Minimum Winter Temperature Research Articles

Substantial Cold Bias During Wintertime Cold Extremes in the Southern Cascadia Region in Historical CMIP6 Simulations

AbstractGlobal climate models often simulate atmospheric conditions incorrectly due to their coarse grid resolution, flaws in their dynamics, and biases resulting from parameterization schemes. Here we document a bias in the magnitude and extent of minimum temperature extremes in the CMIP6 model ensemble, relative to ERA5. The bias is present in the southern Cascadia region (i.e., Pacific Northwestern United States and southwestern British Columbia, Canada, spanning from the coast to the Rocky Mountains), with some models showing a bias magnitude in excess of −10°C in the first percentile of daily winter minimum temperature. The sea level pressure pattern for these events is similar in CMIP6 models and ERA5, showing high anomalies in the Northeast Pacific that are indicative of an atmospheric blocking pattern and consequently more northerly flow. Though this atmospheric blocking pattern is typically concurrent with cold winter temperatures across much of North America, Rocky and Cascade mountain ranges prevent the cold air from reaching the southern Cascadia region as confirmed by the observations and reanalysis. Our results suggest that the bias in CMIP6 minimum temperatures is a result of unresolved topography in the Rockies and Cascade mountain ranges, such that the terrain does not adequately block cold air advection from reaching the southern Cascadia region.

Temperature and carotid intima-medial thickness: The coronary artery risk development in young adults (CARDIA) study

BackgroundFew studies have examined the role of long-term (≥1 year) ambient temperature with quantitative traits of early-stage cardiovascular disease (CVD) such as carotid intima-medial thickness (cIMT). Our objective was to examine associations between temperature and cIMT, a measure of subclinical atherosclerosis. MethodsThis study examined data from 3257 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study, aged 18–30 years at baseline (1985–1986). We used North America Land Data Assimilation System data to derive 12 metrics of ambient daily temperature: Mean, minimum, maximum, and standard deviation temperature in summer, winter, and year-round. We examined associations with cIMT in separate cross-sectional multivariable models at CARDIA year 20 (2005–2006) as well as stratified analyses by self-reported race and sex. We also prospectively examined cumulative temperature by summing temperature variables from Y0-Y20. ResultsAccounting for study center attenuated most associations between cIMT and ambient temperature exposure, but the winter standard deviation remained associated (overall β = −0.0104 mm/°C, 95 % CI: −0.0150 to −0.0059). Minimum summer temperature was also associated with cIMT in the overall study population (β = 0.0020 mm/°C, 95 % CI: 0.0005–0.0035). Associations did not differ substantially by race, but women had stronger associations than men. Cumulative temperature was not associated with cIMT. ConclusionsOur findings suggest a role of geography, particularly ambient temperature in cIMT. Future research to address potential residual confounding is necessary, but if validated these findings have implications for policy and strategies to mitigate health impacts of climate change.

Modeling the distribution of hemlock woolly adelgid under several climate change scenarios

The hemlock woolly adelgid (HWA), Adelges tsugae Annand, has invaded eastern North America and caused significant mortality to eastern hemlock, Tsuga canadensis (L.) Carrière. In eastern North America, HWA’s range is theorized to be limited by minimum winter temperatures. As climate change reduces the severity of winter, the risk of northward expansion of HWA increases. This study used maximum entropy species distribution modeling in conjunction with HWA occurrence records and future climate projections to model habitat suitability for HWA throughout the range of eastern hemlock. Species distribution models were created for present and future climatic conditions using both historical climatic data and future climatic emissions scenarios for mid- and late-century. In addition, present climatic condition reference models for western North America and Asia were generated for comparison with HWA’s current range and earlier predictions of the potential range in eastern North America. Under a low emissions scenario, HWA will be capable of invading almost the entire range of eastern hemlock by the end of the century. More extreme warming scenarios result in a more rapid northwards shift by mid-century. The consequences for eastern hemlock are significant, with infestations likely to become more widespread and severe due to climate change.

Forecast models for start and peak dates of Poaceae pollen season in Tétouan (NW Morocco) using multiple regression analysis.

Poaceae pollen is one of the most widespread sources of aeroallergens in the world. The aim of this study is to build predictive models for the pollen season start day (PSsd) and peak dates of the Poaceae pollen season and thus give an overview of the climatic parameters that have the greatest influence. In Tétouan, sampling was carried out using a volumetric spore trap of the Burkard Hirst type. The relationships between the PSsd, peak dates and meteorological parameters were determined using correlation analysis. The models were constructed using multiple regression analysis with data from 2008 to 2019 and tested on data from 2022. The PSsd was especially significantly influenced by minimum temperature during winter and precipitation in the autumn of the previous year. The peak dates were significantly correlated with precipitation in January, March and April, but not with temperature. Three models were obtained for each of the season's parameters; the most accurate model for the PSsd explained a variability of 61% and includes as main predictors rainfall from the autumn of the previous year and the mean daily average temperature from 23 February to 8 March. The two most efficient peak dates models included precipitation in January and April as the main predictor variables, and explained greater variability (87 and 88%). Precipitation in autumn and the mean daily and the sum of minimum temperature in winter, showed significant decreasing tendencies. However, the PSsd trend delay was not statistically significant. This study draws the importance of the weather during preseason for grass pollen production and emphasises the usefulness of the models for allergic patients to take preventive measures and for healthcare professionals in allergy therapy.

Predictor importance in habitat suitability models for invasive terrestrial plants

AbstractAimDue to the socioeconomic and environmental damages caused by invasive species, predicting the distribution of invasive plants is fundamental for effectively targeting management efforts. A habitat suitability model (HSM) is a powerful tool to predict potential habitat of invasive species to help guide the early detection of invasive plants. Despite numerous studies of the predictors used in HSMs, there is little consensus about the most appropriate predictors to use in creating ecologically realistic predictions from HSMs.LocationThe contiguous United States.MethodsWe explore 220 invasive terrestrial plant species' existing HSMs constructed with consistent modelling algorithms, background generation methods, predictor resolution, and geographic extent, and calculate the relative importance of predictors for each species. We sort predictors into eight groups (topography, temperature, disturbance, atmospheric water, landscape water, substrate, biotic interaction, and radiation) and compare the importance of predictor groups by plant lifeforms and phylogenetic relatedness.ResultsHuman modification and minimum winter temperature were generally the two highest performing individual predictors across the species studied. The highest‐performing predictor groups were disturbance, temperature, and atmospheric water. Across lifeforms, there were minimal differences in the influences of predictor groups, although woody plant models exhibited the largest differences in predictor importance when compared with non‐woody plant models. Additionally, we found no significant relationship between the importance of predictor groups and phylogenetic relatedness.Main ConclusionsThis study has implications for informing predictor selection in invasive plant HSMs, leading to more reliable and accurate models of invasive terrestrial plants. Our results emphasize the need to critically select predictors included in HSMs, with special consideration to temperature and disturbance predictors, to accurately predict habitat of invasive plant for detection and response of invasive plant species. With more accurate predictions, managers will be better prepared to address invasive species and reduce their threats to landscapes.

Amplification of temperature extremes in Arabian Peninsula under warmer worlds

The Paris Agreement and the Special Report on Global Warming of 1.5 °C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11–0.67 °C and 0.09–0.70 °C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies.

Meteorological regime of the Elbrus high-mountain zone during the accumulation period

Unique automated meteorological observations were carried out on the southern slope of Elbrus, near Pastukhov Rocks, at 4700 m a.s.l., during the 2021–2022 accumulation season. Data were obtained on air temperature, humidity, wind speed and direction, snowdrift and radiation fluxes with a temporal resolution of 1 minute or less. Analysis of the data series showed that the representative winter air temperature at this altitude on the southern slope of Elbrus is –10 °С, and the minimum is –36.4 °С; the partial pressure of water vapor does not exceed 3.5 hPa. At the same time, the average daily maximum of wind speed amounted 13.1 m s–1 with the absolute maximum of 54.1 m/s. Snowstorms with a snow transport intensity of more 0.1 kg/m2s–1 are quite common phenomenon in winter, while the maximum average value of the transport reaches 0.87 kg/m2s–1. An empirical relationship was established between the average hourly wind speed and the maximum gust speed for the same period, and it was shown that for these conditions the wind gust exceeds the average hourly wind speed by 1.8 times, while the representative value of the standard deviation of wind speed is 5.8 m s–1. This information may be useful not only for the glaciologic problems and modeling, but also for construction and engineering surveys, which are relevant in view of the present-day active development of the mountain ski infrastructure on the southern macro-slope of the Elbrus. In addition, the obtained series of instrumental observations were used to assess the quality of reanalysis data for high mountain regions taking as an example the ERA5. The ERA5 reanalysis was demonstrated to reproduce rather successfully the air temperature, wind speed and humidity in high mountain conditions, but extreme values for all these parameters are underestimated. Thus, the minimum temperature in winter turned out to be overestimated by 2 °C, and the maximum was underestimated by 4 °C, while the wind speed, according to the ERA5 reanalysis, never exceeded 40 m/s during the above observation period. It is also shown that the FlowCapt4 acoustic blizzard gauge (driftometer) can be used to estimate average wind speeds since it is less sensitive to severe high-altitude conditions compared to acoustic and cup anemometers.

Modeling habitat suitability of wild rice (Zizania spp.) to inform restoration efforts in Michigan, U.S.A.

Wild rice (Zizania aquatica and Zizania palustris) has been an integral component of Michigan wetlands for thousands of years, but is disappearing today due to habitat loss. Identifying suitable habitats and associated environmental conditions for wild rice viability is a critical step toward guiding ongoing restoration efforts statewide. To this end, we used maximum entropy (Maxent), a presence‐only species distribution model, to characterize habitat preferences of wild rice in Michigan and identify suitable habitats for restoration. Extant wild rice occurrences were mapped alongside 11 environmental variables using Maxent to determine probabilities of occurrence throughout the state. The Maxent model (AUC > 0.9) predicted the highest probabilities of wild rice occurrence in the western and southwestern regions of the state. Climatic variables, biotic interactions, and anthropogenic disturbances were all found to influence wild rice occurrence, with land cover, lower May precipitation, and minimum winter temperatures having the highest contributions to model predictions. The results of this study suggest that statewide restoration of wild rice in Michigan may be possible, although localized differences in environmental conditions should be accounted for when selecting restoration sites. With further refinement and the inclusion of more key environmental predictors of wild rice viability, habitat suitability models such as the one created in this study may be powerful and effective tools in guiding wild rice restoration efforts nationally.

Anomalous Warm Temperatures Recorded using Tree Rings in the Headwater of the Jinsha River during the Little Ice Age

As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the “cooler” Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions.

Influence of autumn Kara Sea ice on the subsequent winter minimum temperature over the Northeast China

AbstractMany previous studies have examined the influence of Arctic sea ice on the weather/climate of the Northern Hemisphere. However, the precursor signals of Arctic sea ice regarding East Asian winter low temperatures, which are important for climate prediction, have received little attention. This study identified an out‐of‐phase relationship between the autumn sea ice area of the Kara Sea (SICK) and subsequent winter minimum temperature in Northeast China (NEC) during 1979–2019, that is, diminished SICK facilitates cooling anomalies at NEC. Further results showed that the Arctic Oscillation (AO) acts as a bridge in the linkage between the autumn SICK and minimum temperature in NEC. Diminished autumn SICK leads to a weakened polar vortex in both the troposphere and the stratosphere in the subsequent winter through vertical propagation of planetary waves, contributing to a negative phase of the AO. Accordingly, the SICK is followed by anomalous Rossby wave train that originates from Mediterranean Sea and propagates eastward to Northeast Asia. Thus, the SICK has substantially influences on the Mongolia cyclone and minimum temperature in NEC by modulation of the AO. Moreover, the shrinking SICK could lead to the upper‐level decelerated westerly anomalies at East Asia through altering the equator‐to‐pole temperature gradient and induce negative minimum temperature anomalies at NEC. The results of this study have importance regarding the prediction of low temperature anomalies over NEC.

Freezing and Mechanical Failure of a Habitat-Forming Kelp in the Rocky Intertidal Zone.

Kelp and other habitat-forming seaweeds in the intertidal zone are exposed to a suite of environmental factors, including temperature and hydrodynamic forces, that can influence their growth, survival, and ecological function. Relatively little is known about the interactive effect of temperature and hydrodynamic forces on kelp, especially the effect of cold stress on biomechanical resistance to hydrodynamic forces. We used the intertidal kelp Egregia menziesii to investigate how freezing in air during a low tide changes the kelp's resistance to breaking from hydrodynamic forces. We conducted a laboratory experiment to test how short-term freezing, mimicking a brief low-tide freezing event, affected the kelp's mechanical properties. We also characterized daily minimum winter temperatures in an intertidal E. menziesii population on San Juan Island, WA, near the center of the species' geographic range. In the laboratory, acute freezing events decreased the strength and toughness of kelp tissue by 8-20% (change in medians). During low tides in the field, we documented sub-zero temperatures, snow, and low canopy cover (compared to summer surveys). These results suggest that freezing can contribute to frond breakage and decreased canopy cover in intertidal kelp. Further work is needed to understand whether freezing and the biomechanical performance in cold temperatures influence the fitness and ecological function of kelp and whether this will change as winter conditions, such as freezing events and storms, change in frequency and intensity.

Variations in Seed Dormancy Occurrence and Their Classifications in Thirteen Actinidia Species

As differences in seed dormancy between Actinidia species have not been reported previously, in this study we characterized the variation in the dormancy of seeds in 13 kiwifruit species that originated from different regions of China and Taiwan, and for which mature plants are now growing in New Zealand orchards. Dormancy-breaking treatments, including cold-moist stratification, seed coat scarification and soaking in water and gibberellic acid (GA3), were tested for their efficacy in alleviating dormancy and improving final germination and germination rates. In addition, we assessed seed viability using RNA integrity analysis to distinguish dead seeds from dormant seeds. This study identified that dormancy type in Actinidia seeds is species-specific and can be morphological, morphophysiological or a combination of physiological and physical, and that seed RNA integrity is a useful metric to incorporate into seed dormancy studies. Our results also suggest that species originating from colder climates that experience large differences between winter minimum and summer maximum temperatures exhibit physiological dormancy and require cold-moist stratification, contrasting with species originating in milder climates. Interestingly, although not all seeds from all the species were dormant, the proportion of dormant seeds in each species did not correlate to the climatic data of the region from which they originated. These findings provide new insights into mechanisms of seed dormancy in kiwifruit.

Synoptic dynamics of cold waves over north India: Underlying mechanisms of distinct cold wave conditions

The cold air outbreaks in the northern parts of India exert significant impacts on human health, energy, agriculture and transportation. In this study, we investigate the synoptic dynamics of cold waves and their linkages to large scale circulations for the winter period from 1982 to2020. Cold waves are classified into normal and intense (NCWs and ICWs) based on intensity and we examine the underlying mechanisms of formation and their atmospheric drivers. Notably, the spatial extent of the ICWs is almost double than that of normal ones thereby having the potential to affect a wider population. The NCWs are often influenced by western disturbances, leading to the inflow of cold air from Siberia (a region of shallow high). In contrast, ICWs are mostly linked to the presence of an omega block over the Ural-Siberian region. The downstream portion of the Ural block favours the inflow of cold northerlies into north India, leading to cold air advection and extreme cold wave conditions. The influence of Arctic warming for ICWs is further confirmed through a prominent Quasi-Resonant Amplification (QRA) fingerprint. Furthermore, La Niña condition seems to play a crucial role in triggering ICWs over north India. During La Niña, the prominent low level cyclonic anomaly helps in advecting the cold air from the higher latitudes into the country. The frequency as well as the duration of cold wave events are also found to be higher in La Niña years compared to El Niño and neutral years. The trend analysis of cold wave events over north India reveals a significant decrease in the frequency, duration and intensity during the analysis period due to a combination of various factors such as rising winter minimum temperatures (due to global warming), decreasing number of synoptic winter weather systems and Arctic amplification.

A Bayesian network model to disentangle the effects of stand and climate factors on tree mortality of Chinese fir plantations

Tree mortality is a complex process that not only be affected by the various factors, such as stand and climate factors, but also the various long-term effects of the factors to each other. In this study, based on the long-term spacing trials of Chinese fir in four regions of southern China, a Bayesian network was used to model tree mortality in response to stand and climate factors, as well as comparing this approach with logistic regression and random forest method. The results showed that the Bayesian network method had the highest accuracy in predicting tree mortality. In addition, the Bayesian network approach could find the dependency in the relationship between data and provide a theoretical framework for modeling uncertainty by using probabilistic calculus and underlying graph structure. Sensitivity analysis showed relative diameter was the most important factor, and temperature was the most important climate factor. Furthermore, climate factors not only directly affected tree mortality, but also indirectly affected tree mortality through affecting relative diameter, stand density and Gini coefficient. We also found that stand competition, structural heterogeneity and age affected tree mortality under climate change, and a moderate level of competition condition and stand structure heterogeneity weakened the negative impact of climate factors on tree mortality. Old trees were more sensitive to climate change than young trees, especially under extreme climate conditions. Besides, we found that tree mortality was negatively correlated with moderate annual precipitation, winter mean minimum temperature, and stand structure (Gini), and low age, but positively correlated with low relative diameter, high density and age. The results will provide adaptive options for effective forest management of Chinese fir plantations under the backdrop of global climate change in the future.

A 250-Year Winter Minimum Temperature Reconstruction Based on Tree Rings from Luoji Mountain, Southwest China

Annually resolved temperature records spanning the past few centuries are limited in Southwest China. In this paper, we present a robust 250-year winter minimum temperature reconstruction based on the tree rings of Abies georgei Orr from Luoji Mountain, Southwest China. The tree rings exhibit significant correlations with winter minimum temperatures (Tmin) from the previous November to the current March (pNov–cMar). Based on this relationship, we reconstructed pNov-cMar Tmin from 1765 to 2014. This reconstruction accounts for 37.8% of the Tmin variance during the instrumental 1960–2014 period. Our reconstruction reveals five warm periods (1765–1785, 1795–1804, 1827–1883, 1901–1907, 1989–2014) and four cold periods (1786–1794, 1805–1826, 1884–1900, 1908–1988) over the past 250 years. Spectral analyses revealed several significant interannual (2.3–2.4a, 3.9–4.2a, 8.9–9.7a) and interdecadal (23.0–28.9a) cycles in our reconstruction series. Both spatial correlation analysis and the inter-comparison of paleoclimate records revealed that the winter Tmin reconstruction had significant positive correlations with the Atlantic Multidecadal Oscillation (AMO), with relatively consistent warm and cold periods in their variations over the past 250 years.

Establishment and postrelease recovery of Laricobius nigrinus and Laricobius osakensis (Coleoptera: Derodontidae), released for biological control of Adelges tsugae (Hemiptera: Adelgidae), in the Northeastern United States.

Hemlock woolly adelgid (HWA), Adelges tsugae Annand, is a major forest pest in the eastern United States responsible for killing millions of eastern hemlock, Tsuga canadensis (L.) Carrière and Carolina hemlock, T. caroliniana Engelmann. The US biological control program for HWA has largely invested in the rearing and release of Laricobius nigrinus Fender and more recently L. osakensis Montgomery and Shiyake. Though the establishment of L. nigrinus has been well-documented in the southern, mid-Atlantic, and coastal portions of the northeastern United States, documentation in interior areas of the northeastern United States is limited. Establishment of L. osakensis in the northeastern United States has not yet been documented. Release locations in the northeastern United States were surveyed for L. nigrinus and L. osakensis establishment to examine the relationship between establishment success and winter temperatures, as winter minimum temperatures likely limit the northern range of introduced Laricobius species. Our results suggest that L. nigrinus establishment is limited by winter minimum temperatures and that the probability of establishment declines as absolute minimum temperature declines. We found L. nigrinus established at sites in Maine, New York, and Pennsylvania, but did not recover any L. nigrinus in Massachusetts, New Hampshire, or Vermont. Similarly, we found L. osakensis established at sites in New York and Pennsylvania and recovered individuals in Maine, though further sampling is necessary to confirm presence of the F3 generation. We also report the first field observation of reproduction of silver flies, Leucotaraxis argenticollis (Diptera: Chamaemyiidae), released predator of HWA, in the eastern United States.

Trends in minimum winter temperatures and date of the last spring frost in the main fruit-growing areas of Spain

Trends in minimum winter temperatures and date of the last spring frost in the main fruit-growing areas of Spain

Discovery of an underground chamber to protect kings and queens during winter in temperate termites

Overwintering is a critical part of the annual cycle for species that live in temperate, polar, and alpine regions. Consequently, low-temperature biology is a key determinant of temperate species distribution. Termites are distributed predominantly in tropical regions, and a limited number of species are found in the temperate zone. Here, in the termite Reticulitermes speratus, we report the discovery of an underground chamber that protects kings and queens to survive the winter, which is separate from the one they used during the warmer breeding season. In the spring, the royals inhabited decayed logs on the ground, then moved to their underground chamber located in the roots of stumps in the fall. The winter minimum temperature measured in the royal chamber was higher than that in the logs on the ground. In overwintering termites, the kings and queens had higher cold tolerance than workers and soldiers. Air temperatures dropped below the critical temperature multiple times, as evidenced from the past 140 years of weather records in Kyoto. These results demonstrated the survival strategies of reproductives to overcome the environment at the latitudinal limits. This study helps further the understanding of the termite’s seasonal phenology, long-term survivorship, and life cycle.

Climate seasonality and extremes influence net primary productivity across California’s grasslands, shrublands, and woodlands

Terrestrial vegetation is a substantial carbon sink and plays a foundational role in regional and global climate change mitigation strategies. The state of California, USA, commits to achieving carbon neutrality by 2045 in part by managing terrestrial ecosystems to sequester more than 80 MMT of CO2. We used a 35-year net primary productivity (NPP) remote sensing product with gridded climate, soil, topography, and vegetation data to evaluate spatiotemporal drivers of NPP variation and identify drivers of NPP response to extremes in water availability in California’s major grasslands, shrublands, and woodlands. We used generalized boosted models (GBMs) and linear mixed effects models (LMMs) to identify influential predictors of NPP and characterize their relationships with NPP across seven major vegetation cover types: annual grasslands, blue oak, chamise-redshank chaparral, coastal scrub, coastal oak woodland, mixed chaparral, and montane hardwood. Climate seasonality, specifically greater precipitation and warmer minimum temperatures in early spring and winter, was associated with greater NPP across space, particularly in chaparral, blue oak, and grassland systems. Maximum annual temperature and climatic water deficit (CWD) showed a negative relationship with NPP in most vegetation cover types, particularly chaparral and coastal scrub. We found a significant decrease in NPP over time in most vegetation types, appearing to coincide with the 2012–2016 California mega-drought. However, response to water availability extremes differed by vegetation type. In most vegetation types, especially grasslands, increases in NPP in extreme wet years were greater than declines in NPP in dry years. Our analysis characterizes several climate risks and conservation opportunities in using California’s natural lands to store carbon. Namely, shifts in climate seasonality and water availability extremes threaten these systems’ ability to fix carbon, yet hotspots of NPP resilience may exist and could be enhanced through conservation and restoration. Additional mechanistic work can help illuminate these opportunities and prioritize conservation decision making.

Sex, body size, and winter weather explain migration strategies in a partial migrant population of American Kestrels

Abstract Given increasing evidence that climate change affects the annual cycles of birds, it is important to understand the mechanisms underlying individual migration strategies and population-level patterns in partial migrants. In this study, we found that thermoregulation (body size and winter temperatures) was a key driver of American Kestrel (Falco sparverius) migration decisions. The annual proportion of migrants in the population, however, was not explained by winter weather and may be the result of differential survival. We measured stable hydrogen isotope values (δD) of talon tissues collected from 501 breeding and overwintering birds to distinguish migrant from resident kestrels in a partially migratory population of American Kestrels in southwestern Idaho in 2013–2021. We then evaluated drivers of migration decisions by assessing potential correlates of migration strategies, whether individuals switched migration strategies between years, and whether the proportion of migrants in the population changed over time or was correlated with winter weather. Male kestrels were 1.6 times more likely to migrate than females, and in colder than average winters, smaller birds of both sexes were more likely to migrate than larger birds. Only 27% of 26 recaptured individuals showed evidence of switching their migration strategies on an annual basis. There was no temporal trend in the proportion of migrants in the population, but proportions varied between years. Interestingly, there was no association between winter minimum temperature anomalies and annual migrant proportions in the population, suggesting that differential over-winter survival, or other stochastic processes, may play an important role in population composition. As winters continue to warm, fewer kestrels may migrate and more may remain resident on breeding grounds. However, it is unclear how changes in migration strategies might affect population-level patterns and resilience to climate change.