When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment

Prospective life cycle assessment (LCA) needs to deal with the large epistemological uncertainty about the future to support more robust future environmental impact assessments of technologies. This study proposes a novel approach that systematically changes the background processes in a prospective LCA based on scenarios of an integrated assessment model (IAM), the IMAGE model. Consistent worldwide scenarios from IMAGE are evaluated in the life cycle inventory using ecoinvent v3.3. To test the approach, only the electricity sector was changed in a prospective LCA of an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using six baseline and mitigation climate scenarios until 2050. This case study shows that changes in the electricity background can be very important for the environmental impacts of EV. Also, the approach demonstrates that the relative environmental performance of EV and ICEV over time is more complex and multifaceted than previously assumed. Uncertainty due to future developments manifests in different impacts depending on the product (EV or ICEV), the impact category, and the scenario and year considered. More robust prospective LCAs can be achieved, particularly for emerging technologies, by expanding this approach to other economic sectors beyond electricity background changes and mobility applications as well as by including uncertainty and changes in foreground parameters. A more systematic and structured composition of future inventory databases driven by IAM scenarios helps to acknowledge epistemological uncertainty and to increase the temporal consistency of foreground and background systems in LCAs of emerging technologies.     

Land-use changes assessed by overlay or mosaic methods: Which method is best for management planning?

Environmental planning must determine management practices for a given territory based on the landscape processes that have occurred over time and their consequences. Therefore, environmental planning decisions must be based on strong empirical evidence that can be easily understood by all involved parties. Several studies have highlighted the methodological deficiencies that occur when obtaining and interpreting such issues, particularly in heterogeneous landscapes with complex interactions. In this paper, we evaluated two methodological approaches that are used in management planning, land use/cover change (LUCC) and mosaic change (MC) to compare their effectiveness and suitability for supporting decision-making. We applied these methods to the coastal landscape of São Sebastião Island, Brazil, which has undergone many changes in the last 50 years. For two years, land use/cover maps were produced using GIS and assessed according to changes in landscape elements (LUCC) and boundaries (MC). Overall, the LUCC failed to identify sets with similar structural heterogeneities in the landscape. However, the LUCC is easier for stakeholders to understand and apply than the MC. The MC method better presented the evolution of the relationship between the landscape elements and heterogeneity.     

Introduction: A perspective from the humanities-science boundary

The articles in this special issue range across such influences on climate as solar emissions, orbital precession, atmosphere, oceans, and precipitation, and generally approach, each in some context, human implications of these phenomena. The common underlying theme of all of the papers is the effect the phenomena have on radiation balance as measured by global average temperature. This introductory paper undertakes a formulation of radiation balance theory that makes it serviceable to students of regional science. The objective is to go beyond inference of cause and effect by correlation to causal accounts of cause and effect through regional climatic and cultural processes. This is accomplished primarily by revisualization of the energy system with regions as dependent spatiotemporal entities, and temporally through a protocol for regional episode definition.This special issue ofHuman Ecology consists of the American Anthropological Association Invited Symposium on Global Climate Change.     

A neutron activation technique for manganese measurements in humans

Manganese (Mn) is an essential element for humans, animals, and plants and is required for growth, development, and maintenance of health. Studies show that Mn metabolism is similar to that of iron, therefore, increased Mn levels in humans could interfere with the absorption of dietary iron leading to anemia. Also, excess exposure to Mn dust, leads to nervous system disorders similar to Parkinson's disease. Higher exposure to Mn is essentially related to industrial pollution. Thus, there is a benefit in developing a clean non-invasive technique for monitoring such increased levels of Mn in order to understand the risk of disease and development of appropriate treatments.To this end, the feasibility of Mn measurements with their minimum detection limits (MDL) has been reported earlier from the McMaster group. This work presents improvement to Mn assessment using an upgraded system and optimized times of irradiation and counting for induced gamma activity of Mn. The technique utilizes the high proton current Tandetron accelerator producing neutrons via the ⁷Li(p,n)⁷Be reaction at McMaster University and an array of nine NaI (Tl) detectors in a 4π geometry for delayed counting of gamma rays. The neutron irradiation of a set of phantoms was performed with protocols having different proton energy, current and time of irradiation. The improved MDLs estimated using the upgraded set up and constrained timings are reported as 0.67 μgMn/gCa for 2.3 MeV protons and 0.71 μgMn/gCa for 2.0 MeV protons. These are a factor of about 2.3 times better than previous measurements done at McMaster University using the in vivo set-up. Also, because of lower dose-equivalent and a relatively close MDL, the combination of: 2.0 MeV; 300 μA; 3 min protocol is recommended as compared to 2.3 MeV; 400 μA; 45 s protocol for further measurements of Mn in vivo.     

LiGAPS-Beef,a mechanistic model to explore potential and feed-limited beef production 1: model description and illustration

The expected increase in the global demand for livestock products calls for insight in the scope to increase actual production levels across the world. This insight can be obtained by using theoretical concepts of production ecology. These concepts distinguish three production levels for livestock: potential (i.e. theoretical maximum) production, which is defined by genotype and climate only; feed-limited production, which is limited by feed quantity and quality; and actual production. The difference between the potential or limited production and the actual production is the yield gap. The objective of this paper, the first in a series of three, is to present a mechanistic, dynamic model simulating potential and feed-limited production for beef cattle, which can be used to assess yield gaps. A novelty of this model, named LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle), is the identification of the defining factors (genotype and climate) and limiting factors (feed quality and available feed quantity) for cattle growth by integrating sub-models on thermoregulation, feed intake and digestion, and energy and protein utilisation. Growth of beef cattle is simulated at the animal and herd level. The model is designed to be applicable to different beef production systems across the world. Main model inputs are breed-specific parameters, daily weather data, information about housing, and data on feed quality and quantity. Main model outputs are live weight gain, feed intake and feed efficiency (FE) at the animal and herd level. Here, the model is presented, and its use is illustrated for Charolais and Brahman × Shorthorn cattle in France and Australia. Potential and feed-limited production were assessed successfully, and we show that FE of herds is highest for breeds most adapted to the local climate conditions. LiGAPS-Beef also identified the factors that define and limit growth and production of cattle. Hence, we argue the model has scope to be used as a tool for the assessment and analysis of yield gaps in beef production systems.     

Messy eaters: Swabbing prey DNA from the exterior of inconspicuous predators when foraging cannot be observed

Complex coevolutionary relationships among competitors, predators, and prey have shaped taxa diversity, life history strategies, and even the avian migratory patterns we see today. Consequently, accurate documentation of prey selection is often critical for understanding these ecological and evolutionary processes. Conventional diet study methods lack the ability to document the diet of inconspicuous or difficult‐to‐study predators, such as those with large home ranges and those that move vast distances over short amounts of time, leaving gaps in our knowledge of trophic interactions in many systems. Migratory raptors represent one such group of predators where detailed diet studies have been logistically challenging. To address knowledge gaps in the foraging ecology of migrant raptors and provide a broadly applicable tool for the study of enigmatic predators, we developed a minimally invasive method to collect dietary information by swabbing beaks and talons of raptors to collect trace prey DNA. Using previously published COI primers, we were able to isolate and reference gene sequences in an open‐access barcode database to identify prey to species. This method creates a novel avenue to use trace molecular evidence to study prey selection of migrating raptors and will ultimately lead to a better understanding of raptor migration ecology. In addition, this technique has broad applicability and can be used with any wildlife species where even trace amounts of prey debris remain on the exterior of the predator after feeding.     

Central Place Foraging in Nonpatchy Habitats

This paper deal with a model of optimal foraging in a habitat with arbitrary food distribution. It takes into account an arbitrary risk cost related to the distance to the animal's nest. Food acquisition and risk cost are accounted for in common units of fitness. The resulting problem is solved in the context of Calculus of Variations. The optimal duration of absence from the nest and the optimal spatial allocation of foraging time are obtained: the optimal strategy leads to separate the habitat into a region to exploit and a region to ignore. The definition of these two distinct regions depends on the relative importance of risk and food availability. With realistic risk costs, the resulting strategy indicates a highly selective behaviour when far from the nest, as observed in field studies. The model is also extended to take account of the need of returning to the nest to guard it or to feed the young.