干旱区生态系统稳态转换及其预警信号——基于景观格局特征的识别方法

在日益加剧的气候变化和土地开垦、放牧等人类活动干扰下,具有多稳态特征的干旱区生态系统可能会经历从相对健康状态到退化状态的稳态转换,导致生态系统的功能下降。早期预警信号的识别是生态系统稳态转换研究的热点,也是管理实践中防止生态系统退化的关键环节。以往预警信号研究聚焦于通用信号如自相关性、方差等统计学指标,然而这些指标对于具有特定机制的干旱区生态系统可能并不适用。基于干旱区景观格局特征所发展起来的空间指标为生态系统稳态转换提供了独特的空间视角,对于理解干旱区生态系统退化过程和机理具有科学意义和实践价值。介绍了干旱区生态系统稳态转换现象及其转换机制;聚焦景观生态学的指标和方法,从空间视角总结基于干旱区景观格局特征的关键预警指标(植被覆盖度、植被斑块形态、植被斑块大小频率分布和水文连通性等),重点剖析这些关键指标的概念、量化方法、识别特征及其实践应用;最后针对指标的优势和局限性对未来的研究方向进行展望,包括发掘潜在景观指标,加强干旱区生态系统变化的多种驱动要素的相互作用机制研究,开展多时空尺度的实证研究,构建生态系统稳态转换预警信号的整体分析框架,以及加强指标阈值的量化研究等方面。     

Early warning signals also precede non‐catastrophic transitions

Synthesis The quickly expanding literature on early warning signals for critical transitions in ecosystems suggests that critical slowing down is a key phenomenon to measure the distance to a tipping point in ecosystems. Such work is broadly misinterpreted as showing that slowing down is specific to tipping points. In this contribution, we show why this is not the case. Early warning signals based on critical slowing down indicate a broader class of situations where a system becomes increasingly sensitive to perturbations. Ecosystem responses to external changes can surprise us by their abruptness and irreversibility. Models have helped identifying indicators of impending catastrophic shifts, referred to as ‘generic early warning signals’. These indicators are linked to a phenomenon known as ‘critical slowing down’ which describes the fact that the recovery rate of a system after a perturbation decreases when the system approaches a bifurcation – such as the classical fold bifurcation associated to catastrophic shifts. However, contrary to what has sometimes been suggested in the literature, a decrease in recovery rate cannot be considered as specific to approaching catastrophic shifts. Here, we analyze the behavior of early warning signals based on critical slowing down in systems approaching a range of catastrophic and non‐catastrophic situations. Our results show that slowing down generally happens in situations where a system is becoming increasingly sensitive to external perturbations, independently of whether the impeding change is catastrophic or not. These results highlight that indicators specific to catastrophic shifts are still lacking. More importantly, they also imply that in systems where we have no reason to expect catastrophic transitions, slowing down may still be used in a more general sense as a warning signal for a potential decrease in stability.     

生态系统状态跃变的早期预警信号及检测

生态系统在气候变化和土地利用及人类活动等的影响下其状态会由某一稳态转变到另一稳态。由于环境压力的复杂性、非线性、随机性等特征，往往导致状态转变表现为非线性、突变、跃变等特点。准确界定系统状态跃变的拐点或阈值点存在很大的挑战，而捕捉接近临界拐点前的生态系统结构和属性上的变化特征作为早期预警信号是切实可行的。早期预警信号理论经历理论框架构建、方法确立、机理认知等近半个多世纪的探索，已经由最初的通过仅依赖检测临界点恢复力的速率减慢、方差增加、系统自相关增强等统计学信号过度到更加多样化的检测方法，如检测系统组分属性的变化特征，诊断系统组分各属性之间的关系变化，系统组分的性状变化、系统组分网络结构变化等等，并且试图整合多信号提高预警的精确性。利用来自自然生态系统的长时间高密度数据集和空间代替时间的数据集，基于多度及性状信号的早期预警，结合稳定性、临界恢复力的减速、以及统计参数的指示作用对系统跃变进行早期诊断和预警是预测生态学的主旨。早期预警信号的深入研究不仅能够完善已有理论的不足，同时还能够为生态系统的保护和管理提供切实有效的理论指导。     

Spatial early warning signals for impending regime shifts: A practical framework for application in real‐world landscapes

Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model‐based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land‐managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real‐world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real‐world landscapes based on literature review and examples from real‐world data. Major identified issues include (1) spatial heterogeneity in real‐world landscapes may enhance reversibility of regime shifts and boost landscape‐level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio‐economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well‐informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.     

A test of critical thresholds and their indicators in a desertification‐prone ecosystem: more resilience than we thought

Theoretical models predict that drylands can cross critical thresholds, but experimental manipulations to evaluate them are non‐existent. We used a long‐term (13‐year) pulse‐perturbation experiment featuring heavy grazing and shrub removal to determine if critical thresholds and their determinants can be demonstrated in Chihuahuan Desert grasslands. We asked if cover values or patch‐size metrics could predict vegetation recovery, supporting their use as early‐warning indicators. We found that season of grazing, but not the presence of competing shrubs, mediated the severity of grazing impacts on dominant grasses. Recovery occurred at the same rate irrespective of grazing history, suggesting that critical thresholds were not crossed, even at low cover levels. Grass cover, but not patch size metrics, predicted variation in recovery rates. Some transition‐prone ecosystems are surprisingly resilient; management of grazing impacts and simple cover measurements can be used to avert undesired transitions and initiate restoration.     

Changing skewness: an early warning signal of regime shifts in ecosystems

Empirical evidence for large-scale abrupt changes in ecosystems such as lakes and vegetation of semi-arid regions is growing. Such changes, called regime shifts, can lead to degradation of ecological services. We study simple ecological models that show a catastrophic transition as a control parameter is varied and propose a novel early warning signal that exploits two ubiquitous features of ecological systems: nonlinearity and large external fluctuations. Either reduced resilience or increased external fluctuations can tip ecosystems to an alternative stable state. It is shown that changes in asymmetry in the distribution of time series data, quantified by changing skewness, is a model-independent and reliable early warning signal for both routes to regime shifts. Furthermore, using model simulations that mimic field measurements and a simple analysis of real data from abrupt climate change in the Sahara, we study the feasibility of skewness calculations using data available from routine monitoring.     

Heteroskedasticity as a leading indicator of desertification in spatially explicit data

Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale‐free patterning. These models simulate shifts from extensive vegetative cover to bare, desert‐like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data.     

Spatial variance and spatial skewness: leading indicators of regime shifts in spatial ecological systems

Ecosystems can undergo large-scale changes in their states, known as catastrophic regime shifts, leading to substantial losses to services they provide to humans. These shifts occur rapidly and are difficult to predict. Several early warning signals of such transitions have recently been developed using simple models. These studies typically ignore spatial interactions, and the signal provided by these indicators may be ambiguous. We employ a simple model of collapse of vegetation in one and two spatial dimensions and show, using analytic and numerical studies, that increases in spatial variance and changes in spatial skewness occur as one approaches the threshold of vegetation collapse. We identify a novel feature, an increasing spatial variance in conjunction with a peaking of spatial skewness, as an unambiguous indicator of an impending regime shift. Once a signal has been detected, we show that a quick management action reducing the grazing activity is needed to prevent the collapse of vegetated state. Our results show that the difficulties in obtaining the accurate estimates of indicators arising due to lack of long temporal data can be alleviated when high-resolution spatially extended data are available. These results are shown to hold true independent of various details of model or different spatial dispersal kernels such as Gaussian or heavily fat tailed. This study suggests that spatial data and monitoring multiple indicators of regime shifts can play a key role in making reliable predictions on ecosystem stability and resilience. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Regional productivity mediates the effects of grazing disturbance on plant cover and patch‐size distribution in arid and semi‐arid communities

Patch‐size distribution and plant cover are strongly associated to arid ecosystem functioning and may be a warning signal for the onset of desertification under changes in disturbance regimes. However, the interaction between regional productivity level and human‐induced disturbance regime as drivers for vegetation structure and dynamics remain poorly studied. We studied grazing disturbance effects on plant cover and patchiness in three plant communities located along a regional productivity gradient in Patagonia (Argentina): a semi‐desert (low‐productivity community), a shrub‐grass steppe (intermediate‐productivity community) and a grass steppe (high‐productivity community). We sampled paddocks with different sheep grazing pressure (continuous disturbance gradients) in all three communities. In each paddock, the presence or absence of perennial vegetation was recorded every 10 cm along a 50 m transect. Grazing effects on vegetation structure depended on the community and its association to the regional productivity. Grazing decreased total plant cover while increasing both the frequency of small patches and the inter‐patch distance in all communities. However, the size of these effects was the greatest in the high‐productivity community. Dominant species responses to grazing explained vegetation patch‐ and inter‐patch‐size distribution patterns. As productivity decreases, dominant species showed a higher degree of grazing resistance, probably because traits of species adapted to high aridity allow them to resist herbivore disturbance. In conclusion, our findings suggest that regional productivity mediates grazing disturbance impacts on vegetation mosaic. The changes within the same range of grazing pressure have higher effects on communities found in environments with higher productivity, markedly promoting their desertification. Understanding the complex interactions between environmental aridity and human‐induced disturbances is a key aspect for maintaining patchiness structure and dynamics, which has important implications for drylands management.     

浅水湖泊稳态转换预警识别方法局限与展望

浅水湖泊水体底泥交换强烈,极易受人类活动干扰,超过一定阈值即可能发生灾难性的稳态转换,对其有效识别有助于湖泊富营养化的及时防控与修复。浅水湖泊稳态转换可通过系统关键变量(叶绿素、溶解氧、浮游动物、鱼类等)的时间序列(判别不同稳态)、预警信号及阈值等进行识别,其中预警识别可为湖泊生态系统稳态转换提供预判信息,有利于早预警早行动。目前,浅水湖泊稳态转换预警识别因子(方差及自相关性等)主要用于"临界慢化"现象,但在强大外力作用、强烈随机扰动及极端事件下,这些"临界慢化"因子则可能出现误用或错用。基于浅水湖泊基本特征,针对稳态转换的不同驱动机制,探讨"临界慢化"因子的适用性与局限性,并展望其未来发展方向,旨在为湖泊生态系统稳态转换预警识别提供科学参考。     

Abrupt changes in Great Britain vegetation carbon projected under climate change

Past abrupt ‘regime shifts’ have been observed in a range of ecosystems due to various forcing factors. Large‐scale abrupt shifts are projected for some terrestrial ecosystems under climate change, particularly in tropical and high‐latitude regions. However, there is very little high‐resolution modelling of smaller‐scale future projected abrupt shifts in ecosystems, and relatively less focus on the potential for abrupt shifts in temperate terrestrial ecosystems. Here, we show that numerous climate‐driven abrupt shifts in vegetation carbon are projected in a high‐resolution model of Great Britain's land surface driven by two different climate change scenarios. In each scenario, the effects of climate and CO₂ combined are isolated from the effects of climate change alone. We use a new algorithm to detect and classify abrupt shifts in model time series, assessing the sign and strength of the non‐linear responses. The abrupt ecosystem changes projected are non‐linear responses to climate change, not simply driven by abrupt shifts in climate. Depending on the scenario, 374–1,144 grid cells of 1.5 km × 1.5 km each, comprising 0.5%–1.5% of Great Britain's land area show abrupt shifts in vegetation carbon. We find that abrupt ecosystem shifts associated with increases (rather than decreases) in vegetation carbon, show the greatest potential for early warning signals (rising autocorrelation and variance beforehand). In one scenario, 89% of abrupt increases in vegetation carbon show increasing autocorrelation and variance beforehand. Across the scenarios, 81% of abrupt increases in vegetation carbon have increasing autocorrelation and 74% increasing variance beforehand, whereas for decreases in vegetation carbon these figures are 56% and 47% respectively. Our results should not be taken as specific spatial or temporal predictions of abrupt ecosystem change. However, they serve to illustrate that numerous abrupt shifts in temperate terrestrial ecosystems could occur in a changing climate, with some early warning signals detectable beforehand.     

Grazing and productivity alter individual grass size dynamics in semi-arid woodlands

The spatial arrangement of perennial vegetation is critical for ecosystem function in drylands. While much is known about how vegetation patches respond to grazing and abiotic conditions, the size dynamics of individual plants is mostly limited to theoretical studies. We measured the size distribution (mean, variance, skewness) and density of individual grasses, and grass species composition at 451 sites spanning a range of grazing intensities across three broad vegetation communities in semi-arid eastern Australia. We assessed the relative role of grazing by livestock (cattle and sheep), native (kangaroos) and introduced (rabbits) free ranging herbivores, and several environmental measures (productivity, diversity, composition and groundstorey plant cover) on the size distribution and density of individual grasses. We found mean grass size and density were more sensitive to shifts in grazing intensity and environmental conditions than size variance or the frequency of the smallest individuals (skewness), and shifts were mostly driven by site productivity and cattle and kangaroo grazing. Sheep grazing only reduced mean grass size, and rabbit grazing had no consistent effects. Importantly, we found that site productivity and species composition altered the impacts of grazing on grass density and size distribution. For example, increasing cattle grazing led to larger grasses in low productivity sites. It also led to larger, denser, more variable-sized grasses among grass species from sites with finer soil texture. Increasing kangaroo grazing led to smaller, denser individuals among grass species from sites with coarse soil texture. At high diversity sites kangaroo grazing led to denser, more homogenised grass sizes with a lower frequency of small individuals. Understanding the in situ response of individual plant sizes gives us insights into the processes driving shifts in perennial vegetation patchiness, improving our ability to predict how the spatial arrangement of ecosystems might change under global change scenarios.     

Spatial heterogeneity and irreversible vegetation change in semiarid grazing systems

Recent theoretical studies have shown that spatial redistribution of surface water may explain the occurrence of patterns of alternating vegetated and degraded patches in semiarid grasslands. These results implied, however, that spatial redistribution processes cannot explain the collapse of production on coarser scales observed in these systems. We present a spatially explicit vegetation model to investigate possible mechanisms explaining irreversible vegetation collapse on coarse spatial scales. The model results indicate that the dynamics of vegetation on coarse scales are determined by the interaction of two spatial feedback processes. Loss of plant cover in a certain area results in increased availability of water in remaining vegetated patches through run-on of surface water, promoting within-patch plant production. Hence, spatial redistribution of surface water creates negative feedback between reduced plant cover and increased plant growth in remaining vegetation. Reduced plant cover, however, results in focusing of herbivore grazing in the remaining vegetation. Hence, redistribution of herbivores creates positive feedback between reduced plant cover and increased losses due to grazing in remaining vegetated patches, leading to collapse of the entire vegetation. This may explain irreversible vegetation shifts in semiarid grasslands on coarse spatial scales.     

Biodiversity collapse and early warning indicators in a spatial phase transition between neutral and niche communities

The dynamics of ecological communities have been described by neutral and niche theories that are now increasingly integrated into unified models. It is known that a critical transition exists between these two states, but the spatial aspect of this transition has not been studied. Our aim is to study the spatial aspect of the transition and propose early warning signals to detect it. We used a stochastic, spatially explicit model that spans a continuum from neutral to niche communities, and is driven by the intensity of hierarchical competition. The transition is indicated by the emergence of a large patch formed by one species that connects the whole area. The properties of this patch can be used as early warning indicators of a critical transition. If competition intensity increases beyond the critical point, our model shows a sudden decrease of the Shannon diversity index and a gentle decline in species richness. The critical point occurs at a very low value of competitive intensity, with the rate of migration from the metacommunity greatly influencing the position of this critical point. As an example, we apply our new method of early warning indicators to the Barro Colorado Tropical forest, which, as expected, appears to be far from a critical transition. Low values of competitive intensity were also reported by previous studies for different high‐diversity real communities, suggesting that these communities are located before the critical point. A small increase of competitive interactions could push them across the transition, however, to a state in which diversity is much lower. Thus this new early warnings indicator could be used to monitor high diversity ecosystems that are still undisturbed.     

Gradual regime shifts in spatially extended ecosystems

Ecosystem regime shifts are regarded as abrupt global transitions from one stable state to an alternative stable state, induced by slow environmental changes or by global disturbances. Spatially extended ecosystems, however, can also respond to local disturbances by the formation of small domains of the alternative state. Such a response can lead to gradual regime shifts involving front propagation and the coalescence of alternative-state domains. When one of the states is spatially patterned, a multitude of intermediate stable states appears, giving rise to step-like gradual shifts with extended pauses at these states. Using a minimal model, we study gradual state transitions and show that they precede abrupt transitions. We propose indicators to probe gradual regime shifts, and suggest that a combination of abrupt-shift indicators and gradual-shift indicators might be needed to unambiguously identify regime shifts. Our results are particularly relevant to desertification in drylands where transitions to bare soil take place from spotted vegetation, and the degradation process appears to involve step-like events of local vegetation mortality caused by repeated droughts.     

Herbivores as architects of savannas: inducing and modifying spatial vegetation patterning

In this paper, we address the question whether and through which mechanisms herbivores can induce spatial patterning in savanna vegetation, and how the role of herbivory as a determinant of vegetation patterning changes with herbivore density and the pre-existing pattern of vegetation. We thereto developed a spatially explicit simulation model, including growth of grasses and trees, vertical zonation of browseable biomass, and spatially explicit foraging by grazers and browsers. We show that herbivores can induce vegetation patterning when two key assumptions are fulfilled. First, herbivores have to increase the attractiveness of a site while foraging so that they will revisit this site, e.g. through an increased availability or quality of forage. Second, foraging should be spatially explicit, e.g. when foraging at a site influences vegetation at larger spatial scales or when vegetation at larger spatial scales influences the selection and utilisation of a site. The interaction between these two assumptions proved to be crucial for herbivores to produce spatial vegetation patterns, but then only at low to intermediate herbivore densities. High herbivore densities result in homogenisation of vegetation. Furthermore, our model shows that the pre-existing spatial pattern in vegetation influences the process of vegetation patterning through herbivory. However, this influence decreases when the heterogeneity and dominant scale of the initial vegetation decreases. Hence, the level of adherence of the herbivores to forage in pre-existing patches increases when these pre-existing patches increase in size and when the level of vegetation heterogeneity increases. The findings presented in this paper, and critical experimentation of their ecological validity, will increase our understanding of vegetation patterning in savanna ecosystems, and the role of plant–herbivore interactions therein.     

Effects of grazing on patch structure in a semi‐arid two‐phase vegetation mosaic

Abstract. Question: What are the grazing effects in the spatial organization and the internal structure of high and low cover patches from a two‐phase vegetation mosaic? Location: Patagonian steppe, Argentina. Methods: We mapped vegetation under three different grazing conditions: ungrazed, lightly grazed and heavily grazed. We analysed the spatial patterns of the dominant life forms. Also, in each patch type, we determined density, species composition, richness, diversity, size structure and dead biomass of grasses under different grazing conditions. Results: The vegetation was spatially organized in a two‐phase mosaic. High cover patches resulted from the association of grasses and shrubs and low cover patches were represented by scattered tussock grasses on bare ground. This spatial organization was not affected by grazing, but heavy grazing changed the grass species involved in high cover patches and reduced the density and cover of grasses in both patch types. Species richness and diversity in high cover patches decreased under grazing conditions, whereas in low cover patches it remained unchanged. Also, the decrease of palatable grasses was steeper in high cover patches than in low cover patches under grazing conditions. Conclusions: We suggest that although grazing promotes or inhibits particular species, it does not modify the mosaic structure of Patagonian steppe. The fact that the mosaic remained unchanged after 100 years of grazing suggests that grazing does not compromize population processes involved in maintaining patch structure, including seed dispersal, establishment or biotic interactions among life forms.     

Habitat loss-induced tipping points in metapopulations with facilitation

Habitat loss is known to pervade extinction thresholds in metapopulations. Such thresholds result from a loss of stability that can eventually lead to collapse. Several models have been developed to understand the nature of these transitions and how they are affected by the locality of interactions, fluctuations or external drivers. Most models consider the impact of grazing or aridity as a control parameter that can trigger sudden shifts, once critical values are reached. Others explore instead the role played by habitat loss and fragmentation. Here we consider a minimal model incorporating facilitation between the individuals of the same species along with habitat destruction, with the aim of understanding how local cooperation and habitat loss interact with each other. A mathematical model incorporating facilitation and habitat destruction is derived, along with a spatially explicit simulation model. It is found that a catastrophic shift is expected for increasing levels of habitat loss, but the bifurcation becomes continuous when dispersal is local. Under these conditions, spatial patchiness is found and the qualitative change from discontinuous to continuous results are in agreement with previous studies on ecological systems. Our results suggest that species exhibiting facilitation and displaying short-range dispersal will be markedly more capable of avoiding catastrophic tipping points.     

Spatial heterogeneity and plant species richness at different spatial scales under rabbit grazing

Herbivores influence spatial heterogeneity in soil resources and vegetation in ecosystems. Despite increasing recognition that spatial heterogeneity can drive species richness at different spatial scales, few studies have quantified the effect of grazing on spatial heterogeneity and species richness simultaneously. Here we document both these variables in a rabbit-grazed grassland. We measured mean values and spatial patterns of grazing intensity, rabbit droppings, plant height, plant biomass, soil water content, ammonia and nitrate in sites grazed by rabbits and in matched, ungrazed exclosures in a grassland in southern England. Plant species richness was recorded at spatial scales ranging between 0.0001 and 150 m(2). Grazing reduced plant height and plant biomass but increased levels of ammonia and nitrate in the soil. Spatial statistics revealed that rabbit-grazed sites consisted of a mixture of heavily grazed patches with low vegetation and nutrient-rich soils (lawns) surrounded by patches of high vegetation with nutrient-poor soils (tussocks). The mean patch size (range) in the grazed controls was 2.1 +/- 0.3 m for vegetation height, 3.8 +/- 1.8 m for soil water content and 2.8 +/- 0.9 m for ammonia. This is in line with the patch sizes of grazing (2.4 +/- 0.5 m) and dropping deposition (3.7 +/- 0.6 m) by rabbits. In contrast, patchiness in the ungrazed exclosures had a larger patch size and was not present for all variables. Rabbit grazing increased plant species richness at all spatial scales. Species richness was negatively correlated with plant height, but positively correlated to the coefficient of variation of plant height at all plot sizes. Species richness in large plots (<25 m(2)) was also correlated to patch size. This study indicates that the abundance of strong competitors and the nutrient availability in the soil, as well as the heterogeneity and spatial pattern of these factors may influence species richness, but the importance of these factors can differ across spatial scales.     

Modelling potential impacts of climate change on the spatial distribution of zonal forest communities in Switzerland

Abstract. A spatially explicit, climate-sensitive vegetation model is presented to simulate both present and future distribution of potential natural vegetation types in Switzerland at the level of zonal forest communities. The model has two versions: (1) a ‘basic’ version using geographical region, aspect, bedrock (represented by soil pH), and elevation, and (2) a ‘climate-sensitive’ version obtained by replacing elevation (complex environmental gradient) with temperature (climatic factor). Version 2 is used to predict vegetation response under different (today's and projected) climatic conditions. Two regional climate scenarios are applied: (1) assuming an annual mean temperature increase of 1.1 — 1.4 °C, and (2) assuming an increase of 2.2 — 2.75 °C. Both scenarios result in significant changes of the spatial vegetation patterns as compared with today's climatic conditions. In scenario 1, ca. 33 % of the sample points remain unchanged in terms of the simulated zonal forest community; in scenario 2, virtually all sample points change. The most noticeable changes occur on the Swiss Plateau with Carpinion forests (zonal vegetation of present colline belt) expanding to areas that are occupied today by submontane and low-montane Fagus forests. To estimate the reliability of the simulation, quantitative (comparison with field mapping) and qualitative (comparison with climate types in the Alpine region) tests are performed and the main limitations of the approach are evaluated.