Under a scenario of increased climate change, this study models the climate resilience of beech and spruce forests across Europe. It finds that: 1) natural disturbances like fires, winds and drought are expected to increase, especially in areas projected to lose forest cover; 2) spruce seed production will decline across its range, and even more sharply in areas of projected loss; and 3) areas of projected loss show higher current genetic fragmentation, consistent with expectations of lower adaptation potential. However, impacts are strongly dependent on location. Higher resolution modeling is needed to better understand changes in establishment, growth and spatial patterns.

1. The European Commission’s
science and knowledge service
Joint Research Centre
Macroscale analysis of
climate resilience of beech
and spruce in Europe
Peter Vogt, Giorgio Vacchiano, Davide
Ascoli, Andy Hacket Pain

2. 2
Resilience
Resilience describes the capacity of ecological systems
to maintain a “stable state” despite disturbances,
environmental changes and internal fluctuations

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EU forests provide key ecosystem services that depend on
the resilience of composition, structure and processes:
- Wood and energy biomass
- Non wood forest products
- Nutrient recycling
- Biodiversity and habitat
- Recreation
- Hydrologic protection
European forests in a changing climate

4. 4
European forests in a changing climate
Climate change effects are not homogenous across the
geographical and species space (e.g., temperature vs
water-limited systems).
Planning mitigation, adaptation, and forest management
at the EU scale requires spatially explicit assessment
of climate resilience.

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Problems with current tools:
Process-based models: lack EU-wide parameterization
and validation of life traits parameters
Empirical models (e.g., tree ring width as a function of
climate): cannot be extrapolated beyond their
geographical domain of application; poor at detecting
indirect and interaction effects
Species distribution models (presence-absence): do
not discriminate between impacts of climate change on
different life stages

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Aim:
Model spatially-explicit climate resilience of reproduction,
establishment, growth, and mortality with independent,
recent wall-to-wall datasets on EU forests and climate.
Spruce (Picea abies) Beech (Fagus sylvatica)
European Atlas of Forest Tree Species 2016,
1998-2008 species distribution at 1km

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Resilience metrics
 Reproduction: seed production model,
climate-dependent, calibrated on EU seed
production database (Ascoli et al. 2017, NUTS1)
 Establishment: process-based model pNet-II
(Aber and Ollinger 1995), run on soil database
of Europe and climate layers
 Growth: NPP model, climate and soil
dependent, calibrated on 2000-2012 NPP at 1
km resolution (Neumann et al. 2015)
 Mortality (Disturbance): fire weather index,
daily maximum windspeed, Standardized
Precipitation and Evaporation Index in the
growing season (April-September)

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Seed production model
 MASTREE: ordinal index of seed production (NUTS-1)
 Modeled after seasonal temperature and precipitation
over last 3 years, and seed production of previous year
 Beta regression run on 1950-2014 data
 Only significant predictors retained
Low
Beech seed prod.
High

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Methods
• Resilience metrics: climate-dependent, daily resolution
• Difference between response variable fitted in 2080-
2100 (CanESM2, 2.5°, RCP 8.5) and 1980-2000 (ERA-
Interim Re-analysis, 0.25°)
• Aggregated to whole period (90th percentile)
• Constrained on current species distribution (Probability
>50%), i.e., no species migration considered

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Spatial pattern predictors
Genetic diversity: Contagion Index
(less fragmented -> more diverse)
Dispersal potential: Connectivity
(core, bridge, corridor =1, vs. branch,
edge, islet =0), More connected ->
gene flow is more likely to happen.
Hypothesis: current spatial pattern may affect the ability to
adapt to climate change and is analyzed via:

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Spruce (Picea abies) Beech (Fagus sylvatica)
Isolated Connected
Contagion
Connectivity
Spatial pattern
(current)

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Results: Disturbance hazard 2080-2100
0 30 0 +50 7 kphFire Weather Index Windspeed Drought growing season

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Results: Seed production 2080-2100
Spruce (Picea abies) Beech (Fagus sylvatica)
Ordinal index
1 5
High seed production following sequence of
one cool summer and one hot summer
before the seed year (more likely in continental climate)

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Results: Species probability change
(loss, gain, persistence)
Spruce
(Picea abies)
Beech
(Fagus sylvatica)
Difference between 2080-2100 and current
using SDM from Casalegno et al. 2010

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loss persistence loss persistence loss persistence
Drought change Wind change Fire danger change
Resilience (2080-2100 minus 1980-2000)
340 pixels randomly sampled in area common to both species
Coherence between SDM change and resilience metrics change
Spruce (Picea abies)
Disturbance hazard:
- Increasing in the future
- Constant change on average
- More extreme change in “loss” pixels

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Resilience (2080-2100 minus 1980-2000)
340 pixels randomly sampled in area common to both species
Coherence between SDM change and resilience metrics change
Spruce (Picea abies)
loss persistence loss persistence loss persistence
Seed change
Genetic fragmentation higher in “loss”
Seed production always declining, but more in “loss”

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Summary
Under scenario RCP8.5 (+8.5 W/m2, +3.7° by 2100):
• Increase in natural disturbances (fire, wind, drought)
• More extreme changes in “loss” pixels
• Declining seed production in spruce, even more within “loss”
• Higher genetic fragmentation in “loss”, consistent with hypotheses
• But these vary strongly geographically!

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Discussion
 Coarse resolution (180km, to be re-analyzed at 1km)
 Distributions sampled in non-sensitive Central Europe
 Establishment and growth still missing
 Refinement of spatial metrics, e.g. including distance
between elements
Resilience to climate change is highly complex:
in space, time, and across process space.
Spatially-explicit assessment at 1km will provide more
detailed answers.