Coral reef ecosystems are slowly reaching their physical ecosystem boundaries. Urgent action is required by reducing carbon emissions, halt degradation, and initiate restoration and conservation efforts of coral reef ecosystems, and bring coral reefs back to a safe ecosystem operating space. This research study uses a multidisciplinary approach that aims to understand the dynamic behavior of (sub)tropical social-ecological coral reef ecosystems in the Anthropocene and provide insights for future interventions. The study combines literature reviews, expert interviews, cognitive mapping, and system dynamics modeling to determine the variables, relations, and dynamics within coral reef ecosystems, and draw implications for future intervention. The insights are combined in a qualitative and quantitative stock-flow model, through which dynamics of anthropogenic stressors effects on coral reef behavior are examined, and implications for future intervention in social-ecological coral reef ecosystems are drawn. The findings highlight the importance of considering multiple stressors, understanding social-ecological feedbacks, and taking into account as well global as local stressors to restore coral reefs in the face of anthropogenic stressors in the Anthropocene.

In recent decades, logistic markets havebeen changing. Ecommerce is growing steadily, and the recent Covid19 pandemicgave an extra boost to that. Besides, customers are seeking more flexibility inthe logistic services. Parcel delivery is changing, yet this leads to variousnegative externalities including congestion, air, and noise pollution. Theseeffects let companies seek innovative solutions for their parcel transport. Oneof these innovations is ’crowdshipping’,parcel delivery done by the crowd instead of conventional delivery companies.By making use of existing passenger transport rather than a speciallydispatched driver to ship parcels, parcel shipping should be economically and environmentallymore sustainable. Crowdshipping is a service that has shown potential in pilotsand smallscale researches. However, strategic analyses of the impact ofcrowdshipping on all actors in the transport systems are still lacking. Thegoal of this research is to explore the interactions between travellers and parcelshipments in various strategic crowdshipping contexts and assess their impacton transport use. To achieve that, the following main research question will beanswered: ’How could sustainable crowdshipping impact freightand passenger transport use?’. A simulation model is built using agentbased modelling to explorebehaviour and simulate possible effects. This model consists of interactionsbetween four agents in the system; the customers,crowdshipping platform, travellers and occasional carriers. First, thecustomers place their orders at the platform. When travellers make their trip,they could consider carrying a parcel along their way. They notice their plannedtrip to the platform, which will calculate the optimal parcels for them. Thetravellers could opt for one of the parcels and turn into occasional carriers.The impact of crowdshipping is assessed by calculating the detour theoccasional carriers travel to deliver their parcels. Other outcomes are the providedcompensation and percentage of matched parcels, to determine the viability ofthe platform. The spatial demarcation of the simulation is most of the provinceof South Holland in the Netherlands. In this study area, 2.3 million peoplereside who order over 220,000 parcels each day. Furthermore, 4.1 million tripsare made daily by car and bicycle. Taking the willingness of both customers andtravellers into account, 13,000 parcels and 750,000 traveller trips enter themodel. Four experiments are performed to inspect system behaviour in variouscontexts. The results show that implementing crowdshipping in this study areacould be viable. The average provided compensation is lower than the priceconsignors currently pay for conventional delivery. Besides, the delivery degreeseems acceptable to get a decent level of service. Through crowdshipping, thetravelled distance in the passenger transport system will increase because ofthe detours taken by occasional carriers. This increase subsequently leads to adecrease in freight transport distance through a decreased demand inconventional parcel demand. However, the passenger transport increase exceeds thefreight transport decrease. The crowdshipping platform could limit the takendetours by making strategic choices in their implementation. This might be atthe expense of their delivery degree. It is advised for the public authority toset boundaries for the platform and stimulate strategic matching choices basedon these possible externalities. When interpreting these results, cautionshould be taken. The approach has some shortcomings regarding the spatialdistribution of detours, costs of platform’s viabilityand first leg distances for parcel transport. Furthermore, limitations could befound in the assumptions made for the simulation model. This includes theabstraction that travellers do not deviate from their planned trips andmodalities, and travellers could only carry one parcel. Another simplificationis made in the matching strategy by the platform which might have led tosuboptimal drivers for the parcels. Other limitations are caused by flawed datause. Travellers’ and customers’willingness could therefore be unreliable. Also, pedestrian and publictransport travellers are not considered due to data deficiency. Furtherresearch could be done in three ways within this field of study. First, moredata can be gathered to solve the abovementioned limitations. This includesdata on preferential routes for occasional carriers and willingness data fortravellers in all modes. Secondly, other conceptual choices can be made tooptimise the detours per parcel with forecasted travellers, or to conceptualisethe collaboration between conventional and crowdshipping delivery. Finally,research can be done to study intervention methods and corresponding legalpossibilities for the public administration to limit travellers’ detours.

This research clarifies the relations between the growing e-commerce sector and the logistic sector. The last-mile transportation of goods bought via e-commerce is growing, which leads to negative impacts on the environment and mobility. A Causal Loop Diagram (CLD) illustrating the relations is made and a simulation model is build quantifying these relations, for both models System Dynamics (SD) is used. The models are based on literature and data from CBS. Strategies are developed to assess two policy strategies, the use of (unmanned) pick-up points and the use of light electric freight vehicles (LEFV). The growth of e-commerce leads to logistic efficiency at the beginning, but eventually this efficiency growth will stop. Currently their is still logistic efficiency gained, this results in a less steeper growth of the negative impacts. The use of pick-up points is based on the same parameters providing the logistic efficiencies and are a strong long term solution to the growth. Furthermore, using pick-up points increases the rate of successful first time delivery, this results in less needed shipping capacity. Passenger transport is needed to pick-up the package, this effect is not incorporated. The use of LEFV’s reduces the amount of emitted pollution and the amount of road traffic movements. However more vehicles are needed and the traffic movements will only be moved to bicycle lanes. Both strategies are realistic and some logistic service providers are already implementing the strategies.