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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.

2024

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Abstract

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.

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Abstract

Vegetasjon langs bekker og vannveier er viktig for biologisk mangfold, jordvern, erosjonskontroll, reduksjon av risiko for flom og tørke, og for elvens hydromorfologi. Copernicus Land Monitoring Service tilbyr geografiske produkter til støtte for forvaltning av land og vann. I denne rapporten analyserer vi potensialet til Riparian Zones temakart (RZ) for bruk til kartlegging og overvåking av vegetasjon langs bekker og vannveier i Norge og Polen. Vi inkluderer også analyser av temakartet Small Woody Features (SWF) innenfor områder kartlagt i RZ. Vi sammenlignet RZ med nasjonale data og flybilder for å verifisere kvaliteten til datasettet, både for status og endringer i arealdekke og arealbruk langs bekker og vannveier. Vi konkluderer med at den tematiske nøyaktigheten var ganske god for vann, jordbruksareal og skog, men at andre klasser ikke korresponderte like godt med de nasjonale dataene. Mange av avvikene kan skyldes forskjeller i klassifiseringssystemene, kildedatene og kartleggingsinstruksene for de forskjellige datasettene. I tillegg fant vi at den romlige oppløsningen av RZ er utilstrekkelig for detaljert overvåking, særlig i jordbrukslandskap. Likevel gir RZ en standardisert og harmonisert metodikk for hele Europa, og er et steg i riktig retning for å kunne overvåke arealdekke og arealbruk i disse dynamiske og viktige områdene.

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Abstract

Accurate locating and counting of litopenaeus vannamei fry can provide substantial support for vannamei fry sales and scientific feeding. However, traditional methods not only require visual observation by experts, but also are time-consuming and labor-intensive, with no guarantee to reach consensus between salesmen and customers. In contrast, more innovative methods require more expensive equipment or are only effective under specific conditions. The small size and high density nature of the shrimp fry makes its counting even more challenging. In this study, a point prediction method for counting and localization of litopenaeus vannamei fry with region-based super-resolution enhancement (PPCL-RSE) is proposed. Through the inclusion of three modules of density partitioning, high-density region expansion and regional super-resolution, the accuracy of fry counting and locating is improved. The model is deployed on a cloud server for convenient fry counting and localization based on images taken by smartphone cameras. To achieve this, we create a dataset called Vannamei-983 which contains images with more than 1,000,000 fry labeled. The proposed method shows accuracies of 99.04 % and 97.71 % in counting and localization of shrimp fry in low- and high-density images, respectively. The excellent model performance also demonstrate the effectiveness of the strategies considered in the study.