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. 2018 Dec 18;6(1):coy072. doi: 10.1093/conphys/coy072

Physiological consequences of biologic state and habitat dynamics on the critically endangered Yangtze finless porpoises (Neophocaena asiaeorientalis ssp. asiaeorientalis) dwelling in the wild and semi-natural environment

Ghulam Nabi 1,2, Yujiang Hao 1,✉, Todd R Robeck 3, Zheng Jinsong 1, Ding Wang 1
Editor: Steven Cooke
PMCID: PMC6298535  PMID: 30581572

This research describes the effect of age, sex, reproductive status and habitat location on serum biochemical analytes in the critically endangered Yangtze finless porpoise (Neophocaena asiaeorientalis ssp. asiaeorientalis). Results highlight conservation relevant effects of biologic stages and suggests that without proper management habitat degradation may adversely affect their long-term sustainability.

Keywords: biochemistry, Cetacean, critically endangered, habitat dynamics, hepatic profile, lipid profile, Yangtze Finless Porpoise

Abstract

The objectives of this study were to investigate the effects of habitat and biological state on the physiology of critically endangered wild and semi-natural Yangtze Finless Porpoises (YFPs; Neophocaena asiaeorientalis ssp. asiaeorientalis) by measuring and comparing serum biochemical parameters. A total of 168 YFPs were sampled, 68 living in the semi-natural (Tian-E-Zhou Oxbow) and 98 living in the wild (Poyang Lake, PL) environment. The YFPs in the Tian-E-Zhou Oxbow were sampled from 2002 to 2015 and in the PL from 2009 to 2017. Each population was divided into Juvenile Male, Juvenile Female, Adult Male, Pregnant and Lactating Female life history categories. Overall, with location, 19/33 of the analytes and with season 18/33 of the analytes were significantly different. Similarly, within each location, 15/33 of the analytes changed with time in PL while only 8/33 changed with time in Tian-E-Zhou Oxbow, respectively. Finally, 15/33 of the analytes demonstrated significant differences between the different age and sex groups of animals. In our study, a significant variation, as well as an increasing and decreasing pattern of several parameters in both populations, suggest a worsening ecological environment of both habitats. This study will help in health assessment, improving conservation and management practices, a crucial requisite for biodiversity conservation.

Introduction

Effects of climate change and population growth on global freshwater reserves are increasing to such an extent that in some locations this valuable resource is shrinking, and in some instances, may disappear (Coe and Foley, 2001; Oren et al., 2010). Poyang Lake (PL), the largest freshwater lake in China and an extension of the Yangtze River, is an important habitat for critically endangered Yangtze finless porpoises (YFPs, Neophocaena phocaenoides asiaorientalis; Wang et al., 2013). In addition to significant water loss from a prolonged drought (Mei et al., 2015; Zhang et al., 2016), this crucial habitat is under increasing anthropogenic pressures in the form of sand dredging (Li, 2008), vessel trafficking (Zhang, 2007) and water quality degradation due to Yangtze River watershed alterations (Wu et al., 2004; Mueller et al., 2008). In addition to direct impacts on water quality, habitat fragmentation from these alterations may only increase with future hydroelectric power plant projects (Jiangxi Water Conservancy, 2010). Such changes in the Yangtze River are believed to have played a part in the rapid decrease of the YFP population numbers, which have been declining at the average rate of 13.73% per annum (Mei et al., 2014). These declines have resulted in the latest estimated total YFP population numbers to be around 1000 individuals, with almost half (~450) of the living population in PL (Mei et al., 2014). With the current population trajectory, the YFP may soon join the baiji (Lipotes vexillifer), a previous co-inhabitant of the Yangtze River, in extinction (Turvey et al., 2007).

Worldwide deleterious alterations in habitat quality are believed to be the main cause of almost 40% of all mammalian species experiencing severe population declines (Ceballos et al., 2017; Johnson et al., 2017) with freshwater cetaceans, or river dolphins, appearing to be extremely vulnerable toward these pressures (Turvey et al., 2010; He et al., 2017). Habitat destruction in the biodiversity-rich area around the globe can cause mass extinction, especially for threatened and endemic species (Brooks et al., 2002). Therefore, determining current physiological characteristics of individuals within an at-risk population provides baselines for future investigations on the potential effect of anthropogenic activities on their health and well-being (Schwacke et al., 2009). It is well accepted that habitat quality effects body fitness and physiological functions of the animals living within these locations (Pulliam, 1988; Huey, 1991; Carey, 2005). Therefore, monitoring of physiologic traits can help us to understand and predict organismal and population responses to environmental change and stressors, cause-effect relationships, and specificity of management techniques (Christine et al., 2016).

While the population of YFP in PL represents almost half of the remaining animals living within their historic range, an experimental conservation strategy involving relocation of a small number of animals into a natural ex situ reserve called the Tian-E-Zhou Oxbow (TZO) began in 1990. The use of this reserve, a habitat removed from many of the detrimental anthropogenic activity faced by in situ YFP, if successful over the long-term, would serve as a model for the identification of other natural habitats which could provide shelter for relocated YFP until the natural habitat of the Yangtze River could be sufficiently reclaimed for animal reintroduction. While the use of ex situ populations as a conservation strategy has been successfully implemented in terrestrial mammals, it represents the first application of this model toward a cetacean (O’Brien and Robeck, 2010). The initial success of the ex situ TZO population has been demonstrated by its increased from a net introduction of five animals from the wild since 1990 to a total of 25 in 2010. From 2010 to 2015, due to successful animal breeding, the population exceeds to more than 60 individuals with a net 108% increase in the population (Wang, 2009; 2015). This growing ex situ population, which has been living in a unique environment, may serve as a physiologic control for changes that may have occurred in wild populations of the Yangtze River, Poyang and Dongting Lake system. However, until recently (Nabi et al., 2017a), most efforts at evaluating the health of the TZO ex situ population has focused on their reproductive health and resource management (Wu et al., 2010; Zhao et al., 2010; Zeng et al., 2018). As a result, no information has been published examining the effects of their habitat relocation on their physiology over time. Therefore, the primary objective of our study was to determine if habitat, while controlling for season, had an adverse effect on the YFP health as indicated by differences in serum biochemical parameters within YFP between each location (PL vs. TZO). Secondarily, to determine if indirect evidence exists that habitats have degraded by evaluating changes in YFP serum biochemical profiles within each location over time. And finally, if changes existed between locations, to detect during what age (immature or mature), sex or physiologic state (pregnancy or lactation) they were occurring. The results of this study will help determine the efficacy of establishing ex situ natural reserves and provide evidence for or against the continued expansion of this conservation strategy.

Materials and methods

Animal ethics

The protocols for animal collection and handling were approved under Chinese law and guidelines for wildlife use by the Ministry of Agriculture of China. The Research Ethics Committee of Institute of Hydrobiology, the Chinese Academy of Science reviewed and approved the blood sampling and handling procedures.

Study design

A totals of 168 animals were sampled from TZO (n = 70) and PL (n = 98). Information about animals and sampling dates are summarized in Tables 1 and 2. Data collected in 2002, 2003 and 2015 in the TZO and 2009 and 2015 in the PL have been previously reported (Nabi et al., 2017a, 2018). Animals were grouped based on total body length (Gao and Zhou, 1993) and sex as follows: Juvenile male (JM < 138 cm), adult male (AM > 138 cm), juvenile female (JF < 138 cm) and adult females (AF > 138 cm, Table 1). Adult females were further classified as non-pregnant, lactating females (L) and pregnant non-lactating females (P). No non-pregnant, non-lactating females were sampled. Lactating females were identified based on the presence of milk in the mammary gland and pregnant females (PF) were identified by ultrasonography (LOGIQ Book XP, New York, America) of the reproductive tract.

Table 1:

Basic information of the studied animals in Tian-E-Zhou Oxbow.

Status ID BL (cm) BW (Kg) Year/season Status ID BL (cm) BW (Kg) Year/season
JM 02T-M1 114 23 2002 AM 06-T-M04 164 73.2
JM 02T-M03 129 42 (Fall) AM 06-T-M06 148 65.5
JM 04-T-M04 123 34 2004 (summer) AM 08-T-M02 161 68.75 2008 (spring)
JM 06-T-M07 134 42 2006 AM 08-T-M03 161 70.5
JM 06-T-M08 137 49.4 (spring) AM 08-T-M07 162 77
JM 08-T-M01 133 38.6 2008 AM 08-T-M08 160 69
JM 08-T-M04 133 39.5 (spring) AM 08-T-M12 146 49
JM 08-T-M06 114 29.6 AM 08-T-M13 142 53
JM 08-T-M09 120 33.75 AM 10-T-M01 166 61.3 2010
JM 08-T-M10 134 44 AM 10-T-M02 163 69.9 (Fall)
JM 08-T-M11 118 34 AM 10-T-M03 158 70.6
JM 10-T-M09 121 36.5 2010 AM 10-T-M04 165 68.8
JM 10-T-M10 126 35 (Fall) AM 10-T-M06 143 48.4
JM T15M07 125 31.4 2015 AM 10-T-M07 142 47.9
JM T15M18 133 35.2 (Fall) AM 10-T-M08 145 47.6
AM 02T-M01 152 53 2002 AM T15M02 139 35.5 2015
AM 02T-M02 158 59.05 (Fall) AM T15M05 141 36.8 (winter)
AM 02T-M04 155 57.5 AM T15M08 148 40.8
AM 02T-M05 139 43 AM T15M09 160 42
AM 02T-M06 156 55.4 AM T15M12 151 44.5
AM 02T-M07 157 54.3 AM T15M17 156 46.1
AM 03T-M02 141 32.7 2003 P 08-T-F03 136 59 2008
AM 03T-M03 146 46.15 (Fall) P 08-T-F05 140 53.25 (spring)
AM 03T-M04 158 57 P 08-T-F06 148 71.5
AM 03T-M05 142 41.4 P 08-T-F07 152 63.75
AM 03T-M06 149 50.15 P 08-T-F09 149 67.5
AM 03T-M07 157 55.1 P TEZ 18 149.5 51.1 2015
AM 03T-M08 154 55.8 P TEZ 19 143 55.3 (winter)
AM 04-T-M01 159 59.35 2004 P TEZ 21 147.5 53.4
AM 04-T-M02 147 43.45 (Fall) P TEZ 25 139 45.8
AM 04-T-M03 147 48.45 L 10-T-F01 148 2010
AM 04-T-M05 149 50.45 L 10-T-F03 140 51.2 (Fall)
AM 04-T-M06 149 48.7 L 10-T-F04 149 56
AM 06-T-M01 149 50.2 2006 L 10-T-F09 140 58
AM 06-T-M02 158 73.2 (spring)
AM 06-T-M03 156 55.55
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Table 2:

Basic information of the studied animals in Poyang Lake.

Status ID BL (cm) BW (Kg) Year/season Status ID BL (cm) BW (Kg) Year/season
JM 09PYM006 128 36.95 2009 AM 15PY-M09 160 57.2
JM 09PYM008 127 36 (winter) AM 15PY-M10 152 53.8
JM 09PYM009 136 39.1 AM 15PY-M12 138 46.8
JM 09PYM017 127 34.7 AM 15PY-M13 154 51.2
JM 09PYM020 125 38.1 AM 17PYM15 145 49 2017
JM 10PYM03 127 35.1 2010 AM 17PYM06 150 45.1 (spring)
JM 10PYM04 114 30.9 (spring) AM 17PYM14 142 49.7
JM 11PYM03 124 39.2 2011 AM 17PYM07 146 47.7
JM 11PYM04 124 35.3 (winter) JF 10PYF05 128 34.8 2010
JM 11PYM06 137 45.4 JF 10PYF07 119 25.9 (spring)
JM 11PYM07 113 37.1 JF 11PYF02 127 39.3 2011
JM 11PYM08 113 35 JF 11PYF05 124 36 (winter)
JM 11PYM09 124 33.6 JF 11PYF07 118 37.3
JM 11PYM11 116 38 JF 11PYF09 128 39
JM 11PYM14 124 39.5 JF 11PYF10 112 32.5
JM 11PYM15 116 39.4 JF 11PYF11 123 32.8
JM 15PY-M01 122 36.8 2015 JF 11PYF19 119 33
JM 15PY-M05 124 24 (spring) JF 11PYF23 115 36
JM 15PY-M07 112 31.8 JF 11PYF14 128
JM 15PY-M11 129 37.6 JF 15PY-F04 115 34.7 2015
JM 15PY-M14 129 35.7 JF 15PY-F10 123 40.3 (spring)
JM 17PYM02 135.2 40.4 2017 JF 15PY-F12 127 45.7
JM 17PYM10 128 39.2 (spring) JF 15PY-F17 125 36.3
JM 17PYM01 130 39.4 JF 17PYF14 122 33 2017
JM 17PYM16 132 41.9 JF 17PYF10 118 27.7 (spring)
AM 09PYM004 154 53 2009 P 09PYF002 145 62.9 2009
AM 09PYM007 150 53.5 (winter) P 09PYF003 144 52.2 (winter)
AM 09PYM010 158 83.4 P 09PYF007 152
AM 09PYM011 138 40.6 P 10PYF01 138 50.6 2010
AM 09PYM013 154 52.2 P 10PYF04 149 63.6 (spring)
AM 09PYM014 150 52.4 P 10PYF06 146 62.7
AM 09PYM015 153 53.4 P 11PYF04 147 66.7 2011
AM 09PYM016 158 62.1 P 11PYF06 140 60.4 (winter)
AM 09PYM018 157 48.4 P 11PYF08 130 63.6
AM 09PYM021 146 46.8 P 11PYF13 139 63
AM 10PYM01 149 38.1 2010 P 11PYF15 129 55
AM 10PYM05 152 47.4 (spring) P 11PYF16 137 63.5
AM 11PYM01 168 67.2 2011 P 11PYF18 148 61.1
AM 11PYM02 166 74.1 (winter) P 11PYF20 151 72.3
AM 11PYM05 140 49 P 11PYF21 138 69.9
AM 11PYM10 149 62 P 15PY-F22 138 67.5 2015
AM 11PYM13 146 48.6 P 15PY-F19 134 58.7 (spring)
AM 11PYM16 148 51.6 P 15PY-F18 148
AM 11PYM17 150 59.1 P 15PY-F15 134 60.2
AM 11PYM20 152 73.4 P 15PY-F05 147 72.1
AM 15PY-M03 153 54.4 2015 P 17PYF11 160 2017
AM 15PY-M04 158 69.8 (spring) P 17PYF04 148 62.1 (spring)
AM 15PY-M06 144 53.1 P 17PYF16 140 58.9
AM 15PY-M08 145 49.8 P 17PYF02 162
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Animal collection and blood sampling

Both in the PL and TZO, YFPs were captured by using the ‘sound chase and net capture’ method (Hua, 1987). The detailed information of animal chasing, catching, handling and release are explained in detail by Hao et al. (2009). Briefly, for each capture, animals were randomly selected within different geographical areas of the sampling locations for each collection attempt. The methodology during the capture event, the blood sampling procedure and the timing of blood collection were consistent for both populations. Ten ml of blood were drawn from the major vein of tail fluke aseptically using a disposable 10-ml syringe (Gemtier, G/Ø/ L: 21/0.7/31 mm, 201502, Shanghai, China). The blood was then transferred into serum separator and EDTA Vacutainer® tubes (BD Vacutainer, Becton Dickinson, Franklin Lakes, New Jersey, USA), and placed immediately on ice. After centrifugation (Eppendorf AG, 22332, Hamburg, Germany) at 1500 × g for 15 min, the obtained serum was then immediately transferred into cryotubes (Fisher Scientific, Pittsburgh, Pennsylvania, USA), and stored in a liquid nitrogen kettle for transportation to the laboratory for immediate analysis.

Laboratory analyses

The liver function parameters; Indirect Bilirubin (I-BILI), Direct Bilirubin (D-BILI), Total Bilirubin (T-BILI), Total Bile Acid (TBA), Gamma-glutamyl Transferase (GGT), Alkaline Phosphatase (ALP), Aspartate amino Transferase (AST), Alaline amino Transferase (ALT), lipid profile; Ligh Density Lipoprotein cholesterol (LDL-c), High Density Lipoprotein cholesterol (HDL-c), Triglyceride (TG), Total Cholesterol (TC), enzymes; Lactate Dehydrogenase (LDH), Creatine Kinase (CK), Amylase (AMS), Electrolytes; (PO43−, Ca2+, Cl−, Na+, K+, Mg2+, Fe2+) and other biochemical parameters such as Creatinine (Cr), Urea (UA), Blood Urea Nitrogen (BUN), Carbon Dioxide (CO2), Glucose (GLU), Globulin (GLB), Albumin (AlB) and Total Protein (TP) were investigated using a clinical auto-analyzer (Abbott Aeroset System). Before each assay, the auto-analyzer was calibrated.

Statistical analysis

Based on sampling methodology, and for the analysis, animals were considered to have been randomly selected during each collection period and no animal was sampled more than once. Statistical analysis was performed by either STATA (version 14, Stata Corp LP, College Station, TX, USA) or Graph Pad Prism, version 5.01 (Graph Pad Software Inc., San Diego, CA, USA). Prior to analysis, results for each analyte were evaluated for normality by the Shapiro–Wilk-test (STATA) and transformed as appropriate (natural log or sqrt). For the analysis, individual sample results for each analyte were coded for location (0: PL; 1: TZO), group (JM, JF, AM, PF, LF) and season (winter [W]: November through February; Spring [S]: March through May; Summer [Sm]: June through August; Fall [F]: September through October).

A maximum likelihood (ML) general linear model (GLM, identity link, Gaussian family) was used to determine if the dependent variable (analyte concentration) differed between locations (STATA) and between groups combined across both locations. Many of the analytes evaluated are known to be effective by season (Hall et al., 2007; Macchi et al., 2011; Nollens et al., 2018); therefore, season was added as a covariate Post hoc marginal mean comparison between locations, groups and season were then preformed and data was presented as marginal mean and 95% confidence interval. To determine if changes had occurred for each dependent variable within each location over time (2002–15 for TZO and 2009–17 for PL) a linear regression was used with time as a continuous independent variable and group as a covariate (STATA).

An unpaired Student’s t-test was used to compare the analyte concentration within one group from PL to its respective group in TZO using Graph Pad Prism, version 5.01 (Graph Pad Software Inc., San Diego, CA, USA). Results of the t-test between locations were presented as mean ± SEM. For all analyses, significance was defined as P ≤ 0.05.

Results

Overall, the results of the GLM analysis indicated that 58% (19 of 33) of the analytes were significantly different between locations, while, 55% (18 of 33) demonstrated significant seasonal effects (Table 3). However, a complete picture of the seasonal effects could not be determined due to the lack of sampling during the summer months. Across both locations, 46% (15/33) of the analytes demonstrated significant differences between the different age and sex groups of animals (Fig. 1). Finally, the linear regression results indicated that within each location, 46% (15 of 33) of the analytes changed over time in PL while only 24% (8 of 33) changed over time in TZO, respectively (Table 3).

Table 3:

Effect of habitat (PL and TZO) and time (years, 2002 to 2015 for TZO and 2009 to 2017 for PL) while controlling for season and groups (JM, JF, AM, PF, LF) on biochemical analytes (marginal mean, lower 95% CI to higher 95% CI) from YFPs.

Analyte Poyang Lake (PL) Time PLa Tian-E-Zhou Oxbow (TZO) Time TZOa Location Seasonal Sidak Comparisonc
Coef., P value Coef., P value P valueb
ALT (U/l) 31.7, 28.5–35.3 −0.0476, 0.01 39.1, 34.2 to 44.8 NSD 0.03 S < W & F
AST (U/l) 197.2, 185.1–209.4 −5.973, 0.002 218.9, 203.7–234.1 NSD 0.05 S < W & F
AST/ALT 6.3, 5.7–6.9 NSD 5.5, 4.8–6.3 NSD NSD NSD
GGT (U/l) 38.0, 35.6–40.6 −0.0302, 0.008- 40.3, 36.9–44.0 NSD NSD NSD
ALP (U/l) 130.2, 112.0–151.3 0.0532, 0.03 170.0, 141.1–204.8 NSD NSD NSD
TBA (μmol/l) 4.16, 3.47–5.0 NSD 8.0, 6.39–10.0 NSD < 0.0001 F < W
T-BILI (μmol/l) 3.37, 2.85–3.94 NSD 2.71 2.15–3.34 0.0562, 0.001 NSD NSD
D-BILI (μmol/l) 0.69, 0.52–0.87 NSD 1.01, 0.77–1.3 0.0514, < 0.001 0.06 S & Sm & F < W
I-BILI (μmol/l) 1.99, 1.16–2.47 NSD 1.42, 1.09–1.9 0.0604, 0.01 NSD NSD
TP (g/l) 76.4, 74.7–78.0 NSD 70.3, 68.5–72.3 NSD <0.0001 NSD
ALB (g/l) 43.8, 41.9–45.7 NSD 50.6, 48.1–53.2 −0.762, 0.039 0.0002 W < S
GLB (g/l) 32.8, 30.7–34.9 NSD 18.4, 15.7–21.2 NSD <0.0001 S < W
ALB/GLB 1.34, 1.16–1.55 NSD 3.53, 2.91–4.30 NSD <0.0001 W < S
BUN (mmol/l) 17.6, 16.8–18.5 NSD 18.5, 17.4–19.6 NSD NSD NSD
UA (μmol/l) 48.2, 41.1–56.4 −0.1024, <0.001 41.3, 34.0–50.2 NSD NSD S < W
TC (mmol/l) 5.5, 5.11–5.83 −0.1997, 0.01 6.40, 5.97–6.82 NSD 0.004 NSD
TG (mmol/l) 4.26, 3.44–5.27 NSD 2.37, 1.84–3.04 NSD 0.002 NSD
HDL-C (mmol/l) 2.36, 2.21–2.50 −0.232, <0.001 3.21, 3.03–3.39 NSD <0.0001 S & F < W
LDL-C (mmol/l) 1.75, 1.50–2.04 0.1128, <0.001 1.83, 1.50–2.22 −0.1442, <0.001 NSD W < F
HDL-C/LDL-C 5.81, 4.65–7.26 −2.175, <0.001 8.07, 6.15–10.59 NSD NSD S & F < W
CK (U/l) 90.3, 75.1–106.9 −1.064, <0.001 156.9, 132.0–183.9 NSD 0.0001 S < W
LDH (U/l) 224.0, 203.8–246.2 0.067, <0.001 233.8, 207.5–263.3 NSD NSD F & W < S
AMS (U/l) 15.6, 11.6–20.1 8.577, < 0.001 4.57, 2.11–8.0 NSD 0.0005 F < W
Glucose (mmol/l) 7.64, 7.37–7.91 NSD 7.99, 7.6–8.38 NSD NSD W < F & S
CO2 (mmol/l) 21.6, 20.3–22.8 NSD 26.3, 24.2–28.5 NSD 0.002 NSD
Cr (μmol/l) 75.3, 71.0–80.0 NSD 78.1, 72.5–84.2 NSD NSD F < S
K+ (mmol/l) 4.4, 4.2–4.5 NSD 4.0, 3.8–4.2 −0.012, 0.08 0.032 NSD
Na+ (mmol/l) 156.7, 155.8–157.6 NSD 152.8, 151.7–154.0 −0.344, 0.003 <0.0001 NSD
Cl− (mmol/l) 108.7, 107.8–109.4 NSD 108.3 107.3–109.4 −0.3345, 0.005 NSD W & S < F
Ca2+ (mmol/l) 2.56, 2.53–2.60 −0.0135, 0.008 2.47, 2.42–2.51 NSD 0.003 NSD
PO4 1.58, 2.45–1.70 0.0838, <0.001 1.28, 1.12–1.43 NSD 0.013 W & S < F
Mg2+ (mmol/l) 2.26, 2.15–2.37 0.0584, 0.003 2.06, 1.95–2.18 NSD 0.05 NSD
Fe2+ (μmol/l) 27.6, 23.2–32.3 NSD 33.9, 27.4–41.1 NSD NSD NSD
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NSD: Not significantly different (P > 0.05). JM = juvenile male, JF = juvenile female, AM = adult male, PF = pregnant female, LF = lactating female.

aResults of linear regression using time as the independent variable for analyte data (dependent variable, across all years and animal groups) calculated separately for each location.

bSignificance (P ≤ 0.05) determined by location (TZ vs. PL) specific marginal mean (controlled for variance due to group and season) post hoc sidak comparison of the respective biochemical analytes.

cSignificance (P ≤ 0.05) determined for season (W = winter, S = spring, Sm = summer, F = fall) specific marginal mean (controlled for variance due to group and location) post hoc sidak comparison of the respective biochemical analytes. Only significantly different seasons are shown.

Figure 1:

Figure 1:

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Overall marginal mean (±95% confidence interval) biochemical analyte comparisons in YFP from different groups (JM = juvenile male, JF = Juvenile female, AM = adult male, PF = non-lactating, pregnant female, LF = non-pregnant, lactating female). Marginal mean concentration for each analyte were controlled for variance due to location (TZO and PL) and season. Each biochemical parameter followed by an alternate letter was significantly different at P ≤ 0.05.

Comparison of biochemical parameters from YFP between each habitat (TZO vs. PL)

Significant increases in the hepatic enzymes (ALT, AST,) and the hepatobiliary system (TBA, D-BILI) [approximate significance, P = 0.06] were detected in the animals located at TZO (Table 3). However, PL animals had increased (P < 0.0001) TP, decreased (P = 0.0002) ALB and almost doubled (P < 0.0001) GLB compared to TZO (Table 3). For TZO animals, TC was increased (P = 0.004) while TG was almost half (P = 0.002) than those observed in PL, but HDL-c was increased (P < 0.0001, Table 3). The AMS was three times higher (P = 0.0005) in PL animals, while CK in TZO YFP was almost double (P = 0.0001) than PL animals. Finally, CO2 was elevated (P = 0.002) while K+, Na+ Ca2+ PO4 and Mg2+ were significantly decreased in TZO animals (Table 3).

Biochemical parameter changes across the years for animals living in PL and TZO YFPs, respectively

Poyang Lake

Significant decreases in the liver related analytes ALT, AST and GGT were detected. No other significant changes were noted for liver related biochemical values (Table 3). The lipid profile indicated a significant decrease in TC, HDL-c and HDL-c/LDL-c, while a significant increase in LDL-c was detected (Table 3). Both the UA and CK concentrations decreased significantly, while LDH and AMS both significantly increased. For electrolytes, Ca+ decreased while Mg2+ and PO4 increased (Table 3).

Tian-E-Zhou Oxbow

Significant changes in the hepatic system were characterized by an increase in T-BILI, D-BILI and I-BILI. Similarly, decreases (P = 0.04) in ALB were noted, however, no changes in liver enzymes over time were detected. A decrease (P < 0.001) in LDL-c concentration was also noted. Finally, a significant decrease in the Na+ and Cl- were noted, with a near significant decrease in K+ (P = 0.08; Table 3).

Comparisons of marginal mean biochemical parameters between groups (JM, JF, AM, PF, LF) combined across both locations

The YFPs showed significant decreases in ALP, CK and increased in TP with age (P < 0.05, Fig. 1). The Ca2+ was non-significantly higher in juveniles (JM, JF) versus AM and significantly higher than PF (Fig. 1). Inter sex differences within adults could not be measured directly since we did not sample any non-pregnant, non-lactating adult females and both pregnancy and lactation are known to affect multiple analytes in killer whales (Robeck and Nollens, 2012). However, within the juveniles, only GLU was significantly increased in JM compared to JF. The GGT was significantly greater in adult males compared to JF, PF and LF (Fig. 1). Pregnant YFP had significantly reduced AST, AST/ALT, CO2, Ca2+ compared to JF, and significantly increased GLB, BUN and TG compared to JM, AM and both juveniles and AM, respectively. The LF had significantly increased HDL-c and K+ compared to PF and AM, respectively (Fig. 1).

Comparisons of biochemical parameters in YFP between each location (TZO vs. PL) within each group (JM, JF, AM, P, L)

Juvenile males

The overall results of biochemical parameters are summarized in (Fig. 2). Juvenile male (JM) dwelling in the PL showed significantly higher serum level of GLB, Mg2+, Na+, PO43-, TP and UA. In TZO YFPs, serum ALB, ALB/GLB, HDL-C and TC were significantly higher.

Figure 2:

Figure 2:

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Overall comparison of the biochemical parameters between the Tian-E-Zhou Oxbow (T) and Poyang Lake (P) YFPs. The figures (a, b) compared the biochemical parameters between the T and P juvenile males. The figures (c, d, e) indicate biochemical differences in the adult males between T and P animals. The biochemical differences in pregnant groups are indicated by figures (f, g) between the T and P animals. The significant differences between the two populations are indicated by asterisk at *P < 0.05, **P < 0.01 and ***P < 0.001.

Adult males

For AM living in the TZO, the hepatic enzymes (ALP, ALT, AST), lipid profile (TC, HDL-c, LDL-c) and other biochemical parameters (ALB, ALB/GLB, CK, Cl−, CO2) were significantly higher than the adult males (AM) of PL YFPs. On the other hand, AM living in the PL showed significantly higher serum levels of hepatic enzymes (I-BILI, AST/ALT), lipid profile (TG, HDL-c/LDL-c) and other biochemical parameters (Ca2+, Cr, GLB, PO43−, TP) as shown in (Fig. 2).

Pregnant females

The same as observed in other groups, serum levels of TP, PO43−, Ca2+, Na+ and TG along with TIBILI were significantly higher in the PL YFPs. Only serum ALP and Cr were significantly higher in the TZO individuals (Fig. 2).

Discussion

Biochemical differences between locations and across time

Liver parameters

The hepatobiliary system of the TZO YFPs appeared to be under increased activation as demonstrated by a significant increase in bilirubin (T-BILI, D-BILI and I-BILI) over time and significant increases in liver associated analytes including ALP, AST, ALP, T-BILI, TBA and decreased TP compared to animals located at PL. In addition, during the entire study period, animals at PL had significant decreases in ALT, AST and GGT. Bile acids and bilirubin are typically used as indicators of liver clearance and can be elevated during states of parenchymal liver disease and biliary obstruction (Limdi and Hyde, 2003). Similarly, AST and ALT are typically increased during hepatocellular injury due to multiple clinical etiologies such as viral hepatitis, toxic hepatitis, cholestatic hepatitis and chronic active hepatitis (Rosalki and Mcintyre, 1999; Limdi and Hyde, 2003). Alternatively, significantly higher serum ALT, AST and ALP paired with the significantly increased serum cholesterol concentrations in the TZO animals suggests steatosis (Bayard et al., 2006). Total protein was reduced, albumin, which is produced by the liver and decreased in liver dysfunction, was increased for animals at TZO verses PL. The exact cause for elevated albumin in TZO needs further investigations. Complicating this determination is the fact that cetaceans are known to have heavy reserve capacity for hepatic albumin production. In addition, dehydration can elevate albumin production. Therefore, these factors limit the use of albumin as an early indicator of hepatic disorders (Bossart et al., 2001). The GLB were half and ALB/GLB was double those at TZO verse PL and were the cause of the observed decrease in TP.

Water quality in the TZO has recently been reported as being of reduced quality when compared to PL (Nabi et al., 2017a). We are aware (our unpublished work) that the TZO is primarily influenced by agricultural non-point pollution, natural input, poultry excrement and decayed organic matter pollutants. In addition to pesticides, poultry discharge from local poultry farms have been entering the TZO for over 20 years. Poultry discharge is known to possible contain viruses, bacteria, parasites, veterinary pharmaceuticals and heavy metals (EPA, 1998; University of Iowa and Iowa State Study Group, 2002; Boxall et al., 2003; Wei et al., 2010). All of these toxic chemicals or biologics are metabolized by or can directly affect the liver and may account for the increase in hepatic associated enzymes. Consequently, the significant changes observed in the hepatobiliary system of TZO over time are of important concern.

Lipid profile

In Poyang Lake YFPs, we observed a significant increase in LDL-C, and a significant decrease in TC, HDL-C and HDL-C/LDL-C as compared to TZO, while a significant decrease in LDL-C in the TZO YFPs over time. (Table 3). Variation in the YFPs lipid profile may be affected by changing fisheries resources, overall animal nutritional health, habitat utilization and the reproductive cycle (Pethybridge et al., 2011a, b; Kim et al., 2012; Nabi et al., 2017b). In cetaceans, such as bottlenose dolphins (Tursiops truncates), beluga whales (Delphinapterus leucas) and pantropical spotted dolphins (Stenella attenuata), the effects of diet on the lipid profile has been reported (Asper et al., 1990; Cook et al., 1990; St. Aubin et al., 2013). A significant variation in the lipid profile in response to habitat dynamics may indicated changing prey availability between the two locations (Miller et al., 2012). In the PL, there are ample of evidences that overfishing (Chen et al., 2002; Wei et al., 2007; Li, 2008), illegal fishing, using illegal fish gears (Wang, 2009; Schelle, 2010), and removal of large numbers of fish and shrimps by sand mining machine (Yu et al., 2001), are reducing the availability or diversity of prey for the YFPs. Furthermore, water pollution, acoustic pollution and habitat degradation (Warner, 2008; Chen et al., 2009) have already threatened several fish species within this environment (Chen et al., 2004; Hvistendahl, 2008). Similarly, in the TZO, the increasing population of YFPs (Wang, 2015) combined with possible fish mortality and morbidity by various toxic chemical pollutants in the reserve (Nabi et al., 2017a) deplete or change the availability of prey for the YFPs.

Other enzymes

The significantly higher levels of serum CK and non-significantly higher concentration of LDH in TZO YFPs could be due to rhabdomyolysis linked to capture stress as these animals are occasionally exposed to chasing during capture (Williams and Pulley, 1983; Gasper and Gilchrist, 2005). Despite using the same capture method for both populations, animals in the TZO were apparently more active when compared to the PL (Nabi et al., 2017a). Therefore, the overall significantly higher CK level in the adult male of TZO might be due to the hyper-muscular activities (Paola et al., 2007).

Electrolytes

The significant decrease in serum levels of Na+, K+ and Cl− in TZO as compared to PL, and a significant increase in the serum levels of Mg2+ and PO43− while decrease in the Ca+ levels of PL YFPs over time may reflect endocrine and gastrointestinal conditions (Bossart et al., 2001) of YFPs in response to a changing habitat (Sun et al., 2012; Dong, 2013). Overall, the electrolytes (Ca2+, PO43−, Mg2+, Na+) were significantly higher in the PL YFPs compared to TZO YFPs where only Cl- was significantly higher. In addition to dehydration, hyperaldosteronism, liver and renal dysfunctions elevate Na+ levels in cetacean (Bossart et al., 2001). Similarly, dehydration, renal disease, hypoadrenocorticism and primary hyperparathyroidism increase the serum Ca2+ concentration (Bossart et al., 2001). The Mg2+, PO43− and Cl− levels are affected by renal problems. However, PO43− is also affected by rhabdomyolysis, dietary phosphorus excess, osteolytic bone disease, and hypoparathyroidism and hypercalcemia with normal glomerular filtration (Bossart et al., 2001). While differentiating clinical conditions from normal homeostatic variations in response to dietary, or environmental differences would require further diagnostics, these significant changes are worth noting.

Biochemical profile changes during maturation and reproductive state

Serum ALP was significantly higher in the juveniles compared to the adults. While Ca2+ was also increased in juveniles compared to adults with significant differences found when compared to PF. Both ALP, and Ca2+ have been reported to be increased in juveniles of multiple cetaceans including killer whales, bottlenose dolphins and beluga (Andersen, 1968; St Aubin et al., 2001; Venn-Watson et al., 2011; Nollens et al., 2018). Higher ALP and Ca2+ concentrations in young animals is generally associated with active bone growth (Andersen, 1968; Kovacs, 2001) and has been used to indicate physical maturity in other mammals including finless porpoises (Andersen, 1968). Increased CK in young animals was also observed in killer whales, bottlenose dolphins and pigs (Thorén-Tolling, 1982; Venn-Watson et al., 2007; Nollens et al., 2018). This increase during growth may be an indicator of muscle development in both species, but without isoenzyme identification a similar phenomenon occurring in YFP is only unknown.

Similar to what was observed in killer whales (Robeck and Nollens, 2013), Pregnant YFP had significantly decreased AST, AST/ALT ratio and increased GLB, TG. Liver enzyme decreases were attributed to volume expansion during pregnancy in killer whales and mare (Harvey et al., 2005). However, contrary to our results in YFP whereby BUN increased, this volume expansions also results in increased renal clearance and decreased BUN (Robeck and Nollens, 2013). Therefore, volume expansion may not be as significant in the relatively short gestation of the YFP (~<12 month) as compared to the killer whale (17.5 month, Robeck et al., 2015). Since BUN is considered metabolic waste of protein metabolism, the increase during YFP gestation may simply reflect increase food intake during gestation. The increase in TG were also observed in the killer whale (Robeck and Nollens, 2013) and in humans and horses this change has been attributed to estrogen mediated increase in Very Low Density Lipoprotein (VLDL) (Alvarez et al., 1996; Harvey et al., 2005).

Only HDL-C was elevated during lactation, while this change hints at the well-documented changes in lipid mobilization during lactation in most mammals (Koopman et al., 2002; Struntz et al., 2004), changes in TG, and TC post-partum are commonly observed in other species (Struntz et al., 2004; Robeck and Nollens, 2013). This lack of observed changes in TG and TC during lactation may indicate differences in YFP physiology or is most likely due to extremely small sample set of animals from which detecting significant deviations from the other groups was not possible.

Seasonality in biochemical parameters

While complete evaluation of seasonal changes could not be conducted due to the lack of sampling in the summer months, multiple parameters exhibited significant differences between the remaining three seasons. Serum creatinine in the YFPs showed seasonality with significantly higher levels in spring vs fall suggesting the effects of nutrition as observed in captive and wild bottlenose dolphins (Terasawa et al., 2002; Hall et al., 2007). We are aware (unpublished work) that in both populations of YFPs, prey availability is higher in the spring and summer and therefore these changes could reflect higher intake of prey. Furthermore, increased creatinine concentration during spring and summer months has been attributed to seasonal alteration in muscle mass in bottlenose dolphins (Hall et al., 2007; Macchi et al., 2011). In addition, higher concentrations of creatinine have been associated with increased and prolonged physical exertion (Gasper and Gilchrist, 2005) and this increase in spring for the YFP may be due to the increased socially driven physical activity associated with seasonality of reproduction in both males and females. For YFP, a seasonal spring increase in GLU was also observed and may also indicate metabolic changes in response to increased physical activity. Seasonal changes in activity can also be associated with changes in both demand and types of prey availability. For example, in the polar bear, concentrations of GLU correlate with seasonal changes in the percentage of dietary protein and fat (Bossart et al., 2001). The synthesis of ALB is directly associated with protein intake (Hall et al., 2007), therefore, higher serum ALB and ALB/GLB in spring provides additional support for increased prey consumption during the spring. The increased serum UA concentrations observed in winter for the YFP has also been reported in bottlenose dolphin and could be due to seasonal variation in the nutrient composition of their diet (Hall et al., 2007) as a diet rich in purines can cause hyperuricemia (Villegas et al., 2012). Similarly, seasonal variations in the lipid profile, electrolytes and hepatobiliary parameters of YFPs could be due to changes in the water components, changes in body condition, water temperature or quality, diet, photoperiod and other factors (Domingo-Roura et al., 2001; Terasawa et al., 2002; Sergent et al., 2004; Norman et al., 2013).

Conclusions and future recommendations

In summary, our findings provide indirect evidence for potential changes in fisheries resources in both populations as indicated by a significantly different and changing lipid profiles within and between the two populations. If the cause is from a declining fisheries resources in the TZO, it may be due to pesticides induce fish mortality, morbidity and low productivity. To regulate the Oxbow, fisheries resources and the total population numbers should be closely managed. Similarly, in the PL, illegal fishing and the use of non-selective fishing gears should be strictly avoided. While significant age specific differences were noted, all could be attributed to normal physiologic changes with age that have also been observed in other cetacean species. Across age groups, however, both the populations in general and TZO YFPs specifically showed hepatic dysfunction as indicated by higher hepatobiliary parameters which might be in response to various pollutants such as pesticides and poultry. The TZO also showed differing concentrations of various electrolytes as compared to PL which suggest gastrointestinal and endocrine changes whose etiology requires further investigation. Our findings suggest that YFPs in the TZO have not been removed from the negative effects of escalating anthropogenic activities especially, pesticides pollutions. Therefore, to conserve the YFPs in the TZO, special and immediate attention is required to improve the water quality and control the discharge from agriculture runoffs. In addition, future efforts at quantifying current concentrations of PCBs and other hydrocarbon bioaccumulations in fat and blood in both populations should be prioritized.

Acknowledgements

The authors thank all the member of the Research Group of Conservation Biology of Aquatic Animals of IHB for their cooperation work on the animal capture and blood sampling. This is a SeaWorld technical contribution number 2018-3-F.

Funding

This work was supported by the National Natural Science Foundation of China [no. 31430080].

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