistically significant.

    No between-group differences in body mass (t20 = 0.299, p = 0.704) or BMR (t20 = 0.904, p = 0.377) were found prior to food restriction. However, birds in the FR group underwent a significant decrease in body mass (t20 = 4.838, p < 0.0001; Fig. 1a) and BMR (t20 = 2.292, p = 0.033; Fig. 1b), relative to those in the control group. A significant, positive correlation was found between body mass and BMR (R2 = 0.201, p = 0.036; Fig. 1c).

    Figure  1.  Comparison of body mass (a), basal metabolic rate (b), and the relationship between body mass and basal metabolic rate (c), between Chinese Bulbuls (Pycnonotus sinensis) that were provided with food ad libitum (control group) and those that were provided with half the usual quantity of food (food restriction group), after 12 days. Data are shown as mean ± SEM, *p < 0.05, ***p < 0.001. FR food restriction group

    The FR group had significantly lower body fat (t20 = 4.631, p < 0.0001) and liver fat (t20 = 12.484, p < 0.0001) compared to the control group after 12 days of food restriction (Fig. 2a). The mass of the heart, kidneys, small intestine and total digestive tract was also significantly lower in the FR group than in the control group (Table 1). There was a positive correlation between body mass and body fat (R2 = 0.491, p < 0.0001; Fig. 2b), and between body mass and liver fat (R2 = 0.408, p = 0.001; Fig. 2c). Partial correlation analysis indicated significant, positive correlations between BMR and dry heart mass and between BMR and dry kidney mass (Table 2).

    Figure  2.  Comparison of body and liver fat content (a), the relationship between body mass and body fat mass (b), and the relationship between body mass and liver fat mass (c), between Chinese Bulbuls (Pycnonotus sinensis) that were provided with food ad libitum (control group) and those that were provided with half the usual quantity of food (food restriction group), after 12 days. Data are shown as mean ± SEM, ***p < 0.001. FR food restriction group
    Table  1.  Dry mass of various internal organs (controlled for body mass minus wet organ mass) of Chinese Bulbuls (Pycnonotus sinensis) after 12 days food restriction
    Control FR Significance
    Sample size (n) 12 10
    Muscle (mg) 297.0 ± 22.3 220.0 ± 25.4 F1, 19 = 3.585, p = 0.074
    Brain (mg) 187.5 ± 10.4 203.0 ± 11.9 F1, 19 = 0.664, p = 0.425
    Heart (mg) 75.4 ± 5.3 58.3 ± 6.1 F1, 19 = 4.504, p = 0.047
    Lung (mg) 57.0 ± 3.6 53.9 ± 4.2 F1, 19 = 0.217, p = 0.646
    Liver (mg) 66.0 ± 9.6 84.7 ± 10.9 F1, 19 = 1.143, p = 0.298
    Kidney (mg) 86.4 ± 4.5 71.6 ± 5.2 F1, 19 = 4.418, p = 0.048
    Gizzard (mg) 102.2 ± 10.6 92.1 ± 12.1 F1, 19 = 0.269, p = 0.610
    Small intestine (mg) 242.3 ± 22.3 158.6 ± 25.5 F1, 19 = 7.081, p = 0.015
    Rectum (mg) 15.9 ± 4.5 19.4 ± 5.2 F1, 19 = 0.182, p = 0.674
    Digestive tract (mg) 371.5 ± 30.6 269.9 ± 34.9 F1, 19 = 5.005, p = 0.037
    Data are presented as mean ± SEM
    FR food restriction
     | Show Table
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    Table  2.  Partial, and residual, correlations between basal metabolic rate and the dry mass of various organs (controlled for body mass minus wet organ mass) of Chinese Bulbuls (Pycnonotus sinensis) after 12 days food restriction
    Muscle Brain Heart Lung Liver Kidney Gizzard Small intestine Rectum Digestive tract
    Partial correlations
    R2 0.182 0.006 0.318 0.123 0.138 0.321 0.333 0.049 0.080 0.045
    p 0.047 0.730 0.006 0.109 0.089 0.006 0.096 0.321 0.204 0.346
    Residual correlations
    R2 0.040 0.007 0.129 0.011 0.001 0.135 0.3146 0.052 0.008 0.023
    p 0.369 0.973 0.100 0.649 0.845 0.092 0.806 0.304 0.694 0.505
    p values in italics are statistically significant
     | Show Table
    DownLoad: CSV

    The FR group had significantly decreased levels of state-4 respiration in the liver (t20 = 2.132, p = 0.045) and muscle (t20 = 3.180, p = 0.007) (Fig. 3a), and decreased COX activity in the liver (t20 = 2.828, p = 0.010) and muscle (t20 = 4.554, p < 0.0001) (Fig. 3b), compared to the control group. BMR was positively correlated with and state-4 respiration in the liver (Fig. 4a), and with COX activity in muscle (Fig. 4d).

    Figure  3.  Differences in state-4-respiration (a) and cytochrome C oxidase (b) in the liver and pectoral muscle of Chinese Bulbuls (Pycnonotus sinensis) that were provided with food ad libitum (control group) and those provided with half of the usual quantity of food (food restriction group group), after 12 days. Data are shown as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001. FR food restriction group
    Figure  4.  Correlations between basal metabolic rate (BMR), state-4-respiration, and cytochrome C oxidase in the liver, and pectoral muscle, in Chinese Bulbuls (Pycnonotus sinensis) that were provided with food ad libitum (control group) and in those provided with half the usual quantity of food (food restriction group group), over 12 days

    The FR group had significantly lower avUCP (t11 =3.293, p = 0.007) than the control group (Fig. 5).

    Figure  5.  Differences in levels of avian uncoupling protein in Chinese Bulbuls (Pycnonotus sinensis) that were provided with food ad libitum (control group) and in those provided with half the usual quantity of food (food restriction group group), over 12 days. Data are shown as mean ± SEM, **p < 0.01. FR food restriction group

    Food limitation has been shown to affect a wide variety of morphological, physiological, and behavioral functions in animals (Kelly and Weathers 2002; McKechnie and Wolf 2004; Gutiérrez et al. 2011). We found that 12 days of food restriction decreased the body mass, body fat, energy expenditure, internal organ (kidney, heart and small intestine) mass, and BMR, of Chinese Bulbuls, and also decreased state-4 respiration and COX activity in their liver and muscle mitochondria. Food restriction also caused a decrease in avUCP in muscle.

    Birds, like many other animals, rarely have unlimited access to food in the wild and consequently have evolved the ability to drastically change their morphology and physiology in response to food shortage (Piersma and Lindstrom 1997; Klaassen et al. 2004). Chinese Bulbuls responded to food restriction by decreasing their body mass, BMR and altering their body composition. Body mass is an important index that reflects an animal's nutritional status (Kelly and Weathers 2002) and its stability depends on the balance between energy intake and expenditure (Hegemann et al. 2012). Our results show that 12 days of food restriction was sufficient to cause Chinese Bulbuls to undergo a significant decrease in body mass of 13%. Such a reduction in body mass generally reduces maintenance requirements thereby resulting in a decrease in whole-body energy expenditure. Similar results have been found in Eurasian Tree Sparrows (Passer montanus) (Yang et al. 2010) and White Throated Sparrows (Zonotrichia albicollis) (Pierce and McWilliams 2004). Fat reserves can supply emergency energy reserves during periods of food shortage (O'Connor 1995; Guglielmo and Williams 2003). Increased fat levels in the body and liver in winter, or during migration, are common in many temperate passerines, enabling these birds to meet increased thermoregulatory demands and provide a nutritional buffer against temporary foraging restrictions caused by inclement weather (Dawson and Marsh 1986; Swanson 1991a). Our data show that Chinese Bulbuls in the FR group had lower body and liver fat compared to the control group. The FR birds may have had to consume their fat reserves to compensate for their decreased energy intake (Swanson 1991b; Cooper 2007; Liknes et al. 2014). FR birds also had a lighter heart, kidneys, small intestine and digestive tract than control birds. This suggests that food deprivation has a profound effect on the body composition and digestive organs of birds. Furthermore, our results are consistent with those of previous studies (Liang et al. 2015) in showing that food restriction induces a significant reduction in the BMR of Chinese Bulbuls. These results suggest that the ability to decrease their BMR is an important adaptation used by Bulbuls to survive periods of food shortage. Several authors have suggested that much of the energy used in basal metabolism is consumed by visceral organs (Daan et al. 1990; Piersma and Lindstrom 1997), including the small intestine (storage, digestion and absorption), the heart and lungs (oxygen transport), the liver (catabolism), and the kidneys (waste elimination) (Daan et al. 1990; Li et al. 2017). Although the liver, kidney, heart, and digestive tract comprise less than 10% of total body mass, they consume 50-70% of total energy expenditure (Rolfe and Brown 1997; Clapham 2012). We found that the mass of the heart, kidneys, small intestine and digestive tract decreased significantly in FR bulbuls, compared to those in the control group, which suggests that bulbuls reduce the mass of these organs when food is limited to decrease their energy expenditure and thereby ultimately their metabolic rate.

    The liver is one of the largest and most metabolically active organs in birds and can also contribute to the thermogenesis (Villarin et al. 2003; Dumas et al. 2004; Zheng et al. 2008a, b). Under basal metabolic conditions, the liver has been shown to contribute 25% of total heat production (Li et al. 2001; Zheng et al. 2008b). Skeletal muscles have lower mass-specific metabolic rates, but due to their total mass, contribute significantly to seasonal acclimatization through their role in thermogenesis (Scott and Evans 1992; Chappell et al. 1999). Mitochondrial state-4 respiration, and cytochrome C oxidase (COX) activity are indicators of cellular metabolic intensity and can reflect metabolic activity in these tissues (Zheng et al. 2008a, 2014a; Swanson 2010; Swanson et al. 2014). A reduction in metabolic rate should lead to a decrease in the utilization of substrates by tissues and organs (Sartori et al. 1995), a hypothesis supported by the changes in biochemical markers (i.e., mitochondrial protein content, state-4 respiration and COX activity) we observed in Chinese Bulbuls. Our results show that liver mitochondrial protein content, state-4 respiration and COX activity decreased significantly in the FR group compared to the control group. This result is interesting and, since neither liver nor muscle underwent a significant decrease in organ mass (although both did decreased in mass by 19‒33%), suggests that reducing cellular energy consumption may be more important than reducing organ masses. These decreases are consistent with a mechanistic down regulation of intracellular metabolic capacity in response to food restriction, suggesting that this mechanism may be important to bulbuls' ability to respond to changing seasonal energy demands.

    Birds do not have brown adipose tissue but have the ability to increase the thermogenic capacity of their skeletal muscles through shivering thermogenesis and adaptive non-shivering processes after cold acclimation (Barré et al. 1986; Dridi et al. 2004; Abe et al. 2006). This may be achieved through change in the specific mitochondrial anion carrier avUCP (Dridi et al. 2004). AvUCP mRNA is upregulated in the skeletal muscles of chickens after exposure to cold, which is known to be associated with increased energy expenditure (Toyomizu et al. 2002; Collin et al. 2003; Teulier et al. 2010). However, it is worth noting that the studies relating avUCP to NST in birds were all done on chicks rather than adults (Vianna et al. 2001; Toyomizu et al. 2002; Mozo et al. 2005; Teulier et al. 2010). This suggests that the incomplete muscular development of chicks may reduce their capacity for shivering thermogenesis to the extent that their thermoregulatory demands may need to be supported by NST, whereas adult birds with fully developed shivering capacities may be less reliant on NST. Our results suggest that food restriction induced a significant decrease in the avUCP content of muscle in bulbuls, which is consistent with previous findings in king penguins (Rey et al. 2010). This indicates that rather than thermogenesis or reducing oxidative stress, it is quite possible that the main function of avUCP is to maintain optimized mitochondrial membrane potential (Brand 2000).

    In conclusion, the results of our study demonstrate that Chinese Bulbuls respond to food restriction at the organismal, physiological and molecular levels, including decreasing their body mass and changing their body composition, reducing metabolic thermogenesis, and decreasing enzymatic activity and the amount of mitochondrial anion carrier in specific organs. These morphological, physiological and biochemical responses could be a part of the seasonal acclimatization used by bulbuls to adjust to seasonal changes in food abundance, especially during winter. This phenotypic flexibility may enable the Chinese Bulbul to survive periods of seasonal food limitation (Liang et al. 2015).

    WZ and JL designed the study. YZ, KY, PY and YS performed the work. YZ, KY, and YS analyzed the data, and YZ, KY, WZ and JL wrote the manuscript. All authors participated in revising the manuscript. All authors read and approved the final manuscript.

    We thank Dr. Ron Moorhouse revising the English. Thanks to all the members of Animal Physiological Ecology Group, and the Wenzhou University Institute of Applied Ecology, for their helpful suggestions, and the anonymous reviewers for their helpful comments and suggestions on earlier drafts of this manuscript.

    The authors declare that they have no competing interests.

    Not applicable.

    All experimental procedures were approved by the Animal Care and Use Committee of the Wenzhou University.

    Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

  • Abrahams M, Kattenfeld M. The role of turbidity as a constraint on predator-prey interactions in aquatic environments. Behav Ecol Soc. 1997;40:169-74.
    Ahulu AM, Nunoo FKE, Owusu EH. Food preferences of the common tern, Sterna hirundo (Linnaeus, 1758) at the Densu floodplains, Accra. West Afr J Appl Ecol. 2006;9:1-7.
    Anderson JT, Zadnik AK, Wood PB, Bledsoe K. Evaluation of habitat quality for selected wildlife species associated with island back channels. Open J Ecol. 2013;3:301-10.
    Ansa-Asare OD, Asante KA. A comparative study of the nutrient status of two reservoirs in southeast Ghana. Lakes Reserv Res Manag. 1998;3:205-17.
    Ansa-Asare OD, Asante KA. Changes in the chemistry of the Weija Dam Reservoir in Ghana, twenty years after impoundment. West Afr J Appl Ecol. 2005;8:35-47.
    Asante KA, Quarcoopome T, Amevenku FYK. Water quality of the Weija reservoir after 28 years of impoundment. West Afr J Appl Ecol. 2008;13:125-31.
    Baptist MJ, Leopold MF. Prey capture success of Sandwich Terns Sterna sandvicensis varies non-linearly with water transparency. Ibis. 2010;152:815-25.
    BirdLife Int. Important Bird Areas factsheet: Densu Delta Ramsar Site and vicinity. 2018. Downloaded from on Accessed 07 Mar 2018.
    Bonnington C, Weaver D, Fanning E. The habitat preference of four kingfisher species along a branch of the Kilombero River, southern Tanzania. Afr J Ecol. 2008;46:424-7.
    Borah J. Occupancy pattern and food-niche partitioning among sympatric kingfishers in Bhitarkanika mangroves, Orissa. MSc Thesis. 2011; Saurashtra Univ. Rajkot, India.
    Braby J, Underhill LG, Simmons RE. Prey capture success and chick diet of Damara terns Sterna balaenarum in Namibia. Afr J Mar Sci. 2011;33:225-47.
    Brenninkmeijer AE, Stienen WM, Klaassen M, Kersten M. Foraging ecology of wintering terns in Guinea-Bissau. Ibis. 2002;144:602-13.
    Briggs KT, Ainley DG, Spear LB, Adams PB, Smith SE. Distribution and diet of Cassin's Auklet and Common Murre in relation to central California upwellings. Proc Int Ornithol Congr. 1988;19:983-90.
    Buckley FG, Buckley PA. Comparative feeding ecology of wintering adult and juvenile Royal Terns (Aves: Laridae, Sterninae). Ecology. 1974;55:1053-63.
    Cramp S, Douthwaite R, Reyer H, Westerturp K. Pied Kingfisher Ceryle rudis (Linnaeus). In: Fry H, Keith S, Urban E, editors. The Birds of Africa, vol. 3. San Diego: Academic Press; 1988. p. 299-302.
    Cyrus DP. The influence of turbidity on the foraging behaviour of Little Terns Sterna albifrons off the St. Lucia Mouth, Zululand, South Africa. Mar Ornithol. 1991;19:103-8.
    Davoren GK, Montevecchi WA, Anderson JT. Distributional patterns of a marine bird and its prey: habitat selection based on prey and on specific behaviour. Mar Ecol Prog Ser. 2003;256:229-42.
    Douthwaite RJ. Fishing techniques and foods of the pied kingfisher on Lake Victoria in Uganda. Ostrich. 1976;47:153-60.
    Douthwaite RJ. Changes in Pied Kingfisher (Ceryle rudis) feeding related to endosulfan pollution from tsetse fly control operations in the Okavango Delta, Botswana. J Appl Ecol. 1982;19:133-41.
    Dowsett-Lemaire F, Dowsett RJ. The birds of Ghana. Jupille-Liege: Tauraco Press; 2014. p. 713.
    Dunn EK. Studies on terns, with particular reference to feeding ecology. Ph.D Thesis. South Africa: Durham University. 1972a.
    Dunn EK. Effect of age on the fishing ability of sandwich terns Sterna sandvicensis. Ibis. 1972;114:360-6.
    Elliot A. Family Pelecanidae (Pelicans). In: Handbook of Birds of the World. vol 1. Barcelona: Lynx Editions. 1992.
    Enstipp MR, Grémillet D, Jones DR. Investigating the functional link between prey abundance and seabird predatory performance. Mar Ecol Prog Ser. 2007;331:267-79.
    Eriksson MOG. Prey detectability for fish-eating birds in relation to fish density and water transparency. Ornis Scand. 1985;16:1-7.
    Flemming SP, Smith PC. Environmental influences on Osprey foraging in northeastern Nova Scotia. J Raptor Res. 1990;24:64-7.
    Forsell DJ. Predatory efficiency and energetics of Belted kingfishers wintering along the Mad River. MSc Thesis. Humboldt: Humboldt State University. 1983.
    Gbogbo F. The importance of unmanaged coastal wetlands to waterbirds at coastal Ghana. Afr J Ecol. 2007;45:599-606.
    Gbogbo F, Attuquayefio DK. Issues arising from changes in waterbird population estimates in coastal Ghana. Bird Popul. 2010;10:79-87.
    Gbogbo F, Oduro W, Oppong SK. Nature and pattern of lagoon fisheries resource utilisation and their implications for waterbird management in coastal Ghana. Afr J Aquat Sci. 2008;33:211-22.
    Gbogbo F, Adaworomah BB, Asante E, Brown-Engmann GR. Human related bird flushes are of little consequence to wintering waterbirds in a tropical coastal wetland in Ghana. Wader Stud Group Bull. 2013;120:60-5.
    Grimble R, Ellenbroek W, Willoughby N, Danso E, Ametekpor J. Study of development options for Ghana's wetlands (Vol. 1). Technical report to the Environmental Protection Agency and Natural Resource International. Chatham, Kent; 1998. p. 94.
    Haney JC. Winter habitat of Common loons on the continental shelf of the Southeastern United States. Wilson Bull. 1991;102:253-63.
    Haney JC, Stone AE. Seabird foraging tactics and water clarity: are plunge divers really in the clear? Mar Ecol Prog Ser. 1988;49:1-9.
    Henkel LA. The distribution and abundance of marine birds in nearshore waters of Monterey Bay, California.MSc Thesis. California State University, Monterey Bay. 2003.
    Henkel LA. Effect of water clarity on the distribution of marine birds in nearshore waters of Monterey Bay, California. J Field Ornithol. 2006;77:151-6.
    Johnston DW. Feeding ecology of Pied kingfishers on Lake Malawi, Africa. Biotropica. 1989;21:275-7.
    Junor FJR. Offshore fishing by the Pied Kingfisher Ceryle rudis at Lake Kariba. Ostrich. 1972;43:185.
    Katzir G, Camhi JM. Escape response of Black Mollies (Poecilia sphenops) to predatory dives of a Pied Kingfisher (Ceryle rudis). Copeia. 1993;2:549-53.
    Lamptey AM, Ofori-Danson PK. Review of the distribution of waterbirds in two tropical coastal Ramsar lagoons in Ghana, West Africa. West Afr J Appl Ecol. 2014;22:77-91.
    Newbrey JL, Bozek MA, Niemuth ND. Effects of lake characteristics and human disturbance on the presence of piscivorous birds in Northern Wisconsin, USA. Waterbirds. 2005;28:478-86.
    Ntiamoa-Baidu Y, Nyame SK, Nuoh AA. Trends in the use of a small coastal lagoon by waterbirds: Muni Lagoon (Ghana). Biodivers Conserv. 2000;9:527-39.
    Piersma T, Ntiamoa-Baidu Y. Waterbird ecology and the management of coastal wetlands in Ghana 12. NIOZ Report 1995-1996. 1995. p. 105.
    Quarcoopome T, Amevenku FYK. Fish community structure of Weija reservoir after 28 years of impoundment. J Appl Sci Technol. 2010;15:126-31.
    Recher HF, Recher JA. The foraging behavior of the Reef Heron. Emu. 1972;72:85-90.
    Reyer H-U, Migongo-Bake W, Schmidt L. Field studies and experiments on distribution and foraging of Pied and Malachite Kingfishers at Lake Nakuru (Kenya). J Anim Ecol. 1988;57:595-610.
    Ropert-Coudert Y, Grémillet D, Ryan PG, Kato A, Naito Y, Le Maho Y. Between air and water: the plunge-dive of the cape gannet Morus capensis. Ibis. 2004;146:281-90.
    Ropert-Coudert Y, Daunt F, Kato A, Ryan PG, Lewis S, Kobayashi K, Mori Y, Grémillet D, Wanless S. Underwater wingbeats extend depth and duration of plunge dives in northern gannets Morus bassanus. J Avian Biol. 2009;40:380-7.
    Russell IA, Randall RM, Hanekom N. Spatial and temporal patterns of waterbird assemblages in the Wilderness Lakes Complex, South Africa. Waterbirds. 2014;37:1-18.
    Safina C. Foraging habitat partitioning in Roseate and Common terns. Auk. 1990a;107:351-8.
    Safina C. Bluefish mediation of foraging competition between Roseate and Common Terns. Ecology. 1990b;71:1804-9.
    Safina C, Burger J. Common Tern foraging: seasonal trends in prey fish densities and competition with bluefish. Ecology. 1985;66:1457-63.
    Safina C, Burger J. Ecological dynamics among prey fish, bluefish and foraging Common terns in an Atlantic coastal system. In: Burger J, editor. Seabirds and other marine vertebrates. New York: Columbia University Press; 1988. p. 95-173.
    Shealer DA, Burger J. Comparative foraging success between adult and one-year-old Roseate and Sandwich terns. Colon Waterbirds. 1995;18:93-9.
    Simmons RE, Braine S. Breeding, foraging, trapping and sexing of Damara terns in the Skeleton Coast Park, Namibia. Ostrich. 1994;65:264-73.
    Sohel S, Lindström K. Algal turbidity reduces risk assessment ability of the Three-Spined Stickleback. Ethology. 2015;121:548-55.
    Stempniewicz L, Darecki M, Trudnowska E, Błachowiak-Samołyk K, Boehnke R, Jakubas D, Keslinka-Nawrot L, Kidawa D, Sagan S, Wojczulanis-Jakubas K. Visual prey availability and distribution of foraging little auks (Alle alle) in the shelf waters of West Spitsbergen. Polar Biol. 2013;36:949-55.
    Stienen EWM, Brenninkmeijer A. Voedselecologie van de grote sterns (Sterna sandvicensis): onderzoek ter ondersteuning van een populatie-dynamisch model. Wageningen: Instituut voor Bos- en Natuuronderzoek; 1994 (in Dutch).
    Strod T, Izhaki I, Arad Z, Katzir G. Prey detection by great cormorant (Phalacrocorax carbo sinensis) in clear and in turbid water. J Exp Biol. 2008;211:866-72.
    Taylor IR. Effect of wind on the foraging behaviour of common and sandwich terns. Ornis Scand. 1983;14:90-6.
    WRC Ghana. Densu river basin—integrated water resources management plan. Technical Report. Water Resources Commission of Ghana. 2007. p. 83.
    Watson MJ, Hatch JJ. Differences in foraging performance between juvenile and adult Roseate Terns at a pre-migratory staging area. Waterbirds. 1999;22:463-5.
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