Metabolic rates of giant pandas inform conservation strategies

Ursids evolved dietary diversity without major alterations in metabolic rates

The diets of the eight species of ursids range from carnivory (e.g., polar bears, Ursus maritimus) to insectivory (e.g., sloth bears, Melursus ursinus), omnivory (e.g., brown bears, U. arctos), and herbivory (e.g., giant pandas, Ailuropoda melanoleuca). Dietary energy availability ranges from the high-fat, highly digestible, calorically dense diet of polar bears (~ 6.4 kcal digestible energy/g fresh weight) to the high-fiber, poorly digestible, calorically restricted diet (~ 0.7) of giant pandas. Thus, ursids provide the opportunity to examine the extent to which dietary energy drives evolution of energy metabolism in a closely related group of animals. We measured the daily energy expenditure (DEE) of captive brown bears in a relatively large, zoo-type enclosure and compared those values to previously published results on captive brown bears, captive and free-ranging polar bears, and captive and free-ranging giant pandas. We found that all three species have similar mass-specific DEE when travel distances and energy intake are normalized even though their diets differ dramatically and phylogenetic lineages are separated by millions of years. For giant pandas, the ability to engage in low-cost stationary foraging relative to more wide-ranging bears likely provided the necessary energy savings to become bamboo specialists without greatly altering their metabolic rate.

Giant pandas are losing their edge: Population trend and distribution dynamic drivers of the giant panda

Comprehending the population trend and understanding the distribution range dynamics of species are necessary for global species protection. Recognizing what causes dynamic distribution change is crucial for identifying species' environmental preferences and formulating protection policies. Here, we studied the rear-edge population of the flagship species, giant pandas (Ailuropoda melanoleuca), to (1) assess their population trend using their distribution patterns, (2) evaluate their distribution dynamics change from the second (1988) to the third (2001) survey (2-3 Interval) and third to the fourth (2013) survey (3-4 Interval) using a machine learning algorithm (eXtremely Gradient Boosting), and (3) decode model results to identify driver factors in the first known use of SHapley Additive exPlanations. Our results showed that the population trends in Liangshan Mountains were worst in the second survey (k = 1.050), improved by the third survey (k = 0.97), but deteriorated by the fourth survey (k = 0.996), which indicates a worrying population future. We found that precipitation had the most significant influence on distribution dynamics among several potential environmental factors, showing a negative correlation between precipitation and giant panda expansion. We recommend that further research is needed to understand the microenvironment and animal distribution dynamics. We provide a fresh perspective on the dynamics of giant panda distribution, highlighting novel focal points for ecological research on this species. Our study offers theoretical underpinnings that could inform the formulation of more effective conservation policies. Also, we emphasize the uniqueness and importance of the Liangshan Mountains giant pandas as the rear-edge population, which is at a high risk of population extinction.

Age-related alterations in metabolome and microbiome provide insights in dietary transition in giant pandas

We conducted UPLC-MS-based metabolomics, 16S rRNA, and metagenome sequencing on the fecal samples of 44 captive giant pandas (Ailuropoda melanoleuca) from four age groups (i.e., Cub, Young, Adult, and Old) to comprehensively understand age-related changes in the metabolism and gut microbiota of giant pandas. We characterized the metabolite profiles of giant pandas based on 1,376 identified metabolites, with 152 significantly differential metabolites (SDMs) found across the age groups. We found that the metabolites and the composition/function of the gut microbiota changed in response to the transition from a milk-dominant diet in panda cubs to a bamboo-specific diet in young and adult pandas. Lipid metabolites such as choline and hippuric acid were enriched in the Cub group, and many plant secondary metabolites were significantly higher in the Young and Adult groups, while oxidative stress and inflammatory related metabolites were only found in the Old group. However, there was a decrease in the α-diversity of gut microbiota in adult and old pandas, who exclusively consume bamboo. The abundance of bacteria related to the digestion of cellulose-rich food, such as Firmicutes, Streptococcus, and Clostridium, significantly increased from the Cub to the Adult group, while the abundance of beneficial bacteria such as Faecalibacterium, Sarcina, and Blautia significantly decreased. Notably, several potential pathogenic bacteria had relatively high abundances, especially in the Young group. Metagenomic analysis identified 277 CAZyme genes including cellulose degrading genes, and seven of the CAZymes had abundances that significantly differed between age groups. We also identified 237 antibiotic resistance genes (ARGs) whose number and diversity increased with age. We also found a significant positive correlation between the abundance of bile acids and gut bacteria, especially Lactobacillus and Bifidobacterium. Our results from metabolome, 16S rRNA, and metagenome data highlight the important role of the gut microbiota-bile acid axis in the regulation of age-related metabolism and provide new insights into the lipid metabolism of giant pandas. IMPORTANCE The giant panda is a member of the order Carnivora but is entirely herbivorous. The giant panda's specialized diet and related metabolic mechanisms have not been fully understood. It is therefore crucial to investigate the dynamic changes in metabolites as giant pandas grow and physiologically adapt to their herbivorous diet. This study conducted UPLC-MS-based metabolomics 16S rRNA, and metagenome sequencing on the fecal samples of captive giant pandas from four age groups. We found that metabolites and the composition/function of gut microbiota changed in response to the transition from a milk-dominant diet in cubs to a bamboo-specific diet in young and adult pandas. The metabolome, 16S rRNA, and metagenome results highlight that the gut microbiota-bile acid axis has an important role in the regulation of age-related metabolism, and our study provides new insights into the lipid metabolism of giant pandas.

Field metabolic rates of giant pandas reveal energetic adaptations

Knowledge of energy expenditure informs conservation managers for long term plans for endangered species health and habitat suitability. We measured field metabolic rate (FMR) of free-roaming giant pandas in large enclosures in a nature reserve using the doubly labeled water method. Giant pandas in zoo like enclosures had a similar FMR (14,182 kJ/day) to giant pandas in larger field enclosures (13,280 kJ/day). In winter, giant pandas raised their metabolic rates when living at − 2.4 °C (36,108 kJ/day) indicating that they were below their thermal neutral zone. The lower critical temperature for thermoregulation was about 8.0 °C and the upper critical temperature was about 28 °C. Giant panda FMRs were somewhat lower than active metabolic rates of sloth bears, lower than FMRs of grizzly bears and polar bears and 69 and 81% of predicted values based on a regression of FMR versus body mass of mammals. That is probably due to their lower levels of activity since other bears actively forage for food over a larger home range and pandas often sit in a patch of bamboo and eat bamboo for hours at a time. The low metabolic rates of giant pandas in summer, their inability to acquire fat stores to hibernate in winter, and their ability to raise their metabolic rate to thermoregulate in winter are energetic adaptations related to eating a diet composed almost exclusively of bamboo. Differences in FMR of giant pandas between our study and previous studies (one similar and one lower) appear to be due to differences in activity of the giant pandas in those studies.

Consuming Different Structural Parts of Bamboo Induce Gut Microbiome Changes in Captive Giant Pandas

Giant pandas consume different structural parts of bamboo (shoots, leaves and culms) during different seasons. Previous research showed different bamboo parts have varying nutritional content and that a long-term diet consisting of a single part of bamboo resulted in remarkable metabolic changes within captive giant pandas. However, the effects on the gut microbiome of giant pandas, as a result of a single bamboo part diet, have not been investigated. Here, we evaluated the changes in gut microbial communities based on single bamboo part diets and their potential implications by using 16S rRNA gene-based amplicon sequencing and metagenome shotgun sequencing. We found that the composition and function of the gut microbiome from captive giant pandas fed exclusively culms were significantly different from that of individuals fed shoots or leaves. During the culm feeding period, the gut microbiome showed strongest digestive capabilities for cellulose, hemicellulose and starch, and had the highest potential abilities for the biosynthesis of bile acids, fatty acids and amino acids. This suggests the microbiome aids in breaking down culm, which is more difficult for giant pandas to digest, as a means to compensate for the nutrient poor content of the culm. Genes related to fatty acid metabolism and tricarboxylic acid cycle enzymes were more abundant during the leaf stage diet than that in the shoot and culm stages. Thus, the microbiome may help giant pandas, which typically have low lipase levels, with fat digestion. These results illustrate that adaptive changes in the gut microbiome community and function may be an important mechanism to aid giant panda digestion when consuming different structural parts of bamboo.

Comparative skeletal anatomy of neonatal ursids and the extreme altriciality of the giant panda

Mammalian neonates are born at a wide range of maturity levels. Altricial newborns are born with limited sensory agency and require extensive parental care. In contrast, precocial neonates are relatively mature physically and often capable of independent function shortly after birth. In extant mammals, placental newborns vary from altricial to precocial, while marsupials and monotremes are all extremely altricial at birth. Bears (family Ursidae) have one of the lowest neonatal-maternal mass ratios in placental mammals, and are thought to also have the most altricial placental newborns. In particular, giant pandas (Ailuropoda melanoleuca) are thought to be exceptionally altricial at birth, and possibly marsupial-like. Here we used micro-computer (micro-computed) tomography scanning to visualize the skeletal anatomy of ursid neonates and compare their skeletal maturity with the neonates of other caniform outgroups. Specifically, we asked whether ursid neonates have exceptionally altricial skeletons at birth compared with other caniform neonates. We found that most bear neonates are similar to outgroup neonates in levels of skeletal ossification, with little variation in degree of ossification between ursine bears neonates (i.e. bears of the subfamily Ursinae). Perinatal giant pandas, however, have skeletal maturity levels most similar to a 42-45-day-old beagle fetus (~70% of total beagle gestation period). No bear exhibits the skeletal heterochronies seen in marsupial development. With regards to skeletal development, ursine bears are not exceptionally altricial relative to other caniform outgroups, but characterized largely by the drastic difference between newborn and adult body sizes. A review on the existing hypotheses for ursids' unique reproductive strategy suggests that the extremely small neonatal-maternal mass ratio of ursids may be related to the recent evolution of large adult body size, while life history characteristics retained an ancestral condition. A relatively short post-implantation gestation time may be the proximal mechanism behind the giant panda neonates' small size relative to maternal size and altricial skeletal development at birth.

The metabolic response of the Bradypus sloth to temperature

Poikilotherms and homeotherms have different, well-defined metabolic responses to ambient temperature (T a ), but both groups have high power costs at high temperatures. Sloths (Bradypus) are critically limited by rates of energy acquisition and it has previously been suggested that their unusual departure from homeothermy mitigates the associated costs. No studies, however, have examined how sloth body temperature and metabolic rate vary with T a . Here we measured the oxygen consumption (VO2) of eight brown-throated sloths (B. variegatus) at variable T a 's and found that VO2 indeed varied in an unusual manner with what appeared to be a reversal of the standard homeotherm pattern. Sloth VO2 increased with T a , peaking in a metabolic plateau (nominal 'thermally-active zone' (TAZ)) before decreasing again at higher T a values. We suggest that this pattern enables sloths to minimise energy expenditure over a wide range of conditions, which is likely to be crucial for survival in an animal that operates under severe energetic constraints. To our knowledge, this is the first evidence of a mammal provisionally invoking metabolic depression in response to increasing T a 's, without entering into a state of torpor, aestivation or hibernation.

Energetic costs of locomotion in bears: is plantigrade locomotion energetically economical?

Ursids are the largest mammals to retain a plantigrade posture. This primitive posture has been proposed to result in reduced locomotor speed and economy relative to digitigrade and unguligrade species, particularly at high speeds. Previous energetics research on polar bears (Ursus maritimus) found locomotor costs were more than double predictions for similarly sized quadrupedal mammals, which could be a result of their plantigrade posture or due to adaptations to their Arctic marine existence. To evaluate whether polar bears are representative of terrestrial ursids or distinctly uneconomical walkers, this study measured the mass-specific metabolism, overall dynamic body acceleration, and gait kinematics of polar bears and grizzly bears (Ursus arctos) trained to rest and walk on a treadmill. At routine walking speeds, we found polar bears and grizzly bears exhibited similar costs of locomotion and gait kinematics, but differing measures of overall dynamic body acceleration. Minimum cost of transport while walking in the two species (2.21 J kg^-1 m^-1) was comparable to predictions for similarly sized quadrupedal mammals, but these costs doubled (4.42 J kg^-1 m^-1) at speeds ≥5.4 km h^-1 Similar to humans, another large plantigrade mammal, bears appear to exhibit a greater economy while moving at slow speeds.

An ecophysiological perspective on likely giant panda habitat responses to climate change

Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species' adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species' distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas (Ailuropoda melanoleuca) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7%-52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6%-86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5%-68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning.