Computational methods for the characterization of Apis mellifera comb architecture.

The architecture of honey bee combs embodies a range of expressions associated with swarm intelligence, emergent behaviors, and social organization, which has drawn scientists to study them as a model of collective construction processes. Until recently, however, the development of models to characterize comb-building behavior has relied heavily on laborious manual observations and measurements. The use of high-throughput multi-scale analyses to investigate the geometric features of Apis mellifera comb therefore has the potential to vastly expand our understanding of comb-building processes. Inspired by this potential, here we explore connections between geometry and behavior by utilizing computational methods for the detailed examination of hives constructed within environments designed to observe how natural building rule sets respond to environmental perturbations. Using combs reconstructed from X-ray micro-computed tomography source data, we introduce a set of tools to analyze geometry and material distributions from these scans, spanning from individual cells to whole-hive-level length scales. Our results reveal relationships between cell geometry and comb morphology, enable the generalization of prior research on build direction, demonstrate the viability of our methods for isolating specific features of comb architecture, and illustrate how these results may be employed to investigate hive-level behaviors related to build-order and material distributions.

Making data matter: Voxel printing for the digital fabrication of data across scales and domains.

We present a multimaterial voxel-printing method that enables the physical visualization of data sets commonly associated with scientific imaging. Leveraging voxel-based control of multimaterial three-dimensional (3D) printing, our method enables additive manufacturing of discontinuous data types such as point cloud data, curve and graph data, image-based data, and volumetric data. By converting data sets into dithered material deposition descriptions, through modifications to rasterization processes, we demonstrate that data sets frequently visualized on screen can be converted into physical, materially heterogeneous objects. Our approach alleviates the need to postprocess data sets to boundary representations, preventing alteration of data and loss of information in the produced physicalizations. Therefore, it bridges the gap between digital information representation and physical material composition. We evaluate the visual characteristics and features of our method, assess its relevance and applicability in the production of physical visualizations, and detail the conversion of data sets for multimaterial 3D printing. We conclude with exemplary 3D-printed data sets produced by our method pointing toward potential applications across scales, disciplines, and problem domains.

Design of a multi-agent, fiber composite digital fabrication system.

Swarm-based fabrication of interwoven composite tubes via a fully autonomous, cooperative system can help create architectural-scale structures in effective and efficient ways, including in remote environments.

Large-Scale Land Acquisition and Its Effects on the Water Balance in Investor and Host Countries.

This study examines the validity of the assumption that international large-scale land acquisition (LSLA) is motivated by the desire to secure control over water resources, which is commonly referred to as 'water grabbing'. This assumption was repeatedly expressed in recent years, ascribing the said motivation to the Gulf States in particular. However, it must be considered of hypothetical nature, as the few global studies conducted so far focused primarily on the effects of LSLA on host countries or on trade in virtual water. In this study, we analyse the effects of 475 intended or concluded land deals recorded in the Land Matrix database on the water balance in both host and investor countries. We also examine how these effects relate to water stress and how they contribute to global trade in virtual water. The analysis shows that implementation of the LSLAs in our sample would result in global water savings based on virtual water trade. At the level of individual LSLA host countries, however, water use intensity would increase, particularly in 15 sub-Saharan states. From an investor country perspective, the analysis reveals that countries often suspected of using LSLA to relieve pressure on their domestic water resources--such as China, India, and all Gulf States except Saudi Arabia--invest in agricultural activities abroad that are less water-intensive compared to their average domestic crop production. Conversely, large investor countries such as the United States, Saudi Arabia, Singapore, and Japan are disproportionately externalizing crop water consumption through their international land investments. Statistical analyses also show that host countries with abundant water resources are not per se favoured targets of LSLA. Indeed, further analysis reveals that land investments originating in water-stressed countries have only a weak tendency to target areas with a smaller water risk.

Towards a Spatial Understanding of Trade-Offs in Sustainable Development: A Meso-Scale Analysis of the Nexus between Land Use, Poverty, and Environment in the Lao PDR.

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use-poverty-environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local-highly contextual-development potentials is key to shaping outcomes of the land use-poverty-environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.