Philippa Kaur

Russia invades UkraineThe global science community was quick to condemn Russian’s invasion of Ukraine in February. Research organizations moved fast to cut ties with Russia, stopping funding and collaborations, and journals came under pressure to boycott Russian authors.The situation escalated when Russian forces attacked Europe’s largest nuclear power plant, Zaporizhzhia, in March, prompting fears of a nuclear accident. Russian troops continue to occupy the power plant. Since the invasion began, thousands of civilians have been killed and millions displaced; many others, including scientists, have fled the country.The war has affected research in space and climate science, disrupted fieldwork and played a significant part in the global energy crisis. The invasion could also precipitate a new era for European defence research.JWST delights astronomers

Stephans Quintet, a grouping of five galaxies, taken by NASA’s James Webb Space Telescope.Credit: NASA, ESA, CSA, and STScI via Getty

NASA’s James Webb Space Telescope (JWST) — the most complex telescope ever built — reached its destination in space in January after decades of planning. In July, astronomers were awed by the telescope’s first image — of thousands of distant galaxies in the constellation Volans. Since then, the US$10-billion observatory has captured a steady stream of spectacular images, and astronomers have been working feverishly on early data. Insights include detailed observations of an exoplanet, and leading contenders for the most distant galaxy ever seen.NASA also decided not to rename the telescope, despite calls from some astronomers to do so because the telescope’s namesake, a former NASA administrator, held high-ranking government positions in the 1950s and 1960s, when the United States systematically fired gay and lesbian government employees. A NASA investigation “found no evidence that Webb was either a leader or proponent of firing government employees for their sexual orientation”, the agency said in a statement in November.AI predicts protein structuresResearchers announced in July that they had used the revolutionary artificial-intelligence (AI) network AlphaFold to predict the structures of more than 200 million proteins from roughly one million species, covering almost every known protein from all organisms whose genomes are held in databases. The development of AlphaFold netted its creators at the London-based AI company DeepMind, owned by Alphabet, one of this year’s US$3-million Breakthrough prizes — the most lucrative awards in science.AlphaFold isn’t the only player on the scene. Meta (formerly Facebook), in California, has developed its own AI network, called ESMFold, and used it to predict the shapes of roughly 600 million possible proteins from bacteria, viruses and other microorganisms that have not been isolated or cultured. Scientists are using these tools to dream up proteins that could form the basis of new drugs and vaccines.Monkeypox goes global

The monkeypox virus (shown here as a coloured transmission electron micrograph) is related to the smallpox virus.Credit: CDC/Science Photo Library

The rapid global spread of monkeypox (recently renamed ‘mpox’ by the World Health Organization) this year caught many scientists off guard. Previously, the virus had mainly been confined to Central and West Africa, but from May this year, infections started appearing in Europe, the United States, Canada and many other countries, mostly in young and middle-aged men who have sex with men. The virus is related to smallpox, and the circulating strain only rarely causes severe disease or death. But its fast spread led the World Health Organization to declare the global outbreak a ‘public-health emergency of international concern’, the agency’s highest alert level, in July.As cases soared, researchers got to work trying to understand the dynamics of the disease. Studies confirmed that it is transmitted primarily through repeated skin-to-skin contact, and trials of possible treatments got under way. Existing smallpox vaccines were also used to suppress the virus in some countries. Six months after mpox infections first started increasing, vaccination efforts and behavioural changes seemed to have curbed its spread in Europe and the United States. Researchers predict a range of scenarios from here — the most hopeful being that the virus fizzles out in non-endemic countries over the next few months or years.The Moon has a revivalThe Moon has become a popular destination for space missions this year. First off the launch pad, in August, was South Korea’s Danuri probe, which is expected to arrive at its destination in January and orbit the Moon for a year. The mission is the country’s first foray beyond Earth’s orbit and is carrying a host of experiments.Last month, NASA’s hotly anticipated Artemis programme — which aims to send astronauts to the Moon in the next few years — finally kicked off with the launch of an uncrewed capsule called Orion, a joint venture with the European Space Agency. As part of a test flight to see whether the system can transport people safely to the Moon, the capsule flew out past the Moon and made its way back to Earth safely this month.A lunar spacecraft made by a Japanese company launched this month. ispace’s M1 lander is aiming to be the first of several private ventures to land on the surface of the Moon next year. The lander will carry two rovers, one for the United Arab Emirates and another for the Japan Aerospace Exploration Agency, JAXA. The rovers will be a first for both countries.Climate-change funding

People cross a flooded highway in Sindh province, Pakistan in August.Credit: Waqar Hussein/EPA-EFE/Shutterstock

There were many reasons to feel despondent about the United Nations Climate Change Conference of the Parties (COP27) in Egypt last month, but an agreement on a new ‘loss and damage’ fund was one bright spot. The fund will help low- and middle-income countries to cover the cost of climate-change impacts, such as the catastrophic floods in Pakistan this year, which caused more than US$30 billion worth of damage and economic losses.But calls at COP27 to phase out fossil fuels were blocked by oil-producing states, and many blamed the lack of progress on the energy crisis sparked by Russia’s invasion of Ukraine. High natural-gas prices have led some European nations to rely temporarily on coal. Global carbon emissions from fossil fuels are expected to hit 37.5 billion tonnes this year, a new record. The window to limit warming to 1.5–2 ºC above pre-industrial temperatures is disappearing fast — and might even have passed.Omicron’s offspring drive the pandemicOmicron and its descendants dominated all other coronavirus variants this year. The fast-spreading strain was first detected in southern Africa in November 2021, and quickly spread around the globe. From early on, it was clear that Omicron could evade immune-system defences more successfully than previous variants, which has meant that vaccines are less effective. Throughout the year, a diverse group of immune-dodging offshoots of Omicron has emerged, making it challenging for scientists to predict coming waves of infection.Vaccines based on Omicron variants have been rolled out in some countries in the hope they will offer greater protection than previous jabs, but early data suggest the extra benefit is modest. Nasal sprays against COVID-19 have also become a tool in the vaccine arsenal. The idea is that these stop the virus at the site where it first takes hold. In September, China and India approved needle-free COVID-19 vaccines that are delivered through the nose or mouth, and many similar vaccines are in various stages of development.Pig organs transplanted into people

Surgeons in Baltimore, Maryland transplanted the first pig heart into a person in January.Credit: EyePress News/Shutterstock

In January, US handyman David Bennett became the first person to receive a transplanted heart from a genetically modified pig — a crucial first step in determining whether animals could provide a source of organs for people who need them. Bennett survived for another eight weeks after the transplant, but researchers were impressed that he lived for that long, given that the human immune system attacks non-genetically modified pig organs in minutes. A few months later, two US research groups independently reported transplanting pig kidneys into three people who had been declared legally dead because they did not have brain function. The organs weren’t rejected and started producing urine. Researchers say the next step is clinical trials to test such procedures thoroughly in living people.Elections and science

Luís Inácio Lula da Silva was elected president of Brazil in October.Credit: Fabio Vieira/FotoRua/NurPhoto via Getty

National elections in Brazil, Australia and France brought relief for many researchers. After three years of science-damaging policies under right-wing president Jair Bolsonaro, Brazil narrowly elected leftist labour leader and former president Luiz Inácio Lula da Silva to lead the country in October. Scientists are hopeful that Lula’s return will result in a desperately needed boost to research funding and greater protection for the Amazon rainforest.French researchers were buoyed by President Emmanuel Macron’s victory over far-right candidate Marine Le Pen in April, and the election of Anthony Albanese as prime minister in Australia in May was seen as a good thing for science and climate-change action, too. In China, Xi Jinping cemented his legacy with an historic third term as head of the Chinese Communist Party. Xi has placed science and innovation at the heart of his country’s growth strategy.In other nations, it was unclear how research would fare under new leaders, such as Giorgia Meloni, the far-right candidate elected as Italy’s first female prime minister in October. Science was not a priority for the United Kingdom’s three prime ministers this year, although they have retained previous commitments to raise research funding. After Boris Johnson reisgned, Liz Truss was in the position for just seven weeks before she too resigned and the current Prime Minister Rishi Sunak took over.Environmental push beginsThis week, conservation and political leaders are attempting to finalize a global deal to protect the environment. The UN’s Convention on Biological Diversity Conference of the Parties (COP15) is under way in Montreal, Canada. A new biodiversity treaty, known as the post-2020 Global Diversity Framework, has been delayed by more than two years because of the COVID-19 pandemic. Progress towards an agreement has been slow, and the deal looked under threat when negotiations stalled over financing during international talks in Nairobi in June. Financial pledges from some nations to support biodiversity helped discussions to move forward, but estimates suggest that US$700 billion more is needed annually to protect the natural world. At the meeting, delegates will hopefully agree on targets to stabilize species’ declines by 2030 and reverse them by mid-century. More

Site selection and sampling strategyField sites (Table 1) were selected to represent typical natural vegetation types showing little or no signs of disturbance. Although much of the natural vegetation of China has been altered by human activities, there are still extensive areas of natural vegetation. Access to these areas is facilitated by the existence of a number of ecological transects39,40, the ChinaFlux network (http://www.chinaflux.org) and the Chinese Ecosystem Research Network (http://www.cern.ac.cn/0index/index.asp).About half the sites in CPTDv1 used a stratified sampling approach and this approach was used at all of the new sites added in the CPTDv2. This sampling strategy involves sampling the dominant species within each vegetation stratum so as to be able to characterise trait values at community level18. Specifically, a total of 25 trees, 5 shrubs, 5 lianas or vines, and 5 understorey species (grasses, forbs) were sampled at each site. When there were less than 25 trees at a site, all of the tree species were sampled and additional examples from the other categories were included up to the maximum of 40 species. If there are more than the maximum sampling number in any one category, then the dominant (i.e. most common) representatives of each category were sampled. Sampled individuals of each species were mature, healthy plants. In principle, sun leaves (i.e. leaves in the canopy and fully exposed to sunlight) were sampled. For true shade-tolerant and understory species, the sampled individuals were those in well-lit environments and isolated to minimize interactions with other individuals.Nineteen sites from Xinjiang included in CPTDv1 used a simplified sampling strategy, where only canopy species were sampled. Sixteen sites from Xinjiang were particularly depauperate and thus only a limited number of species were sampled without consideration of abundance. These sites are retained in the database because they sample extremely arid location with α typically less than 0.25Species identification and taxonomic standardisationSampled plants were identified in the field by a taxonomist familiar with the local vegetation, most usually using a regional flora. Species names were subsequently standardised using the online version of the Flora of China (http://www.efloras.org/flora_page.aspx?flora_id=2). Where field-identified species were not accepted or included in the Flora of China, and thus could not be assigned unambiguously to an accepted taxonomic name, we cross-checked whether the species were listed in the Plant List (http://www.theplantlist.org/) (or alternative sources such as the Virtual Herbarium of China, Plants of the World Online or TROPICOS) in order to identify synonyms for these accepted names that were recognised by the Flora of China. In cases where we were unable to identify an accepted name consistent with the Flora of China, we retained the field-assigned name by default (Fig. 3). The decisions about taxonomy are described in the CPTDv2 table “Taxonomic Standardisation” (Table 2). The names assigned originally in the field and the accepted standardized names used in the database are given in the CPTDv2 table “Species Translations” (Table 3). When species were recognised in the Flora of China, we provide the Chinese translation of the species name. The written Chinese nomenclature system does not follow the Linnaean system, so this table of “Species Chinese Name” is designed to facilitate the use of the database by botanists in China (Table 4). There are no translations of names that are not recognized by the Flora of China and are used in the database by default.Fig. 3Flowchart showing the decision tree used to determine the names used in the China Plant Database (accepted names) and encapsulated in the Taxonomic Standardization table. ‘=1’ and ‘ >1’ indicate the number of Synonyms is equal or more than one.Full size imageDataset collection methodsPhotosynthetic pathwayInformation on photosynthetic pathway (Table 5) was obtained for each species from the literature. There are a large number of literature compilations on the photosynthetic pathway of Chinese plants (e.g.41,42,43,44,45,46. Where this information was not available from Chinese studies we used similar compilations from other regions of the world (e.g.47,48,49,50,51,52. Since C4 plants have much less carbon discrimination than C3 plants, the measurements on δ13C were also used as an indicator of the photosynthetic pathway53,54,55,56. δ13C value of –20‰ was applied as a threshold of C3 photosynthetic pathway distinction54. Information about photosynthetic pathway was not included for a species unless confirmed from the literature or δ13C measurements.Leaf physical and chemical traitsPhysical and chemical properties (Table 6) were measured on samples collected in the field following standard methods37. At least 10 g of leaves were collected for each species. Sunlit leaves of tree species were obtained with long-handled twig shears. The samples were subdivided for the measurement of specific leaf area, leaf dry matter content and the contents of carbon, nitrogen, phosphorus and potassium. Recorded values were the average of three replicates. Leaf area was determined by scanning five leaves (or more in the case of small leaves, to make up a total area ≥20 cm2 per species) with a laser scanner. Areas (Average LA) were measured using Photoshop on the scanned images. Leaf fresh weight was measured in the field. Dry weight was obtained after air drying for several days and then oven drying at 75 °C for 48 hours. Leaf dry matter content (LDMC) was expressed as leaf oven-dry weight divided by fresh weight. Specific leaf area (SLA) was then expressed as the ratio between leaf area and leaf dry mass. LMA is the inverse of SLA. Leaf carbon content (Cmass) was measured by the potassium dichromate volumetric method and leaf nitrogen content (Nmass) by the Micro-Kjeldahl method. Leaf phosphorus (Pmass) was analysed colorimetrically (Shimadzu UV-2550). Leaf potassium (Kmass) was measured by Flame Atomic Emission Spectrophotometry (PE 5100 PC). The area-based leaf chemical contents (Carea, Narea, Parea, Karea) were derived as a product of mass-based content and LMA. δ13C (d13C:12C) and δ15N (d15N:14N) were measured using the Isotope Ratio Mass Spectrometer (Thermo Fisher Scientific Inc., USA; Finnigan Corporation, San Jose, CA).Photosynthetic traitsSeveral different methods were used to characterise photosynthetic traits (Supplementary Table 1). Chlorophyll fluorescence measurements were made at the sites along Northeast China Transect. These measurements were recorded as the potential (Fv/Fm) and actual (QY) rates of photosynthetic electron transport. QY is correlated with photosynthetic rate, although it also includes the diversion of electrons to non-photosynthetic activities such as the elimination of reactive oxygen species57. Measurements of photosynthetic traits at most of the sites (about 68% of samples with photosynthetic measurements) were derived from leaf gas-exchange measurements in light-saturated conditions under either ambient or high CO2 levels, made with a portable infrared gas analyser (IRGA) system (LI-6400; Li-Cor Inc., Lincoln, NB, USA). Sunlit terminal branches from the upper canopy were collected and re-cut under water immediately prior to measurement. Measurements were made in the field with relative humidity and chamber block temperature close to that of the ambient air at the time of measurement, and a constant airflow rate (500 μmol s−1). The maximum capacity of carboxylation (Vcmax) and electron-transport (Jmax) were calculated from the light-saturated rate of net CO2 fixation at ambient and high CO2 level respectively using the one-point method for Vcmax58 and two-point method for Jmax59. Although it was indicated that applying one-point method could result in around 20% error in measuring photosynthetic capacity60, this time-saving method indeed allows much more samples to be measured in the field. For sites in CPTDv1, the Vcmax and Jmax values were made on a single specimen of each species at each site, due to the time-consuming nature of the measurement. For the newly collected sites in CPTDv2, for each species the Vcmax and Jmax were measured on three samples collected from three individual tress. The average values were recorded in the database. For Vcmax measurements, the CO2 level was set as the ambient atmospheric CO2 level, ranging from 380 ppm to 400 ppm. The leaves were exposed to a typical photosynthetic photon flux density (PPFD) of 1800 μmol m−2 s−1 with the light source. Pre-processing method was applied to determine the saturating PPFD for alpine plants, which goes up to 2000 μmol m−2 s−1 in the high elevation sites from Mountain Gonga. For Jmax measurements, the CO2 level was set as 1500 ppm or 2000 ppm to avoid any limitation on photosynthesis via carboxylation.There are a few cases (1 site from Cai, et al.61, and 8 sites from Zheng and Shangguan62, Zheng and Shangguan63), where field-measured ratio of leaf internal- to ambient-CO2 concentration (ci:ca) were not provided. In these cases, estimates of the ci:ca ratio were made from δ13C measurements using the method of64 to calculate isotopic discrimination (Δ) from δ13C (correcting for atmospheric δ13C, approximated as a function of time of collection and latitude), and the Ubierna and Farquhar65 method to calculate isotopic discrimination (Δ) from δ13C considering discrimination during stomatal diffusion and carboxylation. The R code for calculating Vcmax and Jcmax from original data was provided (seeing Code availability).Hydraulic traitsCPTDv2 contains information on four important hydraulic traits: specific sapwood conductivity, the sapwood to leaf area ratio (Huber value, vH), turgor loss point and wood density (Table 7). Hydraulic traits were measured on branches with a diameter wider than 7 mm, cut as close to the bifurcation point as possible to minimize any effect of measurement location on measured area. A section was taken from the part of the branch nearest to the bifurcation point, and the cross-sectional area of the xylem was measured at both ends of this section using digital calipers. Sapwood area was calculated as the average of these two measurements. All leaves attached to the branch were removed and dried at 70 °C for 72 hours before weighing. The total leaf area was obtained from dry mass and LMA. vH was calculated as the ratio of sapwood area and leaf area. The vH value recorded for each species at each site was the average of three measurements made on branches from different individuals.Five branches from at least three mature individuals of each species at each site were collected, wrapped in moist towels and sealed in black plastic bags, and then immediately transported to the laboratory. All the samples were re-cut under water, put into water and sealed in black plastic bags to rehydrate overnight. Sapwood-specific hydraulic conductivity, (KS) was measured using the method of Sperry, et al.66. Segments (10–15 cm length) were cut from the rehydrated branches and flushed using 20 mmol L−1 KCl solution for at least 30 minutes (to remove air from the vessels) until constant fluid dripped from the section. The segments were then placed under 0.005 MPa pressure to record the time (t) they took to transport a known water volume (W, m3). Length (L, m), sapwood area of both ends (S1 and S2, m2) and temperature (Tm, °C) were recorded. Sapwood-specific hydraulic conductivity at measurement temperature (KS,m, mol m−1 s−1 MPa−1) was calculated using Eq. (1). This was transformed to KS at mean maximum temperature during the growing season (KS,gt) and standard temperature (KS25) following Eqs. (2–3):$${K}_{S,m}={W,L{rho }_{w}/[0.005,t({S}_{1}+{S}_{2})/2]}(1000/,18)$$
(1)
$${K}_{S,t}={K}_{S,m}{eta }_{m}/{eta }_{t}$$
(2)
$$eta =1{0}^{-3}exp[A+B/,(C+T)]$$
(3)
where ηm and ηt (Pa s) are the water viscosity at measurement temperature and transformed temperature (i.e. mean maximum daytime temperature during the growing season and at a standard temperature of 25 °C), respectively, and ρw (kg m−3) is the density of water. The parameter values used in Eq. (3) were A = −3.719, B = 580 and C = −13867.A small part of each sapwood segment was used to measure wood density, the ratio of dry weight to volume of sapwood. After removal of bark and heartwood, the volume of sapwood was measured by displacement and the sapwood dry weight was obtained after drying at 70 °C for 72 hours to constant weight.The method described by Bartlett, et al.68 was used for the rapid determination of turgor loss point (Ψtlp). After rehydration overnight, discs were sampled using a 6-mm-diameter punch from mature, healthy leaves collected on each branch, avoiding major and minor veins. Leaf discs wrapped in foil were frozen in liquid nitrogen for at least 2 minutes and then punctured 20 times quickly with sharp-tipped tweezers. Five repeat experiments using leaves from multiple individuals were carried out for every species at each site. The osmotic potential (Ψosm) was measured with a VAPRO 5600 vapor pressure osmometer (Wescor, Logan, UT, USA) and Ψtlp (in MPa) was calculated as:$${Psi }_{tlp}=0.83{2Psi }_{osm}-0.631$$
(4)
Morphometric traitsThe morphometric trait data (Supplementary Table 2) were measured systematically by the same people (SPH and ICP) at all the sites. A standardized template for the field measurement of morphometric traits was used (Supplementary Table 5). This template provides a checklist of the traits and the categories used to describe them. The leaf traits assessed were texture, colour, size, thickness, orientation, display, shape, margin form, the presence of hairs, pubescence, pruinosity or rugosity, the presence of surface wax, hypostomatism, marginal curling (involute, revolute), smell (aromatic or fetid), the presence of a terminal notch or drip-tip, surface patterning, succulence, the presence and positioning of spines or thorns on the leaves. Illustrations of the various categories used in the classification of leaf margin and leaf shape are provided in supplementary materials, together with the template for leaf size categories (Supplementary Figs. 1–3). Although the distinction between spines and thorns is sometimes based on the source material (where thorns are derived from shoots and buds, and spines from any part of the leaf containing vascular material), here the differentiation is based on the shape of the protrusion (where thorns are triangular in shape and can be branched, and spines are unbranched and linear features). The checklist template also includes a limited amount of information on stem traits, such as form, colour, whether the stem is photosynthetic, the presence of stem hairs, pubescence, or pruinosity, and the presence of spines or thorns. For woody plants (trees, shrubs, climbers), the checklist also includes information on bark type (deciduous or not, with an indication of whether the bark is strip or chunk deciduous), the presence of furrowing, and also the presence of spines or thorns.Plant Functional TypesThe database includes information on life form, plant phenology, leaf form and leaf phenology (Table 8). Although these four pieces of information are used by many modellers in the definition of plant functional types (PFTs)69,70, they are not strictly species-specific traits. Thus, some species can occur as a tree, a small tree or a shrub (e.g. Cyclobalanopsis obovatifolia), or as a shrub or liana (e.g. Smilax discotis), depending on environmental conditions. Similarly, some species can behave as an evergreen or deciduous plant, depending on moisture availability (e.g. Ulmus parvifolia). Thus, this information is recorded for individual species at each site and no attempt was made to ensure that a given species was classified identically at all sites. In total 20 distinct life forms were recognized, including tree, small tree, low to high shrub, erect dwarf shrub, prostrate dwarf shrub, trailing shrub, liana, climber, forb, cushion forb, rosette forb, graminoid, bamboo, cycad, geophyte, stem succulent, succulent, pteridophyte, epiphyte, parasite. Plant phenology is recorded as perennial, biennial or annual. The primary distinction in leaf phenology is between deciduous and evergreen, but the classification used in the database also recognizes facultative deciduousness (semi-deciduous) and leaf-exchangers (i.e. plants that retain their leaves for nearly the whole year but drop and replace all of the leaves in a single short period, rather than replacing some leaves continuously through the year as evergreens do). The concept of leaf phenology is only relevant for woody plants (trees, shrubs, lianas) and so is not recorded for e.g. forbs or climbers.VegetationThe local vegetation was not recorded in the field at each site, and in any case such descriptions are hard to standardize. The CPTDv2 database contains information on vegetation type extracted from the digital vegetation map of China at the scale of 1:1 million71, which uses 55 plant communities (48 natural plant communities and seven cropping systems). CPTDv2 further provides information on vegetation clusters aggregated from those fundamental plant communities from the Vegetation Atlas of China based on their bioclimatic context72. CPTDv2 also contains information on potential natural vegetation (PNV), derived from an updated version of the73 global mapping of PNV. This PNV map was produced using pollen-based vegetation reconstructions as a target, a set of 160 spatially explicit co-variate data sets representing the climatic, topographic, geologic, and hydrological controls on plant growth and survival, and an ensemble machine-learning approach to account for the relationships between vegetation types and these covariates (Table 9). The original version of the map had a spatial resolution of 1 km; the updated version used here (https://github.com/Envirometrix/PNVmaps) has a resolution of 250 m.ClimateClimatological estimates of monthly temperature, precipitation and fraction of sunshine hours were derived from records from 1814 meteorological stations (740 stations have observations from 1971 to 2000, the rest from 1981 to 1990: China Meteorological Administration, unpublished data), interpolated to a 0.01 grid using a three-dimensional thin-plate spline (ANUSPLIN version 4.36;74. These monthly climatological data were used directly to calculate the mean temperature of the coldest month (MTCO), mean annual temperature (MAT), mean monthly precipitation (MMP) and mean annual precipitation (MAP). Bioclimatic variables at each site were calculated from the interpolated monthly temperature, precipitation and fraction of sunshine hours using the Simple Process-Led Algorithms for Simulating Habitats (SPLASH) model75. The bioclimatic variables include total annual photosynthetically active radiation during the growing season when mean daily temperatures are >0 °C (PAR0), the daily mean photosynthetically active radiation during the growing season (mPAR0), growing degree days above a baseline of 0 °C (GDD0), the daily mean temperature during the growing season (mGDD0), the ratio of actual to equilibrium evapotranspiration (α), and a moisture index (MI) defined as the ratio of mean annual precipitation to potential evapotranspiration. We also calculated the timing of peak rainfall and rainfall seasonality, using metrics described in Kelley, et al.76 (Supplementary Table 3).The topography in the Gongga region is complex, and the standard climate data set is inadequate to capture the elevation impacts of local climate at the sites there13. We therefore also provide alternative estimates of climatic variables for the Gongga elevation transects using 17 weather stations from the region with records from January 2017 to December 2019 (Supplementary Table 4). These 17 stations range in elevation from 422 m to 3951 m, in latitude from 28° to 31° N, and in longitude from 99.1° to 103.8° E. The climatological records for each station were downloaded from China Meteorological Data Service Centre, National Meteorological Information Centre (http://data.cma.cn/data/detail/dataCode/A.0012.0001.html). The monthly maximum and minimum temperature, precipitation, percentage of possible sunshine hours were extracted. The monthly mean temperature was calculated as the average of maximum and minimum temperature. The elevationally-sensitive ANUSPLIN interpolation scheme74 was used to provide estimates of meteorological variables at each site as described above. The bioclimatic variables were calculated following the same methodology as the 0.01 grid data described above.SoilSoil was not sampled in the field, but to facilitate analyses we provide soil information extracted from the Harmonized World Soil Database (HWSD) v1.277 (Table 10). The HWSD v1.2 is a high-resolution (0.05°) soil database with soil characteristics determined from real soil profiles. The soil properties were estimated in a harmonized way, where the actual soil profile data and the development of pedotransfer rules were undertaken in cooperation with ISRIC and ESBN drawing on the WISE soil profile database and some earlier works78,79. The HWSD v1.2 provides information for the uppermost soil layer (0–30 cm) and the deeper soil layer (30–100 cm). Although HWSD v1.2 contains information on a large number of soil properties, we only extracted information on soil texture (sand fraction, silt fraction and clay fraction), the content of organic carbon, soil pH in water, and cation exchange capacity. More

Trichoderma species collectionEighty strains were obtained from 100 soil samples collected from Zoige alpine wetland ecological regions in China. Details of the strains isolated from soil samples are given in Table 1. All strains were subsequently used for morphological identification, while fifty-seven were used for phylogenetic analysis.Table 1 Details of 80 Trichoderma isolates from the Zoige alpine wetland in this study.Full size tablePhylogenetic analysisThe ITS region used preliminarily as a species identification criterion was applied to TrichOKey at www.ISTH.info70. However, the ITS region has a low number of variable sites and long insertions in certain species; thus, it is unsuitable for a phylogenetic reconstruction of this group41. Our study successfully amplified most fragments of the genes tef1, rpb2, and acl1. We also designed a pair of new primers based on the full-length tef1 gene, 5′-GAGAAGTTCGAGAAGGTGAGC-3′ and 5′-ATGTCACGGACGGCGAAAC-3′, with which a 1.4-kb fragment was amplified for most isolates.All samples analyzed in our study were divided into 4 primary clades based on the gpd gene region, including 49 strains from the T. harzianum complex, 3 T. rossicum strains, 1 T. polysporum strain and one unknown species (4 Trichoderma sp. strains) (Fig. 1). Maximum parsimony analysis was conducted among 101 strains, with Protocrea farinosa (CPK 2472) and P. pallida (CBS 299.78) used as outgroup (Table 2). The dataset for the rpb2, tef1 and acl1 genes contained 3403 characteristics, among which 1152 were parsimony-informative, 988 were variable and parsimony-uninformative, and 1263 were constant. The most parsimonious trees are shown in Fig. 2 (tree length = 5054, consistency index = 0.6005, homoplasy index = 0.3995, retention index = 0.8105, rescaled consistency index = 0.4867).Figure 1Neighbor-joining tree based on partial gpd gene sequences from 57 Trichoderma isolates. Parsimony bootstrap values of more than 50% are shown at nodes.Full size imageTable 2 Trichoderma strain included in the multi-gene sequence analysis, with details of clade, strain number, location, and GenBank accessions of the sequences generated.Full size tableFigure 2Maximum parsimony tree of Trichoderma species inferred from the combined rpb2, tef1 and acl1 partial sequences. Maximum parsimony bootstrap values above 50% are shown at nodes. The tree was rooted with Protocrea farinose and P. pallida Isolates from this study are shown in red (new species in bold).Full size imageThe phylogram showed that 57 stains belonged to the following four clades: Harzianum, Polysporum, Stromaticum, and Longibrachiatum. The strains of the first three clades with neighboring named species were well supported by bootstrap values greater than 90%. The Harzianum clade contained T. alni, T. atrobrunneum, T. harzianum and T. pyramidale of the Trichoderma species complex. The Polysporum clade contained only T. polysporum, and the Stromaticum clade contained T. rossicum. The Longibrachiatum clade contained four strains of Trichoderma sp., T25, T43, T44 and T48, which were separated from any other known taxa of this clade showed a low bootstrap value (MPBP = 62%) with T. citrinoviride and T. saturnisporum. We thus regarded it as a new species and named it Trichoderma zoigense, as described in the next section.Growth ratesAs shown in Fig. 3, the genus Trichoderma from Zoige alpine wetland ecological regions was able to grow in a range from 15 to 35 °C, and the suitable growth temperature for most species ranged from 20 to 30 °C. All seven species identified had normal viability at relatively low temperature (15 °C), and they rarely grew well over 35 °C except for T. zoigense. For T. atrobrunneum, T. harzianum and T. pyramidale, the optimum growth temperature on CMD was 25 to 30 °C. T. alni and T. rossicum preferred a cool growth environment, with an optimum temperature of 25 °C, whereas T. zoigense was more partial to a hot environment, with an optimum temperature of 30 °C, and it even grew well up to 35 °C. T. polysporum was the only slow-growing species that grew with less than 6.0 mm/day between 15 and 30 °C and did not survive at 35 °C. The above results showed that all species had different growth rates but were not completely differentiated from each other on CMD. These species were roughly divided into four groups based on their optimum growth temperature.Figure 3Growth rates of 7 species of Trichoderma on CMD given as mm per day at five temperatures. The values were the means of 3–5 experiments, with 1–3 representative isolates per species.Full size imageRelationship with ecological factorsOur results revealed a substantial disparity in the number and distribution of Trichoderma species among Zoige alpine wetland ecological regions (Tables 3, 4). Table 3 showed that T. harzianum was found in all four soil types, but most isolates of this species were obtained from peat soil. T. rossicum, T. alni and T. zoigense were also present in meadow soil and subalpine meadow soil, whereas T. atrobrunneum was found in aeolian sandy soil and peat soil. T. polysporum was found only in peat soil.Table 3 Isolation frequency of Trichoderma species in different soil types (%).Full size tableTable 4 Isolation frequency of Trichoderma species in different soil layers (%) species.Full size tableIn regard to the different soil layers shown in Table 4, T. harzianum was widely distributed in the five soil layers at depths of 0–100 cm. T. rossicum, T. alni and T. zoigense were isolated mainly from the soil layers at depths of 0–50 cm. Both T. atrobrunneum and T. pyramidale were isolated from depths of 0–10 cm, and T. polysporum was found only in the soil layers at depths of 50–100 cm.Regarding isolation frequency, T. harzianum was the most common of the seven species with a 23% isolation frequency, and it was therefore the dominant species in the zone, while the rare species T. polysporum and T. pyramidale had the lowest isolation frequencies at 1%.TaxonomyNew speciesTrichoderma zoigense G.S. Gong & G.T. Tang, sp. nov. (Fig. 4).Figure 4Cultures and asexual morph of Trichoderma zoigense. (a–d). Cultures at 20 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 4 days; and (d) on SNA, 7 days]. (e) Conidiation tuft (CMD, 4 days). (f–k) Conidiophores and phialides (CMD, 5–7 days). (l) Chlamydospores (PDA, 8 days). (m) Conidia (CMD, 5 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageMycoBank: MB 82114.Typification: CHINA. SICHUAN PROVINCE: Zoige Alpine Wetland, on soil, 29 June 2013, G.S. Gong T44 (holotype CGMCC3.20145). GenBank: ITS = KX632531; TEF = KX632588; RPB2 = KX632645; ACL1 = KX632702; GPD = KX632759.Etymology: zoigense (Latin), the specific epithet about the place where the type was found.Description: Cultures and anamorph: optimal growth at 25 °C on all four media. On CMD after 72 h, growth is 25–28 mm at 20 °C and 28–31 mm at 25 °C. Colony is dense and has a wavy to crenate margin. Surface becomes distinctly zonate and white to grayish-green but celadon to atrovirens later, and it is granular in the center and distinctly radially downy outside and shows whitish surface hyphae and reverse-diffusing croci to pale brown pigment (Fig. 4a). Aerial hyphae are numerous to punctate and long, forming radial strands, with white mycelial patches appearing in aged cultures (Fig. 4e). Autolytic excretions are rare, with no coilings observed. Conidiation was noted after 3–4 d at 25 °C, a yellow or greenish color appears after 7 days, conidiation is effuse, and in intense tufts, erect conidiophores occur around the plug and on aerial hyphae. They are mainly concentrated along the colony center, show a white color that turns green, and then finally degenerate, with conidia often adhering in chains. Conidiophores are short and simple with asymmetric branches. Branches produce phialides directly. Phialides are generally solitary along main axes and side branches and sometimes paired in the terminal position of the main axes, sometimes in whorls of 2–3. Phialides are 4.5–10.5 × 2–5 μm ((overline{x }) = 7.5 ± 1.5 × 3 ± 0.5, n = 50) and 1.5–2.5 μm ((overline{x }) = 2 ± 0.2) wide at the base, lageniform or ampulliform, mostly uncinate or slightly curved, less straight, and often distinctly widened in the middle (Fig. 4f–k). Conidia are 3–4.5 × 2.3–4 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.3, n = 50) and initially hyaline, and they turn green and are oblong or ellipsoidal, almost with constricted sides, and smooth, eguttulate or with minute guttules, with indistinct scars (Fig. 4m).On PDA, after 72 h, growth is 35–41 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5 days at 25 °C. Colonies are dense with wavy to crenate margins; and mycelia are conspicuously differentiated in width of the primary and secondary hyphae. Surface becomes distinctly zonate, yellowish-green to prasinous in color and celadon to atrovirens later, and it is farinose to granular in the center, distinctly radially downy outside, with whitish of surface hyphae and reverse-diffusing brilliant yellow to fruit-green pigment (Fig. 4c). Aerial hyphae are numerous, long and ascend several millimeters, forming radial strands, with white mycelial patches appearing in aged cultures. Autolytic excretions are rare; and no coilings are observed. Odor is indistinct or fragrant. Chlamydospores examined after 7 days at 4.5–9 × 4.5–7.5 μm ((overline{x }) = 6 ± 1.1 × 6 ± 0.7, n = 50), and they are terminal, intercalary, globose or ellipsoidal, and smooth (Fig. 4l). Conidiation is noted after 3–4 days and yellow or greenish after 7 days. Conidiophores are short and simple with asymmetric branches; conidia are greenish, ellipsoidal, and smooth.On SNA, after 72 h, growth is 13–15 mm at 20 °C and, 16–21 mm at 25 °C; and mycelium covers the plate after 12–13 days at 25 °C. Colony is similar to that on CMD, with a little wave margin, although mycelia are looser and slower on the agar surface. Aerial hyphae are relatively inconspicuous and long along the colony margin. Autolytic activity and coiling are absent or inconspicuous. No diffusing pigment or distinct odor are produced (Fig. 4d). Conidiation was noted after 3–4 days at 25 °C, and many amorphous, loose white or aqua cottony tufts occur, mostly median from the plug outwards, and they are confluent to masses up and white but then turn green. After 4–5 days, conidiation becomes dense within the tufts, which are loose at their white margins with long, straight, or slightly sinuous sterile ends in the periphery. Tufts consisting of a loose reticulum with branches often at right angles, give rise to several main axes. Main axes are regular and tree-like, with few or many paired or unpaired side branches. Branches are flexuous, and phialides are solitary along the main axes and side branches, and they are sometimes paired in the terminal position of the main axes, sometimes in whorls of 2–3 that are often cruciform or in pseudo-whorls up to 4. Phialides and conidia are similar to that on CMD.New records for ChinaTrichoderma atrobrunneum F. B. Rocha et al., Mycologia 107: 571, 2015 (Fig. 5).Figure 5Cultures and asexual morph of Trichoderma atrobrunneum. (a–d) Cultures at 25 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 15 days; and (d) on SNA, 7 days]. (e) Conidiation tuft (SNA, 7 days). (f–i,k,l) Conidiophores and phialides (CMD, 5–7 days). (j) Conidia (CMD, 6 days). (m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageSpecimen examined: CHINA. SICHUAN PROVINCE: Zoige Alpine Wetland, on soil, 29 June 2013, G.S. Gong T42 (holotype CGMCC.20167). GenBank: ITS = KX632514; TEF = KX632571; RPB2 = KX632628; ACL1 = KX632685; GPD = KX632742.Description: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, after 72 h, growth is 35–37 mm at 20 °C and 46–53 mm at 25 °C; mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow, sinuous and often form strands on the margin (Fig. 5a). Aerial hyphae are slight, forming a thin white to green downy fluffy or floccose mat. The light brown or brown pigment is observed, with no distinct odor noted. Conidiophores are pyramidal, often with opposing and somewhat widely spaced branches, with the main axis and each branch terminating in a cruciate, sometimes verticillate, whorl of up to four phialides. Phialides are ampulliform to lageniform and 4.9–7.6 × 2.2–3.0 μm ((overline{x }) = 6 ± 0.7 × 2.5 ± 0.2, n = 50) and 1.5–2.5 μm ((overline{x }) = 1.5 ± 0.3) wide at the base (Fig. 5f–i,k,l). Conidia are 2.5–4 × 2.5–3.5 μm ((overline{x }) = 3 ± 0.3 × 3 ± 0.2, n = 50), yellow to green, smooth, and circular to ellipsoidal (Fig. 5j).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 5c). Margin is thick and defined. Aerial hyphae are abundant and form a thick green downy mat. Conidiation forms abundantly within 4 days in broad concentric rings. Chlamydospores examined after 7 days are 5–9 × 5.5–8.5 μm ((overline{x }) = 6.5 ± 0.9 × 6.5 ± 0.9, n = 30), globose when terminal, smooth, and intercalary (Fig. 5m).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and yellow to green; hyphae are wide and sinuous, with indistinct strands on the margin (Fig. 5d). Margin is thin and ill-defined. Aerial hyphae are slight, forming a thin green downy fluff appearing in the colony (Fig. 5e). Diffusing pigment was observed in a ring, and no distinct odor was noted. Conidiation is similar to CMD.Accepted species previously reported in ChinaTrichoderma alni Jaklitsch, Mycologia 100: 799. 2008 (Fig. 6).Figure 6Cultures and asexual morph of Trichoderma alni. (a–d). Cultures after 7 days at 25 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. € Coilings of aerial hyphae (PDA, 6 days). (f–j,l). Conidiophores and phialides (CMD, 5–7 days). (k) Conidiation tuft (PDA, 7 days). (m) Conidia (CMD, 6 days). (n,o) Chlamydospores (PDA, 7 days). Scale bars: (e–j,l–o) = 10 μm; (k) = 2 mm.Full size imageDescription: Cultures and anamorph: Optimum growth at 25 °C on all media; no growth at 35 °C. On CMD, after 72 h, growth of 34–36 mm at 20 °C and 50–51 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow and sinuous and often form strands on the margin (Fig. 6a). Aerial hyphae are slight and form a thin white to green downy, fluffy or floccose mat. No diffusing pigment or distinct odor is noted. Conidiophores are hyaline and thick, with side branches on several levels at the base of the elongations that are mostly paired and in right angles with phialides in whorls of 3–5. Phialides are 5.5–11.5 × 2–3.5 μm ((overline{x }) = 8 ± 1.4 × 2.5 ± 0.4, n = 50) and 1.5–2.5 μm ((overline{x }) = 2 ± 0.4) wide at the base, often short and wide, and ampulliform (Fig. 6f–j,l). Conidia are 3–4 × 2.5–3.5 μm ((overline{x }) = 3.5 ± 0.2 × 3 ± 0.2, n = 50), dark green, smooth, and ellipsoidal (Fig. 6m).On PDA, after 72 h, growth is 33–35 mm at 20 °C and 41–43 mm at 25 °C; and mycelium covers the plate after 6–7 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 6c). Margin is thin and ill defined. Aerial hyphae are slight, coiled (Fig. 6e), forming a thin white to green downy, fluffy or floccose mat (Fig. 6k). Chlamydospores examined after 7 days are 6–9.5 × 5–8 μm ((overline{x }) = 7.5 ± 0.9 × 7 ± 0.9, n = 30), globose to oval when terminal, and smooth, and few are intercalary (Fig. 6n,o).On SNA, after 72 h, growth is 18–19 mm at 20 °C and 28–32 mm at 25 °C; and mycelium covers the plate after 6–7 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and yellow to green; hyphae are wide and sinuous and show indistinct strands on the margin (Fig. 6d). Margin is thin and ill-defined. Aerial hyphae are slight and form a thin white downy, fluffy, or floccose mat appearing in distal parts of the colony. No diffusing pigment or distinct odor was noted. Conidiation is similar to CMD.Trichoderma harzianum Rifai, Mycol. Pap. 116: 38, 1969 (Fig. 7).Figure 7Cultures and asexual morph of Trichoderma harzianum. (a–d) Cultures after 7 days at 20 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. (e) Conidiation tuft (CMD, 7 days). (f–j) Conidiophores and phialides (CMD, 5–7 days). (k) Conidia (CMD, 5 days). (l,m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, after 72 h, growth is 34–38 mm at 20 °C and 46–53 mm at 25 °C; mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow, sinuous, and often form strands on the margin (Fig. 7a). Aerial hyphae are abundant and radiating and form thick green downy, fluffy, or floccose mats (Fig. 7e). No diffusing pigment, but fragrant odor noted. Conidiophores are pyramidal with opposing branches, with each branch terminating in a cruciate whorl of up to four or five phialides. Phialides are frequently solitary or in a whorl of three or four. Phialides are ampulliform to lageniform and often constricted below the tip to form a narrow neck of 4.5–8 × 2–3.5 μm ((overline{x }) = 6 ± 0.8 × 2.5 ± 0.3, n = 50) and 1–2.5 μm ((overline{x }) = 2 ± 0.3) wide at the base (Fig. 7f–j). Conidia are subglobose to ovoid, 3–4.5 × 2.5–3.3 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.2, n = 50), laurel-green to bright green, smooth, and ellipsoidal (Fig. 7k).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide and sinuous and often form strands on the margin (Fig. 7c). Margin is thick and ill defined. Aerial hyphae are abundant and radiating and form thick green downy, fluffy or floccose mats. Chlamydospores examined after 7 days are 5.5–9 × 5.5–9.0 μm ((overline{mathrm{x} }) = 7 ± 0.8 × 7 ± 0.8, n = 30), globose to oval when terminal and smooth, showing an almost unobserved intercalary (Fig. 7l,m).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and green; hyphae are narrow and sinuous and show indistinct strands on the margin (Fig. 7d). Margin is thin and ill defined. Aerial hyphae are slight and form a thick downy, fluffy, or floccose mat appearing in the colony. No diffusing pigment or distinct fragrant odor was noted. Conidiation was similar to CMD.Trichoderma polysporum Rifai, Mycol. Pap. 116: 18, 1969 (Fig. 8).Figure 8Cultures and asexual morph of Trichoderma polysporum. (a–d) Cultures at 20 °C [(a) on CMD, 7 days; (b) on MEA, 15 days; (c) on PDA, 15 days; and (d) on SNA, 15 days]. (i) Conidiation tuft (PDA, 15 days). (e–h,j) Conidiophores and phialides (CMD, 5–7 days). (k) Chlamydospores (CMD, 7 days). (l) Conidia (PDA, 6 days). Scale bars: (i) = 2 mm; (e–h,j) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 20 °C on all media, no growth at 35 °C. On CMD, after 72 h, growth is 14–16 mm at 20 °C and 9–12 mm at 25 °C; and mycelium covers the plate after 9–10 days at 20 °C. A colony is hyaline, thin and loose, with little mycelium on the agar surface, and it is indistinctly zonate but becomes zonate by conidiation in white tufts after 4–5 d and grass green to green after 6 days (Fig. 8a). Aerial hyphae are long and dense and forming little greenish aggregates that are granular to pulvinate. No pigment or odor. Conidiation noted after 4–5 days, and it is white to greenish, with sterile smooth to rough helical elongations in the distal zones from pustules. Conidiophores are hyaline and thick with side branches on several levels at the base of the elongations that are mostly paired and at right angles with phialides in whorls of 2–5. Phialides are 5–10.5 × 2.5–4 μm ((overline{x }) = 7 ± 1.9 × 3.5 ± 0.4, n = 50) and 2–4 μm ((overline{x }) = 3 ± 0.5) wide at the base, often short and wide and ampulliform (Fig. 8e–h,j). Conidia are 2.5–4 × 2–3 μm ((overline{x }) = 3.5 ± 0.4 × 2.5 ± 0.2, n = 50), hyaline, smooth, and ellipsoidal (Fig. 10l).On PDA, after 72 h, growth is 24–26 mm at 20 °C and 13–16 mm at 25 °C; and mycelium covers the plate after 8–9 days at 20 °C. A colony is densest, distinctly zonate, and grass green to spearmint green; mycelia are conspicuously dense; and surface hyphae form radial strands (Fig. 8c). Aerial hyphae are long and dense and form greenish aggregates that are granular to pulvinate (Fig. 8i). No diffusing pigment and odor. Chlamydospores examined after 7 days are 5.5–9 × 5–7.5 μm ((overline{x }) = 7 ± 0.9 × 6 ± 0.6, n = 30), globose to oval when terminal, and smooth, with an almost unobserved intercalary (Fig. 8k).On SNA, growth is approximately 7 mm/day at 20 °C and 5 mm/day at 25 °C; and mycelium covers the plate after 10 days at 20 °C. A colony is hyaline, thin, and loose, with little mycelium on the agar surface, not or indistinctly zonate, but becomes zonate by conidiation in white tufts after 4–5 days; and the margin is downy by long aerial hyphae, which degenerating/dissolving soon (Fig. 8d).Trichoderma pyramidale W. Jaklitsch & P. Chaverri, Mycologia 107: 581, 2015 (Fig. 9).Figure 9Cultures and asexual morph of Trichoderma pyramidale. (a–d) Cultures at 25 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 4 days; and (d) on SNA, 4 days]. (e) Conidiation tuft (PDA, 7 days). (f–j) Conidiophores and phialides (CMD, 5–7 days). (k) Conidia (CMD, 6 days). (l) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–l) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media, with little growth at 35 °C. On CMD, after 72 h, growth is 29–32 mm at 20 °C and 48–53 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelium is loose and thin; hyphae are narrow, sinuous, and often form strands on the margin (Fig. 9a). Aerial hyphae are slight, forming a thin white to green downy, fluffy or floccose mat. Brown pigment is shown, but no distinct odor noted. Conidiophores are hyaline and thick with side branches on several levels at the base of the elongations that are mostly paired and at right angles with phialides in whorls of 3–5. Phialides are 5–9.5 × 2.5–3 μm ((overline{x }) = 7 ± 1.1 × 3 ± 0.3, n = 50) and 1–2.5 μm ((overline{x }) = 1.5 ± 0.3) wide at the base and often short, wide, and ampulliform (Fig. 9f–j). Conidia are 2.5–4 × 2.5–3.5 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.2, n = 50), green, smooth, and ellipsoidal (Fig. 9k).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 9c). Margin is thin and ill defined. Aerial hyphae are slight and form a thin white to green downy, fluffy or floccose mat (Fig. 9e). Chlamydospores examined after 7 days are 5.5–10 × 5.5–10 μm ((overline{x }) = 7 ± 0.9 × 7 ± 0.9, n = 30), globose to oval when terminal or intercalary, and smooth (Fig. 9l).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelium is thin, yellow to green; hyphae are wide, sinuous, with indistinct strands on the margin (Fig. 9d). Margin is thin and ill defined. Aerial hyphae are slight and form a thin white downy, fluffy or floccose mat in distal parts of the colony. No diffusing pigment or distinct odor noted. Conidiation similar to CMD.Trichoderma rossicum Bissett et al., Canad. J. Bot. 81: 578, 2003 (Fig. 10).Figure 10Cultures and asexual morph of Trichoderma rossicum. (a–d) Cultures after 7 days at 25 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. € Conidiation tuft (PDA, 7 days). (f–h,j,k) Conidiophores and phialides (CMD, 5–7 days). (i) Elongations (CMD, 6 days). (l,n) Conidia (CMD, 6 days). (m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–n) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, growth of 10–11 mm/day at 20 °C and 15–17 mm/day at 25 °C; and mycelium covers the plate after 6–7 days at 20 °C. Colony is dense with a wavy margin, and the surface becomes distinctly zonate (Fig. 10a). Aerial hyphae are numerous, long, elongate, and villiform in the plate (Fig. 10i). No diffusing pigment or odor. Autolytic activity is variable, and coilings are scarce or inconspicuous. Conidiation noted after 3–4 days at 20 °C. Conidiation is effuse and in intense tufts that are hemispherical or irregular, and they show wide wheel grain banding that is gray green to deep green. Conidiophores radiate from the reticulum and are broad, straight, sinuous or helically twisted, show distally slightly pointed elongations, taper from the main axes to top branches, and present primary branches arranged in pairs or in whorls of 2–3, with secondary branches to solitary. Phialides are 4.5–14 × 2.5–4 μm ((overline{x }) = 7 ± 1.5 × 3.5 ± 0.3, n = 50) and 2–3.5 μm ((overline{x }) = 3 ± 0.4) wide at the base, ampulliform, and in whorls of 3–6 (Fig. 10f–h,j,k). Conidia are 3.5–5.5 × 2.5–4 μm ((overline{x }) = 4.5 ± 0.5 × 3 ± 0.2, n = 50), short cylindrical, and a gray color when single and pea green to yellow green in a group (Fig. 10l,n).On PDA, growth is 12–15 mm/day at 20 °C, 12–16 mm/day at 25 °C; and mycelium covers the plate after 4–5 days at 25 °C. Colony is denser with a wavy margin than that on CMD, and the surface is distinctly zonate (Fig. 10c). Aerial hyphae are numerous, long, and villiform to pulvinate in the plate. No diffusing pigment and odor (Fig. 10e). Autolytic activity is variable, coilings are scarce or inconspicuous. Chlamydospores examined after 7 days are 6.5–9.5 × 6–9 μm ((overline{x }) = 7 ± 1.0 × 7 ± 0.9, n = 30), terminal and intercalary, globose or ellipsoidal, and smooth (Fig. 10m).On SNA, growth is 8–13 mm/day at 20 °C and 8–12 mm/day at 25 °C; and mycelium covers the plate after 6–7 day at 25 °C. Colony is hyaline, thin and dense; and mycelium degenerate rapidly (Fig. 10d). Aerial hyphae are inconspicuous, autolytic activity is scant, and coilings are distinct. Conidiation noted after approximately 4 days and starts in white fluffy tufts spreading from the center to form concentric zones, and they compact to pustules with a white to greenish color. More

Human-modified forests, such as selectively logged forests, are often characterized as degraded ecosystems because of their altered structure and low biomass. The concept of ecosystem degradation can be a double-edged sword. It rightly draws attention to the conservation value of old-growth systems and the importance of ecosystem restoration. However, it can also suggest that human-modified ecosystems are of low ecological value and therefore, in some cases, suitable for conversion to agriculture (such as oil palm plantations) and other land uses3,4,5.Selectively logged and other forms of structurally altered forests are becoming the prevailing vegetation cover in much of the tropical forest biome2. Such disturbance frequently leads to a decline in old-growth specialist species1, and also in non-specialist species in some contexts6,7,8. However, species-focused biodiversity metrics are only one measure of ecosystem vitality and functionality, and rarely consider the collective role that suites of species play in maintaining ecological functions9.An alternative approach is to focus on the energetics of key taxonomic groups, and the number and relative dominance of species contributing to each energetic pathway. Energetic approaches to examining ecosystem structure and function have a long history in ecosystem ecology10. Virtually all ecosystems are powered by a cascade of captured sunlight through an array of autotroph tissues and into hierarchical assemblages of herbivores, carnivores and detritivores. Energetic approaches shine light on the relative significance of energy flows among key taxa and provide insight into the processes that shape biodiversity and ecosystem function. The common currency of energy enables diverse guilds and taxa to be compared in a unified and physically meaningful manner: dominant energetic pathways can be identified, and the resilience of each pathway to the loss of individual species can be assessed. Quantitative links can then be made between animal communities and the plant-based ecosystem productivity on which they depend. The magnitude of energetic pathways in particular animal groups can often be indicators of key associated ecosystem processes, such as nutrient cycling, seed dispersal and pollination, or trophic factors such as intensity of predation pressure or availability of resource supply, all unified under the common metric of energy flux11,12.Energetics approaches have rarely been applied in biodiverse tropical ecosystems because of the range of observations they require11,12,13. Such analyses rely on: population density estimates for a very large number of species; understanding of the diet and feeding behaviour of the species; and reliable estimation of net primary productivity (NPP). Here we take advantage of uniquely rich datasets to apply an energetics lens to examine and quantify aspects of the ecological function and vitality of habitats in Sabah, Malaysia, that comprise old-growth forests, logged forest and oil palm plantation (Fig. 1 and Extended Data Fig. 1). Our approach is to calculate the short-term equilibrium production or consumption rates of food energy by specific species, guilds or taxonomic groups. We focus on three taxonomic groups (plants, birds and mammals) that are frequently used indicators of biodiversity and are relatively well understood ecologically.Fig. 1: Maps of the study sites in Sabah, Borneo.a–d, Maps showing locations of NPP plots and biodiversity surveys in old-growth forest, logged forest and oil palm plantations in the Stability of Altered Forest Ecosystems Project landscape (a), Maliau Basin (b), Danum Valley (c) and Sepilok (d). The inset in a shows the location of the four sites in Sabah. The shade of green indicates old-growth (dark green), twice-logged (intermediate green) or heavily logged (light green) forests. The camera and trap grid includes cameras and small mammal traps. White areas indicate oil palm plantations.Full size imageWe are interested in the fraction of primary productivity consumed by birds and mammals, and how it varies along the disturbance gradient, and how and why various food energetic pathways in mammals and birds, and the diversity of species contributing to those pathways, vary along the disturbance gradient. To estimate the density of 104 mammal and 144 bird species in each of the three habitat types, we aggregated data from 882 camera sampling locations (a total of 42,877 camera trap nights), 508 bird point count locations, 1,488 small terrestrial mammal trap locations (34,058 live-trap nights) and 336 bat trap locations (Fig. 1 and Extended Data Fig. 1). We then calculated daily energetic expenditure for each species based on their body mass, assigned each species to a dietary group and calculated total food consumption in energy units. For primary productivity, we relied on 34 plot-years (summation of plots multiplied by the number of years each plot is monitored) of measurements of the key components of NPP (canopy litterfall, woody growth, fine root production) using the protocols of the Global Ecosystem Monitoring Network14,15,16 across old-growth (n = 4), logged (n = 5) and oil palm (n = 1) plots. This dataset encompasses more than 14,000 measurements of litterfall, 20,000 tree diameter measurements and 2,700 fine root samples.Overall bird species diversity is maintained across the disturbance gradient and peaks in the logged forest; for mammals, there is also a slight increase in the logged forest, followed by rapid decline in the oil palm (Fig. 2b,c). Strikingly, both bird and mammal biomass increases substantially (144% and 231%, respectively) in the logged forest compared to the old-growth forest, with mammals contributing about 75% of total (bird plus mammal) biomass in both habitat types (Fig. 2b,c).Fig. 2: Variation of ecosystem energetics along the disturbance gradient from old-growth forest through logged forest to oil palm.a, Total NPP along the gradient (mean of intensive 1-ha plots; n = 4 for old growth (OG), n = 5 for logged and n = 1 for oil palm (OP); error bars are 95% confidence intervals derived from propagated uncertainty in the individually measured NPP components), with individual plot data points overlaid. b,c, Total body mass (bars, left axis) and number of species counted (blue dots and line, right axis) of birds (b) and mammals (c). d,e, Total direct energetic food intake by birds (d) and mammals (e). f,g, Percentage of NPP directly consumed by birds (f) and mammals (g). In b–e, body mass and energetics were estimated for individual bird and mammal species, with the bars showing the sum. Error bars denote 95% confidence intervals derived from 10,000 Monte Carlo simulation estimates incorporating uncertainty in body mass, population density, the daily energy expenditure equation, assimilation efficiency of the different food types, composition of the diet of each species and NPP. In f,g, the grey bars indicate direct consumption of NPP, white bars denote the percentage of NPP indirectly supporting bird and mammal food intake when the mean trophic level of consumed invertebrates is assumed to be 2.5, with the error bars denoting assumed mean trophic levels of 2.4 and 2.6. Note the log scale of the y axis in f,g. Numbers for d,e provided in Supplementary Data Tables 1, 2.Full size imageThe total flow of energy through consumption is amplified across all energetic pathways by a factor of 2.5 (2.2–3.0; all ranges reported are 95% confidence intervals) in logged forest relative to old-growth forest. In all three habitat types, total energy intake by birds is much greater than by mammals (Fig. 2d,e and Extended Data Table 1). Birds account for 67%, 68% and 90% of the total direct consumption by birds and mammals combined in old-growth forests, logged forests and oil palm, respectively. Although mammal biomass is higher than bird biomass in the old-growth and logged forests, the metabolism per unit mass is much higher in birds because of their small body size; hence, in terms of the energetics and consumption rates, the bird community dominates. The total energy intake by birds alone increases by a factor of 2.6 (2.1–3.2) in the logged forest relative to old-growth forest. This is mainly driven by a 2.5-fold (1.7–2.8) increase in foliage-gleaning insectivory (the dominant energetic pathway), and most other feeding guilds also show an even larger increase (Figs. 2d and 3). However, total bird energy intake in the oil palm drops back to levels similar to those in the old-growth forest, with a collapse in multiple guilds. For mammals, there is a similar 2.4-fold (1.9–3.2) increase in total consumption when going from old-growth to logged forest, but this declines sharply in oil palm plantation. Most notable is the 5.7-fold (3.2–10.2) increase in the importance of terrestrial mammal herbivores in the logged relative to old-growth forests. All four individual old-growth forest sites show consistently lower bird and mammal energetics than the logged forests (Extended Data Fig. 5).Fig. 3: Magnitude and species diversity of energetic pathways in old-growth forest, logged forest and oil palm.The size of the circles indicates the magnitude of energy flow, and the colour indicates birds or mammals. S, number of species; E, ESWI, an index of species redundancy and, therefore, resilience (high values indicate high redundancy; see main text). For clarity, guilds with small energetic flows are not shown, but are listed in Supplementary Data 4. Images created by J. Bentley.Full size imageThe fraction of NPP flowing through the bird and mammal communities increases by a factor of 2.1 (1.5–3.0) in logged forest relative to old-growth forest. There is very little increase in NPP in logged relative to old-growth forests (Fig. 2a) because increased NPP in patches of relatively intact logged forest is offset by very low productivity in more structurally degraded areas such as former logging platforms14,15. In oil palm plantations, oil palm fruits account for a large proportion of NPP, although a large fraction of these is harvested and removed from the ecosystem17. As a proportion of NPP, 1.62% (1.35–2.13%) is directly consumed by birds and mammals in the old-growth forest; this rises to 3.36% (2.57–5.07%) in the logged forest but drops to 0.89% (0.57–1.44%) in oil palm (Fig. 2f,g and Extended Data Table 2).If all invertebrates consumed are herbivores or detritivores (that is, at a trophic level of 2.0), and trophic efficiency is 10% (ref. 10), the total amount of NPP supporting the combined bird and mammal food intake would be 9%, 16% and 5% for old-growth forest, logged forest and oil palm, respectively. However, if the mean trophic level of consumed invertebrates is 2.5 (that is, a mix of herbivores and predators), the corresponding proportions would be 27%, 51% and 17% (Fig. 2f,g). As insectivory is the dominant feeding mode for the avian community, these numbers are dominated by bird diets. For birds in the old-growth forests, 0.35% of NPP supports direct herbivory and frugivory, but around 22% of NPP (assumed invertebrate trophic level 2.5) is indirectly required to support insectivory. The equivalent numbers for birds in logged forest are 0.83% and 46%. Hence, birds account for a much larger indirect consumption of NPP. Bird diet studies in old-growth and logged forest in the region suggest that consumed invertebrates have a mean trophic level of 2.5 (ref. 18; K. Sam, personal communication), indicating that the higher-end estimates of indirect NPP consumption (that is, around 50% in logged forests) are plausible.It is interesting to compare such high fractions of NPP to direct estimates of invertebrate herbivory. Scans of tree leaf litter from these forests suggest that just 7.0% of tree canopy leaf area (1–3% of total NPP) is removed by tree leaf herbivory14,16, but such estimates do not include other pathways available to invertebrates, including herbivory of the understorey, aboveground and belowground sap-sucking, leaf-mining, fruit- and wood-feeding, and canopy, litter and ground-layer detritivory. An increase in invertebrate biomass and herbivory in logged forest compared to old-growth forest has previously been reported in fogging studies in this landscape19. Such high levels of consumption of NPP by invertebrates could have implications on ecosystem vegetation biomass production, suggesting, first, that invertebrate herbivory has a substantial influence on recovery from logging and, second, that insectivorous bird densities may exert substantial indirect controls on ecosystem recovery.The distributions of energy flows among feeding guilds are remarkably stable among habitat types (Fig. 3), indicating that the amplified energy flows in the logged forests do not distort the overall trophic structure of vertebrate communities. Overall bird diet energetics are dominated by insectivory, which accounts for a strikingly invariant 66%, 63% and 66% of bird energetic consumption in old-growth forest, logged forest and oil palm, respectively. Foliage-gleaning dominates as a mode of invertebrate consumption in all three habitat types, with frugivory being the second most energetically important feeding mode (26%, 27% and 19%, respectively). Mammal diet is more evenly distributed across feeding guilds, but frugivory (31%, 30%, 30%) and folivory (24%, 38%, 26%) dominate. Small mammal insectivores are probably under-sampled (see Methods) so the contribution of mammal insectivory may be slightly greater than that estimated here. The apparent constancy of relative magnitude of feeding pathways across the intact and disturbed ecosystems is noteworthy and not sensitive to plausible shifts in feeding behaviour between habitat types (see Supplementary Discussion). There is no evidence of a substantial shift in dominant feeding guild: the principal feeding pathways present in the old-growth forest are maintained in the logged forest.When examining change at species level in the logged forests, the largest absolute increases in bird food consumption were in arboreal insectivores and omnivores (Fig. 4a and Extended Data Fig. 2a). In particular, this change was characterized by large increases in the abundance of bulbul species (Pycnonotus spp.). No bird species showed a significant or substantial reduction in overall energy consumption. In the oil palm plantation, total food consumption by birds was less than in logged forests, but similar to that in old-growth forests. However, this was driven by very high abundance of a handful of species, notably a single arboreal omnivore (yellow-vented bulbul Pycnonotus goiavier) and three arboreal insectivores (Mixornis bornensis, Rhipidura javanica, Copsychus saularis), whereas energy flows through most other bird species were greatly reduced (Fig. 4b and Extended Data Fig. 2b).Fig. 4: Changes in energy consumption by species in logged forest and oil palm relative to old-growth forest.a,b, Changes in energy consumption by species in logged forest relative to old-growth forest (a) and in oil palm relative to old-growth forest (b). The 20 species experiencing the largest increase (red) and decrease (blue) in both habitat types are shown. Bird species are shown in a lighter tone and mammal species are shown in a darker tone. The error bars denote 95% confidence intervals, derived from 10,000 Monte Carlo simulation estimates incorporating uncertainty in body mass, population density, the daily energy expenditure equation, assimilation efficiency of the different food types and composition of the diet of each species.Full size imageFor mammals, the increase in consumption in logged forests is dominated by consumption by large terrestrial herbivores increasing by a factor of 5.7 (3.2–10.2), particularly sambar deer (Rusa unicolor) and Asian elephant (Elephas maximus; Fig. 4a and Extended Data Figs. 2b and 3), along with that by small omnivores, predominantly rodents (native spiny rats, non-native black rat; Fig. 4). A few rainforest species show a strong decline (for example, greater mouse-deer Tragulus napu and brown spiny rat Maxomys rajah). In the oil palm, most mammal species collapse (Fig. 4b) and the limited consumption is dominated by a few disturbance-tolerant habitat generalists (for example, red muntjac Muntiacus muntjak, black rat Rattus rattus, civets), albeit these species are at lower densities than observed in old-growth forest (Extended Data Fig. 2).With very few exceptions, the amplified energy flows in logged forest seem to retain the same level of resilience as in old-growth forest. The diversity and dominance of species within any pathway can be a measure of the resilience of that pathway to loss of species. We assessed energetic dominance within individual pathways by defining an energetic Shannon–Wiener index (ESWI) to examine distribution of energy flow across species; low ESWI indicates a pathway with high dependence on a few species and hence potential vulnerability (Fig. 3). The overall ESWI across guilds does not differ between the old-growth and logged forest (t2,34 = −0.363, P = 0.930), but does decline substantially from old-growth forest to oil palm (t2,34 = −3.826, P = 0.0015), and from logged forest to oil palm (t2,34 = −3.639, P = 0.0025; linear mixed-effects models, with habitat type as fixed effect and guild as random effect; for model coefficients see Supplementary Table 3).Hence, for birds, the diversity of species contributing to dominant energetic pathways is maintained in the transition from old-growth to logged forests but declines substantially in oil palm. Mammals generally show lower diversity and ESWI than birds, but six out of ten feeding guilds maintain or increase ESWI in logged forest relative to the old-growth forests but collapse in oil palm (Fig. 3). Terrestrial herbivory is the largest mammal pathway in the logged forest but is dependent on only four species and is probably the most vulnerable of the larger pathways: a few large mammals (especially sambar deer) play a dominant terrestrial herbivory role in the logged forest. In parallel, bearded pigs (Sus barbatus), the only wild suid in Borneo, form an important and functionally unique component of the terrestrial omnivory pathway. These larger animals are particularly sensitive to anthropogenic pressures such as hunting, or associated pathogenic pressures as evidenced by the recent precipitous decline of the bearded pig in Sabah due to an outbreak of Asian swine fever (after our data were collected)20.Vertebrate populations across the tropics are particularly sensitive to hunting pressure21. Our study site has little hunting, but as a sensitivity analysis we explored the energetic consequences of 50% reduction in population density of those species potentially affected by targeted and/or indiscriminate hunting (Extended Data Fig. 4). Targeted hunted species include commercially valuable birds, and gun-hunted mammals (bearded pig, ungulates, banteng and mammals with medicinal value). Indiscriminately hunted species include birds and mammals likely to be trapped with nets and snares. Hunting in the logged forests lowers both bird and mammal energy flows but still leaves them at levels higher than in faunally intact old-growth forests. Such hunting brings bird energetics levels close to (but still above) those of old-growth forests. For mammals, however, even intensively hunted logged forests seem to maintain higher energetic flows than the old-growth forests. Hence, only very heavy hunting is likely to ‘offset’ the amplified energetics in the logged forest.The amplified energetic pathways in our logged forest probably arise as a result of bottom-up trophic factors including increased resource supply, palatability and accessibility. The more open forest structure in logged forest results in more vegetation being near ground level22,23 and hence more accessible to large generalist mammal herbivores, which show the most striking increase of the mammal guilds. The increased prioritization by plants of competition for light and therefore rapid vegetation growth strategies in logged forests results in higher leaf nutrient content and reduced leaf chemical defences against herbivory24,25, along with higher fruiting and flowering rates19 and greater clumping in resource supply9. This increased resource availability and palatability probably supports high invertebrate and vertebrate herbivore densities25. The act of disturbance displaces the ecosystem from a conservative chemically defended state to a more dynamic state with amplified energy and nutrient flow, but not to an extent that causes heavy disruption in animal community composition. Top-down trophic factors might also play a role in amplifying the energy flows in intermediate trophic levels, through mechanisms such as increased protection of ground-dwelling or nesting mammals and birds from aerial predators in the dense vegetation ground layer. This might partially explain the increased abundance of rodents, but there is little evidence of trophic release at this site because of the persisting high density of mammal carnivores26. Overall, the larger number of bottom-up mechanisms and surge in invertebrate consumption suggest that increased resource supply and palatability largely explains the amplification of consumption pathways in the logged forest. An alternative possibility is that the amplified vertebrate energetics do not indicate amplified overall animal energetics but rather a large diversion of energy from unmeasured invertebrate predation pathways (for example, parasitoids); this seems unlikely but warrants further exploration.Oil palm plantations show a large decline in the proportion of NPP consumed by mammals and birds compared to logged forests12. Mammal populations collapse because they are more vulnerable and avoid humans, and there is no suite of mammal generalists that can step in27,28. Birds show a more modest decline, to levels similar to those observed in old-growth forests, as there is a broad suite of generalist species that are able to adapt to and exploit the habitat types across the disturbance gradient, and because their small size and mobility render them less sensitive to human activity29. There is a consistent decline in the oil palm in ESWI for birds and especially for mammals, indicating a substantial increase in ecosystem vulnerability in many pathways.In conclusion, our analysis demonstrates the tremendously dynamic and ecologically vibrant nature of the studied logged forests, even heavily and repeatedly logged forests such as those found across Borneo. It is likely that the patterns, mechanisms and basic ecological energetics we describe are general to most tropical forests; amplification of multiple ecosystem processes after logging has also been reported for logged forests in Kenya9, but similar detailed analyses are needed for a range of tropical forests to elucidate the importance of biogeographic, climatic or other factors. We stress that our findings do not diminish the importance of protecting structurally intact old-growth forests, but rather question the meaning of degradation by shining a new light on the ecological value of logged and other structurally ‘degraded’ forests, reinforcing their significance to the conservation agenda30. We have shown that a wide diversity of species not only persist but thrive in the logged forest environment. Moreover, such ecological vibrancy probably enhances the prospects for ecosystem structural recovery. In terms of faunal intactness, our study landscape is close to a best-case scenario because hunting pressures were low. If logged forests can be protected from heavy defaunation, our analysis demonstrates that they can be vibrant ecosystems, providing many key ecosystem functions at levels much higher than in old-growth forests. Conservation of logged forest landscapes has an essential role to play in the in the protection of global biodiversity and biosphere function. More

The phototrophic species Rhodovastum atsumiense G2-11 acquired MGCs from an unknown alphaproteobacterial MTB by recent HGTIn a systematic database search for novel MGCs, we identified several orthologs of known magnetosome genes in the recently released draft genome sequence of the culturable anoxygenic phototroph Rhodovastum atsumiense G2-11 [25]. This finding was unexpected as, after isolation of G2-11 from a paddy field more than 20 years ago, no magnetosome formation has been reported [26]. Furthermore, no MTB has been identified so far among phototrophs or within the Acetobacteraceae family to which G2-11 belongs [26] (Fig. 1a).Fig. 1: Phylogeny, chromosome, and MGCs organization of G2-11.a The maximum likelihood phylogenetic tree based on ribosomal proteins demonstrates the position of G2-11 (highlighted in red) within family Acetobacteraceae (highlighted in the yellow box). The Azospirillaceae family was used as an outgroup based on the latest Alphaproteobacteria phylogeny. Branch length represents the number of base substitutions per site. Values at nodes indicate branch support calculated from 500 replicates using non-parametric bootstrap analysis. Bootstrap values 20 genes with no homology to known magnetosome genes (Fig. 1c). In contrast, the compact MGCs in G2-11 include only a few genes that could not be associated with magnetosome biosynthesis.Tetranucleotide usage patterns are frequently employed as a complementary tool to group organisms since they bear a reliable phylogenetic signal [32]. Likewise, deviations of tetranucleotide usage in a certain fragment from the flanking genome regions can indicate HGT [21]. Comparison of the z-normalized tetranucleotide frequencies of the MGCs (27.5 kb) with the flanking upstream (117.7 kb) and downstream (79.5 kb) fragments showed a considerably lower correlation between them (Pearson’s r = 0.88 with both flanking fragments) than between the flanking fragments themselves (Pearson’s r = 0.97, Fig. 1e). This indicates a significant difference in the tetranucleotide composition of the MGCs compared to the flanking genomic regions and supports a foreign origin of the magnetosome genes in G2-11 suggested by the phylogenetic analysis. Besides, the presence of a mobile element (transposase) and position of the MGCs directly downstream of a tRNA gene, a common hotspot for integration of genomic islands [33,34,35], suggests that the MGCs of G2-11 are indeed located on a genomic island, i.e., represent MAI, like in many other MTB [20, 21]. Unfortunately, the lack of other representatives of the genus Rhodovastum makes it impossible to infer whether the MAI was transferred directly to G2-11 or the last common ancestor of the genus. Nonetheless, its compact organization and conspicuous tetranucleotide usage suggest a relatively recent HGT event.G2-11 does not form magnetosomes under laboratory conditionsAlthough magnetosome genes discovered in G2-11 comply with the minimal set required for magnetosome biomineralization in MSR-1 [36], no magnetosomes have been detected in this organism. It might have several explanations: (i) the strain might switch to the magnetotactic lifestyle only under very specific, yet not tested, conditions; (ii) it once was able to synthesize magnetosomes in its natural environment but lost this ability upon subcultivation due to mutations before its characterization; (iii) the strain might naturally not exploit magnetotaxis as its genes might be non-functional or not actively expressed. To clarify which of these explanations is most likely, we first tested whether G2-11 can form magnetosomes under different laboratory conditions. To this end, the strain was cultivated photoheterotrophically, anoxic or microoxic, in a complex medium with potassium lactate and soybean peptone, as commonly used for MSR-1 (FSM) [37], as well as in minimal media with different C-sources previously shown to support growth in G2-11 (glucose, pyruvate, L-glutamine, and ethanol) [26]. All media were supplied with 50 μM ferric citrate to provide sufficient iron for magnetite biomineralization. Since magnetosome biosynthesis is possible only under low oxygen tension, aerobic chemoheterotrophic growth of G2-11 was not tested. The best growth was observed in the complex FSM medium and a minimal medium with glucose or pyruvate, whereas L-glutamine and ethanol supported only weak growth (Supplementary Fig. S3). Irrespective of the growth stage, none of the tested cultures demonstrated magnetic response as measured by a magnetically induced differential light scattering assay (Cmag) [38]. Consistently, micrographs of cells collected from stationary phase cultures did not show any magnetosome-like particles (Supplementary Fig. S3). This confirmed that G2-11 indeed cannot biosynthesize magnetosomes, at least under the conditions available for the laboratory tests. During cultivation, we also noticed that G2-11 cells did not move at any growth stage despite the initial description of this organism as motile using a single polar flagellum [26], and containing several flagellum synthesis operons and other motility-related genes. Moreover, the cells tended to adhere to glass surfaces under all tested conditions and formed a dense clumpy biofilm immersed in a thick extracellular matrix (Supplementary Fig. S3a-ii).Considering that G2-11 generally lacks magnetosomes and appears to have a stationary lifestyle, which is not consistent with magnetotaxis, we assessed whether the maintenance of MGCs comes at fitness costs for the organism. To this end, we deleted the entire region containing the magnetosome genes (in the following, referred to as the MAI region) using the genetic tools we established for G2-11 in this work (Supplementary Fig. S4a, see Materials and Methods for details). After PCR screening, replica plating test, and genome re-sequencing, two of G2-11 ΔMAI mutants were selected for further analysis (Supplementary Fig. S5). These mutants showed no significant differences in the growth behavior compared to the wildtype (WT) when incubated in minimal media supplied with acetate or pyruvate as a sole carbon source (Supplementary Fig. S4b). This finding suggests that the presence of the magnetosome genes neither provides benefits nor poses any substantial metabolic burden for G2-11, at least under the given experimental conditions.RNAseq reveals poor expression levels and antisense transcription in the MGCs of G2-11We set on to determine whether the magnetosome genes are transcribed in G2-11. To this end, we analyzed its whole transcriptome for the photoheterotrophic conditions, under which the best growth was observed, in two biological replicates. The expression levels of all the encoded genes calculated as TPM (transcripts per million) demonstrated a high correlation between the two replicates (Pearson’s r = 0.98). Most genes of the (mms6-like1)(mmsF-like1)mamH1IEKLMOH2 cluster were only poorly or not transcribed at all (Fig. 2a, Supplementary dataset). Transcription of mms6-like1, mamF-like1, mamL, mamH1, mamI, and mamK, for example, did not pass the noise background threshold (TPM ≤ 2) in both replicates and were unlikely to be expressed, whereas mamE, mamM, mamH2, feoAm, and feoBm slightly exceeded the threshold in at least one replicate and might be weakly transcribed (Fig. 2a). Although the TPM of mamO (TPM = 5.67–6.10, Supplementary dataset) exceeded the background threshold, the coverage plot reveals that the number of mapped reads sharply rises at its 3’-end, whereas the 5’-end has low read coverage (Fig. 2b). This indicates the presence of an internal transcription start site (TSS) and its associated promoter within the coding sequence of mamO instead of the full transcription of the gene. Localization of an active promoter within mamO was recently described in MSR-1, suggesting that the transcriptional organization of MGCs may be more broadly conserved across MTB than assumed previously [39].Fig. 2: Transcription of the magnetosome genes in G2-11.a Log10 of the transcript abundances for all genes in the G2-11 genome presented as TPM (transcripts per million). Red dots represent the magnetosome genes. Red rectangle shows genes with TPM below the threshold, and blue rectangle shows genes with expression levels above median. R1 and R2: biological replicates. Pearson’s r and the p value is presented on the graph. b RNAseq coverage of reads mapped on the positive (red) and negative (blue) strands of the genome in the MAI region. The gray balk shows the gene map: genes encoded on the negative strand are colored in black, on the positive – in green. Red arrows indicate the anti-sense transcription in the mamPAQRBST operon. Green arrows indicate the intragenic TSS within mamO. TSS are indicated with dashed lines and black arrowheads that show the direction of transcription.Full size imageTranscription of genes within the mag123, (mms6-like2)(mmsF-like2), and mamAPQRBST clusters significantly exceeded the threshold, with the expression levels of mag1, mamT, and mamS being above the overall median. At the same time, antisense transcription was detected in the mamAPQRBST region, with the coverage considerably exceeding the sense transcription (Fig. 2b). This antisense RNA (asRNA) likely originated from a promoter controlling the tRNA gene positioned on the negative strand downstream of mamT. Such long asRNAs have the potential to interfere with sense transcripts, thereby significantly decreasing the expression of genes encoded on the opposite strand [40].In summary, the RNAseq data revealed extremely low or lack of transcription of several genes that are known to be essential for magnetosome biosynthesis (mamL, mamI, mamM, mamE, and mamO) [27, 41]. Additionally, the detected antisense transcription can potentially attenuate expression of the mamAPQRBST cluster that also comprises essential genes, i.e., mamQ and mamB. Although other factors, like the absence of several accessory genes mentioned above and the potential accumulation of point mutations, might also be involved, the lack or insufficient transcription of the essential magnetosome genes appears to be the primary reason for the absence of magnetosome biosynthesis in G2-11.Magnetosome proteins from G2-11 are functional in a model magnetotactic bacteriumAlthough visual inspection of the G2-11 magnetosome genes did not reveal any frameshifts or other apparent mutations, accumulation of non-obvious functionally deleterious point substitutions in the essential genes could not be excluded. Therefore, we next tested whether at least some of the magnetosome genes from G2-11 still encode functional proteins that can complement isogenic mutants of the model magnetotactic bacterium MSR-1. In addition, we analyzed the intracellular localization of their products in both MSR-1 and G2-11 by fluorescent labeling.One of the key proteins for magnetosome biosynthesis in MSR-1 is MamB, as its deletion mutant is severely impaired in magnetosome vesicle formation and is entirely devoid of magnetite crystals [42, 43]. Here, we observed that expression of MamB[G2-11] partially restored magnetosome chain formation in MSR-1 ΔmamB (Fig. 3a, b-i, b-ii). Consistently, MamB[G2-11] tagged with mNeonGreen (MamB[G2-11]-mNG) was predominantly localized to magnetosome chains in MSR-1, suggesting that the magnetosome vesicle formation was likely restored to the WT levels (Fig. 3b-iii).Fig. 3: Genetic complementation and intracellular localization of magnetosome proteins from G2-11 in MSR-1 isogenic mutants.a TEM micrograph of MSR-1 wildtype (WT). b MSR-1 ΔmamB::mamB[G2-11]. b-i TEM micrograph and b-ii magnetosome chain close-up; b-iii) 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamB::mamB[G2-11]-mNG. c MSR-1ΔmamQ::mamQ[G2-11]. c-i TEM micrograph and c-ii close-up of the particles; c-iii 3D-SIM Z-stack maximum intensity projection. d MSR-1 ΔmamK::mamK[G2-11]. d-i TEM micrograph of MSR-1 ΔmamK; d-ii TEM micrograph of MSR-1 ΔmamK::mamK[G2-11]; d-iii 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamK::mNG-mamK[G2-11]. e MSR-1 ΔmamKY::mamK[G2-11]. e-i-ii Representative cells of MSR-1 ΔmamKY mutant showing examples of a short chain, cluster (e-i), and ring-shaped chain (e-ii); (e-iii) TEM micrograph of MSR ΔmamKY::mamK[G2-11] mutant showing the complemented phenotype; e-iv distribution of cells with different phenotypes in the populations of MSR-1 ΔmamKY and MSR-1 ΔmamKY::mamK[G2-11] mutants (N  > 50 cells for each strain population); e-v 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamKY::mNG-mamK[G2-11]. f MSR-1 ΔmamJ::mamJ-like[G2-11]. f-i TEM micrograph of MSR-1 ΔmamJ; f-ii TEM micrograph of MSR-1 ΔmamJ::mamJ-like[G2-11]; f-iii 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamJ::mamJ-like[G2-11]-gfp. g MSR-1 ΔF3::mmsF-like1[G2-11] and ΔF3::mmsF-like2[G2-11]. g-i TEM micrograph of MSR-1 ΔF3; g-ii TEM micrograph of MSR-1 ΔF3::mmsF-like1[G2-11]; g-iii TEM micrograph of MSR-1 ΔF3::mmsF-like2[G2-11]; g-iv magnetosome diameter distribution in MSR-1 ΔF3 and the mutants complemented with mmsF-like1/mmsF-like2. Asterisks indicate points of significance calculated using Kruskal–Wallis test (****p 50 cells for each of two randomly selected insertion mutants MSR-1 ΔmamKY::mamK[G2-11] revealed that the long magnetosome chains were restored in 35-40% of the population (Fig. 3e-iv). Of note, mNG-MamK[G2-11] formed slightly shorter filaments in MSR-1 ΔmamKY than in ΔmamK, which were also characteristically displaced to the outer cell curvature due to the lack of mamY [46] (Fig. 3e-v).MamJ attaches magnetosomes to the MamK filament in MSR-1, mediating their chain-like arrangement. Elimination of mamJ disrupts this linkage, causing magnetosomes to aggregate owing to magnetic interactions [47] (Fig. 3f-i). In MSR-1, MamJ is encoded within the mamAB operon, between mamE and mamK. Within the (mms6-like1)(mmsF-like1)mamH1IEKLMOH2 cluster of G2-11, there is an open reading frame (ORF) encoding a hypothetical protein that is located in a syntenic locus (Fig. 1c). Although the hypothetical protein from G2-11 and MamJ from MSR-1 differ considerably in length (563 vs. 426 aa), share only a low overall sequence similarity (31%), and are not identified as orthologues by reciprocal blast analyses, multiple sequence alignments revealed a few conserved amino acids at their N- and C-termini (Supplementary Fig. S6). Moreover, in both proteins, these conserved residues are separated by a large region rich in acidic residues (pI 3.3 and 3.2) suggesting that the G2-11 protein might be a distant MamJ homolog. To test if it implements the same function as MamJ, we transferred this gene to MSR-1 ΔmamJ. Interestingly, it indeed restored chain-like magnetosome arrangement, which, however, often appeared as closed rings rather than linear chains (Fig. 3f-ii). Despite this difference, it indicated the ability of the hypothetical protein (hereafter referred to as MamJ-like[G2-11]) to attach magnetosomes to MamK, suggesting that in the native context, it can have a function identical to MamJ. Consistently, its fluorescently labeled version was often observed in ring-like structures within the cytoplasm of MSR-1 ΔmamJ, suggesting that it is indeed localized to magnetosomes (Fig. 3f-iii).In magnetospirilla, magnetosome proteins MmsF, MamF, and MmxF share an extensive similarity. Their individual and collective elimination gradually reduces the magnetite crystal size and disrupts the chain formation in MSR-1 (Fig. 3g-i; Paulus, manuscript in preparation). The MAI of G2-11 includes two genes, whose products have high similarity to these proteins, designated here as MmsF-like1[G2-11] and MmsF-like2[G2-11]. Expression of each of them in the MSR-1 ΔmmsFΔmamFΔmmxF triple mutant (ΔF3) partially restored the magnetosome size and led to the formation of short magnetosome chains in MSR ΔF3::mmsF-like1[G2-11] (Fig. 3g-ii) or clusters in MSR-1 ΔF3::mmsF-like2[G2-11] (Fig. 3g-iii, iv). Consistently, fluorescently tagged mNG-MmsF-like1[G2-11] and mNG-MmsF-like2[G2-11] localized to magnetosomes in the pattern resembling that in the TEM micrographs of the complemented corresponding mutants (Fig. 3g-v, vii), or were perfectly targeted to the magnetosome chains in MSR-1 WT (Fig. 3g-vi, viii).In G2-11, MamB[G2-11]-mNG, mNG-MamQ[G2-11], MamJ-like[G2-11]-GFP, mNG-MmsF-like1[G2-11], and mNG-MmsF-like2[G2-11] were patchy-like or evenly distributed in the inner and intracellular membranes (Supplementary Fig. S7). No linear structures that would indicate the formation of aligned magnetosome vesicles were observed in these mutants. As expected, mNG-MamK[G2-11] formed filaments in G2-11 (Supplementary Fig. S7c).Expression of MamM, MamO, MamE, and MamL failed to complement the corresponding deletion mutants of MSR-1 (not shown). Although detrimental mutations in the genes cannot be excluded, this result can be attributed to the lack of their native, cognate interaction partners, likely due to the large phylogenetic distances between the respective orthologues.Transfer of MGCs from MSR-1 endows G2-11 with magnetosome biosynthesis that is rapidly lost upon subcultivationHaving demonstrated the functionality of several G2-11 magnetosome genes in the MSR-1 background, we wondered whether, conversely, the G2-11 background is permissive for magnetosome biosynthesis. To this end, we transferred the well-studied MGCs from MSR-1 into G2-11, thereby mimicking an HGT event under laboratory conditions. The magnetosome genes from MSR-1 were previously cloned on a single vector pTpsMAG1 to enable the one-step transfer and random insertion into the genomes of foreign organisms [23]. Three G2-11 mutants with different positions of the integrated magnetosome cassette were incubated under anoxic phototrophic conditions with iron concentrations (50 μM) sufficient for biomineralization in the donor organism MSR-1. The obtained transgenic strains indeed demonstrated a detectable magnetic response (Cmag = 0.38 ± 0.11) [38], and TEM confirmed the presence of numerous electron-dense particles within the cells (Fig. 4), which, however, were significantly smaller than magnetosome crystals of MSR-1 (ranging 18.5 ± 4.3 nm to 19.9 ± 5.0 nm in three G2-11 MAG insertion mutants vs 35.4 ± 11.5 nm in MSR-1 WT, Fig. 4b) and formed only short chains or were scattered throughout the cells (Fig. 4a, c-i). Mapping of the particle elemental compositions with energy-dispersive X-ray spectroscopy (EDS) in STEM mode revealed iron- and oxygen-dominated compositions, suggesting they were iron oxides. High-resolution TEM (HRTEM) images and their FFT (Fast Fourier Transform) patterns were consistent with the structure of magnetite (Fig. 4c). Thus, G2-11 was capable of genuine magnetosome formation after acquisition of the MGCs from MSR-1.Fig. 4: Magnetosome biosynthesis by G2-11 upon transfer of the MGCs from MSR-1.a A cell with magnetosomes (i) and a close-up of the area with magnetosome chains (ii). Scale bars: 1 µm. b Violin plots displaying magnetosome diameter in three MAG insertion mutants of G2-11 in comparison to MSR-1. Asterisks indicate points of significance calculated using the Kruskal–Wallis test (**** designates p  More

Gruninger, R. J., Ribeiro, G. O., Cameron, A. & McAllister, T. A. Invited review: Application of meta-omics to understand the dynamic nature of the rumen microbiome and how it responds to diet in ruminants. Animal 13, 1843–1854 (2019).CAS 

Google Scholar 
Morgavi, D. P., Kelly, W. J., Janssen, P. H. & Attwood, G. T. Rumen microbial (meta)genomics and its application to ruminant production. Animal 7, 184–201 (2013).CAS 

Google Scholar 
Bergman, E. N. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol. Rev. 70, 567–590 (1990).CAS 

Google Scholar 
Flint, H. J. The rumen microbial ecosystem—Some recent developments. Trends Microbiol. 5, 483–488 (1997).CAS 

Google Scholar 
Hobson, P. N. & Stewart, C. S. The Rumen Microbial Ecosystem. (Springer, 2012).Moraïs, S. & Mizrahi, I. The road not taken: The rumen microbiome, functional groups, and community states. Trends Microbiol. 27, 538–549 (2019).
Google Scholar 
Cheng, K. J., Forsberg, C. W., Minato, H. & Costerton, J. W. in Physiological Aspects of Digestion and Metabolism in Ruminants (eds T. Tsuda, Y. Sasaki, & R. Kawashima) 595–624 (Academic Press, 1991).McSweeney, C. S., Palmer, B., McNeill, D. M. & Krause, D. O. Microbial interactions with tannins: Nutritional consequences for ruminants. Anim. Feed Sci. Technol. 91, 83–93 (2001).CAS 

Google Scholar 
Skene, I. K. & Brooker, J. D. Characterization of tannin acylhydrolase activity in the ruminal bacterium Selenomonas ruminantium. Anaerobe 1, 321–327 (1995).CAS 

Google Scholar 
Khanbabaee, K. & van Ree, T. Tannins: Classification and definition. Nat. Prod. Rep. 18, 641–649 (2001).CAS 

Google Scholar 
Makkar, H. P. S. & Becker, K. Isolation of tannins from leaves of some trees and shrubs and their properties. J. Agric. Food Chem. 42, 731–734 (1994).CAS 

Google Scholar 
Bhat, T. K., Kannan, A., Singh, B. & Sharma, O. P. Value addition of feed and fodder by alleviating the antinutritional effects of tannins. Agr. Res. 2, 189–206 (2013).CAS 

Google Scholar 
Shimada, T. Salivary proteins as a defense against dietary tannins. J. Chem. Ecol. 32, 1149–1163 (2006).CAS 

Google Scholar 
Zhu, J., Filippich, L. J. & Alsalami, M. T. Tannic acid intoxication in sheep and mice. Res. Vet. Sci. 53, 280–292 (1992).CAS 

Google Scholar 
Kohl, K. D., Stengel, A. & Dearing, M. D. Inoculation of tannin-degrading bacteria into novel hosts increases performance on tannin-rich diets. Environ. Microbiol. 18, 1720–1729 (2016).CAS 

Google Scholar 
Kumar, K., Chaudhary, L. C., Agarwal, N. & Kamra, D. N. Isolation and characterization of tannin-degrading bacteria from the rumen of goats fed oak (Quercus semicarpifolia) leaves. Agr. Res. 3, 377–385 (2014).
Google Scholar 
Odenyo, A. A. et al. Characterization of tannin-tolerant bacterial isolates from East African ruminants. Anaerobe 7, 5–15 (2001).CAS 

Google Scholar 
Grilli, D. J. et al. Analysis of the rumen bacterial diversity of goats during shift from forage to concentrate diet. Anaerobe 42, 17–26 (2016).
Google Scholar 
Tong, J. et al. Illumina sequencing analysis of the ruminal microbiota in high-yield and low-yield lactating dairy cows. PLoS ONE 13, e0198225 (2018).
Google Scholar 
Pope, P. B. et al. Metagenomics of the Svalbard reindeer rumen microbiome reveals abundance of polysaccharide utilization loci. PLoS ONE 7, e38571 (2012).ADS 
CAS 

Google Scholar 
Østbye, K., Wilson, R. & Rudi, K. Rumen microbiota for wild boreal cervids living in the same habitat. FEMS Microbiol. Lett. 363, fnw233 (2016).
Google Scholar 
Gruninger, R. J., Sensen, C. W., McAllister, T. A. & Forster, R. J. Diversity of rumen bacteria in Canadian cervids. PLoS ONE 9, e89682 (2014).ADS 

Google Scholar 
Henderson, G. et al. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Sci. Rep. 5, 14567 (2015).CAS 

Google Scholar 
Reese, A. T. & Kearney, S. M. Incorporating functional trade-offs into studies of the gut microbiota. Curr. Opin. Microbiol. 50, 20–27 (2019).CAS 

Google Scholar 
Moeller, A. H. et al. Social behavior shapes the chimpanzee pan-microbiome. Sci. Adv. 2, e1500997 (2016).ADS 

Google Scholar 
Okano, T. & Matsuda, H. Biocultural diversity of Yakushima Island: Mountains, beaches, and sea. J. Mar. Isl. Cult. 2, 69–77 (2013).
Google Scholar 
Agetsuma, N., Agetsuma-Yanagihara, Y. & Takafumi, H. Food habits of Japanese deer in an evergreen forest: Litter-feeding deer. Mamm. Biol. 76, 201–207 (2011).
Google Scholar 
Higashi, Y., Hirota, S. K., Suyama, Y. & Yahara, T. Geographical and seasonal variation of plant taxa detected in faces of Cervus nippon yakushimae based on plant DNA analysis in Yakushima Island. Ecol. Res. 37, 582–597 (2022).CAS 

Google Scholar 
Kuroiwa, A. Nutritional ecology of the Yakushika (Cervus nippon yakushimae) population under high density Ph.D. thesis, Kyushu University, (2017).Koda, R., Agetsuma, N., Agetsuma-Yanagihara, Y., Tsujino, R. & Fujita, N. A proposal of the method of deer density estimate without fecal decomposition rate: A case study of fecal accumulation rate technique in Japan. Ecol. Res. 26, 227–231 (2011).
Google Scholar 
Yahara, T. in Deer eats world heritages: Ecology of deer and forets (eds T. Yumoto & H. Matsuda) 168–187 (Bunichi-Sogo-Shuppan, 2006).Onoda, Y. & Yahara, T. in Challenges for Conservation Ecology in Space and Time. (eds T. Miyashita & J. Nishihiro) 126–149 (University of Tokyo Press, 2015).Kagoshima Prefecture Nature Conservation Division. The current status of Yakusika in FY 2020, available at https://www.rinya.maff.go.jp/kyusyu/fukyu/shika/attach/pdf/yakushikaWG_R3_2-23.pdf (2020).Kuroiwa, A., Kuroe, M. & Yahara, T. Effects of density, season, and food intake on sika deer nutrition on Yakushima Island, Japan. Ecol. Res. 32, 369–378 (2017).
Google Scholar 
Hiura, T., Hashidoko, Y., Kobayashi, Y. & Tahara, S. Effective degradation of tannic acid by immobilized rumen microbes of a sika deer (Cervus nippon yesoensis) in winter. Anim. Feed Sci. Technol. 155, 1–8 (2010).CAS 

Google Scholar 
Kawarai, S. et al. Seasonal and geographical differences in the ruminal microbial and chloroplast composition of sika deer (Cervus nippon) in Japan. Sci. Rep. 12, 6356 (2022).ADS 
CAS 

Google Scholar 
Li, Z. et al. Response of the rumen microbiota of sika deer Cervus nippon fed different concentrations of tannin rich plants. PLoS ONE 10, e0123481 (2015).
Google Scholar 
McDonald, D. et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618 (2012).CAS 

Google Scholar 
Kim, M., Morrison, M. & Yu, Z. Status of the phylogenetic diversity census of ruminal microbiomes. FEMS Microbiol. Ecol. 76, 49–63 (2011).CAS 

Google Scholar 
Weimer, P. J. Redundancy, resilience, and host specificity of the ruminal microbiota: Implications for engineering improved ruminal fermentations. Front. Microbiol. 6, 296 (2015).
Google Scholar 
Scott, K. P., Gratz, S. W., Sheridan, P. O., Flint, H. J. & Duncan, S. H. The influence of diet on the gut microbiota. Pharmacol. Res. 69, 52–60 (2013).CAS 

Google Scholar 
Tapio, I. et al. Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows. PLoS ONE 12, e0180260 (2017).
Google Scholar 
Ohara, M. in Agriculture in Hokkaido v2 (ed K. Iwama, Ohara, M., Araki, H., Yamada, T., Nakatsuji, H., Kataoka, T., Yamamoto, Y.) 1–18(Faculty of Agriculture, Hokkaido Univ., 2009).Igota, H., Sakuragi, M. & Uno, H. in Sika Deer: Biology and Management of Native and Introduced Populations (eds. Dale R. McCullough, Seiki Takatsuki, & Koichi Kaji) 251–272 (Springer Japan, 2009).Fernando, S. C. et al. Rumen microbial population dynamics during adaptation to a high-grain diet. Appl. Environ. Microbiol. 76, 7482–7490 (2010).ADS 
CAS 

Google Scholar 
Hu, X. et al. High-throughput analysis reveals seasonal variation of the gut microbiota composition within forest musk deer (Moschus berezovskii). Front. Microbiol. 9, (2018).Artzi, L., Morag, E., Shamshoum, M. & Bayer, E. A. Cellulosomal expansion: Functionality and incorporation into the complex. Biotechnol. Biofuels 9, 61 (2016).
Google Scholar 
Biddle, A., Stewart, L., Blanchard, J. & Leschine, S. Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities. Diversity 5, (2013).Eisenhauer, N., Scheu, S. & Jousset, A. Bacterial diversity stabilizes community productivity. PLoS ONE 7, e34517 (2012).ADS 
CAS 

Google Scholar 
Miller, A. W., Oakeson, K. F., Dale, C. & Dearing, M. D. Effect of dietary oxalate on the gut microbiota of the mammalian herbivore Neotoma albigula. Appl. Environ. Microbiol. 82, 2669–2675 (2016).ADS 
CAS 

Google Scholar 
Adams, J. M., Rehill, B., Zhang, Y. & Gower, J. A test of the latitudinal defense hypothesis: Herbivory, tannins and total phenolics in four North American tree species. Ecol. Res. 24, 697–704 (2009).CAS 

Google Scholar 
Nabeshima, E., Murakami, M. & Hiura, T. Effects of herbivory and light conditions on induced defense in Quercus crispula. J. Plant Res. 114, 403–409 (2001).
Google Scholar 
Yang, C.-M., Yang, M.-M., Hsu, J.-M. & Jane, W.-N. Herbivorous insect causes deficiency of pigment–protein complexes in an oval-pointed cecidomyiid gall of Machilus thunbergii leaf. Bot. Bull. Acad. Sin. 44, 315–321 (2003).
Google Scholar 
Agetsuma, N., Agetsuma-Yanagihara, Y., Takafumi, H. & Nakaji, T. Plant constituents affecting food selection by sika deer. J. Wildl. Manag. 83, 669–678 (2019).
Google Scholar 
Couch, C. E. et al. Diet and gut microbiome enterotype are associated at the population level in African buffalo. Nat. Commun. 12, 2267 (2021).ADS 
CAS 

Google Scholar 
Goel, G., Puniya, A. K. & Singh, K. Tannic acid resistance in ruminal streptococcal isolates. J. Basic Microbiol. 45, 243–245 (2005).CAS 

Google Scholar 
Jiménez, N. et al. Genetic and biochemical approaches towards unravelling the degradation of gallotannins by Streptococcus gallolyticus. Microb. Cell Fact. 13, 154 (2014).
Google Scholar 
Nelson, K. E., Thonney, M. L., Woolston, T. K., Zinder, S. H. & Pell, A. N. Phenotypic and phylogenetic characterization of ruminal tannin-tolerant bacteria. Appl. Environ. Microbiol. 64, 3824–3830 (1998).ADS 
CAS 

Google Scholar 
Selwal, M. K. et al. Optimization of cultural conditions for tannase production by Pseudomonas aeruginosa IIIB 8914 under submerged fermentation. World J. Microbiol. Biotechnol. 26, 599–605 (2010).CAS 

Google Scholar 
Kohl, K. D., Weiss, R. B., Cox, J., Dale, C. & Denise Dearing, M. Gut microbes of mammalian herbivores facilitate intake of plant toxins. Ecol. Lett. 17, 1238–1246 (2014).
Google Scholar 
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Method 7, 335–336 (2010).CAS 

Google Scholar 
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).CAS 

Google Scholar 
Caporaso, J. G. et al. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266–267 (2009).
Google Scholar 
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).ADS 

Google Scholar 
R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2020).Osawa, R. Formation of a clear zone on tannin-treated brain heart infusion agar by a Streptococcus sp. isolated from feces of koalas. Appl. Environ. Microbiol. 56, 829–831 (1990).ADS 
CAS 

Google Scholar 
Hamamura, N., Olson, S. H., Ward, D. M. & Inskeep, W. P. Diversity and functional analysis of bacterial communities associated with natural hydrocarbon seeps in acidic soils at Rainbow Springs, Yellowstone National Park. Appl. Environ. Microbiol. 71, 5943–5950 (2005).ADS 
CAS 

Google Scholar 
Benson, D. A. et al. GenBank. Nucleic Acids Res. 41, D36–D42 (2012).ADS 

Google Scholar 
Chen, I.-M. A. et al. The IMG/M data management and analysis system v.6.0: new tools and advanced capabilities. Nucleic Acids Res. 49, D751–D763 (2020)Suzuki, M. T., Taylor, L. T. & Delong, E. F. Quantitative analysis of small-subunit rRNA genes in mixed microbial populations via 5 ’-nuclease assays. Appl. Environ. Microbiol. 66, 4605–4614 (2000).ADS 
CAS 

Google Scholar  More

Study area and soil collectionTwenty NRCS map units were selected across Hawaii Commercial & Sugar Company (HC&S) in central Maui that represented seven soil orders, 10 NRCS soil series, and approximately 77% of the total plantation area (Fig. 1). Soil heterogeneity across the landscape allowed for the comparison of a continuum of soil and soil properties that have experienced the same C4 grass inputs and agricultural treatment under sugarcane production for over 100 years. Conventional sugarcane production involved 2-year growth followed by harvest burn, collection of remaining stalks by mechanical ripper, deep tillage to 40 cm, no crop rotations, and little to no residue return. The sampled soils, collected from September-August 2015, thus represent a baseline of SOC after input-intensive tropical agriculture and long-term soil disturbance. Elemental analyses from this work show consistent agricultural disturbances led to degraded SOC content ranging from 0.23 to 2.91% SOC of soil mass with an average of only 1.16% SOC across all locations and depths.Figure 1Hawaiian Commercial and Sugar in central Maui with main Hawaiian Islands inset (left). Soil series identified by NRCS across HC&S fields (right) with black dots indicating 20 locations where soils were sampled to test landscape level differences in topical soil kinetics and associated soil properties under conventional sugarcane. Maps from Ref.19 created using ESRI ArcGIS with soil series data from: Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture, Web Soil Survey, Available online at http://websoilsurvey.nrcs.usda.gov/. Accessed [07/30/2016]19.Full size imageThe homogenized land use history allowed focused investigation of soil property effects on SOC storage across heterogenous soils (Table 1). Though soil inputs (e.g. water, nutrients, root inputs, residue removal) and disturbance regimes (e.g. burn, rip, till, compaction, no crop rotation) were consistent across the 20 field locations, average annual surface temperatures varied from 22.9 to 25.1 °C with a mean of 24.4 °C, average annual relative humidity varied from 70.4 to 79.2% with a mean of 73.4%, and average annual rainfall varied from 306 to 1493 mm with a mean of 575 mm. Gradients of rainfall, relative humidity, and elevation across the site generally increase in an east/north-east direction towards the prevailing winds and up the western slope of Haleakalā. In contrast, surface temperatures increase in the opposite direction towards Kihei and the southern tip of the West Maui Mountains.Table 1 NRCS soil classification and environmental conditions at 20 field sites.Full size tableaSoil descriptions26.bInterpolated estimates from Ref.25.Soil sampling and analysisPit locations were identified with a handheld GPS and were sampled using NRCS Rapid Carbon Assessment methods27. A total of 75 horizons were identified from the 20 selected map units to a depth of 1 m28,29. The central depth of each horizon was sampled using volumetric bulk density cores up to 50 cm. After 50 cm, a hand auger was used to check for any further horizon changes. The bulk density of horizons past 50 cm were estimated using collected soil mass and known auger size. Collected soils were air dried, processed through a 2 mm sieve, and analyzed for total C and nitrogen percent, SOC percent, soil texture, iron (Fe) and aluminum (Al) minerals, pH, cation and anion exchange capacity, extractable cations, wet and dry size classes, aggregate stability, and soil water potential at -15 kPa. Total C and nitrogen were measured by elemental analysis (Costech, ECS 4010, Valencia, CA), with SOC content determined by elemental analysis after hydrochloric acid digestion to remove carbonates. Soil texture was measured using sedimentary separation, while a 10:1 soil slurry in water was used to test soil pH. Soil pressure plates were used to measure soil water potential at -15 kPa.Fe and Al oxides were quantified in mineral phases using selective dissolutions of collected soils, including: (1) a 20:1 sodium citrate to sodium dithionite extraction, shaken 16 h, to quantify total free minerals30, (2) 0.25 M hydroxylamine hydrochloride and hydrochloric acid extraction, shaken 16 h, to quantify amorphous minerals31, and (3) 0.1 M sodium pyrophosphate (pH 10), shaken 16 h and centrifuged at 20,000g, to quantify organo-bound metals30. Extracted Fe, Al, and Si from al extractions were measured by inductively coupled plasma analysis (PerkinElmer, Optima ICP-OES, Norwalk, CT). Exploratory ratios of Fe/Al, Fe/Si, and Al/Si for the citrate/dithionite (c), hydroxylamine (h), and pyrophosphate (p) extractions were calculated. Crystalline Fe, operationally-defined as the difference between the citrate dithionite and hydroxylamine extraction, and Al + ½ Fe32 were calculated for each extraction.Plant-available phosphorus was extracted by the Olsen method using 0.5 M sodium bicarbonate adjusted to pH 8.5 and measured by continuous flow colorimetry (Hach, Lachat Quickchem 8500, Loveland, CO). Exchangeable cations (i.e. calcium, magnesium, potassium, and sodium), effective cation exchange capacity, and anion exchange capacity were measured by compulsive exchange using barium chloride and magnesium sulfate33. Cations were quantified by continuous flow colorimetry and flame-spectroscopy (Hach, Lachat Quickchem 8500, Loveland, CO). Field soils were air dried and initially passed through a 2 mm sieve before size classes of macroaggregate (2 mm – 250 µm) and microaggregate ( More

Sampling strategies and dataThe inner Oslofjorden phytoplankton dataset is a compilation of data mostly assembled from the monitoring program, financed since 1978 by a cooperation between the municipalities around the fjord, united in the counsel for technical water and sewage cooperation called “Fagrådet for Vann- og avløpsteknisk samarbeid i Indre Oslofjord”. The monitoring program started in 1973 and is ongoing. The program has sampled environmental parameters and chlorophyll since 1973, but for the first 25 years, phytoplankton data is only reported for the years 1973, 1974, 1988/9, 1990, 1994 and 1995. Since 1998, yearly sampling has been conducted, and from 2006 to 2019, the sampling frequency was approximately monthly. In addition, we have compiled research and monitoring data from researchers at the University of Oslo from 1896 and 1916, 1933–34 and 1962–1965.The records from 1896 and 1897 were collected using zoo-plankton net13. The phytoplankton collection in 1916–1917 used buckets or Nansen flasks for sampling. From 1933 to 1984, phytoplankton samples were collected using Nansen bottles and then from 1985–2020 with Niskin bottles from research vessels. The exception is the period from 2006 to 2018 when samples were also collected with FerryBox- equipped ships of opportunity14 with refrigerated autosamplers (Table 2).Since the 1990s, quantitative phytoplankton samples have mostly been preserved in Lugol’s solution, except for spring and autumn samples in the period 1990–2000 that were preserved in formalin. The records from 1896, 1897 and 1916 were preserved in ethanol, and between 1933 and 1990, samples were preserved in formalin. Sampling strategies and methods are listed in Table 2.The records from 1896 and 1897 were quantified by weight, and taxon abundance is categorised as “rare” (r), “rather common” (+), “common” (c) and “very common” (cc)13. In 1916 and 1917, Grans filtration method15 was used, and the number was given in cell counts per litre. From 1916 to 1993, the data is reported only as phytoplankton abundance (N, number of cells per litre). For most years after 1994, the dataset includes both abundance and biomass (μg C per litre), except for 2003, 2004, 2017 and 2018. Phytoplankton was identified and quantified using the sedimentation method of Utermöhl (1958)16. Biovolume for each species is calculated according to HELCOM 200617 and converted to biomass (μg C) following Menden-Deuer & Lessards (2000)18.Data inventoryThe inner Oslofjorden Phytoplankton dataset was compiled in 2020, comprising quantitative phytoplankton cell counts from inner Oslofjorden since 1896. Previously, parts of the data have been available as handwritten or printed tables in reports and published sources19,20,21 (Fig. 2). All sources are digitally available from the University of Oslo Library, the website for “Fagrådet” (http://www.indre-oslofjord.no/) or the NIVA online report database (https://www.niva.no/rapporter). Data from 1994 and onwards have been accessed digitally from the NIVA’s databases. They are also available from client reports from the monitoring project for inner Oslofjorden from the online sites listed above.The first known, published investigation of hydrography and plankton in the upper water column of the inner Oslofjorden was by Hjort & Gran (1900)13. Samples were collected during a hydrographical and biological investigation covering both the Skagerrak and Oslofjorden. There is only one sampling event from Steilene (Dk 1), but some phytoplankton data were obtained at Drøbak, just south of the shallow sill separating the inner and outer Oslofjorden, from winter 1896 to autumn 1897. Twenty years later, Gran and Gaarder (1927)22 conducted a study that included culture experiments at Drøbak field station (at the border between the inner and outer Oslofjorden) in March – April 1916 and August – September 1917. A higher frequency investigation was carried out from June 1933 to May 1934, covering 12 stations in inner and outer Oslofjorden where phytoplankton was analysed by microscopic examination23. The extensive program (the Oslofjord Project) conducted from 1962–1964 covered many parameters, and we have extracted the data for phytoplankton. From 1973 and onward, the research vessel-based monitoring program was financed by the municipalities around the fjord, and since 2006 NIVA has supplemented the monitoring program using FerryBox ships of opportunity. Samples from 4 m depth were collected using a refrigerated autosampler system (Teledyne ISCO) connected to a FerryBox system on M/S Color Festival and M/S Color Fantasy through cooperation between NIVA and Color Line A/S. Since 2018, the FerryBox has been part of the Norwegian Ships of Opportunity Program research infrastructure funded by the Research Council of Norway.The indicated depth of 3.5–4 m is an estimated average, as the actual sampling depth depends on shipload and sea conditions.Several other research projects have sampled from inner Oslofjorden between 1886 and 2000 with different aims. Data from relevant projects reporting on the whole phytoplankton community have also been included in this database.Data compilationThe data already digitalised were compiled from MS Excel files, and other data were manually entered into the standard format in MS Excel files. All collected data were then integrated into one MS Excel database, and this file was used for upload into GBIF. Data can be downloaded from GBIF in different formats and be linked together by the measurementsorfacts table.Quality control and standardisationAfter compilation, the data were checked for errors that could occur during manual digitalisation or just the compilation process. Duplicates and zero values were removed (Fig. 2). The major quantitative unit is phytoplankton abundance in cells per litre. Due to varying scopes of sampling and the development of gear and instruments, the number of species identified may vary between projects. Some of the earliest records were registered as “present”, indicating the amount in comments.Metadata, such as geographical reference, depth and methodology accessed from papers and reports, were accessible from the data source. When data was accessed from the NIVA internal databases, the metadata information was provided by the database owners/researchers.TaxonomyThe taxonomy of microalgae is in constant revision as new knowledge and techniques for identification are developing. Several historical species names recorded in this database are synonyms of accepted names in 2021. We have used the original names in our database and matched them to accepted names and Aphia ID using the taxon match tool available in the open-access reference system; World Register of Marine Species (Worms)24. The taxon match was conducted in March 2021.The nomenclature in Worms is quality assured by a wide range of taxonomic specialists. The Aphia ID is a unique and stable identifier for each available name in the database24. We also cross-checked the last updated nomenclature in Algaebase25 (March 2022) to assign species to a valid taxon name. When Algaebase and Worms were not in accordance, Algaebase taxonomy was usually chosen except in the case of Class Bacillariophyceae.Before matching the species list, the original species names were cleaned from spelling mistakes or just spelling mismatches like spaces, commas, etc. The original name is, however, left in one column in the database. For registrations where a species identification is uncertain, e.g. Alexandrium cf. tamarense, we used only Alexandrium. For registrations where the full name is uncertain, e.g. cf. Alexandrium tamarense, we used the name and Aphia ID for higher taxa, in this case, order. For others, e.g. “pennate diatoms” or “centric diatoms“, we used the name and Aphia ID for class. When names for, e.g. order and class were not recognised automatically by the matching tool in World Register of Marine Species (WoRMS), these were matched manually. Only very few records, mostly “cysts” and “unidentified monads”, could not be matched neither automatically nor manually but were assigned to general “protists” with affiliated ID. More