Influence of Spring and Autumn Phenological Transitions on Forest Ecosystem Productivity

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ¿extra¿ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.JRC.H.5-Land Resources Managemen

Contrasting effects of CO₂ fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO₂ exchange

Continuous atmospheric CO₂ monitoring data indicate an increase in the amplitude of seasonal CO₂-cycle exchange (SCA_(NBP)) in northern high latitudes. The major drivers of enhanced SCA_(NBP) remain unclear and intensely debated, with land-use change, CO₂ fertilization and warming being identified as likely contributors. We integrated CO₂-flux data from two atmospheric inversions (consistent with atmospheric records) and from 11 state-of-the-art land-surface models (LSMs) to evaluate the relative importance of individual contributors to trends and drivers of the SCA_(NBP) of CO₂ fluxes for 1980–2015. The LSMs generally reproduce the latitudinal increase in SCA_(NBP) trends within the inversions range. Inversions and LSMs attribute SCA_(NBP) increase to boreal Asia and Europe due to enhanced vegetation productivity (in LSMs) and point to contrasting effects of CO₂ fertilization (positive) and warming (negative) on SCA_(NBP). Our results do not support land-use change as a key contributor to the increase in SCA_(NBP). The sensitivity of simulated microbial respiration to temperature in LSMs explained biases in SCA_(NBP) trends, which suggests that SCA_(NBP) could help to constrain model turnover times

Lower land-use emissions responsible for increased net land carbon sink during the slow warming period

The terrestrial carbon sink accelerated during 1998–2012, concurrently with the slow warming period, but the mechanisms behind this acceleration are unclear. Here we analyse recent changes in the net land carbon sink (NLS) and its driving factors, using atmospheric inversions and terrestrial carbon models. We show that the linear trend of NLS during 1998–2012 is about 0.17 ± 0.05 Pg C yr−2 , which is three times larger than during 1980–1998 (0.05 ± 0.05 Pg C yr−2). According to terrestrial carbon model simulations, the intensification of the NLS cannot be explained by CO2 fertilization or climate change alone. We therefore use a bookkeeping model to explore the contribution of changes in land-use emissions and find that decreasing land-use emissions are the dominant cause of the intensification of the NLS during the slow warming period. This reduction of land-use emissions is due to both decreased tropical forest area loss and increased afforestation in northern temperate regions. The estimate based on atmospheric inversions shows consistently reduced land-use emissions, whereas another bookkeeping model did not reproduce such changes, probably owing to missing the signal of reduced tropical deforestation. These results highlight the importance of better constraining emissions from land-use change to understand recent trends in land carbon sinks

Precipitation patterns alter growth of temperate vegetation

[1] In this paper, we use growing season Normalized Difference Vegetation Index (NDVI) as an indicator of plant growth to quantify the relationships between vegetation production and intra-annual precipitation patterns for three major temperate biomes in China: grassland, deciduous broadleaf forest, and deciduous coniferous forest. With increased precipitation, NDVI of grassland and deciduous broadleaf forest increased, but that of deciduous coniferous forest decreased. More frequent precipitation significantly increased growth of grassland and deciduous broadleaf forest, but did not alter that of deciduous coniferous forest at low precipitation levels and constrained its growth at high precipitation levels. The relationships between NDVI and average precipitation per event were opposite to those between NDVI and precipitation frequency. Such nonlinear feedback suggests that the responses of vegetation production to changes in precipitation patterns differ by both biome type and precipitation amount. Citation: Fang

Application of the metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height

Aim: Forest height, an important biophysical property, underlies the distribution of carbon stocks across scales. Because in situ observations are labour intensive and thus impractical for large-scale mapping and monitoring of forest heights, most previous studies adopted statistical approaches to help alleviate measured data discontinuity in space and time. Here, we document an improved modelling approach which links metabolic scaling theory and the water–energy balance equation with actual observations in order to produce large-scale patterns of forest heights. Methods: Our model, called allometric scaling and resource limitations (ASRL), accounts for the size-dependent metabolism of trees whose maximum growth is constrained by local resource availability. Geospatial predictors used in the model are altitude and monthly precipitation, solar radiation, temperature, vapour pressure and wind speed. Disturbance history (i.e. stand age) is also incorporated to estimate contemporary forest heights. Results: This study provides a baseline map (c. 2005; 1-km^2 grids) of forest heights over the contiguous United States. The Pacific Northwest/California is predicted as the most favourable region for hosting large trees (c. 100 m) because of sufficient annual precipitation (> 1400 mm), moderate solar radiation (c. 330 W m^(−2)) and temperature (c. 14 °C). Our results at sub-regional level are generally in good and statistically significant (P-value < 0.001) agreement with independent reference datasets: field measurements [mean absolute error (MAE) = 4.0 m], airborne/spaceborne lidar (MAE = 7.0 m) and an existing global forest height product (MAE = 4.9 m). Model uncertainties at county level are also discussed in this study. Main conclusions: We improved the metabolic scaling theory to address variations in vertical forest structure due to ecoregion and plant functional type. A clear mechanistic understanding embedded within the model allowed synergistic combinations between actual observations and multiple geopredictors in forest height mapping. This approach shows potential for prognostic applications, unlike previous statistical approaches

Contrasting effects of CO2 fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO2 exchange

Altres ajuts: European Space Agency Climate Change Initiative/ESRIN/ 4000123002/18/I-NBContinuous atmospheric CO monitoring data indicate an increase in the amplitude of seasonal CO-cycle exchange (SCA) in northern high latitudes. The major drivers of enhanced SCA remain unclear and intensely debated, with land-use change, CO fertilization and warming being identified as likely contributors. We integrated CO-flux data from two atmospheric inversions (consistent with atmospheric records) and from 11 state-of-the-art land-surface models (LSMs) to evaluate the relative importance of individual contributors to trends and drivers of the SCA of CO fluxes for 1980-2015. The LSMs generally reproduce the latitudinal increase in SCA trends within the inversions range. Inversions and LSMs attribute SCA increase to boreal Asia and Europe due to enhanced vegetation productivity (in LSMs) and point to contrasting effects of CO fertilization (positive) and warming (negative) on SCA. Our results do not support land-use change as a key contributor to the increase in SCA. The sensitivity of simulated microbial respiration to temperature in LSMs explained biases in SCA trends, which suggests that SCA could help to constrain model turnover times