| 1. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 2. |
- Makela, Annikki, et al.
(författare)
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Developing an empirical model of stand GPP with the LUE approach: analysis of eddy covariance data at five contrasting conifer sites in Europe
- 2008
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013. ; 14:1, s. 92-108
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Tidskriftsartikel (refereegranskat)abstract
- This paper develops a statistical model for daily gross primary production (GPP) in boreal and temperate coniferous forests. The model applies the light use efficiency (LUE) approach, which estimates the conversion efficiency of daily absorbed photosynthetically active radiation (APAR) into daily GPP as a product of potential LUE and modifying factors. The latter were derived from daily total APAR and daily mean temperature, vapour pressure deficit (VPD) and soil water content (SWC). Modelling data came from five European eddy covariance measurement towers over 2-8 years. The model was tested against independent data from two AmeriFlux stations. The model with the APAR, temperature and VPD modifiers worked well in almost all the site-year combinations, but the SWC modifier only improved the fit in few cases. Geographical variation was found in the modifiers and potential LUE in site-specific models. When a model was fitted to pooled data, differences between sites could be explained by potential LUE, leaf area and environmental conditions. The test against the AmeriFlux data corroborated this finding. The potential LUE varied from 1.9 to 3.1 g C MJ(-1), and a weak correlation was found between foliar nitrogen concentration and potential LUE. Some year-to-year variation remained which could be captured by neither the pooled nor the site-specific models.
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| 3. |
- Peltoniemi, Mikko, et al.
(författare)
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Does canopy mean nitrogen concentration explain variation in canopy light use efficiency across 14 contrasting forest sites?
- 2012
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Ingår i: Tree Physiology. - : Oxford University Press (OUP). - 1758-4469 .- 0829-318X. ; 32:2, s. 200-218
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Tidskriftsartikel (refereegranskat)abstract
- The maximum light use efficiency (LUE = gross primary production (GPP)/absorbed photosynthetic photon flux density (aPPFD)) of plant canopies has been reported to vary spatially and some of this variation has previously been attributed to plant species differences. The canopy nitrogen concentration [N] can potentially explain some of this spatial variation. However, the current paradigm of the N-effect on photosynthesis is largely based on the relationship between photosynthetic capacity (A(max)) and [N], i.e., the effects of [N] on photosynthesis rates appear under high PPFD. A maximum LUE-[N] relationship, if it existed, would influence photosynthesis in the whole range of PPFD. We estimated maximum LUE for 14 eddy-covariance forest sites, examined its [N] dependency and investigated how the [N]-maximum LUE dependency could be incorporated into a GPP model. In the model, maximum LUE corresponds to LUE under optimal environmental conditions before light saturation takes place (the slope of GPP vs. PPFD under low PPFD). Maximum LUE was higher in deciduous/mixed than in coniferous sites, and correlated significantly with canopy mean [N]. Correlations between maximum LUE and canopy [N] existed regardless of daily PPFD, although we expected the correlation to disappear under low PPFD when LUE was also highest. Despite these correlations, including [N] in the model of GPP only marginally decreased the root mean squared error. Our results suggest that maximum LUE correlates linearly with canopy [N], but that a larger body of data is required before we can include this relationship into a GPP model. Gross primary production will therefore positively correlate with [N] already at low PPFD, and not only at high PPFD as is suggested by the prevailing paradigm of leaf-level A(max)-[N] relationships. This finding has consequences for modelling GPP driven by temporal changes or spatial variation in canopy [N].
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