Downstream Influence Research Articles

Exploring causal association between functional/structural connectivity and major depression disorder: A bidirectional Mendelian randomization study

ObjectivesPrior observational studies have suggested a correlation between major depressive disorder (MDD) and communication imbalances within the resting-state brain network (RSN), but the causal relationship remains unclear. This research uses Mendelian randomization (MR) analysis to explore the potential causal effects between functional connectivity (FC), structural connectivity (SC) and MDD. MethodsTwo-sample bidirectional MR analysis was employed in this study. Inverse variance weighted (IVW) was used to explore the causal relationship between the FC/SC and MDD, with various methods such as MR-Egger to conduct sensitivity analyses. ResultsThe IVW analysis results showed that higher genetic predicted dorsal attention network FC, limbic network SC, and dorsal attention network SC were associated with an increased risk of MDD (β: 15.08, 95%CI: 5.89–24.27, p = 0.001; β: 3.79, 95%CI: −0.22-7.8, p = 0.034; β: 9.89, 95%CI: 0.88–18.90, p = 0.031). Reverse MR analysis demonstrated that a genetically predicted elevated risk of MDD was associated with reduced frontal parietal network FC (β: −0.00046, p = 0.041). ConclusionsThe study suggests a causal relationship between the FC and SC within specific RSNs and the risk of MDD. Abnormalities in the dorsal attention network FC/SC and the limbic network SC were risk factors for MDD. The FC abnormality of the frontal parietal network may be the downstream influence following the MDD onset. Further investigation is needed to determine the potential utility of these neuroimaging markers in the prevention of MDD or the evaluation of treatment efficacy.

An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg−1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg−1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg−1 FPCM and 0.006 kg N kg−1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

Child maltreatment during the COVID-19 pandemic: implications for child and adolescent mental health

As societies worldwide addressed the numerous challenges associated with the COVID-19 pandemic, a troubling concern emerged—the possible rise of child maltreatment, which is a pernicious risk factor for child and adolescent mental health difficulties. This narrative review aims to provide a comprehensive understanding of how the many changes and challenges associated with the pandemic influenced worldwide occurrences of child maltreatment and, subsequently, the mental health of children and adolescents. First, we present the well-established evidence regarding the impact of child maltreatment on the mental health of children and adolescents both before and during the COVID-19 pandemic. Next, we examine the existing literature on the prevalence of child maltreatment during the pandemic, explanations for conflicting findings, and key mechanisms influencing the prevalence of maltreatment. Using a heuristic model of child maltreatment and its downstream influence on child mental health, we discuss risk and protective factors for maltreatment as well as mechanisms by which maltreatment operates to influence child and adolescent mental health. Finally, based on the accumulated evidence, we provide important recommendations for advancing research on child maltreatment, emphasizing the necessity for routine monitoring of maltreatment exposure at a population level, and discussing the implications for the field of child protection. This comprehensive review aims to contribute to the understanding of the challenges arising from the intersection of the COVID-19 pandemic and child maltreatment, with the goal of informing effective interventions in the domain of child welfare.

Study on the coupling mechanism and suppression characteristics of swirl premixing combustion self-excited oscillation

The numerical simulation method was used to study the mutual influence of flow field disturbance, vortex change, flame structure change, heat release pulsation, and pressure pulsation on the coupling mechanism and suppression characteristics of self-excited oscillations. The results indicate that perturbations from the jet have a direct impact on the structure of the flame and the alteration of the vortex. Vortex changes have a direct impact on heat release and flame structure. Changes in flame structure can cause pulsations in heat release. Oscillatory combustion is caused by the coupling of multiple factors, including heat release pulsations, flow field perturbations, acoustic vibrations, vortex variations, and flame variations. Pressure pulsations can be suppressed by a circumferentially arranged jet. The optimal solution for suppressing pressure pulsations can be achieved by adjusting the optimal jet angle (φ) and jet rotation direction. Adjusting the value of |φ| can solve the problems of poor local ΔPmax suppression caused by upstream swirled interference and the narrow range of downstream influence of the jet, at |φ| = 10°, the suppression effect is more pronounced in the counter-rotating direction than in the forward-rotating direction.

Analysis of Carbon Emissions in Heterogeneous Traffic Flow within the Influence Area of Highway Off-Ramps

With the continuous advancements in electrification, connectivity, and intelligence in the automotive industry, the mixed traffic of vehicles with different levels of driving automation is changing the carbon emission characteristics in the impact areas of off-ramps on highways. Considering the insufficient research on the carbon emission characteristics of heterogeneous traffic flow in the downstream influence areas of highway off-ramps, this study applied a scenario analysis method. Furthermore, considering factors such as vehicle composition, road control, and platoon management, it establishes and calibrates measurement models for carbon emissions from conventional vehicles, intelligent vehicles, the platoon driving of electric vehicles, and the mixed platoon driving of conventional vehicles and electric vehicles. This study also provides a simulation scenario for a three-lane highway off-ramp based on the actual conditions of the Xi’an Ring Expressway. Finally, by applying the constructed carbon emission calculation models for heterogeneous traffic flow in the intelligent vehicle mixed traffic scenario, a quantitative analysis was conducted to assess the impacts of the intelligent vehicle infiltration rate, off-ramp vehicle proportion, smart-vehicle-dedicated lanes, and platoon driving on carbon emissions in the downstream influence area of off-ramps. The results revealed the impact of intelligent vehicle integration and platoon driving on carbon emission characteristics in the downstream influence areas of highway off-ramps.

Enhance or impair: how does downstream complexity influence supply chain resilience with reconciling effects of intelligent manufacturing?

PurposeThe purpose of this paper is to examine the nuanced effects of downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. Intelligent manufacturing is considered to clarify their boundary conditions.Design/methodology/approachThe ordinary least squares regression was conducted, based on the data collected from 136 high-tech firms in China.FindingsHorizontal downstream complexity has a positive effect on supply chain resilience significantly, while the negative impact of vertical downstream complexity on supply chain resilience is not significant. Contingently, intelligent manufacturing plays a negative moderating role in the relationship between horizontal downstream complexity and supply chain resilience, while it positively moderates the relationship between vertical downstream complexity and supply chain resilience.Originality/valueThis study disentangles the nuanced effects of both horizontal and vertical downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. It also clarifies their boundary conditions by considering the focal firm's intelligent manufacturing level as the contingent factor.

Weakened Relationship between the Tibetan Plateau Heat Source and the Western North Pacific Anomalous Anticyclone in Recent Summers

Abstract Numerous studies have indicated that the atmospheric heat source (AHS) over the Tibetan Plateau (TP) is highly correlated with the western North Pacific anomalous anticyclone (WNPAC) in summer. However, such an interannual relationship has been weakened since the late 1990s. The present work shows that the TP AHS was significantly and positively correlated with the WNPAC during the period 1979–99 (P1), while this relationship became insignificant hereafter [2000–20 (P2)]. From an atmospheric perspective, we identify that the long-term change in the upper-level atmospheric circulation over the TP is an important cause for weakening the relationship. An obvious upper-level anticyclonic trend occurred over the northeastern TP in the past four decades, with an easterly trend on the anticyclone’s southern flank, with anomalous westerlies during P1 but anomalous easterlies during P2 over the main portion of the TP. With the anomalous upper-level westerlies in P1, abnormal high pressure induced by the TP heating (i.e., AHS) extended downstream in the upper troposphere. Subsequently, anomalous descending motions formed over the northwestern Pacific due to the eastward-extended high pressure, together with the vertical transport of negative relative vorticity, favorable for the enhancement of the WNPAC. In P2, the TP heating-induced abnormal high pressure was confined over the southern TP due to the anomalous easterlies, suppressing its downstream influence and finally breaking the connection between the TP AHS and the WNPAC. Modeling results from both linear baroclinic model (LBM) sensitivity experiments and the CESM Large Ensemble dataset further confirm the important role of the change in background circulation in weakening the relationship. Significance Statement The atmospheric heat source (AHS) over the Tibetan Plateau (TP) is generally believed to closely connect with the western North Pacific anomalous anticyclone (WNPAC) during boreal summer. Previous studies have revealed that a significant interannual correlation exists between the TP AHS and the WNPAC; however, such a relationship was weakened recently, but the causes are unknown. This study highlights the important contribution from the change in background circulation to the weakened relationship. An upper-level easterly trend occurred over the TP in recent summers, under which the TP heating-induced abnormal atmospheric response was confined in the TP area, limiting the downstream influence of the TP heating and finally destroying the connection between the TP AHS and the downstream WNPAC.

Estimating the model parameters for remote sensing reflectance pixel by pixel: a neural network approach for optically deep waters

ABSTRACT Remote sensing reflectance (R rs) and inherent optical properties (IOPs) conversions are fundamental in accurate satellite measurements to guarantee the semi-analytical retrieval quality of IOPs and the biogeochemical products. Traditionally, the R rs-IOPs conversions are determined by a quadratic polynomial function with two model parameters (G x = 0,1). However, G x values vary in time and location, which are attributed to the spatial and temporal variability inherent to illumination conditions, sea surface properties, and meteorological states. To improve the performance of three classical existing models used for R rs-IOPs conversions, we designed two novel neural network models (NNG x = 1,2) to quantitatively calculate G x from the R rs spectrum pixel by pixel without requirement of any auxiliary illumination and meteorological data, and then proposed for R rs-IOPs conversions. We evaluated these approaches with numerical simulations and field measurements, and the results show that the NNG x models are more effective in semi-analytically converting R rs into IOPs than the three existing models. Furthermore, we applied the NNG x models to satellite images to understand the downstream influence of the G x values on IOPs estimates for the global oceans. We further confirm that the G x values dramatically change for the global ocean, which is especially true for very oligotrophic gyres, coastal waters, and high latitude oceans. When we use a constant G x for the R rs-IOPs conversions, it leads to substantial uncertainty of up to 30% in the IOPs retrievals for China’s coastal regions. Our results suggest that it is possible to improve the data quality of IOPs for the global oceans by providing accurate pixel-level G x values using NNG x models.

A family of adverse pressure gradient turbulent boundary layers with upstream favourable pressure gradients

A flat-plate turbulent boundary layer (TBL) is experimentally subjected to a family of 22 favourable–adverse pressure gradients (FAPGs) using a ceiling panel of variable convex curvature. We define FAPGs as a sequence of streamwise pressure gradients in the order of favourable followed by adverse, similar in sequence to the pressure gradients over the suction side of an airfoil. For the strongest pressure gradient case, the acceleration parameter, $K$ , varied spatially from $6 \times 10^{-6}$ to $- 4.8 \times 10^{-6}$ . The adverse pressure gradient (APG) region of this configuration is studied using particle image velocimetry in the streamwise–wall-normal plane. The statistics of the APG TBL show that the upstream favourable pressure gradient (FPG) exerts a strong and lasting downstream influence, and that the rapid spatial changes in the pressure gradients imposed cause an internal boundary layer to grow within the TBL for 15 of the cases studied. The internal layer typically occupies 20 $\%$ of the boundary layer thickness and dominates the boundary layer response, containing the peak turbulent production, peak strength and population of vortices, and most of the spectral energy content of the flow. The outer layer, on the other hand, develops in the APG region without considerable changes to the state dictated by the upstream FPG. These trends are in contrast to APG TBLs that originate from a zero pressure gradient region, where the outer/wake region is known to dominate TBL response. The observed changes are quantified across the family of FAPGs imposed.

Causal relations between the loop current penetration and the inflow/outflow conditions inferred with a rigorous quantitative causality analysis

The causal relationship between the Loop Current (LC) penetration into the Gulf of Mexico and the inflow/outflow conditions in the Yucatan Channel and the Straits of Florida is analyzed using a recently developed causality analysis, which is quantitative in nature, and rigorously derived from first principles. Long-term time series from a 23-year high-resolution reanalysis product reveals that the LC penetration is associated with a dipole (tripole) mode of transport (vorticity flux) in both channels. These relationships, though significant from a perspective of correlation, do not necessarily imply causality. By applying the causality analysis, we identify a clear asymmetry of causality, that is, the flow conditions in the Yucatan Channel and the Straits of Florida can both cause the LC penetration. Conversely, the LC path state is less causal to the current variability in the two channels. The spatial causal structures further reveal that the upstream influence from the Yucatan Channel is strong in the main body of the LC as well as its extension area, while the downstream influence from the Straits of Florida is confined within the eastern branch of the LC. The asymmetric causal relations obtained from the data-assimilative reanalysis product are further confirmed in a free-running model simulation forced by three repeated cycles of atmospheric forcing, although the strength of the causality could vary from one simulation cycle to another, due to the intrinsic variability of the LC system.

Association of SNPs in the PAI1 Gene with Disease Recurrence and Clinical Outcome in Bladder Cancer.

Bladder cancer (BCa) is one of the most common cancer types worldwide and is characterized by a high rate of recurrence. In previous studies, we and others have described the functional influence of plasminogen activator inhibitor-1 (PAI1) in bladder cancer development. While polymorphisms in PAI1 have been associated with increased risk and worsened prognosis in some cancers, the mutational status of PAI1 in human bladder tumors has not been well defined. In this study, we evaluated the mutational status of PAI1 in a series of independent cohorts, comprised of a total of 660 subjects. Sequencing analyses identified two clinically relevant 3' untranslated region (UTR) single nucleotide polymorphisms (SNPs) in PAI1 (rs7242; rs1050813). Somatic SNP rs7242 was present in human BCa cohorts (overall incidence of 72%; 62% in Caucasians and 72% in Asians). In contrast, the overall incidence of germline SNP rs1050813 was 18% (39% in Caucasians and 6% in Asians). Furthermore, Caucasian patients with at least one of the described SNPs had worse recurrence-free survival and overall survival (p = 0.03 and p = 0.03, respectively). In vitro functional studies demonstrated that SNP rs7242 increased the anti-apoptotic effect of PAI1, and SNP rs1050813 was related to a loss of contact inhibition associated with cellular proliferation when compared to wild type. Further investigation of the prevalence and potential downstream influence of these SNPs in bladder cancer is warranted.

What Should Be Clinicians' Roles in Regulatory Assessment of Prospective Interventions' Risks of Exacerbating Inequity?

When there is an evidence base that could be used credibly to justify expedited US Food and Drug Administration review, emergency use authorization, or approval, interventions-in-development must be evaluated in terms of their possible downstream influence on public trust and confidence in regulatory processes during a national public health crisis. When regulatory decisions express overconfidence about a prospective intervention's success, there is risk that the costliness of or misinformation about the intervention will exacerbate health inequity. A converse risk is regulators' underestimation of an intervention's value in treating populations at risk for inequitable care. This article considers the nature and scope of clinicians' roles in regulatory processes in which such risks must be considered and balanced to promote public safety and public health.

Influence Area at Signalized and Stop-Control Intersections: Operational Analysis

Understanding the influence of intersections on operating conditions along connecting roadway segments is important for the analysis of highway facilities and corridors. This study aims at assessing the influence area at signalized and stop-control intersections along rural corridors. The study used speed as a performance measure in examining the spatial extent of operational effects at intersections. High-fidelity connected vehicle (CV) trajectory data, collected at 11 different sites in Florida, was used in this study. The CV trajectory data consists of individual waypoints that included timestamps and location coordinates along with other attributes. Drivers’ speed profiles while driving through the intersection were established and analyzed to determine the length of upstream and downstream influence areas. Quantile regression models were developed to estimate the 50th, 70th, and 85th percentiles of upstream and downstream influence areas separately for signalized and stop-control intersections. Study results indicate that the upstream influence area is longer for a signalized intersection than for a stop-control intersection for comparable segment running speeds. Further, the downstream influence area is significantly longer than the upstream influence area at signalized intersections, and this was consistent at all study sites. Traffic flow level did not have a significant effect on the upstream or downstream influence area; however, midblock running speed, percent heavy vehicles, and facility type (multilane versus two-lane) were found to significantly affect the upstream and downstream influence areas at signalized intersections.

Downstream influence of turbulent flow past vortex generators

Abstract Vortex generators (VGs) are typically positioned upstream of a boundary layer separation region. Their effectiveness depends on incoming flow conditions (Mach number, Reynolds number, and boundary layer characteristics), geometrical configuration (vane or ramp, height, width, and angle of incidence), and spacing. Device-induced vortices and following decay allow VGs to be used as a passive control device. This study uses pressure-sensitive paint to determine the global surface pressure pattern for a flat plate flow in the presence of VGs (counter-rotating vanes, co-rotating vanes and ramps). The freestream Mach number is 0.64 and 0.83. The ratio between the height of the VGs and the incoming boundary layer thickness is 0.2, 0.5, and 1.0. The standard deviation in the spanwise pressure in the streamwise direction is used to determine the downstream influence of turbulent flow past VGs. Increasing the height of VGs causes device-induced vortices to propagate farther downstream.

Location, location, location: Fibrin, cells, and fibrinolytic factors in thrombi.

Thrombi are heterogenous in nature with composition and structure being dictated by the site of formation, initiating stimuli, shear stress, and cellular influences. Arterial thrombi are historically associated with high platelet content and more tightly packed fibrin, reflecting the shear stress in these vessels. In contrast, venous thrombi are generally erythrocyte and fibrin-rich with reduced platelet contribution. However, these conventional views on the composition of thrombi in divergent vascular beds have shifted in recent years, largely due to recent advances in thromboectomy and high-resolution imaging. Interestingly, the distribution of fibrinolytic proteins within thrombi is directly influenced by the cellular composition and vascular bed. This in turn influences the susceptibility of thrombi to proteolytic degradation. Our current knowledge of thrombus composition and its impact on resistance to thrombolytic therapy and success of thrombectomy is advancing, but nonetheless in its infancy. We require a deeper understanding of thrombus architecture and the downstream influence on fibrinolytic susceptibility. Ultimately, this will aid in a stratified and targeted approach to tailored antithrombotic strategies in patients with various thromboembolic diseases.

Burning the candle at both ends: Intraretinal signaling of intrinsically photosensitive retinal ganglion cells.

Intrinsically photosensitive retinal ganglion cells (ipRGCs) are photoreceptors located in the ganglion cell layer. They project to brain regions involved in predominately non-image-forming functions including entrainment of circadian rhythms, control of the pupil light reflex, and modulation of mood and behavior. In addition to possessing intrinsic photosensitivity via the photopigment melanopsin, these cells receive inputs originating in rods and cones. While most research in the last two decades has focused on the downstream influence of ipRGC signaling, recent studies have shown that ipRGCs also act retrogradely within the retina itself as intraretinal signaling neurons. In this article, we review studies examining intraretinal and, in addition, intraocular signaling pathways of ipRGCs. Through these pathways, ipRGCs regulate inner and outer retinal circuitry through both chemical and electrical synapses, modulate the outputs of ganglion cells (both ipRGCs and non-ipRGCs), and influence arrangement of the correct retinal circuitry and vasculature during development. These data suggest that ipRGC function plays a significant role in the processing of image-forming vision at its earliest stage, positioning these photoreceptors to exert a vital role in perceptual vision. This research will have important implications for lighting design to optimize the best chromatic lighting environments for humans, both in adults and potentially even during fetal and postnatal development. Further studies into these unique ipRGC signaling pathways could also lead to a better understanding of the development of ocular dysfunctions such as myopia.

The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system

Abstract. Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of near-term climate change and are a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 (Coupled Model Intercomparison Project Phase 6) Decadal Climate Prediction Project (DCPP) decadal hindcasts produced with the operational CMCC (Euro-Mediterranean Center on Climate Change) decadal prediction system (DPS), based on the fully coupled CMCC-CM2-SR5 dynamical model. A 20-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with the skill of an ensemble of non-initialized historical simulations so as to quantify the added value of the initialization. In particular, the CMCC DPS is able to skillfully reproduce past climate surface and subsurface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the skill of the CMCC DPS is significantly higher than that of the historical simulations over a few specific regions, including the Sahel, northern Eurasia, and over western and central Europe. The Atlantic multidecadal variability is also skillfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes, and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1–9 lead year range. Systematic errors also affect the forecast quality of the CMCC DPS, featuring a prominent cold bias over the Northern Hemisphere, which is not found in the historical runs, suggesting that, in some areas, the adopted full-field initialization strategy likely perturbs the equilibrium state of the model climate quite significantly. The encouraging results obtained in this study indicate that climate variability over land can be predictable over a multiyear range, and they demonstrate that the CMCC DPS is a valuable addition to the current generation of DPSs. This stresses the need to further explore the potential of the near-term predictions, further improving future decadal systems and initialization methods, with the aim to provide a reliable tool to inform decision-makers on how regional climate will evolve in the next decade.

Modelling discharge flows at signalised intersections with adjustment of downstream effects

Former studies revealed that before spillbacks happen intersection capacities can still be greatly affected by downstream queues and signals. However, there is no methodology reasonably accounting for this effect. This research aims to propose adjustment factor models (Adj models) for both saturation flow rate (SFR) and start-up lost time (SLT) in through lane groups considering downstream conditions. An improved cell transmission model is created to build a simulation platform that can well reproduce the downstream influence. By the experimental data, Adj models are derived through heuristic optimisation based regression analyses. Proposed adjustment factors are governed by common traffic indicators. Sensitivity analyses proved that approaches with high volumes, short segment lengths, large green ratios, positive offset, or large cycle lengths are more easily affected by downstream conditions. Through the validation, it is proved that the estimation error of SFR and SLT can be significantly reduced by the proposed adjustment factors.

Better together? How evolution of co-branding alliance affects performance

PurposeThe purpose of this study is to examine role stress over the course of an alliance between supply chains. This study examines ambiguity as antecedent to multiple organisational outcomes.Design/methodology/approachThis study subsequently uses a time series design that uses a close replication of the authors’ initial study. The design affords the opportunity to examine the dynamics associated with the evolution of the alliance.FindingsThis study recognises that the relationships developed by collaborating firms are enacted by downstream entrepreneurs in the supply chain, yet this observation is rarely incorporated into interfirm research. The authors illustrate that the alliances have a significant downstream influence on operations at the retail level.Research limitations/implicationsThis longitudinal research has the potential to reduce common method variance and enhance causal inference. The second limitation concerns the simultaneous collection of the predictor and criterion variables. The third limitation is the use of single informants as the primary vehicle for the analysis of the theoretical model when prior research indicates that multiple informants offer enhanced reliability and validity.Practical implicationsThe findings contribute to the management theory of business entrepreneurship and strategic alliances and research on supply chains.Originality/valueThis study underscores the need to examine alliances via time series. Research that attempts to generalise from data collected at a single point in time is unlikely to be able to capture the dynamics associated with the development of a joint venture and offers limited opportunity to make inferences about the causal order of relationships. The model based on longitudinal data reveals that the stage of an alliance influences the level of vertical control and ambiguity and the effect of control on role ambiguity.

Comparative impacts of dam water level regimes on herbaceous plant growth strategies in cascade reservoirs and downstream reaches of a major river

Abstract Flow regulation is a prolific and growing influence on rivers world‐wide. Nine cascade hydropower dams were constructed along the 1,150‐km Wujiang River in China over the past 30 years, disrupting longitudinal continuity. Water level fluctuations in the associated reservoirs range between daily, weekly, seasonal, and annual, depending on the type of regulation, but the comparative impacts of these regimes on plant growth strategies, or the extent of their downstream influence, is unknown. Competitor, stress‐tolerator, and ruderal (CSR) plant strategies were used to assess the impact of reservoir regulation type on the riparian herbaceous plant community based on sampling the inundation zone of nine reservoirs and their downstream river reaches during 2017 and 2018. Our results revealed profound differences in CSR plant strategies of the dominant vegetation with respect to water level regime. While ruderal plants dominated (45%–60% of species), irrespective of regulation type, vegetation in reservoirs exhibited a strong shift from stress‐tolerators (e.g., Cynodon dactylon, C‐11.9:S‐41.5:R‐46.5%) to competitors (e.g., Reynoutria japonica, C‐77.9:S‐0:R‐22.0%) with increasing intensity of water level fluctuation, reflecting the shift from annual to daily regulation. The width of the inundation zone was the best overall variable in explaining the CSR strategies of riparian vegetation, both in the reservoir inundation zone (r2‐adj = 15.4%) and the downstream river (r2‐adj = 7.3%). Retention time significantly explained variation in CSR plant strategies in the reservoir inundation zone (r2‐adj = 3.7%, p = 0.002) but not downstream (p > 0.01). There was also a clear scale dependency of CSR plant strategies, with an increase in stress tolerators (average slope = 0.7%/km) and decline of competitor (average slope = −0.3%/km) and ruderal plants (average slope = −0.9%/km) with increasing distance downstream from dams. The growth strategies of the dominant riparian vegetation changed with the magnitude and frequency of water level fluctuations caused by differences in regulation type, and local environmental conditions. Clear scale dependency in the CSR plant strategies was observed with distance from the dam, with ruderals dominating closest to the reservoirs and declining gradually downstream as stress tolerators increased. Our study helps to evaluate the impact of river damming on the functional traits of riparian vegetation and to predict the resilience and restoration potential of riparian vegetation under different forms of human disturbance.