Appendix B. Estimation equations for pre-reproductive vegetative mass.

Estimation equations for pre-reproductive vegetative mass

Appendix D. Unstandardized path coefficients and intercepts of the structural equations.

Unstandardized path coefficients and intercepts of the structural equations

Relationships between crop growth rate (CGR) and leaf functional trait values: (a) leaf dry matter content (LDMC), (b) leaf area (LA); and relationships between crop N acquisition rate (CNR) and leaf functional trait values: (c) leaf dry matter content (LDMC), (c) leaf area (LA).

<p>The significance of differences was assessed by Student’s t-tests. Values of traits and CGRs are means of both experimental sites.</p

Appendix K. Box and whisker plots of the average biomass produced for each harvest in the two treatments.

Box and whisker plots of the average biomass produced for each harvest in the two treatments

Leaf trait values of cover crop species obtained in the present study compared to trait values of congeneric wild species obtained from the TRY plant-trait database (Kattge et al. [34] and S2 Text).

<p>Traits of wild species are means of annual species of same genus. Values are means ± SDs of species of each family (na: data not available in TRY database). The significance of differences was assessed by Student’s t-tests, testing the global effect for all genera. The relative distance was calculated as the difference between the average values of cover crops and the average values of wild species as: <i>Relative distance rate = (Cover crop trait value—wild species trait value) / wild species trait value</i>.</p><p>Leaf trait values of cover crop species obtained in the present study compared to trait values of congeneric wild species obtained from the TRY plant-trait database (Kattge et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122156#pone.0122156.ref034" target="_blank">34</a>] and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0122156#pone.0122156.s003" target="_blank">S2 Text</a>).</p

Appendix A. Predicted and observed soil water content in the upper 30 cm from January to December in 2008, together with daily rainfall during the same period.

Predicted and observed soil water content in the upper 30 cm from January to December in 2008, together with daily rainfall during the same period

A Functional Characterisation of a Wide Range of Cover Crop Species: Growth and Nitrogen Acquisition Rates, Leaf Traits and Ecological Strategies

<div><p>Cover crops can produce ecosystem services during the fallow period, as reducing nitrate leaching and producing green manure. Crop growth rate (CGR) and crop nitrogen acquisition rate (CNR) can be used as two indicators of the ability of cover crops to produce these services in agrosystems. We used leaf functional traits to characterise the growth strategies of 36 cover crops as an approach to assess their ability to grow and acquire N rapidly. We measured specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC) and leaf area (LA) and we evaluated their relevance to characterise CGR and CNR. Cover crop species were positioned along the Leaf Economics Spectrum (LES), the SLA-LDMC plane, and the CSR triangle of plant strategies. LA was positively correlated with CGR and CNR, while LDMC was negatively correlated with CNR. All cover crops could be classified as resource-acquisitive species from their relative position on the LES and the SLA-LDMC plane. Most cover crops were located along the Competition/Ruderality axis in the CSR triangle. In particular, Brassicaceae species were classified as very competitive, which was consistent with their high CGR and CNR. Leaf functional traits, especially LA and LDMC, allowed to differentiate some cover crops strategies related to their ability to grow and acquire N. LDMC was lower and LNC was higher in cover crop than in wild species, pointing to an efficient acquisitive syndrome in the former, corresponding to the high resource availability found in agrosystems. Combining several leaf traits explained approximately half of the CGR and CNR variances, which might be considered insufficient to precisely characterise and rank cover crop species for agronomic purposes. We hypothesised that may be the consequence of domestication process, which has reduced the range of plant strategies and modified the leaf trait syndrome in cultivated species.</p></div

Dataset_When is the best time to flower and disperse

Data used in "When is the best time to flower and disperse? A comparative analysis of plant reproductive phenology in the Mediterranean". It combines estimated means and standard errors of onset of flowering, onset of seed dispersal and seed maturation period for 138 plant species growing in the Mediterranean region of southern France

Principal component analysis (PCA) based on four functional traits measured on 36 cover crop species.

<p>(a) Correlation circle between SLA (specific leaf area), LDMC (leaf dry matter content), LNC (leaf nitrogen content) and LA (leaf area) and loadings; coordinates position of CGR (crop growth rate) and CNR (crop nitrogen acquisition rate); (b) Botanical families and cover crop species position along the first two axes of the PCA; A: Asteraceae; B: Brassicaceae; F: Fabaceae; H: Hydrophyllaceae; P: Polygonaceae; PC3: C₃ Poaceae; PC4: C₄ Poaceae.</p

Appendix B. Periods of the year and variables used to assess the abiotic controls on biomass production: relative soil water content and temperature.

Periods of the year and variables used to assess the abiotic controls on biomass production: relative soil water content and temperature