River ecosystems play a crucial role in supporting biodiversity and providing essential ecosystem services. They are shaped by complex nonlinear interactions between vegetation, water and sediment, which give rise to both positive and negative feedbacks. Despite their importance, how ecomorphodynamic feedbacks interact with one another and influence river dynamics remains poorly understood. Gaining this understanding is crucial for sustaining and managing healthy and resilient ecosystems, especially in the context of global change. In this work, we use ecomorphodynamic numerical models—both non-spatial and spatial—to investigate the role of feedbacks in governing river ecosystem dynamics. Both models couple hydro-morphodynamics with vegetation dynamics, where the system is periodically disturbed by a succession of floods of constant amplitude. Previous research has demonstrated that the system dominated by a negative feedback loop oscillates and exhibits chaotic behavior. In contrast, here our study reveals that when positive feedbacks and interactions prevail, the non-spatial model exhibits bi-stability, abrupt shifts and tipping points between the vegetated state and bare soil. However, when spatial interactions are included, the system displays multi-stability, self-organizing into multiple stable equilibria defined by specific hydro-morphodynamic conditions and vegetation configurations. This spatial multi-stability expands vegetation persistence, enabling the system to better resist external flood disturbances and enhancing resilience by smoothing abrupt shifts and tipping points. Our results highlight the importance of feedbacks and spatial interactions in maintaining ecosystem resilience, with significant implications for ecosystem management and restoration under increasing environmental disturbances.

Spatially explicit ecosystem models are often used to study changing savanna ecosystems. Many different models have been made with different research goals. An overview of all these existing spatial savanna models is currently lacking. Therefore, we performed a systematic search to gather the literature so far on spatial savanna models. We grouped these models into three different categories of model types: partial differential equations, integrodifferential equations, and cellular automata. We also determined whether the model contained stochastic elements. In addition, we identified the presence of four different ecosystem mechanisms in each model: water, shading, herbivory, and fire. Finally, we determined which types of spatiotemporal dynamics the models generated, where we focused on pattern formation, temporal oscillations, and abrupt changes. We show that some ecosystem mechanisms frequently co-occur with each other, which is mainly based on the type of savanna along a rainfall gradient that is modelled. Moreover, we show that some ecosystem mechanisms frequently co-occur with certain spatiotemporal dynamics. Based on these overviews, we propose that future research should focus on developing a unified spatial savanna model, which considers all of the relevant ecosystem mechanisms along a rainfall gradient. Such a model could be used to predict the response of savanna ecosystems to a changing climate.

Phosphorus (P) is often a limiting nutrient in highly weathered soils. Fire is a major driver of nutrient redistribution and can temporarily increase the pool of plant-available P in P-limited ecosystems. Yet, the long-term effects of frequent fire on soil P in montane grasslands remain poorly understood. We investigated how fire regime influences soil P pools using data from a long-term fire experiment in the South African Drakensberg. Total soil P, moderately labile organic and inorganic P and plant-available P were measured across five prescribed fire regimes varying in frequency (annual, biennial or infrequent) and season of burn (autumn or spring). We hypothesised that frequent fire would not alter total P in the topsoil, but expected it would increase inorganic P and plant-available P. Infrequent and biennial burns had little effect on total P; however, total P was significantly higher under annual spring burns than the other treatments, particularly the infrequent burns and annual or biennial autumn burns. In contrast, plant-available P did not respond to any fire treatment. Frequent spring burns generally increased organic P relative to inorganic P, indicating a shift in the composition of soil P pools with fire frequency and season. Overall, despite changes in topsoil total and organic P, plant-available P remained constrained, reflecting a bottleneck in the P cycle likely driven by the high P-retention capacity of these acidic Andosols. These findings highlight the complex and sometimes counterintuitive effects of fire on nutrient dynamics in montane grasslands.

Tropical ecosystems are increasingly exposed to fire disturbance and their responses have been assessed at regional to global scales. However, these fire-vegetation relationships remain insufficiently understood particularly in intact systems that have not been altered by human activities. Here, we conduct a national-scale assessment of fire impacts on tree cover across Indonesia over two decades, explicitly distinguishing between intact and modified peatlands and comparing their responses with intact and modified non-peatland ecosystems. We find that higher fire occurrence is associated with lower tree cover across all ecosystems, but the magnitude of the relationship differs substantially. Non-peatland ecosystems exhibit consistently strong negative relationships between fire and tree cover under both modified (r = −0.956, mean tree cover = 66%) and intact conditions (r = −0.967, mean tree cover = 73%). In contrast, peatlands show divergent responses: modified peatlands experience substantial tree cover loss due to fire (r = −0.736, mean tree cover = 73%), whereas intact peatlands maintain relatively high tree cover despite repeated fire exposure (r = −0.658, mean tree cover = 84%). These contrasting patterns are found to coincide with differences in ecosystem hydrology: intact peatlands maintain high water tables that dampen fire intensity and limit vegetation loss, while non-peatlands and modified peatlands lack this buffering capacity. Consequently, findings derived primarily from modified or drained peatlands should not be generalized to all peatlands, as those with preserved hydrology may present fundamentally different responses to fire. As human pressures and climate extremes intensify across Indonesia, maintaining hydrological integrity is essential to prevent peatlands from crossing ecological thresholds toward degraded, fire-prone states.

Biogeomorphic systems, key providers of ecosystem services, emerge from self-reinforcing feedbacks between landscape-building biota and geomorphic processes. Typically, these feedbacks are considered to operate at an individual patch scale, yet it remains unclear how interactions between patches shape landscapes at larger scales. Here we show how dune-building grasses form functional clusters of interacting patches that strongly amplify engineering capacity. By analyzing a decade of morphological development in an establishing coastal dune system, we discover that dune height is primarily driven by the initial density of neighboring patches, rather than individual patch size. We identify an S-shaped relationship consistent with a spatial percolation threshold: increasing local patch density triggers an abrupt shift from isolated sand-trapping patches to functionally connected clusters that enhance dune growth. This work reveals an important yet overlooked spatial dimension of ecosystem engineering, one that can be harnessed to inform future restoration designs and enhance ecosystem resilience.

Extensive knowledge exists on plant-species traits and functions, but we understand less about how population- or community-level emergent traits influence ecosystem functioning. This knowledge gap is important for ecosystems like peatlands, arid drylands, salt marshes, seagrass meadows, and mangroves, where emergent traits of plant communities can create plant-environment feedbacks that amplify or dampen ecosystem processes. Recent insights from restoration ecology suggest that these feedbacks can critically influence restoration success. Despite growing recognition of emergent trait-driven feedbacks in other ecosystems, they remain underexplored in peatland restoration, the world's most carbon-dense ecosystem. Here, we review emergent self-amplifying and self-dampening feedbacks with net positive effects for peat moss-dominated systems. We show how these feedbacks can promote key physical, chemical, and biological processes that enhance peat moss growth, increase water retention, and reduce microbial decomposition of organic matter. Understanding and fostering these feedbacks offers a promising framework to accelerate peatland restoration across diverse degradation states.

Forests and savannas frequently co-occur as patches within tropical landscape mosaics, yet the mechanisms controlling their spatial configuration remain unclear. The presence of both vegetation states under similar climatic conditions is often attributed to fire–vegetation feedbacks, but could also reflect variation in overlooked external drivers. In Central Africa, forest–savanna mosaics become more common with increasing topographic roughness, but how well topographic heterogeneity explains the forest–savanna configuration within mosaic landscapes is unknown. Here we address this question and examine the role of individual topographic variables that may influence tree cover by, for instance, changing water availability and fire spread. We identify mosaic landscapes from remotely sensed tree cover data and derive topographic variables from a digital elevation model. We use these variables to develop machine learning algorithms predicting vegetation state within mosaic landscapes. Models achieved an average prediction accuracy of 0.75, with local elevation (relative to the surrounding 500 m or 5000 m) emerging as the strongest predictor of vegetation state. Both model accuracy and the role of topographic predictors varied strongly among landscapes, reflecting the diverse pathways by which topography can influence tree cover. Overall, our findings indicate that topographic heterogeneity is a major driver of forest–savanna mosaics in Central Africa. Mosaic landscapes are more deterministic than previously assumed, suggesting that their response to disturbances and climate change will be spatially heterogeneous, thereby reducing the likelihood of abrupt large-scale shifts between forest and savanna states.

Abstract Differentiation in water use strategies is essential for maintaining the function and resilience of dryland ecosystems. Under prolonged drought, dominant shrubs self‐organize into two typical spatial configurations: scattered with separated individuals and clumped with clustered individuals. How the coordination between root water uptake and leaf physiological traits drives water use strategies of self‐organized shrubs for adapting to drought remains poorly understood. To address this gap, soil moisture, morphological and root traits, leaf‐level physiological traits, and stable isotope (δ2H, δ18O, and δ13C) of scattered and clumped Vitex negundo were observed during 2022–2024 in the semi‐arid Loess Plateau. The scattered shrubs primarily utilized middle and deep soil water (62.3 ± 7.8%), associated with isolated canopies that promote infiltration into deep soil layers. In contrast, clumped shrubs relied on shallow and middle soil water (82.0 ± 6.5%), linked to aggregated canopies and shallow roots. Scattered shrubs showed tight stomatal regulation with high midday leaf water potential and intrinsic water use efficiency (iWUE) during dry season, whereas clumped shrubs exhibited relaxed stomatal regulation, with declines in midday leaf water potential and iWUE. In rainy season, scattered shrubs constrained gas exchange, while clumped shrubs enhanced stomatal conductance and photosynthesis. These findings indicate that scattered shrubs adopt an active deep‐water acquisition with conservative water utilization strategy, enhancing drought resistance, while clumped shrubs exhibit an opportunistic shallow‐water acquisition with acquisitive water utilization strategy, improving water capture efficiency for drought adaptation. This study reveals the ecohydrological processes of self‐organized vegetation in drylands and provides basis for vegetation allocation in ecological restoration.

Resource concentration in the vicinity of plants is observed in drylands as a result of various mechanisms, developed to cope with water scarcity. This often leads to self-organized spatial patterns that enhance drylands’ ecosystem resilience to environmental changes. Numerous vegetation dynamics models have been developed over the past few decades to study this pattern formation. Generally, they represent plant spatial spread as a diffusive process, which captures well species that reproduce via seed dispersal or through clonal growth following the “phalanx” strategy, characterized by slow, compact expansion. However, many dryland species exhibit “guerrilla” clonal growth, characterized by rapid, directional exploration of favourable areas, which is poorly captured by diffusion. To address this limitation, we introduce a novel term for lateral biomass expansion into a classical dryland model.We found conditions suitable for periodic patterns to emerge with a Turing analysis, aiming to test the stability of a uniform solution against uniform and periodic perturbations. However, numerically, these patterns could not be observed by perturbing the homogeneous equilibria with small perturbations, possibly because of the non-linearity of the guerrilla expansion term. Instead, remarkably, the model produced amorphous, far-from-equilibrium patterns when integrated along a rainfall precipitation gradient.These findings highlight the need to represent the diversity of clonal plant strategies in dryland ecosystem models, as they play an important role in pattern formation and, thus, may influence ecosystem resilience and responses to global environmental change. Furthermore, our results highlight the need to move beyond linear analyses when studying systems with nonlinear dispersal dynamics.

Fire is a key driver of montane grassland biodiversity and ecosystem functioning, where rising temperatures linked to climate change are predicted to change the structure and functioning of the plant community. Despite the central role of fire in these systems, the extent to which fire interacts with warming to shape biodiversity and ecosystem functioning remains poorly understood. In 2017, we established a 7-year full-factorial warming experiment using open-top chambers within a long-term fire experiment in the Drakensberg Mountains of South Africa. This represents one of the first in situ warming experiments in an African montane grassland. Across warming and fire treatments, we measured microclimate, biomass and species composition. Our results show that the experimental warming significantly increased average air temperature by 0.6 degrees C (+/- 0.07 degrees C; p < 0.001), with hourly maximum temperatures differing by up to 4.4 degrees C. However, soil and surface temperature, as well as soil moisture, varied between combinations of fire frequency and warming treatments, indicating that vegetation can act as a mediator between macroclimatic (i.e. warming treatment air temperature) and microclimatic conditions. Consistent with expectations of improved plant growth under elevated temperatures, we observed increased plant biomass in warming treatments. We recorded 35 native plant species in the experiment. Their compositional disparity was better explained by fire than by warming, and there was no significant species turnover induced by the 7 years of warming. Synthesis and applications. Our findings suggest that, although plant community composition appeared resistant to direct warming, warming increased biomass, with potential implications for fuel accumulation and fire severity. Differences in biomass and vegetation among fire frequencies mediated the effects of warming on near-surface microclimate, including soil and surface temperature and soil moisture content. By linking vegetation structure, above-ground biomass accumulation and microclimatic buffering, we show that fire interacts with warming to shape ecosystem exposure to climatic extremes. These results indicate that pyrodiversity (the diversity of fire effects over space and time) may enhance resilience by balancing biomass accumulation with microclimatic stability, supporting adaptive fire management under a warmer climate.

River ecosystems play a crucial role in supporting biodiversity and providing essential ecosystem services. They are shaped by complex nonlinear interactions between vegetation, water and sediment, which give rise to both positive and negative feedbacks. Despite their importance, how ecomorphodynamic feedbacks interact with one another and influence river dynamics remains poorly understood. Gaining this understanding is crucial for sustaining and managing healthy and resilient ecosystems, especially in the context of global change. In this work, we use ecomorphodynamic numerical models—both non-spatial and spatial—to investigate the role of feedbacks in governing river ecosystem dynamics. Both models couple hydro-morphodynamics with vegetation dynamics, where the system is periodically disturbed by a succession of floods of constant amplitude. Previous research has demonstrated that the system dominated by a negative feedback loop oscillates and exhibits chaotic behavior. In contrast, here our study reveals that when the negative feedback loop is inhibited and positive feedbacks with reinforcing interactions prevail, the non-spatial model exhibits bi-stability. This leads to abrupt shifts and tipping points between the vegetated state and bare soil. However, when spatial interactions are included, the system displays multi-stability, self-organizing into multiple stable equilibria defined by specific hydro-morphodynamic conditions and vegetation configurations. This spatial multi-stability expands vegetation persistence, enabling the system to better resist external flood disturbances and enhancing resilience by smoothing abrupt shifts and tipping points. Our results highlight the importance of feedbacks and spatial interactions in maintaining ecosystem resilience, with significant implications for ecosystem management and restoration under increasing environmental disturbances.

Understanding how carbon-rich coastal peatlands form is crucial for future carbon storage under environmental change. Phragmites australis (common reed), a key precursor species, facilitates peatland development in saltmarshes by triggering a hydrological switch: creek networks clog through root and organic material accumulation, increasing freshwater retention. Here, we use Holocene peat paleo-records from the Netherlands to reveal past coastal-to-freshwater system transitions consistent with this mechanism. With a numerical biogeomorphic model, we demonstrate how reed expansion reduces creek network complexity, promoting a homogeneous freshwater landscape that further facilitates reed growth. Elevation and vegetation time-series, together with salinity measurements linked to species composition from Saeftinghe (southwestern Netherlands) confirm that reed expansion is associated with creek infilling and a shift in hydrological conditions. Our results identify a strong positive feedback that triggers the hydrological switch accompanied by Phragmites expansion, offering new insight into past peatland establishment and future carbon-rich wetland formation. Common reed expansion reduces creek network complexity, promoting a homogeneous freshwater landscape that further facilitates reed growth, according to analyses of simulations, Holocene peat paleo-records, and in-situ data from the Netherlands.

The Atlantic Meridional Overturning Circulation (AMOC) and the Amazon rainforest are two vital components of the Earth system that regulate global climate and biosphere integrity. There is growing concern that both systems may approach critical thresholds beyond which they could, potentially irreversibly, tip to alternative stable states. However, it remains unclear how their stability changes when they are considered as an interlinked system rather than in isolation.Although ecological rainforest processes and large-scale ocean circulation may appear distinct, they share a key coupling agent: freshwater. Here, we quantify these ocean–vegetation freshwater interactions by combining UTrack, a Lagrangian moisture tracking method, with complex network analysis. We first establish an empirical reference based on ERA5 reanalysis data to characterize present-day moisture pathways and recycling. Next, we extend this analysis to Earth System Model simulations under 2°C of global warming, as well as scenarios with additional AMOC collapse or Amazon rainforest dieback.Under present-day conditions, easterly trade winds transport large amounts of moisture from the Atlantic Ocean to the Amazon (≈ 0.35 Sverdrups, 1 Sv = 10⁶ m³ s⁻¹), sustaining the rainforest and its self-amplifying moisture recycling mechanism (≈ 0.23 Sv). In turn, freshwater is returned to the Atlantic via the Amazon’s exceptionally large river discharge (≈ 0.21 Sv), and atmospheric moisture export (≈ 0.062 Sv), conceivably influencing the salt–advection feedback that drives the AMOC. Our findings suggest that a substantial weakening of the AMOC may alter the strength, spatial configuration, and seasonal variability of the trade winds, thereby affecting both moisture transport to the Amazon and internal moisture recycling within the basin. Conversely, large-scale Amazon forest dieback may influence freshwater fluxes that are relevant for the stability of the AMOC. Together, these results provide a foundation for exploring AMOC–Amazon interactions in (conceptual) coupled modelling frameworks, guiding future research on potential tipping cascades and Earth system resilience.

Early warnings for climate tipping points should clearly convey their significant uncertainties, to maintain transparency and avoid perceptions of overstatement. This includes doubts about the existence of climate tipping points, which must often be assumed a priori in order to assess their early-warning signals, as well as doubts about their proximity. When such uncertainties are not clearly communicated, both updated assessments and continued absence of detected tipping can erode public trust and scientific credibility concerning future warnings for climate tipping. Moreover, this could even be misinterpreted by the public as more general ignorance about impacts of climatic change. So, perceived overstatement in this context may weaken support for climate policy in general. We stress that regardless of uncertain climate tipping points, climate action is already imperative because of the undisputed impacts of climate change. Also, an overemphasis on uncertain tipping points may sometimes obscure well-established evidence for the urgent need for climate policy. Despite strong mathematical foundations, Earth system complexity and unresolved uncertainties constrain the application and communication of tipping-point theory, highlighting the need for further elaboration. The uncertainty of climate tipping points furthermore underscores the need for adaptive planning, considering both tipping-point and non-tipping point scenarios, while safeguarding that climate policy remains based on scientific evidence.

The theory of alternative stable states and tipping points has garnered a lot of attention in the last decades. It predicts potential critical transitions from one ecosystem state to a completely different state under increasing environmental stress. However, typically ecosystem models that predict tipping do not resolve space explicitly. As ecosystems are inherently spatial, it is important to understand the effects of incorporating spatial processes in models, and how those insights translate to the real world. Moreover, spatial ecosystem structures, such as vegetation patterns, are important in the prediction of ecosystem response in the face of environmental change. Models and observations from real savanna ecosystems and drylands have suggested that they may exhibit both tipping behavior as well as spatial pattern formation. Hence, in this paper, we use mathematical models of humid savannas and drylands to illustrate several pattern formation phenomena that may arise when incorporating spatial dynamics in models that exhibit tipping without resolving space. We argue that such mechanisms challenge the notion of large scale critical transitions in response to global change and reveal a more resilient nature of spatial ecosystems.

Terrestrial ecosystem respiration (Re) is a crucial component of the carbon cycle and is expected to increase with anthropogenic warming. The temperature response of Re is typically parameterized using temperature sensitivity Q10, which describes the increase in respiration with a 10oC rise in temperature. The respiration increase largely determines the future direction of the terrestrial-atmosphere carbon balance. However, our current understanding of the mechanisms driving Q10 variation across latitudes and biomes is still insufficient. As a result, it remains difficult to constrain predictions of future Re dynamics. The Michaelis–Menten (MM) kinetics , developed to describe enzyme-catalyzed reactions, is a cornerstone to understand biochemical processes at the cellular and molecular levels. This model effectively captures the relationship between substrate concentration and reaction rates, simplifying complex biochemical interactions into manageable mathematical expressions using the key parameters Vmax (maximum reaction rate) and Km (substrate concentration at half the maximum rate). However, the applicability of this microscopic model to large-scale ecosystem processes can be questioned . Most Earth system models incorporate the Farquhar–von Caemmerer–Berry (FvCB) biochemical model, which is grounded in Michaelis–Menten kinetics, to simulate photosynthesis at ecosystem or larger scales. However, the description of respiration processes over large ecosystem scale still predominantly relies on more empirical models, projecting an exponential temperature response with Arrhenius or Q10 types of functions.

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 vulnerability of tropical ecosystems to global changes is a growing concern, with tree cover distribution patterns playing a pivotal role in their responses to changing environmental conditions. It is important to understand how natural ecosystems respond to these changes to assess the resilience of the ecosystems. While extensive research has investigated tree cover distributions in the tropics, a notable gap exists in understanding the effects of environmental variables to tree cover and the underlying mechanisms in Indonesian natural ecosystems, with its vast peatland areas. In response to this gap, we analyze the relative importance of environmental variables, specifically precipitation and fire, on shaping tree cover distributions in peatland and non-peatland ecosystems in Indonesia. We use the Global Forest Change dataset on tree cover with the spatial resolution of 30 meters. To focus on natural ecosystems, we filter out areas with human intervention. We find a consistent unimodal distribution of tree cover in the gradients of fire frequency and precipitation, marked by a distinct peak in each value range of the variables. In non-peatland, we observe a switch from high to low tree cover mode with increasing fire, which occurs at intermediate fire frequency. In contrast, peatland ecosystems show a remarkable resistance of the high tree cover mode despite increasing fire incidents. This implies that peatland could be more resistant to the same intermediate fire frequency than non-peatland. Our findings are relevant for ecosystem resistance in Indonesian peatlands and non-peatlands and their potential vulnerability to disturbances, particularly in the face of ongoing global environmental changes.

There is concern that climate change might lead to abrupt and irreversible changes in parts of the Earth system at so-called tipping points. Theoretical considerations suggest that statistical measures can be used to detect early warning signals (EWSs) for reduced resilience, which could be interpreted as an increased proximity to climate tipping points. Here we discuss limitations of commonly used EWSs and their detection and discuss how alternative explanations can lead to resilience loss in the absence of tipping points. We argue for better testing of the existence of tipping points, beyond the application of EWSs, and propose a method to better quantify the probability of approaching tipping points using EWSs.

Habitat-modifying plants engineer biogeomorphic landscapes through self-reinforcing interactions with their physical environment, or so-called 'biogeomorphic feedbacks'. Nevertheless, benefits can vary across a biogeomorphic landscape gradient and between plant-life stages. For instance, European marram grass forms dunes by trapping sediments which triggers plant growth, in turn promoting sediment trapping. Yet, by increasing dune height and vegetation cover, marram grass mitigates sediment dynamics, inhibiting sediment-growth feedbacks, which ultimately leads to its demise. However, little is known about how dune formation affects the growth and survival of marram grass at different life stages. Therefore, we performed a two-level field experiment testing the effect of position on marram grass across the biogeomorphological dune gradient (beach, foredune, backdune) on (i) the establishment success of juvenile transplants and (ii) the resilience of mature plants to disturbance by above-ground biomass removal, over one growing season. Although juvenile transplants grew similarly well across the dune gradient, significantly fewer beach transplants (67%) survived compared to the foredune- and backdune transplants. Conversely, survival of mature disturbed marram grass (100%) was unaffected, yet recovery was highest at the beach and significantly decreased across the dune gradient. We could link these opposing responses to habitat modification. In heavily modified dune habitats sediment stabilization aided juvenile establishment, whereas the high sediment dynamics of unmodified beaches facilitated adult resilience indicating dune formation invokes a trade-off between establishment and resilience. Our findings highlight the importance of assessing life stage-dependent differences in environmental requirements of habitat-modifying plants to understand population dynamics and landscape-forming processes.