Local Scale Research Articles

Chasing and surfing seasonal waves: Avian migration through the US tracks land surface phenology in fall, but not spring.

Climate change is altering the timing of seasonal events for many taxa. There is limited understanding of how northward/southward songbird migration follows or is limited by the latitudinal progression of seasonal transitions. Consistent environmental conditions that migrating birds encounter across latitudes likely represent or correlate with important resources or limiting factors for migration. We tested whether migratory passage-observed via radar-consistently tracked land surface variables and phenophases across latitudes in the US Central Flyway in both spring and fall. The daily temperatures, precipitation and vegetation greenness occurring on 10%, 50% and 90% cumulative passage dates changed substantially with latitude, indicating that most migrants experienced rapidly changing conditions as they headed north or south. Temperature did not limit the progression of migration in either season. Peak spring migration in the southern US occurred nearly 40 days after the spring green wave, the northward progression of vegetation growth, but nearly caught up to green-up at 48° N. Spring migration phenology may have evolved to prioritize earlier arrival for breeding. Across all latitudes, peak fall migration coincided with the same land surface phenophase, an interval of 26 days prior to dormancy onset. Migrants may rely on phenological events in vegetation during fall stopovers. Considering that (a) migratory passage tracked fall land surface phenology across latitudes at a continental scale, (b) previous studies at local scales have demonstrated the importance of fruit during fall migratory stopover and (c) fruiting phenology in North America is occurring later over time while fall migration is advancing, the potential for mismatch between fall fruiting and bird migration phenology urgently needs further investigation.

Vertebrates and flying insects provide biocontrol services to Australian urban food gardens

AbstractBiocontrol by wild insects and other organisms is an important service provided to agriculture, but few studies have linked the role of this service to urban garden crop production. In 15 urban food gardens in Sydney, Australia, we assessed predation and parasitism of two sentinel prey species, recorded pest control activities undertaken by gardeners and the produce yielded by garden crops. We observed substantial removal of sentinel prey (mean removal 22% for Tenebrio molitor larvae and 59% for Helicoverpa armigera) but no parasitism. Vertebrate predators primarily consisted of urban adapted birds and mammals common throughout Australian cities. We measured a range of local and landscape scale environmental variables including plant richness and abundance, light, canopy cover, building density and distance to remnant vegetation. We found that gardeners undertook only basic pest control activities with little chemical use, yet high amounts of produce were harvested. Pest control services were poorly explained by environmental variables. Low active pest control activities, and high predation rates suggest pests are either well controlled or in low numbers in the surveyed urban food gardens. Given the vertebrate predators were generalist birds and mammals common to many parts of urban Australia, the provision of predation services to urban gardens by these taxa could be widespread across the continent.

Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands

Abstract. Meteorological fields calculated by numerical weather prediction (NWP) models drive offline chemical transport models (CTMs) to solve the transport, chemical reactions, and atmospheric interaction over the geographical domain of interest. HARMONIE (HIRLAM ALADIN Research on Mesoscale Operational NWP in Euromed) is a state-of-the-art non-hydrostatic NWP community model used at several European weather agencies to forecast weather at the local and/or regional scale. In this work, the HARMONIE WINS50 (cycle 43 cy43) reanalysis dataset at a resolution of 0.025° × 0.025° covering an area surrounding the North Sea for the years 2019–2021 was coupled offline to the LOTOS-EUROS (LOng-Term Ozone Simulation-EURopean Operational Smog model, v2.2.002) CTM. The impact of using either meteorological fields from HARMONIE or from ECMWF on LOTOS-EUROS simulations of NO2 has been evaluated against ground-level observations and TROPOMI tropospheric NO2 vertical columns. Furthermore, the difference between crucial meteorological input parameters such as the boundary layer height and the vertical diffusion coefficient between the hydrostatic ECMWF and non-hydrostatic HARMONIE data has been studied, and the vertical profiles of temperature, humidity, and wind are evaluated against meteorological observations at Cabauw in The Netherlands. The results of these first evaluations of the LOTOS-EUROS model performance in both configurations are used to investigate current uncertainties in air quality forecasting in relation to driving meteorological parameters and to assess the potential for improvements in forecasting pollution episodes at high resolutions based on the HARMONIE NWP model.

Downscaling Future Precipitation over Mi Oya River Basin using Artificial Neural Networks

Studying future precipitation behaviour in river basins is essential for proper water resources and land-use planning within them, as this will help to reduce the risk and mitigate disasters that can occur in the future. General Circulation Models (GCMs) are used to study future precipitation fluctuations, which simulate large-scale climate variations under the effect of greenhouse gas changes. The GCM runs at a coarse spatial resolution which cannot be directly used for climate impact studies. Therefore, downscaling is required to extract the sub-grid and local scale information. This study examines the use of the Long Short-Term Memory (LSTM) neural network for climate downscaling to the Mi-Oya river basin in Sri Lanka using CNRM-CM5 and HadCM3 GCMs and observed annual data for 35 years. The precipitation data were extracted to cover Sri Lanka. Current downscaling models mostly use Convolutional Neural Networks (CNNs) to downscale GCMs. Out of 42 GCMs, two appropriate GCMs were chosen using the data analysis tool Data Integration and Analysis System (DIAS). The best predictor variables were chosen using the LASSO regression method. In this research, Machine Learning models were implemented using the Google TensorFlow platform. The Nash–Sutcliffe coefficient, Pearson correlation coefficient, and root-mean-square error performance indices were used to evaluate the performances of different downscaling models. Statistical downscaling was performed on the data at RCP 2.6, 4.5, and 8.5 using a LSTM. Subsequently, the changes that would take place by the year 2100 were analysed. The results show that precipitation will be reduced in the 2nd and 3rd decades of the 21st century, and precipitation will increase toward the 22nd century.

Spatio‐temporal shift in body size and plumage coloration is associated with the magnitude of climate change in a cosmopolitan owl

AbstractAimClimatic gradients shape geographic variation in phenotypic traits that are involved in animal thermoregulation. Therefore, increasing temperatures under global warming are expected to cause change over time in traits that show predictable spatial patterns according to environmental clines (body and appendage size, tegument coloration), as well exemplified by biogeographic rules and shown by increasing literature at a local scale. However, whether temporal shifts in phenotypic traits vary spatially according to the magnitude of the change in local climatic conditions is still unknown.LocationWorld.TaxonBarn owl species complex (Tyto alba group).MethodsBy using thousands of museum specimens collected across the globe from 1901 to 2018, we calculated within‐population change over time in wing length, bill length and melanin‐based plumage coloration and examined whether these trends differed across geographic regions, latitudes and gradients of climate changes.ResultsWe showed that populations exposed to an increasing warmer climate were subjected to a more marked decrease in body size, as gauged by wing length, and also absolute bill length that displayed a similar, although less steep, pattern of shrinking over time. In addition, phaeomelanin‐based ventral plumage colour has become paler in regions where the climate changed into warmer and drier, and darker where both temperature and precipitation increased.Main ConclusionsThese trends are generally coherent with the predictions based on Bergmann's and Gloger's rules, but not Allen's rule, and suggest that temporal shifts in body size and tegument colour depend on the magnitude of the alteration in climatic conditions, with populations living in regions where the climate has changed the most that are subjected to more marked phenotypic changes. Spatio‐temporal variation in climate has driven within‐species phenotypic clines, and it is expected to increase differences among populations according to the predicted further climate change.

Estimating Forest Stock Volume Based on Airborne Lidar Data

Abstract. Forest stock volume (FSV) stands as an important indicator in evaluating the potential for carbon sequestration. It is crucial for forest resource management at local, regional, and national scales. In order to achieve an accurate estimation of FSV, this article takes Mengyin County, Shandong Province, China as the research area, builds a random forest (RF) model for four tree species based on airborne Lidar data, and forms a monitoring system of "individual tree - grid - county" granularities. The results demonstrated that all four models exhibited excellent generalization capabilities, with no signs of overfitting. In the test phase, the R2 of the poplar and pine models exceeded 0.9, while the R2 of the cypress model was 0.81, and the rRMSE was controlled within 20%, indicating that the fitting effect of the three tree species models was better; the accuracy of the robinia pseudoacacia model was relatively poor, with R2 of 0.60 and rRMSE of 20.60%. This study provides a feasible method for estimating forest stock volume within the county, which provides strong technical support for forest resource management and planning, and helps promote sustainable forestry development.

Wind-urban structure interplay in PM2.5 variation: Insights from multi-seasonal mobile air quality campaign

The health risks associated with particulate matter pollution (PM2.5) highlight the importance of comprehending key drivers of its spatial and temporal variability. While explanatory modeling is widely used for statistical inference in such applications, the role of wind variables (speed, direction) and their interplay with built environment are often overlooked. This study addresses this gap through a mobile air quality campaign in a suburban area over 10 days for each of three distinct seasons. We developed four innovative wind-based buffers to account for the wind factors and assess the impact of LiDAR-derived 3D built environment structure on PM2.5 variability at local and regional scales. Our second objective is to assess the predictive capabilities of wind-based variables. Results indicate that in our low-elevation, low-rise building study area, the built environment does not emerge as a significant factor, contrary to findings in larger, denser urban areas. Wind direction proves more effective in capturing concentration fluctuations than wind speed, and its interaction with pollution source orientation can change pollution dynamics. This study introduces new insights and methodologies for incorporating wind-related factors into the analysis of air pollution dynamics, offering opportunities for further investigation in various urban settings.

Spatio-temporal analysis of carbon storage in urban areas after wildfires: the case of Marmaris fire

Cities and urban areas are the primary source of CO2 worldwide by using around 70% of global energy and emitting more than 71% of CO2. Urban vegetation, referring to all trees and shrubs, are important components of urban environments. They provide many ecosystem services to human beings both directly and indirectly. Especially, they play a key role in reducing carbon emissions in urban areas by storing and capturing the carbon. However, recently, an increase in the number and intensity of wildfires that occur within urban areas has been observed. It resulted in losing stored carbon, releasing GHG to the atmosphere. Hence, quantifying above-ground carbon stored by urban trees and its distribution is essential to better understanding urban vegetation's role in urban environments and to better urban vegetation management. This study aimed to examine how forest fire affects the amount and distribution of stored carbon in the urban environment for the case of the Marmaris fire in the Summer of 2021 in Türkiye. For the study, urban forest carbon storage maps were generated before and after the Marmaris forest fire using remote sensing-based methodology with freely available remote sensing (RS) data. The results indicated that using the existing methodology could be rapid and cost-effective in monitoring the carbon storage change after an anthropogenic and natural disaster. However, for precise and reliable estimation of total carbon storage and the change in total urban carbon storage, the methodology needs to be developed at a local scale using field sampling along with RS data.

MIC distribution analysis identifies differences in AMR between population sub-groups

Background Phenotypic data, such as the minimum inhibitory concentrations (MICs) of bacterial isolates from clinical samples, are widely available through routine surveillance. MIC distributions inform antibiotic dosing in clinical care by determining cutoffs to define isolates as susceptible or resistant. However, differences in MIC distributions between patient sub-populations could indicate strain variation and hence differences in transmission, infection, or selection. Methods The Vivli AMR register contains a wealth of MIC and metadata for a vast range of bacteria-antibiotic combinations. Using a generalisable methodology followed by multivariate regression, we explored MIC distribution variations across 4 bacteria, covering 7,135,070 samples, by key population sub-groups such as age, sex and infection type, and over time. Results We found clear differences between MIC distributions across various patient sub-groups for a subset of bacteria-antibiotic pairings. For example, within Staphylococcus aureus, MIC distributions by age group and infection site displayed clear trends, especially for levofloxacin with higher resistance levels in older age groups (odds of 2.17 in those aged 85+ compared to 19–64), which appeared more often in men. This trend could reflect greater use of fluoroquinolones in adults than children but also reveals an increasing MIC level with age, suggesting either transmission differences or accumulation of resistance effects. We also observed high variations by WHO region, and over time, with the latter likely linked to changes in surveillance. Conclusions We found that MIC distributions can be used to identify differences in AMR levels between population sub-groups. Our methodology could be used more widely to unveil hidden transmission sources and effects of antibiotic use in different patient sub-groups, highlighting opportunities to improve stewardship programmes and interventions, particularly at local scales.

Assessing ecosystem services of mountain lakes

From global to local scales, human-induced environmental changes can impact mountain lakes by, for example, altering species composition, trophic state, and thermal dynamics, thereby affecting ecosystem functions and processes. However, the consequences of these changes on ecosystem services (ES) of mountain lakes are unclear due to a lack of integrative assessments. Therefore, this dissertation adopts an interdisciplinary ES perspective to improve insight into human interactions with mountain lakes and the potential social and ecological impacts of anthropogenic pressures on them. Stakeholder consultations highlighted the importance of regulating, cultural, and provisioning ES of natural mountain lakes, emphasizing habitat, aesthetics, recreation, education and research, and surface water, with nature-based experiences as being a key aspect of human interaction with mountain lakes. Multiple indicators were proposed to quantify potential supply of these ES, revealing variations among case study lakes in the European Alps. These results informed an integrative valuation approach and exposure assessment to anthropogenic pressures, suggesting that ES by mountain lakes are sensitive to climate change-related and human use pressures. Overall, the findings advance a social-ecological understanding of mountain lakes and indicate towards the need for adaptive lake management to maintain ES under potential anthropogenic pressure.

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Integration of LST and NDVI for adjusted night light index (ILNANLI): a novel index to reduce the effect of saturation and blooming of DMSP-OLS data

ABSTRACT DMSP-OLS night-light images have provided an effective way to monitor cities on a global scale. These images can separate urban areas and other human activities from the background without light with correct spatial measurement. However, due to saturation and blooming problems, the ability of these images to describe urban features is limited, especially in urban cores. Therefore, in this research, a new index, ILNANLI, has been developed and presented by integrating LST and NDVI for the adjusted night-light index. This index has two general goals: reducing the effects of saturation in the city centres, increasing the variety of brightness pixel values of night-light images, and reducing the blooming in the surrounding areas. The ILNANLI has been developed in such a way that it has put the indicators and relationships together, taking into account the characteristics of different regions of the city (such as buildings, vegetation, and soil) in such a way that in every urban environment (temperate and dry and semi-desert) to be successful. Another feature is its easy implementation and high success. In fact, the prominent feature of this index, which distinguishes it from the rest of the indices, is that it has been able to work successfully in arid and semi-desert areas in addition to temperate regions. The evaluation results showed that the average overall accuracy of ILNANLI in mapping and extracting built-up areas with automatic thresholds in cities with different climates has effectively increased by 8% compared to other indexes. Also, the examination of transects shows that the proposed index is more effective than the other four indexes in increasing the diversity of values and reducing blooming. Therefore, as a favourable option with easy implementation, the proposed index can be used to reduce the effect of saturation and blooming and study the urban structure at local scales.

Emission ensemble approach to improve the development of multi-scale emission inventories

Abstract. Many studies have shown that emission inventories are one of the inputs with the most critical influences on the results of air quality modelling. Comparing emission inventories among themselves is, therefore, essential to build confidence in emission estimates. In this work, we extend the approach of Thunis et al. (2022) to compare emission inventories by building a benchmark that serves as a reference for comparisons. This benchmark is an ensemble that is based on three state-of-the-art EU-wide inventories: CAMS-REG, EMEP and EDGAR. The ensemble-based methodology screens differences between inventories and the ensemble. It excludes differences that are not relevant and identifies among the remaining ones those that need special attention. We applied the ensemble-based screening to both an EU-wide and a local (Poland) inventory. The EU-wide analysis highlighted a large number of inconsistencies. While the origin of some differences between EDGAR and the ensemble can be identified, their magnitude remains to be explained. These differences mostly occur for SO2 (sulfur oxides), PM (particulate matter) and NMVOC (non-methane volatile organic carbon) for the industrial and residential sectors and reach a factor of 10 in some instances. Spatial inconsistencies mostly occur for the industry and other sectors. At the local scale, inconsistencies relate mostly to differences in country sectorial shares that result from different sectors/activities being accounted for in the two types of inventories. This is explained by the fact that some emission sources are omitted in the local inventory due to a lack of appropriate geographically allocated activity data. We identified sectors and pollutants for which discussion between local and EU-wide emission compilers would be needed in order to reduce the magnitude of the observed differences (e.g. in the residential and industrial sectors). The ensemble-based screening proved to be a useful approach to spot inconsistencies by reducing the number of necessary inventory comparisons. With the progressive resolution of inconsistencies and associated inventory improvements, the ensemble will improve. In this sense, we see the ensemble as a useful tool to motivate the community around a single common benchmark and monitor progress towards the improvement of regionally and locally developed emission inventories.

Anthropogenic warming is a key climate indicator of rising urban fire activity in China

Abstract China, one of the most populous countries in the world, has suffered the highest number of natural disaster-related deaths from fire. On local scales, the main causes of urban fires are anthropogenic in nature. Yet, on regional to national scales, little is known about the indicators of large-scale co-varying urban fire activity in China. Here, we present the China Fire History Atlas (CFHA), which is based on 19 947 documentary records and represents fires in urban areas of China over the twentieth century (1901–1994). We found that temperature variability is a key indicator of urban fire activity in China, with warmer temperatures are correlated with more urban fires, and that this fire–temperature relationship is seasonally and regionally explicit. In the early twentieth century, however, the fire–temperature relationship was overruled by war-related fires in large urban areas. We further used the fire–temperature relationship and multiple emissions scenarios to project fire activity across China into the twenty-first century. Our projections show a distinct increase in future urban fire activity and fire-related economic loss. Our findings provide insights into fire–climate relationships in China for densely-populated areas and on policy-relevant time scales and they contribute spatial coverage to efforts to improve global fire models.

Crouching the tiger, or hiding the dragon? scale in China’s heritage production

In the built heritage studies, the intricate web of social and selective processes that define heritage is evident. These processes are, in many cases, intertwined with the notion of scale, examplified through the production of heritage sites at the local, national, and transnational scales. While heritage and geography scholars have articulated the role played by scale in heritage-making and argue against a rigid, fixed, and hierarchical understanding of scale, they highlight the constant reproduction of scale. There is, so far, limited explanation of how the perception of scale gets reproduced and how crucial actors manipulate scalar power and resources for heritage making and the reproduction of scale. To fill this gap, this paper delves into mainland China’s heritage-making, using the southern Anhui historical villages as an example. Based on intensive 5-month field research, this paper has three findings: 1) The nomination process for a World Heritage Site is notably influenced by politics and selectivity; 2) Diverse stakeholders are pivotal in shaping heritage narratives; 3) Individual contributions to heritage creation directly interact with, and subsequently reshape, ‘scale’, an entity that is simultaneously discursive and tangible. By integrating the notion of ‘scale’ into heritage discussions, we illuminate two concurrent processes: creating hierarchies through rule assimilation by interpreting the UNESCO standard internally and evolving socio-spatial dynamics via the manifestation of individual agency with resource manipulation, scale jumping, and reproduction of scale. This approach aligns with the material orientation in human geography and repositions ‘scale’. Here, it’s not just an epistemological framework but also a tangible force that steers individual perceptions and actions and yields measurable material impacts.

Effects of reduced snowpack due to climate warming on abiotic and biotic soil properties in alpine and boreal forest systems

Reduction in snow cover, depth, onset, and duration of seasonal snow in mid-latitude regions due to climate warming has multiple global and local scale ecosystem impacts. These effects include modulations of the hydrological cycles and increases in land surface solar radiation absorption due to decreased albedo. Changes in snow cover characteristics also affect underlying soils. Snow has an insulating effect on soils by decoupling air and soil temperatures, thus seasonal snow cover reduction leads to overall lower soil temperatures and an increase in freeze-thaw cycles. This is especially prominent during the fall and spring thaw seasons when the snow cover is not as extensive. This in turn has downstream impacts on soil physical, chemical, and biological properties. Among these impacts are soil moisture reduction, temperature, frost regimes, soil pH shifts, and alteration in nutrient flux dynamics during winter, snowmelt period and the following summer growing season. These changes in soil physicochemical properties due to snowpack reduction can then impact the biological soil properties via increased plant root mortality, reduced abundance and diversity of soil arthropods, and shifts in composition, abundance and activity of soil microbial communities. All these soil biotic factors can in turn alter the dynamics of soil nutrient fluxes and future greenhouse gas emissions. Here, we integrate data on the effects of snow cover reduction on abiotic and biotic soil properties, with focus on temperate alpine and forest ecosystems and with an outlook on future impacts.

Local and landscape drivers of natural enemy communities in Indonesian oil palm plantation

Abstract Oil palm plantations are typically managed in a monoculture system over large areas. This system contributes to biodiversity loss and promotes pest outbreaks by reducing natural enemies. However, ecosystem functions in oil palm plantations vary spatially and temporally and can still support biodiversity under certain conditions. We conducted a study on the species richness, abundance and species composition of natural enemies in oil palm plantations and investigated the factors influencing natural enemy communities in oil palm plantations at both local and landscape scales. We selected 12 sites in an oil palm plantation in Central Borneo, Indonesia, which were grouped into 4 sub‐areas based on the presence of natural habitats, which varied in local and landscape characteristics. Arthropods were sampled using canopy knockdown fogging with a pyrethroid insecticide. Different taxa of natural enemies responded differently to changes in habitat characteristics within oil palm plantations. Species richness of spiders was not affected by either local or landscape scale, but their species composition was affected by oil palm tree age (local scale) and the total edge of dominant oil palm tree age (landscape scale). Ant species richness was influenced by the class area of natural habitat (landscape scale), whereas their species composition was not influenced by either local or landscape scale. On the other hand, species richness of parasitoid wasps was influenced by light intensity (local scale) and the variation of oil palm tree age within a landscape (landscape scale). However, their species composition was only affected by light intensity. The results suggest that oil palm management practices need to consider both local and landscape scales to maintain biodiversity and biological control and to achieve sustainable management of oil palm plantations.

Degradation exposure scenario in the Brazilian Amazon: Edge effect on hyperdominant C-cycle tree species

The Amazon basin strongly influences the global carbon cycle, storing billions of tonnes of carbon in a relatively small number of ‘hyperdominant’ tree species. However, the Amazon carbon stock is threatened by land-use change. In the remaining forest patches, trees close to the forest border bear various physical and biotic edge effects that alter plant growth and survival. To assess how edge effects influence tree mortality and carbon storage, we investigated the occurrence of hyperdominant tree species in the Brazilian Amazon between 1988 and 2021. Evaluating tree records from a network of permanent plots and herbarium collections, we found that 22 % of tree occurrence records were in deforested areas, 35% within 1 km of the forest edge, and 43 % in continuous forest. At the local scale in Central Amazonia, tree monitoring data over 30 years revealed that forest fragments hyperdominant trees had twice the mortality rate of continuous forest ones due to edge effects during the 15 years following edge establishment. Although trees in fragments had higher initial growth, this pattern declined over the years and eventually resulted in significant carbon loss, mainly from tree mortality. Edge effects have led to annual declines in the biomass of forest remnants, suggesting that hyperdominant species are also susceptible to disturbances that lead to degradation and forest losses. Conservation of the Amazon forests requires an approach that considers the effects of local disturbances on carbon stocks in the region.

Multicriteria screening evaluation of geothermal resources on mine lands for direct use heating

Direct use of geothermal energy is the oldest and most versatile form of utilizing geothermal energy. In the last decade, this utilization has significantly increased, especially with the installation of geothermal (ground-source) heat pumps. Many current and inactive mine land sites across the U.S. could be redeveloped with clean energy technologies such as direct use geothermal, which would revitalize former mining communities, help with reducing greenhouse gas emissions, and accelerate the transition to a clean energy economy. We present a multicriteria screening framework to evaluate various aspects of direct-use geothermal projects on mine lands. The criteria are divided into three categories: (1) technical potential, (2) demand and benefits, and (3) regulatory and permitting. We demonstrate the framework using publicly available data on a national scale (continental U.S.). Then, using an example of abandoned coal mines in Illinois and focusing on resource potential, we illustrate how this evaluation can be applied at the state or more local scales when a region’s characteristics drive spatial variability estimates. The strength of this approach is the ability to combine seemingly disparate parameters and inputs from numerous sources. The framework is very flexible—additional criteria can be easily incorporated and weights modified if input data support them. Vice versa, the framework can also help identify additional data needed for evaluating those criteria. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

Environmental and Biogeographic Drivers behind Alpine Plant Thermal Tolerance and Genetic Variation.

In alpine ecosystems, elevation broadly functions as a steep thermal gradient, with plant communities exposed to regular fluctuations in hot and cold temperatures. These conditions lead to selective filtering, potentially contributing to species-level variation in thermal tolerance and population-level genetic divergence. Few studies have explored the breadth of alpine plant thermal tolerances across a thermal gradient or the underlying genetic variation thereof. We measured photosystem heat (Tcrit-hot) and cold (Tcrit-cold) thresholds of ten Australian alpine species across elevation gradients and characterised their neutral genetic variation. To reveal the biogeographical drivers of present-day genetic signatures, we also reconstructed temporal changes in habitat suitability across potential distributional ranges. We found intraspecific variation in thermal thresholds, but this was not associated with elevation, nor underpinned by genetic differentiation on a local scale. Instead, regional population differentiation and considerable homozygosity within populations may, in part, be driven by distributional contractions, long-term persistence, and migrations following habitat suitability. Our habitat suitability models suggest that cool-climate-distributed alpine plants may be threatened by a warming climate. Yet, the observed wide thermal tolerances did not reflect this vulnerability. Conservation efforts should seek to understand variations in species-level thermal tolerance across alpine microclimates.