Britte Schilt 10992324 5/7/2018
Bachelor Bèta-gamma, major Biology
Supervisors: K.T.C.A Peijnenburg & A.C. Pierrot-Bults Naturalis Biodiversity Center, Leiden
Chaetognath diversity
along a latitudinal
transect in the South
Atlantic
Abstract
In the South Atlantic, species distributions and community compositions of Chaetognatha (arrow worms) are relatively unknown. In this paper, distribution patterns and their explanations are examined. Along a 7000 km transect in the South Atlantic, seven plankton samples from the AMT27 cruise were analyzed. Previous research has not yet analyzed a latitudinal transect on this scale. Species richness R peaks at subtropical latitudes and there is clear correspondence with community compositions and the biogeographical provinces. Temperature is found to be an important correlate of chaetognath diversity, and the results imply that with a changing climate, distributions and abundances of this second most abundant zooplankton in the world, will be affected.
Introduction
For the last 500 million years, Chaetognatha, also known as arrow worms, have seemingly existed without undergoing major morphological changes (Briggs & Caron, 2017; Budd & Jackson, 2015; Szaniawski, 2005; Vannier, Steiner, Renvoisé, Hu, & Casanova, 2007). The first description of chaetognaths was by Slabber in 1778 (Jennings, Bucklin, & Pierrot-Bults, 2010). Since then, many authors described them as primary carnivores (Reeve, 1970) or even tigers of the plankton (Suthers, Dawon, Pitt, & Miskiewicz, 2009). The biomass of chaetognaths is estimated to be up to 20-30% of that of copepods, which are the most abundant zooplankton in the world and a food source for chaetognaths (Reeve, 1970). Compared to the entire plankton community in all oceanic regions the biomass of chaetognaths is estimated to be 5-15 % (Longhurst, 1985). Currently, approximately 150 species are described, with about half of them being pelagic species (Pierrot-Bults, 2017).
Chaetognaths are widely distributed around the globe (Pierrot-Bults, 2018). As carnivorous members of the marine zooplankton, they play an important role in pelagic food webs, both as consumers as a food source for larger organisms. However, data on distribution and abundance is far from complete. General species ranges have been described by among others Pierrot-Bults & Chidgey (1988), Bone, Kapp, & Pierrot-Bults (1991) and Pierrot-Bults (2018). Specific occurrences are less well known, especially in the South Atlantic (Pierrot-Bults & Angel, 2012). Some descriptions have been made (Kruse, Bathmann, & Brey, 2009; Michel, 1984), and research includes the Brazilian coast (Souza, Luz, & Mafalda Junior, 2014), the eastern part of the South Atlantic (Michel, 1984; Pierrot-Bults & Nair, 2010) and the Southern Ocean (Kruse Barhmann & Brey, 2009) but data on full transects is scarce.
Considering that climate is changing, it is important to know how specific species react to changing environmental factors. Plankton is free-floating (therefore dependent on circulation of water masses) and distribution of plankton is a sensitive indicator of a changing climate (Hays, Richardson & Robinson, 2005). In the year 2100, global surface temperature is expected to rise 3.7 to 4.8 degrees above the average for 1850-1900 (Pachauri & Meyer, 2014). Sea surface temperature increases as well (Cane et al., 1997; Rhein et al., 2013) and extreme weather events are likely to increase (Hegerl, Hanlon, & Beierkuhnlein, 2011;
Kerr, 2011; Rhein et al., 2013; Stocker et al., 2013). Climate change influences community structure, distribution and abundance of plankton communities (Hays, Richardson, & Robinson, 2005). In copepods for example, one of the main food sources of chaetognaths, dramatic shifts have been documented. Warm-water assemblages in the North Atlantic have moved 1000 km further north in the last 40 years (Hays et al., 2005). Edward & Richardson (2004) showed that the responses of species to climate change can differ between trophic levels. Changes in timing of seasonal peaks can lead to mismatches between trophic levels, with possible far-reaching consequences for marine ecosystems. Because chaetognaths are so abundant around the world and are a major component of marine food webs, their ability to respond to a changing environment must be looked into.
Today, still little is known about chaetognaths and even no consensus is found on where to position them among other metazoan phyla (Gasmi et al., 2014; Marlétaz et al., 2006). Furthermore, recent research suggests that their position in marine food webs might be even more important than thought. (Casanova, Barthelemy, Duvert, & Faure, 2012) suggest chaetognaths are more osmotrophic instead of strictly carnivorous, and mainly consume Dissolved Organic Material (DOM). This way, instead of being “primary carnivores”, they might also be of importance in carbon sequestration (Casanova et al., 2012; Giesecke, Gonzalez, & Bathmann, 2009).
To get a better understanding of chaetognaths and their role in the marine environment, research to the distribution and abundance of these species and how those patterns can be explained, is a crucial first step. Latitudinal patterns in species richness seem less clear in marine ecology than terrestrial ecology. Where in most terrestrial groups diversity peaks at the equator, in marine taxa, like among others foraminifers (Rutherford, D'Hondt, & Prell, 1999), and copepods (Rombouts et al., 2009) this is often not the case. Diversity (measured in species or taxon richness) tends to peak in subtropical regions (Rombouts et al., 2009; Tittensor et al., 2010) or show platforms of high richness on the Southern hemisphere and a peak and sharp decline in the Northern hemisphere (Rutherford et al., 1999). These patterns can be explained by the stability of the environment (Pierrot-Bults & Angel, 2012). In regions where the water column is permanently stratified and stable, species richness tends to be higher. Where there is high productivity, the environment is unstable due to upwelling and mixing. Fewer species are adapted to varying, unstable and harsh conditions. Therefore in these more unstable environments like the tropics, and at higher latitudes, species richness and evenness tends to be lower (Pierrot-Bults & Angel, 2012). It has also been found temperature is an important correlate for diversity, with more species occurring at higher temperatures (Fanjul et al., 2018; Tittensor et al., 2010).
To observe the structure and biochemical properties of planktonic ecosystems in the Atlantic Ocean, in 1995 the AMT programme has been set up (Atlantic meridional transect, 2018). Approximately once a year the AMT tracks cover basin-scale transects in the Atlantic Ocean. Metadata on temperature,
oxygen, chlorophyll a
(fluorescence measured) and salinity is collected along the
same track. The cruises cross different water masses on the route. These different water masses have distinct biogeochemical properties (e.g. salinity, primary production and temperature) and based on these differences the Longhurst Provinces can be recognized. In 2007, Longhurst proposed a map for these provinces. In 2014, Reygondeau et.al. revised this map and showed that the provinces have dynamic boundaries and change over seasonal time scales (figure 1). As chaetognaths have been proposed as indicator species for different water masses (Russel, 1935) these provinces can provide an interesting framework for chaetognath distributions and spatial comparison. In 2017, an AMT cruise (the AMT27) crossed the Atlantic, taking samples at 35 stations and collecting metadata along the same track. The total track measured approximately 15.000 km, from 46 to -50 degrees latitude. In 2008 and 2012, similar cruises (the AMT18 and AMT22) have covered the same area, with data on chaetognaths being analysed by Otto (2014). With repeated sampling on this transect, temporal stability can be assessed.
This paper is focusing on chaetognaths in the South Atlantic, from approximately 0 to -50 degrees latitude on seven stations. The AMT27 cruise crossed this part of the Atlantic in October 2017. With this research we hope to find out species distributions, whether chaetognaths follow the pattern of high diversity in the subtropics, and whether there’s correspondence between different community compositions and the Longhurst Provinces. Data on pteropods and heteropods, other marine phyla, are analysed by other bachelor students along the same track. When all complete in the future, distribution patterns can be compared between phyla.
In the oceans, the volume of living space is way greater than on land and the majority is under-sampled, especially the Southern Hemisphere (Pierrot-Bults & Angel, 2012; Webb, Vanden Berghe, & O'Dor, 2010). This research on the AMT27 track will contribute to our knowledge of distribution and diversity of chaetognaths, a poorly understood member of the marine environment.
Hypotheses and predictions
Temperature is expected to be an important correlate factor in species diversity, with more diversity at higher temperatures. Evenness is expected to be low in the Figure 1. Relevant for the analyzed part of the AMT27 track are the Western Tropical Atlantic Province (pink), the South Atlantic Gyral Province (lighter pink), the South Subtropical Convergence Province (lilac), the Subantarctic Province (blue)
Antarctic regions, with only few species accounting for a large part of the chaetognaths. Fluorescence (a measure for chlorophyll a) is expected to be negatively correlated to species richness, because of the instability of areas with high productivity. If chaetognaths follow the same distribution patterns as other marine phyla, diversity will peak at subtropic latitudes. At the AMT27 cruise, oblique tows were made. These tows have greater volume than the vertical hauls made by the AMT18 and AMT22 cruises, therefore higher species richness is expected in the AMT27 samples. According to known occurrences and using the species division of Ritter-Zahony (1911), a total of around 15 different species is expected to be found. If species compositions follow the pattern of the Longhurst Provinces, the cluster analysis will show more similarities between stations sampled in the same province.
Research methods & materials
Plankton samples were taken at 33 stations along the Atlantic Meridional Transect cruise AMT27 in 2017. In this paper, the station numbers 1 t/m 7 will be used instead of the official station names The stations are located in the following Longhurst Provinces, following the boundaries described in Reygondeau et. al. in the month October (figure 1) (Reygondeau et al., 2014).
1 (AMT27 33-17): Western Tropical Atlantic Province (WTAP)
2 (AMT27 43-22): Boundary of WTAP and South Atlantic Gyral Province (SATG) 3 (AMT27 49-25): SATG
4 (AMT27 51-26): SATG
5 (AMT27 57-28): Subtropical Convergence Province (SSTC) 6 (AMT27 63-31): Subantarctic Province (SANT)
7 (AMT27 65-32): Boundary of SANT and Antarctic Province (ANTA)
The exact coordinates of the dynamic provinces were not available. Therefore it is estimated in which province the stations are located. Using the older province boundaries of Longhurst (2007) both station 6 and 7 are located in the SANT, and station 2 is located clearly in the SATG.
Samples have been taken at night with quantitative 0.71m- diameter
Table 1. Overview of station names, coordinates and depth and volume. Of stations 5-7, maximum depth has not been recorded. The volume is used for calculations on abundance.
Table 2. Data collected for CTD plots, analyzing the water column. The Longhurst Provinces are assigned using descriptions from Reygondeau et.al. (2014).
oblique bongo tows (200 µm), at depths between 233 – 422 m with an average
maximum depth of 342 meters. A LOTEK time-depth-recorder and a General Oceanics flowmeter were attached to one net. A quantitative 50% of the zooplankton in the net was immediately preserved in 4% formalin. The other half was preserved in ethanol. The half preserved in formalin was used for collecting chaetognaths. Along the same track, environmental metadata has been collected on temperature, oxygen, chlorophyll a (fluorescence measured) and salinity, as seen in table 2. Analysis of the plankton samples was done at research center Naturalis, Leiden. Chaetognaths were sorted from the samples and morphologically identified to species level. Identification was done using a microscope, using descriptions from (Michel, 1984) Pierrot-Bults & Chidgey (1988), Pierrot-Bults (2017), Pierrot-Bults (2018) and with personal help from specialist Annelies Pierrot-Bults. Characteristics that were used for identification were size, body ratios, shape of eye pigment, seminal vesicles and ovaries, amount of teeth and hooks, presence/absence of a gut diverticula and/or collarette and other characteristics described in Pierrot-Bults & Chidgey (1988). For this research, the species division made by (Von Ritter-Zahony, 1911) is used.
After identification and counting, total abundance, species richness R, evenness J’ and diversity index H’ (Shannon) were calculated for each station. Abundance per 1000 m^3 was calculated using the total sorted water volume and the amount of chaetognaths in the sample, keeping in mind the sample was a quantitative 50% split. The Shannon diversity index is widely used as a measure for biodiversity. H’ and J’ were calculated using the following equation:
Here, pi is the relative abundance of species i. This way this index accounts for both richness and evenness of the species present. High values occur when richness is high and species are about equally abundant.
To examine similarities between samples, the Bray-Curtis dissimilarity measure was used. In ecological research this is a widely used measure to compare species compositions (Lefcheck, 2014; Paliy O. & Shankar V., 2016). With this measure, similarities between stations can be visualized in a dendrogram. The number of individuals of each species was multiplied by 1000, and divided by the volume of the filtered sea water at that station, for fair comparison between stations. Based on a community-by-species matrix this method can show how different the stations are in species composition. This way
the assemblages could be tested for congruence with the Longhurst Provinces. For data visualisation along the transect, GIS was used in combination with maps of ocean temperatures to accurately visualize the coordinates of the stations.
Previous data & analysis
In previous years, AMT18 (2008) and AMT22 (2012) have covered the same area. Data on those samples was collected by Otto (2014) and is available through Naturalis Biodiversity Center, Leiden. The AMT18 and AMT22 cruises did not take quantitative samples, making it impossible to compare species abundance. During these cruises, vertical net hauls were made to 180 and 240 m. Though the locations of the samples do not correspond precisely over the years, a repeated measure ANOVA will be used to find out whether there are differences in diversity H’, and richness R on corresponding latitudes. The seventh station of the AMT27 cruise is left out here, because the other cruises didn’t sample that far south.
Figure 2. Overview of the
chaetognath species found on the AMT27 track. Each pie graph represents one station. Exact coordinates can be found in table 1 and separate pie graphs in Appendix I. The background illustrates the yearly average sea surface temperature.
Results
In figure 2, the compositions of the chaetognath communities are visualized. A total of 5928 chaetognaths have been counted, with 3885 of them being identified. 2043 chaetognaths could not be identified because they didn’thave clear characteristics, were damaged, or were juveniles (lacking ovaries and/or seminal vesicles). A total of fifteen species from four genera have been found. Body mass and body size were not quantified, but on average, individuals found at station 6 and 7 were larger than individuals at other stations. Compared to all other species, the largest indivduals were S. gazellae, only occurring at
those two stations. At station 5, the largest amount of juveniles was found (1024 individuals) which
could not be identified. In most subtropical stations,
S. lyra was the most
Figure 4 (a,b) Diversity plotted against the measured environmental factors: temperature (red) and oxygen concentration (blue). Both relationships are significant (p<0.01).
Figure 3. Cluster dendrogram calculated with the Bray-Curtis dissimilarity measure. Stations grouped closer together have more similarities. Below the station numbers you find the assumed biogeographical provinces.
y = 0.513x + 0.270 R^2 = 0.796
Figure 4 (c,d)
Diversity plotted against fluorescence (green) and salinity (yellow). For fluorescence (p=0.146) and salinity (p=0.0584) correlations are not significant.
dominant species. At station 1, S. serratodentata was most dominant and in the Antarctic regions this was E. hamata. Following E.hamata due to high abundance at station 6, S.lyra was overall the most abundant chaetognath species, being identified 906 times. S. decipiens, with only seven occurrences in two stations was the least abundant species found. Figure 3 visualizes the similarities in species composition between the different stations. Stations that are grouped closer together, have more similarities in occurrences and relative abundances. Station 6 and 7 form a cluster, both located in the Antarctic region. Station 1, being the only station entirely located in the tropical province, is separate from stations 2-5. Furthermore station 2 and 3, and 4 and 5 are grouped together.
When comparing diversity index H’ with the environmental factors, significant correlations were found for temperature and oxygen. Diversity is positively correlated with temperature and negatively with oxygen concentration (p<0.01. figure 4 (a,b)). Significant results were also found when comparing oxygen and temperature with diversity measured in simple species richness (R^2=0.738, p<0.05 & R^2=0.582, p<0.05). In figure 4, the correlations between salinity and fluorescence are also visualized. However, no significant results were found for those environmental factors. Together with the species richness, the overall abundances and diversity indices are visualized in figure 5. The exact values can be found in Appendix II. Above the graph, ODV plots of temperature and oxygen are visualized of the South Atlantic region (AMT, (PML).2018). Of the AMT27 samples, diversity is highest at station 2 (H’=1.51), which is located in the subtropics (South Atlantic Gyral Province). This station is closely followed by station 5 (H’= 1.48), also located in the subtropics, but in the Subtropical Convergence Province. Lowest diversity is found at station 6 (H’=0.26) and at station 7 (H’=0.38), located in the Subantarctic and Arctic Province. Looking at species richness, the highest values are found at station 4 and 5 (10 and 11 species) and the lowest values (2 and 3) are found at station 6 and 7. Overall abundance per 1000 m^3 is highest at station 4 (1948.4) and 6 (1887.6) and lowest at station 2 (271) and 3 (230).
Pressure (dbar)
Pressure (dbar)
Oxygen (umol/L) Temperature (ºC)
Figure 5. The top two images are ODV plots from the South Atlantic, on temperature and oxygen. The left y-axis visualizes the depth. The bottom graph represents diversity H’, richness R and abundance per 1000 m^3 with corresponding latitudes on the x-axis.
Evenness was also calculated for each station. A negative correlation was found between latitude and evenness, with lowest evenness at the highest latitudes. However, with a p-value of 0.063 this was not significant
(supplementary graph I). The combined data on
richness from the AMT18 and AMT22 cruises can be found in figure 6. Stations with comparable latitudes (however not fully corresponding) have been used for comparison. With a repeated measure ANOVA, where the stations are paired, an increase in richness has proven to be significant (p<0.01). On H’, no significant differences have been found between the cruises in 2008, 2012 and 2018. Abundance data has not been compared due to the different ways of sampling. Graphs of species richness with the corresponding latitudes can be found in the Appendix. The species found at the AMT18 and AMT22 cruise were similar to the species found on the AMT27 cruise. Only S. maxima was found by Otto (2014) in some southern stations, which species wasn’t found at the AMT27 cruise. Three new species have been found on the AMT27 transect, being K. mutabii, S. marri and S. decipiens.
Figure 6. Boxplot of the richness R of the different cruises. The boxes indicate the middle two quartiles of the data’s distribution. Whiskers display all the points within 1.5 times the interquartile range.
Discussion
General distributions
In the Antarctic regions, S. gazellae and E. hamata were the most dominant species. This corresponds with other findings in this region (e.g.(Froneman & Pakhomov, 1998). That S. gazellae and S. marri were restricted to the two Antarctic stations was expected, because these are known to be cold-water species (Pierrot-Bults, 2018). E. hamata is epipelagic at high latitudes and meso-to bathypelagic at low latitudes, which fully corresponds with the found high abundance at the Antarctic stations and little to no specimens at the other stations.
In 2014, Souza et. al. researched stations close to the Brazilian coast, finding six species with epipelagic S. enflata, P. draco, S. serratodentata and S. hexaptera being the most dominant ones. In the AMT27 cruise (station 2(43-22)) seven species (including those) were found. Dominance of epi- and mesopelagic S. lyra in the AMT27 samples can easily be explained, because the samples were taken at greater depths than Souza et.al. did.
Some species might be overrepresented in the samples due to different reasons. Characteristics of P. draco for example are very clear, making it possible to identify the species even when the reproductive organs are not fully developed. The same is possible for the S. serratodentata, that stands out because of the serrated hooks. Small species like S. minima can mistakenly be identified as juveniles.
Regarding abundance, at station 7 (65_32), net clogging was reported. This means it’s probably not a quantitative tow, making the abundance data unreliable. Furthermore, all samples were taken at night but it is reported station 4 (51-26) was collected too close to dawn. Migrators may have left the surface already.
Latitudinal patterns
Species richness R (the number of species present in a sample) peaks at station 4 (51-26), where 11 species were recorded. This station is located in the subtropics. This pattern, where diversity (in terms of R) peaks in the subtropics, is also seen in other marine taxa, like foraminifers (Rutherford et al., 1999), and copepods (Rombouts et al., 2009). However, when diversity is measured with the diversity index H’ this pattern is less clear. Diversity H’ is highest at station 2, one of the stations with the lowest abundance recorded. The opposite is found for station 6, where abundance is high and diversity is very low. This low diversity was expected, as the station is located in the extreme Antarctic region.
Regarding evenness, a negative correlation was expected between increasing latitude and evenness J’. With this research however, this relationship was not significant (p=0.063). There does seem to be a correlation, so perhaps with more data points this pattern would be more clear.
Temperature, fluorescence, salinity and oxygen
As seen in figure 4, significant correlations were found between diversity (both measured in diversity index H’ and species richness) and temperature, and diversity and oxygen concentration. This correlation with temperature was expected. The negative relationship with oxygen concentration can be explained
by the overlap in regions with high temperatures and low oxygen (and low temperatures and high oxygen). No significant results were found regarding fluorescence and salinity. Low richness was expected in regions with high productivity (high fluorescence) but this was not the case (p=0.146). Station 5 could be an outlier here, with very high diversity. This station is likely to be located at a place where different water masses mix, which can explain the high diversity.
However not quantified, on average, body size was larger in the Antarctic regions than at the other stations. Larger body size of animals at higher latitudes is a well-known pattern, but not yet fully explained (Chapelle & Peck, 1999). Low temperature is seen as one of the explanatory factors, which corresponds with the findings of this study. On top of that, high oxygen concentration has also been proposed as one of the factors influencing large body size, which can also be seen in the results of sample 6 and 7 (Chapelle & Peck, 1999; McClain & Rex, 2001).
Longhurst Provinces
With the cluster analysis, it was expected to find a correlation between the Longhurst Provinces and the species compositions. The analysis showed interesting similarities between stations. When interpreting the graph (figure 3), station 6 and 7 are separate from the other stations. These stations are located in the Antarctic provinces, which explains the great dissimilarity between the tropical and subtropical stations. Furthermore, station 1 is separate from stations 2-5. This is the only station located fully in the West Atlantic Tropical Province (WTAP). Previously it was unclear whether station 2 was located in the South Atlantic Gyral Province (SATG) or in the WTAP, but this cluster analysis shows there is more similarity between station 2 and 3 than there is between those stations and station 1. The dynamic boundaries of the Longhurst Provinces (Reygondeau, 2014) can explain this uncertainty beforehand. Furthermore are station 4 and 5 more similar to each other than to station 2 and 3. It did look like those stations were located in different provinces (SATG and SSTC (Subtropical Convergence Province) presumably). The similarity between those two can either be explained by the possibility that those biogeographical regions don’t differ much in species compositions, or that station 4 was also located in the SSTC at that time of year. However, no certainty can be given on this topic. Station 5 did show the highest abundance of S. minima compared to all other stations, which is a species associated with regions of mixing of different water masses (Pierrot-Bults & Chidgey, 1988; Pierrot-(Pierrot-Bults, 2018). What can be concluded is that at least three different clusters can be found, a tropical one (station 1), a subtropical one (station 2-5) and an Antarctic one (6 and 7). For a thorough cluster analysis, the analysis of more stations and more data is desired. There are in-between stations that may add to the structure in the dendogram proposed in this paper. AMT18 and AMT22
Higher richness was found in the AMT27 samples than in the AMT18 and AMT22 samples (with a repeated-measures ANOVA). The AMT27 cruise sampled a larger volume than the AMT18 and AMT22. As is always the case with plankton research, the size of the net influences the catch. The AMT18 and AMT24 cruise
made vertical net hauls to 180 and 240 m depth, and the mesh size was 333µm (and 200µm with the AMT27). Species richness, species abundance and diversity are lower with smaller nets (McGowan & Fraundorf, 1966) and bigger with a smaller mesh size (Wu, Shin, & Chiang, 2011). Also, depending on the mesh size, larger or smaller individuals may be caught. Abundance was not compared because the previous cruises didn’t make quantitative tows. For macrozooplankton like chaetognaths, the most effective mesh size seems to be 330µm (Pierrot-Bults, pers.comm. 2018). The small mesh size of this cruise can explain the large amount of juveniles in some samples.
One species was found at the AMT18 and AMT22 cruise that wasn’t found in the AMT27 samples: the S. maxima. In the most Southern stations a few of them were found by Otto (2014). There is great resemblance between S. maxima and S. gazellae, which has been identified, but S. maxima is usually smaller in the Antarctic regions than S. gazellae, and their anterior fin begins slightly more anteriorly. Confusion of these two species could be possible. Furthermore, three more species were found on the AMT27 than at the other cruises. This can be explained by the greater volume that was sampled this time, with higher species richness as a consequence.
Conclusion
Analysis of chaetognath occurrences and abundances showed interesting correspondence with the Longhurst Provinces. This shows that the different biogeographical regions have distinct community compositions. As in other marine groups, chaetognath diversity peaks in subtropical regions and is positively correlated with temperature. Changes in climate and the ocean’s temperature may therefore have consequences for species distributions in the future.
Acknowledgements
I would like to thank Naturalis Biodiversity Center, especially Katja Peijnenburg and Annelies Pierrot-Bults for supervising this thesis and helping with sorting and identifying the chaetognaths. Thank you Emma Otto for making time to come to Leiden to help; and Bertie-Joan, Rob and Kees for facility services at the Biopartner Lab. Furthermore lots of love to Yamell Kuen, Catharina de Weerd, and Mona Hegman for keeping me company in the lab and when they left, thank you Niels van der Windt and Robbert van Himbeeck. Also thanks Radio 10 for always being there for us, especially at 16:10 PM.
References
Atlantic meridional transect, Plymouth marine laboratory (PML). (2018). Retrieved from http://www.amt-uk.org/
Bone, Q., Kapp, H., & Pierrot-Bults, A. C. (1991). The biology of chaetognaths. New York: Oxford University Press.
Briggs, D. E. G., & Caron, J. (2017). A large cambrian chaetognath with
supernumerary grasping spines doi:https://doi.org/10.1016/j.cub.2017.07.003 Budd, G. E., & Jackson, I. S. C. (2015). Ecological innovations in the cambrian
and the origins of the crown group phyla. Philosophical Transactions of the
Royal Society B, 371(1685) doi:DOI: 10.1098/rstb.2015.0287
Cane, M. A., Clement, A. C., Kaplan, A., Kushnir, Y., Pozdnyakov, D., Seager, R., . . . Murtugudde, R. (1997). Twentieth-century sea surface temperature trends. Science, 275, 957-960.
Casanova, J., Barthelemy, R., Duvert, M., & Faure, E. (2012). Chaetognaths feed primarily on dissolved and fine particulate organic matter, not on prey:
Implications for marine food webs. Hypotheses in the Life Sciences, 2(1), 20-29. Chapelle, G., & Peck, L. S. (1999). Polar gigantism dictated by oxygen availability . Nature, 399, 114. doi:10.1038/20099
Fanjul, A., Iriarte, A., Villate, F., Uriarte, I., Atkinson, A., & Cook, K. (2018). Zooplankton seasonality across a latitudinal gradient in the northeast atlantic shelves province doi:https://doi.org/10.1016/j.csr.2018.03.009
Froneman, P. W., & Pakhomov, E. A. (1998). Trophic importance of the
chaetognaths eukrohnia hamata and sagitta gazellae in the pelagic system of the prince edward islands (southern ocean). Polar Biology,
19(4), 242-249. doi:10.1007/s003000050241
Gasmi, S., Nève, G., Pech, N., Tekaya, S., Gilles, A., & Perez, Y. (2014).
Evolutionary history of chaetognatha inferred from molecular and morphological data: A case study for body plan simplification. Frontiers in Zoology, 11(1), 84. doi:10.1186/s12983-014-0084-7
Giesecke, R., Gonzalez, H. E., & Bathmann, U. (2009). The role of the chaetognath sagitta gazellae in the vertical carbon
flux of the southern ocean. Polar Biology, (33), 293-304. doi:DOI 10.1007/s00300-009-0704-4
Hays, G. C., Richardson, A. J., & Robinson, C. (2005). Climate change and marine plankton doi:https://doi.org/10.1016/j.tree.2005.03.004
Hegerl, G. C., Hanlon, H., & Beierkuhnlein, C. (2011). Elusive extremes. [ ] Nature Geoscience, 4(142) doi:http://dx.doi.org/10.1038/ngeo1090
Jennings, R. M., Bucklin, A., & Pierrot-Bults, A. C. (2010). Barcoding of arrow
worms (phylum chaetognatha) from three oceans: Genetic diversity and evolution within an enigmatic phylum. PLoS ONE, 5(4)
doi:https://doi.org/10.1371/journal.pone.0009949
Kerr, R. A. (2011). Humans are driving extreme weather; time to prepare . Science, 334(6050), 1040. doi:10.1126/science.334.6059.1040
Kruse, S., Bathmann, U., & Brey, T. (2009). Meso- and bathypelagic distribution and abundance of chaetognaths in the atlantic sector of the southern ocean. Polar Biology, 32(9), 1359-1376. doi:10.1007/s00300-009-0632-3
Lefcheck, J. (2014). NMDS tutorial in R. Retrieved from https://jonlefcheck.net/2012/10/24/nmds-tutorial-in-r/
Longhurst, A. R. (1985). The structure and evolution of plankton communities
doi:https://doi.org/10.1016/0079-6611(85)90036-9
Marlétaz, F., Martin, E., Perez, Y., Papillon, D., Caubit, X., Fasano, L., . . . Wincker, P. (2006). Chætognath phylogenomics: A protostome with deuterostome-like
development. Current Biology, 16, 577-578.
McClain, C. R., & Rex, M. A. (2001). The relationship between dissolved oxygen concentration and maximum size in deep-sea turrid gastropods, an application of quantile regression. Marine Biology, 139, 681-685.
doi:doi:10.1007/s002270100617
McGowan, J. A., & Fraundorf, V. J. (1966). The relationship between size of net used and estimates of zooplankton diversity1. Limnology and Oceanography, 11(4), 456-469. doi:10.4319/lo.1966.11.4.0456
Michel, H. B. (1984). Chaetognaths of the caribbean sea and adjacent areas. (Technical No. NOAA Technical Report NMFS 15). Washington D.C.: U.S. Department of Commerce.
Pachauri, R. K., & Meyer, L. A. (2014). Climate change 2014: Synthesis report. contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. (). Geneva, Switzerland: IPCC. Paliy O., & Shankar V. (2016). Application of multivariate statistical techniques in microbial ecology. Molecular Ecology, 25(5), 1032-1057. doi:10.1111/mec.13536 Pierrot-Bults, A. C., & Angel, M. V. (2012). Pelagic biodiversity and biogeography of the oceans. International Union of Biological Sciences, (51), 9-32.
Pierrot-Bults, A. C., & Chidgey, K. C. (1988). In Kermack D. M., Barnes R. S. K. (Eds.), Chaetognatha; keys and notes for the identification of the species. London: Brill, E.J.; Backhuys, W.
Pierrot-Bults, A. C. (2017). Chaetognatha. In C. Castellani, & M. Edwards (Eds.), Marine plankton (pp. 551-560) Oxford University Press. doi:DOI:
10.1093/oso/9780199233267.001.0001
Pierrot-Bults, A. C. (2018). Chaetognatha of the world. Retrieved from http://species-identification.org/species.php?
species_group=Chaetognatha&menuentry=soorten
Pierrot-Bults, A. C., & Nair, V. R. (2010). Horizontal and vertical distribution of chaetognatha in the upper 1000m of the western sargasso sea and the central and south-east atlantic doi:https://doi.org/10.1016/j.dsr2.2010.09.021
Reeve, M. R. (1970). The biology of chaetognatha I: Quantitative aspects of growth and egg production in sagitta hispida. In J. H. Steele (Ed.), Marine food chains (pp. 168-189). Great-Britain: University of California Press. Retrieved from https://books.google.nl/books?
hl=nl&lr=&id=Wn2gcNvYNrsC&oi=fnd&pg=PA168&dq=Reeve+1970+chaetogna
tha&ots=vFwICSQSJh&sig=2q1i3LllW88mkgP-igPzv5bgQVY#v=onepage&q=second%20to%20copepods&f=false
Reygondeau, G., Longhurst, A., Martinez, E., Beaugrand, G., Antoine, D., & Maury, O. (2014). Dynamic biogeochemical provinces in the global ocean. Global
Biogeochemical Cycles, 27(4), 1046-1058. doi:10.1002/gbc.20089
Rhein, M., Rintoul, S. R., Aoki, S., Campos, E., Chambers, D., Feely, R. A., . . . Wang, F. (2013). Observations: Ocean. in: Climate change 2013: The physical science basis. contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change [stocker, T.F., D. qin, G.-K. plattner, M. tignor, S.K. allen, J. boschung, A. nauels, Y. xia, V]. (). Cambridge: Cambridge University Press.
Rombouts, I., Beaugrand, G., Ibanez, F., Gasparini, S., Chiba, S., & Legendre, L. (2009). Global latitudinal variations in marine copepod diversity and
environmental factors. Proceedings of the Royal Society B: Biological Sciences, 276(1670), 3053-3062. doi:10.1098/rspb.2009.0742
Russel, F. S. (1935). On the value of certain plankton animals as indicators of water-movements in the english channel and north sea. Marine Biology Association, 20, 309-33.
Rutherford, S., D'Hondt, S., & Prell, W. (1999). Environmental controls on the
geographic distribution of zooplankton diversity. Nature, 400, 749-753.
doi:https://doi.org/10.1038/23449
Souza, C. S. d., Luz, J. A. G., & Mafalda Junior, P. O. (2014). Relationship between spatial distribution of chaetognaths and hydrographic conditions around
seamounts and islands of the tropical southwestern atlantic. Anais Da Academia Brasileira De Ciências, 86(3), 1151-1165. doi: https://dx.doi.org/10.1590/0001-3765201420130101
Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Boschung, J., . . . Midgley, P. M. (2013). IPCC, 2013: Climate change 2013: The physical science basis. contribution of working group I to the fifth assessment report of the
intergovernmental panel on climate change. (). Cambridge: Cambridge University Press.
Suthers, I., Dawon, M., Pitt, K., & Miskiewicz, A. G. (2009). Coastal and marine zooplankton: Diversity and biology. In I. M. Suthers, & D. Rissik (Eds.), Plankton, a guide to their ecology and monitoring for water quality (pp. 181-222). Melbourne: CSIRO Publications.
Szaniawski, H. (2005). Cambrian chaetognaths recognized in burgess shale fossils. Acta Palaeontologica Polonica, 50(1), 1-8.
Tittensor, D. P., Mora, C., Jetz, W., Lotze, H. K., Ricard, D., Berghe, E. v., & Worm, B. (2010). Global patterns and predictors of marine biodiversity across taxa . Nature, 466, 1098. doi:http://dx.doi.org/10.1038/nature09329
Vannier, J., Steiner, M., Renvoisé, E., Hu, S., & Casanova, J. (2007). Early cambrian origin of modern food webs: Evidence from predator arrow worms. Proceedings of the Royal Society B: Biological Sciences, 274(1610), 627-633.
doi:http://doi.org/10.1098/rspb.2006.3761
Von Ritter-Zahony, R. (1911). Revision der chaetognathen. . Dt. Sudpol. Exped. 13, 5(1), 1-71.
Webb, T. J., Vanden Berghe, E., & O'Dor, R. (2010). Biodiversity's big wet secret: The global distribution of marine biological records reveals chronic
under-exploration of the deep pelagic ocean
. PLoS ONE, 5(8) doi:https://doi.org/10.1371/journal.pone.0010223
Wu, C., Shin, C., & Chiang, K. (2011). Does the mesh size of the plankton net affect the result of statistical analyses of the relationship between the copepod community and water masses? Crustaceana, 84, 1069-1083.
Appendix I
Appendix II
Supplementary figures & tables
Supplementary figure 1. The correlation between evenness J’ and latitude is shown. Correlation was not significant (p=0.063)
Supplementary table 1. Counts per station, amounts of identified and unidentified species, abundance values and the exact values of richness R, diversity H’ and evenness J’
Below you can find the data on the tows conducted. For more information on the AMT27 cruise and the cruise report, visit http://www.amt-uk.org/Cruises/AMT27
Supplementary figure 2. Of all three cruises, richness R is displayed with the corresponding latitude. Red = AMT27, orange = AMT22 and grey = AMT18.
Notes: 33-17: 2 ring net tows before this CalBOBL tow.
43-22: EG has CTD water at pre-dawn cast (5, DCM, 500, 1000) as well as a cast to 5000m this day - so very little live sorting of animals.
4925:
-51-26: Ship changed the time over this night, and this sample was collected too close to dawn. Many migrators have left the surface. Freshwater wash of nets after this tow, found large hole for repair. 57-28: Should have been recorded as station 57; all tubes labelled as ZTB-58-28. TDR not working, not on deployment. Final flowmeter taken from Iniital of next day , forgot to write it down at end of deployment. Two ran through A frame of aft deck, on trawl winch / wire. Ship speed 2-3 knots, 65 kg depressor weight.
63-31: Snowing sideways during this tow
65-32: massive net clogging, very large phytoplankton around South Georgia. Clogging
Supplementary table 2(a,b). Data on the AMT27 tows. Below the tables you can find the notes on each tow.
