Factors influencing CO 2 exchange in northern ecosystems - a synthesis (kind of) Anders Lindroth Lund University Geobiosphere Science Centre Physical Geography and Ecosystems Analysis Sölvegatan 12, Lund, Sweden

Part of synthesis work within the Nordic Centre for Ecosystem Carbon Exchange and Its Interactions With the Climate System, NECC (and partly from LUSTRA 1 ) 23 papers to appear in two coming issues of Tellus B Co- authors: Mika Aurela, Brynhildur Bjarnadottir, Torben Röjle Christensen, Ebba Dellwik, Achim Grelle, Andreas Ibrom, Torbjörn Johansson, Leif Klemedtsson, Fredrik Lagergren,Harry Lankreijer, Ola Langvall, Samuli Launiainen, Tuomas Laurila, Magnus Lund, Eero Nikinmma, Mats Nilsson, Kim Pilegaard, Janne Rinne, Jörgen Sagerfors, Bjarni Sigurdsson, Lena Ström, Juha-Pekka Tuovinen, Timo Vesala and Per Weslien 1 LUSTRA; A swedish research programme on developing land-use strategies for reducing emissions in forestry

Part A 1 - understanding differences in CO 2 exchange between forests of different species, age, climate and soils Part B 2 - Productivity and respiration in the forest of similar species but growing in different climates Part C 3 - Factors controling CO 2 exchange in peatlands 1 Lindroth, A., Lagergren, F., Aurela, M., Bjarnadottir, B., Christensen, T., Dellwik, E., Grelle, A., Ibrom, A., Johansson, T., Lankreijer, H., Launiainen, S., Laurila, T., Mölder, T., Nikinmaa, T., Pilegaard, K., Sigurdsson B. and Vesala, T Leaf area index is primary scaling parameter for both gross photosynthesis and ecosystem respiration of Northern deciduous and coniferous forests. Tellus B (accepted) 2 Lindroth, A., Klemedtsson, L., Grelle, A., Weslien, P. and Langvall, O Net ecosystem exchange, productivity and respiration in three spruce forests in Sweden. Biogeochemistry (in press). 3 Lindroth, A., Lund, M., Nilsson, M., Aurela, M., Christensen, T.R., Laurila, T., Rinne, J., Sagerfors, J., Ström, L., Tuovinen, P. and Vesla, T Environmental controls on CO2 exchange of boreal mires in northern Europe. Tellus B doi: /j x

Part A - Eight different forests T = 8.3°C P = 730 mm Beech T = 5.5°C P = 527 mm Pine/Spruce T = 3.0°C P = 700 mm Pine T = -1.0°C P = 429 mm Pine T = 1.2°C P = 523 mm Spruce T = -0.9°C P = 305 mm Birch T = 3.4°C P = 738 mm Larch

Method: Day and night separately One ’normal’ year from all sites F co2 only for u*>threshold Two-week means Daytime analysis Nighttime analysis (Lloyd & Taylor, 1994)

Lloyd & Taylor equation

Two-week means of parameter values air temperature PAR VPD Soil water content Leaf area index Species Age (Latitude)

.and after normalizing for LAI-dependence What about correlation with latitude? (reminding about Valentini et al., 2000)

.and after normalizing for LAI-dependence

After normalization for the LAI-dependency - no correlation with latitude!

..but stand age does matter

Conclusions: Ecosystem respiration is well determined by the Lloyd & Taylor equation with only one fitting parameter, the respiration rate at 10°C. Leaf area index is the parameter that best explaines between stand variations in parametes controling respiration as well as gross photosynthesis After correction for leaf area, stand respiration shows a weak dependency on stand age

Part B - Three similar forests (all are ca. 40 yrs old spruce stands) T = 5.5°C; P = 688 mm Gley podzol Soil C = 23 kg m -2 Basal area = 32.3 m 2 ha -1 T = 3.4°C; P = 613 mm Podzol Soil C = 5.9 kg m -2 Basal area = 14.7 m 2 ha -1 T = 1.2°C; P = 523 mm Podzol Soil C = 7.2 kg m -2 Basal area = 20.7 m 2 ha -1

Method: Grouping into bi-weekly periods Filled when u*<threshold - light response fkn for daytime - exp fkn for nighttime Components separation: P g = F cmeas - modelled R eco Biomass increment from empirical functions within  foot- print area Litterfall & fine root turnover measured in nearby plots

P n a constant fraction of P g ?

Conclusions: Norunda is not unique in being a ’looser’! P n is probably not a constant fraction of P g but varies in the range 30-45%. Unexpected very large losses of soil carbon Large difference in NEP between forests of the same species and age

Part C - Factors controling CO 2 exchange in peatlands T = 6.2°C; P = 700 mm Temperate ombrotrophic bog T = 3.0°C; P = 713 mm Boreal oligotrophic fen T = 1.2°C; P = 523 mm Boreal oligotrophic minerotrophic mire T = -1.1°C; P = 474 mm Sub-arctic mesotrophic fen

Fäje myr The source area is dominated by a mosaic of hummocks, lawns and carpets

Siikaneva The source area is dominated by sedges and moss carpet

Degerö Stormyr The source area is dominated by a lawn plant community

Kaamanen The source area is dominated by the hummock- hollow microstructure

Questions asked: Similarities/differences in seasonal dynamics of NEE, GPP & Reco Similarities/differences in responses of respiration and photosynthesis to enviromental parameters among different types of Nordic peatlands? What are the major controls of CO 2 exchanges?

Methods De-trending of seasonal effects were made using dummy variable Total ecosystem respiration during daytime was estimated as the difference between measured NEE and estimated GPP GPP was estimated using fitted bi-weekly light-response functions Datasets were further divided into 14-days periods for parameter estimations One year of data separated into DAYTIME and NIGHTTIME periods The same method was used at all sites (i.e., Euroflux methodology) Half hourly fluxes of CO 2 net exchange between peatland surface and atmosphere measured by eddy covariance under well-mixed conditions (u*>0.1)

Eddy Covariance Method F

Weather during growing season

Mean diurnal variation in NEE during summer

Seasonal variation of components

Relationship between GPP, Reco and environmental variables Independent variables: - GPP - Reco - GPP_res - Reco_res - GPP_res_norm - Reco_res_norm Dependent variables: - Air temperature - Photon flux density (PPFD) - Vapour pressure deficit (VPD) - Water table depth WTD a (whole season) WTD b (period of decreasing WTD)

De-trending for seasonal effects

Normalizing for temperature dependencies New seasonally de-trended and temperature normalized variable: GPP_res_norm = GPP_res/f(T)

Reco = f(T an ) differences in base respiration and temperature sensitivity due to litter quality?

Fäje myr Degerö Kaamanen Siikaneva Regression analysis

Fäje myr Degerö Kaamanen Siikaneva

Today Reco is % of GPP - how sustainable is this relationship?

NEE (g C m -2 ) What about other peatlands in northern hemisphere?

Conclusions Apart from a high correlation between the two main components themselves, i.e., respiration and photosynthesis, temperature was the single most important variable in explaining the variation in the component fluxes Surprisingly, gross primary productivity was, also after de-trending the inherent seasonal variation, found to be more sensitive to temperature than respiration for the actual sites Water table depth explained variations in respiration and photsynthesis only during consistent drying up phases Wetlands seems to be small but consistent sinks

Thanks for your attention!