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12.3: Temporal variations in the global nitrogen cycle

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    Denitrification and \(\mathrm{N}_2\) fixation are \(\mathrm{N}\) transformation processes which can both control and be controlled by environmental factors (Vitousek et al., 2002; Seitzinger et al., 2006). Together with anammox, \(\mathrm{N}_2\) fixation and denitrification are the primary biological processes that control \(\mathrm{N}_2\) flux from ecosystems (Fox et al., 2014; Nifong et al., 2020). Denitrification is a form of anaerobic respiration in which microbes break down organic carbon (C) for energy and use nitrate \(\left(\mathrm{NO}_3^{-}\right)\)in the place of oxygen \(\left(\mathrm{O}_2\right)\) as an electron acceptor, so supply of organic \(\mathrm{C}\) and \(\mathrm{NO}_3^{-}\)are important limitations on denitrification rates (Wall et al., 2005). Along with the required reactant availability, environmental factors including oxygen concentration and temperature can alter denitrification rates. Biological \(\mathrm{N}_2\) fixation is the microbially-mediated conversion of \(\mathrm{N}_2\) gas into ammonium \(\left(\mathrm{NH}_4^{+}\right)\); it is an energetically expensive process so high availability of \(\mathrm{NH}_4^{+}\)and/or other forms of dissolved inorganic N (DIN) may cause microbes to reduce the process rate to conserve energy (Burris and Roberts, 1993; Bandyopadhyay et al., 2013). Light may be especially important for controlling \(N_2\) fixation rates in shallow aquatic ecosystems like streams, where it is often carried out by cyanobacteria who obtain their energy via photosynthesis (Burris and Roberts, 1993; Scott and Marcarelli, 2012). Light intensity along with these other factors vary through time, and therefore they may lead to temporal variation in rates of both of these \(\mathrm{N}\) transformation processes in aquatic ecosystems. Yet, the mechanisms by which environmental factors affect rates of denitrification and \(\mathrm{N}_2\) fixation may differ depending on the time scale.

    In streams and rivers in temperate climate zones, seasonal changes in denitrification and \(\mathrm{N}_2\) fixation rates in response to changes in environmental conditions may be gradual over the course of days to weeks, caused by the abundance and/or activity of microbes increasing or decreasing, or the identity of the microbes within the community changing. Environmental characteristics that show strong seasonal changes in temperate streams and rivers include nutrient availability, temperature, and light availability (Coble et al., 2019). Low biotic uptake rates in winter can lead to increased inorganic \(N\) concentrations in temperate forested streams (Stottlemyer and Toczydlowski, 1999a,b) which could provide reactants for denitrification and reduce rates of \(\mathrm{N}_2\) fixation. Temperate forests have large inputs of allochthonous organic matter during the fall and high dissolved organic C (DOC) flux during snowmelt (Stottlemyer and Toczydlowski, 1999a), either of which could provide a C source for denitrifying bacteria. Discharge varies seasonally corresponding to rainy seasons or snowmelt, which leads to predictable patterns of disturbance that can move, scour and mobilize riverbed substrates, disturbing microbial communities, and the microenvironments of these communities, which control nutrient cycling processes (O'Connor et al., 2012). Seasonal changes in discharge can also alter nutrient concentrations both by altering patterns of nutrient delivery and via dilution (Meyer and Likens, 1979; Horner et al., 1990; Stottlemyer and Toczydlowski, 1999a). Denitrification and \(\mathrm{N}_2\) fixing microbial communities can both be sensitive to seasonal temperature changes, with \(\mathrm{N}_2\) - fixing microbes often preferring warmer temperatures (Scott and Marcarelli, 2012), and denitrification activity decreasing during periods with colder temperatures such as in the winter (Christensen et al., 1990; Kim et al., 2006). Light also varies seasonally, especially in forested streams where canopy cover will shade streams differently depending on the season and vegetation type (Roberts and Mulholland, 2007; Bowes et al., 2012). Increased light availability in spring and fall due to low canopy cover can lead to higher rates of in-stream nutrient uptake due to increases in primary productivity (Roberts and Mulholland, 2007).

    Environmental factors in temperate streams can also shift much more rapidly over hours to days, which could instead affect rates through enzymatic regulation (Grimm, 1987; Marcarelli and Wurtsbaugh, 2006; Marcarelli et al., 2008). N cycling rates can both increase and decrease over the course of hours with factors such as temperature or substrate availability affecting enzyme activity (Grimm, 1987; Marcarelli and Wurtsbaugh, 2006). Temperature variation can occur on an hourly scale, and the enzymes and microbes facilitating \(\mathrm{N}\) cycling processes may have reduced activity at cold temperatures (Yvon-Durocher et al., 2010; Boulêtreau et al., 2012). Also, changes in light can alter \(\mathrm{N}_2\) fixation rates by cyanobacteria in some ecosystems on a diel cycle because it is tightly coupled with photosynthesis (Howarth et al., 1988; Grimm and Petrone, 1997). Nutrient concentrations can rapidly change due to storm runoff, which could also alter \(\mathrm{N}\) process rates. Because \(\mathrm{N}_2\) fixation is so energy intensive, enzymes can be rapidly deregulated to save energy following an influx of DIN (Howarth et al., 1988; Grimm and Fisher, 1989; Grimm and Petrone, 1997). But, the distinction between community or enzymatic shifts can be complicated because some environmental factors such as temperature and light vary at multiple time scales. For example, hydrological disturbances such as flooding caused by storms are overlain on seasonal patterns created by snowmelt and rainfall, and may therefore alter biogeochemical process rates through a mix of shorter-term enzymatic changes and longer-term community shifts (Grimm and Fisher, 1989). Stormdriven surface runoff can carry nutrients (Meyer and Likens, 1979; Horner et al., 1990; Stottlemyer and Toczydlowski, 1999a), change water temperature, and create short-term increases in water velocity and benthic disturbance (O'Connor et al., 2012), all of which may act independently and in concert to create variation in process rates.

    Understanding relationships between \(\mathrm{N}\) cycling rates and different environmental drivers that vary across time scales may provide insight into how climate change will affect these processes in the future. Climate change can lead to temperature, stream flow, and growing season changes (Barnett et al., 2005; Backlund et al., 2008; Christiansen et al., 2011), all environmental characteristics which may be influential to denitrification and \(\mathrm{N}_2\) fixation rates. Storms are becoming separated by longer periods of drought, but overall higher rainfall can occur driven by more intense storm events (Mathbout et al., 2018). It is also not wellunderstood how resistant and resilient rates of \(\mathrm{N}\) transformations are to hydrologic disturbances, which is important in the face of ongoing climate change. Resistance and recovery (or resilience) are concepts used throughout ecological studies, including studies on the impact of hydrological disturbances, anthropogenic disturbances, and climate change (Holling, 1973; Bahadur et al., 2013; Pope et al., 2014; Reisinger et al., 2017). Resistance describes how much the structure and processes of an ecosystem change in response to disturbances of different magnitudes, while recovery describes how quickly the ecosystem returns to the same structure and/or function after a disturbance event (Hershkovitz and Gasith, 2013; Reisinger et al., 2017). Initial declines in process rates following a hydrologic disturbance may be rapid; however, recovery may be slower if the microbial community was altered or reduced in biomass rather than enzymatic downregulation. Understanding how large hydrological disturbances affect denitrification and \(\mathrm{N}_2\) fixation can provide insight into how they will be affected by changing climactic conditions.

    The complexity of seasonal vs. shorter-term environmental changes coupled with different mechanisms of microbial responses that lead to changes in rates makes it difficult to decipher how and why N cycle processes vary

    References

    Backlund, P., Schimel, D., Janetos, A., Hatfield, J., Ryan, M. G., Archer, S. R., et al. (2008). Introduction. The effects of climate change on agriculture, land resources, water resources, and biodiversity in the United States, in United States Climate Change Science Program Synthesis and Assessment Product, Vol. 4, 11–20..

    Bahadur, A. V., Ibrahim, M., and Tanner, T. (2013). Characterising resilience: unpacking the concept for tackling climate change and development. Clim. Dev. 5, 55–65. doi: 10.1080/17565529.2012.762334.

    Bandyopadhyay, A., Elvitigala, T., Liberton, M., and Pakrasi, H. B. (2013). Variations in the rhythms of respiration and nitrogen fixation in members of the unicellular diazotrophic cyanobacterial genus Cyanothece. Plant Physiol. 161, 1334–1346. doi: 10.1104/pp.112.208231.

    Barnett, T. P., Adam, J. C., and Lettenmaier, D. P. (2005). Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 438, 303–309. doi: 10.1038/nature04141.

    Boulêtreau, S., Salvo, E., Lyautey, E., Mastrorillo, S., and Garabetian, F. (2012). Temperature dependence of denitrification in phototrophic river biofilms. Sci. Total Environ. 416, 323–328. doi: 10.1016/j.scitotenv.2011.11.066.

    Bowes, M. J., Ings, N. L., McCall, S. J., Warwick, A., Barrett, C., Wickham, H. D., et al. (2012). Nutrient and light limitation of periphyton in the River Thames: implications for catchment management. Sci. Total Environ. 434, 201–212. doi: 10.1016/j.scitotenv.2011.09.082

    Burris, R. H., and Roberts, G. P. (1993). Biological nitrogen fixation. Annu. Rev. Nutr. 13, 317–335. doi: 10.1146/annurev.nu.13.070193.001533.

    Christensen, P. B., Nielsen, L. P., Sørensen, J., and Revsbech, N. P. (1990). Denitrification in nitrate-rich streams: Diurnal and seasonal variation related to benthic oxygen metabolism. Limnol. Oceanogr. 35, 640–651. doi: 10.4319/lo.1990.35.3.0640.

    Coble, A. A., Marcarelli, A. M., and Kane, E. S. (2019). Year-round measurements reveal seasonal drivers of nutrient uptake in a snowmelt-driven headwater stream. Freshw. Sci. 38, 156–169. doi: 10.1086/701733.

    Fox, R. J., Fisher, T. R., Gustafson, A. B., Jordan, T. E., Kana, T. M., and Lang, M. W. (2014). Searching for the missing nitrogen: biogenic nitrogen gasses in groundwater and streams. J. Agric. Sci. 152, S96–S106. doi: 10.1017/S0021859614000070.

    Grimm, N. B. (1987). Nitrogen dynamics during succession in a desert stream. Ecology 68, 1157–1170. doi: 10.2307/1939200.

    Grimm, N., and Petrone, K. (1997). Nitrogen fixation in a desert stream ecosystem. Biogeochemistry 37, 33–61. doi: 10.1023/A:1005798410819.

    Grimm, N. B., and Fisher, S. G. (1989). Stability of periphyton and macroinvertebrates to disturbance by flash floods in a desert stream. J. North Am. Benthol. Soc. 8, 293–307. doi: 10.2307/1467493.

    Hershkovitz, Y, and Gasith, A. (2013). Resistance, resilience, and community dynamics in mediterranean-climate streams. Hydrobiologia 719, 59–75. doi: 10.1007/s10750-012-1387-3.

    Holling, C. S. (1973). Resilience and stability of ecological systems. Ann. Rev. Ecol. Syst. 4, 1–23. doi: 10.1146/annurev.es.04.110173.000245.

    Horner, R. R., Welch, E. B., Seele, M. R., and Jacoby, J. M. (1990). Response of periphyton to changes in current velocity, suspended sediment, and phosphorus concentration. Freshw. Biol. 24, 215–232. doi: 10.1111/j.1365-2427.1990.tb00704.x.

    Howarth, R. W., Marino, R., and Cole, J. J. (1988). Nitrogen fixation in freshwater, estuarine, and marine ecosystems. 2. Biogeochemical control. Limnol. Oceanogr. 33(4, Part 2), 688–701. doi: 10.4319/lo.1988.33.4part2.0688.

    Kim, D. J., Lee, D. I., and Keller, J. (2006). Effect of temperature and free ammonia on nitrification and nitrite accumulation in landfill leachate and analysis of its nitrifying bacterial community by FISH. Bioresour. Technol. 97, 459–468. doi: 10.1016/j.biortech.2005.03.032.

    Marcarelli, A. M., and Wurtsbaugh, W. A. (2006). Temperature and nutrient supply interact to control nitrogen fixation in oligotrophic streams: an experimental examination. Limnol. Oceanogr. 51, 2278–2289. doi: 10.4319/lo.2006.51.5.2278.

    Mathbout, S., Lopez-Bustins, J. A., Roy,é, D., Martin-Vide, J., Bech, J., and Rodrigo, F. S. (2018). Observed changes in daily precipitation extremes at annual timescale over the eastern Mediterranean during 1961–2012. Pure Appl. Geophys. 175, 3875–3890. doi: 10.1007/s00024-017-1695-7.

    Meyer, J. L., and Likens, G. E. (1979). Transport and transformation of phosphorus in a forest stream ecosystem. Ecography 60, 1255–1269. doi: 10.2307/1936971

    Nifong, R. L., Taylor, J. M., Adams, G., Moore, M. T., and Farris, J. L. (2020). Recognizing both denitrification and nitrogen consumption improves performance of stream diel N2 flux models. Limnol. Oceanogr.: Methods 18, 169–182. doi: 10.1002/lom3.10361.

    O'Connor, B. L., Harvey, J. W., and McPhillips, L. E. (2012). Thresholds of flow-induced bed disturbances and their effects on stream metabolism in an agricultural river. Water Resour. Res. 48:W08504. doi: 10.1029/2011WR011488.

    Pope, K. L., Allen, C. R., and Angeler, D. G. (2014). Fishing for resilience. Trans. Am. Fish. Soc. 143, 467–478. doi: 10.1080/00028487.2014.880735.

    Reisinger, A. J., Rosi, E. J., Bechtold, H. A., Doody, T. R., Kaushal, S. S., and Groffman, P. M. (2017). Recovery and resilience of urban stream metabolism following Superstorm Sandy and other floods. Ecosphere 8, e01776. doi: 10.1002/ecs2.1776.

    Roberts, B. J., and Mulholland, P. J. (2007). In-stream biotic control on nutrient biogeochemistry in a forested stream, West Fork of Walker Branch. J. Geophys. Res.: Biogeosci. 112, 1–11. doi: 10.1029/2007JG000422.

    Scott, J. T., and Marcarelli, A. M. (2012). Cyanobacteria in freshwater benthic environments, in Ecology of the Cyanobacteria II: Their Diversity in Time and Space, 271–289. doi: 10.1007/978-94-007-3855-3_9.

    Seitzinger, S., Harrison, J., Bohlke, J., Bouwman, A., Lowrance, R., Peterson, B., et al. (2006). Denitrification across landscapes and waterscapes: a synthesis. Ecol. Appl. 16, 2064–2090. doi: 10.1890/1051-0761(2006)016[2064:DALAWA]2.0.CO;2.

    Stottlemyer, R., and Toczydlowski, D. (1999a). Seasonal change in precipitation, snowpack, snowmelt, soil water and stream water chemistry, northern Michigan. Hydrogeol. J. 2231, 2215–2231. doi: 10.1002/(SICI)1099-1085(199910)13:14/15<2215::AID-HYP882>3.0.CO;2-V.

    Stottlemyer, R., and Toczydlowski, D. (1999b). Seasonal relationships between precipitation, forest floor, and stream water nitrogen, Isle Royale, Michigan. Soil Sci. Soc. Am. J. 63, 389–398. doi: 10.2136/sssaj1999.03615995006300020018x.

    Vitousek, P. M., Cassman, K., Cleveland, C., Crews, T., Field, C. B., Grimm, N. B., et al. (2002). Towards an ecological understanding of biological nitrogen fixation. Biogeochemistry 57–58, 1–45. doi: 10.1007/978-94-017-3405-9_1.

    Wall, L. G., Tank, J. L., Royer, T. V., and Bernot, M. J. (2005). Spatial and temporal variability in sediment denitrification within an agriculturally influenced reservoir. Biogeochemistry 76, 85–111. doi: 10.1007/s10533-005-2199-6.

    Yvon-Durocher, G., Jones, J. I., Trimmer, M., Woodward, G., and Montoya, J. M. (2010). Warming alters the metabolic balance of ecosystems. Philos. Trans. R. Soc. B: Biol. Sci. 365, 2117–2126. doi: 10.1098/rstb.2010.0038

    Excerpted from:

    Nevorski, K. C., & Marcarelli, A. M. (2022). High Daily and Year-Round Variability in Denitrification and Nitrogen Fixation in a Northern Temperate River. Frontiers in Water, 4, 894554. Accessed December 2023 at https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2022.894554/full#B65. CC-BY-4.0


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