The Temporal-Spatial Pattern and Coupling Coordination of the Green Transition of Farmland Use: Evidence from Hubei Province

The green transition of farmland use is a future trend in China’s modern agriculture and green development. However, its research framework, including its evaluation system, temporal-spatial distribution, and driving mechanisms, has not been established in the existent literature. With the 17 cities in Hubei Province as an example, we evaluated the green transition of farmland use and explore the characteristics and driving mechanisms of the temporal and spatial evolution from 2000–2019. The findings were as follows: First, the green transition of farmland use in Hubei Province is in infancy, but it has great potential. Second, the growth rate of the green transition of farmland use has noticeable regional differences in the east, central, and western areas of the province. Third, the three dimensions of spatial transition, functional transition, and model transition in the green transition of farmland use have significant spatial differences in coupling and coordination, and decoupling is becoming increasingly prominent. Based on the research findings, we put forward targeted countermeasures and suggestions.

Monitoring Spatial-Temporal Transition Dynamics of Transport Infrastructure Space in Urban Growth Phenomena: A Case Study of Lagos—Nigeria

Lagos is one of the fastest growing world mega-cities with a huge urban mobility crisis, the traditional aggregate city’s development model could not provide reliable scientific solutions to monitor the competing demands of various land-use components and the urbanization’s effects on transport infrastructure space. This study uses a disaggregated predictive spatial modeling approach to investigate the evolutionary dynamics of transportation infrastructure space to address the fragmented urban chain process. The methodology involves analysis and modeling of the land-use spatial transition changes that have occurred over the past three decades using three Landsat imagery epochs (1984, 2013, and 2019) in remote sensing ARC-GIS 10.7. Furthermore, the prediction of the two-temporal milestones (2030 and 2050) using hybrid cellular automata-Markov (CA-Markov) implemented in IDIRISI SELVA 17.0 software when the tides of social-demographic factors were expected to bring about significant urban spatial transformation. The forecast results are expected to increase the area for transport infrastructure spaces by 93 km2 (7.3%) in 2030 and 157 km2 (12.4%) in 2050. The model’s kappa reliability coefficient estimates for the three temporal scales (k1984 = 85%; k2013 = 88% and k2019 = 89%) are higher than the 80% minimum adjudged strong agreement between the ground truth and prediction classified images in literature. The model provides efficient tool in urban development planning and sustainable transport decisions.

Spatial transcriptome sequencing revealed spatial trajectory in the Non-Small Cell Lung Carcinoma

Deepening understanding in the heterogeneity of tumors is critical for clinical treatment. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal lung cancer using the spatial transcriptomics (ST) technology. We identified gene expression gradients in stroma adjacent to tumor regions that allow for re-understanding of the tumor micro-environment. The establishment of these profiles was the first step towards an unbiased view of lung cancer and can serve as a dictionary for future studies. Tumor subclones were detected by ST technology in our research, while we contrast the EMT ability among in subclones which inferred the possible trajectory of tumor metastasis and invasion, which was confirmed by constructing the pseudo-time model of spatial transition within subclones. Together, these results uncovered lung cancer spatial heterogeneity, highlight potential tumor micro-environment differences and spatial evolution trajectory, and served as a resource for further investigation of tumor microenvironment.

Progressive landscape transformation from a fluvial to a glacial topography

<p>Mid-latitude mountain ranges such as the Eastern Alps are characterized by a strong topographic imprint of Pleistocene glaciations. The characteristic geometry of glacial landforms has been quantified in various ways, but studies about the evolution of glacial landscape metrics are lacking. However, such information is needed to interpret the evolutionary state of glacial topography.</p><p>By employing a landscape evolution model for cold climate processes, we trace the fluvial-to-glacial transformation of a synthetic landscape. Our simulations inspired by alpine glaciations of mid-latitude mountain ranges with peaks and ridges towering above the glacier network lead to a general increase in relief. This is expressed as the formation of overdeepened valleys with steepened flanks. Overdeepening starts at the glacier front and progressively extends upstream with ongoing glacial erosion.</p><p>The topographic signature of the progressively transforming landscape is characterized by an increase of mean channel slopes and its variance. However, above the steep flanks, the initial fluvial topography is persisting. Whereas the initial fluvial mountain range is characterized by a monotonic increase of channel slope with elevation, a transition from increasing to decreasing channel slope with elevation emerges above the equilibrium line altitude where (tributary-)headwalls transition to ridges and summits. This turning point and a high slope variance becomes progressively distinctive with ongoing glacial occupation.</p><p>By comparing landscape metrics derived from model time series with those of the Eastern Alps, we found that the temporal transition observed in our numerical experiments occur as spatial transition from the fully glaciated western to a minorly glaciated eastern part of the Alps. Thus, slope-elevation plots serve as a diagnostic tool for interpreting the glacial - fluvial influence in mountain landscapes. However, catchments of the unglaciated part of the Eastern Alps show also turning points in their slope-elevation distributions, but the variance of slope is significantly smaller at all elevation levels, when compared to the glaciated part.</p>

TRANSITIONAL IMPACTS OF ENSO ON WAVE CLIMATE IN COASTAL REGIONS

Amongst all the factors involved in coastal risk assessment, climate variability is key, due to its potential for modifying the coast, particularly through increased seasonal risk of erosion-flooding on the coast (Toimil et al. 2020; Wahl and Plant 2015). The principal driver of interannual variability of the wave climate around the world is El Nio-Southern Oscillation (ENSO). Many researches have focused on the analysis of this phenomenon globally ( Stopa and Cheung 2014), its impacts on regional wave climate (Barnard et al. 2015, 2017; Oderiz et al. 2020; Reguero, Mendez, and Losada 2013) and their local coastal effects ( Mortlock and Goodwin 2016). This interest in ENSO impacts in wave climate is motivated by its capacity to cause coastal erosion (Barnard et al. 2015). Particularly, the temporal and spatial transition of ENSO is nowadays a current issue (Ha et al. 2012). On the worlds coasts, the ENSO impacts delay is not yet fully understood, nor integrated into engineering practices.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/DZbOYztPYW0

Where to Now? Fourteen Characteristics of Teachers’ Transition into Innovative Learning Environments

This chapter places the preceding papers into a wider context. As part of the Innovative Learning Environment and Teacher Change (ILETC) project, seven Transitions symposia were held in five cities across Australasia, Europe and North America during 2017, 2018 and 2019. Each aimed at investigating how teachers adapt to innovative learning environments. The resulting accumulation of approximately 150 papers by graduate researchers and research groups, of which this book’s chapters are a sample, constituted a reasonable representation of international thinking on this topic. When added to three years of ILETC case studies, surveys, systematic literature reviews and teacher workshops, the project team was able to identify consistent patterns in teachers’ spatial transition actions. This chapter places the material of this book within that larger picture, specifically in terms of one project output—the development of a Spatial Transition Pathway. The Pathway emerged from these data and can be seen as an output of the material sampled in previous chapters. Certainly, the considerable work teachers had been doing to re-conceptualise their pedagogies for new spaces (done both intentionally, and at times, without realising) deserved to be mapped as a resource for others undertaking this journey. This chapter makes the case that while each teacher or school’s journey from traditional to ‘innovative’ spaces is unique, there exists some common issues that most seem to face at some time, in some way. It provides a description of fourteen ‘grand themes’ that appear commonly through the data and describes how these can be organised in a way that provides temporal and theme-based strategies and tools, developed by fellow educators to assist in this transition. This final chapter leads the reader to consider ‘where to now’? It celebrates the fact that teachers have enormous capacity to work out how to utilise innovative learning environments well and provides a framework for evidence-based actions into the future.