Global variation in diurnal asymmetry in temperature, cloud cover, specific humidity and precipitation and its association with leaf area index

This is the final version. Available on open access from Wiley via the DOI in this recordThe impacts of the changing climate on the biological world vary across latitudes, habitats and spatial scales. By contrast, the time of day at which these changes are occurring has received relatively little attention. As biologically significant organismal activities often occur at particular times of day, any asymmetry in the rate of change between the daytime and night‐time will skew the climatic pressures placed on them, and this could have profound impacts on the natural world. Here we determine global spatial variation in the difference in the mean annual rate at which near‐surface daytime maximum and night‐time minimum temperatures and mean daytime and mean night‐time cloud cover, specific humidity and precipitation have changed over land. For the years 1983–2017, we derived hourly climate data and assigned each hour as occurring during daylight or darkness. In regions that showed warming asymmetry of >0.5°C (equivalent to mean surface temperature warming during the 20th century) we investigated corresponding changes in cloud cover, specific humidity and precipitation. We then examined the proportional change in leaf area index (LAI) as one potential biological response to diel warming asymmetry. We demonstrate that where night‐time temperatures increased by >0.5°C more than daytime temperatures, cloud cover, specific humidity and precipitation increased. Conversely, where daytime temperatures increased by >0.5°C more than night‐time temperatures, cloud cover, specific humidity and precipitation decreased. Driven primarily by increased cloud cover resulting in a dampening of daytime temperatures, over twice the area of land has experienced night‐time warming by >0.25°C more than daytime warming, and has become wetter, with important consequences for plant phenology and species interactions. Conversely, greater daytime relative to night‐time warming is associated with hotter, drier conditions, increasing species vulnerability to heat stress and water budgets. This was demonstrated by a divergent response of LAI to warming asymmetry.Natural Environment Research Council (NERC)Cornwall Counci

A new system to classify global climate zones based on plant physiology and using high temporal resolution climate data

This is the final version. Available on open access from Wiley via the DOI in this recordAim: Climate classification systems (CCSs) can be used to predict how species’ distributions might be altered by climate change and to increase the reliability of these estimates is an important goal in biogeographical research. We produce an objective, global climate classification system (CCS) at high temporal resolution based on plant physiology as a robust way to predict how climate change may impact terrestrial biomes. Location: Global. Taxon: Plantae. Methods: We construct ten climate variables that capture the physiological processes that determine plant distributions and use cluster analysis to present a new global CCS which accounts for variation in these aspects of climate. We use Kappa statistics to compare the distribution of climate zones in a five- and six-cluster CCS constructed using the physiology variables to the popular Köppen-Geiger and Köppen-Trewartha CCSs, respectively, and find good correlation in both cases. Results: Our CCS highlights ten climate zones for plants. We show that clustering of the physiologically relevant variables reproduces known, present-day patterns of vegetation but also indicates important areas where zone assignment in our physiological CCSs is different to that of the Köppen systems. Main conclusions: The existing Köppen CCSs do not entirely reflect the physiological processes that determine plant distributions. Predictions of climate-driven changes in plant distributions may thus be unreliable in areas where zone assignment by clustering of physiologically relevant variables is different to that of the Köppen systems. Both the physiological relevance and temporal resolution of climate variables used to construct CCSs should be considered in order to predict reliably how climate change may alter plant distributions and to support an appropriate global response to conserve plant biodiversity for the future.Natural Environment Research Council (NERC

Diel niche variation in mammals associated with expanded trait space

This is the final version. Available on open access from Nature Research via the DOI in this record. Data availability: The trait data were extracted principally from the Handbook of the Mammals of the World (Volumes 1–3 & 5–958), PHYLACINE 1.23, Cooke et al.9 and EltonTraits 1.069. The following three datasets are available on figshare (https://doi.org/10.6084/m9.figshare.13623014): Supplementary Data 1, Taxonomic composition of functional hotspots in Fig. 1; Supplementary Data 2, Trait data containing both missing values and imputed data, with data sources; Supplementary Data 3, 25 datasets containing imputed data. Phylogenetic data was downloaded from PHYLACINE 1.23, and are available on the Dryad Digital Data Repository (https://doi.org/10.5061/dryad.bp26v20). Fig. 1 was produced by 2-dimensional ordination of raw trait data. Figs. 2–3 are two-dimensional representations of five-dimensional trait space generated from raw trait data.Code availability: Code for the production of Fig. 1 was adapted from Díaz et al.28 (ftp://pbil.univ-lyon1.fr/pub/datasets/dray/Diaz_Nature/). Code used in the analysis was based on cited packages in the R Statistical Environment59 (Supplementary Table 4).Mammalian life shows huge diversity, but most groups remain nocturnal in their activity pattern. A key unresolved question is whether mammal species that have diversified into different diel niches occupy unique regions of functional trait space. For 5,104 extant mammals we show here that daytime-active species (cathemeral or diurnal) evolved trait combinations along different gradients from those of nocturnal and crepuscular species. Hypervolumes of five major functional traits (body mass, litter size, diet, foraging strata, habitat breadth) reveal that 30% of diurnal trait space is unique, compared to 55% of nocturnal trait space. Almost half of trait space (44%) of species with apparently obligate diel niches is shared with those that can switch, suggesting that more species than currently realised may be somewhat flexible in their activity patterns. Increasingly, conservation measures have focused on protecting functionally unique species; for mammals, protecting functional distinctiveness requires a focus across diel nichesNatural Environment Research Council (NERC

Combining qualitative and quantitative methodology to assess prospects for novel crops in a warming climate

This is the final version. Available on open access from Elsevier via the DOI in this recordContext: Climate change will alter the global distribution of climatically suitable space for many species, including agricultural crops. In some locations, warmer temperatures may offer opportunities to grow novel, high value crops, but non-climatic factors also inform agricultural decision-making. These non-climatic factors can be difficult to quantify and incorporate into suitability assessments, particularly for uncertain futures. Objective: To demonstrate how qualitative and quantitative techniques can be combined to assess crop suitability with consideration for climatic and non-climatic factors. Methods: We carried out a horizon scanning exercise that used Delphi methodology to identify possible novel crops for a region in south-west England. We show how the results of the expert panel assessment could be combined with a crop suitability model that only considered climate to identify the best crops to grow in the region. Results and conclusions: Whilst improving climate and crop models will enhance the ability to identify environmental constraints to growing novel crops, we propose horizon scanning as a useful tool to understand constraints on crop suitability that are beyond the parameterisation of these models and that may affect agricultural decisions. Significance: A similar combination of qualitative and quantitative approaches to assessing crop suitability could be used to identify potential novel crops in other regions and to support more holistic assessments of crop suitability in a changing world.Natural Environment Research Council (NERC)Cornwall Counci

Accounting for inter-annual variability alters long-term estimates of climate suitability

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record Aim: Species respond to environmental conditions and so reliable assessments of climate suitability are important for predicting how climate change could alter their distributions. Long-term average climate data are often used to evaluate the climate suitability of an area, but in these aggregated climate datasets, inter-annual variability is lost. Due to non-linearity in species’ biological responses to climate, estimates of long-term climate suitability from average climate data may be biased and so differ from estimates derived from the average annual suitability over the same period (average response). We investigate the extent to which such differences manifest in a regional assessment of climate suitability for 255 plant species across two 17-year time periods. Location: Cornwall in South-West England provides a case study. Taxon: Plantae. Methods: We run a simple mechanistic climate suitability model and derive quantitative estimates of climate suitability for 1984–2000 and 2001–2017. For each period, we run the model using climate data representing average monthly values for that period. We then run the model for each year using monthly climate data for that year and average the annual suitability scores across each period (average response). We compare estimates of climate suitability from these two approaches. Results: Average climate data gave higher estimates of suitability than the average response, suggesting bias against years of poor suitability in temporally aggregated climate datasets. Differences between suitability estimates were larger in areas of high climate variability and correlated with species’ environmental requirements, being larger for species with small thermal niches and narrow ranges of precipitation tolerance. Main Conclusions: Incorporating inter-annual variability into climate suitability assessments or understanding the extent to which average climate data might obscure this variance will be important to predict reliably the impacts of climate change on species distributions and should be considered when using mechanistic species distribution models.Cornwall CouncilNatural Environment Research Counci

Learning the subtle dance: the experience of therapists who deliver mentalisation-based therapy for borderline personality disorder

Objectives: This study aimed to understand therapists’ lived experiences of delivering mentalisation-based therapy (MBT), including their experiences of service user change. / Method: One-to-one semi-structured interviews or focus groups were conducted with 14 MBT therapists and analysed using interpretative phenomenological analysis (IPA). / Results: Four superordinate themes were identified: 1) experiencing the challenges and complexities of being with service users during MBT; 2) being on a journey of discovery and change; 3) being an MBT therapist: a new way of working and developing a new therapeutic identity; and 4) being a therapist in the group: seeing it all come together / Conclusion: Our findings highlight the complexity, challenges and individualised experience of working therapeutically with service users with a diagnosis of BPD. The study provides a perspective of service use change that is enriched by idiosyncrasies within the therapeutic encounter. We conclude with a consideration of implications for MBT research and clinical practice

Forecasting future crop suitability with microclimate data

This is the final version. Available on open access from Elsevier via the DOI in this recordContext: Against a background of unprecedented climate change, humanity faces the challenge of how to increase global food production without compromising the natural environment. Crop suitability models can indicate the best locations to grow different crops and, in doing so, support efficient use of land to leave space for, or share space with, nature. However, challenges in downscaling the climate data needed to drive these models to make predictions for the future has meant that they are often run using national or regional climate projections. At finer spatial scales, variation in climate conditions can have a substantial influence on yield and so the continued use of coarse resolution climate data risks maladaptive agricultural decisions. Opportunities to grow novel crops, for which knowledge of local variation in microclimate may be critical, may be missed. Objective: We demonstrate how microclimate information can be acquired for a region and used to run a mechanistic crop suitability model under present day and possible future climate scenarios. Methods: We use microclimate modelling techniques to generate 100 m spatial resolution climate datasets for the south-west of the UK for present day (2012–2017) and predicted future (2042–2047) time periods. We use these data to run the mechanistic crop model WOrld FOod STudies (WOFOST) for 56 crop varieties, which returns information on maximum crop yields for each planting month. Results and conclusions: Over short distances, we find that the highest attainable yields vary substantially and discuss how these differences mean that field-level assessments of climate suitability could support land-use decisions, enabling food production whilst protecting biodiversity. Significance: We provide code for running WOFOST in the WofostR R package, thus enabling integration with microclimate models and meaning that our methodology could be applied anywhere in the world. As such, we make available to anyone the tools to predict climate suitability for crops at high spatial resolution for both present day and possible future climate scenarios.Natural Environment Research Council (NERC)European Regional Development Fund (ERDF)Cornwall CouncilCouncil for the Isles of Scill

Endocrine responses to sport-related brain injury in female athletes: a narrative review and a call for action

Sport-related brain injury (SRBI) occurs when a blow to the head causes the brain to move back and forth in the skull, and can lead to neuroendocrine dysfunction. Research has shown that males and females experience and recover from SRBI differently, yet most of what is known regarding diagnosis, treatment, and recovery of SRBI is based on male normative data even though females meet or exceed incidence numbers of SRBIs compared to those of males. Females also have been known to have worse outcomes and a greater number of symptoms following SRBI than males. Research is limited as to why females have worse outcomes, but sex hormones have been suggested as a potential reason. SRBI may cause a dysregulation of the hypothalamic–pituitary–gonadal (HPG) axis, which is responsible for regulating the sex hormones estrogen and progesterone. Initial research has shown that SRBI may suppress estrogen and progesterone, and the concentration of these sex hormones could be indicative of injury severity and recovery trajectory. This review discusses the sex-specific differences in SRBI and also the future direction of research that is needed in order to identify the repercussions of SRBIs for female athletes, which will eventually lead to better clinical treatment, sideline care, and recovery profiles

Which patients with heart failure should receive specialist palliative care?

AIMS: We investigated which patients with heart failure (HF) should receive specialist palliative care (SPC) by first creating a definition of need for SPC in patients hospitalised with HF using patient-reported outcome measures (PROMs) and then testing this definition using the outcome of days alive and out of hospital (DAOH). We also evaluated which baseline variables predicted need for SPC and whether those with this need received SPC. METHODS AND RESULTS: PROMs assessing quality of life (QoL), symptoms, and mood were administered at baseline and every 4 months. SPC need was defined as persistently severe impairment of any PROM without improvement (or severe impairment immediately preceding death). We then tested whether need for SPC, so defined, was reflected in DAOH, a measure which combines length of stay, days of hospital re-admission, and days lost due to death. Of 272 patients recruited, 74 (27%) met the definition of SPC needs. These patients lived one third fewer DAOH than those without SPC need (and less than a quarter of QoL-adjusted DAOH). A Kansas City Cardiomyopathy Questionnaire (KCCQ) summary score of <29 identified patients who subsequently had SPC needs (area under receiver operating characteristic curve 0.78). Twenty-four per cent of patients with SPC needs actually received SPC (n = 18). CONCLUSIONS: A quarter of patients hospitalised with HF had a need for SPC and were identified by a low KCCQ score on admission. Those with SPC need spent many fewer DAOH and their DAOH were of significantly worse quality. Very few patients with SPC needs accessed SPC services

Bio-Benchmarking of Electronic Nose Sensors

BACKGROUND:Electronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna. METHODOLOGY:Here we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs). PRINCIPAL FINDINGS:Compared with a fly's odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs. CONCLUSIONS:The comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system