ALBERT

Description: The past ∼200 million years of Earth's geomagnetic field behavior have been recorded within oceanic basalts, many of which are only accessible via scientific ocean drilling. Obtaining the best possible paleomagnetic measurements from such valuable samples requires an a priori understanding of their magnetic mineralogies when choosing the most appropriate protocol for stepwise demagnetization experiments (either alternating field or thermal). Here, we present a quick, and non‐destructive method that utilizes the amplitude‐dependence of magnetic susceptibility to screen submarine basalts prior to choosing a demagnetization protocol, whenever conducting a pilot study or other detailed rock‐magnetic characterization is not possible. We demonstrate this method using samples acquired during International Ocean Discovery Program Expedition 391. Our approach is rooted in the observation that amplitude‐dependent magnetic susceptibility is observed in basalt samples whose dominant magnetic carrier is multidomain titanomagnetite (∼TM 60–65 , (Ti 0.60–0.65 Fe 0.35–0.40 )Fe 2 O 4 ). Samples with low Ti contents within titanomagnetite or samples that have experienced a high degree of oxidative weathering do not display appreciable amplitude dependence. Due to their low Curie temperatures, basalts that possess amplitude‐dependence should ideally be demagnetized either using alternating fields or via finely‐spaced thermal demagnetization heating steps below 300°C. Our screening method can enhance the success rate of paleomagnetic studies of oceanic basalt samples. Plain Language Summary Oceanic basalts are ideal recorders of the Earth's magnetic field. To decipher magnetic histories recorded in rocks, paleomagnetists need to isolate the magnetization directions and intensities within rocks by one of two possible methods. One method typically involves progressively heating the samples to high temperatures. The other method involves exposing samples to alternating magnetic fields with increasing peak field intensities. Both of these methods are ultimately destructive to the original magnetization preserved within rocks. However, without knowledge of a given rock's magnetic mineralogy, randomly choosing thermal or alternating field demagnetization methods may result in high failure rates. We developed a pre‐screening method to help decide which cleaning method will likely be more successful for a given sample based on low‐field magnetic susceptibility measurements. These measurements do not affect the original magnetic information recorded in a rock, thereby permitting subsequent paleomagnetic studies on the same sample. Our technique can be performed as rapidly as 2 min per sample, is non‐destructive, and does not require complicated sample preparation. Key Points Paleomagnetic studies utilize either alternating field or thermal demagnetization, but it is difficult to choose the best protocol a priori Amplitude‐dependence of magnetic susceptibility measurements permits preliminary magnetic mineralogy characterization in submarine basalts Rapid amplitude‐dependence measurements may aid in deciding upon the best demagnetization protocol for submarine basalt samples

Description: Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analysed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models’ sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models.

Description: China has made substantial investment in agricultural research and development (R&D) to promote technological change (TC). Although the role of TC in enhancing agricultural production and mitigating environmental impacts is widely recognized in separate contexts, knowledge about its’ effects on food security and the environment, especially with a focus on China, is still lacking. This study uses an agro-economic optimization model to assess the impact of TC on food security and climate change mitigation. Our results indicate that TC plays an important role in improving agricultural productivity, which, in turn, contributes to a comparative advantage in agricultural trade. It also strengthens food security through lowering food prices. By contrast, a higher TC level increases greenhouse gas (GHG) emissions, albeit marginally, due to higher agricultural production for exports. This indicates a rebound effect of agricultural productivity on GHG emissions. Therefore, additional efforts are required in China to improve food security without compromising GHG mitigation.

Description: This article investigates the event-triggered adaptive containment control problem for a class of stochastic nonlinear multiagent systems with unmeasurable states. A stochastic system with unknown heterogeneous dynamics is established to describe the agents in a random vibration environment. Besides, the uncertain nonlinear dynamics are approximated by radial basis function neural networks (NNs), and the unmeasured states are estimated by constructing the NN-based observer. In addition, the switching-threshold-based event-triggered control method is adopted with the hope of reducing communication consumption and balancing system performance and network constraints. Moreover, we develop the novel distributed containment controller by utilizing the adaptive backstepping control strategy and the dynamic surface control (DSC) approach such that the output of each follower converges to the convex hull spanned by multiple leaders, and all signals of the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square. Finally, we verify the efficiency of the proposed controller by the simulation examples.

Description: Global climate warming is accelerating permafrost degradation. The large amounts of soil organic matter in permafrost-affected soils are prone to increased microbial decomposition in a warming climate. Along with permafrost degradation, changes to the soil microbiome play a crucial role in enhancing our understanding and in predicting the feedback of permafrost carbon. In this article, we review the current state of knowledge of carbon-cycling microbial ecology in permafrost regions. Microbiomes in degrading permafrost exhibit variations across spatial and temporal scales. Among the short-term, rapid degradation scenarios, thermokarst lakes have distinct biogeochemical conditions promoting emission of greenhouse gases. Additionally, extreme climatic events can trigger drastic changes in microbial consortia and activity. Notably, environmental conditions appear to exert a dominant influence on microbial assembly in permafrost ecosystems. Furthermore, as the global climate is closely connected to various permafrost regions, it will be crucial to extend our understanding beyond local scales, for example by conducting comparative and integrative studies between Arctic permafrost and alpine permafrost on the Qinghai–Tibet Plateau at global and continental scales. These comparative studies will enhance our understanding of microbial functioning in degrading permafrost ecosystems and help inform effective strategies for managing and mitigating the impacts of climate change on permafrost regions.