Causes and consequences of tipping points in river delta social-ecological systems

The sustainability of social-ecological systems within river deltas globally is in question as rapid development and environmental change trigger "negative" or "positive" tipping points depending on actors' perspectives, e.g. regime shift from abundant sediment deposition to sediment shortage, agricultural sustainability to agricultural collapse or shift from rural to urban land use. Using a systematic review of the literature, we show how cascading effects across anthropogenic, ecological, and geophysical processes have triggered numerous tipping points in the governance, hydrological, and land-use management of the world's river deltas. Crossing tipping points had both positive and negative effects that generally enhanced economic development to the detriment of the environment. Assessment of deltas that featured prominently in the review revealed how outcomes of tipping points can inform the long-term trajectory of deltas towards sustainability or collapse. Management of key drivers at the delta scale can trigger positive tipping points to place social-ecological systems on a pathway towards sustainable development.

Toward a network perspective in coastal ecosystem management

Environmental management in coastal ecosystems has been challenged by the complex cumulative effects that occur when many small issues result in large ecological shifts. Current environmental management of these spaces focuses on identifying and limiting problematic stressors via a series of assessment techniques. Whilst there is a strong desire among managers to consider complexity in ecological responses to cumulative effects, current approaches for assessing risk focus on breaking down the issues into multiple cause and effect relationships. However, uncertainty arises when data and information for a place are limited, as is commonly the case, and this creates decision paralysis while more information is generated. Here, we discuss how ecological understanding of network interactions in coastal marine ecosystems can be used as a lens to bring together multiple lines of evidence and create actions. We list and describe four characteristics of marine ecosystem interaction networks including the possibility for; 1) indirect effects, 2) effects that emerge as stressor magnitude increases the number of network components implicated, 3) network interactions that amplify these indirect effects, and 4) feedbacks that reinforce or stabilise against indirect effects. We then link these four characteristics to three case studies of common coastal environmental issues to demonstrate how a general understanding of ecological interaction networks can enhance priorities for stressor management that can be applied even when specific data is limited.

Unlocking and accelerating transformations to the SDGs: a review of existing knowledge

As we cross the 2030 deadline to achieve the Sustainable Development Goals (SDGs), there is a growing sense of urgency around the need to accelerate the necessary transformations. These encompass a broad range of systems and require fundamental changes in system goals and design. In this paper, we undertake a narrative review of the literature relating to the acceleration of transformations and offer a framework for unlocking and accelerating transformations to the SDGs. While there is no blueprint for acceleration, there is an expanding knowledge base on important dynamics, impediments and enabling conditions across diverse literatures which can help to inform strategic interventions by actors. The emerging literature on positive tipping points and deep leverage points identifies opportunities to rewire systems design so that important system feedbacks create the conditions for acceleration. Transformation takes time and actors will need to build momentum to reorient systems around new goals, informed by knowledge of common policy, technology and behavioural feedbacks that govern system dynamics. Where resistance is strong, actors can seek to augment system design in ways that weaken balancing feedbacks that stabilise existing system configurations and strengthen reinforcing feedbacks that promote emerging system configurations oriented towards the SDGs. Well-designed and sequenced interventions can promote innovation and behaviour change and build and maintain political support. This can build critical enabling conditions and push systems towards large-scale tipping points, paving the way for decisive policy action that is crucial for triggering acceleration. We conclude by highlighting gaps and priorities for further research.

Significant tipping points of sediment microeukaryotes forewarn increasing antibiotic pollution

Antibiotic pollution imposes urgent threats to public health and microbial-mediated ecological processes. Existing studies have primarily focused on bacterial responses to antibiotic pollution, but they ignored the microeukaryotic counterpart, though microeukaryotes are functionally important (e.g., predators and saprophytes) in microbial ecology. Herein, we explored how the assembly of sediment microeukaryotes was affected by increasing antibiotic pollution at the inlet (control) and across the outlet sites along a shrimp wastewater discharge channel. The structures of sediment microeukaryotic community were substantially altered by the increasing nutrient and antibiotic pollutions, which were primarily controlled by the direct effects of phosphate and ammonium (-0.645 and 0.507, respectively). In addition, tetracyclines exerted a large effect (0.209), including direct effect (0.326) and indirect effect (-0.117), on the microeukaryotic assembly. On the contrary, the fungal subcommunity was relatively resistant to antibiotic pollution. Segmented analysis depicted nonlinear responses of microeukaryotic genera to the antibiotic pollution gradient, as supported by the significant tipping points. We screened 30 antibiotic concentration-discriminatory taxa of microeukaryotes, which can quantitatively and accurately predict (98.7% accuracy) the in-situ antibiotic concentration. Sediment microeukaryotic (except fungal) community is sensitive to antibiotic pollution, and the identified bioindicators could be used for antibiotic pollution diagnosis.

Understanding the depth limit of the seagrass Cymodocea nodosa as a critical transition: Field and modeling evidence

Changes in light and sediment conditions can sometimes trigger abrupt regime shifts in seagrass meadows resulting in dramatic and unexpected die-offs of seagrass. Light attenuates rapidly with depth, and in seagrass systems with non-linear behaviours, can serve as a sharp boundary beyond which the meadow transitions to bare sand. Determining system behaviour is therefore essential to ensuring resilience is maintained and to prevent stubborn critical ecosystem transitions caused by declines in water quality. Here we combined field and modelling studies to explore the transition from meadow to bare sand in the seagrass Cymodocea nodosa at the limit of its depth distribution in a shallow, light-limited bay. We first describe the relationship between light availability and seagrass density along a depth gradient in an extensive unfragmented meadow (Alfacs bay, NE Spain). We then develop a simple mechanistic model to characterise system behaviour. In the field, we identified sharp decline in shoot density beyond a threshold of ∼1.9 m depth, shifting from a vegetated state to bare sand. The dynamic population model we developed assumes light-dependent growth and an inverse density-dependent mortality due to facilitation between shoots (mortality rate decreases as shoot density increases). The model closely tracked our empirical observations, and both the model and the field data showed signs of bistability. This strongly suggests that the depth limit of C. nodosa is a critical transition driven by photosynthetic light requirements. While the mechanisms still need to be confirmed with experimental evidence, recognizing the non-linear behaviour of C. nodosa meadows is vital not only in improving our understanding of light effects on seagrass dynamics, but also in managing shallow-water meadows. Given the shallow threshold (<2m), light-limited systems may experience significant and recalcitrant meadow retractions with even small changes in sediment and light conditions. Understanding the processes underlying meadow resilience can inform the maintenance and restoration of meadows worldwide.

Tipping points ahead? How laypeople respond to linear versus nonlinear climate change predictions

We investigate whether communication strategies that portray climate change as a nonlinear phenomenon provoke increases in laypeople's climate change risk perceptions. In a high-powered, preregistered online experiment, participants were exposed to linear or nonlinear predictions of future temperature increases that would be expected if global greenhouse gas emissions were not reduced. We hypothesized that the type of climate change portrayal would impact perceptions of qualitative risk characteristics (catastrophic potential, controllability of consequences) which would, in turn, affect laypeople's holistic risk perceptions. The results of the study indicate that the type of climate change portrayal did not affect perceptions of risk or other social-cognitive variables such as efficacy beliefs. While participants who were exposed to a nonlinear portrayal of climate change perceived abrupt changes in the climate system as more likely, they did not perceive the consequences of climate change as less controllable or more catastrophic. Notably, however, participants who had been exposed to a linear or nonlinear portrayal of climate change were willing to donate more money to environmental organizations than participants who had not been presented with a climate-related message. Limitations of the present study and directions for future research are discussed.

Effects of sediment exposure on corals: a systematic review of experimental studies

BACKGROUND

Management actions that address local-scale stressors on coral reefs can rapidly improve water quality and reef ecosystem condition. In response to reef managers who need actionable thresholds for coastal runoff and dredging, we conducted a systematic review and meta-analysis of experimental studies that explore the effects of sediment on corals. We identified exposure levels that 'adversely' affect corals while accounting for sediment bearing (deposited vs. suspended), coral life-history stage, and species, thus providing empirically based estimates of stressor thresholds on vulnerable coral reefs.

METHODS

We searched online databases and grey literature to obtain a list of potential studies, assess their eligibility, and critically appraise them for validity and risk of bias. Data were extracted from eligible studies and grouped by sediment bearing and coral response to identify thresholds in terms of the lowest exposure levels that induced an adverse physiological and/or lethal effect. Meta-regression estimated the dose-response relationship between exposure level and the magnitude of a coral's response, with random-effects structures to estimate the proportion of variance explained by factors such as study and coral species.

REVIEW FINDINGS

After critical appraisal of over 15,000 records, our systematic review of corals' responses to sediment identified 86 studies to be included in meta-analyses (45 studies for deposited sediment and 42 studies for suspended sediment). The lowest sediment exposure levels that caused adverse effects in corals were well below the levels previously described as 'normal' on reefs: for deposited sediment, adverse effects occurred as low as 1 mg/cm²/day for larvae (limited settlement rates) and 4.9 mg/cm²/day for adults (tissue mortality); for suspended sediment, adverse effects occurred as low as 10 mg/L for juveniles (reduced growth rates) and 3.2 mg/L for adults (bleaching and tissue mortality). Corals take at least 10 times longer to experience tissue mortality from exposure to suspended sediment than to comparable concentrations of deposited sediment, though physiological changes manifest 10 times faster in response to suspended sediment than to deposited sediment. Threshold estimates derived from continuous response variables (magnitude of adverse effect) largely matched the lowest-observed adverse-effect levels from a summary of studies, or otherwise helped us to identify research gaps that should be addressed to better quantify the dose-response relationship between sediment exposure and coral health.

CONCLUSIONS

We compiled a global dataset that spans three oceans, over 140 coral species, decades of research, and a range of field- and lab-based approaches. Our review and meta-analysis inform the no-observed and lowest-observed adverse-effect levels (NOAEL, LOAEL) that are used in management consultations by U.S. federal agencies. In the absence of more location- or species-specific data to inform decisions, our results provide the best available information to protect vulnerable reef-building corals from sediment stress. Based on gaps and limitations identified by our review, we make recommendations to improve future studies and recommend future synthesis to disentangle the potentially synergistic effects of multiple coral-reef stressors.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s13750-022-00256-0.

Informing the management of multiple stressors on estuarine ecosystems using an expert-based Bayesian Network model

The approach of applying stressor load limits or thresholds to aid estuarine management is being explored in many global case studies. However, there is growing concern regarding the influence of multiple stressors and their cumulative effects on the functioning of estuarine ecosystems due to the considerable uncertainty around stressor interactions. Recognising that empirical data limitations hinder parameterisation of detailed models of estuarine ecosystem responses to multiple stressors (suspended sediment, sediment mud and metal content, and nitrogen inputs), an expert driven Bayesian network (BN) was developed and validated. Overall, trends in estuarine condition predicted by the BN model were well supported by field observations, including results that were markedly higher than random (71-84% concordance), providing confidence in the overall model dynamics. The general BN framework was then applied to a case study estuary to demonstrate the model's utility for informing management decisions. Results indicated that reductions in suspended sediment loading were likely to result in improvements in estuarine condition, which was further improved by reductions in sediment mud and metal content, with an increased likelihood of high abundance of ecological communities relative to baseline conditions. Notably, reductions in suspended sediment were also associated with an increased probability of high nuisance macroalgae and phytoplankton if nutrient loading was not also reduced (associated with increased water column light penetration). Our results highlight that if stressor limit setting is to be implemented, limits must incorporate ecosystem responses to cumulative stressors, consider the present and desired future condition of the estuary of interest, and account for the likelihood of unexpected ecological outcomes regardless of whether the experts (or empirical data) suggest a threshold has or has not been triggered.

Responses of sediment resistome, virulence factors and potential pathogens to decades of antibiotics pollution in a shrimp aquafarm

Aquaculture ecosystem has become a hotspot of antibiotics resistance genes (ARGs) dissemination, owing to the abuse of prophylactic antibiotics. However, it is still unclear how and to what extent ARGs respond to the increasing antibiotic pollution, a trend as expected and as has occurred. Herein, a significant sediment antibiotic pollution gradient was detected along a drainage ditch after decades of shrimp aquaculture. The increasing antibiotic pollution evidently promoted the diversities and tailored the community structures of ARGs, mobile genetic elements (MGEs), virulence factors and pathogens. The profiles of ARGs and MGEs were directly altered by the concentrations of terramycin and sulphadimidine. By contrast, virulence factors were primarily affected by nutrient variables in sediment. The pathogens potentially hosted diverse virulence factors and ARGs. More than half of the detected ARGs subtypes non-linearly responded to increasing antibiotic pollution, as supported by significant tipping points. However, we screened seven antibiotic concentration discriminatory ARGs that could serve as independent variable for quantitatively diagnosing total antibiotic concentration. Co-occurrence analysis depicted that notorious aquaculture pathogens of Vibrio harveyi and V. parahaemolyticus potentially hosted ARGs that confer resistance to multiple antibiotics, while priority pathogens for humankind, e.g., Helicobacter pylori and Staphylococcus aureus, could have harbored redundant virulence factors. Collectively, the significant tipping points and antibiotic concentration-discriminatory ARGs may translate into warning index and diagnostic approach for diagnosing antibiotic pollution. Our findings provided novel insights into the interplay among ARGs, MGEs, pathogens, virulence factors and geochemical variables under the scenario of increasing antibiotic pollution.

Tipping Cascades in a Multi-patch System with Noise and Spatial Coupling

Forecasting tipping points in spatially extended systems is a key area of interest to ecologists. A slowly declining spatially distributed population is an important example of an ecological system that could exhibit a cascade of tipping points. Here, we develop a spatial two-patch model with environmental stochasticity that is slowly forced through population collapse, in the presence of changing environmental conditions. We begin with a basic spatial model, then introduce a fast-slow version of the model using geometric singular perturbation theory, followed by the inclusion of stochasticity. Using the spectral density of the fluctuating subpopulation in each patch, we derive analytic expressions for candidate indicators of population extinction and evaluate their performance through a simulation study. We find that coupling and spatial heterogeneity decrease the magnitude of the proposed indicators in coupled populations relative to isolated populations. Moreover, the degree of coupling dictates the trends in summary statistics. We conclude that this theory may be applied to other contexts, including the control of invasive species.

Impulsive Fire Disturbance in a Savanna Model: Tree-Grass Coexistence States, Multiple Stable System States, and Resilience

Savanna ecosystems are shaped by the frequency and intensity of regular fires. We model savannas via an ordinary differential equation (ODE) encoding a one-sided inhibitory Lotka-Volterra interaction between trees and grass. By applying fire as a discrete disturbance, we create an impulsive dynamical system that allows us to identify the impact of variation in fire frequency and intensity. The model exhibits three different bistability regimes: between savanna and grassland; two savanna states; and savanna and woodland. The impulsive model reveals rich bifurcation structures in response to changes in fire intensity and frequency-structures that are largely invisible to analogous ODE models with continuous fire. In addition, by using the amount of grass as an example of a socially valued function of the system state, we examine the resilience of the social value to different disturbance regimes. We find that large transitions ("tipping") in the valued quantity can be triggered by small changes in disturbance regime.

Salinity-affected threshold yield loss: A signal of adaptation tipping points for salinity management of dry season rice cultivation in the coastal areas of Bangladesh

The potential existence of threshold yield loss in dry season rice growing systems under coastal saline environment remains unexplored, a scenario that could have policy relevance in government planning of rice intensification in the coastal areas of Bangladesh. This study applied the adaptation tipping points (ATPs) approach to investigate threshold yield loss from multiple perspectives of farmers affected by salinity. Data were generated from 280 randomly-selected farmers (rice farmers, n = 109; shrimp farmers, n = 107; salt farmers, n = 64) from two coastal sub-districts using a semi-structured survey. Key informant interviews and focus group discussions were conducted to complement the survey results. Our study revealed that despite government actions to promote dry season rice cultivation, farmers have been growing less rice in this season, with salinity-affected yield loss being the prime reason. Most of the rice farmers have considered that they would discontinue rice cultivation in this season due to yield loss, while shrimp and salt farmers have already reduced rice cultivation for the same reason and shifted to shrimp and salt farming as they perceived these enterprises as highly profitable and require less labour than rice farming. Rice farmers would tolerate a greater rice yield loss (23%) under saline conditions compared with the shrimp (16%) and salt farmers (14%). The yield loss thresholds indicate the need for government actions to support and encourage integrated land management for rice, shrimp and salt farming, rather than research and extension efforts for dry season rice expansion alone. These actions could strengthen sustainable livelihood options to ensure food security, and contribute to the achievement of sustainable development goals, for instance no poverty (SDG-1), zero hunger (SDG-2), and good health and well-being (SDG-3).

The Role of Stochasticity in Noise-Induced Tipping Point Cascades: A Master Equation Approach

Tipping points have been shown to be ubiquitous, both in models and empirically in a range of physical and biological systems. The question of how tipping points cascade through systems has been less explored and is an important one. A study of noise-induced tipping, in particular, could provide key insights into tipping cascades. Here, we consider a specific example of a simple model system that could have cascading tipping points. This model consists of two interacting populations with underlying Allee effects and stochastic dynamics, in separate patches connected by dispersal, which can generate bistability. From an ecological standpoint, we look for rescue effects whereby one population can prevent the collapse of a second population. As a way to investigate the stochastic dynamics, we use an individual-based modeling approach rooted in chemical reaction network theory. Then, using continuous-time Markov chains and the theory of first passage times, we essentially approximate, or emulate, the original high-dimensional model by a Markov chain with just three states, where each state corresponds to a combination of population thresholds. Analysis of this reduced model shows when the system is likely to recover, as well as when tipping cascades through the whole system.

Minority influence in climate change mitigation

While the majority of people care about environmental quality, they keep engaging in carbon-intensive practices that exacerbate climate change. Can we expect humans to collectively change by themselves, from the bottom up? Social change is often initiated by minorities - individuals who challenge the status quo. The dominant literature paints a rather pessimistic picture about the ability of minorities to instigate change in the environmental domain: environmental activists, vegans, and other minority members often elicit social sanctions, thereby ironically reinforcing the majority's commitment to current, environmentally harmful norms. Recent findings, however, point towards more optimism: pro-environmental minorities can pave the way towards 'tipping points' and spontaneous social change. Policymakers can speed up this process by offering top-down support for minorities - by giving them 'voice'.

Keystone taxa of water microbiome respond to environmental quality and predict water contamination

The human activity introduces strong environmental stresses, and results in great spatiotemporal heterogeneity for the environment. Although the effects of environmental factors on the microbial diversity and succession have been widely studied, knowledge about how keystone taxa respond to environmental stresses remains poorly understood. We examined bacterial and archaeal communities from 45 wetland ponds covering a wide range of waters in Hangzhou. We found that shifts in bacterial and archaeal communities were strongly correlated with water pollution as indicated by the comprehensive water quality identification (CWQI). The SEGMENTED analysis suggested that there were non-linear responses of microbial communities and keystone taxa to the water pollution gradient. Moreover, these significant tipping points (e.g., CWQI > 4.0) would afford a warning line for urban wetland management. Notably, keystone taxa of bacterial communities could be used to successfully (~88.9% accuracy) predict water contamination levels. This study provides new insights into the potential for keystone bacterial taxa to predict water contamination.

Socio-ecological vulnerability to tipping points: A review of empirical approaches and their use for marine management

Sustainability in the provision of ecosystem services requires understanding of the vulnerability of social-ecological systems (SES) to tipping points (TPs). Assessing SES vulnerability to abrupt ecosystem state changes remains challenging, however, because frameworks do not operationally link ecological, socio-economic and cultural elements of the SES. We conducted a targeted literature review on empirical assessments of SES and TPs in the marine realm and their use in ecosystem-based management. Our results revealed a plurality of terminologies, definitions and concepts that hampers practical operationalisation of these concepts. Furthermore, we found a striking lack of socio-cultural aspects in SES vulnerability assessments, possibly because of a lack of involvement of stakeholders and interest groups. We propose guiding principles for assessing vulnerability to TPs that build on participative approaches and prioritise the connectivity between SES components by accounting for component linkages, cascading effects and feedback processes.

Bacterioplankton community responses and the potential ecological thresholds along disturbance gradients

Increasing intensity and frequency of coastal pollutions are the trajectory to be expected due to anthropogenic pressures. However, it is still unclear how and to what extent bacterioplankton communities respond to the two factors, despite the functional importance of bacterioplankton in biogeochemical cycles. In this study, significant organic pollution index (OPI) and offshore distance gradients, as respective proxies of disturbance intensity and disturbance frequency, were detected in a regional scale across the East China Sea. A multiple regression on matrices (MRM) revealed that the biogeography of bacterioplankton community depended on spatial scale, which was governed by local characters. Bacterioplankton community compositions (BCCs) were primarily governed by the conjointly direct (-0.28) and indirect (-0.48) effects of OPI, while offshore distance contributed a large indirectly effect (0.52). A SEGMENTED analysis depicted non-linear responses of BCCs to increasing disturbance intensity and disturbance frequency, as evidenced by significant tipping points. This was also true for the dominant bacterial phyla. Notably, we screened 30 OPI-discriminatory taxa that could quantitatively diagnose coastal OPI levels, with an overall 79.3% accuracy. Collectively, the buffer capacity of bacterioplankton communities to increasing disturbance intensity and disturbance frequency is limited, of which the significant tipping points afford a warning line for coastal management. In addition, coastal pollution level can be accurately diagnosed by a few OPI-discriminatory taxa.

Contribution of the land use allocation model for agroecosystems: The case of Torrecchia Vecchia

In this study, we developed a bio-economic model coupling land use and ecosystem services to investigate the role of forests on a broad set of ecosystem services, including carbon sequestration, soil quality and biodiversity. As a case study, the model was calibrated with economic, agronomic and ecological data from the Torrecchia Vecchia agroecosystem in Italy. In our analysis of optimal land use allocation, the results showed that diversified land use is required to provide a good balance between provisioning and non-provisioning ecosystem services. More specifically, the development of woodlands alongside farming activities had a positive impact on the soil quality score and on landscape heterogeneity, which is a proxy for ecosystem function and resilience. These findings demonstrate that the inclusion of woodlands can alleviate the trade-offs between provisioning and non-provisioning services as they can generate profit while allowing for better soil quality and biodiversity relative to more intensive land use. The study also confirms that a landscape-scale method can be used to investigate agroecosystem management problems when spatially explicit data is not available.

Ecosystem changes following the 2016 Kumamoto earthquakes in Japan: Future perspectives

Major earthquakes cause widespread environmental and socioeconomic disruptions that persist for decades. Extensive ground disturbances that occurred during the shallow-focus Kumamoto earthquakes will affect future sustainability of ecosystem services west of Aso volcano. Numbers of earthquake-initiated landslides per unit area were higher in grasslands than forests, likely owing to greater root reinforcement of trees, and mostly initiated on ridgelines and/or convex/planar hillslopes. Most landslides traveled short distances and did not initially evolve into debris flows; resultant sediments and wood accumulating in headwater channels can be mobilized into debris flows during future storms. Fissures along ridgelines may promote water ingress and induce future landslides and debris flows that affect residents downstream. Native grasses are at risk because of habitat fragmentation caused by ground disturbances, extensive damage to rural roads, and abandonment of traditional pasture management practices. Sustainable management of affected areas needs to consider future risk of cascading hazards and long-term socioeconomic impacts.

How should economists model climate? Tipping points and nonlinear dynamics of carbon dioxide concentrations

Economists modeling climate policy face an array of choices when modeling climate change, including the role of uncertainty/ambiguity, irreversibility, and tipping points. After filtering out estimated cycles due to orbital climate forcing, we use a threshold quantile autoregressive model to characterize anomalies in atmospheric CO₂ concentrations. We then test for local instability and tipping points, and we characterize the stationary distribution of anomalies. We find evidence of nonlinear dynamics, tipping points and a non-normal stationary distribution.

Predicting catastrophic shifts

Catastrophic shifts are known to pose a serious threat to ecology, and a reliable set of early warning indicators is desperately needed. However, the tools suggested so far have two problems. First, they cannot discriminate between a smooth transition and an imminent irreversible shift. Second, they aimed at predicting the tipping point where a state loses its stability, but in noisy spatial system the actual transition occurs when an alternative state invades. Here we suggest a cluster tracking technique that solves both problems, distinguishing between smooth and catastrophic transitions and to identify an imminent shift in both cases. Our method may allow for the prediction, and thus hopefully the prevention of such transitions, avoiding their destructive outcomes.

Adaptive flood risk management planning based on a comprehensive flood risk conceptualisation

Densely populated deltas are so vulnerable to sea level rise and climate change that they cannot wait for global mitigation to become effective. The Netherlands therefore puts huge efforts in adaptation research and planning for the future, for example through the national research programme Knowledge for Climate and the Delta Programme for the Twenty-first century. Flood risk is one of the key issues addressed in both programmes. Adaptive management planning should rely on a sound ex-ante policy analysis which encompasses a future outlook, establishing whether a policy transition is required, an assessment of alternative flood risk management strategies, and their planning in anticipation without running the risk of regret of doing too little too late or too much too early. This endeavour, addressed as adaptive delta management, calls for new approaches, especially because of uncertainties about long-term future developments. For flood risk management, it also entails reconsideration of the underlying principles and of the application of portfolios of technical measures versus spatial planning and other policy instruments. To this end, we first developed a conceptualisation of flood risk which reconciles the different approaches of flood defence management practice and spatial planning practice in order to bridge the gap between these previously detached fields. Secondly, we looked abroad in order to be better able to reflect critically on a possible Dutch bias which could have resulted from many centuries of experience of successful adaptation to increasing flood risk, but which may no longer be sustainable into the future. In this paper, we explain the multiple conceptualisation of flood risk and argue that explicitly distinguishing exposure determinants as a new concept may help to bridge the gap between engineers and spatial planners, wherefore we show how their different conceptualisations influence the framing of the adaptation challenge. Also, we identify what the Netherlands may learn from neighbouring countries with a different framing of the future flood risk challenge.

Regime shifts under forcing of non-stationary attractors: Conceptual model and case studies in hydrologic systems

We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems.