Abstract 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.
Abstract. Permafrost soils store between 1,330–1,580 Pg carbon (C), which is three times the amount of C in global vegetation, almost twice the amount of C in the atmosphere, and half of the global soil organic C pool. Despite the massive amount of C in permafrost, estimates of soil C storage in the high latitude permafrost region are highly uncertain, primarily due to under sampling at all spatial scales; circumpolar soil C estimates lack sufficient continental spatial diversity, regional intensity, and replication at the field-site level. Siberian forests are particularly under sampled, yet the larch forests that dominate this region may store more than twice as much soil C as all other boreal forest types in the continuous permafrost zone combined. Here we present above and belowground C stocks from twenty sites representing a gradient of stand age and structure in a larch watershed of the Kolyma River near Cherskiy, Sakha Republic, Russia. We found that the majority of C stored in the top 1 m of the watershed was stored belowground (91 %), with 20 % in the top 10 cm of soil and 42 % in the top 30 cm. Carbon was more variable in surface soils (10 cm; coefficient of variation (CV) = 0.35 between stands) than in the top 30 cm (CV = 0.14) or soil profile to 1 m (CV = 0.12). Combined active layer and deep frozen deposits (surface – 15 m) contained 205 kg C m-2 (yedoma, non-ice wedge) and 331 kg C m-2 (alas), which, even when accounting for landscape-level ice content, is an order of magnitude more C than that stored in the top meter of soil and two orders of magnitude more C than in aboveground biomass. Aboveground biomass was composed of primarily larch (53 %) but also included understory vegetation (30 %), woody debris (11 %) and snag (6 %) biomass. While aboveground biomass contained relatively little (9 %) of the C stocks in the watershed, aboveground processes were linked to thaw depth and belowground C storage. Thaw depth was significantly negatively related to stand age, and variability of soil C in the top 10 cm was related to soil moisture and moss and lichen cover. These results suggest that as the climate warms, changes in stand age and structure may be as important as direct climate effects on belowground environmental conditions and permafrost C vulnerability.
Abstract Tundra ecosystem fire regimes are intensifying with important implications for regional and global carbon (C) and energy dynamics. Although a substantial portion of the tundra biome is located in Russia, the vast majority of accessible studies describe North American tundra fires. Here we use field observations and high‐resolution satellite remote sensing observations to describe the effects of wildfire on ecosystem C pools and vegetation communities four decades after fire for a tundra ecosystem in northeastern Siberia. Our analyses reveal no differences between soil physical properties and C pools in burned and unburned tundra, which we attribute to low combustion of organic soil associated with low‐severity fire. Field and remote sensing data show no differences in aboveground C pools and vegetation communities indicating recovery to prefire conditions. These results are comparable to observations of ecosystem recovery in North American tundra. An assessment of literature data indicate that the average annual area burned in Russian tundra is an order of magnitude larger than that of Alaskan tundra, highlighting a crucial need to assess Russian tundra fire regimes in order to understand the current and future role of the biome wide fire regime in regional and global C and energy dynamics.
ABSTRACT Satellite remote sensing of climate-driven changes in terrestrial ecosystems continues to improve, yet interpreting and rigorously validating these changes requires extensive ground-truthed data. Satellite measurements of vegetation indices, such as the Normalized Difference Vegetation Index (NDVI, or vegetation greenness), indicate widespread vegetation change in the Arctic that is associated with rapid warming. Plot-based studies have indicated greater vegetation greenness generally corresponds to greater plant biomass and deciduous shrub cover. However, the spatial scale of traditional plot-based sampling is much smaller than the resolution of most satellite imagery and thus does not fully describe how plant characteristics such as structure and taxonomic composition relate to satellite measurements of greenness. To improve interpretation of Landsat measurements of vegetation greenness in the Arctic, we developed and implemented a method that links satellite measurements with ground-based vegetation classifications. Here we describe data collected across the central Brooks Range of Alaska by field sampling hundreds of Landsat pixels per day, with a field campaign total of 23,213 pixels (30 m). Our example dataset shows that vegetation with the greatest Landsat greenness was taller than 1m, woody, and deciduous; vegetation with lower greenness tended to be shorter, evergreen, or non-woody. We also show that understory vegetation influences Landsat greenness. Our methods advance efforts to inform satellite data with ground-based vegetation observations using field samples at spatial scales more closely matched to the resolution of remotely sensed imagery.
Abstract Changes in vegetation distribution are underway in Arctic and boreal regions due to climate warming and associated fire disturbance. These changes have wide ranging downstream impacts—affecting wildlife habitat, nutrient cycling, climate feedbacks and fire regimes. It is thus critical to understand where these changes are occurring and what types of vegetation are affected, and to quantify the magnitude of the changes. In this study, we mapped live aboveground biomass for five common plant functional types (PFTs; deciduous shrubs, evergreen shrubs, forbs, graminoids and lichens) within Alaska and northwest Canada, every five years from 1985 to 2020. We employed a multi-scale approach, scaling from field harvest data and unmanned aerial vehicle-based biomass predictions to produce wall-to-wall maps based on climatological, topographic, phenological and Landsat spectral predictors. We found deciduous shrub and graminoid biomass were predicted best among PFTs. Our time-series analyses show increases in deciduous (37%) and evergreen shrub (7%) biomass, and decreases in graminoid (14%) and lichen (13%) biomass over a study area of approximately 500 000 km 2 . Fire was an important driver of recent changes in the study area, with the largest changes in biomass associated with historic fire perimeters. Decreases in lichen and graminoid biomass often corresponded with increasing shrub biomass. These findings illustrate the driving trends in vegetation change within the Arctic/boreal region. Understanding these changes and the impacts they in turn will have on Arctic and boreal ecosystems will be critical to understanding the trajectory of climate change in the region.
