Ecology

Parasites have frequently been observed on the gills of coleoid cephalopods during ROV dives in the mesopelagic waters of the Monterey Submarine Canyon. Here, we demonstrate that at least two parasite species can be distinguished from ROV-collected specimens. Based on morphology, the first parasite was identified as the protist Hochbergia cf. moroteuthensis. Although the original description of H. moroteuthensis struggled to assign a taxonomic rank, the authors noted that the presence of trichocysts and an apical pore bear similarities to those of dinoflagellates in an encysted life stage29,30. Using Sanger sequencing and dinoflagellate cyst-specific primers, we confirm this parasite to be a dinoflagellate that forms a sister group to members of the Oodinium genus. The second parasite could not be matched to any documented morphological descriptions, and DNA barcoding was only able to resolve a short sequence that does not provide for a reliable identification.Hochbergia moroteuthensis appears to be a common parasite of midwater cephalopods and has previously been collected off the gills of twenty cephalopod species29,30. These include five taxa investigated here (C. calyx, V. infernalis, Galiteuthis spp., Gonatus spp. and Japetella diaphana), with Taonius sp. new to the list. While H. cf. moroteuthensis found in this study was somewhat smaller than the type series (0.5–1.4 mm versus 1.19–1.99)30, it was within the range of those reported by McLean et al.29 on the squids Stigmatoteuthis dofleini Pfeffer, 1912 and Abralia trigonura Berry, 1913 (i.e. 0.56 to 1.10 mm on average in length)29. The latter authors noticed that parasite size, color (i.e. white to yellow) and thecal plate morphology may differ between host species, which could indicate multiple Hochbergia species. It should, however, be noted that it is unknown whether H. moroteuthensis maximum growth is dependent on host size or whether the investigated parasites were simply in different growth stages given the study’s relatively small samples sizes. Although we did not compare H. cf. moroteuthensis morphology across hosts in great detail, the partial 18S rRNA sequences obtained for parasites on Gonatus berryi and Chiroteuthis calyx were identical. Further research is therefore warranted to investigate species-specific parasite differences and speciation among hosts.The genetic relatedness between H. cf. moroteuthensis and its Oodinium sister group is further supported by several morphological features. First, the lack of distinct dinoflagellate characters, ovoid shape and the presence of trichocysts, have also been noted for Oodinium cysts41,42,43. McLean et al.29 further reported that the nucleus of the single-celled H. moroteuthensis cyst contains diffuse chromatin, a feature unlike most dinoflagellates that possess well-defined rod-like chromosomes42. Remarkably, dinoflagellates within Oodinium are known to alternate between both non-dinokaryotic and dinokaryotic nuclei within their life cycles, which could explain H. moroteuthensis’ diffuse chromatin42,43. Similarities between H. moroteuthensis and Oodinium further extend to the parasitic life style with primarily pelagic hosts. Dinoflagellates in the Oodinium genus are all known to be ectoparasitic, infecting ctenophores, chaetognaths, annelids, larvaceans and a hydromedusa41,43,44,45,46.In spite of these similarities, there are also several noteworthy morphological differences between H. moroteuthensis and members of the Oodinium genus. Young Oodinium cysts generally have a white to yellow coloring, with older cysts taking a yellow–brown or dark brown tint41,43,44. Oodinium cysts also possess relatively simple thecal plates and above all, have a distinct peduncle, or stalk, with which they attach to the host and which is thought to serve as feeding apparatus41,43,47. Maximum lengths for Oodinium cysts have been reported up to 0.39 mm43,46. In contrast, cysts in H. moroteuthensis possess a white to yellow coloring, an intricate pattern of triangular plates, reach sizes up to 1.99 mm long, and have a simple holdfast area with an oval aperture that likely anchors them to the host30. Currently, both Oodinium and Hochbergia form a genetically distinct clade within the Dinophyceae and analysis of further specimens and genetic markers might provide more insight into their relatedness and specialization on primarily pelagic hosts. Additionally, analysis of fast- and slow-evolving genetic markers might resolve the polytomy observed in the phylogenetic trees, which were also present in the phylogenetic reconstruction of the DINOREF reference database by Mordret et al.32.The genetic similarity of H. cf. moroteuthensis to an unidentified eukaryote from the water column and the fact that we encountered the protozoans in an encysted stage, strongly suggests that these dinoflagellates infect their cephalopod hosts through a free-living life stage. Many parasitic dinoflagellates, including Oodinium, alternate between a motile free-living stage—the dinospore—that forms a vegetative feeding stage—the trophont—upon attachment to the host41,47,48. During this vegetative stage, the trophont grows greatly in size but without cellular division. Once mature, the trophont detaches from the host to divide into multiple flagellated dinospores. The dinospores disperse into the water column, free to infect new hosts (Fig. 6)41,47,48.Figure 6Theorized life cycle of Hochbergia moroteuthensis. (a) The vegetative trophont (feeding life stage) grows without cellular division on the cephalopod’s gills. (b) The mature trophont detaches and (c) divides into motile dinospores, (d) free to infect new hosts in the water column. Illustration (b) trophont adapted from Shinn & McLean30.Full size imageSuch a free-living life stage is consistent with H. moroteuthensis’ wide geographic distribution. Free-living dinospores are easily dispersed by ocean currents, and observations in both the North Pacific Ocean and the Gulf of Mexico could indicate large-scale ocean connectivity, potentially beyond the distribution reported here29. This dispersal may also offer H. moroteuthensis a wide range of infection possibilities and explain why trophonts are found in twenty-one different cephalopod taxa. Nevertheless, population genetic structure needs to be investigated, as it is currently unknown if the parasites represent multiple species.Free-living dinospores might also explain H. moroteuthensis’ location on the exterior gill tissue. With dinospores free in the water column, the fastest pathway to a cephalopod’s interior is through ‘inhalation’. In this process, cephalopods actively force water through their gills, making these the first organs Hochbergia would encounter. Respiratory organs give direct access to the cephalopod’s blood stream, and therefore offer a suitable environment (i.e. nutrient and oxygen rich) for development into a trophont. Gills also provide interstices that could simply trap dinospores. Either way, there was only one occasion (i.e. out of 355) where trophonts were seen on other body parts besides the gills (Fig. 4e). In comparison, several Oodinium parasites are also known to attach to specific host-body parts, apparently preferring sites involved in locomotor movement. For instance, Oodinium jordani McLean & Nielsen, 1989 is known to attach to the fin of the chaetognath Sagitta elegans Verrill, 187346, while O. pouchetti is mostly found on the tail of appendicularians41, and Oodinium sp. collected off various ctenophores appears to prefer attachment close to or within the beating comb rows44. Whether these surface areas offer highest encounter rates or provide a physical benefit such as enhanced oxygenation remains unknown.The increased prevalence of H. cf. moroteuthensis observed in the most abundant cephalopod, Chiroteuthis, and in the other adult cephalopods is in line with infection dynamics known from other wildlife parasites, where the probability of a parasitic infection increases with host density and age49,50,51. Following this, dinospores in the Monterey Submarine Canyon have more opportunities to encounter common squids like Chiroteuthis52 and longer-lived cephalopods. Alternatively, it is possible that the increased parasite load in adults is simply the result of larger gill surface areas when compared to juveniles. However, when comparing prevalence between host species, it should be noted that the maximum adult sizes for C. calyx (up to 100 mm in mantle length, ML) are smaller than those of Galiteuthis (500 mm ML), Taonius (660 mm ML) and Japetella (144 mm ML) among specimens found in the Monterey Submarine Canyon53,54.Other factors that might explain the observed prevalence include parasite preferences for host physiology (e.g. respiration rates) or confinement to a certain depth range18. Although Chiroteuthis, Galiteuthis, Taonius and Japetella partially overlap in their depth distributions, Chiroteuthis generally remains above the core of the oxygen minimum zone, located around 700 m in Monterey Bay52,55. Galiteuthis, on the other hand, has a bimodal distribution, with older individuals known to migrate below the oxygen minimum core52,55,56. If dinospore viability is restricted to more shallow depths, the probability of infection for Galiteuthis could decrease when living at deeper depths. This is further supported by Taonius, which showed a comparable bimodal distribution to Galiteuthis52 and shared a similar parasite prevalence. Furthermore, Japetella is the deepest living cephalopod investigated and harbored relatively few Hochbergia trophonts. In spite of this, it is unknown how long it takes for H. moroteuthensis dinospores to develop into mature trophonts and over what time frames they may accumulate on their hosts. Lab-based experiments with Oodinium sp. on the ctenophore Beroe abyssicola Mortensen, 1927 showed that trophonts needed approximately 20 days to grow from 35 µm in length to their mature size of 350 µm at 10 °C44. Given that H. moroteuthensis can grow over five times larger and lives at colder temperatures depending on its host distribution, growth periods may be substantially longer.When looking at the prevalence of H. cf. moroteuthensis over time, only Taonius appeared to be showing an increase in infected individuals over the years. Present results, however, are insufficient to determine whether this increase is the result of environmental change or part of natural variability. We therefore recommend continued monitoring to determine long term trends. Based on the monthly prevalence, it is likely that Chiroteuthis acts as a reservoir for Hochbergia parasites throughout the year. Galiteuthis, Japetella and Taonius show more seasonal dynamics. It may be that the reported seasonality is related to upwelling events or environmental cues promoting dinospore formation (e.g. increasing temperatures)50. Alternatively, cephalopods might be more susceptible to infections in certain months, or have higher resistance in others. Taonius, for example, had a markedly lower parasite load on average than Galiteuthis despite similar prevalence estimates (Tables 1 and 2), potentially indicating some sort of resistance mechanism. More research is warranted to confirm any host resistance and the influence of depth or seasonal effects.The other parasite type found in ROV-collected specimens of Vampyroteuthis infernalis and Gonatus spp. needs further characterization. Although DNA barcoding was able to resolve a short sequence that potentially places it within the phylum Apicomplexa, it appears more likely that this genetic material originated from contamination with a different parasite. Apicomplexa reported in cephalopods generally infect the digestive tract and are morphologically different from the parasites observed here19.In conclusion, our findings highlight the need for further investigation of cephalopods and their gill parasites. Considering that parasites influence biodiversity and that cephalopods form key links in pelagic food webs, future research should be focused at assessing potential effects on cephalopod physiology. For example, if H. moroteuthensis limits longevity or reproduction in common squids like C. calyx, then changes in parasite abundance might result in cascading effects on abundance of Chiroteuthis’ prey, predators and competitors. Additionally, baseline estimates of parasite prevalence are crucial to fully understand whether midwater host-parasite systems are at risk from increasing anthropogenic stressors and how they will change over time. While ROV observations have proven key to estimate prevalence and infection intensity here, trawled specimens continue to be valuable for verification of parasite species and obtaining material for genetic analyses, even if slightly damaged. We therefore recommend combining ROV observations with periodic trawling in future studies, since ROVs may not reveal smaller parasites, early infections or parasites in animals with tissue that is not transparent. More

Australia’s tropical rainforests are some of the oldest in the world.Credit: Alexander Schenkin

The rate of tree dying in the old-growth tropical forests of northern Australia each year has doubled since the 1980s, and researchers say climate change is probably to blame.The findings, published today in Nature1, come from an extraordinary record of tree deaths catalogued at 24 sites in the tropical forests of northern Queensland over the past 49 years.“Trees are such long-living organisms that it really requires huge amounts of data to be able to detect changes in such rare events as the death of a tree,” says lead author David Bauman, a plant ecologist at the University of Oxford, UK. The sites were initially surveyed every two years, then every three to four years, he explains, and the analysis focused on 81 key species.Bauman and his team recorded that 2,305 of these trees have died since 1971. But they calculated that, from the mid-1980s, tree mortality risk increased from an average of 1% a year to 2% a year (See ‘Increasing death rate’).

Bauman says that trees help to slow global warming because they absorb carbon dioxide, so an increase in tree deaths reduces forests’ carbon-capturing ability. “Tropical forests are critical to climate change, but they’re also very vulnerable to it,” he explains.Climate changeThe study found that the rise in death rate occurred at the same time as a long-term trend of increases in the atmospheric vapour pressure deficit, which is the difference between the amount of water vapour that the atmosphere can hold and the amount of water it does hold at a given time. The higher the deficit, the more water trees lose through their leaves. “If the evaporative demand at the leaf level can’t be matched by water absorption in fine roots, it can lead to leaves wilting, whole branches dying and, if the stress is sustained, to tree death,” Bauman says.The researchers looked at other climate-related trends — including rising temperatures and an estimate of drought stress in soils — but they found that the drying atmosphere had the strongest effect. “What we show is that this increase [in tree mortality risk] also closely followed the increase in atmospheric water stress, or the drying power of air, which is a consequence of the temperature increase due to climate change,” Bauman explains.Of the 81 tree species that the team studied, 70% showed an increase in mortality risk over the study period, including the Moreton Bay chestnut (Castanospermum australe), white aspen (Medicosma fareana) and satin sycamore (Ceratopetalum succirubrum).The authors also saw differences in mortality in the same tree species across plots, depending on how high the atmospheric vapour pressure deficit was in each plot.“This is one data set where the trees have been monitored in reasonably good detail since the early ’70s, and this is a really top-notch analysis of it,” says Belinda Medlyn, an ecosystem scientist at University of Western Sydney, Australia.But she says that more experiments are needed to determine whether the vapour pressure deficit is the biggest climate-related contributor to the increase in tree deaths. More

Young cerebrospinal fluid probably improves the conductivity of the neurons in ageing mice.Credit: Qilai Shen/Bloomberg/Getty

Young brain fluid improves memory in old miceCerebrospinal fluid (CSF) from young mice can improve memory function in older mice, researchers report in Nature (T. Iram et al. Nature 605, 509–515; 2022).A direct brain infusion of young CSF probably improves the conductivity of the neurons in ageing mice, which improves the process of making and recalling memories.CSF is a cocktail of essential ions and nutrients that cushions the brain and spinal cord and is essential for normal brain development. But as mammals age, CSF loses some of its punch. Those changes might affect cells related to memory, says co-author Tal Iram, a neuroscientist at Stanford University in California.The researchers found that young CSF helps ageing mice to generate more early-stage oligodendrocytes, cells in the brain that produce the insulating sheath around nerve projections and help to maintain brain function.The team suggest that the improvements are largely due to a specific protein in the fluid.“This is super exciting from the perspective of basic science, but also looking towards therapeutic applications,” says Maria Lehtinen, a neurobiologist at Boston Children’s Hospital in Massachusetts.Gender bias worms its way into parasite namingA study examining the names of nearly 3,000 species of parasitic worm discovered in the past 20 years reveals a markedly higher proportion named after male scientists than after female scientists — and a growing appetite for immortalizing friends and family members in scientific names.Robert Poulin, an ecological parasitologist at the University of Otago in Dunedin, New Zealand, and his colleagues combed through papers published between 2000 and 2020 that describe roughly 2,900 new species of parasitic worm (R. Poulin et al. Proc. R. Soc. B https://doi.org/htqn; 2022). The team found that well over 1,500 species were named after their host organism, where they were found or a prominent feature of their anatomy.

Source: R. Poulin et al. Proc. R. Soc. B https://doi.org/htqn (2022)

Many others were named after people, ranging from technical assistants to prominent politicians. But just 19% of the 596 species named after eminent scientists were named after women, a percentage that barely changed over the decades (see ‘Parasite name game’). Poulin and his colleagues also noticed an upward trend in the number of parasites named after friends, family members and even pets of the scientists who formally described them. This practice should be discouraged, Poulin argues.

Sea anemones turn oxybenzone into a light-activated agent that can bleach and kill corals.Credit: Georgette Douwma/Getty

Anemones suggest why sunscreen turns toxic in seaA common but controversial sunscreen ingredient that is thought to harm corals might do so because of a chemical reaction that causes it to damage cells in the presence of ultraviolet light.Researchers have discovered that sea anemones, which are similar to corals, make the sun-blocking molecule oxybenzone water-soluble by tacking a sugar onto it. This inadvertently turns oxybenzone into a molecule that — instead of blocking UV light — is activated by sunlight to produce free radicals that can bleach and kill corals. The animals “convert a sunscreen into something that’s essentially the opposite of a sunscreen”, says Djordje Vuckovic, an environmental engineer at Stanford University in California.It’s not clear how closely these laboratory-based studies mimic the reality of reef ecosystems. The concentration of oxybenzone at a coral reef can vary widely, depending on factors such as tourist activity and water conditions. And other factors threaten the health of coral reefs; these include climate change, ocean acidification, coastal pollution and overfishing. The study, published on 5 May (D. Vuckovic et al. Science 376, 644–648; 2022) does not show where oxybenzone ranks in the list. More

DataAll data was processed and analyzed using R (R Core Team, Version 4.0.3).Dengue case data were collected and shared by the Alcaldía de Medellín, Secretaría de Salud. In Medellin, dengue case surveillance is conducted by public health institutions that classify and report all cases that meet the WHO clinical dengue case criteria for a probable case to Medellin’s Secretaría de Salud through SIVIGILA (“el Sistema Nacional de Vigilancia en Salud Publica). All case data were de-identified and aggregated to the SIT Zone level.Human public transit usage and movement data were collected and shared by the Área Metropolitana del Valle de Aburrá for 50–200 respondents per SIT Zone. The “Encuestas Origen Destino” (Origen Destination Surveys) were conducted in 2005, 2011, and 2016 and published in 2006, 2012, and 2017, with survey methods described by the Área Metropolitana del Valle de Aburrá25. Survey respondents include a randomly selected subset of all Medellin residents in each SIT zone regardless of whether they use public transit or not. Survey respondents reported the start and end locations, purpose for travel, and mode of travel for all movement over the last 24 h from the time the survey was administered. Respondents reported all modes of movement, including public transit, private transit, and movement on foot. The results of the survey published in 2017 are published online by the Área Metropolitana del Valle de Aburrá26, and select data are available through the geodata-Medellin open data portal27. The results and data of the survey published in 2012 are not publicly available and were obtained directly from the Área Metropolitana del Valle de Aburrá.The public transit usage survey data were also used to extract socioeconomic data to the SIT zone; surveyors also reported basic demographic data including household Estrato, which was averaged per SIT zone to estimate zone socioeconomic status. “Estrato” measures socioeconomic status on a scale from 1 (lowest) to 6 (highest). This system is used by the government of Colombia to allocate public services and subsidies (Law 142, 1994). Data from the public transit usage survey were used to extract socioeconomic status data because it is the only location available where the spatial scale of the data matched the spatial scale of the SIT zone.Data on the location of Medellín public transit lines was downloaded as shape files from the geodata-Medellín open data portal27 and subset for each year to the set of transit lines that was available in that year. Data on the opening date of each Medellín public transit line was taken from the Medellín metro website28.Because census data at the zone level were not available for this study and only exists for 2005 and 2018, we used population estimates for each year downloaded from the WorldPop project29 and aggregated by SIT zone. The accuracy of WorldPop estimates were checked against available census data for 2005 and 2018 at the comuna level, accessed via the geodata- Medellín open data portal27.Ethical considerationsNo human subjects research was conducted. All data used was de-identified, and the analysis was conducted on a database of cases meeting the clinical criteria for dengue with no intervention or modification of biological, physical, psychological, or social variables. All methods were performed in accordance with the relevant guidelines and regulations.Data analysisQuantifying public transit usage and distance from nearest transit lineTo quantify public transit usage, we determined if each respondent reported using the metro, metroplus, or ruta alimentadora (supplementary bus route system integrated with the metro system) in the last 24 h. We then calculated the percent of respondents using the public transit system at least once for each SIT zone.To quantify the distance to the nearest public transit line, we calculated the distance from the center point of each zone to the closest metro, metroplus, tranvía, metrocable, ruta alimentadora, or escalera eléctrica. This was recalculated for each year, including new transit lines that were added within that year.Spatial autoregressive models of dengue incidenceDengue incidence per year at the level of the SIT zone was modeled using a fixed effects spatial panel model by maximum likelihood (R package splm30) as described in31. Our fixed effects were socioeconomic status, distance from public transit, a two-way interaction between these factors, and year. To weight dengue cases by population per SIT zone, the model contained a log offset of population per zone per year. Dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year. Year was analyzed as a categorical variable to avoid smoothing epidemic years. All continuous variables were scaled to enable comparison of effect size. Because these panel models require balanced data across time, data was truncated to SIT zones that had data for all years available (247 remaining of 291). Spatial dependency was evaluated, and the model was selected using the Hausman specification test and locally robust panel Lagrange Multiplier tests for spatial dependence. Based on a significant Hausman specification test result, which indicates a poor specification of the random effect model, a fixed effect model was chosen. This result is supported by the fact that we had a nearly exhaustive sample of SIT zones in the Medellin metro area. Lagrange multiplier tests were used to determine the most appropriate spatial dependency specifications. Based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was the most appropriate to incorporate spatial dependency; a SAR model considers that the number of dengue cases in a SIT zone depends on the number in neighboring zones.Because public transit usage was a measurement taken during just two of the study years, we constructed an additional fixed effects spatial panel model by maximum likelihood model of dengue incidence in just 2011 and 2016 that included ridership as an additional predictor variable. Our fixed effects were year, socioeconomic status, distance from public transit, a two-way interaction between socioeconomic status and distance from public transit, percent utilizing public transit, and a two-way interaction between socioeconomic status and percent utilizing public transit. As in our model of all years, the model contained a log offset of population per zone per year and dengue case counts were log transformed after adding one to account for zones with zero dengue cases in a given year, year was analyzed as a categorical variable, and all continuous variables were scaled to enable comparison of effect size. The data was truncated to SIT zones that had data for all years available (251 remaining of 291). We used the same model selection process, and again a fixed effect model was chosen, and based on the results of the Lagrange multiplier tests, a Spatial Autoregressive (SAR) model was determined the most appropriate to incorporate spatial dependency. More

Kelly, A. E. & Goulden, M. L. Rapid shifts in plant distribution with recent climate change. Proc. Natl. Acad. Sci. U.S.A. 105, 11823–11826. https://doi.org/10.1073/pnas.0802891105 (2008).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wiens, J. J. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biol. 14, e2001104. https://doi.org/10.1371/journal.pbio.2001104 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Swinnen, J., Burkitbayeva, S., Schierhorn, F., Prishchepov, A. V. & Müller, D. Production potential in the “bread baskets” of Eastern Europe and Central Asia. Global Food Secur. 14, 38–53. https://doi.org/10.1016/j.gfs.2017.03.005 (2017).Article 

Google Scholar 
Henry, R. J. Innovations in plant genetics adapting agriculture to climate change. Curr. Opin. Plant Biol. 56, 168–173. https://doi.org/10.1016/j.pbi.2019.11.004 (2020).Article 
PubMed 

Google Scholar 
Stokes, C. & Howden, M. Adapting Agriculture to Climate Change: Preparing Australian Agriculture, Forestry and Fisheries for the Future (Csiro Publishing, 2010).Book 

Google Scholar 
Bräutigam, K. et al. Epigenetic regulation of adaptive responses of forest tree species to the environment. Ecol. Evol. 3, 399–415. https://doi.org/10.1002/ece3.461 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Yaish, M. W., Colasanti, J. & Rothstein, S. J. The role of epigenetic processes in controlling flowering time in plants exposed to stress. J. Exp. Bot. 62, 3727–3735. https://doi.org/10.1093/jxb/err177 (2011).CAS 
Article 
PubMed 

Google Scholar 
Yaish, M. W. DNA methylation-associated epigenetic changes in stress tolerance of plants. In Molecular Stress Physiology of Plants (eds Rout, G. R. & Das, A. B.) 427–440 (Springer India, 2013).Chapter 

Google Scholar 
Suji, K. K. & Joel, A. J. An epigenetic change in rice cultivars underwater stress conditions. Electron. J. Plant Breed. 1, 1142–1143 (2010).
Google Scholar 
Peng, H. & Zhang, J. Plant genomic DNA methylation in response to stresses: Potential applications and challenges in plant breeding. Prog. Nat. Sci. 19, 1037–1045. https://doi.org/10.1016/j.pnsc.2008.10.014 (2009).CAS 
Article 

Google Scholar 
Baduel, P. & Colot, V. The epiallelic potential of transposable elements and its evolutionary significance in plants. Philos. Trans. R. Soc. B 376, 20200123. https://doi.org/10.1098/rstb.2020.0123 (2021).CAS 
Article 

Google Scholar 
Labra, M. et al. Analysis of cytosine methylation pattern in response to water deficit in pea root tips. Plant Biol. 4, 694–699. https://doi.org/10.1055/s-2002-37398 (2002).CAS 
Article 

Google Scholar 
Wang, W.-S. et al. Drought-induced site-specific DNA methylation and its association with drought tolerance in rice (Oryza sativa L.). J. Exp. Bot. 62, 1951–1960. https://doi.org/10.1093/jxb/erq391 (2011).CAS 
Article 
PubMed 

Google Scholar 
Šmarda, P., Bureš, P., Horová, L., Foggi, B. & Rossi, G. Genome size and GC content evolution of Festuca: Ancestral expansion and subsequent reduction. Ann. Bot. 101, 421–433. https://doi.org/10.1093/aob/mcm307 (2008).CAS 
Article 
PubMed 

Google Scholar 
Tomczyk, P. P., Kiedrzyński, M., Jedrzejczyk, I., Rewers, M. & Wasowicz, P. The transferability of microsatellite loci from a homoploid to a polyploid hybrid complex: An example from fine-leaved Festuca species (Poaceae). PeerJ 8, e9227. https://doi.org/10.7717/peerj.9227 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Piękoś-Mirkowa, H. & Mirek, Z. Distribution patterns and habitats of endemic vascular plants in the Polish Carpathians. Acta Soc. Bot. Pol. 78, 321–326 (2009).Article 

Google Scholar 
Kiedrzyński, M., Zielińska, K. M., Rewicz, A. & Kiedrzyńska, E. Habitat and spatial thinning improve the Maxent models performed with incomplete data. J. Geophys. Res. Biogeosci. 122(6), 1359–1370. https://doi.org/10.1002/2016JG003629 (2017).Article 

Google Scholar 
Rewicz, A. et al. Morphometric traits in the fine-leaved fescues depend on ploidy level: The case of Festuca amethystina L. PeerJ 6, e5576. https://doi.org/10.7717/peerj.5576 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Kiedrzyński, M. et al. Tetraploids expanded beyond the mountain niche of their diploid ancestors in the mixed-ploidy grass Festuca amethystina L. Sci. Rep. 11, 18735 (2021).ADS 
Article 

Google Scholar 
Mounger, J. et al. Epigenetics and the success of invasive plants. Philos. Trans. R. Soc. B 376, 20200117. https://doi.org/10.1098/rstb.2020.0117 (2021).CAS 
Article 

Google Scholar 
Bewick, A. J. & Schmitz, R. J. Epigenetics in the wild. Elife 4, e07808. https://doi.org/10.7554/eLife.07808 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Sahu, P. P. et al. Epigenetic mechanisms of plant stress responses and adaptation. Plant Cell Rep. 32(8), 1151–1159. https://doi.org/10.1007/s00299-013-1462-x (2013).CAS 
Article 
PubMed 

Google Scholar 
Alonso, C. et al. Interspecific variation across angiosperms in global DNA methylation: Phylogeny, ecology and plant features in tropical and Mediterranean communities. New Phytol. 224(2), 949–960. https://doi.org/10.1111/nph.16046 (2019).CAS 
Article 
PubMed 

Google Scholar 
Angers, B., Castonguay, E. & Massicotte, R. Environmentally induced phenotypes and DNA methylation: How to deal with unpredictable conditions until the next generation and after. Mol. Ecol. 19(7), 1283–1295. https://doi.org/10.1111/j.1365-294X.2010.04580.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Batog, J. & Wawro, A. Process of obtaining bioethanol from sorghum biomass using genome shuffling. Cellul. Chem. Technol. 53, 459–467 (2019).CAS 
Article 

Google Scholar 
Richards, C. L., Schrey, A. W. & Pigliucci, M. Invasion of diverse habitats by few Japanese knotweed genotypes is correlated with epigenetic differentiation. Ecol. Lett. 15, 1016–1025. https://doi.org/10.1111/j.1461-0248.2012.01824.x (2012).Article 
PubMed 

Google Scholar 
Li, N. et al. DNA methylation repatterning accompanying hybridization, whole genome doubling and homoeolog exchange in nascent segmental rice allotetraploids. New Phytol. 223(2), 979–992. https://doi.org/10.1111/nph.15820 (2019).CAS 
Article 
PubMed 

Google Scholar 
Róis, A. S. et al. Epigenetic rather than genetic factors may explain phenotypic divergence between coastal populations of diploid and tetraploid Limonium spp. (Plumbaginaceae) in Portugal. BMC Plant Biol. 13(1), 205. https://doi.org/10.1186/1471-2229-13-205 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Li, A. et al. DNA methylation in genomes of several annual herbaceous and woody perennial plants of varying ploidy as detected by MSAP. Plant Mol. Biol. Rep. 29, 784–793. https://doi.org/10.1007/s11105-010-0280-3 (2011).ADS 
CAS 
Article 

Google Scholar 
Sokolova, D. A., Vengzhen, G. S. & Kravets, A. P. An Analysis of the correlation between the changes in satellite DNA methylation patterns and plant cell responses to the stress. Cell Bio 2, 163–171. https://doi.org/10.4236/cellbio.2013.23018 (2013).CAS 
Article 

Google Scholar 
Johnson, L. I. & Tricker, P. J. Epigenomic plasticity within populations: Its evolutionary significance and potential. Heredity 105, 113–121. https://doi.org/10.1038/hdy.2010.25 (2010).CAS 
Article 
PubMed 

Google Scholar 
Zheng, X. et al. Transgenerational variations in DNA methylation induced by drought stress in two rice varieties with distinguished difference to drought resistance. PLoS One 8(11), e80253. https://doi.org/10.1371/journal.pone.0080253 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Karan, R., DeLeon, T., Biradar, H. & Subudhi, P. K. Salt Stress induced variation in DNA methylation pattern and its influence on gene expression in contrasting rice genotypes. PLoS One 7(6), e40203. https://doi.org/10.1371/journal.pone.0040203 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L. & Pigliucci, M. Epigenetic inheritance. A decade into the extended evolutionary synthesis. Paradigmi 38, 463–494. https://doi.org/10.30460/99624 (2020).Article 

Google Scholar 
Chelaifa, H., Monnier, A. & Ainouche, M. Transcriptomic changes following recent natural hybridization and allopolyploidy in the salt marsh species Spartina × townsendii and Spartina anglica (Poaceae). New Phytol. 186(1), 161–174. https://doi.org/10.1111/j.1469-8137.2010.03179.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Al-Lawati, A., Al-Bahry, S., Victor, R., Al-Lawati, A. H. & Yaish, M. W. Salt stress alters DNA methylation levels in alfalfa (Medicago spp.). Genet. Mol. Res. 15, 15018299. https://doi.org/10.4238/gmr.15018299 (2016).CAS 
Article 
PubMed 

Google Scholar 
Lewandowska-Gnatowska, E. et al. Is DNA methylation modulated by wounding-induced oxidative burst in maize?. Plant Physiol. Biochem. 82, 202–208. https://doi.org/10.1016/j.plaphy.2014.06.003 (2014).CAS 
Article 
PubMed 

Google Scholar 
Marfil, C. et al. Changes in grapevine DNA methylation and polyphenols content induced by solar ultraviolet-B radiation, water deficit and abscisic acid spray treatments. Plant Physiol. Biochem. 135, 287–294. https://doi.org/10.1016/j.plaphy.2018.12.021 (2019).CAS 
Article 
PubMed 

Google Scholar 
Zedek, F. et al. Endopolyploidy is a common response to UV-B stress in natural plant populations, but its magnitude may be affected by chromosome type. Ann. Bot. 126(5), 883–889. https://doi.org/10.1093/aob/mcaa109 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pandey, N. & Pandey-Rai, S. Deciphering UV-B-induced variation in DNA methylation pattern and its influence on regulation of DBR2 expression in Artemisia annua L. Planta 242(4), 869–879. https://doi.org/10.1007/s00425-015-2323-3 (2015).CAS 
Article 
PubMed 

Google Scholar 
Molinier, J. Genome and epigenome surveillance processes underlying UV exposure in plants. Genes 8(11), 316. https://doi.org/10.3390/genes8110316 (2017).CAS 
Article 
PubMed Central 

Google Scholar 
Niederhuth, C. E. et al. Widespread natural variation of DNA methylation within angiosperms. Genome Biol. 17, 194. https://doi.org/10.1186/s13059-016-1059-0 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lira-Medeiros, C. F. et al. Epigenetic variation in mangrove plants occurring in contrasting natural environment. PLoS One 5, e10326. https://doi.org/10.1371/journal.pone.0010326 (2010).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richards, C. L., Verhoeven, K. J. F. & Bossdorf, O. Evolutionary significance of epigenetic variation. In Plant Genome Diversity Vol. 1 (eds Wendel, J. F. et al.) 257–274 (Springer Vienna, 2012).Chapter 

Google Scholar 
Paun, O. et al. Stable epigenetic effects impact adaptation in allopolyploid orchids (Dactylorhiza: Orchidaceae). Mol. Biol. Evol. 27, 2465–2473. https://doi.org/10.1093/molbev/msq150 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xie, H. et al. Global DNA methylation patterns can play a role in defining terroir in grapevine (Vitis vinifera cv. Shiraz). Front. Plant Sci. 8, 130398. https://doi.org/10.3389/fpls.2017.01860 (2017).Article 

Google Scholar 
Herrera, C. M. & Bazaga, P. Epigenetic differentiation and relationship to adaptive genetic divergence in discrete populations of the violet Viola cazorlensis. New Phytol. 187(3), 867–876. https://doi.org/10.1111/j.1469-8137.2010.03298.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Portis, E., Acquadro, A., Comino, C. & Lanteri, S. Analysis of DNA methylation during germination of pepper (Capsicum annuum L.) seeds using methylation-sensitive amplification polymorphism (MSAP). Plant Sci. 166, 169–178. https://doi.org/10.1016/j.plantsci.2003.09.004 (2004).CAS 
Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. http://www.R-project.org (R Foundation for Statistical Computing, 2013).Schloerke, B. et al. GGally: Extension to “ggplot2” R package version 2.1.0. https://CRAN.R-project.org/package=GGally (2021).StatSoft, Inc. STATISTICA (Data Analysis Software System), Version 10. http://www.statsoft.com (2011).Tomczyk, P. Phenotypic measurement of inbreeding depression in grasses—An overview of traits (Fenotypowe miary depresji wsobnej u traw—przegląd cech). Wiad. Bot. https://doi.org/10.5586/wb.2019.005 (2019).Article 

Google Scholar 
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315. https://doi.org/10.1002/joc.5086 (2017).Article 

Google Scholar 
Fox, J. & Weisberg, S. An {R} Companion to Applied Regression (Sage Publications, 2019).
Google Scholar  More

Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).ADS 
Article 

Google Scholar 
Andela, N. et al. A human-driven decline in global burned area. Science 356, 1356–1362 (2017).ADS 
CAS 
Article 

Google Scholar 
United Nations Environment Programme. Spreading like Wildfire–The Rising Threat of Extraordinary Landscape Fires. A UNEP Rapid Response Assessment. (United Nations Environment Programme, Nairobi, 2022).Williams, A. P. et al. Observed impacts of anthropogenic climate change on wildfire in California. Earth’s Future 7, 892–910 (2019).ADS 
Article 

Google Scholar 
Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).ADS 
CAS 
Article 

Google Scholar 
Dennison, P. E., Brewer, S. C., Arnold, J. D. & Moritz, M. A. Large wildfire trends in the western United States, 1984–2011. Geophys. Res. Lett. 41, 2928–2933 (2014).ADS 
Article 

Google Scholar 
Westerling, A. L. Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring. Philos. Trans. R. Soc. B: Biol. Sci. 371, 20150178 (2016).Article 

Google Scholar 
Pyne, S. J. Fire in America: A Cultural History of Wildland and Rural Fire. (University of Washington Press, 2017).Fire and Resource Assessment Program. Fire Perimeters. Available: https://frap.fire.ca.gov/frap-projects/fire-perimeters/. (California Department of Forestry & Fire Protection, 2018).Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase Western U.S. forest wildfire activity. Science 313, 940–943 (2006).ADS 
CAS 
Article 

Google Scholar 
Starrs, C. F., Butsic, V., Stephens, C. & Stewart, W. The impact of land ownership, firefighting, and reserve status on fire probability in California. Environ. Res. Lett. 13, 034025 (2018).ADS 
Article 

Google Scholar 
Lydersen, J. M. et al. Evidence of fuels management and fire weather influencing fire severity in an extreme fire event. Ecol. Appl. 27, 2013–2030 (2017).Article 

Google Scholar 
Parsons, D. J. & DeBenedetti, S. H. Impact of fire suppression on a mixed-conifer forest. For. Ecol. Manag. 2, 21–33 (1979).Article 

Google Scholar 
Vose, R., Easterling, D. R., Kunkel, K. & Wehner, M. Temperature Changes in the United States. (NASA, 2017).Balch, J. K. et al. Human-started wildfires expand the fire niche across the United States. Proc. Natl Acad. Sci. USA 114, 2946–2951 (2017).ADS 
CAS 
Article 

Google Scholar 
Stephens, S. L., Martin, R. E. & Clinton, N. E. Prehistoric fire area and emissions from California’s forests, woodlands, shrublands, and grasslands. For. Ecol. Manag. 251, 205–216 (2007).Article 

Google Scholar 
Sugihara, N. G., Van Wagtendonk, J. W., Fites-Kaufman, J., Shaffer, K. E. & Thode, A. E. Fire in California’s Ecosystems. (University of California Press, 2006).Jin, Y. et al. Identification of two distinct fire regimes in Southern California: implications for economic impact and future change. Environ. Res. Lett. 10, 094005 (2015).ADS 
Article 

Google Scholar 
Trollope, W. in Ecological Effects of Fire In South African Ecosystems. 199–217 (Springer, 1984).Byram, G. M. in Forest Fire: Control and Use (ed. Davis, K. P.) 155–182 (McGraw-Hill, 1959).McLauchlan, K. K. et al. Fire as a fundamental ecological process: Research advances and frontiers. J. Ecol. https://doi.org/10.1111/1365-2745.13403 (2020).Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl Acad. Sci. USA 111, 6347–6352 (2014).ADS 
CAS 
Article 

Google Scholar 
Schroeder, W., Oliva, P., Giglio, L. & Csiszar, I. A. The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment. Remote Sens. Environ. 143, 85–96 (2014).ADS 
Article 

Google Scholar 
Rothermel, R. C. A Mathematical Model for Predicting Fire Spread in Wildland Fuels (USFS, 1972).Hood, S. M., Varner, J. M., van Mantgem, P. & Cansler, C. A. Fire and tree death: understanding and improving modeling of fire-induced tree mortality. Environ. Res. Lett. 13, 113004 (2018).ADS 
Article 

Google Scholar 
Cattau, M. E., Wessman, C., Mahood, A., Balch, J. K. & Poulter, B. Anthropogenic and lightning‐started fires are becoming larger and more frequent over a longer season length in the USA. Glob. Ecol. Biogeogr. 29, 668–681 (2020).Article 

Google Scholar 
Abatzoglou, J. T., Balch, J. K., Bradley, B. A. & Kolden, C. A. Human-related ignitions concurrent with high winds promote large wildfires across the USA. Int. J. Wildland Fire 27, 377–386 (2018).Article 

Google Scholar 
Fried, J. S. et al. Predicting the effect of climate change on wildfire behavior and initial attack success. Clim. Change 87, 251–264 (2008).Article 

Google Scholar 
van Wagtendonk, J. W. The history and evolution of wildland fire use. Fire Ecol. 3, 3–17 (2007).Article 

Google Scholar 
Sullivan, A. L. Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models. Int. J. Wildland Fire 18, 369–386 (2009).Article 

Google Scholar 
Wang, X. et al. Projected changes in fire size from daily spread potential in Canada over the 21st century. Environ. Res. Lett. 15, 104048 (2020).ADS 
Article 

Google Scholar 
Parks, S. A. et al. High-severity fire: evaluating its key drivers and mapping its probability across western US forests. Environ. Res. Lett. 13, 044037 (2018).ADS 
Article 

Google Scholar 
Hantson, S. et al. The status and challenge of global fire modelling. Biogeosciences 13, 3359–3375 (2016).ADS 
Article 

Google Scholar 
Reinhardt, E. D. First Order Fire Effects Model: FOFEM 4.0, User’s Guide. (Intermountain Forest and Range Experiment Station, Forest Service, US …, 1997).Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6, 1–11 (2015).CAS 
Article 

Google Scholar 
Pateiro-Lopez, B. & Rodriguez-Casal, A. alphahull: Generalization of the Convex Hull of a Sample of Points in the Plane v. R package version 2.2 (2019).Edelsbrunner, H., Kirkpatrick, D. & Seidel, R. On the shape of a set of points in the plane. IEEE Trans. Inf. theory 29, 551–559 (1983).MathSciNet 
Article 

Google Scholar 
Rodríguez Casal, A. & Pateiro López, B. Generalizing the Convex Hull of A Sample: the R Package alphahull. (2010).Bell, D. M. et al. Multiscale divergence between Landsat-and lidar-based biomass mapping is related to regional variation in canopy cover and composition. Carbon Balance Manag. 13, 15 (2018).Article 

Google Scholar 
Abatzoglou, J. T. Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol. 33, 121–131 (2013).Article 

Google Scholar 
MTBS. Monitoring Trends in Burn Severity Data Access: Fire Level Geospatial Data. (MTBS). (2018).Miller, J. D. et al. Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sens. Environ. 113, 645–656 (2009).ADS 
Article 

Google Scholar 
Homer, C. et al. Completion of the 2011 National Land Cover Database for the conterminous United States–representing a decade of land cover change information. Photogrammetric Eng. Remote Sens. 81, 345–354 (2015).
Google Scholar  More

Baker, R. W. Membrane Technology and Applications. 3rd edn. ISBN 9780470743720. (Wiley, 2012).Wang, L. K., Chen, J. P., Hung, Y.-T., Shammas, N. K. Membrane and Desalination Technologies. ISBN 978-1-58829-940-6. (Humana Press, 2011).Mahmoudi, E. et al. Enhancing morphology and separation performance of polyamide 6,6 membranes by minimal incorporation of silver decorated graphene oxide nanoparticles. Sci. Rep. 9, 1216. https://doi.org/10.1038/s41598-018-38060-x (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Penkova, A. V., Dmitrenko, M. E., Ermakov, S. S., Toikka, A. M. & Roizard, D. Novel green PVA-fullerenol mixed matrix supported membranes for separating water-THF mixtures by pervaporation. Environ. Sci. Pollut. Res. 25, 20354–20362. https://doi.org/10.1007/s11356-017-9063-9 (2018).CAS 
Article 

Google Scholar 
Atlaskin, A. A. et al. Comprehensive experimental study of membrane cascades type of “continuous membrane column” for gases high-purification. J. Membr. Sci. 572, 92–101. https://doi.org/10.1016/j.memsci.2018.10.079 (2019).CAS 
Article 

Google Scholar 
Koyuncu, I., Sengur, R., Turken, T., Guclu, S., & Pasaoglu, M.E. Advances in water treatment by microfiltration, ultrafiltration, and nanofiltration. in Advances in Membrane Technologies for Water Treatment (eds. Basile, A., Cassano, A., Rastogi, N. K.). 83–128. (Elsevier, 2015).Van der Bruggen, B. Microfiltration, ultrafiltration, nanofiltration, reverse osmosis, and forward osmosis in Fundamental Modelling of Membrane Systems, Membrane and Process Performance (ed. Luis, P.). 25–70. (Elsevier, 2018).Al Aani, S., Mustafa, T. N. & Hilal, N. Ultrafiltration membranes for wastewater and water process engineering: A comprehensive statistical review over the past decade. J. Water Process Eng. 35, 101241. https://doi.org/10.1016/j.jwpe.2020.101241 (2020).Article 

Google Scholar 
Polotskaya, G. A., Goikhman, M. Y., Podeshvo, I. V., Polotsky, A. E. & Cherkasov, A. N. Polybenzoxazinoneimides and their prepolymers as promising membrane materials. Desalination 200, 46–48 (2006).CAS 
Article 

Google Scholar 
Ulbricht, M. Advanced functional polymer membranes. Polymer 47, 2217–2262. https://doi.org/10.1016/j.polymer.2006.01.084 (2006).CAS 
Article 

Google Scholar 
Siagian, U. W. R. et al. High-performance ultrafiltration membrane: Recent progress and its application for wastewater treatment. Curr. Pollut. Rep. 7, 448–462. https://doi.org/10.1007/s40726-021-00204-5 (2021).CAS 
Article 

Google Scholar 
Polotskaya, G. A., Meleshko, T. K., Gofman, I. V., Polotsky, A. E. & Cherkasov, A. N. Polyimide ultrafiltration membranes with high thermal stability and chemical durability. Sep. Sci. Technol. 44, 3814–3831. https://doi.org/10.1080/01496390903256166 (2009).CAS 
Article 

Google Scholar 
Ohya, H., Kudryavtsev, V. V., & Semenova, S. I. Polyimide Membranes. Vol. 314. (Gordon & Breach Publishers, 1996).Liu, R., Qiao, X. & Chung, T.-S. The development of high performance P84 co-polyimide hollow fibers for pervaporation dehydration of isopropanol. Chem. Eng. Sci. 60, 6674–6686. https://doi.org/10.1016/j.ces.2005.05.066 (2005).CAS 
Article 

Google Scholar 
Yang, C. et al. Preparation and characterization of acid and solvent resistant polyimide ultrafiltration membrane. Appl. Surf. Sci. 483, 278–284. https://doi.org/10.1016/j.apsusc.2019.03.226 (2019).ADS 
CAS 
Article 

Google Scholar 
Pulyalina, AYu., Polotskaya, G. A. & Toikka, A. M. Membrane materials based on polyheteroarylenes and their application for pervaporation. Russ. Chem. Rev. 85(1), 81–98 (2016).ADS 
CAS 
Article 

Google Scholar 
Volgin, I. V. et al. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11, 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Pulyalina, A. et al. Preparation and characterization of methanol selective membranes based on polyheteroarylene–Cu(I) complexes for purification of methyl tertiary butyl ether. Polym. Int. 66(12), 1873–1882. https://doi.org/10.1002/pi.5463 (2017).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Sorption and transport of aqueous isopropanol solutions in polyimide-poly(aniline-co-anthranilic acid) composites. Russ. J. Appl. Chem. 84(5), 840–846. https://doi.org/10.1134/S107042721105017X (2011).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Novel approach to determination of sorption in pervaporation process: A case study of isopropanol dehydration by polyamidoimide urea membranes. Sci. Rep. 7, 8415. https://doi.org/10.1038/s41598-017-08420-0 (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Helali, N., Shamaei, L., Rastgar, M. & Sadrzadeh, M. Development of layer-by-layer assembled polyamide-imide membranes for oil sands produced water treatment. Sci. Rep. 11, 8098. https://doi.org/10.1038/s41598-021-87601-4 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Polotskaya, G. et al. Asymmetric membranes based on copolyheteroarylenes with imide, biquinoline, and oxazinone units: Formation and characterization. Polymers 11(10), 1542. https://doi.org/10.3390/polym11101542 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Volgin, I. V. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11(11), 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
White, L. S. Transport properties of a polyimide solvent resistant nanofiltration membrane. J. Membr. Sci. 205, 191–202 (2005).Article 

Google Scholar 
Barsema, J. N., Kapantaidakis, G. C., van der Vegt, N. F. A., Koops, G. H. & Wessling, M. Preparation and characterization of highly selective dense and hollow fiber asymmetric membranes based on BTDA-TDI/MDI co-polyimide. J. Membr. Sci. 216, 195–205. https://doi.org/10.1016/S0376-7388(03)00071-1 (2003).CAS 
Article 

Google Scholar 
Pulyalina, A., Polotskaya, G., Rostovtseva, V., Pientka, Z. & Toikka, A. Improved hydrogen separation using hybrid membrane composed of nanodiamonds and P84 copolyimide. Polymers 10, 828. https://doi.org/10.3390/polym10080828 (2018).CAS 
Article 
PubMed Central 

Google Scholar 
Qiao, X. & Chung, T.-S. Fundamental characteristics of sorption, swelling, and permeation of P84 co-polyimide membranes for pervaporation dehydration of alcohols. Ind. Eng. Chem. Res. 44, 8938–8943. https://doi.org/10.1021/ie050836g (2005).CAS 
Article 

Google Scholar 
Mangindaan, D. W., Shi, G. M. & Chung, T.-S. Pervaporation dehydration of acetone using P84 co-polyimide flat sheet membranes modified by vapor phase crosslinking. J. Membr. Sci. 458, 76–85 (2014).CAS 
Article 

Google Scholar 
Hua, D., Ong, Y. K., Wang, Y., Yang, T. & Chung, T.-S. ZIF-90/P84 mixed matrix membranes for pervaporation dehydration of isopropanol. J. Membr. Sci. 453, 155–167. https://doi.org/10.1016/j.memsci.2013.10.059 (2014).CAS 
Article 

Google Scholar 
Pulyalina, AYu., Putintseva, M. N., Polotskaya, G. A., Rostovtseva, V. A. & Toikka, A. M. Pervaporation purification of oxygenate from an ethyl tert-butyl ether/ethanol azeotropic mixture. Membr. Membr. Technol. 1(2), 99–106. https://doi.org/10.1134/S2517751619020082 (2019).CAS 
Article 

Google Scholar 
Ren, J. & Li, Z. Development of asymmetric BTDA-TDI/MDI (P84) copolyimide flat sheet and hollow fiber membranes for ultrafiltration: Morphology transition and membrane performance. Desalination 285, 336–344. https://doi.org/10.1016/j.desal.2011.10.024 (2012).CAS 
Article 

Google Scholar 
Ren, J., Li, Z., Wong, F.-S. & Li, D. Development of asymmetric BTDA-TDI/MDI (P84) co-polyimide hollow fiber membranes for ultrafiltration: The influence of shear rate and approaching ratio on membrane morphology and performance. J. Membr. Sci. 248, 177–188. https://doi.org/10.1016/j.memsci.2004.09.031 (2005).CAS 
Article 

Google Scholar 
Yusoff, I. I. et al. Durable pressure filtration membranes based on polyaniline-polyimide P84 blends. Polym. Eng. Sci. 5(S1), E82–E92 (2019).Article 

Google Scholar 
Grosso, V. et al. Polymeric and mixed matrix polyimide membranes. Sep. Purif. Technol. 132, 684–696 (2014).CAS 
Article 

Google Scholar 
Renner, R. Ionic liquids: An industrial cleanup solution. Environ. Sci. Technol. 35, 410a–413a (2001).ADS 
CAS 
Article 

Google Scholar 
Wanga, H. H. A novel green solvent alternative for polymeric membrane preparation via nonsolvent-induced phase separation (NIPS). J. Membr. Sci. 574, 44–54 (2019).Article 

Google Scholar 
Lessan, F. & Foudazi, R. Effect of [EMIM][BF4] ionic liquid on the properties of ultrafiltration membranes. Polymer 210, 122977 (2020).CAS 
Article 

Google Scholar 
Xing, D. Y., Peng, N. & Chung, T.-S. Formation of cellulose acetate membranes via phase inversion using ionic liquid, [BMIM]SCN, as the solvent. Ind. Eng. Chem. Res. 49, 8761–8769 (2010).CAS 
Article 

Google Scholar 
Durmaz, E. N. & Çulfaz-Emecen, P. Z. Cellulose-based membranes via phase inversion using [EMIM]OAc-DMSO mixtures as solvent. Chem. Eng. Sci. 178, 93–103 (2018).CAS 
Article 

Google Scholar 
Grekov, K. B. Electronic Waste and Safety Problems (in Rus.). ISBN 9785891601796. (SUT, 2018).Svittsov, A. A. & Abylgaziev, TZh. Micellarly enhanced (reagent) ultrafiltration. Russ. Chem. Rev. 60(11), 1280–1283 (1991).ADS 
Article 

Google Scholar 
Petrov, S. & Stoichev, P. A. Reagent ultrafiltration purification of water contaminated with reactive dyes. Filtr. Sep. https://doi.org/10.1016/S0015-1882(02)80229-4 (2002).Article 

Google Scholar 
Leonard, M. A. & West, T. S. Chelating reactions of 1,2-dihydroxyanthraquinon-3-ylmethyl-amine-NN-diacetic acid with metal cations in aqueous media. J. Chem. Soc. 866, 4477–4486. https://doi.org/10.1039/jr9600004477 (1960).Article 

Google Scholar 
Marczenko, Z., & Balcerzak, M. Fluorine. in Separation, Preconcentration and Spectrophotometry in Inorganic Analysis (ed. Kloczko, E.). 189–197. (Elsevier, 2000).Chai, J.-D. & Head-Gordon, M. Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections. Phys. Chem. Chem. Phys. 10, 6615–6620. https://doi.org/10.1039/B810189B (2008).CAS 
Article 
PubMed 

Google Scholar 
Frisch, M. J. et al. Gaussian 09, Revision C.01. (Gaussian, Inc., 2010).Ochterski, J. W. Thermochemistry in Gaussian. https://gaussian.com/thermo/ (2000).Cherkasov, A. N. A rapid analysis of ultrafiltration membrane structure. Sep. Sci. Tech. 40, 2775–2801. https://doi.org/10.1080/01496390500333111 (2005).CAS 
Article 

Google Scholar 
Zheng, Q.-Z. The relationship between porosity and kinetics parameter of membrane formation in PSF ultrafiltration membrane. J. Membr. Sci. 286, 7–11 (2006).CAS 
Article 

Google Scholar 
Barton, A. F. M. CRC Handbook of Solubility Parameter. Vol. 768. (CRC Press, 1991).Tan, X. & Rodrigue, D. A review on porous polymeric membrane preparation. Part I: Production techniques with polysulfone and poly (vinylidene fluoride). Polymers 11, 1160 (2019).Article 

Google Scholar 
Mulder, M. H. V. Phase Inversion Membranes. Membrane Preparation. Vol. 3331. (Academic Press, 2000).Quijada-Maldonado, E. Pilot plant study on the extractive distillation of toluene–methylcyclohexane mixtures using NMP and the ionic liquid [hmim][TCB] as solvents. Sep. Purif. Technol. 166, 196–204 (2016).CAS 
Article 

Google Scholar 
Polotskaya, G. A. et al. Aromatic copolyamides with anthrazoline units in the backbone: Synthesis, characterization, pervaporation application. Polymers 8(10), 362. https://doi.org/10.3390/polym8100362 (2016).CAS 
Article 
PubMed Central 

Google Scholar 
Mao, J. X. Interactions in 1-ethyl-3-methyl imidazolium tetracyanoborate ion pair: Spectroscopic and density functional study. J. Mol. Struct. 1038, 12–18 (2013).ADS 
CAS 
Article 

Google Scholar  More

Wedding, L. M. et al. From principles to practice: a spatial approach to systematic conservation planning in the deep sea. Proc. R. Soc. B Biol. Sci. 280, 20131684 (2013).CAS 
Article 

Google Scholar 
Kaiser, S., Smith, C. R. & MartínezArbizu, P. Editorial: Biodiversity of the Clarion Clipperton Fracture Zone. Mar. Biodivers. 47, 259–264 (2017).Article 

Google Scholar 
Bluhm, H. Monitoring megabenthic communities in abyssal manganese nodule sites of the East Pacific Ocean in association with commercial deep-sea mining. Aquat. Conserv. Mar. Freshw. Ecosyst. 4, 187–201 (1994).Article 

Google Scholar 
Simon-Lledó, E. et al. Multi-scale variations in invertebrate and fish megafauna in the mid-eastern Clarion Clipperton Zone. Prog. Oceanogr. 187, 102405 (2020).Article 

Google Scholar 
Simon-Lledó, E. et al. Megafaunal variation in the abyssal landscape of the Clarion Clipperton Zone. Prog. Oceanogr. 170, 119–133 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hein, J. R., Mizell, K., Koschinsky, A. & Conrad, T. A. Deep-ocean mineral deposits as a source of critical metals for high- and green-technology applications: Comparison with land-based resources. Ore Geol. Rev. 51, 1–14 (2013).Article 

Google Scholar 
Kuhn, T., Wegorzewski, A., Rühlemann, C. & Vink, A. Composition, formation, and occurrence of polymetallic nodules. In Deep-Sea Mining: Resource Potential Technical and Environmental Considerations (ed. Sharma, R.) 23–63 (Springer, 2017). https://doi.org/10.1007/978-3-319-52557-0_2.Chapter 

Google Scholar 
Simon-Lledó, E. et al. Ecology of a polymetallic nodule occurrence gradient: Implications for deep-sea mining. Limnol. Oceanogr. 64, 1883–1894 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
International Seabed Authority. Deep Seabed Minerals Contractors. https://www.isa.org.jm/deep-seabed-minerals-contractors?qt-contractors_tabs_alt=0#qt-contractors_tabs_alt (2020).Jones, D. O. B. et al. Biological responses to disturbance from simulated deep-sea polymetallic nodule mining. PLoS ONE 12, e0171750 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Niner, H. J. et al. Deep-sea mining with no net loss of biodiversity: An impossible aim. Front. Mar. Sci. 5, 53 (2018).ADS 
Article 

Google Scholar 
Kuhn, T., Uhlenkott, K., Vink, A., Rühlemann, C. & MartínezArbizu, P. Manganese nodule fields from the Northeast Pacific as benthic habitats. In Seafloor Geomorphology as Benthic Habitat: GeoHab Atlas of Seafloor Geomorphic Features and Benthic Habitats (eds Harris, P. T. & Baker, E.) 933–947 (Elsevier, 2020).Chapter 

Google Scholar 
Vanreusel, A., Hilario, A., Ribeiro, P. A., Menot, L. & Martínez Arbizu, P. Threatened by mining, polymetallic nodules are required to preserve abyssal epifauna. Sci. Rep. 6, 26808 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Amon, D. J. et al. Insights into the abundance and diversity of abyssal megafauna in a polymetallic-nodule region in the eastern Clarion-Clipperton Zone. Sci. Rep. 6, 30492 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
De Forges, B. R., Koslow, J. A. & Poore, G. C. B. Diversity and endemism of the benthic seamount fauna in the southwest Pacific. Nature 405, 944–947 (2000).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Lodge, M. et al. Seabed mining: International Seabed Authority environmental management plan for the Clarion-Clipperton Zone: A partnership approach. Mar. Policy 49, 66–72 (2014).Article 

Google Scholar 
Cuvelier, D. et al. Are seamounts refuge areas for fauna from polymetallic nodule fields?. Biogeosciences 17, 2657–2680 (2020).ADS 
Article 

Google Scholar 
Wedding, L. M. et al. Managing mining of the deep seabed. Science 349, 144–145 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
International Seabed Authority. Decision of the Council of the International Seabed Authority relating to amendments to the Regulations on the Prospecting and Exploration for Polymetallic Nodules in the Area and related matters. (2013).International Seabed Authority. Recommendations for the guidance of contractors for the assessment of the possible environmental impacts arising from exploration for marine minerals in the Area. (2020).Jones, D. O. B., Ardron, J. A., Colaço, A. & Durden, J. M. Environmental considerations for impact and preservation reference zones for deep-sea polymetallic nodule mining. Mar. Policy 118, 103312 (2020).Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T. & Martínez Arbizu, P. Predicting meiofauna abundance to define preservation and impact zones in a deep-sea mining context using random forest modelling. J. Appl. Ecol. 57, 1210–1221 (2020).Article 

Google Scholar 
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 
Article 

Google Scholar 
Ostmann, A. & Martínez Arbizu, P. Predictive models using random forest regression for distribution patterns of meiofauna in Icelandic waters. Mar. Biodivers. 48, 719–735 (2018).Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T., Gillard, B. & Martínez Arbizu, P. Meiofauna in a potential deep-sea mining area: Influence of temporal and spatial variability on small scale abundance models. Diversity 13, 3 (2021).CAS 
Article 

Google Scholar 
Gazis, I.-Z., Schoening, T., Alevizos, E. & Greinert, J. Quantitative mapping and predictive modeling of Mn nodules’ distribution from hydroacoustic and optical AUV data linked by random forests machine learning. Biogeosciences 15, 7347–7377 (2018).ADS 
Article 

Google Scholar 
Ellis, N., Smith, S. J. & Pitcher, C. R. Gradient forests: Calculating importance gradients on physical predictors. Ecology 93, 156–168 (2012).PubMed 
Article 

Google Scholar 
Miljutina, M. A., Miljutin, D. M., Mahatma, R. & Galéron, J. Deep-sea nematode assemblages of the Clarion-Clipperton Nodule Province (Tropical North-Eastern Pacific). Mar. Biodivers. 40, 1–15 (2010).Article 

Google Scholar 
Miljutin, D., Miljutina, M. & Messié, M. Changes in abundance and community structure of nematodes from the abyssal polymetallic nodule field, Tropical Northeast Pacific. Deep Sea Res. Oceanogr. Res. Pap. 106, 126–135 (2015).ADS 
Article 

Google Scholar 
Pape, E., Bezerra, T. N., Hauquier, F. & Vanreusel, A. Limited spatial and temporal variability in meiofauna and nematode communities at distant but environmentally similar sites in an area of interest for deep-sea mining. Front. Mar. Sci. 4, 205 (2017).Article 

Google Scholar 
Hauquier, F. et al. Distribution of free-living marine nematodes in the Clarion-Clipperton Zone: Implications for future deep-sea mining scenarios. Biogeosciences 16, 3475–3489 (2019).ADS 
CAS 
Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T. & Martínez Arbizu, P. Meiofauna abundance and distribution predicted with random forest regression in the German exploration area for polymetallic nodule mining, Clarion Clipperton Fracture Zone, Pacific. (2020).Calinski, T. & Harabasz, J. A dendrite method for cluster analysis. Commun. Stat. Theory Methods 3, 1–27 (1974).MathSciNet 
MATH 
Article 

Google Scholar 
Thiel, H. et al. The large-scale environmental impact experiment DISCOL: Reflection and foresight. Deep Sea Res. 48, 3869–3882 (2001).ADS 
Article 

Google Scholar 
Brown, A., Wright, R., Mevenkamp, L. & Hauton, C. A comparative experimental approach to ecotoxicology in shallow-water and deep-sea holothurians suggests similar behavioural responses. Aquat. Toxicol. 191, 10–16 (2017).CAS 
PubMed 
Article 

Google Scholar 
McClain, C. R. Seamounts: identity crisis or split personality?. J. Biogeogr. 34, 2001–2008 (2007).Article 

Google Scholar 
Rogers, A. D. The biology of seamounts: 25 years on. In Advances in Marine Biology Vol. 79 (ed. Sheppard, C.) 137–224 (Academic Press, 2018).
Google Scholar 
Durden, J. M., Bett, B. J., Jones, D. O. B., Huvenne, V. A. I. & Ruhl, H. A. Abyssal hills–hidden source of increased habitat heterogeneity, benthic megafaunal biomass and diversity in the deep sea. Prog. Oceanogr. 137, 209–218 (2015).ADS 
Article 

Google Scholar 
Durden, J. M. et al. Megafaunal ecology of the western Clarion Clipperton Zone. Front. Mar. Sci. 8, 671062 (2021).ADS 
Article 

Google Scholar 
Jones, D. O. B. et al. Environment, ecology, and potential effectiveness of an area protected from deep-sea mining (Clarion Clipperton Zone, abyssal Pacific). Prog. Oceanogr. 197, 102653 (2021).Article 

Google Scholar 
Lutz, M. J., Caldeira, K., Dunbar, R. B. & Behrenfeld, M. J. Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. J. Geophys. Res. Oceans 112, C10011 (2007).ADS 
Article 
CAS 

Google Scholar 
Volz, J. B. et al. Natural spatial variability of depositional conditions, biogeochemical processes and element fluxes in sediments of the eastern Clarion-Clipperton Zone. Pacific Ocean. Deep Sea Res. 140, 159–172 (2018).CAS 
Article 

Google Scholar 
Smith, C. R., De Leo, F. C., Bernardino, A. F., Sweetman, A. K. & Martínez Arbizu, P. Abyssal food limitation, ecosystem structure and climate change. Trends Ecol. Evol. 23, 518–528 (2008).PubMed 
Article 

Google Scholar 
Ramirez-Llodra, E. et al. Deep, diverse and definitely different: unique attributes of the world’s largest ecosystem. Biogeosciences 7, 2851–2899 (2010).ADS 
Article 

Google Scholar 
Kharbush, J. J. et al. Particulate organic carbon deconstructed: Molecular and chemical composition of particulate organic carbon in the ocean. Front. Mar. Sci. 7, 518 (2020).Article 

Google Scholar 
Smith, C. R. et al. Latitudinal variations in benthic processes in the abyssal equatorial Pacific: Control by biogenic particle flux. Deep Sea Res. 44, 2295–2317 (1997).ADS 
CAS 
Article 

Google Scholar 
Kuhn, T. & Rühlemann, C. Exploration of polymetallic nodules and resource assessment: A case study from the German contract area in the Clarion-Clipperton Zone of the tropical Northeast Pacific. Minerals 11, 618 (2021).ADS 
CAS 
Article 

Google Scholar 
Christodoulou, M. et al. Unexpected high abyssal ophiuroid diversity in polymetallic nodule fields of the northeast Pacific Ocean and implications for conservation. Biogeosciences 17, 1845–1876 (2020).ADS 
CAS 
Article 

Google Scholar 
Valavi, R., Elith, J., Lahoz-Monfort, J. J. & Guillera-Arroita, G. Modelling species presence-only data with random forests. Ecography 44, 1731–1742 (2021).Article 

Google Scholar 
Wiedicke-Hombach, M. & Shipboard Scientific Party. Campaign “MANGAN 2008” with R/V Kilo Moana. (2009).Hijmans, R. J. raster: Geographic Data Analysis and Modeling. (2017).Kaufman, L. & Rousseeuw, P. J. Clustering Large Applications (Program CLARA). in Finding Groups in Data 126–163 (Wiley, 1990). https://doi.org/10.1002/9780470316801.ch3.Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M. & Hornik, K. cluster. (2019).Langenkämper, D., Zurowietz, M., Schoening, T. & Nattkemper, T. W. BIIGLE 2.0: Browsing and annotating large marine image collections. Front. Mar. Sci. 4, 83 (2017).Article 

Google Scholar 
Simon-Lledó, E. et al. Preliminary observations of the abyssal megafauna of Kiribati. Front. Mar. Sci. 6, 605 (2019).Article 

Google Scholar 
Amon, D. J. et al. Megafauna of the UKSRL exploration contract area and eastern Clarion-Clipperton Zone in the Pacific Ocean: Annelida, Arthropoda, Bryozoa, Chordata, Ctenophora, Mollusca. Biodivers. Data J. 5, e14598 (2017).Article 

Google Scholar 
Molodtsova, T. N. & Opresko, D. M. Black corals (Anthozoa: Antipatharia) of the Clarion-Clipperton Fracture Zone. Mar. Biodivers. 47, 349–365 (2017).Article 

Google Scholar 
Kersken, D., Janussen, D. & MartínezArbizu, P. Deep-sea glass sponges (Hexactinellida) from polymetallic nodule fields in the Clarion-Clipperton Fracture Zone (CCFZ), northeastern Pacific: Part II—Hexasterophora. Mar. Biodivers. 49, 947–987 (2019).Article 

Google Scholar 
Horton, T. et al. Recommendations for the standardisation of open taxonomic nomenclature for image-based identifications. Front. Mar. Sci. 8, 620702 (2021).Article 

Google Scholar 
Hughes, J. A. & Gooday, A. J. Associations between living benthic foraminifera and dead tests of Syringammina fragilissima (Xenophyophorea) in the Darwin Mounds region (NE Atlantic). Deep Sea Res. 51, 1741–1758 (2004).Article 

Google Scholar 
Liaw, A. & Wiener, M. Classification and regression by random Forest. R News 2, 18–22 (2002).
Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. (2019).R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2019).Wickham, H. Reshaping data with the reshape package. J. Stat. Softw. 21, 1–20 (2007).Article 

Google Scholar 
Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29 (2011).
Google Scholar 
Garnier, S. viridisLite: Default Color Maps from ‘matplotlib’ (Lite Version). (2018).Rabosky, A. R. D. et al. Coral snakes predict the evolution of mimicry across New World snakes. Nat. Commun. 7, 1–9 (2016).
Google Scholar 
Smith, M. R. Ternary: An R package for creating ternary plots. Zenodo https://doi.org/10.5281/zenodo.1068996 (2017). More