Moving beyond the ecosystem in ecosystem health report cards

The health of a software ecosystem reflects the ability of the ecosystem to endure and remain variable and productive over time. Measurements of health in a software ecosystem are applied to inform on how the ecosystem is evolving, evaluate changes, and predict future states. In this study we investigate the influence of software to the overall health of the ecosystem. We propose an approach of measuring the activity of the ecosystem over time and identifying the influence to health. We do this in two ways: (i) we study the evolution of the software network over time to identify changes in the structure of the software network and investigate whether they relate to general changes in the ecosystem. (ii) We propose the identification of the influence of the independent software components to ecosystem health at an activity level. We do so by defining keystone and dominator activities and propose tentative means of measuring them. We apply our proposed approach to the platform of the Apache Cordova ecosystem, an ecosystem with a community-based platform and independent contributions. Our analysis identifies two points in time where the ecosystem is under major change. These points are confirmed independently by both the measures of software network and keystone and dominator activities.

Using plastic products has become a daily habit of humans. Over the past 60 years, plastic production has increased ten-fold. If plastics continue to be produced and used, especially in the massive amounts as predicted, human and ecosystem health will be under threat of nano- and microplastic exposures and impacts. The impacts and risks of plastic pollution to human and ecosystem health will continue to increase if no significant action is taken to reduce the use of plastic products. Changing public thinking and human habits is not easy but doable. To tackle this long-term pollution problem, a systematic approach involving all parties including manufacturers, users, and environmental managers is needed. Enhancing education to increase knowledge, understanding, and awareness of potential ecosystem and human health impacts of plastic pollution by the public is critically important. The public can initiate actions and implement appropriate measures, when they fully understand the problem and realize that their actions could protect their health and the environment they are living in.

The Yangtze River Middle Reaches Urban Agglomeration， is a crucial city cluster in central China and plays an important role in promoting urban biodiversity conservation and sustainable development through its ecosystem health. Based on multisource remote sensing data， a comprehensive "Vigor-Organization-Resilience" model was used to systematically evaluate urban ecosystem health. Further， the geographic convergence cross-mapping （GCCM） model was employed to identify key driving factors of ecosystem health and reveal the causal relationships between ecosystem health and its drivers. The study showed that： ① Over 20 years， the ecosystem health level of the Yangtze River Middle Reaches Urban Agglomeration improved， increasing from 0.784 in 2010 to 0.801 in 2020. The overall ecosystem health was better in the northeastern and western regions compared to that in the central and southern regions， with notable differentiation. ② Based on the GCCM model， human activities and ecosystem health had a relatively stable mutual influence， while the interaction between the natural environment and ecosystem health was unstable. For human landscape indicators， GDP and POP had consistent interaction directions with EH. For natural landscape indicators， TA， MAP， HLI， NDVI， and NPP had inconsistent interaction directions with EH. ③ The GCCM model ranked the driving forces as follows： normalized vegetation index > GDP > nighttime light index > annual precipitation > average annual temperature > population density > net primary productivity. The normalized vegetation index was the most important driving factor， with GDP， nighttime light index， annual precipitation， and average annual temperature being the main driving factors， while population density and net primary productivity contributed less to ecosystem health. This study analyzes the ecosystem functions and changes in the Yangtze River Middle Reaches Urban Agglomeration， providing a scientific basis for future ecosystem management， and has significant theoretical and practical implications for sustainable urban ecosystem health governance and preventive policy formulation.

With the development of open-source technology, open-source software ecosystems (OSSECO) have been formed due to various connections between open-source projects and developers. To measure stability and sustainability, the health of an OSSECO is proposed, like the health of ecosystems in nature. Unfortunately, there are not a set of unified and mature OSSECO health evaluation rules yet, nor have effective governance methods. Existing researches mainly analyze the health of a specific open-source ecosystem or design performance indicators related to OSSECO health. This paper combines the classic OSEHO model with the rapidly developing CHAOSS open-source community metrics, establishes an OSSECO health evaluation model that can provide specific scores based on Entropy Method, and develops an open-source ecosystem health evaluation system based on the model. To the best of our knowledge, we are the first to propose a qualitative and quantitative model to show the health status of open-source ecosystems. Meanwhile, we conduct the automatic evaluation of the health of an OSSECO. Finally, we analyze the software ecosystem health of 10 open-source projects on GitHub by the established evaluation system. The result can prove the effectiveness of the system and provide data support for developers to make governance decisions.

Integrating ecosystem stress into the assessment of ecosystem health in karst areas and exploring its driving factors

Ecosystem health assessment of the Liao River Basin upstream region based on ecosystem services

Understanding the molecular mechanisms of organismal response to human-derived ecosystem change is recognised as a critical tool in monitoring and managing impacts, especially in freshwater systems. Fundamental to this approach is to determine the genes involved in responding to ecosystem change and detect modifications to their expression and activity in natural populations. Potential targets for this approach include well-known detoxification genes that are upregulated in response to stress. Here, we tested whether expression of such genes varied in association with differences in ecosystem health and could be detected in the field. We sampled populations of the freshwater midge, Cricotopus draysoni, from two geographically proximate sites in southeast Queensland, Australia, which differed in their ecosystem health, at multiple time points. We assessed transcriptome-level differential gene expression and predicted greatest differential expression between sites, associated with organismal responses to local physico-chemical factors. In contrast, we observed a clear and dramatic difference in gene expression – including of known detoxification genes – between time points, specifically between periods at the start and end of the austral summer rainfall when in-stream water levels are most different. These data suggest that these waterways experience greatest pollution load when water levels are high following rainfall events.

Environmental report cards are an increasingly widespread tool for reporting ecosystem health. In areport card, overall ecosystem health is typically presented as a grade from A to F, similar to schoolreport cards. This overall grade is a product of assessing indicators of ecosystem health, such aswater quality and biodiversity. In turn, the health of each indicator might be assessed using subindicators(e.g., water quality health might be indicated by salinity, turbidity, nutrient levels, anddissolved oxygen levels). Assessing an indicator requires setting thresholds defining what levels ofsalinity constitutes an A grade, a B grade, a C grade, and so on.When published periodically (often annually), environmental report cards are apt tools forsupporting adaptive management. Adaptive management is an iterative management approachwhereby policies are implemented, their effects monitored and evaluated, and adjusted accordingly(Walters, 2002; Holling, 1978). By periodically synthesising monitoring data, report cards can helpenvironmental managers to see changes in the environment they manage (including the effect oftheir management), and to adapt accordingly (see Harwell et al., 1999).However, current research on report cards tends to focus on the report card product (the documentconstituting the report card) or the methodology of converting raw data into grades (see Connolly etal., 2013). The process of creating a report card has not been examined in depth, at least not insofaras such processes relate to social interactions among stakeholders. And yet it is well established thatsuch social dimensions are critical to environmental and natural resource management (NRM). Inparticular, it is widely recognised that collaborative approaches can lead to better communityengagement, more empowered decision-making, the inclusion of a more diverse set of perspectives,social learning, improved social capital, and greater acceptance of decisions leading to lowered riskof destructive conflict (Whelan & Oliver, 2005; Wondolleck & Yaffee, 2000; Daniels & Walker,2001; Keen et al., 2005).This thesis aims to develop environmental report cards as a tool for the express purpose ofencouraging constructive stakeholder relationships. More specifically, it aims to develop acollaborative report card process that would encourage constructive stakeholder relationships. Thistool is the central output of the thesis. Producing this tool required two linked research components.The first component identified what factors make stakeholder relationships in NRM moreconstructive or destructive. Conducted in the Australian NRM context, a total of 26 interviews withenvironmental managers and other stakeholders yielded over 20 factors, which were categorisedinto four themes. A mental model of these factors was created (the ‘landscape’ model), as a way of helping people involved in NRM to make sense of the interplay between the factors. The findings ofthis study became an analytical framework for the second research component.The second component critically documented an existing report card process, as practiced by theIntegration & Application Network (IAN), within the University of Maryland, USA. IAN's programwas chosen firstly because its report cards are utilised globally, and secondly because itscollaborative process presented opportunities to examine whether and how it could be used toencourage constructive stakeholder relationships. IAN's process was observed over 8 months'participant–observation in 2013/14. Three US report card programs were examined as primary casestudies: Long Island Sound, Arkansas & Red Rivers (within the Mississippi River Basin), andChesapeake Bay. An additional 15 interviews were conducted with participants, funders and usersof the three case studies.Overall, the two components combined to enable IAN’s report card process to be documented andcritically examined from a relationship-building perspective. The result is a report card processdesigned specifically to encourage constructive stakeholder relationships. As report cards becomemore widespread, it is hoped that this thesis will enable them to play an expanded role – not just incommunicating monitoring data, but in navigating the complex social and political relationshipsthat make environmental management so intricate, fascinating, and rewarding.

Background: Assessing the health status of a natural ecosystem is important across all natural fields of study. Ecologists have discussed and used a variety of terms to describe the health of ecosystems, yet consistent use or adoption of a set of terms has not been established. A common vernacular is necessary to convey the status of an ecosystem to any audience, particularly to influence policy. The purpose of this review is to explore the terms associated with general ecosystem health metrics. Methods: A scoping literature review was performed within three databases, using a search string informed by place, interest, and outcome, a modified PICO (Place, Interest, Comparison, Outcome) structure. A three-stage review process was conducted, at title only, abstract, and full text, respectively. The second and third stages were conducted by two independent reviewers. Key ecosystem health indicator terms were extracted from the final article list and categorized into composite terms or individual indicators for the assessment of general ecosystem health. Results: The initial search yielded 4733 articles, of which 701 were included for screening at the abstract level. A subsequent full-text review of 118 peer-reviewed articles found 95 distinct indicators and 109 multi-metric index systems that qualify under the study search criteria from a total of 64 scientific journals over 20 years. Conclusions: We found a substantial diversity of ecological health terminologies and concepts, reflecting various scientific traditions and disciplines, which highlight not only the necessity to standardize the language for communication but also the opportunity for cross-fertilization. Single distinct indicators were as frequently used as multi-metric index systems. For academic purposes, this raises the question of how underlying value statements and ethical dimensions differ between integrated health terminologies and concepts. For advocacy, we emphasize the need of a consistent core terminology to improve the effectiveness of our messaging. One Health impact statement The impact of this work is focused on the systematic investigation of the terminology used for integrated health assessment. We carried out a scoping review of integrated ecosystem health terminology across disciplines, including 64 different journals from 2002 to 2022. This work has the potential to improve actionable policies in favor of environmental and ecosystem protection and remediation. This landscape analysis is a step toward the creation of a meaningful vocabulary of ecosystem health indicators, including how terminology descriptors and their use can be understood by different stakeholders across disciplines, with implications on the dimensions of implicit intrinsic and extrinsic value statements. By having a dedicated terminology associated with the health or disease of ecosystems in general, systems can be compared, and a simplified message can be conveyed, thereby enhancing not only the understanding of the importance of the health of ecosystems but also improving the ways in which we promote ecological health.

Land use change in urban agglomerations is gradually becoming a major cause and a key factor of global environmental change. As a consequence of the interaction between land use and ecological processes, the transformation in natural ecosystem structure and function with human activity disturbances demands a systematic assessment of ecosystem health. Taking the Central Yunnan urban agglomeration, undergoing transition and development, as an example, the current study reveals the typical land use change processes and then emphasizes the importance of spatial heterogeneity of ecosystem services in health assessment. The InVEST model-based ecosystem service assessment is incorporated into the ecosystem health evaluation, and hotspot analysis is performed to quantitatively measure the ecosystem health response degree to land use according to spatial latitude. The study had three major findings: First, the urban land expansion in the urban agglomeration of central Yunnan between 1990 and 2020 is the most significant. Further, the rate of the dynamic change of urban land is 16.86%, which is the highest among all land types. Second, the ecosystem health of the central Yunnan urban agglomeration is improving but with obvious spatial differences, showing a trend of increasing from urban areas to surrounding areas, with the lowest ecosystem health level and significant clustering in the areas where the towns are located. The ecosystem health level is mainly dominated by the two classes of ordinary and well grades, and the sum of the two accounts for 63.35% of the total area. Third, the process of land transfer, mutual transfer between forest and grassland, and conversion from cropland to forest land contributed the most to the improvement of ecosystem health across the study area. Furthermore, the conversion from cropland and grassland to urban land is an important cause of the sustained exacerbation of ecosystem health. Significantly, the study provides a scientific reference for maintaining ecosystem health and formulating policies for macro-control of land in the urban agglomerations of the mountain plateau.

An Ecosystem Health Index for a large and variable river basin: Methodology, challenges and continuous improvement in Queensland’s Fitzroy Basin

In the context of high-quality development, scientifically and objectively assessing regional ecosystem health (EH) is important for ecological civilization. However, the commonly used EH assessment framework typically neglects intrinsic connections, mutual adaptability, and coordination among interrelated indicators. The coupling coordination model was utilized to improve the classic pressure–state–response assessment (PSR) model. The carbon footprint, water footprint, landscape pattern, and response status of the Manas River Basin were used to construct a medium-scale regional EH assessment framework linking natural ecosystems with human socioeconomic elements. A quantitative assessment was conducted on the EH conditions of the Manas River Basin from 2000 to 2020. Over the past 21 years, the EH conditions of the Manas River Basin have fluctuated upward. The ecosystem health index (EHI) increased from 0.18 to 0.37. Compared with the conventional PSR model, the coupling coordination pressure–state–response model (CC–PSR) better reflected the fluctuations in EH conditions caused by “pressure”, “state”, and “response” level changes. In the early stage (2000–2006), increasing human activity strongly pressured the regional ecosystem, limiting EH improvements. The increase in “pressure” was reflected in the increasing trends of the water footprint, carbon footprint, and ecological footprint. During the middle to late period (2009–2020), as the “response” level improved, the regional EH condition continued to increase, and the EHI stabilized between 0.29 and 0.38. Ecosystem resilience improvements and human afforestation projects enhanced the “response” level, but their impacts were noticeably delayed. Over the past 21 years, regional landscape diversity, landscape connectance, and landscape contagion have remained high. The well-maintained landscape pattern has laid the foundation for consolidating and improving the regional EH. The EHI is increasing; its fluctuations stem from periodic fluctuations in the regional water yield and carbon sequestration capacity, which are constrained by the basin climate and vegetation coverage. This study provides a scientific model for basin EH assessment.

Summary1. Stream ecosystem health monitoring and reporting need to be developed in the context of an adaptive process that is clearly linked to identified values and objectives, is informed by rigorous science, guides management actions and is responsive to changing perceptions and values of stakeholders. To be effective, monitoring programmes also need to be underpinned by an understanding of the probable causal factors that influence the condition or health of important environmental assets and values. This is often difficult in stream and river ecosystems where multiple stressors, acting at different spatial and temporal scales, interact to affect water quality, biodiversity and ecosystem processes.2. In this article, we describe the development of a freshwater monitoring programme in South East Queensland, Australia, and how this has been used to report on ecosystem health at a regional scale and to guide investments in catchment protection and rehabilitation. We also discuss some of the emerging science needs to identify the appropriate scale and spatial arrangement of rehabilitation to maximise river ecosystem health outcomes and, at the same time, derive other benefits downstream.3. An objective process was used to identify potential indicators of stream ecosystem health and then test these across a known catchment land‐use disturbance gradient. From the 75 indicators initially tested, 22 from five indicator groups (water quality, ecosystem metabolism, nutrient cycling, invertebrates and fish) responded strongly to the disturbance gradient, and 16 were subsequently recommended for inclusion in the monitoring programme. The freshwater monitoring programme was implemented in 2002, funded by local and State government authorities, and currently involves the assessment of over 120 sites, twice per year. This information, together with data from a similar programme on the region’s estuarine and coastal marine waters, forms the basis of an annual report card that is presented in a public ceremony to local politicians and the broader community.4. Several key lessons from the SEQ Healthy Waterways Programme are likely to be transferable to other regional programmes aimed at improving aquatic ecosystem health, including the importance of a shared common vision, the involvement of committed individuals, a cooperative approach, the need for defensible science and effective communication.5. Thematic implications: this study highlights the use of conceptual models and objective testing of potential indicators against a known disturbance gradient to develop a freshwater ecosystem health monitoring programme that can diagnose the probable causes of degradation from multiple stressors and identify the appropriate spatial scale for rehabilitation or protection. This approach can lead to more targeted management investments in catchment protection and rehabilitation, greater public confidence that limited funds are being well spent and better outcomes for stream and river ecosystem health.

Transitioning from change detection to monitoring with remote sensing: A paradigm shift

With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development.