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This review summarizes the effects of vegetation on runoff and soil loss in three dimensions: vertical vegetation structures (aboveground vegetation cover, surface litter layer and underground roots), plant diversity, vegetation patterns and their scale characteristics. Quantitative relationships between vegetation factors with runoff and soil loss are described. A framework for describing relationships involving vegetation, erosion and scale is proposed. The relative importance of each vegetation dimension for various erosion processes changes across scales. With the development of erosion features (i.e., splash, interrill, rill and gully), the main factor of vertical vegetation structures in controlling runoff and soil loss changes from aboveground biomass to roots. Plant diversity levels are correlated with vertical vegetation structures and play a key role at small scales, while vegetation patterns also maintain a critical function across scales (i.e., patch, slope, catchment and basin/region). Several topics for future study are proposed in this review, such as to determine efficient vegetation architectures for ecological restoration, to consider the dynamics of vegetation patterns, and to identify the interactions involving the three dimensions of vegetation.

Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer‐term in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products. We use recently developed methods using remote‐sensing EVI time‐series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non‐linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non‐linear way. Our findings suggest that spatial self‐organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non‐linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

Identified as essential mechanisms promoting alternative stable states, positive feedbacks have been the focus of most former studies on the potential for catastrophic shifts in drylands. Conversely, little is known about how negative feedbacks could counterbalance the effects of positive feedbacks. A decrease in vegetation cover increases the connectivity of bare-soil areas and entails a global loss of runoff-driven resources from the ecosystem but also a local increase in runoff transferred from bare-soil areas to vegetation patches. In turn, these global resource losses and local resource gains decrease and increase vegetation cover, respectively, resulting in a global positive and a local negative feedback loop. We propose that the interplay of these two interconnected ecohydrological feedbacks of opposite sign determines the vulnerability of dryland ecosystems to catastrophic shifts. To test this hypothesis, we developed a spatially explicit model and assessed the effects of varying combinations of feedback strengths on the dynamics, resilience, recovery potential, and spatial structure of the system. Increasing strengths of the local negative feedback relative to the global positive feedback decreased the risk of catastrophic shifts, facilitated recovery from a degraded state, and promoted the formation of banded vegetation patterns. Both feedbacks were most relevant at low vegetation cover due to the nonlinear increase in hydrological connectivity with decreasing vegetation. Our modelling results suggest that catastrophic shifts to degraded states are less likely in drylands with strong source–sink dynamics and/or strong response of vegetation growth to resource redistribution and that feedback manipulation can be useful to enhance dryland restoration.

Changes to vegetation structure and composition in forests adapted to frequent fire have been well documented. However, little is known about changes to the spatial characteristics of vegetation in these forests. Specifically, patch sizes and detailed information linking vegetation type to specific locations and growing conditions on the landscape are lacking. We used historical and recent aerial imagery to characterize historical vegetation patterns and assess contemporary change from those patterns. We created an orthorectified mosaic of aerial photographs from 1941 covering approximately 100,000 ha in the northern Sierra Nevada. The historical imagery, along with contemporary aerial imagery from 2005, was segmented into homogenous vegetation patches and classified into four relative cover classes using random forests analysis. A generalized linear mixed model was used to compare topographic associations of dense forest cover on the historical and contemporary landscapes. The amount of dense forest cover increased from 30 to 43% from 1941 to 2005, replacing moderate forest cover as the most dominant class. Concurrent with the increase in extent, the area-weighted mean patch size of dense forest cover increased tenfold, indicating greater continuity of dense forest cover and more homogenous vegetation patterns across the contemporary landscape. Historically, dense forest cover was rare on southwesterly aspects, but in the contemporary forest, it was common across a broad range of aspects. Despite the challenges of processing historical air photographs, the unique information they provide on landscape vegetation patterns makes them a valuable source of reference information for forests impacted by past management practices.

Tree-grass coexistence is a defining feature of savanna ecosystems, which play an important role in supporting biodiversity and human populations worldwide. While recent advances have clarified many of the underlying processes, how these mechanisms interact to shape ecosystem dynamics under environmental stress is not yet understood. Here, we present and analyse a minimalistic spatially extended model of tree-grass dynamics in dry savannas. We incorporate tree facilitation of grasses through shading and grass competing with trees for water, both varying with tree life stage. Our model shows that these mechanisms lead to grass-tree coexistence and bistability between savanna and grassland states. Moreover, the model predicts vegetation patterns consisting of trees and grasses, particularly under harsh environmental conditions, which can persist in situations where a non-spatial version of the model predicts ecosystem collapse from savanna to grassland instead (a phenomenon called ‘Turing-evades-tipping’). Additionally, we identify a novel ‘Turing-triggers-tipping’ mechanism, where unstable pattern formation drives tipping events that are overlooked when spatial dynamics are not included. These transient patterns act as early warning signals for ecosystem transitions, offering a critical window for intervention. Further theoretical and empirical research is needed to determine when spatial patterns prevent tipping or drive collapse.

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.

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems.

Since the Last Glacial Maximum (LGM), the global climate has experienced several stages, such as cold and warming events, which provide an ideal model for evaluating climate change in the future. Based on the pollen records in Northeast (NE) China, the vegetation pattern during special periods since the LGM was reconstructed in this work. During the LGM (approximately 18,000 cal yr BP), the steppes expanded rapidly in NE China, and a cold-dry meadow-steppe developed on the Songnen Plain. The Liaohe Plain and the Hulun Buir Plateau were occupied by a steppe-desert, with forest-steppe vegetation grown in the central and southern plains; there were cold-dry coniferous forests and mixed conifer-broadleaf forests in mountainous areas. In the early Holocene (10,000–9,000 cal yr BP), Changbai mountain (CBM) forests thrived in the eastern hilly area and the Sanjiang Plain, while the central region was dominated by steppes, and warm-temperate broadleaf forests developed northward. During the Holocene warm period (approximately 6,000 cal yr BP), CBM forests and cold-temperate coniferous forests developed in the north, while spruce-fir forests developed in the eastern Xiao Hinggan Mountains and the Sanjiang Plain. The distribution centre of deciduous broadleaf forests migrated to the south of the Changbai Mountains and the Liaodong Peninsula. The isolated woodlands increased on the Songnen Plain and the meadow-steppes expanded to the Liaohe Plain. Therefore, the increase in temperature leads to the increase of monsoon precipitation in NE China, which is beneficial to the development of warm-temperate forest vegetation. The increase of summer monsoons and precipitation caused by climate warming may be the main reason for the improved plant load.

The difficulties in predicting whole catchment water balance from observations at patch scales motivate a search for theories that can account for the complexity of interactions in catchments. In this paper we suggest that the spatial patterns of vegetation may offer a lens through which to investigate scale dependence of hydrology within catchments. Vegetation patterns are attractive because they are observable drivers of evapotranspiration, often a dominant component in catchment water balance, and because the spatial distribution of vegetation is often driven by patterns of water availability. We propose that nontrivial, scale‐dependent spatial patterns in both vegetation distribution and catchment water balance are generated by the presence of a convergent network of flow paths and a two‐way feedback between vegetation as a driver of evapotranspiration and vegetation distribution as a signature of water availability. Implementing this hypothesis via a simple network model demonstrated that such organization was controlled by catchment properties related to aridity, the network topology, the sensitivity of the vegetation response to water availability, and the point‐scale controls on partitioning between evapotranspiration and lateral drainage. The resulting self‐organization generated spatial dependence in areally averaged hydrologic variables, water balance, and parameters describing hydrological partitioning. This spatial scale dependence provides a theoretical approach to connect water balance at patch and catchment scales. Theoretical and empirical studies for understanding the controls of vegetation spatial distribution, point‐scale hydrological partitioning, and the implications of complex flow network topologies on the spatial scale dependence of catchment water balance are proposed as a research agenda for catchment ecohydrology. Key Points Vegetation is both a driver and a response to water availability Lateral fluxes of water cause spatial scale dependence in water and vegetation Topography, climate, vegetation, and the flow network modify the scaling

In ‘The chemical basis of morphogenesis’ (1952), Alan Turing introduced an idea that revolutionised our thinking about pattern formation. He proposed that diffusion could lead to the spontaneous formation of regular patterns. Here, we discuss the impact of Turing’s idea on plant science using three well-established examples at different scales: ROP patterning inside single cells, epidermal patterning across several cells and whole vegetation patterns. Also at intermediate levels, e.g., organ spacing, plants look surprisingly regular. But not all regular patterns are Turing patterns, careful observation and prediction of the patterning process—not just the final pattern—is critical to distinguish between mechanisms.