Pastoralp Tools

Cartography

This section displays an updated and static cartography of the Gran Paradiso National Park and Parc Des Ecrins pasture vegetation, according to 13 grassland types, inventoried by integrating field surveys (carried out in 2019-2020-2021) and remotely sensed data. The interactive one can be navigated onto the WEBGIS section.

The pasture mapping activity involved the PNE and PNGP territories differently: in the PNE, some pasture maps produced under the “Alpages Sentinelles” programme were already available. The field work allowed to add six more pasture maps and to resurvey for a total of 2563 ha mapped. In the Gran Paradiso National Park, on the other hand, the surveys and mapping activities were done ex novo. All mountain pastures of Gran Paradiso National Park and closest surroundings, for a total of about 7500 ha, were involved.

The inventory followed a common and shared methodology between the two areas, likely to easily replicable to the whole western Alps, namely:

• The territories of the two Parks lie in the validity zones of three different vegetation typologies, which classify the main plant communities that can be found in subalpine and alpine pastures in French Southern Alps (Jouglet, 1999), Vanoise and Aosta Valley (Bornard et al., 2007) or Piedmont (Cavallero et al., 2007). Categorization criteria were harmonised between the three classifications and common 13 pasture categories were developed.
• The mountain grassland types have been identified by field visual assessments, and mapped according to the existing pasture typologies. This action was implemented in the territories of Gran Paradiso National Parkand closest surroundings (Orco, Cogne and Rhêmes Valleys) as well in targeted pastoral units of Parc Des Ecrins.
• Existing and new remote sensing data (namely Landsat and Sentinel2 images) were used to implement innovative ways of mapping the main types of mountain pastures at a relevant scale for pastoral management. Whenever feasible, a special attention was paid to the cross-validation between field and satellite data. This result was achieved through these steps: a) identification and characterization of a number of properly representative surfaces to cover the range of variation in representative plots; b) processing and analysis of remotely sensed data to select the spectral indices capable of best discriminating the different vegetation types; c) validation of the detection algorithms through the comparison of results derived from satellite imagery with real vegetation on the ground.

The harmonization of classifications to define 13 common pasture categories from the Aosta Valley typology is reported in the figure.

A brief description of pastoral typologies is hereby, while the pasture type correspondences between the three vegetation typologies of the study area is reported in Table 1:

• Productive: vegetation in flatlands and low slopes of the subalpine level with rich soil. Very tall (over 50 cm) and very dense vegetation dominated by broad-leaved graminaceae.
• Subalpine intermediate: vegetation in flatlands and low slopes of the subalpine level with medium-rich soil. 30 to 50 cm high, dense grassy patches dominated by fine to medium-leaved graminaceae.
• Nardus swards: on lowlands and slopes in the subalpine or alpine level, vegetation of medium height (20-30 cm), not very dense, dominated by Nardus stricta.
• Grassy thermophile: on medium and steepy sunny slopes in the subalpine and alpine level, on dry and fairly deep soil. 30 to 50 cm high, very dense vegetation with almost total herbaceous cover.
• Patzkea paniculata swards: on medium sunny slopes in the subalpine level, vegetation very tall (over 50 cm), very dense, dominated by graminaceae with long, thick leaves, especially Patzkea paniculata.
• Brachypodium pinnatum swards: on medium sunny slopes in the subalpine level, vegetation of medium height (20-30 cm), dense, dominated by Brachypodium pinnatum.
• Bare thermophile: medium to steep south-facing slopes in the subalpine and alpine level with dry soil.
• Alpine intermediate: sparse vegetation on medium to moderate slopes, windy ridges and bumps in the alpine level.
• Nival: sparse vegetation in snow combes and moderate slopes in alpine and nival environment.
• Heaths: vegetation with a shrub and herb layer in the subalpine and alpine environment.
• Nitrophilous vegetation: in flatlands and moderate slopes of the subalpine level; these herbaceous formations, dominated by nitrophilous species, develop in areas of accumulation and excess of manure.
• Screes: areas with more than 50% of the surface occupied by stones and rocks, on steep slopes, located under ridges or rock bars.
• Wetlands: very wet areas with temporary or permanent excess of water.

Table 1. Pasture type correspondences between the three vegetation typologies of the study area.

For further details, please refer to Deliverable C.6 (due in January 2022).

Pasture Vegetation in the inner alps: the hierarchy

Monitoring

This section includes real-time data deriving from a series of phenocams and NDVI sensors positioned both in the Gran Paradiso National Park and in the Parc Des Ecrins to monitor the phenology of pastures.

Gran Paradiso National Park: a network of phenocam and NDVI sensors allows to track the seasonal evolution of canopy structural and functional properties and their interactions with climate and grazing; observation sites are located along a management gradient: a low elevation (~1500 m asl) intensively grazed pasture (Epinel), an extensively grazed grassland at 2000 m asl (Lauson) an high elevation grassland (Levionaz) with bouquet in grazing. Collected data are used to understand the feedbacks between taxonomical and functional diversity with site conditions, climate and grazing intensity, frequency and timing. They also represent field observations that can be used to evaluate remotely sensed products and to inform grassland productivity models.

National Parc Des Ecrins: several sensors have been installed, with the aim to monitor pasture’s meadows phenology at different altitudes (e.g. agro-climatic conditions) and pastoral management. Two sites are situated in a pasture (name : Crouzet) of L’Argentière-la-Bessée. One site is located at 1940 m above sea level in a subalpine meadow, and the other one is situated in the alpine zone at 2350 m above sea level, in an alpine meadow. Both sites are equipped with NDVI sensors and cameras for landscape monitoring. The NDVI sensors and the camera installed on the lower site can transmit rea-time data (not available yet), while the camera installed on the higher site does not. Another site is at Lautaret, currently transmitting real time data of air temperature and humidity, wind speed, NDVI values and snow cover.

Please click on one of the buttons below to see the real-time data for the relevant park.

• PNGP
• PNE

Impacts

This section displays outcomes from future climate projections on the case study areas, climate change impact on pastoral productive macro-types performed by means of process-based (DayCent, PaSim) and statistical (Random Forest) modelling approaches. The analysis was carried out by means of meteorological observations and data on pasture management, production, growth and development, which were collected from stations located in the two study areas (Parc National des Ecrins and Gran Paradiso National Park). The section includes three sub-sections, namely:

1. Future Climate impacts: The impacts of future climate are displayed as user friendly maps of the main climatic indicators. These indicators have been calculated from a downscaling and bias correction procedure of Regional Circulation Models so as to produce high-resolution current and future climatic data for the study areas at daily time step under future RCPs (4.5 and 8.5) IPCC scenarios and two time slices (2011–2040 and 2041-2070) as projected by three RCMs (ALADIN, CCLM, ICTP) and the ensemble of them.
2. Pastoral suitability: Pastoral future suitability is displayed as user-friendly maps and derives from a machine learning (Random Forest) approach which was employed to map areas current suited to pastoral resources in the two study areas, and simulate the impact of climate change on their dynamics under two future RCPs (4.5 and 8.5) IPCC scenarios and two time slices (2011–2040 and 2041-2070), as ensembled from three RCMs (ALADIN, CCLM, ICTP).
3. Impacts on pastoral productive macrotypes: changes on pastures Growing season, Biomass peak dates, Biomass peak value, GHG fluxes (NEE, N2O, CH4) NPP, GPP, and Soil water content on three pastoral macrotypes (namely low-medium and high productive) are displayed as graphs as simulated by PaSim and DayCent models under two future RCPs (4.5 and 8.5) IPCC scenarios and two time slices (2011–2040 and 2041-2070) as projected by the ensemble of the three RCMs (ALADIN, CCLM, ICTP). The models were firstly calibrated by means of satellite-derived leaf area index (LAI) and normalised difference vegetation index (NDVI) trajectories, and then run against future climatic dataset so to assess the impacts of future climate on biomass and phenology of three pasture macro-typologies, namely low-medium-high productive pastures.

Maps on climate change impacts for GIS skilled users are available at the WEBGIS section.

Adaptation

This section includes two subsections:

1. List of feasible adaptation strategies: this section displays interactively a list of adaptation strategies identified to address climate change adaptation for the two case study areas. These strategies encompass both technical strategies and policies considering their applicability, impact on biodiversity, success factors, technical difficulties by means of on-field testing, stakeholders consultations, modelling output. These strategies are promoted for the Western Alpine pastoral contexts to address and cope with climate change and extreme climate events (e.g. droughts). A detailed description of these strategies is included in Deliverable C.6 (Feasible adaptation strategies) and will set the basis to develop the climate change action plan in alpine pastoral contexts (Action C.8) advocating adaption for pastures of the entire Alpine chain.

A Glossary is also displayed at the bottom.

2. Outcomes from adaptation strategies application: This subsection displays graphs on outcomes deriving from the application of adaptation strategies to the three pasture productive macro-types as deriving from PaSim and DayCent modelling under two future RCPs (4.5 and 8.5) IPCC scenarios and two time slices (2011–2040 and 2041-2070) .

Please choose one type of adaptation below in order to browse the relevant adaptation tree.

Glossary

Vulnerability

This section includes outcomes from the vulnerability analysis, i.e. modelling outcomes and socio-economic variables, as well as climatic and biodiversity indicators as resulting from Action C.5. The model outcomes are obtained using two distinct models. Pastures productivity and emissions are estimated using two biogeochemical models (PaSim and DayCent), whilst shifts in distribution of pastures are obtained using machine learning approach (Random Forest). List of socio-economic, climatic and biodiversity indicators are defined according to a variety of means including literature scanning, indicator classification, and local stakeholders’ contribution by means of individual questionnaires.

Model outcomes are displayed coupled with climatic indicators (aridity index, hot and cold spells frequency index, etc.), and complemented with biodiversity indicators, in view of a socio-economic assessment. This will allow to create vulnerability indicators for the pastures located in the study area as well as to extrapolate information of the best timing for grazing under current and future climate.

WebGIS

This section makes available all interactive maps produced during the project under a webgis environment, thus requiring a skilled user in Geographical Information Systems (GIS) software. The maps available are the following:

• Current and future climate (absolute values and delta changes)
• Pastoral Suitability
• Pasture Macro types (13 pastoral typologies, 3 productive Pasture macro types)

climate

suitability

macrotypes