Time filter

Source Type

Scheiter S.,Biodiversitat und Klima Forschungszentrum LOEWE BiK F | Higgins S.I.,Goethe University Frankfurt | Osborne C.P.,University of Sheffield | Bradshaw C.,University of Bristol | And 4 more authors.
New Phytologist

Large proportions of the Earth's land surface are covered by biomes dominated by C 4 grasses. These C 4-dominated biomes originated during the late Miocene, 3-8 million years ago (Ma), but there is evidence that C 4 grasses evolved some 20Ma earlier during the early Miocene/Oligocene. Explanations for this lag between evolution and expansion invoke changes in atmospheric CO 2, seasonality of climate and fire. However, there is still no consensus about which of these factors triggered C 4 grassland expansion. We use a vegetation model, the adaptive dynamic global vegetation model (aDGVM), to test how CO 2, temperature, precipitation, fire and the tolerance of vegetation to fire influence C 4 grassland expansion. Simulations are forced with late Miocene climates generated with the Hadley Centre coupled ocean-atmosphere-vegetation general circulation model. We show that physiological differences between the C 3 and C 4 photosynthetic pathways cannot explain C 4 grass invasion into forests, but that fire is a crucial driver. Fire-promoting plant traits serve to expand the climate space in which C 4-dominated biomes can persist. We propose that three mechanisms were involved in C 4 expansion: the physiological advantage of C 4 grasses under low atmospheric CO 2 allowed them to invade C 3 grasslands; fire allowed grasses to invade forests; and the evolution of fire-resistant savanna trees expanded the climate space that savannas can invade. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust. Source

Scheiter S.,Biodiversitat und Klima Forschungszentrum LOEWE BiK F | Higgins S.I.,Goethe University Frankfurt

Aboveground and belowground biomass compartments of vegetation fulfil different functions and they are coupled by complex interactions. These compartments exchange water, carbon and nutrients and the belowground biomass compartment has the capacity to buffer vegetation dynamics when aboveground biomass is removed by disturbances such as herbivory or fire. However, despite their importance, root-shoot interactions are often ignored in more heuristic vegetation models. Here, we present a simple two-compartment grassland model that couples aboveground and belowground biomass. In this model, the growth of belowground biomass is influenced by aboveground biomass and the growth of aboveground biomass is influenced by belowground biomass. We used the model to explore how the dynamics of a grassland ecosystem are influenced by fire and grazing. We show that the grassland system is most persistent at intermediate levels of aboveground-belowground coupling. In this situation, the system can sustain more extreme fire or grazing regimes than in the case of strong coupling. In contrast, the productivity of the system is maximised at high levels of coupling. Our analysis suggests that the yield of a grassland ecosystem is maximised when coupling is strong, however, the intensity of disturbance that can be sustained increases dramatically when coupling is intermediate. Hence, the model predicts that intermediate coupling should be selected for as it maximises the chances of persistence in disturbance driven ecosystems. © 2013 Scheiter, Higgins. Source

Scheiter S.,Biodiversitat und Klima Forschungszentrum LOEWE BiK F | Langan L.,Goethe University Frankfurt | Higgins S.I.,Goethe University Frankfurt
New Phytologist

Dynamic global vegetation models (DGVMs) are powerful tools to project past, current and future vegetation patterns and associated biogeochemical cycles. However, most models are limited by how they define vegetation and by their simplistic representation of competition. We discuss how concepts from community assembly theory and coexistence theory can help to improve vegetation models. We further present a trait- and individual-based vegetation model (aDGVM2) that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow and compete. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to a site's biotic and abiotic conditions. The aDGVM2 simulates how environmental conditions influence the trait spectra of plant communities; that fire selects for traits that enhance fire protection and reduces trait diversity; and the emergence of life-history strategies that are suggestive of colonization-competition trade-offs. The aDGVM2 deals with functional diversity and competition fundamentally differently from current DGVMs. This approach may yield novel insights as to how vegetation may respond to climate change and we believe it could foster collaborations between functional plant biologists and vegetation modellers. © 2013 New Phytologist Trust. Source

Blanco C.C.,Federal University of Rio Grande do Sul | Scheiter S.,Biodiversitat und Klima Forschungszentrum LOEWE BiK F | Sosinski E.,Embrapa Temperate Agriculture | Fidelis A.,Claro | And 2 more authors.
Ecological Modelling

Vegetation changes, such as shrub encroachment and forest expansion over grasslands, prairies and savannas have been related to changes in climatic (mainly rainfall and temperature) and atmospheric conditions (CO2 concentration). However, a longstanding question in ecology is how mosaics of forests and open-canopy ecosystems could persist over millennia in sites where climatic conditions favor forests. Here we tested the influence of interactions between grass-tree competition, environmental heterogeneity (topography), seed dispersal, initial density and spatial aggregation of vegetation patches and disturbance behavior (fire) on the long-term coexistence of forests and grasslands in South Brazil. For this, we incorporated the adaptive dynamic global vegetation model (aDGVM) into a spatially explicit modeling approach (2D-aDGVM). Our results showed that recurrent disturbance related to grasses such as fires plays a key role in maintaining the long-term coexistence of forests and grasslands, mainly through feedbacks between disturbance frequency and grass biomass. Topographic heterogeneity affected the rate of forest expansion by adding spatio-temporal variability in vegetation-fire feedbacks. However, the spatial pattern and connectivity of fire-prone (grasslands) and fire-sensitive (forest) vegetation patches were more important to maintain the long-term coexistence of both alternative vegetation states than the initial proportion of forest and grasslands patches. The model is the first individual-based DGVM to consider the combined effects of topography, seed dispersal and fire spread behavior in a spatially explicit approach. © 2014 Elsevier B.V. Source

Discover hidden collaborations