Abundance of three most abundant species of phytoplankton expressed as time series
Sub-challenge: Abundance of the three most abundant species of phytoplankton expressed as time series.
The definition of plankton is a group of organisms in aquatic environments which are carried along by ocean currents without the means to swim against them. Phytoplankton are the ‘flora’ plankton, or microalgae, and contain chlorophyll for photosynthesis. Primary production in oceans can be measured through chlorophyll concentrations, however this measurement does not distinguish between different species of phytoplankton. Dinoflagellates and diatoms are the two most common classes of phytoplankton.
In the Arctic area, phytoplankton are essential for primary production and serve as the basis of the marine food web. Both the presence of nutrients and light availability limit primary production, giving the Arctic area a distinct seasonal character. Upwelling of warm nutrient-rich Atlantic Water is one of the key factors driving primary production.
As described in Hallegraeff (2010): “Climate change confronts marine ecosystems with multifactorial stressors, such as increased temperature, enhanced surface stratification, alteration of ocean currents, intensification or weakening of nutrient upwelling, stimulation of photosynthesis by elevated CO2, reduced calcification from ocean acidification, and changes in land runoff and micronutrient availability”. Because climate change does not affect the phytoplankton habitat in a singular way, it is difficult to predict the response of the phytoplankton community. For example, the winter sea-ice decline creates favourable conditions for upwelling, creating in turn favourable conditions for phytoplankton (Falk-Petersen et al., 2015). Other studies however indicate a less favourable condition for phytoplankton through freshening of the water by melting ice (Coupel et al., 2015). Larsen et al. (2014) indicate that decreased sea-ice is associated with earlier phytoplankton blooms. It is clear however, that the declining sea-ice extent in the Arctic area is contributing to shifts in primary production (Frey, Moore, Cooper, & Grebmeier, 2015; Logvinova, Frey, Mann, Stubbins, & Spencer, 2015). In 2011, NOAA published a map showing the change in primary productivity, based on a study by Arrigo & van Dijken (2015), see Figure 1.
Higher ocean temperatures create an increasingly stratified water column, inhibiting nutrient rich waters from mixing with nutrient depleted waters. The quantity of larger phytoplankton such as diatoms are predicted to decrease as they need more nutrients to survive, compared with smaller phytoplankton such as cyanobacteria (Lindsey & Scott, 2010). However, in the polar regions the reduced mixing will keep the plankton closer to the surface (and to sunlight), creating favourable conditions for an increase in plankton (Hallegraeff, 2010). In general, the effects of climate change on on phytoplankton is poorly understood (Hoppe et al., 2016).
Figure 1: Changes in primary production between 1998 and 2000. Browns show declines, while greens show increases. Increases in primary production were greatest in the eastern Arctic Ocean, mirroring the areas of greatest sea ice loss in the Kara and East Siberian seas (source: Arrigo & van Dijken 2011 and NOAA 2011).
As can be seen in Figure 1, the primary production varies over the entire Arctic area, even over a limited time span of two years.
The COPEPOD database has a nice summary of available plankton data in the Arctic area. https://www.st.nmfs.noaa.gov/copepod/content/region_arctic.html. COPEPOD stands for ‘The Coastal & Oceanic Plankton Ecology, Production & Observation Database’ and is an online database of plankton abundance, biomass, and composition data compiled from a global assortment of cruises, projects, and institutional holdings. It was created by NOAA's National Marine Fisheries Service. Full database content and method summaries are released roughly every few years (e.g. COPEPOD-2014, COPEPOD-2010, COPEPOD-2007, COPEPOD-2005), with new data content added and immediately available online each month. COPEPOD has an interactive map area for phytoplankton, as shown as a screenshot in Figure 2.
Figure 2: Phytoplankton data in COPEPOD. (http://www.st.nmfs.noaa.gov/copepod/atlas/index-atlas.html#phytoplankton)
As can be seen on the screenshot, the phytoplankton data available is quite limited. All data from COPEPOD can be downloaded and viewed in different images, such as per sub-group or season. The data downloaded from COPEPOD is a compilation of all known phytoplankton data. When only the data from a Latitude of 60 and up are shown, 42747 data points remain, showing data between 1913 to 2015 (this can be downloaded as Excel file). However, as this data is not consistent in time and space, or even in monitoring effort on the same points), creating timeseries would not deliver consistent images. In total, 834 species are listed in this dataset, with Thalassiosira gravida, Nitzschia longissima en Protoperidinium pellucidum counting the most points.
As an example, from the Biological Atlas of the Arctic Seas 2000 (BAAS2000): Phytoplankton data was downloaded from COPEPOD for 158 scientific cruises in the Barents and Kara Seas in the period 1913 - 1999 (part of NOAA, https://www.nodc.noaa.gov/OC5/BARPLANK/start.html). The most abundant species in this data set were: Fragilaria spp, Thalassiosira spp, Chlorophycota spp, Nitzschia spp and Melosira spp. However, due to the spatial and temporal gaps in the data, it is not suitable to create time series. On the website of BAAS2000, there is a small section on changes in the phytoplankton community over time. Three options are available: 1921 vs. 1997 Barents Sea, 1921-1957-1985-1997 Barents Sea and 1921 vs. 1997 Kola Section. When clicking on this, information on the data and some figures come up, as in Figure 3.
Figure 3: Screenshot of the BAAS2000 phytoplankton community changes website (https://www.nodc.noaa.gov/OC5/BARPLANK/WWW/HTML/phyt_ch1.html).
COPEPODITE is a branch from COPEPOD; an interactive time-series explorer analysis toolkit and metabase (http://www.st.nmfs.noaa.gov/copepodite/index.html). It provides a map overview of global monitoring, with clickable monitoring points. As an example, we chose the Siglunes Transect north of Iceland (Figure 4).
Figure 4: Location of Siglunes Transect. Source: COPEPODITE (http://www.st.nmfs.noaa.gov/copepod/time-series/is-30101/)
The site provides data on:
- Total Diatoms (#/l) from 2007 to 2015
- Total Dinoflagellates (#/l) from 2007 to 2015
- Total Flagellates (#/l) from 2007 to 2015
- Total Ciliates (#/l) from 2007 to 2015
- Average Chlorophyll (mg/m3) from 0-25m from 1987 to 2015
Standard plots are available for viewing (Figure 5). However, the original data is not available on theCOPEPODITE website but has to be sought.
Figure 5: Time-series of annual average of total diatoms, dinoflagellates, flagellates and ciliates from the Siglunes transect (north Iceland). Source: COPEPODITE (http://www.st.nmfs.noaa.gov/copepod/time-series/is-30101/html/zoom-groupsbox.html).
Figure 6: Time-series of annual average of Chlorophyll concentration, measured by four different measuring units, from the Siglunes transect (north Iceland). Source: COPEPODITE (http://www.st.nmfs.noaa.gov/copepod/time-series/is-30101/html/zoom-groupsbox.html).
The Phytplankton Monitoring Network offers an interactive viewing map, which shows monitoring data on species level (https://www.ncddc.noaa.gov/website/PMN/viewer.htm). However, when searching for all species, only a three month time period can be shown. When only showing data on blooms, all species can be selected. When searching between 2008 and 2017, no monitoring data in the study area (Arctic) or tributary water systems are available.
The Arctic Ocean Diversity website offers Plankton datasets (http://www.arcodiv.org/Database/Plankton_datasets.html). Of these datasets, only one contains phytoplankton: Phytoplankton of the White Sea, Barents Sea, Amundsen & Nansen Basins, 1993-2003. The data can be downloaded as CSV or XML file.
Data use, availability and gaps
Data is available but sparse, in comparison to the breadth of the question asked. However, the lack of data is relatively easy to explain; data gathering is very time and money consuming. The available data is very specific for a certain time and space and averaging does not work well. Data gaps exist in both time and space, especially on species level. More data is available on species groups level or simply on primary production or chlorophyll concentrations, which is easier to measure. Consistent monitoring is needed to create reliable timeseries.
Conclusion and lessons learned
On species level, it is difficult and unwise to generalize the most common species in of the entire Arctic area, as the area is simply too large and diverse. Even on smaller areas the most common species differ year to year and season to season. No direct conclusion can be drawn from the assembled data. Lessons learned during the gathering of the data are:
- Data on phytoplankton is available, but limited in detail, time and space;
- More data is available on species groups than on individual species level;
- More data is available on Chlorophyll concentrations;
- Phytoplankton are strongly linked to climate change.
- The study area is quite broad and is home to many different types of (eco-)systems, which makes it unwise to generalize the three most abundant species of phytoplankton.
- Even in small geographical areas the most abundant species may change year to year, so the most abundant species one year may not be the most abundant species the next year. The length of a time series can be crucial for the outcomes and the conclusions drawn.
- Most studies focus on either zooplankton or primary production in a broad sense, generally focusing on chlorophyll concentrations rather than on individual species.
- The data which is available is quite sporadic both on a temporal and spatial level, is presented in different formats and need different levels of processing.
- There seem to be gaps in both time and space of monitored areas in the arctic when it comes to individual species of phytoplankton. Data found was not always up-to-date.
- There are not many permanent monitoring stations for phytoplankton, a lot of the data comes from research expeditions or cruises. Differences in time and space makes comparison between datasets difficult.
When interested in phytoplankton species composition and change in the entire Arctic area, an extensive monitoring and research program should be set up. This is highly recommended in the fast-changing Arctic area, focused on melting sea-ice and changing upwelling conditions for many species.
- Pan-Arctic approach on the study of phytoplankton. Set up consistent monitoring programs to better understand the distribution and change in phytoplankton in the Arctic area.
- Create an open sourced phytoplankton datahub for the Arctic area, including data downloads and map availability.
- Focus on the influence of climate change on phytoplankton and translate this into consequences further up the food chain.
- Focus on Ice-edge areas throughout the year to research the phytoplankton community and development.
- Link to alien species and shipping routes, as shipping might be an important factor in bringing alien species of phytoplankton to the Arctic area.
- World-wide or at least Arctic-wide standardisation of monitoring and reporting.
- Arrigo, K. R., & Dijken, G. L. Van. (2015). Continued increases in Arctic Ocean primary production. Progress in Oceanography, 136, 60–70. http://doi.org/10.1016/j.pocean.2015.05.002
- Bopp, L., O. Aumont, P. Cadule, S. Alvain, and M. Gehlen (2005), Response of diatoms distribution to global warming and potential implications: A global model study, Geophys. Res. Lett., 32, L19606, doi:10.1029/2005GL023653 http://onlinelibrary.wiley.com/doi/10.1029/2005GL023653/epdf
- Coupel, P., Ruiz-pino, D., Sicre, M., Chen, J. F., Lee, S. H., Schiffrine, N., … Gascard, J. (2015). The impact of freshening on phytoplankton production in the Pacific Arctic Ocean To. Progress in Oceanography, 131, 113–125. http://doi.org/10.1016/j.pocean.2014.12.003
- Falk-Petersen, S., Pavlov, V., Berge, J., Cottier, F., Kovacs, K. M., & Lydersen, C. (2015). At the rainbow’s end: high productivity fueled by winter upwelling along an Arctic shelf. Polar Biology, 38, 5–11. http://doi.org/10.1007/s00300-014-1482-1
- Frey, K. E., Moore, G. W. K., Cooper, L. W., & Grebmeier, J. M. (2015). Divergent Patterns of Recent Sea Ice Cover across the Bering, Chukchi, and Beaufort Seas of the Pacific Arctic Region. Progress in Oceanography, 136, 32–49. http://doi.org/10.1016/j.pocean.2015.05.009
- Hallegraeff, G. M. (2010). Ocean climate change , phytoplankton community responses, and harmful algal blooms: a formidable predictive challenge. Journal of Phycology, 46, 220–235. http://doi.org/10.1111/j.1529-8817.2010.00815.x
- Hoppe, C. , Schuback, N. , Wolf, K. , Semeniuk, D. , Giesbrecht, K. , Maldonado, M. T. , Varela, D. E. , Rost, B. and Tortell, P. D. (2016): Combined effects of ocean acidification and enhanced irradiances on Arctic phytoplankton assemblages – Why do they not care? , Gordon Research Conference ‘Global Ocean Change Biology’, Waterville Valley, NH, USA, 17 July 2016 - 22 July 2016. http://epic.awi.de/41613/
- Larsen, J. N., Anisimov, O. A., Constable, A., Hollowed, A. B., Maynard, N., Prestrud, P., … Stone, J. M. R. (2014). Polar Regions. In V. R. Bggarros, C. B. Field, D. J. Dokken, M. D. Mastrandrea, K. J. Mach, T. E. Bilir, … L. L. White (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1567–1612). Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press. Retrieved from http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap28_FINAL.pdf
- Logvinova, C., Frey, K., Mann, P., Stubbins, A., & Spencer, R. (2015). Assessing the potential impacts of declining Arctic sea ice cover on the photochemical degradation of dissolved organic matter in the Chukchi and Beaufort Seas. Journal of Geophysical Research Biogeosciences, 120(11), 2326–2344. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/2015JG003052/full
- http://earthobservatory.nasa.gov/Features/Phytoplankton/ (Earth Observatory)
- http://www.arcodiv.org/Database/Plankton_datasets.html (Arctic Ocean Diversity)
- https://www.ncddc.noaa.gov/website/PMN/viewer.htm (Phytoplankton Monitoring Network)
- https://www.nodc.noaa.gov/OC5/BARPLANK/WWW/INV_CRUS/inventory.html (Ocean Climate Laboratory)
- http://www.st.nmfs.noaa.gov/copepod/ (COPEPOD)
- http://www.st.nmfs.noaa.gov/copepod/time-series (COPEPODITE)
- https://www.climate.gov/news-features/features/sea-ice-declines-boost-arctic-phytoplankton-productivity (NOAA Climate.gov)