High-level Resource Research Articles

The direct and indirect impacts of transformational leadership on employee change-oriented organizational citizenship behavior

The purpose of this study is to investigate the relationship between transformational leadership (TL) and change-oriented organizational citizenship behavior (OCB) based on basic assumptions of the job demand-resource (JD-R) model, social exchange theory (SET), and behavioral plasticity theory (BPT). In addition, this study explores the role of the organizational level of resources and individual level of resources on employee wellbeing and attitudes. Based on 698 responses from Jordanian insurance employees, the mediating role of employee wellbeing and the moderating role of core self-evaluation (CSE) were investigated between TL and change-oriented OCB. Data were analyzed based on multiple regression, hierarchical regression, and macro process plugin. The results indicate that transformational leadership is positively related to change-oriented OCB, and this relationship is mediated by employee wellbeing. Moreover, moderated path analysis shows that the positive CSE strengthens the direct effect of TL on employee wellbeing and work attitude, as well as the indirect impact of TL on employee work attitude. The results also suggest that organizational level of support is a critical factor for enhancing employee wellbeing and change-oriented OCB, and this support is more powerful with a high level of personal resources (i.e., positive CSE). The research model provided in this study is the first framework that suggests the mediating effect of employee wellbeing on the direct relationship between TL and change-oriented OCB, as well as the moderating effect of CSE on this indirect relationship.

Transcending the Corporeal in Later Old Age?

This symposium addresses the older body and later life. It focusses on the cultural and social implications of the corporeality of the ageing body. Specifically it seeks to explore the degree to which it is possible to transcend the constraints brought about by the body in later old age. Drawing the distinction between the third and fourth ages for understanding contemporary ageing the papers address three important dimensions of later old age. The first presentation by Gilleard directly addresses the corporeality of late old age noting its seeming undesirability and limitation. Gilleard posits that not only does the ageing body impact on the lived experiences of those in later old age but also acts as a cultural reference point for the representation of this period of the life course. Eliopoulos presents preliminary results from her qualitative study on social exclusion of individuals aged over 80 living in remote island environments of the Pacific Northwest. The research considers how such environments might, even in the absence of high levels of health and social care resources, mitigate some of the constraints associated with the ageing body. The chair, Paul Higgs will discuss the issue of ageism and how it is abstractly inscribed on the ageing body; often with little reference to the lived experiences of older people themselves. He will call for a more reflexive approach to ageism. Overall, the symposium seeks to draw gerontological attention to the complexities and possibilities surrounding the ageing body at later ages.

Harnessing Trichoderma in Agriculture for Productivity and Sustainability

Increased agricultural activities driven by rising food demand have led to environmental problems mostly arising from the high levels of external inputs and resources that are required. Additionally, environmental changes, such as global warming, can lead to various biotic and abiotic stresses, which have negative impacts on crop production. Numerous solutions and agricultural strategies have been introduced to overcome these problems. One of the ways to improve plant production as well as to increase resistance towards biotic and abiotic stresses is by utilizing beneficial microbes as soil inoculants. A better understanding of the ability of Trichoderma to enhance crop production and the mechanisms that are involved are important for deriving maximum benefits from their exploitation. These versatile fungi hold great promise for the development of viable commercial products that can be used widely in agriculture for increasing crop productivity in a more sustainable way. Many previous reviews on Trichoderma have tended to focus on the mechanisms of Trichoderma in enhancing plant growth and yield. This current review discusses the sustainability aspect of using Trichoderma as plant growth regulators, the impact on plant growth and yield as well as their effects in regulating biotic and abiotic stresses.

Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model

BackgroundSustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended—SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding.MethodsResearch was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx—Microsoft Research’s Bayesian Network Authoring and Evaluation Tool.ResultsDue to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks.ConclusionTesting of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.

Optimization of the distance-constrained multi-based multi-UAV routing problem with simulated annealing and local search-based matheuristic to detect forest fires: The case of Turkey

Forests cover nearly a third of the Earth’s land area, and they are a key factor for all life on Earth, but unfortunately, forest fires are the greatest danger to their presence. The wildfires jeopardize general wellbeing, security, and require high levels of government resources. They also lead to noteworthy debasement of nature, property loss, and high rates of human death and injury. This paper proposes an algorithm to use and route unmanned aerial vehicles (UAVs) to mitigate forest fire risks. The developed matheuristic algorithm hybridizes simulated annealing and local search metaheuristics with an integer linear programming model. The mathematical model was developed to solve the distance-constrained multi-based multi-UAV routing problem, and because of the complexity of the problem, the generated metaheuristics helps the model to find better solutions. The effectiveness of the proposed matheuristic is tested with a real-life case study for Turkey and is also compared with a genetic algorithm. The Turkish State Meteorological Service generates forest fire-risk maps countrywide every day to predict fire risks 3 days later by using meteorological data. These maps are used to generate the risky regions to be visited by the UAVs, and the existing airports are considered for the UAVs to take off and land. The algorithm is coded using MATLAB and ILOG. The metaheuristics are designed with problem-based operators, and their parameters are tuned by experiments. Computational results demonstrate the effectiveness of the algorithm and the hybridization procedures. Results demonstrate that the CPU times for the methods are acceptable.

Enabling In-Depot Automated Routing and Recharging Scheduling for Automated Electric Bus Transit Systems

The bus transit system is promising to enable electric and autonomous vehicles for massive urban mobility, which relies on high-level automation and efficient resource management. Besides the on-road automation, the in-depot automated scheduling for battery recharging has not been adequately studied yet. This paper presents an integrated in-depot routing and recharging scheduling (IDRRS) problem, which is modeled as a constraint programming (CP) problem with Boolean satisfiability conditions (SAT). The model is converted to a flexible job-shop problem (FJSP) and is feasible to be solved by a CP-SAT solver for the optimal solution or feasible solutions with acceptable performance. This paper also presents a case study in Shanghai and compares the results from the FJSP model and the first-come first-serve (FCFS) method. The result demonstrates the allocation of routes and chargers under multiple scenarios with different numbers of chargers. The results show that the FJSP model shortens the delay and increases the time conservation for future rounds of operation than FCFS, while FCFS presents the simplicity of programming and better computational efficiency. The multiple random input test suggests that the proposed approach can decide the minimum number of chargers for stochastic charging requests. The proposed method can conserve the investment by increasing the utilization of automated recharging devices, improving vehicles’ in-depot efficiency.

MBA Internalization at Selected Elite Business Schools: Challenges of Geographic Dispersion and Coordination

EXECUTIVE SUMMARY The purpose of this manuscript is to develop a taxonomy for the governance of elite business schools based on two factors: (i) their geographic dispersion and (ii) the coordination between the main campus, international branch campuses, research centers, and other business schools. The research question that drives this manuscript is: Are there different types of governance for elite business schools based on differences in the geographic dispersion and the coordination of other units? The paper contributes to the business school´s internationalization efforts because the research shows a dominant form of governance, the Center of Excellence (CoE). However, the dynamic context of business schools allows three different paths for their internationalization. First, from the CoE to Alliance, schools gradually cooperate with other programs to compete globally. Second, from the CoE to Ecosystem, that occurs when programs grow organically. Third, from the CoE to the Center of Gravity governance; in this case, the CoE moves toward a high level of resources while keeping complexity low because of the lack of interfaces between the business school and other institutions. Finally, some business schools show ambidexterity regarding the governance of their units and subsidiaries.

Systems science for developing policy to improve physical activity, the Caribbean

The World Health Organization (WHO) Global Action Plan on Physical Activity recommends adopting a systems approach to implementing and tailoring actions according to local contexts. We held group model-building workshops with key stakeholders in the Caribbean region to develop a causal loop diagram to describe the system driving the increasing physical inactivity in the region and envision the most effective ways of intervening in that system to encourage and promote physical activity. We used the causal loop diagram to inform how the WHO Global Action Plan on Physical Activity might be adapted to a local context. Although the WHO recommendations aligned well with our causal loop diagram, the diagram also illustrates the importance of local context in determining how interventions should be coordinated and implemented. Some interventions included creating safe physical activity spaces for both sexes, tackling negative attitudes to physical activity in certain contexts, including in schools and workplaces, and improving infrastructure for active transport. The causal loop diagram may also help understand how policies may be undermined or supported by key actors or where policies should be coordinated. We demonstrate how, in a region with a high level of physical inactivity and low resources, applying systems thinking with relevant stakeholders can help the targeted adaptation of global recommendations to local contexts.

Not All Demands Are Exhausted for Healthcare Workers. A Cross-Lagged Study on the Buffering Effect of Leadership Resources

This study investigated the cross-lagged effects of a three job demands on exhaustion and buffering function of leadership resources among Polish healthcare workers. Job demands include quantitative and two emotional (related to engaging in the patient’s personal problems and related to hiding emotions) demands, while leadership resources include quality of leadership and trust in management. The study was conducted in two waves (both of them in COVID-19 pandemic), with a one-year interval between the measurements. Data were collected among 1251 healthcare workers. A moderated regression analysis showed that quantitative demands and demands for hiding emotions (T1 but not emotionally engagement in the patient’s personal problems) were related to high exhaustion (T2). Both leadership resources (T1) diminished the negative impact of quantitative (not emotional) demands on exhaustion, but the buffering effect of trust was stronger. Furthermore, the two leadership resources interact with each other and together neutralize the effects of quantitative demands. Specifically, the lowest level of exhaustion was observed in those healthcare workers who had high levels of both resources, measured one year before. The implications for theory and research on the effects of different job demands on exhaustion in pandemic are discussed.

Transmission line protection algorithm based on voltage sequence component under high penetration of inverter-based resources

• Protection challenges under high penetration of inverter-based resources • A novel protection algorithm is proposed which uses voltage sequence components to identify faulty events occurrence in transmission line network. • The proposed protection algorithm reliability has been investigated under different network's impacts. • The proposed protection algorithm sensitivity is tested on a big transmission network under different contingency scenarios. A new protection algorithm based on sequence voltage components is proposed in this paper. The new algorithm helps overcome the sensitivity and maloperation issues of the traditional protection schemes in the transmission line network, especially with a high penetration level of inverter-based resources. In this algorithm, the differential fault sequence components are used to identify faulty events in the transmission network. The fault voltage component across the protected line is compared to a setting value of multiple parameters-based voltage makes the final decision of tripping for internal faults only. The proposed algorithm has been tested on a 400kV, 50 Hz single circuit transmission line network supplied with a mix of 90% wind turbines and 10% synchronous generators. The new algorithm simulation testing showed high accuracy when it comes to rapid trip activation with high discrimination reliability between internal and external events. High impedance with different fault locations has been tested to improve the proposed algorithm reliability. The study also performed on the IEEE 9-bus system to validate the proposed algorithm under various faults when strong and weak infeed performed into a bigger transmission network.

Using Forecasting Methods to Incorporate Social, Economic, and Political Considerations Into Marine Protected Area Planning

As the global environmental crisis grows in scale and complexity, conservation professionals and policymakers are increasingly called upon to make decisions despite high levels of uncertainty, limited resources, and insufficient data. Global efforts to protect biodiversity in areas beyond national jurisdiction require substantial international cooperation and negotiation, both of which are characterized by unpredictability and high levels of uncertainty. Here we build on recent studies to adapt forecasting techniques from the fields of hazard prediction, risk assessment, and intelligence analysis to forecast the likelihood of marine protected area (MPA) designation in the Southern Ocean. We used two questionnaires, feedback, and a discussion round in a Delphi-style format expert elicitation to obtain forecasts, and collected data on specific biophysical, socioeconomic, geopolitical, and scientific factors to assess how they shape and influence these forecasts. We found that areas further north along the Western Antarctic Peninsula were considered to be less likely to be designated than areas further south, and that geopolitical factors, such as global politics or events, and socioeconomic factors, such as the presence of fisheries, were the key determinants of whether an area was predicted to be more or less likely to be designated as an MPA. Forecasting techniques can be used to inform protected area design, negotiation, and implementation in highly politicized situations where data is lacking by aiding with spatial prioritization, targeting scarce resources, and predicting the success of various spatial arrangements, interventions, or courses of action.

Apprentices’ Resources at Work and School in Switzerland: A Person-Centred Approach

Context: Providing learners with quality resources at work and school is a key element of apprenticeships and is essential for developing vocational competencies and successful vocational careers. Drawing on previous research on situational and personal resources, we first explored work-related and school-related resource profiles of apprentices’ learning environments. We further analysed how core self-evaluations are linked to resource profiles and examined whether learners’ apprenticeship satisfaction and occupational commitment varied according to the resource profiles.Approach: We used latent profile analysis and multinomial logistic regressions, applying an integrative, person-centred approach. Our data came from the Swiss longitudinal study "Transition from Education to Employment" (TREE). The sample consisted of 1,185 apprentices enrolled in the second year of their apprenticeship.Findings: We found four profiles of situational resources (e.g., instruction quality, climate, learning opportunities, autonomy, and demands) at the two learning locations. The profiles embodied different patterns and levels of situational resources. Two profiles were characterised by overall high or average levels of situational resources at both learning locations; the other two illustrated a stark contrast between the resources provided in the workplace and at school. Learners with higher core self-evaluations were more likely to be in profiles with higher situational resources. Apprentices in more beneficial profiles were more satisfied with their apprenticeships and more committed to their occupations than those in profiles with lower resources.Conclusion: The results confirm the importance of providing apprentices with challenging, empowering, and supportive learning environments in the workplace and at vocational schools. To support learning and positive career development in apprenticeships, educators should strengthen learners’ core self-evaluations to empower them to shape their learning according to their needs.

Spectral spatial joint feature based convolution neural network for hyperspectral image classification

AbstractHyperspectral sensor generates huge datasets which conveys abundance of information. However, it poses many challenges in the analysis and interpretation of these data. Deep networks like VGG16, VGG19 are difficult to directly apply for hyperspectral image (HSI) classification because of its higher number of layers which in turn requires high level of system resources. This article suggests a novel framework with lesser number of layers for hyperspectral image classification (HSIC) that takes into account spectral‐spatial context sensitivity of HSI, which focuses on enhancing the discriminating capability of HSIC. The model uses available spectral feature as well as spatial contexts of HSI and consecutively learn the distinctive features. A small training set has been used to optimize the network parameters while the overfitting problem is alleviated using the validation set. Regularization has been performed using batch normalization (BN) layer after each convolution layer. The cost of the model is measured in terms of training and testing time duration under the same platform, which has further been compared with some ensemble learning methods, SVM and other three recent state‐of‐the‐art methods. Experimental results establish that the proposed model performs very well with the three benchmark datasets: Indian Pines, Salinas and University of Pavia, which mostly contain land cover of agriculture, forest, soil, rural, and urban area.

Victorious and Hierarchical: Past Success as a Determinant of Team Hierarchical Differentiation

Hierarchies emerge as collectives attempt to organize toward successful performance. Consequently, research has focused on how hierarchies affect team performance. We adopt a different perspective: performance is not only an output of hierarchy, but also a critical input – teams’ hierarchies may dynamically vary based on whether they are succeeding. Integrating research on exploitation and exploration with work on group attributions, we argue that teams engage in exploitation by committing resources to what they attribute as the cause of their success. Specifically, collectives tend to attribute their success to individuals who held greater influence within the team, and these individuals are subsequently granted relatively high levels of resources, leading to a high degree of hierarchy. We additionally suggest this tendency to attribute, and therefore commit resources, to members believed to be the cause of success is stronger for teams previously high (vs. low) in hierarchy, since a high degree of hierarchal differentiation provides clarity about which members had greater impact over the team outcome. We test our hypotheses experimentally with teams engaging in an online simultaneous game and with archival data from the National Basketball Association. Overall, our work highlights that performance is not only an output of hierarchy, but also serves as a critical input that affects how teams actively and dynamically shape their hierarchy.

Growth and flowering responses of eelgrass to simulated grazing and fecal addition by Brant Geese

AbstractSeagrasses provide a wide range of ecosystem services and are prioritized in conservation planning. Management of this dynamic community requires describing seagrass responses to repeated grazing by dependent herbivores. Using two experimental randomized block designs in Humboldt Bay, California, we tested responses of eelgrass (Zostera marina) to separate and combined effects of simulated Brant Goose (Branta bernicla) grazing (clipping to a uniform height) and fecal pellet addition, and then to medium (MED) and severe (SEV) intensities of simulated Brant flock visitation. In Experiment 1, clipping with fecal addition (FC) stimulated more clonal addition of shoots than controls or clipping and fecal addition alone (standardized β = 0.26 relative to control). The FC treatment also had the largest positive, delayed effect (β = 0.135) on density of flowering shoots. In Experiment 2, the MED intensity treatment had positive effects on shoot density (β = 0.149), rates of leaf extension (β = 0.16), and leaf productivity (β = 0.20). These MED treatment responses resulted in the highest measures of above‐ground (β = 0.099) and below‐ground (β = 0.32) biomass. Whole shoot (βMED = 0.33, βSEV = −0.36) and landscape (βMED = 0.34, βSEV = −0.23) levels of productivity for the MED treatment reflected the parabolic shape predicted by the compensatory regrowth hypothesis, likely because light and nutrient resources were available to the eelgrass and meristems that were not damaged. Meristem injury in the SEV treatment likely explained why productivity was low, but the high SEV resource levels allowed these plants to recover to control levels in approximately eight to 10 weeks after the last treatment applications. The MED level of shoot and landscape productivity would optimize low intertidal accessibility for Brant to the most nutritiously valuable leaves. Brant grazing and detrital pathways of carbon flow are likely linked with Brant‐induced productivity contributing to the detrital pathway when Brant are present and after the birds leave the estuary. The effect of Brant grazing on eelgrass sexual reproduction may increase long‐term resilience of estuarine ecosystems.

Simple Mobile technology health management tool for people with severe mental illness: a randomised controlled feasibility trial

BackgroundSevere mental illness (SMI) is associated with care delivery problems because of the high levels of clinical resources needed to address patient’s psychosocial impairment and to support inclusion in society. Current routine appointment systems do not adequately foster recovery care and are not systematically capturing information suggestive of urgent care needs. This study aimed to assess the feasibility, acceptability, and potential clinical benefits of a mobile technology health management tool to enhance community care for people with severe mental illness.MethodsThis randomised-controlled feasibility pilot study utilised mixed quantitative (measure on subjective quality of life as primary outcome; questionnaires on self-management skills, medication adherence scale as secondary outcomes) and qualitative (thematic analysis) methodologies. The intervention was a simple interactive technology (Short Message Service - SMS) communication system called ‘Florence’, and had three components: medication and appointment reminders, daily individually defined wellbeing scores and optionally coded request for additional support. Eligible participants (diagnosed with schizophrenia, schizoaffective disorder or bipolar disorder ≥1 year) were randomised (1:1) to either treatment as usual (TAU, N = 29) or TAU and the technology-assisted intervention (N = 36).ResultsPreliminary results suggest that the health technology tool appeared to offer a practicable and acceptable intervention for patients with SMI in managing their condition. Recruitment and retention data indicated feasibility, the qualitative analysis identified suggestions for further improvement of the intervention. Patients engaged well and benefited from SMS reminders and from monitoring their individual wellbeing scores; recommendations were made to further personalise the intervention. The care coordinators did not utilise aspects of the intervention per protocol due to a variety of organisational barriers. Quantitative analysis of outcomes (including a patient-reported outcome measure on subjective quality of life, self-efficacy/competence and medication adherence measures) did not identify significant changes between groups over time in favour of the Florence intervention, given high baseline scores. The wellbeing scores, however, were positively correlated with all outcome measures.ConclusionIt is feasible to conduct an adequately powered full trial to evaluate this intervention. Inclusion criteria should be revised to include patients with a higher level of need and clinicians should receive more in-depth assistance in managing the tools effectively. The preliminary data suggests that this intervention can aid recovery care and individually defined wellbeing scores are highly predictive of a range of recovery outcomes; they could, therefore, guide the allocation of routine care resources.Trial registrationISRCTN34124141; retrospectively registered, date of registration 05/11/2019.

Forest and Forestry in Tanzania: Changes and Continuities in Policies and Practices From Colonial Times to the Present

The forest sector has a very important role to play in Tanzania’s economy. Although in absolute terms, their contribution to total gross domestic product (GDP) is relatively low, the country’s forests contain such a high level of resources that make Tanzania one of the richest and most bio-diverse countries. Due to such importance, forestry has variably featured in Tanzanian policies from colonial times to the present. This paper, therefore, examines such policies relating to forests and forestry in Tanzania from colonial to recent times. It argues that, although there has been a change in the approach from a preservationist approach in the colonial andpostcolonial period towards a managerial/win-win approach in the current forest conservation, there is a resurgence of the preservationist tendency inthe focus on managing forest solely to increase carbon stocks. Drawing evidences from various existing policy documents and other literature, this paper concludes that forestry policies have been, and continue to reveal a notable protectionist and reservationist propensity while also expecting revenues from them through various forest products. These policies, to a ngreater extent, have throughout resulted into conflicts between both colonial and post-colonial states and local population who demands free access to theforest resources for their survival.

Interest in and uptake of genetic counseling for preconception carrier screening when offered to predominantly white reproductive-age persons seeking gynecologic care at a single U.S. academic medical center.

The objective of this study was to assess the level of interest in preconception carrier screening among reproductive-aged persons presenting for gynecologic care and to identify demographic factors predictive of pursuing screening. Patients aged 18-40 who were presenting for gynecologic care at a single U.S. academic medical center were provided with information about current options for preconception carrier screening and were offered genetic counseling referral with the possibility to undergo screening. Outcomes of interest were desire for genetic counseling referral and attendance at genetic counseling visit. Statistical analyses were performed as appropriate using R version 3.6.1 with variables significant at 0.1 included in a multivariable logistic regression. Of 193 participants, 79 (41%) desired genetic counseling referral. Participants aged 25-34 (OR 3.39, 95% CI 1.47-8.10) and nulliparas (OR 2.69, 95% CI 1.23-6.03) were more likely to desire referral. Thirty-five participants (44.3% of those who desired referral) attended a visit with genetic counseling. Having an advanced degree (OR 3.27, 95% CI 1.06-10.4) was associated with visit attendance. Thirteen participants underwent screening, and five were found to be a carrier of at least one X-linked or autosomal recessive condition. Surprisingly, presenting for a gynecologic visit directly related to planning a pregnancy was not associated with increased interest in preconception carrier screening. Nulliparas and those aged 25-34 likely expressed greater interest in referral due to high potential for future childbearing in these groups. The increased level of visit attendance in participants with advanced degrees is likely confounded by the high level of health literacy and financial resources in this group.

A stochastic model of epilithic algal succession and patch dynamics in streams

AbstractExplaining spatiotemporal variability in metacommunities is challenging because conducting empirical studies that link mechanisms across scales is difficult. We developed a stochastic model of epilithic algal succession in streams to better understand the underlying interactions that drive patch dynamics at three levels of spatial hierarchy: patch, channel habitat, and reach. The state of an algal patch is specified by one of nine community types, which are defined by growth form. Ninety‐two empirical data sets of epilithic succession were used to estimate Markov transition probabilities among patch types as functions of inputs for light, nutrients, and current. Two additional probability matrices determine the effects of herbivory and disturbance based on user inputs. Testing model predictions of patch composition against independent empirical data indicated good correspondence based on resemblance metrics. Early in succession, most patches were occupied by prostrate and erect diatoms. These persisted under low light and nutrient conditions. Motile and stalked diatom patches characterized later stages when resources were moderate. Succession proceeded to mostly filamentous green algal patches under high resource levels. Sensitivity simulations indicated light most affected succession. Herbivory and disturbance increased the probability of prostrate diatom patches. We then used the model to examine how changes in abiotic and biotic parameters affect patch dynamics at different scales. Changes in nutrients or light affected patch diversity differently at the habitat vs. reach scale. Interactions with local resource levels within a channel habitat determined its alpha diversity. The proportion of channel habitat types within a reach, and their collective response to changes, determined beta diversity. Patch diversity within channel habitats generated by herbivory followed the predation hypothesis only when nutrients were low. At the reach scale, herbivory always increased patch similarity among channel habitats, lowering beta diversity. Diversity within channel habitats followed the intermediate disturbance hypothesis for a variety of habitats. Effects of disturbance on beta diversity at the reach scale depended on channel habitat heterogeneity. The stability of patches at the reach scale was highest when disturbance created high patch diversity, supporting the insurance hypothesis. The ideas generated can improve stream bioassessment methods and provide insight into mechanisms underlying patch dynamics in other ecosystems.

Innovative and m ission‐oriented financing of renewable energy in Sub‐Saharan Africa: A review and conceptual framework

AbstractNotwithstanding the high levels of renewable energy resources across Sub‐Saharan Africa (SSA), modern energy use based on these abundant natural resources remains negligible. Furthermore, the current electrification rates and reliability of available power supply in the region have consistently remained significantly lower than the global average over the last three decades. And of the reasons advanced for this state of affairs, the lack of appropriate financing is said to be a crucial one. Therefore, focusing on a comparative overview of the dominant approaches to financing electrification, we characterize the persistence of this regional gap as a reflection of relative “policy stasis.” We then problematize this condition of stasis by employing the theoretical perspectives of mission‐oriented finance in conjunction with those of innovative finance and renewable energy innovation. In addition, we review relevant peer‐reviewed articles over the same period, and find evidence that indicates an underappreciation of financing models that stimulate endogenous technological innovation in renewable energy in SSA. Our analysis suggests that the types of innovation, associated configurations of financial actors, levels of capital intensity, and perceived risks in relation to beneficiaries, diverge from those accounted for in the dominant financing models. Consequently, we propose a novel, historically path‐dependent conceptual framework that emerges from the intersection among the concepts of mission‐oriented finance, endogenous innovation, and innovative financing, which we term “endogenous innovative financing.” This framework ultimately guides our recommendations for more promising financing mechanisms for resolving the interwoven challenges of sustainable universal electrification and renewable energy innovation in SSA.This article is categorized under: Energy Research & Innovation > Economics and Policy Energy and Development > Economics and Policy Energy and Climate > Economics and Policy