A multicomponent model of phytoplankton size structure

Size-fractionated filtration (SFF) is a direct method for estimating pigment concentration in various size classes. It is also common practice to infer the size structure of phytoplankton communities from diagnostic pigments estimated by high-performance liquid chromatography (HPLC). In this paper, the three-component model of Brewin et al. (2010) was fitted to coincident data from HPLC and from SFF collected along Atlantic Meridional Transect cruises. The model accounted for the variability in each data set, but the fitted model parameters differed for the two data sets. Both HPLC and SFF data supported the conceptual framework of the three-component model, which assumes that the chlorophyll concentration in small cells increases to an asymptotic maximum, beyond which further increase in chlorophyll is achieved by the addition of larger celled phytoplankton. The three-component model was extended to a multicomponent model of size structure using observed relationships between model parameters and assuming that the asymptotic concentration that can be reached by cells increased linearly with increase in the upper bound on the cell size. The multicomponent model was verified using independent SFF data for a variety of size fractions and found to perform well (0.628 ≤ r ≤ 0.989) lending support for the underlying assumptions. An advantage of the multicomponent model over the three-component model is that, for the same number of parameters, it can be applied to any size range in a continuous fashion. The multicomponent model provides a useful tool for studying the distribution of phytoplankton size structure at large scales.

Global carbon budget 2014

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (E-FF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004-2013), E-FF was 8.9 +/- 0.4 GtC yr(-1), E-LUC 0.9 +/- 0.5 GtC yr(-1), G(ATM) 4.3 +/- 0.1 GtC yr(-1), S-OCEAN 2.6 +/- 0.5 GtC yr(-1), and S-LAND 2.9 +/- 0.8 GtC yr(-1). For year 2013 alone, E-FF grew to 9.9 +/- 0.5 GtC yr(-1), 2.3% above 2012, continuing the growth trend in these emissions, E-LUC was 0.9 +/- 0.5 GtC yr(-1), G(ATM) was 5.4 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 2.5 +/- 0.9 GtC yr(-1). G(ATM) was high in 2013, reflecting a steady increase in E-FF and smaller and opposite changes between S-OCEAN and S-LAND compared to the past decade (2004-2013). The global atmospheric CO2 concentration reached 395.31 +/- 0.10 ppm averaged over 2013. We estimate that E-FF will increase by 2.5% (1.3-3.5 %) to 10.1 +/- 0.6 GtC in 2014 (37.0 +/- 2.2 GtCO(2) yr(-1)), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of E-FF and assumed constant E-LUC for 2014, cumulative emissions of CO2 will reach about 545 +/- 55 GtC (2000 +/- 200 GtCO(2)) for 1870-2014, about 75% from E-FF and 25% from E-LUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quere et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

The importance of independent marine evidence provision in a multi-use environment: MBA information resources and The Marine Life Information Network.

One of the most pressing challenges today is the need to manage our oceans on a sustainable basis, balancing opportunities for exploitation with the need for conservation and protection. A vital tool for informing sustainable management is access to accurate, up-to-date marine environmental data and information, which is also seen as ‘independent’ by industry, conservationists, policy-makers and other Stakeholders. The Marine Biological Association has specialised in providing independent evidence for over a century and hosts a number of programmes dedicated to independent evidence provision. For example, the Marine Life Information Network (MarLIN) is the most comprehensive information resource for the marine environment of the British Isles and also the largest review of the effects of human activities and natural events on marine species and habitats ever undertaken. MarLIN, along with the Data Archive for Seabed Species and Habitats (DASSH and other MBA information resources, is currently being used to support a wide range of UK and European legislation as well as providing vital underpinning information for industry (e.g. through informing EIAs). We provide an overview of MarLIN in particular whilst examining the importance of ‘independent’ scientific information in a multi-use environment.

Global Carbon Budget 2015

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).

Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets

Assigning uncertainty to ocean-color satellite products is a requirement to allow informed use of these data. Here, uncertainty estimates are derived using the comparison on a 12th-degree grid of coincident daily records of the remote-sensing reflectance RRS obtained with the same processing chain from three satellite missions, MERIS, MODIS and SeaWiFS. The approach is spatially resolved and produces σ, the part of the RRS uncertainty budget associated with random effects. The global average of σ decreases with wavelength from approximately 0.7– 0.9 10−3 sr−1 at 412 nm to 0.05–0.1 10−3 sr−1 at the red band, with uncertainties on σ evaluated as 20–30% between 412 and 555 nm, and 30–40% at 670 nm. The distribution of σ shows a restricted spatial variability and small variations with season, which makes the multi-annual global distribution of σ an estimate applicable to all retrievals of the considered missions. The comparison of σ with other uncertainty estimates derived from field data or with the support of algorithms provides a consistent picture. When translated in relative terms, and assuming a relatively low bias, the distribution of σ suggests that the objective of a 5% uncertainty is fulfilled between 412 and 490 nm for oligotrophic waters (chlorophyll-a concentration below 0.1 mg m−3). This study also provides comparison statistics. Spectrally, the mean absolute relative difference between RRS from different missions shows a characteristic U-shape with both ends at blue and red wavelengths inversely related to the amplitude of RRS. On average and for the considered data sets, SeaWiFS RRS tend to be slightly higher than MODIS RRS, which in turn appear higher than MERIS RRS. Biases between mission-specific RRS may exhibit a seasonal dependence, particularly in the subtropical belt.

Relationships between biodiversity and the stability of marine ecosystems: comparisons at a European scale using meta-analysis.

The relationship between biodiversity and stability of marine benthic assemblages was investigated using existing data sets (n = 28) covering various spatial (m-km) and temporal (1973-2006) scales in different benthic habitats (emergent rock, rock pools and sedimentary habitats) through meta-analyses. Assemblage stability was estimated by measuring temporal variances of species richness, total abundance (density or % cover) and community species composition and abundance structure (using multivariate analyses). Positive relationships between temporal variability in species number and richness were generally observed at both quadrat (<1 m2) and site (100 m2) scales, while no relationships were observed by multivariate analyses. Positive relationships were also observed at the scale of site between temporal variability in species number and variability in community structure with evenness estimates. This implies that the relationship between species richness or evenness and species richness variability is slightly positive and depends on the scale of observation, suggesting that biodiversity per se is important for the stability of ecosystems. Changes within community assemblages in terms of structure are, however, generally independent of biodiversity, suggesting no effect of diversity, but the potential impact of individual species, and/or environmental factors. Except for sedimentary and rock pool habitats, no relationship was observed between temporal variation of the aggregated variable of total abundances and diversity at either scale. Overall our results emphasise that relationships depend on scale of measurements, type of habitats and the marine systems (North Atlantic and Mediterranean) considered.