Source Ecosystem Research Articles

Empirical assessments of small-scale ecosystem service flows in rural mosaic landscapes in the Ethiopian highlands

Human activities have rapidly altered natural ecosystems worldwide, resulting in fragmented ecosystems that are either culturally or formally protected. These ecosystem patches can be critical for ecosystem services (ES) that support human well-being. In the Ethiopian highlands, the remaining church forests and wetlands have a unique conservation status and are part of the global priority areas for biodiversity conservation. ES flows from these ecosystems to surrounding benefiting areas lack local-scale field evidence data and are not well-understood. Here, we empirically quantify the distance-dependent flows for four ES: grass biomass, microclimate regulation, crop pollination, and soil erosion retention since they exhibit considerable variation in spatial scales and processes of ES flows. The effect of spatial distance on each ES benefit flow was analysed using spatially explicit empirical models. The key findings are as follows: (1) The benefit of ES varies significantly with distance to the source ecosystems. (2) ES supply is determined by the extent (fragmentation) and condition of ecosystems, together with ecosystem type. (3) The quantity and number of ES provided decreases with distance from the source, and beneficiaries up to 3 km of the source only receive one type of ES (grass biomass). Approximately 80 % of the benefiting areas are within a radius of 200 m from forests and wetlands. Bundles of multiple ES types are received at the frontiers of service-providing ecosystems, where number of benefits are compared at particular locations from the source point. The investigated ecosystems (440 km2) provided benefits to 8,770 km2 for the four types of ES. Our findings imply that non-linear effects of key ecosystem variables need to be considered when mapping the distance-dependent ES flows. This study helps to understand the spatial connectivity between ecosystems and beneficiaries in the human-nature interdependency, which is useful for developing different strategies for ES conservation.

Beyond the Repository

Best practices for open source ecosystems researchers.

Software Architectural Practices: Influences on the Open Source Ecosystem Health

The health state of a software ecosystem has been determined by its capacity of growth and longevity. Three health indicators represent a healthy software ecosystem: robustness, productivity, and niche creation. Studies focusing on understanding the causes and processes of the state of health of ecosystems have used these indicators largely. Researchers have intensified studies to understand how to achieve a good health state. Despite the growing number of studies, there is little knowledge about influences and actions to achieve health and, more specifically, that consider the effects of the software architecture on the ecosystem. This article presents a study exploring seven open source ecosystems within different domains to describe the influence of architectural practices on the software ecosystem health in terms of their motivations and effects. Our main goal was to understand how the software architecture and related practices can contribute to a healthy ecosystem. We conducted a netnography-based study to gather practices used to create and maintain the software architecture of these ecosystems. Our study brings evidence that architectural practices play a critical role in the achievement of ecosystems’ health. We found fifty practices that have influenced different aspects of health indicators. We highlight the importance of five influential factors – business goals, experience, requirements, resources, and time-to-market – for motivating the adoption of such practices. These factors may also contribute to understanding different strategies used to achieve a good health state. Moreover, we proposed a novel health indicator, trustworthiness, that accounts for the normal operation of a healthy software ecosystem.

Using the uniqueness of global identifiers to determine the provenance of Python software source code

We consider the problem of identifying the provenance of free/open source software (FOSS) and specifically the need of identifying where reused source code has been copied from. We propose a lightweight approach to solve the problem based on software identifiers-such as the names of variables, classes, and functions chosen by programmers. The proposed approach is able to efficiently narrow down to a small set of candidate origin products, to be further analyzed with more expensive techniques to make a final provenance determination.By analyzing the PyPI (Python Packaging Index) open source ecosystem we find that globally defined identifiers are very distinct. Across PyPI's 244 K packages we found 11.2 M different global identifiers (classes and method/function names-with only 0.6% of identifiers shared among the two types of entities); 76% of identifiers were used only in one package, and 93% in at most 3. Randomly selecting 3 non-frequent global identifiers from an input product is enough to narrow down its origins to a maximum of 3 products within 89% of the cases.We validate the proposed approach by mapping Debian source packages implemented in Python to the corresponding PyPI packages; this approach uses at most five trials, where each trial uses three randomly chosen global identifiers from a randomly chosen python file of the subject software package, then ranks results using a popularity index and requires to inspect only the top result. In our experiments, this method is effective at finding the true origin of a project with a recall of 0.9 and precision of 0.77.

Knowledge graphs for enhancing transparency in health data ecosystems1

Tailoring personalized treatments demands the analysis of a patient’s characteristics, which may be scattered over a wide variety of sources. These features include family history, life habits, comorbidities, and potential treatment side effects. Moreover, the analysis of the services visited the most by a patient before a new diagnosis, as well as the type of requested tests, may uncover patterns that contribute to earlier disease detection and treatment effectiveness. Built on knowledge-driven ecosystems, we devise DE4LungCancer, a health data ecosystem of data sources for lung cancer. In this data ecosystem, knowledge extracted from heterogeneous sources, e.g., clinical records, scientific publications, and pharmacological data, is integrated into knowledge graphs. Ontologies describe the meaning of the combined data, and mapping rules enable the declarative definition of the transformation and integration processes. DE4LungCancer is assessed regarding the methods followed for data quality assessment and curation. Lastly, the role of controlled vocabularies and ontologies in health data management is discussed, as well as their impact on transparent knowledge extraction and analytics. This paper presents the lessons learned in the DE4LungCancer development. It demonstrates the transparency level supported by the proposed knowledge-driven ecosystem, in the context of the lung cancer pilots of the EU H2020-funded project BigMedilytic, the ERA PerMed funded project P4-LUCAT, and the EU H2020 projects CLARIFY and iASiS.

Beyond the Repository

Much of the existing research about open source elects to study software repositories instead of ecosystems. An open source repository most often refers to the artifacts recorded in a version control system and occasionally includes interactions around the repository itself. An open source ecosystem refers to a collection of repositories, the community, their interactions, incentives, behavioral norms, and culture. The decentralized nature of open source makes holistic analysis of the ecosystem an arduous task, with communities and identities intersecting in organic and evolving ways. Despite these complexities, the increased scrutiny on software security and supply chains makes it of the utmost importance to take an ecosystem-based approach when performing research about open source. This article provides guidelines and best practices for research using data collected from open source ecosystems, encouraging research teams to work with communities in respectful ways.

OpenSpyrit: an ecosystem for open single-pixel hyperspectral imaging.

This paper describes OpenSpyrit, an open access and open source ecosystem for reproducible research in hyperspectral single-pixel imaging, composed of SPAS (a Python single-pixel acquisition software), SPYRIT (a Python single-pixel reconstruction toolkit) and SPIHIM (a single-pixel hyperspectral image collection). The proposed OpenSpyrit ecosystem responds to the need for reproducibility and benchmarking in single-pixel imaging by providing open data and open software. The SPIHIM collection, which is the first open-access FAIR dataset for hyperspectral single-pixel imaging, currently includes 140 raw measurements acquired using SPAS and the corresponding hypercubes reconstructed using SPYRIT. The hypercubes are reconstructed by both inverse Hadamard transformation of the raw data and using the denoised completion network (DC-Net), a data-driven reconstruction algorithm. The hypercubes obtained by inverse Hadamard transformation have a native size of 64 × 64 × 2048 for a spectral resolution of 2.3 nm and a spatial resolution that is comprised between 182.4 µm and 15.2 µm depending on the digital zoom. The hypercubes obtained using the DC-Net are reconstructed at an increased resolution of 128 × 128 × 2048. The OpenSpyrit ecosystem should constitute a reference to support benchmarking for future developments in single-pixel imaging.

New paradigms in sustainable energy systems with hydrogen

Climate change, disturbance of the energy security resulting from increasing fuel prices due to conflicts, and disruptions to production and supply chains caused by COVID-19 have highlighted the need for the world to be prepared for future challenges. The environmental and climate change impacts of heavy use of fossil fuels for energy production have yielded numerous crucial challenges and will even cause increasingly more severe effects in the years to come. This is particularly important, as the utilization of fossil fuels is the largest contributor to the increasing emissions of greenhouse gases in the atmosphere, which is leading to climate change and other problems. As a result, there is an emerging need to transition towards low or zero-emission energy systems where renewables and nuclear energy can play a critical role in the new energy equation and help establish the source ecosystem for hydrogen. Hydrogen, being the most abundant, clean, and energy-intensive element in nature, is an attractive alternative to fossil fuels. Furthermore, when produced using renewable energy sources, it is easier to reduce and control upstream emissions to produce or store hydrogen than fossil fuels. This study presents a framework for developing hydrogen technologies, building the necessary infrastructure, and selecting appropriate energy sources to help transition to a more sustainable and resilient energy system. There are also life cycle assessment studies conducted for various energy production technologies, including hydrogen, and their results are comparatively evaluated to confirm renewables and nuclear energy options would be the most suitable sources for hydrogen production. The global warming potential values of electricity production using nuclear and renewable energy are found to be 0.027 and 0.043 kg CO2 eq./kWh. Comparatively, the global warming potential for natural gas, oil and coal are found to be 0.2, 0.3 and 0.36 kg CO2 eq./kWh, respectively.

Application and technology of an open source AI large language model in the medical field

To explore the application prospects of an open source artificial intelligence (AI) large language model (LLM) in the medical field, we conducted an analysis from multiple dimensions, including the introduction of LLM, the classification of model types, and the status quo of the open source ecosystem development. The development of an open source LLM is currently in the rapid expansion phase, and there are many types of models and related tools. After analyzing the advantages and disadvantages of the models, we expounded feasible technical solutions for the application of an LLM in the medical field and made corresponding predictions. At present, LLMs in the medical field are still in the early stages, and there are still many problems related to ethics, technology, legal issues, and medical use.

Connectivity Between Russian Information Sources and Extremist Communities Across Social Media Platforms

The current military conflict between Russia and Ukraine is accompanied by disinformation and propaganda within the digital ecosystem of social media platforms and online news sources. One month prior to the conflict's February 2022 start, a Special Report by the U.S. Department of State had already highlighted concern about the extent to which Kremlin-funded media were feeding the online disinformation and propaganda ecosystem. Here we address a closely related issue: how Russian information sources feed into online extremist communities. Specifically, we present a preliminary study of how the sector of the online ecosystem involving extremist communities interconnects within and across social media platforms, and how it connects into such official information sources. Our focus here is on Russian domains, European Nationalists, and American White Supremacists. Though necessarily very limited in scope, our study goes beyond many existing works that focus on Twitter, by instead considering platforms such as VKontakte, Telegram, and Gab. Our findings can help shed light on the scope and impact of state-sponsored foreign influence operations. Our study also highlights the need to develop a detailed map of the full multi-platform ecosystem in order to better inform discussions aimed at countering violent extremism.

Co-producing industrial public goods on GitHub: Selective firm cooperation, volunteer-employee labour and participation inequality

The global economy’s digital infrastructure is based on free and open source software. To analyse how firms indirectly collaborate via employee contributions to developer-run projects, we propose a formal definition of ‘industrial public goods’ – inter-firm cooperation, volunteer and paid labour overlap, and participation inequality. We verify its empirical robustness by collecting networks of commits made by firm employees to active GitHub software repositories. Despite paid workers making more contributions, volunteers play a significant role. We find which firms contribute most, which projects benefit from firm investments, and identify distinct ‘contribution territories’ since the two central firms never co-contribute to top-20 repositories. We highlight the challenge posed by ‘Big Tech’ to the non-rival status of industrial public goods, thanks to cloud-based systems which resist sharing, and suggest there may be ‘contribution deserts’ neglected by large information technology firms, despite their importance for the open source ecosystem’s sustainability and diversity.

IEEE Solid-State Circuits Society Launches a Technical Committee to Support Open Source Ecosystem Ramp-Up [Society News

IEEE Solid-State Circuits Society Launches a Technical Committee to Support Open Source Ecosystem Ramp-Up [Society News

Cross-scale trade-off analysis for sustainable development: linking future demand for animal source foods and ecosystem services provision to the SDGs

Dietary transition towards higher consumption of animal source foods (ASF) associated with higher incomes across low and middle-income countries could have negative impacts on environmental systems and their potential in the long run to provide services necessary for achieving multiple Sustainable Development Goals (SDGs). In this article, we integrate economic, land use allocation, and biophysical models to investigate trade-offs between the five ecosystem services and their contributions to various SDGs associated with agricultural expansion to meet future demand for ASF, using Tanzania as a case study. Our results show that under the scenario of sustainable socio-economic development, between 2010 and 2030 in Tanzania, per capita income grows by 169% and the share of population at risk of hunger declines from 34.8% to 23%. These changes can be associated on a macro-level with positive contributions to achievement of SDG 1 (No Poverty) and SDG 2 (Zero Hunger). To satisfy feed demand for increased livestock production domestically, an increase by 21.4% of biomass production as compared to 2010 is needed. Analysis of alternative scenarios for meeting this new demand shows potential threats on a landscape level to achieving numerous SDGs and more generally to attaining sustainable food systems. Ecosystem-based contributions primarily decline to SDGs: SDG 3 (Health), SDG 6 (Clean Water), SDG 11 (Sustainable Cities), SDG 13 (Climate) and SDG 15 (Terrestrial Life). We find that higher crop productivity and redesign of agro-ecosystems to increase on-farm tree cover could significantly limit these losses. Alternatively, the growing demand for ASF could be satisfied with imports, which would allow for reducing the trade-offs locally. However, this would result in at least partially only displacing ecosystem service losses to the exporting countries.

Strategizing with Hardware Rich Open Source Ecosystems

Companies are increasingly adopting open source strategies to develop and exploit complex infrastructures and platforms that combine software, hardware and standard interfaces. Such strategies require the development of a vibrant ecosystem of partners that combines the innovation capabilities of hundreds of companies from different industries. Our aim is to help decision makers assess the benefits and challenges associated with creating or joining such ecosystems. We use a case study approach on six major collaborative ecosystems that enable the development of complex, high cost infrastructures and platforms. We characterize their strategy, governance, and their degree of intellectual property (IP) openness. We offer a three-dimensional framework that helps managers characterize such ecosystems. Although all the ecosystems studied aim at scaling up innovative solutions, their strategy, governance and IP openness vary. An upstream strategy aimed at replacing supplier proprietary design with open substitutes requires a democratic governance and an intellectual property policy that maximize the attractiveness of the ecosystem. A downstream strategy aimed at carving a space in new markets requires an autocratic governance and an intellectual property policy that combine attractiveness and value capture opportunities.

An open-path ammonia analyzer for eddy covariance flux measurement

Although biosphere-atmosphere exchanges of ammonia (NH3) are of great environmental importance regarding, e.g., eutrophication and aerosol-related human health problems, their magnitudes are not well constrained due to the challenges in in-situ measurements of NH3 fluxes. In this paper we introduce a portable, low-power and quantum cascade laser-based open-path analyzer for eddy covariance (EC) measurement of NH3 fluxes particularly at sites without grid power. This analyzer minimizes the sampling artifacts due to surface adsorption of NH3 by using an open-path optical Herriott cell configuration, while also increases its portability and convenience in field deployment by assembling most instrumental components in a highly integrated and compact enclosure. Its performance was tested through laboratory experiments and one-week EC measurements at a subtropical rice paddy. Its uncertainty in measuring NH3 concentration is ± 15%, being comparable to those of the currently available high-sensitivity NH3 analyzers. The flux random error averaged at 26 ± 28% during the entire experimental period. The instrumental noise of the analyzer with a sampling frequency of 10 Hz is estimated to be 0.286 and 0.302 nmol mol‒1 (ppbv) under the laboratory and field conditions, respectively. Under the given test conditions, the detection limit of the EC system is 7.1 ± 1.1 μg N m−2 h−1 for half-hourly NH3 flux measurement. Nearly 91% of the half-hourly fluxes observed during the experimental period were larger than the mean detection limit. Such instrumental sensitivity is adequate for quantifying NH3 emissions from most source ecosystems, and also possible to monitor deposition fluxes at ecosystems away from strong sources with low NH3 concentrations. Availability of this open-path NH3 analyzer provides an access to a better understanding of the biosphere-atmosphere NH3 exchanges and to a more reliable estimate of the NH3 inventory at ecosystem or larger scales.

Exploiting data from the NoiseCapture application for environmental noise measurements with a smartphone

NoiseCapture is a smartphone application initially developed as part of a participative approach for environmental noise mapping. After more than 3 years, the database produced from all over the world contributions is considerable (more than 77k contributors, nearly 300k tracks representing about 72 million 1-second measurements, in nearly 200 countries). Beyond the initial objective, other uses of the application have emerged: individually by users for their own needs, by associations of people in charge of the fight against noise pollution, within the framework of educational activities, by researchers for the realization of their own research, by communities to address the subject of noise pollution. As these new applications emerged, the development team of NoiseCapture was led to extend the possibilities of exploitation of these data. Thus, in this paper, we present different possibilities for a user to perform his own data analysis, namely: a local export of data from the smartphone, access to raw data and pre-processed data from the NoiseCapture server, access to formatted GIS layers from OGC standard service. All these methods are enabled thanks to the open source ecosystem, such as Python libraries, R software suite and GIS tools.

Ecologically Dependent Architectural Space as One of the Main Objects of Study in Higher Architectural School

The restoration of the source ecosystems lost during the urban development of the territory is due to the formation of spatial cells that are friendly to the elements of an ecosystem. Thus, education and research in sustainable architecture has to be focused on studying the principles and ways of forming an “ecologically dependent architectural space”, starting with obvious dependencies. Five levels of such a program can be as follows: 1. Principles and methods of forming a climate-oriented architectural space (entry level); 2. Architecture and renewable energy engineering systems interconnection; 3. Green systems in architecture, including city farms and algaetecture; 4. Transformable architectural forms and adaptive landscape design to the dynamics of weather and climatic conditions; 5. The specifics of architecture and urban design integrating natural ecosystems (graduate level). Graduation level main attention is focused on the study of water sensitive urban design and related concepts, as well as the concepts of renovation of the littoral marine zone. One of the obvious outcomes of experience is the need for a specialized educational program “sustainable architecture and design” in a higher architectural school.

Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation

Regulating Transformative Technology in The Quantum Age: Intellectual Property, Standardization & Sustainable Innovation

ПЕРЕДУМОВИ ЮРИДИЧНОЇ СУБ’ЄКТИВАЦІЇ ШТУЧНОГО ІНТЕЛЕКТУ

Статтю присвячено питанням визначення передумов потенційної юридичної суб’єктивації систем штучного інтелекту. Доведено, що виникли передумови наукового дослідження потенційної юридичної суб’єктивації систем штучного інтелекту. Такі передумови розкладаються на окремі групи залежно від сфери. Визначено дві групи передумов – технологічні та юридичні. З’ясовано, що до технологічних передумов відносяться розширення та глобалізація процесів виробництва програмного забезпечення та неспівпадіння «циклів існування» розробників та розроблених ними продуктів. Глобалізація процесів виробництва засобів штучного інтелекту проявляються одразу за двома напрямками – зовнішнім і внутрішнім. Відповідно до зовнішнього напрямку глобалізація виробничих процесів полягає у виходженні за межі національного та державного простору, а отже, наявності різних правових режимів створення, тестування та діяльності програмного забезпечення в окремих країнах та неможливості формування спільної колективної правосуб’єктності всього виробничо-технологічного апарату. Внутрішній напрям глобалізації реалізований з урахуванням розподілу праці та матеріальних ресурсів. До юридичних передумов запропоновано відносити фактори збільшення значимості (в тому числі юридичної) дій, що вчиняються об’єктами ШІ, та формування нового джерела регулювання даних відносин за допомогою ліцензійних угод, договорів співробітництва та звичаїв електронного ділового обороту. З’ясовано, що кількість життєвих ситуацій, що будуть зазнавати вплив дій штучного інтелекту, в майбутньому лише буде збільшуватися, в той час як їх значення буде рости, тому вже зараз необхідно дати оцінку наявним і потенційним видам поведінки, що її вчинює штучний інтелект. Доведено, що формування відносно замкненої екосистеми джерел регулювання, що активно розвивається, призвело до формування альтернативного правопорядку в мережі Інтернет та в ІТ-сфері взагалі. Такий правопорядок заснований на відносній анонімності, технологічній залежності та децентралізованому характері колективних учасників і регуляторних механізмів.

Microbial Ecology of the Planetary Boundary Layer

Aerobiology is a growing research area that covers the study of aerosols with a biological origin from the air that surrounds us to space through the different atmospheric layers. Bioaerosols have captured a growing importance in atmospheric process-related fields such as meteorology and atmospheric chemistry. The potential dissemination of pathogens and allergens through the air has raised public health concern and has highlighted the need for a better prediction of airborne microbial composition and dynamics. In this review, we focused on the sources and processes that most likely determine microbial community composition and dynamics in the air that directly surrounds us, the planetary boundary layer. Planetary boundary layer microbial communities are a mix of microbial cells that likely originate mainly from local source ecosystems (as opposed to distant sources). The adverse atmospheric conditions (i.e., UV radiation, desiccation, presence of radicals, etc.) might influence microbial survival and lead to the physical selection of the most resistant cells during aerosolization and/or aerial transport. Future work should further investigate how atmospheric chemicals and physics influence microbial survival and adaptation in order to be able to model the composition of planetary boundary layer microbial communities based on the surrounding landscapes and meteorology.