Carsten M. Buchmann

Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Simple or complicated agent-based models? A complicated issue

Agent-based models (ABMs) are increasingly recognized as valuable tools in modelling human-environmental systems, but challenges and critics remain. One pressing challenge in the era of Big Data and given the flexibility of representation afforded by ABMs, is identifying the appropriate level of complicatedness in model structure for representing and investigating complex real-world systems. In this paper, we differentiate the concepts of complexity (model behaviour) and complicatedness (model structure), and illustrate the non-linear relationship between them. We then systematically evaluate the trade-offs between simple (often theoretical) models and complicated (often empirically-grounded) models. We propose using pattern-oriented modelling, stepwise approaches, and modular design to guide modellers in reaching an appropriate level of model complicatedness. While ABMs should be constructed as simple as possible but as complicated as necessary to address the predefined research questions, we also warn modellers of the pitfalls and risks of building mid-level models mixing stylized and empirical components. We clarify the terms complexity and complicated in the context of ABM.We comprehensively discuss pros and cons of simple and complicated ABMs.We identify challenges and pitfalls for simple and complicated ABMs.We provide recommendations and good practices for dealing with complicatedness.

The bigger, the better? The influence of urban green space design on cooling effects for residential areas

It is well known that the cooling effect of an urban green space extends into its surroundings, cooling the immediate environment and mitigating urban heat problems. However, the effects of size, shape, and type of an urban green space on cooling remain uncertain. The objectives of our study were to quantify and compare the strength of the cooling effects of urban parks and forests, to determine how far the cooling effects extend into the surrounding residential environment, and to better understand how temperature gradients are driven by physical characteristics of the green space and the surroundings. Mobile air temperature measurements were performed in 62 urban parks and forests in the city of Leipzig, Germany, in the summer of 2013. Three indicators of cooling were calculated: the change in temperature (ΔT) at the park-width distance, the maximum ΔT, and the cooling distance. The relationships of these variables to the physical characteristics of the green spaces and their surroundings were examined in multiple regression models. Analyzing all three indicators revealed that cooling effects were greater in urban forests than in parks. Cooling increased with increasing size but in a different manner for forests and parks, whereas the influence of shape was the same for forests and parks. Generally, the characteristics of the green spaces were more important than the characteristics of the residential surroundings. These findings have the potential to assist in better planning and designing of urban green spaces to increase their cooling effects.

Linking urban sprawl and income segregation : findings from a stylized agent-based model

Urban sprawl and income segregation are two undesired urban patterns that occur during urban development. Empirical studies show that income level and inequality are positively correlated with urban sprawl and income segregation, respectively. However, the relationship between urban sprawl and income segregation is not only rarely investigated but also shows ambiguous empirical results when it is. Therefore, in this study, we built a stylized agent-based model with individual behaviours based on Alonso’s bid rent theory and ran simulations with different combinations of income level and income inequality. We measured the overall emergent patterns with indicators for urban sprawl and income segregation. The model confirms the established positive correlations between income level and urban sprawl and between income inequality and segregation. Furthermore, the model shows a negative correlation between urban sprawl and income segregation under free market conditions. The model indicates that without any policy implementation, a city will either suffer from urban sprawl or income segregation. Thus, this study serves as a starting point to study the effects of different urban planning policies on these two urban problems.