Ecology

1.Sundseth, K. & Creed, P. Natura 2000: Protecting Europe’s Biodiversity (Office for Official Publications of the European Communities, 2008).
Google Scholar 
2.Wilk, T., Jujka, M., Krogulec, J. & Chylarecki, P. Important Bird Areas of International Importance in Poland (OTOP, 2010).
Google Scholar 
3.European Commission. Report on the Status of and Trends for Habitat Types and Species Covered by the Birds and Habitats Directives for the 2007–2012 Period as Required Under Article 17 of the Habitats Directive and Article 12 of the Birds Directive (European Commission DG Environment, 2015).
Google Scholar 
4.Birds Directive. Council Directive 79/409/EEC on the Conservation of Wild Birds. http://www.jncc.gov.uk/page-1373 (1979).5.Butler, S. J., Boccaccio, L., Gregory, R. D., Vorisek, P. & Norris, K. Quantifying the impact of land-use change to European farmland bird populations. Agric. Ecosyst. Environ. 137, 348–357. https://doi.org/10.1016/j.agee.2010.03.005 (2010).Article 

Google Scholar 
6.Gregory, R. D., Skorpilova, J., Vorisek, P. & Butler, S. An analysis of trends, uncertainty and species selection shows contrasting trends of widespread forest and farmland birds in Europe. Ecol. Indic. 103, 676–687. https://doi.org/10.1016/j.ecolind.2019.04.064 (2019).Article 

Google Scholar 
7.European Commission. The Interpretation Manual of European Union Habitats (European Commission DG Environment, 2007).
Google Scholar 
8.Tews, J. et al. Animal species diversity driven by habitat heterogeneity/diversity: The importance of keystone structures. J. Biogeogr. 31, 79–92. https://doi.org/10.1046/j.0305-0270.2003.00994.x (2004).Article 

Google Scholar 
9.Bujoczek, M., Rybicka, J. & Bujoczek, L. Effects of disturbances in a subalpine forest on its structural indicators and bird diversity. Ecol. Indic. 112, 106126. https://doi.org/10.1016/j.ecolind.2020.106126 (2020).Article 

Google Scholar 
10.van Galen, L. G., Jordan, G. J. & Baker, S. C. Relationships between coarse woody debris habitat quality and forest maturity attributes. Conserv. Sci. Pract. 1, e55. https://doi.org/10.1111/csp2.55 (2019).Article 

Google Scholar 
11.Paillet, Y. et al. The indicator side of tree microhabitats: A multi-taxon approach based on bats, birds and saproxylic beetles. J. Appl. Ecol. 55, 2147–2159. https://doi.org/10.1111/1365-2664.13181 (2018).Article 

Google Scholar 
12.Basile, M. et al. What do tree-related microhabitats tell us about the abundance of forest-dwelling bats, birds, and insects?. J. Environ. Manag. 264, 110401. https://doi.org/10.1016/j.jenvman.2020.110401 (2020).Article 

Google Scholar 
13.Wesołowski, T. Lessons from long-term hole-nester studies in a primeval temperate forest. J. Ornithol. 148, 395–405. https://doi.org/10.1007/s10336-007-0198-1 (2007).Article 

Google Scholar 
14.Maziarz, M. & Broughton, R. K. Breeding microhabitat selection by Great Tits Parus major in a deciduous primeval forest (Białowieża National Park, Poland). Bird Study 62, 358–367. https://doi.org/10.1080/00063657.2015.1050994 (2015).Article 

Google Scholar 
15.Van der Hoek, Y., Gaona, G. V. & Martin, K. The diversity, distribution and conservation status of the tree-cavity nesting birds of the world. Divers. Distrib. 23, 1120–1131. https://doi.org/10.1111/ddi.12601 (2017).Article 

Google Scholar 
16.McElhinny, C., Gibbons, P., Brack, C. & Bauhus, J. Forest and woodland stand structural complexity: Its definition and measurement. For. Ecol. Manag. 218, 1–24. https://doi.org/10.1016/j.foreco.2005.08.034 (2005).Article 

Google Scholar 
17.Holmes, R. T., Bonney, R. E. & Pacala, S. W. Guild structure of the Hubbard Brook bird community: A multivariate approach. Ecology 60, 512–520. https://doi.org/10.2307/1936071 (1979).Article 

Google Scholar 
18.Lain, E. J., Haney, A., Burris, J. M. & Burton, J. Response of vegetation and birds to severe wind disturbance and salvage logging in a southern boreal forest. For. Ecol. Manag. 256, 863–871. https://doi.org/10.1016/j.foreco.2008.05.018 (2008).Article 

Google Scholar 
19.Larrieu, L. et al. Tree related microhabitats in temperate and Mediterranean European forest: A hierarchical typology for inventory standarization. Ecol. Indic. 83, 194–207. https://doi.org/10.1016/j.ecolind.2017.08.051 (2018).Article 

Google Scholar 
20.Zielewska-Büttner, K., Heurich, M., Müller, J. & Braunisch, V. Remotely sensed single tree data enable the determination of habitat thresholds for the three-toed woodpecker (Picoides tridactylus). Remote Sens. 10, 1972. https://doi.org/10.3390/rs10121972 (2018).ADS 
Article 

Google Scholar 
21.Mikusiński, G., Gromadzki, M. & Chylarecki, P. Woodpeckers as indicators of forest bird diversity. Conserv. Biol. 15, 208–217 (2001).Article 

Google Scholar 
22.Wesołowski, T. & Rowiński, P. The breeding behaviour of the Nuthatch Sitta europaea in relation to natural hole attributes in a primeval forest. Bird Study 51, 143–155. https://doi.org/10.1080/00063650409461346 (2004).Article 

Google Scholar 
23.Barbaro, L. et al. Hierarchical habitat selection by Eurasian Pygmy Owls Glaucidium passerinum in oldgrowth forests of the southern French Prealps. J. Ornithol. 157, 333–342. https://doi.org/10.1007/s10336-015-1285-3 (2016).Article 

Google Scholar 
24.Basile, M., Balestrieri, R., de Groot, M., Flajšman, K. & Posillico, M. Conservation of birds as a function of forestry. Ital. J. Agron. 11, 42–48 (2016).
Google Scholar 
25.Harestad, A. S. & Keisker, D. G. Nest tree use by primary cavity-nesting birds in south central British Columbia. Can. J. Zool. 67, 1067–1073. https://doi.org/10.1139/z89-148 (1989).Article 

Google Scholar 
26.Walankiewicz, W., Czeszczewik, D., Mitrus, C. & Bida, E. Znaczenie martwych drzew dla zespołu dzięciołów w lasach liściastych Puszczy Białowieskiej. Notatki Ornitol. 43, 61–71 (2002).
Google Scholar 
27.Czeszczewik, D. & Walankiewicz, W. Natural nest sites of the Pied Flycatcher Ficedula hypoleuca in a primeval forest. Ardea 91, 221–230 (2003).
Google Scholar 
28.Kosiński, Z. & Kempa, M. Density distribution and nest−sites selection of woodpeckers Picidae in managed forest of western Poland. Pol. J. Ecol. 55, 519–533 (2007).
Google Scholar 
29.Zawadzka, D. & Zawadzki, G. Charakterystyka drzew gniazdowych dzięcioła czarnego w Puszczy Augustowskiej. Sylwan 161, 1002–1009 (2017).
Google Scholar 
30.Urban, D. L. & Smith, T. M. Microhabitat pattern and the structure of forest bird communities. Am. Nat. 133, 811–829. https://doi.org/10.1086/284954 (1989).Article 

Google Scholar 
31.Piechnik, Ł, Kurek, P., Ledwoń, M. & Holeksa, J. Both natural and anthropogenic microhabitats and fine-scale habitat features of managed forest can affect the abundance of the Eurasian Wren. For. Ecol. Manag. 456, 117695. https://doi.org/10.1016/j.foreco.2019.117695 (2020).Article 

Google Scholar 
32.Sefidi, K., EsfandiaryDarabad, F. & Azaryan, M. Effect of topography on tree species composition and volume of coarse woody debris in an Oriental beech (Fagus orientalis Lipsky) old growth forests, northern Iran. iForest 9, 658. https://doi.org/10.3832/ifor1080-008 (2016).Article 

Google Scholar 
33.Oettel, J. et al. Patterns and drivers of deadwood volume and composition in different forest types of the Austrian natural forest reserves. For. Ecol. Manag. 463, 118016. https://doi.org/10.1016/j.foreco.2020.118016 (2020).Article 

Google Scholar 
34.Bashta, A. T. V. Biotope distribution and habitat preference of breeding bird communities in alpine and subalpine belts in the Tatra and Babia Gora Mts. (Southern Poland). Berkut 14, 145–161 (2005).
Google Scholar 
35.Bouvet, A. et al. Effects of forest structure, management and landscape on bird and bat communities. Environ. Conserv. 43, 148–160. https://doi.org/10.1017/S0376892915000363 (2016).Article 

Google Scholar 
36.Dellinger, R. L., Wood, P. B., Keyser, P. D. & Seidel, G. Habitat partitioning of four sympatric thrush species at three spatial scales on a managed forest in West Virginia. Auk 124, 1425–1438. https://doi.org/10.1093/auk/124.4.1425 (2007).Article 

Google Scholar 
37.Leidinger, J. et al. Formerly managed forest reserves complement integrative management for biodiversity conservation in temperate European forests. Biol. Conserv. 242, 108437. https://doi.org/10.1016/j.biocon.2020.108437 (2020).Article 

Google Scholar 
38.Basile, M., Mikusiński, G. & Storch, I. Bird guilds show different responses to tree retention levels: A meta-analysis. Glob. Ecol. Conserv. 18, e00615. https://doi.org/10.1016/j.gecco.2019.e00615 (2019).Article 

Google Scholar 
39.Müller, J. & Bütler, R. A review of habitat thresholds for dead wood: A baseline for management recommendations in European forests. Eur. J. For. Res. 129, 981–992. https://doi.org/10.1007/s10342-010-0400-5 (2010).Article 

Google Scholar 
40.Kajtoch, Ł, Figarski, T. & Pełka, J. The role of forest structural elements in determining the occurrence of two specialist woodpecker species in the Carpathians, Poland. Ornis Fenn. 90, 23–40 (2013).
Google Scholar 
41.Rodrigues, A. S. & Brooks, T. M. Shortcuts for biodiversity conservation planning: The effectiveness of surrogates. Annu. Rev. Ecol. Evol. Syst. 38, 713–737 (2007).Article 

Google Scholar 
42.Hunter, M. Jr. et al. Two roles for ecological surrogacy: Indicator surrogates and management surrogates. Ecol. Indic. 63, 121–125. https://doi.org/10.1016/j.ecolind.2015.11.049 (2016).Article 

Google Scholar 
43.NFI. Wielkoobszarowa inwentaryzacja stanu lasu. Wyniki za okres 2009–2013 (Biuro Urządzania Lasu i Geodezji Leśnej, 2014).
Google Scholar 
44.CRFOP. Centralny Rejestr Form Ochrony Przyrody. http://crfop.gdos.gov.pl/CRFOP/ (2020).45.GDOS. Generalna Dyrekcja Ochrony Środowiska. https://www.gdos.gov.pl/dane-i-metadane (2020).46.BDL. Bank Danych o Lasach. https://www.bdl.lasy.gov.pl/portal (2020).47.Qgis 3.10. QGIS Geographic Information System. http://www.qgis.org (QGIS Association, 2020).48.ME. Instrukcja wykonywania wielkoobszarowej inwentaryzacji stanu lasu (Typescript of the Ministry of the Environment, 2010).
Google Scholar 
49.Talarczyk, A. National forest inventory in Poland. Balt. For. 20, 333–341 (2014).
Google Scholar 
50.Standard Data Form. Instrukcja wypełniania Standardowych Formularzy Danych. http://natura2000.gdos.gov.pl (2012).51.Balestrieri, R. et al. A guild-based approach to assessing the influence of beech forest structure on bird communities. For. Ecol. Manag. 356, 216–223. https://doi.org/10.1016/j.foreco.2015.07.011 (2015).Article 

Google Scholar 
52.Ameztegui, A. et al. Bird community response in mountain pine forests of the Pyrenees managed under a shelterwood system. For. Ecol. Manag. 407, 95–105. https://doi.org/10.1016/j.foreco.2017.09.002 (2017).Article 

Google Scholar 
53.Czeszczewik, D. et al. Effects of forest management on bird assemblages in the Bialowieza Forest, Poland. iForest Biogeosci. For. 8, 377–385. https://doi.org/10.3832/ifor1212-007 (2015).Article 

Google Scholar 
54.Czuraj, M. Tablice miąższości kłód odziomkowych i drzew stojących (PWRiL, 1990).
Google Scholar 
55.Oramus, M. Breeding habitat of wren (Troglodytes troglodytes) in lower mountain zone forests in Gorce National Park. Master thesis (University of Agriculture in Krakow, Faculty of Forestry, Department of Forest Biodiversity 2017).56.Statistica 13 software. Dell Statistica (data analysis software system), version 13. software.dell.com (2016).57.Ćosović, M., Bugalho, M. N., Thom, D. & Borges, J. G. Stand structural characteristics are the most practical biodiversity indicators for forest management planning in Europe. Forests 11, 343. https://doi.org/10.3390/f11030343 (2020).Article 

Google Scholar 
58.Morán-López, R., Cortés Gañán, E., Uceda Tolosa, O. & Sánchez Guzmán, J. M. The umbrella effect of Natura 2000 annex species spreads over multiple taxonomic groups, conservation attributes and organizational levels. Anim. Conserv. https://doi.org/10.1111/acv.12551 (2019).Article 

Google Scholar 
59.Lindenmayer, D. B., Franklin, J. F. & Fischer, J. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conserv. 131, 433–445. https://doi.org/10.1016/j.biocon.2006.02.019 (2006).Article 

Google Scholar 
60.Gruber, B. et al. “Mind the gap!”—How well does Natura 2000 cover species of European interest?. Nat. Conserv. 3, 45–62. https://doi.org/10.3897/natureconservation.3.3732 (2012).Article 

Google Scholar 
61.Kukkala, A. S. et al. Matches and mismatches between national and EU-wide priorities: Examining the Natura 2000 network in vertebrate species conservation. Biol. Conserv. 198, 193–201. https://doi.org/10.1016/j.biocon.2016.04.016 (2016).Article 

Google Scholar 
62.Donald, P. F. et al. International conservation policy delivers benefits for birds in Europe. Science 317, 810–813. https://doi.org/10.1126/science.1146002 (2007).ADS 
CAS 
Article 
PubMed 

Google Scholar 
63.Nilsson, L., Bunnefeldb, N., Perssonc, J., Žydelisd, R. & Månssona, J. Conservation success or increased crop damage risk? The Natura 2000 network for a thriving migratory and protected bird. Biol. Conserv. 236, 1–7. https://doi.org/10.1016/j.biocon.2019.05.006 (2019).Article 

Google Scholar 
64.Winter, S. et al. The impact of Natura 2000 on forest management: A socio-ecological analysis in the continental region of the European Union. Biodivers. Conserv. 23, 3451–3482. https://doi.org/10.1007/s10531-014-0822-3 (2014).Article 

Google Scholar 
65.Zisenis, M. Is the Natura 2000 network of the European Union the key land use policy tool for preserving Europe’s biodiversity heritage?. Land Use Policy 69, 408–416. https://doi.org/10.1016/j.landusepol.2017.09.045 (2017).Article 

Google Scholar 
66.Bashta, A. T. V. Breeding bird community of monocultural spruce plantation in the Skolivski Beskids (the Ukrainian Carpathians). Berkut 8, 9–14 (1999).
Google Scholar 
67.Baláž, M. & Balážová, M. Diversity and abundance of bird communities in three mountain forest stands: Effect of the habitat heterogeneity. Pol. J. Ecol. 60, 629–634 (2012).
Google Scholar 
68.Puletti, N. et al. A dataset of forest volume deadwood estimates for Europe. Ann. For. Sci. 76, 68. https://doi.org/10.1007/s13595-019-0832-0 (2019).Article 

Google Scholar 
69.Nappi, A., Drapeau, P. & Leduc, A. How important is dead wood for woodpeckers foraging in eastern North American boreal forests?. For. Ecol. Manag. 346, 10–21. https://doi.org/10.1016/j.foreco.2015.02.028 (2015).Article 

Google Scholar 
70.Raphael, M. & White, M. Use of snags by cavity-nesting birds in the Sierra Nevada. Wildl. Monogr. 86, 3–66 (1984).
Google Scholar 
71.Bujoczek, L., Bujoczek, M. & Zięba, S. How much, why and where? Deadwood in forest ecosystems: The case of Poland. Ecol. Indic. 121, 107027. https://doi.org/10.1016/j.ecolind.2020.107027 (2021).Article 

Google Scholar 
72.Lešo, P., Kropil, R. & Kajtoch, Ł. Effects of forest management on bird assemblages in oak-dominated stands of the Western Carpathians-Refuges for rare species. For. Ecol. Manag. 453, 117620. https://doi.org/10.1016/j.foreco.2019.117620 (2019).Article 

Google Scholar 
73.De Zan, L. R., de Gasperis, S. R., Fiore, L., Battisti, C. & Carpaneto, G. M. The importance of dead wood for hole-nesting birds: A two years study in three beech forests of central Italy. Isr. J. Ecol. Evol. 63(1), 19–27. https://doi.org/10.1080/15659801.2016.1191168 (2017).Article 

Google Scholar 
74.Wilk, T., Bobrek, R., Pępkowska-Krol, A., Neubauer, G. & Kosicki, J. Z. The Birds of the Polish Carpathians—Status, Threats, Conservation (OTOP, 2016).
Google Scholar 
75.Jonsson, B. G. et al. Dead wood availability in managed Swedish forests–Policy outcomes and implications for biodiversity. For. Ecol. Manag. 376, 174–182. https://doi.org/10.1016/j.foreco.2016.06.017 (2016).Article 

Google Scholar 
76.Lõhmus, A. Do Ural owls (Strix uralensis) suffer from the lack of nest sites in managed forests?. Biol. Conserv. 110, 1–9. https://doi.org/10.1016/S0006-3207(02)00167-2 (2003).Article 

Google Scholar 
77.Tanona, M. & Czarnota, P. Natural disturbances of the structure of Norway spruce forests in Europe and their impact on the preservation of epixylic lichen diversity: A review. Ecol. Quest. 30, 1–17. https://doi.org/10.12775/EQ.2019.024 (2019).Article 

Google Scholar 
78.Repel, M., Zámečník, M. & Jarčuška, B. Temporal changes in bird communities of wind-affected coniferous mountain forest in differently disturbed stands (High Tatra Mts., Slovakia). Biologia 75, 1931–1943. https://doi.org/10.2478/s11756-020-00455-5 (2020).Article 

Google Scholar 
79.Přívětivý, T. et al. How do environmental conditions affect the deadwood decomposition of European beech (Fagus sylvatica L.)?. For. Ecol. Manag. 381, 177–187. https://doi.org/10.1016/j.foreco.2016.09.033 (2016).Article 

Google Scholar 
80.Wichmann, G. Habitat use of nightjar (Caprimulgus europaeus) in an Austrian pine forest. J. Ornithol. 145, 69–73. https://doi.org/10.1007/s10336-003-0013-6 (2004).Article 

Google Scholar 
81.Müller, D., Schröder, B. & Müller, J. Modelling habitat selection of the cryptic Hazel Grouse Bonasa bonasia in a montane forest. J. Ornithol. 150, 717–732. https://doi.org/10.1007/s10336-009-0390-6 (2009).Article 

Google Scholar 
82.Storch, I. Habitat and survival of capercaillie Tetrao urogallus nests and broods in the Bavarian Alps. Biol. Conserv. 70, 237–243. https://doi.org/10.1016/0006-3207(94)90168-6 (1994).Article 

Google Scholar 
83.Swenson, J. E. The ecology of Hazel Grouse and management of its habitat. Naturschutzreport 10, 227–238 (1995).
Google Scholar 
84.Drapeau, P., Nappi, A., Imbeau, L. & Saint-Germain, M. Standing deadwood for keystone bird species in the eastern boreal forest: Managing for snag dynamics. For. Chron. 85, 227–234. https://doi.org/10.5558/tfc85227-2 (2009).Article 

Google Scholar 
85.Mikusiński, G. et al. Is the impact of loggings in the last primeval lowland forest in Europe underestimated? The conservation issues of Białowieża Forest. Biol. Conserv. 227, 266–274. https://doi.org/10.1016/j.biocon.2018.09.001 (2018).Article 

Google Scholar 
86.Dufour-Pelletier, S., Tremblay, J. A., Hébert, C., Lachat, T. & Ibarzabal, J. Testing the effect of snag and cavity supply on deadwood-associated species in a managed boreal forest. Forests 11, 424. https://doi.org/10.3390/f11040424 (2020).Article 

Google Scholar 
87.Pirovano, A. R. & Zecca, G. Black Woodpecker Dryocopus martius habitat selection in the Italian Alps: Implications for conservation in Natura 2000 network. Bird Conserv. Int. 24, 299–315. https://doi.org/10.1017/S0959270913000439 (2014).Article 

Google Scholar  More

Numerical sex ratioIn each population, the total number of male individuals was higher than that of female individuals, regardless of caste (binomial tests for Okinawa alates, total female:male individuals = 2,427:3,468, p  More

1.Harmon, M. E. et al. Ecology of coarse woody debris in temperate ecosystems. Adv. Ecol. Res. 15, 133–302 (1986).Article 

Google Scholar 
2.Lagomarsino, A. et al. Decomposition of black pine (Pinus nigra J. F. Arnold) deadwood and its impact on forest soil components. Sci. Total Environ. 754, 142039 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
3.Magnússon, R. Í., Tietema, A., Cornelissen, J. H. C., Hefting, M. M. & Kalbitz, K. Tamm review: Sequestration of carbon from coarse woody debris in forest soils. For. Ecol. Manag. 377, 1–15 (2016).Article 

Google Scholar 
4.Vogt, K. Carbon budgets of temperate forest ecosystems. Tree Physiol. 9, 69–86 (1991).PubMed 
Article 

Google Scholar 
5.Stutz, K. P. & Lang, F. Potentials and unknowns in managing coarse woody debris for soil functioning. Forests 8, 37 (2017).Article 

Google Scholar 
6.Ulyshen, M. D. et al. Below- and above-ground effects of deadwood and termites in plantation forests. Ecosphere 8, e01910 (2017).Article 

Google Scholar 
7.Siitonen, J. Ecology of woody debris in boreal forests. Ecol. Bull. 49, 11–41 (2001).
Google Scholar 
8.Pietsch, K. A. et al. Wood decomposition is more strongly controlled by temperature than by tree species and decomposer diversity in highly species rich subtropical forests. Oikos 128, 701–715 (2019).Article 

Google Scholar 
9.Rubenstein, M. A., Crowther, T. W., Maynard, D. S., Schilling, J. S. & Bradford, M. A. Decoupling direct and indirect effects of temperature on decomposition. Soil Biol. Biochem. 112, 110–116 (2017).CAS 
Article 

Google Scholar 
10.Hu, Z. et al. Traits mediate drought effects on wood carbon fluxes. Glob. Chang. Biol. 26, 3429–3442 (2020).ADS 
PubMed 
Article 

Google Scholar 
11.Yoon, T. K., Noh, N. J., Kim, S., Han, S. & Son, Y. Coarse woody debris respiration of Japanese red pine forests in Korea: controlling factors and contribution to the ecosystem carbon cycle. Ecol. Res. 30, 723–734 (2015).Article 

Google Scholar 
12.Wu, D., Pietsch, K. A., Staab, M. & Yu, M. Wood identity alters dominant factors driving fine wood decomposition along a tree diversity gradient in subtropical plantation forests. Biotropica 53, 643–657 (2021).Article 

Google Scholar 
13.Ohtsuka, T. et al. Role of coarse woody debris in the carbon cycle of Takayama forest, central Japan. Ecol. Res. 29, 91–101 (2014).Article 

Google Scholar 
14.Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).ADS 
CAS 
Article 

Google Scholar 
15.Shorohova, E. & Kapitsa, E. Influence of the substrate and ecosystem attributes on the decomposition rates of coarse woody debris in European boreal forests. For. Ecol. Manag. 315, 173–184 (2014).Article 

Google Scholar 
16.Crockatt, M. E. & Bebber, D. P. Edge effects on moisture reduce wood decomposition rate in a temperate forest. Glob. Chang. Biol. 21, 698–707 (2015).ADS 
PubMed 
Article 

Google Scholar 
17.Dossa, G. G. O. et al. Quantifying the factors affecting wood decomposition across a tropical forest disturbance gradient. For. Ecol. Manag. 468, 118166 (2020).Article 

Google Scholar 
18.Eichenberg, D. et al. The effect of microclimate on wood decay is indirectly altered by tree species diversity in a litterbag study. J. Plant Ecol. 10, 170–178 (2017).Article 

Google Scholar 
19.Cornwell, W. K. et al. Plant traits and wood fates across the globe: Rotted, burned, or consumed?. Glob. Chang. Biol. 15, 2431–2449 (2009).ADS 
Article 

Google Scholar 
20.Warren, R. J. & Bradford, M. A. Ant colonization and coarse woody debris decomposition in temperate forests. Insect Soc. 59, 215–221 (2012).Article 

Google Scholar 
21.Acanakwo, E. F., Sheil, D. & Moe, S. R. Wood decomposition is more rapid on than off termite mounds in an African savanna. Ecosphere 10, e02554 (2019).Article 

Google Scholar 
22.Veldhuis, M. P., Laso, F. J., Olff, H. & Berg, M. P. Termites promote resistance of decomposition to spatiotemporal variability in rainfall. Ecology 98, 467–477 (2017).
PubMed 
Article 

Google Scholar 
23.Liu, G. et al. Termites amplify the effects of wood traits on decomposition rates among multiple bamboo and dicot woody species. J. Ecol. 103, 1214–1223 (2015).Article 

Google Scholar 
24.Maynard, D. S., Crowther, T. W., King, J. R., Warren, R. J. & Bradford, M. A. Temperate forest termites: ecology, biogeography, and ecosystem impacts. Ecol. Entomol. 40, 199–210 (2015).Article 

Google Scholar 
25.Jacobsen, R. M., Sverdrup-Thygeson, A., Kauserud, H., Mundra, S. & Birkemoe, T. Exclusion of invertebrates influences saprotrophic fungal community and wood decay rate in an experimental field study. Funct. Ecol. 32, 2571–2582 (2018).Article 

Google Scholar 
26.Ulyshen, M. D., Wagner, T. L. & Mulrooney, J. E. Contrasting effects of insect exclusion on wood loss in a temperate forest. Ecosphere 5, 47 (2014).Article 

Google Scholar 
27.Box, E. O. & Fujiwara, K. A comparative look at bioclimatic zonation, vegetation types, tree taxa and species richness in northeast Asia. Bot. Pac. 1, 5–20 (2012).Article 

Google Scholar 
28.Lee, K.-S. & Jeong, S.-Y. Ecological characteristics of termite (Riticulitermes speratus kyshuensis) for preservation of wooden cultural heritage. Conserv. Stud. 37, 327–348 (2004) ((in Korean with English abstract)).
Google Scholar 
29.Cheesman, A. W., Cernusak, L. A. & Zanne, A. E. Relative roles of termites and saprotrophic microbes as drivers of wood decay: A wood block test. Austral Ecol. 43, 257–267 (2018).Article 

Google Scholar 
30.Stoklosa, A. M. et al. Effects of mesh bag enclosure and termites on fine woody debris decomposition in a subtropical forest. Basic Appl. Ecol. 17, 463–470 (2016).Article 

Google Scholar 
31.Ulyshen, M. D. Interacting effects of insects and flooding on wood decomposition. PLOS ONE 9, e101867 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
32.Noh, N. J. et al. Carbon and nitrogen accumulation and decomposition from coarse woody debris in a naturally regenerated Korean red pine (Pinus densiflora S. et Z.) forest. Forests 8, 214 (2017).Article 

Google Scholar 
33.Yoon, T. K. et al. Coarse woody debris mass dynamics in temperate natural forests of Mt. Jumbong, Korea. J. Ecol. Field Biol. 34, 115–125 (2011).Article 

Google Scholar 
34.Park, S.-W., Baek, G., Byeon, H.-S., Kim, Y. S. & Kim, C. Carbon and nitrogen dynamics of wood stakes as affected by soil amendment treatments in a post-fire restoration area. Korean J. Agric. For. Meteorol. 20, 357–365 (2018) ((in Korean with English abstract)).
Google Scholar 
35.Ulyshen, M. D. Wood decomposition as influenced by invertebrates. Biol. Rev. 91, 70–85 (2016).PubMed 
Article 

Google Scholar 
36.Gentry, J. B. & Whitford, W. G. The relationship between wood litter infall and relative abundance and feeding activity of subterranean termites Reticulitermes spp. in three southeastern coastal plain habitats. Oecologia 54, 63–67 (1982).ADS 
CAS 
PubMed 
Article 

Google Scholar 
37.Schuurman, G. Decomposition rates and termite assemblage composition in semiarid Africa. Ecology 86, 1236–1249 (2005).Article 

Google Scholar 
38.Weedon, J. T. et al. Global meta-analysis of wood decomposition rates: A role for trait variation among tree species?. Ecol. Lett. 12, 45–56 (2009).PubMed 
Article 

Google Scholar 
39.Yoon, T. K. et al. Effects of sample size and temperature on coarse woody debris respiration from Quercus variabilis logs. J. For. Res. 19, 249–259 (2014).Article 

Google Scholar 
40.Roh, Y. et al. Changes in the contribution of termites to mass loss of dead wood among three tree species during 23 months in a lowland tropical rainforest. Sociobiology 65, 59–66 (2018).Article 

Google Scholar 
41.Vasconcellos, A. & de Moura, F. M. S. Wood litter consumption by three species of Nasutitermes termites in an area of the Atlantic coastal forest in northeastern Brazil. J. Insect Sci. 10, 72 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
42.Kim, S. et al. Differential effects of coarse woody debris on microbial and soil properties in Pinus densiflora Sieb. et Zucc. forests. Forests 8, 292 (2017).Article 

Google Scholar 
43.Kim, R.-H. et al. Coarse woody debris mass and nutrients in forest ecosystems of Korea. Ecol. Res. 21, 819–827 (2006).Article 

Google Scholar 
44.Korea Forest Service. Statistical Yearbook of Forestry. Korea Forest Service, Daejeon (2020) (in Korean)45.Hedges, L. V. & Olkin, I. Statistical methods for meta-analysis 75–106 (Academic Press, New York, 1985).MATH 
Book 

Google Scholar 
46.Nakagawa, S. & Cuthill, I. C. Effect size, confidence interval and statistical significance: A practical guide for biologists. Biol. Rev. 82, 591–605 (2007).PubMed 
Article 

Google Scholar  More

Bioleaching processVariation of pH and ORP during bioleaching processpH and ORP of the sludge are widely known to be the important parameters influencing heavy metal solubilization during bioleaching process, as well as the activity of iron-oxidizing microorganisms10,26,27. The variation of sludge pH and ORP during the single bioleaching process is presented in Fig. 1.Figure 1Variation of pH and ORP during bioleaching process.Full size imageAn appropriate pH could enhance the activities of microbes, affecting the release of metals and the stability of metal ions in the liquid phase5. As shown in Fig. 1, the pH value of sewage sludge quickly decreased from 6.44 to 3.07 in the first 6 days, due to the oxidation of Fe2+ and metal sulfides, the production of sulfuric acid, ferric hydroxide and jarosite from the hydrolysis of Fe3+18. Then the pH gradually decreased to 2.89 on the 10th day. The change of ORP followed an opposite trend. ORP value of the sludge rapidly increased from − 155.6 mV to 480.0 mV in the first 6 days, then to 505.0 mV in the following 4 days, due to the oxidation of Fe2+ to Fe3+ by leaching microorganisms.Heavy metals solubilization and chemical speciation distribution during bioleaching processThe removal of heavy metals during bioleaching process and the distribution of chemical fractions of heavy metals before and after bioleaching are presented in Figs. 2 and 3, respectively. The single bioleaching led to the removal of Zn, Cu, Cd, Cr, Mn, Ni, As and Pb of 67.28%, 50.78%, 64.86%, 6.32%, 56.15%, 49.83%, 20.78% and 10.52% in 10 days, respectively. The solubilization efficiency was highly related to the evolution of pH and ORP, the chemical fraction distributions and the nature of heavy metals.Figure 2Removal of heavy metals during bioleaching process.Full size imageFigure 3Chemical speciation distributions of heavy metals in raw sludge and bioleached sludge, total concentration of heavy metals in the raw sludge was set as 100% (RS raw sludge, BS bioleached sludge).Full size imageFigure 2 illustrated that Zn had the highest solubilization and removal efficiency. It was found that below the threshold pH of 6–6.5, Zn could be dissolved28. Thus, the dissolving out of Zn had started at the beginning of leaching experiment with a removal percentage of 10.15% on the 2nd day. Yet the quick solubilization of Zn was observed from the 4th day (pH 4.01). And until the 6th day (pH 3.00) when the solubilization percentage of Zn was 65.71%, the leaching rate of Zn was slowed down due to the stable pH. In the raw sludge, Zn mainly existed in mobile forms (exchangeable/acid soluble and reducible forms) as shown in Fig. 3. After bioleaching, the solubilization efficiencies of Zn in exchangeable/acid soluble form and reducible form was 58.66% and 87.93%, respectively. Meanwhile, 48.27% of Zn in oxidizable form was also dissolved out due to the oxidation of metal sulfide and loss of sludge organic matter. However, Zn in residual form remained almost unchanged in the bioleached sludge due to its high stability.It has been pointed out that Cu could be rapidly solubilized below pH of 3.7 or under a high ORP condition29. As shown in Fig. 2, in the first 4 days, the solubilization efficiency of Cu was relatively low (11.44%). The removal rate of Cu increased rapidly to 43.54% on the 6th day due to the increase of ORP (480 mV). The proportion of Cu in exchangeable/acid soluble form increased by 55.16% after bioleaching, probably because the solubilized Cu2+ was re-adsorbed on the EPS of sludge cells30,31. Most of Cu was present in reducible and oxidizable forms in the raw sludge as shown in Fig. 3, because the complexation of copper and organic materials was relatively stable30,32,33. The removal percentages of Cu in reducible and oxidizable forms were 71.11% and 61.83% after bioleaching, respectively, which was the main reason for Cu removal.Cd could be solubilized rapidly under acidic conditions as shown in Fig. 2, which is consistent with the previous study34. The solubilization of Cd could be finished in 6 days with the removal rate of 64.36%. Cd was mainly present in mobile forms (91.07%) as shown in Fig. 3, which agreed with the findings of Zeng et al.35 Thus, the acid dissolution was the main removal mechanism of Cd34. Due to the low pH of the bioleached sludge, the content of Cd in mobile forms decreased by 62.77% after bioleaching. Furthermore, Cd in immobile forms (oxidizable and residual forms) also reduced significantly.The previous study found that Cr was relatively stable with the dissolved pH threshold of 2.3–3.028. Although the percentage of Cr present in mobile forms was over 40%, the removal rate of Cr (6.32%) was the lowest among all the heavy metals investigated as shown in Fig. 2, because the lowest pH of the bioleached sludge was about 2.9, which was close to the dissolution threshold limit of Cr.As shown in Fig. 2, Mn and Ni were solubilized quickly in the first 4 days. The solubilization percentage of Mn and Ni were 56.14% and 49.83% after bioleaching, respectively. Mn and Ni mainly existed in the mobile forms (Mn 82.05%, Ni 76.08%). In the early stage of bioleaching, the removal rates of Mn and Ni were closely related to the variation of pH and displayed obvious acid dissolution mechanism. After bioleaching, the concentrations of Mn in exchangeable/acid soluble, reducible and oxidizable forms were reduced by 34.65%, 78.82% and 90.84%, respectively. As for Ni, the removal rates in such forms were 34.66%, 74.58% and 64.99%, respectively. Thus, the higher extraction efficiency of Mn and Ni arose from mixed bioleaching mechanisms, which contain acid dissolution, oxidation and reduction by Fe2+/Fe3+.Relatively low removal efficiency of As (20.78%) was observed in this study. One reason, as shown in Fig. 3, was that As was mainly distributed in residual form with high stability. The other reason was that the dissolved As3+ could be oxidized to As5+ (AsO43-) by Fe3+ generated from the metabolism of iron-oxidizing bacteria, and then insoluble FeAsO4 could be produced through the reaction of AsO43- and Fe3+, which resulted in the reprecipitation of As34.Pb in exchangeable/acid soluble form was not detected in the raw sludge, and mainly existed in reducible (59.20%) and oxidizable (23.19%) forms. The removal rates of Pb in reducible and oxidizable forms were 33.51% and 58.17% after bioleaching, respectively. However, the insoluble compounds such as PbSO4 (Ksp = 1.62 × 10–8) could be generated during the bioleaching process36, which resulted in a significant increase in the concentration of Pb in residual form (from 10.89 to 25.00 mg/kg), and thus led to the low removal ratio of Pb (10.52%).To summarize, the solubilization efficiencies of Zn, Cu, Cd, Mn and Ni, which mainly existed in mobile forms in the raw sludge, were relatively high due to the instability of these metals, while the removal rates of Cr, As and Pb, which mainly existed in immobile forms, were relatively low. However, the contents of most heavy metals in mobile forms decreased obviously after bioleaching and would lead to the corresponding reduction of the environmental risk of the sludge.Combined bioleaching/Fenton-like processEffect of H2O2 dosage on the removal of heavy metals under various pH conditionsPrevious studies have shown that the production ability of hydroxyl radical during the Fenton-like reaction process could be enhanced under pH range of 2.5–4.5, and meanwhile, the amount of H2O2 directly influences the production of hydroxyl radical10,18. Therefore, as shown in Fig. 4, the effects of H2O2 dosage on the solubilization efficiencies of heavy metals were investigated at different stages of the bioleaching process, when the pH values of the bioleached sludge were 4.5 (about 3.5th day), 4.0 (4th day) and 3.0 (6th day).Figure 4Effects of H2O2 dosage on the removal efficiency of heavy metals under various pH conditions.Full size imageWith the increasing concentrations of H2O2 (0.0–8.0 g/L), the solubilization efficiency of Zn increased significantly at pH of 4.5 (Fig. 4) due to the oxidation of metal sulfide and organics by hydroxyl radical10. However, the solubilization percentages of Zn barely changed with further increase of H2O2 dosage (from 8.0 to 15.0 g/L). The solubilization percentage of Zn at the H2O2 dosage of 8.0 g/L (pH of 4.5) was significantly higher than when only using single bioleaching (75.31% vs. 67.64%). The enhancement of solubilization efficiency of Zn at a pH of 4.0 and 3.0 was not very noticeable (Fig. 4), because most of the Zn in immobile forms was dissolved out by bioleaching. The highest solubilization percentages of Zn were 74.96% at a pH of 4.0 and 75.53% at a pH of 3.0, which were 7.32% and 7.89% higher than that of the single bioleaching process.Due to the lower dissolved pH threshold of Cu compared with Zn, the solubilization efficiency of Cu was significantly affected by the dosage of H2O2 at a pH of 4.5 and 4.0 as shown in Fig. 4, while when the reaction pH was 3.0, the subsequent Fenton treatment had a relatively small impact on the removal of Cu. The highest removal rate of Cu (52.17%) was obtained at pH of 3.0 and H2O2 dosage of 13.0 g/L, which was slightly higher than that of the single bioleaching (50.78%). The change in solubilization efficiency of Cd was similar to that of Cu. When the pH values were 4.5 and 4.0, the solubilization percentages of Cd with H2O2 dosage of 15.0 g/L were 4.59% and 1.23% higher than that of the single bioleaching process, respectively. Meanwhile, the highest solubilization percentage of Cd (71.91%) could be reached at a pH of 3.0 and H2O2 dosage of 13.0 g/L, which was higher than that of the single bioleaching process (64.86%).The addition of H2O2 did not increase the removal rate of Cr significantly as shown in Fig. 4. At a reaction pH of 4.5, the solubilization percentage of Cr was 7.59% with H2O2 dosage of 15.0 g/L, which was a little higher than that of the single bioleaching process (6.32%), while the highest solubilization percentages of Cr could reach 11.63% and 9.18% at pH of 4.0 and 3.0, respectively, with H2O2 dosage of 15.0 g/L.The solubilization process of Mn and Ni displayed similar trend as shown in Fig. 4. The solubilization percentage of Mn was not significantly improved when the H2O2 dosage was increased from 5.0 to 11.0 g/L at pH of 4.5 and 4.0, but a much faster increase of the removal rate was observed with the H2O2 dosage over 13.0 g/L. It could be due to the enhanced oxidizing ability of Fenton-like reaction with abundant H2O2. However, the solubilization efficiency of Mn under a pH of 3.0 began to increase with H2O2 concentration of 11.0 g/L, which could be attributed to the high efficiency of Fenton action under lower pH15. The highest removal percentage of Mn was 66.29% at pH of 3.0 and H2O2 dosage of 15.0 g/L, while the removal percentage of Mn in the single bioleaching process was 56.14%. The removal behavior of Ni at various pH was consistent with Mn. The highest removal rate of Ni (65.81%) was found at a pH of 3.0 with H2O2 dosage of 15.0 g/L, which was significantly improved, compared with the single bioleaching process (49.83%).On the contrary, the removal efficiency of As and Pb in the combined process was not promoted compared with the single bioleaching process. Due to the strong oxidizing capacity of Fenton-like process, the yield of SO42− and insoluble FeAsO4 could be improved. Correspondingly, Pb2+ could be transformed into residual form, such as insoluble PbSO410. Therefore, the removal efficiencies of As and Pb decreased in the combined process. The highest removal rates of As and Pb after Fenton-like treatment were 12.46% and 10.20%, respectively.In the combined process, higher solubilization efficiencies of most heavy metals (Zn, Cu, Cd, Mn, Ni, Cr) could be achieved in 6 days. The removal efficiency of heavy metals (except Cr, As and Pb) of combined process (pH of 3.0, H2O2 dosage of 15 g/L) is higher than that of the single bioleaching process. The removal rate of Zn, Cu, Cd, Mn and Ni increased by 7.89%, 0.38%, 5.56%, 10.15% and 15.35%, respectively. Meanwhile, the total concentrations of heavy metals measured in this study after treatment could meet the control standards of pollutants in sludge for agricultural use of China (National Standard GB 4284-2018). The removal of As and Pb was not improved by the combined process, other methods such as chemical leaching, electrokinetic remediation and phytoremediation could be considered as alternatives. However, their transformation into insoluble forms may also reduce the bioavailability of heavy metals and increase the environmental safety of the treated sludge. For that reason, the chemical speciation distributions of heavy metals in the combined process were further analyzed in detail.Chemical fraction distributions of heavy metals in the combined processIt can be seen in Fig. 4 that the solubilization efficiency of most heavy metals did not change significantly with H2O2 dosage below 8.0 g/L. Therefore, the chemical speciation changes of heavy metals after Fenton treatment under H2O2 dosage of 11.0, 13.0 and 15.0 g/L, as shown in Fig. 5, were discussed.Figure 5Change of chemical speciation distributions of heavy metals under different H2O2 dosage at a pH of 4.5, 4.0 and 3.0, total concentration of heavy metal in the raw sludge was set as 100%.Full size imageUnder various pH conditions, the contents of Zn in all of the four forms showed a downward trend along with the increasing H2O2 dosage (Fig. 5). After bioleaching, Zn mainly existed in exchangeable/acid soluble form under the final pH of 4.5 (64.89%), pH of 4.0 (73.33%) and pH of 3.0 (80.82%). The removal of Zn in exchangeable/acid soluble form showed good correlation to the dosage of H2O2, which might be attributed to the destruction of EPS, and the released heavy metals were transferred to the liquid phase. Meanwhile, the improvement of sludge dewaterability could also promote the removal of heavy metals. After Fenton-like reaction at a pH of 4.5, the percentages of Zn in exchangeable/acid soluble forms were reduced by 30.35%, 31.41% and 40.09% at H2O2 dosage of 11.0, 13.0 and 15.0 g/L, respectively, compared with the percentage of Zn in the sludge at the end of the single bioleaching process. However, the percentage of Zn in other forms did not change significantly after Fenton-like treatment. Therefore, the further removal of Zn in exchangeable/acid soluble form and the dewaterability improvement of sludge may be the main reasons for the higher removal efficiency of Zn in the combined process.Cu was still mainly associated with the oxidizable form after bioleaching ended at pH of 4.5, 4.0 and 3.0 (Fig. 5), which might be attributed to the preference of Cu for organic materials22. The addition of H2O2 at pH 4.5 significantly boosted the solubilization efficiency of Cu in exchangeable/acid soluble form. The percentages of Cu in exchangeable/acid soluble form in the sludge after Fenton treatment at pH 4.5 were 24.69% (11.0 g/L), 29.50% (13.0 g/L) and 38.15% (15.0 g/L), which were lower than that at the end of the single bioleaching process. Meanwhile, the content of Cu in reducible form was reduced by nearly 50% with H2O2 dosage of 13.0 and 15.0 g/L, compared with its content after bioleaching ended at pH 4.5. However, the highest removal rate of Cu in oxidizable form was only 33.20% with H2O2 dosage of 15.0 g/L. The removal efficiency of Cu in exchangeable/acid soluble and reducible forms increased with the increasing H2O2 dosage at pH 4.0 and 3.0, similar to the observation at pH 4.5. Under a reaction pH of 4.0, 47.2% of Cu in oxidizable form was removed after Fenton treatment with H2O2 dosage of 13.0 g/L, while only 28.6% was removed at H2O2 dosage of 15.0 g/L. In addition, the removal rates of Cu in oxidizable form were only 4.9–17.7% at various H2O2 dosage at a Fenton reaction pH of 3.0. The removal efficiency of Cu was reduced in despite of the increasing oxidation capacity of Fenton-like reaction. The macro-molecular organic matters could be degraded into small organic molecules during Fenton treatment process, releasing partial Cu. However, the generated small molecule organic matters had more undissociated carboxyl that would combine with released Cu31, which formed Cu in oxidizable form. Thus, it could explain the low removal efficiency of Cu in oxidizable form under stronger oxidizing condition. However, the highest removal rate of Cu (52.17%) was observed at pH 3.0 and H2O2 dosage of 15.0 g/L, due to the high reduction ratio of Cu in mobile forms at that condition.Cd mainly existed in mobile forms in the sludge after bioleaching and Fenton treatment, as shown in Fig. 5. The contents of Cd in mobile and oxidizable forms decreased with the increasing H2O2 dosage at pH 4.5. The content of Cd in exchangeable/acid soluble form after Fenton treatment at pH 4.5 and H2O2 dosage of 15.0 g/L was 29.10% lower than that at the end of the single bioleaching process. Meanwhile, the content of Cd in mobile form was decreased by 27.54% (11.0 g/L), 26.56% (13.0 g/L) and 36.72% (15.0 g/L) after Fenton treatment at pH 4.0. The removal of Cd in exchangeable/acid soluble form after Fenton treatment could be largely due to the improvement of sludge dewaterability. However, the reduction of Cd was not obvious after Fenton treatment at pH 3.0, because the solubilization threshold of most of Cd in various forms were reached after the bioleaching process ended at pH 3.0.The removal efficiency of Cr was not improved obviously by Fenton treatment in this study, as shown in Fig. 5. It was also reported that Cr was difficult to be removed by bioleaching or combined process due to its relatively high stability10. However, the content of Cr in oxidizable form after Fenton treatment at pH 4.5 was 4.76% (11.0 g/L), 9.20% (13.0 g/L) and 9.84% (15.0 g/L) lower than that at the end of the single bioleaching process, due to the strong oxidizing capacity of hydroxyl radical. And the lowest content of Cr in oxidizable form was observed after Fenton treatment at pH 4.0 and H2O2 dosages of 13.0 g/L, which was 39.4% lower than that in the bioleached sludge. Meanwhile, the highest Cr removal rate was also obtained at this condition after Fenton-like treatment. Thus, the improvement of Cr removal in combined process was mainly due to the release of Cr in oxidizable form. Furthermore, the released metals could be absorbed on the surface of oxides31, thus inevitably caused the increase of Cr in reducible form as shown in Fig. 5. The chemical speciation change of Cr after Fenton treatment at pH 3.0 was similar to that at pH 4.0.The removal efficiency and chemical speciation distribution of Mn varied obviously after Fenton treatment with different dosages of H2O2. The removal rate of Mn was improved with the increasing dosage of H2O2 at various pH values. Because most of the Mn in reducible form (over 80%) was removed by bioleaching process, the reduction of Mn in exchangeable/acid soluble form should account for the removal of a substantial part of Mn after Fenton treatment. The highest removal rate of Mn in exchangeable/acid soluble form under different pH conditions was 26.27% (pH 4.5), 25.06% (pH 4.0) and 42.18% (pH 3.0), all with H2O2 dosage of 15.0 g/L. Although nearly 30% of Mn in reducible and oxidizable forms was also removed after Fenton treatment with H2O2 dosage of 15.0 g/L at various pH values, it contributed little to the removal of Mn considering the low concentration of Mn in reducible and oxidizable forms in the raw sludge. Furthermore, the changes of Mn in residual form were not obvious under different pH.The chemical speciation change of Ni was similar to that of Mn after Fenton treatment. The contents of Ni in mobile and oxidizable forms decreased along with the increasing dosage of H2O2, as shown in Fig. 5. Meanwhile, the reduction of Ni in exchangeable/acid soluble form after the addition of H2O2 was the prime reason for the higher removal efficiency of Ni after the combined process than that after the single bioleaching process. The highest removal rate of Ni in exchangeable/acid soluble form was found with H2O2 dosage of 15.0 g/L at pH 4.0, which was 34.47% lower than that in the sludge after the signal bioleaching process. However, the highest removal efficiency of Ni (65.19%) was reached when the reaction pH was 3.0 with H2O2 dosages of 15.0 g/L due to the simultaneous reduction of Ni in reducible and oxidizable forms. The contents of Ni in reducible and oxidizable forms were reduced by 50.30% and 52.83% under this reaction condition, respectively, compared with that at the end of the single bioleaching process.As and Pb were mainly present in residual form before Fenton treatment as shown in Fig. 5. The content of As in exchangeable/acid soluble form decreased significantly due to the degradation of EPS at various pH values with the addition of H2O2. However, the content of As in residual form gradually rose with the increasing dosage of H2O2, probably because As3+ could be oxidized to As5+ by hydroxyl radical and/or Fe3+ with the formation of insoluble FeAsO434. The content of Pb in reducible form showed a trend of increase after Fenton treatment. SO42− was generated due to the oxidation of sulfur elements and/or sulfide in sludge by hydroxyl radicals with the production of insoluble PbSO410, and thus the content of Pb in residual form also increased after further Fenton treatment. Although the Fenton treatment had a negative impact on the removal of As and Pb as shown in Fig. 5, because of the formation of insoluble compounds under strong oxidizing condition, the environmental risk of these two heavy metals decreased to some extent under an appropriate condition, due to the increased proportion of immobile fractions, especially residual form. compared with the bioleached sludge.The content and proportion of most heavy metals (Zn, Cu, Cd, Mn, Ni, As) in mobile forms were lower in the treated sludge after the combined bioleaching and Fenton-like process, compared with the single bioleaching process, which was also the main reason for the high removal efficiency of these metals. Their bioavailability and toxicity were also reduced. However, Fenton treatment was found to have a negative impact on the removal of As, but the increased proportion of As in residual form also lowered its bioavailability and mobility in the environment. The increase in the content of Pb in both mobile forms (mainly in reducible form) and immobile forms (mainly in residual form) was observed under different conditions, so special attention should be paid to the chemical speciation distributions of Pb during sludge treatment process.The effect of H2O2 dosage on sludge dewaterability at different pH valuesThe changes of CST of treated sludge under various conditions are presented in Fig. 6. The CST of the raw sludge (98.7 s) was dramatically reduced by bioleaching and Fenton oxidation treatments. After bioleaching ended on the 10th day (pH 2.89), the 6th day (pH 3.0), the 4th day (4.0) and the 3.5th day (pH 4.5), CST values of 20.3 s, 24.2 s, 30.7 s and 35.0 s were observed. The decreased pH after bioleaching process could destroy the EPS and neutralize the negative charge of the sludge flocs, resulting in the release of bound water37. Moreover, sludge dewatering could also be improved by the coagulation effect of Fe2+ 10. Furthermore, hydroxyl radicals were essential to improve sludge dewatering performance by destroying EPS and porous structure during the Fenton treatment process35. Therefore, the CST value of treated sludge was reduced to 20.6 s after Fenton treatment with H2O2 dosage of 15 g/L at pH 4.5, which was comparable to the CST value at the end of the single bioleaching process. The CST values were further reduced along with the decreasing reaction pH (4.0 and 3.0) and the increasing H2O2 dosage. The lowest CST value of 12.4 s was observed at Fenton reaction pH 3.0 and H2O2 dosage of 15.0 g/L, which meant a reduction from the initial CST of 87.44%. Therefore, the combined process could lead to an obvious improvement of the sludge dewaterability and significantly reduced the treatment period.Figure 6Changes of CST under different H2O2 dosage and pH.Full size image More

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

Google Scholar 
2.Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).Article 

Google Scholar 
3.Isbell, F. et al. Linking the influence and dependence of people on biodiversity across scales. Nature 546, 65–72 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
4.Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
5.Bessler, H. et al. Nitrogen uptake by grassland communities: contribution of N2 fixation, facilitation, complementarity, and species dominance. Plant Soil 358, 301–322 (2012).CAS 
Article 

Google Scholar 
6.Karanika, E. D., Alifragis, D. A., Mamolos, A. P. & Veresoglou, D. S. Differentiation between responses of primary productivity and phosphorus exploitation to species richness. Plant Soil 297, 69–81 (2007).CAS 
Article 

Google Scholar 
7.Lange, M. et al. How plant diversity impacts the coupled water, nutrient and carbon cycles. Adv. Ecol. Res. 61, 185–219 (2019).Article 

Google Scholar 
8.Oelmann, Y. et al. Does plant diversity influence phosphorus cycling in experimental grasslands? Geoderma 167-68, 178–187 (2011).ADS 
Article 
CAS 

Google Scholar 
9.Tilman, D., Wedin, D. & Knops, J. Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379, 718–720 (1996).ADS 
CAS 
Article 

Google Scholar 
10.Leimer, S., Oelmann, Y., Wirth, C. & Wilcke, W. Time matters for plant diversity effects on nitrate leaching from temperate grassland. Agric Ecosyst. Environ. 211, 155–163 (2015).CAS 
Article 

Google Scholar 
11.Scherer-Lorenzen, M., Palmborg, C., Prinz, A. & Schulze, E.-D. The role of plant diversity and composition for nitrate leaching in grasslands. Ecology 84, 1539–1552 (2003).Article 

Google Scholar 
12.Elser, J. & Bennett, E. A broken biogeochemical cycle. Nature 478, 29–31 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
13.Lambers, H., Mougel, C., Jaillard, B. & Hinsinger, P. Plant-microbe-soil interactions in the rhizosphere: an evolutionary perspective. Plant Soil 321, 83–115 (2009).CAS 
Article 

Google Scholar 
14.Wassen, M. J., Olde Venterink, H., Lapshina, E. D. & Tanneberger, F. Endangered plants persist under phosphorus limitation. Nature 437, 547–550 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
15.Cordell, D., Drangert, J.-O. & White, S. The story of phosphorus: Global food security and food for thought. Glob. Environ. Change-Hum. Policy Dimens. 19, 292–305 (2009).Article 

Google Scholar 
16.van der Heijden, M. G. A., Martin, F. M., Selosse, M.-A. & Sanders, I. R. Mycorrhizal ecology and evolution: the past, the present, and the future. N. Phytol. 205, 1406–1423 (2015).Article 
CAS 

Google Scholar 
17.van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).ADS 
Article 
CAS 

Google Scholar 
18.Richardson, A. E. & Simpson, R. J. Soil microorganisms mediating phosphorus availability. Plant Physiol. 156, 989–996 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Hacker, N. et al. Plant diversity shapes microbe-rhizosphere effects on P mobilisation from organic matter in soil. Ecol. Lett. 18, 1356–1365 (2015).PubMed 
Article 

Google Scholar 
20.Hacker, N., Wilcke, W. & Oelmann, Y. The oxygen isotope composition of bioavailable phosphate in soil reflects the oxygen isotope composition in soil water driven by plant diversity effects on evaporation. Geochim. Cosmochim. Acta 248, 387–399 (2019).ADS 
CAS 
Article 

Google Scholar 
21.Craven, D. et al. Plant diversity effects on grassland productivity are robust to both nutrient enrichment and drought. Philos. Trans. R. Soc. B 371, 8 (2016).Article 

Google Scholar 
22.Fridley, J. D. Resource availability dominates and alters the relationship between species diversity and ecosystem productivity in experimental plant communities. Oecologia 132, 271–277 (2002).ADS 
PubMed 
Article 

Google Scholar 
23.Weigelt, A., Weisser, W. W., Buchmann, N. & Scherer-Lorenzen, M. Biodiversity for multifunctional grasslands: equal productivity in high-diversity low-input and low-diversity high-input systems. Biogeosciences 6, 1695–1706 (2009).ADS 
CAS 
Article 

Google Scholar 
24.Nyfeler, D. et al. Strong mixture effects among four species in fertilized agricultural grassland led to persistent and consistent transgressive overyielding. J. Appl Ecol. 46, 683–691 (2009).Article 

Google Scholar 
25.Oelmann, Y., Vogel, A., Wegener, F., Weigelt, A. & Scherer-Lorenzen, M. Management intensity modifies plant diversity effects on N yield and mineral N in soil. Soil Sci. Soc. Am. J. 79, 559–568 (2015).ADS 
CAS 
Article 

Google Scholar 
26.Manning P., et al. Transferring biodiversity-ecosystem function research to the management of ‘real-world’ ecosystems. In: Mechanisms Underlying the Relationship between Biodiversity and Ecosystem Function (ed^(eds Eisenhauer N., Bohan D. A., Dumbrell A. J.). Academic Press Ltd-Elsevier Science Ltd (2019).27.Kraft, N. J. B. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015).Article 

Google Scholar 
28.Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18, 834–843 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
29.Collins, C. D. & Foster, B. L. Community-level consequences of mycorrhizae depend on phosphorus availability. Ecology 90, 2567–2576 (2009).PubMed 
Article 

Google Scholar 
30.Klironomos, J. N., McCune, J., Hart, M. & Neville, J. The influence of arbuscular mycorrhizae on the relationship between plant diversity and productivity. Ecol. Lett. 3, 137–141 (2000).Article 

Google Scholar 
31.Busch, V. et al. Will I stay or will I go? Plant species-specific response and tolerance to high land-use intensity in temperate grassland ecosystems. J. Veg. Sci. 30, 674–686 (2019).Article 

Google Scholar 
32.Sorkau, E. et al. The role of soil chemical properties, land use and plant diversity for microbial phosphorus in forest and grassland soils. J. Plant Nutr. Soil Sci. 181, 185–197 (2018).CAS 
Article 

Google Scholar 
33.Wardle, D. A. A comparative assessment of factors which influence microbial biomass carbon and nitrogen levels in soil. Biol. Rev. Camb. Philos. Soc. 67, 321–358 (1992).Article 

Google Scholar 
34.Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 6707 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
35.Eisenhauer, N. et al. Plant diversity effects on soil microorganisms support the singular hypothesis. Ecology 91, 485–496 (2010).CAS 
PubMed 
Article 

Google Scholar 
36.Cleveland, C. C. & Liptzin, D. C. N: P stoichiometry in soil: is there a “Redfield ratio” for the microbial biomass? Biogeochemistry 85, 235–252 (2007).Article 

Google Scholar 
37.Cardinale, B. J. et al. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104, 18123–18128 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
38.Marquard, E. et al. Plant species richness and functional composition drive overyielding in a 6-year grassland experiment. Ecology 90, 3290–3302 (2009).PubMed 
Article 

Google Scholar 
39.Liebisch, F. et al. Seasonal dynamics and turnover of microbial phosphorus in a permanent grassland. Biol. Fertil. Soils 50, 465–475 (2014).CAS 
Article 

Google Scholar 
40.Boeddinghaus, R. S. et al. Plant functional trait shifts explain concurrent changes in the structure and function of grassland soil microbial communities. J. Ecol. 107, 2197–2210 (2019).CAS 
Article 

Google Scholar 
41.Soussana, J. F. et al. Carbon cycling and sequestration opportunities in temperate grasslands. Soil Use Manag. 20, 219–230 (2004).Article 

Google Scholar 
42.Waldrop, M. P., Zak, D. R., Blackwood, C. B., Curtis, C. D. & Tilman, D. Resource availability controls fungal diversity across a plant diversity gradient. Ecol. Lett. 9, 1127–1135 (2006).PubMed 
Article 

Google Scholar 
43.Kour, D. et al. Biodiversity, current developments and potential biotechnological applications of phosphorus-solubilizing and -mobilizing microbes: a review. Pedosphere 31, 43–75 (2021).Article 

Google Scholar 
44.Dijkstra, F. A., He, M. Z., Johansen, M. P., Harrison, J. J. & Keitel, C. Plant and microbial uptake of nitrogen and phosphorus affected by drought using N-15 and P-32 tracers. Soil Biol. Biochem. 82, 135–142 (2015).CAS 
Article 

Google Scholar 
45.Hiiesalu, I. et al. Species richness of arbuscular mycorrhizal fungi: associations with grassland plant richness and biomass. N. Phytol. 203, 233–244 (2014).CAS 
Article 

Google Scholar 
46.Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).ADS 
CAS 
PubMed 
Article 

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

Google Scholar 
48.Hoffmann K., Bivour W., Früh B., Koßmann M., Voß P.-H. Climate studies in Jena for adaption to climate change and ist expected consequences. (In German). Selbstverlag des Deutschen Wetterdienstes (2014).49.IUSS Working Group WRB. World Reference Base for Soil Resources 2014, update 2015: International soil classification system for naming soils and creating legends for soil maps. FAO (2015).50.Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: the biodiversity exploratories. Bas Appl Ecol. 11, 473–485 (2010).Article 

Google Scholar 
51.Alt, F., Oelmann, Y., Herold, N., Schrumpf, M. & Wilcke, W. Phosphorus partitioning in grassland and forest soils of Germany as related to land-use type, management intensity, and land use-related pH. J. Plant Nutr. Soil Sci. 174, 195–209 (2011).CAS 
Article 

Google Scholar 
52.Vogt, J. et al. Eleven years’ data of grassland management in Germany. Biodiver Data J. 7, 38 (2019).Article 

Google Scholar 
53.Alt, F., Oelmann, Y., Schöning, I. & Wilcke, W. Phosphate release kinetics at stable pH in calcareous grassland and forest soils. Soil Sci. Soc. Am. J. 77, 2060–2070 (2013).ADS 
CAS 
Article 

Google Scholar 
54.Jones J. B., Wolf B., Mills H. A. Plant analysis handbook. Micro Macro Publishing (1991).55.Marina, M. A. & Lopez, M. C. B. Determination of phosphorus in raw materials for ceramics: comparison between X-ray fluorescence spectrometry and inductively coupled plasma-atomic emission spectrometry. Anal. Chim. Acta 432, 157–163 (2001).CAS 
Article 

Google Scholar 
56.Hedley, M. J., Stewart, J. W. B. & Chauhan, B. S. Changes in inorganic and organic soil-phosphorus fractions induced by cultivation practices and by laboratory incubations. Soil Sci. Soc. Am. J. 46, 970–976 (1982).ADS 
CAS 
Article 

Google Scholar 
57.Kuo S. Phosphorus. In: Methods of Soil Analysis – Part 3 Chemical Methods (eds Sparks D. L., et al.). SSSA (1996).58.Cross, A. F. & Schlesinger, W. H. A literature review and evaluation of the Hedley fractionation – applications to the biogeochemical cycle of soil phosphorus in natural ecosystems. Geoderma 64, 197–214 (1995).ADS 
CAS 
Article 

Google Scholar 
59.Negassa, W. & Leinweber, P. How does the Hedley sequential phosphorus fractionation reflect impacts of land use and management on soil phosphorus: a review. J. Plant Nutr. Soil Sci. 172, 305–325 (2009).CAS 
Article 

Google Scholar 
60.Murphy, J. & Riley, J. P. A modified single solution method for determination of phosphate in natural waters. Anal. Chim. Acta 26, 31–36 (1962).Article 

Google Scholar 
61.McLaughlin, M. J., Alston, A. M. & Martin, J. K. Measurement of phosphorus in the soil microbial biomass – a modified procedure for field soils. Soil Biol. Biochem. 18, 437–443 (1986).CAS 
Article 

Google Scholar 
62.Kouno, K., Tuchiya, Y. & Ando, T. Measurement of soil microbial biomass phosphorus by an anion exchange membrane method. Soil Biol. Biochem. 27, 1353–1357 (1995).CAS 
Article 

Google Scholar 
63.Bünemann, E. K., Marschner, P., Smernik, R. J., Conyers, M. & McNeill, A. M. Soil organic phosphorus and microbial community composition as affected by 26 years of different management strategies. Biol. Fertil. Soils 44, 717–726 (2008).Article 

Google Scholar 
64.Brookes, P. C., Powlson, D. S. & Jenkinson, D. S. Measurement of microbial biomass phosphorus in soil. Soil Biol. Biochem 14, 319–329 (1982).CAS 
Article 

Google Scholar 
65.Eivazi, F. & Tabatabai, M. A. Phosphatases in soils. Soil Biol. Biochem. 9, 167–172 (1977).CAS 
Article 

Google Scholar 
66.Marx, M. C., Wood, M. & Jarvis, S. C. A microplate fluorimetric assay for the study of enzyme diversity in soils. Soil Biol. Biochem. 33, 1633–1640 (2001).CAS 
Article 

Google Scholar 
67.Berner, D. et al. Land-use intensity modifies spatial distribution and function of soil microorganisms in grasslands. Pedobiologia 54, 341–351 (2011).ADS 
Article 

Google Scholar 
68.White, D. C., Davis, W. M., Nickels, J. S., King, J. D. & Bobbie, R. J. Determination of the sedimentary microbial biomass by extractable lipid phosphate. Oecologia 40, 51–62 (1979).ADS 
CAS 
PubMed 
Article 

Google Scholar 
69.Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).CAS 
PubMed 
Article 

Google Scholar 
70.Kramer, C. & Gleixner, G. Variable use of plant- and soil-derived carbon by microorganisms in agricultural soils. Soil Biol. Biochem. 38, 3267–3278 (2006).CAS 
Article 

Google Scholar 
71.Frostegard, A. & Baath, E. The use of phospholipid fatty acid analysis to estimate bacterial and fungal biomass in soil. Biol. Fertil. Soils 22, 59–65 (1996).Article 

Google Scholar 
72.Zelles, L. Identification of single cultured micro-organisms based on their whole-community fatty acid profiles, using an extended extraction procedure. Chemosphere 39, 665–682 (1999).ADS 
CAS 
PubMed 
Article 

Google Scholar 
73.Dassen, S. et al. Differential responses of soil bacteria, fungi, archaea and protists to plant species richness and plant functional group identity. Mol. Ecol. 26, 4085–4098 (2017).CAS 
PubMed 
Article 

Google Scholar 
74.Kuramae, E. E. et al. Tracking fungal community responses to maize plants by DNA- and RNA-based pyrosequencing. PLoS ONE 8, 8 (2013).Article 
CAS 

Google Scholar 
75.Wubet, T., Weiss, M., Kottke, I. & Oberwinkler, F. Two threatened coexisting indigenous conifer species in the dry Afromontane forests of Ethiopia are associated with distinct arbuscular mycorrhizal fungal communities. Can. J. Bot.-Rev. Canadienne De. Botanique 84, 1617–1627 (2006).CAS 

Google Scholar 
76.Lee, J., Lee, S. & Young, J. P. W. Improved PCR primers for the detection and identification of arbuscular mycorrhizal fungi. FEMS Microbiol. Ecol. 65, 339–349 (2008).CAS 
PubMed 
Article 

Google Scholar 
77.Simon, L., Lalonde, M. & Bruns, T. D. Specific amplification of 18S fungal ribosomal genes from vesicular-arbuscular endomycorrhizal fungi colonizing roots. Appl. Environ. Microbiol. 58, 291–295 (1992).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
78.Lefcheck, J. S. PIECEWISESEM: Piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar 
79.van der Heijden, M. G. A. et al. The mycorrhizal contribution to plant productivity, plant nutrition and soil structure in experimental grassland. N. Phytol. 172, 739–752 (2006).Article 

Google Scholar 
80.Frew, A. Arbuscular mycorrhizal fungal diversity increases growth and phosphorus uptake in C-3 and C-4 crop plants. Soil Biol. Biochem. 135, 248–250 (2019).CAS 
Article 

Google Scholar 
81.Hedlund, K. et al. Plant species diversity, plant biomass and responses of the soil community on abandoned land across Europe: idiosyncracy or above-belowground time lags. Oikos 103, 45–58 (2003).Article 

Google Scholar 
82.Treseder, K. K. The extent of mycorrhizal colonization of roots and its influence on plant growth and phosphorus content. Plant Soil 371, 1–13 (2013).CAS 
Article 

Google Scholar 
83.Köhl, L., Oehl, F. & van der Heijden, M. G. A. Agricultural practices indirectly influence plant productivity and ecosystem services through effects on soil biota. Ecol. Appl. 24, 1842–1853 (2014).PubMed 
Article 

Google Scholar 
84.Fornara, D. A. & Tilman, D. Plant functional composition influences rates of soil carbon and nitrogen accumulation. J. Ecol. 96, 314–322 (2008).CAS 
Article 

Google Scholar 
85.Steinbeiss, S. et al. Plant diversity positively affects short-term soil carbon storage in experimental grasslands. Glob. Change Biol. 14, 2937–2949 (2008).ADS 
Article 

Google Scholar 
86.Hacker N. Phosphorus Release Mechanisms in an Experimental Grassland of Varying Biodiversity. Doctoral thesis, University of Tübingen, Germany (2017). More

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1.Jørgensen BB. Mineralization of organic matter in the sea bed-the role of sulphate reduction. Nature. 1982;296:643–5.Article 

Google Scholar 
2.Kasten S, Jørgensen BB. Sulfate reduction in marine sediments. In: Schulz H, Zabel M, editors. Marine geochemistry. Berlin: Springer; 2000. pp. 263–81.3.Pellerin A, Antler G, Røy H, Findlay A, Beulig F, Scholze C, et al. The sulfur cycle below the sulfate-methane transition of marine sediments. Geochim Cosmochim Acta. 2018;239:74–89.CAS 
Article 

Google Scholar 
4.Reeburgh WS. Oceanic methane biogeochemistry. Chem Rev. 2007;107:486–513.CAS 
Article 

Google Scholar 
5.Holmkvist L, Ferdelman TG, Jørgensen BB. A cryptic sulfur cycle driven by iron in the methane zone of marine sediment (Aarhus Bay, Denmark). Geochim Cosmochim Acta. 2011;75:3581–99.CAS 
Article 

Google Scholar 
6.Starnawski P, Bataillon T, Ettema TJ, Jochum LM, Schreiber L, Chen X, et al. Microbial community assembly and evolution in subseafloor sediment. Proc Natl Acad Sci USA. 2017;114:2940–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
7.Hoehler TM, Jørgensen BB. Microbial life under extreme energy limitation. Nat Rev Microbiol. 2013;11:83–94.CAS 
PubMed 
Article 

Google Scholar 
8.Jørgensen BB, Marshall IP. Slow microbial life in the seabed. Annu Rev Mar Sci. 2016;8:311–32.Article 

Google Scholar 
9.Lever MA, Rogers KL, Lloyd KG, Overmann J, Schink B, Thauer RK, et al. Life under extreme energy limitation: a synthesis of laboratory-and field-based investigations. FEMS Microbiol Rev. 2015;39:688–728.CAS 
PubMed 
Article 

Google Scholar 
10.Button DK. Kinetics of nutrient-limited transport and microbial growth. Microbiol Rev. 1985;49:270–97.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.De Mattos MT, Neijssel OM. Bioenergetic consequences of microbial adaptation to low-nutrient environments. J Biotechnol. 1997;59:117–26.Article 

Google Scholar 
12.Egli T. How to live at very low substrate concentration. Water Res. 2010;44:4826–37.CAS 
PubMed 
Article 

Google Scholar 
13.Li J, Mara P, Schubotz F, Sylvan JB, Burgaud G, Klein F, et al. Recycling and metabolic flexibility dictate life in the lower oceanic crust. Nature. 2020;579:250–5.CAS 
PubMed 
Article 

Google Scholar 
14.Zinke LA, Mullis MM, Bird JT, Marshall IP, Jørgensen BB, Lloyd KG, et al. Thriving or surviving? Evaluating active microbial guilds in Baltic Sea sediment. Environ Microbiol Rep. 2017;9:528–36.CAS 
PubMed 
Article 

Google Scholar 
15.Orsi WD, Jørgensen BB, Biddle JF. Transcriptional analysis of sulfate reducing and chemolithoautotrophic sulfur oxidizing bacteria in the deep subseafloor. Environ Microbiol Rep. 2016;8:452–60.CAS 
PubMed 
Article 

Google Scholar 
16.Orsi WD, Edgcomb VP, Christman GD, Biddle JF. Gene expression in the deep biosphere. Nature. 2013;499:205–8.CAS 
PubMed 
Article 

Google Scholar 
17.Cappenberg TE. A study of mixed continuous cultures of sulfate-reducing and methane-producing bacteria. Microb Ecol. 1975;2:60–72.CAS 
PubMed 
Article 

Google Scholar 
18.Middleton AC, Lawrence AW. Kinetics of microbial sulfate reduction. J Water Pollut Control Fed. 1977;49:1659–70.CAS 

Google Scholar 
19.Nethe-Jaenchen R, Thauer RK. Growth yields and saturation constant of Desulfovibrio vulgaris in chemostat culture. Arch Microbiol. 1984;137:236–40.CAS 
Article 

Google Scholar 
20.Ingvorsen K, Zehnder AJ, Jørgensen BB. Kinetics of sulfate and acetate uptake by Desulfobacter postgatei. Appl Environ Microbiol. 1984;47:403–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
21.Cypionka H, Pfennig N. Growth yields of Desulfotomaculum orientis with hydrogen in chemostat culture. Arch Microbiol. 1986;143:396–9.CAS 
Article 

Google Scholar 
22.Okabe S, Characklis WG. Effects of temperature and phosphorous concentration on microbial sulfate reduction by Desulfovibrio desulfuricans. Biotechnol Bioeng. 1992;39:1031–42.CAS 
PubMed 
Article 

Google Scholar 
23.Okabe S, Nielsen PH, Characklis WG. Factors affecting microbial sulfate reduction by Desulfovibrio desulfuricans in continuous culture: limiting nutrients and sulfide concentration. Biotechnol Bioeng. 1992;40:725–34.CAS 
PubMed 
Article 

Google Scholar 
24.Habicht KS, Salling L, Thamdrup B, Canfield DE. Effect of low sulfate concentrations on lactate oxidation and isotope fractionation during sulfate reduction by Archaeoglobus fulgidus strain Z. Appl Environ Microbiol. 2005;71:3770–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
25.Davidson MM, Bisher ME, Pratt LM, Fong J, Southam G, Pfiffner SM, et al. Sulfur isotope enrichment during maintenance metabolism in the thermophilic sulfate-reducing bacterium Desulfotomaculum putei. Appl Environ Microbiol. 2009;75:5621–30.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
26.Brysch K, Schneider C, Fuchs G, Widdel F. Lithoautotrophic growth of sulfate-reducing bacteria, and description of Desulfobacterium autotrophicum gen. nov., sp. nov. Arch Microbiol. 1987;148:264–74.CAS 
Article 

Google Scholar 
27.Strittmatter AW, Liesegang H, Rabus R, Decker I, Amann J, Andres S, et al. Genome sequence of Desulfobacterium autotrophicum HRM2, a marine sulfate reducer oxidizing organic carbon completely to carbon dioxide. Environ Microbiol. 2009;11:1038–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
28.Dörries M, Wöhlbrand L, Rabus R. Differential proteomic analysis of the metabolic network of the marine sulfate-reducer Desulfobacterium autotrophicum HRM2. Proteomics. 2016;16:2878–93.PubMed 
Article 
CAS 

Google Scholar 
29.Petro C, Zäncker B, Starnawski P, Jochum LM, Ferdelman TG, Jørgensen BB, et al. Marine deep biosphere microbial communities assemble in near-surface sediments in Aarhus Bay. Front Microbiol. 2019;10:758.PubMed 
PubMed Central 
Article 

Google Scholar 
30.Jochum LM, Chen X, Lever MA, Loy A, Jørgensen BB, Schramm A, et al. Depth distribution and assembly of sulfate-reducing microbial communities in marine sediments of Aarhus Bay. Appl Environ Microbiol. 2017;83:e01547–17.PubMed 
PubMed Central 
Article 

Google Scholar 
31.Leloup J, Loy A, Knab NJ, Borowski C, Wagner M, Jørgensen BB. Diversity and abundance of sulfate-reducing microorganisms in the sulfate and methane zones of a marine sediment, Black Sea. Environ Microbiol. 2007;9:131–42.CAS 
PubMed 
Article 

Google Scholar 
32.Tarpgaard IH, Jørgensen BB, Kjeldsen KU, Røy H. The marine sulfate reducer Desulfobacterium autotrophicum HRM2 can switch between low and high apparent half-saturation constants for dissimilatory sulfate reduction. FEMS Microbiol Ecol. 2017;93:fix012.Article 
CAS 

Google Scholar 
33.Marietou A, Røy H, Jørgensen BB, Kjeldsen KU. Sulfate transporters in dissimilatory sulfate reducing microorganisms: a comparative genomics analysis. Front Microbiol. 2018;9:309.PubMed 
PubMed Central 
Article 

Google Scholar 
34.Tarpgaard IH, Røy H, Jørgensen BB. Concurrent low-and high-affinity sulfate reduction kinetics in marine sediment. Geochim Cosmochim Acta. 2011;75:2997–3010.CAS 
Article 

Google Scholar 
35.Volpi M, Lomstein BA, Sichert A, Røy H, Jørgensen BB, Kjeldsen KU. Identity, abundance, and reactivation kinetics of thermophilic fermentative endospores in cold marine sediment and seawater. Front Microbiol. 2017;8:131.PubMed 
PubMed Central 
Article 

Google Scholar 
36.Glombitza C, Pedersen J, Røy H, Jørgensen BB. Direct analysis of volatile fatty acids in marine sediment porewater by two-dimensional ion chromatography-mass spectrometry. Limnol Oceanogr Methods. 2014;12:455–68.CAS 
Article 

Google Scholar 
37.Glombitza C, Jaussi M, Røy H, Seidenkrantz MS, Lomstein BA, Jørgensen BB. Formate, acetate, and propionate as substrates for sulfate reduction in sub-arctic sediments of Southwest Greenland. Front Microbiol. 2015;6:846.PubMed 
PubMed Central 
Article 

Google Scholar 
38.Reese BK, Finneran DW, Mills HJ, Zhu MX, Morse JW. Examination and refinement of the determination of aqueous hydrogen sulfide by the methylene blue method. Aquat Geochem. 2011;17:567.CAS 
Article 

Google Scholar 
39.Beulig F, Røy H, McGlynn SE, Jørgensen BB. Cryptic CH 4 cycling in the sulfate-methane transition of marine sediments apparently mediated by ANME-1 archaea. ISME J. 2019;13:250–62.CAS 
PubMed 
Article 

Google Scholar 
40.Thorup C, Schramm A, Findlay AJ, Finster KW, Schreiber L. Disguised as a sulfate reducer: growth of the deltaproteobacterium Desulfurivibrio alkaliphilus by sulfide oxidation with nitrate. MBio 2017;8:e00671–17.PubMed 
PubMed Central 
Article 

Google Scholar 
41.Markowitz VM, Chen IM, Palaniappan K, Chu K, Szeto E, Grechkin Y, et al. IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Res. 2012;40:D115–22.CAS 
PubMed 
Article 

Google Scholar 
42.Rabus R, Venceslau SS, Wöhlbrand L, Voordouw G, Wall JD, Pereira IAC. Chapter two—a post-genomic view of the ecophysiology, catabolism and biotechnological relevance of sulphate-reducing prokaryotes. Adv Micro Physiol. 2015;66:55–321.CAS 
Article 

Google Scholar 
43.Finke N, Vandieken V, Jørgensen BB. Acetate, lactate, propionate, and isobutyrate as electron donors for iron and sulfate reduction in Arctic marine sediments, Svalbard. FEMS Microbiol Ecol. 2007;59:10–22.CAS 
PubMed 
Article 

Google Scholar 
44.Sonne-Hansen J, Westermann P, Ahring BK. Kinetics of sulfate and hydrogen uptake by the thermophilic sulfate-reducing bacteria Thermodesulfobacterium sp. strain JSP and Thermodesulfovibrio sp. strain R1Ha3. Appl Environ Microbiol. 1999;65:1304–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
45.Keller KL, Wall JD. Genetics and molecular biology of the electron flow for sulfate respiration in Desulfovibrio. Front Microbiol. 2011;2:135.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Molenaar D, Van Berlo R, De Ridder D, Teusink B. Shifts in growth strategies reflect tradeoffs in cellular economics. Mol Syst Biol. 2009;5:323.PubMed 
PubMed Central 
Article 

Google Scholar 
47.Vemuri GN, Altman E, Sangurdekar DP, Khodursky AB, Eiteman MA. Overflow metabolism in Escherichia coli during steady-state growth: transcriptional regulation and effect of the redox ratio. Appl Environ Microbiol. 2006;72:3653–61.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.Meyer B, Kuehl JV, Price MN, Ray J, Deutschbauer AM, Arkin AP, et al. The energy-conserving electron transfer system used by Desulfovibrio alaskensis strain G 20 during pyruvate fermentation involves reduction of endogenously formed fumarate and cytoplasmic and membrane-bound complexes, Hdr-Flox and Rnf. Environ Microbiol. 2014;16:3463–86.CAS 
PubMed 
Article 

Google Scholar 
49.Noguera DR, Brusseau GA, Rittmann BE, Stahl DA. A unified model describing the role of hydrogen in the growth of Desulfovibrio vulgaris under different environmental conditions. Biotechn Bioengin. 1998;59:732–46.CAS 
Article 

Google Scholar 
50.Odom JM, Peck HD Jr. Hydrogen cycling as a general mechanism for energy coupling in the sulfate-reducing bacteria, Desulfovibrio sp. FEMS Microbiol Lett. 1981;12:47–50.CAS 
Article 

Google Scholar 
51.Lupton FS, Conrad R, Zeikus JG. Physiological function of hydrogen metabolism during growth of sulfidogenic bacteria on organic substrates. J Bacteriol. 1984;159:843–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Jin Q, Bethke CM. Cellular energy conservation and the rate of microbial sulfate reduction. Geology. 2009;37:1027–30.CAS 
Article 

Google Scholar 
53.Hoskisson PA, Hobbs G. Continuous culture-making a comeback? Microbiology. 2005;151:3153–9.CAS 
PubMed 
Article 

Google Scholar 
54.Overbeek R, Fonstein M, D’Souza M, Pusch GD, Maltsev N. The use of gene clusters to infer functional coupling. Proc Natl Acad Sci. 1999;96:2896–901.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
55.Hocking WP, Stokke R, Roalkvam I, Steen IH. Identification of key components in the energy metabolism of the hyperthermophilic sulfate-reducing archaeon Archaeoglobus fulgidus by transcriptome analyses. Front Microbiol. 2014;5:95.PubMed 
PubMed Central 
Article 

Google Scholar 
56.Pereira IA, Ramos AR, Grein F, Marques MC, Da Silva SM, Venceslau SS. A comparative genomic analysis of energy metabolism in sulfate reducing bacteria and archaea. Front Microbiol. 2011;2:69.CAS 
PubMed 
PubMed Central 

Google Scholar 
57.Noji H, Yoshida M. The rotary machine in the cell, ATP synthase. J Biol Chem. 2001;276:1665–8.CAS 
PubMed 
Article 

Google Scholar 
58.Plugge CM, Scholten JC, Culley DE, Nie L, Brockman FJ, Zhang W. Global transcriptomics analysis of the Desulfovibrio vulgaris change from syntrophic growth with Methanosarcina barkeri to sulfidogenic metabolism. Microbiol. 2010;156:2746–56.CAS 
Article 

Google Scholar 
59.Phadtare S. Recent developments in bacterial cold-shock response. Curr Issues Mol Biol. 2004;6:125–36.CAS 
PubMed 

Google Scholar 
60.Rabus R, Brüchert V, Amann J, Könneke M. Physiological response to temperature changes of the marine, sulfate-reducing bacterium Desulfobacterium autotrophicum. FEMS Microbiol Ecol. 2002;42:409–17.CAS 
PubMed 
Article 

Google Scholar 
61.Barker HA. Amino acid degradation by anaerobic bacteria. Annu Rev Biochem. 1981;50:23–40.CAS 
PubMed 
Article 

Google Scholar 
62.Zinser ER, Kolter R. Mutations enhancing amino acid catabolism confer a growth advantage in stationary phase. J Bacteriol. 1999;181:5800–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
63.Wick LM, Quadroni M, Egli T. Short- and long-term changes in proteome composition and kinetic properties in a culture of Escherichia coli during transition from glucose-excess to glucose-limited growth conditions in continuous culture and vice versa. Environ Microbiol. 2001;3:588–99.CAS 
PubMed 
Article 

Google Scholar 
64.Vollmer AC, Bark SJ. Twenty-five years of investigating the universal stress protein: function, structure, and applications. In: Advances in applied microbiology. Academic Press; 2018. pp. 1–36.65.Clark ME, He Q, He Z, Huang KH, Alm EJ, Wan XF, et al. Temporal transcriptomic analysis as Desulfovibrio vulgaris Hildenborough transitions into stationary phase during electron donor depletion. Appl Environ Microbiol. 2006;72:5578–88.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
66.Schauder R, Preuß A, Jetten M, Fuchs G. Oxidative and reductive acetyl CoA/carbon monoxide dehydrogenase pathway in Desulfobacterium autotrophicum. Arch Microbiol. 1988;151:84–9.Article 

Google Scholar 
67.Kumari S, Beatty CM, Browning DF, Busby SJ, Simel EJ, Hovel-Miner G, et al. Regulation of acetyl coenzyme A synthetase in. Escherichia coli J Bacteriol. 2000;182:4173–9.CAS 
PubMed 

Google Scholar 
68.Wang Q, Ou MS, Kim Y, Ingram LO, Shanmugam KT. Metabolic flux control at the pyruvate node in an anaerobic Escherichia coli strain with an active pyruvate dehydrogenase. Appl Environ Microbiol. 2010;76:2107–14.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
69.Shimizu K, Matsuoka Y. Regulation of glycolytic flux and overflow metabolism depending on the source of energy generation for energy demand. Biotechnol Adv. 2019;37:284–305.CAS 
PubMed 
Article 

Google Scholar 
70.Verhagen MF, O’Rourke T, Adams MW. The hyperthermophilic bacterium, Thermotoga maritima, contains an unusually complex iron-hydrogenase: amino acid sequence analyses versus biochemical characterization. Biochim Biophys Acta. 1999;1412:212–29.CAS 
PubMed 
Article 

Google Scholar 
71.Rabus RA, Hansen TA, Widdel FR. Dissimilatory sulfate-and sulfur-reducing prokaryotes. Prokaryotes. 2006;2:659–768.Article 

Google Scholar 
72.Santos AA, Venceslau SS, Grein F, Leavitt WD, Dahl C, Johnston DT, et al. A protein trisulfide couples dissimilatory sulfate reduction to energy conservation. Science. 2015;350:1541–5.CAS 
PubMed 
Article 

Google Scholar 
73.Buckel W, Thauer RK. Flavin-based electron bifurcation, ferredoxin, flavodoxin, and anaerobic respiration with protons (Ech) or NAD+ (Rnf) as electron acceptors: a historical review. Front Microbiol. 2018;9:401.PubMed 
PubMed Central 
Article 

Google Scholar 
74.Venceslau SS, Stockdreher Y, Dahl C, Pereira IAC. The “bacterial heterodisulfide” DsrC is a key protein in dissimilatory sulfur metabolism. BBA Bioenerg. 2014;1837:1148–64.CAS 
Article 

Google Scholar 
75.Grein F, Ramos AR, Venceslau SS, Pereira IA. Unifying concepts in anaerobic respiration: insights from dissimilatory sulfur metabolism. BBA Bioenerg. 2013;1827:145–60.CAS 
Article 

Google Scholar 
76.Stahlmann J, Warthmann R, Cypionka H. Na+-dependent accumulation of sulfate and thiosulfate in marine sulfate-reducing bacteria. Arch Microbiol. 1991;155:554–8.CAS 
Article 

Google Scholar 
77.Wöhlbrand L, Ruppersberg H, Feenders C, Blasius B, Braun HP, Rabus R. Analysis of membrane-protein complexes of the marine sulfate reducer Desulfobacula toluolica Tol2 by 1D blue native-PAGE complexome profiling and 2D blue native-/SDS-PAGE. Proteomics. 2016;16:973–88.PubMed 
Article 
CAS 

Google Scholar 
78.Marietou A, Lund MB, Marshall IP, Schreiber L, Jørgensen BB. Complete genome sequence of Desulfobacter hydrogenophilus AcRS1. Mar Genom. 2020;50:100691.Article 

Google Scholar 
79.Zhang W, Culley DE, Wu G, Brockman FJ. Two-component signal transduction systems of Desulfovibrio vulgaris: structural and phylogenetic analysis and deduction of putative cognate pairs. J Mol Evol. 2006;62:473–87.CAS 
PubMed 
Article 

Google Scholar 
80.Rajeev L, Luning EG, Dehal PS, Price MN, Arkin AP, Mukhopadhyay A. Systematic mapping of two component response regulators to gene targets in a model sulfate reducing bacterium. Genome Biol. 2011;12:R99.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
81.Taher R, de Rosny E. A structure-function study of ZraP and ZraS provides new insights into the two-component system Zra. Biochim Biophys Acta. 2020;1865:129810.Article 
CAS 

Google Scholar 
82.Kraft B, Tegetmeyer HE, Sharma R, Klotz MG, Ferdelman TG, Hettich RL, et al. The environmental controls that govern the end product of bacterial nitrate respiration. Science. 2014;345:676–9.CAS 
PubMed 
Article 

Google Scholar 
83.Yoon S, Cruz-García C, Sanford R, Ritalahti KM, Löffler FE. Denitrification versus respiratory ammonification: environmental controls of two competing dissimilatory NO3−/NO2− reduction pathways in Shewanella loihica strain PV-4. ISME J. 2015;9:1093–104.CAS 
PubMed 
Article 

Google Scholar 
84.Greene EA, Hubert C, Nemati M, Jenneman GE, Voordouw G. Nitrite reductase activity of sulphate‐reducing bacteria prevents their inhibition by nitrate‐reducing, sulphide‐oxidizing bacteria. Environ Microbiol. 2003;5:607–17.CAS 
PubMed 
Article 

Google Scholar 
85.Dalsgaard T, Bak F. Nitrate reduction in a sulfate-reducing bacterium, Desulfovibrio desulfuricans, isolated from rice paddy soil: sulfide inhibition, kinetics, and regulation. Appl Environ Microbiol. 1994;60:291–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
86.Ingvorsen K, Jørgensen BB. Kinetics of sulfate uptake by freshwater and marine species of Desulfovibrio. Arch Microbiol. 1984;139:61–6.CAS 
Article 

Google Scholar  More