Energy and Carbon Management Systems

This article examines an important class of information system that serves as the foundation for corporate energy and greenhouse gas (GHG) accounting: energy and carbon management systems (ECMS). Investors, regulators, customers, and employees increasingly demand that organizations provide information about their organizational energy use and GHG emissions. However, there is little transparency about how organizations use ECMS to meet such demands. To shed light on ECMS implementation and application, we collected extensive qualitative interview data from two service‐sector organizations: one that uses a spreadsheet‐based ECMS and another that implemented an ECMS provided by a third‐party vendor. Our analysis of collected data revealed numerous challenges in the areas of business processes, managerial capabilities, data capture and integration, and data quality. Though our study is built on only two organizations and requires confirmation in large‐sample surveys, we provide several recommendations for organizations regarding ECMS. We also provide suggestions for future studies to build on our tentative results.     

Thermal responses of an insect subjected to temperature variations

Temperature responses of the cockroach, Blaberus craniifer, to rapid changes of ambient temperature (T_a) have been studied. In static conditions at T_a = 27°C the body-to-ambient temperature difference was only 0.10 ± 0.07°C. Two test situations were used, either a ramp increase of T_a from 27 to 31°C (0.1°C/min) or “step” changes from 27 to 28°C and back (0.5°C/min). In both cases body temperature closely followed Newtonian model, the body time constants measured in various conditions being very similar: 543 ± 99 sec in ramp tests, 550 ± 68 sec and 542 ± 124 sec in rising and falling step tests respectively. It is concluded that in spite of evident differences between the cockroach and an inert solid, the Newtonian model adequately represents the thermal responses of this insect to moderate changes in ambient temperature.     

Tropicality and abjection: What do we really mean by “Neglected Tropical Diseases”?

Neglected tropical diseases are defined operationally as diseases that prevail in “tropical” regions and are under‐researched, under‐funded, and under‐treated compared with their disease burden. By analysing the adjectives “tropical” and “neglected,” I expose and interrogate the discourses within which the term “neglected tropical disease” derives its meaning. First, I argue that the term “tropical” conjures the notion of “tropicality,” a form of Othering which erroneously explains the disease‐prevalence of “tropical” regions by reference to environmental determinism, rather than colonialism and neocolonialism. Second, I examine the way in which this Othering enables the abjection of tropical regions and their peoples, leading to neglect. I recommend that the term “neglected tropical diseases” be more carefully contextualised within health scholarship, education, and policy.     

Dark diversity in Amazonian stream fish communities: What factors determine species absence along environmental gradients?

1. Species distribution models often fail to predict observed patterns of species diversity, and this is because some species within a regional pool that are tolerant of conditions at a given location may nevertheless be absent from the local community. These missing species have been termed “dark diversity”. In the present study, we investigated which factors explain dark diversity among fish assemblages in Amazonian streams.
2. We sampled 71 streams in areas with different types of land use within two river basins and estimated dark diversity from patterns of species co-occurrence, using Beals’ index, along environmental gradients. From this procedure, taxa are designated as dark diversity components when they are absent from a given stream, but often co-occur with the local species at other streams, indicating similar ecological requirements. We used generalised linear models both to determine whether environmental or landscape variables, connectivity, instream environmental heterogeneity or some combination of these factors explained dark diversity of fishes, and to evaluate whether ecomorphology is associated with the extent to which a species contributes to dark diversity and which specific traits contribute the most to explaining variation in dark diversity.
3. Mean local diversity exceeded observed dark diversity. The magnitude of dark diversity was directly associated with the proportion of secondary forest in the immediate catchment and with the index of proximity to anthropogenic impact. Species that have high affinity for environments with higher current velocity, low swimming ability and that capture food mainly on the surface contributed more to dark diversity, which suggests that swimming ability, habitat preference and aspects related to diet are key predictors of the probability that a given species will be present at locations with suitable habitat.
4. Our findings reinforce the idea that dark diversity results from interactions between species traits and environmental factors, including anthropogenic impacts. Understanding the interplay among environmental factors and species traits that contribute to dark diversity provides targets for improved ecosystem restoration and sustainability of native species assemblages.

     

Decoupling of impact factors reveals the response of German winter wheat yields to climatic changes

Yield development of agricultural crops over time is not merely the result of genetic and agronomic factors, but also the outcome of a complex interaction between climatic and site‐specific soil conditions. However, the influence of past climatic changes on yield trends remains unclear, particularly under consideration of different soil conditions. In this study, we determine the effects of single agrometeorological factors on the evolution of German winter wheat yields between 1958 and 2015 from 298 published nitrogen (N)‐fertilization experiments. For this purpose, we separate climatic from genetic and agronomic yield effects using linear mixed effect models and estimate the climatic influence based on a coefficient of determination for these models. We found earlier occurrence of wheat growth stages, and shortened development phases except for the phase of stem elongation. Agrometeorological factors are defined as climate covariates related to the growth of winter wheat. Our results indicate a general and strong effect of agroclimatic changes on yield development, in particular due to increasing mean temperatures and heat stress events during the grain‐filling period. Except for heat stress days with more than 31°C, yields at sites with higher yield potential were less prone to adverse weather effects than at sites with lower yield potential. Our data furthermore reveal that a potential yield levelling, as found for many West‐European countries, predominantly occurred at sites with relatively low yield potential and about one decade earlier (mid‐1980s) compared to averaged yield data for the whole of Germany. Interestingly, effects related to high precipitation events were less relevant than temperature‐related effects and became relevant particularly during the vegetative growth phase. Overall, this study emphasizes the sensitivity of yield productivity to past climatic conditions, under consideration of regional differences, and underlines the necessity of finding adaptation strategies for food production under ongoing and expected climate change.     

Arthropod community composition along snowmelt gradients in snowbeds in the Snowy Mountains of south‐eastern Australia

Environmental gradients drive variation in community composition across a range of spatial scales. In alpine regions, areas of long‐lasting snow (‘snow patches’) create snowmelt gradients that drive considerable change in vegetation structure and composition over small spatial scales. This study examined whether there is parallel variation in arthropod communities using snowmelt gradients in the Australian Alps. Mites (Acarina) were the most common arthropods in snow patches, followed by springtails while, among the insects, the orders Hymenoptera (primarily Formicidae), Diptera, Coleoptera (primarily Carabidae) and Hemiptera (primarily Cicadellidae) dominated. Along the snowmelt gradient, arthropod assemblages changed from having equal proportions of predators and herbivores in early‐melting zones to being predator‐dominated in late‐melting zones, particularly early in the growing season. This followed a transition in vegetation cover and composition and was driven by higher numbers of predacious carabid beetles in later‐melting zones. Overall, however, our results suggest that snowbed arthropod communities in the Australian alpine zone are more sensitive to short‐term effects, such as time since snowmelt, than to differences in vegetation structure and composition or long‐term patterns of snowmelt. Continued advancement of snowmelt timing due to warmer spring temperatures is therefore likely to have more impact on the seasonality of snowbed arthropod communities than on the overall community composition.     

A process‐based metacommunity framework linking local and regional scale community ecology

The metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: (1) density‐independent responses to abiotic conditions, (2) density‐dependent biotic interactions and (3) dispersal. Stochasticity is incorporated in the demographic realisation of each of these processes. We formalise this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning and stability within metacommunities.     

Between a rock and a hard place: adaptive sensing and site‐specific dispersal

Environmental variability can lead to dispersal: why stay put if it is better elsewhere? Without clues about local conditions, the optimal strategy is often to disperse a set fraction of offspring. Many habitats contain environmentally differing sub‐habitats. Is it adaptive for individuals to sense in which sub‐habitat they find themselves, using environmental clues, and respond plastically by altering the dispersal rates? This appears to be done by some plants which produce dimorphic seeds with differential dispersal properties in response to ambient temperature. Here we develop a mathematical model to show, that in highly variable environments, not only does sensing promote plasticity of dispersal morph ratio, individuals who can sense their sub‐habitat and respond in this way have an adaptive advantage over those who cannot. With a rise in environmental variability due to climate change, our understanding of how natural populations persist and respond to changes has become crucially important.