Philippa Kaur

Many cities in China, such as Xi’an (pictured), have experienced rapid growth in the past few decades.Credit: Xinhua/Shutterstock

On 28 January 2020, a team of Chinese conservation scientists distributed a questionnaire across social-media platforms, asking Chinese citizens how they felt about proposed legislation that would ban the consumption and trade of wildlife in the country.
It was an apposite moment: the questionnaire hit social-media platforms such as WeChat and Weibo just days after China had been forced to close its major cities to prevent the spread of a disease that scientists suspected was transferred to humans from an animal species at a market in Wuhan.
More than 90% of the 74,070 respondents were in favour of a complete ban on wildlife trade — and, a month later, the central government came to the same conclusion and legislated to that effect. Researchers are increasingly studying the impact of these policies, and the country’s biodiversity. But big questions remain about whether China will deliver on its growing list of environmental commitments.

Bin Zhao, an ecologist at Fudan University in Shanghai, China, says that, since the start of the COVID-19 pandemic, people in urban areas have been paying more attention to biodiversity than ever before. “People realized that contact with wild animals could lead to an outbreak of an epidemic, even in urban areas. This not only enhanced people’s understanding of biodiversity, but also promoted the idea that wildlife-protection law needed to be improved,” says Zhao.
It came at a time when China was already committed to changing its approach to ecological protection, he says. In 2018, China amended its constitution to include the goal of becoming an ‘ecological civilization’. In the words of Chinese President Xi Jinping in 2017, economic development could no longer be at the expense of the environment.
Multiple environmentally friendly policies have already been announced, such as the introduction of an ‘ecological red line’ policy to protect more of the Chinese mainland from development (see ‘Protected land’); a new network of national parks; stricter supervision of conservation; and a streamlining of environmental-oversight agencies — all to meet a government target of making the country’s environment ‘beautiful’ by 2035.

Sources: UN/Xinhua/OECD

Big cities, few controls
In 1950, about only 13% of China’s population lived in cities. But since the 1980s, the country’s cities have grown rapidly as the engines of its economic growth (see ‘Urban population’). Millions left homes in rural areas to forge more prosperous lives in growing and newly built cities. Government policies, aimed at bolstering the economy, helped to encourage close to two-thirds of China’s population to move to these new urban areas, and the nation continues to have one of the world’s fastest growing urban populations. This has put intense pressure on the country’s ecology.

Sources: UN/Xinhua/OECD

“From an economic perspective, our ecosystems and environment have historically been considered to be worthless,” says Zhao. China’s natural resources, such as its wetlands, forests and water sources, haven’t received the same level of care from authorities as targets for economic growth, he says (see ‘Vegetation change’).

Sources: UN/Xinhua/OECD

As urban areas grow, there are direct and indirect impacts on ecological systems, according to Rob McDonald, who researches the impact and dependencies of cities on the natural world at The Nature Conservancy in Washington DC.
Land is repurposed for development, and natural resources are needed to construct buildings and provide food and water for city dwellers, he says. These changes can lead to environmental problems, such as water and air pollution, insufficient water availability and deforestation much farther afield than in urban areas themselves.
China’s government has been open about its commitment to tackling these problems, says Alice Hughes, a zoologist at the Xishuangbanna Tropical Botanical Garden in Menglun town, China. In May 2021, China will host the fifteenth United Nations Convention on Biological Diversity, also known as COP 15, in Kunming, where 200 countries will meet to sign off on a legally binding set of global targets to protect the world’s biodiversity. The country has already contributed to some broader environmental targets, including being carbon neutral by 2060.
China has had some success, most notably in reducing air pollution. For example, in 2017, the amount of fine particulate matter in Beijing’s air dropped by just under 40% from the level in 2013, the year when national targets were launched.
But at a press conference to discuss China’s progress on ecological and environmental protection, Cui Shuhong, an official at the Ministry of Ecology and Environment, said the country has much more to do to alleviate the fundamental pressures placed on its natural resources by economic development.
Zhengguang Zhu, an environmental officer at China’s National Marine Environmental Monitoring Center, is familiar with preparations for COP 15: there are multiple working groups operating within the Ministry of Ecology and Environment, which are each responsible for different aspects of the event, from logistics to setting targets for improvements to China’s environment.

Live turtles on display at a wildlife market in Shanghai, China, in August 2020. During the COVID-19 pandemic, the Chinese government issued a policy banning wildlife trade for food, but trade of exotic animals as pets still continues.Credit: Ales Plavevski/EPA-EFE/Shutterstock

These working groups ask China’s public bodies, such as the ministry of agriculture, to offer their opinions on what the country feels should be included in the final roadmap for the coming decade.
“I think the meeting will show that China has done its homework and is willing to be a good host. But leadership is not just about hospitality. It’s about having an ambitious framework that enables change, and I think we’ve got a long way to go before that happens,” says Zhu.
Behaviour change
Conservation researcher Tien Ming Lee, based at the Sun Yat-sen University in Guangzhou, China, says scientists and politicians are currently focused on finding better ways to protect Chinese ecosystems while continuing the country’s urban economic growth.
His research team works across a range of projects, all focused on finding ways to prompt people to act differently and sustainably. For example, he is currently part of a 4-year, €10-million (US$12 million) project, mainly funded by the European Union, called Partners against Wildlife Crime. The project, which began in January 2019, hopes to disrupt the illicit supply chains through which exotic animals and plants, specifically tigers (Panthera tigris), Asian elephants (Elephas maximus), Siamese rosewood (Dalbergia cochinchinensis) and freshwater turtles, are traded throughout Cambodia, China, Laos, Malaysia, Myanmar, Thailand and Vietnam.
As part of this project, Lee’s team and Lishu Li at the Wildlife Conservation Society China Counter Wildlife Trafficking Program are developing marketing materials to change the buying habits of urban Chinese consumers by attempting to dissuade them from illegal acts, such as buying tiger bone or elephant skin online for jewellery and traditional medicine, or keeping endangered freshwater turtles as pets. Lee says the materials have been developed with behavioural-science techniques: they aim to appeal to consumers’ desire to be seen to act in a conscientious manner.

Police patrol the wetlands of the Yellow River Estuary ecotourism area near Dongying City, China.Credit: Costfoto/Barcroft Media via Getty

Lee has also been part of a research project that looked at how trade agreements that stem from the country’s international Belt and Road economic initiative, an infrastructure project that aims to link trade across Europe, Asia and Africa to China, could lead to a greater demand for traditional Chinese medicine across the world. The plant, animal and fungal products used in these practises are often sourced from the wild, which might exacerbate the illegal and unsustainable trade of those species, he says.
His research, a collaboration with Amy Hinsley, a conservation biologist at the University of Oxford, UK, concluded that there was a clear, urgent need for China to introduce carefully managed supply chains and ensure that rural farmers have resources for sustainable farming.
During her four-decade career, Lu Zhi, a conservation biologist at Peking University in Beijing, has seen a shift in her field’s focus. It moved from observing animals in their natural habitats and coming up with ways to protect them from human activity to observing human behaviour: studying what can be done to make people’s lives more ecologically sustainable.
In 2017, Zhi’s Shanshui Conservation Center, a non-governmental organization she founded in 2007 to develop community-based conservation projects, began working with herdsmen in Qinghai province on the Tibetan Plateau. The team wanted to help them to develop livelihoods from conservation activities in an underdeveloped, highly biodiverse area of China. The villagers learnt how to patrol and monitor wildlife, and how to act as guides for tourists interested in animal watching — including for the elusive and endangered snow leopard (Panthera uncia). Similar projects have been rolled out in 42 villages in western China.
Zhi admits that such small projects are certainly not enough to bring the paradigm shift needed to safeguard the country’s vulnerable ecosystems. Government intervention has proved to be effective in tackling the larger issues, such as air and water pollution, she says. But “it’s not fair to ask people in rural areas not to develop their lives for the sake of wildlife, while others live in prosperous cities. We need alternative solutions.” More

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The Sierra de Manantlán biosphere reserve in Mexico is a source of clean water for urban residents in nearby cities.Credit: Adriana Margarita Larios Arellano/Shutterstock

Sierra de Manantlán is a 140,000-hectare biosphere reserve in west central Mexico. It is home to 3,000 plant species and a forest whose soils and limestone mountains enable purified water to reach the nearby town of Colima.
Twenty years ago, researchers at the University of Guadalajara in Mexico proposed that Colima should consider paying to use the forest’s clean water, and that the money could go to supporting the biosphere reserve’s inhabitants.
The 30,000 people who lived in the forest were poor and in ill health. Unemployment was high, and there were few schools or medical clinics. But the absence of buildings, piped water and electric power had an unintended consequence: it was keeping the forest intact. In return for looking after nature, the researchers argued, the people of Sierra de Manantlán should be compensated, and the funds used for education, health care and employment training. Although not a new idea for Mexico, it was rejected by the city’s authorities. The concept that a forest ecosystem had monetary value — and that its custodians could be compensated — was controversial and much misunderstood.

Last week, however, countries took a giant step towards enabling public authorities to put a value on their environment. At its annual meeting, the United Nations Statistical Commission — whose members are responsible for setting and verifying standards for official statistics in their countries — laid out a set of principles for measuring ecosystem health and calculating a monetary value. These principles, known as the System of Environmental-Economic Accounting Ecosystem Accounting (SEEA EA), are set to be adopted by many countries on 11 March.
The principles were agreed after a 3-year writing and review process that involved 100 experts and 500 reviewers from various disciplines and countries. Once adopted, they will give national statisticians an internationally agreed rule book. It will provide a template for payments for ecosystem services — such as those once proposed for Colima — and an official benchmark against which the condition of ecosystems can be judged by policymakers and researchers over time.
The decision didn’t go as far as it might have done. The overwhelming majority of participating countries — led by Brazil, Colombia, India, Mexico and South Africa, among others — wanted the new rules to be designated as a statistical standard. These countries, rich in biodiversity, want to get on with valuing their natural systems, partly so that any ecological losses can be compared with potential gains from economic development. The designation of a statistical standard would also have enabled statistics offices to access public and international funding to carry out what would be regarded as a core part of their work, and not something voluntary or non-essential.
But the United States and a number of European Union countries objected. This was partly on the grounds that there is still much debate over valuation methodology, meaning that it is too soon to use ‘standard’ as a label. This setback was unfortunate: participating countries could have adopted the label while creating a system for revision and refinement, ensuring that the new standard could continue to be improved. Fortunately, the meeting’s attendees chose the next best thing — calling the rules “internationally recognized statistical principles and recommendations”.

The objections raised are a reminder that opinions on setting monetary values for nature are deeply held, with persuasive arguments on all sides. Some argue that nature is too valuable to be regarded in the same way as a commodity, and belongs to all. Valuation in the economic sense suggests that someone has ownership rights — but ecosystem services are rarely, if ever, ‘owned’ by anyone. The new principles do take this into account.
The record of the statisticians’ meeting shows that much debate remains on how to value something that isn’t bought and sold in a conventional way. But at the same time, this is an active area of research. Many studies have been captured in a landmark report, The Economics of Biodiversity: The Dasgupta Review, published last month by the UK Treasury. The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services is also conducting a review of the concept of valuation, which will include additional perspectives from the humanities, and voices from under-represented communities, such as Indigenous peoples.
The debates will continue, but agreement between the world’s statisticians is nevertheless an important step. It means, for example, that those wishing to compensate low-income and marginalized communities for protecting nature — such as the communities in Sierra de Manantlán — now have an internationally agreed template to work from. And policymakers will have to contend with the heads of statistics agencies if they object. UN chief economist Elliot Harris rightly called the new principles a game changer. “The economy needs a bailout, but so does nature,” he said. “What we measure, we value, and what we value, we manage.” Momentum on valuing ecosystem services is now unstoppable, and that is a good thing. More

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Almost 50 years ago, Simmons26 called gyrocotylideans a “century-old enigma” and this status still persists despite the advent of more advanced identification methods3. The poor understanding of the group (e.g., the complete life cycle of none of the species is known) is linked with the scarcity of available data and the biological peculiarities of these tapeworms and their holocephalan hosts. In particular, most of the host species are rarely available deep-sea dwellers, which often could not be examined fresh or were frozen with their parasites prior to examination. If isolated alive, gyrocotylideans exhibit an unusual morphological variability due to the contraction of their large bodies and as a result of different fixative procedures which were tested to ensure their relaxation (e.g.27). Despite these issues, several comprehensive studies have been conducted, e.g.15,16,21,28, which provided deep insight into the biology, ecology and taxonomy of these enigmatic tapeworms. Nevertheless, the poor quality of the specimens studied and the use of different, not always appropriate, methods of parasite fixation, unintentionally affected the quality of morphological descriptions of most gyrocotylidean species, which prevented the establishing of clear morphological borders to delimit individual species. As a result, the informative value of morphological traits used for species delimitation should be re-assessed, based on the simultaneous use of molecular data, i.e., the use of hologenophores to match morphology and molecular data. Existing problems with species delimitation and morphological variability even led to complete omission of morphological characterisation of two new species described just recently6.
Herein, the genotyping of the Gyrocotyle spp. specimens acquired in Taiwan revealed four distinct genotypes, each one more related to the North Atlantic isolates identified as “Gyrocotyle urna” off Ireland (the isolate is genetically diverse from G. urna off Norway), “G. rugosa” off Alaska (probably misidentified, see below), G. discoveryi off Ireland and G. confusa off Norway, respectively, than to each other.
In addition to casting doubts on the restriction of gyrocotylideans to individual oceans, our data also question the proclaimed strict host specificity3,7, because specimens of Gyrocotyle sp. genotype 3 were found in two hosts species, which are not the closest relatives to one another—C. phantasma and C. cf. argiloba (Fig. 4). Broader host specificity was also reported for G. fimbriata, which was found in Hydrolagus colliei and Chimaera phantasma, and for G. rugosa, recorded in Callorhinchus callorynchus and C. milii14,15,24,29. Gyrocotyle urna was also found in several holocephalans, including Chimaera monstrosa, Callorhinchus callorynchus, Hydrolagus ogilbyi Waite and H. colliei24,29,30. In contrast, Bandoni & Brooks16 revised the host spectrum of this parasite, considering C. monstrosa as the only host of G. urna.
The suitability of the molecular markers employed for this group also requires attention, because a considerable amount of phylogenetic information was also lost in the un-rooted dataset due to treatment of the numerous gaps in the 28S rRNA alignment. The involvement of partial COI gene sequences seemed to be informative for estimating gyrocotylidean phylogeny, because we obtained a no-gap COI alignment and improved support for some nodes in the three-gene network. The suitability of this marker requires assessment employing further taxa, because except for our isolates off Taiwan and Argentina, only a single sequence of the COI gene (i.e., that of G. urna off Norway; GenBank acc. no. JQ268546) is currently available.
A single specimen of Gyrocotyle sp. genotype 4 was conspicuously different morphologically from the remaining ones by having few folds on the lateral margins, many acetabular spines, a narrow funnel and a small rosette. However, its formal description as a new species would be premature, because only a single specimen was found. Morphological differences among the specimens of the other genotypes were not so obvious, even though a careful examination of the hologenophores allowed us to find several morphological traits that were characteristic for particular genotypes (see “Results” section). Among them, the number of acetabular spines and the distribution of the body spines and their size may be potentially useful for species differentiation, especially because the body contraction can hardly affect them. Since body contraction cannot be absolutely excluded even when live specimens are properly fixed, its effect could be overcome to some degree by an evaluation of ratios related to the main body dimensions (e.g., length of uterine sac/total body length) rather than comparison of total measurements of internal structures.
The specimens off Taiwan most probably represent several new species, but we decided not to describe them formally as new taxa, mainly because of the shortage of comparative data. In addition to these specimens, two hologenophores of Gyrocotyle rugosa off Argentina were examined, which made it possible to characterise the type species of the genus. The host of G. rugosa described by Diesing10 was questionable until Callorhynchus antarcticus (= C. callorynchus—see31) off New Zealand was finally established as its currently accepted type host3,32. Gyrocotyle rugosa was found in coastal waters of South America, South Africa and New Zealand as a parasite of C. callorynchus and C. milii, suggesting its broader host specificity16,24. Our specimens from C. callorynchus off Argentina were identified as G. rugosa based on crenulated (i.e., without any folds) lateral margins, a tiny uterine sac, a branched uterus and embryonated eggs in the uterine sac; the latter two traits are unique to this species21. Genetically, it clustered with an unspecified isolate of Gyrocotyle from C. milii off Australia, and these specimens seem to be conspecific.
In contrast, an isolate from Hydrolagus colliei off Alaska identified as G. rugosa (GenBank acc. nos. AF286925 and AF124455) was apparently misidentified, because (i) it was found in an unrelated definitive host (H. colliei belongs to the family Chimaeridae, whereas the type host to the family Callorhinchidae), (ii) its distant geographic origin (the type locality of G. rugosa is unclear, but it is definitely in the Southern hemisphere), and (iii) its genetic divergence from our isolate of G. rugosa from the type host off Argentina. The isolate from H. colliei may represent Gyrocotyle fimbriata or G. parvispinosa, which have been reported from this host off the Pacific coast of North America, but its identification was not possible because morphological vouchers were not available to the present authors.
Gyrocotylideans were generally considered to be oioxenous, i.e. strictly specific parasites sensu Euzet and Combes33, with each gyrocotylidean species parasitising a single holocephalan species. Although several species were reported from two or more hosts species16,24, these findings are usually considered as misidentifications due to the unclear taxonomy of the order. Moreover, some holocephalans, such as Ch. monstrosa, H. colliei, H. affinis, and Ca. callorynchus, were often found to harbour two or more gyrocotylidean species, one common and the other rare9,10,21,22,23. Our findings of Gyrocotyle sp. genotypes 1 and 3 in Ch. phantasma and Gyrocotyle sp. genotypes 2, 3 and 4 in Ch. cf. argiloba suggested stenoxenous host specificity (i.e., the occurrence in a few closely related hosts) of gyrocotylideans, because the specimens of genotype 3 were found in both species of Chimaera. The obvious genetic similarity of our G. rugosa specimen from Ca. callorynchus and the isolate of Gyrocotyle sp. from Ca. milii also questions the strict specificity of this group, but morphological vouchers of the latter, which are necessary for the confirmation of their conspecificity, are not available.
Our genetic analyses provided insight into the interrelationships among the gyrocotylideans, even though the absence of a suitable outgroup did not enable us to broadly assess the possible evolutionary scenario of this earliest evolving group of tapeworms. Moreover, genetic data on only half of the nominal species of Gyrocotyle are available, not considering the possibility of misidentifications of previously sequenced specimens, for which hologenophores are not available. However, some clues of host-parasite coevolution can be inferred from the network. The mutual genetic distance of species/genotypes from the same host species suggests multiple colonisation events rather than co-speciation with their hosts within the order. It seems that G. phantasma might have been colonised by Gyrocotyle sp. genotype 1 or genotype 3, because these two genotypes are not the closest relatives in our analyses. The same pattern is obvious for C. cf. argiloba parasitised by Gyrocotyle sp. genotype 2, 3 and 4, and also for C. monstrosa, which harbours G. urna, G. confusa and G. nybelini. Indeed, Colin et al.27 considered these species from C. monstrosa to be conspecific, but our genetic data support the validity of three separate and genetically distant species. Moreover, G. nybelini formed by far the most distant lineage among all isolates, which may suggest the validity of the genus Gyrocotyloides Furhmann, 1931.
Genetic divergence of congeneric tapeworms from the same host species was also observed in several elasmobranch/teleost-cestode assemblages, e.g., Acanthobothrium spp. (Onchoproteocephalidea) and the mumburarr whipray Urogymnus acanthobothrium Last, White & Kyne; Echeneibothrium spp. (Rhinebothriidea) and the yellownose skate Dipturus chilensis (Guichenot); and Pseudoendorchis spp. (Onchoproteocephalidea) and the catfish Pimelodus maculatus Lacepède34,35,36.
The aim of this paper was to provide new insight into the phylogenetic relationships within the enigmatic order Gyrocotylidea, but, in particular, to demonstrate the lack of geographical patterns in the distribution of most its species and the limited suitability of current morphological characteristics for species circumscription. Herein, we have outlined a methodology (fixation of live specimens with hot fixative and the exclusive use of hologenophores) that should be used in future taxonomic, ecological and biogeographical studies of gyrocotylideans in order to reliably circumscribe their actual species diversity and to unravel associations with their hosts, a relict group of marine vertebrates. Gyrocotylideans represent one of the key groups of parasitic flatworms (Neodermata) in terms of a better understanding of their evolutionary history and the switch of free-living flatworms to parasitism. More

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Antibiotic duration experiment
Twenty-eight-week-old female C57BL/6J mice from the same birth cohort were co-housed (5–6 mice per cage) prior to beginning the experiment, and then separated into individual cages 1 week prior to antibiotic treatment. Singly housed mice were exposed to 0.5 mg/mL33 cefoperazone in their drinking water for 0, 2, 4, 8, or 16 days (Fig. 1A). Based on the literature, we calculated the minimum dose of cefoperazone based on the mean and standard deviation of water consumption by C57BL/6J mice ((7.7, mp 0.3,{mathrm{mL}}) per 30 g of body weight)44. If the heaviest mouse in our study (~22 g) consistently consumed water at 2 SD below the mean (i.e. 5.5 of 0.5 mg/mL cefoperazone), they would still receive 125 mg/kg/day of cefoperazone, which is within the therapeutic dosing range for humans (100–150 mg/kg/day; although cefoperazone is administered to humans via intravenous injection)45.
Fig. 1: Effect of antibiotic exposure duration on non-responder phenotype.

The table in the center denotes the number of non-responder and responder mice in each treatment duration group. A Experimental design for the duration experiment. Circles denote sampled time points. Time points were considered sampled “during” antibiotic treatment between day 0 and day 2, 4, 8, and 16, respectively, as denoted by orange shades. B Relative abundance of phyla on the last day of antibiotics treatment. The control panel is an average over all untreated controls from all time points. Only phyla with a relative abundance of at least 0.1% are shown. Each barchart denotes means from at least two samples and white insets are the sample size used for each barchart. C Percentage of mitochondria and chloroplast sequences in 16S amplicon data relative to antibiotic treatment. Colors: red—controls not treated with antibiotics, green—non-responders, blue—responders. D Principal coordinate analysis (PCoA) of samples during and after antibiotic exposure (n = 143 samples with >10,000 reads per sample, day ≥ 0). Ellipses denote 95% confidence intervals from a Student t-distribution. Each point denotes a sample. ASV abundances were rarefied to 10,000 reads for each sample and percentages in brackets denote the explained variance. Samples with less than 10,000 reads per sample were not included in the analysis. E Dynamics of amplicon sequence variants (ASVs). Gained ASVs are variants that were not present before antibiotics treatment but are present after. Similarly, lost ASVs were present before treatment but not after, and persistent ASVs were present before and after. Stars denote significance under a Mann–Whitney U test: *p  More

Specimens
We used brains obtained from three cetacean species (harbour porpoise—Phocoena phocoena, minke whale—Balaenoptera acutorostrata, and humpback whale—Megaptera novaeangliae) and 11 artiodactyl species (sand gazelle—Gazella marica, domestic pig—Sus scrofa, Nubian ibex—Capra nubiana, springbok—Antidorcas marsupialis, blesbok—Damaliscus pygargus, greater kudu—Tragelaphus strepsiceros, blue wildebeest—Connochaetes taurinus, dromedary camel—Camelus dromedarius, nyala—Tragelaphus angasii, river hippopotamus—Hippopotamus amphibius, and African buffalo—Syncerus caffer) (Table 1). All artiodactyl brains were perfusion fixed with 4% paraformaldehyde in 0.1 M phosphate buffer through the carotid arteries following euthanasia45. The harbour porpoise specimens were perfusion fixed through the heart following euthanasia, while the minke whale and humpback whale brains were immersion fixed in 4% paraformaldehyde in 0.1 M phosphate buffer. All brains were then stored in an antifreeze solution at – 20 °C until use45. All specimens were taken under appropriate governmental permissions, with ethical clearance provided by the University of the Witwatersrand Animal Ethics Committee (Clearance number 2008/36/1), which uses guidelines similar to those of the National Institutes of Health regarding the use of animals in scientific research and is compliant with ARRIVE guidelines.
Immunohistochemical staining
Blocks of tissue from the anterior cingulate (dorsal to the rostrum of the corpus callosum, in all species apart from the humpback whale where we did not have this tissue block) and occipital cortex (presumably primary visual cortex, from all species) with underlying white matter were taken from each of the specimens. These were placed in a 30% sucrose in 0.1 M phosphate buffer solution at 4 °C until equilibrated. The blocks were frozen in crushed dry ice, mounted on an aluminium stage and sectioned at 50 µm orthogonal to the pial surface. Alternate sections were stained for Nissl (with 1% cresyl violet), UCP1, UCP2, UCP3, UCP4, UCP5, dopamine-ß-hydroxylase (DBH) and tyrosine hydroxylase (TH). To investigate the presence of neural structures immunolocalizing uncoupling proteins, DBH and TH, we used standard immunohistochemical procedures with antibodies directed against UCP1, UCP2, UCP3, UCP4, UCP5, DBH and TH. While immunolocalization for UCP1, UCP4, UCP5, DBH and TH were clear, only occasional cortical neurons were immunopositive for UCP2, and no immunolocalization could be detected for UCP3 in the species studied. It should be noted here that immunostaining for DBH and TH did not work in the humpback whale specimen, perhaps due to the fixation procedure or the conformation of the targeted proteins in this species preventing recognition of the DBH and TH proteins by the antibodies used. Sections used for the Nissl series were mounted on 0.5% gelatine-coated glass slides, cleared in a solution of 1:1 chloroform and absolute alcohol, then stained with 1% cresyl violet to reveal cell bodies. For the immunohistochemical staining, each section was treated with endogenous peroxidase inhibitor (49.2% methanol:49.2% 0.1 M PB:1.6% of 30% H2O2) for 30 min and subsequently subjected to three 10 min 0.1 M PB rinses. Sections were then incubated for 2 h, at room temperature, in blocking buffer (containing 3% normal rabbit serum, NRS, for the UCP1-5 sections/3% normal horse serum, NHS, for the DBH sections/3% normal goat serum, NGS, for the TH sections, plus 2% bovine serum albumin and 0.25% Triton-X in 0.1 M PB). This was followed by three 10 min rinses in 0.1 M PB. The sections were then placed in the primary antibody solution that contained the appropriately diluted primary antibody in blocking buffer for 48 h at 4°C under gentle shacking. The optimal dilutions for the UCP primary antibodies were determined with a series of stains in which the dilution of the primary antibodies ranged from 1:300 through to 1:9600, with any staining in all species being absent at a dilution of 1:4800 irrespective of fixation method. We used antibodies directed against UCP1 (Santa Cruz Biotechnology, C-17, sc-6528, Lot# D0411, goat polyclonal IgG, dilution 1:300, RRID:AB_2304265), UCP2 (Santa Cruz Biotechnology, C-20, sc-6525, Lot# E0211, goat polyclonal IgG, dilution 1:300, RRID:AB_2213585), UCP3 (Santa Cruz Biotechnology, C-20, sc-7756, Lot# A2511, goat polyclonal IgG, dilution 1:300, RRID:AB_2213922), UCP4 (Santa Cruz Biotechnology, N-16, sc-17582, Lot# E2004, goat polyclonal IgG, dilution 1:300, RRID:AB_793648), UCP5 (Santa Cruz Biotechnology, Q-16, sc-50540, Lot# B1207, goat polyclonal IgG, dilution 1:300, RRID:AB_2286101), DBH (Merck-Millipore, MAB308, mouse monoclonal IgG, dilution 1:4000, RRID:AB_2245740) and TH (Merck-Millipore, AB151, rabbit polyclonal IgG, dilution 1:3000, RRID:AB_10000323). This incubation was followed by three 10 min rinses in 0.1 M PB and the sections were then incubated in a secondary antibody solution (1:1000 dilution of biotinylated anti-goat IgG, BA-5000, Vector Labs, for UCP1-5 sections/1:1000 dilution of biotinylated anti-mouse IgG, BA 2001, Vector labs, for DBH sections/1:1000 dilution of biotinylated anti-rabbit IgG, BA-1000, Vector Labs, for TH sections, in a blocking buffer containing 3% NRS/NHS/NGS and 2% BSA in 0.1 M PB) for 2 h at room temperature. This was followed by three 10 min rinses in 0.1 M PB, after which sections were incubated for 1 h in avidin-biotin solution (at a dilution of 1:125, Vector Labs), followed by three 10 min rinses in 0.1 M PB. Sections were then placed in a solution of 0.05% 3,3′-diaminobenzidine (DAB) in 0.1 M PB for 5 min, followed by the addition of 3 ml of 3% hydrogen peroxide to each 1 ml of solution in which each section was immersed. Chromatic precipitation was visually monitored and verified under a low power stereomicroscope. Staining was allowed to continue until such time as the background stain was at a level that would assist architectural reconstruction and matching without obscuring the immunopositive neurons. Development was halted by placing the sections in 0.1 M PB, followed by two more rinses in 0.1M PB. To test for non-specific staining of the immunohistochemical protocol, in selected sections the primary antibody or the secondary antibody were omitted, which resulted in no staining of the tissue. The immunostained sections were then mounted on 0.5% gelatine coated glass slides, dried overnight, dehydrated in a graded series of alcohols, cleared in xylene and coverslipped with Depex. Digital photomicrographs were captured using Zeiss Axioshop and Axiovision software. No pixilation adjustments, or manipulation of the captured images were undertaken, except for the adjustment of contrast, brightness, and levels using Adobe Photoshop 7.
Western immunoblotting
Protein expression for UCP1 and UCP4 was assayed using standard qualitative Western immunoblotting techniques. To verify the specificity of the UCP1 antibody for the UCP1 protein, we tested this antibody with rat brown fat. For the UCP4 antibody protein samples were extracted from the paraformaldehyde fixed tissue using the Qproteome FFPE Tissue Kit (Qiagen, Germany). The tissue blocks analysed here were taken from the anterior cingulate and occipital cortex (as described above) and contained both gray and white matter. 30–40 mg of the sample were incubated in 100 µl of Extraction Buffer EXB Plus (Qiagen, Germany) containing 6% β-mercaptoethanol on ice for 5 min and mixed by vortexing. The samples were boiled for 20 min at 100°C and subsequently incubated at 50°C overnight with agitation at 300 rpm. The samples were then placed on ice for 1 min and centrifuged for 15 min at 14 000g at 4°C. The supernatant was transferred into clean tubes and the protein concentration was determined using the Bradford protein assay kit (Bio-Rad Laboratories, USA). The protein extracts (20 µg) were made soluble in sample buffer comprised of 0.0625 M Tris–HCl, pH 6.8, 10% glycerol, 2% SDS, 2.5% β-mercaptoethanol and 0.001% bromophenol blue, boiled at 95°C for 5 min and subjected to 12% SDS-polyacrylamide gel electrophoresis and transferred to polyvinylidene difluoride (PVDF) (Millipore) at 20 V/cm for 1h. Electrophoresis and protein transfer was achieved using Mini Trans-Blot Electrophoretic Transfer Cell (Bio-Rad Laboratories, Inc. USA). After the transfer the blots were blocked for 2 h in 1 × Animal-Free Blocker (SP-5030 Vector Labs, USA). The blots were incubated over night at 4°C under gentle agitation in the primary antibody solutions (1:300 goat anti-UCP1, Santa Cruz Biotechnology, sc-6528 or 1:300 goat anti-UCP4, Santa Cruz Biotechnology, sc-17582). The blots were washed for 3 × 10 min in 1 × Animal-Free Blocker and incubated for 1 h at room temperature in HRP-conjugated rabbit anti-goat secondary antibody (1:1000, Dako, USA) for 1 h. This was followed by 3 × 10 min washes with 50 mM Tris buffer, pH 7.2. The protein bands were detected using 3,3′-diaminobenzidine tetrahydrochloride hydrate (DAB) (Sigma, D5637). The blots were incubated in a solution containing 1mg/ml DAB in 50 mM Tris, pH 7.2 for 5 min at room temperature, followed by the addition of an equal amount of 0.02% hydrogen peroxide solution. Development was arrested by placing the blots in 50 mM Tris (pH 7.2) for 10 min, followed by two more 10 min rinses in distilled water.
Stereological analysis
Using a design-based stereological approach we analysed immunohistochemically stained sections in the grey matter of the anterior cingulate and occipital cortex, as well as the underlying white matter from these regions of 14 cetartiodactyl species. Regions of interest (ROI) were drawn from similar locations across species as supported by published anatomical descriptions of the cetacean and artiodactyl brain. Using a light microscope equipped with a motorized stage, digital camera, MicroBrightfield system (MBF Bioscience, USA) system and StereoInvestigator software (MBF Bioscience, version 2018.1.1; 64-bit), we quantified UCP1-immunoreactive neuron densities in the grey matter, UCP4-immunoreactive glia densities in the grey and white matter, and DBH- and TH-immunoreactive bouton densities in the grey and white matter of these cortical regions. Separate pilot studies for each immunohistochemical stain was conducted to optimise sampling parameters, such as the counting frame and sampling grid sizes, and achieve a coefficient of error (CE) below 0.127,46,47,48,49. In addition, we measured the tissue section thickness at every sampling site, and the vertical guard zone was determined according to tissue thickness to avoid errors/biases due to sectioning artefacts27,46,47,48,49. Supplementary Tables S1–S4 provide details of the parameters used for each neuroanatomical region and stain and between the species in the current study. To estimate the ROI total number, we used the ‘Optical Fractionator’ probe.
UCP1- and UCP4-immunoreactive neuron and glia densities were obtained by sampling the cortical areas of interest and subjacent white matter with the aid of an optical disector. The cortex and white matter were outlined separately at low magnification (2X), and the optical disector was performed at 40X. UCP-immunoreactive neuron and glia density was calculated as the total number of UCP-immunoreactive neurons and glia divided by the product of surface area (x, y), the tissue sampling fraction, and the sectioned thickness (50 µm). The tissue sampling fraction was calculated as the ratio of the optical disector height to mean measured section thickness. Given that overall cell density per unit volume is known to vary with differences in brain size, we calculated the percentage of UCP-immunoreactive neurons or glia, expressed as the ratio of UCP-immunoreactive neurons or glia to total neuronal or glial density for each region of interest, to standardize the data for cross species comparison. Using Nissl-stained sections we obtained estimates of neuronal and glial densities within the cortex and glial density within the white matter using optical disector probes combined with a fractionator sampling scheme46. A pilot study determined the optimal sampling parameters and grid dimensions to place disector frames in a systematic-random manner. For DBH and TH bouton densities, ‘spot’ densities were calculated by multiplying the ROI area by the cut section thickness, and then using the generated volume as the denominator to the ROI estimated number. For all tissue sampled the optical fractionator was used while maintaining strict criteria, e.g. only complete boutons were counted, 63 X oil immersion, and obeying all commonly known stereological rules. The stereologic analyses presented here resulted in sampling an average of 118 counting frames per region of interest with a total of 13,053 counting frames investigated.
Statistical analyses
We hypothesized that the percentage of cortical neurons immunoreactive to UCP1 were significantly different between artiodactyls and cetaceans. To test this hypothesis, we compared the proportion of UCP1 expression in the anterior cingulate and occipital cortex of 16 cetartiodactyls. For the anterior cingulate cortex, we sampled a total of 1109 sampling sites (~ 100 sites per species) within the artiodactyl group and found that 36.83% of sampled cortical neurons were immunoreactive to UCP1. In comparison our cetacean sample consisted of 723 sampling sites (~ 145 sites per species), with 87.28% of the sampled cortical neurons immunoreactive to UCP1. For the occipital cortex, we sampled a total of 1 038 sites (~ 94 sites per species) within the artiodactyl group and found that 34% of sampled cortical neurons within the occipital cortex were immunoreactive to UCP1. The cetacean sample consisted of 723 sampling sites (~ 145 sites per species), and we found that 92.36% of the sampled cortical neurons were immunoreactive to UCP1.
To test if the respective underlying proportions were different between the sample groups, we conducted statistical hypothesis testing using the Two-Proportions Z-test as implemented in the R Programming language. Our Null hypothesis (Ho) stated that there is no significant difference between the proportions of artiodactyl immunoreactive UCP1 sampled cortical neurons (π1) and the proportions of cetacean UCP1 sampled cortical neurons (π2)—that is, π1 − π2 = 0. The alternate hypothesis (H1) stated that there is a significant difference in these proportions such that π1 − π2 ≠ 0, with one of the proportions being either less than or greater than the other. We thus conducted a two-sided hypothesis test, with the significance level (α) set at 0.05 (i.e., P-values less than, or equal to, α, would reject the null hypothesis in favour of the alternate hypothesis). Based on these analyses the proportion of immunolabelled UCP1 cortical neurons were found to be significantly different between the groups, with cetaceans having a significantly higher proportion of UCP1-immunoreactive neurons in the anterior cingulate cortex (χ2 = 51.69; df =1, P = 6.49 × 10−13, 95% confidence interval = − 0.122; − 0.067) and occipital cortex (χ2 = 56.30; P = 6.21 × 10−14, 95% confidence interval = − 0.114; − 0.060).
We used a two sample T-test (as implemented in R) to test for significant differences in noradrenergic bouton density between cetaceans and artiodactyls. Cetaceans were found to have significantly higher mean DBH-immunoreactive bouton densities in the anterior cingulate cortex as compared to artiodactyls (t = − 3.595; df =15, P = 0.011). Cetaceans were also found to have significantly higher mean DBH-immunoreactive bouton densities in the occipital cortex as compared to artiodactyls (t = − 4.546; df =15, P = 0.002). Similarly, we tested for significant differences in mean DBH bouton density in the underlying cortical white matter of cetaceans and artiodactyls. We did not find any significant differences in DBH-immunoreactive bouton density for the anterior cingulate (t =− 0.597; df =15, P = 0.585) or occipital cortex (t = − 0.08; df =15, P = 0.941).
To test for the effect of confounding variables on the significant differences observed in DBH bouton density in the cortex, we used an analysis of covariance controlling sequentially for the effect of cortical neuron density, cortical glia density and brain mass. Our analyses revealed that after adjusting for the density of cortical neurons cetaceans still had significantly higher DBH-immunoreactive bouton density in the anterior cingulate cortex (adjusted mean = 10.176) in comparison to artiodactyls (adjusted mean = 8.176) (F = 5.222; df =13, P = 0.041). Adjusting for the covariate cortical neuron density, resulted in a similar result for the occipital cortex (adjusted mean = 14.678) in comparison to artiodactyls (adjusted mean = 10.395) (F = 14.05; df =13, P = 0.00278). When controlling for the density of cortical glia, cetaceans also had significantly higher DBH-immunoreactive bouton densities in the anterior cingulate cortex (adjusted mean = 10.62) in comparison to artiodactyls (adjusted mean = 8.01) (F = 9.72; df =13, P = 0.00889). Similar results were found for the occipital cortex, with cetaceans having significantly higher DBH-immunoreactive bouton density (adjusted mean = 14.471) compared to artiodactyls (adjusted mean = 10.395) (F = 11.2; df =13, P = 0.00581). When controlling for brain mass, cetaceans were also found to have a significantly higher DBH-immunoreactive bouton densities in the anterior cingulate (adjusted mean = 11.36) in comparison to artiodactyls (adjusted mean = 7.75) (F = 11.06; df = 13, P = 0.00604) as well as in the occipital cortex (cetacean adjusted mean = 15.406, artiodactyls adjusted mean = 10.055) (F = 11.85; df = 13, P = 0.00488). More