Upscaling vascular aboveground biomass and topsoil moisture of subarctic fens from Unoccupied Aerial Vehicles (UAVs) to satellite level.

Arctic and subarctic ecosystems are experiencing rapid changes in vegetation composition and productivity due to global warming. Tundra wetlands are especially susceptible to these changes, which may trigger shifts in soil moisture dynamics. It is therefore essential to accurately map plant biomass and topsoil moisture. In this study, we mapped total, wood, and leaf above ground biomass and topsoil moisture in subarctic tundra wetlands located between Norway and Finland by linking models derived from Unoccupied Aerial Vehicles with multiple satellite data sources using the Extreme Gradient Boosting algorithm. The most accurate predictions for topsoil moisture (R2 = 0.73) used a set of red edge-based vegetation indices with a spatial resolution of 20 m per pixel. On the contrary, wood biomass showed the lowest accuracies across all tested models (R2 = 0.38). We found a trade-off between the spatial resolution and the performance of upscaling models, where smaller pixel sizes generally led to lower accuracies. However, we were able to compensate for reduced accuracy at smaller pixel sizes using Copernicus phenology metrics. A modelling uncertainty assessment revealed that the uncertainty of predictions increased with decreasing pixel sizes and increasing number of co-predictors. Our approach could improve efforts to map and monitor changes in vegetation at regional to pan-Arctic scales.

The Arctic Plant Aboveground Biomass Synthesis Dataset.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m-2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

Forest composition change and biophysical climate feedbacks across boreal North America.

Deciduous tree cover is expected to increase in North American boreal forests with climate warming and wildfire. This shift in composition has the potential to generate biophysical cooling via increased land surface albedo. Here we use Landsat-derived maps of continuous tree canopy cover and deciduous fractional composition to assess albedo change over recent decades. We find, on average, a small net decrease in deciduous fraction from 2000 to 2015 across boreal North America and from 1992 to 2015 across Canada, despite extensive fire disturbance that locally increased deciduous vegetation. We further find near-neutral net biophysical change in radiative forcing associated with albedo when aggregated across the domain. Thus, while there have been widespread changes in forest composition over the past several decades, the net changes in composition and associated post-fire radiative forcing have not induced systematic negative feedbacks to climate warming over the spatial and temporal scope of our study.

Soil moisture impacts the tundra carbon balance in a changing climate.

There is growing recognition that soil moisture plays a crucial role in regulating the response of tundra carbon cycling to climate warming.

Response to letter to the editor on "Satellite observations document trends consistent with a boreal biome shift".

Here we response to a Letter to the Editor by Timoney (2022) and maintain our conclusion that "there have been systematic trends in vegetation greenness during recent decades that are consistent with an emerging boreal biome shift associated with ongoing climate warming."

Satellite observations document trends consistent with a boreal forest biome shift.

The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground-based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.

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.

Carbon sequestration and biodiversity co-benefits of preserving forests in the western United States.

Forest carbon sequestration via forest preservation can be a viable climate change mitigation strategy. Here, we identify forests in the western conterminous United States with high potential carbon sequestration and low vulnerability to future drought and fire, as simulated using the Community Land Model and two high carbon emission scenario (RCP 8.5) climate models. High-productivity, low-vulnerability forests have the potential to sequester up to 5,450 Tg CO2 equivalent (1,485 Tg C) by 2099, which is up to 20% of the global mitigation potential previously identified for all temperate and boreal forests, or up to ~6 yr of current regional fossil fuel emissions. Additionally, these forests currently have high above- and belowground carbon density, high tree species richness, and a high proportion of critical habitat for endangered vertebrate species, indicating a strong potential to support biodiversity into the future and promote ecosystem resilience to climate change. We stress that some forest lands have low carbon sequestration potential but high biodiversity, underscoring the need to consider multiple criteria when designing a land preservation portfolio. Our work demonstrates how process models and ecological criteria can be used to prioritize landscape preservation for mitigating greenhouse gas emissions and preserving biodiversity in a rapidly changing climate.

Plant functional trait change across a warming tundra biome.

The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

Land use strategies to mitigate climate change in carbon dense temperate forests.

Strategies to mitigate carbon dioxide emissions through forestry activities have been proposed, but ecosystem process-based integration of climate change, enhanced CO2, disturbance from fire, and management actions at regional scales are extremely limited. Here, we examine the relative merits of afforestation, reforestation, management changes, and harvest residue bioenergy use in the Pacific Northwest. This region represents some of the highest carbon density forests in the world, which can store carbon in trees for 800 y or more. Oregon's net ecosystem carbon balance (NECB) was equivalent to 72% of total emissions in 2011-2015. By 2100, simulations show increased net carbon uptake with little change in wildfires. Reforestation, afforestation, lengthened harvest cycles on private lands, and restricting harvest on public lands increase NECB 56% by 2100, with the latter two actions contributing the most. Resultant cobenefits included water availability and biodiversity, primarily from increased forest area, age, and species diversity. Converting 127,000 ha of irrigated grass crops to native forests could decrease irrigation demand by 233 billion m3⋅y-1 Utilizing harvest residues for bioenergy production instead of leaving them in forests to decompose increased emissions in the short-term (50 y), reducing mitigation effectiveness. Increasing forest carbon on public lands reduced emissions compared with storage in wood products because the residence time is more than twice that of wood products. Hence, temperate forests with high carbon densities and lower vulnerability to mortality have substantial potential for reducing forest sector emissions. Our analysis framework provides a template for assessments in other temperate regions.

Understory vegetation mediates permafrost active layer dynamics and carbon dioxide fluxes in open-canopy larch forests of northeastern Siberia.

Arctic ecosystems are characterized by a broad range of plant functional types that are highly heterogeneous at small (~1-2 m) spatial scales. Climatic changes can impact vegetation distribution directly, and also indirectly via impacts on disturbance regimes. Consequent changes in vegetation structure and function have implications for surface energy dynamics that may alter permafrost thermal dynamics, and are therefore of interest in the context of permafrost related climate feedbacks. In this study we examine small-scale heterogeneity in soil thermal properties and ecosystem carbon and water fluxes associated with varying understory vegetation in open-canopy larch forests in northeastern Siberia. We found that lichen mats comprise 16% of understory vegetation cover on average in open canopy larch forests, and lichen abundance was inversely related to canopy cover. Relative to adjacent areas dominated by shrubs and moss, lichen mats had 2-3 times deeper permafrost thaw depths and surface soils warmer by 1-2°C in summer and less than 1°C in autumn. Despite deeper thaw depths, ecosystem respiration did not differ across vegetation types, indicating that autotrophic respiration likely dominates areas with shrubs and moss. Summertime net ecosystem exchange of CO2 was negative (i.e. net uptake) in areas with high shrub cover, while positive (i.e. net loss) in lichen mats and areas with less shrub cover. Our results highlight relationships between vegetation and soil thermal dynamics in permafrost ecosystems, and underscore the necessity of considering both vegetation and permafrost dynamics in shaping carbon cycling in permafrost ecosystems.

Within-species patterns challenge our understanding of the leaf economics spectrum.

The utility of plant functional traits for predictive ecology relies on our ability to interpret trait variation across multiple taxonomic and ecological scales. Using extensive data sets of trait variation within species, across species and across communities, we analysed whether and at what scales leaf economics spectrum (LES) traits show predicted trait-trait covariation. We found that most variation in LES traits is often, but not universally, at high taxonomic levels (between families or genera in a family). However, we found that trait covariation shows distinct taxonomic scale dependence, with some trait correlations showing opposite signs within vs. across species. LES traits responded independently to environmental gradients within species, with few shared environmental responses across traits or across scales. We conclude that, at small taxonomic scales, plasticity may obscure or reverse the broad evolutionary linkages between leaf traits, meaning that variation in LES traits cannot always be interpreted as differences in resource use strategy.

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data.

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

Plant traits, productivity, biomass and soil properties from forest sites in the Pacific Northwest, 1999-2014.

Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.

Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment.

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg ) series, and its recent successor version 3g (GIMMS3g ), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg ), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg , particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.

Vegetation controls on northern high latitude snow-albedo feedback: observations and CMIP5 model simulations.

The snow-masking effect of vegetation exerts strong control on albedo in northern high latitude ecosystems. Large-scale changes in the distribution and stature of vegetation in this region will thus have important feedbacks to climate. The snow-albedo feedback is controlled largely by the contrast between snow-covered and snow-free albedo (Δα), which influences predictions of future warming in coupled climate models, despite being poorly constrained at seasonal and century time scales. Here, we compare satellite observations and coupled climate model representations of albedo and tree cover for the boreal and Arctic region. Our analyses reveal consistent declines in albedo with increasing tree cover, occurring south of latitudinal tree line, that are poorly represented in coupled climate models. Observed relationships between albedo and tree cover differ substantially between snow-covered and snow-free periods, and among plant functional type. Tree cover in models varies widely but surprisingly does not correlate well with model albedo. Furthermore, our results demonstrate a relationship between tree cover and snow-albedo feedback that may be used to accurately constrain high latitude albedo feedbacks in coupled climate models under current and future vegetation distributions.

Plant response to climate change along the forest-tundra ecotone in northeastern Siberia.

Russia's boreal (taiga) biome will likely contract sharply and shift northward in response to 21st century climatic change, yet few studies have examined plant response to climatic variability along the northern margin. We quantified climate dynamics, trends in plant growth, and growth-climate relationships across the tundra shrublands and Cajander larch (Larix cajanderi Mayr.) woodlands of the Kolyma river basin (657 000 km(2) ) in northeastern Siberia using satellite-derived normalized difference vegetation indices (NDVI), tree ring-width measurements, and climate data. Mean summer temperatures (Ts ) increased 1.0 °C from 1938 to 2009, though there was no trend (P > 0.05) in growing year precipitation or climate moisture index (CMIgy ). Mean summer NDVI (NDVIs ) increased significantly from 1982 to 2010 across 20% of the watershed, primarily in cold, shrub-dominated areas. NDVIs positively correlated (P < 0.05) with Ts across 56% of the watershed (r = 0.52 ± 0.09, mean ± SD), principally in cold areas, and with CMIgy across 9% of the watershed (r = 0.45 ± 0.06), largely in warm areas. Larch ring-width measurements from nine sites revealed that year-to-year (i.e., high-frequency) variation in growth positively correlated (P < 0.05) with June temperature (r = 0.40) and prior summer CMI (r = 0.40) from 1938 to 2007. An unexplained multi-decadal (i.e., low-frequency) decline in annual basal area increment (BAI) occurred following the mid-20th century, but over the NDVI record there was no trend in mean BAI (P > 0.05), which significantly correlated with NDVIs (r = 0.44, P < 0.05, 1982-2007). Both satellite and tree-ring analyses indicated that plant growth was constrained by both low temperatures and limited moisture availability and, furthermore, that warming enhanced growth. Impacts of future climatic change on forests near treeline in Arctic Russia will likely be influenced by shifts in both temperature and moisture, which implies that projections of future forest distribution and productivity in this area should take into account the interactions of energy and moisture limitations.