Academic mobility for field work, research dissemination and global outreach is increasingly recognized as an important contributor to the overall environmental footprint of research institutions. Student mobility, while less studied, also contributes to universities' environmental footprint. Université de Montréal (UdeM) is the largest university in Montréal, Canada. It has a research budget of 450M$, employs 1426 full-time professors, and has a total student population of 33 125 undergraduate and 12 505 graduate students. To assess the footprint of academic mobility at UdeM, we surveyed the research community (n=703; including professors, research professionals and graduate students) about their travel habits. We also measured the contribution from travel undertaken by sports teams and international students as well as students engaged in study abroad and internships programs using data provided by the university. While the average distance travelled for work and research purposes by the UdeM community is around 8525 km/person, professors travel more than 33 000 km/person per year. We also estimated that the 5785 international students or students enroled in study abroad programs travel annually around 12 600 km/person. UdeM's per capita annual travel-related C and N footprints vary, with international students generating for example 3.85 T CO 2 and 0.53 kg N while professors generate 10.76 T CO 2 and 2.19 kg N. Air travel emissions are the main contributors to these footprints. We provide insights into the distribution of travel-related environmental footprint within the university, the main reasons for travelling, the most frequent destinations, and the factors preventing researchers from reducing their travel-related environmental impact.

As human activities increasingly threaten the ecosystems on which they depend, one of the main questions our societies are facing is related to the resilience – seen as a necessary element of sustainability – of social–ecological systems (SESs). SESs are composed of many heterogeneous elements including human actors such as institutions and resource users, and natural components such as land patches, animal species, etc. The numerous relationships between these different entities shape complex, dynamic networks of social–ecological interdependencies. Once described as networks, SESs can be analysed using a variety of network metrics, which may potentially help to better quantify and evaluate the resilience of SESs to external or internal perturbations. In this paper, we provide a broad overview of the latest progress in network theory as applied to SESs and discuss how network metrics may be used to assess the sustainability of an SES.

ABSTRACT. Landscapes are complex systems. Landscape dynamics are the result of multiple interacting biophysical and socioeconomic processes that are linked across a broad range of spatial, temporal, and organizational scales. Understanding and describing landscape dynamics poses enormous challenges and demands the use of new multiscale approaches to modeling. In this synthesis article, we present three regional systems-i.e., a forest system, a marine system, and an agricultural systemand describe how hybrid, bottom-up modeling of these systems can be used to represent linkages across scales and between subsystems. Through the use of these three examples, we describe how modeling can be used to simulate emergent system responses to different conservation policy and management scenarios from the bottom up, thereby increasing our understanding of important drivers and feedback loops within a landscape. The first case study involves the use of an individual-based modeling approach to simulate the effects of forest harvesting on the movement patterns of large mammals in Canada's boreal forest and the resulting emergent population dynamics. This model is being used to inform forest harvesting and management guidelines. The second case study combines individual and agent-based approaches to simulate the dynamics of individual boats and whales in a marine park. This model is being used to inform decision-makers on how to mitigate the impacts of maritime traffic on whales in the Saint Lawrence Estuary in eastern Canada. The third example is a case study of biodiversity conservation efforts on the Eyre Peninsula, South Australia. In this example, the social-ecological system is represented as a complex network of interacting components. Methods of network analysis can be used to explore the emergent responses of the system to changes in the network structure or configuration, thus informing managers about the resilience of the system. These three examples illustrate how bottom-up modeling approaches may contribute to a new landscape science based on scenario building, to find solutions that meet the multiple objectives of integrated resource management in social-ecological systems.

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