Low Synergy Research Articles

What do the sustainable development goals reveal, and are they sufficient for sustainable development?

The Sustainable Development Goals (SDGs) adopted by the United Nations in 2015 represent the current perceptions of humans regarding understanding and monitoring development. Achieving all 17 goals simultaneously is unrealistic. Considering the interconnected nature of SDGs, identifying their critical dimensions, goals, indicators, and mutual relationships is necessary. In addition, with increasing reservations about the sustainability of SDGs, it is crucial to explore consistency across different dimensions to ensure policy coherence in maximizing synergies and minimizing trade-offs. Our study employed multiple factor analysis (MFA) and hierarchical clustering on principal components (HCPC) to investigate these issues and analyze the results based on the public value (PV) theory. The results indicated that the Human Development Index (HDI) and gross domestic product per capita (GDPP) constitute the first principal component (PC) and are determinants in differentiating country clusters. However, they contradict environmental indicators such as CO2 emissions per capita and ecological footprint gha per person (EFP) and have low synergy with the Happy Planet Index (HPI). Additionally, the relationships between income level, inequality, and environmental quality correspond to a combined Kuznets curve and an environmental Kuznets curve (EKC). Moreover, governance capacity has become increasingly crucial in sustainable development, particularly in the capability to prioritize different PVs in a timely and strategic manner. Finally, despite the novelty of EFP and HPI, they cannot reveal the entire development story. SDGs require embracing more such indicators to enrich the value bases of development and achieve a sustainable future.

How does digital technology innovation drive synergies for reducing pollution and carbon emissions?

Digital technological innovation is a key force in reshaping production and achieving green, low-carbon development, provides new impetus to reducing pollution emissions (PE) and carbon emissions (CE). This study employed the coupled coordination model, panel regression model and spatial Durbin model to examine how the digital technology innovation level (DTIL) and digital technology transfer scale (DTTS) affected synergies for reducing pollution and carbon emissions (PCRS) in the Yangtze River Delta region from 2015 to 2021. The results showed that: The evolution of PCRS is characterized by high synergy cities are increasing, low synergy cities are decreasing, and excellent coordination cities are becoming more concentrated. In the synergistic type migration evolution, the core area primarily ascends; the central and peripheral areas remain mostly stable. The effects of DTIL and DTTS on PCRS follow a non-linear inverted U-shaped pattern. DTIL has a stronger effect on reducing PE, while DTTS tends to increase CE. In terms of spatial spillover effects, DTIL has an inverted U-shaped relationship with PCRS in local regions and a positive spillover effect on neighboring regions; DTTS has a negative impact on PCRS in local regions, but shows an inverted U-shaped relationship in neighboring regions. Both of them also affect PCRS through industrial structure and energy efficiency.

The role of reputation to reduce punishment costs in spatial public goods game

In the traditional spatial public goods game (SPGG), punishment mechanisms are considered an effective strategy to promote cooperation. However, in traditional punishment models, the high cost of punishment leads to ineffective cooperation promotion when the synergy factor is low. Therefore, this paper decides to establish a punishment model based on reputation to reduce the cost of punishment, to solve the above problems. Cooperation strategy can accumulate reputation as evolution progresses, where the high-reputation punishing group, acting as the 'main force' of law enforcement, can obtain stronger expulsion capabilities by reducing costs, and the decrease in the revenue difference with ordinary cooperators brings stronger survivability. The research compares the new punishment mechanism with traditional punishment mechanisms, finding that under low synergy factors, the reputation-based punishment model is more likely to achieve cooperation, and after introducing the reputation mechanism, it significantly enhances the promotive effect of punishers on system cooperation.

Economic and Environmental Sustainability Trade-Off Analysis in Sheep Farming Using the Farm Accountancy Data Network Database

Agriculture and livestock farming significantly contribute to the success of all United Nations Sustainable Development Goals of Agenda 2030 and are pivotal in the sustainability transition of the European agri-food sector. However, those sectors have been criticized for generating negative environmental externalities. In this context, adopting indicators able to evaluate agriculture and sheep farming sustainability is essential for fostering sustainable development in the primary sector and defining appropriate policies to support it. Such indicators are crucial for understanding if European Union policies striving to realize win–win opportunities based on synergy between farms’ environmental and economic dimensions are realistic. This paper focuses on this wave of interest and has two aims. First, it intends to investigate the existence of synergies or trade-offs between those dimensions using a trade-off analysis. To this end, a significant set of economic and environmental farm indicators was selected, and two composite indicators were created. Second, it aims to investigate the relationship between those two indicators and some pivotal structural and socio-demographic variables. This study was carried out on 219 Sardinian sheep farms included in the Italian Farm Accountancy Data Network. The findings showed a low synergy between the economic and environmental spheres, a relationship between economic indicators and farmers’ ages and organic production variables, and no relationships between the environmental dimension and the analyzed variables.

A Framework for Assessing Trade-Offs and Synergies in Green Space System Services Based on Ecosystem Services Bundles

Urban green and blue spaces (UGBS) take on critical significance in urban development. In this study, the physical characteristics and landscape-ecology-society-space (LESS) system services of 24 urban parks in 2 greenbelts surrounding Foshan City are analyzed. Five service bundles are proposed based on the four systems, comprising landscape-ecological-social-spatial-composite driving bundles. Subsequently, the trade-offs and synergies (TOS) of the four systems are assessed through principal component analysis (PCA), a self-organization neural network model (SOM), and geographically weighted regression (GWR). As indicated by the results, a high trade-off relationship is identified between the landscape and ecology systems, as well as a low synergy relationship between the ecology system and the society system. Furthermore, there are structural differences in the physical characteristics of the parks in the greenbelts surrounding the city, with parks in the inner ring having higher social and spatial effects, while parks in the outer ring have higher landscape and ecological effects. Lastly, recommendations are presented for planning UGBS around the city. In this study, a feasible framework is developed to achieve high-quality urban living environments based on the multi-objective balanced strategies for UGBS.

Research on the Collaborative Evaluation and Development of Digital Trade and Industrial Clusters: Taking Relevant Industries in Guangzhou as an Example

This paper constructs a synergy model between digital trade and industrial clusters from the perspective of system theory. Five major industrial clusters in Guangzhou, including textile and clothing, beauty and daily chemical, luggage and leather goods, jewelry, and food and beverage, are selected to analyze the evolution trend of the composite system between digital trade and industrial clusters. The study found that the luggage and leather goods industry is in the expansion stage of the synergy between digital trade and industrial clusters. The other four industries are still in the initial stage of digital trade and industrial cluster synergy, with low synergy level. The textile clothing industry has the least obvious growth momentum, showing the lowest level of synergy between digital trade and industrial clusters. By promoting the efficient evolution of the system, the upgrading and transformation of industrial clusters through digital trade can be achieved, and the deepening development of digital service trade based on industrial clusters can be effectively supported. This paper can provide recommendation for the collaborative development of Guangzhou's industrial digitization and digital industrialization.

Research on the Synergistic Effect of the Composite System for High-Quality Development of the Marine Economy in China

The key to achieving the high-quality development of the marine economy (HDME) is to facilitate synergy through the coordination of marine elements. By adopting a perspective concerning complex systems, this paper presents a comprehensive framework—the composite system for high-quality development of the marine economy (CSHDME)—that synergistically integrates the five dimensions of “economy—technology—ecological—society—culture” in the marine domain. Building upon this framework, in this paper, we construct a CSHDME synergy evaluation index system using relevant data from 11 coastal provinces in China from 2010 to 2020. We utilize the subsystem orderliness degree model and composite system synergy degree model to calculate the degree of subsystem orderliness and degree of composite system synergy for the CSHDME as well as analyze the development status of the CSHDME subsystem and the degree of CSHDME synergy. The results indicate that: (1) the five-dimensional subsystem of the CSHDME exhibits an overall trend of year-on-year growth, with significant development disparities; (2) the degree of the synergy of the CSHDME is characterized by strong regional differences, strong fluctuations, instability, and low synergy; (3) the degree of the synergy of the CSHDME demonstrates the spatial evolution characteristics of low synergy, strong differences, strong fluctuations, and high agglomeration; and (4) the degree of orderliness and development speed of subsystems affect the degree of the synergy of the CSHDME. Therefore, measures such as the rational allocation of marine resources, accurate improvement of shortcomings, optimization of the spatial layout, and strengthening of regional cooperation should be considered to further promote the synergistic development of the CSHDME.

MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders.

Accurate prediction of synergistic effects of drug combinations can reduce the experimental costs for drug development and facilitate the discovery of novel efficacious combination therapies for clinical studies. The drug combinations with high synergy scores are regarded as synergistic ones, while those with moderate or low synergy scores are additive or antagonistic ones. The existing methods usually exploit the synergy data from the aspect of synergistic drug combinations, paying little attention to the additive or antagonistic ones. Also, they usually do not leverage the common patterns of drug combinations across different cell lines. In this paper, we propose a multi-channel graph autoencoder (MGAE)-based method for predicting the synergistic effects of drug combinations (DC), and shortly denote it as MGAE-DC. A MGAE model is built to learn the drug embeddings by considering not only synergistic combinations but also additive and antagonistic ones as three input channels. The later two channels guide the model to explicitly characterize the features of non-synergistic combinations through an encoder-decoder learning process, and thus the drug embeddings become more discriminative between synergistic and non-synergistic combinations. In addition, an attention mechanism is incorporated to fuse each cell-line's drug embeddings across various cell lines, and a common drug embedding is extracted to capture the invariant patterns by developing a set of cell-line shared decoders. The generalization performance of our model is further improved with the invariant patterns. With the cell-line specific and common drug embeddings, our method is extended to predict the synergy scores of drug combinations by a neural network module. Experiments on four benchmark datasets demonstrate that MGAE-DC consistently outperforms the state-of-the-art methods. In-depth literature survey is conducted to find that many drug combinations predicted by MGAE-DC are supported by previous experimental studies. The source code and data are available at https://github.com/yushenshashen/MGAE-DC.

The evolution of cooperation in spatial public goods games under a risk-transfer mechanism

An interest coalition of sharing benefits and risks, such as cross shareholding between companies, allows them to transfer risks in a competitive business world. In a public goods game, cooperators are at the risk of being exploited by defectors. This paper studies whether such risk-transfer mechanism can induce cooperative behaviors in social dilemmas. We model a public goods game with coalition mechanism in a structured population. The players are categorized by whether they cooperate as well as whether they are willing to form coalitions. Those who are willing (unwilling) to form coalitions with others are called coalitional (traditional) individuals. By exploring the phase transitions of systems, the spatial dynamics of some phases and the evolution of characteristic spatial distributions of strategies, we study the effect of this mechanism on cooperation. The results show that the positive (negative) impact of such interest coalitions on the competitiveness of cooperators (defectors) can be improved as the closeness of interest relationship within coalitions increases. However, this does not mean that a closer coalition can absolutely increase the overall level of cooperation in a more complex four-strategy system. This is related to the transformation from CCs (coalitional cooperators) to TDs (traditional defectors) due to CCs' breaking of the encirclement formed by CDs (coalitional defectors) at a low synergy coefficient, as well as the invasion of TCs (traditional cooperators) to CCs at the boundary separating CCs, TCs and TDs at a high synergy coefficient.

Dynamic bundles to detect the spatiotemporal characteristics and impact factors of ecosystem services in northern China

Understanding the spatiotemporal distribution of multiple ecosystem services (ESs) and their complex internal relationships is crucial for regional collaborative sustainable development. The lack of research on the temporal dynamics of multiple ESs and their internal relationships limits the effective management of ecosystem services. Based on spatial patterns and temporal dynamics, we mapped the changes in five key ESs and assessed the internal relationships over 1324 counties in northern China from 2000 to 2018. The spatial differences in ES relationships were clustered into four distinct ES bundles, and we quantified the driving force of spatiotemporal pattern changes in ES bundles. Our results showed that the relationships among ESs changed with time. From 2000 to 2018, the ES bundle pattern changed mainly in the east. The relationship of some counties changed from the trade-off between provisioning and regulating ESs to synergy, while the others changed from low synergy to high synergy. The identification of impact factors of the service cluster pattern showed that the dominant force factor for improving ecosystem service synergy in northern China is the initial condition, and the contribution of human land management and economic development is approximately 11.0% in the high-level synergy bundles and greater than 20.0% in other bundles. By addressing the spatiotemporal change in ES bundles, we clearly identified the direction and strength of the ES response to ecosystem management and provided a basis for large-scale land management evaluation and effective information for future policy making in northern China and other areas with similar natural conditions.

Economia de custos de transação e indicações geográficas: uma análise sistemática da literatura

Abstract: Transaction Cost Economics (TCE) is one of the most applied economic theories to studies of agrifood chains, especially for presenting approaches that analyze the role of institutions in the relationship between organizations, making it completely adherent to the concept of Coordination, vital in chain management. Agro-industrial chains have continuously experienced mechanisms to reduce information asymmetry between producer and final consumer, one of these mechanisms being Geographical Indications (GIs), certifications of origin based on geographic location. This work aims to identify the state-of-the-art of TCE in studies related to GIs, identifying how the topics related to theory are approached and whether or not there are literature gaps in this regard. A systematic literature review was made in two substantial scientific databases using Methodi Ordinatio. The results demonstrate a certain homogeneity of studies, which focuses on Coordination and Governance, as well as a low synergy between the themes. Future studies could enrich the academic literature by contemplating an opposite path to this homogeneousness, either by a) exploring how TCE can explain the development of GIs; b) investigating the opportunism between producers and association members; or c) studying the limited rationality of the links downstream the chain.

Coronary Artery Bypass Graft Surgery Brings Better Benefits to Heart Failure Hospitalization for Patients with Severe Coronary Artery Disease and Reduced Ejection Fraction.

Objectives: We compared the outcomes between percutaneous coronary intervention (PCI) and coronary artery bypass graft surgery (CABG) for revascularization in patients with reduced ejection fraction (EF) and severe coronary artery disease (CAD). Methods: Between February 2006 and February 2020, a total of 797 patients received coronary angiograms due to left ventricular EF ≤ 40% at our hospital. After excluding diagnoses of dilated cardiomyopathy, valvular heart disease, prior CABG, acute ST-segment myocardial infarction, and CAD with low Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score (≤22), 181 patients with severe coronary artery disease (CAD) with SYNTAX score >22 underwent CABG or PCI for revascularization. Vascular characteristics as well as echocardiographic data were compared between CABG (n = 58) and PCI (n = 123) groups. Results: A younger age (62 ± 9.0 vs. 66 ± 12.1; p = 0.016), higher new EuroSCORE II (8.6 ± 7.3 vs. 3.2 ± 2.0; p < 0.001), and higher SYNTAX score (40.5 ± 9.8 vs. 35.4 ± 8.3; p < 0.001) were noted in the CABG group compared to those in the PCI group. The CABG group had a significantly higher cardiovascular mortality rate at 1-year (19.6% vs. 5.0%, p = 0.005) and 3-year (25.0% vs. 11.4%, p = 0.027) follow-ups but a lower incidence of heart failure (HF) hospitalization at 1-year (11.1% vs. 28.2%, p = 0.023) and 3-year (3.6% vs. 42.5%, p = 0.001) follow-ups compared to those of the PCI group. Conclusions: Compared with PCI, revascularization with CABG was related to a lower incidence of HF hospitalization but a worse survival outcome in patients with severe CAD and reduced EF. CABG-associated reduction in HF hospitalization was more notable when SYNTAX score ≥33.

Local Knowledge Base and Entrepreneurial Opportunities in Regions: A Configurational Perspective

According to the central hypothesis of the knowledge spillover theory of entrepreneurship – the more knowledge is produced in a region, the more entrepreneurial opportunities are available in it. Recent research extended the theory further, showing that the level of entrepreneurial activities, depends on the configuration of the local knowledge base not only on its size. This paper is aimed at discovering which knowledge profiles are more (and which less) supportive of creating entrepreneurial opportunities. It is motivated by disagreements and conflicting evidence on fundamental matters across all three frequently used dimensions - the type of knowledge source that contributes to new knowledge within a region (i.e., universities or private incumbent firms); the presence/absence of a dominant source of new knowledge within a region (i.e., an anchor tenant); and the specialization/diversity of technological knowledge that is created within a region. We analyze data from 33 regions using statistics on patent filings between 2011 and 2015 and a number of created startups in these regions. Using fuzzy-set Qualitative Comparative Analysis (fsQCA) we confirm that a region’s potential for knowledge spillovers, and, thus, entrepreneurial activities, depends on the configuration of the local knowledge base, specifying what configurations are antecedent to creating more entrepreneurial opportunities. Our analysis also shows low synergy from the simultaneous presence of knowledge created by universities and industry in a given area, as these two are, under some conditions, substituting each other in stimulating knowledge-intensive entrepreneurship at the local level. Third, we show that the specialization/diversity of technological knowledge that is created within a region does not play an important role in creating a high number of entrepreneurial opportunities. These findings bring a new perspective and contribute to settling down some of the lasting debates, opening opportunities for further research and rethinking policy measures.

Multi-Scenario Simulation and Trade-Off Analysis of Ecological Service Value in the Manas River Basin Based on Land Use Optimization in China.

Rapid socio-economic development has had a significant impact on land use/cover (LULC) changes, which bring great pressure to the ecological environment. LULC changes affect ecosystem services by altering the structure and function of ecosystems. It is of great significance to reveal the internal relationship between LULC changes and ecosystem service value (ESV) for the protection and restoration of ecological environments. In this study, based on the spatial and temporal evolution of ecological service values in the Manas River basin from 1980 to 2020 and considering ecological and economic benefits, we coupled the gray multi-objective optimization model (GMOP) and patch-generating land-use simulation (PLUS) model (GMOP–PLUS model) to optimize the LULC structure under three scenarios (a natural development scenario, ND; ecological priority development scenario, (EPD); and balanced ecological and economic development scenario, EED) in 2030, and analyzed the trade-offs and synergies in the relationships among the four services. We found that from 1980 to 2020, farmland and construction land expanded 2017.90 km2 and 254.27 km2, respectively, whereas the areas of grassland and unused land decreased by 1617.38 km2 and 755.86 km2, respectively. By 2030, the trend of LULC changes will be stable under the ND scenario, the area of ecological land will increase by 327.42 km2 under the EPD scenario, and the area of construction land will increase most under the EED scenario, reaching 65.01 km2. From 1980 to 2020, the ESV exhibited an upward trend in the basin. In 2030, the ESV will increase by 7.18%, 6.54%, and 6.04% under the EPD, EED, and ND scenarios, respectively. The clustering of the four services is obvious in the desert area and around the water system with “low–low synergy” and “high–high synergy”; the plain area and mountainous area are mainly “high–low trade-off” and “low–high trade-off” relationships. This paper provides a scientific reference for coordinating economic development and ecological protection in the basin. It also provides a new technical approach to address the planning of land resources in the basin.

How to achieve synergy between carbon dioxide mitigation and air pollution control? Evidence from China

• Explores the CO 2 mitigation and air pollution control synergy degree (CASD) in China. • Explores the factors that influence CASD from multiple perspectives. • The CASD was low in general, with obvious spatial differences. • Higher levels of urbanization and innovation can help increase the CASD. Mitigating carbon dioxide (CO 2 ) emission while controlling air pollution is a critical challenge. However, few studies have explored how to achieve synergy between them from a spatiotemporal perspective. In this study, we constructed index system for CO 2 mitigation and air pollution control performances based on China's 30 provinces. Then, we calculated the CO 2 mitigation and air pollution control synergy degree (CASD) of each province from 2005 to 2018 using a synergy model, and based on its output, we further analyzed the spatiotemporal evolution of CASD at national, regional and local levels. Finally, we identified the key factors that affect CASD and their spatial spillover effects. We found that the CASD was low (no synergy or low synergy) and fluctuated from 2005 to 2018. CASD showed significant spatial variation: the high values appeared mainly in the southern region, and the northeastern region had the worst synergy. Furthermore, the CASD is influenced by many factors, including urbanization, industry, economy, energy, innovation and neighboring areas, driving temporal patterns and regional differences. Therefore, transdepartment and transregional synergistic governance should be implemented. Our findings provide policy references for central and local government to achieve this synergy and thereby support efforts to achieve sustainable development.

Correlation and synergy analysis of urban economy–energy–environment system—A case study of Beijing

AbstractThe coordination of economy, energy, and environment plays an important role for cities seeking green transformation and sustainable development. However, poor information and equivocal data are what often face the related analysis. In this paper, the correlation and synergy of the urban economy–energy–environment system are analyzed. First, the Grey relational analysis and entropy weight method are combined and introduced to analyze the correlation degree in the indicator level and the subsystem level of the 3E system. Then, the concepts of ordinal parameter and comprehensive correlation degree are introduced, to evaluate the ordering degree of subsystems and the synergy degree of compound systems. Finally, the data of Beijing from 2008 to 2017 are used for empirical study. Results suggest that a fluctuating tendency of low synergy or none synergy is observed in the Beijing 3E system. Furthermore, the improvement of the energy subsystem displays dominant effects on the coordinated development of compound systems, and the technological innovation and structural optimization in industries could help to improve the Beijing economy–energy–environment system.

Topology optimization of the manifold microchannels with triple-objective functions

Microchannel is helpful for cooling the microelectronic devices with high heat flux. In this study, topology optimization method with three objective functions (pumping power, bottom wall mean temperature and temperature uniformity) is adopted to optimize the structure of a manifold microchannel. The field synergy principle is used to evaluate the optimized structures. Several single-objective, bi-objective, and triple-objective function problems are numerically studied. It is found that the obtained structures with better cooling performance always present low synergy angle, in consistent with the field synergy principle. The optimized structures perform better than conventional microchannel with ribs. Effects of inlet velocity, thermal diffusivity ratio and heat flux at the bottom wall are also investigated. The topology optimization method with triple-objective functions is effective to improve the performance of manifold microchannels.

Retaining the learning professional: A survival study on workplace learning in professional service firms

AbstractLowering professional turnover is of paramount importance for professional service firms, as with each professional, crucial proprietary knowledge leaves the firm. Based on the need to retain this crucial knowledge in the firm, this study explores whether factors that drive learning at work also mitigate professionals' turnover behavior. Building on insights from both workplace learning and turnover research, this study follows 96 professional auditors across a period of 5 years to determine how drivers for workplace learning at the organizational, the social interaction, and the individual level relate to turnover behavior. Through survival analysis, we find that those auditors who experience a supportive learning climate at the organizational level were less likely to leave their firm and profession, while those who score high on individual‐level reflection were more likely to leave their firm and profession. We also found that professionals scoring high on reflection leave more quickly when they perceive to work in an unsupportive learning climate—when they experience low synergy across workplace learning levels. Especially observable behaviors, such as providing help and feedback, discussing errors, and building trust, made a significant difference. This study adds to extant research in three principal ways: exploring actual turnover behavior, approaching turnover behavior through a lens of workplace learning, and analyzing interactions between individual‐, social‐ and organizational‐level learning. The findings of this study lead to specific insights for HRD practice.

Stability of Action and Kinesthetic Perception in Parkinson's Disease.

We present a review of action and perception stability within the theoretical framework based on the idea of control with spatial referent coordinates for the effectors at a number of hierarchical levels. Stability of salient variables is ensured by synergies, neurophysiological structures that act in multi-dimensional spaces of elemental variables and limit variance to the uncontrolled manifold during action and iso-perceptual manifold during perception. Patients with Parkinson’s disease show impaired synergic control reflected in poor stability (low synergy indices) and poor agility (low indices of anticipatory synergy adjustments prior to planned quick actions). They also show impaired perception across modalities, including kinesthetic perception. We suggest that poor stability at the level of referent coordinates can be the dominant factor leading to poor stability of percepts.

Active mechanisms controlling morphodynamics of a coastal barrier: Ilha Comprida, Brazil

Abstract The Cananeia-Iguape lagoon-estuarine system, where the Ilha Comprida barrier (IC) is located, is one of the most dynamic coastal areas on the southeastern Brazilian coast. IC island is a 63 km-long barrier and it is limited by the Icapara inlet to the north, and the Cananeia inlet to the south. This system has been affected by intense changes in its morphology since the opening of the Valo Grande artificial channel in 1852 A.D., connecting the nearby Ribeira de Iguape river to the Mar Pequeno lagoon. In this context of anthropogenic disturbance on the coastal systems, the objective of this study is to understand the active mechanisms, both natural and anthropogenic, controlling the morphological changes of the northeastern portion of the IC, from monthly as well as centenary timescales. We analyzed successional addition and erosion of beach ridges using a multi-temporal dataset obtained by Optically Stimulated Luminescence, aerial photos (1962 and 2000), satellite images (1980-2016) and GNSS surveys (2015-2017). The results were compared to climatic (rainfall and waves) data. Northeastward migration rates of the IC ranged from 15.5 m/y, on the GNSS surveys, to 154 m/y, calculated based on OSL rates. Changes on rates on the northeastward inlet migration barrier are related to anthropogenic interference, mainly the Valo Grande opening and climate changes. Sediment accumulation occurred mainly during the summer on the baymouth spits. This depositional scheme is consistent with the highest values of Ribeira de Iguape river flow and the low synergy of waves coming from the South. By contrast, the retrogradation of the coastline occurs in the winter, when the wave power is stronger than in the summer. This seasonal configuration is controlled both by the bidirectional longshore drift and by the fluvial discharge.