Warm Years Research Articles

Placing 21st Century Warming in Southern California, USA in a Multi-Century Historical Context

Warming in southern California during the 21st century is unprecedented in the instrumental record. To place this warming in a multi-century historical context, we analyzed tree ring data sampled from Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana) collected from minimally disturbed, old-growth high-elevation forests within Mt. San Jacinto State Park California, USA. Based on a calibration/verification period of 1960–2020 between earlywood radial growth and California Climate Division 6 climate data, we reconstructed annual (November–October) minimum temperature (Tmin) from 1658 to 2020. During the 61-year calibration/verification period, instrumental Tmin increased (r = 0.69, p < 0.01) and was positively associated with annual radial growth (r = 0.71, p < 0.01). Using regime shift analysis, we found that the 363-year reconstruction revealed Tmin stability until 1958 and then decreased until 1980, followed by the two warmest regimes (1981–2007, 2008–2020) on record. The last 13-year period was 0.77 °C warmer than the multi-century average with nine of the ten warmest years in the reconstruction recorded. These results suggest that 21st century warming in southern California is unique in the context of the past four centuries, indicating the rarity of exceptional warmth captured in the tree ring record.

Interactions between runoff volume, timing, and annual temperatures shape migration phenology of a threatened adfluvial sucker

AbstractMigratory fish species have been particularly impacted by changes to the hydrologic and climatic cues to which migration and spawning behaviours have been adapted across generations. While conservation and recovery programs increasingly implement flow management actions to promote successful migration and spawning, uncertainty regarding how spawning migration phenology responds to changing environmental conditions can limit the ability to effectively target such recovery actions. Here, we use a Bayesian hierarchical modelling framework to analyse spawning migration phenology of individually tagged June suckers (Chasmistes liorus) – a federally threatened, long‐lived, iteroparous, adfluvial species endemic to Utah Lake (Utah, USA) and its tributaries. We then examine how annual hydrologic and thermal conditions relate to different components of annual migration phenology, including peak migration date, in‐stream residence time, and among‐individual variation in migration timing. Peak migration date occurred earlier in years with warmer spring air temperatures (a proxy for water temperatures), though this effect interacted with peak runoff timing. Both residence time and among‐individual variation in migration timing were greater in years with larger spring discharge and later peak flows. Residence time was also longer in warmer years. These results highlight how natural and anthropogenic changes to river flow and thermal regimes are likely to impact June sucker migration timing and duration, and our approach can be applied to other migratory species to identify the external drivers of the different components of migration phenology.

Cellulase-assisted refining in a paperboard mill: Avoided emissions from energy savings. A case study of a Finnish paperboard mill

The 2023 being on its way to be the warmest year in the 174-year global surface temperature history it is becoming more and more evident how crucial it is to break the linkage between economic growth and greenhouse gas emissions.The pulp and paper industry is highly energy intensive industry sector. It is the fourth largest industrial energy user and currently produces approximately 1.3% of global greenhouse gas emissions. While the demand for paper and paperboard products keeps rising, it is essential for the industry to find energy efficient solutions for reducing the environmental impact of the pulp and paper products. 80% of the progress in energy efficiency in Finnish paper mills is due to improved technology and more optimal operational modes. Optimizing existing processes has bigger effect on energy efficiency than closing old and starting new paper mills.Pulp refining is one of the most energy intense steps in the paperboard production, representing 15%–18% of the total energy consumption of a paper mill. The effect of a commercial cellulase enzyme product was evaluated for energy savings and avoided emissions in the refining process of a paperboard mill. Data from a paperboard line using Bleached Softwood Kraft Pulp (BSKP) from a separate pulp mill was provided by a Finnish paperboard mill containing production runs both with and without commercial cellulase product ECOPULP® R. Data was collected from the mill automation system to evaluate and compare a refining capacity restricted run and a run that was not refining capacity restricted.Analysis of the data showed a reduction of refining energy by approximately 16%–17% when the cellulase enzyme was used. This corresponds to 2 kg of CO2 emissions avoided per tonne of pulp refined when calculated using the Finnish average electricity emissions intensity in 2022. Use of the cellulase enzyme enabled the refining results that could not have been reached with the bare mechanical refining capacity of the mill.Cellulases can be efficient processing aids in pulp refining. The reduction of required mechanical refining and electrical power to run the refiners to achieve the required freeness can significantly affect the carbon footprint of the paperboard products, whereas the negative impact of emissions from enzyme production is negligible. Reduction of CO2 emissions is especially significant in the areas where the electricity mix used for the production is based heavily on fossil fuels.

Exposure of the Population of Mindanao to Combined Natural and Anthropogenic Environmental Stressors

In 2019, El Niño Southern Oscillation (ENSO) episodes in conjunction with climate change resulted in significant adverse impacts, particularly on developing nations. The year 2019 ranked among the top three warmest years since the mid-1800s. This paper aims to comprehensively analyze the El Niño period and the worsening climate trends observed in Mindanao, Philippines, during that year. The application of spatial analysis techniques revealed the existence of poverty hotspots characterized by below-average precipitation and enduring episodes of dangerous levels of heat index. The study documented instances of crop destruction and farmers' resulting problems. The application of multivariate clustering analysis revealed a significant association between urbanization and elevated mortality rates in climate-sensitive diseases. This finding suggests that the degree of urbanization has an apparent impact on regional mortality rates, ranging from modest to substantial increases. The findings underscore the necessity of implementing early warning systems and developing and implementing mitigation and adaptation methods. This is particularly crucial in sectors susceptible to adverse effects, such as agriculture and healthcare, where the immediate consequences are already observable.

Modeling the larval growth and survival of Pacific cod (Gadus macrocephalus) in the eastern Bering Sea

The eastern Bering Sea (EBS) is a highly productive ecosystem that supports several important commercial species such as the Pacific cod (Gadus macrocephalus). Climate variability affects the population dynamics of this stock throughout its life stages, especially early life stages, since they are particularly susceptible to environmental changes. In recent decades, warm and cold stanzas (i.e., 3–5 year periods) have been observed in the EBS, and there is evidence that they can modulate the recruitment of this stock, causing important socioeconomic impacts. Using a mechanistic individual-based model, this study investigates the spatial and temporal variability of growth and survival of Pacific cod's early life stages during 2000–2020. We examined changes by year and over space and compared our results with published literature to validate our model. We found that temperature played a key role in modulating the survival of fish larvae, observing an increase in starvation events in warmer years or locations. Periods or areas with low prey density, especially small-bodied copepods, also contributed to increased starvation. The average temperature in the fish habitat was negatively correlated with recruitment estimates from the stock assessment model. Growth was primarily temperature-driven; however, food-limited growth became more frequent when larvae were smaller during cold years. Spatially, we found that the environmental conditions in the southeastern Bering Sea may favor larval survival but reduce growth, and higher mortality may be persistent on the middle and outer shelf. Our model produces results that agree with previous field studies, and it offers a valuable tool to investigate other ecological questions on the impact of the environment on early life stages of fishes.

Preconditioning of mountain permafrost towards degradation detected by electrical resistivity

Warming permafrost has been detected worldwide and is projected to continue during the next century by many modelling studies. In mountain regions, this can lead to potentially hazardous impacts on short time-scales by an increased tendency for slope instabilities. However, time scales of permafrost thaw and the role of the ice content are less clear, especially in heterogeneous mountain terrain, where ice content can vary between zero and supersaturated conditions over small distances. Warming of permafrost near the freezing point shows therefore complex inter-annual behaviour due to latent heat effects during thawing and the influence of the snow-cover, which is governed by highly non-linear processes itself. Here, we demonstrate a preconditioning effect within near-surface layers in mountain permafrost that causes non-linear degradation and accelerates thaw. We hypothesise that a summer heat wave, as has occurred in the Central European summers 2003, 2015 and 2022, will enhance permafrost degradation if the active layer and the top of the permafrost layer are already preconditioned, i.e. have reduced latent heat content. This preconditioning can already be effectuated by a singular warm year, leading to exceptionally strong melting of the ground ice. On sloping terrain this ice-loss can be considered as irreversible, as large parts of the melted water will drain during the process, and an equivalent build-up of ice in cold years does not happen on similar time-scales as the melting. We propose a simple geophysical approach based on electrical resistivity tomography surveys that can assess the state of preconditioning in the absence of boreholes. In addition, we will show that resistivity data from a total of 124 permafrost sites in the Andes, Europe, and Antarctic adhere to a distinct power law behaviour between unfrozen and frozen states, which confirms the consistent electrical behaviour of permafrost and active layer materials over a wide range of landforms and material composition.

Interannual Variations in Spring Snowmelt Timing of Alaskan Black Spruce Forests Using a Bulk‐Surface Energy Balance Approach

AbstractSpring snowmelt occurs for a short duration on an annual time scale, but their timings considerably affect the carbon and hydrological cycle in high‐latitude ecosystems. Here, we developed a simple snowmelt model, treating the ecosystem surface as a bulk‐surface layer. Energy fluxes across this bulk surface and the snow‐soil boundary determine snow temperature and the energy utilized for snowmelt. Parameterizing the bulk surface using decade‐long eddy covariance site data from two Alaskan open black spruce forests offered an opportunity to quantitatively evaluate meteorological drivers affecting snowmelt timings without the needs for detailed canopy information. The sensitivity analysis suggested that the total snowfall on the forest floor, ranging from 0.35 m in 2016 to about 1 m in 2018 and 2020, was the most crucial driver for snowmelt timing. This factor accounted for a 10‐day difference in the interannual variations in snow disappearance dates. The importance of the snowfall varied from year to year, and in 2013, the late snowmelt was characterized by low air temperatures, which increased sensible heat loss from the snowpack. The importance of atmospheric radiation was revealed in relatively warm years, such as 2016 and 2019. Our modeling approach necessitates adjusting one empirical parameter that reflects the heat conductivity from the bulk surface to the snow, based on observations. Nevertheless, despite this need for adjustment, the bulk‐surface approach helps identify important meteorological drivers underlying observed snowmelt within a simple theoretical framework.

Factor analysis and countermeasures for global warming based on data science methods

In recent years, the frequent and intensifying occurrence of extreme weather events such as heatwaves, floods, and storms worldwide has led scientists and policymakers to be increasingly concerned about the phenomenon of global warming. The global average temperature has steadily risen over the past few decades, and 2015-2022 has been identified as the warmest years on record. Taking global warming as the research object, the main problem is to find out the factors affecting climate change. The article predicts the global average temperature of the future and builds a model to analyse the relationship between global average temperature, time, location and the factors affecting climate change. The prediction models of ARMIA and EEMD-LSTM were built, and the model with the best fit was obtained after several iterations of tuning and trial optimization. The results showed that Flood, Storm, and Extreme temperature, had a high correlation with the global average temperature. The data of greenhouse gas indicators such as CO2, NO, and CH4, and catastrophes such as earthquakes, Volcanic activity, and wildfires have objective effects on global warming. Random forest regression model pairs were developed, and analysis of the importance of each component to the model showed that CO2 concentration and CH4 concentration had significant effects on global average temperature. Propose measures that can curb or slow down global warming.

Forest-floor respiration, N2O fluxes, and CH4 fluxes in a subalpine spruce forest: drivers and annual budgets

Abstract. Forest ecosystems play an important role in the global carbon (C) budget by sequestering a large fraction of anthropogenic carbon dioxide (CO2) emissions and by acting as important methane (CH4) sinks. The forest-floor greenhouse gas (GHG; CO2, CH4, and nitrous oxide (N2O)) flux, i.e., from soil and understory vegetation, is one of the major components to consider when determining the C or GHG budget of forests. Although winter fluxes are essential to determine the annual C budget, only very few studies have examined long-term, year-round forest-floor GHG fluxes. Thus, we aimed to (i) quantify seasonal and annual variations of forest-floor GHG fluxes; (ii) evaluate their drivers, including the effects of snow cover, timing, and amount of snowmelt; and (iii) calculate annual budgets of forest-floor GHG fluxes for a subalpine spruce forest in Switzerland. We measured GHG fluxes year-round during 4 years with four automatic large chambers at the ICOS Class 1 Ecosystem station Davos (CH-Dav). We applied random forest models to investigate environmental drivers and to gap-fill the flux time series. The forest floor emitted 2336 g CO2 m−2 yr−1 (average over 4 years). Annual and seasonal forest-floor respiration responded most strongly to soil temperature and snow depth. No response of forest-floor respiration to leaf area index or photosynthetic photon flux density was observed, suggesting a strong direct control of soil environmental factors and a weak, or even lacking, indirect control of canopy biology. Furthermore, the forest floor was a consistent CH4 sink (−0.71 g CH4 m−2 yr−1), with annual fluxes driven mainly by snow depth. Winter CO2 fluxes were less important for the CO2 budget (6.0 %–7.3 %), while winter CH4 fluxes contributed substantially to the annual CH4 budget (14.4 %–18.4 %). N2O fluxes were very low (0.007 g N2O m−2 yr−1), negligible for the forest-floor GHG budget at our site. In 2022, the warmest year on record with below-average precipitation at the Davos site, we observed a substantial increase in forest-floor respiration compared with other years. The mean forest-floor GHG budget indicated emissions of 2319 ± 200 g CO2 eq. m−2 yr−1 (mean ± standard deviation (SD) over all years), with respiration fluxes dominating and CH4 offsetting a very small proportion (0.8 %) of the CO2 emissions. Due to the relevance of snow cover, we recommend year-round measurements of GHG fluxes with high temporal resolution. In a future with increasing temperatures and less snow cover due to climate change, we expect increased forest-floor respiration at this subalpine site modulating the carbon sink of the forest ecosystem.

Warming drives phenological changes in coastal zooplankton

Climate warming has led to phenological changes over time, typically displayed as earlier emergence of various organisms in spring or summer in temperate terrestrial and marine systems alike. Similarly, warm conditions can extend seasonal occurrence. Using a time series of zooplankton data from a coastal area in the Gulf of Finland, we calculated the start, end and the length of the season for the occurrence in rotifers and for adult and juvenile stages of three calanoid copepods. We investigated whether the start and end of the season of these taxa have shifted earlier and later, respectively, and whether the season length has increased. We further investigated if potential changes are driven by climate warming. We show that both copepods and rotifers do indeed emerge earlier, but that the pattern in recent years was not conclusive, and that both temperature and ice conditions influenced the seasonal abundance patterns of some taxa. Warmer years led to earlier occurrence of Temora longicornis copepodites. Earlier ice break-up coincided with longer seasons for Acartia and earlier emergence of Eurytemora affinis. The phenological changes in zooplankton demonstrated here may have cascading effects on other trophic levels in the food web. We also demonstrate how decreased sample number influences the ability to capture intra-annual abundance patterns and discuss the implications for monitoring.

Escalating Carbon Export from High-Elevation Rivers in a Warming Climate.

High-elevation mountains have experienced disproportionately rapid warming, yet the effect of warming on the lateral export of terrestrial carbon to rivers remains poorly explored and understood in these regions. Here, we present a long-term data set of dissolved inorganic carbon (DIC) and a more detailed, short-term data set of DIC, δ13CDIC, and organic carbon from two major rivers of the Qinghai-Tibetan Plateau, the Jinsha River (JSR) and the Yalong River (YLR). In the higher-elevation JSR with ∼51% continuous permafrost coverage, warming (>3 °C) and increasing precipitation coincided with substantially increased DIC concentrations by 35% and fluxes by 110%. In the lower-elevation YLR with ∼14% continuous permafrost, such increases did not occur despite a comparable extent of warming. Riverine concentrations of dissolved and particulate organic carbon increased with discharge (mobilization) in both rivers. In the JSR, DIC concentrations transitioned from dilution (decreasing concentration with discharge) in earlier, colder years to chemostasis (relatively constant concentration) in later, warmer years. This changing pattern, together with lighter δ13CDIC under high discharge, suggests that permafrost thawing boosts DIC production and export via enhancing soil respiration and weathering. These findings reveal the predominant role of warming in altering carbon lateral export by escalating concentrations and fluxes and modifying export patterns.

The Evaluation of Sweetcorn (Zea mays saccharata Sturt.) Infestation of Barnyardgrass (Echinochloa crus-galli) Depending on Weather Conditions and Crop Rotation

This paper focuses on the weed species Echinochloa crus-galli, commonly known as barnyardgrass, which is a persistent threat to crop yield and quality, especially in maize (Zea mays) cultivation. It is one of the most problematic weeds in agricultural fields due to its aggressive growth, adaptability to different environmental conditions and prolific seed production. The incidence of Echinochloa crus-galli in maize fields has increased in recent years. This study aims to provide a comprehensive understanding of the characteristics and behavior of Echinochloa crus-galli, and to suggest effective measures to control it. This research on sweetcorn was conducted from 1992 to 2019 at the Research and Education Center Gorzyń, Złotniki branch, which belongs to the Poznań University of Life Sciences. The evaluation of weed infestation was carried out in experiments focusing on chemical weed control in maize. The experiments were designed as a one-factor randomised block design with four field replications. The condition and the degree of weed infestation (number of weeds and fresh weight of weeds) in the control plots was assessed on an annual basis at the end of June and in July. The aim of the study was to evaluate the dynamic changes in the status and extent of barnyardgrass (Echinochloa crus-galli) infestation in maize grown after various other crops in the Wielkopolska region, with a focus on the weather conditions. The study found that barnyardgrass was most likely to occur when maize was sown after winter wheat in a dry and warm year, and least likely when maize was grown in rotation after winter wheat in a cold year with average rainfall. The proportion of barnyardgrass weed mass in the total weed mass was significantly lower after winter rye than after winter wheat, winter oilseed rape and winter triticale. Further research into the biology and ecology of barnyardgrass is key to effectively controlling this weed and safeguarding sweetcorn yields.

Biological and environmental covariates of juvenile sockeye salmon distribution and abundance in the southeastern Bering Sea, 2002-2018.

Climate change is altering the distribution and abundance of marine species, especially in Arctic and sub-Arctic regions. In the eastern Bering Sea, home of the world's largest run of sockeye salmon (Oncorhynchus nerka), juvenile sockeye salmon abundance has increased and their migration path shifted north with warming, 2002-2018. The reasons for these changes are poorly understood. For these sockeye salmon, we quantify environmental and biological covariate effects within spatio-temporal species distribution models. Spatio-temporally, with respect to juvenile sockeye salmon densities: (1) sea surface temperature had a nonlinear effect, (2) large copepod, Calanus, a minor prey item, had no effect, (3) age-0 pollock (Gadus chalcogrammus), a major prey item during warm years, had a positive linear effect, and (4) juvenile pink salmon (O. gorbuscha) had a positive linear effect. Temporally, annual biomass of juvenile sockeye salmon was nonlinearly related to sea temperature and positively related to age-0 pollock and juvenile pink salmon abundance. Results indicate that sockeye salmon distributed with and increased in abundance with increases in prey, and reached a threshold for optimal temperatures in the eastern Bering Sea. Changes in population dynamics and distribution of sockeye salmon in response to environmental variability have potential implications for projecting specific future food securities and management of fisheries in Arctic waters.

Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years

In the past 10 years, extreme weather phenomena have increased, and global warming has markedly advanced; moreover, the intensity of human activity has gradually increased. These have an impact on the growth of global vegetation. Related studies have focused on the Tibetan Plateau and some northern provinces of China to estimate grassland AGB at a large scale but a low resolution. Hulunbuir Grassland is an important supplier of livestock products, and therefore, it is important to precisely map AGB and explore the response of Hulunbuir Grassland AGB to climate change and human activities at a high resolution to identify complex spatial details. In this study, we selected vegetation indices from Landsat 8 OLI and topographic indices and used multiple linear regression and machine learning algorithms to estimate the spatial distribution of AGB from 2013 to 2022. Then, we analyzed the correlations between AGB and cumulative precipitation and daily average temperature in summer and between population density and livestock density at the pixel level. Our results demonstrated that the RF model performed well, with an RMSE of 28.23 and R2 value of 0.74; the AGB was positively correlated with the cumulative precipitation in summer in 94.45 % of the area and negatively correlated with the daily average temperature in summer in 96.32 % of the area. We suggest that it is necessary to reduce grazing activities in future warm and drought years and to adjust sources of income to adapt to the decrease in AGB under global warming conditions. This study will provide reference for the countries or regions that depend on temperate grasslands for husbandry.

Hydrological regimes and evaporative flux partitioning at the climatic ends of high mountain Asia

Abstract High elevation headwater catchments are complex hydrological systems that seasonally buffer water and release it in the form of snow and ice melt, modulating downstream runoff regimes and water availability. In High Mountain Asia (HMA), where a wide range of climates from semi-arid to monsoonal exist, the importance of the cryospheric contributions to the water budget varies with the amount and seasonal distribution of precipitation. Losses due to evapotranspiration and sublimation are to date largely unquantified components of the water budget in such catchments, although they can be comparable in magnitude to glacier melt contributions to streamflow. Here, we simulate the hydrology of three high elevation headwater catchments in distinct climates in HMA over 10 years using an ecohydrological model geared towards high-mountain areas including snow and glaciers, forced with reanalysis data. Our results show that evapotranspiration and sublimation together are most important at the semi-arid site, Kyzylsu, on the northernmost slopes of the Pamir mountain range. Here, the evaporative loss amounts to 28% of the water throughput, which we define as the total water added to, or removed from the water balance within a year. In comparison, evaporative losses are 19% at the Central Himalayan site Langtang and 13% at the wettest site, 24 K, on the Southeastern Tibetan Plateau. At the three sites, respectively, sublimation removes 15%, 13% and 6% of snowfall, while evapotranspiration removes the equivalent of 76%, 28% and 19% of rainfall. In absolute terms, and across a comparable elevation range, the highest ET flux is 413 mm yr−1 at 24 K, while the highest sublimation flux is 91 mm yr−1 at Kyzylsu. During warm and dry years, glacier melt was found to only partially compensate for the annual supply deficit.

Impact of permafrost degradation on the extreme increase of dissolved iron concentration in the Amur river during 1995–1997

Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river, indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest) of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01). Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin.

Temperature has an overriding role compared to photoperiod in regulating the seasonal timing of winter moth egg hatching.

To accurately predict species' phenology under climate change, we need to gain a detailed mechanistic understanding of how different environmental cues interact to produce the seasonal timing response. In the winter moth (Operophtera brumata), seasonal timing of egg hatching is strongly affected by ambient temperature and has been under strong climate change-induced selection over the past 25years. However, it is unclear whether photoperiod received at the egg stage also influences timing of egg hatching. Here, we investigated the relative contribution of photoperiod and temperature in regulating winter moth egg development using two split-brood experiments. We experimentally shifted the photoperiod eggs received by 2-4weeks compared to the actual calendar date and measured the timing of egg hatching, both at a constant temperature and in combination with two naturally changing temperature treatments - mimicking a cold and a warm year. We found an eight-fold larger effect of temperature compared to photoperiod on egg development time. Moreover, the very small photoperiod effects we found were outweighed by both between- and within-clutch variation in egg development time. Thus, we conclude that photoperiod received at the egg stage does likely not play a substantial role in regulating the seasonal timing of egg hatching in the winter moth. These insights into the regulatory mechanism of seasonal timing could have important implications for predicting insect climate change adaptation, as we might expect different targets of selection depending on the relative contribution of different environmental cues.

Dispersal pathways of European green crab larvae into and throughout the eastern Salish Sea

The invasive European green crab (Carcinus maenas) was first detected on the US west coast around 1989 and has expanded its range northward from central California to southern Alaska. The eastern Salish Sea was initially thought to be protected from invasion by the dominant seaward surface current in the Strait of Juan de Fuca (SJdF). However, this “oceanographic barrier” has been breached as established green crab populations have been detected in the eastern Salish Sea in recent years. Here we carried out particle-tracking simulations to understand possible natural pathways of green crab larvae invading the eastern Salish Sea. Both diel vertical migration and temperature-dependent mortality were considered in these simulations. Our results suggest that green crab larvae from the outer coast (outside the Salish Sea) and Sooke Basin (in SJdF) could be carried into the eastern Salish Sea in a narrow time window during the later cold season (esp. in March) when frequent flow reversals in SJdF occur and the seasonally rising water temperature becomes relatively favorable for green crab larvae. The major pathway for larvae to reach the eastern Salish Sea is along the southern coast of SJdF. The probability of live larvae reaching the eastern Salish Sea is highly sensitive to water temperature. Sensitivity simulations indicate that a temperature increase of 0.5–1 °C would double or quadruple the probability of successful arrival in the eastern Salish Sea. This suggests that invading green crabs might have taken advantage of the mild winter conditions in recent warm years. Our results also suggest that the warming climate in the near future may facilitate green crab larval exchange across the Salish Sea.

Intensified Selection, Elevated Mutations, and Reduced Adaptation Potential in Wild Barley in Response to 28 Years of Global Warming

Many studies have investigated the threat of climate change on wild plants, but few have investigated the genetic responses of crop wild relative populations under threat. We characterized the genetic responses of 10 wild barley (Hordeum spontaneum K. Koch) populations in Israel, sampling them in 1980 and again in 2008, through exome capture and RNA-Seq analyses. Sequencing 48 wild barley samples of these populations representing two collection years generated six million SNPs, and SNP annotations identified 12,926 and 13,361 deleterious SNPs for 1980 and 2008 samples, respectively. The assayed wild barley samples displayed intensified selective sweeps and elevated deleterious mutations across seven chromosomes in response to 28 years of global warming. On average, the 2008 samples had lower individual and population mutational burdens, but the population adaptation potential was estimated to be lower in samples from 2008 than in 1980. These findings highlight the genetic risks of losing wild barley under global warming and support the need to conserve crop wild relatives.

Adaptability of Prunus cerasifera Ehrh. to Climate Changes in Multifunctional Landscape

Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban landscapes. This study examines flowering and fruiting in the context of climate characteristics, expressed through the Day of the Year (DOY), Growing Degree Days (GDDs), and a yield over 17 consecutive years. The results indicate significant shifts in the DOY but not in the GDD, apart from the end of flowering. The onset of flowering was earlier and the end postponed, extending the phenophase by an average of 4 days. The cherry plum’s yield was unaffected by climate changes, including extreme events like a late-spring frost. The stability of the cherry plum was confirmed by the phenological patterns of the bullace (cherry plum and blackthorn hybrid) exhibiting repeated flowering in the warmest year of 2023. The cherry plum is an adaptive species, with a high adaptability to a changing climate and a high resistance to late-spring frosts; thus, it is a favorable choice in urban design and planning, demonstrating resilience to climate shifts and thriving in polluted urban environments. It is especially appreciated for multiple ecosystem services: biodiversity conservation in natural and semi-natural areas, yielding good provisions in challenging environments, and the preservation of ornamental values through an extended flowering phenophase.