Comparison of Zooplankton Sampling Performance of Longhurst-Hardy Plankton Recorder and Bongo Nets

Data on the abundance and biomass of zooplankton off the northwestern Portuguese coast, separately estimated with a Longhurst-Hardy Plankton Recorder (LHPR) and a Bongo net, were analysed to assess the comparative performance of the samplers. Zooplankton was collected along four transects perpendicular to the coast, deployments alternating between samplers. Total zooplankton biomass measured using the LHPR was significantly higher than that using the Bongo net. Apart from Appendicularia and Cladocera, abundances of other taxa (Copepoda, Mysidacea, Euphausiacea, Decapoda larvae, Amphipoda, Siphonophora, Hydromedusae, Chaetognatha and Fish eggs) were also consistently higher in the LHPR. Some of these differences were probably due to avoidance by the zooplankton of the Bongo net. This was supported by a comparative analysis of prosome length of the copepod Calanus helgolandicus sampled by the two nets that showed that Calanus in the LHPR samples were on average significantly larger, particularly in day samples. A ratio estimator was used to produce a factor to convert Bongo net biomass and abundance estimates to equate them with those taken with the LHPR. This method demonstrates how results from complementary zooplankton sampling strategies can be made more equivalent.

Differences in performance among four indices used to evaluate diversity in planktonic ecosystems

The performance of four common estimators of diversity are investigated using calanoid copepod data from the Continuous Plankton Recorder (CPR) survey. The region of the North Atlantic and the North Sea was divided into squares of 400 nautical miles for each 2-month period. For each 144 possible cases, Pielou's pooled quadrat method was performed with the aims of determining asymptotic diversity and investigating the CPR sample-size dependence of diversity estimators. It is shown that the performance of diversity indices may greatly vary in space and time (at a seasonal scale). This dependence is more pronounced in higher diverse environments and when the sample size is small. Despite results showing that all estimators underestimate the `actual' diversity, comparison of sites remained reliable from a few pooled CPR samples. Using more than one CPR sample, the Gini coefficient appears to be a better diversity estimator than any other indices and spatial or temporal comparisons are highly satisfactory. In situations where comparative studies are needed but only one CPR sample is available, taxonomic richness was the preferred method of estimating diversity. Recommendations are proposed to maximise the efficiency of diversity estimations with the CPR data.

Comparison of two methods to derive the size-structure of natural populations of phytoplankton

Various methods have been proposed to estimate the size structure of phytoplankton in situ , each exhibiting limitations and advantages. Two common approaches are size-fractionated filtration (SFF) and analysis of pigments derived from High Performance Liquid Chromatography (HPLC), and yet these two techniques have rarely been compared. In this paper, size-fractionated chlorophylls for pico- (View the MathML source<2μm), nano- (View the MathML source2–20μm) and micro-phytoplankton (View the MathML source>20μm) were estimated independently from concurrent measurements of HPLC and SFF data collected along Atlantic Meridional Transect cruises. Three methods for estimating size-fractionated chlorophyll from HPLC data were tested. Size-fractionated chlorophylls estimated from HPLC and SFF data were significantly correlated, with HPLC data explaining between 40 and 88% of the variability in the SFF data. However, there were significant biases between the two methods, with HPLC methods overestimating nanoplankton chlorophyll and underestimating picoplankton chlorophyll when compared with SFF. Uncertainty in both HPLC and SFF data makes it difficult to ascertain which is more reliable. Our results highlight the importance of using multiple methods when determining the size-structure of phytoplankton in situ, to reduce uncertainty and facilitate interpretation of data.

The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Assessing marine plankton community structure from long-term monitoring data with multivariate autoregressive (MAR) models: a comparison of fixed station versus spatially distributed sampling data

We examined how marine plankton interaction networks, as inferred by multivariate autoregressive (MAR) analysis of time-series, differ based on data collected at a fixed sampling location (L4 station in the Western English Channel) and four similar time-series prepared by averaging Continuous Plankton Recorder (CPR) datapoints in the region surrounding the fixed station. None of the plankton community structures suggested by the MAR models generated from the CPR datasets were well correlated with the MAR model for L4, but of the four CPR models, the one most closely resembling the L4 model was that for the CPR region nearest to L4. We infer that observation error and spatial variation in plankton community dynamics influenced the model performance for the CPR datasets. A modified MAR framework in which observation error and spatial variation are explicitly incorporated could allow the analysis to better handle the diverse time-series data collected in marine environments.

Distribution, occurrence and biotoxin composition of the main shellfish toxin producing microalgae within European waters: A comparison of methods of analysis.

Harmful algal blooms (HABs) are a natural global phenomena emerging in severity and extent. Incidents have many economic, ecological and human health impacts. Monitoring and providing early warning of toxic HABs are critical for protecting public health. Current monitoring programmes include measuring the number of toxic phytoplankton cells in the water and biotoxin levels in shellfish tissue. As these efforts are demanding and labour intensive, methods which improve the efficiency are essential. This study compares the utilisation of a multitoxin surface plasmon resonance (multitoxin SPR) biosensor with enzyme-linked immunosorbent assay (ELISA) and analytical methods such as high performance liquid chromatography with fluorescence detection (HPLC-FLD) and liquid chromatography–tandem mass spectrometry (LC–MS/MS) for toxic HAB monitoring efforts in Europe. Seawater samples (n = 256) from European waters, collected 2009–2011, were analysed for biotoxins: saxitoxin and analogues, okadaic acid and dinophysistoxins 1/2 (DTX1/DTX2) and domoic acid responsible for paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP), respectively. Biotoxins were detected mainly in samples from Spain and Ireland. France and Norway appeared to have the lowest number of toxic samples. Both the multitoxin SPR biosensor and the RNA microarray were more sensitive at detecting toxic HABs than standard light microscopy phytoplankton monitoring. Correlations between each of the detection methods were performed with the overall agreement, based on statistical 2 × 2 comparison tables, between each testing platform ranging between 32% and 74% for all three toxin families illustrating that one individual testing method may not be an ideal solution. An efficient early warning monitoring system for the detection of toxic HABs could therefore be achieved by combining both the multitoxin SPR biosensor and RNA microarray.

Distribution, occurrence and biotoxin composition of the main shellfish toxin producing microalgae within European waters: A comparison of methods of analysis.

Harmful algal blooms (HABs) are a natural global phenomena emerging in severity and extent. Incidents have many economic, ecological and human health impacts. Monitoring and providing early warning of toxic HABs are critical for protecting public health. Current monitoring programmes include measuring the number of toxic phytoplankton cells in the water and biotoxin levels in shellfish tissue. As these efforts are demanding and labour intensive, methods which improve the efficiency are essential. This study compares the utilisation of a multitoxin surface plasmon resonance (multitoxin SPR) biosensor with enzyme-linked immunosorbent assay (ELISA) and analytical methods such as high performance liquid chromatography with fluorescence detection (HPLC-FLD) and liquid chromatography–tandem mass spectrometry (LC–MS/MS) for toxic HAB monitoring efforts in Europe. Seawater samples (n = 256) from European waters, collected 2009–2011, were analysed for biotoxins: saxitoxin and analogues, okadaic acid and dinophysistoxins 1/2 (DTX1/DTX2) and domoic acid responsible for paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP), respectively. Biotoxins were detected mainly in samples from Spain and Ireland. France and Norway appeared to have the lowest number of toxic samples. Both the multitoxin SPR biosensor and the RNA microarray were more sensitive at detecting toxic HABs than standard light microscopy phytoplankton monitoring. Correlations between each of the detection methods were performed with the overall agreement, based on statistical 2 × 2 comparison tables, between each testing platform ranging between 32% and 74% for all three toxin families illustrating that one individual testing method may not be an ideal solution. An efficient early warning monitoring system for the detection of toxic HABs could therefore be achieved by combining both the multitoxin SPR biosensor and RNA microarray.

Underway spectrophotometry along the Atlantic Meridional Transect reveals high performance in satellite chlorophyll retrievals

To evaluate the performance of ocean-colour retrievals of total chlorophyll-a concentration requires direct comparison with concomitant and co-located in situ data. For global comparisons, these in situ match-ups should be ideally representative of the distribution of total chlorophyll-a concentration in the global ocean. The oligotrophic gyres constitute the majority of oceanic water, yet are under-sampled due to their inaccessibility and under-represented in global in situ databases. The Atlantic Meridional Transect (AMT) is one of only a few programmes that consistently sample oligotrophic waters. In this paper, we used a spectrophotometer on two AMT cruises (AMT19 and AMT22) to continuously measure absorption by particles in the water of the ship's flow-through system. From these optical data continuous total chlorophyll-a concentrations were estimated with high precision and accuracy along each cruise and used to evaluate the performance of ocean-colour algorithms. We conducted the evaluation using level 3 binned ocean-colour products, and used the high spatial and temporal resolution of the underway system to maximise the number of match-ups on each cruise. Statistical comparisons show a significant improvement in the performance of satellite chlorophyll algorithms over previous studies, with root mean square errors on average less than half (~ 0.16 in log10 space) that reported previously using global datasets (~ 0.34 in log10 space). This improved performance is likely due to the use of continuous absorption-based chlorophyll estimates, that are highly accurate, sample spatial scales more comparable with satellite pixels, and minimise human errors. Previous comparisons might have reported higher errors due to regional biases in datasets and methodological inconsistencies between investigators. Furthermore, our comparison showed an underestimate in satellite chlorophyll at low concentrations in 2012 (AMT22), likely due to a small bias in satellite remote-sensing reflectance data. Our results highlight the benefits of using underway spectrophotometric systems for evaluating satellite ocean-colour data and underline the importance of maintaining in situ observatories that sample the oligotrophic gyres.

Underway spectrophotometry along the Atlantic Meridional Transect reveals high performance in satellite chlorophyll retrievals

To evaluate the performance of ocean-colour retrievals of total chlorophyll-a concentration requires direct comparison with concomitant and co-located in situ data. For global comparisons, these in situ match-ups should be ideally representative of the distribution of total chlorophyll-a concentration in the global ocean. The oligotrophic gyres constitute the majority of oceanic water, yet are under-sampled due to their inaccessibility and under-represented in global in situ databases. The Atlantic Meridional Transect (AMT) is one of only a few programmes that consistently sample oligotrophic waters. In this paper, we used a spectrophotometer on two AMT cruises (AMT19 and AMT22) to continuously measure absorption by particles in the water of the ship's flow-through system. From these optical data continuous total chlorophyll-a concentrations were estimated with high precision and accuracy along each cruise and used to evaluate the performance of ocean-colour algorithms. We conducted the evaluation using level 3 binned ocean-colour products, and used the high spatial and temporal resolution of the underway system to maximise the number of match-ups on each cruise. Statistical comparisons show a significant improvement in the performance of satellite chlorophyll algorithms over previous studies, with root mean square errors on average less than half (~ 0.16 in log10 space) that reported previously using global datasets (~ 0.34 in log10 space). This improved performance is likely due to the use of continuous absorption-based chlorophyll estimates, that are highly accurate, sample spatial scales more comparable with satellite pixels, and minimise human errors. Previous comparisons might have reported higher errors due to regional biases in datasets and methodological inconsistencies between investigators. Furthermore, our comparison showed an underestimate in satellite chlorophyll at low concentrations in 2012 (AMT22), likely due to a small bias in satellite remote-sensing reflectance data. Our results highlight the benefits of using underway spectrophotometric systems for evaluating satellite ocean-colour data and underline the importance of maintaining in situ observatories that sample the oligotrophic gyres.