On Anti-Nuclear Bullshit

https://thebreakthrough.org/issues/energy/on-anti-nuclear-bullshit 

Feb 10, 2021

In his widely read essay, “On Bullshit,” the philosopher Harry Frankfurt famously distinguished between liars and bullshitters. Liars, counterintuitively, Frankfurt argued, actually care about the truth, and hence attempt to conceal or distort it. Bullshit, by contrast, serves a social function, not an epistemic one.

I was reminded of Frankfurt’s distinction recently, with the publication of a new paper by Harrison Fell, Alex Gilbert, Jesse Jenkins, and Matteo Mildenberger reanalyzing data from a study published last fall in Nature Energy by Benjamin Sovacool and colleagues at the University of Sussex Energy Group.

Sovacool and his coauthors claimed to demonstrate that deployment of nuclear energy around the world did not reduce carbon emissions. The reanalysis by Fell, et. al. is devastating, showing Sovacool’s data actually shows the opposite. From the abstract: “employing the same data sources and time periods, we find that nuclear power and renewable energy are both associated with lower per capita CO2 emissions with effects of similar magnitude and statistical significance.”

Of course, you don’t really need a complicated regression analysis to figure this out. France and Sweden boast the lowest per capita emissions among major advanced developed economies globally and get 80% and 50% of their electricity, respectively, from nuclear energy. When nations build nuclear plants, emissions reliably fall and when they shut them down, as we’ve witnessed over the last decade in Japan and California, they reliably rise.

But for decades, Sovacool and other prominent anti-nuclear academics have published a slew of dubious studies in peer-reviewed publications purporting to find that closing nuclear plants reduces emissions, that nuclear energy is fossil fuel intensive, uniquely dangerous, and inherently expensive, and that renewable energy alone can meet 100% of the world’s energy needs.

This is the sort of thing that many people would call bullshit. But in Frankfurt’s parlance, ideological academics like Sovacool are actually liars. By that, I am not suggesting that Sovacool and others are literally lying. Nor does any of it rise to the level of academic fraud.

But the history of anti-nuclear scholarship pretty strongly suggests that peer-review is no defense in the face of tenured academics with strong ideological commitments. Motivated cognition is a powerful thing and faced with an inconvenient truth, that nuclear energy, which environmentalists have long viewed as worse than fossil fuels, is actually one of the better options we have for cutting carbon emissions and addressing climate change, researchers like Sovacool are entirely capable of conjuring scholarly falsehoods via the magic of models, regression analyses, and highly selective data.

Bullshit, by contrast, is a different animal. It involves going along to get along, repeating claims that are prima facie ridiculous because everyone else appears to believe them too. If Sovacool and other anti-nuclear academics are liars in Frankfurt’s parlance, the peer reviewers and editors who went along with publishing the whole absurd exercise are bullshitters.

Sure, peer-review is time-consuming and uncompensated. But that can’t remotely explain how Sovacool was able to take a study that he was forced to retract just three years ago, slap a fresh coat of paint on it, and republish it in a more prestigious journal. Or why Mark Jacobson’s now-debunked 100% renewable study was not only published by the Proceedings of the National Academy of Science but received an award as one of the best studies of the year, before its obvious flaws were exposed. Or, for that matter, why decades of coverage of nuclear energy in the mainstream media has so reliably diverged from the overwhelming evidence about nuclear’s remarkable record of safe operations and low emissions.

The actual technological pathways to deeply decarbonizing the entire global economy are few and far between. Nuclear is without question one of them.

Climate and energy bullshit proliferates not based on the strength of empirical claims upon which it is based but because it fits a social narrative that has been around for a very long time and that was mapped over, almost whole cloth, from earlier environmental claims about population, toxic chemicals, and limits to growth.

At bottom, almost all contemporary framings of the climate issue insist that addressing the problem will require a fundamental break from the past. Our actions, our choices, our determination to fundamentally remake the world, right now, shall determine whether we thrive or burn up in a runaway fossil-fueled cataclysm.

And so, in the popular climate discourse, we imagine more marching and protesting and clever climate communications might radically remake the political economy of carbon and energy on a planet with seven billion people, soon to be nine, that is still overwhelmingly dependent on fossil fuels. We argue that political will is all that stands in the way of an international treaty, a global carbon price, or a Green New Deal and that once the political breakthrough materializes, those measures will magically produce some unnamed and unobjectionable technology to do everything that wind and solar energy can’t.

Nuclear energy’s original sin was that it was plug and play with industrial modernity, promising limitless energy to support economic prosperity and a growing population. Even as most today acknowledge that any serious effort to address climate change will need to accommodate both, the popular climate discourse speaks of carbon budgets and temperature targets as if they were real things while barely mentioning nuclear, a real technology with documented success decarbonizing modern economies, because it doesn’t fit the narrative.

When nations build nuclear plants, emissions reliably fall and when they shut them down, as we’ve witnessed over the last decade in Japan and California, they reliably rise.

Instead, we talk of technologies that have never actually existed: gigantic machines that remove carbon directly from the atmosphere or hydrogen-powered aircraft or pumping sulfur particles into the stratosphere. The environmental movement and philanthropy have even been far more open to bolting costly carbon capture technology onto coal and gas plants than reconsidering nuclear energy, probably because the former is a pollution-control technology that would increase the cost of fossil energy and, not incidentally, is probably only feasible in the event that the world either regulates or taxes carbon dioxide.

Nuclear energy is no panacea either. And perhaps we will figure out how to entirely eliminate emissions with carbon capture or clean hydrogen or something else. But the actual technological pathways to deeply decarbonizing the entire global economy are few and far between. Nuclear is without question one of them. It can do things, like providing heat for industrial processes that renewables simply cannot easily, and is still the only low-carbon technology with a demonstrated track record of significantly decarbonizing a modern, industrialized economy.

As impressive as the falling costs of wind and solar energy have been, we aren’t going to power the entire global economy with variable sources of renewable energy alone. We have no experience or proven capability to operate an electrical grid entirely with wind and solar energy, much less the other 80% of the global energy economy that doesn’t run on electricity.

Most serious observers, in the news media, academia, government, and even environmental NGOs actually know this and most credible global decarbonization scenarios and energy systems models find a significant need for nuclear to deeply decarbonize modern economies. But you wouldn’t know that from our zombie climate discourse.

Successful climate action in the actual world won’t look anything like the heroic fantasias that so easily captivate the chattering classes. More likely, insofar as we succeed, we will do so via a series of partial, stumbling, and half-baked measures. Doing so will require things like nuclear energy, natural gas, carbon capture, and big agriculture that don’t, in the popular imagination, sit weightless on the land. It will require big government, big corporations and big infrastructure. It will accommodate itself to industrial modernity, consumption, and consumerism and will require a revolution in neither sentiment nor technology but rather the slow accumulation of knowledge, technological prowess, institutions, and practices.

In the end, everyone knows what Sovacool, Jacobson, and other anti-nuclear academics are up to. They are simply highly credentialed ideologues. It’s the bullshit that I worry more about, because, in its incoherence, overheated conspiracies, breezy utopias, and empty radicalism, it is far harder to interrogate

 

Open science

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Open_science 

One definition of Open science holds that it is the movement to make scientific research (including publications, data, physical samples, and software) and its dissemination accessible to all levels of an inquiring society, amateur or professional. Open science is transparent and accessible knowledge that is shared and developed through collaborative networks. It encompasses practices such as publishing open research, campaigning for open access, encouraging scientists to practice open-notebook science, and generally making it easier to publish and communicate scientific knowledge.

Usage of the term Open science varies substantially across disciplines, with a notable prevalence in the STEM disciplines. Open research is often used quasi-synonymously to address the gap that the denotion of "science" might have regarding an inclusion of the Arts, Humanities and Social Sciences. The primary focus connecting all disciplines is the widespread uptake of new technologies and tools, and the underlying ecology of the production, dissemination and reception of knowledge from a research-based point-of-view.

As Tennant et al. (2020) note, the term Open science "implicitly seems only to regard ‘scientific’ disciplines, whereas Open Scholarship can be considered to include research from the Arts and Humanities (Eve 2014; Knöchelmann 2019), as well as the different roles and practices that researchers perform as educators and communicators, and an underlying open philosophy of sharing knowledge beyond research communities."

Open Science can be seen as a continuation of, rather than a revolution in, practices begun in the 17th century with the advent of the academic journal, when the societal demand for access to scientific knowledge reached a point at which it became necessary for groups of scientists to share resources with each other so that they could collectively do their work. In modern times there is debate about the extent to which scientific information should be shared. The conflict that led to the Open Science movement is between the desire of scientists to have access to shared resources versus the desire of individual entities to profit when other entities partake of their resources. Additionally, the status of open access and resources that are available for its promotion are likely to differ from one field of academic inquiry to another.

Principles

Open science elements based on UNESCO presentation of 17 February 2021

The six principles of open science are:

• Open methodology
• Open source
• Open data
• Open access
• Open peer review
• Open educational resources

The figure to the right shows a breakdown of elements based on a UNESCO presentation in early 2021. This depiction includes indigenous science.

Open science involves the principles of transparency, accessibility, authorization, and participation, underlying science practice.

Background

Science is broadly understood as collecting, analyzing, publishing, reanalyzing, critiquing, and reusing data. Proponents of open science identify a number of barriers that impede or dissuade the broad dissemination of scientific data. These include financial paywalls of for-profit research publishers, restrictions on usage applied by publishers of data, poor formatting of data or use of proprietary software that makes it difficult to re-purpose, and cultural reluctance to publish data for fears of losing control of how the information is used.

Open Science Taxonomy

According to the FOSTER taxonomy Open science can often include aspects of Open access, Open data and the open source movement whereby modern science requires software to process data and information. Open research computation also addresses the problem of reproducibility of scientific results.

Types

The term "open science" does not have any one fixed definition or operationalization. On the one hand, it has been referred to as a "puzzling phenomenon". On the other hand, the term has been used to encapsulate a series of principles that aim to foster scientific growth and its complementary access to the public. Two influential sociologists, Benedikt Fecher and Sascha Friesike, have created multiple "schools of thought" that describe the different interpretations of the term.

According to Fecher and Friesike ‘Open Science’ is an umbrella term for various assumptions about the development and dissemination of knowledge. To show the term's multitudinous perceptions, they differentiate between five Open Science schools of thought:

Infrastructure School

The infrastructure school is founded on the assumption that "efficient" research depends on the availability of tools and applications. Therefore, the "goal" of the school is to promote the creation of openly available platforms, tools, and services for scientists. Hence, the infrastructure school is concerned with the technical infrastructure that promotes the development of emerging and developing research practices through the use of the internet, including the use of software and applications, in addition to conventional computing networks. In that sense, the infrastructure school regards open science as a technological challenge. The infrastructure school is tied closely with the notion of "cyberscience", which describes the trend of applying information and communication technologies to scientific research, which has led to an amicable development of the infrastructure school. Specific elements of this prosperity include increasing collaboration and interaction between scientists, as well as the development of "open-source science" practices. The sociologists discuss two central trends in the infrastructure school:

1. Distributed computing: This trend encapsulates practices that outsource complex, process-heavy scientific computing to a network of volunteer computers around the world. The examples that the sociologists cite in their paper is that of the Open Science Grid, which enables the development of large-scale projects that require high-volume data management and processing, which is accomplished through a distributed computer network. Moreover, the grid provides the necessary tools that the scientists can use to facilitate this process.

2. Social and Collaboration Networks of Scientists: This trend encapsulates the development of software that makes interaction with other researchers and scientific collaborations much easier than traditional, non-digital practices. Specifically, the trend is focused on implementing newer Web 2.0 tools to facilitate research related activities on the internet. De Roure and colleagues (2008) list a series of four key capabilities which they believe define a Social Virtual Research Environment (SVRE):

• The SVRE should primarily aid the management and sharing of research objects. The authors define these to be a variety of digital commodities that are used repeatedly by researchers.
• Second, the SVRE should have inbuilt incentives for researchers to make their research objects available on the online platform.
• Third, the SVRE should be "open" as well as "extensible", implying that different types of digital artifacts composing the SVRE can be easily integrated.
• Fourth, the authors propose that the SVRE is more than a simple storage tool for research information. Instead, the researchers propose that the platform should be "actionable". That is, the platform should be built in such a way that research objects can be used in the conduct of research as opposed to simply being stored.

Measurement school

The measurement school, in the view of the authors, deals with developing alternative methods to determine scientific impact. This school acknowledges that measurements of scientific impact are crucial to a researcher's reputation, funding opportunities, and career development. Hence, the authors argue, that any discourse about Open Science is pivoted around developing a robust measure of scientific impact in the digital age. The authors then discuss other research indicating support for the measurement school. The three key currents of previous literature discussed by the authors are:

• The peer-review is described as being time-consuming.
• The impact of an article, tied to the name of the authors of the article, is related more to the circulation of the journal rather than the overall quality of the article itself.
• New publishing formats that are closely aligned with the philosophy of Open Science are rarely found in the format of a journal that allows for the assignment of the impact factor.

Hence, this school argues that there are faster impact measurement technologies that can account for a range of publication types as well as social media web coverage of a scientific contribution to arrive at a complete evaluation of how impactful the science contribution was. The gist of the argument for this school is that hidden uses like reading, bookmarking, sharing, discussing and rating are traceable activities, and these traces can and should be used to develop a newer measure of scientific impact. The umbrella jargon for this new type of impact measurements is called altmetrics, coined in a 2011 article by Priem et al., (2011). Markedly, the authors discuss evidence that altmetrics differ from traditional webometrics which are slow and unstructured. Altmetrics are proposed to rely upon a greater set of measures that account for tweets, blogs, discussions, and bookmarks. The authors claim that the existing literature has often proposed that altmetrics should also encapsulate the scientific process, and measure the process of research and collaboration to create an overall metric. However, the authors are explicit in their assessment that few papers offer methodological details as to how to accomplish this. The authors use this and the general dearth of evidence to conclude that research in the area of altmetrics is still in its infancy.

Public School

According to the authors, the central concern of the school is to make science accessible to a wider audience. The inherent assumption of this school, as described by the authors, is that the newer communication technologies such as Web 2.0 allow scientists to open up the research process and also allow scientist to better prepare their "products of research" for interested non-experts. Hence, the school is characterized by two broad streams: one argues for the access of the research process to the masses, whereas the other argues for increased access to the scientific product to the public.

• Accessibility to the Research Process: Communication technology allows not only for the constant documentation of research but also promotes the inclusion of many different external individuals in the process itself. The authors cite citizen science- the participation of non-scientists and amateurs in research. The authors discuss instances in which gaming tools allow scientists to harness the brain power of a volunteer workforce to run through several permutations of protein-folded structures. This allows for scientists to eliminate many more plausible protein structures while also "enriching" the citizens about science. The authors also discuss a common criticism of this approach: the amateur nature of the participants threatens to pervade the scientific rigor of experimentation.
• Comprehensibility of the Research Result: This stream of research concerns itself with making research understandable for a wider audience. The authors describe a host of authors that promote the use of specific tools for scientific communication, such as microblogging services, to direct users to relevant literature. The authors claim that this school proposes that it is the obligation of every researcher to make their research accessible to the public. The authors then proceed to discuss if there is an emerging market for brokers and mediators of knowledge that is otherwise too complicated for the public to grasp effortlessly.

Democratic school

The democratic school concerns itself with the concept of access to knowledge. As opposed to focusing on the accessibility of research and its understandability, advocates of this school focus on the access of products of research to the public. The central concern of the school is with the legal and other obstacles that hinder the access of research publications and scientific data to the public. The authors argue that proponents of this school assert that any research product should be freely available. The authors argue that the underlying notion of this school is that everyone has the same, equal right of access to knowledge, especially in the instances of state-funded experiments and data. The authors categorize two central currents that characterize this school: Open Access and Open Data.

• Open Data: The authors discuss existing attitudes in the field that rebel against the notion that publishing journals should claim copyright over experimental data, which prevents the re-use of data and therefore lowers the overall efficiency of science in general. The claim is that journals have no use of the experimental data and that allowing other researchers to use this data will be fruitful. The authors cite other literature streams that discovered that only a quarter of researchers agree to share their data with other researchers because of the effort required for compliance.
• Open Access to Research Publication: According to this school, there is a gap between the creation and sharing of knowledge. Proponents argue, as the authors describe, that even scientific knowledge doubles every 5 years, access to this knowledge remains limited. These proponents consider access to knowledge as a necessity for human development, especially in the economic sense.

Pragmatic School

The pragmatic school considers Open Science as the possibility to make knowledge creation and dissemination more efficient by increasing the collaboration throughout the research process. Proponents argue that science could be optimized by modularizing the process and opening up the scientific value chain. ‘Open’ in this sense follows very much the concept of open innovation. Take for instance transfers the outside-in (including external knowledge in the production process) and inside-out (spillovers from the formerly closed production process) principles to science. Web 2.0 is considered a set of helpful tools that can foster collaboration (sometimes also referred to as Science 2.0). Further, citizen science is seen as a form of collaboration that includes knowledge and information from non-scientists. Fecher and Friesike describe data sharing as an example of the pragmatic school as it enables researchers to use other researchers’ data to pursue new research questions or to conduct data-driven replications.

History

The widespread adoption of the institution of the scientific journal marks the beginning of the modern concept of open science. Before this time societies pressured scientists into secretive behaviors.

Before journals

Before the advent of scientific journals, scientists had little to gain and much to lose by publicizing scientific discoveries. Many scientists, including Galileo, Kepler, Isaac Newton, Christiaan Huygens, and Robert Hooke, made claim to their discoveries by describing them in papers coded in anagrams or cyphers and then distributing the coded text. Their intent was to develop their discovery into something off which they could profit, then reveal their discovery to prove ownership when they were prepared to make a claim on it.

The system of not publicizing discoveries caused problems because discoveries were not shared quickly and because it sometimes was difficult for the discoverer to prove priority. Newton and Gottfried Leibniz both claimed priority in discovering calculus. Newton said that he wrote about calculus in the 1660s and 1670s, but did not publish until 1693. Leibniz published "Nova Methodus pro Maximis et Minimis", a treatise on calculus, in 1684. Debates over priority are inherent in systems where science is not published openly, and this was problematic for scientists who wanted to benefit from priority.

These cases are representative of a system of aristocratic patronage in which scientists received funding to develop either immediately useful things or to entertain. In this sense, funding of science gave prestige to the patron in the same way that funding of artists, writers, architects, and philosophers did. Because of this, scientists were under pressure to satisfy the desires of their patrons, and discouraged from being open with research which would bring prestige to persons other than their patrons.

Emergence of academies and journals

Eventually the individual patronage system ceased to provide the scientific output which society began to demand. Single patrons could not sufficiently fund scientists, who had unstable careers and needed consistent funding. The development which changed this was a trend to pool research by multiple scientists into an academy funded by multiple patrons. In 1660 England established the Royal Society and in 1666 the French established the French Academy of Sciences. Between the 1660s and 1793, governments gave official recognition to 70 other scientific organizations modeled after those two academies. In 1665, Henry Oldenburg became the editor of Philosophical Transactions of the Royal Society, the first academic journal devoted to science, and the foundation for the growth of scientific publishing. By 1699 there were 30 scientific journals; by 1790 there were 1052. Since then publishing has expanded at even greater rates.

Popular Science Writing

The first popular science periodical of its kind was published in 1872, under a suggestive name that is still a modern portal for the offering science journalism: Popular Science. The magazine claims to have documented the invention of the telephone, the phonograph, the electric light and the onset of automobile technology. The magazine goes so far as to claim that the "history of Popular Science is a true reflection of humankind's progress over the past 129+ years". Discussions of popular science writing most often contend their arguments around some type of "Science Boom". A recent historiographic account of popular science traces mentions of the term "science boom" to Daniel Greenberg's Science and Government Reports in 1979 which posited that "Scientific magazines are bursting out all over. Similarly, this account discusses the publication Time, and its cover story of Carl Sagan in 1980 as propagating the claim that popular science has "turned into enthusiasm". Crucially, this secondary accounts asks the important question as to what was considered as popular "science" to begin with. The paper claims that any account of how popular science writing bridged the gap between the informed masses and the expert scientists must first consider who was considered a scientist to begin with.

Collaboration among academies

In modern times many academies have pressured researchers at publicly funded universities and research institutions to engage in a mix of sharing research and making some technological developments proprietary. Some research products have the potential to generate commercial revenue, and in hope of capitalizing on these products, many research institutions withhold information and technology which otherwise would lead to overall scientific advancement if other research institutions had access to these resources. It is difficult to predict the potential payouts of technology or to assess the costs of withholding it, but there is general agreement that the benefit to any single institution of holding technology is not as great as the cost of withholding it from all other research institutions.

Coining of phrase "OpenScience"

The exact phrase "Open Science" was coined by Steve Mann in 1998 at which time he also registered the domain name openscience.com and openscience.org which he sold to degruyter.com in 2011.

Politics

In many countries, governments fund some science research. Scientists often publish the results of their research by writing articles and donating them to be published in scholarly journals, which frequently are commercial. Public entities such as universities and libraries subscribe to these journals. Michael Eisen, a founder of the Public Library of Science, has described this system by saying that "taxpayers who already paid for the research would have to pay again to read the results."

In December 2011, some United States legislators introduced a bill called the Research Works Act, which would prohibit federal agencies from issuing grants with any provision requiring that articles reporting on taxpayer-funded research be published for free to the public online. Darrell Issa, a co-sponsor of the bill, explained the bill by saying that "Publicly funded research is and must continue to be absolutely available to the public. We must also protect the value added to publicly funded research by the private sector and ensure that there is still an active commercial and non-profit research community." One response to this bill was protests from various researchers; among them was a boycott of commercial publisher Elsevier called The Cost of Knowledge.

The Dutch Presidency of the Council of the European Union called out for action in April 2016 to migrate European Commission funded research to Open Science. European Commissioner Carlos Moedas introduced the Open Science Cloud at the Open Science Conference in Amsterdam on 4–5 April. During this meeting also The Amsterdam Call for Action on Open Science was presented, a living document outlining concrete actions for the European Community to move to Open Science.

Standard setting instruments

There is currently no global normative framework covering all aspects of Open Science. In November 2019, UNESCO was tasked by its 193 Member States, during their 40th General Conference, with leading a global dialogue on Open Science to identify globally-agreed norms and to create a standard-setting instrument. The multistakeholder, consultative, inclusive and participatory process to define a new global normative instrument on Open Science is expected to take two years and to lead to the adoption of a UNESCO Recommendation on Open Science by Member States in 2021.

Two UN frameworks set out some common global standards for application of Open Science and closely related concepts: the UNESCO Recommendation on Science and Scientific Researchers, approved by the General Conference at its 39th session in 2017, and the UNESCO Strategy on Open Access to scientific information and research, approved by the General Conference at its 36th session in 2011.

Advantages and disadvantages

Arguments in favor of open science generally focus on the value of increased transparency in research, and in the public ownership of science, particularly that which is publicly funded. In January 2014 J. Christopher Bare published a comprehensive "Guide to Open Science". Likewise, in 2017, a group of scholars known for advocating open science published a "manifesto" for open science in the journal Nature.

Advantages

Open access publication of research reports and data allows for rigorous peer-review

An article published by a team of NASA astrobiologists in 2010 in Science reported a bacterium known as GFAJ-1 that could purportedly metabolize arsenic (unlike any previously known species of lifeform). This finding, along with NASA's claim that the paper "will impact the search for evidence of extraterrestrial life", met with criticism within the scientific community. Much of the scientific commentary and critique around this issue took place in public forums, most notably on Twitter, where hundreds of scientists and non-scientists created a hashtag community around the hashtag #arseniclife. University of British Columbia astrobiologist Rosie Redfield, one of the most vocal critics of the NASA team's research, also submitted a draft of a research report of a study that she and colleagues conducted which contradicted the NASA team's findings; the draft report appeared in arXiv, an open-research repository, and Redfield called in her lab's research blog for peer review both of their research and of the NASA team's original paper. Researcher Jeff Rouder defined Open Science as "endeavoring to preserve the rights of others to reach independent conclusions about your data and work".

Publicly funded science will be publicly available

Public funding of research has long been cited as one of the primary reasons for providing Open Access to research articles. Since there is significant value in other parts of the research such as code, data, protocols, and research proposals a similar argument is made that since these are publicly funded, they should be publicly available under a Creative Commons Licence.

Open science will make science more reproducible and transparent

Increasingly the reproducibility of science is being questioned and the term "reproducibility crisis" has been coined. For example, psychologist Stuart Vyse notes that "(r)ecent research aimed at previously published psychology studies has demonstrated--shockingly--that a large number of classic phenomena cannot be reproduced, and the popularity of p-hacking is thought to be one of the culprits." Open Science approaches are proposed as one way to help increase the reproducibility of work as well as to help mitigate against manipulation of data.

Open science has more impact

There are several components to impact in research, many of which are hotly debated. However, under traditional scientific metrics parts Open science such as Open Access and Open Data have proved to outperform traditional versions.

Open science will help answer uniquely complex questions

Recent arguments in favor of Open Science have maintained that Open Science is a necessary tool to begin answering immensely complex questions, such as the neural basis of consciousness. The typical argument propagates the fact that these type of investigations are too complex to be carried out by any one individual, and therefore, they must rely on a network of open scientists to be accomplished. By default, the nature of these investigations also makes this "open science" as "big science".

Disadvantages

The open sharing of research data is not widely practiced

Arguments against open science tend to focus on the advantages of data ownership and concerns about the misuse of data.

Potential misuse

In 2011, Dutch researchers announced their intention to publish a research paper in the journal Science describing the creation of a strain of H5N1 influenza which can be easily passed between ferrets, the mammals which most closely mimic the human response to the flu. The announcement triggered a controversy in both political and scientific circles about the ethical implications of publishing scientific data which could be used to create biological weapons. These events are examples of how science data could potentially be misused. Scientists have collaboratively agreed to limit their own fields of inquiry on occasions such as the Asilomar conference on recombinant DNA in 1975, and a proposed 2015 worldwide moratorium on a human-genome-editing technique.

The public may misunderstand science data

In 2009 NASA launched the Kepler spacecraft and promised that they would release collected data in June 2010. Later they decided to postpone release so that their scientists could look at it first. Their rationale was that non-scientists might unintentionally misinterpret the data, and NASA scientists thought it would be preferable for them to be familiar with the data in advance so that they could report on it with their level of accuracy.

Low-quality science

Post-publication peer review, a staple of open science, has been criticized as promoting the production of lower quality papers that are extremely voluminous. Specifically, critics assert that as quality is not guaranteed by preprint servers, the veracity of papers will be difficult to assess by individual readers. This will lead to rippling effects of false science, akin to the recent epidemic of false news, propagated with ease on social media websites. Common solutions to this problem have been cited as adaptations of a new format in which everything is allowed to be published but a subsequent filter-curator model is imposed to ensure some basic quality of standards are met by all publications.

Entrapment by platform capitalism

For Philip Mirowski open science runs the risk of continuing a trend of commodification of science which ultimately serves the interests of capital in the guise of platform capitalism.

Actions and initiatives

Open-science projects

Different projects conduct, advocate, develop tools for, or fund open science.

The Allen Institute for Brain Science conducts numerous open science projects while the Center for Open Science has projects to conduct, advocate, and create tools for open science. Other workgroups have been created in different fields, such as the Decision Analysis in R for Technologies in Health (DARTH) workgroup], which is a multi-institutional, multi-university collaborative effort by researchers who have a common goal to develop transparent and open-source solutions to decision analysis in health.

Organizations have extremely diverse sizes and structures. The Open Knowledge Foundation (OKF) is a global organization sharing large data catalogs, running face to face conferences, and supporting open source software projects. In contrast, Blue Obelisk is an informal group of chemists and associated cheminformatics projects. The tableau of organizations is dynamic with some organizations becoming defunct, e.g., Science Commons, and new organizations trying to grow, e.g., the Self-Journal of Science. Common organizing forces include the knowledge domain, type of service provided, and even geography, e.g., OCSDNet's concentration on the developing world.

The Allen Brain Atlas maps gene expression in human and mouse brains; the Encyclopedia of Life documents all the terrestrial species; the Galaxy Zoo classifies galaxies; the International HapMap Project maps the haplotypes of the human genome; the Monarch Initiative makes available integrated public model organism and clinical data; and the Sloan Digital Sky Survey which regularizes and publishes data sets from many sources. All these projects accrete information provided by many different researchers with different standards of curation and contribution.

Mathematician Timothy Gowers launched open science journal Discrete Analysis in 2016 to demonstrate that a high-quality mathematics journal could be produced outside the traditional academic publishing industry. The launch followed a boycott of scientific journals that he initiated. The journal is published by a nonprofit which is owned and published by a team of scholars.

Other projects are organized around completion of projects that require extensive collaboration. For example, OpenWorm seeks to make a cellular level simulation of a roundworm, a multidisciplinary project. The Polymath Project seeks to solve difficult mathematical problems by enabling faster communications within the discipline of mathematics. The Collaborative Replications and Education project recruits undergraduate students as citizen scientists by offering funding. Each project defines its needs for contributors and collaboration.

Another practical example for open science project was the first "open" doctoral thesis started in 2012. It was made publicly available as a self-experiment right from the start to examine whether this dissemination is even possible during the productive stage of scientific studies. The goal of the dissertation project: Publish everything related to the doctoral study and research process as soon as possible, as comprehensive as possible and under an open license, online available at all time for everyone. End of 2017, the experiment was successfully completed and published in early 2018 as an open access book.

The ideas of open science have also been applied to recruitment with jobRxiv, a free and international job board that aims to mitigate imbalances in what different labs can afford to spend on hiring.

Advocacy

Numerous documents, organizations, and social movements advocate wider adoption of open science. Statements of principles include the Budapest Open Access Initiative from a December 2001 conference and the Panton Principles. New statements are constantly developed, such as the Amsterdam Call for Action on Open Science to be presented to the Dutch Presidency of the Council of the European Union in late May 2016. These statements often try to regularize licenses and disclosure for data and scientific literature.

Other advocates concentrate on educating scientists about appropriate open science software tools. Education is available as training seminars, e.g., the Software Carpentry project; as domain specific training materials, e.g., the Data Carpentry project; and as materials for teaching graduate classes, e.g., the Open Science Training Initiative. Many organizations also provide education in the general principles of open science.

Within scholarly societies there are also sections and interest groups that promote open science practices. The Ecological Society of America has an Open Science Section. Similarly, the Society for American Archaeology has an Open Science Interest Group.

Journal support

Many individual journals are experimenting with the open access model: the Public Library of Science, or PLOS, is creating a library of open access journals and scientific literature. Other publishing experiments include delayed and hybrid models. There are experiments in different fields:

• F1000Research provides open publishing and open peer review for the life sciences.
• The open-science initiative of the Empirical Software Engineering Journal encourages authors to submit a replication package which is assessed with an open science badge.
• The Open Library of Humanities is a non-profit open access publisher for the humanities and social sciences.

Journal support for open-science does not contradict with preprint servers: figshare archives and shares images, readings, and other data; and Open Science Framework preprints, arXiv, and HAL Archives Ouvertes provide electronic preprints across many fields.

Software

A variety of computer resources support open science. These include software like the Open Science Framework from the Center for Open Science to manage project information, data archiving and team coordination; distributed computing services like Ibercivis to use unused CPU time for computationally intensive tasks; and services like Experiment.com to provide crowdsourced funding for research projects.

Blockchain platforms for open science have been proposed. The first such platform is the Open Science Organization, which aims to solve urgent problems with fragmentation of the scientific ecosystem and difficulties of producing validated, quality science. Among the initiatives of Open Science Organization include the Interplanetary Idea System (IPIS), Researcher Index (RR-index), Unique Researcher Identity (URI), and Research Network. The Interplanetary Idea System is a blockchain based system that tracks the evolution of scientific ideas over time. It serves to quantify ideas based on uniqueness and importance, thus allowing the scientific community to identify pain points with current scientific topics and preventing unnecessary re-invention of previously conducted science. The Researcher Index aims to establish a data-driven statistical metric for quantifying researcher impact. The Unique Researcher Identity is a blockchain technology based solution for creating a single unifying identity for each researcher, which is connected to the researcher's profile, research activities, and publications. The Research Network is a social networking platform for researchers.

A scientific paper from November 2019 examined the suitability of blockchain technology to support open science. The results of their research showed that the technology is well suited for open science and can provide advantages, for example, in data security, trust, and collaboration. However, they state that the widespread use of the technology depends on whether the scientific community accepts it and adapts its processes accordingly.

Preprint servers

Preprint Servers come in many varieties, but the standard traits across them are stable: they seek to create a quick, free mode of communicating scientific knowledge to the public. Preprint servers act as a venue to quickly disseminate research and vary on their policies concerning when articles may be submitted relative to journal acceptance. Also typical of preprint servers is their lack of a peer-review process – typically, preprint servers have some type of quality check in place to ensure a minimum standard of publication, but this mechanism is not the same as a peer-review mechanism. Some preprint servers have explicitly partnered with the broader open science movement. Preprint servers can offer service similar to those of journals, and Google Scholar indexes many preprint servers and collects information about citations to preprints. The case for preprint servers is often made based on the slow pace of conventional publication formats. The motivation to start Socarxiv, an open-access preprint server for social science research, is the claim that valuable research being published in traditional venues often takes several months to years to get published, which slows down the process of science significantly. Another argument made in favor of preprint servers like Socarxiv is the quality and quickness of feedback offered to scientists on their pre-published work. The founders of Socarxiv claim that their platform allows researchers to gain easy feedback from their colleagues on the platform, thereby allowing scientists to develop their work into the highest possible quality before formal publication and circulation. The founders of Socarxiv further claim that their platform affords the authors the greatest level of flexibility in updating and editing their work to ensure that the latest version is available for rapid dissemination. The founders claim that this is not traditionally the case with formal journals, which instate formal procedures to make updates to published articles. Perhaps the strongest advantage of some preprint servers is their seamless compatibility with Open Science software such as the Open Science Framework. The founders of SocArXiv claim that their preprint server connects all aspects of the research life cycle in OSF with the article being published on the preprint server. According to the founders, this allows for greater transparency and minimal work on the authors' part.

One criticism of pre-print servers is their potential to foster a culture of plagiarism. For example, the popular physics preprint server ArXiv had to withdraw 22 papers when it came to light that they were plagiarized. In June 2002, a high-energy physicist in Japan was contacted by a man called Ramy Naboulsi, a non-institutionally affiliated mathematical physicist. Naboulsi requested Watanabe to upload his papers on ArXiv as he was not able to do so, because of his lack of an institutional affiliation. Later, the papers were realized to have been copied from the proceedings of a physics conference. Preprint servers are increasingly developing measures to circumvent this plagiarism problem. In developing nations like India and China, explicit measures are being taken to combat it. These measures usually involve creating some type of central repository for all available pre-prints, allowing the use of traditional plagiarism detecting algorithms to detect the fraud. Nonetheless, this is a pressing issue in the discussion of pre-print servers, and consequently for open science.

 

Nutrient cycle

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Nutrient_cycle 

 

Composting within agricultural systems capitalizes upon the natural services of nutrient recycling in ecosystems. Bacteria, fungi, insects, earthworms, bugs, and other creatures dig and digest the compost into fertile soil. The minerals and nutrients in the soil is recycled back into the production of crops.

A nutrient cycle (or ecological recycling) is the movement and exchange of organic and inorganic matter back into the production of matter. Energy flow is a unidirectional and noncyclic pathway, whereas the movement of mineral nutrients is cyclic. Mineral cycles include the carbon cycle, sulfur cycle, nitrogen cycle, water cycle, phosphorus cycle, oxygen cycle, among others that continually recycle along with other mineral nutrients into productive ecological nutrition.

Outline

Fallen logs are critical components of the nutrient cycle in terrestrial forests. Nurse logs form habitats for other creatures that decompose the materials and recycle the nutrients back into production.

The nutrient cycle is nature's recycling system. All forms of recycling have feedback loops that use energy in the process of putting material resources back into use. Recycling in ecology is regulated to a large extent during the process of decomposition. Ecosystems employ biodiversity in the food webs that recycle natural materials, such as mineral nutrients, which includes water. Recycling in natural systems is one of the many ecosystem services that sustain and contribute to the well-being of human societies.

A nutrient cycle of a typical terrestrial ecosystem.

There is much overlap between the terms for the biogeochemical cycle and nutrient cycle. Most textbooks integrate the two and seem to treat them as synonymous terms. However, the terms often appear independently. Nutrient cycle is more often used in direct reference to the idea of an intra-system cycle, where an ecosystem functions as a unit. From a practical point, it does not make sense to assess a terrestrial ecosystem by considering the full column of air above it as well as the great depths of Earth below it. While an ecosystem often has no clear boundary, as a working model it is practical to consider the functional community where the bulk of matter and energy transfer occurs. Nutrient cycling occurs in ecosystems that participate in the "larger biogeochemical cycles of the earth through a system of inputs and outputs."

Complete and closed loop

All systems recycle. The biosphere is a network of continually recycling materials and information in alternating cycles of convergence and divergence. As materials converge or become more concentrated they gain in quality, increasing their potentials to drive useful work in proportion to their concentrations relative to the environment. As their potentials are used, materials diverge, or become more dispersed in the landscape, only to be concentrated again at another time and place.

Ecosystems are capable of complete recycling. Complete recycling means that 100% of the waste material can be reconstituted indefinitely. This idea was captured by Howard T. Odum when he penned that "it is thoroughly demonstrated by ecological systems and geological systems that all the chemical elements and many organic substances can be accumulated by living systems from background crustal or oceanic concentrations without limit as to concentration so long as there is available solar or another source of potential energy" In 1979 Nicholas Georgescu-Roegen proposed the fourth law of entropy stating that complete recycling is impossible. Despite Georgescu-Roegen's extensive intellectual contributions to the science of ecological economics, the fourth law has been rejected in line with observations of ecological recycling. However, some authors state that complete recycling is impossible for technological waste.

A simplified food web illustrating a three-trophic food chain (producers-herbivores-carnivores) linked to decomposers. The movement of mineral nutrients through the food chain, into the mineral nutrient pool, and back into the trophic system illustrates ecological recycling. The movement of energy, in contrast, is unidirectional and noncyclic.

Ecosystems execute closed loop recycling where demand for the nutrients that adds to the growth of biomass exceeds supply within that system. There are regional and spatial differences in the rates of growth and exchange of materials, where some ecosystems may be in nutrient debt (sinks) where others will have extra supply (sources). These differences relate to climate, topography, and geological history leaving behind different sources of parent material. In terms of a food web, a cycle or loop is defined as "a directed sequence of one or more links starting from, and ending at, the same species." An example of this is the microbial food web in the ocean, where "bacteria are exploited, and controlled, by protozoa, including heterotrophic microflagellates which are in turn exploited by ciliates. This grazing activity is accompanied by excretion of substances which are in turn used by the bacteria so that the system more or less operates in a closed circuit."

Ecological recycling

A large fraction of the elements composing living matter reside at any instant of time in the world’s biota. Because the earthly pool of these elements is limited and the rates of exchange among the various components of the biota are extremely fast with respect to geological time, it is quite evident that much of the same material is being incorporated again and again into different biological forms. This observation gives rise to the notion that, on the average, matter (and some amounts of energy) are involved in cycles.

An example of ecological recycling occurs in the enzymatic digestion of cellulose. "Cellulose, one of the most abundant organic compounds on Earth, is the major polysaccharide in plants where it is part of the cell walls. Cellulose-degrading enzymes participate in the natural, ecological recycling of plant material." Different ecosystems can vary in their recycling rates of litter, which creates a complex feedback on factors such as the competitive dominance of certain plant species. Different rates and patterns of ecological recycling leaves a legacy of environmental effects with implications for the future evolution of ecosystems.

Ecological recycling is common in organic farming, where nutrient management is fundamentally different compared to agri-business styles of soil management. Organic farms that employ ecosystem recycling to a greater extent support more species (increased levels of biodiversity) and have a different food web structure. Organic agricultural ecosystems rely on the services of biodiversity for the recycling of nutrients through soils instead of relying on the supplementation of synthetic fertilizers. The model for ecological recycling agriculture adheres to the following principals:

• Protection of biodiversity.
• Use of renewable energy.
• Recycling of plant nutrients.

Where produce from an organic farm leaves the farm gate for the market the system becomes an open cycle and nutrients may need to be replaced through alternative methods.

Ecosystem engineers

An illustration of an earthworm casting taken from Charles Darwin's publication on the movement of organic matter in soils through the ecological activities of worms.

 

From the largest to the smallest of creatures, nutrients are recycled by their movement, by their wastes, and by their metabolic activities. This illustration shows an example of the whale pump that cycles nutrients through the layers of the oceanic water column. Whales can migrate to great depths to feed on bottom fish (such as sand lance Ammodytes spp.) and surface to feed on krill and plankton at shallower levels. The whale pump enhances growth and productivity in other parts of the ecosystem.

The persistent legacy of environmental feedback that is left behind by or as an extension of the ecological actions of organisms is known as niche construction or ecosystem engineering. Many species leave an effect even after their death, such as coral skeletons or the extensive habitat modifications to a wetland by a beaver, whose components are recycled and re-used by descendants and other species living under a different selective regime through the feedback and agency of these legacy effects. Ecosystem engineers can influence nutrient cycling efficiency rates through their actions.

Earthworms, for example, passively and mechanically alter the nature of soil environments. Bodies of dead worms passively contribute mineral nutrients to the soil. The worms also mechanically modify the physical structure of the soil as they crawl about (bioturbation), digest on the molds of organic matter they pull from the soil litter. These activities transport nutrients into the mineral layers of soil. Worms discard wastes that create worm castings containing undigested materials where bacteria and other decomposers gain access to the nutrients. The earthworm is employed in this process and the production of the ecosystem depends on their capability to create feedback loops in the recycling process.

Shellfish are also ecosystem engineers because they: 1) Filter suspended particles from the water column; 2) Remove excess nutrients from coastal bays through denitrification; 3) Serve as natural coastal buffers, absorbing wave energy and reducing erosion from boat wakes, sea level rise and storms; 4) Provide nursery habitat for fish that are valuable to coastal economies.

Fungi contribute to nutrient cycling and nutritionally rearrange patches of ecosystem creating niches for other organisms. In that way fungi in growing dead wood allow xylophages to grow and develop and xylophages, in turn, affect dead wood, contributing to wood decomposition and nutrient cycling in the forest floor.

History

Nutrient cycling has a historical foothold in the writings of Charles Darwin in reference to the decomposition actions of earthworms. Darwin wrote about "the continued movement of the particles of earth". Even earlier, in 1749 Carl Linnaeus wrote in "the economy of nature we understand the all-wise disposition of the creator in relation to natural things, by which they are fitted to produce general ends, and reciprocal uses" in reference to the balance of nature in his book Oeconomia Naturae. In this book he captured the notion of ecological recycling: "The 'reciprocal uses' are the key to the whole idea, for 'the death, and destruction of one thing should always be subservient to the restitution of another;' thus mould spurs the decay of dead plants to nourish the soil, and the earth then 'offers again to plants from its bosom, what it has received from them.'" The basic idea of a balance of nature, however, can be traced back to the Greeks: Democritus, Epicurus, and their Roman disciple Lucretius.

Following the Greeks, the idea of a hydrological cycle (water is considered a nutrient) was validated and quantified by Halley in 1687. Dumas and Boussingault (1844) provided a key paper that is recognized by some to be the true beginning of biogeochemistry, where they talked about the cycle of organic life in great detail. From 1836 to 1876, Jean Baptiste Boussingault demonstrated the nutritional necessity of minerals and nitrogen for plant growth and development. Prior to this time influential chemists discounted the importance of mineral nutrients in soil. Ferdinand Cohn is another influential figure. "In 1872, Cohn described the 'cycle of life' as the "entire arrangement of nature" in which the dissolution of dead organic bodies provided the materials necessary for new life. The amount of material that could be molded into living beings was limited, he reasoned, so there must exist an "eternal circulation" (ewigem kreislauf) that constantly converts the same particle of matter from dead bodies into living bodies." These ideas were synthesized in the Master's research of Sergei Vinogradskii from 1881-1883.

Variations in terminology

In 1926 Vernadsky coined the term biogeochemistry as a sub-discipline of geochemistry. However, the term nutrient cycle pre-dates biogeochemistry in a pamphlet on silviculture in 1899: "These demands by no means pass over the fact that at places where sufficient quantities of humus are available and where, in case of continuous decomposition of litter, a stable, nutrient humus is present, considerable quantities of nutrients are also available from the biogenic nutrient cycle for the standing timber. In 1898 there is a reference to the nitrogen cycle in relation to nitrogen fixing microorganisms. Other uses and variations on the terminology relating to the process of nutrient cycling appear throughout history:

• The term mineral cycle appears early in a 1935 in reference to the importance of minerals in plant physiology: "...ash is probably either built up into its permanent structure, or deposited in some way as waste in the cells, and so may not be free to re-enter the mineral cycle."
• The term nutrient recycling appears in a 1964 paper on the food ecology of the wood stork: "While the periodic drying up and reflooding of the marshes creates special survival problems for organisms in the community, the fluctuating water levels favor rapid nutrient recycling and subsequent high rates of primary and secondary production"
• The term natural cycling appears in a 1968 paper on the transportation of leaf litter and its chemical elements for consideration in fisheries management: "Fluvial transport of tree litter from drainage basins is a factor in natural cycling of chemical elements and in degradation of the land."
• The term ecological recycling appears in a 1968 publication on future applications of ecology for the creation of different modules designed for living in extreme environments, such as space or under sea: "For our basic requirement of recycling vital resources, the oceans provide much more frequent ecological recycling than the land area. Fish and other organic populations have higher growth rates, vegetation has less capricious weather problems for sea harvesting."
• The term bio-recycling appears in a 1976 paper on the recycling of organic carbon in oceans: "Following the actualistic assumption, then, that biological activity is responsible for the source of dissolved organic material in the oceans, but is not important for its activities after death of the organisms and subsequent chemical changes which prevent its bio-recycling, we can see no major difference in the behavior of dissolved organic matter between the prebiotic and post-biotic oceans."

Water is also a nutrient. In this context, some authors also refer to precipitation recycling, which "is the contribution of evaporation within a region to precipitation in that same region." These variations on the theme of nutrient cycling continue to be used and all refer to processes that are part of the global biogeochemical cycles. However, authors tend to refer to natural, organic, ecological, or bio-recycling in reference to the work of nature, such as it is used in organic farming or ecological agricultural systems.

Recycling in Novel Ecosystems

An endless stream of technological waste accumulates in different spatial configurations across the planet and turns into a predator in our soils, our streams, and our oceans. This idea was similarly expressed in 1954 by ecologist Paul Sears: "We do not know whether to cherish the forest as a source of essential raw materials and other benefits or to remove it for the space it occupies. We expect a river to serve as both vein and artery carrying away waste but bringing usable material in the same channel. Nature long ago discarded the nonsense of carrying poisonous wastes and nutrients in the same vessels." Ecologists use population ecology to model contaminants as competitors or predators. Rachel Carson was an ecological pioneer in this area as her book Silent Spring inspired research into biomagification and brought to the world's attention the unseen pollutants moving into the food chains of the planet.

In contrast to the planets natural ecosystems, technology (or technoecosystems) is not reducing its impact on planetary resources. Only 7% of total plastic waste (adding up to millions upon millions of tons) is being recycled by industrial systems; the 93% that never makes it into the industrial recycling stream is presumably absorbed by natural recycling systems In contrast and over extensive lengths of time (billions of years) ecosystems have maintained a consistent balance with production roughly equaling respiratory consumption rates. The balanced recycling efficiency of nature means that production of decaying waste material has exceeded rates of recyclable consumption into food chains equal to the global stocks of fossilized fuels that escaped the chain of decomposition.

Pesticides soon spread through everything in the ecosphere-both human technosphere and nonhuman biosphere-returning from the 'out there' of natural environments back into plant, animal, and human bodies situated at the 'in here' of artificial environments with unintended, unanticipated, and unwanted effects. By using zoological, toxicological, epidemiological, and ecological insights, Carson generated a new sense of how 'the environment' might be seen.

Microplastics and nanosilver materials flowing and cycling through ecosystems from pollution and discarded technology are among a growing list of emerging ecological concerns. For example, unique assemblages of marine microbes have been found to digest plastic accumulating in the worlds oceans. Discarded technology is absorbed into soils and creates a new class of soils called technosols. Human wastes in the Anthropocene are creating new systems of ecological recycling, novel ecosystems that have to contend with the mercury cycle and other synthetic materials that are streaming into the biodegradation chain. Microorganisms have a significant role in the removal of synthetic organic compounds from the environment empowered by recycling mechanisms that have complex biodegradation pathways. The effect of synthetic materials, such as nanoparticles and microplastics, on ecological recycling systems is listed as one of the major concerns for ecosystem in this century.

Technological recycling

Recycling in human industrial systems (or technoecosystems) differs from ecological recycling in scale, complexity, and organization. Industrial recycling systems do not focus on the employment of ecological food webs to recycle waste back into different kinds of marketable goods, but primarily employ people and technodiversity instead. Some researchers have questioned the premise behind these and other kinds of technological solutions under the banner of 'eco-efficiency' are limited in their capability, harmful to ecological processes, and dangerous in their hyped capabilities. Many technoecosystems are competitive and parasitic toward natural ecosystems. Food web or biologically based "recycling includes metabolic recycling (nutrient recovery, storage, etc.) and ecosystem recycling (leaching and in situ organic matter mineralization, either in the water column, in the sediment surface, or within the sediment)."