Human influence on the seasonal cycle of tropospheric temperature

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983-2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

An ecological transcriptome approach to capture the molecular and physiological mechanisms of mass flowering in Shorea curtisii

Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation.

Monitoring spatiotemporal impacts of changes in land surface temperature on near eastern fire salamander (Salamandra infraimmaculata) in the Middle East

Persistence and coexistence of many pond-breeding amphibians depend on seasonality. Temperature, as a seasonal climate component, affects numerous physical and biological processes of pond-breeding amphibians. Satellite-derived land surface temperature (LST) is the radiative skin temperature of the land surface, which has received less attention in spatiotemporal seasonal habitat monitoring. The present study aims to evaluate the increasing and decreasing effects of LST trends at two levels: (1) habitat suitability and connectivity; (2) individual population sites and their longitudinal distribution (with increasing longitude). Habitat suitability modeling was conducted based on an ensemble species distribution model (eSDM). Using electrical circuit theory, the connectivity of interior and intact habitat cores was investigated. An average seasonal LST was prepared separately for each season from 2003 to 2021 and entered into Mann-Kendall (MK) analysis to determine the spatiotemporal effects of LST changes using the Z-Score (ZMK) at two confidence levels of 95 and 99%. Based on the results, in winter, 28.12% and 70.70% of the suitable habitat were affected by an increasing trend of LST at 95% and 99% confidence levels, respectively. The highest spatial overlap of the decreasing trend of LST with the suitable habitat occurred in summer and was 6.4% at the 95% confidence level and 4.2% at the 99% confidence level. Considering population site at 95% confidence interval, the increasing trend of LST was calculated to be 20.2%, 9.5%, 4.2%, and 6.3% of localities in winter, spring, summer, and autumn, respectively. At the 99% confidence level, these percentages reduced to 8.5%, 3.1%, 1%, and 1%, respectively. During winter and summer, based on the results of the longitudinal trend, an increasing trend of LST was observed in sites. Localities of Hatay and Iica village in Turkey experienced seasonally asynchronous climate change regimes. The approach used in this study allowed us to create a link between the life cycle and seasonal changes on a micro-scale (breeding sites) and macro-scale (distribution and connectivity). Findings of this paper can be effectively used by conservation managers to preserve S. infraimmaculata's metapopulation.

Linkages between Sphagnum metabolites and peatland CO2 uptake are sensitive to seasonality in warming trends

Plants produce a wide diversity of metabolites. Yet, our understanding of how shifts in plant metabolites as a response to climate change feedback on ecosystem processes remains scarce. Here, we test to what extent climate warming shifts the seasonality of metabolites produced by Sphagnum mosses, and what are the consequences of these shifts for peatland C uptake. We used a reciprocal transplant experiment along a climate gradient in Europe to simulate climate change. We evaluated the responses of primary and secondary metabolites in five Sphagnum species and related their responses to gross ecosystem productivity (GEP). When transplanted to a warmer climate, Sphagnum species showed consistent responses to warming, with an upregulation of either their primary or secondary metabolite according to seasons. Moreover, these shifts were correlated to changes in GEP, especially in spring and autumn. Our results indicate that the Sphagnum metabolome is very plastic and sensitive to warming. We also show that warming-induced changes in the seasonality of Sphagnum metabolites have consequences on peatland GEP. Our findings demonstrate the capacity for plant metabolic plasticity to impact ecosystem C processes and reveal a further mechanism through which Sphagnum could shape peatland responses to climate change.

Resolving the 21st century temperature trends of the upper troposphere-lower stratosphere with satellite observations

Historically, observational information about atmospheric temperature has been limited due to a lack of suitable measurements. Recent advances in satellite observations provide new insight into the fine structure of the free atmosphere, with the upper troposphere and lower stratosphere comprising essential components of the climate system. This is a prerequisite for understanding the complex processes of this part of the atmosphere, which is also known to have a large impact on surface climate. With unprecedented resolution, latest climate observations reveal a dramatic warming of the atmosphere. The tropical upper troposphere has already warmed about 1 K during the first two decades of the 21st century. The tropospheric warming extends into the lower stratosphere in the tropics and southern hemisphere mid-latitudes, forming a prominent hemispheric asymmetry in the temperature trend structure. Together with seasonal trend patterns in the stratosphere, this indicates a possible change in stratospheric circulation.

Quantification of human contribution to soil moisture-based terrestrial aridity

Current knowledge of the spatiotemporal patterns of changes in soil moisture-based terrestrial aridity has considerable uncertainty. Using Standardized Soil Moisture Index (SSI) calculated from multi-source merged data sets, we find widespread drying in the global midlatitudes, and wetting in the northern subtropics and in spring between 45°N-65°N, during 1971-2016. Formal detection and attribution analysis shows that human forcings, especially greenhouse gases, contribute significantly to the changes in 0-10 cm SSI during August-November, and 0-100 cm during September-April. We further develop and apply an emergent constraint method on the future SSI's signal-to-noise (S/N) ratios and trends under the Shared Socioeconomic Pathway 5-8.5. The results show continued significant presence of human forcings and more rapid drying in 0-10 cm than 0-100 cm. Our findings highlight the predominant human contributions to spatiotemporally heterogenous terrestrial aridification, providing a basis for drought and flood risk management.

A cross-scale approach to unravel the molecular basis of plant phenology in temperate and tropical climates

Plants have evolved to time their leafing, flowering and fruiting in appropriate seasons for growth, reproduction and resting. As a consequence of their adaptation to geographically different environments, there is a rich diversity in plant phenology from temperate and tropical climates. Recent progress in genetic and molecular studies will provide numerous opportunities to study the genetic basis of phenological traits and the history of adaptation of phenological traits to seasonal and aseasonal environments. Integrating molecular data with long-term phenology and climate data into predictive models will be a powerful tool to forecast future phenological changes in the face of global environmental change. Here, we review the cross-scale approach from genes to plant communities from three aspects: the latitudinal gradient of plant phenology at the community level, the environmental and genetic factors underlying the diversity of plant phenology, and an integrated approach to forecast future plant phenology based on genetically informed knowledge. Synthesizing the latest knowledge about plant phenology from molecular, ecological and mathematical perspectives will help us understand how natural selection can lead to the further evolution of the gene regulatory mechanisms in phenological traits in future forest ecosystems.

Shifting seasonal patterns of water availability: ecosystem responses to an unappreciated dimension of climate change

Seasonal patterns of water availability can differ dramatically among ecosystems, with well-known consequences for ecosystem structure and functioning. Less appreciated is that climate change can shift the seasonality of water availability (e.g. to wetter springs, drier summers), resulting in both subtle and profound ecological impacts. Here we (1) review evidence that the seasonal availability of water is being altered in ecosystems worldwide, (2) explore several mechanisms potentially driving these changes, and (3) highlight the breadth of ecological consequences resulting from shifts in the seasonality of water availability. We conclude that seasonal patterns of water availability are changing globally, but in regionally specific ways requiring more rigorous and nuanced assessments of ecosystem vulnerability as well as the ecological consequences.

Robust detection of forced warming in the presence of potentially large climate variability

Climate warming is unequivocal and exceeds internal climate variability. However, estimates of the magnitude of decadal-scale variability from models and observations are uncertain, limiting determination of the fraction of warming attributable to external forcing. Here, we use statistical learning to extract a fingerprint of climate change that is robust to different model representations and magnitudes of internal variability. We find a best estimate forced warming trend of 0.8°C over the past 40 years, slightly larger than observed. It is extremely likely that at least 85% is attributable to external forcing based on the median variability across climate models. Detection remains robust even when evaluated against models with high variability and if decadal-scale variability were doubled. This work addresses a long-standing limitation in attributing warming to external forcing and opens up opportunities even in the case of large model differences in decadal-scale variability, model structural uncertainty, and limited observational records.

Spatiotemporal variations and regional differences in air temperature in the permafrost regions in the Northern Hemisphere during 1980-2018

Surface air temperature is an important factor for the permafrost thermal state in the Northern Hemisphere. It is therefore necessary to understand the variations and regional differences in air temperature to determine the interactions between permafrost degradation and climate change. In this study, we used observational data from the National Centers for Environmental Information, the China Meteorological Administration, and the World Data Centre for Meteorology to quantitatively analyze the variations and regional differences in air temperature from 1980 to 2018. The results demonstrated that the annual mean air temperatures were low in continuous permafrost regions and high in sporadic and isolated permafrost regions, with a significant warming rate of 0.371 ± 0.086 °C/decade. Air temperatures warmed the slowest during the winter and fastest during the spring, and no "warming hiatus" was observed in the permafrost regions of the Northern Hemisphere. The spatial patterns of freezing degree-days (FDDs) and thawing degree-days (TDDs) had different spatial characteristics. The decreasing rate of FDDs was -6.97 °C·days/year, while the increasing rate of TDDs was 6.4 °C·days/year. The air temperatures and warming trends had largely regional differences with respect to high latitude, transitional, and high altitude permafrost regions. Air temperature and its warming trend was the highest in high altitude regions. In addition, air temperature warming trends gradually decreased from the continuous permafrost zone to the island permafrost zone. The FDDs had a significant decreasing trend from the continuous permafrost zone to the island permafrost zone, whereas TDDs exhibited the opposite trend. The results indicate that the air temperature warming rate in the permafrost regions was approximately 2.0 times that of the global warming rate, and 1.3 times the global land warming rate from 1980 to 2018. These findings offer a perspective on the differences in permafrost and its thermal state across different regions under climate change.

Reconstruction of the Daily MODIS Land Surface Temperature Product Using the Two-Step Improved Similar Pixels Method

The MODIS land surface temperature (LST) product is one of the most widely used data sources to study the climate and energy-water cycle at a global scale. However, the large number of invalid values caused by cloud cover limits the wide application of the MODIS LST. In this study, a two-step improved similar pixels (TISP) method was proposed for cloudy sky LST reconstruction. The TISP method was validated using a temperature-based method over various land cover types. The ground measurements were collected at fifteen stations from 2013 to 2018 during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) field campaign in China. The estimated theoretical clear-sky temperature indicates that clouds cool the land surface during the daytime and warm it at nighttime. For bare land, the surface temperature shows a clear seasonal trend and very similar across stations, with a cooling amplitude of 4.14 K in the daytime and a warming amplitude of 3.99 K at nighttime, as a yearly average. The validation result showed that the reconstructed LST is highly consistent with in situ measurements and comparable with MODIS LST validation accuracy, with a mean bias of 0.15 K at night (−0.43 K in the day), mean RMSE of 2.91 K at night (4.41 K in the day), and mean R2 of 0.93 at night (0.90 in the day). The developed method maximizes the potential of obtaining quality MODIS LST retrievals, ancillary data, and in situ observations, and the results show high accuracy for most land cover types.

Seasonality of primary productivity affects coastal species more than its magnitude

While the importance of extreme conditions is recognised, patterns in species' abundances are often interpreted through average environmental conditions within their distributional range. For marine species with pelagic larvae, temperature and phytoplankton concentration are key variables. Along the south coast of South Africa, conspicuous spatial patterns in recruitment rates and the abundances of different mussel species exist, with focal areas characterized by large populations. We studied 15 years of sea surface temperature (SST) and chlorophyll-a (chl-a) satellite data, using spectral analyses to partition their temporal variability over ecologically relevant time periods, including seasonal (101 to 365 days) and intra-seasonal cycles (20 to 100 days). Adult cover and mussel recruitment were measured at 10 sites along the south coast and regression models showed that about 70% of the variability in recruitment and adult cover was explained by seasonal variability in chl-a, while mean annual chl-a and SST only explained 30% of the recruitment, with no significant effect for adult cover. SST and chl-a at two upwelling centres showed less predictable seasonal cycles during the second half of the study period with a significant cooling trend during austral autumn, coinciding with one of the mussel reproductive peaks. This likely reflects recent changes in the Agulhas Current, the world's largest western boundary current, which affects coastal ecosystems by driving upwelling. Similar mechanisms probably operate in other marine systems with the potential to affect the distribution patterns of key ecosystem engineers. We propose that variability in the characteristic timescales of environmental fluctuations can explain the spatial patterns of abundance of foundational species by affecting larval recruitment. This is especially important in a context of global and pervasive climate change, as shifts in the periodicity of environmental fluctuations appear to reflect large scale climatic teleconnections driven by anthropogenic forcing.

Identifying a human signal in the North Atlantic warming hole

North Atlantic sea surface temperatures have large climate impacts affecting the weather of the Northern Hemisphere. In addition to a substantial warming over much of the North Atlantic, caused by increasing greenhouse gases over the 21st century, climate projections show a surprising region of considerable future cooling at midlatitudes, referred to as the North Atlantic warming hole. A similar pattern of surface temperature trends has been observed in recent decades, but it remains unclear whether this pattern is of anthropogenic origin or a simple manifestation of internal climate variability. Here, analyzing state-of-the-art climate models and observations, we show that the recent North Atlantic warming hole is of anthropogenic origin. Our analysis reveals that the anthropogenic signal has only recently emerged from the internal climate variability, and can be attributed to greenhouse gas emissions. We further show that a declining northward oceanic heat flux in recent decades, which is linked to this surface temperature pattern, is also of anthropogenic origin.

Most of the North Atlantic has seen strong increase in surface temperatures in recent decades, except for one region, which has been called the North Atlantic warming hole. Here, the authors employ detection and attribution techniques to show that this temperature pattern in recent decades is being caused by anthropogenic greenhouse gas emissions.

Floods and rivers: a circular causality perspective

An improved understanding of changes in flood hazard and the underlying driving mechanisms is critical for predicting future changes for better adaptation strategies. While recent increases in flooding across the world have been partly attributed to a range of atmospheric or landscape drivers, one often-forgotten driver of changes in flood properties is the variability of river conveyance capacity. This paper proposes a new framework for connecting flood changes to longitudinal variability in river conveyance, precipitation climatology, flows and sediment connectivity. We present a first step, based on a regional analysis, towards a longer-term research effort that is required to decipher the circular causality between floods and rivers. The results show how this system of interacting units in the atmospheric, hydrologic and geomorphological realm function as a nonlinear filter that fundamentally alters the frequency of flood events. To revise and refine our estimation of future flood risk, this work highlights that multidriver attribution studies are needed, that include boundary conditions such as underlying climate, water and sediment connectivity, and explicit estimations of river conveyance properties.

Past warming trend constrains future warming in CMIP6 models

Future global warming estimates have been similar across past assessments, but several climate models of the latest Sixth Coupled Model Intercomparison Project (CMIP6) simulate much stronger warming, apparently inconsistent with past assessments. Here, we show that projected future warming is correlated with the simulated warming trend during recent decades across CMIP5 and CMIP6 models, enabling us to constrain future warming based on consistency with the observed warming. These findings carry important policy-relevant implications: The observationally constrained CMIP6 median warming in high emissions and ambitious mitigation scenarios is over 16 and 14% lower by 2050 compared to the raw CMIP6 median, respectively, and over 14 and 8% lower by 2090, relative to 1995-2014. Observationally constrained CMIP6 warming is consistent with previous assessments based on CMIP5 models, and in an ambitious mitigation scenario, the likely range is consistent with reaching the Paris Agreement target.

Cyst-forming dinoflagellates in a warming climate

Many phytoplankton species, including many harmful algal bloom (HAB) species, survive long periods between blooms through formation of benthic resting stages. Because they are crucial to the persistence of these species and the initiation of new blooms, the physiology of benthic stages must be considered to accurately predict responses to climate warming and associated environmental changes. The benthic stages of dinoflagellates, called resting cysts, germinate in response to the combination of favorable temperature, oxygen-availability, and release from dormancy. The latter is a mechanism that prevents germination even when oxygen and temperature conditions are favorable. Here, evidence of temperature-mediated control of dormancy duration from the dinoflagellates Alexandrium catenella and Pyrodinium bahamense-two HAB species that cause paralytic shellfish poisoning (PSP)-is reviewed and presented alongside new evidence of complementary, temperature-based control of cyst quiescence (the state in which cysts germinate on exposure to favorable conditions). Interaction of the two temperature-based mechanisms with climate is explored through a simple model parameterized using results from recent experiments with A. catenella. Simulations demonstrate the importance of seasonal temperature cycles for the synchronization of cysts' release from dormancy and are consistent with biogeography-based inferences that A. catenella is more tolerant of warming in habitats that experience a larger range of seasonal temperature variation (i.e., have higher temperature seasonality). Temperature seasonality is much greater in shallow, long-residence time habitats than in deep, open-water ones. As warming shifts species' ranges, cyst beds may persist longer in more seasonally variable, shallow inshore habitats than in deep offshore ones, promoting HABs that are more localized and commence earlier each year. Recent field investigations of A. catenella also point to the importance of new cyst formation as a factor triggering bloom termination through mass sexual induction. In areas where temperature seasonality restricts the flux of new swimming cells (germlings) to narrow temporal windows, warming is unlikely to promote longer and more intense HAB impacts-even when water column conditions would otherwise promote prolonged bloom development. Many species likely have a strong drive to sexually differentiate and produce new cysts once concentrations reach levels that are conducive to new cyst formation. This phenomenon can impose a limit to bloom intensification and suggests an important role for cyst bed quiescence in determining the duration of HAB risk periods.

Ectomycorrhizal fungal communities in ice-age relict forests of Pinus pumila on nine mountains correspond to summer temperature

Ectomycorrhizal (ECM) fungi are critical symbionts of major forest trees, and their communities are affected by various environmental factors including temperature. However, previous knowledge concerning temperature effects does not exclude the effects of host species and coexisting plants, which usually change with temperature, and should be rigorously tested under the same vegetation type. Herein we examined ECM fungal communities in ice-age relict forests dominated by a single host species (Pinus pumila) distributed on nine mountains across >1000 km in Japan. Direct sequencing of rDNA ITS regions identified 154 ECM fungal species from 4134 ECM root-tip samples. Gradient analyses revealed a large contribution of temperature, especially summer temperature, to ECM fungal communities. Additionally, we explored global sequence records of each fungal species to infer its potential temperature niche, and used it to estimate the temperature of the observed communities. The estimated temperature was significantly correlated with the actual temperature of the research sites, especially in summer seasons, indicating inherent temperature niches of the fungal components could determine their distribution among the sites. These results indicate that temperature is still a significant determinant in structuring ECM fungal communities after excluding the effects of host species and coexisting plants. The results also imply that the rising temperature under global warming may have been affecting soil microbes unnoticeably, while such microbial community change may have been contributing to the resilience of the same vegetation.

Quantifying stochastic uncertainty in detection time of human-caused climate signals

Large initial condition ensembles of a climate model simulation provide many different realizations of internal variability noise superimposed on an externally forced signal. They have been used to estimate signal emergence time at individual grid points, but are rarely employed to identify global fingerprints of human influence. Here we analyze 50- and 40-member ensembles performed with 2 climate models; each was run with combined human and natural forcings. We apply a pattern-based method to determine signal detection time [Formula: see text] in individual ensemble members. Distributions of [Formula: see text] are characterized by the median [Formula: see text] and range [Formula: see text], computed for tropospheric and stratospheric temperatures over 1979 to 2018. Lower stratospheric cooling-primarily caused by ozone depletion-yields [Formula: see text] values between 1994 and 1996, depending on model ensemble, domain (global or hemispheric), and type of noise data. For greenhouse-gas-driven tropospheric warming, larger noise and slower recovery from the 1991 Pinatubo eruption lead to later signal detection (between 1997 and 2003). The stochastic uncertainty [Formula: see text] is greater for tropospheric warming (8 to 15 y) than for stratospheric cooling (1 to 3 y). In the ensemble generated by a high climate sensitivity model with low anthropogenic aerosol forcing, simulated tropospheric warming is larger than observed; detection times for tropospheric warming signals in satellite data are within [Formula: see text] ranges in 60% of all cases. The corresponding number is 88% for the second ensemble, which was produced by a model with even higher climate sensitivity but with large aerosol-induced cooling. Whether the latter result is physically plausible will require concerted efforts to reduce significant uncertainties in aerosol forcing.

Millennial-Scale Climate Variability and Dinoflagellate-Cyst-Based Seasonality Changes Over the Last ~150 kyrs at "Shackleton Site" U1385

During the last glacial period, climate conditions in the North Atlantic region were determined by the alternation of relatively warm interstadials and relatively cool stadials, with superimposed rapid warming (Dansgaard-Oeschger) and cooling (Heinrich) events. So far little is known about the impact of these rapid climate shifts on the seasonal variations in sea surface temperature (SST) within the North Atlantic region. Here, we present a high-resolution seasonal SST record for the past 152 kyrs derived from Integrated Ocean Drilling Program "Shackleton" Site U1385, offshore Portugal. Assemblage counts of dinoflagellates cysts (dinocysts) in combination with a modern analog technique (MAT), and regression analyses were used for the reconstructions. We compare our records with previously published SST records from the same location obtained from the application of MAT on planktonic foraminifera. Our dinocyst-based reconstructions confirm the impression of the Greenland stadials and interstadials offshore the Portuguese margin and indicate increased seasonal contrast of temperature during the cold periods of the glacial cycle (average 9.0 °C, maximum 12.2 °C) with respect to present day (5.1 °C), due to strong winter cooling by up to 8.3 °C. Our seasonal temperature reconstructions are in line with previously published data, which showed increased seasonality due to strong winter cooling during the Younger Dryas and the Last Glacial Maximum over the European continent and North Atlantic region. In addition, we show that over longer time scales, increased seasonal contrasts of temperature remained characteristic of the colder phases of the glacial cycle.

Are lizards sensitive to anomalous seasonal temperatures? Long-term thermobiological variability in a subtropical species

Alterations in thermal niches have been widely associated with the Anthropocene erosion of reptiles' diversity. They entail potential physiological constraints for organisms' performance, which can lead to activity restrictions and impact fitness and demography. Reptiles are ectotherms which rely on seasonal periodicity to maximize the performance of biological functions. Despite it, the ecological implications of shifts in local temperatures are barely explored at the seasonal scale. This study aims to assess how changes in air temperature and substrate temperature affect the activity, body temperature (Tb) and thermoregulation patterns of the sand lizard, Liolaemus arambarensis (an endangered, microendemic species from southern Brazil), throughout a four-year period. Field surveys were conducted monthly on a restricted population in a sand-dune habitat. The annual fluctuations of the seasonal temperatures led to significant changes in the activity and Tb of L. arambarensis and shaped thermoregulation trends, suggesting biological plasticity as a key factor in the face of such variability. Lizards tended to maintain seasonal Tb in mild and harsh seasons through increased warming/cooling efforts. Anomalous winter conditions seemed especially critical for individual performance due to their apparent high impact favouring/constraining activity. Activity and thermoregulation were inhibited in frigid winters, probably due to a vulnerable physiology to intense cold spells determined by higher preferred body temperatures than Tb. Our results warn of a complex sensitivity in lizards to anomalous seasonal temperatures, which are potentially enhanced by climate change. The current work highlights the importance of multiannual biomonitoring to disentangle long-term responses in the thermal biology of reptiles and, thereby, to integrate conservation needs in the scope of global change.