CC BY
30
2017, Т. 159, кн. 3 С. 492-509
УЧЕНЫЕ ЗАПИСКИ КАЗАНСКОГО УНИВЕРСИТЕТА. СЕРИЯ ЕСТЕСТВЕННЫЕ НАУКИ
ISSN 2542-064X (Print) ISSN 2500-218X (Online)
UDC 574.56
ASSESSMENT OF ACTIVE VERTICAL CARBON TRANSPORT:
NEW METHODOLOGY
L.E. Kwong, E.A. Pakhomov
University of British Columbia, Vancouver, BC V6T1Z4 Canada
Abstract
Estimating active carbon transport in aquatic ecosystems has proven to be a labor-intensive and time-consuming process. This study proposes a novel approach to assess active carbon transport of zooplankton and micronekton based on the biomass spectra theory. This method is unique, as compared to the previous studies, because it relies solely on organism size rather than taxonomy. To predict active carbon transport, we use abundance size spectra during the day and night in the epipelagic zone, binned into log-2 size bins, which can then be used to calculate nominal size class and total abundance for each size bin. These calculations are applied to pre-existing size-dependent rate equations for respiration, excretion, mortality and gut flux, along with system temperature, time spent at depth, and depth of vertical migration. In combination with optical and acoustic methods, we hope that this method will shed light on the vast contribution of zooplankton and micronekton to global carbon export, and encourage the inclusion of active carbon transport estimates into global biogeochemical models. This will aid better understanding of the climate change implications to the global carbon cycling.
Keywords: zooplankton, micronekton, vertical migrations, active carbon transport, biomass spectra theory
1. Introduction
Oceans play a critical role in global carbon cycling by absorbing ~48% of the atmospheric anthropogenic CO2 into surface waters, pumping carbon both passively and actively to the deep ocean [1]. CO2 concentrations in the ocean are high at depth and low at the surface, resulting in a vertical concentration gradient [2]. This gradient is maintained by three pumps: the solubility pump, the carbonate pump, and the soft-tissue pump [2]. The solubility pump is driven by temperature dependent CO2 solubility. The carbonate and soft-tissue pumps form the biological pump, which is responsible for maintaining ~70% of the vertical concentration gradient [2]. The biological carbon pump involves the consumption of CO2 in the surface waters by phytoplankton during photosynthesis to produce organic and/or calcium carbon particles. These particles may then be transported to the mesopelagic zone (200-1000 m depth) by way of gravitational settling (passive transport) or vertically migrating organisms (active carbon transport/flux) [2-4]. When these particles reach the mesopelagic zone, they are either returned to their inorganic form via decomposition and dissolution below the euphotic zone, or re-introduced to the food web through consumption [2]. Aerobic metabolism and decomposition involve consumption of oxygen; therefore, the mesopelagic zone
POC (mgC m"2d )
Fig. 1. Hypothetical POC flux and attenuation with depth. Inspired by [9]
typically coincides with the vertical oxygen minimum zone (OMZ) [5]. Changes in oceanic conditions driven by climate change may therefore influence the efficiency of all three pumps, thereby impacting atmospheric carbon concentrations [2].
Zooplankton and micronekton play a pivotal role in active and passive carbon transport. Passive carbon transport (particulate organic carbon [POC] flux) occurs when phytoplankton sink as marine snow, or after organic matter passes through the guts of zooplankton as compact fecal pellets [6, 7]. As this matter sinks, it is fragmented, degraded, consumed and respired by larger organisms [8]. As such, POC attenuates with depth as depicted in Fig. 1.
In the mesopelagic zone, bacteria and zooplankton contribute substantially to particle transport and attenuation [8, 10]. Measurements of passive carbon flux are highly resolved both spatially and temporally (Fig. 2) [11]. However, the carbon demands of the mesopelagic community are notably higher than the passive flux [10, 12]. This suggests that the mesopelagic carbon budget is largely met by carnivory on vertically migrating organisms (i.e., active carbon transport) [10, 13, 14]. Nevertheless, a portion of this carbon may be met by organic carbon production (e.g., chemoauto-trophy [15]) and lateral transport (coastal to open ocean [16, 17]) within the mesopelagic realm.
Active carbon transport refers to the transport of organic matter by vertically migrating organisms, such as zooplankton and micronekton (Fig. 3) [6, 19, 20], that migrate below the mixed layer [4, 21, 22], diurnally [21, 23, 24], seasonally or ontoge-netically [25-27]. Diel vertical migration (DVM) acts as a mechanism for minimizing the exposure to visual predation [28-31]. During DVM, animals remain below the euphotic zone during the day, and migrate to productive surface waters during
Fig. 2. Global distribution of modelled annual mean log10-transformed passive carbon export at 100 m (mgC m-2 d-1) obtained from [18] with permission
Sft phytoplankton $ Bacteria 1 ' Particle aggregates Zooplankton
Mjrctophids "^Pflfrv Euphausiids
Fig. 3. Conceptual diagram of the biological carbon pump, depicting passive and active carbon flux in the water column
the night to feed (Fig. 3) [20]. After consuming phytoplankton and other non-migrating zooplankton at night, large zooplankton and micronekton metabolize the transported carbon via respiration, excretion, and defecation during the day at depth where they are also exposed to the predation and natural mortality (Fig. 3) [4, 6, 7, 20, 21, 27, 32-34].
Longhurst et al. [33] measured the respiratory flux of zooplankton undergoing DVM for the first time, noting that it added between 5% and 20% to the current estimates
Table 1
Percent range of active to passive flux to at least 100 m depth for the Pacific, Atlantic, Indian, Southern, and Arctic Oceans in tropical, subtropical, temperate, and polar regions. The specific locations of each of the study sites are depicted in Fig. 4. Full data set is available in [43]. NA = no data available
Climatic Region Pacific Atlantic Indian
Tropical 4-53% NA NA
Subtropical 0-95% 18-11% NA
Temperate 1-52% 1-13% NA
Polar NA 100-132% NA
of vertical carbon flux. In doing so, Longhurst and his colleagues set in motion the concept of quantifying active carbon transport by vertically migrating marine organisms such as plankton and nekton. Since then, active carbon transport has been identified as a significant contributor to downward carbon transport [35].
Spatial estimates of active to passive carbon transport ratios in the water column are all recent, highly variable (ranging from 0% to 132%), and limited (Table 1), while temporal estimates are generally absent. This reflects spatial heterogeneity in the distribution, production, and composition of zooplankton and micronekton, as well as methodological limitations [4, 6, 33-38, 39]. In Hawaiian waters, active carbon flux was reported to range from 6% to 25% of the mean passive flux [39], while another study reported that decapod active flux alone ranged from 5% to 8% of the total passive flux to ~700 m depth [40]. Fish-mediated export has been reported to represent 95% of passive carbon transport [41], while other studies have reported ranges of 1% to 73% (Table 1) [42].
Unlike assessment of passive flux (Fig. 2), estimates of active flux are also spatially and temporally limited (Table 1; Fig. 4). Studies have primarily focused on active carbon transport via respiration, excretion, gut flux and/or mortality of individual species [27, 57], groups (i.e., zooplankton or micronekton [19]) or specific size ranges (Fig. 4) [20, 32, 58]. It is crucial that the whole community be assessed, including both small and large migrants [57], and that all fluxes (excretion, respiration, mortality and gut flux) are considered [6, 58]. For example, micronekton is capable of vertically migrating to the lower extent of the mesopelagic zone (500-1000 m [59]) and, due to their long gut passage time (4-10 hours [60]), they can effectively metabolize and excrete their stomach contents at these depths. Therefore, by focusing on a single species, group, flux, or passive carbon transport alone, carbon export to the deep ocean remains substantially underestimated (up to 70%) [32, 58, 61-65].
Currently, there is little understanding of key processes at the zooplankton and micronekton levels, including the contribution of these organisms to global carbon export to the deep ocean [66]. As in the case of terrestrial systems, the structure of aquatic food webs is size dependent [67-72]. A pattern that has been formalized as the biomass spectra theory, in which the abundance/biomass of organisms is plotted against the size class (e.g. length or biomass), gives rise to a linear graph with a slope close to -1 (Fig. 5). The size distribution shows that larger animals are less abundant than smaller animals (Fig. 5). Several studies have confirmed this pattern in various aquatic systems, exhibiting the classic decrease in abundance/biomass of individuals
Fig. 4. Image depicting the locations of past studies of active carbon transport. The circle size represents the relative active carbon flux, the letters represent animals for each study, and the colours represent fluxes for each study: respiration [R], excretion [E], gut flux [G], and mortality [M]. Studies assessing only migratory biomass are not included in this image. Data sources: [4, 10, 19-21, 27, 32-35, 37-39, 41, 42, 44-48, 50-56]
Fig. 5. Conceptual diagram of biomass size spectra
with increasing body size (e.g., [73-84]). These studies focused primarily on pelagic communities and included organisms ranging from bacteria to fish [75, 76, 85, 86]. Biomass size spectra can be used to assess ecosystem health [87], fisheries productivity [68, 88, 89], and pollution/anthropogenic effects [90-94].
Biomass size spectra are of particular interest, because their shape can be used to determine community respiration, mortality, excretion, growth and gut flux rates [95-98], which are directly related to active carbon flux. The previous studies have found that zooplankton size spectra become less negative (flatter) during zooplankton DVM into the epipelagic zone [76, 77, 99]. However, when myctophids and gonosto-matids, two of the most abundant micronekton, are present in the epipelagic, zooplankton biomass size spectra become more negative (i.e., steeper), regardless of time of day [100]. This arises due to strong predation on larger zooplankton during DVM. Thus, these changes in biomass size spectra by depth and time provide an exciting venue, by which we can assess active carbon transport from the epi- to mesopelagic zone.
This paper presents a novel method, by which active carbon transport of zooplankton and micronekton can be quantified by taking a biomass/production size dependent approach based on the fundamentals of the biomass spectra theory. This method provides an approach to estimate spatially and temporally resolved active carbon transport. In combination with optical and acoustical methods, this method provides a promising venue by which the uncertainty associated with active carbon transport can be minimized for inclusion into biogeochemical models.
2. Proposed Methodology
Collectively, total community respiratory (i?), mortality (M), excretory (E ), and gut ((?) fluxes at depth make up the total active carbon flux for the given community: Total Active Carbon Transport = i? + M + £' + G.
Here we use abundance size spectra expressed as the log-transformed average abundance (ind.m-2) against biomass (mgC). By measuring the nighttime epipelagic abundance size spectra of zooplankton and/or micronekton, we can quantify total community active carbon transport. To calculate each of the size dependent rates (respiration, excretion, gut flux, and mortality), the data are first binned (e.g., log2 size bins) and the nominal size class for each bin is determined according to Blanco et al. [101, 102]:
^ = wt fc-lx-^j .
Where WNi is the nominal size class (in mg of carbon weight (CWNi) or dry weight (DWNi)) that represents all organisms within this size bin, Wi is the lower limit of the size class (mg), b is the slope of the size spectra, and c is that rate of geometric increasing of classes (with log2 size bins this is 2). Therefore, the nominal size class for each size bin is the weighted mean size. The abundance of individuals in each nominal size class can then be calculated by integrating the size distribution, such that:
i
= J N(w)dx.
i+i
Where, i represents the lower limit of each size bin and i+1 represents the upper limit of each size bin. This approach has provided us with representative nominal size classes (expressed in mgC) and total abundance in each nominal size class. From there the size dependent rates can be easily calculated, by taking into consideration
the amount of time spent at depth, as well as the temperature in the mesopelagic zone. Ideally, time at depth and depth of export will be determined using acoustics. To account for daytime epipelagic residents, the daytime epipelagic size spectrum is subtracted from the nighttime epipelagic size spectrum. This subtracted abundance size spectrum can then be used to calculate active carbon transport, according to the following methodology. Where daytime epipelagic size spectra are not available, we can also make corrections for daytime epipelagic residents by using acoustics.
To calculate the total community respiratory flux based on the biomass spectra theory, we apply Ikeda's [103] empirical allometric relationship between respiration and carbon weight for a variety of zooplankton and micronekton. The respiratory rate of oxygen uptake is first calculated followed by the respiratory carbon equivalent for each nominal size class. The total community respiratory flux (i?) can be calculated from there as follows:
Where R(CWNi) is the respiration for an individual in nominal size class Ni, NWNi is the total abundance of individuals in nominal size class i.
For excretion, we apply the relationship between CO2 respiration and DOC excretion (E(CWNi)) for macrozooplankton and micronekton from Steinberg et al. [4]. This calculation assumes DOC excretion is 31% of the CO2 respired. Therefore, this can be determined directly from the respiration calculations above. To calculate the total community excretory flux (E) from there, we can then simply add the excretion rates for each nominal size class together as follows:
For mortality, the Zhang and Dam [34] adaption of Peterson and Wroblewski [104] can be applied by first estimating daily size dependent natural mortality. This calculation is based on the total biomass in each nominal size class. Therefore, to calculate total community mortality flux (M), we simply add together the mortality flux (M(CWNl)) for each nominal size class such that:
The most complicated calculation is that for gut flux. Gut flux refers to the non-digested material in the gut which is vertically transported from the epipelagic to the mesopelagic by zooplankton and micronekton. This rate is dependent on temperature, assimilation efficiency, gut passage time, and index of stomach fullness. Thus, several assumptions must be made: (1) assimilation efficiency is constant for all animals (~80%), (2) gut passage time is size dependent, and (3) animals eat to complete satiation at night in the epipelagic zone. The majority of gut passage time measurements in the literature occur over a variety of different temperatures for animals of varying carbon weights. Therefore, to develop a size dependent relationship for gut passage time, these measurements can first be compiled and then converted using the temperature coefficient (Q10) to calculate the size dependent relationship according to the temperature
in the system of interest. In a similar manner, measurements of the index of stomach fullness and carbon weight values can be compiled from the literature to develop a size dependent relationship. It is crucial that index of stomach fullness be calculated using values that represent full stomachs only. From there we can apply Baikov's relation [105, 106] to calculate daily ration as a proportion of carbon weight nominal size class. This can then be converted to carbon weight and using assimilation efficiency (the proportion of ingested matter assimilated into the body) we can calculate the total gut flux for an individual in a given nominal size class (G(CWNi)). Similar to total community respiration, the total community gut flux ((?) is calculated by applying the following equation:
This approach makes several assumptions based on the biomass spectra theory: 1) the system must be in steady state, 2) the only source of mortality is predation, 3) large animals can consume only smaller animals, 4) the smallest size class receives a constant input of energy, and 5) the flow of energy is unidirectional (from smallest to largest). Gaps in the size spectra are assumed to represent size classes, in which biomass exists but may not have been effectively captured by the selected sampling gear (i.e., biomass is continuous). This assumption requires further investigation, because many previous studies argue that these gaps in data points represent areas of zero biomass [107] or that they are filled by benthic biomass [84]. Tittel et al. [107] argued that if these gaps are truly areas of zero biomass and, thus, empty niches, they would likely only exist for a short period of time.
This methodology requires that sampling includes both nighttime and daytime ep-ipelagic abundance size spectra. Alternatively, the nighttime epipelagic abundance size spectra can be used under assumption that larger portion of the size spectra represented by actively migrating macroplankton and micronekton would entirely descend out of surface waters into mesopelagic domain. This is verified by coupling net sampling with daytime acoustics. However, verification of these assumptions requires further research. Indeed, this approach first should be calibrated with the existing methodology for estimating active carbon transport, with future studies focusing on refining size-and temperature-dependent relationships for these critical ecological rates regionally.
The most pressing open question is linked to the assumption that migrating animals do not feed at their daytime depth. Limited studies indicate that some prey consumption at depth may, however, occur (e.g. [40, 108-110]). Consequently, the active carbon transport may have to be reduced by 1/4-1/2 to account for the deep sea feeding [40, 111]. Studies quantifying feeding at daytime depths for major migratory groups of organisms are generally missing. Recently, the term "cryptic food web" that may potentially reduce downward active transport has been introduced and explored [40], but its significance is still awaits further research and subsequent quantification.
3. Assumptions, limitations and recommendations
4. Future applications
The temporal and spatial variability in zooplankton and micronekton abundance and biomass, temperature dependence of ecological rates (respiration, excretion, mortality, gut flux), methodological differences (see Table 3.1 in [43]), and fine-scale temporal changes in solar (i.e., cloud cover) [112] and lunar [28, 113] illumination effects on zooplankton and micronekton behavior result in highly variable estimates of active carbon transport (Table 1; Fig. 4). This variability can be reduced by streamlining the methodology, allowing us to gain insight into the impacts of climate change on biogeochemical cycling. Applying the proposed approach with optical (e.g., Laser Optic Particle Counter, FlowCam) and acoustic methods will prove to be less labor-intensive and time-consuming than current methods. In combination with satellite data and oxygen minimum depth, this method may be used in the future to quantify active-carbon flux in real time. This technique is unique, because it may also be applied to historic data sets to assess temporal changes in active carbon flux in specific oceanic regions (e.g., Fisheries and Oceans Canada [DFO] Line P).
Global estimates of carbon export range from 83 to 91 mgC m-2 day-1 and seldom include the contribution of zooplankton and/or micronekton to carbon export [58, 62, 64, 114]. The uncertainty associated with estimates of active carbon transport contribution to carbon export (active to passive carbon ratio) is vast, yet suggest that the contribution is substantial (Table 1). By applying new methodology to spatial and temporal zooplankton and micronekton data sets, global estimates of carbon export can be refined to include estimates of spatially resolved active carbon transport, shedding light on the impacts of climate change on global carbon export. Changes in ocean temperature, circulation and reduced mixing may lead to intensification of ocean stratification, and thus decreased deep ocean oxygen and surface water nutrient replenishment [115-120]. These processes promote changes in surface productivity and may drive the OMZ expansion. Due to their aerobic nature, the distribution of zooplankton and micronekton is vertically restricted by the OMZ [5]. Therefore, expansion of the OMZ into shallower waters may have a substantial impact on carbon export to the deep ocean, restricting the oceans ability to absorb and/or transport excess atmospheric CO2. In addition, because many vertical migrants generally seek refuge from predators in the upper extent of the OMZ, the expansion of the OMZ will increase the vulnerability of these organisms to predation [121], influencing food pathways and resulting in the "predator-prey compression" phenomena [122-123]. Therefore, refining the proposed methodology and developing a less labor-intensive and time-consuming approach is crucial to assess the effects of climate change on global carbon export. The approach presented here provides a new promising tool for inclusion in biogeo-chemical models.
References
1. Sabine C.L., Feely R.A., Gruber N., Key R.M., Lee K., Bullister J.L., Wanninkhof R., Wong C.S., Wallace D.W.R, Tilbrook B., Millero F.J., Peng T-H., Kozyr A., Ono T., Rios A.F. The oceanic sink for anthropogenic CO2. Science, 2004, vol. 305, no. 5682, pp. 367-371. doi: 10.1126/science.1097403.
2. Volk T., Hoffert M.I. Ocean carbon pumps: Analysis of relative strengths and efficiencies in ocean-drive stmospheric CO2 changes. Geophys. Monogr. Ser., 1985, vol. 32, pp. 99-110.
3. Broecker W.S. The ocean. Sci. Am., 1983, vol. 249, pp. 146-161.
4. Steinberg D.K., Carlson C.A., Bates N.R., Goldthwait S.A., Madin L.P., Michaels A.F. Zooplankton vertical migration and the active transport of dissolved organic and inorganic carbon in the Sargasso Sea. Deep Sea Res., Part I, 2000, vol. 47, no. 1, pp. 137-158. doi: 10.1016/S0967-0637(99)00052-7.
5. Bianchi D., Galbraith E.D., Carozza D.A., Mislan K.A.S., Stock C.A. Intensification of open-ocean oxygen depletion by vertically migrating animals. Nat. Geosci., 2013, vol. 6, pp. 545-548. doi: 10.1038/ngeo1837.
6. Ducklow H.W., Steinberg D.K., Buesseler K.O. Upper ocean carbon export and the biological pump. Oceanography, 2001, vol. 14, no. 4, pp. 50-58.
7. Turner J.T. Zooplankton fecal pellets, marine snow and sinking phytoplankton blooms. Aquat. Microb. Ecol., 2002, vol. 27, no. 1, pp. 57-102. doi: 10.3354/ame027057.
8. Buesseler K.O., Trull T.W., Steinberg D.K., Silver M.W., Siegel D.A., Saitoh S.I., Lamborg C.H., Lam P.J., Karl D.M., Jiao N.Z., Honda M.C., Elskens M., Dehairs F., Brown S.L., Boyd P.W., Bishop J.K.B., Bidigare R.R. VERTIGO (VERtical Transport In the Global Ocean): A study of particle sources and flux attenuation in the North Pacific. Deep Sea Res., Part II, 2008, vol. 55, nos. 14-15, pp. 1522-1539. doi: 10.1016/j.dsr2.2008.04.024.
9. Giering S.L.C., Sanders R., Lampitt R.S., Anderson T.R., Tamburini Ch., Boutrif M., Zubkov M.V., Marsay C.M., Henson S.A., Saw K., Cook K., Mayor D.J. Reconciliation of the carbon budget in the ocean's twilight zone. Nature, 2014, vol. 507, pp. 480-483. doi:10.1038/nature13123.
10. Steinberg D.K., Van Mooy B.A.S., Buesseler K.O., Boyd P.W., Kobari T., Karl D.M. Bacterial vs. zooplankton control of sinking particle flux in the ocean's twilight zone. Limnol. Oceanogr., 2008, vol. 53, no. 4, pp. 1327-1338. doi: 10.4319/lo.2008.53.4.1327.
11. Siegel D.A., Buesseler K.O., Doney S.C., Sailley S.F., Behrenfeld M.J., Boyd P.W. Global assessment of ocean carbon export by combining satellite observations and food-web models. Global Biogeochem. Cycles, 2014, vol. 28, no. 3, pp. 181-196. doi: 10.1002/2013GB004743.
12. Koppelmann R., Weikert H. Temporal changes of deep-sea mesozooplankton abundance in temperate NE Atlantic and estimates of the carbon budget. Mar. Ecol.: Prog. Ser., 1999, vol. 179, pp. 27-40.
13. Hannides C.C.S., Popp B.N., Choy C.A., Drazen J.C. Midwater zooplankton and suspended particle dynamics in the North Pacific Subtropical Gyre: A stable isotope perspective. Limnol. Oceanogr., 2013, vol. 58, no. 6, pp. 1931-1946. doi: 10.4319/lo.2013.58.6.1931.
14. Choy C.A., Wabnitz C.C.C., Weijerman M., Woodworth-Jefcoats P.A., Polovina J.J. Finding the way to the top: How the composition of oceanic mid-trophic micronekton groups determines apex predator biomass in the central North Pacific. Mar. Ecol.: Prog. Ser., 2016, vol. 549, pp. 9-25. doi: 10.3345/meps11680.
15. Reinthaler T., van Aken H.M., Herndl G.J. Major contribution of autotrophy to microbial carbon cycling in the deep North Atlantic's interior. Deep Sea Res., Part II, 2010, vol. 57, no. 16, pp. 1572-1580. doi: 10.1016/j.dsr2.2010.02.023.
16. Michaels A.F., Bates N.R., Buesseler K.O., Carlson C.A., Knap A.H. Carbon-cycle imbalances in the Sargasso Sea. Nature, 1994, vol. 372, pp. 537-540. doi: 10.1038/372537a0.
17. Burd A.B., Hansell D.A., Steinberg D.K., Anderson, T.R., Aristegui J., Buesseler K.O., Dehairs F., Jackson G.A., Baltar F., Beaupre S.R., Kadko D.C., Koppelmann R., Lampitt R.S., Nagata T., Reinthaler T., Robinson C., Robison B.H., Tamburini C., Tanaka T.
Assessing the apparent imbalance between geochemical and biochemical indicators of meso-and bathypelagic biological activity: What the @$#! is wrong with present calculations of carbon budgets? Deep Sea Res., Part II, 2010, vol. 57, no. 16, pp. 1557-1571. doi: 10.1016/j.dsr2.2010.02.022.
18. Siegel D.A., Buesseler K.O., Doney S.C., Sailley S.F., Behrenfeld M.J., Boyd P.W. Global assessment of ocean carbon export by combining satellite observations and food-web models. Global Biogeochem. Cycles, 2014, vol. 28, no. 3, pp. 181-196. doi: 10.1002/2013GB004743.
19. Hidaka K., Kawaguchi K., Murakami M., Takahashi M. Downward transport of organic carbon by diel migratory micronekton in the western equatorial pacific: Its quantitative and qualitative importance. Deep Sea Res., Part I, 2001, vol. 48, no. 8, pp. 1923-1939. doi: 10.1016/S0967-0637(01)00003 -6.
20. Ariza A., Garijo J.C., Landeira J.M., Bordes F., Hernández-León S. Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands). Prog. Oceanogr., 2015, vol. 134, pp. 330-342. doi: 10.1016/j.pocean.2015.03.003.
21. Angel M.V., Pugh P.R. Quantification of diel vertical migration by macroplankton and micronektonic taxa in the northeast Atlantic. Hydrobiologia, 2000, vol. 440, nos. 1-3, pp. 161-179. doi: 10.1023/A:1004115010030.
22. Brodeur R.D., Yamamura O. Micronekton of the North Pacific, PICES Sci. Rep., 2005, vol. 30, pp. 1-115.
23. Longhurst A.R. The Ecology of the Seas. Cushing D.H., Walsh J.J. (Eds.). Vertical Migration. Oxford, Blackwell Sci. Publ., 1976, pp. 116-137.
24. Ringelberg J. Changes in light intensity and diel vertical migration: A comparison of marine and freshwater environments. J. Mar. Biol. Assoc. UK, 1995, vol. 75, pp. 15-25. doi: 10.1017/S0025315400015162.
25. Clarke T.R. Comparison of abundance estimates of small fishes by three towed nets and preliminary results of the use of small purse seines as sampling devices. Biol. Oceanogr., 1983, vol. 2, pp. 311-340.
26. Bailey T.G., Robinson B.H. Food availability as a selective factor on the chemical compositions of midwater fishes in the eastern North Pacific. Mar. Biol., 1986, vol. 91, no. 1, pp. 131-141. doi: 10.1007/BF00397578.
27. Kobari T., Steinberg D.K., Ueda A., Tsuda A., Silver M.W., Kitamura M. Impacts of ontogenetically migrating copepods on downward carbon flux in the western subarctic Pacific Ocean. Deep Sea Res., Part I, 2008, vol. 55, nos. 14-15, pp. 1648-1660. doi: 10.1016/j.dsr2.2008.04.016.
28. Hernández-León S., Franchy G., Moyano M., Menéndez I., Schmoker C., Putzeys S. Carbon sequestration and zooplankton lunar cycles: Could we be missing a major component of the biological pump? Limnol. Oceanogr., 2010, vol. 55, no. 6, pp. 2503-2512. doi: 10.4319/lo.2010.55.6.2503.
29. Iwasa Y. Vertical migration of zooplankton: A game between predator and prey. Am. Nat., 1982, vol. 120, no. 2, pp. 171-180. doi: 10.1086/283980.
30. Vuorinen I. Vertical migration of Eurytemora (Crustacea, Copepoda), a compromise between the risk of predation and decreased fecundity. J. Plankton Res., 1987, vol. 9, pp. 1037-1046.
31. Zaret T.M., Suffern J.S. Vertical migration in zooplankton as a predator avoidance mechanism. Limnol. Oceanogr., 1976, vol. 21, no. 6, pp. 804-813. doi: 10.4319/lo.1976.21.6.0804.
32. Hernández-León S., Gómez M., Pagazaurtundua M., Portillo-Hahnefeld A., Montero I., Almeida C. Vertical distribution of zooplankton in Canary Island waters: Implications for export flux. Deep Sea Res., Part I, 2001, vol. 48, no. 4, pp. 1071-1092. doi: 10.1016/S0967-0637(00)00074-1.
33. Longhurst A.R., Bedo A.W., Harrison W.G., Head E.J.., Sameoto D. Vertical flux of respiratory carbon by oceanic diel migrant biota. Deep-Sea Res., Part A, 1990, vol. 37, no. 4, pp. 685-694. doi: 10.1016/0198-0149(90)90098-G.
34. Zhang X., Dam H.G. Downward export of carbon by diel migrant mesozooplankton in the central equatorial Pacific, Deep Sea Res., Part II, 1997, vol. 44, nos. 9-10, pp. 21912202. doi: 10.1016/S0967-0645(97)00060-X.
35. Dam H.G., Roman M.R., Youngbluth M.J. Downward export of respiratory carbon and dissolved inorganic nitrogen by diel-migrant mesozooplankton at the JGOFS Bermuda time-series station. Deep Sea Res., Part I, 1995, vol. 42, no. 7, pp. 1187-1197. doi: 10.1016/0967-0637(95)00048-B.
36. Le Borgne R., Rodier M. Net zooplankton and the biological pump: A comparison between the oligotrophic and mesotrophic equatorial Pacific. Deep Sea Res., Part II, 1997, vol. 44, nos. 9-10, pp. 2003-2023. doi: 10.1016/S0967-0645(97)00034-9.
37. Rodier M., LeBorgne R. Export flux of particles at the equator in the western and central Pacific Ocean. Deep Sea Res., Part II, 1997, vol. 44, pp. 2085-2113.
38. Morales C.E. Carbon and nitrogen fluxes in the oceans: The contribution by zooplankton migrants to active transport in the North Atlantic during the Joint Global Ocean Flux Study. J. Plankton Res., 1999, vol. 21, no. 9, pp. 1799-1808. doi: 10.1093/plankt/21.9.1799.
39. Al-Mutairi H., Landry M.R. Active export of carbon and nitrogen at station ALOHA by diel migrant zooplankton. Deep Sea Res., Part II, 2001, vol. 48, nos. 8-9, pp. 2083-2103. doi: 10.1016/S0967-0645(00)00174-0.
40. Podeswa Y., Pakhomov E.A. Active carbon transport and feeding ecology of pelagic decapods in the North Pacific subtropical gyre, Arthropoda Sel., 2015, vol. 24, pp. 317-334.
41. Davison P.C. The export of carbon mediated by mesopelagic fishes in the northeast Pacific Ocean. PhD Thesis. San Diego, Calif., Univ. of Calif., 2011. 165 p.
42. Hudson J.M., Steinberg D.K., Sutton T.T., Graves J.E., Latour R.J. Myctophid feeding ecology and carbon transport along the northern Mid-atlantic Ridge. Deep Sea Res., Part I, 2014, vol. 93, pp. 104-116. doi: 10.1016/j.dsr.2014.07.002.
43. Kwong L.E. A novel approach to estimating active carbon flux using the biomass spectra theory. MSc Thesis. Vancouver, B. C., Univ. of B. C., 2016. 105 p.
44. Isla J.A., Ceballos S., Huskin I., Anadón R., Álvarez-Marqués F. Mesozooplankton distribution, metabolism and grazing in an anticyclonic slope water oceanic eddy (SWODDY) in the Bay of Biscay. Mar. Biol., 2004, vol. 145, no. 6,. pp. 1201-1212. doi: 10.1007/s00227-004-1408-5.
45. Isla A., Scharek R., Latasa M. Zooplankton diel vertical migration and contribution to deep active carbon flux in the NW Mediterranean. J. Mar. Syst., 2015, vol. 143, pp. 86-97. doi: 10.1016/j.jmarsys.2014.10.017.
46. Isla J., Anadon R. Mesozooplankton size-fractionated metabolism and feeding off NW Spain during autumn: Effects of a poleward current. ICES J. Mar. Sci., 2004, vol. 61, no. 4, pp. 526-534. doi: 10.1016/j.icesjms.2004.03.014.
47. Kobari T., Kitamura M., Minowa M., Isami H., Akamatsu H., Kawakami H., Matsumoto K., Wakita M., Honda M.C. Impacts of the wintertime mesozooplankton community to downward carbon flux in the subarctic and subtropical Pacific Oceans Deep Sea Res., Part I, 2013, vol. 81, pp. 78-88. doi: 10.1016/j.dsr.2013.07.003.
48. Longhurst A., Williams R. Carbon flux by seasonal vertical migrant copepods is a small number. J. Plankton Res., 1992, vol. 14, no. 11, pp. 1495-1509. doi: 10.1093/plankt/14.11.1495.
49. Packard T.T., Gómez M. Modeling vertical carbon flux from zooplankton respiration. Prog. Oceanogr., 2013, vol. 110, pp. 59-68. doi: 10.1016/j.pocean.2013.01.003.
50. Podeswa Y. Active carbon transport and feeding ecology of pelagic decapods in the North Pacific subtropical gyre. MSc Thesis. Vancouver, B. C., Univ. of B. C., 2012. 129 p.
51. Schukat A., Bode M., Auel H., Carballo R., Martin B., Koppelmann R., Hagen W. Pelagic decapods in the northern Benguela upwelling system: Distribution, ecophysiology and contribution to active carbon flux. Deep Sea Res., Part I, 2013, vol. 75, pp. 146-156. doi: 10.1016/j.dsr.2013.02.003.
52. Schnetzer, A., Steinberg D.K. Active transport of particulate organic carbon and nitrogen by vertically migrating zooplankton in the Sargasso Sea. Mar. Ecol.: Prog. Ser., 2002, vol. 234, pp. 71-84. doi: 10.3354/meps234071.
53. Stukel M., Ohman M., Benitez-Nelson C., Landry M. Contributions of mesozooplankton to vertical carbon export in a coastal upwelling system. Mar. Ecol.: Prog. Ser., 2013, vol. 491, pp. 47-65. doi: 10.3354/meps10453.
54. Takahashi K., Kuwata A., Sugisaki H., Uchikawa K., Saito H. Downward carbon transport by diel vertical migration of the copepods Metridia pacifica and Metridia okho-tensis in the Oyashio region of the western subarctic Pacific Ocean. Deep Sea Res., Part I, 2009, vol. 56, no. 10, pp. 1777-1791. doi: 10.1016/j.dsr.2009.05.006.
55. Williams A., Koslow J.A. Species composition, biomass and vertical distribution of micronekton over the mid-slope region off southern Tasmania, Australia. Mar. Biol., 1997, vol. 130, no. 2, pp. 259-276. doi: 10.1007/s002270050246.
56. Yebra L., Almeida C., Hernández-León S. Vertical distribution of zooplankton and active flux across an anticyclonic eddy in the Canary Island waters. Deep Sea Res., Part I, 2005, vol. 52, no. 1, pp. 69-83. doi: 10.1016/j.dsr.2004.08.010.
57. Darnis G., Fortier L. Zooplankton respiration and the export of carbon at depth in the Amundsen Gulf (Arctic Ocean). J. Geophys. Res., 2012, vol. 117, no. C4, art. C04013, pp. 1-12. doi: 10.1029/2011JC007374.
58. Davison P.C., Checkley D.M., Koslow J.A., Barlow J. Carbon export mediated by mesopelagic fishes in the northeast Pacific Ocean. Prog. Oceanogr., 2013, vol. 116, pp. 14-30. doi: 10.1016/j.pocean.2013.05.013.
59. Baird R.C., Hopkins T.L., Wilson D.F. Diet and feeding chronology of Diaphus taaningi (Myctophidae) in the Cariaco Trench, Copeia, 1975, vol. 2, pp. 356-365.
60. Pakhomov E. A., Perissinotto R., McQuaid C.D. Prey composition and daily rations of myctophid fishes in the Southern Ocean. Mar. Ecol.: Prog. Ser., 1996, vol. 134, pp. 1-14. doi: 10.3354/meps134001.
61. Buesseler K.O., Lamborg C.H., Boyd P.W., Lam P.J., Trull T.W., Bidigare R.R., Bishop J.K.B., Casciotti K.L., Dehairs F., Elskens M., Honda M., Karl D.M., Siegel D., Silver M.W., Steinberg D.K., Valdes J., Mooy B. Van, Wilson S. Revisiting carbon flux through the ocean's twilight zone. Science, 2007, vol. 316, no. 5824, pp. 567-570. doi: 10.1126/science. 1137959.
62. Falkowski P.G., Laws E.A., Barber R.T., Murray J.W. Ocean Biogeochemistry.
Phytoplankton and Their Role in Primary, New, and Export Production. Berlin, Heidelberg, Springer, 2003, pp. 99-121. doi: 10.1007/978-3-642-55844-3_5.
63. Martz T.R., Johnson K.S., Riser S.C. Ocean metabolism observed with oxygen sensors on profiling floats in the South Pacific. Limnol. Oceanogr., 2008, vol. 53, no. 5, part 2, pp. 2094-2111. doi: 10.4319/lo.2008.53.5_part_2.2094.
64. Usbeck R., Schlitzer R., Fischer G., Wefer G. Particle fluxes in the ocean: Comparison of sediment trap data with results from inverse modeling. J. Mar. Syst., 2003, vol. 39, nos. 3-4, pp. 167-183. doi: 10.1016/S0924-7963(03)00029-0.
65. Riser W.C., Reigstad M., Wassmann P. Zooplankton-mediated carbon export: A seasonal study in a northern Norwegian fjord. Mar. Biol. Res., 2010, vol. 6, no. 5, pp. 461-471. doi: 10.1080/17451000903437067.
66. Basedow S.L., Zhou M., Tande K.S. Secondary production at the Polar Front, Barents Sea, August 2007. J. Mar. Syst., 2014, vol. 130, pp. 147-159. doi: 10.1016/j.jmarsys.2013.07.015.
67. Sheldon R.W., Prakash A., Sutcliffe H. The size distribution of particles in the ocean. Limnol. Oceanogr., 1972, vol. 17, no. 3, pp. 327-340. doi: 10.4319/lo.1972.17.3.0327.
68. Sheldon R.W., Sutcliffe W.H. Jr., Paranjape M.A. Structure of pelagic food chain and relationship between plankton and fish production. J. Fish. Res. Board Can., 1977, vol. 34, no. 12, pp. 2344-2353. doi : 10.1139/f77-314.
69. Platt T., Denman K. The structure of pelagic marine ecosystems. J. Cons., Cons. Int. Explor. Mer., 1978, vol. 173, pp. 60-65.
70. Silvert W., Platt T. Evolution and Ecology of Zooplankton Communities. Kerfoot W.C. (Ed.). Dynamic Energy-Flow Model of the Particle Size Distribution in Pelagic Ecosystems. Hanover, Univ. Press of N. Engl., 1980, pp. 754-763.
71. Cousins S.H. Ecosystem Theory for Biological Oceanography. Ulanowicz R.E., Platt T. (Eds.). The Trophic Continuum in Marine Ecosystems Structure and Equations for a Predictive Model. Can. Bull. Fish. Aquat. Sci., 1985, vol. 213, pp. 76-93.
72. Platt T. Structure of the marine ecosystem: Its allometric basis. Can. Bull. Fish. Aquat. Sci., 1985, vol. 213, pp. 55-64.
73. Beers J.R., Read F.M.H., Stewart G.L. Seasonal abundance of the microplankton population in the North Pacific Central Gyre, Deep-Sea Res., Part A, 1982, vol. 29, no. 2, pp. 227-245. doi: 10.1016/0198-0149(82)90111-X.
74. Echevarría F., Carrillo O., Jiménez P., Sánchez-Castillo P., Cruz-Pizarro L., Rodriguez L. The size-abundance distribution and taxonomic composition of plankton in an oligotrophic, high mountain lake (la Caldera, Sierra Nevada, Spain). J. Plankton Res., 1990, vol. 12, no. 2, pp. 415-422. doi: 10.1093/plankt/12.2.415.
75. Platt T., Lewis M., Geiderl R. Flows of Energy and Materials in Marine Ecosystems. Fasham M.J.R. (Ed.). Thermodynamics of the Pelagic Ecosystem: Elementary Closure Conditions for Biological Production in the Open Ocean. New York; NY, Plenum Press, 1984, pp. 49-84.
76. Rodriguez J., Mullin M.M. Relation between biomass and body weight of plankton in a steady state oceanic ecosystem. Limnol. Oceanogr., 1986, vol. 31, no. 2, pp. 361-370. doi: 10.4319/lo.1986.31.2.0361.
77. Rodriguez J., Mullin M. Diel and interannual variation of size distribution of oceanic zooplanktonic biomass. Ecology, 1986, vol. 67, no. 1, pp. 215-222. doi: 10.2307/1938521.
78. Schwinghamer P. Characteristic size distributions of integral benthic communities. Can. J. Fish. Aquat. Sci., 1981, vol. 38, no. 10, pp. 1255-1263. doi: 10.1139/f81-167.
79. Schwinghamer P. Observations on size-structure and pelagic coupling of some shelf and abyssal benthic communities. Proc. 19th Eur. Mar. Biol. Symp. Gobbs P.E. (Ed.). Cambridge, Cambridge Univ. Press, 1985, pp. 347-359.
80. Sprules W.G., Casselman J.M., Shuter B.J. Size distribution of pelagic particles in lakes. Can. J. Fish. Aquat. Sci., 1983, vol. 40, no. 10, pp. 1761-1769. doi: 10.1139/f83-205.
81. Sprules W.G., Knoechel R. Trophic Interactions within Aquatic Ecosystems. Meyers D.G., Strickland R. (Eds.). Lake Ecosystem Dynamics based on Functional Representations of Trophic Components. Boulder, Colo., Westview Press, pp. 383-403.
82. Sprules W.G., Munawar M. Plankton size spectra in relation to ecosystem productivity, size, and perturbation. Can. J. Fish. Aquat. Sci., 1986, vol. 43, no. 9, pp. 1789-1794. doi: 10.1139/f86-222.
83. Warwick R.M., Clarke K.R. Species size distributions in marine benthic communities. Oecologia, 1984, vol. 61, no. 1, pp. 32-41. doi: 10.1007/BF00379085.
84. Witek Z., Krajewska-Soltys A. Some examples of the epipelagic plankton size structure in high latitude oceans. J. Plankton Res., 1989, vol. 11, pp. 1143-1155. doi: 10.1093/plankt/11.6.1143.
85. Clement T.A., Murry B.A., Uzarski D.G. Fish community size structure of small lakes: The role of lake size, biodiversity and disturbance. J. Freshwater Ecol., 2015, vol. 30, no. 4, pp. 557-568. doi: 10.1080/02705060.2015.1030787.
86. Genin A. Biomass and body size of oceanic plankton. Trends Ecol. Evol., 1986, vol. 1, pp. 55-56.
87. Macpherson E., Gordoa A., Garcia-Rubies A. Biomass size spectra in littoral fishes in protected and unprotected areas in the nw mediterranean. Estuarine, Coastal Shelf Sci., 2002, vol. 55, no. 5, pp. 777-788. doi: 10.1006/ecss.2001.0939.
88. Borgmann U., Shear H., Moore J. Zooplankton and potential fish production in Lake Ontario, Can. J. Fish. Aquat. Sci., 1984, vol. 41, no. 9, pp. 1303-1309. doi: 10.1139/f84-159.
89. Moloney C.L., Field J.G. Use of particle-size data to predict potential pelagic-fish yields of some southern African areas. S. Afr. J. Mar. Sci., 1985, vol. 3, pp. 119-128.
90. Thomann R.V. Perspective on Lake Ecosystem Modelling. Scavia D., Robertson A. (Eds.). An Analysis of PCB in Lake Ontario Using Size-Dependent Food Chain Model. Ann Arbor. Sci. Publ., 1979, pp. 293-320.
91. Thomann R.V. Equilibirum model of fate of microcontaminants in diverse aquatic food chains. Can. J. Fish. Aquat. Sci., 1981, vol. 38, no. 3, pp. 280-296. doi: 10.1139/f81-040.
92. Griesbach S., Peters R.H., Youakim S. An allometric model for pesticide bioaccumulation. Can. J. Fish. Aquat. Sci., 1982, vol. 39, no. 5, pp. 727-735. doi: 10.1139/f82-101.
93. Borgmann U., Whittle D.M. Particle-size-conversion efficiency and contaminant concentrations in Lake Ontario biota. Can. J. Fish. Aquat. Sci., 1983, vol. 40, no. 3, pp. 328-336. doi: 10.1139/f83-048.
94. Sabeel R.A.O., Vanreusel A. Potential impact of mangrove clearance on biomass and biomass size spectra of nematode along the Sudanese Red Sea coast. Mar. Environ. Res., 2015, vol. 103, pp. 46-55. doi: 10.1016/j.marenvres.2014.11.003.
95. Zhou M., Huntley M.E. Population dynamics theory of plankton based on biomass spectra. Mar. Ecol.: Prog. Ser., 1997, vol. 159, pp. 61-73.
96. Kerr S.R., Dickie L.M. The Biomass Spectrum: A Predator-Prey Theory of Aquatic Production. New York, Columbia Univ. Press, 2001. 320 p.
97. Zhou M. What determines the slope of a plankton biomass spectrum? J. Plankton Res., 2006, vol. 28, no. 5, pp. 437-448. doi: 10.1093/plankt/fbi119.
98. Zhou M., Carlotti F., Zhu Y. A size-spectrum zooplankton closure model for ecosystem modelling. J. Plankton Res., 2010, vol. 32, pp. 1147-1165.
99. Thompson G.A., Dinofrio E.O., Alder V.A. Structure, abundance and biomass size spectra of copepods and other zooplankton communities in upper waters of the Southwestern Atlantic Ocean during summer. J. Plankton Res., 2013, vol. 35, no. 3, pp. 610-629. doi: 10.1093/plankt/fbt014.
100. Suthers I.M., Taggart C.T., Rissik D., Baird M.E. Day and night ichthyoplankton assemblages and zooplankton biomass size spectrum in a deep ocean island wake. Mar. Ecol.: Prog. Ser., 2006, vol. 322, pp. 225-238. doi: 10.3354/meps322225.
101. Blanco J.M., Echevarria F., Garcia C.M. Dealing with size-spectra: Some conceptual and mathematical problems. Sci. Mar., 1994, vol. 58, nos. 1-2, pp. 17-29.
102. Blanco J.M., Quiñones R. A., Guerrero F., Rodríguez J. The use of biomass spectra and allometric relations to estimate respiration of planktonic communities. J. Plankton Res., 1998, vol. 20, no. 5, pp. 887-900. doi: 10.1093/plankt/20.5.887.
103. Ikeda T. Metabolic rates of epipelagic marine zooplankton as a function of body mass and temperature. Mar. Biol., 1985, vol. 85, no. 1, pp. 1-11. doi: 10.1007/BF00396409.
104. Peterson I., Wroblewski S. Mortality rate of fishes in the pelagic ecosystem. Can. J. Fish. Aquat. Sci., 1984, vol. 41, no. 7, pp. 1117-1120. doi: 10.1139/f84-131.
105. Baikov A.D. How to estimate the daily food consumption of fish under natural conditions. Trans. Am. Fish. Soc., 1935, vol. 65, pp. 288-289.
106. Eggers D.M. Factors in interpreting data obtained by diel sampling of fish stomachs. J. Fish. Res. Board Can., 1977, vol. 34, no. 2, pp. 290-294. doi: 10.1139/f77-045.
107. Tittel J., Zippel B., Geller W., Juliane S. Relationships between plankton community structure and plankton size distribution in lakes of northern Germany. Limnol. Oceanogr., 1998, vol. 43, no. 6, pp. 1119-1132. doi: 10.4319/lo.1998.43.6.1119.
108. Hu V.J.H. Relationships between vertical migration and diet in four species of euphausiids. Limnol. Oceanogr., 1978, vol. 23, no. 2, pp. 296-306. doi: 10.4319/lo.1978.23.2.0296.
109. Roe H.S.J., Badcock J. The diel migrations and distributions within a mesopelagic community in the North East Atlantic. 6. Vertical migrations and feeding of fish. Prog. Oceanogr., 1984, vol. 13, nos. 3-4, pp. 389-424. doi: 10.1016/0079-6611(84)90014-4.
110. Roe H.S.J. The diel migrations and distributions within a mesopelagic community in the North East Atlantic. 2. Vertical migrations and feeding of mysids and decapod crustacea. Prog. Oceanogr., 1984, vol. 13, nos. 3-4, pp. 269-318. doi: 10.1016/0079-6611(84)90011-9.
111. Tseitlin V.B. Energetics of the Deep-Sea Pelagic Communities. Moscow, Nauka, 1986. 112 p. (In Russian)
112. Pinot J.M., Jansá J. Time variability of acoustic backscatter from zooplankton in the Ibiza Channel (western Mediterranean). Deep Sea Res., Part I, 2001, vol. 48, no. 7, pp. 1651-1670. doi: 10.1016/S0967-0637(00)00095-9.
113. Benoit-Bird K.J., Au W.W.L., Wisdom D.W. Nocturnal light and lunar cycle effects on diel migration of micronekton. Limnol. Oceanogr., 2009, vol. 54, no. 5, pp. 1789-1800. doi: 10.4319/lo.2009.54.5.1789.
114. Schlitzer R. Carbon export fluxes in the Southern Ocean: Results from inverse modeling and comparison with satellite-based estimates. Deep Sea Res., Part II, 2002, vol. 49, nos. 9-10, pp. 1623-1644. doi: 10.1016/S0967-0645(02)00004-8.
115. Roemmich D., McGowan J. Climate warming and the decline of zooplankton in the California Current, Science, 1995, vol. 267, no. 5202, pp. 1324-1326. doi: 10.1126/science.267.5202.1324.
116. Sarmiento J.L., Hughes T.M.C., Stouffer R.J., Manabe S. Simulated response of the ocean carbon cycle to anthropogenic climate warming. Nature, 1998, vol. 393, pp. 245-249. doi: 10.1038/30455.
117. Matear R. J., Hirst A.C., McNeill B.I. Changes in dissolved oxygen in the Southern Ocean with climate change. Geochem. Geophys. Geosyst., 2000, vol. 1, no. 11, pp. 1-12.
118. Plattner G.-K., Joos F., Stocker T.F., Marchal O. Feedback mechanisms and sensitivities of ocean carbon uptake under global warming. Tellus B, 2001, vol. 53, no. 5, pp. 564-592. doi: 10.1034/j.1600-0889.2001.530504.x.
119. Bopp L., Que C. Le, Heimann M., Manning A.C., Monfray P. Climate-induced oceanic oxygen fluxes: Implications for the contemporary carbon budget. Global Biogeochem. Cycles, 2002, vol. 16, no. 2, pp. 1022-1035. doi: 10.1029/2001GB001445.
120. Keeling R., Garcia H. The change in oceanic O2 inventory associated with recent global warming. Proc. Natl. Acad. Sci., 2002, vol. 99, no. 12, pp. 7848-7853. doi: 10.1073/pnas.122154899.
121. Stramma L., Prince E.D., Schmidtko S., Luo J., Hoolihan J.P., Visbeck M., Wallace D.W., Brandt P., Körtzinger A. Expansion of oxygen minimum zones may reduce available habitat for tropical pelagic fishes. Nat. Clim. Change., 2011, vol. 2, pp. 33-37. doi: 10.103 8/nclimate1304.
122. Goodyear C.P., Luo J., Prince E.D., Hoolihan J.P., Snodgrass D., Orbesen E.S., Serafy J.E. Vertical habitat use of Atlantic blue marlin Makaira nigricans: Interaction with pelagic longline gear. Mar. Ecol.: Prog. Ser., 2008, vol. 365, pp. 233-245. doi: 10.3354/meps07505.
123. Prince E.D., Goodyear C.P. Hypoxia-based habitat compression of tropical pelagic fishes. Fish. Oceanogr., 2006, vol. 15, no. 6, pp. 451-464. doi: 10.1111/j.1365-2419.2005.00393.x.
Recieved June 15, 2017
Kwong Lian E., PhD student of Department of Earth, Ocean and Atmospheric Sciences
University of British Columbia
2329 West Mall, Vancouver, BC V6T 1Z4 Canada E-mail: [email protected]
Pakhomov Evgeny Alexandrovich, professor (PhD in Biology) of Department of Earth, Ocean and Atmospheric Sciences, and the Institute for the Oceans and Fisheries
University of British Columbia
2329 West Mall, Vancouver, BC V6T 1Z4 Canada E-mail: [email protected]
УДК 574.56
Оценка активного вертикального переноса углерода: новая методология
Л.Е. Квонг, Е.А. Пахомов Университет Британской Колумбии, г. Ванкувер, BC V6T ^4, Канада
Аннотация
Оценка активного вертикального переноса углерода в водных экосистемах является трудоёмким процессом. В статье предлагается новый подход к оценке переноса углерода зоопланктона и микронектона на основе теории спектра биомассы. Этот метод уникален, поскольку он основан исключительно на размере организма, а не на его таксономической принадлежности. Для прогнозирования переноса активного углерода мы используем дневной и ночной спектры размерного состава в эпипелагической зоне, сгруппированные в логарифмические размеры log-2, которые затем могут быть использованы для расчета номинального размера и общего изобилия для каждого размерного интервала. Эти данные используются наряду с ранее известными закономерностями уровня дыхания, выделения, смертности и наполнения желудка, зависящими от размера и температуры среды, со временем, проведенным на глубине, и с глубиной вертикальной миграции. Мы надеемся, что данный метод в сочетании с оптическими и акустическими методами прольёт новый свет на вклад зоопланктона и микронектона в глобальный экспорт углерода и будет способствовать включению оценок активного переноса углерода в глобальные биогеохимические модели. Это поможет лучше понять последствия изменения климата для глобального цикла углерода.
Ключевые слова: зоопланктон, микронектон, вертикальные миграции, активный перенос углерода, теория спектров биомассы
Поступила в редакцию 15.06.17
Квонг Лиан Е., аспирант кафедры исследования земли, океана и атмосферы
Университет Британской Колумбии
2329 Вест Молл, г. Ванкувер, BC V6T 1Z4, Канада E-mail: [email protected]
Пахомов Евгений Александрович, кандидат биологических наук, профессор кафедры исследования земли, океана и атмосферы, Институт по океану и рыболовству
Университет Британской Колумбии
2329 Вест Молл, г. Ванкувер, BC V6T 1Z4, Канада E-mail: [email protected]
For citation: Kwong L.E., Pakhomov E.A. Assessment of active vertical carbon transport: New methodology. Uchenye Zapiski Kazanskogo Universiteta. Seriya Estestvennye Nauki, 2017, vol. 159, no. 3, pp. 492-509.
Для цитирования: Kwong L.E., Pakhomov E.A. Assessment of active vertical carbon transport: New methodology // Учен. зап. Казан. ун-та. Сер. Естеств. науки. - 2017. -Т. 159, кн. 3. - С. 492-509.
