Ecosystem service assessments facilitate the valuation of nature and support decision-making. Ecosystem services are connected to climate; however, ecosystem service values affected by climate change remain unclear. We mapped global ecosystem service values totaling ∼1.3 trillion international dollars for 2005. Transitions in Köppen–Geiger climate classes projected with General Circulation Models under the four IPCC Representative Concentration Pathways (RCP) were modeled providing 20 climate scenarios. The mapped global ecosystem service values were combined with the 20 climate scenarios in order to identify where and how much of the global ecosystem service value is within a climate class transition. By 2050, 252–375 billion international dollars of ecosystem service value (20%–30% of total value) are in a Köppen–Geiger climate transition for both RCP 2.6 and 8.5 scenarios. In RCP 2.6, the 2015 Paris Agreement carbon emission scenario target, Köppen–Geiger climate transitions stabilize after 2050. However, in the RCP 8.5 scenario, ecosystem service values amounting to 467–632 billion international dollars (37%–50% of total value) are in a Köppen–Geiger climate transition by 2085. These results provide an inclusive global overview of climate change impact on evaluated ecosystem services that affect populations and economies.

Understanding the distribution and characterization of natural and non-natural materials on the surface and near-subsurface is important for the development of infrastructure projects. This may be a challenge in highly urbanized areas, where outcrops are scarce, and anthropogenic activities have altered the morphological expression of the landscape. This study tests the integration of ground-penetrating radar (GPR), borehole drilling, aerial imagery, geological mapping, and aerial laser scanning as complementary mapping tools for determining the stratigraphy of glacial and post-glacial Quaternary sediments, the depth to the bedrock, and the distribution of anthropogenic material in Mosvatnet, a lake in Stavanger, Norway. The integration proved to be efficient and enabled the generation of a 3D holistic model, which provided a broad understanding of the subsurface geology and the induced anthropogenic changes in the area through time. Bedrock, till, fluvioglacial, and lacustrine geological units were modeled. Accumulations of post-glacial organic matter were mapped, and the distribution of non-natural infill material was determined. The interpreted dataset suggests that the eastern shoreline of Mosvatnet has artificially prograded about one hundred meters westward since the 1930s and the elevation of the corresponding area has increased by about ten meters relative to the lake level.

The detection and recording of tens to hundreds of centimeter-scale features in archaeological sites represent a challenge in data collection during field work. Traditionally, archaeological field documentation relies on sketches and line drawings made by hand. Sensors facilitate the characterization, mapping, and quantification of millimetre-scale features, which are otherwise difficult to detect with the naked eyes. High-resolution terrestrial laser scanning is an optimal method for documenting cultural heritage sites due to its transportability and efficient collection time, while processed 3D models facilitate detailed analysis. To demonstrate this approach, a Late Bronze Age Mycenaean cemetery in Greece was selected as a study site due to its size and active excavation status despite ongoing looting activities. The cemetery consists of several chamber tombs, which were hewn from a soft marl hillside using sharp tools. Chisel marks were observed in one of the chamber tombs. The cemetery was surveyed, resulting in point clouds with 0.7 mm spacing. The resulting 3D point cloud model was analyzed as a proof of concept to test the semi-automatic detection of the observed chisel marks. Two separate, but complementary methods, were applied to one surveyed tomb, resulting in the identification of 39 chisel marks divided into four linear feature families. Future work can improve the efficiency of detection as well as further classification of features, especially in sites where natural and anthropogenic features need differentiation or to reconstruct the sequence in which features were created.

2% of the disturbed peatlands in the world are known to contribute approximately 4% to global greenhouse gas emission, according to UNEP. Northern peatlands spread above latitude 45 N (e.g. in Canada, USA, Scandinavia and United Kingdon) are biomes where climate change may occur earlier and rapidly thus contributing to greenhouse gas emissions more than many other biomes around the world. Peatlands can be classified as either “intact” or “disturbed” to determine whether they could be CO2 sources or sinks yet, the classification process requires a remote sensing approach because of limited accessibility to physical locations and intensive nature of field mapping. The study presented here uses spectral reflectance from peatland surfaces, together with topographic and climatic properties of the environment to classify peatland areas across Scotland. Distinct spectral reflectance responses in visible red between 0.63 and 0.69 µm, near-infrared between 0.85 and 0.88 µm, and short-wave infrared between 1.6 and 2.2 µm of the optical electromagnetic spectrum, topography, climate and land surface temperature have been used to discriminate between peatlands. A random forest classifier was trained using a 70/15/15 train-validation split, to predict peatland status. The classifier achieved an overall accuracy (F1 Score) of 72%, with a class-level accuracy of 94% for Forested, 84% for Drained and Eroded, 67% for Modified, and 44% for Near-Natural Peatlands at 100m resolution. Based on these results, a national Scottish peatland status map is modelled at 100-meter resolution, demonstrating the potential of using the model for large-scale peatland characterization. This work presents a remote-sensing-based classification framework to support peatland mapping and status monitoring.

Geoscience-based jobs in the oil and gas industry are changing; thus, the education students receive must adapt to maintain work relevancy. In Norway, the confluence of changing industry needs to meet net-zero emissions and increased interest in carbon storage combined with decreased student admission in oil and gas education programs prompted the establishment of a research project to investigate the current and changing competence needs in the Norwegian oil and gas industry and to map competence development within the MSc in Energy, Reservoir, and Earth Sciences, offered in the Department of Energy Resources at the University of Stavanger, Norway. The research project, Defining Future Subsurface Education Needs in Collaboration with the Energy Industry (SUBSET), is supported by the Norwegian Directorate for Higher Education and Skills and collaborates with 5 energy companies and 2 trade unions. We applied a multi-method approach to determine the current and future needs within the Norwegian oil and gas industry. Through analysing interviews with company representatives, surveys with the workforce, discussions with trade unions, and workshops between companies and academia, we created a list of 28 thematic topics and competences. We compared this list to the learning outcomes of a master’s degree program and the courses contained therein to determine which competences were addressed and which were not. The study program is equivalent to 90 ECTS of coursework, consisting of 8 core courses and 4 elective courses, and a 30 ECTS thesis. Students are not obligated to the program electives; however, most students concentrate on the program electives. 27 competences were addressed by between 1 and 9 courses, whereas communication skills are addressed by 10 courses in some manner. Only 1 competence – financial management – was not addressed in the program; however, students could take a non-program elective to meet this competence. According to the competence mapping, the master's degree program contains a high-level of work relevant skills development. In this presentation, we discuss the methodological approach applied and the detailed competence mapping of the master’s degree program with a critical look at the content.