Ecology

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.This is a summary of: Sauterey, B. et al. Early Mars habitability and global cooling by H2-based methanogens. Nat. Astron. https://doi.org/10.1038/s41550-022-01786-w (2022). More

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To our knowledge, this is the only work done on the terrestrial biodiversity status in the direct vicinity of a limited duration volcanic eruption. In this contribution, we document and assess the impact on the main plant and animal groups within the ecosystems during a volcanic eruption (Table 1). While some groups were clearly disadvantaged: ferns and herbaceous plants as well as invertebrates and saurians (lizards and geckos); other groups such as conifers and woody shrubs showed better resilience, as did the birds.This study is particularly important because of its location in a Mediterranean biodiversity hotspot13,14, harbouring a unique ecosystem of oceanic island organisms (38% of the Canary archipelago endemicity). Islands indeed exhibit a disproportionate amount of the world’s biodiversity but unfortunately a high number of extinctions have also occurred there14. The biodiversity in the south of the island is poorer than in the north. This is probably explained in part by the relatively frequent volcanic activity featuring seven major eruptions since 1585, including this one in 2021 (see15), which led to alternating destruction and neo-colonization processes.Concerning the flora, the Canary pine forest was the most affected ecosystem and vegetation type, as it is dominant in the vicinity of the new volcanic vents. The southern slopes of this forest were the most disturbed area due to the location of the volcano, combined with the prevailing northeasterly trade winds (Fig. 1). Tephra fallout and sulphurous gases were the main factors that affected the pine forest, over a vast surface area. Furthermore, the local xerophytic and thermophilous habitats also lost much of their surface area. In contrast to the pine forest, this drastic reduction was caused by the progressive downslope expansion of the lava flows.The Canary Island pine was thus notably affected by tephra fall, sulphuric acid aerosol12, and short episodes of acid rain. However, this conifer shows high resistance to temperature, confirming its great adaptation to volcanic events16, which is probably also one of the keys to its resistance to the more frequent present-day wildfires17. This pine species has evolved among volcanoes for the last 13 My16 and has adapted successfully to high temperatures. Moreover, thunderstorms with lightning occur in the Canaries together with abundant rainfall; consequently, wild forest fires should presumably not have been so frequent in the island’s past, before human colonization. In this habitat it is also remarkable that epiphytic lichens (U. articulata) apparently resisted on the pines until the 12th week, considering their high sensitivity to anthropogenic pollution18.The life cycle of flowering plants was drastically disrupted due to all the above factors, with great impact on foliage, photosynthesis, and growth. However, soil changes due to the deposition of tephra and its lixiviation by rain is one of the most dramatic factors affecting plants and a long-term impact of volcanic eruptions19. The nearest individuals to the crater were most directly affected by intense tephra falls and concentrated volcanic gases (SO2, HCl, HF, CO2). However, plants located in the nearest 200 m to the lava flows but at more than 2 km from the crater were presumably more disturbed by the high temperature of the slow-cooling lava and its lesser gas emissions.Large woody plants exhibited a better frequency of survival than smaller ones in the face of this extreme stress (Table S1 and19). In the Hekla area (Iceland), most trees have thickened trunks, indicating that those trees that survive have had a long life subjected to frequent volcanic damage19. Secondary woodiness of island plants (sensu20) has been traditionally related to drought20,21, ecological shift22 or a counter-selection of inbreeding depression in founding island populations23. However, this adaptation also favours the resistance of many shrubby plants to high temperatures close to craters and lava flows but primarily their resistance to the intense tephra falls that affect a much larger area. In addition, plant and stem height plays a fundamental role in overcoming the deep layers of deposits. This latter effect was particularly important up to 2.5 km from the crater (tephra thickness  > 30 cm) (Figs. 1 and 2), as the herbaceous plants were completely buried, sometimes to more than 1.5 m depth. Therefore, the seed bank has also probably been rendered largely non-functional. However, deposits were recorded over almost the whole island, indicating that longer lasting or more intense eruptions would severely affect an even larger area. Such events have been hitherto ignored in the intensely discussed “island woodiness” debate21,23,24,25,26,27. We found surviving populations of endemic woody taxa heavily impacted by tephra deposits close to lava flows, across a wide range of genera such as Rumex (R. lunaria), Echium (E. brevirame), Euphorbia (E. lamarckii, E. canariensis and E. balsamifera), Aeonium (A. davidbramwellii), Rubia (R. fruticosa), Schizogyne (S. sericea), Carlina (C. falcata) or Sonchus (S. hierrensis) (Table S2), which coincide with the general list of woody Canary plants20. Most members of these genera in other ecosystems on continents are mainly herbaceous. As such eruptions and their impacts due to ash depositions are frequent events on volcanic islands, e.g. several times within a century on La Palma, this is a “frequent” selective process at evolutionary time scales.With regard to the fauna, the invertebrate community collapsed during the first two weeks (Table S2), probably due to rapid deterioration of the growth state of plants. These changes in the invertebrates were caused by the tephra contacting the cuticular lipid layer28 and water loss due to tegument abrasion29. In this period, many insect pests (especially whitefly pupae) in banana plantations (farmers’ observations) were drastically reduced. This sudden decrease in insect populations affected the whole food web and probably caused part of the ecological collapse of saurian and some passerine communities30. In the case of lizards, smaller individuals seem to resist the adverse conditions better than large ones, as observed in other eruptions3. This could be linked to their lower food requirements and greater ease in finding refuges. Loss of body condition in lizards post-eruption has been recorded and negatively affects reproduction quality31. However, some lizards have shown a good ability to find food in the tephra substrate32. We found abundant tephra particles in some vertebrate droppings (lizards, birds, and mammals) during the eruption, probably involuntarily ingested. At least in bats, ingestion during feeding produces physiological stress that is likely related to baldness, high ectoparasite loads or possible mineral deficiencies33.As described in the Canary Islands, some passerines show high fidelity to their territories (see34). During the eruption, Sardinian warblers (Curruca melanocephala) maintained their territories until the imminent arrival of lava flows. Larger birds (kestrels F. tinnunculus, ravens C. corax and buzzards B. buteo) were well able to continue flying in the areas surrounding the crater. Furthermore, some cases like F. tinnunculus showed great feeding plasticity in the first couple of weeks. At least six times, kestrels tried to catch birds (especially small passerines and doves), contrary to their usual diet based on abundant lizards and insects35. Widening of trophic niches in island organisms has traditionally been interpreted as linked to disharmony in island ecosystems36,37,38. However, this plasticity is tremendously beneficial in ecological catastrophes, where food becomes exceptionally scarce. In the case of bats, their flight is limited by the delicate structure of their patagium, which can be damaged by the frequent pyroclastic tephra fall. Furthermore, scarcity of insects in the first few kilometres from the crater probably led to their displacement to other more distant and richer food resource zones.As we learned from the movement capacity of the vertebrate animals that still inhabited the affected area, those with greater mobility, birds and bats, resisted the eruptive process much better than those with less mobility, e.g. saurians.Lastly, during this destructive event on La Palma, we had the opportunity to increase our knowledge of how ecological-evolutionary adaptations have favoured the survival of insular organisms. Such responses are traditionally mentioned in the context of island biology. As already mentioned, one of the most interesting findings verifies the remarkable adaptation of Canary Island pine trees (P. canariensis) to volcanism (see16), including extremely harsh ecological conditions. Other insular trends related to the prevalence of woodiness in insular flowering plants20,21, or the high trophic plasticity of some vertebrates on oceanic islands36, have not previously been associated with their potential evolution along with volcanic processes. However, such evolutionary adaptations most likely played an important role in the survival of plants and animals affected by the volcano. For this reason, it is worth considering and debating whether these previously mentioned evolutionary processes are in fact also linked to repeated volcanic episodes on oceanic islands. More

Precht, W. F., Gintert, B. E., Robbart, M. L., Fura, R. & van Woesik, R. Unprecedented disease-related coral mortality in Southeastern Florida. Sci. Rep. 6, 31374 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
NOAA. Stony Coral Tissue Loss Disease Case Definition. NOAA, Silver Spring, MD 10 (2018).Aeby, G. S. et al. Pathogenesis of a tissue loss disease affecting multiple species of corals along the Florida Reef Tract. Front Mar. Sci. 6, 00678 (2019).
Google Scholar 
Landsberg, J. H. et al. Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology. Front Mar. Sci. 7, 576013 (2020).
Google Scholar 
Neely, K. L., Macaulay, K. A., Hower, E. K. & Dobler, M. A. Effectiveness of topical antibiotics in treating corals affected by Stony Coral Tissue Loss Disease. PeerJ 8, 9289 (2020).
Google Scholar 
Shilling, E. N., Combs, I. R. & Voss, J. D. Assessing the effectiveness of two intervention methods for stony coral tissue loss disease on Montastraea cavernosa. Sci. Rep. 11, 8566 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Walker, B. K., Turner, N. R., Noren, H. K. G., Buckley, S. F. & Pitts, K. A. Optimizing stony coral tissue loss disease (SCTLD) intervention treatments on Montastraea cavernosa in an endemic zone. Front Mar. Sci. 8, 666224 (2021).
Google Scholar 
Work, T. M. et al. Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease. Front Mar. Sci. 8, 750658 (2021).
Google Scholar 
Veglia, A. J. et al. Alphaflexivirus genomes in stony coral tissue loss disease-affected, disease-exposed, and disease-unexposed coral colonies in the U.S. Virgin Islands. Microbiol. Resource Announc. 11, e01199-e1221 (2022).CAS 

Google Scholar 
Rosales, S. M. et al. Bacterial metabolic potential and micro-eukaryotes enriched in stony coral tissue loss disease lesions. Front Mar. Sci. 8, 776859 (2022).
Google Scholar 
Rosales, S. M., Clark, A. S., Huebner, L. K., Ruzicka, R. R. & Muller, E. M. Rhodobacterales and Rhizobiales are associated with stony coral tissue loss disease and its suspected sources of transmission. Front. Microbiol. 11, 681 (2020).PubMed 
PubMed Central 

Google Scholar 
Studivan, M. S. et al. Reef sediments can act as a stony coral tissue loss disease vector. Front Mar. Sci. 8, 815698 (2022).
Google Scholar 
Meyer, J. L. et al. Microbial community shifts associated with the ongoing stony coral tissue loss disease outbreak on the Florida Reef Tract. Front. Microbiol. 10, 2244 (2019).PubMed 
PubMed Central 

Google Scholar 
Ushijima, B. et al. Disease diagnostics and potential coinfections by Vibrio coralliilyticus during an ongoing coral disease outbreak in Florida. Front. Microbiol. 11, 2682 (2020).
Google Scholar 
Meiling, S. S. et al. Variable species responses to experimental stony coral tissue loss disease (SCTLD) exposure. Front Mar. Sci. 8, 670829 (2021).
Google Scholar 
Becker, C. C., Brandt, M., Miller, C. A. & Apprill, A. Microbial bioindicators of stony coral tissue loss disease identified in corals and overlying waters using a rapid field-based sequencing approach. Environ. Microbiol. 24, 1166–1182 (2021).PubMed 

Google Scholar 
Dobbelaere, T., Muller, E. M., Gramer, L. J., Holstein, D. M. & Hanert, E. Coupled epidemio-hydrodynamic modeling to understand the spread of a deadly coral disease in Florida. Front Mar. Sci. 7, 591881 (2020).
Google Scholar 
Dobbelaere, T. et al. Connecting the dots: Transmission of stony coral tissue loss disease from the Marquesas to the Dry Tortugas. Front Mar. Sci. 9, 778938 (2022).
Google Scholar 
Muller, E. M., Sartor, C., Alcaraz, N. I. & van Woesik, R. Spatial epidemiology of the stony-coral-tissue-loss disease in Florida. Front Mar. Sci. 7, 00163 (2020).
Google Scholar 
Sharp, W. C., Shea, C. P., Maxwell, K. E., Muller, E. M. & Hunt, J. H. Evaluating the small-scale epidemiology of the stony-coral-tissue-loss-disease in the middle Florida Keys. PLoS ONE 15, e0241871 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Williamson, O. M., Dennison, C. E., O’Neil, K. L. & Baker, A. C. Susceptibility of Caribbean brain coral recruits to stony coral tissue loss disease (SCTLD). Front Mar. Sci. 9, 821165 (2022).
Google Scholar 
Noonan, K. R. & Childress, M. J. Association of butterflyfishes and stony coral tissue loss disease in the Florida Keys. Coral Reefs 39, 1581–1590 (2020).
Google Scholar 
Dahlgren, C., Pizarro, V., Sherman, K., Greene, W. & Oliver, J. Spatial and temporal patterns of stony coral tissue loss disease outbreaks in the Bahamas. Front Mar. Sci. 8, 682114 (2021).
Google Scholar 
Rosenau, N. A. et al. Considering commercial vessels as potential vectors of stony coral tissue loss disease. Front Mar. Sci. 8, 709764 (2021).
Google Scholar 
Roth, L., Kramer, P., Doyle, E. & O’Sullivan, C. Caribbean SCTLD Dashboard. Available www.agrra.org. Accessed 06 Mar 2021. (2020).Brandt, M. E. et al. The emergence and initial impact of stony coral tissue loss disease (SCTLD) in the United States Virgin Islands. Front Mar. Sci. 8, 715329 (2021).
Google Scholar 
Bailey, S. A. et al. Trends in the detection of aquatic non-indigenous species across global marine, estuarine and freshwater ecosystems: A 50-year perspective. Divers. Distrib. 26, 1780–1797 (2020).MathSciNet 

Google Scholar 
Hewitt, C. L., Gollasch, S. & Minchin, D. The vessel as a vector: Biofouling, ballast water and sediments. In Biological Invasions in Marine Ecosystems Vol. 204 (eds Rilov, G. & Crooks, J. A.) 117–131 (Springer, 2009).
Google Scholar 
Zabin, C. J. et al. Small boats provide connectivity for nonindigenous marine species between a highly invaded international port and nearby coastal harbors. Manag. Biol. Invas. 5, 97–112 (2014).
Google Scholar 
Ashton, G. V., Zabin, C. J., Davidson, I. C. & Ruiz, G. M. Recreational boats routinely transfer organisms and promote marine bioinvasions. Biol. Invas. 24, 1083–1096 (2022).
Google Scholar 
Drake, L. A., Doblin, M. A. & Dobbs, F. C. Potential microbial bioinvasions via ships’ ballast water, sediment, and biofilm. Mar. Pollut. Bull. 55, 333–341 (2007).CAS 
PubMed 

Google Scholar 
Pagenkopp Lohan, K. M., Fleischer, R. C., Carney, K. J., Holzer, K. K. & Ruiz, G. M. Amplicon-based pyrosequencing reveals high diversity of protistan parasites in ships’ ballast water: Implications for biogeography and infectious diseases. Microb. Ecol. 71, 530–542 (2015).PubMed 

Google Scholar 
Ruiz, G. M. et al. Global spread of microorganisms by ships. Nature 408, 49–50 (2000).ADS 
CAS 
PubMed 

Google Scholar 
Hwang, J., Park, S. Y., Lee, S. & Lee, T. K. High diversity and potential translocation of DNA viruses in ballast water. Mar. Pollut. Bull. 137, 449–455 (2018).CAS 
PubMed 

Google Scholar 
Shikuma, N. J. & Hadfield, M. G. Marine biofilms on submerged surfaces are a reservoir for Escherichia coli and Vibrio cholerae. Biofouling 26, 39–46 (2009).
Google Scholar 
Aguirre-Macedo, M. L. et al. Ballast water as a vector of coral pathogens in the Gulf of Mexico: The case of the Cayo Arcas coral reef. Mar. Pollut. Bull. 56, 1570–1577 (2008).CAS 
PubMed 

Google Scholar 
Bruno, J. F. The coral disease triangle. Nat. Clim. Chang. 5, 302–303 (2015).ADS 

Google Scholar 
Lakshmi, E., Priya, M. & Achari, V. S. An overview on the treatment of ballast water in ships. Ocean Coast. Manag. 199, 105296 (2021).
Google Scholar 
Petersen, N. B., Madsen, T., Glaring, M. A., Dobbs, F. C. & Jørgensen, N. O. G. Ballast water treatment and bacteria: Analysis of bacterial activity and diversity after treatment of simulated ballast water by electrochlorination and UV exposure. Sci. Total Environ. 648, 408–421 (2019).ADS 
CAS 
PubMed 

Google Scholar 
Romero-Martínez, L., Moreno-Andrés, J., Acevedo-Merino, A. & Nebot, E. Evaluation of ultraviolet disinfection of microalgae by growth modeling: Application to ballast water treatment. J. Appl. Phycol. 28, 2831–2842 (2016).
Google Scholar 
First, M. R. et al. Stratification of living organisms in ballast tanks: How do organism concentrations vary as ballast water is discharged?. Environ. Sci. Technol. 47, 4442–4448 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Drake, L. A. et al. Microbial ecology of ballast water during a transoceanic voyage and the effects of open-ocean exchange. Mar. Ecol. Prog. Ser. 233, 13–20 (2002).ADS 

Google Scholar 
Khandeparker, L., Kuchi, N., Desai, D. V. & Anil, A. C. Changes in the ballast water tank bacterial community during a trans-sea voyage: Elucidation through next generation DNA sequencing. J. Environ. Manag. 273, 111018 (2020).
Google Scholar 
Ruiz, G. M., Lorda, J., Arnwine, A. & Lion, K. Shipping patterns associated with the Panama Canal: Effects on biotic exchange? In Bridging Divides Vol. 83 (eds Gollasch, S. et al.) 113–126 (Springer, 2006).
Google Scholar 
Pagano, A., Wang, G., Sánchez, O., Ungo, R. & Tapiero, E. The impact of the Panama Canal expansion on Panama’s maritime cluster. Marit. Policy Manag. 43, 164–178 (2016).
Google Scholar 
Muirhead, J. R., Minton, M. S., Miller, W. A. & Ruiz, G. M. Projected effects of the Panama Canal expansion on shipping traffic and biological invasions. Divers. Distrib. 21, 75–87 (2015).
Google Scholar 
Ros, M. et al. The Panama Canal and the transoceanic dispersal of marine invertebrates: Evaluation of the introduced amphipod Paracaprella pusilla Mayer, 1890 in the Pacific Ocean. Mar. Environ. Res. 99, 204–211 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Stehouwer, P. P., Buma, A. & Peperzak, L. A comparison of six different ballast water treatment systems based on UV radiation, electrochlorination and chlorine dioxide. Environ. Technol. 36, 2094–2104 (2015).CAS 
PubMed 

Google Scholar 
Wu, Y., Li, Z., Du, W. & Gao, K. Physiological response of marine centric diatoms to ultraviolet radiation, with special reference to cell size. J. Photochem. Photobiol., B 153, 1–6 (2015).CAS 

Google Scholar 
Aguirre, L. E. et al. Diatom frustules protect DNA from ultraviolet light. Sci. Rep. 8, 5138 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
First, M. R. & Drake, L. A. Life after treatment: Detecting living microorganisms following exposure to UV light and chlorine dioxide. J. Appl. Phycol. 26, 227–235 (2014).CAS 

Google Scholar 
Liebich, V., Stehouwer, P. P. & Veldhuis, M. Re-growth of potential invasive phytoplankton following UV-based ballast water treatment. Aquat. Invas. 7, 29–36 (2012).
Google Scholar 
Hess-Erga, O. K., Moreno-Andrés, J., Enger, Ø. & Vadstein, O. Microorganisms in ballast water: Disinfection, community dynamics, and implications for management. Sci. Total Environ. 657, 704–716 (2019).ADS 
CAS 
PubMed 

Google Scholar 
Endresen, Ø., Lee Behrens, H., Brynestad, S., Bjørn Andersen, A. & Skjong, R. Challenges in global ballast water management. Mar. Pollut. Bull. 48, 615–623 (2004).CAS 
PubMed 

Google Scholar 
Vorkapić, A., Radonja, R. & Zec, D. Cost efficiency of ballast water treatment systems based on ultraviolet irradiation and electrochlorination. Promet Traffic Transp. 30, 343–348 (2018).
Google Scholar 
King, D., Hagan, P., Riggio, M. & Wright, D. Preview of global ballast water treatment markets. J. Mar. Eng. Technol. 11, 3–15 (2012).
Google Scholar 
Wang, Z., Saebi, M., Corbett, J. J., Grey, E. K. & Curasi, S. R. Integrated biological risk and cost model analysis supports a geopolitical shift in ballast water management. Environ. Sci. Technol. 55, 12791–12800 (2021).CAS 
PubMed 

Google Scholar 
Moreno-Andrés, J. & Peperzak, L. Operational and environmental factors affecting disinfection byproducts formation in ballast water treatment systems. Chemosphere 232, 496–505 (2019).ADS 
PubMed 

Google Scholar 
David, M., Linders, J., Gollasch, S. & David, J. Is the aquatic environment sufficiently protected from chemicals discharged with treated ballast water from vessels worldwide? A decadal environmental perspective and risk assessment. Chemosphere 207, 590–600 (2018).ADS 
CAS 
PubMed 

Google Scholar 
U.S. Environmental Protection Agency. Generic protocol for the verification of ballast water treatment technology, version 5.1. Report number EPA/600/R-10/146. Washington, D.C. 157 (2010).Evans, J. S., Paul, V. J., Ushijima, B. & Kellogg, C. A. Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases. Biol. Methods Protocols 7, bpac007 (2022).
Google Scholar 
Fujimoto, M. et al. Application of Ion Torrent sequencing to the assessment of the effect of alkali ballast water treatment on microbial community diversity. PLoS ONE 9, e107534 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
United States Coast Guard. Ballast Water Best Management Practices to Reduce the Likelihood of Transporting Pathogens That May Spread Stony Coral Tissue Loss Disease. Marine Safety Information Bulletin 07–19. Washington, D.C. 2 (2019).Bolton, J. R. & Linden, K. G. Standardization of methods for fluence (UV dose) determination in bench-scale UV experiments. J. Environ. Eng. 129, 209–215 (2003).CAS 

Google Scholar 
Enochs, I. C. et al. The influence of diel carbonate chemistry fluctuations on the calcification rate of Acropora cervicornis under present day and future acidification conditions. J. Exp. Mar. Biol. Ecol. 506, 135–143 (2018).CAS 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Preprint at https://www.r-project.org/ (2019).Therneau, T. M. survival: A package for survival analysis in R. R package version 3.2–13. (2021).Kassambara, A., Kosinski, M. & Biecek, P. survminer: Drawing survival curves using “ggplot2”. R package version 0.4.9. (2021).Bakalar, G. Review of interdisciplinary devices for detecting the quality of ship ballast water. Springerplus 3, 468 (2014).PubMed 
PubMed Central 

Google Scholar 
Water Environmental Federation & American Public Health Association. Standard methods for the examination of water and wastewater. Washington, D.C. 21 (2005).Steinberg, M. K., Lemieux, E. J. & Drake, L. A. Determining the viability of marine protists using a combination of vital, fluorescent stains. Mar. Biol. 158, 1431–1437 (2011).
Google Scholar 
Oksanen, J. et al. vegan: Community ecology package. R package version 2.0–10. (2015).Martinez Arbizu, P. pairwiseAdonis: Pairwise multilevel comparison using adonis. R package version 0.4. (2020).Studivan, MS. Mstudiva/SCTLD-ballast-transmission: Stony coral tissue loss disease ballast transmission and treatment (Version 1.0), Zenodo, https://doi.org/10.5281/zenodo.6561517 (2022). More

Howe, B. M. et al. Observing the oceans acoustically. Front. Mar. Sci. 6, 426. https://doi.org/10.3389/fmars.2019.00426 (2019).Article 

Google Scholar 
Molenaar, M. M., Hill, D., Webster, P., Fidan, E. & Birch, B. First downhole application of distributed acoustic sensing for hydraulic-fracturing monitoring and diagnostics. SPE Drill. Complet. 27, 32–38. https://doi.org/10.2118/140561-PA (2012).Article 

Google Scholar 
Lindsey, N. J. et al. Fiber-optic network observations of earthquake wavefields. Geophys. Res. Lett. 44, 11792–11799. https://doi.org/10.1002/2017GLO75722 (2017).Article 
ADS 

Google Scholar 
Jousset, P. et al. Dynamic strain determination using fibre-optic cables allows imaging of seismological and structural features. Nat. Commun. 9, 1–11. https://doi.org/10.1038/s41467-018-04860-y (2018).Article 
CAS 

Google Scholar 
Ajo-Franklin, J. B. et al. Distributed acoustic sensing using dark fiber for near-surface characterization and broadband seismic event detection. Sci. Rep. 9, 1–14. https://doi.org/10.1038/s41598-018-36675-8 (2019).Article 
CAS 

Google Scholar 
Williams, E. F. et al. Distributed sensing of microseisms and teleseisms with submarine dark fibers. Nat. Commun. 10, 1–11. https://doi.org/10.1038/s41467-019-13262-7 (2019).Article 
CAS 

Google Scholar 
Lindsey, N. J., Dawe, T. C. & Ajo-Franklin, J. B. Illuminating seafloor faults and ocean dynamics with dark fiber distributed acoustic sensing. Science 366, 1103–1107. https://doi.org/10.1126/science.aay5881 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Sladen, A. et al. Distributed sensing of earthquakes and ocean-solid Earth interactions on seafloor telecom cables. Nat. Commun. 10, 5777. https://doi.org/10.1038/s41467-019-13793-z (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Williams, E. F. et al. Surface gravity wave interferometry and ocean current monitoring with ocean-bottom DAS. J. Geophys. Res. Oceans 127, e2021JC018375. https://doi.org/10.1029/2021JC018375 (2022).Article 
ADS 

Google Scholar 
Zhan, Z. et al. Optical polarization-based seismic and water wave sensing on transoceanic cables. Science 371, 931–936. https://doi.org/10.1126/science.abe6648 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Waagaard, O. H. et al. Real-time low noise distributed acoustic sensing in 171 km low loss fiber. OSA Contin. 4, 688–701. https://doi.org/10.1364/OSAC.408761 (2021).Article 
CAS 

Google Scholar 
Rivet, D., de Cacqueray, B., Sladen, A., Roques, A. & Calbris, G. Preliminary assessment of ship detection and trajectory evaluation using distributed acoustic sensing on an optical fiber telecom cable. J. Acoust. Soc. Am. 149, 2615–2627. https://doi.org/10.1121/10.0004129 (2021).Article 
ADS 
PubMed 

Google Scholar 
Taweesintananon, K., Landrø, M., Brenne, J. K. & Haukanes, A. Distributed acoustic sensing for near-surface imaging using submarine telecommunication cable: a case study in the Trondheimsfjord, Norway. Geophysics 86, B303–B320. https://doi.org/10.1190/geo2020-0834.1 (2021).Article 

Google Scholar 
Matsumoto, H. et al. Detection of hydroacoustic signals on a fiber-optic submarine cable. Sci. Rep. 11, 2797. https://doi.org/10.1038/s41598-021-82093-8 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Bouffaut, L. et al. Eavesdropping at the speed of light: Distributed acoustic sensing of baleen whales in the Arctic. Front. Mar. Sci. 9, 901348. https://doi.org/10.3389/fmars.2022.901348 (2022).Article 

Google Scholar 
Jones, N. The quest for quieter seas. Nature 568, 158–161. https://doi.org/10.1038/d41586-019-01098-6 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Williams, R. et al. Chronic ocean noise and cetacean population models. J. Cetacean Res. Manag. 21, 85–94. https://doi.org/10.47536/jcrm.v21i1.202 (2020).Article 

Google Scholar 
Roman, J. et al. Whales as marine ecosystem engineers. Front. Ecol. Environ. 12, 377–385. https://doi.org/10.1890/130220 (2014).Article 

Google Scholar 
Pershing, A. J., Christensen, L. B., Record, N. R., Sherwood, G. D. & Stetson, P. B. The impact of whaling on the ocean carbon cycle: Why bigger was better. PLoS ONE 5, 1–9. https://doi.org/10.1371/journal.pone.0012444 (2010).Article 
CAS 

Google Scholar 
IUCN – SSC Cetacean Specialist Group. Status of the World’s cetaceans (2021). https://iucn-csg.org/status-of-the-worlds-cetaceans/.Bailey, H. et al. Behavioural estimation of blue whale movements in the Northeast Pacific from state-space model analysis of satellite tracks. Endanger. Species Res. 10, 93–106. https://doi.org/10.3354/esr00239 (2010).Article 

Google Scholar 
Thomas, P. O., Reeves, R. R. & Brownell, R. L. Jr. Status of the world’s baleen whales. Mar. Mamm. Sci. 32, 682–734. https://doi.org/10.1111/mms.12281 (2016).Article 

Google Scholar 
Grigoli, F. et al. Current challenges in monitoring, discrimination, and management of induced seismicity related to underground industrial activities: A European perspective. Rev. Geophys. 55, 310–340. https://doi.org/10.1002/2016RG000542 (2017).Article 
ADS 

Google Scholar 
Bigg, G. R. & Hanna, E. Impacts and effects of ocean warming on the weather. In: Laffoley, D. & Baxter, J. M. (eds.) Explaining ocean warming: Causes, scale, effects and consequences, 359–372, https://doi.org/10.2305/IUCN.CH.2016.08.en (International Union for Conservation of Nature and Natural Resources (IUCN), Gland, Switzerland, 2016).Hartog, A. H. An Introduction to Distributed Optical Fibre Sensors 1st edn. (CRC Press, 2017). https://doi.org/10.1201/9781315119014.Book 

Google Scholar 
Lin, J., Fang, S., Li, X., Wu, R. & Zheng, H. Seismological observations of ocean swells induced by Typhoon Megi using dispersive microseisms recorded in coastal areas. Remote Sens.https://doi.org/10.3390/rs10091437 (2018).Article 

Google Scholar 
Munk, W. H., Miller, G. R., Snodgrass, F. E., Barber, N. F. & Deacon, G. E. R. Directional recording of swell from distant storms. Philos. Trans. R. Soc. Lond. Ser. A Math. Phys. Sci. 255, 505–584. https://doi.org/10.1098/rsta.1963.0011 (1963).Article 
ADS 

Google Scholar 
Mellinger, D. K. & Clark, C. W. Blue whale (balaenoptera musculus) sounds from the North Atlantic. J. Acoust. Soc. Am. 114, 1108–1119. https://doi.org/10.1121/1.1593066 (2003).Article 
ADS 
PubMed 

Google Scholar 
Ou, H., Au, W. W., Van Parijs, S., Oleson, E. M. & Rankin, S. Discrimination of frequency-modulated baleen whale downsweep calls with overlapping frequencies. J. Acoust. Soc. Am. 137, 3024–3032. https://doi.org/10.1121/1.4919304 (2015).Article 
ADS 
PubMed 

Google Scholar 
Saito, T. & Tsushima, H. Synthesizing ocean bottom pressure records including seismic wave and tsunami contributions: Toward realistic tests of monitoring systems. J. Geophys. Res. Solid Earth 121, 8175–8195. https://doi.org/10.1002/2016JB013195 (2016).Article 
ADS 

Google Scholar 
Rørstadbotnen, R. A. et al. Analysis of a local earthquake in the Arctic using a 120 km long fibre-optic cable. In 83rd EAGE Annual Conference & Exhibition, vol. 2022 of Conference Proceedings, 1–5, https://doi.org/10.3997/2214-4609.202210404 (European Association of Geoscientists & Engineers, 2022).Bromirski, P. D. & Duennebier, F. K. The near-coastal microseism spectrum: Spatial and temporal wave climate relationships. J. Geophys. Res. Solid Earth 107, ESE 5-1-20. https://doi.org/10.1029/2001JB000265 (2002).Article 

Google Scholar 
Pasch, R. J. National hurricane center tropical cyclone report: Tropical storm Edouard (AL052020). Technical report, National Oceanic and Atmospheric Administration (2021). https://www.nhc.noaa.gov/data/tcr/AL052020_Edouard.pdf.Gobato, R. & Heidari, A. Cyclone Bomb hits Southern Brazil in 2020. J. Atmos. Sci. Res. 3, 8–12. https://doi.org/10.30564/jasr.v3i3.2163 (2020).Article 

Google Scholar 
Khalid, A., de Lima, Ad. S., Cassalho, F., Miesse, T. & Ferreira, C. Hydrodynamic and wave responses during storm surges on the Southern Brazilian Coast: A real-time forecast system. Water 12, 3397. https://doi.org/10.3390/w12123397 (2020).Article 

Google Scholar 
Ćirić, J. Weather warning for Central Highland, Northwest Iceland (2020). https://www.icelandreview.com/travel/weather-warning-for-central-highland-northwest-iceland/.Schoeman, R. P., Patterson-Abrolat, C. & Plön, S. A global review of vessel collisions with marine animals. Front. Mar. Sci. 7, 292. https://doi.org/10.3389/fmars.2020.00292 (2020).Article 

Google Scholar 
Ringrose, P. S. et al. Storage of carbon dioxide in saline aquifers: Physicochemical processes, key constraints, and scale-up potential. Annu. Rev. Chem. Biomol. Eng. 12, 471–494. https://doi.org/10.1146/annurev-chembioeng-093020-091447 (2021).Article 
CAS 
PubMed 

Google Scholar 
Nishimura, T. et al. Source location of volcanic earthquakes and subsurface characterization using fiber-optic cable and distributed acoustic sensing system. Sci. Rep. 11, 6319. https://doi.org/10.1038/s41598-021-85621-8 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ardhuin, F. & Herbers, T. H. C. Noise generation in the solid Earth, oceans and atmosphere, from nonlinear interacting surface gravity waves in finite depth. J. Fluid Mech. 716, 316–348. https://doi.org/10.1017/jfm.2012.548 (2013).Article 
ADS 
MATH 

Google Scholar 
Airy, G. B. Encyclopaedia Metropolitana (1817–1845), vol. 3 of Mixed Sciences, chap. Tides and waves (London, 1841).Craik, A. D. The origins of water wave theory. Annu. Rev. Fluid Mech. 36, 1–28. https://doi.org/10.1146/annurev.fluid.36.050802.122118 (2004).Article 
ADS 
MathSciNet 
MATH 

Google Scholar 
Matsumoto, H., Inoue, S. & Ohmachi, T. Dynamic response of bottom water pressure due to the 2011 Tohoku earthquake. J. Disaster Res. 7, 468–475. https://doi.org/10.20965/jdr.2012.p0468 (2012).Article 

Google Scholar 
Landrø, M. & Hatchell, P. Normal modes in seismic data: Revisited. Geophysics 77, W27–W40. https://doi.org/10.1190/geo2011-0094.1 (2012).Article 
ADS 

Google Scholar  More

Urbanization is fast progressing in the Global South, requiring new solutions for infrastructure, services, industrial development and land and energy use for these regions. In this context, fast-growing cities in Africa can take on a leadership role in driving climate change mitigation and adaptation, disaster risk reduction and sustainable development.
Credit: Stefan Rotter / Alamy Stock PhotoCities in Africa and elsewhere in the Global South continue to grapple with the challenge of delivering equitable services, infrastructure, housing and action to respond to climate change extremes and disasters. One well-known problem is a mismatch between the pace of urban growth and the slower development of basic services and critical infrastructure. This results in, for example, deficient sanitation, water supply systems and localized waste management for large parts of the population, which in turn contribute substantially to heightened poverty and inequality. For inclusive, equitable, prosperous and climate-resilient cities, urban management needs to integrate low-income communities into the urban economy by ensuring access to water, sanitation, energy transition, waste management, poverty reduction and by improving resilience through innovative solutions.
Credit: Patrick J. Endres/Corbis Documentary/GettySuch an equitable urban transition requires changes in the urban infrastructure, and land and energy use, as well as water and ecosystem management. The key research question in this field is to find ways to ensure city-wide access to infrastructure and services, while minimizing emissions and resource use, and building resilience to climate change impacts. In this regard, cities in the Global South and Africa in particular can serve as examples for other parts of the world as they have the potential to adopt disruptive, innovative yet practical solutions to low emissions, resource minimization and resilience building.
Credit: Nature Picture Library / Alamy Stock PhotoFor example, rapid urbanization creates the opportunity to develop economic structures in African cities that strongly integrate waste by promoting recovery, recycling, re-use and repair for lengthening lifecycles. Such a circular economy can create business opportunities, while also reducing resource use, thus creating a pathway for sustainable development. Another potential solution is hybrid systems for urban water management that are off-grid and utilize multiple water sources and treatment but that can also connect to centralized water systems. Business models for micro-to-medium enterprises have the potential to integrate some of the low-income groups through these kinds of technology and building social resilience.
Credit: Images of Africa Photobank / Alamy Stock PhotoThese examples are part of a broader assessment of urban infrastructure innovations, their disruption of centralized systems and rethinking of urban form for more compact, walkable, co-located land use for low carbon intensity towards net-zero cities. However, to translate research on these new solutions into action, a shift is necessary in the planning, governing and managing of cities so as to allow for opportunities for leapfrogging to emerge and expand the possibilities of urban development for inclusive and resilient African cities. More

Bascompte, J. & Jordano, P. Mutualistic Networks (Princeton Univ. Press, Princeton, NJ, 2013).Cordeiro, N. J. & Howe, H. F. Forest fragmentation severs mutualism between seed dispersers and an endemic African tree. Proc. Natl Acad. Sci. USA 100, 14052–14056 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wandrag, E. M., Dunham, A. E., Duncan, R. P. & Rogers, H. S. Seed dispersal increases local species richness and reduces spatial turnover of tropical tree seedlings. Proc. Natl Acad. Sci. USA 114, 10689–10694 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2003).
Google Scholar 
Fahrig, L. Ecological responses to habitat fragmentation per se. Annu. Rev. Ecol. Evol. Syst. 48, 1–23 (2017).
Google Scholar 
Haddad, N. M. et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1, e1500052 (2015).PubMed 
PubMed Central 

Google Scholar 
Fricke, E. C. & Svenning, J. C. Accelerating homogenization of the global plant-frugivore meta-network. Nature 585, 74–78 (2020).CAS 
PubMed 

Google Scholar 
Fontúrbel, F. E. et al. Meta-analysis of anthropogenic habitat disturbance effects on animal-mediated seed dispersal. Glob. Change Biol. 21, 3951–3960 (2015).
Google Scholar 
Poisot, T. et al. Global knowledge gaps in species interaction networks data. J. Biogeogr. 48, 1552–1563 (2021).
Google Scholar 
Hortal, J. et al. Seven shortfalls that beset large-scale knowledge of biodiversity. Annu. Rev. Ecol. Evol. Syst. 46, 523–549 (2015).
Google Scholar 
Magrach, A., Laurance, W. F., Larrinaga, A. R. & Santamaria, L. Meta-analysis of the effects of forest fragmentation on interspecific interactions. Conserv. Biol. 28, 1342–1348 (2014).PubMed 

Google Scholar 
Pocock, M. J. O., Evans, D. M. & Memmott, J. The robustness and restoration of a network of ecological networks. Science 335, 973–977 (2012).CAS 
PubMed 

Google Scholar 
Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363 (2008).PubMed 

Google Scholar 
de Assis Bomfim, J., Guimarães, P. R. Jr., Peres, C. A., Carvalho, G. & Cazetta, E. Local extinctions of obligate frugivores and patch size reduction disrupt the structure of seed dispersal networks. Ecography 41, 1899–1909 (2018).
Google Scholar 
Emer, C. et al. Seed dispersal networks in tropical forest fragments: Area effects, remnant species, and interaction diversity. Biotropica 52, 81–89 (2020).
Google Scholar 
Evans, D. M., Pocock, M. J. O. & Memmott, J. The robustness of a network of ecological networks to habitat loss. Ecol. Lett. 16, 844–852 (2013).PubMed 

Google Scholar 
Grass, I., Jauker, B., Steffan-Dewenter, I., Tscharntke, T. & Jauker, F. Past and potential future effects of habitat fragmentation on structure and stability of plant-pollinator and host-parasitoid networks. Nat. Ecol. Evol. 2, 1408–1417 (2018).PubMed 

Google Scholar 
Neff, F. M. et al. Changes in plant-herbivore network structure and robustness along land-use intensity gradients in grasslands and forests. Sci. Adv. 7, eabf3985 (2021).PubMed 
PubMed Central 

Google Scholar 
Dunne, J. A., Williams, R. J. & Martinez, N. D. Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecol. Lett. 5, 558–567 (2002).
Google Scholar 
James, A., Pitchford, J. W. & Plank, M. J. Disentangling nestedness from models of ecological complexity. Nature 487, 227–230 (2012).CAS 
PubMed 

Google Scholar 
Jordano, P. Patterns of mutualistic interactions in pollination and seed dispersal: connectance, dependence asymmetries, and coevolution. Am. Nat. 129, 657–677 (1987).
Google Scholar 
Vieira, M. C. & Almeida-Neto, M. A simple stochastic model for complex coextinctions in mutualistic networks: robustness decreases with connectance. Ecol. Lett. 18, 144–152 (2015).PubMed 

Google Scholar 
Olesen, J. M., Bascompte, J., Dupont, Y. L. & Jordano, P. The modularity of pollination networks. Proc. Natl Acad. Sci. USA 104, 19891–19896 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
Gilarranz, L. J., Rayfield, B., Liñán-Cembrano, G., Bascompte, J. & Gonzalez, A. Effects of network modularity on the spread of perturbation impact in experimental metapopulations. Science 357, 199–201 (2017).CAS 
PubMed 

Google Scholar 
Liu, H. et al. Geographic variation in the robustness of pollination networks is mediated by modularity. Glob. Ecol. Biogeogr. 30, 1447–1460 (2021).
Google Scholar 
Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant-animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 9383–9387 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018–1020 (2009).CAS 
PubMed 

Google Scholar 
Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. B. 271, 2605–2611 (2004).PubMed 
PubMed Central 

Google Scholar 
Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. 9, 16–36 (2019).
Google Scholar 
Fortuna, M. A. et al. Nestedness versus modularity in ecological networks: two sides of the same coin? J. Anim. Ecol. 79, 811–817 (2010).PubMed 

Google Scholar 
Song, C., Rohr, R. P. & Saavedra, S. Why are some plant-pollinator networks more nested than others? J. Anim. Ecol. 86, 1417–1424 (2017).PubMed 

Google Scholar 
Schleuning, M., Böhning-Gaese, K., Dehling, D. M. & Burns, K. C. At a loss for birds: insularity increases asymmetry in seed-dispersal networks. Glob. Ecol. Biogeogr. 23, 385–394 (2014).
Google Scholar 
Aizen, M. A., Sabatino, M. & Tylianakis, J. M. Specialization and rarity predict nonrandom loss of interactions from mutualist networks. Science 335, 1486–1489 (2012).CAS 
PubMed 

Google Scholar 
Fortuna, M. A. & Bascompte, J. Habitat loss and the structure of plant-animal mutualistic networks. Ecol. Lett. 9, 278–283 (2006).
Google Scholar 
Spiesman, B. J. & Inouye, B. D. Habitat loss alters the architecture of plant-pollinator interaction networks. Ecology 94, 2688–2696 (2013).PubMed 

Google Scholar 
Traveset, A. et al. Bird-flower visitation networks in the Galápagos unveil a widespread interaction release. Nat. Commun. 6, 6376 (2015).CAS 
PubMed 

Google Scholar 
Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).PubMed 

Google Scholar 
Monteiro, E. C. S., Pizo, M. A., Vancine, M. H. & Ribeiro, M. C. Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks. Oikos 2022, e08240 (2022).
Google Scholar 
Whittaker, R. J., Fernández-Palacios, J. M., Matthews, T. J., Borregaard, M. K. & Triantis, K. A. Island biogeography: taking the long view of nature’s laboratories. Science 357, eaam8326 (2017).PubMed 

Google Scholar 
Vizentin-Bugoni, J. et al. Structure, spatial dynamics, and stability of novel seed dispersal mutualistic networks in Hawai’i. Science 364, 78–82 (2019).CAS 
PubMed 

Google Scholar 
Diamond, J. Dammed experiments! Science 294, 1847–1848 (2001).CAS 
PubMed 

Google Scholar 
Jones, I. L., Bunnefeld, N., Jump, A. S., Peres, C. A. & Dent, D. H. Extinction debt on reservoir land-bridge islands. Biol. Conserv. 199, 75–83 (2016).
Google Scholar 
Wu, J., Huang, J., Han, X., Xie, Z. & Gao, X. Three-Gorges dam–experiment in habitat Fragmentation? Science 300, 1239–1240 (2003).CAS 
PubMed 

Google Scholar 
Wilson, M. C. et al. Habitat fragmentation and biodiversity conservation: key findings and future challenges. Landsc. Ecol. 31, 219–227 (2016).
Google Scholar 
Trøjelsgaard, K. et al. Island biogeography of mutualistic interaction networks. J. Biogeogr. 40, 2020–2031 (2013).
Google Scholar 
Emer, C., Venticinque, E. M. & Fonseca, C. R. Effects of dam-induced landscape fragmentation on amazonian ant-plant mutualistic networks. Conserv. Biol. 27, 763–773 (2013).PubMed 

Google Scholar 
Zhu, C. et al. Arboreal camera trapping: a reliable tool to monitor plant-frugivore interactions in the trees on large scales. Remote Sens. Ecol. Conserv. 8, 92–104 (2022).
Google Scholar 
Zhu, C., Li, W., Wang, D., Ding, P. & Si, X. Plant-frugivore interactions revealed by arboreal camera trapping. Front. Ecol. Environ. 19, 149–151 (2021).
Google Scholar 
Galiana, N. et al. The spatial scaling of species interaction networks. Nat. Ecol. Evol. 2, 782–790 (2018).PubMed 

Google Scholar 
Hanski, I., Zurita, G. A., Bellocq, M. I. & Rybicki, J. Species-fragmented area relationship. Proc. Natl Acad. Sci. USA 110, 12715–12720 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Sugiura, S. Species interactions-area relationships: biological invasions and network structure in relation to island area. Proc. R. Soc. B. 277, 1807–1815 (2010).PubMed 
PubMed Central 

Google Scholar 
Galiana, N. et al. Ecological network complexity scales with area. Nat. Ecol. Evol. 6, 307–314 (2022).PubMed 

Google Scholar 
Santos, M., Cagnolo, L., Roslin, T., Marrero, H. J. & Vázquez, D. P. Landscape connectivity explains interaction network patterns at multiple scales. Ecology 100, e02883 (2019).PubMed 

Google Scholar 
Si, X., Pimm, S. L., Russell, G. J. & Ding, P. Turnover of breeding bird communities on islands in an inundated lake. J. Biogeogr. 41, 2283–2292 (2014).
Google Scholar 
Si, X. et al. Functional and phylogenetic structure of island bird communities. J. Anim. Ecol. 86, 532–542 (2017).PubMed 

Google Scholar 
Rosenfeld, J. S. Functional redundancy in ecology and conservation. Oikos 98, 156–162 (2002).
Google Scholar 
Sebastián-González, E. Drivers of species’ role in avian seed-dispersal mutualistic networks. J. Anim. Ecol. 86, 878–887 (2017).PubMed 

Google Scholar 
Donoso, I. et al. Downsizing of animal communities triggers stronger functional than structural decay in seed-dispersal networks. Nat. Commun. 11, 1582 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Müller, C. B. & Caflisch, A. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecol. Lett. 13, 442–452 (2010).PubMed 

Google Scholar 
Dalsgaard, B. et al. Opposed latitudinal patterns of network-derived and dietary specialization in avian plant-frugivore interaction systems. Ecography 40, 1395–1401 (2017).
Google Scholar 
Borrvall, C., Ebenman, B. & Jonsson, T. Biodiversity lessens the risk of cascading extinction in model food webs. Ecol. Lett. 3, 131–136 (2000).
Google Scholar 
Liao, J. et al. Robustness of metacommunities with omnivory to habitat destruction: disentangling patch fragmentation from patch loss. Ecology 98, 1631–1639 (2017).PubMed 

Google Scholar 
Rumeu, B. et al. Predicting the consequences of disperser extinction: richness matters the most when abundance is low. Funct. Ecol. 31, 1910–1920 (2017).
Google Scholar 
Wong, B. B. M. & Candolin, U. Behavioral responses to changing environments. Behav. Ecol. 26, 665–673 (2015).
Google Scholar 
Betts, M. G. et al. Extinction filters mediate the global effects of habitat fragmentation on animals. Science 366, 1236–1239 (2019).CAS 
PubMed 

Google Scholar 
Menke, S., Böhning-Gaese, K. & Schleuning, M. Plant-frugivore networks are less specialized and more robust at forest–farmland edges than in the interior of a tropical forest. Oikos 121, 1553–1566 (2012).
Google Scholar 
Redhead, J. W. et al. Potential landscape-scale pollinator networks across Great Britain: structure, stability and influence of agricultural land cover. Ecol. Lett. 21, 1821–1832 (2018).PubMed 

Google Scholar 
Si, X. et al. The importance of accounting for imperfect detection when estimating functional and phylogenetic community structure. Ecology 99, 2103–2112 (2018).PubMed 

Google Scholar 
Schoereder, J. H. et al. Should we use proportional sampling for species-area studies? J. Biogeogr. 31, 1219–1226 (2004).
Google Scholar 
Liu, J. et al. The distribution of plants and seed dispersers in response to habitat fragmentation in an artificial island archipelago. J. Biogeogr. 46, 1152–1162 (2019).
Google Scholar 
Olson, E. R. et al. Arboreal camera trapping for the Critically Endangered greater bamboo lemur Prolemur simus. Oryx 46, 593–597 (2012).
Google Scholar 
Li, H.-D. et al. The functional roles of species in metacommunities, as revealed by metanetwork analyses of bird-plant frugivory networks. Ecol. Lett. 23, 1252–1262 (2020).PubMed 

Google Scholar 
Snow, B. & Snow, D. Birds and berries: a study of an ecological interaction (T & AD Poyser, Calton, 1988).Si, X., Kays, R. & Ding, P. How long is enough to detect terrestrial animals? Estimating the minimum trapping effort on camera traps. PeerJ 2, e374 (2014).PubMed 
PubMed Central 

Google Scholar 
Vázquez, D. P. et al. Species abundance and asymmetric interaction strength in ecological networks. Oikos 116, 1120–1127 (2007).
Google Scholar 
Chao, A. & Jost, L. Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size. Ecology 93, 2533–2547 (2012).PubMed 

Google Scholar 
Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).
Google Scholar 
Beckett, S. J. Improved community detection in weighted bipartite networks. R. Soc. Open. Sci. 3, 140536 (2016).PubMed 
PubMed Central 

Google Scholar 
Almeida-Neto, M. & Ulrich, W. A straightforward computational approach for measuring nestedness using quantitative matrices. Environ. Modell. Softw. 26, 173–178 (2011).
Google Scholar 
Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556 (2010).CAS 
PubMed 

Google Scholar 
Schleuning, M. et al. Ecological networks are more sensitive to plant than to animal extinction under climate change. Nat. Commun. 7, 13965 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Nic Lughadha, E. & Vorontsova, M. S. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nat. Ecol. Evol. 3, 1043–1047 (2019).PubMed 

Google Scholar 
Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).CAS 
PubMed 

Google Scholar 
Rogers, H. S., Donoso, I., Traveset, A. & Fricke, E. C. Cascading impacts of seed disperser loss on plant communities and ecosystems. Annu. Rev. Ecol. Evol. Syst. 52, 641–666 (2021).
Google Scholar 
Dormann, C. F., Gruber, B. & Fründ, J. Introducing the bipartite package: analysing ecological networks. R News 8, 8–11 (2008).
Google Scholar 
Patefield, W. M. Algorithm AS 159: An efficient method of generating random R × C tables with given row and column totals. Appl. Stat. 30, 91–97 (1981).
Google Scholar 
Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).
Google Scholar 
Kabacoff, R. R in Action: Data Analysis and Graphics with R (Manning Publications Co, 2015).R Core Team. R: A Language And Environment For Statistical Computing (R Foundation for Statistical Computing, 2021). More

Study areaSituated in western India’s southwestern part of the Gujarat state, the Saurashtra region typically represents the semi-arid Gujarat-Rajputana province 4B23, which covers 11 out of 33 districts of the state. The region forms a rocky tableland (altitude 300–600 m) fringed by coastal plains with an undulating central plain broken by hills and dissected by various rivers that flow in all directions24. With the longest coastline (~ 1600 km) in India, Gujarat is endowed with rich coastal biodiversity25,26. The Saurashtra coast in Gujarat is encircled by the open sea between two Gulfs (68° 58′–71° 30′ N and 22° 15′–20° 50′ E) and divided into two segments, viz. the southwestern coast from Dwarka to Diu (~ 300 km stretch) and south-eastern coast from Diu to Bhavnagar (~ 250 km stretch)26.The Asiatic Lion Landscape covers an area of ~ 30,000 km2 (permanent lion distribution range: ~ 16,000 km2; visitation record range: ~ 14,000 km2) of varied habitat types within Saurashtra. The landscape includes five protected areas (Gir National Park, Gir Wildlife Sanctuary, Paniya Wildlife Sanctuary, Mitiyala Wildlife Sanctuary, and Girnar Wildlife Sanctuary) and other forest classes (reserved forests, protected forests, and unclassed forests).The coastal habitats extend across the districts of Bhavnagar, Amreli, Gir-Somnath, and Junagadh (Fig. 1). Within these districts (Fig. 1), the tehsils (sub-divisions/taluka) of Mangrol, Malia, Patan-Veraval, Sutrapada, Kodinar and Una are categorized under the southwestern coast (hereafter western coastal habitat), Jafrabad, Rajula, form the south-eastern coast and Mahuva and Talaja constitute the Bhavnagar coast and represent distinct lion range units (Fig. 1). The total area covered in the study is 2843 km2 on the eastern coast and 1413 km2 on the western coast (Fig. 1).The Saurashtra region is bestowed with three distinct seasons, viz. dry and hot summer (March–June), monsoon (July–October), and primarily dry winter (November–February). It receives a mean annual rainfall of ~ 600 mm, with most rainfall during the southwest monsoon27. The mean maximum and minimum temperatures are 34 °C and 19 °C, respectively28. There is a 110 km2 stretch of forests along the coast. The rest of the areas are multi-use consisting of private, industrial, pastoral and wastelands of varied ownerships. The natural vegetation primarily consists of Prosopis juliflora and Casuarina equistsetifolia. On the beach and dune areas, vegetation such as Ipomea pescaprae, Sporobolus trinules, Fimrystylis sp., Crotalaria sp., and Euphorbia nivuleria29. The mudflats along the coast are restricted to Talaja, Mahuva, Pipavav Port, Jafrabad creek, and Porbandar, sparsely covered by the Avicennia marina29. Fisheries, agriculture, horticulture, livestock rearing, and some large- and small-scale industries are the leading economies in the coastal belt.Coastal segments are characterized by the variety of vegetation, sandy beaches, small cliffs, wave-cut platforms, open and submerged dunes, minor estuaries, embankments, and transition from the open sea to gulf environment with tidal mud26,29 and also support a diverse assemblage of biodiversity25. This biodiversity is further enriched by several perennial/ephemeral rivers originating from the Gir PA (Shetrunji, Machundari, Raval, Ardak, Bhuvatirth, Shinghoda, Hiran, Saraswati, etc.)12. These rivers meet the sea at different sections of the coast, forming prominent coastal ecosystems25. The riverine tracts act as important corridors for wildlife movement9,12,30. Dispersing through these corridors, lions have started inhabiting these coastal habitats30,31.MethodsAll the research activities involved in this study on Asiatic lions were carried out after taking due permission from the Ministry of Environment, Forests & Climate Change (MoEF&CC), Government of India (Letter No.: F. No. 1-50/2018 WL) and Principal Chief Conservator of Forests (Wildlife) & Chief Wildlife Warden, Gujarat State, Gandhinagar (Letter No.: WLP 26B 781-83/2019-20). Procedures and protocols were followed as per the Standard Operating Procedures of the Gujarat Forest Department, Government of Gujarat, concerning the handling of wild animals. Qualified and experienced veterinarians and their team carried out all procedures related to radio-collaring. Moreover, the study is reported in accordance with ‘Animal Research: Reporting of In Vivo Experiments’ (ARRIVE) guidelines as applicable.A long-term lion monitoring project was initiated in 2019 by the Gujarat Forest Department to understand the movement patterns and ecology of lions in the Asiatic Lion Landscape. Looking at the heterogeneity and vastness of the coastal areas, ten individuals were carefully selected for satellite radio-collaring based on their frequent movement in different coastal habitats and monitored from 2019 to 2021.The lions were deployed with Vertex Plus GPS Collars (Vectronics Aerospace GmbH, Berlin, Germany) that weighed less than three per cent of the individual’s body weight, irrespective of age and sex. The lions were immobilized using a combination of Ketamine hydrochloride (2.2 mg per kg body weight; Ketamine, Biowet, Pulawy) and Xylazine hydrochloride (1.1 mg per kg body weight; Xylaxil, Brilliant Bio Pharma Pvt. Ltd., Telangana)32 administered intramuscularly using a gas-powered Telinject™ G.U.T 50 (Telinject Inc., Dudenhofen, Germany) dart delivery system. A blindfold was placed to protect the eyes and decrease visual stimuli33,34. Each sedated individual was sexed, aged, and measured as per the standard operating procedure (SOP) of the Gujarat Forest Department, Government of Gujarat, and recorded the data in the trapping datasheet. The radio-collars were deployed considering the neck girth of the individual, ensuring free movement of it so as not to hamper the individual’s routine activities. After deploying the radio-collar, we used the specific antidote for Xylazine, i.e., Yohimbine hydrochloride (0.1–0.15 mg per kg body weight; Yohimbe, Equimed, USA) intravenously, resulting in the total recovery of immobilized individuals32 within 5–10 min. The individuals were intensively monitored for 72 h and, after that, regularly monitored throughout the functional period of the radio-collars. The entire radio-collaring exercise was carried out by trained and experienced veterinary officers and their teams that constituted wildlife health care personnel and field staff.Each collar had a unique VHF and UHF frequency. The radio-collars were equipped with a programmable GPS schedule and configured to record the location fixes at every hour and provided the data through the constellation of low-earth-orbit Iridium satellite data service (Iridium Communications Inc., Virginia, USA) at four-hour intervals after getting activated. The data logs included location fixes in degree decimal format (latitude/longitude), speed (km/hour), altitude (meters above mean sea level), UTC timestamp (dd-mm-yyyy h:m:s), direction (degrees), and temperature (Celsius). Radio-collars were equipped with mortality sensors and a programmable drop-off activation system. Gir Hi-Tech Monitoring Unit, Sasan-Gir, Gujarat, monitored and coordinated these activities. The location data from each radio-collar was downloaded using the GPS Plus X software (Vectronics Aerospace GmbH, Berlin, Germany) in the Gir Hi-Tech Monitoring Unit (a technology-driven scientific monitoring initiative in the landscape established in 2019 at Sasan-Gir, Gujarat).Data analysisIn this study, we calculated the home range of lions resident in the coastal region using the Fixed Kernel method. We expressed them as 90% and 50% Fixed Kernel (FK) to summarize the overall home range and core area, respectively35,36,37. Additionally, the home range of lions categorized as “link lions” and lions of the protected area was summarized for comparison (Table 1).MaxEnt (version 3.4.1) stand-alone software38 was applied for fine-scaled lion distribution modelling39,40. The logistic output format was set for the MaxEnt output. 30% random lion occurrence points were used as test data to evaluate model performance. The area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative ability of the model based on the values of sensitivity (correct discrimination of true positive location points) and specificity (correct discrimination of true negative absence points)41. The Jackknife regularised training gain for the species was used to understand the effect of each variable in model building. The logical output by the MaxEnt was presented in a table format as “percent contribution” and “permutation importance” values (from 0 to 100%). Spatial inputs were prepared on the GIS platform using ArcMap (version 10.8.1, ESRI, Redlands, USA)42. Input data for MaxEnt were categorized as (i) lion occurrence data, (ii) model variables were prepared as described below:

i.

Occurrence data
At the first level, inconsistent location fixes (records with missing coordinates, time stamps, and elevation) and outliers were filtered out. Next, each lion’s hourly GPS location fixes obtained from remotely monitored radio-telemetry data were randomized to overcome spatial and temporal biases. The data was reduced by taking every three-hour location fix43,44. The data was further categorized season-wise, viz. summer, monsoon and winter. This consolidated data was then subject to spatial thinning of one kilometre using SDMtoolbox (version 2.0)45,46.

ii.

Model variables

The variables used for distribution modelling broadly included different categories of land use, including both natural habitats and anthropogenic factors, namely, roads and human settlement areas. All variables were rasterized at 10 m spatial resolution.Land Use Land Cover (LULC) data of Saurashtra was obtained from Bhaskaracharya National Institute for Space Applications and Geo-informatics (BISAG-N), Gandhinagar, Gujarat. The data was then further classified into 18 sub-classes—Forest, Sandy areas, Salt-affected, Saltpan, open scrub, dense scrub (Wastelands), Waterlogged, River/Stream/Drain, Lakes and Ponds, Mining/Industrial areas, Reservoir/Tanks, Mangrove/Swamp Area, Crop Land, Agriculture Plantation (horticulture and agro-forestry), Core urban, Mixed settlement, Peri-urban, Village (Fig. 2).Roads and highways were also analyzed as separate variables in the model. Roads were classified as village roads, major district roads, and state and national highways and digitized individually to estimate Euclidean distance further (Table 2). Euclidean distance from the human settlement (Core-urban, Peri-urban, villages and mixed settlement) was analyzed and taken as a separate input variable for the model. More