Longitudinal physicochemical patterns of the Sitka stream (annual means). Hyporheic water means mix of interstitial water taken from the depth 10 up to 50 cm of the sediment depth
\r\n\tFurther development of geophysical methods in the direction of constructing more and more adequate models of media and phenomena necessarily leads to more and more complex problems of mathematical geophysics, for which not only inverse, but also direct problems become significantly incorrect. In this regard, it is necessary to develop a new concept of regularization for simultaneously solving a system of heterogeneous operator equations.
\r\n\r\n\tCurrently, the study of processes associated not only with geophysics and astrophysics but also with biology and medicine requires even more complication of interpretation models from non-linear and heterogeneous to hierarchical. This book will be devoted to the creation of new mathematical theories for solving ill-posed problems for complicated models.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"d93195bb64405dd9e917801649f991b3",bookSignature:"Prof. Olga Alexandrovna Hachay",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8253.jpg",keywords:"Ill-Posed, Inverse Problems, Geophysics, Seismic, Electromagnetic, Thermal, Magnetic, Medicine, \r\nMathematical, Algorithms, Hierarchical, Nonlinear, Historical Description, Regularization",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 7th 2019",dateEndSecondStepPublish:"March 27th 2020",dateEndThirdStepPublish:"May 26th 2020",dateEndFourthStepPublish:"August 14th 2020",dateEndFifthStepPublish:"October 13th 2020",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"150801",title:"Prof.",name:"Olga",middleName:"Alexandrovna",surname:"Hachay",slug:"olga-hachay",fullName:"Olga Hachay",profilePictureURL:"https://mts.intechopen.com/storage/users/150801/images/system/150801.jpg",biography:"Dr. Olga A. Hachay graduated with a degree in Astrophysics from Ural State University in 1969. She obtained her PhD from the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation of the Russian Academy of Sciences (IZMIRAN) in 1979 with her thesis 'The inverse problem for electromagnetic research of one-dimensional medium.”\nSince 1969, she has been a scientific member of the Institute of Geophysics Ural Branch of Russian Academy of Sciences (UB RAS), Ekaterinburg, Russia. From 1995 to 2004, she served as chief of the group of seismic and electromagnetic research. Her research interests include developing new methods for searching the structure and the state of the Earth’s upper crust, as well as elaborating a new theory of interpretation of electromagnetic and seismic fields. From 2002, she has been the main scientific researcher of the Institute of geophysics UB RAS. Since 2008, she has been a lead scientific researcher for UB RAS in the laboratory of borehole geophysics. Dr. Hachay is a member of various organizations and societies, including the American Mathematical Society, Mathematical Association of America, International Association of Geomechanics, and the European Geosciences Union, among others. \nDr. Hachay is fluent in Russian, English and German language",institutionString:"Ural Branch of the Russian Academy of Sciences",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Ural Branch of the Russian Academy of Sciences",institutionURL:null,country:{name:"Russia"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"15",title:"Mathematics",slug:"mathematics"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"247865",firstName:"Jasna",lastName:"Bozic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/247865/images/7225_n.jpg",email:"jasna.b@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3621",title:"Silver Nanoparticles",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"silver-nanoparticles",bookSignature:"David Pozo Perez",coverURL:"https://cdn.intechopen.com/books/images_new/3621.jpg",editedByType:"Edited by",editors:[{id:"6667",title:"Dr.",name:"David",surname:"Pozo",slug:"david-pozo",fullName:"David Pozo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"44416",title:"Methanogenic System of a Small Lowland Stream Sitka, Czech Republic",doi:"10.5772/52718",slug:"methanogenic-system-of-a-small-lowland-stream-sitka-czech-republic",body:'Methane (CH4) is an atmospheric trace gas present at concentration of about 1.8 ppmv, that represents about 15% of the anthropogenic greenhouse effect (Forster et al. 2007). The atmospheric CH4 concentration has increased steadily since the beginning of the industrial revolution (~ 0.7 ppmv) and is stabilized at ~1.8 ppmv from 1999 to 2005 (Forster et al. 2007). An unexpected increase in the atmospheric growth of CH4 during the year 2007 has been recently reported (Rigby et al. 2008), indicating that the sources and sinks of atmospheric CH4 are dynamics, evolving, and not well understood. Freshwater sediments, including wetlands, rice paddies and lakes, are thought to contribute 40 to 50 % of the annual atmospheric methane flux (Cicerone & Oremland 1988; Conrad 2009).
The river hyporheic zone, volume of saturated sediment beneath and beside streams containing some proportion of water from surface channel, plays a very important role in the processes of self-purification because the river bed sediments are metabolically active and are responsible for retention, storage and mineralization of organic matter transported by the surface water (Hendricks 1993; Jones & Holmes 1996, Baker et al. 1999, Storey et al. 1999, Fischer et al. 2005). The seemingly well-oxygenated hyporheic zone contains anoxic and hypoxic pockets („anaerobic microzones“) associated with irregularities in sediment surfaces, small pore spaces or local deposits of organic matter, creating a ‘mosaic’ structure of various environments, where different microbial populations can live and different microbially mediated processes can occur simultaneously (Baker et al. 1999, Morrice et al. 2000, Fischer et al. 2005). Moreover, hyporheic-surface exchange and subsurface hydrologic flow patterns result in solute gradients that are important in microbial metabolism. Oxidation processes may occur more readily where oxygen is replenished by surface water infiltration, while reduction processes may prevail where surface-water exchange of oxygen is less, and the reducing potential of the environment is greater (Hendricks 1993). As water moves through the hyporheic zone, decomposition of the organic matter consumes oxygen, creating oxygen gradients along the flow path. Thus,compared to marine or lake surface sediments, where numerous studies on O2 profiles have showed that O2 concentrations become zero within less than 3 mm from the surface, the hyporheic sediment might be well-oxygenated habitats even up to the depth of 80 cm (e.g. Bretschko 1981, Holmes et al. 1994). The extent of the oxygen gradient is determined by the interplay between flow path lengh, water velocity, the ratio of surface to ground water, and the amount and quality of organic matter. Organic matter decomposition in sediments is an important process in global and local carbon budgets as it ultimately recycles complex organic compounds from terrestrial and aquatic environments to carbon dioxide and methane. Methane is a major component in the carbon cycle of anaerobic aquatic systems, particularly those with low sulphate concentrations. Since a relatively high production of methane has been measured in river sediments (e.g. Schindler & Krabbenhoft 1998, Hlaváčová et al. 2005, Sanders et al. 2007, Wilcock & Sorrell 2008, Sanz et al. 2011), we proposed that river sediments may act as a considerable source of this greenhouse gas which is important in global warming (Hlaváčová et al. 2006).
Breakdown of organic matter and gas production are both results of well functioned river self-purification. This degrading capacity, however, requires intensive contact of the water with biologically active surfaces. Flow over various morphological features ranging in size from ripples and dunes to meanders and pool-riffle sequences controls such surface-subsurface fluxes. Highly permeable streambeds create opportunities for subsurface retention and long-term storage, and exchange with the surface water is frequent. Thus, study of the methane production within hyporheic zone and its subsequent emission to the atmosphere can be considered as a measure of mineralization of organic matter in the freshwater ecosystem and might be used in evaluation of both the health and environmental quality of the rivers studied.
Methane (CH4) is mostly produced by methanogenic archaea (Garcia et al. 2000, Chaban et al. 2006) as a final product of anaerobic respiration and fermentation, but there is also aerobic methane formation (e.g. Karl et al. 2008). Methanogenic archaea are ubiquitous in anoxic environments and require an extremely low redox potential to grow. They can be found both in moderate habitats such as rice paddies (Grosskopf et al. 1998a,b), lakes (Jürgens et al. 2000, Keough et al. 2003) and lake sediments (Chan et al. 2005), as well as in the gastrointestinal tract of animals (Lin et al. 1997) and in extreme habitats such as hydrothermal vents (Jeanthon et al. 1999), hypersaline habitats (Mathrani & Boone 1995) and permafrost soils (Kobabe et al. 2004, Ganzert et al. 2006). Rates of methane production and consumption in sediments are controlled by the relative availability of substrates for methanogenesis (especially acetate or hydrogen and carbon dioxide). The most important immediate precursors of methanogenesis are acetate and H2/CO2. The acetotrophic methanogens convert acetic acid to CH4 and CO2 while the hydrogenotrophic methanogens convert CO2 with H2 to CH4 (Conrad 2007).
Methane oxidation can occur in both aerobic and anaerobic environments; however, these are completely different processes involving different groups of prokaryotes. Aerobic methane oxidation is carried out by aerobic methane oxidizing bacteria (methanotrophs, MOB), while anaerobic methane oxidizers, discovered recently, thrive under anaerobic conditions and use sulphate or nitrate as electron donors for methane oxidation (e.g. Strous & Jetten 2004). MOB are a physiologically specialized group of methylotrophic bacteria capable of utilizing methane as a sole source of carbon and energy, and they have been recognized as major players in local and global elemental cycling in aerobic environments (Hanson & Hanson 1996, Murrell et al. 1998, Costelo & Lidstrom 1999, Costelo et al. 2002, McDonald et al. 2008). Aerobic MOB have been detected in a variety of environments, and in some they represent significant fractions of total microbial communities (e.g. Henckel et al. 1999; Carini et al, 2005, Trotsenko & Khmelenina 2005, Kalyuzhnaya et al. 2006). However, the data on the diversity and activity of methanotrophic communities from the river ecosystems are yet fragmentary. Methanotrophs play an important role in the oxidation of methane in the natural environment, oxidizing methane biologically produced in anaerobic environments by the methanogenic archaea and thereby reducing the amount of methane released into the atmosphere.
The present investigation is a part of a long-term study focused on organic carbon and methane dynamics and microbial communities in hyporheic zone of a Sitka, small lowland stream in Czech Republic. The overall purpose of this research was to characterize spatial distribution of both methanogens and methanotrophs within hyporheic sediments and elucidate the differences in methane pathways and methane production/consumption as well as methane fluxes and atmospheric emissions at different sites along a longitudinal profile of the stream.
The sampling sites are located on the Sitka stream, Czech Republic (Fig. 1). The Sitka is an undisturbed, third-order, 35 km long lowland stream originating in the Hrubý Jeseník mountains at 650 m above sea level. The catchment area is 118.81km2, geology being composed mainly of Plio-Pleistocene clastic sediments of lake origin covered by quaternary sediments. The mean annual precipitation of the downstream part of the catchment area varies from 500 to 600 mm. Mean annual discharge is 0.81 m3.s-1. The Sitka stream flows in its upper reach till Šternberk through a forested area with a low intensity of anthropogenic effects, while the lower course of the stream naturally meanders through an intensively managed agricultural landscape. Except for short stretches, the Sitka stream is unregulated with well-established riparian vegetation. River bed sediments are composed of gravels in the upper parts of the stream (median grain size 13 mm) while the lower part, several kilometres away from the confluence, is characterised by finer sediment with a median grain size of 2.8 mm. The Sitka stream confluences with the Oskava stream about 5 km north of Olomouc. More detailed characteristics of the geology, gravel bar, longitudinal physicochemical (e.g. temperature, pH, redox, conductivity, O2, CH4, NO3, SO4) patterns in the sediments and a schematic view of the site with sampling point positions have been published previously (Rulík et al. 2000, Rulík & Spáčil 2004). Earlier measurements of a relatively high production of methane, as well as potential methanogenesis, confirmed the suitability of the field sites for the study of methane cycling (Rulík et al. 2000, Hlaváčová et al. 2005, 2006).
A map showing the location of the Sitka stream. Black circles represents the study sites (1-5)
Five localities alongside stream profile were chosen for sampling sediment and interstitial water samples based on previous investigations (Figure 2, Table 1). Hyporheic sediments were collected with a freeze-core using N2 as a coolant (Bretschko & Klemens 1986) throughout summer period 2009-2011. At each locality, three cores were taken for subsequent analyses. After sampling, surface 0-25 cm sediment layer and layer of 25-50 cm in depth were immediately separated and were stored at a low temperature whilst being transported to the laboratory. Just after thawing, wet sediment of each layer was sieved and only particles < 1 mm were considered for the following microbial measurements and for all microbial activity measurements since most of the biofilm is associated with this fraction (Leichtfried 1988).
Graphic depiction of the thalweg of the Sitka stream with sampling localities. The main source of pollution is an effluent from Šternberk city sewage water plant, located just in the middle between stretch II and III.
Variable/ Locality | I. | II. | III. | IV. | V. |
elevation above sea-level [m] | 535 | 330 | 240 | 225 | 215 |
distance from the spring [km] | 6,9 | 18,2 | 25,6 | 30,9 | 34,9 |
channel width [cm] | 523 | 793 | 672 | 444 | 523 |
average flow velocity [m.s-1] | 0,18 | 0,21 | 0,46 | 0,42 | 0,18 |
stretch longitude [km] | 12,6 | 9,3 | 6,3 | 4,7 | 2,3 |
stretch surface area [km2] | 0,043 | 0,06 | 0,043 | 0,024 | 0,012 |
stretch surface area (%) | 24 | 32 | 24 | 13 | 7 |
dominant substrate composition | gravel | gravel | gravel | silt-clay | gravel-sand |
grain median size [mm] | 12,4 | 12,9 | 13,2 | 0,2 | 5,4 |
surface water PO43- [mg L-1] | 0,15 | 0,24 | 7,0 | 2,6 | 1,8 |
surface water N - NO3- [mg L-1] | 0,01 | 0,21 | 1,2 | 0,5 | 0,18 |
surface water N - NH4+ [mg L-1] | 0,39 | 0,26 | 0,66 | 0,72 | 0,61 |
surface dissolved oxygen saturation [%] | 101,7 | 110,0 | 105,8 | 108,5 | 103,5 |
surface water conductivity [µS.cm-1] hyporheic water conductivity [µS.cm-1] | 107,5 | 127,5 | 404,8 | 394,0 | 397,7 |
115,3 | 138,3 | 414,5 | 506,5 | 416,2 | |
surface water temperature [°C] | 8,1 | 9,7 | 10,7 | 11,1 | 8,9 |
surface water DOC [mg L-1] hyporheic water DOC [mg L-1] | 2,47 | 0,81 | 2,62 | 2,69 | 3,74 |
2,05 | 1,31 | 2,71 | 5,76 | 2,62 |
Longitudinal physicochemical patterns of the Sitka stream (annual means). Hyporheic water means mix of interstitial water taken from the depth 10 up to 50 cm of the sediment depth
A few randomly selected subsamples (1 mL) were used for extraction of bacterial cells and, consequently, for estimations of bacterial numbers; other sub-samples were used for measurement of microbial activity and respiration, organic matter content determination, etc. Sediment organic matter content was determined by oven-drying at 105 oC to constant weight and subsequent combustion at 550 oC for 5 hours to obtain ash-free dry weight (AFDW). Organic matter values were then converted to carbon equivalents assuming 45 % carbon content of organic matter (Meyer et al. 1981). Sediment from another freeze-core was oven-dried at 105 °C and subjected to granulometric analysis. Grain size distribution and descriptive sediment parameters were computed using the database SeDi (Schönbauer & Lewandowski 1999).
Surface water was collected from running water at a depth of 10 cm below the surface level in autumn 2009 at each study site. Interstitial water samples were collected using a set of 5–6 minipiezometers (Trulleyová et al. 2003) placed at a depth of about 20-50 cm randomly in sediments at each study site. The initial 50–100 mL of water was used as a rinse and discarded. As usual, two subsamples of interstitial water from each minipiezometer were collected from a continuous column of water with a 100 mL polypropylene syringe connected to a hard PVC tube, drawn from a minipiezometer and injected into sterile, clear vials (40 mL) with screw-tops, covered by a polypropylene cap with PTFE silicone septa (for analysis of dissolved gasses) and stored before returning to the laboratory. All samples were taken in the morning between 9 a.m. and 12 noon. All measurements were done during the normal discharge levels (i.e. no spates or high flood levels were included). Interstitial water temperature, dissolved oxygen (mg L-1 and percent saturation) and conductivity were measured in the field with a portable Hanna HI 9828 pH/ORP/EC/DO meter. Dissolved organic carbon (DOC) was measured by Pt-catalysed high temperature combustion on a TOC FORMACSHT analyser. Long term observation of interstitial water temperature was carried out using temperature dataloggers Minikin (EMS Brno, Czech Republic) buried in the sediment depth of 25-30 cm for a period of one year. Dissolved ferrous iron (Fe2+) concentration was measured using absorption spectrophotometry after reaction with 1,10-phenanthroline. Concentrations of organic acids were meausred using capilary electrophoresis equipped with diode array detector HP 3D CE Agilent (Waldbron, Germany). Limits of detection for particular organic acids were set as following: LOD (acetate) = 6,2 μmol L-1; LOD (propionate) = 4,8 μmol L-1; LOD (butyrate) = 2,9 μmol L-1; LOD 32 (valerate) = 1,8 μmol L-1.
Concentrations of dissolved methane in the stream and interstitial water were measured directly using a headspace equilibration technique. Dissolved methane was extracted from the water by replacing 10 mL of water with N2 and then vigorously shaking the vials for 15 seconds (to release the supersaturated gas from the water to facilitate equilibration between the water and gas phases). All samples were equilibrated with air at laboratory temperature. Methane was analysed from the headspace of the vials by injecting 2ml of air sub-sample with a gas-tight syringe into a CHROM 5 gas chromatograph, equipped with the flame ionization detector (CH4 detection limit = 1μg L-1) and with the 1.2m PORAPAK Q column (i.d. 3 mm), with nitrogen as a carrier gas. Gas concentration in water was calculated using Henry’s law. The saturation ratio (R) was calculated as the measured concentration of gas divided by the concentration in equilibrium with the atmosphere at the temperature of the water sample using the solubility data of Wiesenburg & Guinasso (1979).
The rate of methane production (methanogenesis) was measured using the PMP method (Segers 1998). C-amended solutions (flushed for 5 minutes with N2) with acetate Ca(CH3COO)2 (100 mg C in the incubation flask) were used for the examination of methanogenic potential. All laboratory sediment incubations were performed in 250-mL dark glass flasks, capped with rubber stoppers, using approximately 100 g (wet mass) of sediment (grain size < 1 mm) and 180 mL of amended solution or distilled water. The headspace was maintained at 20 mL. Typically, triplicate live and dead (methanogenesis was inhibited by addition of 1.0 mM chloroform) samples from each depth were stored at 20°C in the dark and the incubation time was 72 hours; however, subsamples from the headspace atmosphere were taken every 24 hours. Gas production was calculated from the difference between final and initial headspace concentration and volume of the flask; results are expressed per volume unit of wet sediment (CH4 mL-1 WW hour‐1) or per unit dry weight of sediment per one day (μg CH4 kg-1 DW day-1). Rate of potential methane oxidation (methanotrophy) was measured using modified method of methane oxidation in soil samples from Hanson (1998). Briefly, 50 mL of methane was added by syringe to the closed incubation flask with the sieved sediment and then the pressure was balanced to atmospheric pressure. All laboratory sediment incubations were performed in 250-mL dark glass flasks, capped with rubber stoppers, using approximately 100 g (wet mass) of sediment (grain size < 2 mm). Typically, triplicate live and dead (samples killed by HgCl2 to arrest all biological activity) samples from each depth were stored at 20°C in the dark, and incubation time was 72 hours; however, subsamples from the headspace atmosphere were taken every 24 hours. Potential CH4 oxidation rates at the different concentrations were obtained from the slope of the CH4 decrease with time (r2 > 0.90; methane oxidation was calculated from the difference between final and initial headspace concentration and volume of the flask; results are expressed per volume unit of wet sediment (CH4 mL-1 WW hour‐1) or per unit dry weight of sediment per one day (mg CH4 kg-1 DW day-1).
Fluxes of methane across the sediment-water interface were estimated either by direct measurement with benthic chambers or calculated by applying Fick´s first law.
The methane fluxes across the sediment-water interface were measured using the method of benthic chambers (e.g. Sansone et al. 1998). Fluxes were measured during the summer months (VII, VIII, IX). The plexiglas chamber (2.6 dm3) covered an area 0.0154 m2. The chambers (n = 7) were installed randomly and gently anchored on the substrate without disturbing the sediment. Samples to determine of initial concentration of CH4 were collected from each chamber before the beginning of incubation. Incubation time was 24 hours. Samples of water were stored in 40 ml glass vials closed by cap with PTFE/silicone septum until analysis.
Fluxes of methane between the sediment and overlying water were calculated from Fick´s first law as described by Berner (1980):
where J is the diffusive flux in µg m-2 s-1, Ф is the porosity of the sediment, DS is the bulk sediment diffusion coefficient in cm-2 s-1, ∆C/∆x is the methane concetrations gradient in µg cm-3 cm-1. Bulk sediment diffusion coefficient (DS) is based on diffusion coefficient for methane in the water (D0) and tortuosity (θ) according to the formula:
Tortuosity (θ) is possible calculate from porosity according to equation (Boudreau 1996):
Diffusive fluxes of CH4 were determined at all five study sites along the longitudinal profile of the Sitka stream.
Gas flux across the air-water interface was determined by the floating chamber method four times during the year period in 2005 – 2006. The open-bottom floating PE chambers (5L domes with an area of 0.03 m2) were maintained on the water’s surface by a floating body (Styrene) attached to the outside. The chambers (n = 4 – 5) were allowed to float on the water‘s surface for a period of 3 hours. Previous measurements confirmed that time to be quite enough to establish linear dependence of concentration change inside the chambers on time for the gas samples collected every 30 min over a 3 hour period. Due to trees on the banks, the chambers at all study sites were continuously in the shade. On each sampling occasion, ambient air samples were collected for determining the initial background concentrations. Samples of headspace gas were collected through the rubber stopper inserted at the chamber’s top, and stored in 100mL PE gas-tight syringes until analysis. Emissions were calculated as the difference between initial background and final concentration in the chamber headspace, and expressed on the 1m2 area of the surface level per day according to the formula:
where F is a gas flux in mg m-2day-1; cI is a concentration of particular gas in the chamber headspace in μg L-1; cR is a concentration of particular gas in background air; V is volume of the chamber in L; t is time of incubation in hr; p is an area of chamber expressed in m2. For each chamber, the fluxes were calculated using linear regression based on the concentration change as a function of time, regardless of the value of the coefficient of determination (cf. Duchemin et al. 1999, Silvenoinen et al. 2008).
In order to assess emissions produced from a total stream area, the stream was divided into five stretches according to the channel width, water velocity and substrate composition. For each stretch we have then chosen one representative sampling site (locality I-V) where samples of both stream and interstitial waters and sediments, respectively, were repeatedly taken. Localities were chosen in respect to their character and availability by car and measuring equipments. For calculation of whole-stream gases emissions into the atmosphere, the total stream area was derived from summing of 14 partial stretches. The area of these stretches was caculated from known lenght and mean channel width (measured by a metal measuring type). Longitudinal distance among the stretches was evaluated by using ArcGIS software and GPS coordinates that have been obtained during the field measurement and from digitalised map of the Sitka stream. The total area of the Sitka stream was estimated to be 181 380 m2 or 0.18 km2. Stretches have differed in their percentual contribution to this total area and also by their total lenght (Table 1).
The total annual methane emissions to the atmosphere from the five segments of the Sitka stream, Ea (kg yr-1) were derived from seasonal average, maximum or minimum emissions measured on every locality and extrapolated to the total area of the particular segment. The total methane emissions produced by the Sitka stream annualy were then calculated according to the following formula:
where Ea is average, maximal or minimal assess of emission of methane from the total stream area in kilograms per year; pi is an area of stretch (in m2) representing given locality; Fi is average, maximal or minimal assess of the methane from a given locality expressed in mg m-2day-1.
Interstitial water samples for carbon isotopic analysis of methane and carbon dioxide were collected in 2010 - 2011 through three courses at study site. Sampling was performed by set of minipiezometers placed in a depth of 20 to 60 cm randomly in a sediment. After sampling, refrigerated samples were transported (within 72 hours) in 250 mL bottles to laboratory at the Department of Plant Physiology, Faculty of Science University of South Bohemia in Ceske Budejovice, which are equipped with mass spectrometry for carbon isotopes measurements. Firstly both water samples, for methane and for carbon dioxide, were extracted to helium headspace. After relaxation time isotopic equilibrium was achieved and four subsamples of gas were determined by GasBanch (ThermoScientific) and IRMS DeltaplusXL equiped by TC/EA (ThermoFinnigan) for analysis of δ13CO2. Afterwards δ13CO2 of water samples were calculated from gaseous δ13CO2 by fractionation factor from a linear equation (Szaran 1997):
Stable isotope analysis of 13C/12C in gas samples was performed using preconcentration, kryoseparation of CO2 and gas chromatograph combustion of CH4 in PreCon (ThermoFinnigan) coupled to isotope ratio mass spectrometer (IRMS, Delta Plus XL, ThermoFinnigan, Brehmen, Germany). After conversion of CH4 to CO2 in the Finningan standard GC Combustion interface CO2 will be tranfered into IRMS. The obtained 13C/12C ratios (R) will be referenced to 13C/12C of standard V-PDB (Vienna-Pee-Dee Belemnite)(Rs), and expressed as δ13C = (Rsample/Rstandard – 1) x 1000 in ‰. The standard deviation of δ13C determination in standard samples is lower than 0.1‰ with our instrumentation. From our data, we also calculated an apparent fractionation factor αC that is defined by the measured δCH4 and δCO2 (Whiticar et al. 1986):
This fractionation factor gives rough idea of magnitude of acetoclastic and hydrogenotrophic methanogenesis.
For measuring of microbial parameters, formaldehyde fixed samples (2 % final conc.) were first mildly sonicated for 30 seconds at the 15 % power (sonotroda MS 73, Sonopuls HD2200, Sonorex, Germany), followed by incubation for 3 hours under mild agitation with 10 mL of detergent mixture (Tween 20 0.5%, vol/vol, tetrasodium pyrophosphate 0.1 M and distilled water) and density centrifugation (Santos Furtado & Casper 2000, Amalfitano & Fazi 2008). For density centrifugaton, the non-ionic medium Nycodenz (1.31 g mL-1; Axis- Shield, Oslo, Norway) was used at 4600 G for 60 minutes (Rotofix 32A, Hettich, Germany). After the preparation processes, a 1 mL of Nycodenz was placed underneath 2 ml of treated slurry using a syringe needle (Fazi et al. 2005). 1 ml of supernatant was then taken for subsequent analysis.
The supernatant was filtered onto membrane filters (0.2 μm GTTP; Millipore Germany), stained for 10 minutes in cold and in the dark with DAPI solution (1 mg/ ml; wt/ vol; Sigma, Germany) and gently rinsed in distilled water and 80 % ethanol. Filters were air-dried and fixed in immersion oil. Stained cells were enumerated on an epifluorescence microscope (Olympus BX 60) equipped with a camera (Olympus DP 12) and image analysis software (NIS Elements; Laboratory Imaging, Prague, Czech Republic). At least 200 cells within at least 20 microscopic fields were counted in three replicates from each locality. TCN was expressed as bacterial numbers per 1 mL of wet sediments.
The methanogenic archaea, three selected methanogen families (Methanobacteriaceae, Methanosetaceae and Methanosarcinaceae) and methanotrophic bacteria belonging to groups I and II were detected using FISH (Fluorescence in situ hybridization) with 16S rRNA-targeted oligonucleotide probe labelled with indocarbocyanine dye Cy3. The prokaryotes were hybridized according to the protocol by Pernthaler et al. (2001). Briefly, the supernatants which were used also for TCN were filtered onto polycarbonate membrane filters (0.2 μm GTTP; Millipore), filters were cut into sections and placed on glass slides. For the hybridization mixtures, 2 μL of probe-working solution was added to 16 μL of hybridization buffer in a microfuge tube. Hybridization mix was added to the samples and the slides with filter sections were incubated at 46 °C for 3 hours. After incubation, the sections were transferred into preheated washing buffer (48 °C) and incubated for 15 minutes in a water bath at the same temperature. The filter sections were washed and air-dried. The DAPI staining procedure followed as previously described. Finally, the samples were mounted in a 4:1 mix of Citifluor and Vecta Shield. The methanogens and methanotrophs were counted in three replicates from each locality and the relative proportion of bacteria, archaea, methanogens and methanotrophs to the total number of DAPI stained cells was then calculated.
Nucleic acids were extracted from 0,3 g of sieved sediment with a Power Soil DNA isolation kit (MoBio, Carlsbad, USA) according to the manufacturer’s instructions. 16S rRNA gene fragments (~350 bp) were amplified by PCR using primer pair specific for methanogens. Primer sequences are as follows, 0357 F-GC 5’-CCC TAC GGG GCG CAG CAG-3‘ (GC clamp at 5’-end CGC CCG CCG CGC GCG GCG GGCGGG GCG GGG GCA CGG GGG G) and 0691 R 5’- GGA TTA CAR GAT TTC AC -3‘ (Watanabe et al. 2004). PCR amplification was carried out in 50 µL reaction mixture contained within 0.2 mL, thin walled micro-tubes. Amplification was performed in a TC-XP thermal cycler (Bioer Technology, Hangzhou, China). The reaction mixture contained 5 µL of 10 × PCR amplification buffer, 200 µM of each dNTP, 0,8 µM of each primer, 8 µL of template DNA and 5.0 U of FastStart Taq DNA polymerase (Polymerase dNTPack; Roche, Germany). The initial enzyme activation and DNA denaturation were performed for 6 min at 95°C, followed by 35 cycles of 1 min at 95°C, 1 min at 55°C and 2 min at 69°C and a final extension at 69°C for 8 min (protocol by Watanabe et al. 2004). PCR products were visualised by electrophoresis in ethidium bromide stained, 1.5% (w/v) agarose gel.
DGGE was performed with an INGENYphorU System (Ingeny, Netherlands). PCR products were loaded onto a 7% (w/v) polyacrylamide gel (acrylamide: bisacrylamide, 37.5:1). The polyacrylamide gels were made of 0.05% (v/v) TEMED (N,N,N,N-tetramethylenediamine), 0.06% (w/v) ammonium persulfate, 7 M (w/v) urea and 40 % (v/v) formamide. Denaturing gradients ranged from 45 to 60%. Electrophoresis was performed in 1×TAE buffer (40 mM Tris, 1 mM acetic acid, 1 mM EDTA, pH 7.45) and run initially at 110V for 10 min at 60°C, afterwatds for 16 h at 85 V. After electrophoresis, the gels were stained for 60 min with SYBR Green I nucleic acid gel stain (1:10 000 dilution) (Lonza, Rockland USA) DGGE gel was then photographed under UV transilluminator (Molecular Dynamics). Images were arranged by Image analysis (NIS Elements, Czech Republic). A binary matrix was created from the gel image by scoring of the presence or absence of each bend and then the cluster tree was constructed (programme GEL2k; Svein Norland, Dept. Of Biology, University of Bergen).
Fragments of the methanogen DNA (~470 bp) were amplified by PCR using mcrA gene specific primers. Primer sequences for mcrA gene are as follows, mcrA F 5’-GGTGGTGTACGGATTCACACAAGTACTGCATACAGC-3‘,mcrA R 5’-TTCATTGCAGTAGTTATGGAGTAGTT-3‘. PCR amplification was carried out in 50 µl reaction mixture contained within 0.2 mL thin walled micro-tubes. Amplification was performed in a TC-XP thermal cycler (Bioer Technology, Hangzhou, China). The reaction mixture contained 5 µL of 10 x PCR amplification buffer, 200 µM of each dNTP, 0.8 µM of each primer, 2 µL of template DNA and 2.5 U of FastStart Taq DNA polymerase (Polymerase dNTPack; Roche, Mannheim, Germany). The initial enzyme activation and DNA denaturation were performed for 6 min at 95°C, followed by 5 cycles of 30s at 95°C, 30s at 55°C and 30s at 72°C, and the temperature ramp rate between the annealing and extension segment was set to 0.1°C/s because of the degeneracy of the primers. After this, the ramp rate was set to 1°C/s, and 30 cycles were performed with the following conditions: 30 s at 95°C, 30 s at 55°C, 30s at 72°C and a final extension at 72°C for 8 min. PCR products were visualised by electrophoresis in ethidium bromide stained, 1.5% (w/v) agarose gel.
Purified PCR amplicons (PCR purification kit; Qiagen, Venlo, Netherlands) were ligated into TOPO TA cloning vectors and transformed into chemically competent Escherichia coli TOP10F’ cells according to the manufacturer’s instructions (Invitrogen, Carlsbad, USA). Positive colonies were screened by PCR amplification with the primer set and PCR conditions described above. Plasmids were extracted using UltraClean 6 Minute Plasmid Prep Kit (MoBio, Carlsbad, USA), and nucleotide sequences of cloned genes were determined by sequencing with M13 primers in Macrogen company (Seoul, Korea). Raw sequences obtained after sequencing were BLAST analysed to search for the sequence identity between other methanogen sequences available in the GenBank database. Then these sequences were aligned by using CLUSTAL W in order to remove any similar sequences. The most appropriate substitution model for maximum likelihood analysis was identified by Bayesian Information Criterion implemented in MEGA 5.05 software. The phylogenetic tree was constructed by the maximum likelihood method (Kimura 2-parameter model). The tree topology was statistically evaluated by 1000 bootstrap replicates (maximum likelihood) and 2000 bootstrap replicates (neighbour joining).
The physicochemical sediment and interstitial water properties of the investigated sites showed large horizontal and vertical gradients. Sediment grain median size decreased along a longitudinal profile while organic carbon content in a sediment fraction < 1 mm remained unchaged (Table 2). Generally, interstitial water revealed relatively high dissolved oxygen saturation with the exceptions of localities IV and V where concentration of dissolved oxygen sharply decreased with the depth, however, never dropped below ~ 10%. Vice versa, these two localities were characterized by much higher concentrations of ferrous iron and dissolved methane (Table 2) compared to those sites located upstream. Concentration of the ferrous iron reflects anaerobic conditions of the sediment and showed the highest concentration to occur in the deepest sediment layers (40-50cm). Average annual temperatures of interstitial water at localities in downstream part of the Sitka stream were about 2.5 oC higher compared to localities upstream and may probably promote higher methane production occuring here. Precursors of methanogenesis, acetate, propionate and butyrate were found to be present in the interstitial water at all study sites, however, only acetate was measured regularly at higher concentration with maximum concentration reached usually during a summer period.
Variable/ Locality | I | II | III | IV | V |
particulate organic C in sediment < 1 mm [%] | 0.9 | 0.9 | 0.6 | 1.3 | 0.7 |
interstitial dissolved O2 saturation [%] | 80.5 | 88.1 | 82.3 | 38.5 | 50.9 |
ferrous iron [mg L-1] | < 1 | < 1 | 1.8 | 8.1 | 4.2 |
acetate [mmol L-1] | 0.21 | 0.34 | 0.52 | 1.87 | 0.29 |
interstitial CH4 concentration [µg L-1] | 4.9 | 0.7 | 8.1 | 2 480.2 | 42.8 |
methanogenic potential[pM CH4 mL‐1 WW hour‐1] | 6.6 | 1.9 | 2.9 | 80.7 | 9.7 |
methanotrophic activity[nM CH4 mL‐1 WW hour‐1] | 0.3 | 1.3 | 28.5 | 30.3 | 25.1 |
average daily interstitial water temperature [oC] | 8.7 | 9.4 | 11.6 | 11.2 | 11.4 |
Selected physicochemical parameters (annual means) of the hyporheic interstitial water and sediments of studied localities taken from the depth 25-30 cm.
Methanogenic potential (MP) was found to be significantly higher in the upper sediment layer compared to that from deeper sediment layer. Generally, average MP varied between 0.74‐158.6 pM CH4 mL‐1 WW hour‐1 with the highest values found at site IV. Average methanotrophic activity (MA) varied between 0.02– 31.3 nM CH4 mL‐1 WW hour‐1 and the highest values were found to be at the downstream localities while sediment from sites located upstream showed much lower or even negative activity. Similar to MP, values of MA were significantly higher in sediments from upper layers compared to those from deeper layers (e.g. Figs. 3c, 3d).
Methane concentrations ranged between 0.18 – 35.47 µg L-1 in surface water and showed no expected trend of gradual increase from upstream localities to those laying downstream. However, significant enhancement of CH4 concentration was found on locality IV and V, respectively. Concentrations of dissolved CH4 inboth surface and interstitial waters peaked usually during summer and autumn period (Hlaváčová et al. 2005, Mach et al. in review).
Generally, methane concentrations measured in interstitial water were much higher compared to those from surface stream water and on a long-term basis ranged between 0.19 - 11 698.9 µg L-1. Due to low methane concentrations in interstitial water at localities I and II, vertical distribution of its concentrations was studied only at the downstream located sites III-V. Significant increase of the methane with the sediment depth was observed at the localities IV and V, respectively. Namely locality IV proved to be a methane pool, methane concentrations in a depth of 40 cm were found to be one order of magnitude greater than those from the depth of 20 cm (Tab. 3). Recent data from locality IV show much lower methane concentrations in the upper sediment horizons compared to those from deeper layers (Fig. 3a). Considerable lowering of methane concentration in upper sediment horizons is likely caused by oxidizing activity of methanotrophic bacteria (Fig. 3d). while dissolved oxygen concentration sharply decreased with the sediment depth (Fig. 3b).
Locality | Profile (depth) | CH4 [µg L-1] |
III. | Surface water | 1.8 |
Interstitial water (depth 20cm) | 1.44 | |
Interstitial water (depth 40 cm) | 1.52 | |
IV. | Surface water | 5.52 |
Interstitial water (depth 20 cm) | 1 523.9 | |
Interstitial water (depth 40 cm) | 11 390.54 | |
V. | Surface water | 4.72 |
Interstitial water (depth 20 cm) | 6.92 | |
Interstitial water (depth 40 cm) | 24.4 |
Average concentrations of methane in the vertical sediment profile at localities III-V compared to those from surface water at the same sites
Usually, both the surface and interstitial water were found to be supersaturated compared to the atmosphere with locality IV displaying saturation ratio R to be almost 195 000. This high supersaturation greatly promote diffusive fluxes of methane to the atmosphere across air-water interface and is also an important mechanisms for loss of water column CH4.
Stable carbon isotope signature of carbon dioxide (δ13C-CO2) measured in the interstitial water ranged from -19.8 ‰ to -0.8 ‰, while carbon isotope signature of methane (δ13C-CH4) ranged between -72 ‰ to -19.8 ‰. This relatively high variation in the methane isotopic values could be caused due to consequential fractionation effects preferring light carbon isotopes like methane oxidation or fractionation through diffusion and through flow of an interstitial water. Contrary, the narrow range of the δ13C-CH4 was found in the sediment depth of 40-60 cm where a high methane production has occured. Here, the δ13C-CH4 values varied only from -67.9 ‰ to -72 ‰. Apparent fractionation factor (αC) varied also greatly from 1,004 to 1,076. Usually values of αC > 1.065 and αC < 1.055 are characteristic for environments dominated by hydrogenothropic and acetoclastic methanogenesis, respectively. Our measurements indicate predominant occurrence of a hydrogenothropic methanogenesis in the high methanogenic zones where the most amount of methane is produced and δ13C of CO2 values were markedly depleted (i.e. 13C enriched). This could be caused by enhanced carbon dioxide consumption by hydrogenothrophic methanogens, strongly preferring light isotopes. Nevertheless, both acetoclastic and hydrogenotrophic pathways take part in the methanogenesis along the longitudinal profile of the Sitka stream.
Vertical distribution of methane concentration in the interstitial water at study site IV, horizontal bars indicate 1 SE
Methane diffusion rate from deeper sediment layers depends on a methane concentration gradient whilst is affected by oxidation and rate of methanotrophic bacteria consumption. When diffusion fluxes are positive (positive values indicate net CH4 production), then surface water is enriched by methane which in turn may be a part of downstream transport or is further emitted to the atmosphere (Fig. 4).
Possible fate of the methane within hyporheic zone and two kinds of chambers for measurement of methane fluxes. Providing that some sites along the longitudinal stream profile should be sources of methane for the stream water, we chose locality IV to be suitable for benthic fluxes measurements.
On the contrary, when the fluxes of methane across the sediment-water interface are negative then all methane produced in the sediments is likely oxidized and consumed by methanotrophic bacteria here or transported via subsurface hyporheic flow.
Calculated diffusive fluxes of CH4 ranged from 0.03 to 2307.32 µg m-2 day-1 along the longitudinal profile. The lowest average values of diffusive fluxes were observed at study site II (0.11 ± 0.05 µg m-2 day-1) while the highest average values were those observed at study site IV (885.81 ± 697.54 µg m-2 day-1). Direct benthic fluxes of CH4 using the benthic chambers were measured at study site IV only and ranged from 0.19 to 82.17 mg m-2 day-1. We observed clear negative relationships between benthic methane fluxes and the flow discharge. During higher discharges when the stream water is pushed into sediments, methane diffusing from deeper sediments upward is either transported by advection through sediments downstream or is probably almost completely oxidized by methanotrophic bacteria due to increasing oxygen supply from the surface stream. As a consequence, very low or no benthic fluxes were recorded during the time of high flow discharge. Compared to calculated diffusive fluxes it is clear that fluxes obtained by direct measurement were approximately 15× higher than the fluxes calculated with using Fick´s first law. Thus, direct benthic fluxes were used for a calculation of water column CH4 budget.
Gaseous fluxes from surface water to the atmosphere were found at all localities except locality I, where emissions were not mesured directly but were calculated lately using a known relationships between concentrations of gases in surface water and their emissions to the atmosphere found at downstream laying localities II-V. Methane showed an increase in emissions toward downstream where highest surface water concentrations have also occured (Table 4). Methane emissions measured at localities II-V ranged from 0 – 167.35 mg m-2 day-1 and no gradual increase in downstream end was found in spite of our expectation. However, sharp increase in the amount of methane emitted from the surface water was measured at lowermost localities IV and V (Tab. 4). We found positive, but weak correlation between surface water methane concentrations and measured emissions (rs = 0.45, p < 0.05)(Fig. 5).
Locality/Gas | CH4 [mg m-2day-1] |
Locality I. | 2.39 |
Locality II. | 0.25 (0 – 0.6) n = 9 |
locality III. | 1.3 (0 – 5.01) n = 10 |
Locality IV. | 32.1 (7.3 – 87.9) n = 8 |
Locality V. | 36.3 (2.8 – 167.4) n = 12 |
Average emissions to the atmosphere and their range in parenthesis and from all localities except locality I. Emissions values for the locality I were calculated using a known relationships between concentrations of methane gas in surface water and its emissions to the atmosphere found at downstream laying localities II-V. n means sample size
Depending on the time of year we measured the emissions, values of Ea ranged from 430 to 925 kg year-1 for methane. Annually, approximately 0.7 tonne of methane was emitted to the atmosphere from the water level of the Sitka stream (total area ca 0.2 km2). The majority of annual methane emissions (90 %) occured in the lower 7 km of the stream (stretch IV and V) that represents only 1/5 of the total stream area. In addition, contribution of methane emissions to the total annual emissions was found to be the highest during spring-summer period (Mach et al. in review).
Relationships between atmospheric emissions and surface water concentrations of the methane. Each point represents the mean of five replicate emission measurements and the two replicates of stream water methane concentrations at all
The potentially important source and sinks terms for dissolved methane in the water column of the Sitka stream are shown in Figure 6. Previously calculated rates of inputs (benthic fluxes) and loss of dissolved CH4 through evasion to the atmosphere can be combined together with advection inputs and losses to yield a CH4 dynamics (budget) for any particular section of the stream.
Simple box model used to calculate a CH4 budget for the Sitke stream experimental section; advection in + supply = advection out + removal (box adjusted after de Angelis & Scranton 1993)
The CH4 budget determined for the 2011 sampling period in an experimental stream section is summarized in Figure 7. Benthic fluxes were measured along a stream section 45 m long with an area being ~ 200 m2. Positive fluxes of CH4 were found to occur at 30.9 % of the study area. Assuming that average benthic flux of methane across the sediment-water interface was 15.40 mg m-2 day-1, the benthic flux of 3081.39 mg CH4 day-1 should occur from the whole area of 200 m2. Average emission flux of CH4 across the water-air interface for all study sites was determined to be 14.47 ± 4.73 mg CH4 m-2 day-1. This value is slightly lower than the direct benthic flux of CH4 and suggests that some portion of methane released from the bottom sediments may contribute to increasing concentration of CH4 in the surface water. Average flow of the Sitka stream during time of benthic fluxes measurements was 0.351 m3s-1 (i.e. 351 L-1s-1). Therefore, we may expect that water column was enriched at least by 187.4 mg (i.e. 0.006 µg L-1) of CH4 from sediment at 45 m long section near study site IV during one day. Next study site V is located some 4 km downstream from the site IV. Average CH4 concentration difference in the stream water between these study sites was found to be 3.2 µg L-1 of CH4 indicating that CH4 supply exceeds slightly CH4 removal. Methane fluxes from the sediment would contribute to this concentration difference only by 0.6 µg L-1, thus, the immediate difference in the CH4 budget found between two studied sites IV and V indicates that there must likely be other sources of methane supply to the stream water (Fig. 7). This „missing source“ seems to be relatively small (0.9 mg CH4 0.351 m-3s-1), however, net accumulation of CH4 in the stream water during 4 km section of the Sitka stream below study site IV was almost 78 g CH4 per one day.
CH4 budget in mol day-1 for a section of the Sitka stream between study sites IV and V (lenght ca 4 km). The arrows correspond to those depicted in Figure 6.
Both methanogenic archaea and aerobic methanotrophs were found at all localities along the longitudinal stream profile. The proportion of these groups to the DAPI-stained cells was quite consistent and varied only slightly but a higher proportion to the DAPI-stained cells in deeper sediment layer 25-50 cm was observed. On average 23,4 % of DAPI-stained cells were detected by FISH with a probe for methanogens while type I methanotrophs reached ~ 21,4 % and type II methanotrophs 11,9 %, respectively. All three groups also revealed non-significant higher proportion to the TCN in deeper sediment layer; the abundance of methanogens and methanotrophs remained almost unchanged with increasing sediment depth. The average abundance of methanogens (0,88 ± 0,28 and 1,07 ± 0,23 x 106 cells mL-1 in the upper and deeper layer, respectively) and type II methanotrophs (0,44 ± 0,14 x 106 cells mL-1 and 0,56± 0,1 x 106 cells mL-1) increased slightly with the sediment depth, while type I methanotrophs revealed average abundance 0,98 ± 0,23 x 106 cells mL-1 in the deeper layer being lower compared to abundance 1,07± 0,28 x 106 cells mL-1 found in upper sediment layer (Buriánková et al. 2012). Very recently, however, using the FISH method we found that abundance of methanogens belonging to three selected families reached their maximum in the sediment depth of 20-30 cm and had closely reflected vertical distribution of acetate concentrations. Species of family Methanobacteriaceae grow only with hydrogen, formate and alcohols (except methanol), Methanosarcinaceae can grow with all methanogenic substrates except formate, and members of Methanosaetaceae grow ecxlusively with acetate as energy source. All three families also showed similar proportion to the DAPI stained cells, ranging in average (depth 10-50 cm) from 9.9% (Methanosarcinaceae) to 12.3% (Methanobacteriaceae) (Fig. 8).
The percentage of chosen methanogenic families as compared to the total bacterial cell numbers found in different sediment layers at locality no. IV, horizontal bars indicate 1 SE
Methanogenic communities associated with hyporheic sediments at two different depths (0-25 cm and 25-50 cm) along the longitudinal stream profile were compared based on the DGGE patterns. As shown in Fig. 9, the DGGE patterns varied highly among study localities (Fig. 9A), irrespective of the depth (Fig. 9B). However, presence of the bands in all samples indicates that methanogens may occur up to 50 cm of the sediment depth. The number of DGGE bands of the methanogenic archaeal communities was compared either among localites or among different sediment depths. A total of 22 different bands were observed in the DGGE image ranging from 4 (locality II) to 16 (locality IV) in the samples (Fig. 9A).
The number of DGGE bands also ranged from 2 to 10 for the samples from upper layer (0-25 cm) and from 2 to 11 for the samples from deeper layer (25-50 cm), respectively (Fig. 9B). We found no clear trend in the number of DGGE bands with increasing depth (Fig. 9B). Locality IV appears to be the richest in number of DGGE bands. We suppose that this might be due to most favorable conditions prevailing for the methanogens life as indicated by a relatively low grain median size, lower dissolved oxygen concentration or higher concentration of the ferrous iron compared to other localities (cf. Table 2).
The methanogenic community diversity in hyporheic sediment of Sitka stream was also analysed by PCR amplification, cloning and sequencing of methyl coenzyme M reductase (mcrA) gene. A total of 60 mcrA gene sequences revealed 26 different mcrA gene clones.
Number of DGGE bands associated with hyporheic sediments at two different depths along the longitudinal stream profile. A – Total number of all bands detected at each locality; B – number of bands found at different sediment depths
Most of the clones showed low affiliation with known species (< 97% nucleotide identity) and probably represented genes of novel methanogenic archeal genera/species, but all of them were closely related to uncultured methanogens from environmental samples (> 97% similarity) retrieved from BLAST. The 25 clones were clustered to four groups and were confirmed to be affiliated to Methanosarcinales, Methanomicrobiales and Methanobacteriales orders and other unclassified methanogens. The members of all three orders and novel methanogenic cluster were detected to occur in a whole bottom sediment irrespective of a depth, nevertheless, the richness of methanogenic archaea in the sediment was slightly higher in the upper sediment layer 0-25 cm (15 clones) than in the deeper sediment layer 25-50 cm (11 clones)(Buriánková et al. in review). The clones affiliated with Methanomicrobiales predominated in the deeper layer while Methanosarcinales clones dominated in the upper sediment layer. This prevalence of Methanosarcinales in the upper sediment layer was also confirmed by our FISH analyses as has been mentioned above.
In spite of commonly held view of streams as well-oxygenated habitats, we found both surface and interstitial water to be supersaturated with methane compared to the atmosphere at all five localities (Mach et al. in review). Availability of interstitial habitats for bacteria and archaea carrying out anaerobic processes has been confirmed by our previous (Hlaváčová et al. 2005, 2006; Cupalová & Rulík 2007) and contemporary findings. During this study we found relatively well developed populations of methanogenic archaea at all localities and that all localities also showed positive methanogenic potential. Emissions of methane from water ecosystems results from complex microbial activity in the carbon cycle (production and consumption processes), which depends upon a large number of environmental parameters such as availability of carbon and terminal electron acceptors, flow velocity and turbulence, water depth. In our previous paper (Hlaváčová et al. 2006), we suggested that surface water concentrations, and as a consequence methane gas emissions to the atmosphere would result from downstream transport of gases by stream water (advection in/out), and moreover, from autochthonous microbial metabolism within the hyporheic zone. If so, surface water is continually saturated by gases produced by hyporheic metabolism, leading to supersaturation of surface water and induced diffusion of these gases out of river water (volatizing). Moreover, the run-off and drainage of adjacent soils can also contribute greatly to the degree of greenhouse gas supersaturation (De Angelis & Lilley 1987, Kroeze & Seitzinger 1998, Worral & Lancaster 2005, Wilcock & Sorrell 2008). For example, CH4 in the estuarine waters may come from microbial production in water, sediment release, riverine input and inputs of methane-rich water from surrounding anoxic environments (Zhang et al. 2008b). For the European estuaries, riverine input contribute much to the estuarine CH4 due to high CH4 in the river waters and wetlands also play important roles. However, low CH4 in the Changjiang Estaury (China) may be resulted from the low CH4 in the Changjiang water together with the low net microbial production and low input from adjacent salt marshes (Zhang et al. 2008b). Dissolved methane concentrations in a surface water of Sitka stream is consistent with literature data on methane in rivers published by Middelburg et al. (2002) and Zhang et al. (2008b).
A knowledge of the stable carbon isotopic ratio of methane δ13C-CH4 in natural systems can be useful in studies of the mechanisms and pathways of CH4 cycling (Sansone et al. 1997). Values of carbon isotope signature of methane (δ13C-CH4) indicate biogenic nature of the methane, being usually in the range -27 ‰ up to -100 ‰ (Conrad 2004; Michener & Lajtha 2007). Whiticar et al. (1986) demonstrated that methane in freshwater sediments is isotopically distinguished by being relatively enriched in 13C (δ13C = -65 to -50‰) in contrast to marine sediments (-110 to -60‰). Accordingly, the two precursors of methane, namely acetate and CO2/H2, yield methane with markedly different δ13C values; methane from acetate is relatively enriched in 13C. Average minimum in the carbon isotopic composition of CH4 (-61.4 ‰) occurred deeper in sediments (60 cm) while average maximum in δ13C-CH4 occured in the lower sediment depth of 30 cm. Enrichment of 13C in CH4 probably reflects aerobic CH4 oxidation because oxidation would result in residual CH4 with δ13C-CH4 values less negative than the source CH4 (Barker & Fritz 1981; Chanton et al. 2004). However, this effect has been observed only at the study site IV.
Our working hypotesis suggested that along with the longitudinal profile of a stream, slope and flow conditions also change together with corresponding settling velocity, sediment composition and organic matter content. Thus, according to this prediction, sediment with prevalence of fine-grained particles containg higher amount of organic matter should dominate at the downstream stretches. Moreover, due to prevalence of anoxic environment, production of methane and its emissions was expected to be also higher here compared to that from upstream stretches. Based on our findings, it seems that this presumption is valid for the methane. In addition, we found higher methane concentrations in both the surface and interstitial water at the uppermost locality I compared to lower situated locality II. Similar situation with high methane concentration in the upstream part with subsequent decline further downstream was also reported from USA by Lilley et al. (1996). Dissimilarity of this first stretch is apparent in a comparison with the next, downstream laying stretch (locality II), represented by profile with steep valley and high slope. Generally, there were found very low methane concentrations either in surface or interstitial water and fluxes of emissions to atmosphere were also very low.
Flux rates of gaseous emissions into atmosphere depend on partial pressure of particular gas in the atmosphere and its concentration in a water, water temperature and further on the water depth and flow velocity. Thus, maximum peak of emissions may be expected during summer period and in well torrential stretch of the river. Silvennoinen et al. (2008), for example, found that the most upstream river site, surrounded by forests and drained peatlands, released significant amounts of CO2 and CH4. The downstream river sites surrounded by agricultural soils released significant amounts of N2O whereas the CO2 and CH4 concentrations were low compared to the upstream site. When consider seasonal distribution of methane emissions, it is clear, in concordance with above mentioned presumption, that majority of methane emissions was relesed during a warm period of the year (81%). Effect of temperature on methane production was also observed in southeastern USA where the most methane reased to the atmosphere during warm months (Pulliam 1993). In addition, close correlation between methane emissions and temperature was reported also from south part of Baltic Sea; the temperature has been found to be a key factor driving methane emissions (Heyer & Berger 2000).
These findings also indicate that we should be very carefull in making any generalization in total emissions estimation for any given stream or river. Even though some predictions can be made based on gas concentrations measured in the surface or interstitial water, results may be very different. From this point, noteworthy was locality IV; enormous concentrations of a methane found in the deep interstitial water were caused probably by very fine, clayed sediment containing high amount of organic carbon, as well as high DOC concentrations. Supersaturation led also to the enrichment of the surface water with methane - such places may be considered as very important methane sources for surface stream and, consequently source of emissons to the atmosphere.
CH4 can be produced and released into overlying near-bottom water through exchange at sediment-water interface. Methane released from the sediments into the overlying water column can be consumed by methanotrophs. Methanotrophs can oxidize as much as 100 % of methane production (Le Mer & Roger 2001). According to the season, 13-70 % of methane was consumed in a Hudson River water column (de Angelis et Scranton 1993). For the Sitka stream, measurement of benthic fluxes into the overlying surface waters indicates that methane consumption by methanotrophic bacteria is likely a dominant way of a methane loss, nevertheless some methane still supports relatively high average methane concentrations in the surface water and, in turn, high emissions to the atmosphere.
The methane production (measured as methanogenic potential) was found to be 3 orders of magnitude lower than the oxidation (methanotrophic activity), thus, almost all methane should be oxidized and consumed by methanotrophic bacteria and no methane would occur within the sediments. However, situation seems to be quite different suggesting that namely methanotrophic activity measured in a laboratory could be overestimated. Since oxidation of methane requires both available methane and oxygen, methanotrophic activity is expected to be high at sites where both methane and dissolved oxygen are available. Therefore, high values of the MA were usually found in the upper layers of the sediments (Segers 1998) or at interface between oxic and anoxic zones, respectively. Relatively high methanotrophic activity found in deeper sediments of the localities III-V indicates that methane oxidation is not restricted only to the surface sediments as is common in lakes but it also takes place at greater depths. It seems likely that oxic zone occurs in a vertical profile of the sediments and that methane diffusing from the deeper layer into the sedimentary aerobic zone is being oxidized by methanotrophs here. Increased methanotrophic activity at this hyporheic oxic-anoxic interface is probably evident also from higher abundance of type II methanotrophs in the same depth layer. Similar pathway of methane cycling has been observed by Kuivila et al. (1988) in well oxygenated sediments of Lake Washington, however, methane oxidation within the sediments would be rather normal in river sediments compared to lakes. All the above mentioned findings support our previous suggestions that coexistence of various metabolic processes in hyporheic sediments is common due to vertical and horizontal mixing of the interstitial water and occurrence of microbial biofilm (Hlaváčová et al. 2005, 2006).
The presence of relatively rich assemblage of methanogenic archaea in hyporheic river sediments is rather surprising, however it is in accordance with other studies. The number of total different bands (i.e. estimated diversity of the methanoges) observed in the DGGE patterns of the methanogenic archaeal communities was comparable with a number of the DGGE bands found in other studies. For example, Ikenaga et al. (2004) in their study of methanogenic archaeal community in rice roots found 15-19 DGGE bands, while Watanabe et al. (2010) showed 27 bands at different positiosns in the DGGE band pattern obtained from Japanese paddy field soils. Our results from the DGGE analysis are supported by cloning and sequencing of methyl coenzyme M reductase (mcrA) gene which also retrieved relatively rich diversity (25 different mcrA gene clones) of the methanogenic community in the Sitka stream hyporheic sediments. Similar richness in number of clones was also mentioned in a methanogenic community in Zoige wetland, where 21 different clones were found (Zhang et al. 2008a), while 20 clones were described in the methane cycle of a meromictic lake in France (Biderre-Petit et al. 2011). In addition, soils from Ljubljana marsh (Slovenia) showed 17 clones (Jerman et al. 2009), for example. Both DGGE and mcrA gene sequencing results suggest that both hydrogenotrophic and acetoclastic methanogenesis are an integral part of the CH4 - producing pathway in the hyporheic zone and were represented by appropriate methanogenic populations. Further, these methanogenic archaea form important component of a hyporheic microbial community and may substantially affect CH4 cycling in the Sitka stream sediments.
To our knowledge this study is the first analysis of the composition of active methanogenic/methanotrophic communities in river hyporheic sediments. By use of various molecular methods we have shown that both methanogenic archaea and aerobic methanotrophs can be quantitatively dominant components of hyporheic biofilm community and may affect CH4 cycling in river sediments. Their distribution within hyporheic sediments, however, only partly reflects potential methane production and consumption rates of the sediments. Rather surprising is the detection of methanotrophs in the deep sediment layer 25-50 cm, indicating that suitable conditions for methane oxidation occur here. In addition, this work constitutes the first estimation of sources, sinks and fluxes of CH4 in the Sitka stream and in 3rd order stream environment. Fluxes of CH4 from supersaturated interstitial sediments appear to be a main CH4 source toward the water column. Compared with CH4 production rates, the diffusive fluxes are very low due to efficient aerobic oxidation by methanotrophic bacteria, especially during higher flow discharges. Although fluxes to the atmosphere from the Sitka stream seems to be insignificant, they are comparable or higher in comparison with fluxes from other aquatic ecosystems, especially those measured in running waters. Finally, our results suggest that the Sitka Stream is a source of methane into the atmosphere, and loss of carbon via the fluxes of this greenhouse gas out into the ecosystem can participate significantly in river self-purification.
This work was supported by the Czech Grant Agency grant 526/09/1639 and partly by the Ministry of Education, Youth and Sports grants 1708/G4/2009 and 2135/G4/2009 and Palacký University IGA grant 913104161/31. We thank Lubomir Čáp and Vítězslav Maier for analyses of dissolved methane and acetic acids, Martina Vašková and Jiří Šantrůček are ackowledged for their help and suggestions when performing stable isotope analysis of 13C/12C in gas samples.
The concepts of hybrid threat and hybrid warfare are, presently, key concepts within strategic studies1 and intelligence studies2, with a core relevance in the new defense and security context that was enabled by the twenty-first century’s Fourth Industrial Revolution, driven by the synergization of cyberspace and artificial intelligence (AI), fueled by the accelerated and disruptive exponential expansion of machine learning (ML) [1, 2, 3]. Cyber operations, presently, constitute a key determinant component of hybrid strategies and tactics that configure the profile of hybrid threats and hybrid warfare [1]. Hybrid strategies, in the twenty-first century, involve the use of Information and Communication Technology (ICT) and AI tools to combine conventional and unconventional operations, amplifying the impact of these operations [1, 2, 3].
In the current context of hybrid operations, there are, presently, three major dimensions of hybrid strategic power, understood as the ability to achieve one’s strategic goals through hybrid operations, and these are:
Network power
AI power
Cooperation power
The first type of power is enabled by social networks and the ability to use cyberspace for propaganda, disinformation, and viral campaigns in what constitutes a form of information-based warfare as well as for implementing cyberattacks that can disrupt different sectors as well as stealing (and possibly leaking) of critical data.
The second type of power involves the use of AI, in particular ML tools, as support tools for different cyber operations that may, in turn, support hybrid strategies. The range of AI applications can go from operations that take advantage of network power to cyber disruption of key infrastructures.
The third type of power is specific of today’s defense and security environment, involving the cooperation of different state and non-state entities, the latter which include, for instance, organized criminal groups and terrorist groups that can cooperate with each other, supporting and enhancing each other’s operations.
In the present work, we address the relevance of cyberspace-based operations and AI for the implementation of hybrid strategies and reflect on what this cyber dimension of hybrid operations implies for the concept of what constitutes a cyberweapon, as well as strategies that take advantage of the weaponization of cyberspace. We also address the concept of human intelligence (HUMINT) operations and their role in hybrid operations, in particular, how HUMINT was used in the past to support hybrid operations and can play a key role in the present; this leads us to the conceptualization of hybrid HUMINT.
In Section 2, we review main concepts linked to hybrid operations and address the strategic profile of hybrid operations in its different dimensions.
In Section 3, we focus on cyber psychological operations (cyops) as a major part of hybrid strategies and address how the use of AI and ML in cyops can be employed for the operationalization of hybrid strategies, targeted at weaponizing social networks, showing that AI constitutes a central driver of the future of these operations and allowing us to produce an assessment of the near future of hybrid threats, including a new face of cyber terrorism.
In Section 4, we address another dimension of hybrid operations and hybrid threats which is the role of HUMINT and the concept of hybrid agent, reviewing how HUMINT was used in the past for the implementation of hybrid operations and how it can be used in the present as a nexus for the successful implementation of these operations. In Section 5, we conclude with a final reflection on the role of cyberspace and the need for an extended concept of hybrid resilience as a way to face hybrid threats.
Hybrid operations can be defined as the use of military and nonmilitary means to achieve one’s strategic goals [1, 2, 3]. This means that rather than open battle, one may use intelligence activities, subterfuge, and subversion in order to gain an advantage over the adversary.
Hybrid operations find a deep tradition in strategic thinking that can be traced back to the classics of strategic studies, in particular, to two of the main military classics of Ancient China [1, 4]: Sun Tzu’s Art of War and T’ai Kung’s Six Secret Teachings. These two works also inspired Japanese classical thinking about unconventional warfare and espionage and the use of specialized operatives that also implemented what can be considered today as hybrid operations. Operations with strategic and tactical dimensions were recorded during the transition from the Warring States period to the Edo period in different works. Of these different works, the Sandai Hidensho stands out, which consists of the scrolls that include the Bansenshukai [5], the Shoninki [6] and the Shinobi Hiden [7], these are three classical works on spying and on how to conduct subversive, covert, and unorthodox warfare, which also recognize the influence of Sun Tzu’s Art of War and T’ai Kung’s Six Secret Teachings [5, 6, 7].
While there is a deep tradition for hybrid operations in both Chinese and Japanese classics on warfare and spying, it is also important to stress that a thinking that is convergent with the Asian classics is also found in European Philosophical thinking about strategy and war, in particular in Machiavelli’s The Art of War [8], which also addresses what are considered today as operations that fall within the scope of hybrid operations in books six and seven of this work.
In T’ai Kung’s Six Secret Teachings, hybrid operations included corrupting key officials, using diplomacy as a weapon, compromising a kingdom’s economy, alienating the ruler from the people, spreading rumors, and using propaganda and what is known today as psychological warfare [4]; similar operations are also described in the main Japanese classic on the art of spying, the Bansenshukai [5].
In what regards hybrid operations, the strategic action is not, thus, restricted to the battlefield but rather includes acting on the economic, financial, social, and political levels as a way to avoid open warfare or to weaken the adversary so that if open warfare does take place, one can easily win over that adversary [4, 5].
Specifically military hybrid operations are covered in the T’ai Kung’s Six Secret Teachings, particularly in the Dragon Secret Teaching, in the section corresponding to the unorthodox army, and in the section addressing the civil offensive, in the Martial Secret Teaching [4], which is convergent with both the Japanese classics [5, 6, 7] and the European thinking [8].
One lesson that comes out of these classics of strategic studies and intelligence studies is the need for good governance and public policies as a way to guard against hybrid operations [4, 5], a point to which we will return in the last section of the present chapter. Disrupting governance goes to the key role of hybrid operations in classical strategy and intelligence thinking to undermine a country’s governance and to make the people turn against the policymakers.
This is a point that is recovered in today’s defense and security environment, present in different countries’ military thinking. On the Russian side, as stressed by Chekinov and Bogdanov [9], two Russian Defense specialists, information technologies make the new face of warfare to be dominated by information and psychological warfare.
The central driving forces behind the twenty-first century’s hybrid operations are cyber psychological operations (cyops), where information superiority plays a key role [1, 3, 9]. As stressed in [9], the new face of conflict is such that nonmilitary actions and measures are employed with ICTs used in order to target all public institutions in a target country. While this illustrates the Russian perspective on the twenty-first century conflict [1], we get a similar standpoint from Treverton [3], who is a former Chairman of the US National Intelligence Council. Treverton identified, in the pattern of hybrid operations, typical information cyop-based warfare tactics, using propaganda, fake news, strategic leaks, funding of organizations and supporting political parties, organizing protest movements (taking advantage of social networks), using cyber tools for espionage, attack and manipulation, economic leverage, use of proxies and unacknowledged war and supporting paramilitary organizations.
While deeply rooted in the past thinking of strategic studies and in past military practice, the above references [1, 2, 3, 9] show that the renewal of the concept of hybrid operations and the relevance of this concept in the twenty-first century strategic thinking and doctrine come from the fact that these operations now have an effectiveness amplified by the use of cyberspace, which is a determinant factor in the change of the profile of the defense and security threats coming from hybrid operations; more properly, as it is addressed in [1], the twenty-first century hybrid operations can be implemented by both state and non-state agents, and this implies a major shift in strategic power, where individuals and groups, which may not be state-sponsored, can use cyberspace and even AI-based systems to implement hybrid operations that can have significant impact on a given country’s governance [1, 2].
This adds a new dimension to hybrid threats, making the profile more complex from a defense and security standpoint, in the sense that we can have three types of hybrid operations’ profiles:
Type 1: state-sponsored operations implemented by a specific country or countries: these are implemented by countries and involve the human and technical resources of that country’s Armed Forces.
Type 2: non-state-sponsored operations: these are implemented by non-state agents and groups, not supported financially, politically, and logistically by any state.
Type 3: state-sponsored operations implemented by non-state agents: the use of hackers and techno-mercenarism, the political, financial, and logistic support to non-state agents and groups opens up the way for the implementation of joint operations that involve non-state agents and different countries (with an added level of plausible deniability for countries).
These three types of operations are key for the characterization of hybrid operations. The type 1 operation profile has always been an integral part of strategic thinking and doctrine regarding unorthodox strategies and tactics and the way in which one may win one’s goals without using conventional military forces, an approach that is considered in high regard within the context of the Chinese classics [4] and that is recovered also in the Japanese context of the employment of specialized operatives called shinobi no mono that were used as spies and specialists in covert operations, subversion, information warfare, and what are considered in the T’ai Kung’s Six Secret Teachings as unorthodox ways [5, 6, 7]. Currently, however, cyberspace has amplified the effectiveness potential of these unorthodox ways, making hybrid operations a core dimension of military doctrine and the twenty-first century conflict, a point argued extensively in [1, 2, 3, 9].
However, the state-sponsored hybrid operations, implemented by a country’s armed forces, intelligence agencies, or even specific cyber warfare units and, possibly, hybrid warfare units, are just part of the three types of hybrid operation profiles.
The type 2 operation profile is characteristic of a change in the strategic power dynamics due to cyberspace and availability of AI systems and is specific of the new defense and security framework of hybrid threats, namely, small groups, or even a sufficiently knowledgeable individual, with sufficiently sophisticated hacking skills, can perform hybrid operations, taking advantage of cyberattacks and AI tools and target a country’s governance, significantly disrupting that country with the same effectiveness as any state-sponsored attack. The threat ecosystem is, thus, no longer just one of the countries fighting each other but also of countries’ governments and infrastructures being threatened by non-state agents that can implement hybrid operations as disruptive as any type 1 operation.
The key to the issue is the fact that cyber tools and even AI systems are freely available and the exponential trend linked to AI and ML and the increased usage of connected devices and smart government solutions open up the way for an exponential increase in the ability and opportunities to attack a country’s governance with a low budget, this increases the disruptive potential of type 2 operation profile, which can be evaluated in terms of the increasingly low cost availability of means (including freely available bots and open-source malicious code dispersal), the increased dispersal of targets (due to the exponential trend associated with the Internet of Things (IoT)), and the ability to use cyberspace, including the dark web, to connect with like-minded individuals that are willing to support viral campaigns against specific targets.
Given the Fourth Industrial Revolution’s foreseeable trend, the type 2 operation profile is typically a profile that involves most operations in cyberspace, given the high impact and low cost of these operations. The ability of sufficiently motivated individuals and groups, sometimes involved with criminal organizations, to successfully implement a hybrid operation with the same level of impact as a state-sponsored campaign is a point that only recently has been addressed in the literature on hybrid threats [1, 3, 10, 11], a point raised in [10]. This is a gap in that literature since there may be an underestimation of rapidly emergent threats. The main problem lies in the fact that hybrid operations can be implemented with significantly less investment, especially if their main component is cyberspace-based, and this can be considered as low-cost warfare or, as stated in [11], war on the cheap.
The Fourth Industrial Revolution has opened up the ability for weaker opponents, both state and non-state, to effectively engage opponents with stronger military forces, decreasing the comparative advantage of these stronger opponents. The network power and AI power allow for a non-state agents to launch a hybrid campaign on a targeted country from anywhere in the world, such that one may have difficulty in ascribing a given physical/national territory to the attacker and single out that attacker’s country for a targeted conventional military response. A sufficiently sophisticated group can remain anonymous and even be transnational in the composition of its members, transitioning the defense problem from the traditional military dimension to a more complex response nexus of defense, intelligence, and law enforcement.
While type 2 operation profile is now being recognized as an increasing threat [1, 10, 11], with the tendency to increase in disruptive ability in the years to come, the type 3 operation profile has the potential for the most damage in that it involves the joint cooperation between state and non-state agents. This last operations’ profile takes advantage of the cooperation power; cooperation in hybrid operations can take the form of cooperation between different non-state agents, including terrorist groups and different criminal organizations; between different countries; and between state and non-state agents.
The cooperation between state and non-state agents may become a main source of state-sponsored hybrid threats [10, 11]; rather than engaging in large-scale state-on-state conflict, different states can support non-state agents or act in a timing that is confluent with the actions of non-state agents, enhancing the ability of non-state agents to produce a large disruption on a targeted country’s governance.
We are reaching a strategic context where both state and non-state agents can engage any given country by means of cyber operations, sabotage, espionage, and subversion [11], a point that also circles back to Sun Tzu’s Art of War [4]. Hybrid operations, whatever their profile, allow an opponent or opponents to produce an imbalance of power, acting on the target’s weaknesses, without engaging in conventional direct conflict and, possibly, even hiding their identities in the process.
The imbalance of power is linked, in Sun Tzu’s thinking, to the concept of power as the ability to exercise one’s authority and deliberative autonomy toward effective action; in this case, hybrid operations directly target a state’s power by undermining its governance.
These operations can, in particular, take advantage of:
Internal challenges to a state’s governance by certain groups that wish to undermine a state’s authority
Failure of a state in adapting to society’s concerns and its people’s problems, being unable to respond to disruptions to the state’s finances, economic problems, environmental problems, and social and political problems
A view in a country’s society that a regime has lost its legitimacy to rule
The above three targeted state-level weaknesses match what Margolis in [11] identified, respectively, as sources of three types of crises:
Crises of authority that result from a state’s inability to enforce its rule, not being able to control all of its territory, or becoming unable to enforce all its laws
Crises of resilience that result from a state’s inability to adapt to different disruptions
Crises of legitimacy that result from society’s view that a regime has lost its right to rule because it is wrong or unjust
These three types of crises can occur in a given country and be triggered by hybrid operations or amplified by well-timed hybrid operations, in particular, those that use information and cyberspace as a weapon.
Connecting the three profiles and crises, in Figure 1, we synthesize, in scheme, the links between the profiles of hybrid operations and the three types of crises identified by Margolis [11].
Hybrid operations profiles and crisis profiles.
The type 1 and type 2 operations are confluent with each other in the cooperation involved in type 3 operations. It is important to notice that, in some cases, a type 1 or a type 2 operation can lead to a type 3 operation, and that the timing of a type 1 with a type 2 operation can lead to a type 3 operation due to synchronized hybrid tactical actions. The three types of operations can all target the three weaknesses, authority, resilience, and legitimacy, amplifying state instability and leading a country into a crisis situation that may, in the limit, produce the fall of a government.
Now, regarding the means and vulnerabilities, it is important to stress that the Fourth Industrial Revolution also opens up the way for cyber-physical attacks, including attacks using drones and drone swarms, as well as cyberattacks on automated systems and cyber-physical systems; all these are dimensions of the wider cyber-enhanced synergy of conventional and unconventional operations that constitute the strategic and tactical ground for hybrid operations and that may predictably characterize the new level of hybrid operations in years to come.
The other side, which we are already seeing today, is situated in the virtual space but still able to severely affect countries’ governance; as stated above, this is the weaponization of cyberspace, using social networks and AI for hybrid operations. In this case, the actions are situated only in the virtual space, but they can have severe social, (geo) political, and economic consequences.
Platforms, in particular social networks, the manipulation of contents, and the use of AI, ML, and data science to manipulate people’s behavior, online and offline, are a major component in these operations, and it is the subject of the next section.
The strategic level of hybrid operations involves the definition of the main objectives for hybrid operations, the targets, and possible collaboration networks. The choice of resources and ways to combine them to operationalize the hybrid strategy depends upon the strategic deliberation. On the other hand, the means also condition the set of available tactics that may allow one to operationalize a given strategy.
The strategic power of hybrid operations in allowing for a state or non-state agents to achieve their strategic objectives has increased due to the resources available that allow for high yield with low investment; these resources are linked to the network power and AI power, defined at the beginning of the present chapter.
In what regards hybrid operations, the network power and AI power cannot presently be considered separately, since it is precisely the synergy of cyberspace and AI, in particular through ML, that determine the present strategic and tactical momentum of hybrid operations and that allow one to anticipate the future of hybrid threats. We now address one of the major components of hybrid operations, namely, information warfare and psychological operations using cyberspace.
Psychological operations (psyops) involve the use of different means and tactics in order to influence the behavior of target audiences. While, traditionally, psyops were employed by countries and constitute an integrating part of military doctrine, the expansion of cyberspace has led to the possibility of groups that are not part of any country’s official military branch to implement these operations. An example of this is ISIS’ online propaganda as well as hacktivist groups such as anonymous online activities.
The use of cyberspace and hacking, including the defacement of a country’s websites, the online dispersal of sensitive and/or compromising data through social media platforms, the possibility of using the dark web for the disclosure of sensitive data that can then be made public in the surface web, and the use of social media for propaganda and recruitment, for the denouncement of different causes, and for the manipulation of citizen journalism as a way to publish both true and fake news as well as to disperse other fake contents (including images, audio, and videos), all these are examples of ways in which psyops can be implemented using cyberspace, so, at present, psychological operations are an integral component of hybrid warfare in what constitute cyber psychological operations or cyops for short.
As stated previously, in the present chapter, cyops are a major part of hybrid operations, and cyber psychological tactics involved in cyops typically include [3]:
Propaganda (in particular, dispersed online through social media)
Fake contents (in particular, fake news)
Online dispersal of sensitive data (leaks)
Each of these tactics takes advantage of network power, AI power, and cooperation power. There are three drivers that have amplified the effectiveness of the above tactics:
The increased dispersal of connected devices, including smartphones and tablets that allow an easy and frequent access to the Internet
Search engines and online services that adapt to each user’s interaction pattern
The growing use of social media over traditional media
Added to this infrastructural accessibility to these devices is the high frequency use of these devices and sometimes addictive component associated with this use, an addictive component usually linked to social networks.
A specific pattern of usage favors the dispersal of sensitive data, news, and general contents in social media: the fact that the online reading of social media contents usually does not involve a high level of reflection but rather engages the users in a way that is meant to be appealing and to be shared quickly with as most people as possible, users seldom read or reflect deeply on the contents that they are sharing, usually skimming through them and sharing the most appealing ones.
This is a pattern that is particularly useful for dispersal of contents that are presented in the form of scandals, sensitive information that was not known, conspiracies’ denouncements, and so on. This point leaves a marker in data on fake content dispersal as shown in a study on the differential diffusion of verified (true) and false rumors on Twitter from 2006 to 2017, published in [12]. In the study, politics and urban legends stand out as the two categories with the highest frequency in rumor cascades.
The study concluded that rumors about politics, urban legends, and science spread to the most people, while politics and urban legends exhibited more intense viral patterns [12].
The study found a significant difference in the spread of fake contents vis-à-vis true contents, namely, true contents are rarely diffused to more than 1000 people, while the top 1% of fake rumor cascades are routinely diffused between 1000 and 100,000 people [12]. The authors’ results showed that fake contents reached more people at every depth of a cascade, which the authors defined as instances of a rumor spreading pattern that exhibit an unbroken retweet chain with a common, singular origin.
The result that fake contents reached more people at every depth of a cascade means that more people retweeted fake contents than true ones, a spread that was amplified by a viral dynamics. The authors found that fake contents did not just spread through broadcast dynamics but, instead, through peer-to-peer diffusion with viral branching.
Another relevant point, for hybrid operations, was that fake political contents traveled deeper and are more broadly reaching more people and exhibiting a stronger viral pattern than any other categories and diffusing deeper more quickly. This dynamics is not however due to users who spread fake contents having a greater number of followers; the study found exactly the opposite with a high statistical significance. In inferential terms, users who spread fake contents tend to have fewer followers, to follow fewer people, to be less active on Twitter, are verified less often, and have been on Twitter for less time. However, fake contents were 70% more likely to be retweeted than true contents with a p-value of 0.0 in Wald chi-square test.
The fact that user connectedness and network structure did not seem to play a relevant role in fake content dispersal made the authors seek other explanations for the differences in fake content versus true content dispersal. The authors reported that fake contents usually inspired greater number of replies exhibiting surprise and disgust. The authors’ hypothesis is that novelty may be a key factor in false rumor dispersal.
However, there is a relevant point to take into account when looking at the study’s results, which can be expressed by the following extreme example: an account with no followers and not following anyone can still get a high number of retweets and exposure on a content if it uses hashtags on hot topics and builds its tweet in a specific way that increases the probability of it being retweeted.
Moving beyond this specific study and considering social networks in general, working with the conceptual basis of strategic studies, we are led to introduce the concept of tactical accounts, defined as accounts that are created for tactical purposes in the support of a cyop strategy; these accounts can be managed by a single individual or staffs, and its operations can involve the use of bots that automatically generate contents with certain specifications, mostly aimed at making the contents viral in the spread.
The viral content design along with multiple accounts operated by bots are major tools for a tactical account system manager, that is, any operative can use multiple tactical accounts simultaneously to create a fake content dispersal so that it can gain momentum and become viral.
In general, fake contents can spread on hot topics by the use of hashtags or other means of dispersal, which diminishes the connectivity need for any single tactical account’s effective impact. Furthermore, from a cyops’ standpoint, it is easier to fly under the radar by managing multiple newly created fake accounts that can even be managed by a single agent, who may then use these accounts to disperse fake contents incorporating hashtags on political issues and composing the messages so that they have an appealing emotive content, making it more likely for people to select them.
Returning to the study [12], the fact that the authors did not find strong evidence that algorithms were biased toward spreading of fake contents but rather that fake contents were being dispersed by people is favorable to the point of the way in which the message is built as the key factor in getting a fake content to gain traction. This point is echoed in [13] where it is argued that the belief in fake contents is driven by emotional responses amplified by macro social, political, and cultural trends.
Social media are particularly sensitive to the careful crafting of the message to fit viral conditions, in the sense that these media are managed by platform-based businesses, optimized for quick spread of information to reach target audiences and mass dispersal; in this sense, they are aimed by design at viral dynamics and addictive usage patterns that increase the interaction time with the platform and create value for these businesses.
The technology is thus an enabler of viral dynamics and, in that way, facilitates fake contents’ dispersal by the way in which these contents are produced, in terms of the message that they contain, the emotional responses which they are aimed to evoke, and their timing and their management of conditions of dispersal (for instance, the use of hashtags on trending topics in Twitter); all this contributes to the increased likelihood that fake rather than true carefully crafted and reflection demanding content become viral.
Hybrid tactics can take advantage of multiple (fake) tactical accounts and use methods of automation of content generation, with possible applications of data science, in order to generate the content presentation that may be the most effective in getting people to adhere to and, thus, share. By working with data on viral tweets, ML algorithms may be trained in predicting the structure of a content that may make it more probable to become viral and use this to help a cyops operative design the message in order to make it more viral and then use tactical accounts to disperse it. Message contents, including hashtags, emoticons, and gifs, are useful tools in manipulating the message content to better fit a target audience [14].
Another way to manipulate viral content dispersal is cyberattacks aimed at compromising search engines and recommendation engines in order to disperse fake content that fits the goals of an intended cyop.
Search engine poisoning or even a more sophisticated search engineering has been applied in the past by black hats to spread malware and fake contents [15, 16].
There are various methods employed in this last context that can be highly effective for hybrid operations: the first is content injection in websites, online forums, and social media in the form of spam posts that can also point to specific websites used within a cyop; this is a task that can be automated.
A second level is the creation of networks of websites and social media accounts that spread alternate media messages and that reinforce echo chambers for specific content that can, thus, become viral, taking advantage of a concerted social media campaign that divulges these accounts.
The sharing of these accounts can, in turn, become viral and link to different alternate media websites that can be used for cyops and manipulate a user’s web search and interaction with different content platforms. If, in the interaction, with any search engine and content platform, there is a powerful algorithmic adaptation to each user’s pattern, then, any user, influenced by viral content, will have a tendency to be fed back the content that the cyop is aimed at. In this way, by strategically using viral dynamics, a cyop can manipulate a vast amount of users and engineer massive echo chambers where massive amounts of users get personalized content that fits the cyop in question.
In this case, the hacker or hackers do not need to compromise the AI systems that manage a social media platform; rather, they are hacking people’s behaviors and are taking advantage of the effectiveness of the platform’s own AI systems in adapting content to user interaction profile. Since the way a user interacts with a platform leads to a specific response on the part of the platform for automatic user personalization, each user gets his/her own experience; however, the commonality of usage patterns allows for collectives of users with common tastes to receive similar or confluent viral contents.
Creating and financing tactical networks of social media accounts amplify this hybrid strategy, as long as the platform adapts very quickly to a user’s profile facilitating the echo chamber engineering needed for the cyop to be successful. Similar tactics can be employed on any type of social network. However, of the different online media platforms, Facebook seems to stand out in terms of effectiveness of fake news dispersal, with a higher frequency of cases of visits to fake news websites occurring near a Facebook visit, as reported in [17].
Besides content injection in blogs, forums, and social media, another way for search poisoning involves content injection in compromised websites, as well as search redirection. Search redirection attacks employ sites that have been compromised to be used in a search redirection operation and whose owners usually do not suspect that their website has been compromised [16]. These source infections in turn redirect to traffic brokers that redirect traffic to specific destinations that fit the hackers’ main goal [16]. Currently, ML algorithms are being trained against redirection as a defense against it [18]; however, ML algorithms and data science can also be employed to manipulate content, including written text, pictures, and even videos. In the foreseeable future, a higher ability of deep fake videos to fool people may greatly enhance the impact of fake content dispersal.
While disinformation and propaganda, through online fake content and propaganda dispersal operations, have become highly impactful in terms of their strategic and tactical value [3, 17], there is another level of cyops that may be implemented by any state or non-state agent that can have a strong impact on society. This is exemplified by the Blue Whale Challenge, which is an example of the power of what can be considered a gamification attack.
Gamification attacks use the Internet to introduce a game which leads the players through a series of challenges down a path where those players are led to either self-harm or even murder. In the case of the Blue Whale Challenge, the players were led to self-harm. The game involved a series of life-threatening tasks given to players by a curator, and each player had to fulfill these tasks which ended with the suicide of the player [19]. In a certain sense, this constitutes a cyberspace-enabled form of murder, by leading a person to commit suicide. The Blue Whale Challenge’s curators can be treated as a new breed of serial killers that use the Internet for psychological and physical torture, eventually leading their victims to kill themselves as the endgame of the tasks that they give their victims.
If we replace the final task of suicide with a final task where the player has to murder someone else or even a number of people, perhaps even in exchange for the player’s own life (an either kill yourself or commit murder option), then, the Blue Whale Challenge becomes the first example of designing a web game that can lead not only people to suicide but also to murder on a scale and intensity that can be comparable to those of standard terrorist networks.
One should stress that this is a form of cyops that can easily be engineered by someone not affiliated to any terrorist group. A single person can take advantage of the power of cyberspace and of social networks to create such challenges; furthermore, even if the individual is caught and arrested, the game can go on independently of the individual, where anyone can become a curator. The game itself becomes the terror referent and the platform for terror practices.
This breaks with any traditional approach to engaging and handling terrorist organizations, since a terror game can be played by anyone, without any political goal, without any political affiliation, and with no end other than the exercise of violence. These new serial killers that become curators of these games can be caught and imprisoned, but the game can go on with different iterations. There is a form of digital autonomy and continuation of a terror game as a collective dynamics that is sustained by its players, but that goes on despite the catching of particular curator players, as long as it is available for playing; the game can even come back with new variations and remain, and even if it has no players, it can be played again at any time.
This is not a terror network that one can address with traditional tactics; it is a terror game, and the Blue Whale Challenge is just the first example of this. The game becomes the referent for any players, who may never have physically met. Systemically, the game becomes a dispositional driver for a typological order of cyber-enabled terrorist practices. Another point is that, potentially, such terror games can be sustained by non-humans, that is, by AI systems, and even if all human curators were caught and arrested, bots could take over and play the same role as a human curator (the player that abuses the other players). In this sense, a single individual, using AI systems, can create terror games, sustained by an “army” of cyop bots that will be difficult to stop. A new breed of the twenty-first-century serial killers can become a source of new cyber-enabled terrorism that uses gamification as a way to resiliently murder on a global scale, with an impact on par with that of major standard terrorist organizations.
The reason why bots can be used here as cyber psychological weapons, in such games as the Blue Whale Challenge, is linked to the algorithmic basis of these games’ approach; in particular, the behavior of curators can be algorithmically replicated by cyop bots. Indeed, the process involves using social networks to search for young people who fit specific profiles, which can include being depressed or showing addictive behavior. The list of tasks includes dynamics that introduce sleep deprivation, listening to psychedelic music, watching videos with disturbing contents sent by the curator, and inflicting wounds on one’s body, among other tasks [20]. The tasks follow a prescribed set of steps that lead the victim into a disturbed mental state and susceptible to the influence of the curator, the victim is a target of a form of cyop that falls within a pattern that can easily be turned into an algorithm.
The gamification of cyops in terror operations is in its infancy; however, the tools available to it are amplified by the IoT, mobile devices, and platform usage. In the Blue Whale Challenge, we see a new tactics based on platform weaponization, that is, the use of platform-based businesses to compromise its users and eventually lead to their deaths (in the case of the Blue Whale Challenge) or even to the killing of others (if instead of suicide the player is led to kill others).
Empowered by cyop bots, a small number of individuals, or even one individual, can create a game that may go on independently of them; the game can persist as a dynamics that continues to be played in the platform, which functions as a replicator for the deviant and predatory behavioral patterns needed for the terror game to go on. Having been played once, the dynamics that characterize the game can always come back; in this sense, the platform works as a way for the digital continuation of the terror game.
This is very different from the case of a terrorist network that has a hierarchical structure and that has cells and individuals that play different roles within an organization.
A terror game is just a set of behavioral patterns, with algorithmic components, that can be replicated like a form of social virus which goes on as long as there are players. There is no stable hierarchy and no cells and no individuals that can be targeted which may harm the game, because the game has a virtual fluid existence that can be perpetuated as a dynamics to be retrieved any time, any place.
The terror game is characteristic of a side of platforms, especially social networking platforms that make them highly weaponizable, namely, platforms are means for the exercise of biopower in the sense of Foucault [21], a point that is convergent with the issues addressed in [22].
Platforms can function as means for the exercise of control, reward, and punishment and of manipulation of its users’ desires, fears, and sources of inclusion and exclusion, integration and segregation, connection and isolation, and friendship and bullying.
By increasingly sharing one’s life in platforms and by using integrated systems, in particular IoT devices, the new stage of the Internet revolution is such that any heavy user of these systems can be datafied, profiled, and manipulated by hacked devices (including hacked AI systems) and manipulated by predators that use fake accounts and their victims’ profiles to launch directed cyops that can, in the end, as was the case with the Blue Whale Challenge, lead to a person’s death.
According to data, reported in [20], Instagram ranks higher in posts than the Russian VK social network (which was where the game spread initially) and Twitter. On Twitter, the large majority number of posts related to the Blue Whale Challenge was identified by the authors as coming from smartphones with the Android OS, which shows how mobile devices are useful in feeding terror gamification operations.
Another pattern revealed in these authors’ research is a key common factor in online cyop campaigns. In particular, many accounts talking about the Blue Whale Challenge were new accounts with not many followers; this shows again the possible use of tactical accounts. This is a basic necessary tactical choice for predators operating online, who will want to hide their identity; furthermore, in order to gain online traction on a cyop, the use of multiple tactical accounts is a necessary step. Thus, just as in state agents, non-state agents, including cyber-enabled serial killers, may tend to use multiple tactical accounts in online platforms when addressing their targets.
The use of challenges like the Blue Whale Challenge and the Momo Challenge directly targets a large amount of victims and constitutes a security and law enforcement problem [23].
Returning to cyops, whatever their profile, these are currently about using cyberspace and ML for hacking people’s behaviors. In this sense, while a cyop against a given country may take advantage of resilience, authority, or legitimacy vulnerabilities, the increasing use of the platform-based technologies, managed by ML algorithms, where each user’s data is exposed and available for exploitation, leads to another level of vulnerability which is the ability to use citizens’ own data and behavioral patterns against them or to manipulate citizens into patterns of behavior that interest a given state or non-state agent.
The fact that cyops have certain components that are algorithmizable implies that one can program bots as cyop weapons that function as a form of new computer virus, a behaviorally conditioning content-based virus that is aimed at hacking people’s behaviors, delivered through platforms for both mass exposure and personalization. The current trend of using algorithms for decision-making and in everyday life, integrated in platforms and that feed on each user’s data and adapting the service and contents to each user’s profile, makes AI weapons, employed in cyops, increasingly effective tools.
While the cyops that were discussed above include the creation and manipulation of contents to produce responses and manipulate people’s behaviors, the impact of these contents can become even more amplified if the dispersal of these contents is timed with the leak of true contents. In this case, people tend to believe the fake content that is consistent with the true content. The leak of true content can initiate a fake content campaign, where the true content provides the context for the fake contents that will be used in the fake content campaign.
In this case, leak platforms, like WikiLeaks, can be used by hackers, whistleblowers, as well as other agents (state and non-state agents) to disperse true content and provide the timing for initiating fake content campaigns. However, besides leak platforms, there is another level of hybrid operations which also increases the threat of these types of operations for any country; this is the new hybrid human intelligence/counterintelligence (CI) context, in which the concept of a new field agent is a key factor.
The concept of human intelligence involves a twofold dimension: to gather information from human sources that are not HUMINT operatives and to gather information from HUMINT operatives. In terms of operations, HUMINT involves [24]:
The clandestine acquisition of relevant data
The overt collection of relevant information by people overseas
The debriefing of foreign nationals and citizens who travel abroad
Official contacts with foreign governments
While budget restrictions, the cyberspace expansion, and the development of data science have fueled the interest in signals intelligence (SIGINT) and open-source intelligence (OSINT) and led to some divestment in HUMINT, considered, for instance, more expensive in terms of time and resources involved than OSINT, an approach that considers an opposition of HUMINT vs OSINT and HUMINT vs SIGINT is the wrong way to look at things from an intelligence/counterintelligence effectiveness standpoint, within the new defense and security context, characterized by the critical threat of hybrid operations.
In fact, one can robustly argue, from a technical and technological standpoint, that HUMINT is a major centerpiece driver of hybrid operations, a nexus around which SIGINT and OSINT can be leveraged, with the new agents on the ground being able to both gather strategic and tactical information, implement (cyber) subversive maneuvers, steal data, and even compromise critical systems of any organization.
In the new context of hybrid operations, a new breed of HUMINT operative is not only a spy but also a hacker and a hybrid operations specialist that can infiltrate an organization and bring it down from the inside. We call this the hybrid agent.
From a counterintelligence standpoint, the new dimensions of the threat of covert human agents need to be critically addressed. The first thing to stress is that the threat level is very high for any state; on the other hand, the operational advantage of the new breed of HUMINT operative is also very high, so that, from an intelligence/CI standpoint, states need to invest in both these new hybrid agents and to find countermeasures for them.
To fully realize the implications and measures of the concept of a hybrid agent, which is the main point of this section, we need to first address some conceptual dimensions from intelligence studies and strategic studies, since while the tools of the hybrid agent have changed and the profile and impact is new, there was an old case of a form of spy that fit this profile of hybrid agent which was employed in Japan’s Warring States period (Sengoku Jidai) and later in the Edo period. This old hybrid agent fits a similar profile and role that the new hybrid agent may come to fit in the years to come.
During the Sengoku Jidai, spies were mainly employed from the Samurai and Ashigaru classes, but progressively, especially in the Iga and Koka provinces, spying was systematized, developed, and integrated in a body of knowledge and skills that were taught to warriors, a body of knowledge that was built on top of the warrior normal training.
Different regions and Samurai clans also had their trained spies. It is important to stress at this point that there coexisted two types of spies in Japan: warriors who were employed as spies but that were not trained spies and warriors who, besides their normal martial training, were trained as spies. Another division that arose was between the trained spies that were a part of a Daimyo’s army and thus served the Daimyo and the spies for hire, mercenary spies.
Due to their skills, Iga and Koka spies became mercenary spies, that is, spies for hire that also operated based on alliances of these regions with different groups. It is important to consider what constitutes the body of knowledge that the Japanese incorporated in what they considered to be the art of spying, called shinobi no jutsu or ninjutsu, erroneously addressed in popular culture as a martial art, as assassination, and/or as warriors that opposed the samurai, all incorrect misconceptions [25].
The fact that traditional scrolls on this body of knowledge are hard to track down, being, in many instances, in private collections, in some way contributed to the misconception to be perpetuated and has produced a gap in the literature on intelligence which usually cites Sun Tzu’s Art of War but overlooks, in the study of the history of intelligence, the deep development of the theory, strategies, and tactics of intelligence that is present in the traditional texts on shinobi no jutsu, which, as a relevant point in dispelling the misconception, never cover any kind of hand-to-hand fighting techniques [5, 6, 7, 25, 26].
Recently, thanks to the efforts of the historian Antony Cummins and Yoshie Minami, the major texts are now translated into modern English, and Cummins has tracked down scrolls beyond the main known texts and translated them to English, making them available to the wider audience.
These texts allow people, researching in intelligence studies, to find new references that deepen Sun Tzu’s Art of War’s last chapter. These works, in particular [5, 26], develop in great detail a full body of knowledge in what the Japanese considered the art of spying and operationalize Sun Tzu’s Art of War’s last chapter into a detail that provides an insight into the history of intelligence.
The relevant point is that these works on shinobi no jutsu introduce a profile of an operative, the shinobi no mono, which is largely a hybrid warfare specialist, and also constitute some of the few examples of classical works that are only devoted to intelligence, that is, these are some of the few examples of Classical Intelligence Manuals that form a compendium of the main strategies and tactics of intelligence in Japan’s Warring States and Edo periods, some of which hold, in terms of their main patterns and principles, for any period and place.
If one analyzes these different classical Japanese works on what are today called intelligence studies [5, 6, 7, 25], one finds that, in Japan, the art of spying (shinobi no jutsu) included, among other specialized knowledge, a core of areas of expertise that, under close scrutiny, are generalizable to other countries and historical periods [27], and these areas include:
Military strategy and tactics
Scouting
Infiltration and tactical disruption
Unconventional warfare, including deep knowledge of subversive maneuvers and psychological operations
Deep knowledge of counterintelligence
Infiltration came in two ways [5]:
Yojutsu: which involved infiltrating the enemy in plain sight, that is, using long-term undercover agents
In jutsu: which involved stealing in, hiding from the enemy
In jutsu was largely employed during the Sengoku Jidai and already included the conventional and unconventional, where the trained agents infiltrated the enemy ranks, usually at night and used fire and unconventional tactics to disrupt the enemy in a way that allowed for a well-timed conventional open attack to ensue. These were the precursors of battlefield hybrid operations and are documented in detail in the Bansenshukai [5].
Yo jutsu usually needed someone with some level of scholarship, namely, from the Samurai class. This was the long-term undercover operative, which not only gathered information just like any HUMINT specialist but also employed subversive maneuvers, disinformation, counterintelligence, and political manipulation. One finds an example of this in the Bansenshukai [5], which reportedly is an Iga manual, but that may also contain a synthesis of Iga and Koka knowledge, where it is stated that an agent needed to obtain and keep copies of the marks and seals of the lords of various castles so that these could be used to forge letters in order to incriminate a target for conspiracy. Using agents to frame key people sow discord among the enemy’s ranks and even for assassination (in particular, through poisoning).
Undercover operatives (using yo jutsu) were employed for disrupting the enemy’s intelligence and decision-making process (disinformation), making false charges, spreading rumors (the dispersal of fake contents was already present in this period), and sowing domestic conflicts, discord, and doubts among the enemy’s vassalage, as well as for setting fires or causing confusion among the enemy’s castle in order for an open strike to occur. These are documented in the Bansenshukai [5] and are all parts of hybrid operations. Indeed, the play between the conventional and unconventional which is a key characteristic of shinobi no jutsu is strongly convergent with the two the major Chinese classics of strategy: Sun Tzu’s Art of War and T’ai Kung’s Six Secret Teachings [4], the latter which is considered in [5, 7] a Chinese reference on what the Japanese called shinobi no jutsu.
The Japanese knew of both works, and they are referenced in the different Japanese classical texts on shinobi no jutsu [5, 6, 7, 25, 26]. In particular, Sun Tzu’s five types of agents were employed and elaborated upon in terms of intelligence strategies and tactics in the context of the Japanese classics, and these five types are [4]:
Local spies (employing of locals to gather information)
Internal spies (employing people who hold government positions)
Double agents (employing the enemy’s agents)
Expendable spies (employed to spread disinformation outside the state; in the Japanese case, they used these in conjunction with the highly trained undercover operatives, which, due to their training, were not considered expendable but were, rather, high-valued assets that were used for what are today considered the core of hybrid warfare: disinformation, psyops, fake content and rumor spreading, sowing discord and unconventional strategies and tactics, besides spying per se)
Living spies (who returned with their reports)
In [26] these five types of spies are explicitly addressed with an in-depth analysis on the strategies and tactics that are involved in their usage.
To these five types, one can add another type, which holds a key value for the new hybrid operations’ context: the unwitting agent, who is supplying information for the enemy but is unaware of this fact. One can already find this type of agent in some passages of the Bansenshukai [5].
Now, taking into account this historical context, let us consider what we called the twenty-first century hybrid agent, which, in terms of operational profile, is used in the same manner as the shinobi no mono, namely, we have an expert in strategy and tactics that can be infiltrated in an organization (yo jutsu) and who will be used to both gather critical information (the standard classical HUMINT aspect) and find the main vulnerabilities of the target organization and, if given the activation order, is capable of disrupting the organization from the inside using cyberattacks, compromising key employees, releasing compromising data, and/or launching a fake content campaign against the organization.
Mirroring the setting of fire and the compromising of the intelligence cycle used in Medieval Japan, we now have the possibility of a long-term undercover operative to physically install malware and cyberweapons and hack critical systems to corrupt key data and disrupt the organization’s normal functioning.
Business, banking, healthcare, and government are particularly vulnerable sectors that can be hacked in this way. The businesses’ use of ML-supported OSINT can be compromised by malware aimed at attacking the ML infrastructure and thus corrupt strategic decisions, business secrets, and strategically sensitive data which can be stolen to undermine a target country’s business (state-sponsored corporate espionage) either by using these data for gaining a negotiation leverage, an R&D and competitive advantage or, simply, to disclose it, bringing losses to these businesses.
Companies and banking that employ platforms, in the new 4.0 paradigm, can have their platforms compromised by a hybrid agent, undermining the stakeholder confidence.
If there are corruption practices or any key figures in key business, banking and/or political sectors fall prey to entrapment (even digital entrapment); then, this can be used to disrupt a country’s business, banking, and even political sectors, even to turn the people against these sectors in well-orchestrated hybrid campaigns that use social networks to amplify the disruption effect. The principles behind this economic and political warfare, which is a key dimension of hybrid strategies, are expanded in detail in T’ai Kung’s Six Secret Teachings.
Our main point is that the new hybrid agent is a key player in making this type of hybrid operations effective. The reason for this is that while remote hacking, SIGINT, OSINT, and even cyber intelligence (CYBERINT) can be effective, the hybrid operative is more disruptive and may greatly enhance SIGINT, OSINT, and CYBERINT; there are a few reasons for this.
Hacking an organization becomes exponentially more effective if it is done by someone who is undercover inside the organization, and this person can have direct access to an organization’s critical systems and compromise them by physically installing malware. Social engineering also becomes easier and more effective if combined with direct personal interaction with human targets that can be hacked. Hacking colleagues’ smartphones, for instance, and other IoT devices can lead to a new form of unwitting agent: the person who takes his/her devices everywhere, devices that can be accessed by the hybrid operative and used to record audio, video, geographical data, and other personal data. This means that conversations can be recorded, video can be recorded, and even personal data can be gathered and used to compromise a target individual.
With increasing sensorization of organizations, a successful hybrid operative can turn the organization’s sensorization systems into his/her own listening devices. Furthermore, standard HUMINT can be combined with OSINT and SIGINT, where the hybrid operative can directly interact with a human target, hacking the target’s devices, employing social engineering tactics, and then combining the cyber intrusion with fake social network accounts, managed by a remote team that may follow the target on such places as Facebook, Twitter, Instagram, and so on, further interacting with this human target, using the social media, private chat systems, and even video chat sessions with remote support team operatives, in order to manipulate the target and find the target’s weaknesses, gaining the target’s confidence and possibly compromising the target or using that target as an (unwitting) source of information.
The trained hybrid operative must then be:
An expert in cyops
An expert in hybrid operations
A hacker with strong skills in social engineering
From a CI standpoint this is a major threat on two fronts:
On the state-sponsored front: the hybrid operative is a key nexus for combining synergistically HUMINT, OSINT, SIGINT, Social Network Intelligence (SOCINT), CYBERINT, and cyops, taking all this to a new level which can seriously disrupt a country’s key public and private organizations.
On the non-state-sponsored front: a very skillful hacker team or even an individual hacker, with strong social engineering skills, who have physically infiltrated a target and are supported by bots that automate the fake content dispersal, can, with very low cost, produce the same effect as a trained state-sponsored team.
The second front is a major problem, since it opens up the way for new hybrid warfare mercenarism; just as the Iga and Koka shinobi no mono were employed as mercenaries, it also opens up the way for non-state-sponsored hybrid attacks from individuals or groups that have a cause or even just a grudge against a target, individuals, and groups who are skilled hackers that can perform similar operations as a hybrid agent.
In this sense, there can be three operational profiles for hybrid agents which mirror the three operational profiles for hybrid threats addressed in Section 2:
Type 1 hybrid agent: an agent that belongs to a given state’s intelligence agency and that is operating covertly
Type 2 hybrid agent: an agent not linked to any intelligence agency but highly skilled in hacking and social engineering that is not operating on behalf of any state but is either a lone wolf or operating on behalf of some non-state group
Type 3 hybrid agent: an agent not linked to any intelligence agency but that performs hybrid operations for hire
The three types of agents may coexist and constitute a major threat for countries’ national security and defense; on the other hand, one may also recognize that, while constituting a threat, any state may take advantage of these three types of agents in its own operations, with particular relevance to types 1 and 3 as well as the relevance of the tactical openings provided by the actions of type 2 agents. There is a fluid border between the three types, where agents can change their profile along the course of their activities.
The question that can be raised is: what responses need to be implemented in terms of CI to deal with the twenty-first century hybrid agent? The answer is somewhat complex, in the sense that the threat landscape is changing with the exponential technological revolution that greatly enhances the disruptive power of the new hybrid HUMINT, which can synergistically combine traditional with high-tech methods to become one of the most disruptive forces in the new defense and security context, but, given an identification of major targets, in particular economic and financial targets (that may become key parts of economic, financial and political warfare), there are specific responses that need to come into play with some urgency. This forms part of our final reflection on the whole chapter and is integrated in the next section, which concludes the chapter.
Throughout the chapter we laid out the profile as well as the current and foreseeable evolution of hybrid operations and hybrid threats (Section 2). We also addressed the issue of weaponization of cyberspace, the use of AI and data science, and the threat patterns of cyber psychological operations in the context of hybrid operations (Section 3), and, in Section 4, we introduced the concept of hybrid agent, evaluating its overall pattern of activity and threat to countries’ defense and security.
Some major points need to be highlighted, when dealing with hybrid threats, namely:
Operations on the virtual space can have physical consequences, even in the cases where the operation does not directly disrupt physical systems.
Related to the previous point, behavioral hacking is a major component of cyops and can take advantage of the impact of fake contents, propaganda, disinformation, as well as strategic leaks of critical data, in order to affect people’s behaviors.
Gamification and implementation of viral online challenges can support terror games that may gain a form of digital continuity, such that the game can be recovered anytime, even after the arrest of key individuals and groups, being perpetuated independently of what happens to the initiators of these terror games, and can be kept going by bots as well as by people willing to play the game, taking advantage of the dynamics between AIs and social media.
A new form of operative, the hybrid agent, leads to an amplification of the synergy between HUMINT, SIGINT, and OSINT with HUMINT playing the nexus role, in which an undercover agent takes advantage of the physical presence on any given organization and employs classical HUMINT strategies and tactics along with hacking and cyops to enable and enhance the disruptive potential of well-orchestrated hybrid campaigns.
These are some major points that were addressed in detail in the previous sections. Now, as part of a final reflection, the question may be raised: what to do about all this?
From the work developed throughout the sections, one thing becomes clear: there is an urgent need for the strategic integration in key state and private organizations, including the defense and security community, of a concept of hybrid resilience, of which cyber resilience is just an aspect. In this sense, in what regards CYBERINT [28], its focus needs to address the profile of cyber-threats and cyop profiles associated with hybrid strategies, in the sense that tactical dynamics of cyberattacks may obey to the pattern needed for a given hybrid strategy, and it needs to cooperate with HUMINT/CI in order to find countermeasures against hybrid HUMINT operatives.
The concept of hybrid resilience as the ability to resist and recover from hybrid campaigns should be a major component of countries’ national defense and security strategies.
Now, secondly, organizations should have training and a hybrid defense and CI division or at least subcontract specialized people in this area, covering both cyber defense and cyber resilience as well as hybrid defense and resilience.
Faced with the threat of economic, financial, and (geo) political hybrid warfare, any country’s major business and financial targets should have specialized training programs and people involved in hybrid defense strategies and hybrid resilience, including CI-based defense against possible disruption from what may become the new disruptive face of HUMINT: the hybrid HUMINT.
It is not enough to secure the technical side of cybersecurity, and one needs to address the social and human aspect of cyber intrusion, in which people’s behavior can be turned against them, including the behaviors and vulnerabilities that come from incorrect social network usage.
Campaigns in the standard media against fake contents need to be addressed, as well as large-scale educational programs that should start in schools, educating civil society on the correct usage of cyberspace, on both the positive and negative, on how people can protect themselves against cyberbullying and hybrid campaigns, and on how people should read and reflect on the contents that they read and share.
While these are some of the major changes needed to be implemented for any country’s successful national hybrid defense strategy, there is a main point of hybrid resilience that was already identified in the old Chinese and Japanese classics, in particular in Tai Kung’s Six Secret Teachings [4] and in the Bansenshukai [5]: without good governance there is always a fundamental vulnerability to hybrid strategies.
The three major crisis profiles that were addressed in [29] and recovered in Section 2 come out of bad governance that is unable to face crises that affect its country’s people (resilience problems), that is totalitarian and oppressive and that enforces its rule by force or has alienated a large part of its people due to rising inequalities and widespread political, business, and financial corruption (legitimacy problems), or that is unable to manage its territory (authority problems). All these three problems open up any country to hybrid threats and reduce a country’s hybrid resilience.
IntechOpen aims to ensure that original material is published while at the same time giving significant freedom to our Authors. To that end we maintain a flexible Copyright Policy guaranteeing that there is no transfer of copyright to the publisher and Authors retain exclusive copyright to their Work.
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\\n\\nThe Corresponding Author shall obtain written informed consent for publication from people who might recognize themselves or be identified by others (e.g. from case reports or photographs).
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\\n\\nThe Corresponding Author also warrants and represents that: (i) they have the full power to enter into this Publication Agreement on their own behalf and on behalf of each Co-Author; and (ii) they have the necessary rights and/or title in and to the Chapter to grant IntechOpen, on behalf of themselves and any Co-Author, the rights and licenses expressed to be granted in this Publication Agreement. If the Chapter was prepared jointly by the Corresponding Author and any Co-Author, the Corresponding Author warrants and represents that: (i) each Co-Author agrees to the submission, license and publication of the Chapter on the terms of this Publication Agreement; and (ii) they have the authority to enter into this Publication Agreement on behalf of and bind each Co-Author. The Corresponding Author shall: (i) ensure each Co-Author complies with all relevant provisions of this Publication Agreement, including those relating to confidentiality, performance and standards, as if a party to this Publication Agreement; and (ii) remain primarily liable for all acts and/or omissions of each such Co-Author.
\\n\\nThe Corresponding Author agrees to indemnify and hold IntechOpen harmless against all liabilities, costs, expenses, damages and losses and all reasonable legal costs and expenses suffered or incurred by IntechOpen arising out of or in connection with any breach of the aforementioned representations and warranties. This indemnity shall not cover IntechOpen to the extent that a claim under it results from IntechOpen's negligence or willful misconduct.
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The Corresponding Author (acting on behalf of all Authors) and INTECHOPEN LIMITED, incorporated and registered in England and Wales with company number 11086078 and a registered office at 5 Princes Gate Court, London, United Kingdom, SW7 2QJ conclude the following Agreement regarding the publication of a Book Chapter:
\n\n1. DEFINITIONS
\n\nCorresponding Author: The Author of the Chapter who serves as a Signatory to this Agreement. The Corresponding Author acts on behalf of any other Co-Author.
\n\nCo-Author: All other Authors of the Chapter besides the Corresponding Author.
\n\nIntechOpen: IntechOpen Ltd., the Publisher of the Book.
\n\nBook: The publication as a collection of chapters compiled by IntechOpen including the Chapter. Chapter: The original literary work created by Corresponding Author and any Co-Author that is the subject of this Agreement.
\n\n2. CORRESPONDING AUTHOR'S GRANT OF RIGHTS
\n\n2.1 Subject to the following Article, the Corresponding Author grants and shall ensure that each Co-Author grants, to IntechOpen, during the full term of copyright and any extensions or renewals of that term the following:
\n\nThe aforementioned licenses shall survive the expiry or termination of this Agreement for any reason.
\n\n2.2 The Corresponding Author (on their own behalf and on behalf of any Co-Author) reserves the following rights to the Chapter but agrees not to exercise them in such a way as to adversely affect IntechOpen's ability to utilize the full benefit of this Publication Agreement: (i) reprographic rights worldwide, other than those which subsist in the typographical arrangement of the Chapter as published by IntechOpen; and (ii) public lending rights arising under the Public Lending Right Act 1979, as amended from time to time, and any similar rights arising in any part of the world.
\n\nThe Corresponding Author confirms that they (and any Co-Author) are and will remain a member of any applicable licensing and collecting society and any successor to that body responsible for administering royalties for the reprographic reproduction of copyright works.
\n\nSubject to the license granted above, copyright in the Chapter and all versions of it created during IntechOpen's editing process (including the published version) is retained by the Corresponding Author and any Co-Author.
\n\nSubject to the license granted above, the Corresponding Author and any Co-Author retains patent, trademark and other intellectual property rights to the Chapter.
\n\n2.3 All rights granted to IntechOpen in this Article are assignable, sublicensable or otherwise transferrable to third parties without the Corresponding Author's or any Co-Author’s specific approval.
\n\n2.4 The Corresponding Author (on their own behalf and on behalf of each Co-Author) will not assert any rights under the Copyright, Designs and Patents Act 1988 to object to derogatory treatment of the Chapter as a consequence of IntechOpen's changes to the Chapter arising from translation of it, corrections and edits for house style, removal of problematic material and other reasonable edits.
\n\n3. CORRESPONDING AUTHOR'S DUTIES
\n\n3.1 When distributing or re-publishing the Chapter, the Corresponding Author agrees to credit the Book in which the Chapter has been published as the source of first publication, as well as IntechOpen. The Corresponding Author warrants that each Co-Author will also credit the Book in which the Chapter has been published as the source of first publication, as well as IntechOpen, when they are distributing or re-publishing the Chapter.
\n\n3.2 When submitting the Chapter, the Corresponding Author agrees to:
\n\nThe Corresponding Author will be held responsible for the payment of the Open Access Publishing Fees.
\n\nAll payments shall be due 30 days from the date of the issued invoice. The Corresponding Author or the payer on the Corresponding Author's and Co-Authors' behalf will bear all banking and similar charges incurred.
\n\n3.3 The Corresponding Author shall obtain in writing all consents necessary for the reproduction of any material in which a third-party right exists, including quotations, photographs and illustrations, in all editions of the Chapter worldwide for the full term of the above licenses, and shall provide to IntechOpen upon request the original copies of such consents for inspection (at IntechOpen's option) or photocopies of such consents.
\n\nThe Corresponding Author shall obtain written informed consent for publication from people who might recognize themselves or be identified by others (e.g. from case reports or photographs).
\n\n3.4 The Corresponding Author and any Co-Author shall respect confidentiality rights during and after the termination of this Agreement. The information contained in all correspondence and documents as part of the publishing activity between IntechOpen and the Corresponding Author and any Co-Author are confidential and are intended only for the recipient. The contents may not be disclosed publicly and are not intended for unauthorized use or distribution. Any use, disclosure, copying, or distribution is prohibited and may be unlawful.
\n\n4. CORRESPONDING AUTHOR'S WARRANTY
\n\n4.1 The Corresponding Author represents and warrants that the Chapter does not and will not breach any applicable law or the rights of any third party and, specifically, that the Chapter contains no matter that is defamatory or that infringes any literary or proprietary rights, intellectual property rights, or any rights of privacy. The Corresponding Author warrants and represents that: (i) the Chapter is the original work of themselves and any Co-Author and is not copied wholly or substantially from any other work or material or any other source; (ii) the Chapter has not been formally published in any other peer-reviewed journal or in a book or edited collection, and is not under consideration for any such publication; (iii) they themselves and any Co-Author are qualifying persons under section 154 of the Copyright, Designs and Patents Act 1988; (iv) they themselves and any Co-Author have not assigned and will not during the term of this Publication Agreement purport to assign any of the rights granted to IntechOpen under this Publication Agreement; and (v) the rights granted by this Publication Agreement are free from any security interest, option, mortgage, charge or lien.
\n\nThe Corresponding Author also warrants and represents that: (i) they have the full power to enter into this Publication Agreement on their own behalf and on behalf of each Co-Author; and (ii) they have the necessary rights and/or title in and to the Chapter to grant IntechOpen, on behalf of themselves and any Co-Author, the rights and licenses expressed to be granted in this Publication Agreement. If the Chapter was prepared jointly by the Corresponding Author and any Co-Author, the Corresponding Author warrants and represents that: (i) each Co-Author agrees to the submission, license and publication of the Chapter on the terms of this Publication Agreement; and (ii) they have the authority to enter into this Publication Agreement on behalf of and bind each Co-Author. The Corresponding Author shall: (i) ensure each Co-Author complies with all relevant provisions of this Publication Agreement, including those relating to confidentiality, performance and standards, as if a party to this Publication Agreement; and (ii) remain primarily liable for all acts and/or omissions of each such Co-Author.
\n\nThe Corresponding Author agrees to indemnify and hold IntechOpen harmless against all liabilities, costs, expenses, damages and losses and all reasonable legal costs and expenses suffered or incurred by IntechOpen arising out of or in connection with any breach of the aforementioned representations and warranties. This indemnity shall not cover IntechOpen to the extent that a claim under it results from IntechOpen's negligence or willful misconduct.
\n\n4.2 Nothing in this Publication Agreement shall have the effect of excluding or limiting any liability for death or personal injury caused by negligence or any other liability that cannot be excluded or limited by applicable law.
\n\n5. TERMINATION
\n\n5.1 IntechOpen has a right to terminate this Publication Agreement for quality, program, technical or other reasons with immediate effect, including without limitation (i) if the Corresponding Author or any Co-Author commits a material breach of this Publication Agreement; (ii) if the Corresponding Author or any Co-Author (being an individual) is the subject of a bankruptcy petition, application or order; or (iii) if the Corresponding Author or any Co-Author (being a company) commences negotiations with all or any class of its creditors with a view to rescheduling any of its debts, or makes a proposal for or enters into any compromise or arrangement with any of its creditors.
\n\nIn case of termination, IntechOpen will notify the Corresponding Author, in writing, of the decision.
\n\n6. INTECHOPEN’S DUTIES AND RIGHTS
\n\n6.1 Unless prevented from doing so by events outside its reasonable control, IntechOpen, in its discretion, agrees to publish the Chapter attributing it to the Corresponding Author and any Co-Author.
\n\n6.2 IntechOpen has the right to use the Corresponding Author’s and any Co-Author’s names and likeness in connection with scientific dissemination, retrieval, archiving, web hosting and promotion and marketing of the Chapter and has the right to contact the Corresponding Author and any Co-Author until the Chapter is publicly available on any platform owned and/or operated by IntechOpen.
\n\n6.3 IntechOpen is granted the authority to enforce the rights from this Publication Agreement, on behalf of the Corresponding Author and any Co-Author, against third parties (for example in cases of plagiarism or copyright infringements). In respect of any such infringement or suspected infringement of the copyright in the Chapter, IntechOpen shall have absolute discretion in addressing any such infringement which is likely to affect IntechOpen's rights under this Publication Agreement, including issuing and conducting proceedings against the suspected infringer.
\n\n7. MISCELLANEOUS
\n\n7.1 Further Assurance: The Corresponding Author shall and will ensure that any relevant third party (including any Co-Author) shall, execute and deliver whatever further documents or deeds and perform such acts as IntechOpen reasonably requires from time to time for the purpose of giving IntechOpen the full benefit of the provisions of this Publication Agreement.
\n\n7.2 Third Party Rights: A person who is not a party to this Publication Agreement may not enforce any of its provisions under the Contracts (Rights of Third Parties) Act 1999.
\n\n7.3 Entire Agreement: This Publication Agreement constitutes the entire agreement between the parties in relation to its subject matter. It replaces and extinguishes all prior agreements, draft agreements, arrangements, collateral warranties, collateral contracts, statements, assurances, representations and undertakings of any nature made by or on behalf of the parties, whether oral or written, in relation to that subject matter. Each party acknowledges that in entering into this Publication Agreement it has not relied upon any oral or written statements, collateral or other warranties, assurances, representations or undertakings which were made by or on behalf of the other party in relation to the subject matter of this Publication Agreement at any time before its signature (together "Pre-Contractual Statements"), other than those which are set out in this Publication Agreement. Each party hereby waives all rights and remedies which might otherwise be available to it in relation to such Pre-Contractual Statements. Nothing in this clause shall exclude or restrict the liability of either party arising out of its pre-contract fraudulent misrepresentation or fraudulent concealment.
\n\n7.4 Waiver: No failure or delay by a party to exercise any right or remedy provided under this Publication Agreement or by law shall constitute a waiver of that or any other right or remedy, nor shall it preclude or restrict the further exercise of that or any other right or remedy. No single or partial exercise of such right or remedy shall preclude or restrict the further exercise of that or any other right or remedy.
\n\n7.5 Variation: No variation of this Publication Agreement shall be effective unless it is in writing and signed by the parties (or their duly authorized representatives).
\n\n7.6 Severance: If any provision or part-provision of this Publication Agreement is or becomes invalid, illegal or unenforceable, it shall be deemed modified to the minimum extent necessary to make it valid, legal and enforceable. If such modification is not possible, the relevant provision or part-provision shall be deemed deleted.
\n\nAny modification to or deletion of a provision or part-provision under this clause shall not affect the validity and enforceability of the rest of this Publication Agreement.
\n\n7.7 No partnership: Nothing in this Publication Agreement is intended to, or shall be deemed to, establish or create any partnership or joint venture or the relationship of principal and agent or employer and employee between IntechOpen and the Corresponding Author or any Co-Author, nor authorize any party to make or enter into any commitments for or on behalf of any other party.
\n\n7.8 Governing law: This Publication Agreement and any dispute or claim (including non-contractual disputes or claims) arising out of or in connection with it or its subject matter or formation shall be governed by and construed in accordance with the law of England and Wales. The parties submit to the exclusive jurisdiction of the English courts to settle any dispute or claim arising out of or in connection with this Publication Agreement (including any non-contractual disputes or claims).
\n\nLast updated: 2020-11-27
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