Lake methane emissions are commonly upscaled from lake area, with recognition that smaller, non-inventoried lakes emit more per unit area. There is also growing awareness of the importance of lake aquatic vegetation and potential “double-counting” with wetlands, but lack of consensus on which is most impactful. Here, we combine high-resolution data with the comprehensive lake inventory HydroLAKES to rank these three variables based on emissions sensitivity. Including non-inventoried small lakes <0.1 km2 (+30 [range: 9.0 to 82]% change) is greatest, followed by double-counting (−20 [−11 to −34]%) and lake aquatic vegetation (+14 [2.7 to 43]%). Significantly, emissions from non-inventoried lakes contribute far less than the ∼40% previously determined globally through statistical area extrapolation. We produce a first pan-Arctic estimate of lake aquatic vegetation in 1.37 million km2 of lakes, but after correcting for persistent double-counting, its net effect is to decrease emissions estimates by 9%. Thus, previous global emissions estimates are likely too high.

Abstract With over 700 million km2 Siberia is the largest expanse of the northern boreal forest—deciduous-needleleaf larch. Temperatures are increasing across this region, but the consequences to carbon balances are not well understood for larch forests. We present flux measurements from a larch forest near the southern edge of Central-Siberia where permafrost degradation and ecosystem shifts are already observed. Results indicate net carbon exchanges are influenced by the seasonality of permafrost active layers, temperature and humidity, and soil water availability. During periods when surface soils are fully thawed, larch forest is a significant carbon sink. During the spring-thaw and fall-freeze transition, there is a weak signal of carbon uptake at mid-day. Net carbon exchanges are near-zero when the soil is fully frozen from the surface down to the permafrost. We fit an empirical ecosystem functional model to quantify the dependence of larch-forest carbon balance on climatic drivers. The model provides a basis for ecosystem carbon budgets over time and space. Larch differs from boreal evergreens by having higher maximum productivity and lower respiration, leading to an increased carbon sink. Comparison to previous measurements from another northern larch site suggests climate change will result in an increased forest carbon sink if the southern larch subtype replaces the northern subtype. Observations of carbon fluxes in Siberian larch are still too sparse to adequately determine age dependence, inter-annual variability, and spatial heterogeneity though they suggest that boreal larch accounts for a larger fraction of global carbon uptake than has been previously recognized.

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.