The problem of scale in predicting biological responses to climate

This is the final version. Available on open access from Wiley via the DOI in this record Many analyses of biological responses to climate rely on gridded climate data derived from weather stations, which differ from the conditions experienced by organisms in at least two respects. First, the microclimate recorded by a weather station is often quite different to that near the ground surface, where many organisms live. Second, the temporal and spatial resolutions of gridded climate datasets derived from weather stations are often too coarse to capture the conditions experienced by organisms. Temporally and spatially coarse data have clear benefits in terms of reduced model size and complexity, but here we argue that coarse-grained data introduce errors that, in biological studies, are too often ignored. However, in contrast to common perception, these errors are not necessarily caused directly by a spatial mismatch between the size of organisms and the scale at which climate data are collected. Rather, errors and biases are primarily due to (i) systematic discrepancies between the climate used in analysis and that experienced by organisms under study and (ii) the non-linearity of most biological responses in combination with differences in climate variance between locations and time periods for which models are fitted and those for which projections are made. We discuss when exactly problems of scale can be expected to arise and highlight the potential to circumvent these by spatially and temporally down-scaling climate. We also suggest ways in which adjustments to deal with issues of scale could be made without the need to run high-resolution models over wide extents.European Regional Development Fund (ERDF

Determination of digestible energy values and fermentabilities of dietary fibre supplements: a European interlaboratory study in vivo

The performance of methods to determine energy conversion factors for dietary fibre (DF) supplements and fermentability (D) values of their non-starch polysaccharides (NSP) was investigated. Heats of combustion, digestible energy (DE) and D values were determined on five DF supplements in five European laboratories on five separate occasions. In each instance the DF supplements were fed to juvenile male VVistar rats at two doses, 50 and 100 g/kg basal diet, for 3 weeks with food and faeces collected in the 3rd week. Among-laboratory variations in heats of combustion (DHC<) were <2%. DE values (kJ/g dry weight) at the upper and lower doses respectively were: 10·4 and 9·9 for a high-methoxyl apple pectin, 9·5 and 9·4 for a sugar-beet DF supplement, 12·2 and 12·7 for soyabean DF supplement, 38 and 4·0 for maize bran, and 0·3 and 0·3 for Solka-floc cellulose. Variations among laboratories, among occasions and among animals were <1, <2 and <2·5 kJ/g respectively. The among-occasion: among-laboratory variance ratio for DE was 0·5, suggesting the method performed equally well in all laboratories. There was no evidence of learning or fatigue in the performance of the method. D values were also independent of dose and at the high and lower doses were: pectin 0·92 and 0·95, sugar-beet NSP 0·68 and 0·68, soyabean NSP 0·86 and 0·88, maize bran 0·17 and 0·18, cellulose 0·07 and 0·06. Among-laboratory variance tended to increase with decreasing fermentability and ranged from 0·03 to 0·18. The DE and D data were not significantly different from a previously proposed relationship DE = 0·7 × DHc × D, where DHc is the heat of combustion of the supplement. We conclude that while the among-laboratory variation in the D of difficult-to-ferment NSP is too large for the reliable prediction of energy value the method for the direct determination of DE is both reproducible and repeatable, that DE is independent of dosage of DF supplement up to 100 g/kg diet, and that it is safe to discriminate between energy values with a precision of 3 kJ/g. The conversion of both DE and D to net metabolizable energy for the purpose of food labelling, tables and databases is describe

Adaptation to climate change: a comparative analysis of modelling methods for heat-related mortality

Background: Multiple methods are employed for modelling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known on the relative sensitivity of impacts to “adaptation uncertainty” (i.e. the inclusion/exclusion of adaptation modelling), relative to using multiple climate models and emissions scenarios. Objectives: (1) Compare the range in projected impacts that arises from using different adaptation modelling methods; (2) compare the range in impacts that arises from adaptation uncertainty to ranges from using multiple climate models and emissions scenarios; (3) recommend modelling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070-2099, for 14 European cities, applying six different methods for modelling adaptation; also with climate projections from five climate models, run under two emissions scenarios to explore the relative effects of climate modelling and emissions uncertainty. Results: The range of the difference (%) in impacts between including and excluding adaptation, irrespective of climate modelling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modelling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modelling. We recommend absolute threshold shifts and reductions in slope

The Climatic Water Balance and Topography Control Spatial Patterns of Atmospheric Demand, Soil Moisture, and Shallow Subsurface Flow

Catchment hydrometeorology and the organization of shallow subsurface flow are key drivers of active contributing areas and streamflow generation. However, understanding how the climatic water balance and complex topography contribute to these processes from hillslope to catchment scales remains difficult. We compared time series of vapor pressure deficits and soil moisture to the climatic water balance and topographic variables across six zero-order catchments in the Lubrecht Experimental Forest (Montana, USA). We then evaluated how local hydrometeorology (volumetric water content and atmospheric vapor pressure deficit) affected the spatial occurrence of shallow subsurface flow. Generalized linear mixed model analysis revealed significant, temporally stable (monthly and seasonal average) patterns of hydrometeorology that can be predicted by the topographic wetness index and the dynamic climatic water deficit (CWD = potential evapotranspiration - actual evapotranspiration). Intracatchment patterns were significantly correlated to the topographic wetness index, while intercatchment patterns were correlated to spatiotemporal variance in the CWD during each time period. Spatial patterns of shallow subsurface flow were related to the hydrometeorological conditions of the site. We observed persistent shallow subsurface flow in convergent hillslope positions, except when a catchment was positioned in locations with high CWDs (low elevations and southerly aspects). Alternatively, we observed persistent subsurface flow across all hillslope positions (even 70-m upslope from the hollow) when catchments were positioned in locations with especially low CWDs (northerly aspects and high elevations). These results highlight the importance of considering the superposition of the catchment-scale climatic water balance and hillslope-scale topography when characterizing hydrometeorology and shallow subsurface flow dynamics.USDA NIFA McIntire Stennis award [233327]; NSF grants [DEB-1457749, DEB-1457720]; NASA applied science program Wildland Fire award [NNH11ZDA001N-FIRES]; NSF EPSCoR through the Montana Institute on Ecosystems6 month embargo; published online: 19 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Nectar, humidity, honey bees (Apis mellifera) and varroa in summer: a theoretical thermofluid analysis of the fate of water vapour from honey ripening and its implications on the control of Varroa destructor

This theoretical thermofluid analysis investigates the relationships between honey production rate, nectar concentration and the parameters of entrance size, nest thermal conductance, brood nest humidity and the temperatures needed for nectar to honey conversion. It quantifies and shows that nest humidity is positively related to the amount, and water content of the nectar being desiccated into honey and negatively with respect to nest thermal conductance and entrance size. It is highly likely that honeybees, in temperate climates and in their natural home, with much smaller thermal conductance and entrance, can achieve higher humidities more easily and more frequently than in man-made hives. As a consequence, it is possible that Varroa destructor, a parasite implicated in the spread of pathogenic viruses and colony collapse, which loses fecundity at absolute humidities of 4.3 kPa (approx. 30 gm−3) and above, is impacted by the more frequent occurrence of higher humidities in these low conductance, small entrance nests. This study provides the theoretical basis for new avenues of research into the control of varroa, via the modification of beekeeping practices to help maintain higher hive humidities

Recent Food Shortage Is Associated with Leprosy Disease in Bangladesh: A Case-Control Study

Although intensive control programs reduced the prevalence of leprosy worldwide, new cases of this infectious disease are still detected in several of the poorest areas of the world. Therefore the disease is known as a disease of poverty. To be able to control the disease it is important to know which aspects of poverty play a role in transmission and acquiring clinical signs of disease. In this study socio-economic circumstances of recently diagnosed leprosy patients were compared with those of a control population in the poverty stricken northwest area of Bangladesh where leprosy is common. A recent period of food shortage was the only socio-economic factor that was found related to leprosy disease in this study and not poverty as such. Food shortage is seasonal and poverty related in northwest Bangladesh, while malnutrition is known to lower immunity and make people more vulnerable to infectious diseases. Therefore it was concluded that malnutrition as an aspect of poverty played an important role in the development of the clinical signs of leprosy. We therefore recommend that nutritional support for high risk groups should be included in leprosy control programmes to reduce risk of disease in areas where leprosy is common

Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health. Keywords: Dietary assessment; Food intake biomarkers; Food metabolome; Metabolomics

A Deletion in the N-Myc Downstream Regulated Gene 1 (NDRG1) Gene in Greyhounds with Polyneuropathy

The polyneuropathy of juvenile Greyhound show dogs shows clinical similarities to the genetically heterogeneous Charcot-Marie-Tooth (CMT) disease in humans. The pedigrees containing affected dogs suggest monogenic autosomal recessive inheritance and all affected dogs trace back to a single male. Here, we studied the neuropathology of this disease and identified a candidate causative mutation. Peripheral nerve biopsies from affected dogs were examined using semi-thin histology, nerve fibre teasing and electron microscopy. A severe chronic progressive mixed polyneuropathy was observed. Seven affected and 17 related control dogs were genotyped on the 50k canine SNP chip. This allowed us to localize the causative mutation to a 19.5 Mb interval on chromosome 13 by homozygosity mapping. The NDRG1 gene is located within this interval and NDRG1 mutations have been shown to cause hereditary motor and sensory neuropathy-Lom in humans (CMT4D). Therefore, we considered NDRG1 a positional and functional candidate gene and performed mutation analysis in affected and control Greyhounds. A 10 bp deletion in canine NDRG1 exon 15 (c.1080_1089delTCGCCTGGAC) was perfectly associated with the polyneuropathy phenotype of Greyhound show dogs. The deletion causes a frame shift (p.Arg361SerfsX60) which alters several amino acids before a stop codon is encountered. A reduced level of NDRG1 transcript could be detected by RT-PCR. Western blot analysis demonstrated an absence of NDRG1 protein in peripheral nerve biopsy of an affected Greyhound. We thus have identified a candidate causative mutation for polyneuropathy in Greyhounds and identified the first genetically characterized canine CMT model which offers an opportunity to gain further insights into the pathobiology and therapy of human NDRG1 associated CMT disease. Selection against this mutation can now be used to eliminate polyneuropathy from Greyhound show dogs