| Literature DB >> 27571971 |
Jaime Madrigal-González1, Paloma Ruiz-Benito1,2, Sophia Ratcliffe3, Joaquín Calatayud1,4, Gerald Kändler5, Aleksi Lehtonen6, Jonas Dahlgren7, Christian Wirth3,8, Miguel A Zavala1.
Abstract
Neglecting tree size and stand structure dynamics might bias the interpretation of the diversity-productivity relationship in forests. Here we show evidence that complementarity is contingent on tree size across large-scale climatic gradients in Europe. We compiled growth data of the 14 most dominant tree species in 32,628 permanent plots covering boreal, temperate and Mediterranean forest biomes. Niche complementarity is expected to result in significant growth increments of trees surrounded by a larger proportion of functionally dissimilar neighbours. Functional dissimilarity at the tree level was assessed using four functional types: i.e. broad-leaved deciduous, broad-leaved evergreen, needle-leaved deciduous and needle-leaved evergreen. Using Linear Mixed Models we show that, complementarity effects depend on tree size along an energy availability gradient across Europe. Specifically: (i) complementarity effects at low and intermediate positions of the gradient (coldest-temperate areas) were stronger for small than for large trees; (ii) in contrast, at the upper end of the gradient (warmer regions), complementarity is more widespread in larger than smaller trees, which in turn showed negative growth responses to increased functional dissimilarity. Our findings suggest that the outcome of species mixing on stand productivity might critically depend on individual size distribution structure along gradients of environmental variation.Entities:
Mesh:
Year: 2016 PMID: 27571971 PMCID: PMC5004187 DOI: 10.1038/srep32233
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Fixed effects selection using the Bayesian Information Criterion (BIC).
| Fixed effects selection | df | BIC | Delta BIC | R2-m | R2-c |
|---|---|---|---|---|---|
| Full-model (round #1) | 33 | 610912.3 | 0 | ||
| SIZE × SBA × POFT (removed) | 32 | 610889.8 | −12.5 | ||
| SIZE × POFT × PET (removed) | 31 | 610937.1 | 24.8 | ||
| POFT × SBA × PET (removed) | 31 | 610900.8 | −11.5 | ||
| SIZE × SBA × PET (removed) | 31 | 610914.1 | 1.8 | ||
| Full-model (round #2) | 28 | 610891.0 | 0 | ||
| SIZE × SBA (removed) | 27 | 614430.1 | 3539.1 | ||
| POFT × SBA (removed) | 27 | 610885.3 | −5.7 | ||
| PET × SBA (removed) | 26 | 611043.7 | 152.7 | ||
| Best-supported model | 23 | 610885.3 | 0 | 0.367 | 0.705 |
| null model (intercept only) | 6 | 719146.1 | 108260.8 |
We used a hierarchical backward selection of fixed terms starting with a full model that included all the possible three-variable interactions between the proportion of other functional types (POFT), tree basal area (SIZE, m2), stand basal area (SBA, m2 ha−1), and potential evapotranspiration (PET, mm). We tested the contribution of each interaction by removing them one at a time. R2-m is the marginal pseudo R2 (fixed effects only) and R2-c is the conditional pseudo R2 (including both fixed and conditional effects).
*The round#2 of the backward selection started with the best supported model obtained in the first round.
**Best supported model: SIZE × POFT × PET+SIZE × SBA + PET × SBA.
Figure 1Predicted tree growth as function of potential evapotranspiration and stand basal area keeping size and the proportion of other functional types constant in mean values.
Red arrows indicate the main trends of tree growth at low, intermediate and high PET values.
Figure 2Predicted tree growth as function of potential evapotranspiration and the proportion of other functional types for small (a) and large trees (b) (basal area 0.008 m2 and 0.35 m2 respectively) keeping stand basal area in the mean value (25 m2 ha−1). Plots on the right represent predicted growth relative to growth in monoculture (%) for small (c) and large trees (d) keeping stand basal area in the mean value (25 m2 ha−1). Red arrows are indicative of the main trends of tree growth along low, intermediate and high PET values.
Descriptive statistics of plot-level information for each National Forest Inventory (NFI) for the randomly selected populations of trees across Europe.
| Spain | Wallonia | Germany | Sweden | Finland | Total | |
|---|---|---|---|---|---|---|
| No. plots | 18 083 | 90 | 7 649 | 4 621 | 1 619 | 32 628 |
| No. trees | 146 799 | 668 | 38 620 | 48 902 | 15 888 | 275 558 |
| No. species | 11 | 4 | 9 | 5 | 6 | 14 |
| PET (±SD) | 1018.9 ± 163.2 | 715.8 ± 42.1 | 732.9 ± 49.1 | 508.8 ± 57.9 | 505.6 ± 42.5 | 812.2 ± 241.7 |
| SBA (±SD) | 9.4 ± 9.5 | 23.3 ± 12.5 | 25.6 ± 14.8 | 12.6 ± 10.7 | 10.3 ± 8.5 | 20.131 ± 13.0 |
| MTBA (±SD) | 0.06 ± 0.08 | 0.15 ± 0.18 | 0.09 ± 0.09 | 0.03 ± 0.03 | 0.03 ± 0.02 | 0.06 ± 0.08 |
Species ID (alphabetical order): Abies alba (1), Acer pseudoplatanus (2), Betula pendula (3), Betula pubescens (4), Carpinus betulus (5), Castanea sativa (6), Fagus sylvativa (7), Juniperus thurifera (8), Picea abies (9), Pinus halepensis (10), Pinus sylvestris (11), Quercus ilex (12), Quercus pyrenaica (13), Quercus robur (14). PET–Potential Evapotranspiration (mm); SBA–Stand Basal Area (m2 ha−1); MTBA– Mean Tree Basal Area (m2).
Figure 3(a) Location of forest inventory plots across the study area (Europe) and (b) potential evapotranspiration (units) throughout the study area. Own preparation based on (a) plot coordinates included in the National Forest Inventories considered, and (b) Potential Evapotranspiration data available in CGIAR-CSI GeoPortal60 using software ArcGIS 13.0 by Esri (license University of Alcalá).