Variations In Elevation Research Articles

Defecation Site Preferences and Spatial Ecological Segregation of Forest Musk Deer and Siberian Roe Deer in North China.

The forest musk deer (Moschus berezovskii) and Siberian roe deer (Capreolus pygargus) are browsers with a broad sympatric distribution in North and Southwest China. However, little is known about their spatial utilization of microhabitats and habitats. This study, conducted on Huanglong Mountain in China, analyzed the defecation site distribution, indicating preferences of forest musk deer and Siberian roe deer for their habitat demands. Using generalized linear mixed models (GLMMs), we compared the defecation site preferences of both species and further examined their spatial utilization patterns. The results indicated that the primary factors influencing defecation site preferences for forest musk deer were slope (15.79%), elevation (4.26%), herbaceous cover (19.93%), herb height (33.73%), and tree diversity (15.64%). Conversely, for Siberian roe deer, elevation (54.63%) and herbaceous cover (29.31%) were the key factors. Significant differences were found in elevation (p < 0.001) and herbaceous diversity (p < 0.01) between the defecation sites of the two species, with additional notable differences in slope position, tree diversity, and average tree height (p < 0.05). Furthermore, forest musk deer primarily utilized broadleaf forests, coniferous forests, mixed conifer-broadleaf forests, and sparse woodlands. In contrast, Siberian roe deer utilized broadleaf forests, sparse woodlands, and coniferous forests, showing a significant difference (p = 0.01). These findings suggest distinct spatial ecological segregation between forest musk deer and Siberian roe deer regarding their microhabitat preferences and vegetation type utilization at the habitat scale.

A comparative analysis of gamete production in distylous Primula: Associations with floral traits and elevation

AbstractDespite the importance of gamete production this topic has rarely been investigated in angiosperms using comparative approaches. Here, we investigated pollen and ovule numbers per flower in 73 species and 99 populations of Primula comprising both distylous and homostylous reproductive systems. We investigated whether phylogenetic relationships influenced associations between variation in gamete production, floral traits and elevation, and whether the evolutionary breakdown of distyly to homostyly resulted in parallel changes to gamete production. We used a Bayesian approach facilitated by the MCMCglmm method to model pollen and ovule traits across species and determined whether they exhibited phylogenetic signals. We detected significant positive correlations between pollen number and elevation in both the long‐styled and short‐styled morphs (L‐morph and S‐morph, respectively), whereas ovule number was not influenced by elevation. Pollen production was significantly higher in the L‐morph than in the S‐morph, but there was no significant difference between morphs in ovule number. Pollen volume exhibited a positive correlation with the style length of compatible morphs. The transition from distyly to homostyly was associated with significant decreases in pollen production but not ovule number. Our findings demonstrate the importance of elevation on pollen production, perhaps because of selection to improve pollen‐transfer efficiency in uncertain pollinator environments. In contrast, ovule number variation appears to be more constrained by phylogenetic relationships. Our comparative analyses of a well defined angiosperm lineage highlight the complex interactions between intrinsic and extrinsic factors influencing gamete production in plants and emphasize the importance of considering pollen and ovule data separately.

Cretaceous coastal mountain building and potential impacts on climate change in East Asia.

Crustal thickness and elevation variations control mountain building and climate change at convergent margins. As an archetypal Andean-type convergent margin, eastern Asia preserves voluminous magmas ideal for quantifying these processes and their impacts on climate. Here, we use Sr/Y and Ce/Y proxies to show that the crust experienced alternating thickening and thinning during the Late Mesozoic. We identify a noticeably thickened (50 to 55 kilometers) crust associated with tectonic shortening at 120 to 105 million years, corresponding to a >2500-meter-high coastal mountain range. Using climate simulation with the Community Earth System Model, we demonstrate that the mountain uplift changed Asian atmospheric circulation and precipitation patterns, increased inland aridity (~15%), and prompted the eastward desert expansion, contributing substantially to the arid zonal belt across mid- to low-latitude Asia. These findings-compatible with independent geological, geophysical, and climatic observations-have global implications for broadening our understanding of Earth-system interactions in the Cretaceous greenhouse world.

Phylogenetic Relationships Plays a More Important Role than Environmental Factors in Influencing Leaf Si and Ca Stoichiometry Along the Elevation Gradient in a Chinese Subtropical Forest

Silicon (Si) and calcium (Ca), as elements abundant in the Earth’s crust, are closely related to plant growth and stress resistance and have similar roles. Understanding the stoichiometry of Si and Ca can provide more insight into the mechanical and stress resistance of plants, as well as their preferences for the absorption and use of Si and Ca. Here, we measured the content of Si and Ca in the leaves of the dominant tree species located in the Mount Wuyi National Park, with an elevation ranging from 800 m to 1700 m, in an attempt to reveal changes in the Si and Ca content and ratio in the leaves along the altitude, as well as their possible relationships with environmental factors and phylogeny. The results indicated that the leaf Si and the leaf Si/Ca decreased, while the leaf Ca increased significantly with the increase in elevation. Changes in environmental factors induced by variations in elevation affected the silicon and calcium stoichiometry characteristics of the leaves, either directly or indirectly. Specifically, the mean annual precipitation, soil available silicon, soil organic matter, and soil bulk density accounted for most of the variations in leaf silicon and calcium. The leaf silicon and calcium stoichiometry was phylogenetically conservative, suggesting more similar characteristics among closely related tree species. Structural equation modeling and variation partitioning indicated that phylogeny might be more important than environmental factors in influencing leaf Si and Ca stoichiometry. Additionally, the shared effects of environmental factors and taxonomic levels indicated changes in the forest community, and the differential responses of different functional types due to elevation variation also affected the altitudinal patterns of leaf Si and Ca stoichiometry.

Analyzing the impact of variations in land use and elevation on selected soil microbial indices and spatial distribution.

Soil biological characteristics are highly sensitive to land use changes, making them valuable indicators of soil quality. This study assesses the effects of three land use types (agriculture, rangeland, and forest) and elevation variations on soil microbial parameters and their spatial distribution in the Khaneghah region. Standard physicochemical and biological properties of the soil were measured on a total of 72 soil samples collected using systematic and random sampling techniques. Spatial distribution maps of the biological indices were generated using geostatistical techniques, specifically the Kriging method, within a geographic information system (GIS). The results revealed significantly higher values for microbial biomass carbon (MBC = 900 mg Cmic-CO2 kg-1), nitrogen (MBN = 8.97 mg Nmic kg-1), basal respiration (BR = 25.1 mg C-CO2 g-1 day-1), and the total microbial population (MPN = 0.63 × 109 cells g-1) in forest soils compared to rangeland and agricultural soils. The alignment between land use maps and biological index maps reinforced these findings. Although the correlations between biological indices and physicochemical properties were generally weak (positive or negative), organic matter content, field capacity moisture, and silt percentage exhibited a slight positive correlation with most of the microbial indices evaluated. The comparison of soil microbial indices with the digital elevation model map indicated higher levels of MBC, MBN, BR, and MPN at elevated regions. However, the microbial quotient and metabolic quotient (qCO₂) did not show significant changes with increasing elevation. The study also confirmed the effectiveness of Kriging interpolation in mapping specific soil microbial indices, as the correlation between Kriging estimates and measured values at sampling points exceeded 0.2, demonstrating statistical significance at a 5% confidence level.

Phylotranscriptomic and ecological analyses reveal the evolution and morphological adaptation of Abies.

Coniferous forests are under severe threat of the rapid anthropogenic climate warming. Abies (firs), the fourth-largest conifer genus, is a keystone component of the boreal and temperate dark-coniferous forests and harbors a remarkably large number of relict taxa. However, the uncertainty of the phylogenetic and biogeographic history of Abies significantly impedes our prediction of future dynamics and efficient conservation of firs. In this study, using 1,533 nuclear genes generated from transcriptome sequencing and a complete sampling of all widely recognized species, we have successfully reconstructed a robust phylogeny of global firs, in which four clades are strongly supported and all intersectional relationships are resolved, although phylogenetic discordance caused mainly by incomplete lineage sorting and hybridization was detected. Molecular dating and ancestral area reconstruction suggest a Northern Hemisphere high-latitude origin of Abies during the Late Cretaceous, but all extant firs diversified during the Miocene to the Pleistocene, and multiple continental and intercontinental dispersals took place in response to the late Neogene climate cooling and orogenic movements. Notably, four critically endangered firs endemic to subtropical mountains of China, including A. beshanzuensis, A. ziyuanensis, A. fanjingshanensis and A. yuanbaoshanensis from east to west, have different origins and evolutionary histories. Moreover, three hotspots of species richness, including western North America, central Japan, and the Hengduan Mountains, were identified in Abies. Elevation and precipitation, particularly precipitation of the coldest quarter, are the most significant environmental factors driving the global distribution pattern of fir species diversity. Some morphological traits are evolutionarily constrained, and those linked to elevational variation (e.g., purple cone) and cold resistance (e.g., pubescent branch and resinous bud) may have contributed to the diversification of global firs. Our study sheds new light on the spatiotemporal evolution of global firs, which will be of great help to forest management and species conservation in a warming world.

Cover Image:

Firs (Abies spp.) are keystone components of the boreal and temperate dark‐coniferous forests and this genus harbors a number of relict taxa. Wei et al. (pages 2664‐2682) reconstructed a transcriptomebased phylogeny and revealed the spatiotemporal evolution of global firs based on complete species sampling. Evolutionary and ecological analyses indicate that all extant firs underwent diversification in the Late Cenozoic, with the species richness distribution driven primarily by elevation and precipitation of the coldest quarter. Some morphological traits linked to elevational variation and cold tolerance may have contributed to the diversification of global firs. This work may inform forest management and species conservation in a warming world. The cover shows the dark blue cones of an alpine fir (Abies georgei var. smithii).

Assessing flood risk and vegetation dynamics: Implications for sustainable land management in Fars province

The design of effective flood risk mitigation strategies and their subsequent implementation is crucial for sustainable development in mountain areas. The assessment of the dynamic evolution of flood risk is the pillar of any subsequent planning process that is targeted at a reduction of the expected adverse consequences of the hazard impact. This study focuses on riverbed cities, aiming to analyze flood occurrences and their influencing factors. Through an extensive literature review, five key criteria commonly associated with flood events were identified: slope height, distance from rivers, topographic index, and runoff height. Utilizing the network analysis process within Super Decision software, these factors were weighted, and a final flood risk map was generated using the simple weighted sum method. 75% of the data was used for training, and 25% of it was used for testing. Additionally, vegetation changes were assessed using Landsat imagery from 2000 and 2022 and the normalized difference vegetation index (NDVI). The focus of this research is Qirokarzin city as a case study of riverbed cities, situated in Fars province, with Qir city serving as its central hub. Key rivers in Qirokarzin city include the Qara Aghaj River, traversing the plain from north to south; the primary Mubarak Abad River, originating from the east; and the Dutulghaz River, which enters the eastern part of the plain from the southwest of Qir, contributing to plain nourishment during flood events. The innovation of this paper is that along with the objective to produce a reliable delineation of hazard zones, a functional distinction between the loading and the response system (LS and RS, respectively) is made. Results indicate the topographic index as the most influential criterion, delineating Qirokarzin city into five flood risk zones: very low, low, moderate, high, and very high. Notably, a substantial portion of Qirokarzin city (1849.8 square kilometers, 8.54% of the area) falls within high- to very-high flood risk zones. Weighting analysis reveals that the topographic humidity index and runoff height are the most influential criteria, with weights of 0.27 and 0.229, respectively. Conversely, the height criterion carries the least weight at 0.122. Notably, 46.7% of the study area exhibits high flood intensity, potentially attributed to variations in elevation and runoff height. Flood potential findings show that the middle class covers 32.3%, indicating moderate flood risk due to changes in elevation and runoff height. The low-level risk is observed sporadically from the east to the west of the study area, comprising 12.4%. Analysis of vegetation changes revealed a significant decline in forest and pasture cover despite agricultural and horticultural development, exacerbating flood susceptibility.

A new enhanced TDEEC protocol for 3D HWSN

Wireless sensor networks (WSNs) are classified as three-dimensional (3D) when the elevation variation of deployed sensor nodes is significant relative to the length and breadth of the operating area. This paper introduces and evaluates a novel protocol, Enhanced Three-Dimensional Efficient TDEEC (ETDEEC-3D), which employs multidimensional scaling to optimize energy consumption in 3D heterogeneous wireless sensor networks (HWSNs) through an improved clustering approach. By excluding nodes closest to the base station from the clustering process, the protocol significantly extends the network lifetime. Performance evaluations indicate that ETDEEC-3D outperforms the TDEEC-3D algorithm in terms of packet delivery, energy efficiency, and the number of cluster heads (CH) formed per round. MATLAB simulations reveal a 24 % improvement in the First Node Dies (FND) metric, a 33 % reduction in energy consumption, and enhanced energy efficiency, achieved by strategically selecting CHs based on nodes' residual energy levels.

Can storage-discharge characteristics of karst matrix system quantified through recession analysis be reliable?

Storage and subsequent release of water in matrix system is a key function of karst catchments that controlling baseflow variation. Hydrograph recession analysis is currently the economic way to assess storage-discharge characteristics broadly at the catchment scale. However, there is large uncertainty in the related quantification due to recession data extraction. This study, by combining recursive digital filters with different automatic extraction methods, slow flow recession segments were extracted for hydrograph recession analysis and the further dynamic matrix storage (DMS) and related recession time (RT) assessment. The diversity and consistence among DMS and RT derived from different recession extraction methods (REMs) were analyzed, using hydrometric data in 20 catchments in the Wujiang river Basin in southwest China. Results indicate that the estimates of DMS and RT remarkedly varied between different REMs, however the order in which they ranked was mostly consistent. Moreover, the relationships between the derived DMS and RT with catchment physical features that potentially control storage and release processes are mostly consistent. Larger DMS are strongly associated with catchments featured as lower soil saturated hydraulic conductivity and smoother hydrographs. Longer RT are mostly related with drier catchments characterized as less variation of elevation and lower soil saturated hydraulic conductivity. This study highlights not only the uncertainty in quantifying storage and accompanied release characteristics, but also the reliability of storage-discharge characteristics quantified through recession analysis in terms of catchment comparison. Considering the diversity among catchments, ensemble of multi-method estimates of DMS and RT can enhance our understanding of the storage-discharge processes in the karst matrix system.

Genome-Wide Dissection of Selection on microRNA Target Genes Involved in Rice Flower Development.

Although genome-wide studies have identified a number of candidate regions evolving under selection in domesticated animals and cultivated plants, few attempts have been made, from the point of a definite biological process, to assess sequence variation and characterize the regimes of the selection on miRNA-associated motifs. Here, we performed a genome-wide dissection of nucleotide variation and selection of miRNA targets associated with rice flower development. By sampling and resequencing 26 miRNA targets for globally diverse representative populations of Asian cultivated rice and wild relatives, we found that purifying selection has reduced genetic variation at the conserved miRNA binding sites on the whole, and highly conserved miRNA binding sequences were maintained in the studied rice populations. Conversely, non-neutral evolution of positive and/or artificial selection accelerates the elevated variations at nonconserved binding sites in a population-specific behavior which may have contributed to flower development-related phenotypic variation. Taken together, our results elucidate that miRNA targets involved in flower development are under distinctive selection regimes during rice evolution.

Length–Weight Relationship and Spatiotemporal Distribution Pattern of Three Schizothoracinae Fishes Along the Nujiang River in the Qinghai–Tibetan Plateau, China

The Qinghai–Tibet Plateau (QTP) is a unique ecological area that has faced issues like diminishing ecosystem stability and increasing pressures on resources and the environment. These issues have arisen as a result of the combined impact of global warming and human activities in recent times. The study of the growth and distribution patterns of schizothoracinae fishes can support guiding policy decisions about the conservation of aquatic species and ecological habitats in the QTP. The investigation on fish resources was carried out in the QTP section of the Nujiang River during the spring and autumn seasons of 2017, 2018, and 2019. A total of seven sampling sites were established based on variations in elevation. According to length–weight relationship (LWR) analysis, Schizothorax nukiangensis mainly displayed a negative allometric growth while Ptychobarbus kaznakovi and Schizopygopsis thermalis mainly showed near isometric growth or positive allometric growth in the QTP section of the Nujiang River. Due to temperature and food abundance, the three schizothoracinae fishes showed better growth performance in autumn than spring. Spatial heterogeneity exhibited a greater influence on the LWR of S. nukiangensis and P. kaznakovi than seasonal variation. In contrast, seasonal variation on S. thermalis showed greater influence than spatial heterogeneity. According to the linear mixed effect model (LMM), both spatial factors and seasons had influence on fish growth in the QTP. Schizothorax nukiangensis was identified as the predominant species from CWL to BS, spanning an altitude range of 1800 to 2700 m. Ptychobarbus kaznakovi was identified as the main species at LL, BB, and BR, occupying an altitude range of 2700 to 3800 m. Schizopygopsis thermalis is primarily distributed at altitudes beyond 4000 m and along the tributary river Yuqu. Principal coordinates analysis (PCOA) and nonmetric multidimensional scaling (NMDS) divided schizothoracinae fish populations into three clusters by spatial differences. Redundancy analysis (RDA) and Monte Carlo Permutation analysis revealed that habitat elevation and water temperature had a significant impact on schizothoracinae fish distribution. This article enhances our understanding of the distribution and environmental adaptation of indigenous fish in the Qinghai–Tibet Plateau.

Unravelling spatial scale effects on elevational diversity gradients: insights from montane small mammals in Kenya

BackgroundMontane ecosystems play crucial roles as global biodiversity hotspots. However, climatic changes and anthropogenic pressure increasingly threaten the stability of montane community dynamics, such as diversity-elevation interactions, creating a challenge in understanding species biogeography and community ecology dynamics in these crucial conservation areas. We examined how varying sampling spatial grains influence small mammal diversity patterns within Kenya’s tallest montane ecosystems.MethodsEmploying a combination of multidimensional alpha diversity metrics and multisite beta diversity characteristics (species richness, phylogenetic and functional diversity and divergence, and multisite beta diversity) alongside spatial generalized additive multivariate regression analyses, we tested how spatial scaling influences elevational diversity gradient patterns and their associations with environmental and human activity variables.ResultsThe diversity-elevation associations were generally homogeneous across spatial grains; however, idiosyncratic patterns emerged across mountains. The total (taxonomic, phylogenetic, and functional) beta diversity, nestedness, and turnover resultant components monotonically increased or decreased with varying spatial grains. The associations between the diversity patterns and the environmental and human footprint variables increased with spatial grain size but also presented variations across mountains and indices. Species richness and phylogenetic and functional richness indices were more strongly influenced by spatial scale variations than were the divergence and community structure indices in both the diversity distribution patterns and their associations with the environmental and human variables.ConclusionsThe diversity-elevation and diversity-environment (including human activity pressure) relationships across spatial grains suggest that montane small mammal diversity patterns portray subtle but systematic sensitivity to sampling spatial grain variation and underscore the importance of geographical context in shaping these elevational diversity gradients. For improved effectiveness, conservation efforts should consider these spatial effects and the unique geographical background of individual montane ecosystems.

The Fungal Community Structure Regulates Elevational Variations in Soil Organic Carbon Fractions in a Wugong Mountain Meadow.

Soil organic carbon (SOC) fractions are vital intrinsic indicators of SOC stability, and soil fungi are the key drivers of soil carbon cycling. However, variations in SOC fractions along an elevational gradient in mountain meadows and the role of the fungal community in regulating these variations are largely unknown, especially in subtropical areas. In this study, an elevation gradient experiment (with experimental sites at 1500, 1700, and 1900 m) was set up in a Miscanthus sinensis community in a meadow on Wugong Mountain, Southeast China, to clarify the effects of elevation on soil fungal community composition, microbial residue carbon, and SOC fractions. The results showed that the contribution of soil microbial residue carbon to SOC was only 16.1%, and the contribution of soil fungal residue carbon to SOC (15.3%) was far greater than that of bacterial residue carbon (0.3%). An increase in elevation changed the fungal community structure and diversity, especially in the topsoil (0-20 cm depth) compared with that in the subsoil (20-40 cm depth), but did not affect fungal residue carbon in the two soil layers. When separating SOC into the fractions mineral-associated organic carbon (MAOC) and particulate organic carbon (POC), we found that the contribution of MAOC (66.6%) to SOC was significantly higher than that of POC (20.6%). Although an increased elevation did not affect the SOC concentration, it significantly changed the SOC fractions in the topsoil and subsoil. The soil POC concentration and its contribution to SOC increased with an increasing elevation, whereas soil MAOC showed the opposite response. The elevational variations in SOC fractions and the POC/MAOC ratio were co-regulated by the fungal community structure and total nitrogen. Our results suggested that SOC stabilization in mountain meadows decreases with an increasing elevation and is driven by the fungal community structure, providing scientific guidance for SOC sequestration and stability in mountain meadows in subtropical areas.

30 years of terrestrial insect richness patterns across elevation: What have we learned? A global meta-analysis.

Understanding elevation variation in biodiversity is a classic question in ecology and has implications for understanding climate change impacts on mountain ecosystems. While insects are the largest group of animals, the global trend in insect species richness with elevation is unknown. To date, single studies and taxa-specific syntheses have provided no single picture, finding variable patterns of insect richness with elevation. A global synthesis across systems would provide a better understanding of how insect species richness changes with elevation and the possible environmental correlates of those patterns. We used published studies of terrestrial insect elevation gradients from 1990 to 2020 to ask: How do insect species richness change with elevation, and which environmental variables best explain this relationship statistically? With 1486 sites spanning 151 species richness-elevation gradients from 80 studies from four diverse insect taxonomic groups and five biomes, we found that overall proportional richness reached a low-elevation plateau and then decreased. We also show that mean annual temperature and seasonality best explain this trend. We suggest best practices and areas of interest for the future of insect richness-elevation studies, including underrepresented groups, geographic areas, and more standardized methods.

A novel flood conditioning factor based on topography for flood susceptibility modeling

Flood is one of the most devastating natural hazards. Employing machine learning models to construct flood susceptibility maps has become a pivotal step for decision-makers in disaster prevention and management. Existing flood conditioning factors inadequately account for regional characteristics of flood in the depiction of topography, potentially leading to an overestimation of flood susceptibility in flat areas. Addressing this gap, this study proposes a novel flood conditioning factor, local convexity factor (LCF), to enhance the accuracy of flood susceptibility modeling. Initially, LCF is computed based on a standard normal Gaussian surface to highlight elevation variations in local terrain. Subsequently, LCF is applied to flood susceptibility modeling using seven machine learning models across four distinct basins. Comparative analysis is conducted between flood susceptibility maps with and without the application of LCF to evaluate its impact on flood susceptibility modeling. The results demonstrate that the proposed LCF can enhance the accuracy of flood susceptibility modeling to varying degrees, across the four basins investigated. The Fujiang basin exhibited the most substantial improvement, with its AUC improved from 0.861 to 0.886, Producer’s Agreement improved from 0.869 to 0.899, and Overall Agreement improved from 0.778 to 0.811. Comparation with hydrodynamic inundation maps shows that particularly in relatively flat terrain areas, flood susceptibility maps incorporating LCF offer more precise delineation between flood-prone and non-flood-prone zones. This research holds potential for widespread application in the prediction of flood susceptibility using machine learning models, providing a novel perspective for enhancing their accuracy.

Untangling the influence of biotic and abiotic factors on the elevational variation of plant intrinsic water-use efficiency and nitrogen availability in an alpine-gorge region on the eastern Qinghai-Tibetan Plateau

Untangling the influence of biotic and abiotic factors on the elevational variation of plant intrinsic water-use efficiency and nitrogen availability in an alpine-gorge region on the eastern Qinghai-Tibetan Plateau

Road Surface Texture Evaluation and Relation to Low-Speed Skid Resistance for Different Types of Mixtures

Pavement skid resistance is significant for driving safety. British Pendulum Number (BPN) is commonly used as a low-speed skid resistance indicator, whereas sometimes it is impractical for data collection on roads in service. Since skid resistance is greatly affected by pavement surface texture, this research aims to evaluate pavement surface texture comprehensively and estimate the low-speed friction BPN from road surface texture on macro- and micro- scale. Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA) were included. Road surface texture was evaluated from four aspects, texture depth, amplitude-related Root Means Square (RMS), elevation variances corresponding to different wavebands and texture spectral analysis. Texture depth indicators include Mean Texture Depth (MTD) and Mean Profile Depth (MPD). Elevation variances with three wavebands, from 5 mm to 50 mm, from 0.5 mm to 5 mm and from 0.024 mm to 0.5 mm respectively, were obtained. The results show that MPD is well correlated with MTD. Elevation variances with different wavebands demonstrates that the elevation variance of macro-texture with long wavelengths from 5 mm to 50 mm dominates the total variance. Spectral analysis shows that texture level is larger when the wavelength is beyond 4 mm, which is consistent with elevation variances. A linear regression between BPN and single texture index, as well as multiple linear regression analysis were conducted. The former regression result indicates that it is not feasible to estimate BPN using single index due to low correlation coefficient R2. The latter shows that the BPN can be estimated from texture levels corresponding to 64 mm and 2 mm, and the micro-texture. The R2 can be up to 0.684. This research will contribute to fast acquisition of BPN from pavement surface texture, thus improving skid resistance.

Evidence of Intraspecific Adaptive Variation in the American Pika (Ochotona princeps) on a Continental Scale Using a Target Enrichment and Mitochondrial Genome Skimming Approach.

Montane landscapes present an array of abiotic challenges that drive adaptive evolution amongst organisms. These adaptations can promote habitat specialisation, which may heighten the risk of extirpation from environmental change. For example, higher metabolic rates in an endothermic species may contribute to heightened cold tolerance, whilst simultaneously limiting heat tolerance. Here, using the climate-sensitive American pika (Ochotona princeps), we test for evidence of intraspecific adaptive variation amongst environmental gradients across the Intermountain West of North America. We leveraged results from previous studies on pika adaptation to generate a custom nuclear target enrichment design to sequence several hundred candidate genes related to cold, hypoxia and dietary detoxification. We also applied a 'genome skimming' approach to sequence mitochondrial DNA. Using genotype-environment association tests, we identified rare genomic variants associated with elevation and temperature variation amongst populations. Amongst mitochondrial genes, we identified intraspecific variation in selective signals and significant changes to the amino acid property equilibrium constant, which may relate to electron transport chain efficiency. These results illustrate a complex dynamic of adaptive variation amongst O. princeps where lineages and populations have adapted to unique regional conditions. Some of the clearest signals of selection were in a genetic lineage that includes pikas of the Great Basin region, which is also where recent localised extirpations have taken place and highlights the risk of losing adaptive alleles during environmental change.

Analysis of resting status reveals distinct elevational variation in metabolisms of lizards.

Animals spend a considerable proportion of their life span at rest. However, resting status has often been overlooked when investigating how species respond to environmental conditions. This may induce a large bias in understanding the local adaptation of species across environmental gradients and their vulnerability to potential environmental change. Here, we conducted an empirical study on montane agamid lizards, combined with mechanistic modeling, to compare elevational variations in body temperature and metabolisms (cumulative digestion and maintenance cost) between resting and active status. Our study on three populations of an agamid lizard along an elevational gradient revealed a trend of decreasing body temperature toward higher elevations, the main contributor of which was resting status of the lizards. Using population-specific reaction norms, we predicted greater elevational variation in hourly and cumulative digestion for resting lizards than for active lizards. Climate-change impacts, estimated as the change in cumulative digestion, also show greater elevational variation when resting status is factored into the analysis. Further, our global analysis of 98 agamid species revealed that in about half of their combined distributional range, the contribution of resting status in determining the elevational variation in cumulative digestion and maintenance cost of lizards was greater than the contribution made by a lizard's active status. Our study highlights the importance of considering resting status when investigating how species respond to environmental conditions, especially for those distributed over tropical and subtropical mountain areas.