Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy

Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.     

Pontine A5 region modulation of the cardiorespiratory response evoked from the midbrain dorsolateral periaqueductal grey

Journal of Physiology and Biochemistry - Connections between the midbrain dorsolateral periaqueductal grey (dlPAG) and the pontine A5 region have been shown. The stimulation of both regions evokes...     

Agriculture erases climate constraints on soil nematode communities across large spatial scales

Anthropogenic conversion of natural to agricultural land reduces aboveground biodiversity. Yet, the overall consequences of land‐use changes on belowground biodiversity at large scales remain insufficiently explored. Furthermore, the effects of conversion on different organism groups are usually determined at the taxonomic level, while an integrated investigation that includes functional and phylogenetic levels is rare and absent for belowground organisms. Here, we studied the Earth's most abundant metazoa—nematodes—to examine the effects of conversion from natural to agricultural habitats on soil biodiversity across a large spatial scale. To this aim, we investigated the diversity and composition of nematode communities at the taxonomic, functional, and phylogenetic level in 16 assemblage pairs (32 sites in total with 16 in each habitat type) in mainland China. While the overall alpha and beta diversity did not differ between natural and agricultural systems, all three alpha diversity facets decreased with latitude in natural habitats. Both alpha and beta diversity levels were driven by climatic differences in natural habitats, while none of the diversity levels changed in agricultural systems. This indicates that land conversion affects soil biodiversity in a geographically dependent manner and that agriculture could erase climatic constraints on soil biodiversity at such a scale. Additionally, the functional composition of nematode communities was more dissimilar in agricultural than in natural habitats, while the phylogenetic composition was more similar, indicating that changes among different biodiversity facets are asynchronous. Our study deepens the understanding of land‐use effects on soil nematode diversity across large spatial scales. Moreover, the detected asynchrony of taxonomic, functional, and phylogenetic diversity highlights the necessity to monitor multiple facets of soil biodiversity in ecological studies such as those investigating environmental changes.     

A novel circulating tamiami mammarenavirus shows potential for zoonotic spillover

A detailed understanding of the mechanisms underlying the capacity of a virus to break the species barrier is crucial for pathogen surveillance and control. New World (NW) mammarenaviruses constitute a diverse group of rodent-borne pathogens that includes several causative agents of severe viral hemorrhagic fever in humans. The ability of the NW mammarenaviral attachment glycoprotein (GP) to utilize human transferrin receptor 1 (hTfR1) as a primary entry receptor plays a key role in dictating zoonotic potential. The recent isolation of Tacaribe and lymphocytic choriominingitis mammarenaviruses from host-seeking ticks provided evidence for the presence of mammarenaviruses in arthropods, which are established vectors for numerous other viral pathogens. Here, using next generation sequencing to search for other mammarenaviruses in ticks, we identified a novel replication-competent strain of the NW mammarenavirus Tamiami (TAMV-FL), which we found capable of utilizing hTfR1 to enter mammalian cells. During isolation through serial passaging in mammalian immunocompetent cells, the quasispecies of TAMV-FL acquired and enriched mutations leading to the amino acid changes N151K and D156N, within GP. Cell entry studies revealed that both substitutions, N151K and D156N, increased dependence of the virus on hTfR1 and binding to heparan sulfate proteoglycans. Moreover, we show that the substituted residues likely map to the sterically constrained trimeric axis of GP, and facilitate viral fusion at a lower pH, resulting in viral egress from later endosomal compartments. In summary, we identify and characterize a naturally occurring TAMV strain (TAMV-FL) within ticks that is able to utilize hTfR1. The TAMV-FL significantly diverged from previous TAMV isolates, demonstrating that TAMV quasispecies exhibit striking genetic plasticity that may facilitate zoonotic spillover and rapid adaptation to new hosts.     

Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama

In tropical regions, rainfall gradients often explain the abundance and distribution of plant species. For example, many tree and liana species adapted to seasonal drought are more abundant and diverse in seasonally-dry forests, characterized by long periods of seasonal water deficit. Mean annual precipitation (MAP) is commonly used to explain plant distributions across climate gradients. However, the relationship between MAP and plant distribution is often weak, raising the question of whether other seasonal precipitation patterns better explain plant distributions in seasonally-dry forests. In this study, we examine the relationship between liana abundance and multiple metrics of seasonal and annual rainfall distribution to test the hypothesis that liana density and diversity increase with increasing seasonal drought along a rainfall gradient across the isthmus of Panama. We found that a normalized seasonality index, which combines MAP and the variability of monthly rainfall throughout the year, was a significant predictor of both liana density and species richness, whereas MAP, rainfall seasonality and the mean dry season precipitation (MDP) were far weaker predictors. The strong response of lianas to the normalized seasonality index indicates that, in addition to the total annual amount of rainfall, how rainfall is distributed throughout the year is an important determinant of the hydrological conditions that favor liana proliferation. Our findings imply that changes in annual rainfall and rainfall seasonality will determine the future distribution and abundance of lianas. Models that aim to predict future plant diversity, distribution, and abundance may need to move beyond MAP to a more detailed understanding of rainfall variability at sub-annual timescales.     

PEATmoss (Physcomitrella Expression Atlas Tool): a unified gene expression atlas for the model plant Physcomitrella patens

Physcomitrella patens is a bryophyte model plant that is often used to study plant evolution and development. Its resources are of great importance for comparative genomics and evo‐devo approaches. However, expression data from Physcomitrella patens were so far generated using different gene annotation versions and three different platforms: CombiMatrix and NimbleGen expression microarrays and RNA sequencing. The currently available P. patens expression data are distributed across three tools with different visualization methods to access the data. Here, we introduce an interactive expression atlas, Physcomitrella Expression Atlas Tool (PEATmoss), that unifies publicly available expression data for P. patens and provides multiple visualization methods to query the data in a single web‐based tool. Moreover, PEATmoss includes 35 expression experiments not previously available in any other expression atlas. To facilitate gene expression queries across different gene annotation versions, and to access P. patens annotations and related resources, a lookup database and web tool linked to PEATmoss was implemented. PEATmoss can be accessed at https://peatmoss.online.uni-marburg.de     

Efficient deletion of LoxP-flanked selectable marker genes from the genome of transgenic pigs by an engineered Cre recombinase

Genetically modified (GM) pigs hold great promises for pig genetic improvement, human health and life science. When GM pigs are produced, selectable marker genes (SMGs) are usually introduced into their genomes for host cell or animal recognition. However, the SMGs that remain in GM pigs might have multiple side effects. To avoid the possible side effects caused by the SMGs, they should be removed from the genome of GM pigs before their commercialization. The Cre recombinase is commonly used to delete the LoxP sites-flanked SMGs from the genome of GM animals. Although SMG-free GM pigs have been generated by Cre-mediated recombination, more efficient and cost-effective approaches are essential for the commercialization of SMG-free GM pigs. In this article we describe the production of a recombinant Cre protein containing a cell-penetrating and a nuclear localization signal peptide in one construct. This engineered Cre enzyme can efficiently excise the LoxP-flanked SMGs in cultured fibroblasts isolated from a transgenic pig, which then can be used as nuclear donor cells to generate live SMG-free GM pigs harboring a desired transgene by somatic cell nuclear transfer. This study describes an efficient and far-less costly method for production of SMG-free GM pigs.

     

Species specificity and intraspecific variation in the chemical profiles of Heliconius butterflies across a large geographic range

In many animals, mate choice is important for the maintenance of reproductive isolation between species. Traits important for mate choice and behavioral isolation are predicted to be under strong stabilizing selection within species; however, such traits can also exhibit variation at the population level driven by neutral and adaptive evolutionary processes. Here, we describe patterns of divergence among androconial and genital chemical profiles at inter‐ and intraspecific levels in mimetic Heliconius butterflies. Most variation in chemical bouquets was found between species, but there were also quantitative differences at the population level. We found a strong correlation between interspecific chemical and genetic divergence, but this correlation varied in intraspecific comparisons. We identified “indicator” compounds characteristic of particular species that included compounds already known to elicit a behavioral response, suggesting an approach for identification of candidate compounds for future behavioral studies in novel systems. Overall, the strong signal of species identity suggests a role for these compounds in species recognition, but with additional potentially neutral variation at the population level.     

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.     

Trophic level and basal resource use of soil animals are hardly affected by local plant associations in abandoned arable land

Plants provide resources and shape the habitat of soil organisms thereby affecting the composition and functioning of soil communities. Effects of plants on soil communities are largely taxon‐dependent, but how different functional groups of herbaceous plants affect trophic niches of individual animal species in soil needs further investigation. Here, we studied the use of basal resources and trophic levels of dominating soil meso‐ and macrofauna using stable isotope ratios of carbon and nitrogen in arable fallow systems 3 and 14–16 years after abandonment. Animals were sampled from the rhizosphere of three plant species of different functional groups: a legume (Medicaco sativa), a nonlegume herb (Taraxacum officinale), and a grass (Bromus sterilis). We found virtually no consistent effects of plant identity on stable isotope composition of soil animals and on thirteen isotopic metrics that reflect general food‐web structure. However, in old fallows, the carbon isotope composition of some predatory macrofauna taxa had shifted closer to that of co‐occurring plants, which was particularly evident for Lasius, an aphid‐associated ant genus. Trophic levels and trophic‐chain lengths in food webs were similar across plant species and fallow ages. Overall, the results suggest that variations in local plant diversity of grassland communities may little affect the basal resources and the trophic level of prey consumed by individual species of meso‐ and macrofauna belowground. By contrast, successional changes in grassland communities are associated with shifts in the trophic niches of certain species, reflecting establishment of trophic interactions with time, which shapes the functioning and stability of soil food webs.