Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Forfattere
Ravindu Panditharathne Miyuru Gunathilake Imiya M. Chathuranika Upaka Rathnayake Mukand S. Babel Manoj K. JhaSammendrag
Rainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen’s slope test, Pettitt’s test, indicators of hydrological alteration (IHA), and Pearson’s correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt’s test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning, flood and disaster mitigation, agricultural operations planning, and hydropower generation in the NRB.
Sammendrag
Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today’s world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction.
Forfattere
Jian LiuSammendrag
Det er ikke registrert sammendrag
Sammendrag
Prosjektet hadde som mål å øke kunnskapen om økologisk tilstand i vannforekomster i jordbruksområder på Østlandet, der vannforekomstene er kraftig påvirket av hydromorfologiske inngrep, men ikke nødvendigvis er definert som sterkt modifiserte vannforekomster (SMVF) etter vannforskriften. For å få et representativt utvalg, ble ulike grader av utrettinger av elvestrengen valgt ut. Seks av åtte elver hadde mer enn 80 % av elveløpet rettet ut. Vi fant en sammenheng mellom graden av utretting og manglende kantvegetasjon. Halvparten av elvene hadde mindre enn 10 % intakt kantvegetasjon. Vi fant også en sammenheng mellom økende andel naturlig meandrerende deler av elva og økt tetthet av ørret (Salmo trutta). Tetthet av ørret øker også med andel kantvegetasjon langs hele elveløpet og økt variasjon i bunnsubstratet. Der det var mye hydromorfologiske variasjon i vannstrengen, var det flere arter av bunndyr enn der det var mindre hydromorfologiske variasjon. Ørret og laks kan brukes som indikatorarter for endret hydromorfologi, med dagens indekser. Vi vil anbefale å utvikle en indeks for bunndyr som responderer på hydromorfologiske endringer i vannstrengen. Bunndyr-indeksen ASPT ser ikke ut til å kunne benyttes. Vi vil anbefale å utarbeide indekser for graden av modifisering av vassdraget, herunder en indeks for graden av kantvegetasjon.
Forfattere
Karin Juul Hesselsøe Anne friederike Borchert Trygve S. Aamlid Bjarni Hannesson Karin Normann Per Rasmussen Jørgen Hornslien Pia Heltoft ThomsenSammendrag
Det er ikke registrert sammendrag
Forfattere
Karin Juul Hesselsøe Anne friederike Borchert Karin Normann Trygve S. Aamlid Pia Heltoft ThomsenSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Through their ephemeral reproductive structures (fruiting bodies), ectomycorrhizal forest soil fungi provide a resource for a plethora of organisms. Thus, resolving what biotic and abiotic factors determine the occurrence and abundance of fruiting bodies is fundamental for understanding the dynamics of forest trophic networks. While the influence of abiotic factors such as moisture and temperature on fungal fruiting are relatively well established, little is known about how these processes interact with the evolutionary history of fungal species to determine when, where, and in which abundance fungal fruiting bodies will emerge. A specific knowledge gap relates to whether species' responses to their environment are phylogenetically structured. Here, we ask whether related fungal taxa respond similarly to climatic factors and forest habitat characteristics, and whether such correlated responses will affect the assembly of fungal fruiting communities. To resolve these questions, we fitted joint species distribution models combining data on the species composition and abundance of fungal fruiting bodies, environmental variation, and phylogenetic relationships among fungal taxa. Our results show that both site-level forest characteristics (dominant tree species and forest age) and climatic factors related to phenology (effective heat sum) greatly influence the occurrence and abundance of fruiting bodies. More importantly, while different fungal species responded unequally to their shared environment, there was a strong phylogenetic signal in their responses, so that related fungal species tended to fruit under similar environmental conditions. Thus, not only are fruiting bodies short-lived and patchily distributed, but the availability of similar resources will be further aggregated in time and space. These strong constraints on resource availability for fungus-associated taxa highlight the potential of fungus-based networks as a model system for studies on the ecology and evolution of resource–consumer relations in ephemeral systems of high spatiotemporal patchiness.
Sammendrag
Resource specialization and ecological speciation arising through host-associated genetic differentiation (HAD) are frequently invoked as an explanation for the high diversity of plant-feeding insects and other organisms with a parasitic lifestyle. While genetic studies have demonstrated numerous examples of HAD in insect herbivores, the rarity of comparative studies means that we still lack an understanding of how deterministic HAD is, and whether patterns of host shifts can be predicted over evolutionary timescales. We applied genome-wide single nucleotide polymorphism and mitochondrial DNA sequence data obtained through genome resequencing to define species limits and to compare host-plant use in population samples of leaf- and bud-galling sawflies (Hymenoptera: Tenthredinidae: Nematinae) collected from seven shared willow (Salicaceae: Salix) host species. To infer the repeatability of long-term cophylogenetic patterns, we also contrasted the phylogenies of the two galler groups with each other as well as with the phylogeny of their Salix hosts estimated based on RADseq data. We found clear evidence for host specialization and HAD in both of the focal galler groups, but also that leaf gallers are more specialized to single host species compared with most bud gallers. In contrast to bud gallers, leaf gallers also exhibited statistically significant cophylogenetic signal with their Salix hosts. The observed discordant patterns of resource specialization and host shifts in two related galler groups that have radiated in parallel across a shared resource base indicate a lack of evolutionary repeatability in the focal system, and suggest that short- and long-term host use and ecological diversification in plant-feeding insects are dominated by stochasticity and/or lineage-specific effects.