Search

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 (DT) at the park-width distance, the maximum DT, 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. [ABSTRACT FROM AUTHOR]

Over the last two decades, macroecology - the analysis of large-scale, multi-species ecological patterns and processes - has established itself as a major line of biological research. Analyses of statistical links between environmental variables and biotic responses have long and successfully been employed as a main approach, but new developments are due to be utilized. Scanning the horizon of macroecology, we identified four challenges that will probably play a major role in the future. We support our claims by examples and bibliographic analyses. 1) Integrating the past into macroecological analyses, e.g. by using paleontological or phylogenetic information or by applying methods from historical biogeography, will sharpen our understanding of the underlying reasons for contemporary patterns. 2) Explicit consideration of the local processes that lead to the observed larger-scale patterns is necessary to understand the fine-grain variability found in nature, and will enable better prediction of future patterns (e.g. under environmental change conditions). 3) Macroecology is dependent on large-scale, high quality data from a broad spectrum of taxa and regions. More available data sources need to be tapped and new, small-grain large-extent data need to be collected. 4) Although macroecology already lead to mainstreaming cutting-edge statistical analysis techniques, we find that more sophisticated methods are needed to account for the biases inherent to sampling at large scale. Bayesian methods may be particularly suitable to address these challenges. To continue the vigorous development of the macroecological research agenda, it is time to address these challenges and to avoid becoming too complacent with current achievements. [ABSTRACT FROM AUTHOR]