Vegetation height products between 60° S and 60° N from ICESat GLAS data.

We present new coarse resolution (0.5� ×0.5�)vegetation height and vegetation-cover fraction data sets between 60� S and 60� N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70m in 0.5m intervals for each 0.5�×0.5�. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r =0.33 to r =0.78, decreases the root-mean-square error by a factor 3 to about 6m (RMSE) or 4.5m (68% error distribution) and decreases the bias from 5.7m to −1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5–6m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r =0.67); the GLAS treecover fraction is compared with the MODIS tree-cover fraction (r =0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface

The positive net radiative greenhouse gas forcing of increasing methane emissions from a thawing boreal forest-wetland landscape

At the southern margin of permafrost in North America, climate change causes widespread permafrost thaw. In boreal lowlands, thawing forested permafrost peat plateaus (‘forest’) lead to expansion of permafrost‐free wetlands (‘wetland’). Expanding wetland area with saturated and warmer organic soils is expected to increase landscape methane (CH4) emissions. Here, we quantify the thaw‐induced increase in CH4 emissions for a boreal forest‐wetland landscape in the southern Taiga Plains, Canada, and evaluate its impact on net radiative forcing relative to potential long‐term net carbon dioxide (CO2) exchange. Using nested wetland and landscape eddy covariance net CH4 flux measurements in combination with flux footprint modeling, we find that landscape CH4 emissions increase with increasing wetland‐to‐forest ratio. Landscape CH4 emissions are most sensitive to this ratio during peak emission periods, when wetland soils are up to 10 °C warmer than forest soils. The cumulative growing season (May–October) wetland CH4 emission of ~13 g CH4 m−2 is the dominating contribution to the landscape CH4 emission of ~7 g CH4 m−2. In contrast, forest contributions to landscape CH4 emissions appear to be negligible. The rapid wetland expansion of 0.26 ± 0.05% yr−1 in this region causes an estimated growing season increase of 0.034 ± 0.007 g CH4 m−2 yr−1 in landscape CH4 emissions. A long‐term net CO2 uptake of >200 g CO2 m−2 yr−1 is required to offset the positive radiative forcing of increasing CH4 emissions until the end of the 21st century as indicated by an atmospheric CH4 and CO2 concentration model. However, long‐term apparent carbon accumulation rates in similar boreal forest‐wetland landscapes and eddy covariance landscape net CO2 flux measurements suggest a long‐term net CO2 uptake between 49 and 157 g CO2 m−2 yr−1. Thus, thaw‐induced CH4 emission increases likely exert a positive net radiative greenhouse gas forcing through the 21st century

Monitoring boreal forest biomass and carbon storage change by integrating airborne laser scanning, biometry and eddy covariance data

AbstractThis study presents a comparison and integration of three methods commonly used to estimate the amount of forest ecosystem carbon (C) available for storage. In particular, we examine the representation of living above- and below-ground biomass change (net accumulation) using plot-level biometry and repeat airborne laser scanning (ALS) of three dimensional forest plot structure. These are compared with cumulative net CO2 fluxes (net ecosystem production, NEP) from eddy covariance (EC) over a six-year period within a jack pine chronosequence of four stands (~94, 30, 14 and 3years since establishment from 2005) located in central Saskatchewan, Canada. Combining the results of the two methods yield valuable observations on the partitioning of C within ecosystems. Subtracting total living biomass C accumulation from NEP results in a residual that represents change in soil and litter C storage. When plotted against time for the stands investigated, the curve produced is analogous to the soil C dynamics described in Covington (1981). Here, ALS biomass accumulation exceeds EC-based NEP measured in young stands, with the residual declining with age as stands regenerate and litter decomposition stabilizes. During the 50–70year age-period, NEP and live biomass accumulation come into balance, with the soil and litter pools of stands 70–100years post-disturbance becoming a net store of C. Biomass accumulation was greater in 2008–2011 compared to 2005–2008, with the smallest increase in the 94-year-old “old jack pine” stand and greatest in the 14-year-old “harvested jack pine 1994” stand, with values of 1.4 (±3.2) tCha−1 and 12.0 (±1.6) tCha−1, respectively. The efficiency with which CO2 was stored in accumulated biomass was lowest in the youngest and oldest stands, but peaked during rapid regeneration following harvest (14-year-old stand). The analysis highlights that the primary source of uncertainty in the data integration workflow is in the calculation of biomass expansion factors, and this aspect of the workflow needs to be implemented with caution to avoid large error propagations. We suggest that the adoption of integrated ALS, in situ and atmospheric flux monitoring frameworks is needed to improve spatio-temporal partitioning of C balance components at sub-decadal scale within rapidly changing forest ecosystems and for use in national carbon accounting programs

A synthesis of three decades of hydrological research at Scotty Creek, NWT, Canada

Scotty Creek, Northwest Territories (NWT), Canada, has been the focus of hydrological research for nearly three decades. Over this period, field and modelling studies have generated new insights into the thermal and physical mechanisms governing the flux and storage of water in the wetland-dominated regions of discontinuous permafrost that characterises much of the Canadian and circumpolar subarctic. Research at Scotty Creek has coincided with a period of unprecedented climate warming, permafrost thaw, and resulting land cover transformations including the expansion of wetland areas and loss of forests. This paper (1) synthesises field and modelling studies at Scotty Creek, (2) highlights the key insights of these studies on the major water flux and storage processes operating within and between the major land cover types, and (3) provides insights into the rate and pattern of the permafrost-thaw-induced land cover change and how such changes will affect the hydrology and water resources of the study region.</p

Upscaling of methane exchange in a boreal forest using soil chamber measurements and high-resolution LiDAR elevation data

Forest soils are generally considered to be net sinks of methane (CH4), but CH4 fluxes vary spatially depending on soil conditions. Measuring CH4 exchange with chambers, which are commonly used for this purpose, might not result in representative fluxes at site scale. Appropriate methods for upscaling CH4 fluxes from point measurements to site scale are therefore needed. At the boreal forest research site, Norunda, chamber measurements of soils and vegetation indicate that the site is a net sink of CH4, while tower gradient measurements indicate that the site is a net source of CH4. We investigated the discrepancy between chamber and tower gradient measurements by upscaling soil CH4 exchange to a 100 ha area based on an empirical model derived from chamber measurements of CH4 exchange and measurements of soil moisture, soil temperature and water table depth. A digital elevation model (DEM) derived from high-resolution airborne Light Detection and Ranging (LiDAR) data was used to generate gridded water table depth and soil moisture data of the study area as input data for the upscaling. Despite the simplistic approach, modeled fluxes were significantly correlated to four out of five chambers with R>0.68. The upscaling resulted in a net soil sink of CH4 of -10 mu mol m(-2) h(-1), averaged over the entire study area and time period June-September, 2010). Our findings suggest that additional contributions from CH4 soil sources outside the upscaling study area and possibly CH4 emissions from vegetation could explain the net emissions measured by tower gradient measurements. (C) 2015 Elsevier B.V. All rights reserved

Microtopographic drivers of vegetation patterning in blanket peatlands recovering from erosion

Blanket peatlands are globally rare, and many have been severely eroded. Natural recovery and revegetation (‘self-restoration’) of bare peat surfaces are often observed but are poorly understood, thus hampering the ability to reliably predict how these ecosystems may respond to climatic change. We hypothesised that morphometric/topographic-related microclimatic variables may be key controls on successional pathways and vegetation patterning in self-restoring blanket peatlands. We predicted the occurrence probability of four common peatland plant species (Calluna vulgaris, Eriophorum vaginatum, Eriophorum angustifolium, and Sphagnum spp.) using a digital surface model (DSM) generated from drone imagery at a pixel size of 20 cm, a suite of variables derived from the DSM, and an ensemble learning method (random forests). All four species models provided accurate fine-scale predictions of habitat suitability (accuracy > 90%, area under curve (AUC) > 0.9, recall and precision > 0.8). Mean elevation (within a 1 m radius) was often the most influential variable. Topographic position, wind exposure, and the heterogeneity or ruggedness of the surrounding surface were also important for all models, whilst light-related variables and a wetness index were important in the Sphagnum model. Our approach can be used to improve prediction of future responses and sensitivities of peatland recovery to climatic changes and as a tool to identify areas of blanket peatlands that may self-restore successfully without management intervention