# Towards a transdisciplinary framework for studying the DYNAMICS OF WOODY ALPINE VEGETATION in a WARMING CLIMATE CONTEXT

Loïc Francon, Thierry Améglio, Christophe Corona, Guillaume Charrier, Katline Charra-Vaskou, Jörg Löffler

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Loïc Francon, Thierry Améglio, Christophe Corona, Guillaume Charrier, Katline Charra-Vaskou, et al. Towards a transdisciplinary framework for studying the DYNAMICS OF WOODY ALPINE VEGETATION in a WARMING CLIMATE CONTEXT. 13th International Plant Cold Hardiness Seminar, Aug 2024, Clermont-Ferrand, France. hal-04864847

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# Towards a transdisciplinary framework for studying the DYNAMICS OF WOODY ALPINE VEGETATION in a WARMING CLIMATE CONTEXT

Loïc Francon – University of Bonn - loicfrancon63@gmail.com

13th International Plant Cold Hardiness Seminar

Clermont-Ferrand, 26-30 August 2024

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# The treeline ecotone and the alpine tundra

<figure><img src="image_4.png" /></figure>
<figure><img src="image_5.png" /><figcaption># Woody plants in the alpine zone: TREE SPECIES INDIVIDUALS and SHRUBS (<3 meters high)</figcaption></figure>
# The treeline ecotone and the alpine tundra

<figure><img src="image_6.png" /><figcaption>Mont-Blanc, France</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Valais, Switzerland</figcaption></figure>
# The treeline ecotone and the alpine tundra

<figure><img src="image_8.png" /><figcaption>Oisans, France</figcaption></figure>
ipcc
INTERGOVERNMENTAL PANEL ON climate change

Climate Change 2021
The Physical Science Basis

<figure><img src="image_9.png" /></figure>

WGI

Working Group I Contribution to the
Sixth Assessment Report of the
Intergovernmental Panel on Climate Change

<figure><img src="image_10.png" /></figure>

WMO

<figure><img src="image_11.png" /></figure>

UNEP

CLIMATE CHANGE

"Global surface temperatures are more likely than not **unprecedented in the past 125,000 years**"

"Over the last 50 years, **global temperature has increased at a rate unprecedented** in at least the last 2000 years"
# CLIMATE CHANGE IN TUNDRA ECOSYSTEMS

<figure><img src="image_12.png" /><figcaption>Global temperature increase (2001-2020)
 (vs 1881-1910)</figcaption></figure>

* ✓ +1.2°C in average

* ✓ +2.5°C in the Alps

* ✓ At least +4°C in the Arctic
ECOSYSTEM RESPONSE: VEGETATION GREENING

<figure><img src="image_13.png" /></figure>

Berner et al. (2021)

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2000 - 2016

<figure><img src="image_15.png" /></figure>

Source: ESRI

Choler et al. (2021)

<figure><img src="image_16.png" /></figure>

Mishra and Mainali (2017)
However:

Greening is widespread but not uniform: “Sparsely vegetated ecosystems on north-facing slopes and experiencing prolonged snow cover duration are the most highly responsive to ongoing warming” Choler et al. (2021)

About remote sensing methods: “measured reflectances and derived indices and trends are subject to biases” Bayle et al. (2024)

The ecophysiological processes underlying alpine greening have rarely been investigated

→ Especially in complex mountains terrains

remotely sensed vegetation indices are subject to biases and need
validation from the ground
In the Arctic, the **increasing woody vegetation cover** is the main driver of greening
<figure><img src="image_17.png" /></figure>

Mekonnen et al., (2021)

Remote sensing

<figure><img src="image_18.png" /></figure>

Dendroecology

**Observed changes**

Tundra greenness
(2000 - 2020)

<figure><img src="image_19.png" /></figure>

Shrub cover, growth,
biomass or reproduction
 variable time periods)

<figure><img src="image_20.png" /></figure>

Archives:
phytosociological relevés,
photos, other doc...

Ecophysiology:
Dendrometry

Not existing or
very rare

<figure><img src="image_21.png" /><figcaption>a) Annual growth rings in
*Salix alaxensis*</figcaption></figure>

<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

Tape et al., (2006)
In the Arctic, the increasing woody vegetation cover is the main driver of greening

Such observations remain lacking in mountain regions
This overall trend towards greenness should be reflected in
the landscape through landscape changes linked to woody
vegetation dynamics and ecophysiological processes at
different temporal and spatial scales:

Increasing **radial growth**, increasing **canopy height**,
increasing **number of individuals**, increasing **patchiness**
and shifting **treeline** and **shrubline**

<figure><img src="image_24.png" /></figure>
In order to quantify the response of **woody vegetation to climate change** and its **spatial and temporal dynamics** across mountain ranges, we call for a **transdisciplinary approach combining the four compartments**.

Remote sensing

Dendroecology

Archives:
phytosociological relevés,
photos, other doc...

Ecophysiology:
Dendrometry
The greening in the European Alps

Remote sensing

<figure><img src="image_25.png" /></figure>

Choler et al. (2021)
Archives:

phytosociological relevés,
photos, other doc...

The input of past archives

Example: The use of
historical phytosociological
maps allows to compare with
current state of vegetation

<figure><img src="image_26.png" /></figure>
Dendroecology

The input of dendroecology

<figure><img src="image_27.png" /><figcaption>*Rhododendron ferrugineum*</figcaption></figure>
Dendroecology

Mean ring width = 0.13mm

Maximal age: 215 years

<figure><img src="image_28.png" /><figcaption>Rhododendron ferrugineum</figcaption></figure>

1 cm
8 sites-network designed to be representative of the topographic and climatic contrasts across the French Alps

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<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>
# SHRUBS CLIMATE SENSITIVITY (1960-2017)

## Inner vs. outer Alps

<figure><img src="image_34.png" /></figure>

## South vs. North slopes

<figure><img src="image_35.png" /></figure>

Drought and frost effects
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Francon et al. (unpublished)

We calculate various **frost indices** for low stature vegetation, **using snowpack and temperature** data for the entire French Alps
<figure><img src="image_37.png" /><figcaption>B - Freeze-thaw cycles</figcaption></figure>

<figure><img src="image_38.png" /></figure>

Francon et al. (unpublished)

**Frost exposure risk**
is increasing for low
stature vegetation,
**in most locations**
within the French
Alps
LIMITATIONS

Growth ring width
= Black box

* One value per year

* Integrating stressful events (frost, heat waves)

<figure><img src="image_39.png" /></figure>

RWI

WE NEED ECOPHYSIOLOGICAL DATA
<figure><img src="image_40.png" /><figcaption>Francon</figcaption></figure>

## Hourly monitoring of diameter variations: water status and irreversible growth

Phase 1. Transpiration → (yellow) shrinkage

Phase 2. Rehydration → (orange) expansion

Phase 3. Growth → (red) Stem Radius Increment (SRI)

Stem Water Deficit (SWD) → stress

### Sensor rhodo Bassies S152

<figure><img src="image_41.png" /><figcaption>Francon et al. (unpublished)</figcaption></figure>
EXAMPLE: THE EUROPEAN ALPS

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Francon

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<figure><img src="image_45.png" /><figcaption>Astragalus granatensis</figcaption></figure>

<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /><figcaption>Cytisus galianoi</figcaption></figure>

<figure><img src="image_48.png" /></figure>

<figure><img src="image_49.png" /><figcaption>Genista versicolor</figcaption></figure>

<figure><img src="image_50.png" /></figure>

<figure><img src="image_51.png" /><figcaption>Betula nana</figcaption></figure>

<figure><img src="image_52.png" /></figure>

<figure><img src="image_53.png" /><figcaption>Empetrum hermaphroditum</figcaption></figure>

<figure><img src="image_54.png" /></figure>

<figure><img src="image_55.png" /><figcaption>Phyllodoce caerulea</figcaption></figure>

<figure><img src="image_56.png" /></figure>

Löffler et al. (2022)

B. nana

<figure><img src="image_57.png" /></figure>

A. granatensis

<figure><img src="image_58.png" /></figure>

E. hermaphroditum

<figure><img src="image_59.png" /></figure>

C. galianoi

<figure><img src="image_60.png" /></figure>

P. caerulea

<figure><img src="image_61.png" /></figure>

G. versicolor

<figure><img src="image_62.png" /></figure>

Dobbert et al. (2022)
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Source: ESRI
# NEW FRAMEWORK

<figure><img src="image_65.png" /></figure>

Source: ESRI

<figure><img src="image_66.png" /></figure>

Elevation
gradient

Dry slope

Wet slope

Image © 2024 Maxar Technologies

Data: Landat /©Copernicus

Google Earth
In each plot:

* Extraction of vegetation indices (greening or browning trend?)

* Research of historical archives (aerial images, photographs, vegetation surveys)

* Reconstruction of trees and shrubs recruitment using establishment and death dating

* Extraction of dendroecological signal

* Dendrometers → effect of short term climatic trends and frost/drought

* ...
<figure><img src="image_67.png" /><figcaption>NEW FRAMEWORK</figcaption></figure>
In order to understand trajectories of alpine
landscapes on a global scale, research efforts
need to be continued in the field of:

✓ Remote sensing studies in different mountain regions (still lacking in many areas)

✓ Dendroecological studies, (still lacking for many shrub species)

✓ Ecophysiology of shrubs, and response to extreme frost/drought events
However, the exact drivers of landscape greening are largely unknown

* ✓ Complex topography in mountains makes it difficult (compared to the Arctic)

* ✓ We don't know much on ecological processes behind greening (or browning) trends

* ✓ The physiological mechanisms behind landscape or individual scale response to climate change are largely unknown
It is therefore urgently necessary to combine
different approaches:

✓ To fully capture landscape trajectories in time and space

✓ To reveal the actual drivers of vegetation change

✓ To predict the ecosystem response to one of the most
significant environmental changes of the last millennia (or
millions of years?): the anthropogenic climate change
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Thank you!

Christophe Corona
Thierry Améglio
Guillaume Charrier
Katline Charra-Vaskou
Philippe Choler
Arthur Bayle
Baptiste Nicoud
Markus Stoffel
Eike Albrecht
Jörg Löffler

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