Trends in NDVI and Tundra Community Composition in the Arctic of NE Alaska Between 1984 and 2009

Canopy reflectance models illustrate varying NDVI responses to change in high latitude ecosystems

Multiyear trends in Normalized Difference Vegetation Index (NDVI) have been used as metrics of high latitude ecosystem change based on the assumption that NDVI change is associated with ecological change, generally as changes in green vegetation amount (green leaf area index [LAI] or plant cover). Further, no change in NDVI is often interpreted as no change in these variables. Three canopy reflectance models including linear mixture model, the SAIL (Scattering from Arbitrarily Inclined Leaves) model, and the GeoSail model were used to simulate scenarios representing high latitude landscape NDVI responses to changes in LAI and plant cover. The simulations showed inconsistent NDVI responses. Clear increases in NDVI are generally associated with increases in LAI and plant cover. At higher values of LAI, the change in NDVI per unit change in LAI decreases, with very little change in spruce forest NDVI where crown cover is >50% and at the tundra-taiga ecotone with transitions from shrub tundra to spruce woodland. These lower responses may bias the interpretation of greening/browning trends in boreal forests. Variations in water or snow coverage were shown to produce outsized nonbiological NDVI responses. Inconsistencies in NDVI responses exemplify the need for care in the interpretation of NDVI change as a metric of high latitude ecosystem change, and that landscape characteristics in terms of the type of cover and its characteristics, such as the initial plant cover, must be taken into account in evaluating the significance of any observed NDVI trends.

Spring phenology drives range shifts in a migratory Arctic ungulate with key implications for the future

Annual variation in phenology can have profound effects on the behavior of animals. As climate change advances spring phenology in ecosystems around the globe, it is becoming increasingly important to understand how animals respond to variation in the timing of seasonal events and how their responses may shift in the future. We investigated the influence of spring phenology on the behavior of migratory, barren-ground caribou (Rangifer tarandus), a species that has evolved to cope with short Arctic summers. Specifically, we examined the effect of spring snow melt and vegetation growth on the current and potential future space-use patterns of the Porcupine Caribou Herd (PCH), which exhibits large, inter-annual shifts in their calving and post-calving distributions across the U.S.-Canadian border. We quantified PCH selection for snow melt and vegetation phenology using machine learning models, determined how selection resulted in annual shifts in space-use, and then projected future distributions based on climate-driven phenology models. Caribou exhibited strong, scale-dependent selection for both snow melt and vegetation growth. During the calving season, caribou selected areas at finer scales where the snow had melted and vegetation was greening, but within broader landscapes that were still brown or snow covered. During the post-calving season, they selected vegetation with intermediate biomass expected to have high forage quality. Annual variation in spring phenology predicted major shifts in PCH space-use. In years with early spring phenology, PCH predominately used habitat in Alaska, while in years with late phenology, they spent more time in Yukon. Future climate conditions were projected to advance spring phenology, shifting PCH calving and post-calving distributions further west into Alaska. Our results demonstrate that caribou selection for habitat in specific phenological stages drive dramatic shifts in annual space-use patterns, and will likely affect future distributions, underscoring the importance of maintaining sufficient suitable habitat to allow for behavioral plasticity.

Unexpected greening in a boreal permafrost peatland undergoing forest loss is partially attributable to tree species turnover

Time series of vegetation indices derived from satellite imagery are useful in measuring vegetation response to climate warming in remote northern regions. These indices show that productivity is generally declining in the boreal forest, but it is unclear which components of boreal vegetation are driving these trends. We aimed to compare trends in the normalized difference vegetation index (NDVI) to forest growth and demographic data taken from a 10 ha mapped plot located in a spruce-dominated boreal peatland. We used microcores to quantify recent growth trends and tree census data to characterize mortality and recruitment rates of the three dominant tree species. We then compared spatial patterns in growth and demography to patterns in Landsat-derived maximum NDVI trends (1984-2019) in 78 pixels that fell within the plot. We found that NDVI trends were predominantly positive (i.e., "greening") in spite of the ongoing loss of black spruce (the dominant species; 80% of stems) from the plot. The magnitude of these trends correlated positively with black spruce growth trends, but was also governed to a large extent by tree mortality and recruitment. Greening trends were weaker (lower slope) in areas with high larch mortality, and high turnover of spruce and birch, but stronger (higher slope) in areas with high larch recruitment. Larch dominance is currently low (~11% of stems), but it is increasing in abundance as permafrost thaw progresses and will likely have a substantial influence on future NDVI trends. Our results emphasize that NDVI trends in boreal peatlands can be positive even when the forest as a whole is in decline, and that the magnitude of trends can be strongly influenced by the demographics of uncommon species.

The Shrinking Resource Base of Pastoralism: Saami Reindeer Husbandry in a Climate of Change

The productive performance of large ungulates in extensive pastoral grazing systems is modulated simultaneously by the effects of climate change and human intervention independent of climate change. The latter includes the expansion of private, civil and military activity and infrastructure and the erosion of land rights. We used Saami reindeer husbandry in Norway as a model in which to examine trends in, and to compare the influence of, both effects on a pastoral grazing system. Downscaled projections of mean annual temperature over the principal winter pasture area (Finnmarksvidda) closely matched empirical observations across 34 years to 2018. The area, therefore, is not only warming but seems likely to continue to do so. Warming notwithstanding, 50-year (1969–2018) records of local weather (temperature, precipitation and characteristics of the snowpack) demonstrate considerable annual and decadal variation which also seems likely to continue and alternately to amplify and to counter net warming. Warming, moreover, has both positive and negative effects on ecosystem services that influence reindeer. The effects of climate change on reindeer pastoralism are evidently neither temporally nor spatially uniform, nor indeed is the role of climate change as a driver of change in pastoralism even clear. The effects of human intervention on the system, by contrast, are clear and largely negative. Gradual liberalization of grazing rights from the 18th Century has been countered by extensive loss of reindeer pasture. Access to ~50% of traditional winter pasture was lost in the 19th Century owing to the closure of international borders to the passage of herders and their reindeer. Subsequent to this the area of undisturbed pasture within Norway has decreased by 71%. Loss of pasture due to piecemeal development of infrastructure and to administrative encroachment that erodes herders' freedom of action on the land that remains to them, are the principal threats to reindeer husbandry in Norway today. These tangible effects far exceed the putative effects of current climate change on the system. The situation confronting Saami reindeer pastoralism is not unique: loss of pasture and administrative, economic, legal and social constraints bedevil extensive pastoral grazing systems across the globe.

Summer warming explains widespread but not uniform greening in the Arctic tundra biome

Arctic warming can influence tundra ecosystem function with consequences for climate feedbacks, wildlife and human communities. Yet ecological change across the Arctic tundra biome remains poorly quantified due to field measurement limitations and reliance on coarse-resolution satellite data. Here, we assess decadal changes in Arctic tundra greenness using time series from the 30 m resolution Landsat satellites. From 1985 to 2016 tundra greenness increased (greening) at ~37.3% of sampling sites and decreased (browning) at ~4.7% of sampling sites. Greening occurred most often at warm sampling sites with increased summer air temperature, soil temperature, and soil moisture, while browning occurred most often at cold sampling sites that cooled and dried. Tundra greenness was positively correlated with graminoid, shrub, and ecosystem productivity measured at field sites. Our results support the hypothesis that summer warming stimulated plant productivity across much, but not all, of the Arctic tundra biome during recent decades.

Regional mapping of species-level continuous foliar cover: beyond categorical vegetation mapping

The ability to quantify spatial patterns and detect change in terrestrial vegetation across large landscapes depends on linking ground-based measurements of vegetation to remotely sensed data. Unlike non-overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species-level gradients of foliar cover are consistent with the ecological theories of individualistic response of species and niche space. We collected foliar cover data for vascular plant, bryophyte, and lichen species and 17 environmental variables in the Arctic Coastal Plain and Brooks Foothills of Alaska from 2012 to 2017. We integrated these data into a standardized database with 13 additional vegetation survey and monitoring data sets in northern Alaska collected from 1998 to 2017. To map the patterns of foliar cover for six dominant and widespread vascular plant species in arctic Alaska, we statistically associated ground-based measurements of species distribution and abundance to environmental and multi-season spectral covariates using a Bayesian statistical learning approach. For five of the six modeled species, our models predicted 36% to 65% of the observed species-level variation in foliar cover. Overall, our continuous foliar cover maps predicted more of the observed spatial heterogeneity in species distribution and abundance than an existing categorical vegetation map. Mapping continuous foliar cover at the species level also revealed ecological patterns obscured by aggregation in existing plant functional type approaches. Species-level analysis of vegetation patterns enables quantifying and monitoring landscape-level changes in species, vegetation communities, and wildlife habitat independently of subjective categorical vegetation types and facilitates integrating spatial patterns across multiple ecological scales. The novel species-level foliar cover mapping approach described here provides spatial information about the functional role of plant species in vegetation communities and wildlife habitat that are not available in categorical vegetation maps or quantitative maps of broadly defined vegetation aggregates.

Changes in Vegetation Phenology and Productivity in Alaska Over the Past Two Decades

Understanding trends in vegetation phenology and growing season productivity at a regional scale is important for global change studies, particularly as linkages can be made between climate shifts and the vegetation’s potential to sequester or release carbon into the atmosphere. Trends and geographic patterns of change in vegetation growth and phenology from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets were analyzed for the state of Alaska over the period 2000 to 2018. Phenology metrics derived from the MODIS Normalized Difference Vegetation Index (NDVI) time-series at 250 m resolution tracked changes in the total integrated greenness cover (TIN), maximum annual NDVI (MAXN), and start of the season timing (SOST) date over the past two decades. SOST trends showed significantly earlier seasonal vegetation greening (at more than one day per year) across the northeastern Brooks Range Mountains, on the Yukon-Kuskokwim coastal plain, and in the southern coastal areas of Alaska. TIN and MAXN have increased significantly across the western Arctic Coastal Plain and within the perimeters of most large wildfires of the Interior boreal region that burned since the year 2000, whereas TIN and MAXN have decreased notably in watersheds of Bristol Bay and in the Cook Inlet lowlands of southwestern Alaska, in the same regions where earlier-trending SOST was also detected. Mapping results from this MODIS time-series analysis have identified a new database of localized study locations across Alaska where vegetation phenology has recently shifted notably, and where land cover types and ecosystem processes could be changing rapidly.

Status and trends in Arctic vegetation: Evidence from experimental warming and long-term monitoring

Changes in Arctic vegetation can have important implications for trophic interactions and ecosystem functioning leading to climate feedbacks. Plot-based vegetation surveys provide detailed insight into vegetation changes at sites around the Arctic and improve our ability to predict the impacts of environmental change on tundra ecosystems. Here, we review studies of changes in plant community composition and phenology from both long-term monitoring and warming experiments in Arctic environments. We find that Arctic plant communities and species are generally sensitive to warming, but trends over a period of time are heterogeneous and complex and do not always mirror expectations based on responses to experimental manipulations. Our findings highlight the need for more geographically widespread, integrated, and comprehensive monitoring efforts that can better resolve the interacting effects of warming and other local and regional ecological factors.

Vegetation expansion in the subnival Hindu Kush Himalaya

The mountain systems of the Hindu Kush Himalaya (HKH) are changing rapidly due to climatic change, but an overlooked component is the subnival ecosystem (between the treeline and snow line), characterized by short-stature plants and seasonal snow. Basic information about subnival vegetation distribution and rates of ecosystem change are not known, yet such information is needed to understand relationships between subnival ecology and water/carbon cycles. We show that HKH subnival ecosystems cover five to 15 times the area of permanent glaciers and snow, highlighting their eco-hydrological importance. Using satellite data from the Landsat 5, 7 and 8 missions, we measured change in the spatial extent of subnival vegetation from 1993 to 2018. The Landsat surface reflectance-derived Normalized Difference Vegetation Index product was thresholded at 0.1 to indicate the presence/absence of vegetation. Using this product, the strength and direction of time-series trends in the green pixel fraction were measured within three regions of interest. We controlled for cloud cover, snow cover and evaluated the impact of sensor radiometric differences between Landsat 7 and Landsat 8. Using Google Earth Engine to expedite data processing tasks, we show that there has been a weakly positive increase in the extent of subnival vegetation since 1993. Strongest and most significant trends were found in the height region of 5,000-5,500 m a.s.l. across the HKH extent: R2  = .302, Kendall's τ = 0.424, p < .05, but this varied regionally, with height, and according to the sensors included in the time series. Positive trends at lower elevations occurred on steeper slopes whilst at higher elevations, flatter areas exhibited stronger trends. We validated our findings using online photographs. Subnival ecological changes have likely impacted HKH carbon and water cycles with impacts on millions of people living downstream, but the strength and direction of impacts of vegetation expansion remain unknown.

NDVI Changes Show Warming Increases the Length of the Green Season at Tundra Communities in Northern Alaska: A Fine-Scale Analysis

A warming Arctic has been associated with increases in aboveground plant biomass, specifically shrubs, and changes in vegetation cover. However, the magnitude and direction of changes in NDVI have not been consistent across different tundra types. Here we examine the responsiveness of fine-scale NDVI values to experimental warming at eight sites in northern Alaska, United States. Warming in our eight sites ranged in duration from 2‑23 seasons. Dry, wet and moist tundra communities were monitored for canopy surface temperatures and NDVI in ambient and experimentally-warmed plots at near-daily frequencies during the summer of 2017 to assess the impact of the warming treatment on the magnitude and timing of greening. Experimental warming increased canopy-level surface temperatures across all sites (+0.47 to +3.14˚C), with the strongest warming effect occurring during June and July and for the southernmost sites. Green-up was accelerated by warming at six sites, and autumn senescence was delayed at five sites. Warming increased the magnitude of peak NDVI values at five sites, decreased it at one site, and at two sites it did not change. Warming resulted in earlier peak NDVI at three sites and no significant change in the other sites. Shrub and graminoid cover was positively correlated with the magnitude of peak NDVI (r=0.37 to 0.60) while cryptogam influence was mixed. The magnitude and timing of peak NDVI showed considerable variability across sites. Warming extended the duration of the summer green season at most sites due to accelerated greening in the spring and delayed senescence in the autumn. We show that in a warmer Arctic (as simulated by our experiment) the timing and total period of carbon gain may change. Our results suggest these changes are dependent on community composition and abundance of specific growth forms and therefore will likely impact net primary productivity and trophic interactions.

Landscape Change Detected over a Half Century in the Arctic National Wildlife Refuge Using High-Resolution Aerial Imagery

Rapid warming has occurred over the past 50 years in Arctic Alaska, where temperature strongly affects ecological patterns and processes. To document landscape change over a half century in the Arctic National Wildlife Refuge, Alaska, we visually interpreted geomorphic and vegetation changes on time series of coregistered high-resolution imagery. We used aerial photographs for two time periods, 1947–1955 and 1978–1988, and Quick Bird and IKONOS satellite images for a third period, 2000–2007. The stratified random sample had five sites in each of seven ecoregions, with a systematic grid of 100 points per site. At each point in each time period, we recorded vegetation type, microtopography, and surface water. Change types were then assigned based on differences detected between the images. Overall, 23% of the points underwent some type of change over the ~50-year study period. Weighted by area of each ecoregion, we estimated that 18% of the Refuge had changed. The most common changes were wildfire and postfire succession, shrub and tree increase in the absence of fire, river erosion and deposition, and ice-wedge degradation. Ice-wedge degradation occurred mainly in the Tundra Biome, shrub increase and river changes in the Mountain Biome, and fire and postfire succession in the Boreal Biome. Changes in the Tundra Biome tended to be related to landscape wetting, mainly from increased wet troughs caused by ice-wedge degradation. The Boreal Biome tended to have changes associated with landscape drying, including recent wildfire, lake area decrease, and land surface drying. The second time interval, after ~1982, coincided with accelerated climate warming and had slightly greater rates of change.

Reduced arctic tundra productivity linked with landform and climate change interactions

Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (~60,000 km²) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.

Coupled long-term summer warming and deeper snow alters species composition and stimulates gross primary productivity in tussock tundra

Climate change is expected to increase summer temperature and winter precipitation throughout the Arctic. The long-term implications of these changes for plant species composition, plant function, and ecosystem processes are difficult to predict. We report on the influence of enhanced snow depth and warmer summer temperature following 20 years of an ITEX experimental manipulation at Toolik Lake, Alaska. Winter snow depth was increased using snow fences and warming was accomplished during summer using passive open-top chambers. One of the most important consequences of these experimental treatments was an increase in active layer depth and rate of thaw, which has led to deeper drainage and lower soil moisture content. Vegetation concomitantly shifted from a relatively wet system with high cover of the sedge Eriophorum vaginatum to a drier system, dominated by deciduous shrubs including Betula nana and Salix pulchra. At the individual plant level, we observed higher leaf nitrogen concentration associated with warmer temperatures and increased snow in S. pulchra and B. nana, but high leaf nitrogen concentration did not lead to higher rates of net photosynthesis. At the ecosystem level, we observed higher GPP and NEE in response to summer warming. Our results suggest that deeper snow has a cascading set of biophysical consequences that include a deeper active layer that leads to altered species composition, greater leaf nitrogen concentration, and higher ecosystem-level carbon uptake.