The influence of location on the structure and functioning of private land conservation networks in the Western Cape province of South Africa

Protected areas are an important tool for biodiversity conservation. Statutory protected areas are, however, perceived to currently be insufficient in extent and functioning for achieving conservation goals. Conservation action on privately owned land plays an increasingly vital role in expanding the global conservation estate. Private Land Conservation Areas (PLCAs) exist with internal properties and external contexts and do not occur isolated in space and time. They can thus best be described as linked social-ecological systems. Little comprehensive work has yet been done concerning the structure and functioning of PLCAs. However, an understanding of their emergence, long-term persistence and contribution to conservation is highly relevant. How can PLCAs maintain their identity against disturbances in order to be resilient into the future? Spatial patterns and relationships determine the answer to this question. Geographical location influences the private conservation estate through different drivers, namely biophysical conditions, network connections and membership, as well as socio-economic conditions. I thus used a comparative, spatially explicit and holistic approach to better understand spatial resilience of PLCAs in the Western Cape Province of South Africa as case study region. The approach was based on assessing representative measures for four elements of system identity (being components, relationships, sources of continuity, and sources of innovation). I expected that geographical location and spatial variation in social-ecological factors strongly influence PLCA types, socio-economic interaction networks among protected areas and other stakeholders, contribution to conservation by PLCAs and their ecotourism performance. Information and data for this research were obtained from personal interviews conducted with owners and managers of 70 PLCAs across the province. Additional data were derived via conservation authorities and online tools. My findings show that the identity and resilience of PLCAs are strongly dominated by the influence of spatial location and heterogeneity in factors such as ecological features or socioeconomic context. I was able to verify existing PLCA types, namely game and habitat reserves, which strongly depended on the biophysical context. Visitation rates were influenced by location which determined the adopted corporate model of PLCAs. Clear neighbourhood effects emerged in socioeconomic interaction networks, which further highlighted great potential to enhance collaboration across scales. PLCAs provided a substantial contribution to conservation targets in terms of importance (covering critical biodiversity areas) and urgency (protecting ecosystems of threatened status). My findings will be valuable to highlight opportunities for more effective conservation in the study region, and to advance insights into the spatial resilience of social-ecological systems

A survey on Human Mobility and its applications

Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, traffic engineering, traffic prediction and urban planning. In this survey we review major characteristics of human mobility studies including from trajectory-based studies to studies using graph and network theory. In trajectory-based studies statistical measures such as jump length distribution and radius of gyration are analyzed in order to investigate how people move in their daily life, and if it is possible to model this individual movements and make prediction based on them. Using graph in mobility studies, helps to investigate the dynamic behavior of the system, such as diffusion and flow in the network and makes it easier to estimate how much one part of the network influences another by using metrics like centrality measures. We aim to study population flow in transportation networks using mobility data to derive models and patterns, and to develop new applications in predicting phenomena such as congestion. Human Mobility studies with the new generation of mobility data provided by cellular phone networks, arise new challenges such as data storing, data representation, data analysis and computation complexity. A comparative review of different data types used in current tools and applications of Human Mobility studies leads us to new approaches for dealing with mentioned challenges

The Role of Spatial Interaction in Social Networks

This article addresses the role of spatial interaction in social networks. We analyse empirical data describing a network of leisure contacts and show that the probability to accept a person as a contact scales in distance with similar to d (-aEuro parts per thousand 1.4). Moreover, the analysis reveals that the number of contacts an individual possesses is independent from its spatial location and the spatial distribution of opportunities. This means that individuals living in areas with a low accessibility to other persons (rural areas) exhibit at average the same number of contacts compared to individuals living in areas with high accessibility (urban areas). Low accessibility is thus compensated with a higher background probability to accept other candidates as social contacts. In addition, we propose a model for large-scale social networks involving a spatial and social interaction between individuals. Simulation studies are conducted using a synthetic population based on census data as input. The results show that the model is capable of reproducing the spatial structure, but, however, fails to reproduce other topological characteristics. Both, the analysis of empirical data and the simulation results provide a further evidence that spatial interaction is a crucial aspect of social networks. Yet, it appears that spatial proximity does only explain the spatial structure of a network but has no significant impact on its topology