Self-organized Vegetation Patterns Research Articles

Self-organization as a mechanism of resilience in dryland ecosystems

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the resilience of drylands. Overall, our findings contribute to a deeper understanding of the relationship between spatial vegetation patterns and dryland resilience. They also represent a significant step forward in the development of indicators for ecosystem resilience, which are critical tools for managing and preserving these valuable ecosystems in a warmer and more arid world.

Role of herbivory in shaping the dryland vegetation ecosystem: Linking spiral vegetation patterns and nonlinear, nonlocal grazing.

Self-organized vegetation patterns are an amazing aspect of dryland ecosystems; in addition to being visually appealing, patterns control how these water-deprived systems react to escalating environmental stress. Although there is a wide variety of vegetation patterns, little is known about the mechanisms behind spiral patterns. The well-known models that explain other vegetation patterns such stripes, rings, and fairy circles cannot account for these spirals. Here we have adopted a modeling approach in which the interplay between herbivore grazing and vegetation is found to be the reason why spirals form. To comprehend the nonlinear dependence of grazing on the availability vegetation, we have introduced a grazing term that gets saturated when forage is abundant. To account for the impact of the spatial nonhomogeneity in vegetation layout, it is thought that grazing is dependent on mean vegetation density rather than density at a single site. Results show how the system dynamics is changed fundamentally depending on the different types of grazing response. Incorporation of nonlocality into the herbivore grazing leads to spiral-shaped vegetation patterns only in natural grazing scenarios; however, no patterning is seen in human controlled herbivory. Overall, our research points to the nonlocal, nonlinear grazing behavior of herbivores as one of the major driving forces for the development of spiral patterns.

Effect of nonlocal grazing on dry-land vegetation dynamics.

Dry-land ecosystems have become a matter of grave concern, due to the growing threat of land degradation and bioproductivity loss. Self-organized vegetation patterns are a remarkable characteristic of these ecosystems; apart from being visually captivating, patterns modulate the system response to increasing environmental stress. Empirical studies hinted that herbivory is one the key regulatory mechanisms behind pattern formation and overall ecosystem functioning. However, most of the mathematical models have taken a mean-field strategy to grazing; foraging has been considered to be independent of spatial distribution of vegetation. To this end, an extended version of the celebrated plant-water model due to Klausmeier has been taken as the base here. To encompass the effect of heterogeneous vegetation distribution on foraging intensity and subsequent impact on entire ecosystem, grazing is considered here to depend on spatially weighted average vegetation density instead of density at a particular point. Moreover, varying influence of vegetation at any location over gazing elsewhere is incorporated by choosing a suitable averaging function. A comprehensive analysis demonstrates that inclusion of spatial nonlocality alters the understanding of system dynamics significantly. The grazing ecosystem is found to be more resilient to increasing aridity than it was anticipated to be in earlier studies on nonlocal grazing. The system response to rising environmental pressure is also observed to vary depending on the grazer. Obtained results also suggest the possibility of multistability due to the history dependence of the system response. Overall, this work indicates that the spatial heterogeneity in grazing intensity has a decisive role to play in the functioning of water-limited ecosystems.

Towards creating a mechanistic predictive theory of self-organized vegetation patterns: Comment on "Belowground feedbacks as drivers of spatial self-organization and community assembly" by Inderjit, Callaway and Meron.

Towards creating a mechanistic predictive theory of self-organized vegetation patterns: Comment on "Belowground feedbacks as drivers of spatial self-organization and community assembly" by Inderjit, Callaway and Meron.

Spatial dynamics of a vegetation model in an arid flat environment

Self-organized vegetation patterns in space were found in arid and semi-arid areas. In this paper, we modelled a vegetation model in an arid flat environment using reaction-diffusion form and investigated the pattern formation. By using Hopf and Turing bifurcation theory, we obtain Turing region in parameters space. It is found that there are different types of stationary patterns including spotted, mixed, and stripe patterns by amplitude equation. Moreover, we discuss the changes of the wavelength with respect to biological parameters. Specifically, the wavelength becomes smaller as rainfall increases and larger as plant morality increases. The results may well explain the vegetation pattern observed in the real world and provide some new insights on preventing from desertification.

Self-organized vegetation patterning effects on surface soil hydraulic conductivity: A case study in the Qilian Mountains, China

A tension infiltrometer technique was used to determine the effects of vegetation patterning on the hydraulic properties of surface soils in an alpine catchment unit previously used as rain-fed agricultural land but now exhibiting a significantly self-organized vegetation pattern, with a shrub-covered surface on the north-facing slope and a grass-covered surface on the south-facing slope. We hypothesized that the surface soils in the catchment unit had a random pattern with relatively uniform variance before the fencing program began in 2000, because of long-term tillage and crop production, and we found a slightly organized and apparently heterogeneous pattern of Ks after the recovery period. While a relatively higher average Ks was observed on the north-facing slope than on the south-facing slope, the difference was not statistically significant. The surface soil hydraulic pattern in the catchment unit was controlled mainly by terrain-related processes such as runoff sealing and compaction, and vegetation patterning did not contribute as much as we expected to its development. Although the positive feedbacks between vegetation and soil we postulated in this work were not observed, such a positive feedback may exist in the root-zone soil profile, as indicated by the significant differences in physical and chemical parameters of soil profiles on different slope positions, e.g. bulk density, field capacity, total C, N and available P, etc. Assertion of the statement, however, is still subject to debate because of the limited data, and deserves much more detailed research and investigation in the future.

Slowing Down in Spatially Patterned Ecosystems at the Brink of Collapse

Predicting the risk of critical transitions, such as the collapse of a population, is important in order to direct management efforts. In any system that is close to a critical transition, recovery upon small perturbations becomes slow, a phenomenon known as critical slowing down. It has been suggested that such slowing down may be detected indirectly through an increase in spatial and temporal correlation and variance. Here, we tested this idea in arid ecosystems, where vegetation may collapse to desert as a result of increasing water limitation. We used three models that describe desertification but differ in the spatial vegetation patterns they produce. In all models, recovery rate upon perturbation decreased before vegetation collapsed. However, in one of the models, slowing down failed to translate into rising variance and correlation. This is caused by the regular self-organized vegetation patterns produced by this model. This finding implies an important limitation of variance and correlation as indicators of critical transitions. However, changes in such self-organized patterns themselves are a reliable indicator of an upcoming transition. Our results illustrate that while critical slowing down may be a universal phenomenon at critical transitions, its detection through indirect indicators may have limitations in particular systems.

Spatial and temporal signatures of fragility and threshold proximity in modelled semi-arid vegetation

Understanding the behaviour of complex environmental systems, particularly as critical thresholds are approached, is vitally important in many contexts. Among these are the moisture-limited vegetation systems in semi-arid (SA) regions of the World, which support approximately 36 per cent of the human population, maintain considerable biodiversity and which are susceptible to rapid stress-induced collapse. Change in spatially self-organized vegetation patterning has previously been proposed as a means of identifying approaching thresholds in these systems. In this paper, a newly developed cellular automata model is used to explore spatial patterning and also the temporal dynamics of SA vegetation cover. Results show, for the first time, to my knowledge, in a cellular automata model, that 'critical slowdown' (a pronounced reduction in post-perturbation recovery rates) provides clear signals of system fragility as major thresholds are approached. A consequence of slowing recovery rates is the appearance of quasi-stable population states and increased potential for perturbation-induced multi-staged population collapse. The model also predicts a non-patterned cover where environmental stress levels are high, or where more moderate stress levels are accompanied by frequent perturbations. In the context of changing climatic and environmental pressures, these results provide observable indicators of fragility and threshold proximity in SA vegetation systems that have direct relevance to management policies.

Positive feedbacks promote power-law clustering of Kalahari vegetation

The concept of local-scale interactions driving large-scale pattern formation has been supported by numerical simulations, which have demonstrated that simple rules of interaction are capable of reproducing patterns observed in nature. These models of self-organization suggest that characteristic patterns should exist across a broad range of environmental conditions provided that local interactions do indeed dominate the development of community structure. Readily available observations that could be used to support these theoretical expectations, however, have lacked sufficient spatial extent or the necessary diversity of environmental conditions to confirm the model predictions. We use high-resolution satellite imagery to document the prevalence of self-organized vegetation patterns across a regional rainfall gradient in southern Africa, where percent tree cover ranges from 65% to 4%. Through the application of a cellular automata model, we find that the observed power-law distributions of tree canopy cluster sizes can arise from the interacting effects of global-scale resource constraints (that is, water availability) and local-scale facilitation. Positive local feedbacks result in power-law distributions without entailing threshold behaviour commonly associated with criticality. Our observations provide a framework for integrating a diverse suite of previous studies that have addressed either mean wet season rainfall or landscape-scale soil moisture variability as controls on the structural dynamics of arid and semi-arid ecosystems.

Self‐organized vegetation patterning as a fingerprint of climate and human impact on semi‐arid ecosystems

SummarySpatially periodic vegetation patterns are well known in arid and semi‐arid regions around the world.Mathematical models have been developed that attribute this phenomenon to a symmetry‐breaking instability. Such models are based on the interplay between competitive and facilitative influences that the vegetation exerts on its own dynamics when it is constrained by arid conditions, but evidence for these predictions is still lacking. Moreover, not all models can account for the development of regularly spaced spots of bare ground in the absence of a soil prepattern.We applied Fourier analysis to high‐resolution, remotely sensed data taken at either end of a 40‐year interval in southern Niger. Statistical comparisons based on this textural characterization gave us broad‐scale evidence that the decrease in rainfall over recent decades in the sub‐Saharan Sahel has been accompanied by a detectable shift from homogeneous vegetation cover to spotted patterns marked by a spatial frequency of about 20 cycles km−1.Wood cutting and grazing by domestic animals have led to a much more marked transition in unprotected areas than in a protected reserve.Field measurements demonstrated that the dominant spatial frequency was endogenous rather than reflecting the spatial variation of any pre‐existing heterogeneity in soil properties.All these results support the use of models that can account for periodic vegetation patterns without invoking substrate heterogeneity or anisotropy, and provide new elements for further developments, refinements and tests.This study underlines the potential of studying vegetation pattern properties for monitoring climatic and human impacts on the extensive fragile areas bordering hot deserts. Explicit consideration of vegetation self‐patterning may also improve our understanding of vegetation and climate interactions in arid areas.