Browsing HVL Open by Author "Halvorsen, Rune"
Now showing items 1-7 of 7
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Advancing restoration ecology: A new approach to predict time to recovery
Rydgren, Knut; Halvorsen, Rune; Töpper, Joachim Paul; Auestad, Inger; Hamre, Liv Norunn; Jongejans, Eelke; Sulavik, Jan (Journal article; Peer reviewed, 2018)1. Species composition is a vital attribute of any ecosystem. Accordingly, ecological restoration often has the original, or “natural,” species composition as its target. However, we still lack adequate methods for predicting ... -
Assessing recovery of alpine spoil heaps by vascular plant, bryophyte, and lichen functional traits
Sulavik, Jan; Auestad, Inger; Halvorsen, Rune; Rydgren, Knut (Peer reviewed; Journal article, 2020)Functional traits are linked to ecosystem processes and services and therefore relevant in recovery assessment. However, traits of bryophytes and lichens, important components of many ecosystems, have received less attention ... -
Assessing restoration success by predicting time to recovery- But by which metric?
Rydgren, Knut; Auestad, Inger; Halvorsen, Rune; Hamre, Liv Norunn; Jongejans, Eelke; Töpper, Joachim Paul; Sulavik, Jan (Peer reviewed; Journal article, 2019)1. Restoration of degraded ecosystems may take decades or even centuries. Accordingly, information about the current direction and speed of recovery provided by methods for predicting time to recovery may give important ... -
Bunching up the background betters bias in species distribution models
Vollering, Julien Martin Marie; Halvorsen, Rune; Auestad, Inger; Rydgren, Knut (Journal article; Peer reviewed, 2019)Sets of presence records used to model species’ distributions typically consist of observations collected opportunistically rather than systematically. As a result, sampling probability is geographically uneven, which may ... -
Composite landscape predictors improve distribution models of ecosystem types
Simensen, Trond; Horvath, Peter; Vollering, Julien; Erikstad, Lars; Halvorsen, Rune; Bryn, Anders (Peer reviewed; Journal article, 2020)Aim Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red‐list assessments. While distribution modelling methods have been applied ... -
The MIAmaxent R package: Variable transformation and model selection for species distribution models
Vollering, Julien; Halvorsen, Rune; Mazzoni, Sabrina (Peer reviewed; Journal article, 2019)The widely used “Maxent” software for modeling species distributions from presence‐only data (Phillips et al., Ecological Modelling, 190, 2006, 231) tends to produce models with high‐predictive performance but low‐ecological ... -
Use climatic space-for-time substitutions with care: Not only climate, but also local environment affect performance of the key forest species bilberry along elevation gradient
Auestad, Inger; Rydgren, Knut; Halvorsen, Rune; Avdem, Ingrid Hofmo; Berge, Rannveig; Bollingberg, Ina Marie; Lima, Oline (Peer reviewed; Journal article, 2023)An urgent aim of ecology is to understand how key species relate to climatic and environmental variation, to better predict their prospects under future climate change. The abundant dwarf shrub bilberry (Vaccinium myrtillus ...