Cross-scale Analysis Research Articles

Unveiling the Power of Model-Agnostic Multiscale Analysis for Enhancing Artificial Intelligence Models in Breast Cancer Histopathology Images.

Developing AI models for digital pathology has traditionally relied on single-scale analysis of histopathology slides. However, a whole slide image is a rich digital representation of the tissue, captured at various magnification levels. Limiting our analysis to a single scale overlooks critical information, spanning from intricate high-resolution cellular details to broad low-resolution tissue structures. In this study, we propose a model-agnostic multiresolution feature aggregation framework tailored for the analysis of histopathology slides in the context of breast cancer, on a multicohort dataset of 2038 patient samples. We have adapted 9 state-of-the-art multiple instance learning models on our multi-scale methodology and evaluated their performance on grade prediction, TP53 mutation status prediction and survival prediction. The results prove the dominance of the multiresolution methodology, and specifically, concatenating or linearly transforming via a learnable layer the feature vectors of image patches from a high (20x) and low (10x) magnification factors achieve improved performance for all prediction tasks across domain-specific and imagenet-based features. On the contrary, the performance of uniresolution baseline models was not consistent across domain-specific and imagenet-based features. Moreover, we shed light on the inherent inconsistencies observed in models trained on whole-tissue-sections when validated against biopsy-based datasets. Despite these challenges, our findings underscore the superiority of multiresolution analysis over uniresolution methods. Finally, cross-scale analysis also benefits the explainability aspects of attention-based architectures, since one can extract attention maps at the tissue- and cell-levels, improving the interpretation of the model's decision.

Pore structures and deterioration mechanism of concrete after cryogenic freeze-thaw cycles: Effects of moisture contents and aggregates

With the popularization of all-concrete liquefied natural gas (ACLNG) storage tanks, the performance of concrete after cryogenic exposure (−170 °C) has garnered significant interests from researchers. To investigate the damage mechanism of pore structures and the corresponding influencing factors, this study involved subjecting concrete with two moisture contents, namely air-dried and water-saturated to 10 cryogenic freeze-thaw cycles (CFTCs) to assess the variation laws in strengths. The mercury intrusion porosimetry (MIP), nitrogen adsorption and desorption (NAD), scanning electron microscopy (SEM), backscattered scanning electron (BSE) and low-temperature calorimeter (LTC) methods were employed to evaluate pore characteristics and the phase transition of pore water. Furthermore, pore structures were conducted using fractal dimensions based on the Zhang model and Frenkel-Halsey-Hill model. Findings indicate that there is a more pronounced reduction in strengths after 10 CFTCs in water-saturated state. Following cryogenic exposure, the porosity of paste increases from 4.97 % to 5.58 % and 7.04 %, and the porosity of mortar rises from 6.05 % to 7.20 % and 8.76 %, respectively. Aggregates in mortar contribute to more severe damage to pore structures in cryogenic circumstances, particularly capillary and macropores. The nucleation of pore water and ice contents are greatly influenced by moisture contents, and the frozen fraction is only 84.3 % in air-dried state. The destruction of gel pores is attributed to the continuous multi-order phase transition in water-saturated state. This work conducts a thorough cross-scale analysis of the pore structure in both paste and mortar, and it quantitatively evaluates the phase transition of pore water under cryogenic conditions using the LTC method. Ultimately, the influence of moisture contents and aggregates on the pore structures are evaluated, which provides deeper insights into the deterioration mechanism of concrete following cryogenic exposure.

Evolution characteristics of calcareous sand force chain based on particle breakage

Abstract Calcareous sand is easily broken under external force, which brings great difficulties to island reef engineering. Based on the particle flow program, a discrete element model that can reproduce the results of laboratory tests is established, the large principal stress method is introduced to identify the particle force chain, and the bond strength between particles is increased to obtain an unbreakable model with the same initial conditions, and different confining pressures are compared and analyzed. The evolution law of the force chain of the following two models establishes a macro-meso cross-scale analysis in the deformation process of calcareous sand, explores the internal mechanism of the crushing of calcareous sand particles. The results show that particle breakage plays an important role in the evolution of the force chain. Particle breakage will reduce the probability of the force chain on both sides of the axis, forcing the probability of the axial force chain to rise steadily. The macroscopic deviatoric stress is the external manifestation of the probability of the axial force chain on the meso level. The faster the probability of the force chain in the direction of the potential shear band increases, the more obvious the shear band is.

Vegetation growth responses to climate change: A cross-scale analysis of biological memory and time lags using tree ring and satellite data.

Vegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree-species level VGC and LCE with ecosystem-scale photosynthetic processes, we utilized tree-ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite-based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree-species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species-specific patterns; compared to CE and CH (diffuse-porous species), LF (ring-porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree-ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models.

Cross-scale analysis for the thermo-hydro-mechanical (THM) effects on the mechanical behaviors of fractured rock: Integrating mesostructure-based DEM modeling and machine learning

The excavation process induces the emergence of damage zones in the on-site engineering rock masses, significantly affecting the parameter evaluation of surrounding rock masses. Therefore, an in-depth understanding of the thermo-hydro-mechanical (THM) effects on the cross-scale failure process of fractured rock becomes progressively crucial in natural energy exploitation projects. In this study, a coupled thermo-hydro-mesostructure-based DEM (T-H-MSBM) model was developed to reconstruct rock microstructures and distinguish the THM responses of varying mineral grains, micro-defects and cracks in fractured granite. Five sets of numerical fractured granite in terms of different damage degrees were generated by restoring the form of excavation damage on site, and a series of compression simulations were conducted on the T-H-MSBMs under coupled temperature (25–250 °C), pore pressure (0–15 MPa) and confining pressure (15 MPa) conditions. Based on the cross-scale failure analysis on the fractured granite during the THM-compression loading process, the interplay between THM treatment and damage degree on the mechanical properties of fractured granite was revealed, and the main mechanisms affecting the varied macro mechanical properties were further discussed. Results indicate that both temperature and pore pressure exert the amplified deteriorating effect on the macro mechanical properties of fractured granite with increasing damage degree, while the temperature dependence becomes significantly more pronounced in the fractured granite with low damage degree. With an increase in the damage degree of fractured rock, the abundance of intra-mineral tensile cracks accelerates the initiation of pore pressure-induced cracks, and the coupled increase in pore pressure and temperature enhances the role of quartz-feldspar cracks in promoting the cracks in quartz. Finally, utilizing the optimized kernel ridge regression (KRR) model employed the grid search method, the correlation information database of rock macro-mechanical strength and THM factors were generated. The entire training time was less than 3 s, with the relative average errors of 0.7 MPa, which demonstrated the robust capability of machine learning method in predicting the coupled THM phenomena spanning multiple scales in geological materials and systems.

How does rapid urban construction land expansion affect the spatial inequalities of ecosystem health in China? Evidence from the country, economic regions and urban agglomerations

Identifying the adaptation mechanisms between urban construction land expansion (UCE) and ecosystem health (EHI) is a crucial aspect of sustainable management. However, there is still progress room for existing studies in distinguishing the impact mechanisms of UCE on the EHI of China's cities, different economic subregions and urban agglomerations. These gaps hinder the development of differentiated supportive frameworks for urban land management policies and ecosystem restoration initiatives across various scales in China. This study integrated multivariate satellite remote sensing data to monitor the heterogeneous evolution patterns of EHI and UCE in Chinese cities, economic subregions and urban agglomerations. A set of spatial measure models are utilized to distinguish the variability impact of UCE on China's EHI from a multi-dimensional perspective, including global and local, whole-area and sub-area, and direct and indirect influences. The results indicate that as UCE continues to grow, EHI steadily declined, reaching 0.512 with an average annual decrease of 1.507% from 2000 to 2020. A diminishing cluster pattern of EHI was observed, primarily concentrated in urban agglomerations such as BTH, GBA, and YRD. UCE exhibited a significant negative spatial dependence on EHI, and both global and local perspectives, UCE had a gradually weakening negative effect on the EHI of Chinese cities and economic subregions. However, the impacts of UCE on EHI in mature urban agglomerations (e.g., GBA, BTH, and YRD) were dominated by spatial spillovers, whereas growing urban agglomerations (e.g., MRYRU and CCU) were more affected by direct shocks from UCE. Our investigation informs site-specific ecologically sustainable management strategies in China based on cross-scale analyses, providing new perspectives into establishing cooperative mechanisms for cross-regional ecological management while emphasizing ecological risks management under the integration of urban agglomerations.

Multiscale modeling of coupled thermo-hydro-mechanical behavior in ice-bonded granular media subject to freeze-thaw cycles

We present a novel multiscale framework that integrates the single-point multiphase material point method (MPM) and the discrete element method (DEM) to model the complex freeze-thaw behavior of ice-bonded granular media. The proposed numerical framework is featured by (a) employing the continuum-based MPM to solve the macroscopic governing equations for granular systems involving thermo-hydro-mechanical (THM) coupling and phase transitions, and (b) using the grain-scale discontinuum-based DEM to capture the thermodynamically sensitive mechanical behaviors of ice-bonded granular media. The multiscale framework is constructed by attaching a DEM-based representative volume element (RVE) at each material point in MPM. This RVE serves as a live sample of each material point to track the state-dependent effective stress with respect to the local deformation and thermodynamic conditions like ice saturation, bridging the macroscopic phenomena and the underlying microstructural evolution. In particular, we implement a semi-implicit staggered integration scheme for the macroscale THM-coupled MPM to boost computational efficiency and enhance numerical stability. We also propose an innovative ice saturation-dependent bond contact to effectively reproduce the thermodynamically sensitive mechanical behaviors. The new multiscale framework is first benchmarked against analytical solutions for 1D non-isothermal consolidation problems. We then demonstrate its exceptional capability in simulating intricate freeze-thaw behavior of granular media through a boundary value problem involving cyclic freeze-thaw actions. Further cross-scale analyses reveal its potential in capturing key loading- and state-dependent THM responses with explainable microstructural mechanisms during complex freezing and thawing loading conditions.

Food deserts exposure, density of fast-food restaurants, and park access: Exploring the association of food and recreation environments with obesity and diabetes using global and local regression models.

To prevent obesity and diabetes environmental interventions such as eliminating food deserts, restricting proliferation of food swamps, and improving park access are essential. In the United States, however, studies that examine the food and park access relationship with obesity and diabetes using both global and local regression are lacking. To guide county, state, and federal policy in combating obesity and diabetes, there is a need for cross-scale analyses to identify that relationship at national and local levels. This study applied spatial regression and geographically weighted regression to the 3,108 counties in the contiguous United States. Global regression show food deserts exposure and density of fast-food restaurants have non-significant association with obesity and diabetes while park access has a significant inverse association with both diseases. Geographically weighted regression that takes into account spatial heterogeneity shows that, among southern states that show high prevalence of obesity and diabetes, Alabama and Mississippi stand out as having opportunity to improve park access. Results suggest food deserts exposure are positively associated with obesity and diabetes in counties close to Alabama, Georgia, and Tennessee while density of fast-food restaurants show positive association with two diseases in counties of western New York and northwestern Pennsylvania. These findings will help policymakers and public health agencies in determining which geographic areas need to be prioritized when implementing public interventions such as promoting healthy food access, limiting unhealthy food options, and increasing park access.

Cross-scale analysis reveals interacting predictors of annual and perennial cover in Northern Great Basin rangelands.

Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity. We analyzed regional-scale and local-scale patterns of annual grass, perennial grass, and shrub cover, and examined to what extent plot-level variation was contingent on pasture-level predictions of site favorability. Annual grasses were widespread at burned and unburned sites alike, contrary to assumptions of annual grasses depending on fire, and more common at lower elevations and higher temperatures regionally, as well as on warmer slopes locally. Pasture-level grazing pressure interacted with temperature such that annual grass cover was associated positively with grazing pressure at higher temperatures but associated negatively with grazing pressure at lower temperatures. This suggests that pasture-level temperature and grazing relationships with annual grass abundance are complex and context dependent, although the causality of this relationship deserves further examination. At the plot-level within pastures, annual grass cover did not vary with grazing metrics, but perennial cover did; perennial grasses, for example, had lower cover closer to water sources, but higher cover at higher dung counts within a pasture, suggesting contrasting interpretations of these two grazing proxies. Importantly for predictions of ecosystem response to temperature change, we found that pasture-level and plot-level favorability interacted: perennial grasses had a higher plot-level cover on cooler slopes, and this difference across topography was starkest in pastures that were less favorable for perennial grasses regionally. Understanding the mechanisms behind cross-scale interactions and contingent responses of vegetation to grazing in these increasingly invaded ecosystems will be critical to land management in a changing world.

Cross-Scale Reliability Analysis Framework for LNG Storage Tanks Considering Concrete Material Uncertainty

The reliability of liquefied natural gas (LNG) storage tanks is an important factor that must be considered in their structural design. Concrete is a core component of LNG storage tanks, and the geometric uncertainty of concrete aggregate material has a significant impact on their reliability. However, owing to the significant size difference between the concrete aggregate compared to the LNG storage tank, structural analysis using an accurate finite element model that includes all the geometric characteristics of the aggregate incurs significant analytical costs. In particular, for reliability analysis requiring a large number of samples, the computational costs incurred by finite element models are infeasible. Therefore, a dual acceleration strategy based on the asymptotic homogenization method and surrogate model technology is proposed to improve the efficiency of LNG storage tank reliability analysis. In the cross-scale analysis of a LNG storage tank based on asymptotic homogenization, order reduction of the LNG storage tank analysis model was realized. Based on this, a surrogate model construction method with the aggregate fraction and mass moment as inputs was proposed to further accelerate the reliability analysis of LNG storage tanks. Subsequently, a Monte Carlo method was used to perform a reliability analysis of the LNG storage tank considering the uncertainty of the concrete aggregate geometry and distribution under the action of liquid weight and wind load. The analysis showed that the wind load has a significant influence on the safety of the design of the roof of a LNG storage tank. The directionality of the wind load has a significant impact on the distribution of the sample point response for reliability analysis and the failure mode of the LNG storage tank. Owing to the directionality of the wind load, the response distributions of the maximum displacement and maximum stress of LNG were more concentrated, and the reliability of the LNG storage tank decreased after considering the wind load. In particular, the stress reliability of the tank decreased by 5.86%. When only the liquid load was considered, the maximum displacement and stress exhibited asynchronous failure, and the two almost never occurred simultaneously. When the wind load was considered, the failure mode of the LNG storage tank was dominated by the maximum stress. Moreover, the numerical example also demonstrated that the degree of freedom involved in structural analysis, as well as the time of structural analysis can be significantly reduced. So, the proposed cross-scale analysis framework can significantly improve the efficiency of reliability analysis. The conclusions established in this study provide theoretical and methodological guidance for the reliable design of LNG storage tanks.

A cross-scale method for predicting equivalent elastic constants of needled C/SiC composite considering manufacturing defects

For the ceramic matrix composites, manufacturing defects are the key issues that make their elastic constants difficult to predict. A method is proposed to predict equivalent elastic constants of needled C/SiC composite. This method consisted of multiscale model construction and cross-scale analysis. In the model construction, two types of manufacturing defects, pore and fiber deflection, were analyzed and characterized in two scale models. In the cross-scale analysis, theoretical prediction method was used to link the microscopic and mesoscopic scales. The periodic boundary condition method was used to link the mesoscopic and macroscopic scales. The comparison between the predicted results and the experimental data showed that the method considering manufacturing defects was in great agreement with experiment. By discussing the effects of different manufacturing defects on the elastic constants of needled C/SiC composite, it was demonstrated that manufacturing defects in needled C/SiC composite played an important role in dispersion of material properties. Reducing the number of manufacturing defects by optimizing the relevant process parameters can improve the dispersion of material properties.

Exploring potential futures: Evaluating the influence of deep uncertainties in urban planning through scenario planning: A case study in Rome, Italy

Cities play a critical role in developing adaptable strategies to address the challenges posed by climate change. However, the inherent complexity of urban environments and their uncertain future conditions necessitate exploring innovative approaches and tools to assist the current planning practices. This paper presents a workflow rooted in model-based scenario planning for long-term adaptation planning given uncertain futures. To demonstrate the workflow’s effectiveness, a pertinent case study was conducted in a flood-prone area of Rome. The study employed a land-use change model to examine potential urban growth patterns, considering the uncertain implementation of new poles of attraction. This interdisciplinary study constitutes an initial stride toward implementing uncertainty within urban planning frameworks. Future prospects encompass the integration of multiple models for cross-scale analysis, embracing further critical environmental and social aspects. This research contributes to advancing urban resilience strategies. It enhances the understanding of adapting to an uncertain future in the face of climate change, as urban areas must embrace comprehensive planning to ensure flexible adaptation when faced with climate-driven uncertainties in long-term planning. In conclusion, the study underscores that embracing uncertainty is a challenge and a pivotal opportunity to shape resilient and adaptable urban futures.

Sustaining Hierarchies: A Cross-Level and Cross-Scale Analysis of Power, Politics, and Dominant Discourse in Adaptive Decision Making

Climate change adaptation is a power-laden process that requires engagement and negotiation between people with diverse needs, interests, and levels of authority. Entrenched hierarchies in adaptation decision making influence what is considered legitimate policy and action, whose values are prioritized, and the interests of which actors are excluded. Through content and discourse analysis of interviews and focus group discussions with policymakers and decision makers across multiple spatial and jurisdictional levels, we illustrate how specific actors involved in adaptation efforts comprehend and engage with tensions, institutional politics, and community-level power dynamics, focusing on the experiences of rural farmers who are often sidelined in adaptation processes. We advance critical scholarship on the politics of adaptation and the politics of scale to demonstrate how power relations move within and across levels of decision making, by scrutinizing the discursive and material construction of scales and subjects. We argue that nuanced investigations of power and its (re)production across levels and scales are crucial to expose the underrepresentation of marginalized citizens in adaptation debates and to envision subversive political interventions toward climate justice. Key Words: agriculture, climate change adaptation, climate justice, decision making, Ghana.

Cross-Scale Analysis on the Working Performance of Micropile Group and Talus Slope System

Micropile groups (MPGs), combined with the advantages of the anti-slip pile and anchor cable, offer an efficient support system that can be used as countermeasures for stabilizing the talus slopes. However, the performance of MPGs in stabilizing the talus slopes is rarely numerically investigated from the continuous-discontinuous viewpoints. To fulfil this knowledge gap, a numerical method coupled with the discrete element method (DEM) with the finite element method (FEM) is proposed first, and validated to be with good accuracy by the centrifuge model tests. A series of cross-scale analysis cases are then adopted to assess the behavior of MPG in the talus slopes, in which the influencing factors are also taken into account. The numerical results indicate that the MPGs reinforcement can significantly improve the stability of the talus slopes, avoiding the potential progressive shallow slip. For the MPGs with different pile spacing, the distribution laws of deformation and internal force are rather similar, but the one whose pile spacing is four times the pile diameter shows better performance. Moreover, the effective anchorage length of MPG is approximately 1/3 of the pile length, and the axial force distribution is influenced by the type of pile bottom constraint and the tangential contact between the micropile and the bedrock. Finally, the “bidirectional anchorage” attributed to the platform and the bedrock can greatly improve the performance of the MPG, which is a non-negligible part of the anti-slip mechanism of the MPG. This study is of great significance for facilitating the design of MPG in stabilizing the talus slopes.

Pecora 22: Remote Sensing for Freshwater and Marine Environments

Pecora 22: Remote Sensing for Freshwater and Marine Environments

Evaluation of the dynamic behaviors of a train braking system considering disc–block interface characteristics

Disc–block interface properties have prominent influence on the dynamic behaviors of train braking systems. In this study, the tribological characteristics of small-scale train friction blocks with different perforation diameters at the centre of the block surface were investigated using a disc–block test rig. And the Stribeck model parameters of the disc–block friction interface were identified to intuitively characterize the evolution law of stick–slip characteristics with the variation of block perforation diameters. Then, a trailer bogie braking system model of a high-speed train considering the coupling effects between the essential brake unit, wheelset and bogie frame was established. And the identified Stribeck parameters were introduced into the proposed braking system dynamics model to establish a relationship between the friction characteristics of the disc–block interface and the dynamic behaviors of the train braking system. Based on this, the cross-scale analysis was performed to evaluate the dynamic performance of a train braking system affected by the perforated friction block via classical stability theory and numerical simulation. The results show that the friction block with a perforation diameter of 3 mm can effectively suppress the stick–slip vibration of the disc–block friction interface, then reducing the oscillation of system components and enhancing the stability of the entire trailer bogie system.

Reconciling policy instruments with drivers of deforestation and forest degradation: cross-scale analysis of stakeholder perceptions in tropical countries

Cross-scale studies combining information on policy instruments and on drivers of deforestation and forest degradation are key to design and implement effective forest protection measures. We investigated the scale and country dependency of stakeholder perceptions about future threats to tropical forests (e.g. agriculture, logging, woodfuel) and preferred policy instruments (e.g. reforestation, protected areas, combat illegal logging), by interviewing 224 representatives of forest-related institutions. We conducted analysis of variance and principal component analysis for eighteen variables across three countries (Zambia, Ecuador and the Philippines) and four spatial levels (from international to local). We found that the overall alertness about commercial drivers and the confidence in policy instruments are significantly lower at subnational levels and also in Zambia. Stakeholder expectations about the most important drivers and the most effective policies in the coming decade follow regional narratives, suggesting that there are no one-size-fits-all solutions in international forest policy. However, we found an unexpected consensus across scales, indicating potential for collaboration between institutions operating at different geographical levels. Overall, agriculture remains the driver with the highest expected influence (43%), while a strong favoritism for reforestation and forest restoration (38%) suggests a paradigm shift from protected areas to a stronger focus on integrative approaches.

A cross-scale analysis method for predicting the compressive mechanical properties of tin-based bearing alloy

A cross-scale analysis method for predicting the compressive mechanical properties of tin-based bearing alloy

From good intentions to unexpected results — a cross-scale analysis of a fishery improvement project within the Indonesian blue swimming crab

Private actors have become prominent players in the work to drive social and environmental sustainability transitions. In the fisheries sector, fishery improvement projects (FIPs) aim to address environmental challenges by leveraging the capacity of industry actors and using value chains to incentivize change. Despite globally rising FIP numbers, the incentive structures behind FIP establishment and the role of internal dynamics remain poorly understood. This paper uses institutional entrepreneurship as an analytical lens to examine the institutional change surrounding the management and trade of the Indonesian blue swimming crab and sheds light on how global market dynamics, local fishery dynamics, and value chain initiatives interact to affect the trajectory towards sustainability over time. We contribute to the institutional entrepreneurship framework by extending it with social-ecological dynamics, different actors’ ability to realize or resist change, and outcomes of institutional change. These additions can improve its explanatory power in relation to sustainability initiatives in fisheries governance and beyond. Our cross-scale historical analysis of the value chain shows not only the entrepreneurship behind the FIP’s establishment, and its institutional interventions, but also why these have been unsuccessful in improving the ecological sustainability of fishers’ and traders’ behavior. This provides valuable empirical grounding to a wider debate about industry leadership and private incentives for sustainability at large and helps disentangle under what conditions such initiatives are more (or less) likely to have intended effects.

MASTIFF: A mechanistic model for cross-scale analyses of the functioning of multiple stressed riverine ecosystems

Riverine ecosystems provide various ecosystem services. One of these services is the biological control of eutrophication by grazing macroinvertebrates. However, riverine ecosystems are subject to numerous stressors that affect community structure, functions, and stability properties. To manage rivers in response to these stressors, a better understanding of the ecological functions underlying services is needed. This requires consideration of local and regional processes, which requires a metacommunity approach that links local food webs through drift and dispersal. This takes into account long-distance interactions that can compensate for local effects of stressors. Our modular model MASTIFF (Multiple Aquatic STressors In Flowing Food webs) is stage-structured, spatially explicit, and includes coupled food webs consisting of benthic resource-consumer interactions between biofilm and three competing macroinvertebrate functional types. River segments are unidirectionally connected through organismal drift and bidirectionally connected through dispersal. Climate and land use stressors along the river can be accounted for. Biocontrol of biofilm eutrophication is used as an exemplary functional indicator. We present the model and the underlying considerations, and show in an exemplary application that explicit consideration of drift and dispersal is essential for understanding the spatiotemporal biocontrol of eutrophication. The combination of drift and dispersal reduced eutrophication events. While dispersal events were linked to specific periods in the species life cycles and therefore had limited potential to control, drift was ubiquitous and thus responded more readily to changing habitat conditions. This indicates that drift is an important factor for coping with stress situations. Finally, we outline and discuss the potential and possibilities of MASTIFF as a tool for mechanistic, cross-scale analyses of multiple stressors to advance knowledge of riverine ecosystem functioning.