Greening of Svalbard.

Svalbard, located between 76°30'N and 80°50'N, is among the regions in the world with the most rapid temperature increase. We processed a cloud-free time-series of MODIS-NDVI for Svalbard. The dataset is interpolated to daily data during the 2000-2022 period with 232 m pixel resolution. The onset of growth, with a clear phenological definition, has been mapped each year. Then the integrated NDVI from the onset (O) of growth each year to the time of average (2000-2022) peak (P) of growth (OP NDVI) have been calculated. OP NDVI has previously shown high correlation with field-based tundra productivity. Daily mean temperature data from 11 meteorological stations are compared with the NDVI data. The OP NDVI values show very high and significant correlation with growing degree days computed from onset to time of peak of growth for all the meteorological stations used. On average for the entire Svalbard, the year 2016 first had the highest greening (OP NDVI values) recorded since the year 2000, then the greening in 2018 surpassed 2016, then 2020 surpassed 2018, and finally 2022 was the year with the overall highest greening by far for the whole 2000-2022 period. This shows a rapid recent greening of Svalbard very strongly linked to temperature increase, although there are regional differences: the eastern parts of Svalbard show the largest variability between years, most likely due to variability in the timing of sea-ice break-up in adjacent areas. Finally, we find that areas dominated by manured moss-tundra in the polar desert zone require new methodologies, as moss does not share the seasonal NDVI dynamics of tundra communities.

Outbreaks by canopy-feeding geometrid moth cause state-dependent shifts in understorey plant communities.

The increased spread of insect outbreaks is among the most severe impacts of climate warming predicted for northern boreal forest ecosystems. Compound disturbances by insect herbivores can cause sharp transitions between vegetation states with implications for ecosystem productivity and climate feedbacks. By analysing vegetation plots prior to and immediately after a severe and widespread outbreak by geometrid moths in the birch forest-tundra ecotone, we document a shift in forest understorey community composition in response to the moth outbreak. Prior to the moth outbreak, the plots divided into two oligotrophic and one eutrophic plant community. The moth outbreak caused a vegetation state shift in the two oligotrophic communities, but only minor changes in the eutrophic community. In the spatially most widespread communities, oligotrophic dwarf shrub birch forest, dominance by the allelopathic dwarf shrub Empetrum nigrum ssp. hermaphroditum, was effectively broken and replaced by a community dominated by the graminoid Avenella flexuosa, in a manner qualitatively similar to the effect of wild fires in E. nigrum communities in coniferous boreal forest further south. As dominance by E. nigrum is associated with retrogressive succession the observed vegetation state shift has widespread implications for ecosystem productivity on a regional scale. Our findings reveal that the impact of moth outbreaks on the northern boreal birch forest system is highly initial-state dependent, and that the widespread oligotrophic communities have a low resistance to such disturbances. This provides a case for the notion that climate impacts on arctic and northern boreal vegetation may take place most abruptly when conveyed by changed dynamics of irruptive herbivores.

The northernmost hyperspectral FLoX sensor dataset for monitoring of high-Arctic tundra vegetation phenology and Sun-Induced Fluorescence (SIF).

A hyperspectral field sensor (FloX) was installed in Adventdalen (Svalbard, Norway) in 2019 as part of the Svalbard Integrated Arctic Earth Observing System (SIOS) for monitoring vegetation phenology and Sun-Induced Chlorophyll Fluorescence (SIF) of high-Arctic tundra. This northernmost hyperspectral sensor is located within the footprint of a tower for long-term eddy covariance flux measurements and is an integral part of an automatic environmental monitoring system on Svalbard (AsMovEn), which is also a part of SIOS. One of the measurements that this hyperspectral instrument can capture is SIF, which serves as a proxy of gross primary production (GPP) and carbon flux rates. This paper presents an overview of the data collection and processing, and the 4-year (2019-2021) datasets in processed format are available at: https://thredds.met.no/thredds/catalog/arcticdata/infranor/NINA-FLOX/raw/catalog.html associated with https://doi.org/10.21343/ZDM7-JD72 under a CC-BY-4.0 license. Results obtained from the first three years in operation showed interannual variation in SIF and other spectral vegetation indices including MERIS Terrestrial Chlorophyll Index (MTCI), EVI and NDVI. Synergistic uses of the measurements from this northernmost hyperspectral FLoX sensor, in conjunction with other monitoring systems, will advance our understanding of how tundra vegetation responds to changing climate and the resulting implications on carbon and energy balance.

Changes in Onset of Vegetation Growth on Svalbard, 2000-2020.

The global temperature is increasing, and this is affecting the vegetation phenology in many parts of the world. The most prominent changes occur at northern latitudes such as our study area, which is Svalbard, located between 76°30'N and 80°50'N. A cloud-free time series of MODIS-NDVI data was processed. The dataset was interpolated to daily data during the 2000-2020 period with a 231.65 m pixel resolution. The onset of vegetation growth was mapped with a NDVI threshold method which corresponds well with a recent Sentinel-2 NDVI-based mapping of the onset of vegetation growth, which was in turn validated by a network of in-situ phenological data from time lapse cameras. The results show that the years 2000 and 2008 were extreme in terms of the late onset of vegetation growth. The year 2020 had the earliest onset of vegetation growth on Svalbard during the 21-year study. Each year since 2013 had an earlier or equally early timing in terms of the onset of the growth season compared with the 2000-2020 average. A linear trend of 0.57 days per year resulted in an earlier onset of growth of 12 days on average for the entire archipelago of Svalbard in 2020 compared to 2000.

Plant phenological variation related to temperature in Norway during the period 1928-1977.

First flowering was observed in some native herbaceous and woody plants in Norway at latitudes of ∼58°N to nearly 71°N from 1928 to 1977. For woody plants, the timing for first bud burst was also often observed. Generally, there were highly significant correlations (0.1% level) between the timing of nearly all spring-early summer observations in plants and gridded mean monthly temperatures for the various phenophases (up to 65% of the variance was accounted for, less so for the autumn phenophases). Analyses by a low pass Gaussian smoothing technique showed early phenophases in the warm period of the early 1930s, delayed phases for most sites and species in colder periods in the early 1940s, mid-1950s, late 1960s and also towards the end of the study period in the late 1970s, all in approximately 10- to 12-year cycles. The study thus starts in a relatively early (warm) period and ends towards a late (cooler) period, resulting in mainly weak linear trends in phenophases throughout the total period. The end of the observation period in 1977 also predates the strongly increasing "earliness" in phenology of plants in most Norwegian lowland areas due to global warming. The strong altitudinal and latitudinal variations in Norway, however, do cause regional differences in trends. The study showed a tendency towards earlier spring phenophases all along the western coast from south to north in the country. On the other hand, the northeasternmost site and also the more continental sites in the southeast showed tendencies to weak trends for later phenophases during the 50 years of these field observations.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.

Disentangling the coupling between sea ice and tundra productivity in Svalbard.

The rapid decline in Arctic sea ice poses urgent questions concerning its ecological effects, such as on tundra terrestrial productivity. However, reported sea ice/terrestrial productivity linkages have seldom been constrained, and the mechanism governing them remains elusive, with a diversity of spatial scales and metrics proposed, at times in contradiction to each other. In this study, we use spatially explicit remotely sensed sea ice concentration and high-resolution terrestrial productivity estimates (Normalised Difference Vegetation Index, NDVI) across the Svalbard Archipelago to describe local/sub-regional and large-scale components of sea ice/terrestrial productivity coupling. Whereas the local/sub-regional component is attributed to sea breeze (cold air advection from ice-covered ocean onto adjacent land during the growing season), the large-scale component might reflect co-variability of sea ice and tundra productivity due to a common forcing, such as large-scale atmospheric circulation (North Atlantic Oscillation, NAO). Our study clarifies the range of mechanisms in sea ice/terrestrial productivity coupling, allowing the generation of testable hypotheses about its past, present, and future dynamics across the Arctic.

Variability of the start of the growing season in Fennoscandia, 1982-2002.

Fennoscandia is characterized by a large degree of climatic diversity. Vegetation phenology may respond differently to climate change according to the climatic gradients within the region. To map the annual and spatial variability of the start of the growing season (SOS) in Fennoscandia, the twice-monthly GIMMS-NDVI satellite dataset was used. The data set has an 8 x 8 km(2) spatial resolution and covers the period from 1982 to 2002. The mapping was done by applying pixel-specific threshold values to the NDVI data. These threshold values were determined form surface phenology data on birch (Betula sp.). Then, we produced NDVI based maps of SOS for each of the 21 years. Finally, the time differences between the SOS and the last day of snow cover, as well as dates of passing different temperatures, were analyzed for 21 meteorological stations. The analyses showed that 1985 was the most extreme year in terms of late SOS. In terms of early SOS, the year 1990 was by far the most extreme. Locally, the SOS has an average range of 1 month between the earliest and latest recorded SOS, with a trend towards a bigger range in the oceanic parts. The results indicate that a 1 degrees C increase in spring temperatures in general corresponds to an advancement of 5-6 days in SOS. However, there is a clear trend according to the degree of oceanity, with a 1 degrees C increase in the most oceanic parts corresponding roughly to 7-9 days earlier SOS, compared to less than 5 days earlier in the continental parts.