Showing papers on "Patterned vegetation published in 2017"
TL;DR: In this article, the response of vegetation dynamics in drylands to oscillating precipitation and local disturbances is studied, and it is shown that large amplitude oscillations of the precipitation rate can lead to a collapse of the vegetation in one range, while in the other range, they result in the convergence to a patterned state with a preferred wavelength.
Abstract: The response of dynamical systems to varying conditions and disturbances is a fundamental aspect of their analysis. In spatially extended systems, particularly in pattern-forming systems, there are many possible responses, including critical transitions, gradual transitions and locally confined responses. Here, we use the context of vegetation dynamics in drylands in order to study the response of pattern-forming ecosystems to oscillating precipitation and local disturbances. We focus on two precipitation ranges, a bistability range of bare soil with a patterned vegetation state, and a bistability range of uniform vegetation with a patterned vegetation state. In these ranges, there are many different stable states, which allow for both abrupt and gradual transitions between the system states to occur. We find that large amplitude oscillations of the precipitation rate can lead to a collapse of the vegetation in one range, while in the other range, they result in the convergence to a patterned state with a preferred wavelength. In addition, we show that a series of local disturbances results in the collapse of the vegetation in one range, while it drives the system toward fluctuations around a finite average biomass in the other range. Moreover, it is shown that under certain conditions, local disturbances can actually increase the overall vegetation density. These significant differences in the system response are attributed to the existence of localized states in one of the bistability ranges.
19 citations
23 Nov 2017
TL;DR: In this paper, the influence of different parameters, including the so-far not contemplated evaporation, on the long-term model results was analyzed and it was shown that vegetation is beneficial for semi-arid ecosystems, that is, vegetation is present for a broader parameter range.
Abstract: Semi-arid ecosystems made up of patterned vegetation, for instance, are thought to be highly sensitive. This highlights the importance of understanding the dynamics of the formation of vegetation patterns. The most renowned mathematical model describing such pattern formation consists of two partial differential equations and is often referred to as the Klausmeier model. This paper provides analytical and numerical investigations regarding the influence of different parameters, including the so-far not contemplated evaporation, on the long-term model results. Another focus is set on the influence of different initial conditions and on environmental noise, which has been added to the model. It is shown that patterning is beneficial for semi-arid ecosystems, that is, vegetation is present for a broader parameter range. Both parameter variability and environmental noise have only minor impacts on the model results. Increasing mortality has a high, nonlinear impact underlining the importance of further studies in order to gain a sufficient understanding allowing for suitable management strategies of this natural phenomenon.
6 citations
TL;DR: A fossil pollen record from a regularly patterned ribbon forest in Colorado is used to examine whether past changes in wildfire and climate produced abrupt vegetation shifts, and shows how extensive disturbances can trigger persistent new vegetation states and alter how vegetation responds to climate.
Abstract: Ecosystems may shift abruptly when the effects of climate change and disturbance interact, and landscapes with regularly patterned vegetation may be especially vulnerable to abrupt shifts. Here we use a fossil pollen record from a regularly patterned ribbon forest (alternating bands of forests and meadows) in Colorado to examine whether past changes in wildfire and climate produced abrupt vegetation shifts. Comparing the percentages of conifer pollen with sedimentary δ18O data (interpreted as an indicator of temperature or snow accumulation) indicates a first-order linear relationship between vegetation composition and climate change with no detectable lags over the past 2500 years (r = 0.55, P < 0.001). Additionally, however, we find that the vegetation changed abruptly within a century of extensive wildfires, which were recognized in a previous study to have burned approximately 80% of the surrounding 1000 km2 landscape 1000 years ago when temperatures rose ~0.5 °C. The vegetation change was larger than expected from the effects of climate change alone. Pollen assemblages changed from a composition associated with closed subalpine forests to one similar to modern ribbon forests. Fossil pollen assemblages then remained like those from modern ribbon forests for the following ~1000 years, providing a clear example of how extensive disturbances can trigger persistent new vegetation states and alter how vegetation responds to climate.
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TL;DR: In this article, the authors developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning.
Abstract: Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.