No abstract

No abstract

Abstract. Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

To determine how epiphytes affect the canopy hydrology of old-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forests, we measured rainfall interception by individual branches and an entire stand from March 2003 to May 2004. Epiphyte-laden branches at heights of 3.1, 24.8 and 46.5 m remained partially saturated for most of the wet season and required more than 30 mm of rainfall to become saturated. We used the mean, minimum, and individual storm methods to estimate canopy water storage capacity. Canopy water storage capacity averaged 3.1–5.0 mm, but these are probably underestimates of the maximum canopy water storage capacity, because the canopy was partially saturated prior to most storm events and the saturation of the canopy was delayed by preferential flow through the epiphyte-laden branches. Contrary to expectation, the water stored on epiphyte-laden branches after exposure to natural rainfall increased with rainfall intensity because the rough three-dimensional structure of the lichen and bryophyte mats limits water loss from raindrop splash and impedes the drainage of water from the branch. We conclude that epiphytic lichens and bryophytes increase canopy water storage capacity, prolong the time required for the canopy to saturate and dry, and alter the transfer of water through the canopy.

No abstract