Assessing the impact of temperature on acute exacerbation of chronic obstructive pulmonary disease hospitalizations in residents of Panzhihua City: a multi-districts study using a distributed lag non-linear model.

BACKGROUND: Temperature fluctuations can impact the occurrence and progression of respiratory system diseases. However, the current understanding of the impact of temperature on acute exacerbation of chronic obstructive pulmonary disease (AECOPD) remains limited. Therefore, our study aims to investigate the relationship between daily mean temperature (DMT) and the risk of AECOPD hospitalizations within Panzhihua City. METHODS: We systematically collected data on AECOPD hospitalizations at Panzhihua Central Hospital from 2015 to 2020 and meteorological factors across Panzhihua City's districts. A two-stage analysis method was used to establish a distributed lag non-linear model to elucidate the influence of DMT on the frequency of admissions for AECOPD. Subgroup analyses were conducted by gender and age to identify populations potentially susceptible to the impact of DMT. RESULTS: A total of 5299 AECOPD hospitalizations cases were included. The DMT and the risk of AECOPD hospitalization showed a non-linear exposure-response pattern, with low temperatures exacerbating the risk of hospitalizations. The lag effects of low temperature and relatively low temperature peaked at 2th day, with the lag effects disappearing at 16-17 days. Females and elders aged ≥ 65 years were more sensitive to effects of low and relatively low temperature at lag 0-4 days, while male AECOPD patients exhibited longer lasting lag effects. CONCLUSIONS: Low temperatures are associated with an increased risk of AECOPD hospitalizations. Females or elders aged ≥ 65 years with chronic obstructive pulmonary disease should pay more attention to taking protective measures in cold environments. These findings are crucial for the formulation of public health policies, as they will help significantly alleviate the burden of AECOPD and improve respiratory health in the face of climate challenges.

Increased stress from compound drought and heat events on vegetation.

Compound drought and heat events (CDHEs), which are frequently occurring compound extreme climate events, have garnered considerable attention because of their detrimental effects on ecosystems. However, the intricacies of the spatial and temporal distributions of different durations of compound events, along with the variability in vegetation responses remain unclear. Here, we delineated the CDHEs based on meteorological observation data and investigated the spatial and temporal characteristics of CDHEs from 1993 to 2020 using the Theil-Sen trend test and Mann-Kendall nonparametric test. Furthermore, we utilized sliding correlation analysis to evaluate the impacts of CDHEs on vegetation among different climatic regions and ecosystems. Our findings indicate significant increasing trends in both the frequency and persistence of CDHEs from 1993 to 2020. The average trend of CDHEs frequency across different duration periods amounted to 13.80 %/decade. The fractional contribution of CDHEs lasting more than three days exhibited a significant increase, with an average trend of 2.00 %/decade. We also observed that vegetation is most significantly affected by compound events lasting 5-9 days. During the study period, the geographical extent of vegetation significantly impacted by CDHEs expanded by 0.89 %, correlation strength increased by 0.02, and lag time decreased by 0.25 months. These insights highlight the growing impact of CDHEs on vegetation under climate change, improving our understanding of vegetation responses to these compound events.

Influence of Time-Lag Effects between Winter-Wheat Canopy Temperature and Atmospheric Temperature on the Accuracy of CWSI Inversion of Photosynthetic Parameters.

When calculating the CWSI, previous researchers usually used canopy temperature and atmospheric temperature at the same time. However, it takes some time for the canopy temperature (Tc) to respond to atmospheric temperature (Ta), suggesting the time-lag effects between Ta and Tc. In order to investigate time-lag effects between Ta and Tc on the accuracy of the CWSI inversion of photosynthetic parameters in winter wheat, we conducted an experiment. In this study, four moisture treatments were set up: T1 (95% of field water holding capacity), T2 (80% of field water holding capacity), T3 (65% of field water holding capacity), and T4 (50% of field water holding capacity). We quantified the time-lag parameter in winter wheat using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis. Based on the time-lag parameter, we modified the CWSI theoretical and empirical models and assessed the impact of time-lag effects on the accuracy of the CWSI inversion of photosynthesis parameters. Finally, we applied several machine learning algorithms to predict the daily variation in the CWSI after time-lag correction. The results show that: (1) The time-lag parameter calculated using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis are 44-70, 32-44, 42-58, and 76-97 min, respectively. (2) The CWSI empirical model corrected by the time-lag mutual information method has the highest correlation with photosynthetic parameters. (3) GA-SVM has the highest prediction accuracy for the CWSI empirical model corrected by the time-lag mutual information method. Considering time lag effects between Ta and Tc effectively enhanced the correlation between CWSI and photosynthetic parameters, which can provide theoretical support for thermal infrared remote sensing to diagnose crop water stress conditions.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States.

BACKGROUND: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. METHODS: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. RESULTS: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. CONCLUSIONS: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Investigating the cumulative lag effects of environmental exposure under urban differences on COVID-19.

Although all walks of life are paying less attention to COVID-19, the spread of COVID-19 has never stopped. As an infectious disease, its transmission speed is closely related to the atmosphere environment, particularly the temperature (T) and PM2.5 concentrations. However, How T and PM2.5 concentrations are related to the spread of SARS-CoV-2 and how much their cumulative lag effect differ across cities is unclear. To identify the characteristics of cumulative lag effects of environmental exposure under city differences, this study used a generalized additive model to investigate the associations between T/PM2.5 concentrations and the daily number of new confirmed COVID-19 cases (NNCC) during the outbreak period in the second half of 2021 in Shaoxing, Shijiazhuang, and Dalian. The results showed that except for PM2.5 concentrations in Shaoxing, the NNCC in the three cities generally increased with the unit increase of T and PM2.5 concentrations. In addition, the cumulative lag effects of T/PM2.5 concentrations on NNCC in the three cities reached a peak at lag 26/25, lag 10/26, and lag 18/13 days, respectively, indicating that the response of NNCC to T and PM2.5 concentrations varies among different regions. Therefore, combining local meteorological and air quality conditions to adopt responsive measures is an important way to prevent and control the spread of SARS-CoV-2.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States.

Background: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health. Methods: We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season. Results: Short-term exposure increases of 1 µg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)]. Conclusions: Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods. Classification: environmental public health, fine particulate matter air pollution, respiratory infections.

The effect of short-term air pollutants exposure on outpatient admission for blepharitis in Shanghai, China: a hospital-based study.

Blepharitis is a very common ophthalmologic disease, and few studies have examined if air pollutants contribute to the risk of blepharitis. We investigated the presence of any potential correlation between exposure to air pollution and outpatient admission for blepharitis in Shanghai, China. Data on daily outpatient admission for blepharitis were collected from January 2017 to July 2022. Air pollution and meteorological data were acquired from the Shanghai Environmental Protection Agency. Using the distributed lag non-linear model (DLNM) we investigated the relationship between air pollutants and blepharitis. Seasonal stratified analysis was carried out. In total, 10,681 blepharitis patients were recruited. In the single-pollutant model, a 10 µg/m3 increase in particulate matter with < 2.5 µm PM2.5 and 10 µm PM10 along with sulfur dioxide (SO2) and 100 µg/m3 increase in carbon monoxide (CO) was significantly associated with outpatient visits for blepharitis. In the multi-pollutant model, a 10 µg/m3 increase in ozone (O3) and nitrogen dioxide (NO2) and a 100 µg/m3 increase in carbon monoxide (CO) was significantly associated with outpatient visits for blepharitis. Moreover, there was an obvious relationship between blepharitis and PM2.5 and O3 in the summers and blepharitis and PM10, NO2, and SO2 during the winters. Exposure to short-term air pollution increases the risk of blepharitis outpatient visits in Shanghai, China.

The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: A seven-year time series study.

BACKGROUND: Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing. OBJECTIVE: The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB. METHODS: Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM10, PM2.5, SO2, NO2, CO and O3, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing. RESULTS: In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 µg/m3 increase in NO2 in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 µg/m3 increase in O3 in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO2, O3, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM2.5, SO2, sunshine duration and TB cases. CONCLUSION: Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.

Age-Related Hearing Loss, Cognitive Performance, and Metabolic Risk in Healthy Adults: A Seven-Year Longitudinal Study.

OBJECTIVES: Sensorineural hearing loss (presbycusis) affects up to half of the adults, is associated with cognitive decline. Whether this association reflects the cause, the consequence, or parallel processes driven by other factors remains unclear. Both presbycusis and cognition are linked to elevated metabolic risk, which in turn raises with age. METHOD: In a multioccasion longitudinal design, we used latent change score models with strong factorial invariance to assess the change in pure-tone threshold auditory function, fluid intelligence, metabolic risk, variability therein, and the dynamic relationships among the 3 domains. We examined, up to 4 times over more than 7 years, a sample of relatively healthy 687 adults (aged 18.17-83.25 years). RESULTS: We found that levels of auditory and cognitive functioning at time t-1 influence each other's subsequent change between times t-1 and t, even when controlling for the reciprocal effects of metabolic risk on both. Thus, auditory and cognitive functioning do not only decline in parallel in healthy adults, but also affect each other's trajectories. To the best of our knowledge, this is the first long-term study with such evidence. DISCUSSION: Our results are in accord with extant hypotheses about auditory-cognitive associations in old age (e.g., social isolation, cognitive load, increased inflammation, reduced gene expression, and other microvascular or neuropathological factors). They also echo previous reports underscoring the need for improving access to hearing aids and other rehabilitative services aimed at reducing hearing loss. If applied early in the aging process, such interventions may mitigate cognitive decline.

Air Pollution in Kosovo: Short Term Effects on Hospital Visits of Children Due to Respiratory Health Diagnoses.

The Republic of Kosovo is a small country in the Balkans. The capital city of Pristina hosts most of its population and is situated in a mountain basin with poor air exchange, especially during winter. Domestic heating, road transport, industry and coal-fired power plants contribute to high levels of air pollution. We performed a time-series analysis on effects of particulate air pollution (PM2.5) on respiratory health of children and adolescents, using hospital admission and ambulatory visit numbers from the pediatric university clinic. From 2018 until 2020, daily mean concentrations of PM2.5 ranged between 2.41 and 161.03 µg/m³. On average, there were 6.7 ambulatory visits per day with lower numbers on weekends and during the first COVID-19 wave in 2020. An increase in PM2.5 led to an immediate increase in visit numbers that lasted over several days. Averaged over a full week, this amounted to about a 1% increase per 10 µg/m³. There were, on average, 1.7 hospital admissions per day. Two and three days after a rise in air pollution, there was also a rise in admission numbers, followed by a decline during the consecutive days. This might indicate that the wards were overstressed because of high admission numbers and restricted additional admissions.

Short-term effects of ambient temperature on the risk of preeclampsia in Nanjing, China: a time-series analysis.

OBJECTIVES: Previous studies on the association between temperature and preeclampsia mainly considered temperature on a monthly or seasonal time scale. The objective of this study was to assess the preeclampsia risk associated with short-term temperature exposure using daily data. STUDY DESIGN: Daily preeclampsia hospitalization data, daily meteorological data and daily air pollutant data from Nanjing were collected from 2016 to 2017. Both the T test and distributed lag nonlinear model (DLNM) were applied to assess the short-term effect of temperature on preeclampsia risk. Three kinds of daily temperature, including the daily mean temperature, daily minimum temperature and daily maximum temperature, were analysed. RESULTS: When the daily number of preeclampsia hospital admissions was divided into two subgroups based on temperature, it was significantly larger on cold days than on hot days. Regarding the mean temperature, a very low level of mean temperature (4.5 °C, lag = 0-20) and a low level of mean temperature (9.1 °C, lag = 0-20) increased the cumulative relative risk of preeclampsia by more than 60%. At the same time, a very high level of mean temperature (28.7 °C, lags = 0-10, 0-15, 0-20) and a high level of mean temperature (24.1 °C, lags = 0-10, 0-15) decreased the cumulative relative risk of preeclampsia by more than 35%. At a minimum temperature, a very low level of minimum temperature (0.9 °C, lag 0-5) and a low level of minimum temperature (5.6 °C, lag 0-5) increased the cumulative relative risk of preeclampsia by more than 55%. At the same time, a high level of mean temperature (20.9 °C, lags = 0, 0-5) decreased the cumulative relative risk of preeclampsia by more than 20%. The maximum temperature result was similar to the mean temperature result. CONCLUSIONS: Both direct and lag effects of low temperature on preeclampsia were demonstrated to be significant risk factors. These results could be used to help pregnant women and the government reduce preeclampsia risk.

Life-history traits predict responses of wild bees to climate variation.

Life-history traits, which are physical traits or behaviours that affect growth, survivorship and reproduction, could play an important role in how well organisms respond to environmental change. By looking for trait-based responses within groups, we can gain a mechanistic understanding of why environmental change might favour or penalize certain species over others. We monitored the abundance of at least 154 bee species for 8 consecutive years in a subalpine region of the Rocky Mountains to ask whether bees respond differently to changes in abiotic conditions based on their life-history traits. We found that comb-building cavity nesters and larger bodied bees declined in relative abundance with increasing temperatures, while smaller, soil-nesting bees increased. Further, bees with narrower diet breadths increased in relative abundance with decreased rainfall. Finally, reduced snowpack was associated with reduced relative abundance of bees that overwintered as prepupae whereas bees that overwintered as adults increased in relative abundance, suggesting that overwintering conditions might affect body size, lipid content and overwintering survival. Taken together, our results show how climate change may reshape bee pollinator communities, with bees with certain traits increasing in abundance and others declining, potentially leading to novel plant-pollinator interactions and changes in plant reproduction.

Unravelling insect declines: can space replace time?

Temporal trends in insect numbers vary across studies and habitats, but drivers are poorly understood. Suitable long-term data are scant and biased, and interpretations of trends remain controversial. By contrast, there is substantial quantitative evidence for drivers of spatial variation. From observational and experimental studies, we have gained a profound understanding of where insect abundance and diversity is higher-and identified underlying environmental conditions, resource change and disturbances. We thus propose an increased consideration of spatial evidence in studying the causes of insect decline. This is because for most time series available today, the number of sites and thus statistical power strongly exceed the number of years studied. Comparisons across sites allow quantifying insect population risks, impacts of land use, habitat destruction, restoration or management, and stressors such as chemical and light pollution, pesticides, mowing or harvesting, climatic extremes or biological invasions. Notably, drivers may not have to change in intensity to have long-term effects on populations, e.g. annually repeated disturbances or mortality risks such as those arising from agricultural practices. Space-for-time substitution has been controversially debated. However, evidence from well-replicated spatial data can inform on urgent actions required to halt or reverse declines-to be implemented in space.

Effects of ambient temperature on outpatient visits for dermatitis in Xinxiang, China: a time-series analysis.

Previous studies have reported regional variations in the relationship between ambient temperature and dermatitis, which therefore remain inconclusive. This study aimed to understand the short-term effects of ambient temperature in outpatients with dermatitis in Xinxiang. Routine data of dermatitis outpatient visits between January 1, 2015, and December 31, 2018 were acquired from the First Affiliated Hospital of Xinxiang Medical University. A distributed lag nonlinear model (DLNM) in combination with a generalized additive model (GAM) was applied to investigate the acute impact of ambient temperature on dermatitis outpatients. Two stratified analyses based on age and sex were conducted to explore their potential modification effects. A total of 18,064 dermatitis outpatient records were retrieved during the study period. The relationship between ambient temperature and dermatitis outpatients was found to be nonlinear; exposure-response curves were approximately "J" shaped. The risk of dermatitis outpatient increased with a corresponding elevation in temperature from 11.5 to 27.5°C. However, the significance was lost when the temperature exceeded the given range. Stratified analysis demonstrated higher sensitivity to temperature in females than in males, and the young groups (<15 years) might be sensitive to heat temperature. This study provides first-hand epidemiological evidence demonstrating a higher risk of dermatitis outpatient visits associated with moderately higher temperatures. The outcomes of this study create awareness among citizens to take the necessary precautions to prevent the adverse effects of moderate heat temperature during early summer and autumn seasons.

Spatial and dynamic effects of air pollution on under-five children's lower respiratory infections: an evidence from China 2006 to 2017.

Air pollution has been a deeply concerned issue posing an immediate and profound threat to human's lower respiratory health in China. The health of children under 5 years old, regarded as a key index of public health progress in a country, is closely related to the long-term human capital development. Hence, it is vital to investigate the potential association between air pollution and children's lower respiratory health outcomes and to explore related policy implications regarding the public health and the pollution regulation. As air pollutants diffuse across adjacent regions rather easily, considering the spatial spillover effect is meaningful in course of acquiring the aforementioned association. Based on the proposed province-level panel dataset of China during 2006-2017, this study constructs a dynamic spatial panel Durbin model to investigate the impact of air pollution on under-five children's lower respiratory infections. As a result, (1) both air pollution and children's respiratory health have obvious spatial spillover effects, and the latter has an outstanding characteristic of path dependence in time. (2) In the short term, air pollution presents significant negative impact on children's respiratory health, while in the long run, the impact decreases dramatically. (3) Regional comparison indicates that children in the western China are the most susceptible to air pollution followed by children in the central and eastern regions. (4) Other control variables have significant and varying impacts both in the short and long term. Particularly, this paper proves the existence of "siphon effect" in children healthcare system in China. From a broader and more comprehensive perspective, this study provides effective and constructive basis for policy making, in favor of improving children's health under air pollution and promoting sustainable development in China.

R&D Investments, Debt Capital, and Ownership Concentration: A Three-Way Interaction and Lag Effects on Firm Performance in China's Pharmaceutical Industry.

The existing literature has yet to provide consistent evidence on the relationship between R&D investments and firm performance. The current study attempted to fill this gap in the literature by examining the effect of lag structure and the moderating role of financial governance, in terms of debt capital and ownership concentration, on the returns of R&D. Analyzing a sample of China's pharmaceutical firms from 2009 to 2018, we found that the effect of R&D upon growth begins in the second year after R&D spending and increases thereafter. There exists a vigorous debate about the choice between debt and ownership structure. To fill this gap, we proposed a three-way interactive effect. The results suggest that firms that invest heavily in R&D may achieve their highest performance when the use of debt capital and the extent of ownership concentration are both low. This study contributes to the R&D investments and financial governance literature by reconciling previous mixed evidence about the returns of R&D and the debt-equity choices on R&D investment decisions.

Maternal effects and the outcome of interspecific competition.

Maternal environmental effects create lagged population responses to past environments. Although they are ubiquitous and vary in expression across taxa, it remains unclear if and how their presence alters competitive interactions in ecological communities.Here, we use a discrete-time competition model to simulate how maternal effects alter competitive dynamics in fluctuating and constant environments. Further, we explore how omitting maternal effects alter estimates of known model parameters from observational time series data.Our simulations demonstrate that (i) maternal effects change competitive outcomes, regardless of whether competitors otherwise interact neutrally or exhibit non-neutral competitive differences, (ii) the consequences of maternal effects for competitive outcomes are mediated by the temporal structure of environmental variation, (iii) even in constant conditions, competitive outcomes are influenced by species' maternal effects strategies, and (iv) in observational time series data, omitting maternal effects reduces variation explained by models and biases parameter estimates, including competition coefficients.Our findings demonstrate that the ecological consequences of maternal effects hinge on the competitive environment. Evolutionary biologists have long recognized that maternal effects can be an important but often overlooked strategy buffering populations from environmental change. We suggest that maternal effects are similarly critical to ecology and call for research into maternal effects as drivers of dynamics in populations and communities.

Response of grassland net primary productivity to dry and wet climatic events in four grassland types in Inner Mongolia.

Increasing frequency and intensity of climate extremes have profound impacts on grassland biodiversity functioning and stability. Using Moderate Resolution Imaging Spectroradiometer (MODIS) net primary productivity (NPP) data and standardized precipitation evapotranspiration index, we assessed the response of NPP to growing-season and annual climate extremes and time-lag of climatic conditions across four grassland types (meadow steppe, typical steppe, steppe desert, and desert steppe) in Inner Mongolia, China from the period 2000 to 2019. Results showed that annual NPP varied significantly across four grassland types, with the highest NPP in meadow steppe and the lowest in desert steppe. Annual NPP of all grassland types increased over the past 20 years, but NPP in meadow steppe and typical steppe decreased for the period 2012-2019. Irrespective of grassland type, the 1- and 2-month time-lag of climatic conditions showed significant effects on annual NPP. Growing-season climate was found the better predictor of annual NPP in all grassland types than the annual climate. Compared with growing-season normal climates, annual NPP was lowest in extreme dry events in all grasslands, while highest in extreme wet events in meadow steppe and typical steppe, and in moderate wet events in steppe desert and desert steppe. Typical steppe and steppe desert are highly vulnerable to the increasing intensity of climate extremes, as we found that the losses of NPP in these grasslands in extreme dry were almost double than that of moderate dry events. Surprisingly, for meadow steppe and desert steppe, the losses of NPP for both moderate and extreme dry events were almost the same, which highlights that a low-intensity drought may have profound impacts on the annual NPP of these grasslands. The study provides the key insight in scientific basis to improve our understanding of the effects of climate extremes on grassland NPP, which is critical to sustainable management of grassland and maintain ecosystem stability.

A Markov Mixed-Effect Multinomial Logistic Regression Model for Nominal Repeated Measures with an Application to Syntactic Self-Priming Effects.

Syntactic priming effects have been investigated for several decades in psycholinguistics and the cognitive sciences to understand the cognitive mechanisms that support language production and comprehension. The question of whether speakers prime themselves is central to adjudicating between two theories of syntactic priming, activation-based theories and expectation-based theories. However, there is a lack of a statistical model to investigate the two different theories when nominal repeated measures are obtained from multiple participants and items. This paper presents a Markov mixed-effect multinomial logistic regression model in which there are fixed and random effects for own-category lags and cross-category lags in a multivariate structure and there are category-specific crossed random effects (random person and item effects). The model is illustrated with experimental data that investigates the average and participant-specific deviations in syntactic self-priming effects. Results of the model suggest that evidence of self-priming is consistent with the predictions of activation-based theories. Accuracy of parameter estimates and precision is evaluated via a simulation study using Bayesian analysis.

Behavioural responses of breeding arctic sandpipers to ground-surface temperature and primary productivity.

Most birds incubate their eggs, which requires time and energy at the expense of other activities. Birds generally have two incubation strategies: biparental where both mates cooperate in incubating eggs, and uniparental where a single parent incubates. In harsh and unpredictable environments, incubation is challenging due to high energetic demands and variable resource availability. We studied the relationships between the incubation behaviour of sandpipers (genus Calidris) and two environmental variables: temperature and a proxy of primary productivity (i.e. NDVI). We investigated how these relationships vary between incubation strategies and across species among strategies. We also studied how the relationship between current temperature and incubation behaviour varies with previous day's temperature. We monitored the incubation behaviour of nine sandpiper species using thermologgers at 15 arctic sites between 2016 and 2019. We also used thermologgers to record the ground surface temperature at conspecific nest sites and extracted NDVI values from a remote sensing product. We found no relationship between either environmental variables and biparental incubation behaviour. Conversely, as ground-surface temperature increased, uniparental species decreased total duration of recesses (TDR) and mean duration of recesses (MDR), but increased number of recesses (NR). Moreover, small species showed stronger relationships with ground-surface temperature than large species. When all uniparental species were combined, an increase in NDVI was correlated with higher mean duration, total duration and number of recesses, but relationships varied widely across species. Finally, some uniparental species showed a lag effect with a higher nest attentiveness after a warm day while more recesses occurred after a cold day than was predicted based on current temperatures. We demonstrate the complex interplay between shorebird incubation strategies, incubation behaviour, and environmental conditions. Understanding how species respond to changes in their environment during incubation helps predict their future reproductive success.