Philippa Kaur

Farmery, A. K., Hendrie, G. A., O’Kane, G., McManus, A. & Green, B. S. Sociodemographic variation in consumption patterns of sustainable and nutritious seafood in Australia. Front. Nutr. 5, 118. https://doi.org/10.3389/fnut.2018.00118 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Guillen, J. et al. Global seafood consumption footprint. Ambio 48, 111–122. https://doi.org/10.1007/s13280-018-1060-9 (2019).Article 
PubMed 

Google Scholar 
Norse, E. A. et al. Sustainability of deep-sea fisheries. Mar. Policy 36, 307–320. https://doi.org/10.1016/j.marpol.2011.06.008 (2012).Article 

Google Scholar 
Baco, A. R. et al. A synthesis of genetic connectivity in deep-sea fauna and implications for marine reserve design. Mol. Ecol. 25, 3276–3298. https://doi.org/10.1111/mec.13689 (2016).Article 
PubMed 

Google Scholar 
Victorero, L., Watling, L., Deng Palomares, M. L. & Nouvian, C. Out of sight, but within reach: A global history of bottom-trawled deep-sea fisheries from > 400 m depth. Front. Mar. Sci. 5, 98. https://doi.org/10.3389/fmars.2018.00098 (2018).Article 

Google Scholar 
Cowen, R. K. & Sponaugle, S. Larval dispersal and marine population connectivity. Ann. Rev. Mar. Sci. 1, 443–466. https://doi.org/10.1146/annurev.marine.010908.163757 (2009).Article 
PubMed 

Google Scholar 
Taylor, M. L. & Roterman, C. N. Invertebrate population genetics across Earth’s largest habitat: The deep-sea floor. Mol. Ecol. 26, 4872–4896. https://doi.org/10.1111/mec.14237 (2017).CAS 
Article 
PubMed 

Google Scholar 
Allendorf, F. W., England, P. R., Luikart, G., Ritchie, P. A. & Ryman, N. Genetic effects of harvest on wild animal populations. Trends Ecol. Evol. 23, 327–337. https://doi.org/10.1016/j.tree.2008.02.008 (2008).Article 
PubMed 

Google Scholar 
Carreras, C. et al. Population genomics of an endemic Mediterranean fish: Differentiation by fine scale dispersal and adaptation. Sci. Rep. 7, 43417. https://doi.org/10.1038/srep43417 (2017).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Coleman, F. C. & Williams, S. L. Overexploiting marine ecosystem engineers: Potential consequences for biodiversity. Trends Ecol. Evol. 17, 40–44. https://doi.org/10.1016/S0169-5347(01)02330-8 (2002).Article 

Google Scholar 
Neubauer, P., Jensen, O. P., Hutchings, J. A. & Baum, J. K. Resilience and recovery of overexploited marine populations. Science 340, 347–349. https://doi.org/10.1126/science.1230441 (2013).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Ovenden, J. R., Berry, O., Welch, D. J., Buckworth, R. C. & Dichmont, C. M. Ocean’s eleven: A critical evaluation of the role of population, evolutionary and molecular genetics in the management of wild fisheries. Fish Fish. 16, 125–159. https://doi.org/10.1111/faf.12052 (2015).Article 

Google Scholar 
Pinsky, M. L. & Palumbi, S. R. Meta-analysis reveals lower genetic diversity in overfished populations. Mol. Ecol. 23, 29–39. https://doi.org/10.1111/mec.12509 (2014).Article 
PubMed 

Google Scholar 
Sundqvist, L., Keenan, K., Zackrisson, M., Prodöhl, P. & Kleinhans, D. Directional genetic differentiation and relative migration. Ecol. Evol. 6, 3461–3475. https://doi.org/10.1002/ece3.2096 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Waples, R. S. et al. Guidelines for genetic data analysis. J. Cetac. Res. Manag. 18, 33–80 (2018).ADS 

Google Scholar 
Hauser, L., Adcock, G. J., Smith, P. J., Bernal Ramírez, J. H. & Carvalho, G. R. Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus). Proc. Natl. Acad. Sci. 99, 11742–11747. https://doi.org/10.1073/pnas.172242899 (2002).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Laikre, L., Palm, S. & Ryman, N. Genetic population structure of fishes: Implications for coastal zone management. AMBIO A J. Hum. Environ. 34, 111–119. https://doi.org/10.1579/0044-7447-34.2.111 (2005).Article 

Google Scholar 
Gaggiotti, O. E. Population genetic models of source–sink metapopulations. Theor. Popul. Biol. 50, 178–208. https://doi.org/10.1006/tpbi.1996.0028 (1996).CAS 
Article 
PubMed 
MATH 

Google Scholar 
Hughes, A. R., Inouye, B. D., Johnson, M. T. J., Underwood, N. & Vellend, M. Ecological consequences of genetic diversity. Ecol. Lett. 11, 609–623. https://doi.org/10.1111/j.1461-0248.2008.01179.x (2008).Article 
PubMed 

Google Scholar 
Bracco, A., Liu, G., Galaska, M. P., Quattrini, A. M. & Herrera, S. Integrating physical circulation models and genetic approaches to investigate population connectivity in deep-sea corals. J. Mar. Syst. 198, 103189. https://doi.org/10.1016/j.jmarsys.2019.103189 (2019).Article 

Google Scholar 
Liu, S.-Y.V., Hsin, Y.-C. & Cheng, Y.-R. Using particle tracking and genetic approaches to infer population connectivity in the deep-sea scleractinian coral Deltocyathus magnificus in the South China sea. Deep Sea Res. Part I 161, 103297. https://doi.org/10.1016/j.dsr.2020.103297 (2020).Article 

Google Scholar 
Dambach, J., Raupach, M. J., Leese, F., Schwarzer, J. & Engler, J. O. Ocean currents determine functional connectivity in an Antarctic deep-sea shrimp. Mar. Ecol. 37, 1336–1344. https://doi.org/10.1111/maec.12343 (2016).ADS 
CAS 
Article 

Google Scholar 
Selkoe, K. A., Henzler, C. M. & Gaines, S. D. Seascape genetics and the spatial ecology of marine populations. Fish Fish. 9, 363–377. https://doi.org/10.1111/j.1467-2979.2008.00300.x (2008).Article 

Google Scholar 
Yan, R.-J., Schnabel, K. E., Rowden, A. A., Guo, X.-Z. & Gardner, J. P. A. Population structure and genetic connectivity of squat lobsters (Munida Leach, 1820) associated with vulnerable marine ecosystems in the southwest Pacific Ocean. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00791 (2020).Article 

Google Scholar 
Breusing, C. et al. Biophysical and population genetic models predict the presence of “phantom” stepping stones connecting Mid-Atlantic Ridge vent ecosystems. Curr. Biol. 26, 2257–2267. https://doi.org/10.1016/j.cub.2016.06.062 (2016).CAS 
Article 
PubMed 

Google Scholar 
Fisheries New Zealand. Fisheries Assessment: Scampi (SCI). https://fs.fish.govt.nz/Page.aspx?pk=113&dk=24443 (2017).Botsford, L. W. et al. Connectivity, sustainability, and yield: Bridging the gap between conventional fisheries management and marine protected areas. Rev. Fish Biol. Fish. 19, 69–95. https://doi.org/10.1007/s11160-008-9092-z (2009).Article 

Google Scholar 
NIWA. Annual Distribution of Scampi. Ministry for Primary Industries, New Zealand. https://mpi.maps.arcgis.com/home/item.html?id=97da6c1a912b45a8855bf741211f5911 (2016).Heasman, K. G. & Jeffs, A. G. Fecundity and potential juvenile production for aquaculture of the New Zealand scampi, Metanephrops challengeri (Balss, 1914) (Decapoda: Nephropidae). Aquaculture 511, 634184. https://doi.org/10.1016/j.aquaculture.2019.05.069 (2019).Article 

Google Scholar 
Smith, P. J. Allozyme variation in scampi (Metanephrops challengeri) fisheries around New Zealand. NZ J. Mar. Freshw. Res. 33, 491–497. https://doi.org/10.1080/00288330.1999.9516894 (1999).Article 

Google Scholar 
Berry, P. The biology of Nephrops andamanicus Wood-Mason (Decapoda, Reptantia). Report No. 22, 1–55 (South African Association for Marine Biological Research, Oceanographic Research Institute, Durban, South Africa, 1969).Major, R. N. & Jeffs, A. G. Orientation and food search behaviour of a deep sea lobster in turbulent versus laminar odour plumes. Helgol. Mar. Res. 71, 9. https://doi.org/10.1186/s10152-017-0489-8 (2017).Article 

Google Scholar 
Tuck, I. D., Parsons, D. M., Hartill, B. W. & Chiswell, S. M. Scampi (Metanephrops challengeri) emergence patterns and catchability. ICES J. Mar. Sci. 72, i199–i210. https://doi.org/10.1093/icesjms/fsu244 (2015).Article 

Google Scholar 
Chiswell, S. M. & Booth, J. D. Sources and sinks of larval settlement in Jasus edwardsii around New Zealand: Where do larvae come from and where do they go?. Mar. Ecol. Prog. Ser. 354, 201–217. https://doi.org/10.3354/meps07217 (2008).ADS 
Article 

Google Scholar 
Silva, C. N. S., Macdonald, H. S., Hadfield, M. G., Cryer, M. & Gardner, J. P. A. Ocean currents predict fine-scale genetic structure and source-sink dynamics in a marine invertebrate coastal fishery. ICES J. Mar. Sci. 76, 1007–1018. https://doi.org/10.1093/icesjms/fsy201 (2019).Article 

Google Scholar 
Singh, S. P., Groeneveld, J. C., Hart-Davis, M. G., Backeberg, B. C. & Willows-Munro, S. Seascape genetics of the spiny lobster Panulirus homarus in the Western Indian Ocean: Understanding how oceanographic features shape the genetic structure of species with high larval dispersal potential. Ecol. Evol. 8, 12221–12237. https://doi.org/10.1002/ece3.4684 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Singh, S. P., Groeneveld, J. C. & Willows-Munro, S. Between the current and the coast: Genetic connectivity in the spiny lobster Panulirus homarus rubellus, despite potential barriers to gene flow. Mar. Biol. 166, 36. https://doi.org/10.1007/s00227-019-3486-4 (2019).Article 

Google Scholar 
Thomas, L. & Bell, J. J. Testing the consistency of connectivity patterns for a widely dispersing marine species. Heredity 111, 345–354. https://doi.org/10.1038/hdy.2013.58 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Baeza, J. A., Holstein, D., Umaña-Castro, R. & Mejía-Ortíz, L. M. Population genetics and biophysical modeling inform metapopulation connectivity of the Caribbean king crab Maguimithrax spinosissimus. Mar. Ecol. Prog. Ser. 610, 83–97 (2019).ADS 
CAS 
Article 

Google Scholar 
Hedgecock, D., Barber, P. H. & Edmands, S. Genetic approaches to measuring connectivity. Oceanography 20, 70–79 (2007).Article 

Google Scholar 
Jahnke, M. & Jonsson, P. R. Biophysical models of dispersal contribute to seascape genetic analyses. Philos. Trans. R. Soc. B Biol. Sci. 377, 20210024. https://doi.org/10.1098/rstb.2021.0024 (2022).Article 

Google Scholar 
Sebastian, W. et al. Genomic investigations provide insights into the mechanisms of resilience to heterogeneous habitats of the Indian Ocean in a pelagic fish. Sci. Rep. 11, 20690. https://doi.org/10.1038/s41598-021-00129-5 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Lal, M. M., Southgate, P. C., Jerry, D. R., Bosserelle, C. & Zenger, K. R. A parallel population genomic and hydrodynamic approach to fishery management of highly-dispersive marine invertebrates: The case of the Fijian black-lip pearl oyster Pinctada margaritifera. PLoS ONE 11, e0161390. https://doi.org/10.1371/journal.pone.0161390 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Xu, T. et al. Hidden historical habitat-linked population divergence and contemporary gene flow of a deep-sea patellogastropod limpet. Mol. Biol. Evol. 38, 5640–5654. https://doi.org/10.1093/molbev/msab278 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
de Souza, J. M. A. C. et al. Moana Ocean Hindcast—A 25+ years simulation for New Zealand Waters using the ROMS v3.9 model. EGUsphere https://doi.org/10.5194/egusphere-2022-41 (2022).Norrie, C., Dunphy, B., Roughan, M., Weppe, S. & Lundquist, C. Spill-over from aquaculture may provide a larval subsidy for the restoration of mussel reefs. Aquac. Environ. Interact. 12, 231–249 (2020).Article 

Google Scholar 
Larsson, J. et al. Regional genetic differentiation in the blue mussel from the Baltic Sea area. Estuar. Coast. Shelf Sci. 195, 98–109. https://doi.org/10.1016/j.ecss.2016.06.016 (2017).ADS 
Article 

Google Scholar 
Nicolle, A. et al. Modelling larval dispersal of Pecten maximus in the English Channel: A tool for the spatial management of the stocks. ICES J. Mar. Sci. 74, 1812–1825. https://doi.org/10.1093/icesjms/fsw207 (2017).Article 

Google Scholar 
Hold, N. et al. Using biophysical modelling and population genetics for conservation and management of an exploited species, Pecten maximus L. Fish. Oceanogr. 30, 740–756. https://doi.org/10.1111/fog.12556 (2021).Article 

Google Scholar 
Truelove, N. K. et al. Biophysical connectivity explains population genetic structure in a highly dispersive marine species. Coral Reefs 36, 233–244. https://doi.org/10.1007/s00338-016-1516-y (2017).ADS 
Article 

Google Scholar 
Busch, K. et al. Population connectivity of fan-shaped sponge holobionts in the deep Cantabrian Sea. Deep Sea Res. Part I 167, 103427. https://doi.org/10.1016/j.dsr.2020.103427 (2021).Article 

Google Scholar 
Ross, P. M., Hogg, I. D., Pilditch, C. A. & Lundquist, C. J. Phylogeography of New Zealand’s coastal benthos. NZ J. Mar. Freshw. Res. 43, 1009–1027. https://doi.org/10.1080/00288330.2009.9626525 (2009).Article 

Google Scholar 
Tuck, I. D. Characterisation and a length-based assessment model for scampi (Metanephrops challengeri) at the Auckland Islands (SCI 6A). Report No. 2015/21, 160 (Ministry for Primary Industries, Wellington, 2015).Verry, A. J. F., Walton, K., Tuck, I. D. & Ritchie, P. A. Genetic structure and recent population expansion in the commercially harvested deepsea decapod, Metanephrops challengeri (Crustacea: Decapoda). NZ J. Mar. Freshw. Res. 54, 251–270. https://doi.org/10.1080/00288330.2019.1707696 (2020).CAS 
Article 

Google Scholar 
Selkoe, K. A. et al. A decade of seascape genetics: Contributions to basic and applied marine connectivity. Mar. Ecol. Prog. Ser. 554, 1–19. https://doi.org/10.3354/meps11792 (2016).ADS 
Article 

Google Scholar 
Hare, M. P. et al. Understanding and estimating effective population size for practical application in marine species management. Conserv. Biol. 25, 438–449. https://doi.org/10.1111/j.1523-1739.2010.01637.x (2011).Article 
PubMed 

Google Scholar 
Ashry, N. A. Plant biodiversity and biotechnology. In From Plant Genomics to Plant Biotechnology (eds Poltronieri, P. et al.) 205–222 (Woodhead Publishing, 2013).Chapter 

Google Scholar 
Sgrò, C. M., Lowe, A. J. & Hoffmann, A. A. Building evolutionary resilience for conserving biodiversity under climate change. Evol. Appl. 4, 326–337. https://doi.org/10.1111/j.1752-4571.2010.00157.x (2011).Article 
PubMed 

Google Scholar 
Kerr, L. A., Cadrin, S. X. & Secor, D. H. Simulation modelling as a tool for examining the consequences of spatial structure and connectivity on local and regional population dynamics. ICES J. Mar. Sci. 67, 1631–1639. https://doi.org/10.1093/icesjms/fsq053 (2010).Article 

Google Scholar 
Carroll, E. L. et al. Perturbation drives changing metapopulation dynamics in a top marine predator. Proc. R. Soc. B Biol. Sci. 287, 20200318. https://doi.org/10.1098/rspb.2020.0318 (2020).Article 

Google Scholar 
Chiswell, S. M., Bostock, H. C., Sutton, P. J. H. & Williams, M. J. M. Physical oceanography of the deep seas around New Zealand: A review. NZ J. Mar. Freshw. Res. 49, 286–317. https://doi.org/10.1080/00288330.2014.992918 (2015).Article 

Google Scholar 
Chiswell, S. M. & Roemmich, D. The East Cape Current and two eddies: A mechanism for larval retention?. NZ J. Mar. Freshw. Res. 32, 385–397. https://doi.org/10.1080/00288330.1998.9516833 (1998).Article 

Google Scholar 
Condie, S. & Condie, R. Retention of plankton within ocean eddies. Glob. Ecol. Biogeogr. 25, 1264–1277. https://doi.org/10.1111/geb.12485 (2016).Article 

Google Scholar 
Lesser, J. H. R. Phyllosoma larvae of Jasus edwardsii (Hutton) (Crustacea: Decapoda: Palinuridae) and their distribution off the east coast of the North Island, New Zealand. NZ J. Mar. Freshw. Res. 12, 357–370. https://doi.org/10.1080/00288330.1978.9515763 (1978).Article 

Google Scholar 
Kawecki, T. J. Ecological and evolutionary consequences of source-sink population dynamics. In Ecology, Genetics and Evolution of Metapopulations (eds Hanski, I. & Gaggiotti, O. E.) 387–414 (Academic Press, 2004).Chapter 

Google Scholar 
Figueira, W. F. & Crowder, L. B. Defining patch contribution in source-sink metapopulations: the importance of including dispersal and its relevance to marine systems. Popul. Ecol. 48, 215–224. https://doi.org/10.1007/s10144-006-0265-0 (2006).Article 

Google Scholar 
Heinrichs, J. A. et al. Recent advances and current challenges in applying source-sink theory to species conservation. Curr. Landsc. Ecol. Rep. 4, 51–60. https://doi.org/10.1007/s40823-019-00039-3 (2019).Article 

Google Scholar 
Hastings, A. & Botsford, L. W. Persistence of spatial populations depends on returning home. Proc. Natl. Acad. Sci. 103, 6067–6072. https://doi.org/10.1073/pnas.0506651103 (2006).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Heinrichs, J. A., Lawler, J. J. & Schumaker, N. H. Intrinsic and extrinsic drivers of source-sink dynamics. Ecol. Evol. 6, 892–904. https://doi.org/10.1002/ece3.2029 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Gilroy, J. J. & Edwards, D. P. Source-sink dynamics: A neglected problem for landscape-scale biodiversity conservation in the Tropics. Curr. Landsc. Ecol. Rep. 2, 51–60. https://doi.org/10.1007/s40823-017-0023-3 (2017).Article 

Google Scholar 
Lal, M. M., Bosserelle, C., Kishore, P. & Southgate, P. C. Understanding marine larval dispersal in a broadcast-spawning invertebrate: A dispersal modelling approach for optimising spat collection of the Fijian black-lip pearl oyster Pinctada margaritifera. PLoS ONE 15, e0234605. https://doi.org/10.1371/journal.pone.0234605 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Chassé, J. & Miller, R. J. Lobster larval transport in the southern Gulf of St. Lawrence. Fish. Oceanogr. 19, 319–338. https://doi.org/10.1111/j.1365-2419.2010.00548.x (2010).Article 

Google Scholar 
Lindegren, M., Andersen, K. H., Casini, M. & Neuenfeldt, S. A metacommunity perspective on source–sink dynamics and management: the Baltic Sea as a case study. Ecol. Appl. 24, 1820–1832. https://doi.org/10.1890/13-0566.1 (2014).Article 
PubMed 

Google Scholar 
Tuck, I. D. et al. Estimating the abundance of scampi in SCI 6A (Auckland Islands) in 2013. Report No. 2015/10, 48 (Ministry for Primary Industries, 2015).Brierley, A. S. & Kingsford, M. J. Impacts of climate change on marine organisms and ecosystems. Curr. Biol. 19, R602–R614. https://doi.org/10.1016/j.cub.2009.05.046 (2009).CAS 
Article 
PubMed 

Google Scholar 
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G. & Saba, V. Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature 556, 191–196. https://doi.org/10.1038/s41586-018-0006-5 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Thornalley, D. J. R. et al. Anomalously weak Labrador Sea convection and Atlantic overturning during the past 150 years. Nature 556, 227–230. https://doi.org/10.1038/s41586-018-0007-4 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
van Gennip, S. J. et al. Going with the flow: The role of ocean circulation in global marine ecosystems under a changing climate. Glob. Change Biol. 23, 2602–2617. https://doi.org/10.1111/gcb.13586 (2017).ADS 
Article 

Google Scholar 
Bashevkin, S. M. et al. Larval dispersal in a changing ocean with an emphasis on upwelling regions. Ecosphere 11, e03015. https://doi.org/10.1002/ecs2.3015 (2020).Article 

Google Scholar 
Gerber, L. R., Mancha-Cisneros, M. D. M., O’Connor, M. I. & Selig, E. R. Climate change impacts on connectivity in the ocean: Implications for conservation. Ecosphere 5, 1–18. https://doi.org/10.1890/es13-00336.1 (2014).Article 

Google Scholar 
Hoegh-Gulderg, O. & Pearse, J. Temperature, food availability, and the development of marine invertebrate larvae. Am. Zool. 35, 415–425. https://doi.org/10.1093/icb/35.4.415 (1995).Article 

Google Scholar 
O’Connor, M. I. et al. Temperature control of larval dispersal and the implications for marine ecology, evolution, and conservation. Proc. Natl. Acad. Sci. USA 104, 1266–1271. https://doi.org/10.1073/pnas.0603422104 (2007).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Cetina-Heredia, P., Roughan, M., van Sebille, E., Feng, M. & Coleman, M. A. Strengthened currents override the effect of warming on lobster larval dispersal and survival. Glob. Change Biol. 21, 4377–4386. https://doi.org/10.1111/gcb.13063 (2015).ADS 
Article 

Google Scholar 
Borja, A. et al. Past and future grand challenges in marine ecosystem ecology. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00362 (2020).Article 

Google Scholar 
Ogilvie, S. et al. Mātauranga Māori driving innovation in the New Zealand scampi fishery. NZ J. Mar. Freshw. Res. 52, 590–602. https://doi.org/10.1080/00288330.2018.1532441 (2018).Article 

Google Scholar 
Andrews, S. FastQC: A quality control tool for high throughput sequence data v. 0.11.7 (Babraham Bioinformatics, 2010). http://www.bioinformatics.babraham.ac.uk/projects/fastqc.Rochette, N. C., Rivera-Colón, A. G. & Catchen, J. M. Stacks 2: Analytical methods for paired-end sequencing improve RADseq-based population genomics. Mol. Ecol. 28, 4737–4754. https://doi.org/10.1111/mec.15253 (2019).CAS 
Article 
PubMed 

Google Scholar 
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158. https://doi.org/10.1093/bioinformatics/btr330 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing v. 4.1.0 (R Studio v1.4.1106) (R Foundation for Statistical Computing, Vienna, Austria, 2021). https://www.R-project.org/.Díaz-Arce, N. & Rodríguez-Ezpeleta, N. Selecting RAD-seq data analysis parameters for population genetics: The more the better?. Front. Genet. 10, 533. https://doi.org/10.3389/fgene.2019.00533 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Potapov, V. & Ong, J. L. Examining sources of error in PCR by single-molecule sequencing. PLoS ONE 12, e0169774. https://doi.org/10.1371/journal.pone.0169774 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Goudet, J. & Jombart, T. hierfstat: Estimation and Tests of Hierarchical F-Statistics v. 0.04-22 (Comprehensive R Archive Network (CRAN), 2015). https://CRAN.R-project.org/package=hierfstat.Nei, M. Molecular Evolutionary Genetics (Columbia University Press, 1987).Book 

Google Scholar 
Nei, M. & Chesser, R. K. Estimation of fixation indices and gene diversities. Ann. Hum. Genet. 47, 253–259. https://doi.org/10.1111/j.1469-1809.1983.tb00993.x (1983).CAS 
Article 
PubMed 
MATH 

Google Scholar 
Archer, F. I., Adams, P. E. & Schneiders, B. B. stratag: An R package for manipulating, summarizing and analysing population genetic data. Mol. Ecol. Resour. 17, 5–11. https://doi.org/10.1111/1755-0998.12559 (2017).CAS 
Article 
PubMed 

Google Scholar 
Kamvar, Z. N., Tabima, J. F. & Grünwald, N. J. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2, e281. https://doi.org/10.7717/peerj.281 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Kamvar, Z. N., Brooks, J. C. & Grünwald, N. J. Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front. Genet. 6, 208. https://doi.org/10.3389/fgene.2015.00208 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Jombart, T. adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405. https://doi.org/10.1093/bioinformatics/btn129 (2008).CAS 
Article 
PubMed 

Google Scholar 
Jombart, T. & Ahmed, I. adegenet 1.3–1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3071. https://doi.org/10.1093/bioinformatics/btr521 (2011).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Miller, J. M., Cullingham, C. I. & Peery, R. M. The influence of a priori grouping on inference of genetic clusters: Simulation study and literature review of the DAPC method. Heredity 125, 269–280. https://doi.org/10.1038/s41437-020-0348-2 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Keenan, K., McGinnity, P., Cross, T. F., Crozier, W. W. & Prodöhl, P. A. diveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol. Evol. 4, 782–788. https://doi.org/10.1111/2041-210x.12067 (2013).Article 

Google Scholar 
Nei, M. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. 70, 3321–3323. https://doi.org/10.1073/pnas.70.12.3321 (1973).ADS 
CAS 
Article 
PubMed 
PubMed Central 
MATH 

Google Scholar 
Dagestad, K. F., Röhrs, J., Breivik, Ø. & Ådlandsvik, B. OpenDrift v1.0: A generic framework for trajectory modelling. Geosci. Model Dev. 11, 1405–1420. https://doi.org/10.5194/gmd-11-1405-2018 (2018).ADS 
Article 

Google Scholar 
Jeffs, A., Daniels, C. & Heasman, K. In Fisheries and Aquaculture: Natural History of Crustacea, Vol. 9 (eds Lovrich, G. & Thiel, M.) 285–311 (Oxford University Press, 2020).Lundquist, C. J., Oldman, J. W. & Lewis, M. J. Predicting suitability of cockle Austrovenus stutchburyi restoration sites using hydrodynamic models of larval dispersal. NZ J. Mar. Freshw. Res. 43, 735–748. https://doi.org/10.1080/00288330909510038 (2009).Article 

Google Scholar 
Lundquist, C. J., Thrush, S. F., Oldman, J. W. & Senior, A. K. Limited transport and recolonization potential in shallow tidal estuaries. Limnol. Oceanogr. 49, 386–395. https://doi.org/10.4319/lo.2004.49.2.0386 (2004).ADS 
Article 

Google Scholar 
Okubo, A. & Ebbesmeyer, C. C. Determination of vorticity, divergence, and deformation rates from analysis of drogue observations. Deep-Sea Res. Oceanogr. Abstr. 23, 349–352. https://doi.org/10.1016/0011-7471(76)90875-5 (1976).ADS 
Article 

Google Scholar 
Pierce, D. ncdf4: Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files v. 1.17 (Comprehensive R Archive Network (CRAN), 2019). https://CRAN.R-project.org/package=ncdf4.Coelho, S. C. C., Gherardi, D. F. M., Gouveia, M. B. & Kitahara, M. V. Western boundary currents drive sun-coral (Tubastraea spp.) coastal invasion from oil platforms. Sci. Rep. 12, 5286. https://doi.org/10.1038/s41598-022-09269-8 (2022).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Demmer, J. et al. The role of wind in controlling the connectivity of blue mussels (Mytilus edulis L.) populations. Mov. Ecol. 10, 3. https://doi.org/10.1186/s40462-022-00301-0 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Atalah, J., South, P. M., Briscoe, D. K. & Vennell, R. Inferring parental areas of juvenile mussels using hydrodynamic modelling. Aquaculture 555, 738227. https://doi.org/10.1016/j.aquaculture.2022.738227 (2022).Article 

Google Scholar 
McGeady, R., Lordan, C. & Power, A. M. Long-term interannual variability in larval dispersal and connectivity of the Norway lobster (Nephrops norvegicus) around Ireland: When supply-side matters. Fish. Oceanogr. 31, 255–270. https://doi.org/10.1111/fog.12576 (2022).Article 

Google Scholar 
Pante, E. & Simon-Bouhet, B. marmap: A package for importing, plotting and analyzing bathymetric and topographic data in R. PLoS ONE 8, e73051. https://doi.org/10.1371/journal.pone.0073051 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 

Google Scholar 
Becker, R. A., Wilks, A. R. & Brownrigg, R. mapdata: Extra Map Databases v. 2.3.0 (Comprehensive R Archive Network (CRAN), 2018). https://CRAN.R-project.org/package=mapdata.McIlroy, D., Brownrigg, R., Minka, T. P. & Bivan, R. mapproj: Map Projections v. 1.2.7 (Comprehensive R Archive Network (CRAN), 2020). https://CRAN.R-project.org/package=mapproj.South, A. rnaturalearth: World Map Data from Natural Earth v. 0.1.0 (Comprehensive R Archive Network (CRAN), 2017). https://CRAN.R-project.org/package=rnaturalearth. More

Bolger, D. T., Newmark, W. D., Morrison, T. A. & Doak, D. F. The need for integrative approaches to understand and conserve migratory ungulates. Ecol. Lett. 11, 63–77 (2008).PubMed 

Google Scholar 
Fryxell, J. M., Greever, J. & Sinclair, A. R. E. Why are migratory ungulates so abundant. Am. Nat. 131, 781–798 (1988).Article 

Google Scholar 
Holdo, R. M., Holt, R. D., Sinclair, A. R., Godley, B. J. & Thirgood, S. in Animal Migration: A Synthesis (eds Milner-Gulland, E. J. et al.) 131–143 (Oxford Univ. Press, 2011).Bauer, S. & Hoye, B. J. Migratory animals couple biodiversity and ecosystem functioning worldwide. Science 344, 1242552 (2014).CAS 
PubMed 
Article 

Google Scholar 
Middleton, A. D. et al. Conserving transboundary wildlife migrations: recent insights from the Greater Yellowstone Ecosystem. Front. Ecol. Environ. 18, 83–91 (2020).Article 

Google Scholar 
Aikens, E. O. et al. Wave-like patterns of plant phenology determine ungulate movement tactics. Curr. Biol. 30, 3444–3449 (2020).CAS 
PubMed 
Article 

Google Scholar 
Mueller, T. & Fagan, W. F. Search and navigation in dynamic environments—from individual behaviors to population distributions. Oikos 117, 654–664 (2008).Article 

Google Scholar 
Fryxell, J. M. Forage quality and aggregation by large herbivores. Am. Nat. 138, 478–498 (1991).Article 

Google Scholar 
Drent, R., Ebbinge, B. & Weijand, B. Balancing the energy budgets of arctic-breeding geese throughout the annual cycle: a progress report. Verh. Ornithol. Ges. Bayern 23, 239–264 (1978).
Google Scholar 
van der Graaf, S. A. J., Stahl, J., Klimkowska, A., Bakker, J. P. & Drent, R. H. Surfing on a green wave—how plant growth drives spring migration in the Barnacle Goose Branta leucopsis. Ardea 94, 567–577 (2006).
Google Scholar 
Merkle, J. A. et al. Large herbivores surf waves of green-up during spring. Proc. R. Soc. B. 283, 20160456 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Aikens, E. O. et al. The greenscape shapes surfing of resource waves in a large migratory herbivore. Ecol. Lett. 20, 741–750 (2017).PubMed 
Article 

Google Scholar 
Middleton, A. D. et al. Green-wave surfing increases fat gain in a migratory ungulate. Oikos https://doi.org/10.1111/oik.05227 (2018).Jesmer, B. R. et al. Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals. Science 361, 1023–1025 (2018).CAS 
PubMed 
Article 

Google Scholar 
Sawyer, H. et al. A framework for understanding semi‐permeable barrier effects on migratory ungulates. J. Appl. Ecol. 50, 68–78 (2013).Article 

Google Scholar 
Kauffman, M. J. et al. Mapping out a future for ungulate migrations. Science 372, 566–569 (2021).CAS 
PubMed 
Article 

Google Scholar 
Doherty, T. S., Hays, G. C. & Driscoll, D. A. Human disturbance causes widespread disruption of animal movement. Nat. Ecol. Evol. 5, 513–519 (2021).PubMed 
Article 

Google Scholar 
Berry, J. Aspects of wildebeest Connochaetes taurinus ecology in the Etosha National Park—a synthesis for future management. Madoqua 1997, 137–148 (1997).
Google Scholar 
Williamson, D. & Williamson, J. Botswana’s fences and the depletion of Kalahari wildlife. Oryx 18, 218–222 (1984).Article 

Google Scholar 
Northrup, J. M. & Wittemyer, G. Characterising the impacts of emerging energy development on wildlife, with an eye towards mitigation. Ecol. Lett. 16, 112–125 (2013).PubMed 
Article 

Google Scholar 
Kauffman, M. J., Meacham, J. E., Sawyer, H., Rudd, W. & Ostlind, E. Wild Migrations: Atlas of Wyoming’s Ungulates (Oregon State Univ. Press, 2018).Wyckoff, T. B., Sawyer, H., Albeke, S. E., Garman, S. L. & Kauffman, M. J. Evaluating the influence of energy and residential development on the migratory behavior of mule deer. Ecosphere 9, e02113 (2018).Article 

Google Scholar 
Lendrum, P. E., Anderson, C. R. Jr., Monteith, K. L., Jenks, J. A. & Bowyer, R. T. Migrating mule deer: effects of anthropogenically altered landscapes. PLoS ONE 8, e64548 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lendrum, P. E., Anderson, C. R. Jr, Long, R. A., Kie, J. G. & Bowyer, R. T. Habitat selection by mule deer during migration: effects of landscape structure and natural‐gas development. Ecosphere 3, 82 (2012).Sawyer, H. & Kauffman, M. J. Stopover ecology of a migratory ungulate. J. Anim. Ecol. 80, 1078–1087 (2011).PubMed 
Article 

Google Scholar 
Sawyer, H., LeBeau, C. W., McDonald, T. L., Xu, W. & Middleton, A. D. All routes are not created equal: an ungulate’s choice of migration route can influence its survival. J. Appl. Ecol. 56, 1860–1869 (2019).
Google Scholar 
Bischof, R. et al. A migratory northern ungulate in the pursuit of spring: jumping or surfing the green wave? Am. Nat. 180, 407–424 (2012).PubMed 
Article 

Google Scholar 
Skarin, A., Nellemann, C., Rönnegård, L., Sandström, P. & Lundqvist, H. Wind farm construction impacts reindeer migration and movement corridors. Landsc. Ecol. 30, 1527–1540 (2015).Article 

Google Scholar 
Mysterud, A., Langvatn, R., Yoccoz, N. G. & Stenseth, N. C. Plant phenology, migration and geographical variation in body weight of a large herbivore: the effect of a variable topography. J. Anim. Ecol. 70, 915–923 (2001).Article 

Google Scholar 
Johnson, H. E. et al. Increases in residential and energy development are associated with reductions in recruitment for a large ungulate. Glob. Change Biol. 23, 578–591 (2017).Article 

Google Scholar 
Sawyer, H., Korfanta, N. M., Nielson, R. M., Monteith, K. L. & Strickland, D. Mule deer and energy development—long-term trends of habituation and abundance. Glob. Change Biol. 23, 4521–4529 (2017).Article 

Google Scholar 
Sawyer, H., Lambert, M. S. & Merkle, J. A. Migratory disturbance thresholds with mule deer and energy development. J. Wildl. Manag. 84, 930–937 (2020).Article 

Google Scholar 
Uezu, A., Metzger, J. P. & Vielliard, J. M. E. Effects of structural and functional connectivity and patch size on the abundance of seven Atlantic Forest bird species. Biol. Conserv. 123, 507–519 (2005).Article 

Google Scholar 
Keeley, A. T. H., Beier, P. & Jenness, J. S. Connectivity metrics for conservation planning and monitoring. Biol. Conserv. 255, 109008 (2021).Article 

Google Scholar 
Abrahms, B. et al. Emerging perspectives on resource tracking and animal movement ecology. Trends Ecol. Evol. 36, 308–320 (2021).PubMed 
Article 

Google Scholar 
Aikens, E. O. et al. Migration distance and maternal resource allocation determine timing of birth in a large herbivore. Ecology 102, e03334 (2021).PubMed 
Article 

Google Scholar 
Aikens, E. O. et al. Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate. Glob. Change Biol. 26, 4215–4225 (2020).Article 

Google Scholar 
Sawyer, H., Merkle, J. A., Middleton, A. D., Dwinnell, S. P. H. & Monteith, K. L. Migratory plasticity is not ubiquitous among large herbivores. J. Anim. Ecol. 88, 450–460 (2019).PubMed 

Google Scholar 
Schlaepfer, M. A., Runge, M. C. & Sherman, P. W. Ecological and evolutionary traps. Trends Ecol. Evol. 17, 474–480 (2002).Article 

Google Scholar 
Delibes, M., Gaona, P. & Ferreras, P. Effects of an attractive sink leading into maladaptive habitat selection. Am. Nat. 158, 277–285 (2001).CAS 
PubMed 
Article 

Google Scholar 
Sawyer, H., Kauffman, M. J., Nielson, R. M. & Horne, J. S. Identifying and prioritizing ungulate migration routes for landscape-level conservation. Ecol. Appl. 19, 2016–2025 (2009).PubMed 
Article 

Google Scholar 
Sawyer, H., Hayes, M., Rudd, B. & Kauffman, M. J. The Red Desert to Hoback Mule Deer Migration Assessment (Univ. Wyoming, 2014).Berger, J., Young, J. K. & Berger, K. M. Protecting migration corridors: challenges and optimism for Mongolian saiga. PLoS Biol. 6, e165 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
Sikes, R. S. & Gannon, W. L. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. J. Mammal. 92, 235–253 (2011).Article 

Google Scholar 
Vermote, E. MOD09A1 Surface Reflectance 8-day L3 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015).Pettorelli, N., Mysterud, A., Yoccoz, N. G., Langvatn, R. & Stenseth, N. C. Importance of climatological downscaling and plant phenology for red deer in heterogeneous landscapes. Proc. R. Soc. B. 272, 2357–2364 (2005).PubMed 
PubMed Central 
Article 

Google Scholar 
Pettorelli, N. et al. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol. Evol. 20, 503–510 (2005).PubMed 
Article 

Google Scholar 
Hamel, S., Garel, M., Festa-Bianchet, M., Gaillard, J. M. & Cote, S. D. Spring normalized difference vegetation index (NDVI) predicts annual variation in timing of peak faecal crude protein in mountain ungulates. J. Appl. Ecol. 46, 582–589 (2009).Article 

Google Scholar 
Geremia, C. et al. Migrating bison engineer the green wave. Proc. Natl Acad. Sci. USA 116, 25707–25713 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Thompson, R. L. et al. Acceleration of global N2O emissions seen from two decades of atmospheric inversion. Nat. Clim. Change 9, 993–998 (2019).CAS 
Article 

Google Scholar 
Tian, H. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).CAS 
PubMed 
Article 

Google Scholar 
Zhuang, Q., Lu, Y. & Chen, M. An inventory of global N2O emissions from the soils of natural terrestrial ecosystems. Atm. Environ. 47, 66–75 (2012).CAS 
Article 

Google Scholar 
Huang, J. et al. Estimation of regional emissions of nitrous oxide from 1997 to 2005 using multinetwork measurements, a chemical transport model, and an inverse method. J. Geophys. Res. 113, D17313 (2008).Article 

Google Scholar 
D’Amelio, M. T. S., Gatti, L. V., Miller, J. B. & Tans, P. Regional N2O fluxes in Amazonia derived from aircraft vertical profiles. Atmos. Chem. Phys. 9, 8785–8797 (2009).Article 

Google Scholar 
Teh, Y. A., Murphy, W. A., Berrio, J.-C., Boom, A. & Page, S. E. Seasonal variability in methane and nitrous oxide fluxes from tropical peatlands in the western Amazon basin. Biogeosciences 14, 3669–3683 (2017).CAS 
Article 

Google Scholar 
Finn, D. R. et al. Methanogens and methanotrophs show nutrient-dependent community assemblage patterns across tropical peatlands of the Pastaza-Marañón Basin, Peruvian Amazonia. Front. Microbiol. 11, 746 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Buessecker, S. et al. Effects of sterilization techniques on chemodenitrification and N2O production in tropical peat soil microcosms. Biogeosciences 16, 4601–4612 (2019).CAS 
Article 

Google Scholar 
Heil, J., Liu, S., Vereecken, H. & Brüggemann, N. Abiotic nitrous oxide production from hydroxylamine in soils and their dependence on soil properties. Soil Biol. Biochem. 84, 107–115 (2015).CAS 
Article 

Google Scholar 
Samarkin, V. A. et al. Abiotic nitrous oxide emission from the hypersaline Don Juan Pond in Antarctica. Nat. Geosci. 3, 341–344 (2010).CAS 
Article 

Google Scholar 
Otte, J. M. et al. N2O formation by nitrite-induced (chemo)denitrification in coastal marine sediment. Sci. Rep. 9, 10691 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Jones, L. C., Peters, B., Pacheco, J. S. L., Casciotti, K. L. & Fendorf, S. Stable isotopes and iron oxide mineral products as markers of chemodenitrification. Environ. Sci. Technol. 49, 3444–3452 (2015).CAS 
PubMed 
Article 

Google Scholar 
Tolman, W. B. Binding and activation of N2O at transition-metal centers: recent mechanistic insights. Angew. Chem. Int. Ed. 49, 1018–1024 (2010).CAS 
Article 

Google Scholar 
Holtan-Hartwig, L., Dörsch, P. & Bakken, L. R. Low temperature control of soil denitrifying communities: kinetics of N2O production and reduction. Soil Biol. Biochem. 34, 1797–1806 (2002).CAS 
Article 

Google Scholar 
Gorelsky, S. I., Ghosh, S. & Solomon, E. I. Mechanism of N2O reduction by the μ4-S tetranuclear CuZ cluster of nitrous oxide reductase. J. Am. Chem. Soc. https://doi.org/10.1021/ja055856o (2005).Tsai, M.-L. et al. [Cu2O]2+ active site formation in Cu–ZSM-5: geometric and electronic structure requirements for N2O activation. J. Am. Chem. Soc. https://doi.org/10.1021/ja4113808 (2014).Sanford, R. A. et al. Unexpected nondenitrifier nitrous oxide reductase gene diversity and abundance in soils. Proc. Natl Acad. Sci. USA 109, 19709–19714 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jones, C. M. et al. Recently identified microbial guild mediates soil N2O sink capacity. Nat. Clim. Change 4, 801–805 (2014).CAS 
Article 

Google Scholar 
Hallin, S., Philippot, L., Löffler, F. E., Sanford, R. A. & Jones, C. M. Genomics and ecology of novel N2O-reducing microorganisms. Trends Microbiol. 26, 43–55 (2018).CAS 
PubMed 
Article 

Google Scholar 
Lycus, P. et al. A bet-hedging strategy for denitrifying bacteria curtails their release of N2O. Proc. Natl Acad. Sci. USA 115, 11820–11825 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Burns, L. C., Stevens, R. J. & Laughlin, R. J. Determination of the simultaneous production and consumption of soil nitrite using 15N. Soil Biol. Biochem. 27, 839–844 (1995).CAS 
Article 

Google Scholar 
Burns, L. C., Stevens, R. J. & Laughlin, R. J. Production of nitrite in soil by simultaneous nitrification and denitrification. Soil Biol. Biochem. 28, 609–616 (1996).CAS 
Article 

Google Scholar 
Wullstein, L. H. & Gilmour, C. M. Non-enzymatic formation of nitrogen gas. Nature 210, 1150–1151 (1966).CAS 
Article 

Google Scholar 
Liu, S., Schloter, M., Hu, R., Vereecken, H. & Brüggemann, N. Hydroxylamine contributes more to abiotic N2O production in soils than nitrite. Front. Environ. Sci. https://doi.org/10.3389/fenvs.2019.00047 (2019).Thorn, K. A. & Mikita, M. A. Nitrite fixation by humic substances: nitrogen-15 nuclear magnetic resonance evidence for potential intermediates in chemodenitrification. Soil Sci. Soc. Am. J. 64, 568–582 (2000).CAS 
Article 

Google Scholar 
Thorn, K. A., Younger, S. J. & Cox, L. G. Order of functionality loss during photodegradation of aquatic humic substances. J. Environ. Qual. 39, 1416–1428 (2010).CAS 
PubMed 
Article 

Google Scholar 
Klüpfel, L., Piepenbrock, A., Kappler, A. & Sander, M. Humic substances as fully regenerable electron acceptors in recurrently anoxic environments. Nat. Geosci. 7, 195–200 (2014).Article 

Google Scholar 
Lovley, D. R. & Blunt-Harris, E. L. Role of humic-bound iron as an electron transfer agent in dissimilatory Fe(III) reduction. Appl. Environ. Microbiol. 65, 4252–4254 (1999).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kappler, A., Benz, M., Schink, B. & Brune, A. Electron shuttling via humic acids in microbial iron(III) reduction in a freshwater sediment. FEMS Microbiol. Ecol. 47, 85–92 (2004).CAS 
PubMed 
Article 

Google Scholar 
Van Cleemput, O., Patrick, W. H. & McIlhenny, R. C. Nitrite decomposition in flooded soil under different pH and redox potential conditions. Soil Sci. Soc. Am. J. 40, 55–60 (1976).Article 

Google Scholar 
Van Cleemput, O. & Baert, L. Nitrite: a key compound in N loss processes under acid conditions? Plant Soil 76, 233–241 (1984).Article 

Google Scholar 
Porter, L. K. Gaseous products produced by anaerobic reaction of sodium nitrite with oxime compounds and oximes synthesized from organic matter. Soil Sci. Soc. Am. J. 33, 696–702 (1969).CAS 
Article 

Google Scholar 
Liu, B., Mørkved, P. T., Frostegård, Å. & Bakken, L. R. Denitrification gene pools, transcription and kinetics of NO, N2O and N2 production as affected by soil pH. FEMS Microbiol. Ecol. 72, 407–417 (2010).CAS 
PubMed 
Article 

Google Scholar 
Palmer, K., Biasi, C. & Horn, M. A. Contrasting denitrifier communities relate to contrasting N2O emission patterns from acidic peat soils in arctic tundra. ISME J. 6, 1058–1077 (2012).CAS 
PubMed 
Article 

Google Scholar 
Domeignoz-Horta, L. et al. The diversity of the N2O reducers matters for the N2O:N2 denitrification end-product ratio across an annual and a perennial cropping system. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.00971 (2015).Domeignoz-Horta, L. A. et al. Peaks of in situ N2O emissions are influenced by N2O-producing and reducing microbial communities across arable soils. Glob. Change Biol. 24, 360–370 (2018).Article 

Google Scholar 
Onley, J. R., Ahsan, S., Sanford, R. A. & Löffler, F. E. Denitrification by Anaeromyxobacter dehalogenans, a common soil bacterium lacking the nitrite reductase genes nirS and nirK. Appl. Environ. Microbiol. 84, 4 (2018).Article 

Google Scholar 
Sanford, R. A., Cole, J. R. & Tiedje, J. M. Characterization and description of Anaeromyxobacter dehalogenans gen. nov., sp. nov., an aryl-halorespiring facultative anaerobic myxobacterium. Appl. Environ. Microbiol. 68, 893–900 (2002).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mohr, K. I., Zindler, T., Wink, J., Wilharm, E. & Stadler, M. Myxobacteria in high moor and fen: an astonishing diversity in a neglected extreme habitat. MicrobiologyOpen 6, e00464 (2017).PubMed Central 
Article 

Google Scholar 
Hori, T., Müller, A., Igarashi, Y., Conrad, R. & Friedrich, M. W. Identification of iron-reducing microorganisms in anoxic rice paddy soil by ¹³C-acetate probing. ISME J. 4, 267–278 (2010).CAS 
PubMed 
Article 

Google Scholar 
Kawaichi, S. et al. Ardenticatena maritima gen. nov., sp. nov., a ferric iron- and nitrate-reducing bacterium of the phylum ‘Chloroflexi’ isolated from an iron-rich coastal hydrothermal field, and description of Ardenticatenia classis nov. Int. J. Sys. Evol. Microbiol. 63, 2992–3002 (2013).CAS 
Article 

Google Scholar 
Podosokorskaya, O. A. et al. Characterization of Melioribacter roseus gen. nov., sp. nov., a novel facultatively anaerobic thermophilic cellulolytic bacterium from the class Ignavibacteria, and a proposal of a novel bacterial phylum Ignavibacteriae. Environ. Microbiol. 15, 1759–1771 (2013).CAS 
PubMed 
Article 

Google Scholar 
Yoon, S. et al. Nitrous oxide reduction kinetics distinguish bacteria harboring clade I nosz from those harboring clade II NosZ. Appl. Environ. Microbiol. 82, 3793–3800 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Maher, B. A. & Taylor, R. M. Formation of ultrafine-grained magnetite in soils. Nature 336, 368–370 (1988).CAS 
Article 

Google Scholar 
Sanchez, P. A. Properties and Management of Soils in the Tropics (Wiley, 1976).White, A. F. et al. Chemical weathering in a tropical watershed, Luquillo Mountains, Puerto Rico: I. Long-term versus short-term weathering fluxes. Geochim. Cosmochim. Acta 62, 209–226 (1998).CAS 
Article 

Google Scholar 
Hall, S. J., Liptzin, D., Buss, H. L., DeAngelis, K. & Silver, W. L. Drivers and patterns of iron redox cycling from surface to bedrock in a deep tropical forest soil: a new conceptual model. Biogeochemistry 130, 177–190 (2016).CAS 
Article 

Google Scholar 
Buchwald, C., Grabb, K., Hansel, C. M. & Wankel, S. D. Constraining the role of iron in environmental nitrogen transformations: dual stable isotope systematics of abiotic NO2− reduction by Fe(II) and its production of N2O. Geochim. Cosmochim. Acta 186, 1–12 (2016).CAS 
Article 

Google Scholar 
Grabb, K. C., Buchwald, C., Hansel, C. M. & Wankel, S. D. A dual nitrite isotopic investigation of chemodenitrification by mineral-associated Fe(II) and its production of nitrous oxide. Geochim. Cosmochim. Acta 196, 388–402 (2017).CAS 
Article 

Google Scholar 
Drewer, J. et al. Linking nitrous oxide and nitric oxide fluxes to microbial communities in tropical forest soils and oil palm plantations in Malaysia in laboratory incubations. Front. For. Glob. Change 3, 4 (2020).Article 

Google Scholar 
Yvon-Durocher, G., Jones, J. I., Trimmer, M., Woodward, G. & Montoya, J. M. Warming alters the metabolic balance of ecosystems. Phil. Trans. R. Soc. B 365, 2117–2126 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
Yvon-Durocher, G. et al. Reconciling the temperature dependence of respiration across timescales and ecosystem types. Nature 487, 472–476 (2012).CAS 
PubMed 
Article 

Google Scholar 
Jauhiainen, J., Kerojoki, O., Silvennoinen, H., Limin, S. & Vasander, H. Heterotrophic respiration in drained tropical peat is greatly affected by temperature – a passive ecosystem cooling experiment. Environ. Res. Lett. 9, 105013 (2014).Article 

Google Scholar 
Wang, S., Zhuang, Q., Lähteenoja, O., Draper, F. C. & Cadillo-Quiroz, H. Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate. Proc. Natl Acad. Sci. USA 115, 12407–12412 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Stumm, W. & Lee, G. F. Oxygenation of ferrous iron. Ind. Eng. Chem. 53, 143–146 (1961).CAS 
Article 

Google Scholar 
Theis, T. L. & Singer, P. C. Complexation of iron(II) by organic matter and its effect on iron(II) oxygenation. Environ. Sci. Technol. 8, 569–573 (1974).CAS 
Article 

Google Scholar 
Wan, X. et al. Complexation and reduction of iron by phenolic substances: implications for transport of dissolved Fe from peatlands to aquatic ecosystems and global iron cycling. Chem. Geol. 498, 128–138 (2018).CAS 
Article 

Google Scholar 
Daugherty, E. E., Gilbert, B., Nico, P. S. & Borch, T. Complexation and redox buffering of iron(II) by dissolved organic matter. Environ. Sci. Technol. 51, 11096–11104 (2017).CAS 
PubMed 
Article 

Google Scholar 
Prananto, J. A., Minasny, B., Comeau, L.-P., Rudiyanto, R. & Grace, P. Drainage increases CO2 and N2O emissions from tropical peat soils. Glob. Change Biol. 26, 4583–4600 (2020).Article 

Google Scholar 
Stirling, E., Fitzpatrick, R. W. & Mosley, L. Drought effects on wet soils in inland wetlands and peatlands. Earth Sci. Rev. 210, 103387 (2020).CAS 
Article 

Google Scholar 
Hodgkins, S. B. et al. Tropical peatland carbon storage linked to global latitudinal trends in peat recalcitrance. Nat. Commun. 9, 3640 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 23, 3581–3599 (2017).Article 

Google Scholar 
IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Babbin, A. R., Bianchi, D., Jayakumar, A. & Ward, B. B. Rapid nitrous oxide cycling in the suboxic ocean. Science 348, 1127–1129 (2015).CAS 
PubMed 
Article 

Google Scholar 
Hamilton, S. K. & Ostrom, N. E. Measurement of the stable isotope ratio of dissolved N2 in 15N tracer experiments. Limnol. Oceanogr. Methods 5, 233–240 (2007).CAS 
Article 

Google Scholar 
Ostrom, N. E., Gandhi, H., Trubl, G. & Murray, A. E. Chemodenitrification in the cryoecosystem of Lake Vida, Victoria Valley, Antarctica. Geobiology 14, 575–587 (2016).CAS 
PubMed 
Article 

Google Scholar 
Stumm, W. & Morgan, J. J. Aquatic Chemistry 3rd edn (John Wiley & Sons, 1996).Homyak, P. M., Kamiyama, M., Sickman, J. O. & Schimel, J. P. Acidity and organic matter promote abiotic nitric oxide production in drying soils. Glob. Change Biol. 23, 1735–1747 (2017).Article 

Google Scholar 
Henry, S., Bru, D., Stres, B., Hallet, S. & Philippot, L. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ genes in soils. Appl. Environ. Microbiol. 72, 5181–5189 (2006).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jones, C. M., Graf, D. R., Bru, D., Philippot, L. & Hallin, S. The unaccounted yet abundant nitrous oxide-reducing microbial community: a potential nitrous oxide sink. ISME J. 7, 417–426 (2013).CAS 
PubMed 
Article 

Google Scholar 
Zhang, B. et al. A new primer set for clade I nosZ that recovers genes from a broader range of taxa. Biol. Fertil. Soils 57, 523–531 (2021).CAS 
Article 

Google Scholar 
Herbold, C. W. et al. A flexible and economical barcoding approach for highly multiplexed amplicon sequencing of diverse target genes. Front. Microbiol. 6, 8966 (2015).Article 

Google Scholar 
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).CAS 
PubMed 
Article 

Google Scholar 
Edgar, R. C. UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. Preprint at https://www.biorxiv.org/content/early/2016/10/15/081257 (2016).Wang, Q. et al. Ecological patterns of nifH genes in four terrestrial climatic zones explored with targeted metagenomics using Framebot, a new informatics tool. mBio 4, e00592-13 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).CAS 
PubMed 
Article 

Google Scholar 
Fish, J. A. et al. FunGene: the functional gene pipeline and repository. Front. Microbiol. 4, 291 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Huson, D. H. et al. MEGAN Community Edition – interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput. Biol. 12, e1004957 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Huson, D. H. et al. MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs. Biol. Direct 13, 6 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics 12, 385 (2011).PubMed 
PubMed Central 
Article 

Google Scholar 
Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Orcutt BN, Sylvan JB, Knab NJ, Edwards KJ. Microbial ecology of the dark ocean above, at, and below the seafloor. Microbiol Mol Biol Rev. 2011;75:361–422.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Whitman WB, Coleman DC, Wiebe WJ. Prokaryotes: the unseen majority. Proc Natl Acad Sci USA. 1998;95:6578–83.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Arístegui J, Gasol JM, Duarte CM, Herndl GJ. Microbial oceanography of the dark ocean’s pelagic realm. Limnol Oceanogr. 2009;54:1501–29.Article 

Google Scholar 
Ebrahimi A, Schwartzman J, Cordero OX. Cooperation and spatial self-organization determine rate and efficiency of particulate organic matter degradation in marine bacteria. Proc Natl Acad Sci USA. 2019;116:23309–16.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Fontanez KM, Eppley JM, Samo TJ, Karl DM, DeLong EF. Microbial community structure and function on sinking particles in the North Pacific Subtropical Gyre. Front Microbiol. 2015;6:469.PubMed 
PubMed Central 
Article 

Google Scholar 
Simon M, Grossart HP, Schweitzer B, Ploug H. Microbial ecology of organic aggregates in aquatic ecosystems. Aquat Microb Ecol. 2002;28:175–211.Article 

Google Scholar 
Alldredge AL, Silver MW. Characteristics, dynamics and significance of marine snow. Progr Oceanogr. 1988;20:41–82.Article 

Google Scholar 
Zehr JP, Kudela RM. Nitrogen cycle of the open ocean: from genes to ecosystems. Ann Rev Mar Sci. 2011;3:197–225.PubMed 
Article 

Google Scholar 
Bergauer K, Fernandez-Guerra A, Garcia JAL, Sprenger RR, Stepanauskas R, Pachiadaki MG, et al. Organic matter processing by microbial communities throughout the Atlantic water column as revealed by metaproteomics. Proc Natl Acad Sci USA. 2018;115:E400–8.CAS 
PubMed 
Article 

Google Scholar 
Acinas SG, Sánchez P, Salazar G, Cornejo-Castillo FM, Sebastián M, Logares R, et al. Deep ocean metagenomes provide insight into the metabolic architecture of bathypelagic microbial communities. Commun Biol. 2021;4:604.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Teira E, Lebaron P, van Aken H, Herndl GJ. Distribution and activity of Bacteria and Archaea in the deep water masses of the North Atlantic. Limnol Oceanogr. 2006;51:2131–44.CAS 
Article 

Google Scholar 
Herndl GJ, Reinthaler T, Teira E, van Aken H, Veth C, Pernthaler A, et al. Contribution of Archaea to total prokaryotic production in the deep Atlantic Ocean. Appl Environ Microbiol. 2005;71:2303–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gasol JM, Alonso-Sáez L, Vaqué D, Baltar F, Calleja ML, Duarte CM, et al. Mesopelagic prokaryotic bulk and single-cell heterotrophic activity and community composition in the NW Africa-Canary Islands coastal-transition zone. Progr Oceanogr. 2009;83:189–96.Article 

Google Scholar 
Dekas AE, Parada AE, Mayali X, Fuhrman JA, Wollard J, Weber PK, et al. Characterizing chemoautotrophy and heterotrophy in marine archaea and bacteria with single-cell multi-isotope NanoSIP. Front Microbiol. 2019;10:2682.PubMed 
PubMed Central 
Article 

Google Scholar 
Musat N, Foster R, Vagner T, Adam B, Kuypers MMM. Detecting metabolic activities in single cells, with emphasis on nanoSIMS. FEMS Microbiol Rev. 2012;36:486–511.CAS 
PubMed 
Article 

Google Scholar 
Orphan VJ, House CH. Geobiological investigations using secondary ion mass spectrometry: microanalysis of extant and paleo-microbial processes. Geobiology. 2009;7:360–72.CAS 
PubMed 
Article 

Google Scholar 
Pett-Ridge J, Weber PK. NanoSIP: NanoSIMS applications for microbial biology. Methods Mol Biol. 2012;881:375–408.CAS 
PubMed 
Article 

Google Scholar 
Nuñez J, Renslow R, Cliff JB, Anderton CR. NanoSIMS for biological applications: current practices and analyses. Biointerphases. 2018;13:03B301.Article 

Google Scholar 
Dawson KS, Scheller S, Dillon JG, Orphan VJ. Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment. Front Microbiol. 2016;7:774.PubMed 
PubMed Central 
Article 

Google Scholar 
Arandia-Gorostidi N, Weber PK, Alonso-Sáez L, Morán XAG, Mayali X. Elevated temperature increases carbon and nitrogen fluxes between phytoplankton and heterotrophic bacteria through physical attachment. ISME J. 2017;11:641–50.CAS 
PubMed 
Article 

Google Scholar 
Kopf SH, McGlynn SE, Green-Saxena A, Guan Y, Newman DK, Orphan VJ. Heavy water and (15) N labelling with NanoSIMS analysis reveals growth rate-dependent metabolic heterogeneity in chemostats. Environ Microbiol. 2015;17:2542–56.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Schreiber F, Littmann S, Lavik G, Escrig S, Meibom A, Kuypers MMM, et al. Phenotypic heterogeneity driven by nutrient limitation promotes growth in fluctuating environments. Nat Microbiol. 2016;1:16055.CAS 
PubMed 
Article 

Google Scholar 
Berthelot H, Duhamel S, L’Helguen S, Maguer JF, Wang S, Cetinic I, et al. NanoSIMS single cell analyses reveal the contrasting nitrogen sources for small phytoplankton. ISME J. 2019;13:651–62.CAS 
PubMed 
Article 

Google Scholar 
Calabrese F, Voloshynovska I, Musat F, Thullner M, Schlömann M, Richnow HH, et al. Quantitation and comparison of phenotypic heterogeneity among single cells of monoclonal microbial populations. Front Microbiol. 2019;10:1–23.Article 

Google Scholar 
Calabrese F, Stryhanyuk H, Moraru C, Schlömann M, Wick LY, Richnow HH, et al. Metabolic history and metabolic fitness as drivers of anabolic heterogeneity in isogenic microbial populations. Environ Microbiol. 2021;23:6764–76.CAS 
PubMed 
Article 

Google Scholar 
Gini C. Variabilità e Mutuabilità. Contributo allo Studio delle Distribuzioni e delle Relazioni Statistiche. C. Cuppini, Bologna; 1912.Fernández-Tschieder E, Binkley D. Linking competition with growth dominance and production ecology. Ecol Manag. 2018;414:99–107.Article 

Google Scholar 
Cordonnier T, Kunstler G. The Gini index brings asymmetric competition to light. Perspect Plant Ecol Evol Syst. 2015;17:107–15.Article 

Google Scholar 
Harch BD, Correll RL, Meech W, Kirkby CA, Pankhurst CE. Using the Gini coefficient with BIOLOG substrate utilisation data to provide an alternative quantitative measure for comparing bacterial soil communities. J Microbiol Methods. 1997;30:91–101.CAS 
Article 

Google Scholar 
Li J, Ma YB, Hu HW, Wang JT, Liu YR, He JZ. Field-based evidence for consistent responses of bacterial communities to copper contamination in two contrasting agricultural soils. Front Microbiol. 2015;6:31.PubMed 
PubMed Central 

Google Scholar 
Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.CAS 
PubMed 
Article 

Google Scholar 
Polerecky L, Adam B, Milucka J, Musat N, Vagner T, Kuypers MM. Look@NanoSIMS-a tool for the analysis of nanoSIMS data in environmental microbiology. Environ Microbiol. 2012;14:1009–23.CAS 
PubMed 
Article 

Google Scholar 
Stryhanyuk H, Calabrese F, Kümmel S, Musat F, Richnow HH, Musat N. Calculation of single cell assimilation rates from SIP-nanoSIMS-derived isotope ratios: a comprehensive approach. Front Microbiol. 2018;9:2342.PubMed 
PubMed Central 
Article 

Google Scholar 
Arandia‐Gorostidi N, Alonso‐Sáez L, Stryhanyuk H, Richnow HH, Morán XAG, Musat N. Warming the phycosphere: Differential effect of temperature on the use of diatom‐derived carbon by two copiotrophic bacterial taxa. Environ Microbiol. 2020;22:1381–96.PubMed 
Article 

Google Scholar 
Mayali X, Weber PK, Pett-Ridge J. Taxon-specific C/N relative use efficiency for amino acids in an estuarine community. FEMS Microbiol Ecol. 2013;83:402–12.CAS 
PubMed 
Article 

Google Scholar 
Meyer NR, Fortney JL, Dekas AE. NanoSIMS sample preparation decreases isotope enrichment: magnitude, variability and implications for single-cell rates of microbial activity. Environ Microbiol. 2021;23:81–98.CAS 
PubMed 
Article 

Google Scholar 
Kemp PF, Lee S, Laroche J. Estimating the growth rate of slowly growing marine bacteria from RNA content. Appl Environ Microbiol. 1993;59:2594–601.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Baltar F, Arístegui J, Gasol J, Sintes E, van Aken H, Herndl G. High dissolved extracellular enzymatic activity in the deep central Atlantic Ocean. Aquat Micro Ecol. 2010;58:287–302.Article 

Google Scholar 
Lønborg C, Nieto-Cid M, Hernando-Morales V, Hernández-Ruiz M, Teira E, Álvarez-Salgado XA. Photochemical alteration of dissolved organic matter and the subsequent effects on bacterial carbon cycling and diversity. FEMS Microbiol Ecol. 2016;92:fiw048.PubMed 
Article 

Google Scholar 
Nagata T, Fukuda H, Fukuda R, Koike I. Bacter-ioplankton distribution and production in deep Pacific waters: large-scale geographic variations and possible coupling with sinking particle fluxes. Limnol Oceanogr. 2000;45:426–35.CAS 
Article 

Google Scholar 
Teira E, Reinthaler T, Pernthaler A, Pernthaler J, Herndl GJ. Combining catalyzed reporter deposition-fluorescence in situ hybridization and microautoradiography to detect substrate utilization by bacteria and Archaea in the deep ocean. Appl Environ Microbiol. 2004;70:4411–4.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mestre M, Hofer J. The microbial conveyor belt: connecting the globe through dispersion and dormancy. Trends Microbiol. 2020;29:482–92.PubMed 
Article 

Google Scholar 
Giering SLC, Evans C. Overestimation of prokaryotic production by leucine incorporation—and how to avoid it. Limnol Oceanogr. 2022;67:726–38.Article 

Google Scholar 
Amos CM, Castelao RM, Medeiros PM. Offshore transport of particulate organic carbon in the California Current System by mesoscale eddies. Nat Commun. 2019;10:4940.PubMed 
PubMed Central 
Article 

Google Scholar 
Bauer JE, Druffel ERM. Ocean margins as a significant source of organic matter to the deep open ocean. Nature. 1998;392:482–5.CAS 
Article 

Google Scholar 
Tamburini C, Boutrif M, Garel M, Colwell RR, Deming JW. Prokaryotic responses to hydrostatic pressure in the ocean—a review. Environ Microbiol. 2013;15:1262–74.CAS 
PubMed 
Article 

Google Scholar 
Arrieta JM, Mayol E, Hansman RL, Herndl GJ, Dittmar T, Duarte CM. Dilution limits dissolved organic carbon utilization in the deep ocean. Science. 2015;348:331–3.CAS 
PubMed 
Article 

Google Scholar 
Alonso C, Musat N, Adam B, Kuypers M, Amann R. HISH-SIMS analysis of bacterial uptake of algal-derived carbon in the Río de la Plata estuary. Syst Appl Microbiol. 2012;35:541–8.CAS 
PubMed 
Article 

Google Scholar 
Klawonn I, Bonaglia S, Whitehouse MJ, Littmann S, Tienken D, Kuypers MMM, et al. Untangling hidden nutrient dynamics: rapid ammonium cycling and single-cell ammonium assimilation in marine plankton communities. ISME J. 2019;13:1960–74.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Campbell BJ, Yu L, Heidelberg JF, Kirchman DL. Activity of abundant and rare bacteria in a coastal ocean. Proc Natl Acad Sci USA. 2011;108:12776–81.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kirchman DL. Growth rates of microbes in the oceans. Annu Rev Mar Sci. 2016;8:150720190448005.Article 

Google Scholar 
Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J. 2013;7:2061–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Licht TR, Tolker-Nielsen T, Holmstrøm K, Krogfelt KA, Molin S. Inhibition of Escherichia coli precursor-16S rRNA processing by mouse intestinal contents. Environ Microbiol. 1999;1:23–32.CAS 
PubMed 
Article 

Google Scholar 
Sukenik A, Kaplan-Levy RN, Welch JM, Post AF. Massive multiplication of genome and ribosomes in dormant cells (akinetes) of Aphanizomenon ovalisporum (Cyanobacteria). ISME J. 2012;6:670–9.CAS 
PubMed 
Article 

Google Scholar 
Dekas AE, Connon SA, Chadwick GL, Trembath-Reichert E, Orphan VJ. Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses. ISME J. 2016;10:678–92.CAS 
PubMed 
Article 

Google Scholar 
Wu J, Gao W, Johnson R, Zhang W, Meldrum D. Integrated metagenomic and metatranscriptomic analyses of microbial communities in the meso- and bathypelagic realm of North Pacific Ocean. Mar Drugs. 2013;11:3777–801.PubMed 
PubMed Central 
Article 

Google Scholar 
Ackermann M. A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Microbiol. 2015;13:497–508.CAS 
PubMed 
Article 

Google Scholar  More

Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Houghton, R. A. & Nassikas, A. A. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob. Biogeochem. Cycles 31, 456–472 (2017).ADS 
CAS 
Article 

Google Scholar 
Phelps, L. N. & Kaplan, J. O. Land use for animal production in global change studies: Defining and characterizing a framework. Glob. Change Biol. 23, 4457–4471 (2017).ADS 
Article 

Google Scholar 
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hong, C. et al. Global and regional drivers of land-use emissions in 1961–2017. Nature 589, 554–561 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Knorr, W., Prentice, I. C., House, J. & Holland, E. Long-term sensitivity of soil carbon turnover to warming. Nature 433, 298–301 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Shi, Z. et al. The age distribution of global soil carbon inferred from radiocarbon measurements. Nat. Geosci. 13, 555–559 (2020).ADS 
CAS 
Article 

Google Scholar 
Sanderman, J., Hengl, T. & Fiske, G. J. Soil carbon debt of 12,000 years of human land use. Proc. Natl. Acad. Sci. 114, 9575–9580 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623–1627 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).ADS 
Article 

Google Scholar 
Yue, C., Ciais, P., Houghton, R. A. & Nassikas, A. A. Contribution of land use to the interannual variability of the land carbon cycle. Nat. Commun. 11, 1–11 (2020).Article 

Google Scholar 
Zomer, R. J. et al. Global tree cover and biomass carbon on agricultural land: The contribution of agroforestry to global and national carbon budgets. Sci. Rep. 6, 1–12 (2016).Article 

Google Scholar 
De Stefano, A. & Jacobson, M. G. Soil carbon sequestration in agroforestry systems: a meta-analysis. Agrofor. Syst. 92, 285–299 (2018).
Google Scholar 
Bossio, D. et al. The role of soil carbon in natural climate solutions. Nat. Sustain. 3, 391–398 (2020).Article 

Google Scholar 
England, J. R., O’Grady, A. P., Fleming, A., Marais, Z. & Mendham, D. Trees on farms to support natural capital: An evidence-based review for grazed dairy systems. Sci. Total Environ. 704, 135345 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ma, Z., Chen, H. Y., Bork, E. W., Carlyle, C. N. & Chang, S. X. Carbon accumulation in agroforestry systems is affected by tree species diversity, age and regional climate: A global meta-analysis. Glob. Ecol. Biogeogr. 29, 1817–1828 (2020).Article 

Google Scholar 
FAOSTAT. Data/Inputs/land use. In: Food Agriculture Organization. http://www.fao.org/faostat/en/#data/RL. (2020). Accessed 12 Sept 2020.Shukla, P. R. et al. Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. (Intergovernmental Panel on Climate Change, 2019).Galdino, S. et al. Large-scale modeling of soil erosion with RUSLE for conservationist planning of degraded cultivated Brazilian pastures. Land Degrad. Dev. 27, 773–784 (2016).Article 

Google Scholar 
Stanimirova, R. et al. Sensitivity of global pasturelands to climate variation. Earth’s Future 7, 1353–1366 (2019).ADS 
Article 

Google Scholar 
Tolimir, M. et al. The conversion of forestland into agricultural land without appropriate measures to conserve SOM leads to the degradation of physical and rheological soil properties. Sci. Rep. 10, 1–12 (2020).Article 

Google Scholar 
Mendoza-Ponce, A., Corona-Núñez, R., Kraxner, F., Leduc, S. & Patrizio, P. Identifying effects of land use cover changes and climate change on terrestrial ecosystems and carbon stocks in Mexico. Glob. Environ. Change. 53, 12–23 (2018).Article 

Google Scholar 
Castillo-Santiago, M., Hellier, A., Tipper, R. & De Jong, B. Carbon emissions from land-use change: An analysis of causal factors in Chiapas, Mexico. Mitig. Adapt. Strat. Glob. Change 12, 1213–1235 (2007).Article 

Google Scholar 
Kolb, M. & Galicia, L. Scenarios and story lines: drivers of land use change in southern Mexico. Environ. Dev. Sustain. 20, 681–702 (2018).Article 

Google Scholar 
Aryal, D. R. et al. Biomass accumulation in forests with high pressure of fuelwood extraction in Chiapas, Mexico. Revista Árvore 42, e420307 (2018).Article 

Google Scholar 
Aryal, D. R. et al. Soil organic carbon depletion from forests to grasslands conversion in Mexico: A review. Agriculture 8, 181 (2018).CAS 
Article 

Google Scholar 
Griscom, B. W. et al. Natural climate solutions. Proc. Natl. Acad. Sci. 114, 11645–11650 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chapman, M. et al. Large climate mitigation potential from adding trees to agricultural lands. Glob. Change Biol. 26, 4357–4365 (2020).ADS 
Article 

Google Scholar 
Hayek, M. N., Harwatt, H., Ripple, W. J. & Mueller, N. D. The carbon opportunity cost of animal-sourced food production on land. Nat. Sustain. 4, 21–24 (2021).Article 

Google Scholar 
Kothandaraman, S., Dar, J. A., Sundarapandian, S., Dayanandan, S. & Khan, M. L. Ecosystem-level carbon storage and its links to diversity, structural and environmental drivers in tropical forests of Western Ghats, India. Sci. Rep. 10, 1–15 (2020).Article 

Google Scholar 
Havlík, P. et al. Climate change mitigation through livestock system transitions. Proc. Natl. Acad. Sci. 111, 3709–3714 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Resende, L. O. et al. Silvopastoral management of beef cattle production for neutralizing the environmental impact of enteric methane emission. Agroforestry Syst. 94, 893–903 (2020).Article 

Google Scholar 
Sans, G. H. C., Verón, S. R. & Paruelo, J. M. Forest strips increase connectivity and modify forests’ functioning in a deforestation hotspot. J. Environ. Manage. 290, 112606 (2021).Article 

Google Scholar 
Searchinger, T. D., Wirsenius, S., Beringer, T. & Dumas, P. Assessing the efficiency of changes in land use for mitigating climate change. Nature 564, 249–253 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Lawson, G., Dupraz, C. & Watté, J. Can silvoarable systems maintain yield, resilience, and diversity in the face of changing environments? in Agroecosystem Diversity 145–168 (Elsevier, 2019).Ramakrishnan, S. et al. Silvopastoral system for resilience of key soil health indicators in semi-arid environment. Arch. Agron. Soil Sci. 67, 1834–1847 (2021).CAS 
Article 

Google Scholar 
Gerber, P. J. et al. Tackling Climate Change Through Livestock: A Global Assessment of Emissions and Mitigation Opportunities (Food and Agriculture Organization of the United Nations (FAO), 2013).
Google Scholar 
Haberl, H. Method précis: Human appropriation of net primary production (HANPP). In Social Ecology. Society-Nature Relations across Time and Space (eds Haberl, H. et al.) 332–334 (Springer Nature, 2016).
Google Scholar 
Smith, P. et al. Global change pressures on soils from land use and management. Glob. Change Biol. 22, 1008–1028 (2016).ADS 
Article 

Google Scholar 
Herrero, M. et al. Greenhouse gas mitigation potentials in the livestock sector. Nat. Clim. Change. 6, 452–461 (2016).ADS 
Article 

Google Scholar 
Lorenz, K. & Lal, R. Soil organic carbon sequestration in agroforestry systems. A review. Agron. Sustain. Develop. 34, 443–454 (2014).CAS 
Article 

Google Scholar 
Michalk, D. L. et al. Sustainability and future food security—A global perspective for livestock production. Land Degrad. Dev. 30, 561–573 (2019).Article 

Google Scholar 
Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth Environ. 2, 720–735 (2021).ADS 
Article 

Google Scholar 
Pinheiro, F. M., Nair, P. R., Nair, V. D., Tonucci, R. G. & Venturin, R. P. Soil carbon stock and stability under Eucalyptus-based silvopasture and other land-use systems in the Cerrado biodiversity hotspot. J. Environ. Manage. 299, 113676 (2021).CAS 
PubMed 
Article 

Google Scholar 
Jose, S., Walter, D. & Kumar, B. M. Ecological considerations in sustainable silvopasture design and management. Agrofor. Syst. 93, 317–331 (2019).Article 

Google Scholar 
Oldfield, E. E. et al. Crediting agricultural soil carbon sequestration. Science 375, 1222–1225 (2022).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Udawatta, R. P., Walter, D. & Jose, S. Carbon sequestration by forests and agroforests: A reality check for the United States. Carbon Footprints 1, 8 (2022).Article 

Google Scholar 
Adame-Castro, D. E. et al. Diurnal and seasonal variations on soil CO2 fluxes in tropical silvopastoral systems. Soil Use Manag. 36, 671–681 (2020).Article 

Google Scholar 
Contosta, A. R., Asbjornsen, H., Orefice, J., Perry, A. & Smith, R. G. Climate consequences of temperate forest conversion to open pasture or silvopasture. Agric. Ecosyst. Environ. 333, 107972 (2022).CAS 
Article 

Google Scholar 
Vargas-Zeppetello, L. R. et al. Consistent cooling benefits of silvopasture in the tropics. Nat. Commun. 13, 1–9 (2022).
Google Scholar 
Casanova-Lugo, F. et al. Effect of tree shade on the yield of Brachiaria brizantha grass in tropical livestock production systems in Mexico. Rangel. Ecol. Manage. 80, 31–38 (2022).Article 

Google Scholar 
Valenzuela Que, F. G. et al. Silvopastoral systems improve carbon stocks at livestock ranches in Tabasco, Mexico. Soil Use Manag. 38, 1237–1249 (2022).Article 

Google Scholar 
Nair, P. R. Classification of agroforestry systems. Agrofor. Syst. 3, 97–128 (1985).Article 

Google Scholar 
Somarriba, E., Kass, D. & Ibrahim, M. Definition and classification of agroforestry systems. Agroforestry Prototypes for Belize. Agroforestry Project. CATIE (Tropical Agricultural Research and Higher Education Center), Costa rica 3 (1998).Schroth, G. et al. Agroforestry and Biodiversity Conservation in Tropical Landscapes (Island Press, 2004).
Google Scholar 
Harvey, C. A. et al. Patterns of animal diversity in different forms of tree cover in agricultural landscapes. Ecol. Appl. 16, 1986–1999 (2006).PubMed 
Article 

Google Scholar 
Cardinael, R., Mao, Z., Chenu, C. & Hinsinger, P. Belowground functioning of agroforestry systems: Recent advances and perspectives. Plant Soil. 1–13 (2020).Ibrahim, M. & Beer, J. Agroforestry Prototypes for Belize Vol. 28 (CATIE, 1998).
Google Scholar 
Ibrahim, M., Villanueva, C., Casasola, F. & Rojas, J. Sistemas silvopastoriles como una herramienta para el mejoramiento de la productividad y restauración de la integridad ecológica de paisajes ganaderos. Pastos y Forrajes 29, 383–419 (2006).
Google Scholar 
Phalan, B., Onial, M., Balmford, A. & Green, R. E. Reconciling food production and biodiversity conservation: Land sharing and land sparing compared. Science 333, 1289–1291 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Van Zanten, H. H. et al. Defining a land boundary for sustainable livestock consumption. Glob. Change Biol. 24, 4185–4194 (2018).ADS 
Article 

Google Scholar 
Torres, C. M. M. E. et al. Greenhouse gas emissions and carbon sequestration by agroforestry systems in southeastern Brazil. Sci. Rep. 7, 1–7 (2017).Article 

Google Scholar 
Haile, S. G., Nair, V. D. & Nair, P. R. Contribution of trees to carbon storage in soils of silvopastoral systems in Florida, USA. Glob. Change Biol. 16, 427–438 (2010).ADS 
Article 

Google Scholar 
Chatterjee, N., Nair, P. R., Chakraborty, S. & Nair, V. D. Changes in soil carbon stocks across the Forest-Agroforest-Agriculture/Pasture continuum in various agroecological regions: A meta-analysis. Agric. Ecosyst. Environ. 266, 55–67 (2018).Article 

Google Scholar 
Aynekulu, E. et al. Carbon storage potential of silvopastoral systems of Colombia. Land 9, 309 (2020).Article 

Google Scholar 
Birkhofer, K. et al. Land-use type and intensity differentially filter traits in above-and below-ground arthropod communities. J. Anim. Ecol. 86, 511–520 (2017).PubMed 
Article 

Google Scholar 
Dahlsjö, C. A. et al. The local impact of macrofauna and land-use intensity on soil nutrient concentration and exchangeability in lowland tropical Peru. Biotropica 52, 242–251 (2020).Article 

Google Scholar 
Vizcaíno-Bravo, Q., Williams-Linera, G. & Asbjornsen, H. Biodiversity and carbon storage are correlated along a land use intensity gradient in a tropical montane forest watershed, Mexico. Basic Appl. Ecol. 44, 24–34 (2020).Article 

Google Scholar 
Villanueva-López, G., Martínez-Zurimendi, P., Ramírez-Avilés, L., Aryal, D. R. & Casanova-Lugo, F. Live fences reduce the diurnal and seasonal fluctuations of soil CO 2 emissions in livestock systems. Agron. Sustain. Dev. 36, 23 (2016).Article 

Google Scholar 
López-Santiago, J. G. et al. Carbon storage in a silvopastoral system compared to that in a deciduous dry forest in Michoacán, Mexico. Agroforestry Syst. 93, 199–211 (2019).Article 

Google Scholar 
Aryal, D. R., Gómez-González, R. R., Hernández-Nuriasmú, R. & Morales-Ruiz, D. E. Carbon stocks and tree diversity in scattered tree silvopastoral systems in Chiapas, Mexico. Agroforestry Syst. 93, 213–227 (2019).Article 

Google Scholar 
Beckert, M. R., Smith, P., Lilly, A. & Chapman, S. J. Soil and tree biomass carbon sequestration potential of silvopastoral and woodland-pasture systems in North East Scotland. Agrofor. Syst. 90, 371–383 (2016).Article 

Google Scholar 
Cárdenas, A., Moliner, A., Hontoria, C. & Ibrahim, M. Ecological structure and carbon storage in traditional silvopastoral systems in Nicaragua. Agrofor. Syst. 93, 229–239 (2019).Article 

Google Scholar 
Lehmann, J. et al. Persistence of soil organic carbon caused by functional complexity. Nat. Geosci. 13, 529–534 (2020).ADS 
CAS 
Article 

Google Scholar 
Amézquita, M. C., Ibrahim, M., Llanderal, T., Buurman, P. & Amézquita, E. Carbon sequestration in pastures, silvo-pastoral systems and forests in four regions of the Latin American tropics. J. Sustain. For. 21, 31–49 (2004).Article 

Google Scholar 
Rosenstock, T. S. et al. Making trees count: Measurement and reporting of agroforestry in UNFCCC national communications of non-Annex I countries. Agric. Ecosyst. Environ. 284, 106569 (2019).Article 

Google Scholar 
Junior, M. A. L., Fracetto, F. J. C., da Silva Ferreira, J., Silva, M. B. & Fracetto, G. G. M. Legume-based silvopastoral systems drive C and N soil stocks in a subhumid tropical environment. CATENA 189, 104508 (2020).Article 

Google Scholar 
Villanueva-Partida, C. et al. Influence of the density of scattered trees in pastures on the structure and species composition of tree and grass cover in southern Tabasco, Mexico. Agric. Ecosyst. Environ. 232, 1–8 (2016).Article 

Google Scholar 
Morantes-Toloza, J. L. & Renjifo, L. M. Live fences in tropical production systems: A global review of uses and perceptions. Rev. Biol. Trop. 66, 739–753 (2018).Article 

Google Scholar 
MoralesRuiz, D. E. et al. Carbon contents and fine root production in tropical silvopastoral systems. Land Degrad. Develop. 32, 738–756 (2021).Article 

Google Scholar 
Hoosbeek, M. R., Remme, R. P. & Rusch, G. M. Trees enhance soil carbon sequestration and nutrient cycling in a silvopastoral system in south-western Nicaragua. Agrofor. Syst. 92, 263–273 (2018).
Google Scholar 
Aryal, D. R. et al. Fine wood decomposition rates decline with the sge of tropical successional forests in Southern Mexico: Implications to ecosystem carbon storage. Ecosystems 25, 661–677 (2022).CAS 
Article 

Google Scholar 
Dignac, M.-F. et al. Increasing soil carbon storage: Mechanisms, effects of agricultural practices and proxies. A review. Agron. Sustain. Develop. 37, 1–27 (2017).CAS 
Article 

Google Scholar 
Sánchez-Silva, S. et al. Fine root biomass stocks but not the production and turnover rates vary with the age of tropical successional forests in Southern Mexico. Rhizosphere 21, 100474 (2022).Article 

Google Scholar 
Montejo-Martínez, D. et al. Fine root density and vertical distribution of Leucaena leucocephala and grasses in silvopastoral systems under two harvest intervals. Agrofor. Syst. 94, 843–855 (2020).Article 

Google Scholar 
Sánchez-Silva, S., De Jong, B. H., Aryal, D. R., Huerta-Lwanga, E. & Mendoza-Vega, J. Trends in leaf traits, litter dynamics and associated nutrient cycling along a secondary successional chronosequence of semi-evergreen tropical forest in South-Eastern Mexico. J. Trop. Ecol. 34, 364–377 (2018).Article 

Google Scholar 
Waters, C. M., Orgill, S. E., Melville, G. J., Toole, I. D. & Smith, W. J. Management of grazing intensity in the semi-arid rangelands of Southern Australia: Effects on soil and biodiversity. Land Degrad. Dev. 28, 1363–1375 (2017).Article 

Google Scholar 
Baldassini, P. & Paruelo, J. M. Deforestation and current management practices reduce soil organic carbon in the semi-arid Chaco, Argentina. Agric. Syst. 178, 102749 (2020).Article 

Google Scholar 
Abdalla, M. et al. Critical review of the impacts of grazing intensity on soil organic carbon storage and other soil quality indicators in extensively managed grasslands. Agric. Ecosyst. Environ. 253, 62–81 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 1–8 (2015).ADS 
Article 

Google Scholar 
Wiesmeier, M. et al. Soil organic carbon storage as a key function of soils—A review of drivers and indicators at various scales. Geoderma 333, 149–162 (2019).ADS 
CAS 
Article 

Google Scholar 
Lim, S.-S. et al. Soil organic carbon stocks in three Canadian agroforestry systems: From surface organic to deeper mineral soils. For. Ecol. Manage. 417, 103–109 (2018).ADS 
Article 

Google Scholar 
Nair, P. Carbon sequestration studies in agroforestry systems: A reality-check. Agrofor. Syst. 86, 243–253 (2012).Article 

Google Scholar 
Montagnini, F., Ibrahim, M. & Murgueitio, E. Silvopastoral systems and climate change mitigation in Latin America. Bois et forêts des tropiques 316, 3–16 (2013).Article 

Google Scholar 
Allison, S. D., Wallenstein, M. D. & Bradford, M. A. Soil-carbon response to warming dependent on microbial physiology. Nat. Geosci. 3, 336–340 (2010).ADS 
CAS 
Article 

Google Scholar 
Sarto, M. V. et al. Soil microbial community and activity in a tropical integrated crop-livestock system. Appl. Soil. Ecol. 145, 103350 (2020).Article 

Google Scholar 
Malik, A. A. et al. Land use driven change in soil pH affects microbial carbon cycling processes. Nat. Commun. 9, 1–10 (2018).ADS 
CAS 
Article 

Google Scholar 
Bautista, F., Palacio-Aponte, G., Quintana, P. & Zinck, J. A. Spatial distribution and development of soils in tropical karst areas from the Peninsula of Yucatan, Mexico. Geomorphology 135, 308–321 (2011).ADS 
Article 

Google Scholar 
Kaiser, M. et al. The influence of mineral characteristics on organic matter content, composition, and stability of topsoils under long‐term arable and forest land use. J. Geophys. Res. Biogeosci. 117, (2012).Castillo, M. S., Tiezzi, F. & Franzluebbers, A. J. Tree species effects on understory forage productivity and microclimate in a silvopasture of the Southeastern USA. Agric. Ecosyst. Environ. 295, 106917 (2020).Article 

Google Scholar 
Yang, Y., Tilman, D., Furey, G. & Lehman, C. Soil carbon sequestration accelerated by restoration of grassland biodiversity. Nat. Commun. 10, 1–7 (2019).
Google Scholar 
Grass, I. et al. Land-sharing/-sparing connectivity landscapes for ecosystem services and biodiversity conservation. People Nat. 1, 262–272 (2019).
Google Scholar 
Orefice, J., Smith, R. G., Carroll, J., Asbjornsen, H. & Howard, T. Forage productivity and profitability in newly-established open pasture, silvopasture, and thinned forest production systems. Agrofor. Syst. 93, 51–65 (2019).Article 

Google Scholar 
Aryal, D. R. et al. Potencial de almacenamiento de carbono en áreas forestales en un sistema ganadero. Revista mexicana de ciencias forestales 9, 150–180 (2018).Article 

Google Scholar 
Gobierno de la Republica. Intended Nationally Determined Contribution, Mexico. (Instituto Nacional de Ecología y Cambio Climático, Mexico City, 2015).Bonilla-Moheno, M. & Aide, T. M. Beyond deforestation: Land cover transitions in Mexico. Agric. Syst. 178, 102734 (2020).Article 

Google Scholar 
INEGI. Mapa de uso de suelo y vegetación de México: Series I–VII. Instituto Nacional de Estadística y Geografía (INEGI), Aguascalientes, Mexico. https://www.inegi.org.mx/temas/usosuelo/#Map (2018). Accessed 17 Aug 2022.Gosling, E., Reith, E., Knoke, T. & Paul, C. A goal programming approach to evaluate agroforestry systems in Eastern Panama. J. Environ. Manage. 261, 110248 (2020).PubMed 
Article 

Google Scholar 
Bergier, I. et al. Could bovine livestock intensification in Pantanal be neutral regarding enteric methane emissions?. Sci. Total Environ. 655, 463–472 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Barkin, D. E. uso de la tierra agrícola en Mexico. Problemas del Desarrollo 12, 59–85 (1981).
Google Scholar 
Valdivieso-Pérez, I. A., García-Barrios, L. E., Álvarez-Solís, D. & Nahed-Toral, J. From cornfields to grasslands: Change in the quality of soil. Terra Latinoamericana. 30, 363–374 (2012).
Google Scholar 
Goldstein, A. et al. Protecting irrecoverable carbon in Earth’s ecosystems. Nat. Clim. Chang. 10, 287–295 (2020).ADS 
CAS 
Article 

Google Scholar 
CONAFOR. Acciones Tempranas REDD+ Mexico. https://www.gob.mx/conafor/documentos/acciones-tempranas-redd (2017). Accessed 04 Oct 2020.CATIE. Bidiversidad y paisajes ganaderos agrosilvopastoriles sostenibles. https://www.biopasos.com (2020). Accessed 04 Oct 2020.Freire-Santos, P. Z. F., Crouzeilles, R. & Sansevero, J. B. B. Can agroforestry systems enhance biodiversity and ecosystem service provision in agricultural landscapes? A meta-analysis for the Brazilian Atlantic Forest. For. Ecol. Manage. 433, 140–145 (2019).Article 

Google Scholar 
Zanne, A. et al. Data from: Towards a worldwide wood economics spectrum. (2009). 10.5061/dryad.234.Chave, J. et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Change Biol. 20, 3177–3190 (2014).ADS 
Article 

Google Scholar 
Bojórquez, A. et al. Improving the accuracy of aboveground biomass estimations in secondary tropical dry forests. For. Ecol. Manage. 474, 118384 (2020).Article 

Google Scholar 
Cairns, M. A., Brown, S., Helmer, E. H. & Baumgardner, G. A. Root biomass allocation in the world’s upland forests. Oecologia 111, 1–11 (1997).ADS 
PubMed 
Article 

Google Scholar 
Shannon, C.E., Weaver. A Mathematical Theory of Communication Vol. 27 (University of Illinois Press, 1964).Sorensen, T. A. A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analyses of the vegetation on Danish commons. Biol. Skar. 5, 1–34 (1948).
Google Scholar 
Pielou, E. C. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13, 131–144 (1966).ADS 
Article 

Google Scholar 
Van Wagner, C. Practical Aspects of the Line Intersect Method Vol. 12 (Canadian Forestry Service, 1982).
Google Scholar 
Heanes, D. Determination of total organic-C in soils by an improved chromic acid digestion and spectrophotometric procedure. Commun. Soil Sci. Plant Anal. 15, 1191–1213 (1984).CAS 
Article 

Google Scholar  More

Doney, S. C. et al. Climate change impacts on marine ecosystems. Annu. Rev. Mar. Sci. 4, 11–37. https://doi.org/10.1146/annurev-marine-041911-111611 (2012).ADS 
Article 

Google Scholar 
Hoegh-Guldberg, O., Poloczanska, E. S., Skirving, W. & Dove, S. Coral reef ecosystems under climate change and ocean acidification. Front. Mar. Sci. 4, 158 (2017).Article 

Google Scholar 
Weis, V. M. Cellular mechanisms of Cnidarian bleaching: stress causes the collapse of symbiosis. J. Exp. Biol. 211, 3059–3066 (2008).CAS 
PubMed 
Article 

Google Scholar 
Fitt, W., Brown, B., Warner, M. & Dunne, R. Coral bleaching: interpretation of thermal tolerance limits and thermal thresholds in tropical corals. Coral Reefs 20, 51–65. https://doi.org/10.1007/s003380100146 (2001).Article 

Google Scholar 
Fujise, L., Yamashita, H., Suzuki, G. & Koike, K. Expulsion of zooxanthellae (Symbiodinium) from several species of scleractinian corals: comparison under non-stress conditions and thermal stress conditions. Galaxea, JCRS 15, 29–36. https://doi.org/10.3755/galaxea.15.29 (2013).Article 

Google Scholar 
Rädecker, N. et al. Heat stress destabilizes symbiotic nutrient cycling in corals. PNAS USA https://doi.org/10.1073/pnas.2022653118 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570-2580.e6. https://doi.org/10.1016/j.cub.2018.07.008 (2018).CAS 
Article 
PubMed 

Google Scholar 
Wooldridge, S. A. Breakdown of the coral-algae symbiosis. Towards formalising a linkage between warm-water bleaching thresholds and the growth rate of the intracellular zooxanthellae. Biogeosciences 10, 1647–1658 (2013).ADS 
Article 

Google Scholar 
Wiedenmann, J. et al. Nutrient enrichment can increase the susceptibility of reef corals to bleaching. Nat. Clim. Change 3, 160–164 (2013).ADS 
CAS 
Article 

Google Scholar 
Peña-García, D., Ladwig, N., Turki, A. J. & Mudarris, M. S. Input and dispersion of nutrients from the Jeddah Metropolitan Area, Red Sea. Mar. Pollut. Bull. 80, 41–51. https://doi.org/10.1016/j.marpolbul.2014.01.052 (2014).CAS 
Article 
PubMed 

Google Scholar 
Morris, L. A., Voolstra, C. R., Quigley, K. M., Bourne, D. G. & Bay, L. K. Nutrient availability and metabolism affect the stability of coral–Symbiodiniaceae symbioses. Trends Microbiol. 27, 678–689 (2019).CAS 
PubMed 
Article 

Google Scholar 
Ferrier-Pagés, C., Gattuso, J.-P., Dallot, S. & Jaubert, J. Effect of nutrient enrichment on growth and photosynthesis of the zooxanthellate coral Stylophora pistillata. Coral Reefs 19, 103–113. https://doi.org/10.1007/s003380000078 (2000).Article 

Google Scholar 
Rosset, S., Wiedenmann, J., Reed, A. J. & D’angelo, C. Phosphate deficiency promotes coral bleaching and is reflected by the ultrastructure of symbiotic dinoflagellates. Mar. Pollut. Bull. 118, 180–187. https://doi.org/10.1016/j.marpolbul.2017.02.044 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Patterson, K. et al. Distinct signalling pathways and transcriptome response signatures differentiate ammonium- and nitrate-supplied plants. Plant Cell Environ. 33, 1486–1501 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ezzat, L., Maguer, J.-F., Grover, R. & Ferrier-Pagès, C. New insights into carbon acquisition and exchanges within the coral–dinoflagellate symbiosis under NH 4+ and NO 3− supply. Proc. R. Soc. B. 282, 20150610 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Guan, Y., Hohn, S., Wild, C. & Merico, A. Vulnerability of global coral reef habitat suitability to ocean warming, acidification and eutrophication. Glob. Change Biol. 26, 5646–5660 (2020).ADS 
Article 

Google Scholar 
Roff, G. & Mumby, P. J. Global disparity in the resilience of coral reefs. Trends Ecol. Evol. 27, 404–413 (2012).PubMed 
Article 

Google Scholar 
Knowlton, N. & Jackson, J. B. C. Shifting baselines, local impacts, and global change on coral reefs. PLoS Biol. 6, e54 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
Vollstedt, S., Xiang, N., Simancas-Giraldo, S. M. & Wild, C. Organic eutrophication increases resistance of the pulsating soft coral Xenia umbellata to warming. PeerJ 8, e9182 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Fabricius, K. E., Cséke, S., Humphrey, C. & De’ath, G. Does trophic status enhance or reduce the thermal tolerance of scleractinian corals? A review, experiment and conceptual framework. PloS one 8, e54399 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cardini, U. et al. Functional significance of dinitrogen fixation in sustaining coral productivity under oligotrophic conditions. Proc. Biol. Sci. 282, 20152257 (2015).PubMed 
PubMed Central 

Google Scholar 
Baker, D. M., Freeman, C. J., Wong, J. C. Y., Fogel, M. L. & Knowlton, N. Climate change promotes parasitism in a coral symbiosis. ISME J. 12, 921–930. https://doi.org/10.1038/s41396-018-0046-8 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
de Barros, F. et al. Unravelling the different causes of nitrate and ammonium effects on coral bleaching. Sci. Rep. 10, 11975 (2020).ADS 
Article 

Google Scholar 
Steinberg, R. K., Dafforn, K. A., Ainsworth, T. & Johnston, E. L. Know thy anemone. A review of threats to octocorals and anemones and opportunities for their restoration. Front. Mar. Sci. 7, 590 (2020).Article 

Google Scholar 
Norström, A. V., Nyström, M., Lokrantz, J. & Folke, C. Alternative states on coral reefs. Beyond coral–macroalgal phase shifts. Mar. Ecol. Prog. Ser. 376, 295–306 (2009).ADS 
Article 

Google Scholar 
van de Water, J. A. J. M., Allemand, D. & Ferrier-Pagès, C. Host-microbe interactions in octocoral holobionts—recent advances and perspectives. Microbiome 6, 64 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Syms, C. & Jones, G. P. Dysturbance, habitat structure, and the dynamics of a coral-reef fish community. Ecology 81, 2714–2729 (2000).Article 

Google Scholar 
Syms, C. & Jones, G. P. Soft corals exert no direct effects on coral reef fish assemblages. Oecologia 127, 560–571. https://doi.org/10.1007/s004420000617 (2001).ADS 
Article 
PubMed 

Google Scholar 
Epstein, H. E. & Kingsford, M. J. Are soft coral habitats unfavourable? A closer look at the association between reef fishes and their habitat. Environ. Biol. Fishes 102, 479–497 (2019).Article 

Google Scholar 
Janes, M. P. Distribution and diversity of the soft coral family Xeniidae (Coelenterata: Octocorallia) in Lembeh Strait, Indonesia. Galaxea, JCRS 15, 195–200 (2013).Article 

Google Scholar 
Fox, H. E., Pet, J. S., Dahuri, R. & Caldwell, R. L. Recovery in rubble fields. Long-term impacts of blast fishing. Mar. Pollut. Bull. 46, 1024–1031 (2003).CAS 
PubMed 
Article 

Google Scholar 
Al-Sofyani, A. A. & Niaz, G. R. A comparative study of the components of the hard coral Seriatopora hystrix and the soft coral Xenia umbellata along the Jeddah coast, Saudi Arabia. Rev. Biol. Mar. Oceanogr. 42, 207–219 (2007).Article 

Google Scholar 
Kremien, M., Shavit, U., Mass, T. & Genin, A. Benefit of pulsation in soft corals. PNAS USA 110, 8978–8983 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Swart, P. K., Saied, A. & Lamb, K. Temporal and spatial variation in the δ 15 N and δ 13 C of coral tissue and zooxanthellae in Montastraea faveolata collected from the Florida reef tract. Limnol. Oceanogr. 50, 1049–1058 (2005).ADS 
CAS 
Article 

Google Scholar 
Grottoli, A. G., Tchernov, D. & Winters, G. Physiological and biogeochemical responses of super-corals to thermal stress from the northern gulf of Aqaba, Red Sea. Front. Mar. Sci. 4, 215 (2017).Article 

Google Scholar 
Tanaka, Y., Miyajima, T., Koike, I., Hayashibara, T. & Ogawa, H. Imbalanced coral growth between organic tissue and carbonate skeleton caused by nutrient enrichment. Limnol. Oceanogr. 52, 1139–1146 (2007).ADS 
CAS 
Article 

Google Scholar 
Marubini, F. & Davies, P. S. Nitrate increases zooxanthellae population density and reduces skeletogenesis in corals. Mar. Biol. 127, 319–328 (1996).CAS 
Article 

Google Scholar 
Dagenais-Bellefeuille, S. & Morse, D. Putting the N in dinoflagellates. Front. Microbiol. https://doi.org/10.3389/fmicb.2013.00369 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Wooldridge, S. A. A new conceptual model for the warm-water breakdown of the coral—algae endosymbiosis. Mar. Freshwater Res. 60, 483 (2009).CAS 
Article 

Google Scholar 
Moed, J. R. & Hallegraeff, G. M. Some problems in the estimation of chlorophyll-a and phaeopigments from pre- and post-acidification spectrophotometrie measurements. Int. Revue Ges. Hydrobiol. Hydrogr. 63, 787–800 (1978).CAS 
Article 

Google Scholar 
Redfield, A. C. The biological control of chemical factors in the environment. Am. Sci. 46, A221-230A (1958).
Google Scholar 
Pupier, C. A., Bednarz, V. N. & Ferrier-Pagès, C. Studies with soft corals—recommendations on sample processing and normalization metrics. Front. Mar. Sci. 5, 2620 (2018).Article 

Google Scholar 
Pupier, C. A. et al. Dissolved nitrogen acquisition in the symbioses of soft and hard corals with Symbiodiniaceae: A key to understanding their different nutritional strategies?. Front. Microbiol. 12, 657759 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Bednarz, V. N., Naumann, M. S., Niggl, W. & Wild, C. Inorganic nutrient availability affects organic matter fluxes and metabolic activity in the soft coral genus Xenia. J. Exp. Biol. 215, 3672–3679 (2012).CAS 
PubMed 

Google Scholar 
Béraud, 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. 216, 2665–2674 (2013).PubMed 

Google Scholar 
Ezzat, L., Towle, E., Irisson, J.-O., Langdon, C. & Ferrier-Pagès, C. The relationship between heterotrophic feeding and inorganic nutrient availability in the scleractinian coral T. reniformis under a short-term temperature increase. Limnol. Oceanogr. 61, 89–102 (2016).ADS 
Article 

Google Scholar 
Dobson, K. L. et al. Moderate nutrient concentrations are not detrimental to corals under future ocean conditions. Mar. Biol. https://doi.org/10.1007/s00227-021-03901-3 (2021).Article 

Google Scholar 
Strychar, K. B., Coates, M., Sammarco, P. W., Piva, T. J. & Scott, P. T. Loss of Symbiodinium from bleached soft corals Sarcophyton ehrenbergi, Sinularia sp. and Xenia sp.. J. Exp. Mar. Biol. Ecol. 320, 159–177. https://doi.org/10.1016/j.jembe.2004.12.039 (2005).Article 

Google Scholar 
Sammarco, P. W. & Strychar, K. B. Responses to high seawater temperatures in zooxanthellate octocorals. PloS one 8, e54989 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Osman, E. O. et al. Thermal refugia against coral bleaching throughout the northern Red Sea. Glob. Change Biol. 24, e474–e484. https://doi.org/10.1111/gcb.13895 (2018).Article 

Google Scholar 
Fine, M., Gildor, H. & Genin, A. A coral reef refuge in the Red Sea. Glob. Change Biol. 19, 3640–3647 (2013).ADS 
Article 

Google Scholar 
Evensen, N. R., Fine, M., Perna, G., Voolstra, C. R. & Barshis, D. J. Remarkably high and consistent tolerance of a Red Sea coral to acute and chronic thermal stress exposures. Limnol. Oceanogr. 66, 1718–1729 (2021).ADS 
Article 

Google Scholar 
Sawall, Y. et al. Extensive phenotypic plasticity of a Red Sea coral over a strong latitudinal temperature gradient suggests limited acclimatization potential to warming. Sci. Rep. 5, 8940 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Carpenter, E. J., Harvey, H., Fry, B. & Capone, D. G. Biogeochemical tracers of the marine cyanobacterium Trichodesmium. Deep-Sea Res. I: Oceanogr. Res. Pap. 44, 27–38 (1997).ADS 
CAS 
Article 

Google Scholar 
Kürten, B. et al. Influence of environmental gradients on C and N stable isotope ratios in coral reef biota of the Red Sea, Saudi Arabia. J. Sea Res. 85, 379–394 (2014).ADS 
Article 

Google Scholar 
Karcher, D. B. et al. Nitrogen eutrophication particularly promotes turf algae in coral reefs of the central Red Sea. PeerJ 8, e8737 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Sterner, R. W. & Elser, J. J. Ecological Stoichiometry. The Biology of Elements from Molecules to the Biosphere (Princeton University Press, 2002).Tilstra, A. et al. Light induced intraspecific variability in response to thermal stress in the hard coral Stylophora pistillata. PeerJ 5, e3802 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Siebeck, U. E., Marshall, N. J., Klüter, A. & Hoegh-Guldberg, O. Monitoring coral bleaching using a colour reference card. Coral Reefs 25, 453–460 (2006).ADS 
Article 

Google Scholar 
Venn, A. A., Wilson, M. A., Trapido-Rosenthal, H. G., Keely, B. J. & Douglas, A. E. The impact of coral bleaching on the pigment profile of the symbiotic alga, Symbiodinium. Plant Cell Environ. 29, 2133–2142 (2006).CAS 
PubMed 
Article 

Google Scholar 
Dubinsky, Z. V. Y. et al. The effect of external nutrient resources on the optical properties and photosynthetic efficiency of Stylophora pistillata. Proc. R. Soc. B.: Biol. Sci. 239, 231–246 (1990).ADS 

Google Scholar 
Fabricius, K. E. Effects of irradiance, flow, and colony pigmentation on the temperature microenvironment around corals: Implications for coral bleaching?. Limnol. Oceanogr. 51, 30–37 (2006).ADS 
Article 

Google Scholar 
Nordemar, I., Nyström, M. & Dizon, R. Effects of elevated seawater temperature and nitrate enrichment on the branching coral Porites cylindrica in the absence of particulate food. Mar. Biol. 142, 669–677 (2003).CAS 
Article 

Google Scholar 
Lewis, J. B. Feeding behaviour and feeding ecology of the Octocorallia (Coelenterata: Anthozoa). J. Zool. 196, 371–384 (1982).Article 

Google Scholar 
Studivan, M. S., Hatch, W. I. & Mitchelmore, C. L. Responses of the soft coral Xenia elongata following acute exposure to a chemical dispersant. SpringerPlus 4, 80 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Parrin, A. P. et al. Symbiodinium migration mitigates bleaching in three octocoral species. J. Exp. Mar. Biol. Ecol. 474, 73–80 (2016).Article 

Google Scholar 
Parrin, A. P. et al. Within-colony migration of symbionts during bleaching of octocorals. Biol. Bull. 223, 245–256 (2012).PubMed 
Article 

Google Scholar 
Bourne, D. G., Morrow, K. M. & Webster, N. S. Insights into the coral microbiome. Underpinning the health and resilience of reef ecosystems. Annu. Rev. Microbiol. 70, 317–340 (2016).CAS 
PubMed 
Article 

Google Scholar 
Furnas, M., Mitchell, A., Skuza, M. & Brodie, J. In the other 90%: phytoplankton responses to enhanced nutrient availability in the Great Barrier Reef Lagoon. Mar. Pollut. Bull. 51, 253–265 (2005).CAS 
PubMed 
Article 

Google Scholar 
Ziegler, M. et al. Coral microbial community dynamics in response to anthropogenic impacts near a major city in the central Red Sea. Mar. Pollut. Bull. https://doi.org/10.1016/j.marpolbul.2015.12.045 (2016).Article 
PubMed 

Google Scholar 
Gruber, R. et al. Marine monitoring program: Annual report for inshore water quality monitoring 2018–19. Report for the Great Barrier Reef Marine Park Authority. GBRMPA, Townsville (2020).Dinesen, Z. D. Patterns in the distribution of soft corals across the central Great Barrier Reef. Coral Reefs 1, 229–236. https://doi.org/10.1007/BF00304420 (1983).ADS 
Article 

Google Scholar 
Benayahu, Y. et al. Octocorals of the Indo-Pacific. In Mesophotic Coral Ecosystems Vol. 12 (eds Loya, Y. et al.) 709–728 (Springer International Publishing, Cham, 2019).Chapter 

Google Scholar 
Tilot, V., Leujak, W., Ormond, R. F. G., Ashworth, J. A. & Mabrouk, A. Monitoring of South Sinai coral reefs: Influence of natural and anthropogenic factors. Aquat. Conserv. 18, 1109–1126 (2008).Article 

Google Scholar 
D’Angelo, C. & Wiedenmann, J. Impacts of nutrient enrichment on coral reefs. New perspectives and implications for coastal management and reef survival. Curr. Opin. Environ. Sustain. 7, 82–93 (2014).Article 

Google Scholar 
Wooldridge, S. A. & Done, T. J. Improved water quality can ameliorate effects of climate change on corals. Ecol. Appl. 19, 1492–1499 (2009).PubMed 
Article 

Google Scholar 
Nugues, M. M. & Roberts, C. M. Partial mortality in massive reef corals as an indicator of sediment stress on coral reefs. Mar. Pollut. Bull. 46, 314–323 (2003).CAS 
PubMed 
Article 

Google Scholar 
LeGresley, M. & McDermott, G. Counting chamber methods for quantitative phytoplankton analysis – haemocytometer, Palmer-Maloney cell and Sedgewick-Rafter cell. In Microscopic and Molecular Methods for Quantitative Phytoplankton Analysis, edited by B. Karlson, C. Cusack & E. Bresnan (IOC UNESCO, Paris, France, 2010), pp. 25–30.Jeffrey, S. W. & Humphrey, G. F. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem. Physiol. Pflanz. 167, 191–194 (1975).CAS 
Article 

Google Scholar 
D’Angelo, C. et al. Blue light regulation of host pigment in reef-building corals. Mar. Ecol. Prog. Ser. 364, 97–106 (2008).ADS 
Article 

Google Scholar 
Feys, J. Nonparametric tests for the interaction in two-way factorial designs using R. R J. 8, 367 (2016).Article 

Google Scholar 
Noguchi, K., Gel, Y. R., Brunner, E. & Konietschke, F. nparLD An R software package for the nonparametric analysis of longitudinal data in factorial experiments. J. Stat. Soft. 50, 1–23 (2012).Article 

Google Scholar 
Schlöder, C. & D’Croz, L. Responses of massive and branching coral species to the combined effects of water temperature and nitrate enrichment. J. Exp. Mar. Biol. Ecol. 313, 255–268 (2004).Article 

Google Scholar 
Faxneld, S., Jörgensen, T. L. & Tedengren, M. Effects of elevated water temperature, reduced salinity and nutrient enrichment on the metabolism of the coral Turbinaria mesenterina. Estuar. Coast. Shelf Sci. 88, 482–487 (2010).ADS 
CAS 
Article 

Google Scholar 
Chumun, P. K. et al. High nitrate levels exacerbate thermal photo-physiological stress of zooxanthellae in the reef-building coral Pocillopora damicornis. Eco-Eng. 25, 1–9 (2013).
Google Scholar 
Higuchi, T., Yuyama, I. & Nakamura, T. The combined effects of nitrate with high temperature and high light intensity on coral bleaching and antioxidant enzyme activities. Reg. Stud. Mar. Sci. 2, 27–31 (2015).
Google Scholar  More

Wyatt, T. Pheromones and Animal Behavior: Communication by Smell and Taste (Cambridge University Press, 2003).Book 

Google Scholar 
Wyatt, T. D. Fifty years of pheromones. Nature 457, 262–263 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Burgener, N., Dehnhard, M., Hofer, H. & East, M. Does anal gland scent signal identity in the spotted hyena?. Anim. Behav. 77, 707–715 (2009).Article 

Google Scholar 
Kent, L. & Tang-Martínez, Z. Evidence of individual odors and individual discrimination in the raccoon, Procyon lotor. J. Mamm. 95, 1254–1262 (2014).Article 

Google Scholar 
Klücklich, M., Weiß, B. M., Birkemere, C., Einspanier, A. & Widdig, A. Chemical cues of female fertility states in a non-human primate. Sci. Rep. 9, 9–12 (2019).
Google Scholar 
Setchell, J. M. et al. Chemical composition of scent-gland secretions in an Old World monkey (Mandrillus sphinx): Influence of sex, male status, and individual identity. Chem. Sens. 35, 205–220 (2010).CAS 
Article 

Google Scholar 
Marneweck, C., Jurgens, A. & Shrader, A. M. Dung odours signal sex, age, territorial and oestrous state in white rhinos. Proc. R. Soc. B 284, 20162376 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Heth, G., Todrank, J., Busquet, N. & Baudoin, C. Genetic relatedness assessment through individual odour similarities (G-ratios) in mice. Biol. J. Lin. Soc. 78, 595–603 (2003).Article 

Google Scholar 
Heth, G., Todrank, J., Begall, S., Wegner, R. & Burda, H. Genetic relatedness discrimination in eusocial Cryptomys anselli mole-rats, Bathyergidae, Rodentia. Folia Zool. 53, 269–278 (2004).
Google Scholar 
Busquet, N. & Baudoin, C. Odour similarities as a basis for discriminating degrees of kinship in rodents: Evidence from Mus spicilegus. Anim. Behav. 70, 997–1002 (2005).Article 

Google Scholar 
Stoffel, M. A. et al. Chemical fingerprints encode mother–offspring similarity, colony membership, relatedness, and genetic quality in fur seals. PNAS 112(36), E5005–E5012 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Charpentier, M., Boulet, M. & Drea, C. Smelling right: The scent of male lemurs advertises genetic quality and relatedness. Mol. Ecol. 17, 3225–3233 (2008).CAS 
PubMed 
Article 

Google Scholar 
Boulet, M., Charpentier, M. J. E. & Drea, C. M. Decoding an olfactory mechanism of kin recognition and inbreeding avoidance in primates. BMC Evol. Biol. 9, 281 (2009).PubMed 
PubMed Central 
Article 

Google Scholar 
Kean, E. F., Bruford, M., Russo, I. R., Müller, C. & Chadwick, E. Odour dialects among wild mammals. Sci. Rep. 7, 13593 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wedekind, C., Seebeck, T., Bettens, F. & Paepke, A. J. MHC-dependent mate preferences in humans. Proc. Biol. Sci. 260, 245–249 (1995).CAS 
PubMed 
Article 

Google Scholar 
Penn, D. & Potts, W. K. Untrained mice discriminate MHC-determined odors. Phys. Behav. 64(3), 235–243 (1998).CAS 
Article 

Google Scholar 
Sun, L. & Müller-Schwarze, D. Anal gland secretion codes for family membership in beaver. Behav. Ecol. Sociobiol. 44(3), 199–208 (1998).Article 

Google Scholar 
Bloss, J., Acree, T. E., Bloss, J. M., Hood, W. R. & Kunz, T. H. Potential use of chemical cues for colony-mate recognition in the big brown bat, Eptesicus fuscus. J. Chem. Ecol. 28(4), 819–834 (2002).CAS 
PubMed 
Article 

Google Scholar 
Weiß, B. M. et al. A non-invasive method for sampling the body odour of mammals. Methods Ecol. Evol. 9, 420–429 (2018).Article 

Google Scholar 
O’Riain, M. J. & Jarvis, J. U. M. Colony member recognition and xenophobia in the naked mole-rat. Anim. Behav. 53, 487–498 (1997).Article 

Google Scholar 
Henkel, S. & Setchell, J. Group and kin recognition via olfactory cues in chimpanzees (Pan troglodytes). Proc. R. Soc. B. 285, 20181527 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Henkel, S., Lambides, A. R., Berger, A., Thomsen, R. & Widdig, A. Rhesus macaques (Macaca mulatta) recognize group membership via olfactory cues alone. Behav. Ecol. Sociobiol. 69, 2019–2034 (2015).Article 

Google Scholar 
Tzur, S., Todrank, J., Jürgens, A., Nevo, E. & Heth, G. Odour–genes covariance within a natural population of subterranean Spalax galili blind mole rats. Biol. J. Lin. Soc. 96, 483–490 (2009).Article 

Google Scholar 
Leclaire, S., Jacob, S., Greene, L. K., Dubay, G. R. & Drea, C. M. Social odours covary with bacterial community in the anal secretions of wild meerkats. Sci. Rep. 7, 1–13 (2017).CAS 
Article 

Google Scholar 
Archie, E. & Theis, K. Animal behavior meets microbial ecology. Anim. Behav. 82, 425–436 (2011).Article 

Google Scholar 
Sukumar, R. The Living Elephants: Evolutionary Ecology, Behavior and Conservation (Oxford University Press, 2003).
Google Scholar 
Jachowski, D. The Amboseli Elephants: A long-term perspective on a long-lived mammal by C. J. Moss; H. Croze; P. C. Lee. J. Mammal. 93, 294–295 (2012).Article 

Google Scholar 
Slotow, R., van Dyk, G., Poole, J., Page, B. & Klocke, A. Older bull elephants control young males. Nature 408, 425–426 (2000).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Niimura, Y., Matsui, A. & Touhara, K. Extreme expansion of the olfactory receptor gene repertoire in African elephants and evolutionary dynamics of orthologous gene groups in 13 placental mammals. Genome Res. 24, 1485–1496 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Goodwin, T. E., Broederdorf, L. J. & Burkert, B. A. Chemical signals of elephant musth: Temporal aspects of microbially-mediated modifications. J. Chem. Ecol. 38, 81–87 (2012).CAS 
PubMed 
Article 

Google Scholar 
Schulte, B. A. & Rasmussen, L. E. L. Musth, sexual selection, testosterone and metabolites. In Advances in Chemical Communication in Vertebrates (eds Johnston, R. E. et al.) 383–397 (Plenum Press, New York, 1999).
Google Scholar 
Rasmussen, L. E. L. Chemical communication: An integral part of functional Asian elephant (Elephas maximus) society. Ecoscience 5, 410–426 (1998).Article 

Google Scholar 
Rasmussen, L. E. L. & Krishnamurthy, V. How chemical signals integrate Asian elephant society: The known and the unknown. Zool. Biol. 19, 405–423 (2000).CAS 
Article 

Google Scholar 
Greenwood, D. R., Comesky, D., Hunt, M. B. & Rasmussen, L. E. L. Chirality in elephant pheromones. Nature 438, 1097–1098 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Clutton-Brock, T. H. & Huchard, E. Social competition and selection in males and females. Phil. Trans. R. Soc. 368, 20130074 (2013).CAS 
Article 

Google Scholar 
Wittemyer, G. & Getz, W. M. Hierarchical dominance structure and social organization in African elephants Loxodonta africana. Anim. Behav. 73, 671–681 (2007).Article 

Google Scholar 
Moss, C. Elephant memories (William Morrow, 1988).
Google Scholar 
Buss, I. O., Rasmussen, L. E. L. & Smuts, G. L. Role of stress and individual recognition in the function of the African elephants’ temporal gland. Mammalia 40(3), 437–451 (1976).Article 

Google Scholar 
Wittemyer, G., Douglas-Hamilton, I. & Getz, W. M. The socioecology of elephants: Analysis of the processes creating multi-tiered social structures. Anim. Behav. 69(6), 1357–1371 (2005).Article 

Google Scholar 
Bates, L. A. et al. African elephants have expectations about the locations of out-of-sight family members. Biol. Lett. 4(1), 34–36 (2008).PubMed 
Article 

Google Scholar 
Bates, L. A. et al. Elephants classify human ethnic groups by odor and garment color. Curr. Biol 17(22), 1938–1942 (2007).CAS 
PubMed 
Article 

Google Scholar 
Plotnik, J. M. et al. Elephants have a nose for quantity. PNAS 116(25), 12566–12571 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
de Silva, S., Schmid, V. & Wittemyer, G. Fission–fusion processes weaken dominance networks of female Asian elephants in a productive habitat. Behav. Ecol. https://doi.org/10.1093/beheco/arw153 (2016).Article 

Google Scholar 
Archie, E. A., Moss, C. J. & Alberts, S. C. The ties that bind: Genetic relatedness predicts the fission and fusion of social groups in wild African elephants. Proc. R. Soc. Lond. 273, 513–522 (2006).CAS 

Google Scholar 
Allen, C. R. B., Brent, L. J. N., Motsentwa, T., Weiss, M. N. & Croft, D. P. Importance of old bulls: Leaders and followers in collective movements of all-male groups in African savannah elephants (Loxodonta africana). Sci. Rep. https://doi.org/10.1038/s41598-020-70682-y (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Goodwin, T. et al. The Role of Bacteria in Chemical Signals of Elephant Musth. In Chemical Signals in Vertebrates Vol. 13 (eds Schulte, B. et al.) (Springer, 2016).
Google Scholar 
Wittemyer, G. et al. Where sociality and relatedness diverge: The genetic basis for hierarchical social organization in African elephants. Proc. Biol. Sci. 7(276), 3513–3521 (2009).
Google Scholar 
Stoeger, A. & Baotic, A. Information content and acoustic structure of male African elephant social rumbles. Sci. Rep. 6, 27585 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McComb, K., Reby, D., Baker, L., Moss, C. & Sayialel, S. Long-distance communication of social identity in African elephants. Anim. Behav. 65, 317–329 (2003).Article 

Google Scholar 
Archie, E. A. et al. Behavioural inbreeding avoidance in wild African elephants. Molec. Ecol 16, 4138–4148 (2007).CAS 
Article 

Google Scholar 
von Dürckheim, K. Olfaction and scent discrimination in African elephants. PhD thesis, Stellenbosch University, South Africa (2021).Goodwin, T. E. et al. African elephant sesquiterpenes. II. Identification and synthesis of new derivatives of 2,3-dihydrofarnesol. J. Nat. Prod. 65, 1319–1322 (2002).CAS 
PubMed 
Article 

Google Scholar 
Goodwin, T. E. et al. Chemical analysis of African elephant urine: A search for putative pheromones. In Chemical Signals in Vertebrates 10 (eds Mason, R. T. et al.) 128–139 (Springer Press, 2005).Chapter 

Google Scholar 
Goodwin, T. E. et al. Insect pheromones and precursors in female African elephant urine. J. Chem. Ecol. 32, 1849–1853 (2006).CAS 
PubMed 
Article 

Google Scholar 
Burger, B. V. Mammalian semiochemicals. In The chemistry of Pheromones and Other Semiochemicals II. Topics in Current Chemistry Vol. 240 (ed. Schulz, S.) 231–278 (Springer, 2005).
Google Scholar 
Charpentier, M. J. E., Barthes, N., Proffit, M., Bessière, J. M. & Grison, C. Critical thinking in the chemical ecology of mammalian communication: Roadmap for future studies. Funct. Ecol. 26, 769–774 (2012).Article 

Google Scholar 
Apps, P., Weldon, P. & Kramer, M. Chemical signals in terrestrial vertebrates: Search for design features. Nat. Prod. Rep. 32, 1131–1153 (2015).CAS 
PubMed 
Article 

Google Scholar 
Burgener, N., East, M., Hofer, H. & Dehnhard, M. Do spotted hyena scent marks code for clan membership? In Chemical Signals in Vertebrates XI (eds Hurst, J. L. et al.) 169–178 (Springer, 2008).Chapter 

Google Scholar 
Lukas, D. & Clutton-Brock, T. Social complexity and kinship in animal societies. Ecol. Lett. 21, 1129–1134. https://doi.org/10.1111/ele.13079 (2018).Article 
PubMed 

Google Scholar 
Meyer, J. M., Goodwin, T. E. & Schulte, B. A. Intrasexual chemical communication and social responses of captive female African elephants, Loxodonta africana. Anim. Behav. 76, 163–174 (2008).Article 

Google Scholar 
Soltis, J., Leong, K. & Savage, A. African elephant vocal communication II: Rumble variation reflects the individual identity and emotional state of callers. Anim. Behav. 70(3), 589–599 (2005).Article 

Google Scholar 
Scordato, E. S. & Drea, C. M. Scents and sensibility: Information content of olfactory signals in the ringtailed lemur, Lemur catta. Anim. Behav. 73, 301–314 (2007).Article 

Google Scholar 
Palagi, E. & Dapporto, L. Beyond odor discrimination: Demonstrating individual recognition by scent in Lemur catta. Chem. Sens. 31, 437–443 (2006).Article 

Google Scholar 
Johnston, R. E., Derzie, A., Chiang, G., Jernigan, P. & Lee, H. C. Individual scent signatures in golden hamsters: Evidence for specialization of function. Anim. Behav. 45, 1061–1070 (1993).Article 

Google Scholar 
Coffin, H., Watters, J. & Mateo, J. Odor-based recognition of familiar and related conspecifics: A first test conducted on captive Humboldt Penguins (Spheniscus humboldti). PLoS ONE 6, e25002 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Leclaire, S. et al. An individual and a sex odor signature in kittiwakes? Study of the semiochemical composition of preen secretion and preen down feathers. Naturwissenschaften 98, 615–624 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
von Dürckheim, K. et al. African elephants (Loxodonta africana) display remarkable olfactory acuity in human scent matching to sample performance. Appl. Anim. Behav. 200, 123–129 (2018).Article 

Google Scholar 
Bates, L. A., Poole, J. H. & Byrne, R. W. Elephant cognition. Curr. Biol. 18, 544–546. https://doi.org/10.1016/j.cub.2008.04.019 (2008).CAS 
Article 

Google Scholar 
Kean, E., Müller, C. & Chadwick, E. Otter scent signals age, sex, and reproductive status. Chem. Sens. 36, 555–564 (2011).CAS 
Article 

Google Scholar 
Kioko, J., Taylor, K., Milne, H. J., Hayes, K. Z. & Kiffner, C. Temporal gland secretion in African elephants (Loxodonta africana). Mamm. Biol. 82, 34–44 (2017).Article 

Google Scholar 
Macdonald, E., Fernandez-Duque, E., Sian, E. & Hagey, L. Sex, age, and family differences in the chemical composition of owl monkey (Aotus nancymaae) subcaudal scent secretions. Am. J. Primatol. 70, 12–18 (2008).CAS 
PubMed 
Article 

Google Scholar 
Zhang, J. et al. Potential chemosignals in the anogenital gland secretion of giant pandas, Ailuropoda melanoleuca, associated with sex and individual identity. J. Chem. Ecol. 34, 398–407 (2008).CAS 
PubMed 
Article 

Google Scholar 
Theis, K. R. et al. Symbiotic bacteria appear to mediate hyena social odors. Proc. Natl. Acad. Sci. 110(49), 19832–19837 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Merritt, G. C., Goodrich, B. S., Hesterman, E. R. & Myktowycz, R. Microflora and volatile fatty acids present in the inguinal pouches of the wild rabbit, Oryctolagus cuniculus in Australia. J. Chem. Ecol. 8, 217–1225 (1982).Article 

Google Scholar 
Müller-Schwarze, D. & Heckman, S. The social role of scent in beaver (Castor canadensis). J. Chem. Ecol. 6, 81–95 (1980).Article 

Google Scholar 
Albone, E. S., Eglinton, G., Walker, J. M. & Ware, G. C. Anal sac secretion of red fox (Vulpes vulpes), its chemistry and microbiology: Comparison with anal sac secretion of lion (Panthera leo). Life Sci. 14, 387–400 (1974).CAS 
PubMed 
Article 

Google Scholar 
Gorman, M. L. A mechanism for individual recognition by odour in Herpestes auropunctatus (Carnivora: Viverridae). Anim. Behav. 24, 141–145 (1976).Article 

Google Scholar 
Theis, K. R., Schmidt, M. S. & Holekamp, K. E. Evidence for a bacterial mechanism for group-specific social odors among hyenas. Sci. Rep. 2, 615 (2012).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Theis, K. R., Heckla, A. L., Verge, J. R. & Holekamp, K. E. The ontogeny of pasting behavior in free-living spotted hyenas, Crocuta crocuta. In Chemical Signals in Vertebrates Vol. 11 (eds Hurst, J. L. et al.) 179–188 (Springer, 2008).
Google Scholar 
Chiyo, P. I. et al. The influence of social structure, habitat, and host traits on the transmission of Escherichia coli in wild elephants. PLoS ONE 9(4), e93408 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Archie, E. A., Moss, C. J. & Alberts, S. C. Characterization of tetranucleotide microsatellite loci in the African Savannah elephant (Loxodonta africana africana). Mol. Ecol. Notes. 3, 244–246 (2003).CAS 
Article 

Google Scholar 
Comstock, K. E., Wasser, S. K. & Ostrander, E. A. Polymorphic microsatellite DNA loci identified in the African elephant (Loxodonta africana). Mol. Ecol. 9, 1004–1006 (2000).CAS 
PubMed 
Article 

Google Scholar 
Eggert, L. S., Eggert, J. A. & Woodruff, D. S. Estimating population sizes for elusive animals: The forest elephants of Kakum National Park, Ghana. Mol. Ecol. 12, 1389–1402 (2003).CAS 
PubMed 
Article 

Google Scholar 
Toonen, R. J. & Hughes, S. Increased throughput for fragment analysis on an ABI PRISM 377 automated sequencer using a membrane comb and STRand software. Biotechniques 6, 1320–1324 (2001).
Google Scholar 
Belkhir, K., Castric, V. & Bonhomme, F. IDENTIX, a software to test for relatedness in a population using permutation methods. Mol. Ecol. Notes 2, 611–614 (2002).Article 

Google Scholar 
Queller, D. & Goodnight, K. Estimating relatedness using genetic markers. Evolution 43(2), 258–275 (1989).PubMed 
Article 

Google Scholar 
Marshall, T. C., Slate, J., Kruuk, L. E. B. & Pemberton, J. M. Statistical confidence for likelihood-based paternity inference in natural populations. Mol. Ecol. 7, 639–655 (1998).CAS 
PubMed 
Article 

Google Scholar 
Ottensmann, M., Stoffel, M. A., Nichols, H. J. & Hoffman, J. I. GCalignR: An R Package for aligning gas-chromatography data for ecological and evolutionary studies. PLoS ONE 13(6), e0198311 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Morelli, T. et al. Relatedness communicated in lemur scent. Naturwissenschaften 100, 769–777 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Oksanen, J., Blanchet, F., Guillaume. F., Kindt, R., Legendre, P., Minchin, P., O’Hara, R.B., Simpson, G., Solymos, P., Stevens, M.H.H., Wagner, H. Vegan: community ecology package. R package vegan, vers. 2.2-1. (2015). More

Abram, D. The spell of the sensuous: Perception and language in a more-than-human world. Vintage (2012).Ingold, T. Being alive: Essays on movement, knowledge and description. Routledgehttps://doi.org/10.4324/9780203818336 (2011).Article 

Google Scholar 
Kimmerer, R.W. Braiding sweetgrass: Indigenous wisdom, scientific knowledge and the teachings of plants (Milkweed editions, 2013).Tucker, M. A. et al. Moving in the Anthropocene: Global reductions in terrestrial mammalian movements. Science 359(6374), 466–469 (2018).ADS 
CAS 
Article 

Google Scholar 
Gibbs, J.P. Amphibian movements in response to forest edges, roads, and streambeds in southern New England. in The Journal of Wildlife Management (1998), pp. 584–589. https://doi.org/10.2307/3802333.Moller, H., Berkes, F., O’Brian Lyver, P., & Kislalioglu, M. Combining science and traditional ecological knowledge: Monitoring populations for co-management. in Ecology and society (2004).Lorimer, J. Wildlife in the Anthropocene: conservation after nature. (U of Minnesota Press, 2015).Wiens, J. A. Spatial scaling in ecology. Funct. Ecol. 3(4), 385–397 (1989).Article 

Google Scholar 
Abram, D. Becoming animal: An earthly cosmology. Vintage (2010).Nathan, R. et al. A movement ecology paradigm for unifying organismal movement research. Proc. Natl. Acad. Sci. 105(49), 19052–19059 (2008).ADS 
CAS 
Article 

Google Scholar 
Tischendorf, L. & Fahrig, L. On the usage and measurement of landscape connectivity. Oikos 90(1), 7–19. https://doi.org/10.1034/j.1600-0706.2000.900102.x (2000).Article 

Google Scholar 
Rudnick, D., Ryan, S.J., Beier, P., Cushman, S.A., Dieffenbach, F., Epps, C., Gerber, L.R., Hartter, J.N., Jenness, J.S., & Kintsch, J. et al. The role of landscape connectivity in planning and implementing conservation and restoration priorities. Issues in Ecology (2012).Hilty, J.A., Lidicker, W.Z., & Merenlender, A.M. Corridor Ecology: The Science and Practice of Linking Landscapes for Biodiversity Conservation (Island Press, 2012).Cushman, S.A., McRae, B.H., Adriaensen, F., Beier, P., Shirley, M., & Zeller, K. Biological corridors and connectivity [Chapter 21]. in Key Topics in Conservation Biology 2nd ed. (eds Macdonald, D.W., Willis, K.J.) pp. 384–404 (Hoboken, NJ: Wiley-Blackwell, 2013).Unnithan Kumar, S., Turnbull, J., Hartman Davies, O., Hodgetts, T., & Cushman, S.A. Moving beyond landscape resistance: Considerations for the future of connectivity modelling and conservation science. in Landscape Ecology (2022).Zeller, K. A., McGarigal, K. & Whiteley, A. R. Estimating landscape resistance to movement: a review. Landscape Ecol. 27(6), 777–797 (2012).Article 

Google Scholar 
Adriaensen, F. et al. The application of ‘least-cost’ modelling as a functional landscape model. Landsc. Urban Plan. 64(4), 233–247 (2003).Article 

Google Scholar 
Cushman, S. A. & McKelvey, K. S. Use of empirically derived source-destination models to map regional conservation corridors. Conserv. Biol. 23(2), 368–376. https://doi.org/10.1111/j.1523-1739.2008.01111.x (2009).Article 
PubMed 

Google Scholar 
Moilanen, A. On the limitations of graph-theoretic connectivity in spatial ecology and conservation. J. Appl. Ecol. pp. 1543–1547 (2011).Compton, B. W., McGarigal, K., Cushman, S. A. & Gamble, L. R. A resistant kernel model of connectivity for amphibians that breed in vernal pools. Conserv. Biol. 21(3), 788–799. https://doi.org/10.1111/j.1523-1739.2007.00674.x (2007).Article 
PubMed 

Google Scholar 
McRae, B. H., Dickson, B. G., Keitt, T. H. & Shah, V. B. Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89(10), 2712–2724. https://doi.org/10.1890/07-1861.1. (2008).Article 
PubMed 

Google Scholar 
Zeller, K. A. et al. Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data. Divers. Distrib. 24(7), 868–879. https://doi.org/10.1111/ddi.12742. (2018).Article 

Google Scholar 
Pullinger, M. G. & Johnson, C. J. Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information. Landscape Ecol. 25(10), 1547–1560 (2010).Article 

Google Scholar 
Sawyer, S. C., Clinton, W. E. & Brashares, J. S. Placing linkages among fragmented habitats: do least-cost models reflect how animals use landscapes?. J. Appl. Ecol. 48(3), 668–678 (2011).Article 

Google Scholar 
Laliberté, J. & St-Laurent, M.-H. Validation of functional connectivity modeling: The Achilles’ heel of landscape connectivity mapping. Landsc. Urban Plan. 202, 103878 (2020).Article 

Google Scholar 
Landguth, E. L. & Cushman, S. A. CDPOP: A spatially explicit cost distance popula tion genetics program. Mol. Ecol. Resour. 10(1), 156–161. https://doi.org/10.1111/j.1755-0998.2009.02719.x. (2010).CAS 
Article 
PubMed 

Google Scholar 
Landguth, E. L. et al. Quantifying the lag time to detect barriers in landscape genetics. Mol. Ecol. 19(19), 4179–4191. https://doi.org/10.1111/j.1365-294X.2010.04808.x (2010).CAS 
Article 
PubMed 

Google Scholar 
Cushman, S. A. & Landguth, E. L. Scale dependent inference in landscape genetics. Landsc. Ecol. 25(6), 967–979 (2010).Article 

Google Scholar 
Cushman, S. A., Shirk, A. J. & Landguth, E. L. Separating the effects of habitat area, fragmentation and matrix resistance on genetic differentiation in complex landscapes. Landscape Ecol. 27(3), 369–380. https://doi.org/10.1007/s10980-011-9693-0 (2012).Article 

Google Scholar 
Macdonald, E. A. et al. Simulating impacts of rapid forest loss on population size, connectivity and genetic diversity of Sunda clouded leopards (Neofelis diardi) in Borneo. PLoS ONE 13(9), e0196974 (2018).Article 

Google Scholar 
Schumaker, N. H. et al. Mapping sources, sinks, and connectivity using a simulation model of northern spotted owls. Landscape Ecol. 29(4), 579–592 (2014).Article 

Google Scholar 
Unnithan Kumar, S., Kaszta, Ż & Cushman, S. A. Pathwalker: A new individual-based movement model for conservation science and connectivity modelling. ISPRS Int. J. Geo Inf. 11(6), 329 (2022).Article 

Google Scholar 
Virtanen, P. et al. SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nat. Methods 17(3), 261–272 (2020).CAS 
Article 

Google Scholar 
Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14(6), 927–930 (2003).Article 

Google Scholar 
Dray, S., Royer-Carenzi, M. & Calenge, C. The exploratory analysis of autocorrelation in animal-movement studies. Ecol. Res. 25(3), 673–681. https://doi.org/10.1007/s11284-010-0701-7 (2010).Article 

Google Scholar 
Cushman, S.A. Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis. in Spatial Complexity, Informatics, and Wildlife Conservation (Springer, 2010), pp. 131-149.Zeller, K. A. et al. Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: pumas as a case study. Landscape Ecol. 29(3), 541–557 (2014).Article 

Google Scholar 
Kareiva, P. M. & Shigesada, N. Analyzing insect movement as a correlated random walk. Oecologia 56(2), 234–238 (1983).ADS 
CAS 
Article 

Google Scholar 
Schumaker, N.H. Using landscape indices to predict habitat connectivity. Ecology (1996), pp. 1210–1225.Schumaker, N. H. & Brookes, A. HexSim: A modeling environment for ecology and conservation. Landscape Ecol. 33(2), 197–211 (2018).Article 

Google Scholar 
Bocedi, G., Palmer, S. C. F., Malchow, A.-K., Zurell, D. & Watts, K. RangeShifter 2.0: An extended and enhanced platform for modelling spatial eco-evolutionary dynamics and species’ responses to environmental changes. Ecography 44(10), 1453–1462 (2021).Article 

Google Scholar 
Kaszta, Ż, Cushman, S. A. & Slotow, R. Temporal non-stationarity of path- selection movement models and connectivity: An example of African elephants in Kruger national park. Front. Ecol. Evol. 9, 207 (2021).Article 

Google Scholar 
Osipova, L. et al. Using step-selection functions to model landscape connectivity for African elephants: Accounting for variability across individuals and seasons. Anim. Conserv. 22(1), 35–48 (2019).Article 

Google Scholar 
Vergara, M., Cushman, S. A. & Ruiz-González, A. Ecological differences and limiting factors in different regional contexts: landscape genetics of the stone marten in the Iberian Peninsula. Landscape Ecol. 32(6), 1269–1283 (2017).Article 

Google Scholar 
Reddy, P. A., Puyravaud, J.-P., Cushman, S. A. & Segu, H. Spatial variation in the response of tiger gene ow to landscape features and limiting factors. Anim. Conserv. 22(5), 472–480 (2019).Article 

Google Scholar 
Zeller, K. A., Lewsion, R., Fletcher, R. J., Tulbure, M. G. & Jennings, M. K. Understanding the importance of dynamic landscape connectivity. Land 9(9), 303. https://doi.org/10.3390/land9090303 (2020).Article 

Google Scholar 
Cronon, W. The trouble with wilderness: or, getting back to the wrong nature. Environ. Hist. 1(1), 7–28 (1996).Article 

Google Scholar 
Ingold, T. The Perception of the Environment: Essays on Livelihood, Dwelling and Skill (Routledge, 2021).Boettiger, A. N. et al. Inferring ecological and behavioral drivers of African elephant movement using a linear filtering approach. Ecology 92(8), 1648–1657 (2011).Article 

Google Scholar 
Pooley, S. et al. An interdisciplinary review of current and future approaches to improving human-predator relations. Conserv. Biol. 31(3), 513–523. https://doi.org/10.1111/cobi.12859 (2017).CAS 
Article 
PubMed 

Google Scholar 
Benson, E. S. Minimal animal: Surveillance, simulation, and stochasticity in wildlife biology. Antennae 30, 39 (2014).
Google Scholar 
Kaszta, Ż et al. Integrating Sunda clouded leopard (Neofelis diardi) conservation into development and restoration planning in Sabah (Borneo). Biol. Cons. 235, 63–76 (2019).Article 

Google Scholar 
Penjor, U., Astaras, C., Cushman, S. A., Kaszta, Ż & Macdonald, D. W. Contrasting effects of human settlement on the interaction among sympatric apex carnivores. Proc. R. Soc. B 289(1973), 20212681 (2022).Article 

Google Scholar 
Barua, M. Bio-geo-graphy: Landscape, dwelling, and the political ecology of human-elephant relations. Environ. Plann. D Soc. Space 32(5), 915–934 (2014).Article 

Google Scholar 
Elliot, N. B., Cushman, S. A., Macdonald, D. W. & Loveridge, A. J. The devil is in the dispersers: Predictions of landscape connectivity change with demography. J. Appl. Ecol. 51(5), 1169–1178 (2014).Article 

Google Scholar 
Kareiva, P. & Marvier, M. What is conservation science?. Bioscience 62(11), 962–969 (2012).Article 

Google Scholar 
Bennett, N. J. et al. Conservation social science: Understanding and integrating human dimensions to improve conservation. Biol. Conserv. 205, 93–108 (2017).Article 

Google Scholar 
Bunnefeld, N., Nicholson, E., & Milner-Gulland, E.J. Decision-Making in Conservation and Natural Resource Management: Models for Interdisciplinary Approaches. (Vol. 22, Cambridge University Press, 2017).Parathian, H. E., McLennan, M. R., Hill, C. M., Fraza o-Moreira, A. & Hockings, K. J. Breaking through disciplinary barriers: Human-wildlife interactions and multispecies ethnography. Int. J. Primatol. 39(5), 749–775 (2018).Article 

Google Scholar 
Hodgetts, T. Connectivity as a multiple: In with and as “nature’’. Area 50(1), 83–90. https://doi.org/10.1111/area.12353 (2018).Article 
PubMed 

Google Scholar 
Berkes, F. Sacred ecology (Routledge, 2017). https://doi.org/10.4324/9781315114644.Parrenas, J.S. Decolonizing Extinction: The Work of Care in Orangutan Rehabilitation (Duke University Press, 2018).Bill Adams, W., & Mulligan, M. Decolonizing Nature: Strategies for Conservation in a Post-Colonial Era (Routledge, 2012). More