Conducting robust ecological analyses with climate data

Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. And we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require

Data report: evaluation of shipboard magnetostratigraphy by alternating field demagnetization of discrete samples, Expedition 361, Site U1475

The paleomagnetic shipboard data of International Ocean Discovery Program Site U1475, with a record reaching back to approximately 7 Ma, allowed for the identification of major magnetic polarity chrons and subchrons back to ~3.5 Ma. However, the natural remanent magnetization (NRM) was very weak, and transitional intervals with unclear polarity were as thick as several meters. The midpoints of these transitional intervals were reported in the shipboard results without decimal places because of the poor data quality. To evaluate and possibly refine the shipboard magnetostratigraphy, subsampling was performed across the polarity transitions. Detailed alternating field (AF) demagnetization experiments were conducted on these discrete samples and were complemented by anhysteretic remanent magnetization acquisition measurements and subsequent demagnetization. AF demagnetization data of NRM were analyzed using anchored principal component analysis (PCA) to obtain the characteristic remanent magnetization. These PCA results generally confirm the smoothed signal across polarity transitions at Site U1475. However, the midpoint depths of the top of the Keana Subchron, the Gauss-Matuyama and Matuyama-Brunhes boundaries, and the base of the Olduvai Subchron were adjusted

Interpretable machine learning models for classifying low back pain status using functional physiological variables.

PURPOSE:To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting. METHODS:Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3. RESULTS:Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak [Formula: see text]  = 0.047) in model 1, the deltoid muscle (peak [Formula: see text] =  0.052) in model 2, and the iliocostalis muscle (peak [Formula: see text] =  0.16) in model 3. CONCLUSION:The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk. These slides can be retrieved under Electronic Supplementary Material

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

A Chi-Square Test for the Association and Timing of Tree Ring-Daily Weather Relationships: A New Technique for Dendroclimatology

This study introduces a new analytical procedure based on the chi-square (x²) statistic to evaluate tree- ring weather relationships. An iterative x² method, developed previously for relating annual crop production to daily values of meteorological measurements, is applied to tree-ring data and compared to results obtained from correlation and bootstrapped response function analyses. All three analytical procedures use a southern Arizona chronology (Pinus arizonica Engelm.) and the latter two use monthly average meteorological data. The x² analysis revealed most of the relationships exhibited by the correlation and response function analyses as well as new linear and nonlinear associations. In addition, cardinal values were obtained that define daily thresholds of the meteorological variables at which the limitation to growth becomes significant. Some of the associations are plausible from the physical system but require more study to confirm or refute a real cause and effect. A few associations appear to be too late in the season or too early in the previous year to affect ring width. We recommend that this x² technique be added to the existing dendroclimatic procedures because it reveals many more possible cause and effect relationships.This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. It was digitized from a physical copy provided by the Laboratory of Tree-Ring Research at The University of Arizona. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at [email protected]

Aerial insect biomass, but not phenological mismatch, is associated with chick survival of an insectivorous bird

Recent insect abundance declines may have affected populations of insectivorous bird species, but evidence for this is limited. Here, we use spatially overlapping 29-year time-series of aerial insect biomass and Barn Swallow Hirundo rustica numbers and breeding success from southern England to model the association between changes in invertebrate prey abundance, Swallow productivity, and population trends. We found a positive statistical relationship between Swallow chick survival and the biomass of aerial insects available for chicks. In nests where at least one chick fledged, 96.7% of chicks were predicted to survive to fledging where there was high insect biomass (an average of 0.62 g day-1), compared to 87.4% of chicks surviving to fledging where there was the lowest insect biomass (0.02 g day-1; excluding the greatest and smallest 5% of insect biomass measurements). The amount of food available for chicks was largely a function of annual variation in insect abundance rather than the phenology of egg laying and insect emergence. However, we did not find a correlation between annual insect abundance and subsequent Swallow population growth. In the context of concerns about declining insect abundance, this study shows how changes in insect biomass may affect the productivity of an insectivorous bird at a regional scale, but with uncertain implications for population size at that same scal

Projected increase in continental runoff due to plant responses to increasing carbon dioxide

In addition to influencing climatic conditions directly through radiative forcing, increasing carbon dioxide concentration influences the climate system through its effects on plant physiology1. Plant stomata generally open less widely under increased carbon dioxide concentration2, which reduces transpiration1, 3, 4, 5, 6 and thus leaves more water at the land surface7. This driver of change in the climate system, which we term 'physiological forcing', has been detected in observational records of increasing average continental runoff over the twentieth century8. Here we use an ensemble of experiments with a global climate model that includes a vegetation component to assess the contribution of physiological forcing to future changes in continental runoff, in the context of uncertainties in future precipitation. We find that the physiological effect of doubled carbon dioxide concentrations on plant transpiration increases simulated global mean runoff by 6 per cent relative to pre-industrial levels; an increase that is comparable to that simulated in response to radiatively forced climate change (11 6 per cent). Assessments of the effect of increasing carbon dioxide concentrations on the hydrological cycle that only consider radiative forcing9, 10, 11 will therefore tend to underestimate future increases in runoff and overestimate decreases. This suggests that freshwater resources may be less limited than previously assumed under scenarios of future global warming, although there is still an increased risk of drought. Moreover, our results highlight that the practice of assessing the climate-forcing potential of all greenhouse gases in terms of their radiative forcing potential relative to carbon dioxide does not accurately reflect the relative effects of different greenhouse gases on freshwater resources

C/EBPβ regulates transcription factors critical for proliferation and survival of multiple myeloma cells

CCAAT/enhancer-binding protein β (C/EBPβ), also known as nuclear factor–interleukin-6 (NF-IL6), is a transcription factor that plays an important role in the regulation of growth and differentiation of myeloid and lymphoid cells. Mice deficient in C/EBPβ show impaired generation of B lymphocytes. We show that C/EBPβ regulates transcription factors critical for proliferation and survival in multiple myeloma. Multiple myeloma cell lines and primary multiple myeloma cells strongly expressed C/EBPβ, whereas normal B cells and plasma cells had little or no detectable levels of C/EBPβ. Silencing of C/EBPβ led to down-regulation of transcription factors such as IRF4, XBP1, and BLIMP1 accompanied by a strong inhibition of proliferation. Further, silencing of C/EBPβ led to a complete down-regulation of antiapoptotic B-cell lymphoma 2 (BCL2) expression. In chromatin immunoprecipitation assays, C/EBPβ directly bound to the promoter region of IRF4, BLIMP1, and BCL2. Our data indicate that C/EBPβ is involved in the regulatory network of transcription factors that are critical for plasma cell differentiation and survival. Targeting C/EBPβ may provide a novel therapeutic strategy in the treatment of multiple myeloma