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Plant-soil feedback (PSF) describes the process whereby plant species modify the soil environment, which subsequently impacts the growth of the same or another plant species. Our aim was to explore PSF by two maize varieties (a landrace and a hybrid variety) and three arbuscular mycorrhizal fungi (AMF) species (Funneliformis mosseae, Claroideoglomus etunicatum, Gigaspora margarita, and the mixture). We carried out a pot experiment with a conditioning and a feedback phase to determine PSF with different species of AMF and with a non-mycorrhizal control. Sterilized soil was conditioned separately by each variety, with or without AMF; in the feedback phase, each soil community was used to grow each in its "home" soil and in the "away" soil. Plant performance was assessed as shoot biomass, phosphorus (P) concentration and P content, and fungal performance was assessed as mycorrhizal colonization and hyphal length density. Both maize varieties were differentially influenced by AMF in the conditioning phase. In the feedback phase, PSF was generally negative for non-mycorrhizal plants or when plants were colonized by G. margarita, whereas PSF was positive in the other three AMF treatments. When plants were grown on home soil, hyphal length density was larger than on away soil. We conclude that different maize varieties can strengthen positive plant-soil feedback for themselves through beneficial mutualists for themselves, but not across the maize varieties.

Plant-soil feedback (PSF) describes the process whereby plant species modify the soil environment, which subsequently impacts the growth of the same or another plant species. Our aim was to explore PSF by two maize varieties (a landrace and a hybrid variety) and three arbuscular mycorrhizal fungi (AMF) species (Funneliformis mosseae, Claroideoglomus etunicatum, Gigaspora margarita, and the mixture). We carried out a pot experiment with a conditioning and a feedback phase to determine PSF with different species of AMF and with a non-mycorrhizal control. Sterilized soil was conditioned separately by each variety, with or without AMF; in the feedback phase, each soil community was used to grow each in its "home" soil and in the "away" soil. Plant performance was assessed as shoot biomass, phosphorus (P) concentration and P content, and fungal performance was assessed as mycorrhizal colonization and hyphal length density. Both maize varieties were differentially influenced by AMF in the conditioning phase. In the feedback phase, PSF was generally negative for non-mycorrhizal plants or when plants were colonized by G. margarita, whereas PSF was positive in the other three AMF treatments. When plants were grown on home soil, hyphal length density was larger than on away soil. We conclude that different maize varieties can strengthen positive plant-soil feedback for themselves through beneficial mutualists for themselves, but not across the maize varieties.

AbstractAlthough canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite‐borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest‐savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna‐like sparse tree cover that have a forest‐like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

AbstractAlthough canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite‐borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest‐savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna‐like sparse tree cover that have a forest‐like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

Small but numerically dominant species such as the cyanobacteria Prochlorococcus play a pivotal role in major nutrient cycles. To understand how Prochlorococcus populations affect nutrient flows, we present and analyze two alternative population models. These models − one including over-shading effects and one not − are based on Dynamic Energy Budget (DEB) theory to describe how growth may be affected by the availability of CO2 and/or inorganic nutrients and by changes in light conditions. In these models individuals have reserves for C, N, and P from which fluxes for maintenance and growth are mobilized. Time series data from laboratory studies of growth under three different nutrient concentrations are used to calibrate the models. The model with carbon, nitrogen and phosphate as limiting factors can reasonably describe the growth in the low N and low P media experiments, while the model with over-shading gives a proper description of the growth under all tested experimental conditions. Modeled C:N:P ratios are within range of reported in scientific literature ones and similar to measured ratios. The results suggest that (1) reserves play a critical role for cyanobacteria to thrive under the often oligotrophic conditions in which they live, and (2) over-shading has a considerable effect as co-limiting factor on the growth of cyanobacteria. We argue that an individual DEB-based model in which multiple nutrient limitations are presented can be used to successfully describe cyanobacterium growth patterns in batch cultures.

Small but numerically dominant species such as the cyanobacteria Prochlorococcus play a pivotal role in major nutrient cycles. To understand how Prochlorococcus populations affect nutrient flows, we present and analyze two alternative population models. These models − one including over-shading effects and one not − are based on Dynamic Energy Budget (DEB) theory to describe how growth may be affected by the availability of CO2 and/or inorganic nutrients and by changes in light conditions. In these models individuals have reserves for C, N, and P from which fluxes for maintenance and growth are mobilized. Time series data from laboratory studies of growth under three different nutrient concentrations are used to calibrate the models. The model with carbon, nitrogen and phosphate as limiting factors can reasonably describe the growth in the low N and low P media experiments, while the model with over-shading gives a proper description of the growth under all tested experimental conditions. Modeled C:N:P ratios are within range of reported in scientific literature ones and similar to measured ratios. The results suggest that (1) reserves play a critical role for cyanobacteria to thrive under the often oligotrophic conditions in which they live, and (2) over-shading has a considerable effect as co-limiting factor on the growth of cyanobacteria. We argue that an individual DEB-based model in which multiple nutrient limitations are presented can be used to successfully describe cyanobacterium growth patterns in batch cultures.