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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2026

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Abstract

This report examines how co-occurring non-native species can interact to create cumulative impacts on ecosystems. Non-native species may interact in additive, antagonistic, or synergistic ways. Through literature review, we found theoretical foundations and empirical examples showing that such interactions often occur. Synergistic interactions are of particular concern. Certain ecosystems appear particularly susceptible, including agricultural landscapes, urban environments, riparian systems, shipping-influenced marine areas, and islands with naïve fauna. We conclude that cumulative effects are ecologically important, and that it would be beneficial to incorporate multispecies interactions into risk assessments of non-native species in Norway.

Abstract

Foredrag om den norske rødlista for naturtyper. Foredraget tar for seg hvordan rødlistingen foregår, IUCN-kriteriene, kunnskapsgjennomgang og hovedresultater. NAturtypen kystlynghei brukes som eksempel.

Abstract

Agricultural production is highly dependent upon pollinators to achieve maximum yield and increase global food security. Wild pollinators, such as bees, are declining due to a loss of habitat from agricultural intensification, and the use of domesticated honeybees to supplement pollination services is increasing. Apple is an important, pollinator dependent food crop that commonly experiences pollination and production deficits worldwide. In this thesis, I explored whether pollination and production deficits occur in Norwegian apple orchards and what factors might be driving potential deficits. To test for pollination (seed set) and production (yield) deficits I conducted a supplemental pollination experiment for three cultivars, in eighteen orchards, in two distinct growing regions in Norway, over two years. I also assessed which pollinators are present in Norwegian apple orchards and how different groups of bees and their behaviour affect pollination of apple. Lastly, I studied different management practices to increase bee diversity and pollination success, by increasing alternate floral resources and evaluating orchard design that promotes cross-pollination. Pollination and production deficits were found across all locations, with differences in pollination deficits among cultivars. I also found that a high abundance of wild bees increases seed set in apples—a key indicator of pollination success. Behaviour also varied among bee groups, for example bumblebees visited more flowers, while solitary bees were slow, but potentially more thorough, foragers, which increases pollen deposition. Wild bees visited more apple flowers than dandelion flowers (Taraxacum spp.) when orchards were left unmowed. I also found that a higher abundance of dandelions increased bee visitation to apple flowers, suggesting higher floral diversity can increase pollination success and support a greater diversity of bees. In addition, block design orchards appear to limit cross-pollination among apple cultivars, and management actions to decrease the distance among compatible apple cultivars is needed to achieve sufficient pollination. Overall, my results suggest that greater pollination and production of apples in Norway is possible, and management actions should focus on increasing wild bee abundance and diversity, increasing alternate floral resources, and optimising orchard design to facilitate cross-pollination across shorter distances. Such actions have the potential to ensure greater yields of higher quality apples for human consumption and increased economic output for farmers.

2025

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Abstract

Pollinator conservation schemes typically focus on conserving existing, restoring degraded, or creating new wild bee habitats. Their effectiveness depends on dispersal corridors enabling habitat colonization by bees. However, the role of seminatural linear landscape structures (LLS) in connecting pollinator communities across intensively managed landscapes remains poorly understood. We analyzed 953 occurrences of wild bees comprising 79 nonparasitic species sampled at 68 study sites across a Norwegian and a Danish landscape. We first tested whether bee species richness was positively associated with the lengths of seminatural LLS in bee foraging ranges of study sites while controlling for local plant species richness. We then combined maps identifying seminatural LLS with least‐cost path (LCP) analysis to determine whether bee species compositional similarity, a proxy for connectivity, decreased as LCP length increased. The length of seminatural LLS, such as forest edges, was positively correlated with bee species richness and habitat connectivity. Specifically, wild bee species richness sampled along roadsides increased as the length of seminatural LLS increased in 1.5 km circles around the study sites, and increased as local plant species richness increased. The most likely dispersal routes between our bee communities tracked forest edges. The length of LCPs provided better models of bee species compositional similarity than geographic distance, suggesting that seminatural LLS, particularly forest edges, act as dispersal corridors in intensively managed landscapes. However, bee species compositional similarity among communities depended on site‐specific plant species richness and similarity in plant community composition, which highlights the importance of improving the habitat quality of seminatural LLS if they are to function as dispersal corridors. Our findings suggest that maps of LCPs can be used to identify important dispersal corridors between bee habitats and to direct wild bee habitat management actions along seminatural LLS to facilitate the dispersal of bees in intensively managed landscapes.

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Abstract

As droughts become longer and more intense, impacts on terrestrial primary productivity are expected to increase progressively. Yet, some ecosystems appear to acclimate to multiyear drought, with constant or diminishing reductions in productivity as drought duration increases. We quantified the combined effects of drought duration and intensity on aboveground productivity in 74 grasslands and shrublands distributed globally. Ecosystem acclimation with multiyear drought was observed overall, except when droughts were extreme (i.e., ≤1-in-100-year likelihood of occurrence). Productivity losses after four consecutive years of extreme drought increased by ~2.5-fold compared with those of the first year. These results portend a foundational shift in ecosystem behavior if drought duration and intensity increase, from maintenance of reduced functioning over time to progressive and profound losses of productivity when droughts are extreme.

To document

Abstract

A number of modelling frameworks exist to estimate resilience from ecological datasets. A subset of these frameworks seeks to estimate the whole ‘stability landscape', which can be used to calculate resilience and identify stable states and tipping points. These methods provide opportunities for insights into possible causes and consequences of variation in ecosystem resilience and dynamics. However, because such models can be complex to implement, there has so far been a substantial barrier to their application in ecological research. Here, we present the ‘mixglm' package for R software, which parametrizes stability landscapes using a mixture model approach. It provides tools for the calculation of resilience, identification of stable states and tipping points, as well as visualization functions. Flexible model specification allows the mean, precision, and probability of each mixture component to be linked to multiple predictors, such as environmental covariates. ‘mixglm' is based on Bayesian inference via NIMBLE and supports normal, beta, gamma, and negative binomial distributed response variables. We illustrate the use of ‘mixglm' with a published case of tree cover in South America, which reports a stability landscape with distinct stable states. Using ‘mixglm', we replicated the identification of these states. Moreover, we quantified the uncertainty of our estimates, and computed resilience estimates of South America's forests. We also conducted a power analysis to provide guidance regarding required sample sizes. ‘mixglm' can be readily used to describe stability landscapes and identify stable states in most spatial datasets, and it is accompanied by tools for the calculation of resilience estimates.