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.

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.

Modelling snow cover duration improves predictions of functional and taxonomic diversity for alpine plant communities.

BACKGROUND AND AIMS: Quantifying relationships between snow cover duration and plant community properties remains an important challenge in alpine ecology. This study develops a method to estimate spatial variation in energy availability in the context of a topographically complex, high-elevation watershed, which was used to test the explanatory power of environmental gradients both with and without snow cover in relation to taxonomic and functional plant diversity. METHODS: Snow cover in the French Alps was mapped at 15-m resolution using Landsat imagery for five recent years, and a generalized additive model (GAM) was fitted for each year linking snow to time and topography. Predicted snow cover maps were combined with air temperature and solar radiation data at daily resolution, summed for each year and averaged across years. Equivalent growing season energy gradients were also estimated without accounting for snow cover duration. Relationships were tested between environmental gradients and diversity metrics measured for 100 plots, including species richness, community-weighted mean traits, functional diversity and hyperspectral estimates of canopy chlorophyll content. KEY RESULTS: Accounting for snow cover in environmental variables consistently led to improved predictive power as well as more ecologically meaningful characterizations of plant diversity. Model parameters differed significantly when fitted with and without snow cover. Filtering solar radiation with snow as compared without led to an average gain in R(2) of 0·26 and reversed slope direction to more intuitive relationships for several diversity metrics. CONCLUSIONS: The results show that in alpine environments high-resolution data on snow cover duration are pivotal for capturing the spatial heterogeneity of both taxonomic and functional diversity. The use of climate variables without consideration of snow cover can lead to erroneous predictions of plant diversity. The results further indicate that studies seeking to predict the response of alpine plant communities to climate change need to consider shifts in both temperature and nival regimes.

Long-term modeling of the forest-grassland ecotone in the French Alps: implications for land management and conservation.

Understanding decadal-scale land-cover changes has the potential to inform current conservation policies. European mountain landscapes that include numerous protected areas provide a unique opportunity to weigh the long-term influences of land-use practices and climate on forest-grassland ecotone dynamics. Aerial photographs from four dates (1948, 1978, 1993, and 2009) were used to quantify the extent of forest and grassland cover at 5-m resolution across a 150-km2 area in a protected area of the southwestern French Alps. The study area included a grazed zone and a nongrazed zone that was abandoned during the 1970s. We estimated time series of a forestation index (FI) and analyzed the effects of elevation and grazing on FI using a hierarchical linear mixed effect model. Forest extent (composed primarily of mountain pine, Pinus uncinata) expanded from 50.6 km2 in 1948 to 85.5 km2 in 2009, i.e., a 23% increase in relative cover at the expense of grassland communities. Over the sixty-year period, the treeline rose by 118 m, from 1564 to 1682 m. Rapid forest expansion within the nongrazed zone followed the cessation of logging activities and was likely accelerated by climate warming during the 1980s. Within the grazed zone, the maintained presence of sheep did not fully counteract mountain pine expansion and led to highly contrasting rates of land-cover change based on the location of shepherds' cabins and water sources. Projections of FI for 2030 showed remnant patches of intensively used grasslands interspersed in a densely forested matrix. Our analysis of mountain land-cover dynamics provided strong evidence for forest encroachment into grassland habitat despite consistent grazing pressure. This pattern may be attributed to the disappearance of traditional land-use practices such as shrub burning and removal. Our findings prompt land managers to reconsider their initial conservation priority (i.e., the protection of a renowned mountain pine forest) and to implement proactive management strategies in order to preserve landscape heterogeneity and biological diversity. Projecting historical trends in the forest-grassland ecotone to 2030 provides stakeholders with a policy relevant tool for near-term land management.

Working toward integrated models of alpine plant distribution.

Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial-temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.