Ecosystem Science Research Articles

BEYOND LEGAL FRAMEWORKS AND SECURITY CONTROLS FOR ACCESSING CONFIDENTIAL SURVEY DATA IN THE UNITED STATES: ENGAGING DATA USERS IN DATA PROTECTION.

With growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentialy of survey data and privacy of data subjects is increasingly important. Doing so requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (e.g., longitudinal data, social network data, sensitive information, biomarkers, and geographic data), the current motivation for data reuse, and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and data misuse are observed even in well-established restricted data access systems, indicating that the systems may all rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; and Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.

Autonomous, bidding, credible, decentralized, ethical, and funded (ABCDEF) publishing.

Scientists write research articles, process ethics reviews, evaluate proposals and research, and seek funding. Several strategies have been proposed to optimize these operations and to decentralize access to research resources and opportunities. For instance, we previously proposed the trinity review method, combining registered reports with financing and research ethics assessments. However, previously proposed systems have a number of shortcomings, including how to implement them, e.g., who manages them, how incentives for reviewers are paid, etc. Various solutions have been proposed to address these issues, employing methods based on blockchain technologies, called "decentralized science (DeSci)". Decentralized approaches that exploit these developments offer potentially profound improvements to the troubled scientific ecosystem. Here, we propose a system that integrates ethics reviews, peer reviews, and funding in a decentralized manner, based on Web3 technology. This new method, named ABCDEF publishing, would enhance the speed, fairness, and transparency of scientific research and publishing.

Main aspects of the development of economic science in the Republic of Kazakhstan

The author examines the main aspects of the development of economic science in the Republic of Kazakhstan, noting its important role in the functioning and development of society. The purpose of the study is to analyze the state of economic science in Kazakhstan as an important part of the general socio-economic policy of the state, reflecting the attitude to science, technology and innovation in the economy. The practical and effective use of the results of fundamental and applied sciences has become an important factor in the sustainable development of mankind. To strengthen the role of science in the socio-economic development of the country, it is extremely important to develop an effective mechanism for stimulating the scientific and technological development of economic and social sectors. Applied economics is formed and implemented on the basis of the interrelation and interaction of the following subjects: public administration, external experts and the scientific ecosystem in determining strategic priorities and program documents of the state. In order to identify the main challenges and problems in the field of improving the effectiveness of the formation and development of applied economics, the author conducted a research in the form of a survey. The article also noted the special role in the further development of fundamental and applied economics of the principles and provisions laid down in the annual Messages of the Head of State Kassym-Jomart Tokayev to the people of Kazakhstan. Based on the conducted research, the author provides recommendations and suggestions in the article to improve the efficiency of scientists in the field of economic science in the Republic of Kazakhstan. In the context of globalization and the transition to a new paradigm of economic development, the results of scientific research should serve as a basis for developing recommendations and economic policy measures to improve the economic sphere.

Untangle the Characteristics of Disruptive and Consolidating Citations of Nobel‐winning Papers

ABSTRACTScientific breakthroughs have the potential to revolutionize the course of research and shape the trajectory of scientific knowledge. This study investigates the characteristics of Disruptive Citing Papers (DCP) and Consolidating Citing Papers (CCP) associated with Nobel‐winning scientific breakthroughs, aiming to provide insights into the mechanisms of knowledge creation and dissemination. By analyzing a dataset of Nobel‐winning papers and their citation networks, we find that Nobel‐winning papers tend to attract a higher proportion of DCP compared to CCP. However, CCP exhibit a higher impact, as evidenced by their citation counts and likelihood of becoming hit papers. Furthermore, DCP are associated with larger research teams, highlighting the collaborative nature of disruptive research, while CCP employ a higher degree of professional language style characterized by shorter titles and specialized jargon. These findings deepen our understanding of the role played by disruptive and consolidating impact in scientific breakthroughs, shedding light on the dynamics of knowledge creation and dissemination in the scientific community. This research contributes to the broader understanding of scientific progress and provides valuable insights for researchers, policymakers, and stakeholders in the scientific ecosystem.

Localization of a Module on Ecosystem (Science 7) in Schools Near the Mapanuepe Lake, Zambales

Creating an original instructional material in teaching science by relating learning content to local information and materials from the learner’s community is one of the main features of the K to 12 Curriculum that will enhance students’ achievement. The study aimed to develop and determine the acceptability of a localized module on ecosystem (Science 7) in Schools near the Mapanuepe Lake, Zambales. The study utilized mixed method- concurrent transformative design. The respondents of the study were four (4) selected evaluators and specialists in the field of Science from the Schools Division of Zambales. The researcher reviewed the grade 7 science curriculum guide then conducted a thorough observation on community near the Mapanuepe Lake, Zambales. Afterwards, he developed a localized module that was given to the respondents identified by the researcher together with the evaluation form. The results of the evaluation were used by the researcher in improving some aspects of the module to come up with a Localized Module on Interaction (Science 7). Results revealed that lessons in Grade 7 Science that concerned with the environment are components of an ecosystem, ecological relationships, and transfer of energy through trophic levels. The module was acceptable. The overall mean 4.52 indicates that the module is Excellent. This means that the aspects of module are very adequately covered and the quality is superior. Five major themes emerged to describe the comments and suggestions of the evaluators and specialists in the improvement of the module. These are the following: Localized activities, Activities are organized, Objectives are met, Translate localized terms, Complete and Simplified.

Value exclusion in social–scientific approaches for assessing and valuing ecosystem features: Implications for behavioral compliance

Abstract Value inclusion is critical for effective ecosystem science policy and largely emerged from critiques of the value-exclusionary attributes of ecological and economic approaches to value assessments and valuations. But whether and how value is excluded during social–scientific approaches to the assessments and valuations of ecosystem features has not received adequate attention. We identify and discuss instances of when and how value is excluded during social–scientific approaches to the assessments and valuations of ecosystem features to which people ascribe value. We illustrate the implications of value exclusion on social compliance with ecosystem management and policy recommendations, a vital overlooked aspect of policy effectiveness. We also extend the meaning of value exclusion beyond value omission to include misidentification and misattribution of salience to valued ecosystem features. We offer suggestions for enabling value inclusion where ways to minimize exclusion are inapparent.

Ideas and perspectives: Beyond model evaluation – combining experiments and models to advance terrestrial ecosystem science

Abstract. Ecosystem manipulative experiments are a powerful tool to understand terrestrial ecosystem responses to global change because they measure real responses in real ecosystems and yield insights into causal relationships. However, their scope is limited in space and time due to cost and labour intensity. This makes generalising results from such experiments difficult, which creates a conceptual gap between local-scale process understanding and global-scale future predictions. Recent efforts have seen results from such experiments used in combination with dynamic global vegetation models, most commonly to evaluate model predictions under global change drivers. However, there is much more potential in combining models and experiments. Here, we discuss the value and potential of a workflow for using ecosystem experiments together with process-based models to enhance the potential of both. We suggest that models can be used prior to the start of an experiment to generate hypotheses, identify data needs, and in general guide experimental design. Models, when adequately constrained with observations, can also predict variables which are difficult to measure frequently or at all, and together with the data they can provide a more complete picture of ecosystem states. Finally, models can be used to help generalise the experimental results in space and time, by providing a framework in which process understanding derived from site-level experiments can be incorporated. We also discuss the potential for using manipulative experiments together with models in formalised model–data integration frameworks for parameter estimation and model selection, a path made possible by the increasing number of ecosystem experiments and diverse observation streams. The ideas presented here can provide a roadmap to future experiment–model studies.

A meso-scale cartography of the AI ecosystem

Abstract Recently, the set of knowledge referred to as “artificial intelligence” (AI) has become a mainstay of scientific research. AI techniques have not only greatly developed within their native areas of development but have also spread in terms of their application to multiple areas of science and technology. We conduct a large-scale analysis of AI in science. The first question we address is the composition of what is commonly labeled AI, and how the various subfields within this domain are linked together. We reconstruct the internal structure of the AI ecosystem through the co-occurrence of AI terms in publications, and we distinguish between 15 different specialties of AI. Furthermore, we investigate the spreading of AI outside its native disciplines. We bring to light the dynamics of the diffusion of AI in the scientific ecosystem and we describe the disciplinary landscape of AI applications. Finally we analyze the role of collaborations for the interdisciplinary spreading of AI. Although the study of science frequently emphasizes the openness of scientific communities, we show that collaborations between those scholars who primarily develop AI and those who apply it are quite rare. Only a small group of researchers can gradually establish bridges between these communities.

Hidden knowledge networks: Influence of invisible colleges on scientific research

This review article explores the concept of the invisible college and its fundamental role in the formation and evolution of scientific research. Through an exhaustive analysis of the most relevant literature identified, we examined how these informal networks of scientists and academics facilitate the exchange of information, knowledge, and resources and assess their significant influence on research trends and the dissemination of scientific knowledge. A study was conducted with a qualitative and critical approach, operationalized through a scoping review design. The mechanisms through which these networks foster interdisciplinary collaboration and promote innovations, the challenges and opportunities for scientific policy and research management were analyzed, and strategies were suggested to recognize and enhance their value in the global scientific ecosystem. Finally, future directions are proposed to investigate the impact of these hidden networks on science to improve the understanding of their role in advancing knowledge.

Autonomous, bidding, credible, decentralized, ethical, and funded (ABCDEF) publishing

Scientists write research articles, process ethics reviews, evaluate proposals and research, and seek funding. Several strategies have been proposed to optimize these operations and to decentralize access to research resources and opportunities. For instance, we previously proposed the trinity review method, combining registered reports with financing and research ethics assessments. However, previously proposed systems have a number of shortcomings, including how to implement them, e.g., who manages them, how incentives for reviewers are paid, etc. Various solutions have been proposed to address these issues, employing methods based on blockchain technologies, called “decentralized science (DeSci)”. Decentralized approaches that exploit these developments offer potentially profound improvements to the troubled scientific ecosystem. Here, we propose a system that integrates ethics reviews, peer reviews, and funding in a decentralized manner, based on Web3 technology. This new method, named ABCDEF publishing, would enhance the speed, fairness, and transparency of scientific research and publishing.

Design and redesign of a bottom trawl survey in Chesapeake Bay, USA

Fisheries-independent surveys that reliably sample a broad size range of exploited and ecologically important species provide valuable data in support of fisheries management and ecosystem science. The operational consistency of surveys over time and space is fundamental to the interpretation of data in the contexts of population dynamics processes, community interactions, policy impacts, and environmental forcing. However, the need to maintain historic sampling protocols over extended time periods limits the utilization of new technologies that could lead to improved data collection. Survey vessel replacements also become inevitable as the maturity of sampling programs becomes multidecadal. This case study describes the motivational origin, initial design, and redesign of a bottom trawl survey operating in Chesapeake Bay, the largest estuary in the United States. Regional aspirations to consider ecosystem principles in fisheries management aided initial development of the survey, and the need to collect specific data types to support that endeavor impacted several early design elements. Following the beginning years of full-scale survey operations, a consistently evolving awareness of potential areas of improvement for the survey grew from formal efforts to engage with scientific and industry partners on trawl gear design, leverage the program for additional survey opportunities, utilize gear testing technology, and analyze extant data. When the delivery of a new, state-of-the-art research vessel forced the transfer of survey operations to a new platform, all potential changes were incorporated simultaneously. A subsequent paired-tow experiment was conducted to build a calibration database that successfully provided estimates of relative selectivity for routinely sampled taxa. This experience yielded several lessons learned that are intended to aid investigators faced with adopting structural changes to fisheries-independent surveys in the future.

Reconciling critical zone science with ecosystem and soil science—a personal-scientist perspective

The critical zone has been the subject of much discussion and debate as a term in the ecosystem, soil and earth system science communities, and there is a need to reconcile how this term is used within these disciplines. I suggest that much like watershed and soil ecosystems, the critical zone is an ecosystem and is defined by deeper spatial and temporal boundaries to study its structure and function. Critical zone science, however, expands the scope of ecosystem and soil science and more fully embraces the integration of earth sciences, ecology, and hydrology to understand key mechanisms driving critical zone functions in a place-based setting. This integration of multiple perspectives and expertise is imperative to make new discoveries at the interface of these disciplines. I offer solid examples highlighting how critical zone science as an integrative science contributes to ecosystem and soil sciences and exemplify this emerging field.

Registration of ‘Cedar Creek’ switchgrass

Abstract‘Cedar Creek’ (Reg. no. CV‐290, PI 700113) switchgrass (Panicum virgatum L.) was selected for increased winter survivorship for three cycles, using surviving plants from ‘Kanlow’. The first two cycles were conducted at multiple locations in Wisconsin, and the third cycle was conducted at the Cedar Creek Ecosystem Science Reserve, East Bethel, MN. All seed production and increases were conducted by either Illinois State University or the University of Illinois. Field evaluations of the third‐cycle population were conducted at five locations in Wisconsin between 2017 and 2021, located within USDA hardiness zones 3–5. Field experiments were planted in both 2016 and 2017. Averaged over the five locations and all trial years, Cedar Creek had 91% ground cover, compared with 96% for Cave‐in‐Rock, 95% for Shawnee, and 91% for Liberty. Biomass yield of Cedar Creek averaged 12.17 Mg ha−1, which was 20% higher than Liberty, 30% higher than Cave‐in‐Rock, 31% higher than Shawnee, and 520% higher than Kanlow. Cedar Creek is a high‐biomass lowland‐type of switchgrass and is the first lowland‐type adapted to USDA hardiness zones 3–5. Cedar Creek was released to the public by USDA‐ARS in 2021.

Decomposition decreases molecular diversity and ecosystem similarity of soil organic matter

Soil organic matter (SOM) is comprised of a diverse array of reactive carbon molecules, including hydrophilic and hydrophobic compounds, that impact rates of SOM formation and persistence. Despite clear importance to ecosystem science, little is known about broad-scale controls on SOM diversity and variability in soil. Here, we show that microbial decomposition drives significant variability in the molecular richness and diversity of SOM between soil horizons and across a continental-scale gradient in climate and ecosystem type (arid shrubs, coniferous, deciduous, and mixed forests, grasslands, and tundra sedges). The molecular dissimilarity of SOM was strongly influenced by ecosystem type (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 10% P < 0.001) and soil horizon (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 21%, P < 0.001), as assessed using metabolomic analysis of hydrophilic and hydrophobic metabolites. While the proportion of shared molecular features was significantly higher in the litter layer than subsoil C horizons across ecosystems (12 times and 4 times higher for hydrophilic and hydrophobic compounds, respectively), the proportion of site-specific molecular features nearly doubled from the litter layer to the subsoil horizon, suggesting greater differentiation of compounds after microbial decomposition within each ecosystem. Together, these results suggest that microbial decomposition of plant litter leads to a decrease in SOM α-molecular diversity, yet an increase in β-molecular diversity across ecosystems. The degree of microbial degradation, determined by the position in the soil profile, exerts a greater control on SOM molecular diversity than environmental factors, such as soil texture, moisture, and ecosystem type.

Mdapy: A flexible and efficient analysis software for molecular dynamics simulations

The mdapy is a library for pre- and postprocessing molecular dynamics simulation data. Benefitting from the just-in-time compile technology of TaiChi mdapy can be written in pure Python while possessing similar speed to those written in C++. mdapy is designed with highly paralleled and makes full advantages of modern computer resources on both multicore CPU and GPU architecture. The package implements a fast module to find the neighbors of particles in both free and periodic boundaries, based on which it offers a wide variety of methods to analyze atomic environments, such as standard centrosymmetry parameters, radial distribution function and newer methods, such as atomic entropy fingerprint. In addition, mdapy can be used to create the geometric structure of polycrystals with metallic or graphene grain boundaries by Voronoi diagram. mdapy can directly read the DUMP and DATA format defined in LAMMPS code, and, in practice, it accepts any other format by converting it into NumPy ndarray format. This design philosophy enables seamless integration with abundant scientific ecosystems in the Python community and easy cooperation with other analysis codes like OVITO or freud. Program summaryProgram Title: mdapyCPC Library link to program files:https://doi.org/10.17632/dtdkxvcsc9.1Developer's repository link:https://github.com/mushroomfire/mdapyCode Ocean capsule:https://codeocean.com/capsule/5271472Licensing provisions: BSD 3-clauseProgramming language: Python, C++Nature of problem: Atomic environment analysis and generation of the initial structure are important in molecular dynamics simulations. Many analysis methods relying on particle neighbors, such as radial distribution functions and atomic entropy, are computationally intensive and need to be carefully implemented to scale to large systems. Traditional code is often written in C++ or Fortran to guarantee performance while causing difficulty in installation and secondary development due to the complexity of the programming language.Solution method: mdapy is written in parallel to quickly perform neighbor finding, provides a set of analysis methods and creates an atomic geometry structure on multicore CPU and GPU. Over 95 percent of mdapy is written in Python with a uniform API to call. All data are stored in NumPy ndarray, making users easy to install, use and secondary develop.Additional comments including restrictions and unusual features:1. mdapy provides fast parallel implementations of neighbor finding in periodic and free boundary system.2. mdapy can generate a polycrystalline model with graphene grain boundaries.3. mdapy is helpful for analyzing the melting process by the mean squared displacement and Lindemann index at the atomic level.4. mdapy is very easy to install via pip install mdapy without any compile steps and can be run on Windows, Linux and Mac OS with Python 3.7-3.10.5. mdapy has detailed documentation to make it easier to use.

Timing and magnitude of drought impacts on carbon uptake across a grassland biome.

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remain unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5km2 temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C4 -dominated shortgrass steppe and the C3 -dominated northern mixed prairies. Across over 700,000 pixel-year combinations covering more than 600,000 km2 , we studied how the driest years between 2003-2020 altered the daily and bi-weekly dynamics of grassland carbon (C) uptake. Reductions to C uptake intensified into the early summer during drought and peaked in mid- and late June in both ecoregions. Stimulation of spring C uptake during drought was small and insufficient to compensate for losses during summer. Thus, total grassland C uptake was consistently reduced by drought across both ecoregions; however, reductions were twice as large across the more southern and warmer shortgrass steppe. Across the biome, increased summer vapor pressure deficit (VPD) was strongly linked to peak reductions in vegetation greenness during drought. Rising VPD will likely exacerbate reductions in C uptake during drought across the western US Great Plains, with these reductions greatest during the warmest months and in the warmest locations. High spatiotemporal resolution analyses of grassland response to drought over large areas provide both generalizable insights and new opportunities for basic and applied ecosystem science in these water-limited ecoregions amid climate change.

Unblocking recognition: A token system for acknowledging academic contribution

Here we present a blockchain-backed token recognition system to reward the contributions that academics make to the scientific ecosystem. Recognition is important in science but current methods, systems and incentives are limited. Specifically, the traditional focus on narrow publication metrics means diverse contributions are not captured, while bias toward senior, established scientists is common. To tackle this challenge, we explore the potential of harnessing blockchain’s collaborative, decentralised and trust-brokering properties to develop a token reward system for use by research funders. Academics would be awarded tokens for undertaking common but vital tasks such as peer review, sitting on funding committees and submitting reports. These tokens would not be tradable or specifically monetisable but would serve as a validated record of scientific contribution. They would have value in professional recruitment and job placement, support grant and award applications, and inform performance appraisals and file reviews. Coordination and cooperation across multiple funding agencies in developing the platform would provide an opportunity to aggregate and standardise recognition, given academics often work with several funders. This system’s goals are to expand recognition metrics, promote efficiencies, improve the robustness of professional assessments and enable cross-funder collaboration, thereby optimising research processes and practices in a decentralised and democratised manner.

AutodiDAQt: Simple Scientific Data Acquisition Software with Analysis-in-the-Loop

Scientific data acquisition is a problem domain that has been underserved by its computational tools despite the need to efficiently use hardware, to guarantee validity of the recorded data, and to rapidly test ideas by configuring experiments quickly and inexpensively. High-dimensional physical spectroscopies, such as angle-resolved photoemission spectroscopy, make these issues especially apparent because, while they use expensive instruments to record large data volumes, they require very little acquisition planning. The burden of writing data acquisition software falls to scientists, who are not typically trained to write maintainable software. In this paper, we introduce AutodiDAQt to address these shortfalls in the scientific ecosystem. To ground the discussion, we demonstrate its merits for angle-resolved photoemission spectroscopy and high bandwidth spectroscopies. AutodiDAQt addresses the essential needs for scientific data acquisition by providing simple concurrency, reproducibility, retrospection of the acquisition sequence, and automated user interface generation. Finally, we discuss how AutodiDAQt enables a future of highly efficient machine-learning-in-the-loop experiments and analysis-driven experiments without requiring data acquisition domain expertise by using analysis code for external data acquisition planning.

Cadaver imprint on soil chemistry and microbes - Knowns, unknowns, and perspectives

Cadaver-decomposition unleashes an ephemeral pulse of matter input that modifies microbial communities, as well as nutrient pools and fluxes. This leaves behind a measurable imprint on affected soils. However, the persistence of this imprint remains poorly understood. We define cadaver imprint persistence as the entire period between time of cadaver deposition and time when cadaver effects on microbial community structure and chemical indicators are no longer detectable. We present a brief overview of published results on the cadaver-induced changes in the bio-elements carbon, nitrogen and phosphorus, which regulate the structure and functions of the soil microbiome. Based on this, we identified conceptual and methodological gaps and biases and suggest potential research avenues to address them. This will help to better understand the relationships between cadaver-derived matter and microbial taxa and functions, as well as the role of cadaver-decomposition within and across ecosystems. The proposed future research on cadaver-derived imprint on soils has the potential to serve as a hub for connecting soil chemistry, microbial ecology, forensic sciences, and ecosystems science.

How Do Oysters Remove Nitrogen?

Nitrogen is natural and necessary, yet nitrogen levels above natural levels can cause algal blooms and eutrophication of coastal systems. The purpose of this document is to describe how oysters and oyster reefs remove nitrogen. This new 7-page publication of the UF/IFAS Department of Soil, Water, and Ecosystem Sciences is intended for policymakers, environmental organizations, and coastal residents who want to know about oysters' role in improving water quality through nitrogen removal. Written by Heather Donnelly, Ashley Smyth, Shirley Baker, Laura Reynolds, and Angela Collins.https://edis.ifas.ufl.edu/ss711