Climatic Drivers of Greening Trends in the Alps

Microbial mechanisms regulate soil organic carbon mineralization under carbon with varying levels of nitrogen addition in the above-treeline ecosystem

Climate change is leading to the upward migration of treelines in mountainous regions, resulting in changes to the carbon and nitrogen inputs in soils. The impact of these alterations on the microbial mineralization of the existing soil organic carbon (SOC) pool remains uncertain, making it challenging to anticipate their effects on the carbon balance. To enhance our prediction and understanding of native SOC mineralization in Himalayan regions resulting from treeline shifts, a study was conducted to quantify soil priming effects (PEs) at high elevations above the treeline ecosystem. In laboratory incubation, soils were treated with a combination of 13C-glucose and varying nitrogen rates, along with carbon-only treatments and control groups without any amendments. The addition of carbon with varying nitrogen addition rates exhibited diverse PEs on native SOC. A highly positive PE was observed under low nitrogen input due to a high carbon/nitrogen imbalance and increased L-leucine aminopeptidase (LAP) activity, coupled with low nitrogen availability and carbon use efficiency (CUE). In contrast, a positive PE declined following high nitrogen input due to a low carbon/nitrogen imbalance and LAP activity, coupled with high nitrogen availability and CUE. These findings support the concept that multiple mechanisms (i.e., microbial nitrogen mining and microbial metabolic efficiency) exist that regulate SOC mineralization under the addition of carbon with varying nitrogen rates. Thus, an increase in nitrogen availability fulfils microbial nitrogen demand, reduces the microbial carbon/nitrogen imbalance, decreases enzyme activity that requires nitrogen and enhances microbial metabolic efficiency. Consequently, this mechanism reduces the positive PE, thereby serving as a potential tool for stabilizing native SOC in above-treeline ecosystems.

Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity

Global climate change is having significant effects on plant growth patterns and mountain plants can be particularly vulnerable to accelerated warming. Rising temperatures are releasing plants from cold limitation, such as at high elevations and latitudes, but can also induce drought limitation, as documented for trees from lower elevations and latitudes. Here we test these predictions using a unique natural experiment with Himalayan alpine shrub Rhododendron anthopogon and its growth responses to changing climate over a large portion of its latitudinal and elevational ranges, including steep precipitation and temperature gradients. We determined growth dynamics during the last three decades, representing period of accelerated warming, using annual radial growth increments for nine populations growing on both wet and warm southern localities and drier and cold northern localities in the Himalayas along elevation gradients encompassing the lower and upper species range limits. A significant growth increase over past decades was observed after controlling for confounding effect of shrub age and microsites. However, the magnitude of increase varied among populations. Particularly, populations situated in the lower elevation of the northernmost (cold and dry) locality exhibited most substantial growth enhancement. The relationship between growth variability and climate varied among populations, with the populations from the coldest location displaying the strongest responsiveness to increasing minimum temperatures during July. Minimum temperatures of April and August were the most important factor limiting the growth across most populations. Potential warming-induced drought limitation had no significant impact on growth variation in any part of the species geographic range. Overall, our findings indicate that plant growth is continuously increasing in recent decades and growth-climate relationships are not consistent across populations, with populations from the coldest and wettest localities showing stronger responses. The observed patterns suggest that dwarf-shrubs benefit from ongoing warming, leading to increased shrubification of high elevation alpine ecosystems.

Hydrogeological characteristics and water availability in the mountainous aquifer systems of Italian Central Alps: A regional scale approach

Groundwater resources in mountain areas are strategically important to maintain adequate water supply for domestic uses, farming, industrial activities, and energy production, also considering the expected growing demand due to ongoing climate changes. Within this framework, the objective of the study is to develop a regional approach, compliant with the European requirements of the Water Framework Directive 2000/60/EC and Groundwater Directive 2006/118/EC, that could support public agencies and water companies to efficiently manage and protect the available water resources in mountainous environments. The proposed approach identifies and delineates groundwater bodies by coupling a 3D hydro-stratigraphic model with the definition of the water budget and water hydrochemical fingerprints in a geologically complex Alpine environment in Northern Italy. Sixteen groundwater bodies (GWBs) have been identified all over the 10.290 km² area, showing an average storage capacity of more than 500 Mm³ y^-1 (about 3% of the average total inflow from precipitation and snowmelt), with differences up to four times between GWBs mainly constituted of carbonate rocks and those prevalently composed of crystalline or terrigenous rocks. Groundwater quality in the study domain is generally excellent, with few exceptions due to geogenic (i.e., natural) or anthropogenic sources of contamination. The results of this study show the advantages of coupling 3D hydro-stratigraphic modelling combined with meteorological, hydrological and hydrogeological information, which consist in: i) identifying the most Strategic Storage Reservoir both in terms of quality and storage capacity; ii) evaluating the present ground- and surface water availability; iii) detecting areas of specific interest for implementing groundwater monitoring networks; iv) recognising recharge areas of the most relevant springs, to implement protection strategies of the resource.

Vessels in a Rhododendron ferrugineum (L.) population do not trace temperature anymore at the alpine shrubline

INTRODUCTION

Mean xylem vessel or tracheid area have been demonstrated to represent powerful proxies to better understand the response of woody plants to changing climatic conditions. Yet, to date, this approach has rarely been applied to shrubs.

METHODS

Here, we developed a multidecadal, annually-resolved chronology of vessel sizes for Rhododendron ferrugineum shrubs sampled at the upper shrubline (2,550 m asl) on a north-facing, inactive rock glacier in the Italian Alps.

RESULTS AND DISCUSSION

Over the 1960-1989 period, the vessel size chronology shares 64% of common variability with summer temperatures, thus confirming the potential of wood anatomical analyses on shrubs to track past climate variability in alpine environments above treeline. The strong winter precipitation signal recorded in the chronology also confirms the negative effect of long-lasting snow cover on shrub growth. By contrast, the loss of a climate-growth relation signal since the 1990s for both temperature and precipitation, significantly stronger than the one found in radial growth, contrasts with findings in other QWA studies according to which stable correlations between series of anatomical features and climatic parameters have been reported. In a context of global warming, we hypothesize that this signal loss might be induced by winter droughts, late frost, or complex relations between increasing air temperatures, permafrost degradation, and its impacts on shrub growth. We recommend future studies to validate these hypotheses on monitored rock glaciers.

Remote sensing hydrological indication: Responses of hydrological processes to vegetation cover change in mid-latitude mountainous regions

Hydrological processes in mid-latitude mountainous regions are greatly affected by changes in vegetation cover that induced by the climate change. However, studies on hydrological processes in mountainous regions are limited, because of difficulties in building and maintaining basin-wide representative hydrological stations. In this study, a new method, remote sensing technology for monitoring river discharge by combining satellite remote sensing, unmanned aerial vehicles and hydrological surveying, was used for evaluating the runoff processes in the Changbai Mountains, one of the mid-latitude mountainous regions in the eastern part of Northeast China. Based on this method, the impact of vegetation cover change on hydrological processes was revealed by combining the data of hydrological processes, meteorology, and vegetation cover. The results showed a decreasing trend in the monitored river discharge from 2000 to 2021, with an average rate of -5.13 × 10⁵ m³ yr^-1. At the monitoring section mainly influenced by precipitation, the precipitation-induced proportion of changes in river discharge to annual average river discharge and its change significance was only 6.5 % and 0.23, respectively, showing the precipitation change was not the cause for the decrease in river discharge. A negative impact of evapotranspiration on river discharge was found, and the decrease in river discharge was proven to be caused by the increasing evapotranspiration, which was induced by the drastically increased vegetation cover under a warming climate. Our findings suggested that increases in vegetation cover due to climate change could reshape hydrological processes in mid-latitude mountainous regions, leading to an increase in evapotranspiration and a subsequent decrease in river discharge.

Assessing the Sensitivity of Vegetation Cover to Climate Change in the Yarlung Zangbo River Basin Using Machine Learning Algorithms

Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60%–4.68% when the temperature increased by 1.5 °C, while it only changed by 0.06%–0.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau.

The tempo of greening in the European Alps: Spatial variations on a common theme

The long-term increase in satellite-based proxies of vegetation cover is a well-documented response of seasonally snow-covered ecosystems to climate warming. However, observed greening trends are far from uniform, and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on above-treeline ecosystems in the European Alps. NDVI changes in these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We observed widespread greening for the 2000-2020 period, a pattern that is consistent with the overall increase in summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north-facing slopes between 1900 and 2400 m. Using high-resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snow melt and green-up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water-related habitat amelioration above treeline.

Land Use Modeling Predicts Divergent Patterns of Change Between Upper and Lower Elevations in a Subalpine Watershed of the Alps

The synergic influence of land use and climate change on future forest dynamics is hard to disentangle, especially in human-dominated forest ecosystems. Forest gain in mountain ecosystems often creates different spatial–temporal patterns between upper and lower elevation belts. We analyzed land cover dynamics over the past 50 years and predicted Business as Usual future changes on an inner subalpine watershed by using land cover maps, derived from five aerial images, and several topographic, ecological, and anthropogenic predictors. We analyzed historical landscape patterns through transition matrices and landscape metrics and predicted future forest ecosystem change by integrating multi-layer perceptron and Markov chain models for short-term (2050) and long-term (2100) timespans. Below the maximum timberline elevation of the year 1965, the dominant forest dynamic was a gap-filling process through secondary succession at the expense of open areas leading to an increase of landscape homogeneity. At upper elevations, the main observed dynamic was the colonization of unvegetated soil through primary succession and timberline upward shift, with an increasing speed over the last years. Future predictions suggest a saturation of open areas in the lower part of the watershed and stronger forest gain at upper elevations. Our research suggests an increasing role of climate change over the last years and on future forest dynamics at a landscape scale.

Introducing intense rainfall and snowmelt variables to implement a process-related non-stationary shallow landslide susceptibility analysis

The study objective was to derive a susceptibility model for shallow landslides that could include process-related non-stationary variables, to be adaptable to climate changes. We selected the territory of the Mont-Emilius and Mont-Cervin Mountain Communities (northern Italy) as the study area. To define summary variables related to landslide predisposing and triggering processes, we investigated the relationships between landslide occurrences and intense rainfall and snowmelt events (period 1991-2020). For landslide susceptibility mapping, we set up a Generalized Additive Model. We defined a reference model through variable penalization (relief, NDVI, land cover and geology predictors). Similarly, we optimized a model including the climate variables, checking their smooth functions to ensure physical plausibility. Finally, we validated the optimized model through a k-fold cross-validation and performed an evaluation based on contingency tables, area under the receiver operating characteristic curve (AUROC) and variable importance (decrease in explained variance). The climate variables that resulted as being statistically and physically significant are the effective annual number of rainfall events with intensity-duration characteristics above a defined threshold (EAT_ean) and the average number of melting events occurring in a hydrological year (ME_n). In the optimized model, EAT_ean and ME_n accounted for 5% of the explained deviance. Compared to the reference model, their introduction led to an increase in true positive rate and AUROC of 2.4% and 0.8%, respectively. Also, their inclusion caused a transition of the vulnerability class in 11.0% of the study area. The k-fold validation confirmed the statistical significance and physical plausibility of the meteorological variables in 74% (EAT_ean) and 93% (ME_n) of the fitted models. Our results demonstrate the validity of the proposed approach to introduce process-related, non-stationary, physically-plausible climate variables within a shallow landslide susceptibility analysis. Not only do the variables improve the model performance, but they make it adaptable to map the future evolution of landslide susceptibility including climate changes.

Climate Change Affects Vegetation Differently on Siliceous and Calcareous Summits of the European Alps

The alpine life zone is expected to undergo major changes with ongoing climate change. While an increase of plant species richness on mountain summits has generally been found, competitive displacement may result in the long term. Here, we explore how species richness and surface cover types (vascular plants, litter, bare ground, scree and rock) changed over time on different bedrocks on summits of the European Alps. We focus on how species richness and turnover (new and lost species) depended on the density of existing vegetation, namely vascular plant cover. We analyzed permanent plots (1 m × 1 m) in each cardinal direction on 24 summits (24 × 4 × 4), with always four summits distributed along elevation gradients in each of six regions (three siliceous, three calcareous) across the European Alps. Mean summer temperatures derived from downscaled climate data increased synchronously over the past 30 years in all six regions. During the investigated 14 years, vascular plant cover decreased on siliceous bedrock, coupled with an increase in litter, and it marginally increased on higher calcareous summits. Species richness showed a unimodal relationship with vascular plant cover. Richness increased over time on siliceous bedrock but slightly decreased on calcareous bedrock due to losses in plots with high plant cover. Our analyses suggest contrasting and complex processes on siliceous versus calcareous summits in the European Alps. The unimodal richness-cover relationship and species losses at high plant cover suggest competition as a driver for vegetation change on alpine summits.

Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

The frequent acquisitions of fine spatial resolution imagery (10 m) offered by recent multispectral satellite missions, including Sentinel-2, can resolve single agricultural fields and thus provide crop-specific phenology metrics, a crucial information for crop monitoring. However, effective phenology retrieval may still be hampered by significant cloud cover. Synthetic aperture radar (SAR) observations are not restricted by weather conditions, and Sentinel-1 thus ensures more frequent observations of the land surface. However, these data have not been systematically exploited for phenology retrieval so far. In this study, we extracted crop-specific land surface phenology (LSP) from Sentinel-1 and Sentinel-2 of major European crops (common and durum wheat, barley, maize, oats, rape and turnip rape, sugar beet, sunflower, and dry pulses) using ground-truth information from the "Copernicus module" of the Land Use/Cover Area frame statistical Survey (LUCAS) of 2018. We consistently used a single model-fit approach to retrieve LSP metrics on temporal profiles of CR (Cross Ratio, the ratio of the backscattering coefficient VH/VV from Sentinel-1) and NDVI (Normalized Difference Vegetation Index from Sentinel-2). Our analysis revealed that LSP retrievals from Sentinel-1 are comparable to those of Sentinel-2, particularly for winter crops. The start of season (SOS) timings, as derived from Sentinel-1 and -2, are significantly correlated (average r of 0.78 for winter and 0.46 for summer crops). The correlation is lower for end of season retrievals (EOS, r of 0.62 and 0.34). Agreement between LSP derived from Sentinel-1 and -2 varies among crop types, ranging from r = 0.89 and mean absolute error MAE = 10 days (SOS of dry pulses) to r = 0.15 and MAE = 53 days (EOS of sugar beet). Observed deviations revealed that Sentinel-1 and -2 LSP retrievals can be complementary; for example for winter crops we found that SAR detected the start of the spring growth while multispectral data is sensitive to the vegetative growth before and during winter. To test if our results correspond reasonably to in-situ data, we compared average crop-specific LSP for Germany to average phenology from ground phenological observations of 2018 gathered from the German Meteorological Service (DWD). Our study demonstrated that both Sentinel-1 and -2 can provide relevant and at times complementary LSP information at field- and crop-level.

Monitoring the Seasonal Hydrology of Alpine Wetlands in Response to Snow Cover Dynamics and Summer Climate: A Novel Approach with Sentinel-2

Climate change in the European Alps during recent years has led to decreased snow cover duration as well as increases in the frequency and intensity of summer heat waves. The risk of drought for alpine wetlands and temporary pools, which rely on water from snowmelt and provide habitat for specialist plant and amphibian biodiversity, is largely unknown and understudied in this context. Here, we test and validate a novel application of Sentinel-2 imagery aimed at quantifying seasonal variation in water surface area in the context of 95 small (median surface area <100 m2) and shallow (median depth of 20 cm) alpine wetlands in the French Alps, using a linear spectral unmixing approach. For three study years (2016–2018), we used path-analysis to correlate mid-summer water surface area to annual metrics of snowpack (depth and duration) and spring and summer climate (temperature and precipitation). We further sought to evaluate potential biotic responses to drought for study years by monitoring the survival of common frog (Rana temporaria) tadpoles and wetland plant biomass production quantified using peak Normalized Difference Vegetation Index (NDVI). We found strong agreement between citizen science-based observations of water surface area and Sentinel-2 based estimates (R2 = 0.8–0.9). Mid-summer watershed snow cover duration and summer temperatures emerged as the most important factors regulating alpine wetland hydrology, while the effects of summer precipitation, and local and watershed snow melt-out timing were not significant. We found that a lack of summer snowfields in 2017 combined with a summer heat wave resulted in a significant decrease in mid-summer water surface area, and led to the drying up of certain wetlands as well as the observed mortality of tadpoles. We did not observe a negative effect of the 2017 summer on the biomass production of wetland vegetation, suggesting that wetlands that maintain soil moisture may act as favorable microhabitats for above treeline vegetation during dry years. Our work introduces a remote sensing-based protocol for monitoring the surface hydrology of alpine wetland habitats at the regional scale. Given that climate models predict continued reduction of snow cover in the Alps during the coming years, as well as particularly intense warming during the summer months, our conclusions underscore the vulnerability of alpine wetlands in the face of ongoing climate change.

Some (do not) like it hot: shrub growth is hampered by heat and drought at the alpine treeline in recent decades

PREMISE

Mountain ecosystems are particularly sensitive to climate change. However, only a very small number of studies exist so far using annually resolved records of alpine plant growth spanning the past century. Here we aimed to identify the effects of heat waves and drought, driven by global warming, on annual radial growth of Rhododendron ferrugineum.

METHODS

We constructed two century-long shrub ring-width chronologies from R. ferrugineum individuals on two adjacent, north- and west-facing slopes in the southern French Alps. We analyzed available meteorological data (temperature, precipitation and drought) over the period 1960-2016. Climate-growth relationships were evaluated using bootstrapped correlation functions and structural equation models to identify the effects of rising temperature on shrub growth.

RESULTS

Analysis of meteorological variables during 1960-2016 revealed a shift in the late 1980s when heat waves and drought increased in intensity and frequency. In response to these extreme climate events, shrubs have experienced significant changes in their main limiting factors. Between 1960 and 1988, radial growth on both slopes was strongly controlled by the sum of growing degree days during the snow free period. Between 1989 and 2016, August temperature and drought have emerged as the most important.

CONCLUSIONS

Increasing air temperatures have caused a shift in the growth response of shrubs to climate. The recently observed negative effect of high summer temperature and drought on shrub growth can, however, be buffered by topographic variability, supporting the macro- and microrefugia hypotheses.