In sub-Saharan Africa, population growth coupled with weak or missing markets for clean energy means that the absolute number of people relying on woodfuels for cooking is growing. Charcoal, which has distinctly different environmental and economic implications from firewood, has become one of the most consumed fuels in the region. However, among rural populations, the drivers and consequences of charcoal use remain under-studied. We examine rural woodfuel dynamics in Malawi, a majority rural country with high poverty, rapid population growth, lagging economic development, and abundant but rapidly declining forest resources. We examine how household energy transitions are influenced by concurrent demographic, economic, and land use changes. Using four waves of national household surveys and satellite-derived forest cover datasets, we investigate trends in household energy consumption, identify factors driving rural household fuel choices, and characterize geographic patterns of forest cover loss during 2004–2020. During this time, the share of rural households using charcoal grew from 3.9% to 13.4%. Rural households that are smaller, headed by younger individuals, and are asset-rich but land-poor had greater odds of using charcoal compared to firewood, indicating that rural livelihood dynamics have important consequences for household energy transitions. Several protected areas have experienced > 20% forest cover loss since 2001, characterized by geographic patterns consistent with unsanctioned woodfuel extraction. These findings emphasize a renewed need for integrated natural resources, energy, and livelihoods management strategies. Our insights provide information for policy makers to better predict and understand the continued growth of charcoal’s popularity in Malawi and similar contexts.
Baleen whales are key consumers in marine habitats that serve as vectors of nutrients, but their populations have been slow to recover from past commercial whaling due to their low reproductive rates and ongoing anthropogenic threats. Climate impacts have become central to the demography and habitat use of baleen whales, and conservation efforts must account for these impacts to be effective. However, knowledge of baleen whale climate responses is lacking, and current survey effort is insufficient to capture changes in migration and habitat use for many species. Due to their unique combination of ecological and life history characteristics, baleen whales are particularly vulnerable to climate change and their climate responses should be expected to differ fundamentally from those of other marine consumers. These characteristics include the need for both large quantities and high densities of prey, the need to accumulate large energy reserves seasonally, as well as highly migratory movements and the reliance on high-latitude foraging areas with narrow seasonal windows in resource availability. Climate responses in baleen whales may involve abrupt changes in foraging habitat in contrast to more gradual poleward shifts observed in other species, changes in the timing, extent or tendency for migration, and changes in energy accumulation or fitness. Recognizing that climate impacts may differ from other species is critical to measuring and anticipating changes to baleen whale populations in the face of ongoing climate change, and to effectively managing their populations in the future. North Atlantic right whales (Eubalena glacialis), arguably the best studied baleen whale species at a population scale, exemplify expectations for baleen whale climate responses and the implications for future management and conservation. Right whales have shown abrupt changes to traditional patterns of habitat use and migratory behavior, with major implications for the effectiveness of existing protections. Understanding and detecting baleen whale climate responses and effectively guiding management in the face of ongoing change will require increased survey effort and novel methods to survey remote habitats; improved knowledge of mechanisms of prey aggregation and climate impacts on these processes; and continued development and refinement of mechanistic models and dynamic management strategies.
Organizations pursuing activities that advance the public interest often require support from their local communities, but such support may be harder to come by in more racially diverse communities. In this study, we argue that this negative effect of racial diversity on support for organizations serving the public interest will be weaker the more inclusive the community, especially where community inclusion is accompanied by shared values among members of different groups and where the organizations themselves are racially representative. We test and find support for these predictions by looking at one specific type of public service organization: public schools in the United States. Specifically, we find that community support for public schools-both generally in terms of local spending per pupil and specifically as the bond amounts residents vote to approve-is negatively associated with racial diversity within a school district, but this negative relation only holds for less inclusive communities where members of different groups are less likely to live close to each other or to have social ties with each other. We further find that this moderating effect of community inclusion is complemented by shared values and organizational representativeness, so that diversity has the most negative effect in less inclusive communities where members of different races differ in their political beliefs and schools are relatively segregated, and no significant effect in inclusive communities with shared values and integrated schools. Our study sheds new light on the conditions under which organizations seeking to address grand challenges can benefit from strong community support.
The interactions between gas and galaxies are of paramount importance to our understanding of structure formation. A fundamental element of such baryon cycle studies is a complete census of the condensed matter (stars and cold gas) in both galaxies and their immediate surroundings, the so-called circumgalactic medium. Of particular importance are the processes of converting molecular gas into stars and deciphering whether this < 100 K gas is tracing gas flows. The MUSE-ALMA Haloes survey assembled probes of the neutral atomic gas H I, ionised gas, and stellar component for a sample of 79 z similar to 0.5 galaxies. This was achieved by combining absorption-line spectroscopy of background quasars with a projected impact parameter as low as 5 kpc and as high as 250 kpc to probe the low-density circumgalactic gas with emission-line tracers of both ionised gas and stars. This paper presents the Large Programme observational setup and releases the data characterising the molecular phase of some of the MUSE-ALMA Haloes targets so as to reach a complete census of their condensed baryons. ALMA's unique millimetre coverage and high sensitivity are ideal for characterising the CO emission of these z similar to 0.5 H I-selected galaxies. By measuring the molecular mass, kinematics, gas flows, and gas fractions, this project (i) quantifies the role of molecular gas in H I-rich galaxies, (ii) characterises the molecular phase of gas flows from morpho-kinematics analyses, and (iii) establishes a census of the condensed baryons in the interstellar and circumgalactic media. Ultimately, these results will provide unique insights into the baryon cycle - a crucial component of galaxy formation.
Networks of atom-centered coordination octahedra commonly occur in inorganic and hybrid solid-state materials. Characterizing their spatial arrangements and characteristics is crucial for relating structures to properties for many materials families. The traditional method using case-by-case inspection becomes prohibitive for discovering trends and similarities in large datasets. Here, we operationalize chemical intuition to automate the geometric parsing, quantification, and classification of coordination octahedral networks. We find axis-resolved tilting trends in ABO$_{3}$ perovskite polymorphs, which assist in detecting oxidation state changes. Moreover, we develop a scale-invariant encoding scheme to represent these networks, which, combined with human-assisted unsupervised machine learning, allows us to taxonomize the inorganic framework polytypes in hybrid iodoplumbates (A$_x$Pb$_y$I$_z$). Consequently, we uncover a violation of Pauling's third rule and the design principles underpinning their topological diversity. Our results offer a glimpse into the vast design space of atomic octahedral networks and inform high-throughput, targeted screening of specific structure types.
