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In old and heavily weathered soils, the availability of P might be so small that the primary production of plants is limited. However, plants have evolved several mechanisms to actively take up P from the soil or mine it to overcome this limitation. These mechanisms involve the active uptake of P mediated by mycorrhiza, biotic de-occlusion through root clusters, and the biotic enhancement of weathering through root exudation. The objective of this paper is to investigate how and where these processes contribute to alleviate P limitation on primary productivity. To do so, we propose a process-based model accounting for the major processes of the carbon, water, and P cycles including chemical weathering at the global scale. Implementing P limitation on biomass synthesis allows the assessment of the efficiencies of biomass production across different ecosystems. We use simulation experiments to assess the relative importance of the different uptake mechanisms to alleviate P limitation on biomass production. We find that active P uptake is an essential mechanism for sustaining P availability on long timescales, whereas biotic de-occlusion might serve as a buffer on timescales shorter than 10 000 yr. Although active P uptake is essential for reducing P losses by leaching, humid lowland soils reach P limitation after around 100 000 yr of soil evolution. Given the generalized modelling framework, our model results compare reasonably with observed or independently estimated patterns and ranges of P concentrations in soils and vegetation. Furthermore, our simulations suggest that P limitation might be an important driver of biomass production efficiency (the fraction of the gross primary productivity used for biomass growth), and that vegetation on old soils has a smaller biomass production rate when P becomes limiting. With this study, we provide a theoretical basis for investigating the responses of terrestrial ecosystems to P availability linking geological and ecological timescales under different environmental settings.
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.
Ongoing and predicted global change makes understanding and predicting species’ range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.
Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere–atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere–atmosphere interactions under current and changing climatic conditions in the region.