Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

• Published in: Ecological modelling 2011-09, Vol.222 (17), p.3236-3249
• Main Authors: Wang, Z., Grant, R.F., Arain, M.A., Chen, B.N., Coops, N., Hember, R., Kurz, W.A., Price, D.T., Stinson, G., Trofymow, J.A., Yeluripati, J., Chen, Z.
• Format: Article
• Language: English
• Subjects: 3PG; air temperature; Animal and plant ecology; Animal, plant and microbial ecology; anthropogenic activities; biogeochemical cycles; Biological and medical sciences; Can-IBIS; Carbon budget; carbon dioxide; Carbon flux; carbon sinks; CBM-CFS3; CN-CLASS; coniferous forests; correlation; Disturbance; Ecosys; Ecosystem models; eddy covariance; forest canopy; Forest productivity; forest stands; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Techniques; humus; inventories; land cover; meteorological data; Methods and techniques (sampling, tagging, trapping, modelling...); net ecosystem production; primary productivity; rivers; Synecology; weathering
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2011.06.005

• Productivity of a coniferous forest was adversely affected by short-term rises in temperature. • These rises caused these forests to change from carbon sinks to sources at a daily time scale. • Consequently warmer summers were found to reduce annual forest productivity. • This reduction was simulated by four different process models, and so appeared to be robust. • A simple equation was developed to estimate weather effects on productivity in inventory models. Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models ( ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity ( NPP), net ecosystem productivity ( NEP) and net biome productivity ( NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July–September ( T amax ) in all process models ( R 2 = 0.4–0.6), indicating that these correlations were robust. The negative correlation between T amax and NEP was attributed to different processes in different models, which were tested by comparing CO 2 fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures ( T a ). The general agreement in sensitivity of annual NPP to T amax among the process models led to th