As a mountainous country, Nepal is most susceptible to precipitation extremes and related hazards, including severe floods, landslides and droughts that cause huge losses of life and property, impact the Himalayan environment, and hinder the socioeconomic development of the country. Given that the countrywide assessment of such extremes is still lacking, we present a comprehensive picture of prevailing precipitation extremes observed across Nepal. First, we present the spatial distribution of daily extreme precipitation indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) from 210 stations over the period of 1981–2010. Then, we analyze the temporal changes in the computed extremes from 76 stations, featuring long-term continuous records for the period of 1970–2012, by applying a non-parametric Mann−Kendall test to identify the existence of a trend and Sen’s slope method to calculate the true magnitude of this trend. Further, the local trends in precipitation extremes have been tested for their field significance over the distinct physio-geographical regions of Nepal, such as the lowlands, middle mountains and hills and high mountains in the west (WL, WM and WH, respectively), and likewise, in central (CL, CM and CH) and eastern (EL, EM and EH) Nepal. Our results suggest that the spatial patterns of high-intensity precipitation extremes are quite different to that of annual or monsoonal precipitation. Lowlands (Terai and Siwaliks) that feature relatively low precipitation and less wet days (rainy days) are exposed to high-intensity precipitation extremes. Our trend analysis suggests that the pre-monsoonal precipitation is significantly increasing over the lowlands and CH, while monsoonal precipitation is increasing in WM and CH and decreasing in CM, CL and EL. On the other hand, post-monsoonal precipitation is significantly decreasing across all of Nepal while winter precipitation is decreasing only over the WM region. Both high-intensity precipitation extremes and annual precipitation trends feature east−west contrast, suggesting significant increase over the WM and CH region but decrease over the EM and CM regions. Further, a significant positive trend in the number of consecutive dry days but significant negative trend in the number of wet (rainy) days are observed over the whole of Nepal, implying the prolongation of the dry spell across the country. Overall, the intensification of different precipitation indices over distinct parts of the country indicates region-specific risks of floods, landslides and droughts. The presented findings, in combination with population and environmental pressures, can support in devising the adequate region-specific adaptation strategies for different sectors and in improving the livelihood of the rural communities in Nepal.

Climate warming is expected to induce treelines to advance to higher elevations. Empirical studies in diverse mountain ranges, however, give evidence of both advancing alpine treelines and rather insignificant responses. The inconsistency of findings suggests distinct differences in the sensitivity of global treelines to recent climate change. It is still unclear where Himalayan treeline ecotones are located along the response gradient from rapid dynamics to apparently complete inertia. This paper reviews the current state of knowledge regarding sensitivity and response of Himalayan treelines to climate warming, based on extensive field observations, published results in the widely scattered literature, and novel data from ongoing research of the present authors. Several sensitivity indicators such as treeline type, treeline form, seed-based regeneration, and growth patterns are evaluated. Since most Himalayan treelines are anthropogenically depressed, observed advances are largely the result of land use change. Near-natural treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Nevertheless, intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth–climate relationships show mature treeline trees to be responsive to temperature change, in particular in winter and pre-monsoon seasons. High pre-monsoon temperature trends will most likely drive tree growth performance in the western and central Himalaya. Ecological niche modelling suggests that bioclimatic conditions for a range expansion of treeline trees will be created during coming decades.

Himalayan treelines are exposed to above average climate change impact, resulting in complex tree growth–climate relationships for Himalayan Silver Fir (Abies spectabilis (D. Don) Spach) at central Himalayan treelines. The majority of recent studies detected current tree growth sensitivity to dry conditions during pre-monsoon seasons. The aim of this study was to analyze growth–climate relationships for more than a century for a treeline ecotone in east-central Nepal and to test for Blue Intensity (BI; used as a surrogate of maximum late wood density) as climate proxy. We determined the relationships of Abies spectabilis radial tree growth and BI to climate by correlating both to temperature, precipitation and drought index data. The results showed a significantly unstable dendroclimatic signal over time. Climate warming-induced moisture deficits during pre-monsoon seasons became a major factor limiting radial tree growth during recent decades. Earlier in time, the dendroclimatic signal was weaker, predominantly reflecting a positive relationship of tree growth and summer temperature. Compared to radial tree growth, BI showed a different but strong climate signal. Temporally unstable correlations may be attributed to increasing effects of above-average rates of climate warming. An extended network of Himalayan tree-ring sites is needed to further analyze cause–effect relationships and to solve this attribution problem.

Comparing and evaluating global climate datasets and their effect on model performance in regions with limited data availability has received little attention in ecological modeling studies so far. In this study, we aim at comparing the interpolated climate dataset Worldclim 1.4, which is the most widely used in ecological modeling studies, and the quasi-mechanistical downscaled climate dataset Chelsa, as well as their latest versions Worldclim 2.1 and Chelsa 1.2, with regard to their suitability for modeling studies. To evaluate the effect of these global climate datasets at the meso-scale, the ecological niche of Betula utilis in Nepal is modeled under current and future climate conditions. We underline differences regarding methodology and bias correction between Chelsa and Worldclim versions and highlight potential drawbacks for ecological models in remote high mountain regions. Regarding model performance and prediction plausibility under current climatic conditions, Chelsa-based models significantly outperformed Worldclim-based models, however, the latest version of Chelsa contains partially inherent distorted precipitation amounts. This study emphasizes that unmindful usage of climate data may have severe consequences for modeling treeline species in high-altitude regions as well as for future projections, if based on flawed current model predictions. The results illustrate the inevitable need for interdisciplinary investigations and collaboration between climate scientists and ecologists to enhance climate-based ecological model quality at meso- to local-scales by accounting for local-scale physical features at high temporal and spatial resolution.

Modelling ecological niches across vast distribution ranges in remote, high mountain regions like the Himalayas faces several data limitations, in particular nonavailability of species occurrence data and fine-scale environmental information of sufficiently high quality. Remotely sensed data provide key advantages such as frequent, complete, and long-term observations of land surface parameters with full spatial coverage. The objective of this study is to evaluate modelled climate data as well as remotely sensed data for modelling the ecological niche of Betula utilis in the subalpine and alpine belts of the Himalayan region covering the entire Himalayan arc. Using generalized linear models (GLM), we aim at testing factors controlling the species distribution under current climate conditions. We evaluate the additional predictive capacity of remotely sensed variables, namely remotely sensed topography and vegetation phenology data (phenological traits), as well as the capability to substitute bioclimatic variables from downscaled numerical models by remotely sensed annual land surface temperature parameters. The best performing model utilized bioclimatic variables, topography, and phenological traits, and explained over 69% of variance, while models exclusively based on remotely sensed data reached 65% of explained variance. In summary, models based on bioclimatic variables and topography combined with phenological traits led to a refined prediction of the current niche of B. utilis, whereas models using solely climate data consistently resulted in overpredictions. Our results suggest that remotely sensed phenological traits can be applied beneficially as supplements to improve model accuracy and to refine the prediction of the species niche. We conclude that the combination of remotely sensed land surface temperature parameters is promising, in particular in regions where sufficient fine-scale climate data are not available.