Reduction in plant size and tissue nutrient concentration is widely considered to increase 30 seedling drought resistance in dry and oligotrophic plantation sites. However, much evidence 31 indicates that increase in size and tissue nutrient concentration improves seedling survival in 32 Mediterranean forest plantations. This suggests that the ecophysiological processes and 33 functional attributes relevant for early seedling survival in Mediterranean climate must be 34 reconsidered. We propose a physiological conceptual model for seedling survival in 35 Mediterranean-climate plantations to provide a physiological explanation of the frequent 36 positive relationship between outplanting performance and seedling size and nutrient 37 concentration. The model considers the physiological processes outlined in the plantation 38 establishment model of Burdett (1990), but incorporates other physiological processes that 39 drive seedling survival, such as N remobilization, carbohydrate storage and plant hydraulics.40 The model considers that seedling survival in Mediterranean climates is linked to high growth 41 capacity during the wet season. The model is for container plants and is based on three main 42 principles, 1) Mediterranean climates are not dry the entire year but usually have two 43 seasons of contrasting water availability; 2) summer drought is the main cause of seedling 44 mortality; in this context deep and large roots is a key trait for avoiding lethal water stress; 3) 45 attainment of large root systems in the dry season is promoted when seedlings have high 46 growth during the wet season. High growth is achieved when seedlings can divert large 47 amount of resources to support new root and shoot growth. Functional traits that confer high 48 photosynthesis, nutrient remobilization capacity, and non-structural carbohydrate storage 49 promote high growth. Increases in seedling size and nutrient concentration, strongly affect 50 these physiological processes. Traits that confer high drought resistance are of low value 51 during the wet season because hinder growth capacity. We provide specific evidence to 52 support the model and finally we discuss its implications and the factors that may alter the 53 frequent increase in performance with increase in seedling size and tissue nutrient 54 concentration.

Summary 1.Competitive and facilitative interactions shape plant communities. Whereas a number of studies have addressed competition and direct facilitation among plants in dry ecosystems, indirect facilitation has received little attention. 2. We investigated the relative importance of direct and indirect facilitation by the nurse plant Retama sphaerocarpa on late-successional Quercus ilex seedlings mediated by herb suppression in a Mediterranean shrubland in 2006 and 2007. We also studied whether facilitation outcome depended on the size of the facilitated seedlings. 3. A field experiment was carried out to test the effect of (i) position of Q. ilex seedling with respect to shrub canopy (under shrubs or in gaps), (ii) herb competition (presence or absence), and (iii) seedling size. 2006 was an average rainfall year while 2007 had a much more humid spring and a dryer summer than 2006. 4. In both years, nurse shrubs reduced seedling mortality whereas herbs increased it. In the average rainfall year, seedling mortality under shrubs was unaffected by herbs whereas in gaps it was significantly higher in presence of herbs. This showed that the nurse shrub indirectly facilitated the seedlings by reducing the competitive capacity of herbs. Conversely, facilitation was predominately direct during the humid spring and dry summer year since herbs hindered seedling survival similarly under the nurse shrub and in gaps. The nurse shrub directly facilitated the seedlings by reducing seedling photoinhibition and water stress. 5. Improvement of environmental conditions by Retama benefited smaller seedlings but not larger seedlings since the nurse shrub reduced mortality of smaller seedlings relative to that in gaps, but this effect was not observed for larger seedlings. This indicates that individuals within a seedling population may not have the same response to facilitation. 6. Synthesis. Both indirect and direct facilitation are important mechanisms for Q. ilex regeneration in Retama shrubland and their importance seems to vary with climatic conditions. Indirect facilitation by release of herb competition under nurse shrubs is important in years of dry springs when competition between nurse shrubs and herbs is high, whereas direct facilitation mediated by microclimate amelioration increases with summer aridity.

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Abstract. The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree–grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass–fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.

Abstract. The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future, due to global climate change. Dynamic Global Vegetation Models (DGVMs) are very useful to understand vegetation dynamics under present climate, and to predict its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modelling. Model outcomes, obtained including different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need an improved representation in the DGVMs. The first mechanism includes water limitation to tree growth, and tree-grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass-fire feedback, which maintains both forest and savanna occurrences in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant savanna trees, and fire-resistant and shade-intolerant forest trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.