Vulnerability to climate change impacts is defined by three dimensions of human–environmental systems, such as exposure, sensitivity, and adaptive capacity. Climate change affects various aspects of human–environmental interactions, such as water stress, food security, human health, and well-being at multiple spatial and temporal scales. However, the existing protocols of vulnerability assessment fail to incorporate the multitude of scales associated with climate change processes.

Agriculture and animal husbandry are important contributors to global emissions of greenhouse (GHG) and acidifying gases. Moreover, they contribute to water pollution and to consumption of non-renewable natural resources such as land and energy. The Life Cycle Assessment (LCA) methodology allows evaluation of the environmental impact of a process from the production of inputs to the final product and to assess simultaneously several environmental impact categories among which GHG emissions, acidification, eutrophication, land use and energy use.

Summary The relationship between woody fuel consumption and fireline intensity was assessed using data collected at controlled fires and wildfires in south-western Western Australia, central Victoria and south-eastern New South Wales. The combined dataset consisted of fires in a range of dry eucalypt forests. Fire behaviour varied from slow, self-extinguishing prescribed burns to intense, fast—moving fires burning under conditions of extreme fire danger. Fireline intensity ranged from 50 kW m⁻ˡ to

AIM: Habitat fragmentation threatens species’ persistence by increasing subpopulation isolation and vulnerability to stochastic events, and its impacts are expected to worsen under climate change. By reconnecting isolated fragments, habitat corridors should dampen the synergistic impacts of habitat and climate change on population viability. Choosing which fragments to reconnect is typically informed by past and current environmental conditions. However, habitat and climate are dynamic and change over time.

Artificial neural networks (ANN) are nonlinear models widely investigated in hydrology due to their properties of universal approximation and parsimony. Their performance during the training phase is very good, and their ability to generalize can be improved by using regularization methods such as early stopping and cross-validation. In our research, two kinds of generic models are implemented: the feed-forward model and the recurrent model.

Non-Urbanised Areas (NUAs) are part of agricultural and green infrastructures that provide ecosystem services. Their role is fundamental for the minimization of urban pollution and adaptation to climate change. Like all natural ecosystems, NUAs are endangered by urban sprawl. The regulation of sprawl is a key issue for land-use planning. We propose a land use suitability strategy model to orient Land Uses of NUAs, based on integration of Land Cover Analysis (LCA) and Fragmentation Analysis (FA). With LCA the percentage of evapotranspiring surface is defined for each land use.

In light of impending water and arable land shortages, population growth and climate change, it is more important than ever to examine how forest tree domestication can be accelerated to sustainably meet future demands for wood, biomass, paper, fuel and biomaterials. Because of long breeding cycles, tree domestication cannot be rapidly achieved through traditional genetic improvement methods alone. Integrating modern genetic and genomic techniques with conventional breeding will expedite tree domestication.

In response to climate change, research is being undertaken to understand the on-farm greenhouse gas emissions and water use for agricultural systems and investigate options farmers may have for mitigating or offsetting emissions. In the present study, a life cycle assessment framework is used to determine on-farm GHG emissions and water use, and the overall 'cradle-to-farm gate' GHG emissions and water use attributed to beef production.

Cities are facing considerable challenges resulting from imminent climate change impacts. Urban planning to minimise adverse impacts of climate change at the city level can establish a climate-resilient city. Mitigation strategies to reduce CO₂ emissions would lead to a climate-friendly city. Integrating climate change adaptation and mitigation into sustainable city planning should not be merely added as a single level of sustainable city planning, but requires a wide range of multi-level cooperation.

By the year 2050, agriculture will have to provide the food and nutrition requirements of some 9 billion people. Moreover, to maintain that level of productivity indefinitely it must do so using environmentally sustainable production systems. This task will be profoundly complicated by the effects of climate change, increasing competition for water resources and loss of productive lands.

The urban heat island effect poses a challenge in several cities, and may affect human and ecosystem health. It was proven that relatively small urban conglomerations in mid-latitudes, such as the case study region of Rostock, have undergone a considerable effect recently, noticeable particularly in the warm season. Due to climatic changes, these effects are expected to alter in intensity and/or frequency. This was investigated using a model that focuses on interactions between land use and surface temperatures and on specific air conditions in cities.

Five main drivers of population declines have been identified: climate change, habitat degradation, invasive alien species (IAS), overexploitation and pollution. Each of these drivers interacts with the others, and also with the intrinsic traits of individual species, to determine species’ distribution and range dynamics.