More stories

  • in

    Globally invariant metabolism but density-diversity mismatch in springtails

    Data reportingThe data underpinning this study is a compilation of existing datasets and therefore, no statistical methods were used to predetermine sample size, the experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. The measurements were taken from distinct samples, repeated measurements from the same sites were averaged in the main analysis.Inclusion & ethicsData were primarily collected from individual archives of contributing co-authors. The data collection initiative was openly announced via the mailing list of the 10th International Seminar on Apterygota and via social media (Twitter, Researchgate). In addition, colleagues from less explored regions (Africa, South America) were contacted via personal networks of the initial authors group and literature search. All direct data providers who collected and standardised the data were invited as co-authors with defined minimum role (data provision and cleaning, manuscript editing and approval). For unpublished data, people who were directly involved in sorting and identification of springtails, including all local researchers, were invited as co-authors. Principal investigators were normally not included as co-authors, unless they contributed to conceptualisation and writing of the manuscript. All co-authors were informed and invited to contribute throughout the research process—from the study design and analysis to writing and editing. The study provided an inclusive platform for researchers around the globe to network, share and test their research ideas.Data acquisitionBoth published and unpublished data were collected, using raw data whenever possible entered into a common template. In addition, data available from Edaphobase47 was included. The following minimum set of variables was collected: collectors, collection method (including sampling area and depth), extraction method, identification precision and resources, collection date, latitude and longitude, vegetation type (generalized as grassland, scrub, woodland, agriculture and other for the analysis), and abundances of springtail taxa found in each soil sample (or sampling site). Underrepresented geographical areas (Africa, South America, Australia and Southeast Asia) were specifically targeted by a literature search in the Web of Science database using the keywords ‘springtail’ or ‘Collembola’, ‘density’ or ‘abundance’ or ‘diversity’, and the region of interest; data were acquired from all found papers if the minimum information listed above was provided. All collected datasets were cleaned using OpenRefine v3.3 (https://openrefine.org) to remove inconsistencies and typos. Geographical coordinates were checked by comparing the dataset descriptions with the geographical coordinates. In total, 363 datasets comprising 2783 sites were collected and collated into a single dataset (Supplementary Fig. 1).Calculation of community parametersCommunity parameters were calculated at the site level. Here, we defined a site as a locality that hosts a defined springtail community, is covered by a certain vegetation type, with a certain management, and is usually represented by a sampling area of up to a hundred metres in diameter, making species co-occurrence and interactions plausible. To calculate density, numerical abundance in all samples was averaged and recalculated per square metre using the sampling area. Springtail communities were assessed predominantly during active vegetation periods (i.e., spring, summer and autumn in temperate and boreal biomes, and summer in polar biomes). Our estimations of community parameters therefore refer to the most favourable conditions (peak yearly densities). This seasonal sampling bias is likely to have little effect on our conclusions, since most springtails survive during cold periods38,48. Finally, we used mean annual soil temperatures49 to estimate the seasonal mean community metabolism (described below) and tested for the seasonal bias in additional analysis (see Linear mixed-effects models).All data analyses were conducted in R v. 4.0.250 with RStudio interface v. 1.4.1103 (RStudio, PBC). Data was transformed and visualised with tidyverse packages51,52, unless otherwise mentioned. Background for the global maps was acquired via the maps package53,54. To calculate local species richness, we used data identified to species or morphospecies level (validated by the expert team). Since the sampling effort varied among studies, we extrapolated species richness using rarefaction curves based on individual samples with the Chao estimator51,52 in the vegan package53. For some sites, sample-level data were not available in the original publications, but site-level averages were provided, and an extensive sampling effort was made. In such cases, we predicted extrapolated species richness based on the completeness (ratio of observed to extrapolated richness) recorded at sites where sample-level data were available (only sites with 5 or more samples were used for the prediction). We built a binomial model to predict completeness in sites where no sample-level data were available using latitude and the number of samples taken at a site as predictors: glm(Completeness~N_samples*Latitude). We found a positive effect of the number of samples (Chisq = 1.97, p = 0.0492) and latitude (Chisq = 2.07, p = 0.0391) on the completeness (Supplementary Figs. 17–19). We further used this model to predict extrapolated species richness on the sites with pooled data (435 sites in Europe, 15 in Australia, 6 in South America, 4 in Asia, and 3 in Africa).To calculate biomass, we first cross-checked all taxonomic names with the collembola.org checklist55 using fuzzy matching algorithms (fuzzyjoin R package56) to align taxonomic names and correct typos. Then we merged taxonomic names with a dataset on body lengths compiled from the BETSI database57, a personal database of Matty P. Berg, and additional expert contributions. We used average body lengths for the genus level (body size data on 432 genera) since data at the species level were not available for many morphospecies (especially in tropical regions), and species within most springtail genera had similar body size ranges. Data with no genus-level identifications were excluded from the analysis. Dry and fresh body masses were calculated from body length using a set of group-specific length-mass regressions (Supplementary Table 1)58,59 and the results of different regressions applied to the same morphogroup were averaged. Dry mass was recalculated to fresh mass using corresponding group-specific coefficients58. We used fresh mass to calculate individual metabolic rates60 and account for the mean annual topsoil (0–5 cm) temperature at a given site61. Group-specific metabolic coefficients for insects (including springtails) were used for the calculation: normalization factor (i0) ln(21.972) [J h−1], allometric exponent (a) 0.759, and activation energy (E) 0.657 [eV]60. Community-weighted (specimen-based) mean individual dry masses and metabolic rates were calculated for each sample and then averaged by site after excluding 10% of maximum and 10% of minimum values to reduce impact of outliers. To calculate site-level biomass and community metabolism, we summed masses or metabolic rates of individuals, averaged them across samples, and recalculated them per unit area (m2).Parameter uncertaintiesOur biomass and community metabolism approximations contain several assumptions. To account for the uncertainty in the length-mass and mass-metabolism regression coefficients, in addition to the average coefficients, we also used maximum (average + standard error) and minimum coefficients (average—standard error; Supplementary Table 1) in all equations to calculate maximum and minimum estimations of biomass and community metabolism reported in the main text. Further, we ignored latitudinal variation in body sizes within taxonomic groups62. Nevertheless, latitudinal differences in springtail density (30-fold), environmental temperature (from −16.0 to +27.6 °C in the air and from −10.2 to +30.4 °C in the soil), and genus-level community compositions (there are only few common genera among polar regions and the tropics)55 are higher than the uncertainties introduced by indirect parameter estimations, which allowed us to detect global trends. Although most springtails are concentrated in the litter and uppermost soil layers20, their vertical distribution depends on the particular ecosystem63. Since sampling methods are usually ecosystem-specific (i.e. sampling is done deeper in soils with developed organic layers), we treated the methods used by the original data collectors as representative of a given ecosystem. Under this assumption, we might have underestimated the number of springtails in soils with deep organic horizons, so our global estimates are conservative and we would expect true global density and biomass to be slightly higher. To minimize these effects, we excluded sites where the estimations were likely to be unreliable (see data selection below).Data selectionOnly data collection methods allowing for area-based recalculation (e.g. Tullgren or Berlese funnels) were used for analysis. Data from artificial habitats, coastal ecosystems, caves, canopies, snow surfaces, and strong experimental manipulations beyond the bounds of naturally occurring conditions were excluded (Supplementary Fig. 1). To ensure data quality, we performed a two-step quality check: technical selection and expert evaluation. Collected data varied according to collection protocols, such as sampling depth and the microhabitats (layers) considered. To technically exclude unreliable density estimations, we explored data with a number of diagnostic graphs (Supplementary Table 2; Supplementary Figs. 12–20) and filtered it, excluding the following: (1) All woodlands where only soil or only litter was considered; (2) All scrub ecosystems where only ground cover (litter or mosses) was considered; (3) Agricultural sites in temperate zones where only soil with sampling depth 90% of cases were masked on the main maps; for the map with density-species richness visualisation, two corresponding masks were applied (Fig. 2).To estimate spatial variability of our predictions while accounting for the spatial sampling bias in our data (Fig. 1a) we performed a spatially stratified bootstrapping procedure. We used the relative area of each IPBES79 region (i.e., Europe and Central Asia, Asia and the Pacific, Africa, and the Americas) to resample the original dataset, creating 100 bootstrap resamples. Each of these resamples was used to create a global map, which was then reduced to create mean, standard deviation, 95% confidence interval, and coefficient of variation maps (Supplementary Figs. 4–7).Global biomass, abundance, and community metabolism of springtails were estimated by summing predicted values for each 30 arcsec pixel10. Global community metabolism was recalculated from joule to mass carbon by assuming 1 kg fresh mass = 7 × 106 J80, an average water proportion in springtails of 70%58, and an average carbon concentration of 45% (calculated from 225 measurements across temperate forest ecosystems)81. We repeated the procedure of global extrapolation and prediction for biomass and community metabolism using minimum and maximum estimates of these parameters from regression coefficient uncertainties (see Parameter uncertainties).Path analysisTo reveal the predictors of springtail communities at the global scale, we performed a path analysis. After filtering the selected environmental variables (see above) according to their global availability and collinearity, 13 variables were used (Supplementary Fig. 9b): mean annual air temperature, mean annual precipitation (CHELSA database67), aridity (CGIAR database68), soil pH, sand and clay contents combined (sand and clay contents were co-linear in our dataset), soil organic carbon content (SoilGrids database73), NDVI (MODIS database72), human population density (GPWv4 database74), latitude, elevation69, and vegetation cover reported by the data providers following the habitat classification of European Environment Agency (woodland, scrub, agriculture, and grasslands; the latter were coded as the combination of woodland, scrub, and agriculture absent). Before running the analysis, we performed the Rosner’s generalized extreme Studentized deviate test in the EnvStats package82 to exclude extreme outliers and we z-standardized all variables (Supplementary R Code).Separate structural equation models were run to predict density, dry biomass, community metabolism, and local species richness in the lavaan package83. To account for the spatial clustering of our data in Europe, instead of running a model for the entire dataset, we divided the data by the IPBES79 geographical regions and selected a random subset of sites for Eurasia, such that only twice the number of sites were included in the model as the second-most represented region. We ran the path analysis 99 times for each community parameter with different Eurasian subsets (density had n = 723 per iteration, local species richness had n = 352, dry biomass had n = 568, and community metabolism had n = 533). We decided to keep the share of the Eurasian dataset larger than other regions to increase the number of sites per iteration and validity of the models. The Eurasian dataset also had the best data quality among all regions and a substantial reduction in datasets from Eurasia would result in a low weight for high-quality data. We additionally ran a set of models in which the Eurasian dataset was represented by the same number of sites as the second-most represented region, which yielded similar effect directions for all factors, but slightly higher variations and fewer consistently significant effects. In the paper, only the first version of analysis is presented. To illustrate the results, we averaged effect sizes for the paths across all iterations and presented the distribution of these effect sizes using mirrored Kernel density estimation (violin) plots. We marked and discussed effects that were significant at p  More

  • in

    Co-cultivation of Mortierellaceae with Pseudomonas helmanticensis affects both their growth and volatilome

    The growth behaviour of Linnemannia is strain-specificMost strains showed comparable morphological characteristics on both media as well as in pure and co-culture. However, Linnemannia solitaria and Entomortierella galaxiae produced more aerial mycelium on PDA compared to LcA. There was more/less aerial mycelium in co-cultures with P. helmanticensis compared to pure cultures depending on the strain (Fig. 1, SI Fig. S3).The comparison of Linnemannia and E. galaxiae daily radial growth rates did not support a difference between these genera (p ≥ 0.3). The overall linear model indicated that the fungal daily growth rates mainly differed among species (Table 1). In addition, the effect of strains highlighted the heterogeneity among strains within species (Fig. 2, SI Figs. S4, S5). Although there was no relevant main effect of medium on the daily radial growth rate of the fungi, the medium did affect the fungi in a strain-specific manner (Table 1, Fig. 2, SI Figs. S4, S5). On nutrient poor LcA, the fungal daily radial growth rates were reduced for all species, except for L. solitaria, which grew better on LcA (SI Figs. S3, S4).Table 1 The effect of experimental factors on the fungal daily radial growth rate.Full size tableFigure 2Daily radial growth rate of pure Linnemannia and Entomortierella cultures as well as co-cultures with P. helmanticensis on nutrient rich PDA medium. (a) L. exigua, (b) L. gamsii, (c) L. hyalina, (d) L. sclerotiella, (e) L. solitaria, (f) E. galaxiae.Full size imageThe main effect of co-plating P. helmanticensis on radial growth rate was small, yet significant (0.7%, p  More

  • in

    Upwelling, climate change, and the shifting geography of coral reef development

    Kennedy, E. V. et al. Avoiding coral reef functional collapse requires local and global action. Curr. Biol. 23, 912–918. https://doi.org/10.1016/j.cub.2013.04.020 (2013).Article 
    CAS 

    Google Scholar 
    Beck, M. W. et al. The global flood protection savings provided by coral reefs. Nat. Commun. 9, 2186. https://doi.org/10.1038/s41467-018-04568-z (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Kuffner, I. B. & Toth, L. T. A geological perspective on the degradation and conservation of western Atlantic coral reefs. Conserv. Biol. 30, 706–715. https://doi.org/10.1111/cobi.12725 (2016).Article 

    Google Scholar 
    Allemand, D. et al. Biomineralisation in reef-building corals: From molecular mechanisms to environmental control. C. R. Palevol. 3, 453–467. https://doi.org/10.1016/j.crpv.2004.07.011 (2004).Article 

    Google Scholar 
    Glynn, P. W. Bioerosion and coral-reef growth: A dynamic balance. In Life and Death of Coral Reefs (ed Birkeland, C.) 68–95 (Chapman & Hall, 1997).Eyre, B. D., Andersson, A. J. & Cyronak, T. Benthic coral reef calcium carbonate dissolution in an acidifying ocean. Nat. Clim. Change 4, 969–976. https://doi.org/10.1038/nclimate2380 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Enochs, I. C. et al. Upwelling and the persistence of coral-reef frameworks in the eastern tropical Pacific. Ecol. Monogr. 91, e01482. https://doi.org/10.1002/ecm.1482 (2021).Article 
    CAS 

    Google Scholar 
    Alvarado, J. J., Grassian, B., Cantera-Kintz, J. R., Carballo, J. L. & Londoño-Cruz, E. Coral reef bioerosion in the eastern tropical Pacific. In Coral Reefs of the Eastern Tropical Pacific (eds Glynn, P. W., Manzello, D. P., Enochs, I. C.) 369–403 (Springer, 2017).Perry, C. T. et al. Caribbean-wide decline in carbonate production threatens coral reef growth. Nat. Commun. 4, 1402. https://doi.org/10.1038/ncomms2409 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Oppenheimer, M. et al. Sea level rise and implications for low-lying islands, coasts and communities. In IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (2019).Alvarez-Filip, L., González-Barrios, F. J., Pérez-Cervantes, E., Molina-Hernández, A. & Estrada-Saldívar, N. Stony coral tissue loss disease decimated Caribbean coral populations and reshaped reef functionality. Commun. Biol. 5, 440. https://doi.org/10.1038/s42003-022-03398-6 (2022).Article 

    Google Scholar 
    Perry, C. T. et al. Loss of coral reef growth capacity to track future increases in sea level. Nature 558, 396–400. https://doi.org/10.1038/s41586-018-0194-z (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    van Woesik, R. & Cacciapaglia, C. W. Carbonate production of Micronesian reefs suppressed by thermal anomalies and Acanthaster as sea-level rises. PLoS ONE 14, e0224887. https://doi.org/10.1371/journal.pone.0224887 (2019).Article 
    CAS 

    Google Scholar 
    van Woesik, R. & Cacciapaglia, C. W. Thermal stress jeopardizes carbonate production of coral reefs across the western and central Pacific Ocean. PLoS ONE 16, e0249008. https://doi.org/10.1371/journal.pone.0249008 (2021).Article 
    CAS 

    Google Scholar 
    van Woesik, R. & Cacciapaglia, C. W. Keeping up with sea-level rise: Carbonate production rates in Palau and Yap, western Pacific Ocean. PLoS ONE 13, e0197077. https://doi.org/10.1371/journal.pone.0197077 (2018).Article 
    CAS 

    Google Scholar 
    Eakin, C. M. Where have all the carbonates gone? A model comparison of calcium carbonate budgets before and after the 1982–1983 El Niño at Uva Island in the eastern Pacific. Coral Reefs 15, 109–119. https://doi.org/10.1007/BF01771900 (1996).Article 
    ADS 

    Google Scholar 
    Perry, C. T. & Morgan, K. M. Bleaching drives collapse in reef carbonate budgets and reef growth potential on southern Maldives reefs. Sci. Rep. 7, 40581. https://doi.org/10.1038/srep40581 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Connell, J. H. Disturbance and recovery of coral assemblages. Coral Reefs 16, S101–S113. https://doi.org/10.1007/s003380050246 (1997).Article 

    Google Scholar 
    Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83. https://doi.org/10.1126/science.aan8048 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Dana, T. F. Development of contemporary eastern Pacific coral reefs. Mar. Biol. 33, 355–374. https://doi.org/10.1007/BF00390574 (1975).Article 

    Google Scholar 
    Cortés, J. Eastern tropical Pacific coral reefs. In The Encyclopedia of Modern Coral Reefs: Structure, Form and Process. 351–358 (2011).O’Dea, A., Hoyos, N., Rodríguez, F., Degracia, B. & de Gracia, C. History of upwelling in the tropical eastern Pacific and the paleogeography of the Isthmus of Panama. Palaeogeogr. Palaeoclimatol. Palaeoecol. 348–349, 59–66. https://doi.org/10.1016/j.palaeo.2012.06.007 (2012).Article 

    Google Scholar 
    Glynn, P. W. & Colgan, M. W. Sporadic disturbances in fluctuating coral reef environments: El Niño and coral reef development in the Eastern Pacific. Am. Zool. 32, 707–718. https://doi.org/10.1093/icb/32.6.707 (1992).Article 

    Google Scholar 
    Manzello, D. P. et al. Poorly cemented coral reefs of the eastern tropical Pacific: Possible insights into reef development in a high-CO2 world. Proc. Natl. Acad. Sci. USA 105, 10450–10455. https://doi.org/10.1073/pnas.0712167105 (2008).Article 
    ADS 

    Google Scholar 
    Eakin, C. M. & Glynn, P. W. Low tidal exposures and reef mortalities in the eastern Pacific. Coral Reefs 15, 120 (1996).Article 

    Google Scholar 
    Glynn, P. W. Some physical and biological determinants of coral community structure in the eastern pacific. Ecol. Monogr. 46, 431–456. https://doi.org/10.2307/1942565 (1976).Article 

    Google Scholar 
    Toth, L. T., Macintyre, I. G. & Aronson, R. B. Holocene reef development in the eastern tropical Pacific. In Coral Reefs of the Eastern Tropical Pacific (eds Glynn, P. W., Manzello, D. P., Enochs, I. C.) 177–201 (Springer, 2017).Cortés, J., Macintyre, I. G. & Glynn, P. W. Holocene growth history of an eastern Pacific fringing reef, Punta Islotes, Costa Rica. Coral Reefs 13, 65–73. https://doi.org/10.1007/BF00300763 (1994).Article 
    ADS 

    Google Scholar 
    Glynn, P. W. et al. Eastern pacific coral reef provinces, coral community structure and composition: An overview. In Coral Reefs of the Eastern Tropical Pacific (eds Glynn, P. W., Manzello, D. P., Enochs, I. C.) 107–176 (Springer, 2017).Glynn, P. W. & Macintyre, I. G. Growth rate and age of coral reefs on the Pacific coast of Panama. In Proceedings of the 3rd International Coral Reef Symposium, Miami, vol. 2, 251–259 (1977).Glynn, P. W. & Stewart, R. H. Distribution of coral reefs in the Pearl Islands (Gulf of Panama) in relation to thermal conditions. Limnol. Oceanogr. 18, 367–379. https://doi.org/10.4319/lo.1973.18.3.0367 (1973).Article 
    ADS 

    Google Scholar 
    Glynn, P. W., Druffel, E. M. & Dunbar, R. B. A dead Central American coral reef tract: Possible link with the Little Ice Age (Costa Rica, Gulf of Papagayo, Gulf of Panama). J. Mar. Res. 41, 605–637. https://doi.org/10.1357/002224083788519740 (1983).Article 

    Google Scholar 
    Glynn, P. W. & Leyte Morales, G. E. Coral reefs of Huatulco, west México: Reef development in upwelling Gulf of Tehuantepec. Rev. Biol. Trop. 45, 1033–1047 (1997).
    Google Scholar 
    Tribollet, A. & Golubic, S. Cross-shelf differences in the pattern and pace of bioerosion of experimental carbonate substrates exposed for 3 years on the northern Great Barrier Reef, Australia. Coral Reefs 24, 422–434. https://doi.org/10.1007/s00338-005-0003-7 (2005).Article 
    ADS 

    Google Scholar 
    D’Croz, L. & O’Dea, A. Variability in upwelling along the Pacific shelf of Panama and implications for the distribution of nutrients and chlorophyll. Estuar. Coast. Shelf S. 73, 325–340. https://doi.org/10.1016/j.ecss.2007.01.013 (2007).Article 
    ADS 

    Google Scholar 
    Randall, C. J., Toth, L. T., Leichter, J. J., Maté, J. L. & Aronson, R. B. Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific. Ecology 101, e02918. https://doi.org/10.1002/ecy.2918 (2020).Article 

    Google Scholar 
    Tyberghein, L. et al. Bio-ORACLE: A global environmental dataset for marine species distribution modelling. Glob. Ecol. Biogeogr. 21, 272–281. https://doi.org/10.1111/j.1466-8238.2011.00656.x (2012).Article 

    Google Scholar 
    Assis, J. et al. Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Glob. Ecol. Biogeogr. 27, 277–284. https://doi.org/10.1111/geb.12693 (2018).Article 

    Google Scholar 
    R Development Core Team. R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. R Foundation for Statistical Computing vol. 2.Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer, 2016). ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.Dunnington, D. ggspatial: Spatial Data Framework for ggplot2. (2022). https://paleolimbot.github.io/ggspatial/, https://github.com/paleolimbot/ggspatial.Toth, L. T. et al. ENSO drove 2500-year collapse of eastern Pacific coral reefs. Science 336, 81–84. https://doi.org/10.1126/science.1221168 (2012).Article 
    ADS 
    CAS 

    Google Scholar 
    Toth, L. T. et al. Climatic and biotic thresholds of coral-reef shutdown. Nat. Clim. Change 5, 369–374. https://doi.org/10.1038/nclimate2541 (2015).Article 
    ADS 

    Google Scholar 
    Guzman, H. & Cortés, J. Arrecifes coralinos del Pacífico oriental tropical: revisión y perspectivas. Rev. Biol. Trop. 41, 535–557 (1993).
    Google Scholar 
    Chollett, I., Mumby, P. J. & Cortés, J. Upwelling areas do not guarantee refuge for coral reefs in a warming Ocean. Mar. Ecol. Prog. Ser. 416, 47–56. https://doi.org/10.3354/meps08775 (2010).Article 
    ADS 

    Google Scholar 
    Glynn, P. W., Maté, J. L., Baker, A. C. & Calderón, M. O. Coral bleaching and mortality in Panama and Ecuador during the 1997–1998 El Niño-Southern Oscillation event: Spatial/temporal patterns and comparisons with the 1982–1983 event. Bull. Mar. Sci. 69, 79–109 (2001).
    Google Scholar 
    Paz-García, D. A., Hellberg, M. E., García-de-León, F. J. & Balart, E. F. Switch between morphospecies of Pocillopora corals. Am. Nat. 186, 434–440. https://doi.org/10.1086/682363 (2015).Article 

    Google Scholar 
    Tortolero-Langarica, J. J. A., Rodríguez-Troncoso, A. P., Cupul-Magaña, A. L. & Carricart-Ganivet, J. P. Calcification and growth rate recovery of the reef-building Pocillopora species in the northeast tropical Pacific following an ENSO disturbance. PeerJ 2017, e3191. https://doi.org/10.7717/peerj.3191 (2017).Article 

    Google Scholar 
    Medellín-Maldonado, F. et al. Calcification of the main reef-building coral species on the Pacific coast of southern Mexico. Cienc. Mar. 42, 209–225. https://doi.org/10.7773/cm.v42i3.2650 (2016).Article 
    CAS 

    Google Scholar 
    Cabral-Tena, R. A. et al. Calcification of coral assemblages in the eastern Pacific: Reshuffling calcification scenarios under climate change. Ecol. Indic. 95, 726–734. https://doi.org/10.1016/j.ecolind.2018.08.021 (2018).Article 
    CAS 

    Google Scholar 
    Glynn, P. Coral growth in upwelling and nonupwelling areas off the Pacific coast of Panama. J. Mar. Res. 35, 567–585 (1977).
    Google Scholar 
    Guzman, H. M. & Cortes, J. Growth rates of eight species of scleractinian corals in the eastern Pacific (Costa Rica). Bull. Mar. Sci. 44, 1186–1194 (1989).
    Google Scholar 
    Cabral-Tena, R. A. et al. Functional potential of coral assemblages along a typical eastern tropical Pacific reef tract. Ecol. Indic. 119, 106795. https://doi.org/10.1016/j.ecolind.2020.106795 (2020).Article 

    Google Scholar 
    Manzello, D. P. Coral growth with thermal stress and ocean acidification: Lessons from the eastern tropical Pacific. Coral Reefs 29, 749–758. https://doi.org/10.1007/s00338-010-0623-4 (2010).Article 
    ADS 

    Google Scholar 
    González-Barrios, F. J. & Álvarez-Filip, L. A framework for measuring coral species-specific contribution to reef functioning in the Caribbean. Ecol. Indic. 95, 877–886. https://doi.org/10.1016/j.ecolind.2018.08.038 (2018).Article 

    Google Scholar 
    Jokiel, P. L., Maragos, J. & Franzisket, L. Coral growth: Buoyant weight technique. In Coral Reefs: Research Methods (eds Stoddart, D. R., & Johannes, R. E.) 529–541 (UNESCO, 1978).Kuffner, I. B., Hickey, T. D. & Morrison, J. M. Calcification rates of the massive coral Siderastrea siderea and crustose coralline algae along the Florida Keys (USA) outer-reef tract. Coral Reefs 32, 987–997. https://doi.org/10.1007/s00338-013-1047-8 (2013).Article 
    ADS 

    Google Scholar 
    Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl. Acad. Sci. USA 118, e2015265118. https://doi.org/10.1073/pnas.201526511 (2021).Article 
    CAS 

    Google Scholar 
    Rose, C. S. & Risk, M. J. Increase in Cliona delitrix infestation of Montastrea cavernosa heads on an organically polluted portion of the Grand Cayman fringing reef. Mar. Ecol. 6, 345–363. https://doi.org/10.1111/j.1439-0485.1985.tb00142.x (1985).Article 
    ADS 

    Google Scholar 
    Prouty, N. G. et al. Vulnerability of coral reefs to bioerosion from land-based sources of pollution. J. Geophys. Res-Oceans 122, 9319–9331. https://doi.org/10.1002/2017JC013264 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Eakin, C. M. The damselfish-algal lawn symbiosis and its influence on the bioerosion of an El Niño impacted coral reef, Uva Island, Pacific Panama. ProQuest Dissertations and Theses (1991).Alvarado, J. J., Reyes-Bonilla, H. & Benítez-Villalobos, F. Diadema mexicanum, erizo de mar clave en los arrecifes coralinos del Pacífico Tropical Oriental: Lo que sabemos y perspectivas futuras (Diadematoida: Diadematidae). Rev. Biol. Trop. 63(Suppl 2), 135–157. https://doi.org/10.15517/rbt.v63i2.23140 (2015).Article 

    Google Scholar 
    Glynn, P. W. Widespread coral mortality and the 1982–83 El Niño warming event. Environ. Conserv. 11, 133–146. https://doi.org/10.1017/S0376892900013825 (1984).Article 

    Google Scholar 
    Glynn, P. W. El Niño warming, coral mortality and reef framework destruction by echinoid bioerosion in the eastern Pacific. Galaxea 7, 129–160 (1988).
    Google Scholar 
    Eakin, C. M. A tale of two ENSO events: Carbonate budgets and the influence of two warming disturbances and intervening variability, Uva Island, Panama. Bull. Mar. Sci. 69, 171–186 (2001).ADS 

    Google Scholar 
    Russ, G. R., Questel, S. L. A., Rizzari, J. R. & Alcala, A. C. The parrotfish–coral relationship: Refuting the ubiquity of a prevailing paradigm. Mar. Biol. 162, 2029–2045. https://doi.org/10.1007/s00227-015-2728-3 (2015).Article 

    Google Scholar 
    Wellington, G. M. & Glynn, P. W. Responses of Coral Reefs to El Niño-Southern Oscillation Sea-Warming Events. In Geological Approaches to Coral Reef Ecology (ed Aronson, R. B.) 342–385 (Springer, 2007).Guzmán, H. M. & Cortés, J. Changes in reef community structure after fifteen years of natural disturbances in the eastern Pacific (Costa Rica). Bull. Mar. Sci. 69, 133–149 (2001).
    Google Scholar 
    Guzman, H. M. & Cortés, J. Reef recovery 20 years after the 1982–1983 El Niño massive mortality. Mar. Biol. 151, 401–411. https://doi.org/10.1007/s00227-006-0495-x (2007).Article 

    Google Scholar 
    Edmunds, P. J. et al. Why more comparative approaches are required in time-series analyses of coral reef ecosystems. Mar. Ecol. Prog. Ser. 608, 297–306. https://doi.org/10.3354/meps12805 (2019).Article 
    ADS 

    Google Scholar 
    Enochs, I. C. et al. Enhanced macroboring and depressed calcification drive net dissolution at high-CO2 coral reefs. Proc. R. Soc. B 283, 20161742. https://doi.org/10.1098/rspb.2016.1742 (2016).Article 
    CAS 

    Google Scholar 
    Roff, G. Reef accretion and coral growth rates are decoupled in Holocene reef frameworks. Mar. Geol. 419, 106065. https://doi.org/10.1016/j.margeo.2019.106065 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Perry, C. T. et al. Regional-scale dominance of non-framework building corals on Caribbean reefs affects carbonate production and future reef growth. Glob. Change Biol. 21, 1153–1164. https://doi.org/10.1111/gcb.12792 (2015).Article 
    ADS 

    Google Scholar 
    IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC (2014).Neumann, A. C. & Macintyre, I. Reef response to sea level rise: Keep-up, catch-up or give up. In Proceedings 5th International Coral Reef Congress, Tahiti 3, 105–110 (1985).Macintyre, I. G. Modern coral reefs of western Atlantic: New geological perspective. AAPG Bull. 72, 1360–1369. https://doi.org/10.1306/703C99A1-1707-11D7-8645000102C1865D (1988).Article 

    Google Scholar 
    Hallock, P. & Schlager, W. Nutrient excess and the demise of coral reefs and carbonate platforms. Palaios 1, 389–398. https://doi.org/10.2307/3514476 (1986).Article 
    ADS 

    Google Scholar 
    Kleypas, J. A. Coral reef development under naturally turbid conditions: Fringing reefs near Broad Sound, Australia. Coral Reefs 15, 153–167. https://doi.org/10.1007/BF01145886 (1996).Article 
    ADS 

    Google Scholar 
    van Woesik, R. & Done, T. J. Coral communities and reef growth in the southern Great Barrier Reef. Coral Reefs 16, 103–115. https://doi.org/10.1007/s003380050064 (1997).Article 

    Google Scholar 
    Sully, S. & van Woesik, R. Turbid reefs moderate coral bleaching under climate-related temperature stress. Glob. Change Biol. 26, 1367–1373. https://doi.org/10.1111/gcb.14948 (2020).Article 
    ADS 

    Google Scholar 
    Grottoli, A. G., Rodrigues, L. J. & Palardy, J. E. Heterotrophic plasticity and resilience in bleached corals. Nature 440, 1186–1189. https://doi.org/10.1038/nature04565 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Romero-Torres, M. et al. Coral reef resilience to thermal stress in the eastern tropical Pacific. Glob. Change Biol. 26, 3880–3890. https://doi.org/10.1111/gcb.15126 (2020).Article 
    ADS 

    Google Scholar 
    Martínez-Castillo, V., Rodríguez-Troncoso, A. P., Mayfield, A. B., Rodríguez-Zaragoza, F. A. & Cupul-Magaña, A. L. Coral recovery in the central Mexican Pacific 20 years after the 1997–1998 El Niño Event. Oceans 3, 48–59. https://doi.org/10.3390/oceans3010005 (2022).Article 

    Google Scholar 
    Anton, A. et al. Differential thermal tolerance between algae and corals may trigger the proliferation of algae in coral reefs. Glob. Change Biol. 26, 4316–4327. https://doi.org/10.1111/gcb.15141 (2020).Article 
    ADS 

    Google Scholar 
    Roth, F. et al. High summer temperatures amplify functional differences between coral- and algae-dominated reef communities. Ecology 102, e03226. https://doi.org/10.1002/ecy.3226 (2021).Article 

    Google Scholar 
    Roik, A., Röthig, T., Pogoreutz, C., Saderne, V. & Voolstra, C. R. Coral reef carbonate budgets and ecological drivers in the central Red Sea—A naturally high temperature and high total alkalinity environment. Biogeosciences 15, 6277–6296. https://doi.org/10.5194/bg-15-6277-2018 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Wyatt, A. S. J. et al. Heat accumulation on coral reefs mitigated by internal waves. Nat. Geosci. 13, 28–34. https://doi.org/10.1038/s41561-019-0486-4 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Smith, T. B., Glynn, P. W., Maté, J. L., Toth, L. T. & Gyory, J. A depth refugium from catastrophic coral bleaching prevents regional extinction. Ecology 95, 1663–1673. https://doi.org/10.1890/13-0468.1 (2014).Article 

    Google Scholar 
    Guest, J. R. et al. A framework for identifying and characterising coral reef “oases” against a backdrop of degradation. J. Appl. Ecol. 55, 2865–2875. https://doi.org/10.1111/1365-2664.13179 (2018).Article 

    Google Scholar 
    Courtney, T. A. et al. Disturbances drive changes in coral community assemblages and coral calcification capacity. Ecosphere 11, e03066. https://doi.org/10.1002/ecs2.3066 (2020).Article 

    Google Scholar 
    Bachman, S. D., Kleypas, J. A., Erdmann, M. & Setyawan, E. A global atlas of potential thermal refugia for coral reefs generated by internal gravity waves. Front. Mar. Sci. 9, 1346. https://doi.org/10.3389/fmars.2022.921879 (2022).Article 

    Google Scholar 
    Dixon, A. M., Forster, P. M., Heron, S. F., Stoner, A. M. & Beger, M. Future loss of local-scale thermal refugia in coral reef ecosystems. PLoS Clim. 1, e0000004. https://doi.org/10.1371/journal.pclm.0000004 (2022).Article 

    Google Scholar 
    Kuffner, I. B., Stathakopoulos, A., Toth, L. T. & Bartlett, L. A. Reestablishing a stepping-stone population of the threatened elkhorn coral Acropora palmata to aid regional recovery. Endanger. Species Res. 43, 461–473. https://doi.org/10.3354/esr01083 (2020).Article 

    Google Scholar 
    Perry, C. T., Lange, I. D. & Januchowski-Hartley, F. A. ReefBudget Indo Pacific: Online resource and methodology. http://geography.exeter.ac.uk/reefbudget/ (2018).Nava, H. & Carballo, J. L. Chemical and mechanical bioerosion of boring sponges from Mexican Pacific coral reefs. J. Exp. Biol. 211, 2827–2831. https://doi.org/10.1242/jeb.019216 (2008).Article 

    Google Scholar 
    Carballo, J. L., Bautista, E., Nava, H., Cruz-Barraza, J. A. & Chávez, J. A. Boring sponges, an increasing threat for coral reefs affected by bleaching events. Ecol. Evol. 3, 872–886. https://doi.org/10.1002/ece3.452 (2013).Article 

    Google Scholar 
    Smith, T. B. Temperature effects on herbivory for an Indo-Pacific parrotfish in Panamá: Implications for coral-algal competition. Coral Reefs 27, 397–405. https://doi.org/10.1007/s00338-007-0343-6 (2008).Article 
    ADS 

    Google Scholar 
    Glynn, P. W., Enochs, I. C., Afflerbach, J. A., Brandtneris, V. W. & Serafy, J. E. Eastern Pacific reef fish responses to coral recovery following El Niño disturbances. Mar. Ecol. Prog. Ser. 495, 233–247. https://doi.org/10.3354/meps10594 (2014).Article 
    ADS 

    Google Scholar 
    Palacios, M. M., Muñoz, C. G. & Zapata, F. A. Fish corallivory on a pocilloporid reef and experimental coral responses to predation. Coral Reefs 33, 625–636. https://doi.org/10.1007/s00338-014-1173-y (2014).Article 
    ADS 

    Google Scholar 
    Toth, L. T. Holocene Coral-Reef Development in the Tropical Eastern Pacific. (Florida Institute of Technology, 2013).Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and nonlinear mixed effects models. https://cran.r-project.org/package=nlme.R-project (2021).Holgate, S. J. et al. New data systems and products at the permanent service for mean sea level. J. Coast. Res. 29, 493–504. https://doi.org/10.2112/JCOASTRES-D-12-00175.1 (2013).Article 

    Google Scholar 
    Permanent Service for Mean Sea Level. Balboa Tide Gauge Data. http://www.psmsl.org/data/obtaining/ (2022). More

  • in

    Restoration of insect communities after land use change is shaped by plant diversity: a case study on carabid beetles (Carabidae)

    Loreau, M. et al. Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294, 804–808 (2001).Article 
    ADS 
    CAS 

    Google Scholar 
    Pimm, S. L., Russell, G. J., Gittleman, J. L. & Brooks, T. M. The future of biodiversity. Science 269, 347–350 (1995).Article 
    ADS 
    CAS 

    Google Scholar 
    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50. https://doi.org/10.1038/nature14324 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Cardoso, P. et al. Scientists’ warning to humanity on insect extinctions. Biol. Conserv. 242, 108426. https://doi.org/10.1016/j.biocon.2020.108426 (2020).Article 

    Google Scholar 
    Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809. https://doi.org/10.1371/journal.pone.0185809 (2017).Article 
    CAS 

    Google Scholar 
    Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674. https://doi.org/10.1038/s41586-019-1684-3 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: A review of its drivers. Biol. Cons. 232, 8–27. https://doi.org/10.1016/j.biocon.2019.01.020 (2019).Article 

    Google Scholar 
    Yang, L. H. & Gratton, C. Insects as drivers of ecosystem processes. Curr. Opin. Insect Sci. 2, 26–32. https://doi.org/10.1016/j.cois.2014.06.004 (2014).Article 

    Google Scholar 
    Bowler, D. E., Heldbjerg, H., Fox, A. D., de Jong, M. & Böhning-Gaese, K. Long-term declines of European insectivorous bird populations and potential causes. Conserv. Biol. 33, 1120–1130. https://doi.org/10.1111/cobi.13307 (2019).Article 

    Google Scholar 
    Biesmeijer, J. C. et al. Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313, 351–354. https://doi.org/10.1126/science.1127863 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Tscharntke, T., Klein, A. M., Kruess, A., Steffan-Dewenter, I. & Thies, C. Landscape perspectives on agricultural intensification and biodiversity – ecosystem service management. Ecol. Lett. 8, 857–874. https://doi.org/10.1111/j.1461-0248.2005.00782.x (2005).Article 

    Google Scholar 
    Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556. https://doi.org/10.1038/nature09492 (2010).Article 
    ADS 
    CAS 

    Google Scholar 
    Siemann, E., Tilman, D. & Haarstad, J. Insect species diversity, abundance and body size relationships. Nature 380, 704–706. https://doi.org/10.1038/380704a0 (1996).Article 
    ADS 
    CAS 

    Google Scholar 
    Borer, E. T., Seabloom, E. W. & Tilman, D. Plant diversity controls arthropod biomass and temporal stability. Ecol. Lett. 15, 1457–1464. https://doi.org/10.1111/ele.12006 (2012).Article 

    Google Scholar 
    Ebeling, A. et al. Plant diversity effects on arthropods and arthropod-dependent ecosystem functions in a biodiversity experiment. Basic Appl. Ecol. 26, 50–63. https://doi.org/10.1016/j.baae.2017.09.014 (2018).Article 

    Google Scholar 
    Ebeling, A. et al. Plant diversity induces shifts in the functional structure and diversity across trophic levels. Oikos 127, 208–219. https://doi.org/10.1111/oik.04210 (2018).Article 

    Google Scholar 
    Ebeling, A. et al. Plant diversity impacts decomposition and herbivory via changes in aboveground arthropods. PLoS ONE 9, e106529. https://doi.org/10.1371/journal.pone.0106529 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Marquard, E. et al. Plant species richness and functional composition drive overyielding in a six-year grassland experiment. Ecology 90, 3290–3302 (2009).Article 

    Google Scholar 
    Tilman, D. et al. Diversity and productivity in a long-term grassland experiment. Science 294, 843–845. https://doi.org/10.1126/science.1060391 (2001).Article 
    ADS 
    CAS 

    Google Scholar 
    Simons, N. K. et al. Resource-mediated indirect effects of grassland management on arthropod diversity. PLoS ONE 9, e107033. https://doi.org/10.1371/journal.pone.0107033 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Wardle, D. A., Nicholson, K. S., Bonner, K. I. & Yeates, G. W. Effects of agricultural intensification on soil-associated arthropod population dynamics, community structure, diversity and temporal variability over a seven-year period. Soil Biol. Biochem. 31, 1691–1706 (1999).Article 
    CAS 

    Google Scholar 
    Luff, M. L. & Rushton, S. P. The ground beetle and spider fauna of managed and unimproved upland pasture. Agr. Ecosyst. Environ. 25, 195–206 (1989).Article 

    Google Scholar 
    Dennis, P., Young, M. R., Howard, C. L. & Gordon, I. J. The response of epigeal beetles (Col, Carabidae, Staphylinidae) to varied grazing regimes on upland Nardus stricta grasslands. J. Appl. Ecol. 34, 433–443 (1997).Article 

    Google Scholar 
    Murdoch, W. W., Evans, F. C. & Peterson, C. H. Diversity and pattern in plants and insects. Ecology 53, 819–829 (1972).Article 

    Google Scholar 
    Siemann, E., Tilman, D., Haarstad, J. & Ritchie, M. Experimental tests of the dependence of arthropod diversity on plant diversity. Am. Nat. 152, 738–750 (1998).Article 
    CAS 

    Google Scholar 
    Joern, A. & Laws, A. N. Ecological mechanisms underlying arthropod species diversity in grasslands. Annu. Rev. Entomol. 58, 19–36. https://doi.org/10.1146/annurev-ento-120811-153540 (2013).Article 
    CAS 

    Google Scholar 
    Hunter, M. D. & Price, P. W. Playing chutes and ladders: Heterogeneity and relative roles of bottom-up and top-down forces in natural communities. Ecology 73, 724–732 (1992).Article 

    Google Scholar 
    Knops, J. M. H. et al. Effects of plant species richness on invasion dynamics, disease outbreaks, insect abundances and diversity. Ecol. Lett. 2, 286–293 (1999).Article 
    CAS 

    Google Scholar 
    Thiele, H. U. Carabid beetles in their environment. A study on habitat selection by adaptions in physiology and behaviour. (Springer- Verlag, 1977).Harvey, J. A., van der Putten, W. H., Turin, H., Wagenaar, R. & Bezemer, T. M. Effects of changes in plant species richness and community traits on carabid assemblages and feeding guilds. Agr. Ecosyst. Environ. 127, 100–106 (2008).Article 

    Google Scholar 
    Luff, M. L. Use of Carabids as environmental indicators in grasslands and cereals. Ann. Zool. Fenn. 33, 185–195 (1996).
    Google Scholar 
    Kotze, D. J. et al. Forty years of carabid beetle research in Europe—from taxonomy, biology, ecology and population studies to bioindication, habitat assessment and conservation. ZooKeys https://doi.org/10.3897/zookeys.100.1523 (2011).Article 

    Google Scholar 
    Barnes, A. D. et al. Biodiversity enhances the multitrophic control of arthropod herbivory. Sci. Adv. 6, eabb6603. https://doi.org/10.1126/sciadv.abb6603 (2020).Article 
    ADS 

    Google Scholar 
    Bianchi, F. J. J. A., Booij, C. J. H. & Tscharntke, T. Sustainable pest regulation in agricultural landscapes: A review on landscape composition, biodiversity and natural pest control. Proc. R. Soc. B: Biol. Sci. 273, 1715–1727. https://doi.org/10.1098/rspb.2006.3530 (2006).Article 
    CAS 

    Google Scholar 
    Lövei, G. L. & Magura, T. Ground beetle (Coleoptera: Carabidae) diversity is higher in narrow hedges composed of a native compared to non-native trees in a Danish agricultural landscape. Insect Conserv. Divers. 10, 141–150. https://doi.org/10.1111/icad.12210 (2017).Article 

    Google Scholar 
    Loreau, M. Consumers as maximizers of matter and energy flow in ecosystems. Am. Nat. 145, 22–42. https://doi.org/10.1086/285726 (1995).Article 

    Google Scholar 
    Mielke, L. et al. Nematode grazing increases the allocation of plant-derived carbon to soil bacteria and saprophytic fungi, and activates bacterial species of the rhizosphere. Pedobiologia 90, 150787. https://doi.org/10.1016/j.pedobi.2021.150787 (2022).Article 

    Google Scholar 
    Holland, J. M. & Luff, M. L. The effects of agricultural practices on Carabidae in temperate agroecosystems. Integr. Pest Manag. Rev. 5, 109–129. https://doi.org/10.1023/A:1009619309424 (2000).Article 

    Google Scholar 
    Roscher, C. et al. The role of biodiversity for element cycling and trophic interactions: An experimental approach in a grassland community. Basic Appl. Ecol. 5, 107–121 (2004).Article 

    Google Scholar 
    Weisser, W. W. et al. Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: Patterns, mechanisms, and open questions. Basic Appl. Ecol. https://doi.org/10.1016/j.baae.2017.06.002 (2017).Article 

    Google Scholar 
    Freude, H., Harde, K. W. & Lohse, G. A. Die Käfer Mitteleuropas Bd.1–11. (Goecke & Evers, 1965–83).Koch, K. Die Käfer Mitteleuropas. Ökologie Bd.1–6. (Goecke & Evers, 1989–95).R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2021).Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

    Google Scholar 
    Schmid, B., Baruffol, M., Wang, Z. & Niklaus, P. A. A guide to analyzing biodiversity experiments. J. Plant Ecol. 10, 91–110. https://doi.org/10.1093/jpe/rtw107 (2017).Article 

    Google Scholar 
    Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed effects models and extensions in ecology with R. (Springer, 2009).Oksanen, J. et al. vegan: Community Ecology Package v. 2.6–2 (2022).Lenth, R. et al., emmeans: Estimated Marginal Means, aka Least-Squares Means v. 1.8.1-1 (2022).Lovei, G. L. & Sunderland, K. D. Ecology and behavior of ground beetles (Coleoptera: Carabidae). Annu. Rev. Entomol. 41, 231–256 (1996).Article 
    CAS 

    Google Scholar 
    Ravenek, J. M. et al. Long-term study of root biomass in a biodiversity experiment reveals shifts in diversity effects over time. Oikos 123, 1528–1536. https://doi.org/10.1111/oik.01502 (2014).Article 

    Google Scholar 
    Root, R. Organization of a plant -arthropod association in simple and diverse habitats: the fauna of collards (Brassica oleracea). Ecol. Monogr. 43, 95–124 (1973).Article 

    Google Scholar 
    Duelli, P. & Obrist, M. K. Regional biodiversity in an agricultural landscape: The contribution of seminatural habitat islands. Basic Appl. Ecol. 4, 129–138 (2003).Article 

    Google Scholar 
    Perner, J. & Malt, S. Assessment of changing agricultural land use: Response of vegetation, ground-dwelling spiders and beetles to the conversion of arable land into grassland. Agr. Ecosyst. Environ. 98, 169–181 (2003).Article 

    Google Scholar 
    Purtauf, T., Dauber, J. & Wolters, V. Carabid communities in the spatio-temporal mosaic of a rural landscape. Landsc. Urban Plan. 67, 185–193 (2004).Article 

    Google Scholar 
    Eisenhauer, N. et al. Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Res. Ideas Outcomes https://doi.org/10.3897/rio.5.e47042 (2019).Article 

    Google Scholar 
    Guerrero-Ramirez, N. R. et al. Diversity-dependent temporal divergence of ecosystem functioning in experimental ecosystems. Nat. Ecol. Evol. 1, 1639–1642. https://doi.org/10.1038/s41559-017-0325-1 (2017).Article 

    Google Scholar 
    Reich, P. B. et al. Impacts of biodiversity loss escalate through time as redundancy fades. Science 336, 589–592. https://doi.org/10.1126/science.1217909 (2012).Article 
    ADS 
    CAS 

    Google Scholar 
    Isbell, F. I., Polley, H. W. & Wilsey, B. J. Biodiversity, productivity and the temporal stability of productivity: Patterns and processes. Ecol. Lett. 12, 443–451. https://doi.org/10.1111/j.1461-0248.2009.01299.x (2009).Article 

    Google Scholar 
    Blake, S., Foster, G. N., Fisher, G. E. J. & Ligertwood, G. L. Effects of management practices on the carabid faunas of newly established wildflower meadows in southern Scotland. Ann. Zool. Fenn. 33, 139–147 (1996).
    Google Scholar 
    Boetzl, F. A., Krimmer, E., Krauss, J. & Steffan-Dewenter, I. Agri-environmental schemes promote ground-dwelling predators in adjacent oilseed rape fields: Diversity, species traits and distance-decay functions. J. Appl. Ecol. 56, 10–20. https://doi.org/10.1111/1365-2664.13162 (2019).Article 

    Google Scholar 
    Knapp, M., Seidl, M., Knappová, J., Macek, M. & Saska, P. Temporal changes in the spatial distribution of carabid beetles around arable field-woodlot boundaries. Sci. Rep. 9, 8967. https://doi.org/10.1038/s41598-019-45378-7 (2019).Article 
    ADS 
    CAS 

    Google Scholar  More

  • in

    Colombian biodiversity is governed by a rich and diverse policy mix

    Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).Article 
    CAS 

    Google Scholar 
    Gadgil, M., Berkes, F. & Folke, C. Indigenous knowledge for biodiversity conservation. Ambio 22, 151–156 (1993).
    Google Scholar 
    Gadgil, M., Berkes, F. & Folke, C. Indigenous knowledge: from local to global. Ambio 50, 967–969 (2021).Article 

    Google Scholar 
    The IPBES regional assessment report on biodiversity and ecosystem services for the Americas. IPBES https://doi.org/10.5281/zenodo.3236252 (2018).Claes, J. et al. Valuing nature conservation: a methodology for quantifying the benefits of protecting the planet’s natural capital (McKinsey & Company, 2020).Retsa, A., Schelske, O., Wilke, B., Rutherford, G. & de Jong, R. Biodiversity and ecosystem services: a business case for re/insurance (Swiss Re, 2020).Petersson, M. & Stoett, P. Lessons learnt in global biodiversity governance. Int. Environ. Agreem. Polit. Law Econ. 22, 333–352 (2022).
    Google Scholar 
    Dasgupta, P. The economics of biodiversity: the Dasgupta review. GOV.UK www.gov.uk/official-documents. (2021).Furumo, P. R. & Lambin, E. F. Scaling up zero-deforestation initiatives through public-private partnerships: a look inside post-conflict Colombia. Glob. Environ. Change 62, 1–13 (2020).Article 

    Google Scholar 
    Hale, T. & Roger, C. Orchestration and transnational climate governance. Rev. Int. Organ. 9, 59–82 (2014).Article 

    Google Scholar 
    Ring, I. & Barton, D. N. Economic instruments in policy mixes for biodiversity conservation and ecosystem governance. in Handbook of Ecological Economics (eds Martinez-Alier, J. & Muradian, R.) Ch, 17 (Edward Elgar, 2015).Von Essen, M. & Lambin, E. Jurisdictional approaches to sustainable resource use. Front. Ecol. Environ. 19, 159–167 (2021).Article 

    Google Scholar 
    Taylor, C., Pollard, S., Rocks, S. & Angus, A. Selecting policy instruments for better environmental regulation: a critique and future research agenda. Environ. Policy Gov. 22, 268–292 (2012).Article 

    Google Scholar 
    Ring, I. & Schröter-Schlaack, C. Instrument mixes for biodiversity policies. POLICYMIX Report https://policymix.nina.no (2011).Howlett, M. & Rayner, J. Design principles for policy mixes: cohesion and coherence in ‘new governance arrangements’. Policy Soc. 26, 1–18 (2007).
    Google Scholar 
    Soulé, M. The “new conservation”. Conserv. Biol. 27, 895–897 (2013).Article 

    Google Scholar 
    Mace, G. M. Whose conservation? Science 345, 1558–1560 (2014).Article 
    CAS 

    Google Scholar 
    Runhaar, H., Driessen, P. & Uittenbroek, C. Towards a systematic framework for the analysis of environmental policy integration. Environ. Policy Gov. 24, 233–246 (2014).Article 

    Google Scholar 
    Visseren-Hamakers, I. J. Integrative governance: the relationships between governance instruments taking center stage. Environ. Plan. C. Polit. Space 36, 1341–1354 (2018).Article 

    Google Scholar 
    Lafferty, W. & Hovden, E. Environmental policy integration: towards an analytical framework. Environ. Polit. 12, 1–22 (2003).Article 

    Google Scholar 
    Milner-Gulland, E. J. et al. Four steps for the Earth: mainstreaming the post-2020 global biodiversity framework. One Earth 4, 75–87 (2021).Article 

    Google Scholar 
    Decision adopted by the conference of the parties to the Convention on Biological Diversity. 14/3 Mainstreaming biodiversity in the energy and mining, infrastructure, manufacturing and processing sectors. Convention on Biological Diversity https://www.cbd.int/doc/decisions/cop-14/cop-14-dec-03-en.pdf (2018).Update of the zero draft of the post-2020 global biodiversity framework. Convention on Biological Diversity https://www.cbd.int/doc/c/3064/749a/0f65ac7f9def86707f4eaefa/post2020-prep-02-01-en.pdf (2020).Whitehorn, P. R. et al. Mainstreaming biodiversity: a review of national strategies. Biol. Conserv. 235, 157–163 (2019).Article 

    Google Scholar 
    Alpízar, F. et al. Mainstreaming of natural capital and biodiversity into planning and decision-making: cases from Latin America and the Caribbean (IDB, 2020).Daily, G. Nature’s Services (Island Press, 1997).Hill, R. et al. Working with indigenous, local and scientific knowledge in assessments of nature and nature’s linkages with people. Curr. Opin. Environ. Sustain. 43, 8–20 (2020).Article 

    Google Scholar 
    Baptiste, B. et al. Greening peace in Colombia. Nat. Ecol. Evol. 1, 1–3 (2017).Article 

    Google Scholar 
    Biodiversidad en cifras. Instituto Alexander von Humboldt https://cifras.biodiversidad.co/ (2022).Censo nacional de población y vivienda. Estadísticas para grupos étnicos. DANE https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/grupos-etnicos/informacion-tecnica (2018).Boyd, E., Corbera, E. & Estrada, M. UNFCCC negotiations (pre-Kyoto to COP-9): what the process says about the politics of CDM-sinks. Int. Environ. Agreem. Polit. Law Econ. 8, 95–112 (2008).
    Google Scholar 
    Alvarez, C. F. et al. Evaluación nacional de biodiversidad y servicios ecosistémicos: resumen para tomadores de decisión. Instituto Alexander von Humboldt. http://www.humboldt.org.co/images/pdf/10721/RTDFinalv290621.pdf (2021).Lambin, E. F. et al. Effectiveness and synergies of policy instruments for land use governance in tropical regions. Glob. Environ. Change 28, 129–140 (2014).Article 

    Google Scholar 
    Hoban, S. et al. Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biol. Conserv. 248, 108654 (2020).Article 

    Google Scholar 
    Laikre, L. Genetic diversity is overlooked in international conservation policy implementation. Conserv. Genet. 11, 349–354 (2010).Article 

    Google Scholar 
    Ministerio de Ambiente y Desarrollo Sostenible. Resolución 1912 del 15 de Septiembre de 2017, listado de especies silvestres amenazadas de la diversidad biológica colombiana continental y marino costera en el territorio nacional. (2017). https://www.minambiente.gov.co/wp-content/uploads/2021/10/resolucion-1912-de-2017.pdfNewton, A. C. Biodiversity risks of adopting resilience as a policy goal. Conserv. Lett. 9, 369–376 (2016).Article 

    Google Scholar 
    Jeanrenaud, S. Changing people/nature representations in international conservation discourses. IDS Bull. 33, 111–122 (2002).Article 

    Google Scholar 
    Louder, E. & Wyborn, C. Biodiversity narratives: stories of the evolving conservation landscape. Environ. Conserv. 47, 251–259 (2020).Article 

    Google Scholar 
    Bonilla-Mejía, L. & Higuera-Mendieta, I. Protected areas under weak institutions: evidence from Colombia. World Dev. 122, 585–596 (2019).Article 

    Google Scholar 
    African Development Bank Group et al. Joint statement by the Multilateral Development Banks at Paris, COP21. European Investment Bank https://www.eib.org/attachments/press/joint-mdb-statement-climate_nov-28_final.pdf (2021).Smith, T. et al. Biodiversity means business: reframing global biodiversity goals for the private sector. Conserv. Lett. 13, e12690 (2020).Article 

    Google Scholar 
    Friedman, K., Garcia, S. M. & Rice, J. Mainstreaming biodiversity in fisheries. Mar. Policy 95, 209–220 (2018).Article 

    Google Scholar 
    Turismo de naturaleza, oportunidad para conocer y proteger la biodiversidad de Colombia. MADS https://www.minambiente.gov.co/negocios-verdes/turismo-de-naturaleza-oportunidad-para-conocer-y-proteger-la-biodiversidad-de-colombia/ (2022).Pacheco, P., Schoneveld, G., Dermawan, A., Komarudin, H. & Djama, M. Governing sustainable palm oil supply: disconnects, complementarities, and antagonisms between state regulations and private standards. Regul. Gov. 14, 568–598 (2020).Article 

    Google Scholar 
    Peters, B. G. & Pierre, J. Developments in intergovernmental relations: towards multi-level governance. Policy Polit. 29, 131–135 (2001).Article 

    Google Scholar 
    Lustig, N. Fiscal redistribution in middle income countries. OECD Social, Employment and Migration Working Papers. 171 (2015).Mooney, H. A. & Cleland, E. E. The evolutionary impact of invasive species. Proc. Natl Acad. Sci. USA 98, 5446–5451 (2001).Article 
    CAS 

    Google Scholar 
    Rule of law index 2020. World Justice Project https://worldjusticeproject.org/sites/default/files/documents/WJP-ROLI-2020-Online_0.pdf (2020).Recommendation of the council on policy coherence for sustainable development OECD/LEGAL/0381. OECD https://www.oecd.org/gov/pcsd/recommendation-on-policy-coherence-for-sustainable-development-eng.pdf (2019).Arellana, J., Oviedo, D., Guzman, L. A. & Alvarez, V. Urban transport planning and access inequalities: a tale of two Colombian cities. Res. Transp. Bus. Manag. https://doi.org/10.1016/j.rtbm.2020.100554 (2020).Leyes | Ministerio de Ambiente y Desarrollo Sostenible. MADS https://www.minambiente.gov.co/index.php/normativa/leyes (2021).Cavelier Adarve, I. & Rodríguez Becerra, M. in Nuevos Enfoques para el Estudio de las Relaciones Internacionales de Colombia (eds Tickner A.B. & Bitar, S.) Ch. 4 (Ediciones Uniandes-Universidad de los Andes, 2017).Política Nacional para la Gestión Integral de la biodiversidad y los Servicios Ecosistémicos (PNGIBSE) MADS (2012). https://www.minambiente.gov.co/wp-content/uploads/2021/10/Poli%CC%81tica-Nacional-de-Gestio%CC%81n-Integral-de-la-Biodiver.pdfPotts, J., Wenban-Smith, M. & Turley, L. State of sustainability initiatives review: standards and the extractive economy (IISD, 2018).Junguito Bonnet, R. El papel de los gremios en la economía colombiana. Rev. Desarro. Soc. 82, 103–131 (2019).Article 

    Google Scholar 
    Savvidou, G., Dzebo, A. & Atteridge, A. Aid Atlas: new tool to visualize development finance flows. JSTOR https://www.jstor.org/stable/resrep22982 (2019).BIOFIN- Movilizando recursos para la biodiversidad en Colombia, plan financiero. UNDP https://www.biofin.org/sites/default/files/content/knowledge_products/Plan%20Financiero%20Movilizando%20recursos%20para%20la%20biodiversidad%20en%20Colombia.pdf (2018).Echeverri, A. et al. Data for: a policy mix approach to biodiversity governance in Colombia (Dryad, 2022).Gibbs, G. Analyzing Qualitative Data (SAGE Publications, 2007).Maxwell, J. A. Qualitative Research Design: An Interactive Approach (SAGE Publications, 2012).Gould, R. K. et al. A protocol for eliciting nonmaterial values through a cultural ecosystem services frame. Conserv. Biol. 29, 575–586 (2015).Article 

    Google Scholar 
    Kremen, C. Managing ecosystem services: what do we need to know about their ecology? Ecol. Lett. 8, 468–479 (2005).Article 

    Google Scholar 
    Robinson, J. G. Ethical pluralism, pragmatism, and sustainability in conservation practice. Biol. Conserv. 144, 958–965 (2011).Article 

    Google Scholar 
    Sandbrook, C. What is conservation? Oryx 49, 565–566 (2015).Article 

    Google Scholar 
    Ricotta, C. et al. Measuring the functional redundancy of biological communities: a quantitative guide. Methods Ecol. Evol. 7, 1386–1395 (2016).Article 

    Google Scholar 
    Dı́az, S. & Cabido, M. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).Article 

    Google Scholar 
    Laliberté, E. & Legendre, P. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91, 299–305 (2010).Article 

    Google Scholar  More

  • in

    Enhancing the ecological value of oil palm agriculture through set-asides

    Phalan, B. et al. Crop expansion and conservation priorities in tropical countries. PLoS ONE 8, e51759 (2013).Article 
    CAS 

    Google Scholar 
    Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).Article 
    CAS 

    Google Scholar 
    Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).Article 
    CAS 

    Google Scholar 
    Searchinger, T. D., Wirsenius, S., Beringer, T. & Dumas, P. Assessing the efficiency of changes in land use for mitigating climate change. Nature 564, 249–253 (2018).Edwards, D. P. et al. Conservation of tropical forests in the Anthropocene. Curr. Biol. 29, R1008–R1020 (2019).Article 
    CAS 

    Google Scholar 
    Newbold, T. et al. Global patterns of terrestrial assemblage turnover within and among land uses. Ecography 39, 1151–1163 (2016).Article 

    Google Scholar 
    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).Article 
    CAS 

    Google Scholar 
    Gibbs, H. K. et al. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proc. Natl Acad. Sci. USA 107, 16732–16737 (2010).Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).Article 
    CAS 

    Google Scholar 
    Newbold, T. et al. A global model of the response of tropical and sub-tropical forest biodiversity to anthropogenic pressures. Proc. R. Soc. B 281, 20141371 (2014).Article 

    Google Scholar 
    Clough, Y. et al. Combining high biodiversity with high yields in tropical agroforests. Proc. Natl Acad. Sci. USA 108, 8311–8316 (2011).Article 
    CAS 

    Google Scholar 
    Giam, X. Global biodiversity loss from tropical deforestation. Proc. Natl Acad. Sci. USA 114, 5775–5777 (2017).Article 
    CAS 

    Google Scholar 
    van der Werf, G. R. et al. CO2 emissions from forest loss. Nat. Geosci. 2, 737–738 (2009).Article 

    Google Scholar 
    Harvey, C. A. et al. Climate‐smart landscapes: opportunities and challenges for integrating adaptation and mitigation in tropical agriculture. Conserv. Lett. 7, 77–90 (2014).Article 

    Google Scholar 
    Harris, N. L. et al. Baseline map of carbon emissions from deforestation in tropical regions. Science 336, 1573–1576 (2012).Article 
    CAS 

    Google Scholar 
    Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).Quezada, J. C., Etter, A., Ghazoul, J., Buttler, A. & Guillaume, T. Carbon neutral expansion of oil palm plantations in the Neotropics. Sci. Adv. 5, eaaw4418 (2019).Article 
    CAS 

    Google Scholar 
    Oil Palm and Biodiversity: a Situation Analysis by the IUCN Oil Palm Task Force (International Union for Conservation of Nature, 2018). https://doi.org/10.2305/IUCN.CH.2018.11.enMeijaard, E. & Sheil, D. The moral minefield of ethical oil palm and sustainable development. Front. For. Glob. Change 2, 22 (2019).The Future of Food and Agriculture – Alternative Pathways to 2050 (FAO, 2018).Henders, S., Persson, U. M. & Kastner, T. Trading forests: land-use change and carbon emissions embodied in production and exports of forest-risk commodities. Environ. Res. Lett. 10, 125012 (2015).Article 

    Google Scholar 
    Donofrio, S., Rothrock, P. & Leonard, J. Supply Change: Tracking Corporate Commitments to Deforestation-Free Supply Chains (Forest Trends, 2017).Terrenoire, E., Hauglustaine, D. A., Gasser, T. & Penanhoat, O. The contribution of carbon dioxide emissions from the aviation sector to future climate change. Environ. Res. Lett. 14, 084019 (2019).Article 
    CAS 

    Google Scholar 
    Parsons, S., Raikova, S. & Chuck, C. J. The viability and desirability of replacing palm oil. Nat. Sustain. 3, 412–418 (2020).Article 

    Google Scholar 
    Taheripour, F., Hertel, T. W. & Ramankutty, N. Market-mediated responses confound policies to limit deforestation from oil palm expansion in Malaysia and Indonesia. Proc. Natl Acad. Sci. USA 116, 19193–19199 (2019).Article 
    CAS 

    Google Scholar 
    Laurance, W. F. et al. Improving the performance of the roundtable on sustainable palm oil for nature conservation. Conserv. Biol. 24, 377–381 (2010).Article 

    Google Scholar 
    Meijaard, E., Abrams, J. F., Juffe-Bignoli, D., Voigt, M. & Sheil, D. Coconut oil, conservation and the conscientious consumer. Curr. Biol. 30, R757–R758 (2020).Article 
    CAS 

    Google Scholar 
    Driving Change With Sustainable Palm Oil (Roundtable on Sustainable Palm Oil, accessed August 2022). https://rspo.org/aboutGarrett, R. D., Carlson, K. M., Rueda, X. & Noojipady, P. Assessing the potential additionality of certification by the round table on responsible soybeans and the roundtable on sustainable palm oil. Environ. Res. Lett. 11, 045003 (2016).Article 

    Google Scholar 
    Mittermeier, R. A., Myers, N., Mittermeier, C. G. & Robles, G. Hotspots: Earth’s Biologically Richest and Most Endangered Terrestrial Ecoregions (Conservation International, 1999).Gaveau, D. L. et al. Rapid conversions and avoided deforestation: examining four decades of industrial plantation expansion in Borneo. Sci. Rep. 6, 32017 (2016).Article 
    CAS 

    Google Scholar 
    Luke, S. H. et al. Riparian buffers in tropical agriculture: scientific support, effectiveness and directions for policy. J. Appl. Ecol. 56, 85–92 (2019).Article 

    Google Scholar 
    Mitchell, S. L. et al. Riparian reserves help protect forest bird communities in oil palm dominated landscapes. J. Appl. Ecol. 55, 2744–2755 (2018).Article 

    Google Scholar 
    Scriven, S. A. et al. Testing the benefits of conservation set-asides for improved habitat connectivity in tropical agricultural landscapes. J. Appl. Ecol. 56, 2274–2285 (2019).Article 

    Google Scholar 
    Deere, N. J. et al. Riparian buffers can help mitigate biodiversity declines in oil palm agriculture. Front. Ecol. Environ. 20, 459–466 (2021).Woodham, C. R. et al. Effects of replanting and retention of mature oil palm riparian buffers on ecosystem functioning in oil palm plantations. Front. Glob. Change 2, 29 (2019).Article 

    Google Scholar 
    Carlson, K. M. et al. Influence of watershed‐climate interactions on stream temperature, sediment yield, and metabolism along a land use intensity gradient in Indonesian Borneo. J. Geophys. Res. Biogeosci. 119, 1110–1128 (2014).Article 

    Google Scholar 
    Carlson, K. M. et al. Effect of oil palm sustainability certification on deforestation and fire in Indonesia. Proc. Natl Acad. Sci. USA 115, 121–126 (2018).Article 
    CAS 

    Google Scholar 
    Fleiss, S. et al. Conservation set-asides improve carbon storage and support associated plant diversity in certified sustainable oil palm plantations. Biol. Conserv. 248, 108631 (2020).Article 

    Google Scholar 
    Wunder, S., Angelsen, A. & Belcher, B. Forests, livelihoods, and conservation: broadening the empirical base. World Dev. 64, S1–S11 (2014).Struebig, M. J. et al. Quantifying the biodiversity value of repeatedly logged rainforests: gradient and comparative approaches from Borneo. Adv. Ecol. Res. 48, 183–224 (2013).Article 

    Google Scholar 
    Shevade, V. S. & Loboda, T. V. Oil palm plantations in Peninsular Malaysia: determinants and constraints on expansion. PLoS ONE 14, e0210628 (2019).Article 
    CAS 

    Google Scholar 
    Pirker, J., Mosnier, A., Kraxner, F., Havlík, P. & Obersteiner, M. What are the limits to oil palm expansion? Glob. Environ. Change 40, 73–81 (2016).Article 

    Google Scholar 
    Launching the RSPO Jurisdictional Approach (JA) Piloting Framework (Roundtable on Sustainable Palm Oil, accessed August 2022).Abram, N. K. et al. Synergies for improving oil palm production and forest conservation in floodplain landscapes. PLoS ONE 9, e95388 (2014).Article 

    Google Scholar 
    Othman, N. et al. Shift of paradigm needed towards improving human–elephant coexistence in monoculture landscapes in Sabah. Int. Zoo Yearb. 53, 161–173 (2019).Article 

    Google Scholar 
    Horton, A. J. et al. Can riparian forest buffers increase yields from oil palm plantations? Earths Future 6, 1082–1096 (2018).Article 

    Google Scholar 
    Ewers, R. M. et al. A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project. Phil. Trans. R. Soc. Lond. B 366, 3292–3302 (2011).Article 

    Google Scholar 
    Pfeifer, M. et al. Creation of forest edges has a global impact on forest vertebrates. Nature 551, 187–191 (2017).Ewers, R. M., Thorpe, S. & Didham, R. K. Synergistic interactions between edge and area effects in a heavily fragmented landscape. Ecology 88, 96–106 (2007).Article 

    Google Scholar 
    Deere, N. J. et al. High carbon stock forests provide co-benefits for tropical biodiversity. J. Appl. Ecol. 55, 997–1008 (2018).Article 
    CAS 

    Google Scholar 
    Hemprich-Bennett, D. R. et al. Altered structure of bat–prey interaction networks in logged tropical forests revealed by metabarcoding. Mol. Ecol. 30, 5844–5857 (2021).Article 

    Google Scholar 
    Williamson, J. et al. Riparian buffers act as microclimatic refugia in oil palm landscapes. J. Appl. Ecol. 58, 431–442 (2021).Article 

    Google Scholar 
    Slade, E. M., Mann, D. J. & Lewis, O. T. Biodiversity and ecosystem function of tropical forest dung beetles under contrasting logging regimes. Biol. Conserv. 144, 166–174 (2011).Article 

    Google Scholar 
    Gray, R. E. J. et al. Movement of forest-dependent dung beetles through riparian buffers in Bornean oil palm plantations. J. Appl. Ecol. 59, 238–250 (2022).Woodman, S. M. et al. esdm: a tool for creating and exploring ensembles of predictions from species distribution and abundance models. Methods Ecol. Evol. 10, 1923–1933 (2019).Article 

    Google Scholar 
    Liu, C., Berry, P. M., Dawson, T. P. & Pearson, R. G. Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28, 385–393 (2005).Article 

    Google Scholar 
    Piccini, I. et al. Greenhouse gas emissions from dung pats vary with dung beetle species and with assemblage composition. PloS ONE 12, e0178077 (2017).Article 

    Google Scholar 
    Raine, E. H. & Slade, E. M. Dung beetle–mammal associations: methods, research trends and future directions. Proc. R. Soc. B 286, 20182002 (2019).Article 

    Google Scholar 
    Nichols, E., Gardner, T., Peres, C., Spector, S. & Network, S. R. Co‐declining mammals and dung beetles: an impending ecological cascade. Oikos 118, 481–487 (2009).Article 

    Google Scholar 
    Asner, G. P. et al. Mapped aboveground carbon stocks to advance forest conservation and recovery in Malaysian Borneo. Biol. Conserv. 217, 289–310 (2018).Article 

    Google Scholar 
    Jucker, T. et al. Estimating aboveground carbon density and its uncertainty in Borneo’s structurally complex tropical forests using airborne laser scanning. Biogeosciences 15, 3811–3830 (2018).Article 

    Google Scholar 
    Philipson, C. D. et al. Active restoration accelerates the carbon recovery of human-modified tropical forests. Science 369, 838–841 (2020).Article 
    CAS 

    Google Scholar 
    Nunes, M. H. et al. Recovery of logged forest fragments in a human-modified tropical landscape during the 2015–16 El Niño. Nat. Commun. 12, 1526 (2021).Article 
    CAS 

    Google Scholar 
    Woittiez, L. S., van Wijk, M. T., Slingerland, M., van Noordwijk, M. & Giller, K. E. Yield gaps in oil palm: a quantitative review of contributing factors. Eur. J. Agron. 83, 57–77 (2017).Article 

    Google Scholar  More

  • in

    Nocardiopsis changdeensis sp. nov., an endophytic actinomycete isolated from the roots of Eucommia ulmoides Oliv

    Rainey FA, WardRainey N, Kroppenstedt RM, Stackebrandt E. The genus Nocardiopsis represents a phylogenetically coherent taxon and a distinct actinomycete lineage: proposal of Nocardiopsaceae fam. nov. Int J Syst Evol Microbiol. 1996;46:1088–92.CAS 

    Google Scholar 
    Goodfellow M, Order XV Streptosporangiales ord. nov. In: Goodfellow M, Kämpfer P, Busse HJ, Trujillo ME, Suzuki K, Ludwig W, Whitman WB (eds), Bergey’s Manual of Systematic Bacteriology vol. 5, 2nd edn., Springer, New York, 2012, p. 1805.Meyer J. Nocardiopsis, a new genus of the order Actinomycetales. Int J Sys Bacteriol. 1976;26:487–93.Article 

    Google Scholar 
    Chen YG, Cui XL, Kroppenstedt RM, Stackebrandt E, Wen ML, et al. Nocardiopsis quinghaiensis sp. nov. isolated from saline soil in China. Int J Syst Evol Microbiol. 2008;58:699–705.Article 
    CAS 

    Google Scholar 
    Chen YG, Zhang YQ, Tang SK, Liu ZX, Xu LH, et al. Nocardiopsis terrae sp. nov., a halophilic actinomycete isolated from saline soil. Antonie van Leeuwenhoek. 2010;98:31–8.Article 

    Google Scholar 
    Pan HQ, Zhang DF, Li L, Jiang Z, Li WJ. Nocardiopsis oceani sp. nov. and nocardiopsis nanhaiensis sp. nov. actinomycetes isolated from marine sediment of the south china sea. Int J Syst Evol Microbiol. 2015;65:3384–91.Article 
    CAS 

    Google Scholar 
    Akhwale JK, Göker M, Rohde M, Schumann P, Boga HI, et al. Nocardiopsis mwathae sp. nov., isolated from the haloalkaline Lake Elmenteita in the African Rift Valley. Antonie van Leeuwenhoek. 2016;109:421–30.Article 
    CAS 

    Google Scholar 
    Schippers A. Nocardiopsis metallicus sp. nov. a metal-leaching actinomycete isolated from an alkaline slag dump. Int J Syst Evol Microbiol. 2002;52:2291–5.CAS 

    Google Scholar 
    Devi AM, Nimaichand S, Hamidah I, Xiao-Tong Z, Bull AT, et al. Nocardiopsis deserti sp. nov. isolated from a high altitude atacama desert soil. Int J Syst Evol Microbiol. 2020;70:3210–8.Article 

    Google Scholar 
    Hamedi J, Mohammadipanah F, Von JM, Potter G, Schumann P, et al. Nocardiopsis sinuspersici sp. nov. isolated from sandy rhizospheric soil. Int J Syst Evol Microbiol. 2010;60:2346–52.Article 
    CAS 

    Google Scholar 
    Zhang YG, Lu XH, Ding YB, Zhou XK, Wan HF, et al. Nocardiopsis rhizosphaerae sp. nov., isolated from rhizosphere soil of Halocnermum strobilaceum (Pall.) Bieb. Int J Syst Evol Microbiol. 2016;66:5129–33.Article 
    CAS 

    Google Scholar 
    Muangham S, Suksaard P, Mingma R, Matsumoto A, Takahashi Y, et al. Nocardiopsis sediminis sp. nov., isolated from mangrove sediment Free. Int J Syst Evol Microbiol. 2016;66:3835–40.Article 
    CAS 

    Google Scholar 
    Qin S, Li J, Chen HH, Zhao GZ, Zhu WY, et al. Isolation, diversity, and antimicrobial activity of rare actinobacteria from medicinal plants of tropical rain forests in Xishuangbanna, China. Appl Environ Microbiol. 2009;75:6176–86.Article 
    CAS 

    Google Scholar 
    Sindhuphak W, Macdonald E. Head actinomycetoma caused by Nocardiopsis dassonvillei. Arch. Dermatol. 1985;121:1332–4.Article 
    CAS 

    Google Scholar 
    Mordarska H, Zakrzewska-Czerwiñska J, Paściak M, Szponar B, Rowiñski S. Rare, suppurative pulmonary infection caused by Nocardiopsis dassonvillei recognized by glycolipid markers. FEMS Immunol Med Microbiol. 1998;21:47–55.Article 
    CAS 

    Google Scholar 
    Bennur T, Kumar AR, Zinjarde SS, Javdekar V. Nocardiopsis species: a potential source of bioactive compounds. J Appl Microbiol. 2016;120:1–16.Article 
    CAS 

    Google Scholar 
    Mo P, Yu YZ, Zhao JR, Gao J. Streptomyces xiangtanensis sp. nov., isolated from a manganese-contaminated soil. Antonie van Leeuwenhoek. 2017;110:297–304.Article 
    CAS 

    Google Scholar 
    Atlas RM In: Parks LC (ed) Handbook of microbiological media. CRC Press, Boca Raton, 1993;pp: 666–72.Shirling EB, Gottlieb D. Methods for characterization of Streptomyces species. Int J Syst Bacteriol. 1966;16:313–40.Article 

    Google Scholar 
    Ridgway R Color standards and color nomenclature. Ridgway, Washington, DC, 1912;pp: 1–43.Ruan JS, Huang Y Rapid identification and systematics of Actinobacteria. Science Press, Beijing, China, 2011;pp: 72–7.Xu LH, Li WJ, Liu ZH, Jiang CL Actinomycetes systematics: principles, methods and practices. Science Press, Beijing, China. 2007;pp: 40–53.MIDI. Sherlock Microbial Identification System Operating Manual, Version 6.0. Newark DE: MIDI Inc. 2005;pp: 1–7.Hasegawa T, Takizawa M, Tanida S. A rapid analysis for chemical grouping of aerobic actinomycetes. J Gen Appl Microbiol. 1983;29:319–22.Article 
    CAS 

    Google Scholar 
    Lechevalier MP, Lechevalier H. Chemical composition as a criterion in the classification of aerobic actinomycetes. Int J Syst Bacteriol. 1970;20:435–43.Article 
    CAS 

    Google Scholar 
    Collins MD, Pirouz T, Goodfellow M, Minnikin DE. Distribution of menaquinones in actinomycetes and corynebacteria. J Gen Microbiol. 1977;100:221–30.Article 
    CAS 

    Google Scholar 
    Kroppenstedt RM Fatty acid and menaquinone analysis of actinomycetes and related organisms. In: Goodfellow M, Minnikin DE (eds) Chemical methods in bacterial systematics. Academic Press, London, England, pp, 1985: 173–99.Kates M Techniques of Lipidology, 2nd ed. Amsterdam: Elsevier, 1986.Komagata K, Suzuki KI. 4 lipid and cell-wall analysis in bacterial systematics. Method Microbiol. 1988;19:161–207.Article 

    Google Scholar 
    Lane, DJ 16S/23S rRNA sequencing. In: nucleic acid techniques in bacterial systematics. Stackebrandt E, Goodfellow M, eds., John Wiley and Sons, New York, NY, pp, 1991: 115–75.Yoon SH, Ha SM, Kwon S, Lim J, Kim Y, et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol. 2017;67:1613–7.Article 
    CAS 

    Google Scholar 
    Saitou N, Nei M. The Neighbor-joining Method: A New Method for Reconstructing Phylogenetic Trees. Mol Biol Evol. 1987;4:406–25.CAS 

    Google Scholar 
    Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol. 1981;17:368–76.Article 
    CAS 

    Google Scholar 
    Fitch WM. Toward defining the course of evolution: minimum change for a specific tree topology. Syst Biol. 1971;20:406–16.Article 

    Google Scholar 
    Kumar S, Stecher G, Tamura K. MEGA 7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.Article 
    CAS 

    Google Scholar 
    Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution. 1985;39:783–91.Article 

    Google Scholar 
    Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, et al. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5:8365.Article 

    Google Scholar 
    Overbeek R, Olson R, Pusch GD, Olsen GJ, Stevens R, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42:D206–214.Article 
    CAS 

    Google Scholar 
    Meier-Kolthoff JP, Göker M. TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat. Commun. 2019;10:2182.Article 

    Google Scholar 
    Richter M, Rosselló-Móra R, Ckner FOG, Peplies J. JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. Bioinformatics. 2015;32:929–31.Article 

    Google Scholar 
    Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform. 2013;14:1–14.Article 

    Google Scholar 
    Rodriguez RL, Gunturu S, Harvey WT, Rossello-Mora R, Tiedje JM, et al. The Microbial Genomes Atlas (MiGA) webserver: taxonomicand gene diversity analysis of Archaea and Bacteria at the whole genome level. Nucleic Acids Res. 2018;46:W282–W288.Article 

    Google Scholar 
    Wayne LG, Brenner DJ, Colwell RR, Grimont PAD, Kandler O. International committee on systematic bacteriology. report of the ad hoc committee on the reconciliation of approaches to bacterial systematics. Int J Syst Bacteriol. 1987;37:463–4.Article 

    Google Scholar 
    Richter M, Rossello-Mora R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Nat Acad Sci USA. 2009;106:19126–31.Article 
    CAS 

    Google Scholar 
    Vincent L, Richard D, Olivier G. FastME 2.0: a comprehensive, accurate, and fast distance-based phylogeny inference program. Mol Biol Evol. 2015;32:2798–800.Article 

    Google Scholar 
    Farris JS. Estimating phylogenetictrees from distance matrices. Am Nat. 1972;106:645–68.Article 

    Google Scholar 
    Fang CY, Zhang JL, Pang HC, Li YY, Xin YH, et al. Nocardiopsis flavescens sp. nov., an actinomycete isolated from marine sediment. Int J Syst Evol Microbiol. 2011;61:2640–5.Article 
    CAS 

    Google Scholar  More

  • in

    Aerial transport of bacteria by dust plumes in the Eastern Mediterranean revealed by complementary rRNA/rRNA-gene sequencing

    Katra, I. et al. Richness and diversity in dust stormborne biomes at the Southeast Mediterranean. Sci. Rep. 4, 5265 (2014).CAS 

    Google Scholar 
    Kellogg, C. A. & Griffin, D. W. Aerobiology and the global transport of desert dust. Trends Ecol. Evolution 21, 638–644 (2006).
    Google Scholar 
    Mazar, Y., Cytryn, E., Erel, Y. & Rudich, Y. Effect of dust storms on the atmospheric microbiome in the eastern Mediterranean. Environ. Sci. Technol. 50, 4194–4202 (2016).CAS 

    Google Scholar 
    Gat, D., Mazar, Y., Cytryn, E. & Rudich, Y. Origin-dependent variations in the atmospheric microbiome community in Eastern Mediterranean Dust Storms. Environ. Sci. Technol. 51, 6709–6718 (2017).CAS 

    Google Scholar 
    Lang-Yona, N. et al. Links between airborne microbiome, meteorology, and chemical composition in northwestern Turkey. Sci. Total Environ. 725, 138227 (2020).CAS 

    Google Scholar 
    Gat, D. et al. Size-resolved community structure of bacteria and fungi transported by dust in the Middle East. Front. Microbiol. 12 (2021) https://doi.org/10.3389/fmicb.2021.744117.Hill, T. C. J. et al. Sources of organic ice nucleating particles in soils. Atmos. Chem. Phys. 16, 7195–7211 (2016).CAS 

    Google Scholar 
    Pandey, R. et al. Ice-nucleating bacteria control the order and dynamics of interfacial water. Sci. Adv. 2, e1501630 (2016).
    Google Scholar 
    Fröhlich-Nowoisky, J. et al. Ice nucleation activity in the widespread soil fungus Mortierella alpina. Biogeosciences 12, 1057–1071 (2015).
    Google Scholar 
    Estillore, A. D., Trueblood, J. V. & Grassian, V. H. Atmospheric chemistry of bioaerosols: heterogeneous and multiphase reactions with atmospheric oxidants and other trace gases. Chem. Sci. 7, 6604–6616 (2016).CAS 

    Google Scholar 
    Brodie, E. L. et al. Urban aerosols harbor diverse and dynamic bacterial populations. Proc. Natl. Acad. Sci. 104, 299–304 (2007).CAS 

    Google Scholar 
    Šantl-Temkiv, T. et al. Characterization of airborne ice-nucleation-active bacteria and bacterial fragments. Atmos. Environ. 109, 105–117 (2015).
    Google Scholar 
    Rahav, E., Ovadia, G., Paytan, A. & Herut, B. Contribution of airborne microbes to bacterial production and N2 fixation in seawater upon aerosol deposition. Geophys. Res. Lett. 43, 719–727 (2016).CAS 

    Google Scholar 
    Failor, K. C., Schmale, D. G., Vinatzer, B. A. & Monteil, C. L. Ice nucleation active bacteria in precipitation are genetically diverse and nucleate ice by employing different mechanisms. ISME J. 11, 2740–2753 (2017).CAS 

    Google Scholar 
    de Araujo, G. G., Rodrigues, F., Gonçalves, F. L. T. & Galante, D. Survival and ice nucleation activity of Pseudomonas syringae strains exposed to simulated high-altitude atmospheric conditions. Sci. Rep. 9, 7768 (2019).
    Google Scholar 
    Lazaridis, M. Bacteria as Cloud Condensation Nuclei (CCN) in the Atmosphere. Atmosphere 10, 786 (2019).CAS 

    Google Scholar 
    Amato, P. et al. Active microorganisms thrive among extremely diverse communities in cloud water. PLOS ONE 12, e0182869 (2017).
    Google Scholar 
    Amato, P. et al. Metatranscriptomic exploration of microbial functioning in clouds. Sci. Rep. 9, 4383 (2019).
    Google Scholar 
    Vaïtilingom, M. et al. Potential impact of microbial activity on the oxidant capacity and organic carbon budget in clouds. Proc. Natl. Acad. Sci. 110, 559–564 (2013).
    Google Scholar 
    Triadó-Margarit, X., Cáliz, J. & Casamayor, E. O. A long-term atmospheric baseline for intercontinental exchange of airborne pathogens. Environ. Int. 158, 106916 (2022).
    Google Scholar 
    Brodie, E. L. et al. Urban aerosols harbor diverse and dynamic bacterial populations. Proc. Natl. Acad. Sci. 104, 299 (2007).CAS 

    Google Scholar 
    Archer, S. D. J. et al. Airborne microbial transport limitation to isolated Antarctic soil habitats. Nat. Microbiol 4, 925–932 (2019).CAS 

    Google Scholar 
    Mayol, E. et al. Long-range transport of airborne microbes over the global tropical and subtropical ocean. Nat. Commun. 8, 201 (2017).
    Google Scholar 
    Favet, J. et al. Microbial hitchhikers on intercontinental dust: catching a lift in Chad. ISME J. 7, 850–867 (2013).CAS 

    Google Scholar 
    Cáliz, J., Triadó-Margarit, X., Camarero, L. & Casamayor, E. O. A long-term survey unveils strong seasonal patterns in the airborne microbiome coupled to general and regional atmospheric circulations. Proc. Natl. Acad. Sci. 115, 12229–12234 (2018).
    Google Scholar 
    Du, P., Du, R., Ren, W., Lu, Z. & Fu, P. Seasonal variation characteristic of inhalable microbial communities in PM2.5 in Beijing city, China. Sci. Total Environ. 610-611, 308–315 (2018).CAS 

    Google Scholar 
    Lang-Yona, N. et al. Links between airborne microbiome, meteorology, and chemical composition in northwestern Turkey. Sci. Total Environ. 725, 138227 (2020).CAS 

    Google Scholar 
    Gong, J., Qi, J., E, B., Yin, Y. & Gao, D. Concentration, viability and size distribution of bacteria in atmospheric bioaerosols under different types of pollution. Environ. Pollut. 257, 113485 (2020).CAS 

    Google Scholar 
    Zhang, T., Li, X., Wang, M., Chen, H. & Yao, M. Time- and size-resolved bacterial aerosol dynamics in highly polluted air: new clues for haze formation mechanism. bioRxiv, 513093 (2019) https://doi.org/10.1101/513093.Wei, M. et al. Size distribution of bioaerosols from biomass burning emissions: Characteristics of bacterial and fungal communities in submicron (PM1.0) and fine (PM2.5) particles. Ecotoxicol. Environ. Saf. 171, 37–46 (2019).CAS 

    Google Scholar 
    Blazewicz, S. J., Barnard, R. L., Daly, R. A. & Firestone, M. K. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. Isme J. 7, 2061–2068 (2013).CAS 

    Google Scholar 
    Barnard, R. L., Osborne, C. A. & Firestone, M. K. Responses of soil bacterial and fungal communities to extreme desiccation and rewetting. ISME J. 7, 2229–2241 (2013).CAS 

    Google Scholar 
    Schostag, M. et al. Distinct summer and winter bacterial communities in the active layer of Svalbard permafrost revealed by DNA- and RNA-based analyses. Front. Microbiol. 6 (2015) https://doi.org/10.3389/fmicb.2015.00399.Campbell, B. J., Yu, L., Heidelberg, J. F. & Kirchman, D. L. Activity of abundant and rare bacteria in a coastal ocean. Proc. Natl Acad. Sci. 108, 12776–12781 (2011).CAS 

    Google Scholar 
    Denef, V. J., Fujimoto, M., Berry, M. A. & Schmidt, M. L. Seasonal succession leads to habitat-dependent differentiation in ribosomal RNA:DNA Ratios among freshwater lake bacteria. Front. Microbiol.7 (2016) https://doi.org/10.3389/fmicb.2016.00606.Zhang, Y., Zhao, Z., Dai, M., Jiao, N. & Herndl, G. J. Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea. Mol. Ecol. 23, 2260–2274 (2014).CAS 

    Google Scholar 
    Hospodsky, D., Yamamoto, N. & Peccia, J. Accuracy, precision, and method detection limits of quantitative PCR for airborne bacteria and fungi. Appl Environ. Microbiol 76, 7004–7012 (2010).CAS 

    Google Scholar 
    Nieto-Caballero, M., Savage, N., Keady, P. & Hernandez, M. High fidelity recovery of airborne microbial genetic materials by direct condensation capture into genomic preservatives. J. Microbiological Methods 157, 1–3 (2019).CAS 

    Google Scholar 
    Behzad, H., Gojobori, T. & Mineta, K. Challenges and opportunities of airborne metagenomics. Genome Biol. Evol. 7, 1216–1226 (2015).CAS 

    Google Scholar 
    Šantl-Temkiv, T., Gosewinkel, U., Starnawski, P., Lever, M. & Finster, K. Aeolian dispersal of bacteria in southwest Greenland: their sources, abundance, diversity and physiological states. FEMS Microbiol. Ecol. 94 (2018) https://doi.org/10.1093/femsec/fiy031.Klein, A. M., Bohannan, B. J. M., Jaffe, D. A., Levin, D. A. & Green, J. L. Molecular evidence for metabolically active bacteria in the atmosphere. Front. Microbiol. 7, 772–772 (2016).
    Google Scholar 
    Amato, P. et al. Active microorganisms thrive among extremely diverse communities in cloud water. PLoS One 12, e0182869 (2017).
    Google Scholar 
    Vellend, B. M. Conceptual synthesis in community ecology. Q. Rev. Biol. 85, 183–206 (2010).
    Google Scholar 
    Bodenheimer, S., Lensky, I. M. & Dayan, U. Characterization of Eastern Mediterranean dust storms by area of origin; North Africa vs. Arabian Peninsula. Atmos. Environ. 198, 158–165 (2019).CAS 

    Google Scholar 
    Kishcha, P., Volpov, E., Starobinets, B., Alpert, P. & Nickovic, S. Dust dry deposition over Israel. Atmosphere 11, 197 (2020).
    Google Scholar 
    Krasnov, H., Katra, I. & Friger, M. Increase in dust storm related PM10 concentrations: A time series analysis of 2001-2015. Environ. Pollut. 213, 36–42 (2016).CAS 

    Google Scholar 
    Zittis, G. et al. Climate change and weather extremes in the eastern Mediterranean and Middle East. Rev. Geophysics 60, e2021RG000762 (2022).
    Google Scholar 
    Griffin, D. W. Atmospheric movement of microorganisms in clouds of desert dust and implications for human health. Clin. Microbiol Rev. 20, 459–477 (2007).
    Google Scholar 
    Prospero, J. M. Long-range transport of mineral dust in the global atmosphere: Impact of African dust on the environment of the southeastern United States. Proc. Natl. Acad. Sci. 96, 3396–3403 (1999).CAS 

    Google Scholar 
    Klingmüller, K., Pozzer, A., Metzger, S., Stenchikov, G. L. & Lelieveld, J. Aerosol optical depth trend over the Middle East. Atmos. Chem. Phys. 16, 5063–5073 (2016).
    Google Scholar 
    Notaro, M., Alkolibi, F., Fadda, E. & Bakhrjy, F. Trajectory analysis of Saudi Arabian dust storms. J. Geophys. Res. Atmospheres 118, 6028–6043 (2013).
    Google Scholar 
    Tegen, I. & Schepanski, K. The global distribution of mineral dust. IOP Conf. Ser. Earth Environ. Sci. 7, 012001 (2009).
    Google Scholar 
    Klappenbach, J. A., Saxman, P. R., Cole, J. R. & Schmidt, T. M. rrndb: the Ribosomal RNA Operon Copy Number Database. Nucleic Acids Res. 29, 181–184 (2001).CAS 

    Google Scholar 
    Bremer, H. & Dennis, P. P. Modulation of chemical composition and other parameters of the cell at different exponential growth rates. EcoSal Plus 3 (2008) https://doi.org/10.1128/ecosal.5.2.3.Schneider, D. A., Ross, W. & Gourse, R. L. Control of rRNA expression in Escherichia coli. Curr. Opin. Microbiol 6, 151–156 (2003).CAS 

    Google Scholar 
    Gralla, J. D. Escherichia coli ribosomal RNA transcription: regulatory roles for ppGpp, NTPs, architectural proteins and a polymerase-binding protein. Mol. Microbiol 55, 973–977 (2005).CAS 

    Google Scholar 
    Oliveira, A. et al. Insight of genus corynebacterium: ascertaining the role of pathogenic and non-pathogenic species. Front. Microbiol. 8, 1937–1937 (2017).
    Google Scholar 
    Wexler, H. M. Bacteroides: the good, the bad, and the nitty-gritty. Clin. Microbiol Rev. 20, 593–621 (2007).CAS 

    Google Scholar 
    Duar, R. M. et al. Lifestyles in transition: evolution and natural history of the genus Lactobacillus. FEMS Microbiol. Rev. 41, S27–S48 (2017).
    Google Scholar 
    Magzal, F. et al. Increased physical activity improves gut microbiota composition and reduces short-chain fatty acid concentrations in older adults with insomnia. Sci. Rep. 12, 2265 (2022).CAS 

    Google Scholar 
    Wang, L. et al. Increased abundance of Sutterella spp. and Ruminococcus torques in feces of children with autism spectrum disorder. Mol. Autism 4, 42 (2013).CAS 

    Google Scholar 
    Tavella, T. et al. Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly. Gut microbes 13, 1–19 (2021).
    Google Scholar 
    Bennur, T., Kumar, A. R., Zinjarde, S. & Javdekar, V. Nocardiopsis species: Incidence, ecological roles and adaptations. Microbiological Res. 174, 33–47 (2015).
    Google Scholar 
    Jones, S. E. & Elliot, M. A. Streptomyces exploration: competition, volatile communication and new bacterial behaviours. Trends Microbiol. 25, 522–531 (2017).CAS 

    Google Scholar 
    Gtari, M. et al. Contrasted resistance of stone-dwelling Geodermatophilaceae species to stresses known to give rise to reactive oxygen species. FEMS Microbiol. Ecol. 80, 566–577 (2012).CAS 

    Google Scholar 
    Weon, H.-Y. et al. Adhaeribacter aerophilus sp. nov., Adhaeribacter aerolatus sp. nov. and Segetibacter aerophilus sp. nov., isolated from air samples. Int. J. Syst. Evolut. Microbiol. 60, 2424–2429 (2010).CAS 

    Google Scholar 
    Marín, I. et al.) 115-133 (Springer Berlin Heidelberg, 2014).Yoon, J.-H. et al.) 1099-1113 (Springer New York, 2006).Steinberg, J. P. & Burd, E. M. in Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases (Eighth Edition) (eds John E. Bennett, R. Dolin, & M. J. Blaser) 2667-2683.e2664 (W.B. Saunders, 2015).Kelly, D. P., et al.) 232-249 (Springer New York, 2006).Silby, M. W., Winstanley, C., Godfrey, S. A. C., Levy, S. B. & Jackson, R. W. Pseudomonas genomes: diverse and adaptable. FEMS Microbiol. Rev. 35, 652–680 (2011).CAS 

    Google Scholar 
    Hyeon, J. W. & Jeon, C. O. Roseomonas aerofrigidensis sp. nov., isolated from an air conditioner. Int. J. Syst. Evolut. Microbiol. 67, 4039–4044 (2017).CAS 

    Google Scholar 
    Battista, J. R. & Rainey, F. A. in Bergey’s Manual of Systematics of Archaea and Bacteria 1-13.Angly, F. E. et al. Marine microbial communities of the Great Barrier Reef lagoon are influenced by riverine floodwaters and seasonal weather events. PeerJ 4, e1511 (2016).
    Google Scholar 
    Cárdenas, A., Rodriguez-R, L. M., Pizarro, V., Cadavid, L. F. & Arévalo-Ferro, C. Shifts in bacterial communities of two caribbean reef-building coral species affected by white plague disease. ISME J. 6, 502–512 (2012).
    Google Scholar 
    Kämpfer, P., Lodders, N., Huber, B., Falsen, E. & Busse, H. J. Deinococcus aquatilis sp. nov., isolated from water. Int J. Syst. Evol. Microbiol 58, 2803–2806 (2008).
    Google Scholar 
    Gallego, V., Sánchez-Porro, C., García, M. T. & Ventosa, A. Roseomonas aquatica sp. nov., isolated from drinking water. Int J. Syst. Evol. Microbiol 56, 2291–2295 (2006).CAS 

    Google Scholar 
    Roskin, J., Katra, I. & Blumberg, D. G. Particle-size fractionation of eolian sand along the Sinai–Negev erg of Egypt and Israel. GSA Bull. 126, 47–65 (2014).
    Google Scholar 
    Ganor, E. & Foner, H. A. Mineral dust concentrations, deposition fluxes and deposition velocities in dust episodes over Israel. J. Geophys. Res.: Atmospheres 106, 18431–18437 (2001).CAS 

    Google Scholar 
    Amir, A., Ozel, E., Haberman, Y. & Shental, N. Achieving pan-microbiome biological insights via the dbBact knowledge base. bioRxiv, 2022.2002.2027.482174 (2022) https://doi.org/10.1101/2022.02.27.482174.Eisenhofer, R. et al. Contamination in low microbial biomass microbiome studies: issues and recommendations. Trends Microbiol. 27, 105–117 (2019).CAS 

    Google Scholar 
    Labeda, D. P. & Goodfellow, M. in Bergey’s Manual of Systematics of Archaea and Bacteria 1-7.Rickard, A. H. et al. Adhaeribacter aquaticus gen. nov., sp. nov., a Gram-negative isolate from a potable water biofilm. Int J. Syst. Evol. Microbiol 55, 821–829 (2005).CAS 

    Google Scholar 
    Guo, L. et al. Oligotrophic bacterium Hymenobacter latericoloratus CGMCC 16346 degrades the neonicotinoid imidacloprid in surface water. AMB Express 10, 7 (2020).CAS 

    Google Scholar 
    Philippon, T. et al. Denitrifying bio-cathodes developed from constructed wetland sediments exhibit electroactive nitrate reducing biofilms dominated by the genera Azoarcus and Pontibacter. Bioelectrochemistry 140, 107819 (2021).CAS 

    Google Scholar 
    Jurado, V., Miller, A. Z., Alias-Villegas, C., Laiz, L. & Saiz-Jimenez, C. Rubrobacter bracarensis sp. nov., a novel member of the genus Rubrobacter isolated from a biodeteriorated monument. Syst. Appl Microbiol 35, 306–309 (2012).CAS 

    Google Scholar 
    de Vries, H. J. et al. Isolation and characterization of Sphingomonadaceae from fouled membranes. npj Biofilms Microbiomes 5, 6 (2019).
    Google Scholar 
    Vacca, M. et al. The Controversial Role of Human Gut Lachnospiraceae. Microorganisms 8, 573 (2020).CAS 

    Google Scholar 
    Baldani, J. I. et al. in The Prokaryotes: Alphaproteobacteria and Betaproteobacteria (eds Eugene Rosenberg et al.) 919-974 (Springer Berlin Heidelberg, 2014).Dastager, S. G., et al.) 455-498 (Springer Berlin Heidelberg, 2014).Ivanova, N. et al. Complete genome sequence of Geodermatophilus obscurus type strain (G-20). Stand Genom. Sci. 2, 158–167 (2010).
    Google Scholar 
    Alonso-Reyes, D. et al. Genomic Insights of an Andean Multi-resistant Soil Actinobacterium of Biotechnological Interest. bioRxiv, 2020.2012.2021.423370 (2020) https://doi.org/10.1101/2020.12.21.423370.Kumar, C. G. & Sujitha, P. Kocuran, an exopolysaccharide isolated from Kocuria rosea strain BS-1 and evaluation of its in vitro immunosuppression activities. Enzym. Micro. Technol. 55, 113–120 (2014).CAS 

    Google Scholar 
    Raguénès, G. et al. A novel exopolymer-producing bacterium, Paracoccus zeaxanthinifaciens subsp. payriae, isolated from a “kopara” mat located in Rangiroa, an atoll of French Polynesia. Curr. Microbiol 49, 145–151 (2004).
    Google Scholar 
    Bailey, A. C. et al. Draft Genome Sequence of Massilia sp. Strain BSC265, Isolated from Biological Soil Crust of Moab, Utah. Genome Announc 2, e01199–01114 (2014).
    Google Scholar 
    Denef, V. J., Fujimoto, M., Berry, M. A. & Schmidt, M. L. Seasonal succession leads to habitat-dependent differentiation in ribosomal RNA:DNA Ratios among freshwater lake bacteria. Front Microbiol 7, 606 (2016).
    Google Scholar 
    Salazar, G. et al. Particle-association lifestyle is a phylogenetically conserved trait in bathypelagic prokaryotes. Mol. Ecol. 24, 5692–5706 (2015).
    Google Scholar 
    Schmidt, M. L., White, J. D. & Denef, V. J. Phylogenetic conservation of freshwater lake habitat preference varies between abundant bacterioplankton phyla. Environ. Microbiol. 18, 1212–1226 (2016).
    Google Scholar 
    Stepanauskas, R. et al. Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles. Nat. Commun. 8, 84 (2017).
    Google Scholar 
    Doughari, H. J., Ndakidemi, P. A., Human, I. S. & Benade, S. The ecology, biology and pathogenesis of Acinetobacter spp.: an overview. Microbes Environ. 26, 101–112 (2011).
    Google Scholar 
    Bläckberg, A., Falk, L., Oldberg, K., Olaison, L. & Rasmussen, M. infective endocarditis due to corynebacterium species: clinical features and antibiotic resistance. Open Forum Infect. Dis. 8 (2021) https://doi.org/10.1093/ofid/ofab055.Zhang, Q. et al. Hymenobacter xinjiangensis sp. nov., a radiation-resistant bacterium isolated from the desert of Xinjiang, China. Int J. Syst. Evol. Microbiol 57, 1752–1756 (2007).CAS 

    Google Scholar 
    Lee, J.-J. et al. Hymenobacter aquaticus sp. nov., a radiation-resistant bacterium isolated from a river. Int. J. Syst. Evolut. Microbiol. 67, 1206–1211 (2017).CAS 

    Google Scholar 
    Alessa, O. et al. Comprehensive comparative genomics and phenotyping of methylobacterium species. Front. Microbiol. 12 (2021) https://doi.org/10.3389/fmicb.2021.740610.Titécat, M., Wallet, F., Vieillard, M. H., Courcol, R. J. & Loïez, C. Ruminococcus gnavus: an unusual pathogen in septic arthritis. Anaerobe 30, 159–160 (2014).
    Google Scholar 
    Weber, B. S., Harding, C. M. & Feldman, M. F. Pathogenic acinetobacter: from the cell surface to infinity and beyond. J. Bacteriol. 198, 880–887 (2015).
    Google Scholar 
    Hacker, E., Antunes, C. A., Mattos-Guaraldi, A. L., Burkovski, A. & Tauch, A. Corynebacterium ulcerans, an emerging human pathogen. Future Microbiol. 11, 1191–1208 (2016).CAS 

    Google Scholar 
    Smith, K. F. & Oram, D. M. in Encyclopedia of Microbiology (Third Edition) (ed Moselio Schaechter) 94-106 (Academic Press, 2009).Kovaleva, J., Degener, J. E. & van der Mei, H. C. Methylobacterium and its role in health care-associated infection. J. Clin. Microbiol 52, 1317–1321 (2014).
    Google Scholar 
    Dyer, J. & Harris, P. Paracoccus yeei—An emerging pathogen or incidental finding? Pathology 52, S123 (2020).
    Google Scholar 
    Moradali, M. F., Ghods, S. & Rehm, B. H. A. Pseudomonas aeruginosa lifestyle: a paradigm for adaptation, survival, and persistence. Front. Cellular Infect. Microbiol. 7 (2017) https://doi.org/10.3389/fcimb.2017.00039.Ryan, M. P. & Adley, C. C. Sphingomonas paucimobilis: a persistent Gram-negative nosocomial infectious organism. J. Hosp. Infect. 75, 153–157 (2010).CAS 

    Google Scholar 
    Souto, A., Guinda, M., Mera, A. & Pardo, F. Septic arthritis caused by Sphingomonas paucimobilis in an immunocompetent patient. Reumatol. Clin. 8, 378–379 (2012).
    Google Scholar 
    Lanoix, J. P. et al. Sphingomonas paucimobilis bacteremia related to intravenous human immunoglobulin injections. Med Mal. Infect. 42, 37–39 (2012).
    Google Scholar 
    van Bruggen, A. H., Brown, P. R. & Jochimsen, K. N. Corky root of lettuce caused by strains of a gram-negative bacterium from muck soils of Florida, new york, and wisconsin. Appl Environ. Microbiol 55, 2635–2640 (1989).
    Google Scholar 
    VAN BRUGGEN, A. H. C., JOCHIMSEN, K. N. & BROWN, P. R. Rhizomonas suberifaciens gen. nov., sp. nov., the Causal Agent of Corky Root of Lettuce. Int. J. Syst. Evolut. Microbiol. 40, 175–188 (1990).
    Google Scholar 
    Davis, J. H. & Williamson, J. R. Structure and dynamics of bacterial ribosome biogenesis. Philos. Trans. R Soc. Lond. B Biol. Sci. 372 (2017) https://doi.org/10.1098/rstb.2016.0181.Maitra, A. & Dill, K. A. Bacterial growth laws reflect the evolutionary importance of energy efficiency. Proc. Natl Acad. Sci. 112, 406–411 (2015).CAS 

    Google Scholar 
    Klumpp, S. & Hwa, T. Traffic patrol in the transcription of ribosomal RNA. RNA Biol. 6, 392–394 (2009).CAS 

    Google Scholar 
    Jia, Y. et al. Rare taxa exhibit disproportionate cell-level metabolic activity in enriched anaerobic digestion microbial communities. mSystems 4, e00208–e00218 (2019).CAS 

    Google Scholar 
    Zhou, Y. et al. Profiling airborne microbiota in mechanically ventilated buildings across seasons in hong kong reveals higher metabolic activity in low-abundance bacteria. Environ. Sci. Technol. 55, 249–259 (2021).CAS 

    Google Scholar 
    Fessler, M., Gummesson, B., Charbon, G., Svenningsen, S. L. & Sørensen, M. A. Short-term kinetics of rRNA degradation in Escherichia coli upon starvation for carbon, amino acid or phosphate. Mol. Microbiol. 113, 951–963 (2020).CAS 

    Google Scholar 
    Lahtinen, S. J. et al. Degradation of 16S rRNA and attributes of viability of viable but nonculturable probiotic bacteria. Lett. Appl Microbiol 46, 693–698 (2008).CAS 

    Google Scholar 
    Li, R. et al. Comparison of DNA-, PMA-, and RNA-based 16S rRNA Illumina sequencing for detection of live bacteria in water. Sci. Rep. 7, 5752 (2017).
    Google Scholar 
    McKillip, J. L., Jaykus, L. A. & Drake, M. rRNA stability in heat-killed and UV-irradiated enterotoxigenic Staphylococcus aureus and Escherichia coli O157:H7. Appl Environ. Microbiol 64, 4264–4268 (1998).CAS 

    Google Scholar 
    Sheridan, G. E., Masters, C. I., Shallcross, J. A. & MacKey, B. M. Detection of mRNA by reverse transcription-PCR as an indicator of viability in Escherichia coli cells. Appl. Environ. Microbiol. 64, 1313–1318 (1998).CAS 

    Google Scholar 
    Villarino, A., Bouvet, O. M., Regnault, B., Martin-Delautre, S. & Grimont, P. A. D. Exploring the frontier between life and death in Escherichia coli: evaluation of different viability markers in live and heat- or UV-killed cells. Res Microbiol 151, 755–768 (2000).CAS 

    Google Scholar 
    Schostag, M. D., Albers, C. N., Jacobsen, C. S. & Priemé, A. Low turnover of soil bacterial rRNA at low temperatures. Front. Microbiol. 11 (2020) https://doi.org/10.3389/fmicb.2020.00962.Emerson, J. B. et al. Schrödinger’s microbes: Tools for distinguishing the living from the dead in microbial ecosystems. Microbiome 5, 86 (2017).
    Google Scholar 
    Wang, Y. et al. Characterizing microbial community viability with RNA-based high-throughput sequencing. Microbiome Version 1, posted 22 Jul, 2022 (2022) https://doi.org/10.21203/rs.3.rs-1870950/v1.Mbareche, H., Veillette, M., Bilodeau, G. J., Duchaine, C. & Schaffner, D. W. Bioaerosol sampler choice should consider efficiency and ability of samplers to cover microbial diversity. Appl. Environ. Microbiol. 84, e01589–01518 (2018).CAS 

    Google Scholar 
    Pan, M., Lednicky, J. A. & Wu, C.-Y. Collection, particle sizing and detection of airborne viruses. J. Appl. Microbiol. 127, 1596–1611 (2019).CAS 

    Google Scholar 
    Nieto-Caballero, M., Savage, N., Keady, P. & Hernandez, M. High fidelity recovery of airborne microbial genetic materials by direct condensation capture into genomic preservatives. J. Microbiol Methods 157, 1–3 (2019).CAS 

    Google Scholar 
    Šantl-Temkiv, T., Gosewinkel, U., Starnawski, P., Lever, M. & Finster, K. Aeolian dispersal of bacteria in southwest Greenland: their sources, abundance, diversity and physiological states. FEMS Microbiol Ecol 94 (2018) https://doi.org/10.1093/femsec/fiy031.Maki, T. et al. Aeolian dispersal of bacteria associated with desert dust and anthropogenic particles over continental and oceanic surfaces. J. Geophys. Res.: Atmospheres 124, 5579–5588 (2019).
    Google Scholar 
    Gonzalez-Martin, C., Teigell-Perez, N., Valladares, B. & Griffin, D. W. in Advances in Agronomy Vol. 127 (ed Donald Sparks) 1-41 (Academic Press, 2014).Tisch Environmental, I. (2004).Krasnov, H., Katra, I. & Friger, M. Increase in dust storm related PM10 concentrations: A time series analysis of 2001–2015. Environ. Pollut. 213, 36–42 (2016).CAS 

    Google Scholar 
    Varga, G., Újvári, G. & Kovács, J. Spatiotemporal patterns of Saharan dust outbreaks in the Mediterranean Basin. Aeolian Res. 15, 151–160 (2014).
    Google Scholar 
    Dayan, U. & Levy, I. Relationship between synoptic-scale atmospheric circulation and ozone concentrations over Israel. J. Geophys. Res.: Atmospheres 107, ACL 31-31–ACL 31-12 (2002).
    Google Scholar 
    Klein, A. M., Bohannan, B. J. M., Jaffe, D. A., Levin, D. A. & Green, J. L. Molecular Evidence for Metabolically Active Bacteria in the Atmosphere. Front. Microbiol. 7 (2016) https://doi.org/10.3389/fmicb.2016.00772.Luhung, I. et al. Experimental parameters defining ultra-low biomass bioaerosol analysis. npj Biofilms Microbiomes 7, 37 (2021).CAS 

    Google Scholar 
    Stein, A. F. et al. Noaa’s Hysplit Atmospheric Transport and Dispersion Modeling System. Bull. Am. Meteorological Soc. 96, 2059–2077 (2015).
    Google Scholar 
    Rolph, G., Stein, A. & Stunder, B. Real-time Environmental Applications and Display sYstem: READY. Environ. Model. Softw. 95, 210–228 (2017).
    Google Scholar 
    Acker, J. G. & Leptoukh, G. Online analysis enhances use of NASA Earth science data. Eos, Trans. Am. Geophys. Union 88, 14–17 (2007).
    Google Scholar 
    Brauer, S. L. et al. Culturable Rhodobacter and Shewanella species are abundant in estuarine turbidity maxima of the Columbia River. Environ. Microbiol. 13, 589–603 (2011).CAS 

    Google Scholar 
    Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. Isme J. 6, 1621–1624 (2012).CAS 

    Google Scholar 
    Soergel, D. A. W., Dey, N., Knight, R. & Brenner, S. E. Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. ISME J. 6, 1440–1444 (2012).CAS 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581 (2016).CAS 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).CAS 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).CAS 

    Google Scholar 
    Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A. & Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 226 (2018).
    Google Scholar 
    Martin-Fernandez, J. A., Hron, K., Templ, M., Filzmoser, P. & Palarea-Albaladejo, J. Bayesian-multiplicative treatment of count zeros in compositional data sets. Stat. Model. 15 (2015) https://doi.org/10.1177/1471082×14535524.Palarea-Albaladejo, J. & Martin-Fernandez, J. A. zCompositions—R Package for multivariate imputation of left-censored data under a compositional approach. Chemometrics Intell. Lab. Syst. 143, 85–96 (2015).CAS 

    Google Scholar 
    van den Boogaart, K. G. & Tolosana-Delgado, R. “compositions”: A unified R package to analyze compositional data. Comput. Geosci. 34, 320–338 (2008).
    Google Scholar 
    Amato, P. et al. In Microbiology of Aerosols 1–21 (2017).Rao, A. K. & Whitby, K. T. Nonideal collection characteristics of single stage and cascade impactors. Am. Ind. Hyg. Assoc. J. 38, 174–179 (1977).CAS 

    Google Scholar 
    Jari Oksanen, F. G. B. et al. vegan: Community Ecology Package. (2020).Gilmour, S. G. In Wiley StatsRef: Statistics Reference Online.Margolin, B. H. In Wiley StatsRef: Statistics Reference Online.Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 57, 289–300 (1995).
    Google Scholar 
    Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLOS Comput. Biol. 17, e1009442 (2021).CAS 

    Google Scholar  More