Halyomorpha halys (Hemiptera: Pentatomidae) Winter Survival, Feeding Activity, and Reproduction Rates Based on Episodic Cold Shock and Winter Temperature Regimes

Globally distributed nonnative insects thrive by having a generalist diet and persisting across large latitudinal gradients. Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) is a cold-tolerant invasive species that enters reproductive diapause in temperate North American and European climates. While it can survive the acute effects of subzero (°C) temperatures, it is poorly understood how exposure to infrequent cold temperatures affects postdiapause survival and behavior. We studied the impacts of episodic cold shock at temperatures of -6 to -2 (°C) at the onset of H. halys diapause, followed by an extended overwintering period. These conditions simulated three distinct climates, with above-freezing, near-freezing, and below-freezing daily low temperatures, to explore a range of possible effects on H. halys. We measured mortality regularly and evaluated postdiapause feeding damage and fecundity in each treatment. Postdiapause survival rates ranged from 40 to 50% in all treatments, except for -6°C. At this temperature, fewer than 25% H. halys survived. Feeding damage was greatest in the warmest simulated climate. The highest number of egg masses was laid under subfreezing episodic cold shock conditions. The controlled diapause simulations suggest that brief exposure to cold temperatures as low as -4°C does not have immediate or long-term effects on H. halys mortality. Exposure to cold temperatures may, however, increase postdiapause fecundity. These data provide insight into the impacts of cold exposure on postdiapause survival, reproduction, and feeding and can help predict H. halys-related crop risk based on preceding winter conditions.

Temperature and nitrogen supply interact to determine protein distribution gradients in the wheat grain endosperm

Gradients exist in the distribution of storage proteins in the wheat (Triticum aestivum) endosperm and determine the milling properties and protein recovery rate of the grain. A novel image analysis technique was developed to quantify both the gradients in protein concentration, and the size distribution of protein bodies within the endosperm of wheat plants grown under two different (20 or 28 °C) post-anthesis temperatures, and supplied with a nutrient solution with either high or low nitrogen content. Under all treatment combinations, protein concentration was greater in the endosperm cells closest to the aleurone layer and decreased towards the centre of the two lobes of the grain, i.e. a negative gradient. This was accompanied by a decrease in size of protein bodies from the outer to the inner endosperm layers in all but one of the treatments. Elevated post-anthesis temperature had the effect of increasing the magnitude of the negative gradients in both protein concentration and protein body size, whilst limiting nitrogen supply decreased the gradients.

Precipitation frequency alters peatland ecosystem structure and CO2 exchange: Contrasting effects on moss, sedge, and shrub communities

Climate projections forecast a redistribution of seasonal precipitation for much of the globe into fewer, larger events spaced between longer dry periods, with negligible changes in seasonal rainfall totals. This intensification of the rainfall regime is expected to alter near-surface water availability, which will affect plant performance and carbon uptake. This could be especially important in peatland systems, where large stores of carbon are tightly coupled to water surpluses limiting decomposition. Here, we examined the role of precipitation frequency on vegetation growth and carbon dioxide (CO₂ ) balances for communities dominated by a Sphagnum moss, a sedge, and an ericaceous shrub in a cool temperate poor fen. Field plots and laboratory monoliths received one of three rainfall frequency treatments, ranging from one event every three days to one event every 14 days, while total rain delivered in a two-week cycle and the entire season to each treatment remained the same. Separating incident rain into fewer but larger events increased vascular cover in all peatland communities: vascular plant cover increased 6× in the moss-dominated plots, nearly doubled in the sedge plots, and tripled in the shrub plots in Low-Frequency relative to High-Frequency treatments. Gross ecosystem productivity was lowest in moss communities receiving low-frequency rain, but higher in sedge and shrub communities under the same conditions. Net ecosystem exchange followed this pattern: fewer events with longer dry periods increased CO₂ flux to the atmosphere from the moss while vascular plant-dominated communities became more of a sink for CO₂ . Results of this study suggest that changes to rainfall frequency already occurring and predicted to continue will lead to increased vascular plant cover in peatlands and will impact their carbon-sink function.

Temperature fluctuations and maternal estrogens as critical factors for understanding temperature-dependent sex determination in nature

Vertebrates with temperature-dependent sex determination (TSD) have justifiably received a lot of attention when it comes to the potential effects of climate change. Freshwater turtles have long been used to characterize the physiological and genetic mechanisms underlying TSD and provide a great system to investigate how changing climatic conditions will affect vertebrates with TSD. Unfortunately, most of what we know about the mechanisms underlying TSD comes from laboratory conditions that do not accurately mimic natural conditions (i.e., constant incubation temperatures and supraphysiological steroid manipulations). In this paper, we review recent advances in our understanding of how TSD operates in nature that arose from studies using more natural fluctuating incubation temperatures and natural variation in maternal estrogens within the yolk. By incorporating more natural conditions into laboratory studies, we are better able to use these studies to predict how changing climatic conditions will affect species with TSD.

Warming-induced upward migration of the alpine treeline in the Changbai Mountains, northeast China

Treeline responses to environmental changes describe an important phenomenon in global change research. Often conflicting results and generally too short observations are, however, still challenging our understanding of climate-induced treeline dynamics. Here, we use a state-of-the-art dendroecological approach to reconstruct long-term changes in the position of the alpine treeline in relation to air temperature at two sides in the Changbai Mountains in northeast China. Over the past 160 years, the treeline increased by around 80 m, a process that can be divided into three phases of different rates and drives. The first phase was mainly influenced by vegetation recovery after an eruption of the Tianchi volcano in 1702. The slowly upward shift in the second phase was consistent with the slowly increasing temperature. The last phase coincided with rapid warming since 1985, and shows with 33 m per 1°C, the most intense upward shift. The spatial distribution and age structure of trees beyond the current treeline confirm the latest, warming-induced upward shift. Our results suggest that the alpine treeline will continue to rise, and that the alpine tundra may disappear if temperatures will increase further. This study not only enhances mechanistic understanding of long-term treeline dynamics, but also highlights the effects of rising temperatures on high-elevation vegetation dynamics.

Trends in the consecutive days of temperature and precipitation extremes in China during 1961-2015

BACKGROUND AND AIMS

Consecutive climatic extremes have more intense impacts on natural ecosystems and human activities than occasional events. There were many studies about the frequency or intensity of extreme weather events, but few focused on the consecutiveness or continuousness of climatic extremes. We analyzed the temporal and spatial distributions and tendencies in the consecutive temperature and precipitation extremes in China during 1961-2015.

METHODS

Daily temperature and precipitation data at 1867 meteorological stations over China was used and four consecutive indices of climate extremes, i.e. cold spell duration indicator (CSDI), warm spell duration indicator (WSDI), consecutive dry days (CDD) and consecutive wet days (CWD), were calculated by RClimDex 1.0. Linear trends in the time series of consecutive days of temperature and precipitation extremes were examined and their statistical significance was evaluated using Mann-Kendall test.

RESULTS AND DISCUSSION

There were obvious differences in the spatial distributions of consecutive days of climate extremes in China. During 1961-2015, CSDI and CWD decreased significantly at rates of 0.9 and 0.1 days per decade respectively, while WSDI increased significantly at rate of 0.8 days per decade in China. Spatially, CSDI decreased at rates of 0-3.0 days per decade in almost all parts of China, and WSDI increased at rates of 0-2.0 days per decade in most parts of China. The spatial trends of CDD and CWD were significant only in several regions of China. CSDI and WSDI had higher percent changes than those of CDD and CWD. Changes in the CSDI and WSDI were associated with large-scale oceanic and atmospheric circulation oscillations, such as Atlantic Multidecadal Oscillation (AMO), El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). With global warming, there will be fewer cold extremes, more frequent hot extremes and precipitation extremes.

CONCLUSIONS

Given the increases in the frequency and intensity of some consecutive climatic extremes and an increasing physical exposure and socio-economic vulnerability to such extremes in China, more strategies and capacities of mitigation and adaptation to consecutive climatic extremes are essential for the local government and climate-sensitive sectors.

Statistical Modeling of Extreme Precipitation with TRMM Data

This paper improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar locations are pooled to increase the quality of the resulting model parameter estimates to compensate for the short data record. The regional analysis is divided into two stages. First, the region defined by the TRMM measurements is partitioned into approximately 28,000 non-overlapping clusters using a recursive k-means clustering scheme. Next, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of applying the block-maxima approach used in the existing system, where the Generalized Extreme Value probability distribution is fit to the annual precipitation maxima at each site separately, the present work adopts the peak-over-threshold method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate using the Point Process framework for modeling extremes. The fitted parameters are used to estimate trends and to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is. This information could be used by policy makers for disaster monitoring and prevention. The new methodology eliminates much of the noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center ground-based observations. Furthermore, the proposed methodology can be applied to other extreme climate records.

Global, Regional, and Megacity Trends in the Highest Temperature of the Year: Diagnostics and Evidence for Accelerating Trends

Trends in short-lived high-temperature extremes record a different dimension of change than the extensively studied annual and seasonal mean daily temperatures. They also have important socioeconomic, environmental, and human health implications. Here, we present analysis of the highest temperature of the year for approximately 9000 stations globally, focusing on quantifying spatially explicit exceedance probabilities during the recent 50- and 30-year periods. A global increase of 0.19°C per decade during the past 50 years (through 2015) accelerated to 0.25°C per decade during the last 30 years, a faster increase than in the mean annual temperature. Strong positive 30-year trends are detected in large regions of Eurasia and Australia with rates higher than 0.60°C per decade. In cities with more than 5 million inhabitants, where most heat-related fatalities occur, the average change is 0.33°C per decade, while some east Asia cities, Paris, Moscow, and Houston have experienced changes higher than 0.60°C per decade.

Future extreme climate changes linked to global warming intensity

Based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) daily dataset, we investigate changes of the terrestrial extreme climates given that the global mean temperature increases persistently under the Representative Concentration Pathways 8.5 (RCP8.5) scenario. Compared to preindustrial conditions, more statistically significant extreme temperatures, precipitations, and dry spells are expected in the 21st century. Cold extremes decrease and warm extremes increase in a warmer world, and cold extremes tend to be more sensitive to global warming than the warm ones. When the global mean temperature increases, cold nights, cold days, and warm nights all display nonlinear relationships with it, such as the weakening of the link projected after 3 °C global warming, while the other indices generally exhibit differently, with linear relationships. Additionally, the relative changes in the indices related to extreme precipitation show significantly consistent linear changes with the global warming magnitude. Compared with the precipitation extremes, changes in temperature extremes are more strongly related to the global mean temperature changes. For the projection of the extreme precipitation changes, models show higher uncertainty than that in extreme temperature changes, and the uncertainty for the precipitation extremes becomes more remarkable when the global warming exceeds 5 °C.

Modeling the Spatial and Temporal Variability of Precipitation in Northwest Iran

Spatial and temporal variability analysis of precipitation is an important task in water resources planning and management. This study aims to analyze the spatial and temporal variability of precipitation in the northeastern corner of Iran using data from 24 well-distributed weather stations between 1991 and 2015. The mean annual rainfall, precipitation concentration index (PCI), and their coefficients of variation were mapped to examine the spatial variability of rainfall. An artificial neural network (ANN) in association with the inverse distance weighted (IDW) method was proposed as a hybrid interpolation method to map the spatial distribution of the detected trends of mean annual rainfall and PCI over the study region. In addition, principal component analysis (PCA) was applied to annual precipitation time series in order to verify the results of the analysis using the mean annual rainfall and PCI data sets. Results show high variation in inter-annual precipitation in the west, and a moderate to high intra-annual variability over the whole region. Irregular year-to-year precipitation concentration is also observed in the northeastern and northwestern parts. All in all, the highest variations in inter-annual and intra-annual precipitation occurred over the western and northern parts, while the lowest variability was observed in the eastern part (i.e., the coastal region).

Rainfall Variability and Trend Analysis of Multiannual Rainfall in Romanian Plain

The IPCC climate models predict, for the Central Europe, are for climate changes, being seen variability of temperature, with a growing trend of 1-2,5° C (with 1° C for alpine zone – Carpathians and 2-2,5° C for plains). Current observations in the Romanian plain are not consistent, with an existence of a multiannual variability of temperature and precipitations depending on cyclonal and anti-ciclonal activity. The research is based on calculation of reduced centered index, also the graphical chronological method in information processing (MGCTI) of „Bertin Matrix” type, to show current trends of the spatio-temporal variability of precipitation in the context of global climate change. These are in line with the movement of air masses in Europe in general, and implicitly in Romania, with particular regard to the southern region of the country where the Romanian Plain. The variability of short-term global climate is generally associated with coupling phases of oceanic and atmospheric phenomena including El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). While El Niño Southern Oscillation (ENSO) affects climate variability in the world, the North Atlantic Oscillation (NAO) is the climate model dominant in the North Atlantic region. The latter cyclic oscillation whose role is still under debate could explain the variability of rainfall in much of the, central Europe area, and support the hypothesis of a return of the rains marking the end of years of drought in Romanian plain. Faced with such great changes that today affect the central Europe region and given the complexity of spatial and temporal dimensions of the climatic signal, a more thorough research of causes and retroactions would allow for a better understanding of the mechanisms behind this new trend.

Patterns of change in high frequency precipitation variability over North America

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data, we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. Further, these changes are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Existence of localized clusters with opposing trend to that of broader geographic variation illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns over the entire North American continent have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.

Increase of Elderly Population in the Rainstorm Hazard Areas of China

In light of global warming, increased extreme precipitation events have enlarged the population exposed to floods to some extent. Extreme precipitation risk assessments are of great significance in China and allow for the response to climate change and mitigation of risks to the population. China is one of the countries most influenced by climate change and has unique national population conditions. The influence of extreme precipitation depends on the degree of exposure and vulnerability of the population. Accurate assessments of the population exposed to rising rainstorm trends are crucial to mapping extreme precipitation risks. Studying the population exposed to rainstorm hazard areas (RSHA) at the microscale is extremely urgent, due to the local characteristics of extreme precipitation events and regional diversity of the population. The spatial distribution of population density was mapped based on the national population census data from China in 1990, 2000 and 2010. RSHA were also identified using precipitation data from 1975-2015 in China, and the rainstorm tendency values were mapped using GIS in this paper. The spatial characteristics of the rainstorm tendencies were then analyzed. Finally, changes in the population in the RSHA are discussed. The results show that the extreme precipitation trends are increasing in southeastern China. From 1990 to 2010, the population in RSHA increased by 110 million, at a rate of 14.6%. The elderly in the region increased by 38 million at a rate of 86.4%. Studying the size of the population exposed to rainstorm hazards at the county scale can provide scientific evidence for developing disaster prevention and mitigation strategies from the bottom up.

TOTAL AND EXTREME PRECIPITATION CHANGES OVER THE NORTHEASTERN UNITED STATES

The Northeastern United States has experienced a large increase in precipitation over recent decades. Annual and seasonal changes of total and extreme precipitation from station observations in the Northeast are assessed over multiple time periods spanning 1901-2014. Spatially averaged, both annual total and extreme precipitation across the Northeast have increased significantly since 1901, with changepoints occurring in 2002 and 1996, respectively. Annual extreme precipitation has experienced a larger increase than total precipitation; extreme precipitation from 1996-2014 was 53% higher than from 1901-1995. Spatially, coastal areas received more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the domain. Increases in annual total precipitation across the 2002 changepoint have been driven by significant total precipitation increases in fall and summer, while increases in annual extreme precipitation across the 1996 changepoint have been driven by significant extreme precipitation increases in fall and spring. The ability of gridded observed and reanalysis precipitation data to reproduce station observations was also evaluated. Gridded observations perform well in reproducing averages and trends of annual and seasonal total precipitation, but extreme precipitation trends show significantly different spatial and domain-averaged trends than station data. North American Regional Reanalysis generally underestimates annual and seasonal total and extreme precipitation means and trends relative to station observations, and also shows substantial differences in the spatial pattern of total and extreme precipitation trends within the Northeast.

Recent changes in daily climate extremes in an arid mountain region, a case study in northwestern China's Qilian Mountains

Changes in climate extremes pose far-reaching consequences to ecological processes and hydrologic cycles in alpine ecosystems of the arid mountain regions. Therefore, regional assessments in various climates and mountain regions are needed for understanding the uncertainties of the change trends for extreme climate events. The objective of this study was to assess the spatial distribution and temporal trends of extreme precipitation and temperature events responses to global warming on the arid mountain regions of China. Results found that temperature extremes exhibited a significant warming trend, consistent with global warming. Warming trend in autumn and winter were greater than in spring and summer. Besides, precipitation extremes also exhibited statistically increase trend, such as number of days with heavy precipitation and rain day precipitation, etc. The distribution of the number of rainy days was showed a significant increasing trend in many sites, indicating that the increase of rain day precipitation mainly contributed by the increase of single precipitation event duration and moderate-rain days. The greater increasing trend of extreme climate events mainly existed in higher altitudes. This results lend an evidence to earlier predictions that the climate in northwestern China is changing from cold-dry to warm-wet.

Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections

The water content of the topsoil is one of the key factors controlling biogeochemical processes, greenhouse gas emissions and biosphere - atmosphere interactions in many ecosystems, particularly in northern peatlands. In these wetland ecosystems, the water content of the photosynthetic active peatmoss layer is crucial for ecosystem functioning and carbon sequestration, and is sensitive to future shifts in rainfall and drought characteristics. Current peatland models differ in the degree in which hydrological feedbacks are included, but how this affects peatmoss drought projections is unknown. The aim of this paper was to systematically test whether the level of hydrological detail in models could bias projections of water content and drought stress for peatmoss in northern peatlands using downscaled projections for rainfall and potential evapotranspiration in the current (1991-2020) and future climate (2061-2090). We considered four model variants that either include or exclude moss (rain)water storage and peat volume change, as these are two central processes in the hydrological self-regulation of peatmoss carpets. Model performance was validated using field data of a peatland in northern Sweden. Including moss water storage as well as peat volume change resulted in a significant improvement of model performance, despite the extra parameters added. The best performance was achieved if both processes were included. Including moss water storage and peat volume change consistently reduced projected peatmoss drought frequency with >50%, relative to the model excluding both processes. Projected peatmoss drought frequency in the growing season was 17% smaller under future climate than current climate, but was unaffected by including the hydrological self-regulating processes. Our results suggest that ignoring these two fine-scale processes important in hydrological self-regulation of northern peatlands will have large consequences for projected climate change impact on ecosystem processes related to topsoil water content, such as greenhouse gas emissions.

Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather.

Large Scale Influences on Summertime Extreme Precipitation in the Northeastern United States

Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the Northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here we use a state-of-the-art atmospheric reanalysis to examine such events in detail. Daily extreme precipitation events defined at the 75^th and 95^th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern Era Retrospective Analysis for Research and Applications - Version 2 (MERRA-2) are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500 hPa heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95^th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10% of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cut off low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the east coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic scale baroclinic disturbances.

Rainfall Variability and Trend Analysis of Annual Rainfall in North Africa

The IPCC climate models predict, for the Maghreb countries, lower rainfall and increased aridity. Current observations in the three countries of central Maghreb (Morocco, Algeria, and Tunisia) are not consistent with these predictions. To demonstrate this new trend, a detailed regional analysis of rainfall evolution is conducted. This investigation is based on the calculation of the reduced centered index and the chronological graphical method of processing information (MGCTI) of “Bertin matrix” type. The results show extreme variability of this parameter and the severe past drought (more intense for Morocco, in which the drastic conditions from the seventies are observed). The results also show the beginning of a gradual return to wetter conditions since the early 2000s in Algeria and Tunisia and from 2008 for Morocco (this trend is confirmed by recent agricultural production data in 2011/2012 and 2012/2013).

Hydrological impacts of precipitation extremes in the Huaihe River Basin, China

Precipitation extremes play a key role in flooding risks over the Huaihe River Basin, which is important to understand their hydrological impacts. Based on observed daily precipitation and streamflow data from 1958 to 2009, eight precipitation indices and three streamflow indices were calculated for the study of hydrological impacts of precipitation extremes. The results indicate that the wet condition intensified in the summer wet season and the drought condition was getting worse in the autumn dry season in the later years of the past 50 years. The river basin had experienced higher heavy rainfall-related flooding risks in summer and more severe drought in autumn in the later of the period. The extreme precipitation events or consecutive heavy rain day events led to the substantial increases in streamflow extremes, which are the main causes of frequent floods in the Huaihe River Basin. The large inter-annual variation of precipitation anomalies in the upper and central Huaihe River Basin are the major contributor for the regional frequent floods and droughts.

Climate Shocks and the Timing of Migration from Mexico

Although evidence is increasing that climate shocks influence human migration, it is unclear exactly when people migrate after a climate shock. A climate shock might be followed by an immediate migration response. Alternatively, migration, as an adaptive strategy of last resort, might be delayed and employed only after available in-situ (in-place) adaptive strategies are exhausted. In this paper, we explore the temporally lagged association between a climate shock and future migration. Using multilevel event-history models, we analyze the risk of Mexico-U.S. migration over a seven-year period after a climate shock. Consistent with a delayed response pattern, we find that the risk of migration is low immediately after a climate shock and increases as households pursue and cycle through in-situ adaptive strategies available to them. However, about three years after the climate shock, the risk of migration decreases, suggesting that households are eventually successful in adapting in-situ.

Enemies with benefits: parasitic endoliths protect mussels against heat stress

Positive and negative aspects of species interactions can be context dependant and strongly affected by environmental conditions. We tested the hypothesis that, during periods of intense heat stress, parasitic phototrophic endoliths that fatally degrade mollusc shells can benefit their mussel hosts. Endolithic infestation significantly reduced body temperatures of sun-exposed mussels and, during unusually extreme heat stress, parasitised individuals suffered lower mortality rates than non-parasitised hosts. This beneficial effect was related to the white discolouration caused by the excavation activity of endoliths. Under climate warming, species relationships may be drastically realigned and conditional benefits of phototrophic endolithic parasites may become more important than the costs of infestation.

Demographic responses to weather fluctuations are context dependent in a long-lived amphibian

Weather fluctuations have been demonstrated to affect demographic traits in many species. In long-lived organisms, their impact on adult survival might be buffered by the evolution of traits that reduce variation in interannual adult survival. For example, skipping breeding is an effective behavioral mechanism that may limit yearly variation in adult survival when harsh weather conditions occur; however, this in turn would likely lead to strong variation in recruitment. Yet, only a few studies to date have examined the impact of weather variation on survival, recruitment and breeding probability simultaneously in different populations of the same species. To fill this gap, we studied the impact of spring temperatures and spring rainfall on survival, on reproductive skipping behavior and on recruitment in five populations of a long-lived amphibian, the yellow-bellied toad (Bombina variegata). Based on capture-recapture data, our findings demonstrate that survival depends on interactions between age, population and weather variation. Varying weather conditions in the spring result in strong variation in the survival of immature toads, whereas they have little effect on adult toads. Breeding probability depends on both the individual's previous reproductive status and on the weather conditions during the current breeding season, leading to high interannual variation in recruitment. Crucially, we found that the impact of weather variation on demographic traits is largely context dependent and may thus differ sharply between populations. Our results suggest that studies predicting the impact of climate change on population dynamics should be taken with caution when the relationship between climate and demographic traits is established using only one population or few populations. We therefore highly recommend further research that includes surveys replicated in a substantial number of populations to account for context-dependent variation in demographic processes.