Ecology

1.The State of World Fisheries and Aquaculture 2020 (Food and Agriculture Organization of the United Nations, 2020).2.Ohayon, S., Granot, I. & Belmaker, J. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-021-01502-3 (2021).3.Lester, S. E. et al. Mar. Ecol. Prog. Ser. 384, 33–46 (2009).Article 

Google Scholar 
4.Dwyer, R. G. et al. Curr. Biol. 30, 480–489 (2020).CAS 
Article 

Google Scholar 
5.Krueck, N. C. et al. Conserv. Lett. 11, e12415 (2018).Article 

Google Scholar 
6.Harrison, H. B., Bode, M., Williamson, D. H., Berumen, M. L. & Jones, G. P. Proc. Natl Acad. Sci. USA 117, 25595–25600 (2020).CAS 
Article 

Google Scholar 
7.Harrison, H. B. et al. Curr. Biol. 22, 1023–1028 (2012).CAS 
Article 

Google Scholar 
8.Williamson, D. H. et al. Mol. Ecol. 25, 6039–6054 (2016).Article 

Google Scholar 
9.Edgar, G. J. et al. Nature 506, 216–220 (2014).CAS 
Article 

Google Scholar 
10.Cinner, J. E. et al. Proc. Natl Acad. Sci. USA 115, E6116–E6125 (2018).CAS 
Article 

Google Scholar 
11.McClanahan, T. R. Mar. Policy 119, 104022 (2020).Article 

Google Scholar 
12.Worm, B. & Branch, T. A. Trends Ecol. Evol. 27, 594–599 (2012).Article 

Google Scholar 
13.Costello, C. et al. Proc. Natl Acad. Sci. USA 113, 5125–5129 (2016).CAS 
Article 

Google Scholar 
14.Mora, C. et al. PLoS Biol. 7, e1000131 (2009).Article 

Google Scholar 
15.White, A. T. et al. Coastal Manage. 42, 87–106 (2014).Article 

Google Scholar 
16.Abesamis, R. A. & Russ, G. R. Ecol. Appl. 15, 1798–1812 (2005).Article 

Google Scholar 
17.Claudet, J. et al. Ecol. Lett. 11, 481–489 (2008).Article 

Google Scholar 
18.Halpern, B. S., Gaines, S. D. & Warner, R. R. Ecol. Appl. 14, 1248–1256 (2004).Article 

Google Scholar 
19.Krueck, N. C. et al. Ecol. Appl. 27, 925–941 (2017).Article 

Google Scholar 
20.Krueck, N. C. et al. PLoS Biol. 15, e2000537 (2017).Article 

Google Scholar 
21.Kellner, J. B., Tetreault, I., Gaines, S. D. & Nisbet, R. M. Ecol. Appl. 17, 1039–1054 (2007).Article 

Google Scholar 
22.Krueck, N. C., Abdurrahim, A. Y., Adhuri, D. S., Mumby, P. J. & Ross, H. Ecol. Soc. 24, 6 (2019).Article 

Google Scholar 
23.Green, A. L. et al. Biol. Rev. 90, 1215–1247 (2015).Article 

Google Scholar  More

1.Pan, Y. D. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).Article 

Google Scholar 
2.Baccini, A. et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Change 2, 182–185 (2012).Article 

Google Scholar 
3.Matricardi, E. A. T. et al. Long-term forest degradation surpasses deforestation in the Brazilian Amazon. Science 369, 1378–1382 (2020).Article 

Google Scholar 
4.Bullock, E. L., Woodcock, C. E., Souza, C. & Olofsson, P. Satellite-based estimates reveal widespread forest degradation in the Amazon. Glob. Change Biol. 26, 2956–2969 (2020).Article 

Google Scholar 
5.Aragao, L. E. O. C. et al. 21st century drought-related fires counteract the decline of Amazon deforestation carbon emissions. Nat. Commun. 9, 536 (2018).Article 

Google Scholar 
6.Chaplin-Kramer, R. et al. Degradation in carbon stocks near tropical forest edges. Nat. Commun. 6, 10158 (2015).Article 

Google Scholar 
7.Taubert, F. et al. Global patterns of tropical forest fragmentation. Nature 554, 519–522 (2018).Article 

Google Scholar 
8.Kunert, N., Teophilo Aparecido, L. M., Higuchi, N., dos Santos, J. & Trumbore, S. Higher tree transpiration due to road-associated edge effects in a tropical moist lowland forest. Agric. For. Meteorol. 213, 183–192 (2015).Article 

Google Scholar 
9.Broadbent, E. N. et al. Forest fragmentation and edge effects from deforestation and selective logging in the Brazilian Amazon. Biol. Conserv. 141, 1745–1757 (2008).Article 

Google Scholar 
10.Laurance, W. F. et al. Biomass collapse in Amazonian forest fragments. Science 278, 1117–1118 (1997).Article 

Google Scholar 
11.Qie, L. et al. Long-term carbon sink in Borneo’s forests halted by drought and vulnerable to edge effects. Nat. Commun. 8, 1966 (2017).Article 

Google Scholar 
12.Haddad, N. M. et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1, e150005 (2015).Article 

Google Scholar 
13.Briant, G., Gond, V. & Laurance, S. G. W. Habitat fragmentation and the desiccation of forest canopies: a case study from eastern Amazonia. Biol. Conserv. 143, 2763–2769 (2010).Article 

Google Scholar 
14.Laurance, W. F. et al. The fate of Amazonian forest fragments: a 32-year investigation. Biol. Conserv. 144, 56–67 (2011).Article 

Google Scholar 
15.FAOSTAT Database (FAO, 2020); http://www.fao.org/faostat/en/#data/FO16.World Urbanization Prospects: The 2018 Revision (UN Department of Economic and Social Affairs, 2018).17.Brandt, M. et al. Reduction of tree cover in West African woodlands and promotion in semi-arid farmlands. Nat. Geosci. 11, 328–333 (2018).Article 

Google Scholar 
18.Hufkens, K. et al. Historical aerial surveys map long-term changes of forest cover and structure in the central Congo basin. Remote Sens. 12, 638 (2020).Article 

Google Scholar 
19.van der Werf, G. R. et al. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009). Atmos. Chem. Phys. 10, 11707–11735 (2010).Article 

Google Scholar 
20.Ichoku, C. et al. Biomass burning, land-cover change, and the hydrological cycle in northern sub-Saharan Africa. Environ. Res. Lett. 11, 095005 (2016).Article 

Google Scholar 
21.Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).Article 

Google Scholar 
22.Santoro, M. et al. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations. Preprint at Copernicus https://doi.org/10.5194/essd-2020-148 (2020).23.Santoro, M. & Cartus, O. GlobBiomass dataset of forest biomass, Africa (25 m). Zenodo https://doi.org/10.5281/zenodo.4725667 (2020).24.Chuvieco, E., Pettinari, L. M., Lizundia Loiola, J., Storm, T. & Padilla Parellada, M. ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Grid Product Version 5.1 (Centre for Environmental Data Analysis, 2019).25.Friedl, M. & Sulla-Menashe, D. MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2019); https://doi.org/10.5067/MODIS/MCD12Q1.00626.Laurance, W. F. Theory meets reality: how habitat fragmentation research has transcended island biogeographic theory. Biol. Conserv. 141, 1731–1744 (2008).Article 

Google Scholar 
27.Brinck, K. et al. High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle. Nat. Commun. 8, 14855 (2017).Article 

Google Scholar 
28.Kato, S. et al. Surface irradiances of edition 4.0 Clouds and the Earth’s radiant Energy System (CERES) Energy Balanced and Filled (EBAF) data product. J. Clim. 31, 4501–4527 (2018).Article 

Google Scholar 
29.Running, S., Mu, Q. & Zhao, M. MOD16A2 MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2017); https://doi.org/10.5067/MODIS/MOD16A2.00630.Hurtt, G. C. et al. Harmonization of global land-use change and management for the period 850–2100 (LUH2) for CMIP6. Geosci. Model Dev. 13, 5425–5464 (2020).Article 

Google Scholar 
31.Gaviria, J., Turner, B. L. & Engelbrecht, B. M. J. Drivers of tree species distribution across a tropical rainfall gradient. Ecosphere 8, e01712 (2017).Article 

Google Scholar 
32.Alemayehu, T., van Griensven, A., Woldegiorgis, B. T. & Bauwens, W. An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems. Hydrol. Earth Syst. Sci. 21, 4449–4467 (2017).Article 

Google Scholar 
33.Kotto-Same, J., Woomer, P. L., Appolinaire, M. & Louis, Z. Carbon dynamics in slash-and-burn agriculture and land use alternatives of the humid forest zone in Cameroon. Agric. Ecosyst. Environ. 65, 245–256 (1997).Article 

Google Scholar 
34.Tyukavina, A. et al. Congo basin forest loss dominated by increasing smallholder clearing. Sci. Adv. 4, eaat2993 (2018).Article 

Google Scholar 
35.Rejou-Mechain, M. et al. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences 11, 6827–6840 (2014).Article 

Google Scholar 
36.Tropek, R. et al. Comment on “high-resolution global maps of 21st-century forest cover change”. Science 344, 981 (2014).Article 

Google Scholar 
37.Global Forest Watch (World Resources Institute, 2019); https://data.globalforestwatch.org/datasets/planted-forests38.Roteta, E., Bastarrika, A., Padilla, M., Storm, T. & Chuvieco, E. Development of a Sentinel-2 burned area algorithm: generation of a small fire database for sub-Saharan Africa. Remote Sens. Environ. 222, 1–17 (2019).Article 

Google Scholar 
39.Bouvet, A. et al. An above-ground biomass map of African savannahs and woodlands at 25 m resolution derived from ALOS PALSAR. Remote Sens. Environ. 206, 156–173 (2018).Article 

Google Scholar 
40.Laurance, S. G. W. Responses of understory rain forest birds to road edges in central Amazonia. Ecol. Appl. 14, 1344–1357 (2004).Article 

Google Scholar 
41.Cochrane, M. A. & Laurance, W. F. Synergisms among fire, land use, and climate change in the Amazon. AMBIO 37, 522–527 (2008).Article 

Google Scholar 
42.Khanna, J., Medvigy, D., Fueglistaler, S. & Walko, R. Regional dry-season climate changes due to three decades of Amazonian deforestation. Nat. Clim. Change 7, 200–204 (2017).Article 

Google Scholar 
43.Brienen, R. J. W. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344–348 (2015).Article 

Google Scholar  More

1.Costello, M. J. & Ballantine, B. Biodiversity conservation should focus on no-take marine reserves: 94% of marine protected areas allow fishing. Trends Ecol. Evol. 30, 507–509 (2015).PubMed 
PubMed Central 

Google Scholar 
2.Edgar, G. J. et al. Global conservation outcomes depend on marine protected areas with five key features. Nature 506, 216–220 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
3.Giakoumi, S. et al. Ecological effects of full and partial protection in the crowded Mediterranean Sea: a regional meta-analysis. Sci. Rep. 7, 8940 (2017).PubMed 
PubMed Central 

Google Scholar 
4.Sala, E. & Giakoumi, S. No-take marine reserves are the most effective protected areas in the ocean. ICES J. Mar. Sci. 75, 1166–1168 (2018).
Google Scholar 
5.Woodroffe, R. & Ginsberg, J. R. Edge effects and the extinction of populations inside protected areas. Science 280, 2126–2128 (1998).CAS 
PubMed 
PubMed Central 

Google Scholar 
6.Hansen, A. J. & Defries, R. Ecological mechanisms linking protected areas to surrounding lands. Ecol. Appl. 17, 974–988 (2016).
Google Scholar 
7.Roberts, C. M., Halpern, B., Palumbi, S. R. & Warner, R. R. Designing marine reserve networks. Why small, isolated protected areas are not enough. Conserv. Pract. 2, 10–17 (2001).
Google Scholar 
8.Walters, C. Impacts of dispersal, ecological interactions, and fishing effort dynamics on efficacy of marine protected areas: how large should protected areas be? Bull. Mar. Sci. 66, 745–757 (2000).
Google Scholar 
9.Kramer, D. L. & Chapman, M. R. Implications of fish home range size and relocation for marine reserve function. Environ. Biol. Fishes 55, 65–79 (1999).
Google Scholar 
10.Guidetti, P. et al. Large-scale assessment of Mediterranean marine protected areas effects on fish assemblages. PLoS One 9, e91841 (2014).PubMed 
PubMed Central 

Google Scholar 
11.Lester, S. E. et al. Biological effects within no-take marine reserves: a global synthesis. Mar. Ecol. Prog. Ser. 384, 33–46 (2009).
Google Scholar 
12.Di Lorenzo, M., Claudet, J. & Guidetti, P. Spillover from marine protected areas to adjacent fisheries has an ecological and a fishery component. J. Nat. Conserv. 32, 62–66 (2016).
Google Scholar 
13.Harmelin-Vivien, M. et al. Gradients of abundance and biomass across reserve boundaries in six Mediterranean marine protected areas: evidence of fish spillover? Biol. Conserv. 141, 1829–1839 (2008).
Google Scholar 
14.Abesamis, R. A. & Russ, G. R. Density-dependent spillover from a marine reserve: long-term evidence. Ecol. Appl. 15, 1798–1812 (2005).
Google Scholar 
15.Murawski, S. A., Wigley, S. E., Fogarty, M. J., Rago, P. J. & Mountain, D. G. Effort distribution and catch patterns adjacent to temperate MPAs. ICES J. Mar. Sci. 62, 1150–1167 (2005).
Google Scholar 
16.Kellner, J. B., Tetreault, I., Gaines, S. D. & Nisbet, R. M. Fishing the line near marine reserves in single and multispecies fisheries. Ecol. Appl. 17, 1039–1054 (2007).PubMed 
PubMed Central 

Google Scholar 
17.Stelzenmüller, V. et al. Spatial assessment of fishing effort around European marine reserves: implications for successful fisheries management. Mar. Pollut. Bull. 56, 2018–2026 (2008).PubMed 
PubMed Central 

Google Scholar 
18.Halpern, B. S., Lester, S. E. & Kellner, J. B. Spillover from marine reserves and the replenishment of fished stocks. Environ. Conserv. 36, 268–276 (2010).
Google Scholar 
19.Newmark, W. D. Isolation of African protected areas. Front. Ecol. Environ. 6, 321–328 (2008).
Google Scholar 
20.Defries, R., Hansen, A., Newton, A. C. & Hansen, M. C. Increasing isolation of protected areas in tropical forests over the past twenty years. Ecol. Appl. 15, 19–26 (2005).
Google Scholar 
21.MPAtlas (Marine Conservation Institute, accessed 4 July 2020); http://www.mpatlas.org22.Willis, T. J., Millar, R. B., Babcock, R. C. & Tolimieri, N. Burdens of evidence and the benefits of marine reserves: putting Descartes before des horse? Environ. Conserv. 30, 97–103 (2003).
Google Scholar 
23.Roberts, C. M. et al. Application of ecological criteria in selecting marine reserves and developing reserve networks. Ecol. Appl. 13, 215–228 (2003).
Google Scholar 
24.Huntington, B. E., Karnauskas, M., Babcock, E. A. & Lirman, D. Untangling natural seascape variation from marine reserve effects using a landscape approach. PLoS One 5, e12327 (2010).PubMed 
PubMed Central 

Google Scholar 
25.Miller, K. I. & Russ, G. R. Studies of no-take marine reserves: methods for differentiating reserve and habitat effects. Ocean Coast. Manag. 96, 51–60 (2014).
Google Scholar 
26.Gill, D. A. et al. Capacity shortfalls hinder the performance of marine protected areas globally. Nature 543, 665–671 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
27.Brill, G. C. & Raemaekers, S. J. P. N. A decade of illegal fishing in Table Mountain National Park (2000–2009): trends in the illicit harvest of abalone Haliotis midae and West Coast rock lobster Jasus lalandii. African. J. Mar. Sci. 35, 491–500 (2013).
Google Scholar 
28.Harasti, D., Davis, T. R., Jordan, A., Erskine, L. & Moltschaniwskyj, N. Illegal recreational fishing causes a decline in a fishery targeted species (snapper: Chrysophrys auratus) within a remote no-take marine protected area. PLoS One 14, e0209926 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
29.Kleiven, P. J. N. et al. Fishing pressure impacts the abundance gradient of European lobsters across the borders of a newly established marine protected area. Proc. R. Soc. B Biol. Sci. 286, 20182455 (2019).
Google Scholar 
30.Simpson, S. D. et al. Anthropogenic noise increases fish mortality by predation. Nat. Commun. 7, 10544 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
31.Sarà, G. et al. Effect of boat noise on the behavior of bluefin tuna Thunnus thynnus in the Mediterranean Sea. Mar. Ecol. Prog. Ser. 331, 243–253 (2007).
Google Scholar 
32.Tran, D. S. C., Langel, K. A., Thomas, M. J. & Blumstein, D. T. Spearfishing-induced behavioral changes of an unharvested species inside and outside a marine protected area. Curr. Zool. 62, 39–44 (2016).PubMed 
PubMed Central 

Google Scholar 
33.Jiao, J., Pilyugin, S. S., Riotte-Lambert, L. & Osenberg, C. W. Habitat-dependent movement rate can determine the efficacy of marine protected areas. Ecology 99, 2485–2495 (2018).PubMed 
PubMed Central 

Google Scholar 
34.Potts, J. R., Hillen, T. & Lewis, M. A. The ‘edge effect’ phenomenon: deriving population abundance patterns from individual animal movement decisions. Theor. Ecol. 9, 233–247 (2016).
Google Scholar 
35.Gerber, L. R. et al. Population models for marine reserve design: a retrospective and prospective synthesis. Ecol. Appl. 13, 47–64 (2003).
Google Scholar 
36.Malvadkar, U. & Hastings, A.Persistence of mobile species in marine protected areas. Fish. Res. 91, 69–78 (2008).
Google Scholar 
37.Di Lorenzo, M., Guidetti, P., Calò, A. & Claudet, J. Assessing spillover from marine protected areas and its drivers: a meta-analytical approach. Fish Fish. 21, 906–915 (2020).
Google Scholar 
38.Goñi, R., Quetglas, A. & Reñones, O. Spillover of spiny lobsters Palinurus elephas from a marine reserve to an adjoining fishery. Mar. Ecol. Prog. Ser. 308, 207–219 (2006).
Google Scholar 
39.Stamoulis, K. A. & Friedlander, A. M. A seascape approach to investigating fish spillover across a marine protected area boundary in Hawai’i. Fish. Res. 144, 2–14 (2013).
Google Scholar 
40.Protected Planet: the World Database on Protected Areas (WDPA) (UNEP-WCMC and IUCN, accessed July 2020); http://www.protectedplanet.net41.Kulbicki, M. et al. Global biogeography of reef fishes: a hierarchical quantitative delineation of regions. PLoS One 8, e81847 (2013).PubMed 
PubMed Central 

Google Scholar 
42.Parravicini, V. et al. Global patterns and predictors of tropical reef fish species richness. Ecography 36, 1254–1262 (2013).
Google Scholar 
43.Froese, R. & Pauly, D. (eds). FishBase (accessed May 2020); http://www.fishbase.org44.Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).
Google Scholar 
45.Wood, S. N. Generalized Additive Models: An Introduction with R 2nd edn (CRC Press, 2017).46.Harrison, X. A. et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 6, e4794 (2018).PubMed 
PubMed Central 

Google Scholar 
47.R Core Team. R: a language and environment for statistical computing. v.3.6.1 (2019).48.QGIS Geographic Information System. Open Source Geospatial Foundation Project (QGIS Development Team, 2020); http://qgis.osgeo.org49.Harmelin-Vivien, M. et al. Species richness, abundance and biomass data for assessing fish spillover from Mediterranean marine protected areas. SEANOE https://doi.org/10.17882/74396 (2020). More

In order to study the impact of biochar application into the soil for the emanation coefficient and radon exhalation rate, biochar was applied to the soil in various doses. Then, after the soil stabilization period, samples were taken for laboratory tests and field measurements of exhalation arte were carried out. Based on the obtained results, a discussion was conducted focused on the perspective of environmental changes in the context of radon emission from soil depending on the dose of biochar. A detailed description of the materials and measurement methods used to conduct the research is presented in the following subsections.BiocharThe biochar incorporated in the field experiment was produced from sunflower husk in the pyrolysis process in the temperature range of 450–550 °C and consist on grains with diameters from 50 μm up to 10 mm. The biochar was characterized by specific surface area of 2.0 m2 g−1 in occupancy of Cu ions and 5.1 m2 g−1 for Ag ions23.Field experimentThe field experiment was conducted in ten plots, each with a dimension of 1.1 m × 1.1 m, located in Lublin/Felin at the Institute of Agrophysics of Polish Academy of Science. In addition one plot was left without biochar as a reference. The biochar was applied into the soil in April 2018. The soil presented on the fields were classified as Haplic Luvisol with 66% of sand, 23% of silt 11% of clay and 0.91% of organic matter (data for 0–15 cm layer)32. The following doses of biochar were applied for the following fields: 1, 5, 10, 20, 30, 40, 50, 60, 80, and 100 Mg ha−1 (which corresponded to the percentage of biochar per unit mass of soil: 0.05, 0.24, 0.48, 0.95, 1.43, 1.90, 2.28, 2.86, 3.81, and 4.76%, respectively). The fields were kept without vegetation by application of herbicide (Roundup 360 PLUS at 2.5 L ha−1). For the purpose of presented work six fields were investigated: with 0 (control), 20, 40, 60, 80 and 100 Mg ha−1 biochar doses.Soil sample collection and preparationThe soil samples were collected from five experimental plots, where the biochar was applied into the soil at the doses of 20, 40, 60, 80, and 100 Mg ha−1, and from a control field, where no biochar was applied (denoted as 0 Mg ha−1). Soil samples were collected from each field at five statistically chosen points to get about 2 kg of soil. After collection, the soil was mixed and dried at room temperature for two weeks. One sample for laboratory examinations was prepared from each part of the soil. The sample was a 4.7 cm high and 5.2 cm diameter steel cylinder, as presented in Fig. 1. The volume of each sample was 100 cm3. The bulk density of each sample was evaluated. The soil net weight of each sample was measured by measurements of each sample and subtraction of the weight of the steel cylinder. Next, the cylinders were closed on the bottom with a rubber cap to reduce the radon emanation surface to the size of 19.62 cm2 at the top of the sample.Figure 1The example of sample collected from the experimental field and prepared for measurements within the small accumulation chamber in the process of radon emanation assessment.Full size imageTotal porosity measurementsThe total porosity was measured with the weight method after water saturation. First, the samples were dried at 105 °C for 1 h and weighed to measure the total mass of the soil-biochar samples. To assess the total pore volume, the samples were placed in a tray filled with water for 24 h to reach saturation and the weight measurements were repeated. The total porosity η was calculated according to the equation:$$eta =frac{{V}_{p}}{{V}_{s}}=frac{{m}_{w}}{{rho }_{w}cdot {V}_{s}}=frac{left({m}_{s}-{m}_{d}right)}{{rho }_{w}cdot {V}_{s}}$$where ms is the mass of a saturated sample, md is the mass of a dried sample, Vs and Vp represent the sample volume (100 cm3) and pore volume, respectively, and ρw is water density. The weight measurements were realized by electronic laboratory balance with the accuracy of 0.1 mg. The total uncertainty of the method was assessed for 5%.The uncertainty for radon in air concentration measurements were assessed for 18% basing on the data provided by the instrument.Emanation coefficient assessmentThe radon emission from samples in the laboratory environment were measured using an AlphaGUARD instrument equipped with a measuring chamber made of stainless steel, as presented on the left in Fig. 2. The chamber was 11 cm in diameter and 12 cm in height, giving 0.00114 m3 of volume. The measurement of the radon concentration in air was made setting a 1 dm3 min−1 flow rate and 10 min reading cycles. Data were next averaged for 1 h, resulting to one data point represents the average values from six originally measured data points. Measurement for one sample took 20 h. Values of radon concentration in air was registered with the uncertainty for each data point assessed directly by the instrument.Figure 2Set up for radon accumulation measurements for assessment of the emanation coefficient in the laboratory environment. Set include the small accumulation chamber with the total volume of 0.00114 m3 (present on the left side) operating with the AlphaGuard instrument (presented on the right).Full size imageThe emanation coefficient ε was determined based on the Ra-226 activity concentration and radon potential Ω according to the methodology proposed by33 and making an additional assumption that the samples were dried to zero humidity, which implied that no pores filled with water were present within the samples during measurements. The assumption reduces the equation for calculating the time bound exhalation constant.The emanation coefficient expressed in % was evaluated according to the equation:$$varepsilon =frac{{Omega }}{{Ac}_{Ra}}cdot 100{%}$$
(2)
where AcRa represents the Ra-226 activity concentration in a soil sample expressed in Bq kg−1.The AcRa was assessed using gamma spectrometry and a high purity germanium detector according to the methodology described by25. For properly Ra-226 activity concentration in soil assessment the impact of 185.7 keV gammas from U-235 was subtracted after its evaluation basing on the 63.3 keV peak of Th-234.The main advantage of the proposed method is the ability to assess the emanation coefficient based on short-time measurements (below 24 h) with a cumulative chamber method. Originally, in the methodology developed by33, the assessment requires evaluation of Ω according to the formula:$$Omega = frac{{a + lambda _{{eff}} cdot C_{{Rn}}^{0} }}{{lambda _{{Rn}} }}~frac{{V_{e} }}{m}$$
(3)
where a (Bq m−3 s−1) represents the slope of the linear fit of radon exhalation rate data series measured in the cumulative chamber, λeff is an effective time constant (s−1), CRn0 is the initial Rn-222 concentration in the accumulation chamber (Bq m−3), λRn denotes the Rn-222 decay constant, Ve describes the effective accumulation volume in the experimental setup (m3), and m (kg) is the mass of the sample.The effective time constant describes the effective time of the presence of radon exhaled within the experimental set up and is the sum of the Rn-222 decay constant λRn (s−1), the bound exhalation constant λb (s−1) characterizing the sample, and the leakage constant characterizing the accumulation chamber equipment λl (s−1):$${lambda }_{eff}={lambda }_{Rn}+{lambda }_{b}+{lambda }_{l}$$
(4)
The λb coefficient is dependent on the soil sample porosity according to the simplified equation:$${lambda }_{b}={lambda }_{Rn}eta frac{{V}_{0}}{{V}_{e}}$$
(5)
where η represents the total porosity of the sample, as the assumption of zero humidity of samples during measurements was made, and V0 represents the volume of the sample.λl was evaluated experimentally by measuring the Rn-222 decay in the empty accumulation chamber system with a natural radon concentration at the starting point. The most significant compound of total uncertainty for the emanation coefficient was associated with estimation for slope a, CRn0 and with assessment of the total porosity for the samples η. The uncertainty was evaluated using differentiation method.Radon exhalation rate assessmentThe radon exhalation rate (ERn) was assessed according to the methodology presented in25. The field radon exhalation rate was assessed indirectly by measurement of radon concentration in air using an AlphaGUARD instrument equipped with accumulation open-wall chamber placed on the ground as presented on the Fig. 3. The chamber volume was 0.024 m3. The setup measuring parameters were the same as in the case of the laboratory measurements with the small closed chamber but the measuring time was 70 min giving seven data points for each field. Values of radon concentration in air was registered with the uncertainty for each data point assessed directly by the instrument.Figure 3Setup for assessment of the radon exhalation rate in the field measurements. The set consist of the accumulation chamber with 0.024 m3 in volume and the AlphaGuard instrument.Full size imageThe increase of radon concentration in air (CRn) in accumulation box were registered and the linear function was interpolated basing on seven measuring points registered for each experimental field. Basing on the measurement of radon concentration in air the radon exhalation rate could be assessed according to the equation:$${E}_{Rn}=frac{V}{A}frac{partial {C}_{Rn}}{partial t}$$
(6)
where V/A are the ratio of accumulation chamber volume to area covered by the chamber and is a constant value of 0.2, (frac{partial {C}_{Rn}}{partial t}) is a change of radon concentration in air registered in accumulation chamber in time t and was represented as a linear fit into the experimental data as:$${C}_{Rn}=acdot t+b$$
(7)
After differentiation we can compute the radon exhalation rate as slope, a of linear fit scaled by 0.2:$${E}_{Rn}=0.2a$$
(8)
The uncertainty for radon exhalation rate assessment was associated mainly with the assessment of the slope of linear fit ad was calculated as a standard deviation for data point used for linear fits. More

Nature-based solutions (NBS) are increasingly recognised as an effective response to a number of major urban challenges. These include heatwaves1,2,3, flooding4,5,6, water quality7,8 and public health and wellbeing9,10,11. While the concept of NBS emerged as recently as 201512, the idea of using urban nature to address these issues also features prominently in the more established fields of ecosystem services (which emerged in 2005)13 and green infrastructure (2002)14.Despite mounting evidence of their benefits, strategies built around NBS are seldom practically realised15; implementation in cities has been slow, inconsistent and often limited to demonstration sites16,17,18,19,20,21. For example, 6 years after Copenhagen embraced green infrastructure as a response to its acute flooding problems in 2011, the implementation of green infrastructure was only just ‘taking off’ in 2017, and remained highly contested22. Even retaining existing urban NBS remains a challenge; tree canopy cover, central to mitigation of urban heat island effects, is declining in many cities23,24. For example, metropolitan Melbourne experienced a loss of 2000 hectares between 2014 and 201825. In the US, an average of 36 million trees were lost each year from urban areas between 2009 and 201426.Barriers within the organisations responsible for implementing NBS are frequently identified as a primary reason for limited NBS delivery16,17,23,27,28,29. Delivery organisations have significant path dependencies; existing regimes are self-enforcing, and change is difficult30,31.The reasons for non-delivery have been characterised in detail in a broad range of literature. Barriers are highlighted in studies focused on urban forestry32,33, urban water management18,29,34, nature-based solutions35,36 and climate adaptation37,38. The issue has been investigated through the lenses of mainstreaming39,40, governance19,21,33,34,41,42, transitions31,36,43,44,45 and general analyses of barriers17,23,46,47. Papers describing the barriers to NBS have drawn on interviews with experts17,23,33,34,36,48, and direct project experiences49,50. At the time of writing, we are aware of nine review papers that present typologies of barriers to NBS delivery, based on systematic reviews of the considerable literature16,18,21,29,32,37,41,46,47.These studies have identified a largely consistent set of eight essential (and frequently lacking) traits for successful NBS implementation in local government. Leadership support is critical, both at the political and executive level18,20,21,29,34,41,51,52. A project team with the right capacity and timeframes to implement projects is also important32,37,51,53,54, as is a framework of internal mechanisms that facilitate the delivery of NBS, including clear approval processes, supportive policies and laws, and well-established standards for NBS design and maintenance16,18,20,35,47,55,56,57. A positive, supportive organisational culture for delivering new projects is also necessary, recognising that new NBS projects often have inherent (and novel) risks and trade-offs17,19,20,32,33,47,52,58. Finally, access to teams within the organisation that are both suitably skilled and supportive is vital16,18,23,46,54,59,60. Beyond the organisation itself, it is common for other levels of government to play an important role in approving aspects of NBS projects; an absence of support or clear process from higher regulatory authorities can pose a significant barrier32,33,38,44,51. Effective community engagement is also noted as important, recognising that many NBS need public support and/or private property owner consent to be successful23,37,38,46,49,61,62,63,64.While the barriers to NBS delivery have been the subject of significant attention, the implementation gap persists, with recent publications continuing to note the difficulty of NBS delivery33,36,52,57.A range of theoretical frameworks offer insight into how the implementation gap might be addressed. In the field of governance, The Policy Arrangement Model65 has been used to conceptualise governance in urban forestry32,33 and urban stormwater management21,34 as the temporary balance of a set of actors, discourses, rules and resources; changes to these variables may lead to changes in governance.In the Policy Arrangement Model, each of these four elements is significant, as is their interplay33. The actors included (or excluded) in a policy arrangement are crucial, given the range of agendas in typical stakeholders (e.g. politicians, community groups, chambers of commerce, financiers etc.), as are the relations between these actors (some may operate as coalitions, or as antagonists). Discourses include tacit and explicit conceptualisations of what the policy problem is, how it should be solved, and what values matter most. These are important in lending legitimacy to rules, which define interactions and roles between actors. These may be as formal as laws and design standards, or as informal as a set of undocumented organisational processes and norms (e.g. “talk to Anne in our compliance branch, she usually decides what is safe”). These elements are all vital in determining who deploys resources such as staff time, skills, budgets or equipment, and how they are deployed. Collectively, the dynamics between these four elements constitute a policy arrangement; changes in one element have the potential to affect others, and in turn spark shifts in governance65. However, these systems can be strongly entrenched66. Governance shifts are theorised to be typically driven by at least four factors: policy entrepreneurs (or ‘champions’), shock events, socio-political changes and ‘adjacent arrangements’ (developments in policy domains in related sectors or institutions)67.Policy entrepreneurs are also a focus of mainstreaming research, which highlights how these individuals advance NBS uptake by working within organisations to involve key stakeholders, engage citizens and contract technical expertise while incrementally introducing NBS considerations into planning practice35. This work is conceptualised as ‘horizontal’ mainstreaming, as officers champion NBS across their organisations, but it is argued that this must be supported by ‘vertical’ actions by top-down actors (such as executives and elected leaders) with the power to determine resource allocations and organisational structures39,40.To support NBS development and planning, the European Union’s Horizon 2020 programme initiated a series of large international demonstration projects, each involving collaborations between a number of cities, consultancies and universities. These include the UnaLab, ProGIreg, Connecting Nature, GrowGreen, Urban GreenUP and EdiCitNet projects68. These projects generally fund dedicated staff, as well as on-ground delivery of NBS, and have potential to address some or all of the barriers to NBS delivery that cities face. When considered in terms of the Policy Arrangement Model, the new actors, discourses and resources introduced by these projects all challenge the ‘temporary balance’ theorised to constitute the organisational status quo65. These projects also may encourage governance shifts67, by both facilitating the hiring of NBS policy entrepreneurs, and increasing a city’s exposure to influential adjacent arrangements in other centres of NBS expertise, such as university research units or exemplar municipalities. With the involvement of organisational champions/policy entrepreneurs, mainstreaming activities such as stakeholder outreach, citizen engagement and intra-organisational collaboration become increasingly possible35.This paper investigates the Horizon 2020 NBS project, Urban GreenUP. Urban GreenUP focuses on supporting partner cities to prepare NBS plans, as well as funding a multi-million Euro programme of investment in NBS interventions including floating vegetated islands, green walls on private structures, and streambank renaturalisation. The seven cities participating actively as project partners are Liverpool (UK), Ludwigsburg (Germany), Mantova (Italy), Valladolid (Spain), Izmir (Turkey), Quy Nhon (Vietnam) and Medellín (Colombia). This group of cities represents a wide range of governance arrangements and urban contexts in which NBS delivery occurs; Liverpool is a significant post-industrial centre emerging from sustained economic challenges compounded by government austerity, while Mantova has large areas of UNESCO world heritage and a legacy of industrial pollution. Quy Nhon is a coastal holiday town fairly new to NBS, while Ludwigsburg has extensive environmental legislation and has already successfully carried out major streambank restoration works on their local river. The former is largely governed by provincial government, with more operational management at a local level, whereas the latter has individual portfolio mayors, including one for the city’s environment. Valladolid has a population of 300,000 and a fairly compact urban form, whereas Medellin numbers over two million residents. We were able to work with each of these cities, effectively capturing the full range of capabilities and experiences in the Urban GreenUP project, and a significant variety of landscapes and organisational contexts in which NBS may be implemented.While the ‘generalisability’ of case studies is often limited, the constraints can be at least partially addressed through strategic sampling of cases69. Our sample is diverse, and while limited to seven cities, it does represent the full cohort of cities participating in this major EU programme designed to promote NBS innovation. A smaller sample size allows for a close, qualitative study of each case. Urban GreenUP presents a valuable opportunity to investigate the persistence of NBS barriers within local governments with ambitions for NBS implementation, with implications both for future innovation-oriented programmes such as Horizon 2020, and potentially the broader practice of NBS delivery in cities.Many cities beyond the Urban GreenUP group are preparing new NBS plans and programmes, and could benefit from insights arising from this study. Each GreenUP city is embarking on NBS planning and delivery and, at the time of our research, each had an individual or team employed with a specific NBS delivery role (with potential to serve the policy entrepreneur role highlighted in the literature). Local government often plays a key role in the implementation of urban NBS39,47,70, and Urban GreenUP places these organisations at its centre. Citizen engagement is an explicit focus of the project, as is the making of plans; these are both emphasised as opportunities for mainstreaming new practices35,71.We analyse the NBS implementation capacity of the cities within this study using an approach generally consistent with the practice of theory-based evaluation72,73. This ‘theory-based’ method breaks an implementation programme into its component elements, and assesses each element against available theory regarding what is required for success. This poses significant advantages over other evaluative methods because it focuses on the causative elements that lead to policy success or failure, rather than just the final outcomes achieved74, and is therefore more conducive to reforms of the institutional barriers discussed above.Theory-based evaluation typically takes place at the end of projects, but ours is ex ante; an approach noted by Weiss in her seminal outline of theory-based evaluation as having the potential to improve programme planning72. Evaluative practices have been noted as a particular weakness in local government NBS programmes, both at the political and officer level, due to a fear that acknowledging problems would lead to criticism of failures36. We sought to mitigate this issue both through use of an ex ante approach, and by designing a tool that creates distance between evaluators and individual practitioners.This paper investigates the enduring difficulties faced by cities seeking to deploy NBS, in the context of a major NBS project spanning seven cities. We had two key research questions. First, do case study cities have the capabilities required for successful NBS delivery, or are there barriers that continue to make this difficult? Second, does identifying and measuring a city’s NBS delivery capabilities facilitate improvements in these capabilities?We elicited organisational barriers from NBS practitioners in participating cities using a purpose-built diagnostic tool. We used this approach because tools that enable organisations to learn about their success factors have the potential to address implementation gaps44,71.The tool was developed to bring lessons from the literature into an operational context, by enabling practitioners to assess and rate their organisation’s capability levels across eight key areas, such as political support, alignment between teams, and technical knowledge (refer to Table 1). The tool posed a series of questions pertaining to each of these eight capability areas; users answered by selecting from a set of pre-defined answers. The tool associated each answer with a level of capability, which was reported as a final assessment of an organisation’s capabilities. This was provided to the practitioner directly on completion of the tool’s questions, enabling an immediate estimate of their organisation’s NBS delivery capacity, and a diagnosis of any key barriers they would be likely to face in future NBS projects. These results formed the basis for our reflections on NBS delivery capacity within Urban GreenUP, as well as discussions with practitioners to understand how results of the tool were received.Table 1 Eight success factors for urban NBS in local government.Full size tableOur research proceeded in three steps. First, we drew on the literature to define a set of eight key capabilities—which we call ‘success factors’—for NBS; these formed the basis of the tool. Second, practitioners within NBS teams in participating cities used the tool to identify their capability levels. Finally, we interviewed users to evaluate the impact of the tool. More

Evaluation of the lithological, geochemical, and fossil diatom evidenceWe obtained a short, 270-cm sediment core ( 250 m40. Lake Chalco lies in the central region of the Trans-Mexican Volcanic Belt (Fig. 1). It is bounded to the north by the Sierra de Santa Catarina, to the east by the Sierra Nevada (Volcanoes Popocatepetl, Iztaccíhuatl, Tláloc and Telapón), and to the west, by Volcano Teuhtli, which is the closest volcano to the waterbody (~ 6.5 km)41. Lake sediments are composed mainly of clays that have been described as impermeable. The Lake Chalco Basin, however, is a highly complex system and seismically active. Therefore, the presence of active fractures during the Holocene is possible. Active fractures may result in inflow from the deep aquifer. Historical data indicate the existence of freshwater springs in upper parts of the aquifer, mainly at the eastern piedmont42. For instance, mineral and thermal waters at Peñón del los Baños, near the Mexico City airport (33 km from Lake Chalco), have been reported since Aztec times around AD 1,325. This spring is associated with a system of seismically active fractures. No thermal waters have been reported in modern Lake Chalco, however phreatomagmatic activity ( > 100,000 years BP) from the Xico Volcano has been documented43. Recent studies showed that the water table position changes from the upper parts of the watershed to central Texcoco, 45 km from Lake Chalco. In this study four components of the flow system were identified, including waters of recent infiltration and local circulation, evidencing intermediate chemical evolution, and waters more chemically evolved of large flow trajectories and of deep circulation44.The lithology of the studied sediment sequence is as follows: (1) Sediments from 270 to 250 cm are characterized by lapilli, ash and black to light brown silty ashes (massive to stratified); (2) Sediments in the interval 250–235 cm are composed of diatomite (yellow); (3) From 235 to 200 cm, sediments are characterized by massive black to brown sandy silts (brown); (4) From 200 to 70 cm, sandy brown to reddish, banded laminated silts, with scattered or banded pumice fragments (red) are present; (5) Sediments from 70 to 60 cm are black silty sands with organic material; (6) From 60 to 50 cm sediments are sandy brown to reddish, laminated silt, with scattered or banded pumice fragments (red); (7) Sediments from 50 to 40 cm are characterized by lapilli, ash and black to light brown silty ashes, massive to stratified, and (8) uppermost sediments from 40 to 0 cm are black silty sands with organic material (Fig. 3)36.Figure 3Taxonomic diversity revealed by metagenomic and fossil diatom analysis, and geochemical variables from the Lake Chalco Holocene sediment sequence. Each horizontal bar represents a collected sample, with the exception of the upper row, which shows the average of surface samples S1 (0 cm, i.e., modern) and S2 (0 cm, i.e., modern) (Supplementary Table S1). The lithology of the 270-cm sediment sequence is shown in the first column. The Upper Toluca Pumice (UTP) is represented as tephra underneath the first column (from left to right). Taxonomic diversity is depicted as the relative abundance of phyla Bacteria (green), Archaea (pink), and Eukarya (blue) (columns 2–4). Percent values correspond to the diversity of peptide sequences corresponding to each domain. Geochemical variables related to biological processes and past conditions are shown in columns 5–7. Results of fossil diatom analysis are shown in column 8. Dark horizontal lines show the boundaries for each delimited paleoenvironmental zone: (1) freshwater, (2) hyposaline and (3) subsaline. Edited in CorelDRAW 2020 version 22.0.Full size imageElemental geochemistry and fossil diatoms in sediment cores can be used as indicators of past wet and dry climate intervals. We measured geochemical indicators including element concentrations and ratios, and Total Organic Carbon (TOC) throughout the core (Supplementary Table S1). Total organic carbon is an important component of sediments and soils and can be used to assess the environmental status of terrestrial and aquatic ecosystems45. Maximum TOC values characterize the period of hyposaline conditions. The Mn/Fe ratio, often used to track past O2 content in bottom waters and changing redox conditions, was used as a proxy for water-column oxygen concentration46. The Mn/Fe ratios display highest values at depths of 200, 150 and 60 cm, suggesting periods of permanent anoxia during warmer conditions and excessive nutrient inputs47. The Fe/Ti ratio provides information about fluvial sediment sources. Changes in the abundance of iron oxides can be used to infer fluctuations in inputs of land‐derived detrital material48. We observed increasing Fe/Ti ratio values in superficial layers, and highest values at 100 cm. We performed cluster analysis based on Euclidean distance which revealed three groups of samples (Supplementary Fig. S1).We identified three zones in the Lake Chalco Holocene sediment sequence, based on geochemical analysis and diatom assemblages, which reflect different paleoenvironmental conditions: (1) a cool, freshwater lake (235–210 cm), (2) a warm, hyposaline lake (185–60 cm), and (3) a temperate, subsaline lake (50–0 cm) (Figs. 3, 5, Supplementary Fig. S1, Table S1).Fossil diatom assemblages provide information about past environmental changes and water quality7,49. Fossil diatom analysis, along with knowledge of species ecological preferences, enables inference of past limnological variables such as temperature, salinity, pH, electrical conductivity, and phosphorus concentration7. Inferences from our fossil diatom record concur with an earlier diatom-based paleoclimate study from Lake Chalco. Our studies revealed that during the last deglacial (~ 19,500–11,500 cal years BP), conditions were colder and much wetter than present. Assemblages are dominated by small araphid diatoms Gomphonema affine and Cocconeis placentula (Fig. 3). From 11,500 to 4,500 cal years BP, Lake Chalco was characterized by hyposaline conditions, with higher evaporation rates until ~ 6,500 cal years BP. Typical diatoms taxa include Anomoeoneis costata, Halamphora veneta and small araphids. After ~ 6,500 cal years BP, salinity in Lake Chalco declined, mean annual precipitation increased slightly, and summer insolation, seasonality, and evaporation decreased7. Assemblages are composed of H. veneta, Nitzschia frustulum, Cyclotella meneghiniana and small araphid diatoms.Meta-taxonomic analysis of Prokaryote and Eukaryote diversityOur metagenomic analysis identified 36,722 OTUs (genera) in the sediments of Lake Chalco. Among those genera, 81% correspond to bacteria (29,818 ± 106 identified to genera [ig]), 15% to Archaea (5,710 ± 118 ig), 3% to Eukarya (1,147 ± 6 ig), and 76. Iron is considered a potentially harmful element (PHE), which may be indicative of human-mediated contamination. For instance, high Fe concentrations in surficial sediments could be related to inputs of clastic sediments, and often reflect agricultural activities77. We determined 13 plant genera, five belonging to the family Poaceae (58%), including the genus Zea (corn), known to have been cultivated and consumed by early settlers78, and Oryza, a fast-growing weed that is indicative of human-mediated habitat disturbance. Twelve microscopic fungal genera were observed, including taxa that are pathogenic on wheat and rice (Gibberella and Cladochytrium), plants, keratin, and flies (Supplementary Fig. S10)79, and a protozoan that is pathogenic in humans (Giardia). We found high abundances of the family Culicidae (18%) (Supplementary Fig. S10) during the period of human occupation. The subsaline zone displays 290 unique pfams and the highest number of representatives of potassium metabolism throughout the entire Holocene (Supplementary Fig. S4B). The abundance of genes related to Cyanobacteria in this zone is much lower (9%), in contrast with findings from the Blastp against MetaProt database of the freshwater (30%) and hyposaline zones (60%) (Supplementary Fig. S10, Table S3).Our findings suggest that the biota in and around Lake Chalco during the Holocene responded mainly to changes in temperature, salinity, and trophic state, reflecting climate and human impacts over the last 6,000 years. This implies landscape modifications, agricultural activities and accelerated lake eutrophication. Furthermore, prokaryotic assemblages revealed gradual deposition of microbial communities capable of anaerobic fermentation of organic material and methanogenesis, as well as evidence for volcanic activity, inferred from the metabolic potential for sulfur cycling in the deeper zones (hyposaline and freshwater). This study generated information on Neotropical Prokaryote and Eukaryote diversity and microbial metabolic pathways during the Holocene. Nevertheless, we recommend that future studies focus on detailed characterization of microbial substrates and constrain post-depositional processes. Such studies should also consider selection processes that result from gradual depletion of substrates during burial52,59,63. Finally, we highlight the importance of including additional geochemical measures, such as porewater chemistry80. and sedimentology81 in future studies and measuring biomass by qPCR assay. More

Study site and soil samplingThe soil was collected at 5 − 20 cm (Ap horizon) from an agricultural field in Southern Germany (Freising, Bavaria, 48°23’53.8“N, 11°38’39.7“E) in December 2017. The sampling area is situated within the lower Bavarian upland, and characterized by a mean annual temperature of 7.8 °C and mean annual precipitation of 786 mm. The soil type is a Cambisol (silty clay loam; 32% clay, 53% silt, and 14% sand) with a considerable amount of loess mixed with underlying Neogene sandy sediments. The soil was selected to represent a widely distributed soil type and land use. The collected soil was oven-dried (2 days, 40 °C), sieved ( More

1.Rohwer F, Breitbart M, Jara J, Azam F, Knowlton N. Diversity of bacteria associated with the Caribbean coral Montastraea franksi. Coral Reefs. 2001;20:85–91.Article 

Google Scholar 
2.Kellogg CA. Tropical Archaea: diversity associated with the surface microlayer of corals. Mar Ecol Prog Ser. 2004;273:81–8.CAS 
Article 

Google Scholar 
3.Wegley L, Edwards R, Rodriguez-Brito B, Liu H, Rohwer F. Metagenomic analysis of the microbial community associated with the coral Porites astreoides. Environ Microbiol. 2007;9:2707–19.CAS 
PubMed 
Article 

Google Scholar 
4.Thurber RV, Payet JP, Thurber AR, Correa AMS. Virus–host interactions and their roles in coral reef health and disease. Nat Rev Microbiol. 2017;15:205–16.CAS 
PubMed 
Article 

Google Scholar 
5.Siboni N, Rasoulouniriana D, Ben-Dov E, Kramarsky-Winter E, Sivan A, Loya Y, et al. Stramenopile microorganisms associated with the massive coral favia sp. J Eukaryot Microbiol. 2010;57:236–44.CAS 
PubMed 

Google Scholar 
6.Harvell CD. Emerging marine diseases-climate links and anthropogenic factors. Science. 1999;285:1505–10.CAS 
PubMed 
Article 

Google Scholar 
7.Reshef L, Koren O, Loya Y, Zilber-Rosenberg I, Rosenberg E. The coral probiotic hypothesis. Environ Microbiol. 2006;8:2068–73.CAS 
PubMed 
Article 

Google Scholar 
8.Ainsworth TD, Thurber RV, Gates RD. The future of coral reefs: a microbial perspective. Trends Ecol Evol. 2010;25:233–40.PubMed 
Article 

Google Scholar 
9.Welsh RM, Rosales SM, Zaneveld JR, Payet JP, McMinds R, Hubbs SL, et al. Alien vs. predator: bacterial challenge alters coral microbiomes unless controlled by Halobacteriovorax predators. PeerJ. 2017;5:e3315.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
10.Rosenberg E, Koren O, Reshef L, Efrony R, Zilber-Rosenberg I. The role of microorganisms in coral health, disease and evolution. Nat Rev Microbiol. 2007;5:355–62.CAS 
PubMed 
Article 

Google Scholar 
11.Kimes NE, Van Nostrand JD, Weil E, Zhou J, Morris PJ. Microbial functional structure of Montastraea faveolata, an important Caribbean reef-building coral, differs between healthy and yellow-band diseased colonies. Environ Microbiol. 2010;12:541–56.CAS 
PubMed 
Article 

Google Scholar 
12.Raina JB, Tapiolas D, Willis BL, Bourne DG. Coral-associated bacteria and their role in the biogeochemical cycling of sulfur. Appl Environ Microbiol. 2009;75:3492–501.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
13.Rädecker N, Pogoreutz C, Voolstra CR, Wiedenmann J, Wild C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 2015;23:490–7.PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
14.Pogoreutz C, Rädecker N, Cárdenas A, Gärdes A, Wild C, Voolstra CR. Nitrogen fixation aligns with nifH abundance and expression in two coral trophic functional groups. Front Microbiol. 2017;8:1–7.Article 

Google Scholar 
15.Falkowski PG, Dubinsky Z, Muscatine L, McCloskey L. Population control in symbiotic corals. Bioscience. 1993;43:606–11.Article 

Google Scholar 
16.Falkowski PG. Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean. Nature. 1997;387:272–5.CAS 
Article 

Google Scholar 
17.Tyrrell T. The relative influences of nitrogen and phosphorus on oceanic primary production. Nature. 1999;400:525–31.CAS 
Article 

Google Scholar 
18.Lesser MP, Mazel CH, Gorbunov MY, Falkowski PG. Discovery of symbiotic nitrogen fixing cyanobacteria in coral. Science. 2004;997:997–1000.Article 
CAS 

Google Scholar 
19.Wafar MM, Wafar S, David JJ. Nitrification in reef corals. Limnol Oceanogr. 1990;35:725–30.CAS 
Article 

Google Scholar 
20.Tilstra A, El-Khaled YC, Roth F, Rädecker N, Pogoreutz C, Voolstra CR, et al. Denitrification aligns with N2 fixation in Red Sea corals. Sci Rep. 2019;9:1–9.Article 
CAS 

Google Scholar 
21.Beraud E, Gevaert F, Rottier C, Ferrier-Pagès C. The response of the scleractinian coral Turbinaria reniformis to thermal stress depends on the nitrogen status of the coral holobiont. J Exp Biol. 2013;216:2665–74.PubMed 

Google Scholar 
22.Dubinsky Z, Jokiel PL. Ratio of energy and nutrient fluxes regulates symbiosis between zooxanthellae and corals. Pacific Sci. 1994;48:313–24.
Google Scholar 
23.Rädecker N, Pogoreutz C, Ziegler M, Ashok A, Barreto MM, Chaidez V, et al. Assessing the effects of iron enrichment across holobiont compartments reveals reduced microbial nitrogen fixation in the Red Sea coral Pocillopora verrucosa. Ecol Evol. 2017;7:6614–21.PubMed 
PubMed Central 
Article 

Google Scholar 
24.Middelburg JJ, Mueller CE, Veuger B, Larsson AI, Form A, Van Oevelen D. Discovery of symbiotic nitrogen fixation and chemoautotrophy in cold-water corals. Sci Rep. 2015;5:1–9.
Google Scholar 
25.Zhang Y, Ling J, Yang Q, Wen C, Yan Q, Sun H, et al. The functional gene composition and metabolic potential of coral-associated microbial communities. Sci Rep. 2015;5:16191.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
26.Bourne DG, Morrow KM, Webster NS. Insights into the coral microbiome: underpinning the health and resilience of reef ecosystems. Annu Rev Microbiol. 2016;70:317–40.CAS 
PubMed 
Article 

Google Scholar 
27.Thompson JR, Rivera HE, Closek CJ, Medina M. Microbes in the coral holobiont: partners through evolution, development, and ecological interactions. Front Cell Infect Microbiol. 2015;4:1–20.Article 

Google Scholar 
28.Agostini S, Suzuki Y, Higuchi T, Casareto BE, Yoshinaga K, Nakano Y, et al. Biological and chemical characteristics of the coral gastric cavity. Coral Reefs. 2012;31:147–56.Article 

Google Scholar 
29.Bythell JC, Wild C. Biology and ecology of coral mucus release. J Exp Mar Bio Ecol. 2011;408:88–93.Article 

Google Scholar 
30.Shashar N, Banaszak AT, Lesser MP, Amrami D. Coral endolithic algae: life in a protected environment. Pacific Sci. 1997;51:167–73.
Google Scholar 
31.Lesser MP, Morrow KM, Pankey SM, Noonan SHC. Diazotroph diversity and nitrogen fixation in the coral Stylophora pistillata from the Great Barrier Reef. ISME J. 2018;12:813–24.CAS 
PubMed 
Article 

Google Scholar 
32.Benavides M, Houlbrèque F, Camps M, Lorrain A, Grosso O, Bonnet S. Diazotrophs: a non-negligible source of nitrogen for the tropical coral Stylophora pistillata. J Exp Biol. 2016:jeb.139451. https://doi.org/10.1242/jeb.139451.33.Koop K, Booth D, Broadbent A, Brodie JE, Bucher D, Capone DG, et al. ENCORE: the effect of nutrient enrichment on coral reefs. Synthesis of results and conclusions. Mar Pollut Bull. 2001;42:91–120.CAS 
PubMed 
Article 

Google Scholar 
34.Hatcher AI, Hatcher BG. Seasonal and spatial variation in dissolved inorganic nitrogen in the one tree reef lagoon. Proc 4th Int Coral Reef Symp. 1981;1:419–24.
Google Scholar 
35.Mohr W, Großkopf T, Wallace DWR, LaRoche J. Methodological underestimation of oceanic nitrogen fixation rates. PLoS ONE. 2010;5:1–7.Article 
CAS 

Google Scholar 
36.Lewicka-Szczebak D, Well R, Giesemann A, Rohe L, Wolf U. An enhanced technique for automated determination of 15N signatures of N2, (N2+N2O) and N2O in gas samples. Rapid Commun Mass Spectrom. 2013;27:1548–58.CAS 
PubMed 
Article 

Google Scholar 
37.Sigman DM, Casciotti KL, Andreani M, Barford C, Galanter M, Böhlke JK. A bacterial method for the nitrogen isotopic analysis of nitrate in seawater and freshwater. Anal Chem. 2001;73:4145–53.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
38.Montoya JP, Voss M, Kahler P, Capone DG. A simple, high-precision, high-sensitivity tracer assay for N2 fixation. Appl Environ Microbiol. 1996;62:986–93.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
39.Grover R, Maguer JF, Reynaud-Vaganay S, Ferrier-Pagès C. Uptake of ammonium by the scleractinian coral Stylophora pistillata: effect of feeding, light, and ammonium concentrations. Limnol Oceanogr. 2002;47:782–90.Article 

Google Scholar 
40.Grover R, Maguer JF, Allemand D, Ferrier-Pagès C. Nitrate uptake in the scleractinian coral Stylophora pistillata. Limnol Oceanogr. 2003;48:2266–74.CAS 
Article 

Google Scholar 
41.Aalto SL, Suurnäkki S, von Ahnen M, Siljanen HMP, Pedersen PB, Tiirola M. Nitrate removal microbiology in woodchip bioreactors: a case-study with full-scale bioreactors treating aquaculture effluents. Sci Total Environ. 2020;723:138093.CAS 
PubMed 
Article 

Google Scholar 
42.Pandey CB, Kumar U, Kaviraj M, Minick KJ, Mishra AK, Singh JS. DNRA: a short-circuit in biological N-cycling to conserve nitrogen in terrestrial ecosystems. Sci Total Environ. 2020;738:139710.CAS 
PubMed 
Article 

Google Scholar 
43.Beman JM, Roberts KJ, Wegley L, Rohwer F, Francis CA. Distribution and diversity of archaeal ammonia monooxygenase genes associated with corals. Appl Environ Microbiol. 2007;73:5642–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
44.Yang S, Sun W, Zhang F, Li Z. Phylogenetically diverse denitrifying and ammonia-oxidizing bacteria in corals Alcyonium gracillimum and Tubastraea coccinea. Mar Biotechnol. 2013;15:540–51.CAS 
Article 

Google Scholar 
45.El-Khaled YC, Roth F, Tilstra A, Rädecker N, Karcher DB, Kürten B, et al. In situ eutrophication stimulates dinitrogen fixation, denitrification, and productivity in Red Sea coral reefs. Mar Ecol Prog Ser. 2020;645:55–66.CAS 
Article 

Google Scholar 
46.Siboni N, Ben-Dov E, Sivan A, Kushmaro A. Global distribution and diversity of coral-associated archaea and their possible role in the coral holobiont nitrogen cycle. Environ Microbiol. 2008;10:2979–90.CAS 
PubMed 
Article 

Google Scholar 
47.Shashar N, Cohen Y, Loya Y. Extreme diel fluctuations of oxygen in diffusive boundary layers surrounding stony corals. Biol Bull. 1993;185:455–61.CAS 
PubMed 
Article 

Google Scholar 
48.Risk MJ, Muller HR. Poreweater in coral heads: evidence for nutrient regeneration. Limnol Oceanogr. 1983;28:1004–8.Article 

Google Scholar 
49.Guerrero MA, Jones RD. Photoinhibition of marine nitrifying bacteria. II. Dark recovery after monochromatic or polychromatic irradiation. Mar Ecol Prog Ser. 1996;141:193–8.Article 

Google Scholar 
50.Merbt SN, Stahl DA, Casamayor EO, Martí E, Nicol GW, Prosser JI. Differential photoinhibition of bacterial and archaeal ammonia oxidation. FEMS Microbiol Lett. 2012;327:41–6.CAS 
PubMed 
Article 

Google Scholar 
51.Pernice M, Raina JB, Rädecker N, Cárdenas A, Pogoreutz C, Voolstra CR. Down to the bone: the role of overlooked endolithic microbiomes in reef coral health. ISME J. 2020;14:325–34.PubMed 
Article 

Google Scholar 
52.Shashar N, Cohen Y, Loya Y, Sar N. Nitrogen fixation (acetylene reduction) in stony corals—evidence for coral–bacteria interactions. Mar Ecol Prog Ser. 1994;111:259–64.CAS 
Article 

Google Scholar 
53.Lesser MP, Falcón LI, Rodríguez-Román A, Enríquez S, Hoegh-Guldberg O, Iglesias-Prieto R. Nitrogen fixation by symbiotic cyanobacteria provides a source of nitrogen for the scleractinian coral Montastraea cavernosa. Mar Ecol Prog Ser. 2007;346:143–52.CAS 
Article 

Google Scholar 
54.Lema KA, Willis BL, Bourne DG. Corals form characteristic associations with symbiotic nitrogen-fixing bacteria. Appl Environ Microbiol. 2012;78:3136–44.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
55.Crossland CJ, Barnes DJ. Acetylene reduction by coral skeletons. Limnol Oceanogr. 1976;21:153–6.Article 

Google Scholar 
56.Cai L, Zhou G, Tian R-M, Tong H, Zhang W, Sun J, et al. Metagenomic analysis reveals a green sulfur bacterium as a potential coral symbiont. Sci Rep. 2017;7:9320.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
57.Olson ND, Ainsworth TD, Gates RD, Takabayashi M. Diazotrophic bacteria associated with Hawaiian Montipora corals: diversity and abundance in correlation with symbiotic dinoflagellates. J Exp Mar Bio Ecol. 2009;371:140–6.CAS 
Article 

Google Scholar 
58.Cardini U, Bednarz VN, Naumann MS, van Hoytema N, Rix L, Foster RA, et al. Functional significance of dinitrogen fixation in sustaining coral productivity under oligotrophic conditions. Proc R Soc B Biol Sci. 2015;282:20152257.Article 
CAS 

Google Scholar 
59.Grover R, Ferrier-Pagès C, Maguer JF, Ezzat L, Fine M. Nitrogen fixation in the mucus of Red Sea corals. J Exp Biol. 2014;217:3962–3.PubMed 

Google Scholar 
60.Bednarz VN, Grover R, Maguer JF, Fine M. The assimilation of diazotroph-derived nitrogen by scleractinian corals. Amer Soc Microbiol. 2017;8:1–14.
Google Scholar 
61.Knapp AN. The sensitivity of marine N2 fixation to dissolved inorganic nitrogen. Front Microbiol. 2012;3:1–14.
Google Scholar 
62.Bednarz VN, Naumann MS, Cardini U, van Hoytema N, Rix L, Al-Rshaidat MMD, et al. Contrasting seasonal responses in dinitrogen fixation between shallow and deep-water colonies of the model coral Stylophora pistillata in the northern Red Sea. PLoS ONE. 2018;13:e0199022.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
63.Larkum AWD, Kennedy IR, Muller WJ. Nitrogen fixation on a coral reef. Mar Biol. 1988;98:143–55.Article 

Google Scholar 
64.Shashar N, Feldstein T, Cohen Y, Loya Y. Nitrogen fixation (acetylene reduction) on a coral reef. Coral Reefs. 1994;13:171–4.Article 

Google Scholar 
65.Santos HF, Carmo FL, Duarte G, Dini-Andreote F, Castro CB, Rosado AS, et al. Climate change affects key nitrogen-fixing bacterial populations on coral reefs. ISME J. 2014;8:2272–9.PubMed 
PubMed Central 
Article 

Google Scholar 
66.Bythell JC. Nutrient uptake in the reef-building coral Acropora palmata at natural environmental concentrations. Mar Ecol Prog Ser. 1990;68:65–9.Article 

Google Scholar 
67.Furnas MJ. Net in situ growth rates of phytoplankton in an oligotrophic, tropical shelf ecosystem. Limnol Oceanogr. 1991;36:13–29.Article 

Google Scholar 
68.Badgley BD, Lipschultz F, Sebens KP. Nitrate uptake by the reef coral Diploria strigosa: effects of concentration, water flow, and irradiance. Mar Biol. 2006;149:327–38.CAS 
Article 

Google Scholar 
69.Tanaka Y, Miyajima T, Koike I, Hayashibara T, Ogawa H. Translocation and conservation of organic nitrogen within the coral-zooxanthella symbiotic system of Acropora pulchra, as demonstrated by dual isotope-labeling techniques. J Exp Mar Bio Ecol. 2006;336:110–9.CAS 
Article 

Google Scholar 
70.Fernandes de Barros Marangoni L, Ferrier-Pagès C, Rottier C, Bianchini A, Grover R. Unravelling the different causes of nitrate and ammonium effects on coral bleaching. Sci Rep. 2020;10:1–14.Article 
CAS 

Google Scholar 
71.Munn CB. The role of vibrios in diseases of corals. Microbiol Spectr. 2015;3:1–12.CAS 
Article 

Google Scholar 
72.Rubio-Portillo E, Gago JF, Martínez-García M, Vezzulli L, Rosselló-Móra R, Antón J, et al. Vibrio communities in scleractinian corals differ according to health status and geographic location in the Mediterranean Sea. Syst Appl Microbiol. 2018;41:131–8.PubMed 
Article 

Google Scholar 
73.Tout J, Siboni N, Messer LF, Garren M, Stocker R, Webster NS, et al. Increased seawater temperature increases the abundance and alters the structure of natural Vibrio populations associated with the coral Pocillopora damicornis. Front Microbiol. 2015;6:1–12.Article 

Google Scholar 
74.Erler DV, Santos IR, Eyre BD. Inorganic nitrogen transformations within permeable carbonate sands. Cont Shelf Res. 2014;77:69–80.Article 

Google Scholar 
75.Tiedje JM, Sexstone AJ, Myrold DD, Robinson JA. Denitrification: ecological niches, competition and survival. Antonie Van Leeuwenhoek. 1983;48:569–83.Article 

Google Scholar 
76.Stremińska MA, Felgate H, Rowley G, Richardson DJ, Baggs EM. Nitrous oxide production in soil isolates of nitrate-ammonifying bacteria. Environ Microbiol Rep. 2012;4:66–71.PubMed 
Article 
CAS 

Google Scholar 
77.Gardner WS, McCarthy MJ, An S, Sobolev D, Sell KS, Brock D. Nitrogen fixation and dissimilatory nitrate reduction to ammonium (DNRA) support nitrogen dynamics in Texas estuaries. Limnol Oceanogr. 2006;51:558–68.CAS 
Article 

Google Scholar 
78.Giblin AE, Weston NB, Banta GT, Tucker J, Hopkinson CS. The effects of salinity on nitrogen losses from an oligohaline estuarine sediment. Estuaries Coasts. 2010;33:1054–68.CAS 
Article 

Google Scholar 
79.Giblin AE, Tobias CR, Song B, Weston N, Banta GT, Rivera-Monroy VH. The importance of dissimilatory nitrate reduction to ammonium (DNRA) in the nitrogen cycle of coastal ecosystems. Oceanography. 2013;26:124–31.Article 

Google Scholar  More