We study an evolutionary algorithm used for optimizing in a chaotically changing dynamic environment. The corresponding chaotic non–stationary fitness landscape can be characterized by quantifiers of the underlying dynamics–generating system. We give experimental results about how these quantifiers, namely the Lyapunov exponents, together with the environmental change period of the landscape in...

In a greening Arctic, Iceland stands out as an area with very high increases in the AVHRR Normalized Difference Vegetation Index (NDVI, 1982–2010). We investigated the possible sources of this anomalous greening in Iceland’s dynamic landscape, analyzing changes due to volcanism and warming temperatures, and the effects of agricultural and industrial land use changes. The analysis showed the inc...

Repeated sequences of digitised and georeferenced historical aerial photography provide a powerful means of understanding landscape change over time scales beyond conventional ecological monitoring, especially in remote areas. We use this method to develop spatially explicit models of vegetation change at five sites in the Australian monsoon tropics, and assess the goodness-of-fit of the model ...

Land use change is one of the most important anthropogenic factors affecting terrestrial ecosystems, causing habitat loss, fragmentation, and interactions with other components of global change, such as biological invasions of non-native species. In southern California, population growth and economic expansion are the primary drivers of land use change, and the population is expected to double ...

Landscape metrics are useful tools in investigating spatial structure and in describing the heterogeneity of landscapes, but are sensitive to grain size. Thus, it is necessary to determine the appropriate grain size before researching landscape patterns. However, there have been few large-scale investigations in high-precision research about the effect of grain size on landscape patterns, espec...