Plymouth Marine Laboratory

Abstract In the early 1980s, a strategy for graphical representation of multivariate (multi‐species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instructive to: (i) identify which elements of this often‐quoted strategy have proved most useful in practical assessment of community change resulting from pollution impact; and (ii) ask to what extent evolution of techniques in the intervening years has added self‐consistency and comprehensiveness to the approach. The pivotal concept has proved to be that of a biologically‐relevant definition of similarity of two samples, and its utilization mainly in simple rank form, for example ‘sample A is more similar to sample B than it is to sample C’. Statistical assumptions about the data are thus minimized and the resulting non‐parametric techniques will be of very general applicability. From such a starting point, a unified framework needs to encompass: (i) the display of community patterns through clustering and ordination of samples; (ii) identification of species principally responsible for determining sample groupings; (iii) statistical tests for differences in space and time (multivariate analogues of analysis of variance, based on rank similarities); and (iv) the linking of community differences to patterns in the physical and chemical environment (the latter also dictated by rank similarities between samples). Techniques are described that bring such a framework into place, and areas in which problems remain are identified. Accumulated practical experience with these methods is discussed, in particular applications to marine benthos, and it is concluded that they have much to offer practitioners of environmental impact studies on communities.

Recently developed techniques for estimating bacterial biomass and productivity indicate that bacterial biomass in the sea is related to phytoplankton concentration and that bacteria utilise 10 to 50 % of carbon fixed by photosynthesis. Evidence is presented to suggest that numbers of free bacteria are controlled by nanoplankton~c heterotrophic flagellates which are ubiquitous in the marine water column. The flagellates in turn are preyed upon by microzooplankton. Heterotrophic flagellates and microzooplankton cover the same size range as the phytoplankton, thus providing the means for returning some energy from the 'microbial loop' to the conventional planktonic food chain.

Human-dominated marine ecosystems are experiencing accelerating loss of populations and species, with largely unknown consequences. We analyzed local experiments, long-term regional time series, and global fisheries data to test how biodiversity loss affects marine ecosystem services across temporal and spatial scales. Overall, rates of resource collapse increased and recovery potential, stability, and water quality decreased exponentially with declining diversity. Restoration of biodiversity, in contrast, increased productivity fourfold and decreased variability by 21%, on average. We conclude that marine biodiversity loss is increasingly impairing the ocean's capacity to provide food, maintain water quality, and recover from perturbations. Yet available data suggest that at this point, these trends are still reversible.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Small plastic detritus, termed "microplastics", are a widespread and ubiquitous contaminant of marine ecosystems across the globe. Ingestion of microplastics by marine biota, including mussels, worms, fish, and seabirds, has been widely reported, but despite their vital ecological role in marine food-webs, the impact of microplastics on zooplankton remains under-researched. Here, we show that microplastics are ingested by, and may impact upon, zooplankton. We used bioimaging techniques to document ingestion, egestion, and adherence of microplastics in a range of zooplankton common to the northeast Atlantic, and employed feeding rate studies to determine the impact of plastic detritus on algal ingestion rates in copepods. Using fluorescence and coherent anti-Stokes Raman scattering (CARS) microscopy we identified that thirteen zooplankton taxa had the capacity to ingest 1.7-30.6 μm polystyrene beads, with uptake varying by taxa, life-stage and bead-size. Post-ingestion, copepods egested faecal pellets laden with microplastics. We further observed microplastics adhered to the external carapace and appendages of exposed zooplankton. Exposure of the copepod Centropages typicus to natural assemblages of algae with and without microplastics showed that 7.3 μm microplastics (>4000 mL(-1)) significantly decreased algal feeding. Our findings imply that marine microplastic debris can negatively impact upon zooplankton function and health.

The accumulation of plastic litter in natural environments is a global issue. Concerns over potential negative impacts on the economy, wildlife, and human health provide strong incentives for improving the sustainable use of plastics. Despite the many voices raised on the issue, we lack a consensus on how to define and categorize plastic debris. This is evident for microplastics, where inconsistent size classes are used and where the materials to be included are under debate. While this is inherent in an emerging research field, an ambiguous terminology results in confusion and miscommunication that may compromise progress in research and mitigation measures. Therefore, we need to be explicit on what exactly we consider plastic debris. Thus, we critically discuss the advantages and disadvantages of a unified terminology, propose a definition and categorization framework, and highlight areas of uncertainty. Going beyond size classes, our framework includes physicochemical properties (polymer composition, solid state, solubility) as defining criteria and size, shape, color, and origin as classifiers for categorization. Acknowledging the rapid evolution of our knowledge on plastic pollution, our framework will promote consensus building within the scientific and regulatory community based on a solid scientific foundation.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions andtheir redistribution among the atmosphere, ocean, and terrestrial biospherein a changing climate – the “global carbon budget” – is important tobetter understand the global carbon cycle, support the development ofclimate policies, and project future climate change. Here we describe andsynthesize data sets and methodology to quantify the five major componentsof the global carbon budget and their uncertainties. Fossil CO2emissions (EFOS) are based on energy statistics and cement productiondata, while emissions from land-use change (ELUC), mainlydeforestation, are based on land use and land-use change data andbookkeeping models. Atmospheric CO2 concentration is measured directlyand its growth rate (GATM) is computed from the annual changes inconcentration. The ocean CO2 sink (SOCEAN) and terrestrialCO2 sink (SLAND) are estimated with global process modelsconstrained by observations. The resulting carbon budget imbalance(BIM), the difference between the estimated total emissions and theestimated changes in the atmosphere, ocean, and terrestrial biosphere, is ameasure of imperfect data and understanding of the contemporary carboncycle. All uncertainties are reported as ±1σ. For the lastdecade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), andELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ± 0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budgetimbalance BIM of −0.1 GtC yr−1 indicating a near balance betweenestimated sources and sinks over the last decade. For the year 2019 alone, thegrowth in EFOS was only about 0.1 % with fossil emissions increasingto 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEANwas 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminarydata for 2020, accounting for the COVID-19-induced changes in emissions,suggest a decrease in EFOS relative to 2019 of about −7 % (medianestimate) based on individual estimates from four studies of −6 %, −7 %,−7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in thecomponents of the global carbon budget are consistently estimated over theperiod 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for therepresentation of semi-decadal variability in CO2 fluxes. Comparison ofestimates from diverse approaches and observations shows (1) no consensusin the mean and trend in land-use change emissions over the last decade, (2)a persistent low agreement between the different methods on the magnitude ofthe land CO2 flux in the northern extra-tropics, and (3) an apparentdiscrepancy between the different methods for the ocean sink outside thetropics, particularly in the Southern Ocean. This living data updatedocuments changes in the methods and data sets used in this new globalcarbon budget and the progress in understanding of the global carbon cyclecompared with previous publications of this data set (Friedlingstein et al.,2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014,2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

The method of choice for multivariate representation of community structure is often non-metric multi-dimensional scaling (MDS). This has great flexibility in accomn~odating biologically relevant (i.e. non correlation-based) definitions of similarity In species composition of 2 samples, and in preserving the rank-order relations amongst those similarities in the placing of samples in an ordination. Correlation-based techniques (such as Canonical Correlation) are then inappropriate in linking the observed biotic structure to measured environmental variables; a more natural approach is simply to compare separate sample ordinations from biotic and abiotic variables and choose that subset of environmental variables which provides a good match between the 2 configurations. In fact, the fundamental constructs here are not the ordination plots but the (rank) similarity matrices which underlie them: a suitable measure of agreement between 2 such matrices is therefore proposed and used to define an optimal subset of environmental variables w h ~c h 'best explains' the biotic structure. This simple technique is illustrated wlth 3 data sets, from studles of macrobenthic, meiobenthic and diatom communities in estuarine and coastal waters.

Plastics debris is accumulating in the environment and is fragmenting into smaller pieces; as it does, the potential for ingestion by animals increases. The consequences of macroplastic debris for wildlife are well documented, however the impacts of microplastic (< 1 mm) are poorly understood. The mussel, Mytilus edulis, was used to investigate ingestion, translocation, and accumulation of this debris. Initial experiments showed that upon ingestion, microplastic accumulated in the gut. Mussels were subsequently exposed to treatments containing seawater and microplastic (3.0 or 9.6 microm). After transfer to clean conditions, microplastic was tracked in the hemolymph. Particles translocated from the gut to the circulatory system within 3 days and persisted for over 48 days. Abundance of microplastic was greatest after 12 days and declined thereafter. Smaller particles were more abundant than larger particles and our data indicate as plastic fragments into smaller particles, the potential for accumulation in the tissues of an organism increases. The short-term pulse exposure used here did not result in significant biological effects. However, plastics are exceedingly durable and so further work using a wider range of organisms, polymers, and periods of exposure will be required to establish the biological consequences of this debris.

A strategy is presented for analysing marine biological survey data and relating the biotic patterns to environmental data. To avoid circular argument, biotic and environmental data are kept separate. The strategy is illustrated by a worked example using data on the distribution of 182 nematode species in 107 samples in the River Exe estuary. Nineteen stations are grouped Into 4 main clusters using complementary classification and multi-dimensional scaling (MDS) ordination techniques. These are both based on root-root transformed abundance data with the Bray-Curtis measure of similarity. Indicator species characterising each group are extracted using information statistics. Inverse analyses give clusters of CO-occurnng species which are strongly related to the station groups. Relationships of station groups to environmental variables are revealed by superimposing data for one variable a t a time on the MDS plot, showing that some station groups differ in sediment granulometry and others in salinity, for example. Some of the other factors plotted show no difference between station groups. Similarly, physiognomic charactcrlstics of the species are superimposed on the MDS plots of the inverse analysis of species groups, revealing differences in setal length and trophic status between the species groups. Finally, the 4 major station groups and species groups are related to one another in terms of morphological adaptation to the habitat.

Abstract We document the development of the first version of the U.K. Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre‐industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC −1 .

The ocean moderates anthropogenic climate change at the cost of profound alterations of its physics, chemistry, ecology, and services. Here, we evaluate and compare the risks of impacts on marine and coastal ecosystems—and the goods and services they provide—for growing cumulative carbon emissions under two contrasting emissions scenarios. The current emissions trajectory would rapidly and significantly alter many ecosystems and the associated services on which humans heavily depend. A reduced emissions scenario—consistent with the Copenhagen Accord's goal of a global temperature increase of less than 2°C—is much more favorable to the ocean but still substantially alters important marine ecosystems and associated goods and services. The management options to address ocean impacts narrow as the ocean warms and acidifies. Consequently, any new climate regime that fails to minimize ocean impacts would be incomplete and inadequate.

Microscopic plastic debris, termed “microplastics”, are of increasing environmental concern. Recent studies have demonstrated that a range of zooplankton, including copepods, can ingest microplastics. Copepods are a globally abundant class of zooplankton that form a key trophic link between primary producers and higher trophic marine organisms. Here we demonstrate that ingestion of microplastics can significantly alter the feeding capacity of the pelagic copepod Calanus helgolandicus. Exposed to 20 μm polystyrene beads (75 microplastics mL(–1)) and cultured algae ([250 μg C L(–1)) for 24 h, C. helgolandicus ingested 11% fewer algal cells (P = 0.33) and 40% less carbon biomass (P < 0.01). There was a net downward shift in the mean size of algal prey consumed (P < 0.001), with a 3.6 fold increase in ingestion rate for the smallest size class of algal prey (11.6–12.6 μm), suggestive of postcapture or postingestion rejection. Prolonged exposure to polystyrene microplastics significantly decreased reproductive output, but there were no significant differences in egg production rates, respiration or survival. We constructed a conceptual energetic (carbon) budget showing that microplastic-exposed copepods suffer energetic depletion over time. We conclude that microplastics impede feeding in copepods, which over time could lead to sustained reductions in ingested carbon biomass.

An accurate, dependable determination of 0–60 μg-at./l. of NO − 3 -N in sea water has been developed. The sample is treated with tetrasodium ethylenediaminetetraacetate solution and passed through a column of copperized cadmium filings. A nearly quantitative reduction of nitrate to nitrite results. Nitrite is then determined by a diazotization method. Neither sulphide nor high nitrite concentrations interferes. Approximately eight samples per hour per column can be analysed with a standard deviation of 0.12 μg-at./l. at the 20 μg-at./l. level. Introduction Accurate determinations of nitrate ions in sea water have been difficult, especially under shipboard conditions. The colorimetric method described by Harvey (1926, 1930) and improved by Cooper (1932), Zwicker &amp; Robinson (1944), and others uses strychnidine in concentrated sulphuric acid to produce a red colour. The reagent lacks reliable sensitivity, because it is dependent on the rates of mixing and cooling. In a method by Armstrong (1963), the absorbance of nitrosyl chloride in the UV region is measured with a spectrophotometer. While the method is good for small samples containing high concentrations of nitrate, the use of concentrated sulphuric acid and lack of sensitivity limit its use in routine analysis. A method in which nitrate is quantitatively reduced to nitrite would be advantageous, because nitrite can be readily determined by the sensitive diazotization method proposed by Griess (1879). Several such methods have been proposed. FØyn (1951), Vatova (1956), and Chow &amp; Johnstone (1962) used zinc powder for the reduction, but the reduction is sensitive to temperature, and it is necessary to centrifuge or filter each sample.

Summary For biological community data (species‐by‐sample abundance matrices), Warwick &amp; Clarke (1995) defined two biodiversity indices, capturing the structure not only of the distribution of abundances amongst species but also the taxonomic relatedness of the species in each sample. The first index, taxonomic diversity (δ), can be thought of as the average taxonomic ‘distance’ between any two organisms, chosen at random from the sample: this distance can be visualized simply as the length of the path connecting these two organisms, traced through (say) a Linnean or phylogenetic classification of the full set of species involved. The second index, taxonomic distinctness (δ * ), is the average path length between any two randomly chosen individuals, conditional on them being from different species. This is equivalent to dividing taxonomic diversity, δ, by the value it would take were there to be no taxonomic hierarchy (all species belonging to the same genus). δ * can therefore be seen as a measure of pure taxonomic relatedness, whereas δ mixes taxonomic relatedness with the evenness properties of the abundance distribution. This paper explores the statistical sampling properties of δ and δ * . Taxonomic diversity is seen to be a natural extension of a form of Simpson's index, incorporating taxonomic (or phylogenetic) information. Importantly for practical comparisons, both δ and δ * are shown not to be dependent, on average, on the degree of sampling effort involved in the data collection; this is in sharp contrast with those diversity measures that are strongly influenced by the number of observed species. The special case where the data consist only of presence/absence information is dealt with in detail: δ and δ * converge to the same statistic (δ + ), which is now defined as the average taxonomic path length between any two randomly chosen species. Its lack of dependence, in mean value, on sampling effort implies that δ + can be compared across studies with differing and uncontrolled degrees of sampling effort (subject to assumptions concerning comparable taxonomic accuracy). This may be of particular significance for historic (diffusely collected) species lists from different localities or regions, which at first sight may seem unamenable to valid diversity comparison of any sort. Furthermore, a randomization test is possible, to detect a difference in the taxonomic distinctness, for any observed set of species, from the ‘expected’δ + value derived from a master species list for the relevant group of organisms. The exact randomization procedure requires heavy computation, and an approximation is developed, by deriving an appropriate variance formula. This leads to a ‘confidence funnel’ against which distinctness values for any specific area, pollution condition, habitat type, etc., can be checked, and formally addresses the question of whether a putatively impacted locality has a ‘lower than expected’ taxonomic spread. The procedure is illustrated for the UK species list of free‐living marine nematodes and sets of samples from intertidal sites in two localities, the Exe estuary and the Firth of Clyde.

Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes [1]. In practice, this means sequence databases need to be populated with enormous quantities of data for which we have some certainties about the source. Most important is the taxonomic identity of the organism from which a sequence is derived and as much functional identification of the encoded proteins as possible. In an ideal world, such information would be available as a large set of complete, well-curated, and annotated genomes for all the major organisms from the environment in question. Reality substantially diverges from this ideal, but at least for bacterial molecular ecology, there is a database consisting of thousands of complete genomes from a wide range of taxa, supplemented by a phylogeny-driven approach to diversifying genomics [2]. For eukaryotes, the number of available genomes is far, far fewer, and we have relied much more heavily on random growth of sequence databases [3],[4], raising the question as to whether this is fit for purpose.

Abstract When sea ice forms it scavenges and concentrates particulates from the water column, which then become trapped until the ice melts. In recent years, melting has led to record lows in Arctic Sea ice extent, the most recent in September 2012. Global climate models, such as that of Gregory et al. (2002), suggest that the decline in Arctic Sea ice volume (3.4% per decade) will actually exceed the decline in sea ice extent, something that Laxon et al. (2013) have shown supported by satellite data. The extent to which melting ice could release anthropogenic particulates back to the open ocean has not yet been examined. Here we show that Arctic Sea ice from remote locations contains concentrations of microplastics are several orders of magnitude greater than those that have been previously reported in highly contaminated surface waters, such as those of the Pacific Gyre. Our findings indicate that microplastics have accumulated far from population centers and that polar sea ice represents a major historic global sink of man‐made particulates. The potential for substantial quantities of legacy microplastic contamination to be released to the ocean as the ice melts therefore needs to be evaluated, as do the physical and toxicological effects of plastics on marine life.

Here we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site off Plymouth, UK. Data treatment effected the estimation of community richness over a 6-year period, whereby 8794 operational taxonomic units (OTUs) were identified using single-linkage preclustering and 21 130 OTUs were identified by denoising the data. The Alphaproteobacteria were the most abundant Class, and the most frequently recorded OTUs were members of the Rickettsiales (SAR 11) and Rhodobacteriales. This near-surface ocean bacterial community showed strong repeatable seasonal patterns, which were defined by winter peaks in diversity across all years. Environmental variables explained far more variation in seasonally predictable bacteria than did data on protists or metazoan biomass. Change in day length alone explains >65% of the variance in community diversity. The results suggested that seasonal changes in environmental variables are more important than trophic interactions. Interestingly, microbial association network analysis showed that correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or between bacteria and environmental variables.

Microplastic litter is a pervasive pollutant present in aquatic systems across the globe. A range of marine organisms have the capacity to ingest microplastics, resulting in adverse health effects. Developing methods to accurately quantify microplastics in productive marine waters, and those internalized by marine organisms, is of growing importance. Here we investigate the efficacy of using acid, alkaline and enzymatic digestion techniques in mineralizing biological material from marine surface trawls to reveal any microplastics present. Our optimized enzymatic protocol can digest >97% (by weight) of the material present in plankton-rich seawater samples without destroying any microplastic debris present. In applying the method to replicate marine samples from the western English Channel, we identified 0.27 microplastics m(-3). The protocol was further used to extract microplastics ingested by marine zooplankton under laboratory conditions. Our findings illustrate that enzymatic digestion can aid the detection of microplastic debris within seawater samples and marine biota.