Individual-Inclusive Ecosystem Model of Rehabilitation for Inclusion of Children with Disabilities in Childcare Institutions

In childcare institutions (CCIs) in India, children with mild or moderate levels of disability are often placed with non-disabled children for care and protection. Generally, children with intellectual disability (ID), learning disability, hearing and speech impairment and multiple disabilities with ID are found to be living in these CCIs. In this best practice article, the challenges faced by these children with disabilities and the potential for inclusion within the CCI are discussed based on the field action project intervention of the Tata Institute of Social Sciences (TISS), Mumbai, with selected government CCIs. The article suggests a multi-pronged intervention approach for the Children with disability (CWD) at the levels of the individual CWD, peer group, CCI and the juvenile justice (JJ) System, which are together recognised as the stakeholders of an ‘inclusive ecosystem’. The article arrives at the ‘Inclusive Ecosystem Model of Rehabilitation’ by drawing from the individual–environment interaction model of disability.

Carbon variation of dry grasslands in Central Asia in response to climate controls and grazing appropriation

Quantification of grassland carbon (C) variations is necessary for understanding how grazing and climate change interact to regulate carbon capture and release. Central Asia (CA) has the largest temperate grassland belt in the world and unique temperate dryland ecosystems, which experienced severe climate change and grazing-induced disturbances. However, the impact of grazing on C dynamics is highly uncertain owing to climate variations. Here, an arid ecosystem model (AEM) supplemented with a grazing module that specifically addressed physiological and ecological characteristics of dryland vegetation was developed to quantitatively simulate grassland C dynamics in response to changes in precipitation, temperature, grazing intensity, and CO2 level in the past decades. The regional simulation results showed that net primary productivity (NPP) was affected mainly by precipitation (in 59% of the studied area). Grazing had a negative effect on NPP and C stocks, whereas overcompensation occurred in 25.71% of the studied area, mainly in the dry western parts. The complex interaction effects of climate, CO2, and grazing negatively affected productivity, with a grassland NPP decrease of − 1.14 g C/m2/a and high interannual variability. We found that the temporal pattern of cumulative C sequestration, especially total C and vegetation C (VEGC), closely followed the annual fluctuations of precipitation. VEGC stocks decreased from 182.22 to 177.82 g C/m2, with a very low value between 1998 and 2008, when precipitation significantly decreased. The results indicate that southern Xinjiang and the Turgay Plateau of Kazakhstan are ecologically fragile areas due to grassland degradation.

Factors Influencing the Interannual Variation in Biomass of Bottom-Cultured Yesso Scallop (Patinopecten yessoensis) in the Changhai Sea Area, China

Understanding how environmental factors impact the interannual variation in scallop growth and subsequently developing an easily obtained parameter to indicate this variation could provide a scientific basis for optimizing their aquaculture. In this study, we have set a growth scenario of uniformly sowed scallops of the same initial size in the Changhai sea area. The Yesso scallop culture ecosystem model was used to simulate the growth of bottom-cultured Yesso scallop each year from December 1, 2006 to November 30, 2017. The results show that the annual growth rate was higher in the northwest than in the southeast, and there were obvious high-value areas near the islands. The scallop biomass was significantly lower in 2009–2010 and reached its highest point in 2013–2014. Based on the match-mismatch conditions of bottom-water temperature, food availability, and the Yesso scallop growth process, three factors were determined: suitable growth days (SGD), restricted growth days (RGD), and food accumulation (FA). Subsequently, a multiple regression relationship was proposed with scallop biomass to explore the reasons affecting the interannual variations in scallop growth. We found that the anomaly of the contribution of SGD and FA for the scallop growth was small, and the interannual variation in scallop biomass was mainly regulated by RGD in winter. Our results indicated that the interannual variation in RGD in winter was closely related to the regional averaged air temperature in early winter. The air temperature in early winter is easily obtained in practice. Consequently, it could be used to predict the interannual growth of bottom-cultured scallops to improve aquaculture planning and management.

Adaptive time step algorithms for the simulation of marine ecosystem models using the transport matrix method implementation Metos3D (v0.5.0)

The reduction of the computational effort is desirable for the simulation of marine ecosystem models. Using a marine ecosystem model, the assessment and the validation of annual periodic solutions (i.e., steady annual cycles) against observational data are crucial to identify biogeochemical processes, which, for example, influence the global carbon cycle. For marine ecosystem models, the transport matrix method (TMM) already lowers the runtime of the simulation significantly and enables the application of larger time steps straightforwardly. However, the selection of an appropriate time step is a challenging compromise between accuracy and shortening the runtime. Using an automatic time step adjustment during the computation of a steady annual cycle with the TMM, we present in this paper different algorithms applying either an adaptive step size control or decreasing time steps in order to use the time step always as large as possible without any manual selection. For these methods and a variety of marine ecosystem models of different complexity, the accuracy of the computed steady annual cycle achieved the same accuracy as solutions obtained with a fixed time step. Depending on the complexity of the marine ecosystem model, the application of the methods shortened the runtime significantly. Due to the certain overhead of the adaptive method, the computational effort may be higher in special cases using the adaptive step size control. The presented methods represent computational efficient methods for the simulation of marine ecosystem models using the TMM but without any manual selection of the time step.

Modeling polar marine ecosystem functions guided by bacterial physiological and taxonomic traits

Heterotrophic marine bacteria utilize organic carbon for growth and biomass synthesis. Thus, their physiological variability is key to the balance between the production and consumption of organic matter and ultimately particle export in the ocean. Here we investigate a potential link between bacterial traits and ecosystem functions in the rapidly warming West Antarctic Peninsula (WAP) region based on a bacteria-oriented ecosystem model. Using a data assimilation scheme, we utilize the observations of bacterial groups with different physiological traits to constrain the group-specific bacterial ecosystem functions in the model. We then examine the association of the modeled bacterial and other key ecosystem functions with eight recurrent modes representative of different bacterial taxonomic traits. Both taxonomic and physiological traits reflect the variability in bacterial carbon demand, net primary production, and particle sinking flux. Numerical experiments under perturbed climate conditions demonstrate a potential shift from low nucleic acid bacteria to high nucleic acid bacteria-dominated communities in the coastal WAP. Our study suggests that bacterial diversity via different taxonomic and physiological traits can guide the modeling of the polar marine ecosystem functions under climate change.

Trophic interactions with heterotrophic bacteria limit the range of Prochlorococcus

Prochlorococcus is both the smallest and numerically most abundant photosynthesizing organism on the planet. While thriving in the warm oligotrophic gyres, Prochlorococcus concentrations drop rapidly in higher-latitude regions. Transect data from the North Pacific show the collapse occurring at a wide range of temperatures and latitudes (temperature is often hypothesized to cause this shift), suggesting an ecological mechanism may be at play. An often used size-based theory of phytoplankton community structure that has been incorporated into computational models correctly predicts the dominance of Prochlorococcus in the gyres, and the relative dominance of larger cells at high latitudes. However, both theory and computational models fail to explain the poleward collapse. When heterotrophic bacteria and predators that prey nonspecifically on both Prochlorococcus and bacteria are included in the theoretical framework, the collapse of Prochlorococcus occurs with increasing nutrient supplies. The poleward collapse of Prochlorococcus populations then naturally emerges when this mechanism of “shared predation” is implemented in a complex global ecosystem model. Additionally, the theory correctly predicts trends in both the abundance and mean size of the heterotrophic bacteria. These results suggest that ecological controls need to be considered to understand the biogeography of Prochlorococcus and predict its changes under future ocean conditions. Indirect interactions within a microbial network can be essential in setting community structure.

Innovative Ecosystem Model of Vaccine Lifecycle Management

The COVID-19 pandemic has severely tested humanity, revealing the need to develop and improve the medical, economic, managerial, and IT components of vaccine management systems. The vaccine lifecycle includes vaccine research and development, production, distribution, and vaccination of the population. To manage this cycle effectively the proper organizational and IT support model of the interaction of vaccine lifecycle management stakeholders is needed—which are an innovation ecosystem and an appropriate virtual platform. A literature review has revealed the lack of methodological basis for the vaccine innovation ecosystem and virtual platform. This article is devoted to the development of a complex approach for the development of an innovation ecosystem based on vaccine lifecycle management and a virtual platform which provides the data exchange environment and IT support for the ecosystem stakeholders. The methodological foundation of the solution, developed in the article, is an enterprise architecture approach, CALS technologies, supply chain management and an open innovation philosophy. The results, presented in the article, are supposed to be a reference set of models for the creation of a vaccine innovation ecosystem, both during pandemics and periods of stable viral load.

Digital Wallet Ecosystem in Promoting Financial Inclusion

Digital wallet is expanding largely driven by the evolution of internet and smartphone penetration. Numerous digital wallet providers have risen in many countries including Brunei Darussalam. However, the level of adoption is still low, and cashless society is still far from an expected target. There's no magic formula in deploying a guaranteed successful digital wallet, but developing a digital wallet ecosystem that is tailored to the local markets will be expected to increase digital culture and cashless society. The research assesses the existing digital wallet ecosystem, then analyses the extent of compatibility of local market demand. Furthermore, it introduces an improved digital wallet ecosystem model in order to support financial inclusion achieved through a holistic digital wallet ecosystem. The chapter also examines external factors that contribute to the digital wallet ecosystem's width of usage.

Scientific Community-Driven Ecosystem as a Supporter to Co-Create and Co-Evolute Science

One critical aspect of science is the ability to reproduce the same experiment by another researcher. In other to do so, the same ambient, variables, data, setup should be considered. The method tells how the original researcher planned and did their research, but how can others replicate or even advance the preview research? The scientific community has been focusing on efforts to increase transparency and reproducibility and develop a “culture of reproducibility.” When researchers share their data, their workflow, and co-evolute a way of doing research, all the players win. The value co-creation is established in a business ecosystem. The actor who is part of the business platform by the co-creation can leverage the advantage of one or more partners that make up the platform. Thus, the knowledge created from the interaction between the different technological domains and knowledge shared on the platform can improve all the research and researchers. Stating that, this chapter proposes a business ecosystem model to ensure research repeatability.