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We have analyzed decade‐long methane flux data set from a boreal fen, Siikaneva, together with data on environmental parameters and carbon dioxide exchange. The methane flux showed seasonal cycle but no systematic diel cycle. The highest fluxes were observed in July–August with average value of 73 nmol m−2s−1. Wintertime fluxes were small but positive, with January–March average of 6.7 nmol m−2s−1. Daily average methane emission correlated best with peat temperatures at 20–35 cm depths. The second highest correlation was with gross primary production (GPP). The best correspondence between emission algorithm and measured fluxes was found for a variable‐slope generalized linear model (r2= 0.89) with peat temperature at 35 cm depth and GPP as explanatory variables, slopes varying between years. The homogeneity of slope approach indicated that seasonal variation explained 79% of the sum of squares variation of daily average methane emission, the interannual variation in explanatory factors 7.0%, functional change 5.3%, and random variation 9.1%. Significant correlation between interannual variability of growing season methane emission and that of GPP indicates that on interannual time scales GPP controls methane emission variability, crucially for development of process‐based methane emission models. Annual methane emission ranged from 6.0 to 14 gC m−2and was 2.7 ± 0.4% of annual GPP. Over 10‐year period methane emission was 18% of net ecosystem exchange as carbon. The weak relation of methane emission to water table position indicates that space‐to‐time analogy, used to extrapolate spatial chamber data in time, may not be applicable in seasonal time scales. Methane emission from a boreal wetland was measured over one decade. Methane emission shows strong seasonal cycle, with highest emission in late summer and lowest emission during winter. No diel cycle was observed. The methane emission is an important part of the carbon balance of the wetland as 18% of carbon taken up as carbon dioxide was emitted back into atmosphere as methane. The seasonal cycle of the emission was controlled first by peat temperature and second by ecosystem photosynthesis. The interannual variability of methane emission was more related to photosynthesis. A large part of the interannual variability remained unexplained by the measured environmental parameters. Methane emission was insensitive to water table variations observed during decade‐long periodSoil temperature was the dominant driver of methane emission during shorter periods of time (<1 year), while interannual variation was more related to variation in GPPSeventy‐nine percent of the variability of daily average methane emission is due to seasonal change of drivers, 7.0% is due to interannual variation of drivers, and 5.3% is due to functional change

AbstractThe concept of ecosystem services is entering the agenda of land-use planning and scientists optimistically expect it to inform planners and decision-makers about the benefits that ecosystems provide. While tools and methods have been developed for mapping and valuing ecosystem services, only little attention has been paid to the practical application of the approach or its institutional preconditions and implications. We empirically analysed two urban planning processes for building residential areas in the outskirts of growing population centres in Finland. Our analysis of documents and interviews with planners focused on the benefits provided by ecosystems as well as the associated rights and responsibilities. We found that the concept ‘ecosystem service’ was not used, yet various benefits were identified. The rights of different stakeholders to ecosystem services were not explicitly identified, but many ecosystem services were perceived as public goods and particularly access to recreation was highlighted as an important justification for green areas. The results show that while the ecosystem services approach introduces new insights to land-use planning, it is still not embedded in the current practices or institutions. Operationalizing ecosystem services requires institutional adaptation, case-specific tailoring of methods, and deliberation among practitioners and stakeholders.

The enhanced vegetation index (EVI) obtained from satellite imagery has often been used as a proxy of vegetation functioning and productivity in the Amazon rainforest. However, recent studies indicate that EVI patterns are strongly affected by satellite data artifacts. Hence, it is unclear if EVI is sensitive to subtle seasonal variations in evergreen Amazon forest productivity. This study analyzes 12 years of Moderate Resolution Imaging Spectroradiometer (MODIS) EVI in order to evaluate its response to factors driving productivity in the Amazon. We show that, after removing cloud and aerosol contamination, and correcting bidirectional reflectance distribution function effects, radiation and rainfall extremes show no influence on EVI anomalies. However, EVI seasonal patterns are still evident after accounting for Sun‐sensor geometry effects. This remaining pattern cannot be explained by solar radiation or rainfall, but it is significantly correlated to gross primary production (GPP). Nevertheless, we argue that the causality between GPP and EVI should be interpreted with caution. Monthly EVI anomalies are not sensitive to radiation or rainfall extremesEVI seasonality in the Amazon is still present after BRDF correctionAlthough EVI and GPP correlate, interpretations of causality require caution