High-elevation Regions Research Articles

Recent changes in heatwaves and maximum temperatures over a complex terrain in the Himalayas

The temperature response to anthropogenic global warming and forest cover changes is dependent on regional climatic characteristics. It is challenging to segregate the impacts of the two anthropogenic changes on local temperatures and heatwaves over complex mountainous regions. Here we present estimates of regional and local heat stress responses to the recent global climate change and local forest cover loss in complex terrain in the Himalayas using a satellite-based high-resolution land-surface temperature dataset. We find large-scale decreasing trends in the observed frequency of heatwaves and heat days, and localized increases in urbanized and high-elevation regions. Our results show large-scale significant decreasing trends in annual maximum and mean surface temperatures over the period 2003–2019. In locations that have witnessed large-scale forest losses, the declines in the surface temperatures were steeper compared to no-loss regions.We develop a regional multiple linear regression model to estimate the regional and local temperature responses to global climatic change and to segregate them from the response to forest cover losses. Our model estimates a regional decrease of about 2.0 °C in annual maximum temperature over the recent 2003–2019 period, which is locally modulated by the extent of urbanization, forest cover, and elevation. At the locations of intense deforestation, our model successfully predicts a steeper decrease in maximum surface temperature, and estimates the temperature response due to forest loss, after controlling for elevation and initial forest cover. The local cooling effect due to deforestation was reaffirmed by comparing the regions with contrasting forest cover losses. The results suggest that forest clearing amplifies the anthropogenic climate change over the region.

Flower phenological events and duration pattern is influenced by temperature and elevation in Dhauladhar mountain range of Lesser Himalaya

Studying phenology is undeniably one of the most effective ways to monitor and perceive how a particular plant species interact and respond to varying environmental conditions. In this study, the shifts in flowering phenological events of 24 herbaceous species with the changing elevation and temperature were observed in Dhauladhar Mountain range of Lesser Himalaya. Five permanent plots (20 × 20 m2) were established from 2,000 m to 4,000 m elevation at each rising 500 m distance for the documentation of herbaceous flora. Abundance-based documentation of flowering phenological events (onset of flowering duration [OFD] ≥ 10% to 30%, the peak of flowering duration [PFD] > 30% to 80%, the end of flowering duration [EFD] > 80% and total flowering duration [FD] as the difference of end and onset of flowering DOY) was done in each plot. The onset, the peak, and the end of the flowering day of the year (DOY) were recorded at 20%, 55%, and 90% floral abundance, respectively, from 1st of January. Upon analyses, the Linear-mixed effects model depicted significant differences in the flowering phenological events with elevation and soil temperature. The onset of flowering DOY and peak of the flowering DOY varied significantly with soil temperature gradient, while the end of flowering DOY showed non-significant interaction. The linear model of ANOVA demonstrated that OFD, PFD, EFD and FD varied significantly with elevation at p < 0.001. FD increased with elevation for most of the species, whereas two species, Aquilegia pubiflora and Primula denticulata, showed early incidences of flowering compared to other species. Temperature played an imperative role in influencing the day of initiation and duration of these phenological events. High plasticity of flowering phenological events is advantageous in high elevation regions where pollinators are scarcely present. Therefore, documenting shifting incidences of flowering phenological events would help the researcher to effectively predict climate change effects on alpine communities in near future.

Ozone and its precursors in a high-elevation and highly forested region in central China: Origins, in-situ photochemistry and implications of regional transport

Atmospheric chemistry observation and modelling in alpine areas have strong indication of regional air quality. In this study, one-month continuous ozone (O3) measurement at a high-elevation and highly forested site in central China, in combination with observations at similar stations, indicated elevated O3 levels in the free troposphere (FT) over China. Uninterrupted O3 injuries to the old-growth forest in the study region were expected. FT O3 overwhelmed daytime photochemical formation at the site, and the transport of O3 from the north (e.g., Guanzhong Plain) was most significant. Air masses from the adjacent southwest and south regions (e.g., Chongqing) contained higher levels of nitric oxide, sulfur dioxide, fine particles and volatile organic compounds (VOCs) in association with vehicular and industrial emissions. In contrast, air masses from the northeast (e.g., North China Plain) were laden with combustion tracers. The in-situ photochemistry modelling confirmed weak O3 formation at the site. For the reasons, the insufficient nitrogen oxides suppressed transformation of peroxyl radicals to alkoxy and hydroxyl radicals, resulting in considerable losses of peroxyl radicals via self-reactions. VOCs showed little impact on in-situ O3 production, and accounted for net consumption of OH, with isoprene as the most predominant OH depleting species. This study fills the gaps in observation of O3 and its precursors and modelling of in-situ photochemistry in high-elevation regions of central China, and provides hints for the impacts of transport on air pollution in this region.

Atmospheric controls on precipitation isotopes and hydroclimate in high-elevation regions in Eastern Africa since the Last Glacial Maximum

Tropical Africa experienced large changes in hydroclimatic conditions since the Last Glacial Maximum (LGM), ∼26.5 to 19 thousand years (ka or kyr) ago. The hydrogen isotopic composition of fossil leaf waxes (δDwax), assumed to record past variations in the hydrogen isotopic composition of precipitation (δDprecip), is increasingly being used to study past hydroclimatic change in Africa, and are commonly interpreted to reflect variation in the amount of precipitation through time (i.e., the amount effect). Although there are now many such δDprecip records from tropical Africa, there are few robust δDprecip records from easternmost equatorial Africa of sufficient length and resolution to evaluate the mechanisms governing hydroclimate variation during and since the LGM. We produced a new δDprecip record based on analyses of δDwax in sediment cores collected from Lake Rutundu, situated at an elevation of 3,078 meters above sea level (m asl) on Mt. Kenya. This record displays large variations in δDprecip corresponding with known climate events over the past 25 kyr, including D-enrichment during the Heinrich 1 stadial (H1) and the Younger Dryas (YD), and D-depletion during the Holocene portion of the African Humid Period (AHP). We also observe D-depletion during the LGM relative to the late Holocene, which, considering the amount effect, could be interpreted to imply that LGM climate conditions were wetter than today. However, because other hydroclimate proxies at this site indicate a drier LGM climate at Lake Rutundu, and since precipitation isotopes at this high-elevation site are likely influenced by different processes than at low elevations, we used a single-column Rayleigh distillation model to evaluate temperature and altitude-related effects on high-elevation δDprecip. This revealed that a change in the temperature lapse rate exerts strong control on δDprecip in this high-elevation setting, and that a steeper lapse rate could explain the observed D-depletion during the LGM at our site. Comparison of the Lake Rutundu δDprecip record with other leaf-wax based δDprecip records from East Africa indicates that changes in the meridional precipitation gradient associated with the mean annual position and intensity of the tropical rain belt, in turn driven by precessional insolation forcing, were likely a primary control on East African hydroclimate over the past 25 kyr, thereby contributing to overall regional drying during the LGM.

Ensemble Models Predict Invasive Bee Habitat Suitability Will Expand under Future Climate Scenarios in Hawai'i.

Simple SummaryClimate change exacerbates the threat of biological invasions by increasing climatically suitable regions for species to invade outside of their native range. Island ecosystems may be particularly sensitive to the synergistic effects of climate change and biological invasions. In Hawai’i there are 21 non-native bees that have the capacity to spread pathogens and compete for resources with native bees. We performed an ensemble of species distribution models (SDM) for eight non-native bee species (Hymenoptera: Anthophila) in Hawai’i to predict climatically suitable niches across current and future climate scenarios. We found a significant difference in habitat suitability between SDMs that were constructed with specimen records from their native and non-native (Hawai’i) range. Although SDMs predict expansion of suitable habitat into higher elevations under 2070 climate scenarios, species-rich areas are predicted to stay below 500 m elevation. Our models can inform decisions on the management of non-native bees in Hawai’i by assessing risk of invasion into new areas around the archipelago.Climate change is predicted to increase the risk of biological invasions by increasing the availability of climatically suitable regions for invasive species. Endemic species on oceanic islands are particularly sensitive to the impact of invasive species due to increased competition for shared resources and disease spread. In our study, we used an ensemble of species distribution models (SDM) to predict habitat suitability for invasive bees under current and future climate scenarios in Hawai’i. SDMs projected on the invasive range were better predicted by georeferenced records from the invasive range in comparison to invasive SDMs predicted by records from the native range. SDMs estimated that climatically suitable regions for the eight invasive bees explored in this study will expand by ~934.8% (±3.4% SE). Hotspots for the invasive bees are predicted to expand toward higher elevation regions, although suitable habitat is expected to only progress up to 500 m in elevation in 2070. Given our results, it is unlikely that invasive bees will interact directly with endemic bees found at >500 m in elevation in the future. Management and conservation plans for endemic bees may be improved by understanding how climate change may exacerbate negative interactions between invasive and endemic bee species.

Spatiotemporal change and attribution of potential evapotranspiration over China from 1901 to 2100

Global warming has accelerated surface water loss around the world. This study investigates in detail the change and attribution of potential evapotranspiration (PET) across China from 1901 to 2100 by the Hargreaves model, based on a 1-km temperature dataset downscaled from the low-spatial-resolution datasets using a Delta downscaling framework. Results showed that (1) relative to 1961–1990, PET increased by 0.62% in the historic period (1901–2017) and 6.43–12.89% for the future period (2018–2100), suggesting considerable future drying for China. Moreover, these increments had strong spatial variations and the largest increases were detected in high-elevation regions; (2) PET over entire China demonstrated a nonsignificant upward trend during the historic period and significant upward trends for the future period. For each period and GCM, significant upward PET trends occupied a much larger percent area than significant downward trends; (3) PET variations during the historic period were most sensitive to mean temperature (TMP), while in the future period it was more sensitive to maximum temperature (TMX), suggesting a change in the primary sensitivity factor due to global warming; (4) minimum temperature (TMN) made the largest contribution (45%) to PET variations during the historic period, while TMX had the largest contribution (36–40%) in the future period. Therefore, the primary contributing factor might transform from TMN to TMX under climate change; and (5) PET variations exhibited strong spatial heterogeneity, detected on fine geographic scales, due to the use of downscaled dataset. Overall, the results present a deep insight for planning coping strategies of global warming in China.

Vegetation responses to 26 years of warming at Latnjajaure Field Station, northern Sweden

Climate change is rapidly warming high latitude and high elevation regions influencing plant community composition. Changes in vegetation composition have motivated the coordination of ecological monitoring networks across the Arctic, including the International Tundra Experiment. We have established a long-term passive warming experiment using open-top chambers, which includes five distinct plant communities (Dry Heath; Tussock Tundra; and Dry, Mesic, and Wet Meadow). We measured changes in plant community composition based on relative abundance differences over 26 years. In addition, relative abundance changes in response to fertilization and warming treatments were analyzed based on a seven-year Community-Level Interaction Program experiment. The communities had distinct soil moisture conditions, leading to community-specific responses of the plant growth forms (deciduous shrubs, evergreen shrubs, forbs, and graminoids). Warming significantly affected growth forms, but the direction of the response was not consistent across the communities. Evidence of shrub expansion was found in nearly all communities, with soil moisture determining whether it was driven by deciduous or evergreen shrubs. Graminoids increased in relative abundance in the Dry Meadow due to warming. Growth form responses to warming are likely mediated by edaphic characteristics of the communities and their interactions with climate.

Impact of climate change on the Andean distribution of Poa scaberula (Poaceae)

Grasslands play an important ecological role and are the dominant landscape in the whole extent of the Andes and high elevation regions of South America. Climate change models indicate a strong impact on mountain systems. The climatic conditions of mountain systems are greatly influenced by topography and elevation. Poa scaberula Hook. f. is an Andean grass and its habitat may be threatened by climate change and human practices. Species distribution models, using bioclimatic variables, are often used to predict the future distribution and environmental requirements of species. In this study we prepared two bioclimatic models for P. scaberula using the Maxent algorithm, the first based on the inclusion of the variable elevation (E +) and the second on the exclusion of elevation (E-) to identify the main environmental variables for habitat suitability shift, to examine changes in the extent of the area of suitable habitat under current and future climate scenarios, and to project and quantify the spatial pattern of shifts in the areal extent of suitable habitat under future climate conditions. We then compared both projections and evaluate the contribution of the elevation variable in the performance of the models. We observed that the inclusion of elevation decreased the performance of the models. In models with omission of the elevation mean cold hardiness, temperature seasonality and annual mean temperature emerge as the critical factors shaping habitat suitability for P. scaberula. Under the low and higher concentration greenhouse gas emissions scenario, the range of the species may decrease as global warming intensifies. The information gained from this study should be an useful reference for development biogeographic studies and the impact of global warming on regions of high elevations, and contribute to implement conservation and management strategies for Andean grassland and high elevation grasslands.

The alteration of the suitability patterns of Leishmania infantum due to climate change in Iran

ABSTRACT Leishmaniasis is the most important parasitic infection in Iran. The aim of this study was to model the changing suitability patterns of Leishmania infantum, the causative agent of visceral leishmaniasis for the 21st century in the country. Temperature, precipitation, and aridity-nature distribution limiting bioclimatic variables were involved in the ecological modelling. The altitudinal trends were considered by using 100 m bars. In Iran, the topographical patterns strongly impact the changing patterns of the suitability of L. infantum due to climate change. In general, climate change will decrease the parasite’s suitability in the areas at low altitudes and increase in the middle and higher elevation regions. Increasing values are mainly predicted in the West, the decreasing suitability values in the East part of Iran. The altitudinal shifts and the reduced spatial distribution of L. infantum in the arid regions of East and Central Iran were modelled.

High microbial diversity stabilizes the responses of soil organic carbon decomposition to warming in the subsoil on the Tibetan Plateau

Soil microbes are directly involved in soil organic carbon (SOC) decomposition, yet the importance of microbial biodiversity in regulating the temperature sensitivity of SOC decomposition remains elusive, particularly in alpine regions where climate change is predicted to strongly affect SOC dynamics and ecosystem stability. Here we collected topsoil and subsoil samples along an elevational gradient on the southeastern Tibetan Plateau to explore the temperature sensitivity (Q10 ) of SOC decomposition in relation to changes in microbial communities. Specifically, we tested whether the decomposition of SOC would be more sensitive to warming when microbial diversity is low. The estimated Q10 value ranged from 1.28 to 1.68, and 1.80 to 2.10 in the topsoil and subsoil, respectively. The highest Q10 value was observed at the lowest altitude of forests in the topsoil, and at the highest altitude of alpine meadow in the subsoil. Variations in Q10 were closely related to changes in microbial properties. In the topsoil the ratio of gram-positive to gram-negative bacteria (G+:G-) was the predominant factor associated with the altitudinal variations in Q10 . In the subsoil, SOC decomposition showed more resilience to warming when the diversity of soil bacteria (both whole community and major groups) and fungi was higher. Our results partly support the positive biodiversity-ecosystem stability hypothesis. Structural equation modeling further indicates that variations in Q10 in the subsoil were directly related to changes in microbial diversity and community composition, which were affected by soil pH. Collectively our results provide compelling evidence that microbial biodiversity plays an important role in stabilizing SOC decomposition in the subsoil of alpine montane ecosystems. Conservation of belowground biodiversity is therefore of great importance in maintaining the stability of ecosystem processes under climate change in high-elevation regions of the Tibetan Plateau.

Impact of Soil Moisture Initializations on WRF‐Simulated North American Monsoon System

AbstractThis study investigates the influence of soil moisture initialization on the North American Monsoon System (NAMS) using the Weather Research and Forecasting (WRF) model coupled with Noah‐MP Land Surface Model. Five sets of experiments using different soil moisture initializations were conducted from May 1 to October 1 in 2015–2017. The model forecast for each set of experiments consists of five ensemble members. The simulation using North American Regional Reanalysis is the control run (WRF‐Ctrl). Four sets of sensitivity experiments were conducted with extremely wet (WRF‐Wet) and dry (WRF‐dry) initial conditions and using different soil moisture products from the Global Land Data Assimilation System (WRF‐GLDAS) and NASA Soil Moisture Active Passive L4 (WRF‐SMAP). Results show that the WRF model can capture the key features of the NAMS, but it exhibits a wet bias in the higher elevation regions and a dry bias in the lower elevation regions. Our analysis of extremely wet and dry cases reveals that initial soil moisture conditions can affect precipitation through both modulating surface energy partitioning and influencing large‐scale pressure and wind patterns. When different soil moisture products are used to initialize the model, it can lead to substantial changes in spatial pattern of the NAM precipitation. Initializing the model with SMAP and GLDAS can reduce the overestimation of precipitation over high terrain areas. The results indicate that high‐quality soil moisture products have the potential to improve model representation of the NAMS, especially with future improvements in model convective parameterization.

Spatial uncertainty of rainfall and its impact on hydrological hazard forecasting in a small semiarid mountainous watershed

Rainfall in mountainous watershed presents high spatial variability due to elevation effects, and this introduces uncertainty in forecasting hydrological hazards such as water floods and debris flows. This study investigated the spatial variation of rainfall in a small watershed with a network of 10 rain gauges. A rainfall-elevation relationship was established based on data from 52 rainstorm events, which provides a method for rainfall estimation within the watershed. Result indicated that lower errors of interpolation occur when the rainfall amount is high, and that it is more difficult to estimate rainfall in high-elevation regions. Rain gauges become less representative when the distance between gauges is >3.0 km. The spatial variation of rainfall suggests that the gauge at the lowest elevation, or a single gauge within the source region, shows non-negligible errors with regard to calculating water flood discharge and identifying rainfall thresholds for debris flows. This study contributes to the understanding of event rainfall distribution and its impact on hydrological hazard forecasting in a small mountainous watershed.

Range extension of two xerophytic mosses in China based on molecular and morphological data

Feng, C., Kou, J., Zhang, G.-L. & Wang, Z. 2020. Range extension of two xerophytic mosses in China based on molecular and morphological data. – Herzogia 33: 300 –308.An abnormal morphotype of Grimmia crinitoleucophaea Cardot, a species widely known as G. poecilostoma Cardot & Sebille, has been found in Inner Mongolian typical steppe, and its identification confirmed based on molecular and morphological data. Its morphological variation and taxonomic status are also discussed. Didymodon canoae C.Feng, J.Kou & L.Feng, a species previously known only from its type location in Inner Mongolia, was discovered in Tibet which extends its distribution range to a high elevation region of southwest China. Diagnostic characters, differences compared to similar species, distributional remarks and photographs of the two species are provided.

Projections for Mexico’s Tropical Rainforests Considering Ecological Niche and Climate Change

The tropical rainforest is one of the lushest and most important plant communities in Mexico’s tropical regions, yet its potential distribution has not been studied in current and future climate conditions. The aim of this paper was to propose priority areas for conservation based on ecological niche and species distribution modeling of 22 species with the greatest ecological importance at the climax stage. Geographic records were correlated with bioclimatic temperature and precipitation variables using Maxent and Kuenm software for each species. The best Maxent models were chosen based on statistical significance, complexity and predictive power, and current potential distributions were obtained from these models. Future potential distributions were projected with two climate change scenarios: HADGEM2_ES and GFDL_CM3 models and RCP 8.5 W/m2 by 2075–2099. All potential distributions for each scenario were then assembled for further analysis. We found that 14 tropical rainforest species have the potential for distribution in 97.4% of the landscape currently occupied by climax vegetation (0.6% of the country). Both climate change scenarios showed a 3.5% reduction in their potential distribution and possible displacement to higher elevation regions. Areas are proposed for tropical rainforest conservation where suitable bioclimatic conditions are expected to prevail.

A dual state-parameter updating scheme using the particle filter and high-spatial-resolution remotely sensed snow depths to improve snow simulation

Snow varies widely in space and time over high mountain regions. Accurately representing the spatial distribution of snow water equivalent (SWE) is critically important for improving our understanding of snow accumulation and melt processes. Despite its importance, in situ observations are lacking in poorly gauged regions such as the headwater region of the Yangtze River (HRYR). Traditional remotely sensed retrievals are highly uncertain due to the effect of cloudiness (e.g., optical remote sensing-derived snow cover area) and the coarse spatial resolution (e.g., passive microwave remote sensing-derived snow depth). Hydrological modeling is a powerful way to understand the snow processes, but uncertainty still exists due to model deficiency and errors of forcing data. Assimilating high-spatial-resolution remotely sensed snow data into a snowmelt model may be potentially valuable for more accurate snow predictions. In this study, a high-spatial-resolution remotely sensed snow depth data set (500 m, derived by integrating snow cover area, land surface temperature, and passive microwave brightness temperature products) was assimilated into a snowmelt model within a particle filter (PF) assimilation framework, which updates both model state variables and parameters simultaneously. After assimilation, the time series of basin-averaged SWE estimation showed an appreciable improvement with respect to the simulation with the traditional calibration (TC) method, in terms of the Nash-Sutcliffe efficiency (NSE) coefficient increased by ~ 10–20% and root‐mean‐square error (RMSE) decreased by ~ 7–18%. The PF approach also greatly improved the spatial distribution of SWE estimation with RMSE decreased by ~ 15–30%. The SWE estimation from the PF was also comparable or even better than that from another assimilation scheme, namely, the direct insertion. Comparison with in situ snowfall data indicated that the simulated snowfall from the PF outperformed the TC, with RMSE decreased by ~ 15–32% and correlation coefficient increased by ~ 58–83%. Furthermore, the evolution of parameters suggested the applicability of the PF method with spatially variable parameters. With spatiotemporally variable parameters in the PF, the snow model could perfectly simulate the actual snow distribution particularly over high elevation regions where the average temperature was lower than 0 °C, while fixed parameters in the TC cannot simulate the variable snow distribution. The proposed data assimilation framework has large potential of improving the accuracy of snow prediction across poorly gauged high mountain areas.

The potential future change of the suitability patterns of six leishmaniasis vectors in Iran.

Visceral and cutaneous leishmaniasis are endemic in Iran. The aim of this study was to model the changing suitability patterns of five confirmed and one suspected leishmaniasis vector Phlebotomus species resident in the country. The potential present and future suitability patterns of the sandfly species in Iran were modelled using climate envelope forecasting method for the reference period 1970-2000 and the future period 2041-2060. The reference period climate of Iran seemed to be the most suitable for Phlebotomus perfiliewi and Phlebotomus tobbi and less suitable for Phlebotomus simili, while Phlebotomus neglectus, Phlebotomus papatasi and Phlebotomus sergenti showed intermediate values among the studied sandfly species. The modelled changes in the suitability values show a similar pattern in the case of the six species, even the exact magnitude of the modelled values varied. The model results indicate that climate change could decrease the sandfly habitability in the present-day arid regions in Central Iran. The Iranian sandfly populations will move to higher elevation regions, and the suitability values of the sandfly species are predicted to increase in the foothills of the mountainous regions in the northern and the western part of the country. The increase of the maximally suitable areas in Iran was found which was predicted to be accompanied by the parallel shrinkage of the sandfly-inhabited areas in the arid regions of the country. Topographical conditions could strongly influence the suitability patterns of the vectors in Iran.

The expansion of the Acheulian to the Southeastern Ethiopian Highlands: Insights from the new early Pleistocene site-complex of Melka Wakena

Current models of early hominin biological and cultural evolution are shaped almost entirely by the data accumulated from the East African Rift System (EARS) over the last decades. In contrast, little is known about the archaeological record from the high-elevation regions on either side of the Rift. Melka Wakena is a newly discovered site-complex on the Southeastern Ethiopian Highlands (SEH) (>2300 m above mean sea level) just east of the central sector of the Main Ethiopian Rift (MER), where eight archaeological and two paleontological localities were discovered to date. Nine archaeological horizons from three localities were tested so far, all dated to the second half of the early Pleistocene (∼1.6 to >0.7 Ma). All the lithic assemblages belong to the Acheulian technocomplex. Here we report on geochronological, stratigraphic, paleontological and lithic technological aspects of the tested localities and contextualize them in the broader framework of hominin cultural evolution in eastern Africa. Findings from Melka Wakena, assessed against the backdrop of the few other highland sites (Melka Kunture and Gadeb), support a scenario of expansion rather than dispersal from the Rift to the highlands. When considered in the context of the Rift-highlands interface, results of the first-phase research at Melka Wakena help to parse existing general models into archaeologically testable hypotheses and demonstrate the site’s potential to contribute to research of early prehistory and to understanding the dynamics of early Pleistocene hominin populations in eastern Africa.

The best-fitting distribution of water balance and the spatiotemporal characteristics of drought in Guizhou Province, China

Drought is one of the most severe natural hazards with a significant impact on water resources. Droughts affect the sustainability of water resources and may result in environmental degradation of a region. The appropriate drought index is playing an important role on drought assessment. This paper addresses the best-fitting distribution of monthly water balance (WB), and the spatiotemporal characteristics of drought in Guizhou Province, China, during 1960–2017. The best-fitting distribution of monthly WB calculated using three potential evapotranspiration (PET) estimation methods was determined based on the goodness-of-fit test. The Standardized Precipitation Evapotranspiration Index (SPEI) at various timescales was computed based on the optimal distribution. The modified Mann-Kendall method, run theory, and inverse distance weight (IDW) interpolation method were used to investigate spatiotemporal evolution of drought. Over result revealed that the common log-logistic distribution was not the most suitable distribution for WB in Guizhou Province and the gen. extreme value distribution is optimum fit for the WB series calculated based on different methods for 76.47% of the stations. Moreover, different calculation methods seem to have little influence on the fitting results. The drought shows an upward trend in spring and autumn and a downward trend in summer and winter during 1960–2017; the increasing magnitude of summer and autumn drought was greater in the northeastern and northwestern Guizhou Province. The annual droughts are significantly increasing (p = 0.05) at Anshun and Panxian. The drought frequency showed a decreasing trend from light drought to severe drought in Guizhou Province, and the drought intensity was relatively more severe during 2010–2017 than other periods. These findings are helpful for water resource management in Guizhou Province and indicate that we should pay more attention to the drought mitigation of the higher-elevation regions.

Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya

The performance of gridded precipitation products is especially important over mountainous regions because of the lack of observations. This study provides a detailed evaluation of the spatial precipitation patterns presented by the ERA-Interim, ERA5, ERA5-Land, and refined HAR datasets with spatial resolutions from coarse to fine (0.7°, 0.25°, 0.1°, and 0.1°, respectively) over the southern slope of central Himalaya, Nepal. The major findings are as follows: (1) The high-resolution ERA5-Land and ERA5 datasets well present the observed spatial pattern of precipitation but with a generally overestimated amount; the refined HAR dataset also presents many fine-scale details, while the coarse resolution ERA-Interim dataset tends to exhibit a too gentle spatial characteristic in mountainous Nepal. (2) The four datasets well reproduce the seasonal precipitation variation (R > 0.90) over the country; however, their performance varies spatially across the western, central, and eastern regions. The spatial resolution is also important in representing the terrain blocking of water vapor from the Bay of Bengal, which is transported from east to west in Nepal. (3) The high-resolution datasets can reproduce the elevation dependency as revealed by the observed dataset, while the coarse-resolution cannot capture the elevation dependency in the high-elevation regions. Moreover, all four datasets show very similar performance in low–elevation plane areas, however, higher resolution simulations (ERA5, ERA5–Land, and HAR) better reflect blocking effect of orographic precipitation and outperform ERA-Interim in high–elevation areas where the terrain is very complex and the slope is very steep.

Spatial distribution of Poa scaberula (poaceae) along the andes

Mountains support a great diversity of species and habitat types. Grasslands are the dominant landscape in the Andes and play an important ecological role. However, they are threatened by many factors, including climate change and human activities. The spatial distribution of species that compose, and the ecological and evolutionary factors that provide for the spatial biodiversity patterns, are little known. The largest Poa L. (Poaceae) genera are widely diversified and distributed in the Andes. In particular, P. scaberula Hook. f. shows great environmentally mediated phenotypic plasticity, and is distributed from North America to the tip of South America. However, the impact of environmental variables has on the spatial distribution of this species, remain largely unknown. Using high-resolution climatic data, herein we modeled the current suitable habitat for P. scaberula and identified the main climatic variables that best predict its potential distribution. In addition, we assess the species status in the predicted habitats through herbarium data and relate it with species distribution models. The models showed that P. scaberula has a suitable habitat of ca. 162.747 km2 along the Andes and high elevation regions. The most influential variables with a 68.5% contribution to the distribution of the species, particularly high elevation areas, included mean cold hardiness, water vapor pressure and temperature seasonality. The areas of greatest suitability with the highest occurrence of the species were identified geographically by the models. The present study provides useful information that can assist in the identification of areas where the species is most sensitive to different variables, including climate change and human activities and contributes in assessing the conservation status of Andean grassland at a regional scale.