This article identifies equity outcomes associated with three biofuel systems in Brazil, Ethiopia and Guatemala. Acknowledging that winners and losers are socially and politically generated, the article identifies some of the factors behind the distribution of winners and losers along different stages of three sugarcane-ethanol supply chains. Analysing the outcomes for equity within each case study reveals an uneven distribution that we argue is related to the procedure and structure of the given sugarcane-ethanol system, and the recognition of the impacts on different actors within those structures. Increasing equity in sugarcane-ethanol systems will require greater openness in decision making processes, in order that multiple voices are taken into account in the promotion, production and consumption of biofuels – particularly those of smaller and less powerful actors.

The unicellular green microalga Desmodesmus sp. S1 can produce more than 50% total lipid of cell dry weight under high light and nitrogen-limitation conditions. After irradiation by heavy ¹²C⁶⁺ ion beam of 10, 30, 60, 90 or 120 Gy, followed by screening of resulting mutants on 24-well microplates, more than 500 mutants were obtained. One of those, named D90G-19, exhibited lipid productivity of 0.298 g L^-1⋅d^-1, 20.6% higher than wild type, likely owing to an improved maximum quantum efficiency (Fv/Fm) of photosynthesis under stress. This work demonstrated that heavy-ion irradiation combined with high-throughput screening is an effective means for trait improvement. The resulting mutant D90G-19 may be used for enhanced lipid production.

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO₂) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO₂ emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO₂ emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

The apolipoprotein E (APOE) e4 genotype is a powerful risk factor for late-onset Alzheimer’s disease (AD). In the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, we previously reported significant baseline structural differences in APOE e4 carriers relative to non-carriers, involving the left hippocampus more than the right—a difference more pronounced in e4 homozygotes than heterozygotes. We now examine the longitudinal effects of APOE genotype on hippocampal morphometry at 6-, 12- and 24-months, in the ADNI cohort. We employed a new automated surface registration system based on conformal geometry and tensor-based morphometry. Among different hippocampal surfaces, we computed high-order correspondences, using a novel inverse-consistent surface-based fluid registration method and multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance. At each time point, using Hotelling’s T² test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the full cohort as well as in the non-demented (pooled MCI and control) subjects at each follow-up interval. In the complete ADNI cohort, we found greater atrophy of the left hippocampus than the right, and this asymmetry was more pronounced in e4 homozygotes than heterozygotes. These findings, combined with our earlier investigations, demonstrate an e4 dose effect on accelerated hippocampal atrophy, and support the enrichment of prevention trial cohorts with e4 carriers.

In traditional public good experiments participants receive an endowment from the experimenter that can be invested in a public good or kept in a private account. In this paper we present an experimental environment where participants can invest time during five days to contribute to a public good. Participants can make contributions to a linear public good by logging into a web application and performing virtual actions. We compared four treatments, with different group sizes and information of (relative) performance of other groups. We find that information feedback about performance of other groups has a small positive effect if we control for various attributes of the groups. Moreover, we find a significant effect of the contributions of others in the group in the previous day on the number of points earned in the current day. Our results confirm that people participate more when participants in their group participate more, and are influenced by information about the relative performance of other groups.

Differences in governance relationships and community efforts to remove an exotic, rapidly spreading invasive plant, the-mile-a-minute weed (Mikania micrantha), are explored in five case study community forests in the subtropical region of Chitwan, Nepal. An institutional analysis informs an examination of the de jure (formal) versus de facto (on the ground) institutions and actor relationships relevant to Mikania removal efforts. Contrary to the expectations set by the de jure situation, we find heterogeneous governance relationships and norms related to Mikania management across community forests. Content analysis of interview data illuminates reoccurring themes and their implications for social and ecological outcomes in the communities. Complex governance relationships and regular discussion of distrust of government and non-government officials help explain collective action efforts and management decisions. The content analysis suggests that Mikania is impacting people’s daily lives but the degree of severity and the response to the disruption varies substantially and is heavily affected by other problems experienced by community forest members. Our results indicate that understanding how the de facto, or on the ground situation, differs from the de jure institutions may be vital in structuring successful efforts to manage invasive species and understanding collective action problems related to other social-ecological threats. We present data-informed propositions about common pool resource management and invasive species. This study contributes to a better scientific understanding of how institutions mediate social-ecological challenges influencing common pool resources more broadly.

The International Long-Term Ecological Research (ILTER) network comprises > 600 scientific groups conducting site-based research within 40 countries. Its mission includes improving the understanding of global ecosystems and informs solutions to current and future environmental problems at the global scales. The ILTER network covers a wide range of social-ecological conditions and is aligned with the Programme on Ecosystem Change and Society (PECS) goals and approach. Our aim is to examine and develop the conceptual basis for proposed collaboration between ILTER and PECS. We describe how a coordinated effort of several contrasting LTER site-based research groups contributes to the understanding of how policies and technologies drive either toward or away from the sustainable delivery of ecosystem services. This effort is based on three tenets: transdisciplinary research; cross-scale interactions and subsequent dynamics; and an ecological stewardship orientation.

The overarching goal is to design management practices taking into account trade-offs between using and conserving ecosystems toward more sustainable solutions. To that end, we propose a conceptual approach linking ecosystem integrity, ecosystem services, and stakeholder well-being, and as a way to analyze trade-offs among ecosystem services inherent in diverse management options. We also outline our methodological approach that includes: (i) monitoring and synthesis activities following spatial and temporal trends and changes on each site and by documenting cross-scale interactions; (ii) developing analytical tools for integration; (iii) promoting trans-site comparison; and (iv) developing conceptual tools to design adequate policies and management interventions to deal with trade-offs. Finally, we highlight the heterogeneity in the social-ecological setting encountered in a subset of 15 ILTER sites. These study cases are diverse enough to provide a broad cross-section of contrasting ecosystems with different policy and management drivers of ecosystem conversion; distinct trends of biodiversity change; different stakeholders’ preferences for ecosystem services; and diverse components of well-being issues.

Recently, an approach for global sustainability, the planetary-boundary approach (PBA), has been proposed, which combines the concept of tipping points with global-scale sustainability indicators. The PBA could represent a significant step forward in monitoring and managing known and suspected global sustainability criteria. However, as the authors of the PBA describe, the approach faces numerous and fundamental challenges that must be addressed, including successful identification of key global sustainability metrics and their tipping points, as well as the coordination of systemic individual and institutional actions that are required to address the sustainability challenges highlighted. We apply a previously published framework for systematic and strategic development toward a robust basic definition of sustainability, i.e., the framework for strategic sustainable development (FSSD), to improve and inform the PBA.

The FSSD includes basic principles for sustainability, and logical guidelines for how to approach their fulfillment. It is aimed at preventing unsustainable behavior at both the micro, e.g., individual firm, and macro, i.e., global, levels, even when specific global sustainability symptoms and metrics are not yet well understood or even known. Whereas the PBA seeks to estimate how far the biosphere can be driven away from a “normal” or “natural” state before tipping points are reached, because of ongoing violations of basic sustainability principles, the FSSD allows for individual planners to move systematically toward sustainability before all impacts from not doing so, or their respective tipping points, are known. Critical weaknesses in the PBA can, thus, be overcome by a combined approach, significantly increasing both the applicability and efficacy of the PBA, as well as informing strategies developed in line with the FSSD, e.g., by providing a “global warning system” to help prioritize strategic actions highlighted by the FSSD. Thus, although ongoing monitoring of known and suspected global sustainability metrics and their possible tipping points is a critical part of the evolving sustainability landscape, effective and timely utilization of planetary-boundary information on multiple scales requires coupling to a strategic approach that makes the underlying sustainability principles explicit and includes strategic guidelines to approach them.

Outside of such a rigorous and systems-based context, the PBA, even given its global scale, risks leading individual organizations or planners to (i) focus on “shares” of, e.g., pollution within the PBs and negotiations to get as high proportion of such as possible, and/or (ii) awaiting data on PBs when such do not yet exist before they act, and/or (iii) find it difficult to manage uncertainties of the data once such have arrived. If global sustainability problems are to be solved, it is important that each actor recognizes the benefits, not the least self-benefits, of designing and executing strategies toward a principled and scientifically robust definition of sustainability. This claim is not only based on theoretical reasoning. A growing number of sectors, businesses, and municipalities/cities around the world are already doing it, i.e., not estimating “allowed” shares of, say fossil CO[subscript 2] emissions, but gradually moving away from unsustainable use of fossil fuels and other unsustainable practices altogether.

Alzheimer’s disease (AD) involves a gradual breakdown of brain connectivity, and network analyses offer a promising new approach to track and understand disease progression. Even so, our ability to detect degenerative changes in brain networks depends on the methods used. Here we compared several tractography and feature extraction methods to see which ones gave best diagnostic classification for 202 people with AD, mild cognitive impairment or normal cognition, scanned with 41-gradient diffusion-weighted magnetic resonance imaging as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. We computed brain networks based on whole brain tractography with nine different methods – four of them tensor-based deterministic (FACT, RK2, SL, and TL), two orientation distribution function (ODF)-based deterministic (FACT, RK2), two ODF-based probabilistic approaches (Hough and PICo), and one “ball-and-stick” approach (Probtrackx). Brain networks derived from different tractography algorithms did not differ in terms of classification performance on ADNI, but performing principal components analysis on networks helped classification in some cases. Small differences may still be detectable in a truly vast cohort, but these experiments help assess the relative advantages of different tractography algorithms, and different post-processing choices, when used for classification.

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying different stages of Alzheimer's disease.