Due to impacts of albedo on climate change, benefits of afforestation/reforestation regimes are under debate. In this paper we investigate how to incorporate albedo changes in a carbon accounting tool to show the net effect of land use change on the climate. Using a study area in southern Europe, albedo and carbon sequestration modelling results are linked to determine the combined radiative forcing balance.

Many studies have done econometric estimates of how climate alters crop yields and or land rents in an effort to gain information on potential effects of climate change. However, an important related factor, the atmospheric carbon dioxide (CO2) concentration, and in fact a driver of climate change is ignored. This means the prior econometric estimates are biased as they infer what will happen under climate change from observations in the recent past, but without consideration of CO2 effects.

Climate change is predicted to have widespread impacts on freshwater lake and reservoir nutrient budgets by altering both hypolimnetic hypoxia and runoff, which will in turn alter the magnitude of internal and external nutrient loads. To examine the effects of these potential climate scenarios on nitrogen (N) and phosphorus (P) budgets, we conducted a whole-catchment manipulation of hypolimnetic oxygen conditions and external loads to Falling Creek Reservoir (FCR), an old, eutrophic reservoir in a reforested catchment with a history of agricultural land use.

The relationship between sustainable urban development and environmental sustainability is crucial to every strategy of urban transformation, renewal and regeneration. In particular, urban regeneration entails programmes of urban transformation that involve the rehabilitation of existing parts of a city, re-use previously built-up area and abandoned buildings, and redevelop blighted urban spaces to increase urban sustainability.

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data.

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 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.