Eva Lieungh

• Wilcox, Kevin R.; Chen, Anping; Avolio, Meghan L.; Butler, Ethan E.; Collins, Scott & Fisher, Rosie [Show all 22 contributors for this article] (2023). Accounting for herbaceous communities in process-based models will advance our understanding of “grassy” ecosystems. Global Change Biology. ISSN 1354-1013. doi: 10.1111/gcb.16950. Full text in Research Archive Show summary

  Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

• Keetz, Lasse Torben; Lieungh, Eva; Karimi-Asli, Kaveh; Geange, Sonya Rita; Gelati, Emiliano & Tang, Hui [Show all 24 contributors for this article] (2023). Climate–ecosystem modelling made easy: The Land Sites Platform. Global Change Biology. ISSN 1354-1013. 29(15), p. 4440–4452. doi: 10.1111/gcb.16808. Full text in Research Archive Show summary

  Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.

• Naas, Adam Eindride; Halvorsen, Rune; Horvath, Peter; Wollan, Anders Kvalvåg; Bratli, Harald & Brynildsrud, Katrine Marie [Show all 16 contributors for this article] (2023). What explains inconsistencies in field-based ecosystem mapping? Applied Vegetation Science. ISSN 1402-2001. 26(1). doi: 10.1111/avsc.12715. Full text in Research Archive Show summary

  Questions Field-based ecosystem mapping is prone to observer bias, typically resulting in a mismatch between maps made by different mappers, that is, inconsistency. Experimental studies testing the influence of site, mapping scale, and differences in experience level on inconsistency in field-based ecosystem mapping are lacking. Here, we study how inconsistencies in field-based ecosystem maps depend on these factors. Location Iškoras and Guollemuorsuolu, northeastern Norway, and Landsvik and Lygra, western Norway. Methods In a balanced experiment, four sites were field-mapped wall-to-wall to scales 1:5000 and 1:20,000 by 12 mappers, representing three experience levels. Thematic inconsistency was calculated by overlay analysis of map pairs from the same site, mapped to the same scale. We tested for significant differences between sites, scales, and experience-level groups. Principal components analysis was used in an analysis of additional map inconsistencies and their relationships with site, scale and differences in experience level and time consumption were analysed with redundancy analysis. Results On average, thematic inconsistency was 51%. The most important predictor for thematic inconsistency, and for all map inconsistencies, was site. Scale and its interaction with site predicted map inconsistencies, but only the latter were important for thematic inconsistency. The only experience-level group that differed significantly from the mean thematic inconsistency was that of the most experienced mappers, with nine percentage points. Experience had no significant effect on map inconsistency as a whole. Conclusion Thematic inconsistency was high for all but the dominant thematic units, with potentially adverse consequences for mapping ecosystems that are fragmented or have low coverage. Interactions between site and mapping system properties are considered the main reasons why no relationships between scale and thematic inconsistency were observed. More controlled experiments are needed to quantify the effect of other factors on inconsistency in field-based mapping.

• Lieungh, Eva; Bjureke, Kristina; Evju, Marianne; Johaadien, Rukaya Sarah; Olsen, Siri Lie & Skarpaas, Olav [Show all 8 contributors for this article] (2022). Presence-absence of plant habitat specialists in 15 patches of dry calcareous grassland. Biodiversity Data Journal. ISSN 1314-2836. 10. doi: 10.3897/BDJ.10.e94057. Full text in Research Archive
• Halvorsen, Rune; Skarpaas, Olav; Bryn, Anders; Bratli, Harald; Erikstad, Lars & Simensen, Trond [Show all 7 contributors for this article] (2020). Towards a systematics of ecodiversity: the Ecosyst framework. Global Ecology and Biogeography. ISSN 1466-822X. 29(11), p. 1887–1906. doi: 10.1111/geb.13164. Full text in Research Archive Show summary

  Background Although a standard taxonomy of organisms has existed for nearly 300 years, no consensus has yet been reached on principles for systematization of ecological diversity (i.e., the co‐ordinated variation of abiotic and biotic components of natural diversity). In a rapidly changing world, where nature is under constant pressure, standardized terms and methods for characterization of ecological diversity are urgently needed (e.g., to enhance precision and credibility of global change assessments). Aim The aim is to present the EcoSyst framework, a set of general principles and methods for systematization of natural diversity that simultaneously addresses biotic and abiotic variation, and to discuss perspectives opened by this framework. Innovation EcoSyst provides a framework for systematizing natural variation in a consistent manner across different levels of organization. At each ecodiversity level, EcoSyst principles can be used to establish: (a) an extensive attribute system with descriptive variables that cover all relevant sources of variation; (b) a hierarchical‐type system; and (c) a set of guidelines for land‐cover mapping that is consistent across spatial scales. EcoSyst type systems can be conceptualized as multidimensional models, by which a key characteristic (the response) is related to variation in one or more key sources of variation (predictors). EcoSyst type hierarchies are developed by a gradient‐based iterative procedure, by which the “ecodiversity distance” (i.e., the extent to which the key characteristic differs between adjacent candidate types) is standardized and the ecological processes behind observed patterns are explicitly taken into account. Application We present “Nature in Norway” (NiN), an implementation of the EcoSyst framework for Norway for the ecosystem and landscape levels of ecodiversity. Examples of applications to research and management are given. Conclusion The EcoSyst framework provides a theoretical platform, principles and methods that can complement and enhance initiatives towards a global‐scale systematics of ecodiversity. iodiversity complex gradient continuum theory ecodiversity ecosystem geodiversity gradient landscape mapping typology

• Eriksen, Eva Lieungh; Ullerud, Heidrun Asgeirsdatter; Halvorsen, Rune; Aune, Sigrun; Bratli, Harald & Horvath, Peter [Show all 9 contributors for this article] (2018). Point of view: error estimation in field assignment of land-cover types. Phytocoenologia. ISSN 0340-269X. 49(2), p. 135–148. doi: 10.1127/phyto/2018/0293. Full text in Research Archive Show summary

  Questions: Substantial variation between observers has been found when comparing parallel land-cover maps, but how can we know which map is better? What magnitude of error and inter-observer variation is expected when assigning land-cover types and is this affected by the hierarchical level of the type system, observer characteristics, and ecosystem properties? Study area: Hvaler, south-east Norway. Methods: Eleven observers assigned mapping units to 120 stratified random points. At each observation point, the observers first assigned a mapping unit to the point independently. The group then decided on a ‘true’ reference mapping unit for that point. The reference was used to estimate total error. ‘Ecological distance’ to the reference was calculated to grade the errors. Results: Individual observers frequently assigned different mapping units to the same point. Deviating assignments were often ecologically close to the reference. Total error, as percentage of assignments that deviated from the reference, was 35.0% and 16.4% for low and high hierarchical levels of the land-covertype system, respectively. The corresponding figures for inter-observer variation were 42.8% and 19.4%, respectively. Observer bias was found. Particularly high error rates were found for land-cover types characterised by human disturbance. Conclusions: Access to a ‘true’ mapping unit for each observation point enabled estimation of error in addition to the inter-observer variation typically estimated by the standard pairwise comparisons method for maps and observers. Three major sources of error in the assignment of land-cover types were observed: dependence on system complexity represented by the hierarchical level of the land-cover-type system, dependence on the experience and personal characteristics of the observers, and dependence on properties of the mapped ecosystem. The results support the necessity of focusing on quality in land-cover mapping, among commissioners, practitioners and other end users.

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• Lieungh, Eva; Keetz, Lasse Torben & Melteig, Elina (2023). Alle har gratis tilgang til en av verdens mest komplekse vitenskapelige modeller. Nå blir den enklere å bruke. [Internet]. Forskning.no.
• Lieungh, Eva; Yilmaz, Yeliz; Tang, Hui; Keetz, Lasse Torben; Olsen, Siri Lie & Gya, Ragnhild [Show all 11 contributors for this article] (2023). Complementary field and modelling experiments: alpine vegetation under climate warming.
• Lieungh, Eva (2023). Computer simulation of a field experiment in the Norwegian mountains.
• Lieungh, Eva; Melteig, Elina & Keetz, Lasse Torben (2023). Nå er det lettere å bli klimaforsker. [Internet]. titan.no.
• Bryn, Anders; Brynildsrud, Katrine Marie; Horvath, Peter; Keetz, Lasse Torben; Lieungh, Eva & Naas, Adam Eindride [Show all 9 contributors for this article] (2023). “Ground-truth" from field-based ecosystem mapping.
• Lieungh, Eva (2022). The Land Sites Platform makes CLM-FATES modelling easy. Now what? Show summary

  https://www.mn.uio.no/geo/english/research/projects/emerald/events/webinar/webinar-dec-2022.html

• Karimi-Asli, Kaveh; Keetz, Lasse Torben; Lieungh, Eva; Yilmaz, Yeliz A.; Tang, Hui & Torma, Michal [Show all 7 contributors for this article] (2022). NorESMhub/noresm-land-sites-platform: Release v1.0.0.
• Gya, Ragnhild; Töpper, Joachim Paul; Olsen, Siri Lie; Lieungh, Eva; Hjortland Östman, Silje Andrea & Egelkraut, Dagmar Dorothea [Show all 7 contributors for this article] (2022). Population dynamics of two alpine species in response to transplant, removal and warming experiments.
• Lieungh, Eva & Brynildsrud, Katrine Marie (2021). Opplæring og kartlegging med Natur i Norge.
• Fouilloux, Anne Claire; Tang, Hui; Lieungh, Eva; Geange, Sonya Rita; Horvath, Peter & Bryn, Anders (2020). FATES on GALAXY facilitates ecologist and climate modeler collaboration.
• Fouilloux, Anne Claire; Tang, Hui; Lieungh, Eva; Geange, Sonya Rita; Horvath, Peter & Bryn, Anders (2020). Climate JupyterLab as an interactive tool in Galaxy.
• Fouilloux, Anne Claire; Tang, Hui; Lieungh, Eva; Geange, Sonya Rita; Horvath, Peter & Bryn, Anders (2020). Functionally Assembled Terrestrial Ecosystem Simulator (FATES) with Community Land Model in Galaxy.
• Lieungh, Eva; Bryn, Anders; Stordal, Frode; Bjerke, Jarle W.; Tonjer, Lea-Rebekka & Bright, Ryan M. (2020). Norske fjell gror igjen i et varmere klima. Aftenposten (morgenutg. : trykt utg.). ISSN 0804-3116. p. 20–21.
• Lieungh, Eva (2019). Plantenes planet.
• Skarpaas, Olav; Eriksen, Eva Lieungh & Bryn, Anders (2019). Klimaforskning ved NHM.
• Eriksen, Eva Lieungh (2019). Plantenes planet.
• Vandvik, Vigdis; Töpper, Joachim Paul; Alexander, Jake M.; Skarpaas, Olav; Olsen, Siri Lie & Klanderud, Kari [Show all 14 contributors for this article] (2019). INCLINE: Indirect climate change impacts on alpine plant communities.
• Halvorsen, Rune; Eriksen, Eva Lieungh; Wollan, Anders Kvalvåg; Ullerud, Heidrun Asgeirsdatter; Bryn, Anders & Bratli, Harald [Show all 7 contributors for this article] (2018). Forarbeid til standard for kontroll av kvalitet i naturtypekart etter NiN. FoU rapport 1. Artsdatabanken. ISSN 978-82-92838-51-8.
• Wollan, Anders Kvalvåg; Bratli, Harald; Bryn, Anders; Eriksen, Eva Lieungh; Nilsen, Anne-Barbi & Ullerud, Heidrun Asgeirsdatter [Show all 7 contributors for this article] (2018). Test av metoder for etterkontroll av kvalitet i naturtypekart etter NiN versjon 2, på Jeløya 2017. Natur i Norge FoU-Rapport 2. . Artsdatabanken.

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