Institution
Leibniz Institute of Marine Sciences
Facility•Kiel, Germany•
About: Leibniz Institute of Marine Sciences is a facility organization based out in Kiel, Germany. It is known for research contribution in the topics: Geology & Phytoplankton. The organization has 1656 authors who have published 4862 publications receiving 157829 citations.
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TL;DR: A historical review, a meta-analysis, and recommendations for users about weight–length relationships, condition factors and relative weight equations are presented, indicating a tendency towards slightly positive-allometric growth (increase in relative body thickness or plumpness) in most fishes.
Abstract: Summary This study presents a historical review, a meta-analysis, and recommendations for users about weight–length relationships, condition factors and relative weight equations. The historical review traces the developments of the respective concepts. The meta-analysis explores 3929 weight–length relationships of the type W ¼ aL b for 1773 species of fishes. It shows that 82% of the variance in a plot of log a over b can be explained by allometric versus isometric growth patterns and by different body shapes of the respective species. Across species median b ¼ 3.03 is significantly larger than 3.0, thus indicating a tendency towards slightly positive-allometric growth (increase in relative body thickness or plumpness) in most fishes. The expected range of 2.5 < b < 3.5 is confirmed. Mean estimates of b outside this range are often based on only one or two weight–length relationships per species. However, true cases of strong allometric growth do exist and three examples are given. Within species, a plot of log a vs b can be used to detect outliers in weight–length relationships. An equation to calculate mean condition factors from weight–length relationships is given as Kmean ¼ 100aL b)3 . Relative weight Wrm ¼ 100W/ (amL b m ) can be used for comparing the condition of individuals across populations, where am is the geometric mean of a and bm is the mean of b across all available weight–length relationships for a given species. Twelve recommendations for proper use and presentation of weight–length relationships, condition factors and relative weight are given.
3,227 citations
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University of Exeter1, École Normale Supérieure2, Norwich Research Park3, Wageningen University and Research Centre4, University of Groningen5, Ludwig Maximilian University of Munich6, Max Planck Society7, Commonwealth Scientific and Industrial Research Organisation8, Université Paris-Saclay9, Stanford University10, National Oceanic and Atmospheric Administration11, National Institute for Space Research12, University of Southampton13, Bermuda Institute of Ocean Sciences14, PSL Research University15, National Institute for Environmental Studies16, Japan Agency for Marine-Earth Science and Technology17, University of Maryland, College Park18, University of Leeds19, International Institute of Minnesota20, Flanders Marine Institute21, ETH Zurich22, University of East Anglia23, German Aerospace Center24, Woods Hole Research Center25, University of Illinois at Urbana–Champaign26, University of Toulouse27, Japan Meteorological Agency28, Plymouth Marine Laboratory29, University of Paris30, Hobart Corporation31, Oeschger Centre for Climate Change Research32, Tsinghua University33, National Center for Atmospheric Research34, Appalachian State University35, University of Colorado Boulder36, University of Washington37, Atlantic Oceanographic and Meteorological Laboratory38, Princeton University39, Met Office40, Leibniz Institute of Marine Sciences41, Auburn University42, University of Tasmania43, VU University Amsterdam44, Oak Ridge National Laboratory45, Sun Yat-sen University46, Nanjing University47
TL;DR: In this paper, the authors describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade 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), and ELUC 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 budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 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 was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 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 CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in 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 of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quere 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).
1,764 citations
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Atlantic Oceanographic and Meteorological Laboratory1, Earth System Research Laboratory2, Pacific Marine Environmental Laboratory3, Oregon State University4, Monterey Bay Aquarium Research Institute5, University of East Anglia6, Pierre-and-Marie-Curie University7, Hokkaido University8, National Institute for Environmental Studies9, Leibniz Institute of Marine Sciences10, University of Iceland11, Hobart Corporation12, Bjerknes Centre for Climate Research13, Fisheries and Oceans Canada14, University of Liège15
TL;DR: In this article, a global mean distribution for surface water pCO2 over the global oceans in non-El Nino conditions has been constructed with spatial resolution of 4° (latitude) × 5° (longitude) for a reference year 2000 based upon about 3 million measurements of surface water PCO2 obtained from 1970 to 2007.
Abstract: A climatological mean distribution for the surface water pCO2 over the global oceans in non-El Nino conditions has been constructed with spatial resolution of 4° (latitude) ×5° (longitude) for a reference year 2000 based upon about 3 million measurements of surface water pCO2 obtained from 1970 to 2007. The database used for this study is about 3 times larger than the 0.94 million used for our earlier paper [Takahashi et al., 2002. Global sea–air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature effects. Deep-Sea Res. II, 49, 1601–1622]. A time-trend analysis using deseasonalized surface water pCO2 data in portions of the North Atlantic, North and South Pacific and Southern Oceans (which cover about 27% of the global ocean areas) indicates that the surface water pCO2 over these oceanic areas has increased on average at a mean rate of 1.5 μatm y−1 with basin-specific rates varying between 1.2±0.5 and 2.1±0.4 μatm y−1. A global ocean database for a single reference year 2000 is assembled using this mean rate for correcting observations made in different years to the reference year. The observations made during El Nino periods in the equatorial Pacific and those made in coastal zones are excluded from the database.
Seasonal changes in the surface water pCO2 and the sea-air pCO2 difference over four climatic zones in the Atlantic, Pacific, Indian and Southern Oceans are presented. Over the Southern Ocean seasonal ice zone, the seasonality is complex. Although it cannot be thoroughly documented due to the limited extent of observations, seasonal changes in pCO2 are approximated by using the data for under-ice waters during austral winter and those for the marginal ice and ice-free zones.
The net air–sea CO2 flux is estimated using the sea–air pCO2 difference and the air–sea gas transfer rate that is parameterized as a function of (wind speed)2 with a scaling factor of 0.26. This is estimated by inverting the bomb 14C data using Ocean General Circulation models and the 1979–2005 NCEP-DOE AMIP-II Reanalysis (R-2) wind speed data. The equatorial Pacific (14°N–14°S) is the major source for atmospheric CO2, emitting about +0.48 Pg-C y−1, and the temperate oceans between 14° and 50° in the both hemispheres are the major sink zones with an uptake flux of −0.70 Pg-C y−1 for the northern and −1.05 Pg-C y−1 for the southern zone. The high-latitude North Atlantic, including the Nordic Seas and portion of the Arctic Sea, is the most intense CO2 sink area on the basis of per unit area, with a mean of −2.5 tons-C month−1 km−2. This is due to the combination of the low pCO2 in seawater and high gas exchange rates. In the ice-free zone of the Southern Ocean (50°–62°S), the mean annual flux is small (−0.06 Pg-C y−1) because of a cancellation of the summer uptake CO2 flux with the winter release of CO2 caused by deepwater upwelling. The annual mean for the contemporary net CO2 uptake flux over the global oceans is estimated to be −1.6±0.9 Pg-C y−1, which includes an undersampling correction to the direct estimate of −1.4±0.7 Pg-C y−1. Taking the pre-industrial steady-state ocean source of 0.4±0.2 Pg-C y−1 into account, the total ocean uptake flux including the anthropogenic CO2 is estimated to be −2.0±1.0 Pg-C y−1 in 2000.
1,653 citations
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National Oceanography Centre, Southampton1, Stanford University2, Bar-Ilan University3, Centre national de la recherche scientifique4, University of Tasmania5, University of Otago6, McGill University7, University of Essex8, Pierre-and-Marie-Curie University9, ETH Zurich10, University of East Anglia11, University of Exeter12, Cornell University13, University of Vigo14, University of Pennsylvania15, University of California, Irvine16, Nagoya University17, Leibniz Institute of Marine Sciences18, Woods Hole Oceanographic Institution19, University of Bergen20, University of Tokyo21, University of Concepción22
TL;DR: In this paper, the authors reveal two broad regimes of phytoplankton nutrient limitation in the modern upper ocean: Nitrogen availability tends to limit productivity throughout much of the surface low-latitude ocean, where the supply of nutrients from the subsurface is relatively slow.
Abstract: Microbial activity is a fundamental component of oceanic nutrient cycles. Photosynthetic microbes, collectively termed phytoplankton, are responsible for the vast majority of primary production in marine waters. The availability of nutrients in the upper ocean frequently limits the activity and abundance of these organisms. Experimental data have revealed two broad regimes of phytoplankton nutrient limitation in the modern upper ocean. Nitrogen availability tends to limit productivity throughout much of the surface low-latitude ocean, where the supply of nutrients from the subsurface is relatively slow. In contrast, iron often limits productivity where subsurface nutrient supply is enhanced, including within the main oceanic upwelling regions of the Southern Ocean and the eastern equatorial Pacific. Phosphorus, vitamins and micronutrients other than iron may also (co-)limit marine phytoplankton. The spatial patterns and importance of co-limitation, however, remain unclear. Variability in the stoichiometries of nutrient supply and biological demand are key determinants of oceanic nutrient limitation. Deciphering the mechanisms that underpin this variability, and the consequences for marine microbes, will be a challenge. But such knowledge will be crucial for accurately predicting the consequences of ongoing anthropogenic perturbations to oceanic nutrient biogeochemistry.
1,516 citations
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Smithsonian Environmental Research Center1, University of California, San Diego2, Leibniz Institute of Marine Sciences3, University of Liège4, Monterey Bay Aquarium Research Institute5, Lund University6, Centre national de la recherche scientifique7, Fisheries and Oceans Canada8, Cayetano Heredia University9, University of the Philippines Diliman10, State University of New York College of Environmental Science and Forestry11, Kuwait Institute for Scientific Research12, University of Cape Town13, Department of Agriculture, Forestry and Fisheries14, Louisiana State University15, University of Maryland Center for Environmental Science16, University of South Florida St. Petersburg17, Polish Academy of Sciences18, University of Hong Kong19, East China Normal University20
TL;DR: Improved numerical models of oceanographic processes that control oxygen depletion and the large-scale influence of altered biogeochemical cycles are needed to better predict the magnitude and spatial patterns of deoxygenation in the open ocean, as well as feedbacks to climate.
Abstract: BACKGROUND Oxygen concentrations in both the open ocean and coastal waters have been declining since at least the middle of the 20th century. This oxygen loss, or deoxygenation, is one of the most important changes occurring in an ocean increasingly modified by human activities that have raised temperatures, CO 2 levels, and nutrient inputs and have altered the abundances and distributions of marine species. Oxygen is fundamental to biological and biogeochemical processes in the ocean. Its decline can cause major changes in ocean productivity, biodiversity, and biogeochemical cycles. Analyses of direct measurements at sites around the world indicate that oxygen-minimum zones in the open ocean have expanded by several million square kilometers and that hundreds of coastal sites now have oxygen concentrations low enough to limit the distribution and abundance of animal populations and alter the cycling of important nutrients. ADVANCES In the open ocean, global warming, which is primarily caused by increased greenhouse gas emissions, is considered the primary cause of ongoing deoxygenation. Numerical models project further oxygen declines during the 21st century, even with ambitious emission reductions. Rising global temperatures decrease oxygen solubility in water, increase the rate of oxygen consumption via respiration, and are predicted to reduce the introduction of oxygen from the atmosphere and surface waters into the ocean interior by increasing stratification and weakening ocean overturning circulation. In estuaries and other coastal systems strongly influenced by their watershed, oxygen declines have been caused by increased loadings of nutrients (nitrogen and phosphorus) and organic matter, primarily from agriculture; sewage; and the combustion of fossil fuels. In many regions, further increases in nitrogen discharges to coastal waters are projected as human populations and agricultural production rise. Climate change exacerbates oxygen decline in coastal systems through similar mechanisms as those in the open ocean, as well as by increasing nutrient delivery from watersheds that will experience increased precipitation. Expansion of low-oxygen zones can increase production of N 2 O, a potent greenhouse gas; reduce eukaryote biodiversity; alter the structure of food webs; and negatively affect food security and livelihoods. Both acidification and increasing temperature are mechanistically linked with the process of deoxygenation and combine with low-oxygen conditions to affect biogeochemical, physiological, and ecological processes. However, an important paradox to consider in predicting large-scale effects of future deoxygenation is that high levels of productivity in nutrient-enriched coastal systems and upwelling areas associated with oxygen-minimum zones also support some of the world’s most prolific fisheries. OUTLOOK Major advances have been made toward understanding patterns, drivers, and consequences of ocean deoxygenation, but there is a need to improve predictions at large spatial and temporal scales important to ecosystem services provided by the ocean. Improved numerical models of oceanographic processes that control oxygen depletion and the large-scale influence of altered biogeochemical cycles are needed to better predict the magnitude and spatial patterns of deoxygenation in the open ocean, as well as feedbacks to climate. Developing and verifying the next generation of these models will require increased in situ observations and improved mechanistic understanding on a variety of scales. Models useful for managing nutrient loads can simulate oxygen loss in coastal waters with some skill, but their ability to project future oxygen loss is often hampered by insufficient data and climate model projections on drivers at appropriate temporal and spatial scales. Predicting deoxygenation-induced changes in ecosystem services and human welfare requires scaling effects that are measured on individual organisms to populations, food webs, and fisheries stocks; considering combined effects of deoxygenation and other ocean stressors; and placing an increased research emphasis on developing nations. Reducing the impacts of other stressors may provide some protection to species negatively affected by low-oxygen conditions. Ultimately, though, limiting deoxygenation and its negative effects will necessitate a substantial global decrease in greenhouse gas emissions, as well as reductions in nutrient discharges to coastal waters.
1,469 citations
Authors
Showing all 1757 results
Name | H-index | Papers | Citations |
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Ulf Riebesell | 89 | 333 | 25958 |
Mojib Latif | 81 | 322 | 27236 |
Helmut Hillebrand | 75 | 225 | 26232 |
Andreas Kappler | 68 | 350 | 17497 |
Thorsten B. H. Reusch | 66 | 235 | 13647 |
Ute Hentschel | 65 | 219 | 16351 |
Ulrich Sommer | 65 | 263 | 16103 |
John P. Dunne | 64 | 189 | 17987 |
Martin Frank | 64 | 272 | 14772 |
Eric P. Achterberg | 63 | 326 | 12631 |
Kaj Hoernle | 62 | 264 | 11334 |
Erwin Suess | 60 | 138 | 12039 |
Anton Eisenhauer | 59 | 236 | 10277 |
Andreas Oschlies | 58 | 277 | 14855 |
Martin Visbeck | 58 | 159 | 17822 |