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1 REPORT OF THE MID-TERM WORKSHOP COMPONENT 1 FFEM FFEM PROJECT "MAXIMIZE THE PRODUCTION OF GOODS AND SERVICES OF MEDITERRANEAN FOREST ECOSYSTEMS IN THE CONTEXT OF GLOBAL CHANGES" COMPONENT 1 "PRODUCTION OF DATA AND DEVELOPMENT OF TOOLS TO SUPPORT DECISION AND MANAGEMENT OF VULNERABLE MEDITERRANEAN FOREST ECOSYSTEMS AFFECTED BY CLIMATE CHANGE AND THE ABILITY OF THESE FOREST ECOSYSTEMS TO ADAPT TO GLOBAL CHANGE" Tunis, Tunisia 2-5 June 2014

REPORT OF THE MID-TERM WORKSHOP COMPONENT 1 FFEM … · LoA: Letter of Agreement (MOU) MENA: ... DGF Tunisia Youssef Saadani [email protected] GIZ Tunisia Abdelmajid Jemaï [email protected]

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Page 1: REPORT OF THE MID-TERM WORKSHOP COMPONENT 1 FFEM … · LoA: Letter of Agreement (MOU) MENA: ... DGF Tunisia Youssef Saadani ysaadani04@yahoo.fr GIZ Tunisia Abdelmajid Jemaï abdelmajid.jemai@giz.de

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REPORT OF THE MID-TERM WORKSHOP

COMPONENT 1 FFEM

FFEM PROJECT "MAXIMIZE THE PRODUCTION OF GOODS AND SERVICES OF

MEDITERRANEAN FOREST ECOSYSTEMS

IN THE CONTEXT OF GLOBAL CHANGES"

COMPONENT 1 "PRODUCTION OF DATA AND DEVELOPMENT OF TOOLS TO

SUPPORT DECISION AND MANAGEMENT OF VULNERABLE MEDITERRANEAN

FOREST ECOSYSTEMS AFFECTED BY CLIMATE CHANGE AND THE ABILITY OF

THESE FOREST ECOSYSTEMS TO ADAPT TO GLOBAL CHANGE"

Tunis, Tunisia

2-5 June 2014

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This report was drafted by Sophie Valley (AIFM) under the LoA of 26.04.2013 signed between AIFM

and FAO. It was then validated by team of FAO (V. Garavaglia and C. Besacier).

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Table of contents

ACRONYMS .............................................................................................................................................. 4

PURPOSE AND AGENDA OF THE WORKSHOP IN TUNIS .......................................................................... 5

SESSION1: FIRST RESULTS AND WORKPLAN 2014 .................................................................................. 8

PILOT SITE OF SENALBA (ALGERIA) .......................................................................................................... 8

PILOT SITE OF JABAL MOUSSA (LEBANON) ........................................................................................... 11

PILOT SITE OF MAÂMORA (MOROCCO) ................................................................................................ 15

PILOT SITE OF SILIANA (TUNISIA) .......................................................................................................... 17

PILOT SITE OF DÜZLERÇAMI (TURKEY) .................................................................................................. 20

SESSION 2: STATE OF THE ART OF CLIMATE CHANGE IMPACTS ON MEDITERRANEAN FOREST SPECIES

IN THE PILOT SITES OF COMPONENT 1 ................................................................................................. 24

SESSION 3: STATE OF THE ART ON STUDIES/RESEARCH FOR THE ADAPTATION AND MITIGATION OF

CLIMATE CHANGE IN MEDITERRANEAN FOREST ECOSYSTEMS: FIRST RESULTS AND WORKPLAN 2014

......................................................................................................... ERROR! BOOKMARK NOT DEFINED.

SESSION 4: COMMON DAY C1/C2 ......................................................................................................... 30

PRESENTATION OF RESULTS OF THE FIRST CAPACITY BUILDING WORKSHOP FOR ORGANIZED IN

COLLABORATION WITH VITO ................................................................................................................ 35

PRESENTATION OF GIZ ACTIVITIES ON THE VULNERABILITY ASSESSMENT OF ECOSYSTEMS IN TUNISIA

............................................................................................................................................................... 37

SESSION 5: SUMMARY OF EXCHANGES IN EACH PILOT SITE TO IDENTIFY NEXT STEPS AND OVERCOME

DIFFICULTIES TO FINALIZE THE VULNERABILITY ANALYSIS BY THE END OF 2014 .... ERROR! BOOKMARK

NOT DEFINED.

ANNEXE 1: AGENDA OF THE WORKSHOP IN TUNIS .............................................................................. 42

ANNEXE 2: METHODOLOGY "IMPACTS OF CLIMATE CHANGE ON THE DISTRIBUTION OF NATIVE TREE

SPECIES IN LEBANON: POTENTIAL PROJECTIONS BY 2050" .................................................................. 43

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Acronyms

ADMJ: Development Association Menzel Jemil (Tunisia)

AIFM: International Association for Mediterranean Forests

ASIS: Agricultural Stress Index System (Water Stress Indicator)

APJM: Association for the Protection of Jabal Moussa (Lebanon)

CTS: Center of Space Techniques (Algeria)

DGF: General Directorate of Forests

FAO: Food and Agriculture Organization of the United Nations

FFEM: French Global Environment Facility

GBIF: Global Biodiversity Information Facility

IPCC: Intergovernmental Panel on Climate Change

GIZ: Deutsche Gesellschaft für Internationale Zusammenarbeit (German Technical Cooperation)

IFN: National Forest Inventory

INRA: National Institute for Agricultural Research

LoA: Letter of Agreement (MOU)

MENA: Middle-East and North-Africa

MoA: Ministry of Agriculture (Ministry of Agriculture of Lebanon)

NDVI: Normalized Difference Vegetation Index

CPMF: Collaborative Partnership on Mediterranean Forests

UNDP - United Nations Development Programme

PSI: Seasonality Precipitation Index (seasonal rainfall)

FGR: Forest Genetic Resources

GIS: Geographic Information System

SPI: Standardized Precipitation Index (standardized precipitation index)

EU: European Union

VITO: Vision on Technology

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Purpose and agenda of the workshop in Tunis Valentina Garavaglia (FAO - Silva Mediterranea)

I) PARTICIPANTS LIST

Country Participants Institution Contact

Algeria Wissam Toubal thematic referent [email protected]

Gacemi Mohamed El Amine national expert [email protected]

Lebanon

Maya Mohanna thematic referent [email protected] [email protected]

Miguel Ángel Navarrete Poyatos national expert [email protected]

Salim Roukoz national expert [email protected]

Chadi Mohanna focal point [email protected]

Morocco

Mustapha Bengueddour thematic referent [email protected]

Bakhiyi Belghazi national expert [email protected]

Fouad Mounir national expert [email protected]

Fayçal Benchekroun focal point [email protected]

Tunisia

Ameur Mokhtar thematic referent [email protected]

Kamel Tounsi national expert [email protected]

Ali Aloui national expert [email protected]

Saleh El Mensi focal point [email protected]

Turkey

Sükran Gökdemir thematic referent [email protected]

Murat Turkes national expert [email protected]

Nebiye Musaoglu national expert [email protected]

Ayse Ayata Kelten focal point [email protected] [email protected]

DGF Tunisia Youssef Saadani [email protected]

GIZ Tunisia Abdelmajid Jemaï [email protected]

INRA Nadine Wazen [email protected]

AIFM Sophie Vallée [email protected]

FAO Christophe Besacier [email protected]

Valentina Garavaglia [email protected]

II) SUMMARY OF THE FFEM PROJECT

The overall objective of the FFEM project is to encourage stakeholders to manage and restore

Mediterranean forests in order to ensure a sustainable supply of goods and services through those

ecosystems.

The project focuses on five major components that meet five key objectives:

Include climate change impacts in forest policy by providing information and technical tools

related to vulnerability and adaptive capacity of Mediterranean forests component 1

Assess the economic and social value of goods and services provided by Mediterranean

forest ecosystems to support decision and promote integration among sectoral policies

component 2

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Improve participative governance approaches at territorial scale through stakeholder

participation in the development and implementation of strategies to reduce human

pressures on ecosystems, while ensuring users that the goods and services on which they

depend can be maintained over the long term component 3

Maximize and valorise the mitigation potential of Mediterranean forests (carbon sinks)

through the development of methodological tools to value local efforts of protection and

restoration of ecosystems component 4

Strengthen coordination and exchanges of experiences among stakeholders in the region

(coordination and communication through the CPMF) by opening a dialogue on common

guidelines for adaptation and mitigation of climate change in the forestry sector in the

Mediterranean component 5

Each component occurs in three stages to provide concrete answers to forest managers, based on

pilot sites, while providing a strategic and political vision.

Step 1: capitalization of existing data and studies and production of a synthesis;

Step 2: focus on some pilot sites and implementation of activities in the five countries;

Step 3: exchanges at the regional level and communication at the international level.

Pilot site for country

Component 1 Component 2 Component 3 Component 4

Algeria Djelfa/Senalba Chrea Chrea Djelfa/Senalba

Lebanon Jabal Moussa Jabal Moussa Jabal Moussa Tout le pays

Morocco Maâmora Maâmora Maâmora Maâmora

Tunisia Siliana - Barbara Barbara and Siliana

Turkey Düzlerçami Düzlerçami Düzlerçami Düzlerçami

III) PRESENTATION OF ACTIVITIES PLANNED FOR COMPONENT 1 AND MAIN OBJECTIVES

OF THE WORKSHOP OF TUNIS

Regarding Component 1 "Production of data and development of tools to support decision and

management of vulnerable Mediterranean forest ecosystems affected by climate change and

the ability of these forest ecosystems to adapt to global change" the 5 priority actions include:

Literature review and synthesis on the impacts of climate change on Mediterranean forest

ecosystems and key genetic resources;

Review and synthesis on activities implemented to adapt Mediterranean forests to

climate change in the region;

Analysis of vulnerability and adaptation capacities of Mediterranean forest ecosystems

to climate change impacts in five pilot sites;

Capitalization of outcomes and elaboration of tools to support decision in terms of

adaptation to climate change for forest managers and policy makers;

Exchanges of experiences between countries, including countries involved in the project

ForClimAdapt, through a regional workshop.

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Regarding the vulnerability analysis of Mediterranean forest ecosystems to the impacts of climate

change on five pilot sites the stages are the following:

workshop to define and adopt a common methodology (Solsona, Spain, May 2013);

work of INRA: "ecological niche" approach (regional mapping of current limits range of

repartition and modelling of future areas of repartition of the main species present in the

selected pilot sites of the FFEM project);

workshop for training national experts on "multifactorial spatial analysis approach of

ecosystems vulnerability on pilot sites selected by Component 1 for climate change" in

cooperation with GIZ Tunisia (Tunis, Tunisia, 21-25 April 2014);

workshop for training national experts on "Cartographic material on the evolution of

forest cover, land use and climatic conditions of the pilot sites" in cooperation with VITO

(Mol, Belgium, 19-23 May 2014);

workshop for training national experts on "Cartographic material on the evolution of

forest cover, land use and climatic conditions of the pilot sites" in cooperation with VITO

(Rabat, Morocco, 22-26 September 2014);

final restitution workshop of Component 1 (Antalya, Turkey - late 2014)

Vulnerability maps of ecosystems (multifactorial spatial analysis - GIZ methodology)

+ Maps of forest cover change (and other wooded land - link to C4)

+ Evolution of climatic conditions at the level of pilot sites (temperature, precipitation,

Emberger coefficient)

+ Knowledge of the pilot site by national experts

Quantification of changes in forest cover

Estimation of changes in temperature and rainfall

How changing climatic conditions influence forest ecosystems of the pilot sites?

Anthropogenic pressures?

Possible future developments (IPCC scenarios)

The objectives of the regional mid-term workshop are:

Check the progress of vulnerability assessment to climate change in the pilot sites

Discuss the next steps and the agenda 2014

Promote collaborations with Component 2

Solve any issues/concerns and find solutions

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SESSION 1: FIRST RESULTS AND WORKPLAN 2014

Pilot Site of Senalba (Algeria) Gacemi El Amine

Notes on the site:

Location Wilaya of Djelfa - 300 km south of Algiers

Surface 62,172 ha of which 27,820 ha forested

Population on the site 49,000 inhabitants, with 20,000 users of woodlands

Bioclimatic stage semi-arid with cold fresh variant

Ecosystems origin yeuseraie dominant associated with juniperus oxycèdre

Ecosystems currently present

pure forest of Pinus Halepensis

mixed forest of Pinus Halepensis, Quercus Ilex and Juniperus

scrubland with Rosmarinus officinalis

ala steppes

Evaluation of goods and services:

- Benefits for direct use (socio-economic activities)

Wood products (timber, firewood)

Charcoal

Aromatic and medicinal plants

Tannins, pine resin

Hunting activities

Silvopastoralism

- Benefits for indirect use Recreational space

Protection against desertification

Carbon sequestration

Fight against erosion

Regulating water flow (protection against flooding)

Pressures from human activities

Overgrazing

Repeated fires

Crime cuts

Owner (s) of woodlands State (national forest estate)

Manager (s) of woodlands DGF (Directorate General of Forests)

Current forest management Management plans (lasting 20 years) since 1984:

Operation of 25,000 m3 / year throughout the period

Reconstruction of 19 859 ha of degraded areas

Reforestation after harvesting at a rate of 600 ha / year

Planning forest trails: 93 km

Opening tracks: 130 km

Forestry work for the improvement of young stands

Works pastoral improve conditions for residents

Past forest management

Health of forests Aging tendency of forests (Avg. Age = 105, 80% of the stands were over 100 years)

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health problem: bark beetle attack (cleaning process from 1989 to 1992)

Steps implemented since the workshop of Solsona (May 2013) to define a methodology for a vulnerability analysis of Mediterranean forest ecosystems in the pilot sites

Selection of national experts Gacemi Mohamed El-Amine (Centre of Space Techniques - CTS)

Signatures of MoUs/ agreements with FAO

No contract signed with the local structure. Expenses incurred directly by the Permanent Representative of FAO in Algiers (Field Budget Authorization)

Others Coordination meeting at the DGF for the launch of the project (C1 and C4). Support mission on the pilot site of Senalba along with experts (FAO and ONFI). Review and discussion of the methodological guide for component 1 (Part I) with the FAO expert on data availability and existing inventories. Adoption of the terms of reference related to health aspects of forests and recruitment of a consultant to support the management of this component within the CTFC

First data collection for analysis of vulnerability to climate change:

Physiographic and forest data

Map of site limit and forest/non-forest limit Paper charts of the forest Inventory of 1984 (to be digitized) Maps of land cover (1987, 2001, 2011) Map of forest types Map of aging Map of soil depth, soil texture map Geological map Maps of altitudes, slopes, drainage networks, exhibitions Map of Fires Map of desertification sensitivity (CTS, 2010) Forest Inventory 2008

Meteorological data Rainfall, temperature (AGRI4CAST) T min, T max, HR, P, etc. (Tutiempo.net)

Demographic and socio-economic data

Population density, livestock

Satellite images Google, Microsoft Bing (good resolution)

First results, if available Change of the Pluviometric Quotient of Emberger since 1975 and overlaid on Emberger's Statistical Graphs -> Since 1975 the region of Djelfa experienced 3 bioclimatic stages

Training in collaboration with GIZ Tunisia on "Multifactorial space approach for the analysis of vulnerability of ecosystems of Component 1 pilot sites to face climate change" (21-25 April 2014):

Applicability in the pilot site Yes technically

Problems Parameters, coefficients and weights used in this approach change from one area to another, and require the opinion of several experts every time

The factors used are not the same (no fire, but strong trend towards desertification)

Possible Solutions Tool for calculating vulnerability dynamically and automatically

Training in collaboration with VITO about "Cartographic material on the evolution of forest cover, land use and climatic conditions of the pilot sites" (19-23 May 2014)

Applicability in the pilot site Yes

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Landsat images downloaded for free

1975, 1987, 1990, 2000, 2001, 2002, 2005, 2006, 2010, 2011, 2013, 2014

Reference data available Forest inventory maps 1984

Problems Use of the software Spirit

Possible Solutions Additional training on the software Spirit or tutorial

Next steps 1 - Formatting data collected and their standardization following the multifactor spatial analysis approach of the ecosystems vulnerability of GIZ 2 - A field mission for:

studying some vulnerability factors with forestry experts on the pilot site

updated maps of forest inventory 3 - Application of the multifactor spatial analysis approach with the available data 4 - Analysis of Landsat data downloaded 5 - Formatting downloaded weather data 6- Production of documents on the evolution of forest cover, land use and climate

Budgetary constraints/ budget situation

The budget was approved by both parties. No constraints at this stage for the implementation via FAO Algiers

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Pilote site of Jabal Moussa (Lebanon) Miguel Ángel Navarrete Poyatos

Notes on the site

Location

Qadaa of Keserwan, 45 km north-east of Beirut western side of Mount

Lebanon

Altitude 750 -1 250 m

Surface 6500 ha including 1250 ha of woodland

Population on the site About 15 000 inhabitants, with 1 500 users of woodlands

Notes on the site Biosphere Reserve (UNESCO)

Bioclimatic stage Sub-humid and humid for lower areas (Thermo-and Eu-

Mediterranean)

Humid temperate in medium altitude areas (Supra-Mediterranean)

Per-humid fresh at the highest peaks (Montagnard or

Mediterranean-mountain)

Geology/Soil science Calcareous soils

Ecosystems origin Forest series, from low to high altitude: Quercus calliprinos,

Quercus infectoria, Platanus orientalis, Quercus cerris, Ostrya

carpinifolia and Fraxinus ornus

High scrubland Calicotome and Spartium

Lawns

Ecosystems currently

present

Species present Presence of rare and / or endemic species: Asperula libanotica, Cyclamen

libanoticum, Origanum libanoticum, Pentapera sicula var. libanotica, Malus

tribolata, Acer tauricolum

Evaluation of goods and

services:

- Benefits for direct use

(socio-economic activities)

Wood products (timber, firewood)

Charcoal

Agroforestry (fruits)

Aromatic and medicinal plants

Silvopastoralism

tourist activities (ecotourism, hiking)

Nursery seedling producing local

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- Benefits for indirect use Recreational space

Landscape, cultural and historical

Pressures from human

activities

Extraction of material (rocks, sand)

Construction/urban/infrastructure

Overgrazing (related to the number of animal data)

Coal (currently regulated by the Ministry of Agriculture through

permits coal)

Significant tourist traffic in the summer

Fires

Owner (s) of woodlands Macha'a (commons)

Religious WAAF

Family WAAF (Zouaine)

Private owners

Bank of Lebanon

Manager (s) of woodlands Municipalities

Religious institutions

Private owners

Association for the Protection of Jabal Moussa (APJM)

Health of forests Mistletoe on juniper trees

Steps implemented since the workshop of Solsona (May 2013) to define a methodology for a vulnerability analysis of Mediterranean forest ecosystems in the pilot sites

Selection of national experts

2 experts recruited: Miguel Ángel Navarrete Poyatos as a national expert

and Salim Roukoz as a support for GIS

Signatures of MoUs/ agreements with FAO

LoA signed between FAO and APJM (Association for the Protection of

Jabal Moussa). Contracts signed between the Ministry of Agriculture of

Lebanon and APJM

Others Regular meetings between APJM, MoA and the experts

First data collection for analysis of vulnerability to climate change:

Physiographic and forest data

Forest Inventory (random sampling, stratified - 2012) Map of models of forest fuels Land use maps (LULC - 2002, 2005) Geological map, map of soil types, soil depth map Maps of altitudes, slopes, drainage networks, exhibitions Map for risk of erosion and landslides

Meteorological data 2011-2014 monthly data series: solar radiation, wind direction (degrees), precipitation, wind speed, leaf wetness, air temperature, relative humidity, dew point, soil temperature, air pressure, reference evapotranspiration

First results, if available Delimitation of population, crossing layers of slope, aspect, type and soil depth and altitudinal range (threshold of 1000 m)

Evapotranspiration, available water capacity

State of health of populations obtained through remote sensing techniques

Potentiality species to current and future climate conditions

Map of fire risk potential by combining forest slope and fuel

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type

Training in collaboration with GIZ Tunisia on "Multifactorial space approach for the analysis of vulnerability of ecosystems of Component 1 pilot sites to face climate change" (21-25 April 2014):

Applicability in the pilot site Yes for some factors, but not for others

Problems Problems for some risk factors

Possible Solutions Biophysical factors: No change

Water stress: No data on vegetation stress => Change to the

potential of species to climatic factors

Ageing: No data on the age of trees => Change to the health of

forests

Grazing pressure: No data of pastoral inventory, impossible to

estimate forage units => Ignore this factor (factor interrelation

with forest fires)

Risk of forest fires: No change

Training in collaboration with VITO about "Cartographic material on the evolution of forest cover,

land use and climatic conditions of the pilot sites" (19-23 May 2014)

Applicability in the pilot site Partially.

Quotient Emberger and water stress indicator (ASIS) will be calculated.

Impossible to work with the data MARS available

Landsat images downloaded for free

10-15 images of 1990, 2000 and 2010.

Work for GIS and estimation of the Normalized Difference Vegetation

Index (NDVI) in progress

Reference data available Points of presence by species (vector files) to form the model.

Classification of vegetation in progress

Problems Impossible to work with the set of proposed climate data (March) due to

its spatial resolution (25x25 km). A pixel is larger than the entire

Biosphere Reserve of Jabal Moussa.

Possible Solutions Modelling with BIOMOD2 (see note below and Appendix 2)

Next steps 1. Development of a synthetic factor of vulnerability according to

multivariate spatial modelling

2. Classification of vegetation by Remote Sensing

3. Calculate quotient Emberger and water stress indicator (ASIS).

Analysis of the evolution of the NDVI

4. Preparation of final results

Budgetary constraints/ budget situation

First transfer received. Waiting for the second transfer. Budget lines met.

Uncertainties regarding the cost of data to be collected, it will be

quantified in the following months.

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Modelling with BIOMOD2 (Thuiller et al., 2013), an additional package used in the statistical software

R, allows the modelling of current and future potential distribution of species. The modelling requires

two types of data: climatic variables (past and current) and points of presence/absence of the

species. The idea is to identify the areas with favourable conditions for the presence of a species.

In the case of Lebanon, climate data were issued from WorldClim (resolution 1 km²). The selected

scenarios of climate change are those of the IPCC: A2 (pessimistic) and B1 (optimistic). The horizon

predicted is 2050. Collinearity analysis was performed in order to eliminate redundant variables (with

a strong correlation). Three non-collinear variables were selected: winter minimum temperatures,

summer maximum temperatures and summer precipitation.

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Pilot site of Maa mora (Morocco) Fouad Mounir and Belghazi Bakhiyi

Note on the site:

Location East of Rabat and Kenitra, the western part is 10 km from the ocean

Altitude 7 m West and 290 m to the East

Surface 132,000 ha of which 126,200 ha of woodland

Population on the site approximately 341 360 hab. including 173,500 users of woodlands

Notes on the site largest cork oak lowland in the world

Bioclimatic stage subhumid in the Western part

semi-arid in Central and Eastern

Geology/Soil science sandy soils called "beige" soil (Quaternary dunes on Miocene marl)

Ecosystems origin cork oak (Quercus suber) in the Maamora Poirier (Pirus mamorensis)

Ecosystems currently present

Quercus suber in the Maamora Poirier (Pirus mamorensis)

plantations of non-native species (eucalyptus, various

pines, acacia)

Species In addition to those mentioned before: Pistacia lentiscus, Pistacia

Atlantica, Olea europea ssp. Oleaster, Phillyrea latifolia, Teline

linifolia, Halimium halimifolium, Cistus salviifolius, Lavandula

stoechas, aAphodelus microcarpus, Chamearops humilis, Rhus

penthaphyllum, etc.

Evaluation of goods and

services:

- Benefits for direct use

(socio-economic activities)

Wood products (lumber, industrial wood, firewood)

Cork

Aromatic and medicinal plants

Mushroom picking

Various pickings: snails, acorns, asparagus

Beekeeping

Silvopastoralism

Forage production

Ecotourism

- Benefits for indirect use Recreational space

Reservoir of biodiversity

Protection of groundwater

Pressures from human

activities

Overgrazing (4 times the capacity)

Excessive timber extraction (3 times the potential)

Topping and limbing

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Iillegal practices (illegal logging, crimes, illegal trimming illegal

Gathering acorns

Urbanization (pressure on space forest)

Fire

Owner (s) of woodlands State (national forest estate)

Manager (s) of woodlands State and population (organized)

Current forest management Regeneration, restoration and protection of the cork oak

Improved governance of forest areas

Extension of the principle of multifunctionality of forests

Past forest management Rescue Plan Maâmora (1918 - 1950)

Vidal Development (1951-1972)

Danish Development (1973-1992)

Development coordinated with FAO (1992-2011)

Health of forests Problem of decline of cork oak (aging, occurrence of drought,

pathogens: Hypoxylon mediterraneum, Lymanthria dispar)

Phoracantha semipuncta: mushroom eucalyptus

Steps implemented since the workshop Solsona (May 2013) to define a methodology for vulnerability analysis of Mediterranean forest ecosystems in the pilot sites

Selection of national experts 2 experts recruited: Bakhiyi Belghazi and Fouad Mounir

Signatures of MoUs/ agreements with FAO

Agreement signed with a local structure

First data collection for analysis of vulnerability to climate change:

Physiographic and forest data

General forest data, data on forest fires

History of forest management, forest crimes

General physiographic data with clay floor, deep sand, slope map

Demographic and socio-

economic data

Total population, households, population users, livestock

Identification of socio-economic sectors

Data on cork harvesting

First results, if available Assessment of available soil resources, water deficit

Analysis of the dynamics of Maamora forest (1990-2010)

Assessment of acorns seedling and plantations of cork oak

Training in collaboration with GIZ Tunisia on "Multifactorial space approach for the analysis of

vulnerability of ecosystems of Component 1 pilot sites to face climate change" (21-25 April 2014):

Applicability in the pilot site Yes

Training in collaboration with VITO about "Cartographic material on the evolution of forest cover,

land use and climatic conditions of the pilot sites" (19-23 May 2014)

Applicability in the pilot site Yes

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Pilot site of Siliana (Tunisia) Kamel Tounsi and Ali Aloui

Note on the site:

Location Siliana region, about 120 km southwest of Tunis

Surface 91 000 ha of which 23 500 ha forest areas

Population on the site Around 11 600 hab., 8 300 forest users

Bioclimatic stage Semiarid

Ecosystems origin Aleppo pine forest

Ecosystems currently present

Summit: Montpellier maple

Mid-slope: low and dense scrub of Aleppo

Pine and green oak

Low slope: garrigue with oleaster, mastic, rosemary,

Cistus

Evaluation of goods and services: Economic evaluation of goods and services of Tunisian forests

(Daly et al., 2012)

- Benefits for direct use

(socio-economic activities)

Wood products (wood work, wood industry , firewood)

Aromatic and medicinal plants , extraction of essential

oils

Collection of mushrooms

Various crops: snails, acorns, asparagus, Aleppo pine

cones, pods, etc.

Beekeeping

Forage production

Hunting activities

- Benefits for indirect use Recreational space

Biodiversity reserve

Reduction of sedimentation in the dam

Carbon sequestration

Protection against erosion

Pressures from human activities Grazing (pastoral overload)

Anthropic pressure (many crops, woody and non-

woody)

Owner (s) of woodlands State and local communities (communal lands)

Manager (s) of woodlands State (DGF) and user population

Current forest management Conservation, protection and regeneration of mountain

maples

Preserving, protecting and management of oaks for

the production of acorns and wood

Introduction of animal species that used to populate

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the mountains, like the Barbary sheep and Cuvier's

gazelle

Environmental education for school

Structure and organization of the population through a

participatory approach, in view of improving their

quality of life through the development and the

development and implementation of development

plans

Steps implemented since the workshop Solsona (May 2013) to define a methodology for a vulnerability analysis of Mediterranean forest ecosystems in the pilot sites

Selection of national experts 2 experts recruited: Ali Aloui and Kamel Tounsi

Signatures of MoUs/ agreements with FAO

MoU signed between FAO and Development Association

Menzel Jemil (ADMJ)

First data collection for analysis of vulnerability to climate change:

Physiographic and forest data Pastoral and forest inventories 1995 and 2005

Thematic maps: soil science, slopes, exhibitions

Map of the sectors (administrative division)

Map of bioclimatic zones

Thematic map of altitudes classified by classes 100 m

Fire Statistics 1985-2014

Phyto-ecological map of Northern Tunisia – scanned

(C. Floret, J.L. Guillerm, E. Le Floch and A. SRouler–

1966).

Meteorological data Climatic data: rainfall, temperatures for Siliana, Kef, Jendouba,

Beja, Sidi Bouzid,

Demographic and socio-economic

data

Data from 2004 and earlier populations + projection

2034

Agricultural Statistics 1995 and 2005 (livestock) and

projection by OEP

Satellite images Google Earth

First results, if available 1. result: the choice of spatial reference unit: the

administrative sector (beyond the watershed)

2. result: methodological choice: Multifactor spatial

approach

3. result: preparing the cartographic database:

screenwriting, geo-referencing, scanning, decoding

existing maps, initial geospatial analysis

4. result: monitoring forest degradation through the

characterization and comparison of the cover land

Training in collaboration with GIZ Tunisia on "Multifactorial space approach for the analysis of

vulnerability of ecosystems of Component 1 pilot sites to face climate change" (21-25 April 2014):

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Applicability in the pilot site Yes

Training in collaboration with VITO about "Cartographic material on the evolution of forest cover,

land use and climatic conditions of the pilot sites" (19-23 May 2014)

Applicability in the pilot site Yes

Next steps 1. Defining the matrix of factors explaining the vulnerability of

forests for each of the 41 sectors

2 Determine the factor and synthetic vulnerabilities:

thresholding, weighting, etc.

3. Projecting levels of vulnerability to time horizons selected in

the models of the last IPCC report

4. Identify changes in forests and quantify the gains and losses

surfaces since 1966 (last available date)

Budgetary constraints/ budget situation

Financing of the second training module organized by VITO in

Morocco

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Pilot Site of Du zlerçami (Turkey) Nebiye Musaoğlu and Murat Turkes

Note on the site

Location Antalya province, 10 km North of Antalya

Altitude 70-1 550 m

Surface 29 168 ha of which 17 703 ha of woodland

Population on the site About 28 000 inhabitants

Bioclimatic stage Subhumid to semi-arid (depending on altitude)

Geology/Soil science Calcareous soils

Ecosystems origin Pinus brutia

Sclerophyllous evergreen bush

Ecosystems currently present Pinus Brutia

Sclerophyllous evergreen bush

Deciduous-coniferous mixed forests

Juniperus excelsa

Species Pinus brutia

Cedrus libani

Juniperus exelca

Pinus pinea

Cupressus sempervirens

Pinus halepensis

Quercus ithaburensis subsp. macrocarpa

Quercus infectoria subsp. boissieri

Platanus orientalis

Eucalyptus spp.

There are also many endemic and/or rare species of

flora and fauna Pholomis lycia (flowering plant),

Pseudophoxinus antalyae (fish)

Evaluation of goods and services:

- Benefits for direct use

(socio-economic activities)

Wood products (lumber, industrial wood,

fuelwood)

Agroforestry (olive, pomegranate, lemon trees,

etc.).

Aromatic and medicinal plants

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Mushroom picking

Beekeeping

Farming, silvopastoralism

Hunting activities

Tourism

- Benefits for indirect use Recreational space

Reservoir of biodiversity

Protection of groundwater

Study area for forest research

Presence of numerous archaeological sites

Pressures from human activities Grazing (overgrazing)

Limestone quarries

Fires

Urbanization (pressure on forested areas)

Criminal hunting (outside authorized periods

for example)

Owner (s) of woodlands State (Directorate General of Forests) mainly, but also

some forests subject to easements (rights to use the

local population)

Manager (s) of woodlands State (Directorate General of Forests)

Current forest management Development Plan 2012-2021

Health of forests Significant presence of the Pine processionary

(Thaumetopea pityocampa)

Steps implemented since the workshop Solsona (May 2013) to define a methodology for a

vulnerability analysis of Mediterranean forest ecosystems in the pilot sites

Selection of national experts 2 experts recruited: Murat Türkeş and Nebiye

Musaoğlu

Signatures of MoUs/ agreements with FAO No contract with a local structure or FAO

Representation in Ankara (Field Budget Authorization).

Expenses incurred directly by FAO Representation in

Ankara.

First data collection for analysis of vulnerability to climate change:

Physiographic and forest data Area of the pilot site

Administrative categories and land use rights

Management Units, including: improvement

areas wildlife, protected areas, protected

archaeological areas, etc.

Biophysical data topographic maps 1/25 000

map elevations, slope map and map of the

river networks

Land use maps (Corine - 1990 and 2006)

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Ownership

Forest stands (maps of 1997 and 2012)

Data on forest fire 1997

Maps of high-voltage lines (1997 and 2012)

Map of soil types

Meteorological data Monthly climate and weather data

Demographic and socio-economic data Location of mining activities

Grazing plans

First results, if available First results of the statistical analysis, climate and time

series:

Monthly climatological and meteorological data

Quotient pluviothermic Emberger or aridity

index Q (E)

Precipitation Seasonality Index (PSI) and inter-

annual variability of rainfall and quotient of

Emberger (in %)

Geographical distribution of the quotient

Emberger and its inter-annual variability in the

region (including the Forest District

Duzlercami)

Time series analysis of the Precipitation

Seasonality Index (PSI) and Quotient of

Emberger Q (E):

a/ Climate variations and long-term trends in annual and

seasonal PSI and Q (E)

b/ Nature and amplitude (statistical significance) of long-

term trends for the PSI and Q (E)

(Non-parametric Mann-Kendal test (MK) and its

sequential analysis method of Least Squares Linear

Regression (LSLR) with Student's t test for the

significance of the regression coefficient β)

Training in collaboration with GIZ Tunisia on "Multifactorial space approach for the analysis of

vulnerability of ecosystems of Component 1 pilot sites to face climate change" (21-25 April 2014):

Applicability in the pilot site Yes

Training in collaboration with VITO about "Cartographic material on the evolution of forest cover,

land use and climatic conditions of the pilot sites" (19-23 May 2014)

Applicability in the pilot site Yes

Landsat images downloaded for free From 1988 to 2000

Next steps Future changes the average air temperature

and rainfall of the district of Duzlerçami for the

period 2000-2030 and 2030-2050 compared to

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the current climate (1971-2000) will be

projected using the regional climate model

(RegCM4.3.5).

Global climate model HadGEM2 (Hadley

Global Environment Model 2) will be used for

small scale study area including Forest District

of Duzlerçami.

Emission scenarios RCP4.5 and RCP8.5 will

be used to study the changes and variability of

future climate.

1. Perform studies and detailed analyses on the

basis of GIS and remote sensing

2. Achieving climate analysis and climate model

projections for the future climate of the pilot site

and region

3. Start the vulnerability assessment.

Clarification:

A time series is a sequence of data points, measured typically at successive points in time spaced at

uniform time intervals. Time series are very frequently plotted via line charts. Time series are used in

statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather

forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, and

communications engineering.

One of the main goals of time series analysis is the determination of trends in these series as well as

the stability of values (and their variation) over time.

The Mann-Kendall trend test (M-K) is a non-parametric test to be used when a trend is identified in a

series, even if there is a seasonal component in the series.

In the case of seasonal Mann-Kendall test, we take into account the seasonality of the series. This

means that for monthly data with seasonality of 12 months, one will not try to find out if there is a

trend in the overall series, but if from one month of January to another, and from one month

February and another, and so on, there is a trend. For this test, we first calculate all Kendall's tau for

each season, and then calculate an average Kendall’s tau. The variance of the statistic can be

calculated assuming that the series are independent (e.g. values of January and February are

independent) or dependent, which requires the calculation of a covariance.

The method of least squares is a standard approach to the approximate solution of over determined

systems, i.e., sets of equations in which there are more equations than unknowns. "Least squares"

means that the overall solution minimizes the sum of the squares of the errors made in the results of

every single equation.

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SESSION 2: STATE OF THE ART OF CLIMATE CHANGE IMPACTS ON MEDITERRANEAN FOREST SPECIES IN THE PILOT SITES OF COMPONENT 1 Nadine Wazen (INRA Avignon)

I) FIRST RESULTS AND WORKPLAN 2014

After the workshop of Solsona, FAO asked INRA Avignon the implementation of the following action:

"Specifying the location of the pilot sites for each of their forest species in terms of geographical

marginality (limits range) and risk in relation to climate change"

The expected products are the following:

Cartographic documents detailing the distribution of major forest species in the selected

pilot sites for each component of the FFEM project;

A state of art of marginal areas and at risk for forest genetic resources in relation to climate

change (for each species present in the in the selected pilot sites for each component of the

FFEM project);

Recommendations for the management of forest genetic resources in the selected pilot sites

for each component of the FFEM project.

Basically, information has been collected on the geographical distribution of core populations and

marginal populations of a number of key Mediterranean forest species and their ecological and

genetic attributes. The choice of species studied was made after a compilation of all species in all

pilot sites (based on the description of the pilot sites). They were selected on the basis of their

presence in the majority of sites, their importance and their interest in the region, after the approval

there was a final selection.

The table below shows the 24 species identified:

Latin name Common name (English/French)

Acer hyrcanum subsp. tauricolum (Boiss. & Balansa) Yalt. Taurus Maple/Érable du Taurus

Arbutus unedo L. Strawberry tree/Arbousier

Cedrus atlantica (Endl.) Manetti ex Carriere Atlas Cedar/Cèdre de l'Atlas

Cedrus libani A. Rich. Cedar of Lebanon/Cèdre du Liban

Chamaerops humilis L. Mediterranean dwarf palm/Palmier nain

Ilex aquifolium L. Holly/Houx

Juniperus drupacea Labill. Syrian juniper/Genévrier de Syrie

Juniperus excelsa M.-Bieb. Greek juniper/Genévrier grec

Juniperus oxycedrus L. Prickly juniper/Genévrier oxycèdre

Juniperus phoenicea L. Phoenician juniper/Genévrier rouge

Laurus nobilis L. Bay laurel/Laurier noble

Pinus brutia Ten. Turkish pine/Pin de Calabre

Pinus halepensis Mill. Aleppo pine/Pin d'Alep

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Pinus nigra J.F. Arnold European black pine/Pin noir

Pinus pinea L. Stone pine/Pin pignon

Pistacia lentiscus Mastic tree/Lentisque

Platanus orientalis L. Oriental plane/Platane d'Orient

Quercus coccifera L. Kermes oak/Chêne kermès

Quercus cerris L. Turkey oak/Chêne de Turquie

Quercus ilex L. Holm oak/Chêne vert

Quercus canariensis Willd. Algerian oak/Chêne Zéen ou zen

Quercus suber L. Cork oak/Chêne liège

Taxus baccata L. European yew/If

Tetraclinis articulata (Vahl) Mast. Barbary thuja/Thuya de Berberie

The purpose is to produce maps of the 24 native species distribution and determine the marginal

populations. The approach is the following:

1. Collection and compilation of all available data

2. Screening and optimization of selected data

3. Production of maps

GIS software used: Q-GIS

Collection of data: 3 data types:

points of presence (entered by users or different observers),

geographic coordinates (X, Y) of actual populations in scientific publications,

online shapefiles on the distribution of species (including NFI maps).

Collection: Data sources:

GBIF online database (Global Biodiversity Information Facility): information on the presence

of only one species (and not on the density), based on observations not always scientific of

users. This may be also seeds, fossils, herbarium ...

META database (INRA-Avignon, compiled by Cyrille Conord): info on populations until 2009

EUFORGEN database (European Forest Genetic Resources Programme): maps of distribution

of only a few species, including those from Europe.

How to filter information on autochthone distribution (native distribution) of selected species?

Several sources, more or less reliable, were consulted: Catalogue of Life, Med Checklist, KEW World

Checklist and EURO+MED. Many problems were encountered: the information is not consistent or

specific, often incomplete and sometimes contradictory.

Some maps are available: Quercus suber, Pinus halepensis, Cedrus libani, Juniperus phoenica.

The distribution areas defined by EUFORGEN are then compared with the actual data (data

digitization national papers).

In the case of Quercus suber for example, problems of resolution and therefore the detail of the

information arise: are there wooded areas of Quercus suber that connect the various cork oak

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landscapes between them? What is the interest to keep such detailed information? From when

(density, area) the information should be available?

The pilot site of Siliana (Tunisia) illustrates this example: there are approximately 1 000 individual

Quercus pubescent. This small isolated patch is bonded to a microclimate, this is a marginal

population. This geographical marginality has a genetic interest in Tunisian forest.

It is important to have the two types of information: large areas where populations are dense and

geographically marginal populations

The next steps are:

Feedback from national experts (important to determine the exact regions with the

presence of the species in a country, also useful for the distribution of native species);

Consultation of national forest inventories (e.g. forest inventory 2008 in Algeria)

Scanning paper maps remaining before September 2014;

Updating the database META by June 2014 (2009-2014 - Susana Pereira - INRA

Avignon);

Latest comments of national experts;

Creation of maps;

Provision of maps (shapefiles and jpeg) to the scientific community by November

2014.

This work will localize marginal and peripheral populations and identify populations at risk, hence

the importance of having detailed and accurate maps.

In addition, this work allows to link with Component 2: What is the impact of changing woodland

(distribution areas of different species) on the provision of goods and services?

II) Next steps of the study conducted by INRA Avignon - Challenges and actions to be

implemented/data to be mobilized to achieve the objectives of this study by the end of

2014

Country Referent Information to be transmitted Date

Algeria Assia Azzi

National Forest Inventory

Pinus halepensis reforestation green dam (period: seventies)

Morocco

Fouad Mounir NAFLO database/some forestry inventory maps of 1994

from 9 to 13 June 2014

Bakhiyi Belghazi Map of vegetation After June 15, 2014

Fayçal Benchekroun National Forest Inventory (map /shapefile)

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Remarks:

As a result:

There is an urgent need to collect shapefiles data with accurate information on the

source and date of the data.

The results of this study will be presented on maps at Mediterranean-basin level and

not at national level.

It is necessary to have consistency for the 24 selected species, with the same level of

detail (e.g. case of cork oak).

When there is enough information for a species, it will be possible to produce more

detailed maps.

It is necessary to distinguish the area of distribution of the species and the actual

presence of the species.

With respect to maps of natural distribution of species, INRA expects the accuracy of

national experts. For example, the Pinus Pinea was planted in many places in Tunisia,

and the Pinus Halepensis has often been planted in the Mediterranean in areas of cork

oak.

Different data types are employed: bibliographic data, paper maps, forest inventories.

Can we illustrate all these data if we mix them? Can we mix data with different dates?

Algeria: The last forest inventory in 2008 could give a lot of new information. However, it is rather an

administrative forest inventory made by the province and not by forest groups.

Tunisia: Many data are available at the CEFE-CNRS of Montpellier (including data on species in

shapefiles and "map phytoecological of Northern Tunisia" in 1967). However, some data (including

the study on cork oak and degradation in Tunisia) are available in paper charts and need to be

scanned.

Morocco: Maps of species distribution by Emberger in 1939 should be scanned ("Overview of

vegetation in Morocco"). This study is quite complete for common forest species, but there is little

information available for most secondary species such as Arbutus Unedo or Chamerops Humilis.

Lebanon: Data should not exceed the framework of the project.

Tunisia Ali Aloui National Forest Inventory (map/shapefile)

Phytoecological map of Northern Tunisia in 1967

Lebanon

Miguel Angel Navarrete Poyatos

Absence/presence of species in Lebanon

Salim Roukoz Shapefile forest 1965 from 5 to 13

June 2014

Shapefile land cover 2005

Turkey Murat Turkes

Forest Atlas of Turkey (website) from 9 to 13 June 2014

Data and shapefiles for the pilot site

Shapefile data of forest atlas

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SESSION 3: STATE OF THE ART ON STUDIES/RESEARCH FOR THE ADAPTATION AND MITIGATION OF CLIMATE CHANGE IN MEDITERRANEAN FOREST ECOSYSTEMS: FIRST RESULTS AND WORKPLAN 2014 Valentina Garavaglia

The bibliographic collection made by FAO (Carolina Gallo Granizo) of all studies/researches on

adaptation and mitigation to climate change in Mediterranean forest ecosystems will allow to

establish a basis for inter-component data, which will be available on the webpage of the FFEM

project /Silva Mediterranea (http://www.fao.org/forestry/82782/en/), with a link to the platform

FFEM of Plan Bleu (http://planbleu.org/en/activites/foret/optimiser-la-production-de-biens-et-

services-par-les-ecosystemes-boises).

For each publication there will be a summary table containing: Title, Author, Publication Date, Name

of the journal (if applicable), Volume (for review), Publisher, Language, Study area, Species studied (if

applicable), Component(s) concerned, Pilot site(s) concerned, Keywords, Abstract.

Example of the summary table for each publication

The database online will include search engine keywords (component, country, species).

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Below the current statistics by component, country and species:

Note: Component 5 corresponds to Guides and Guidelines on forest management.

The number of articles is currently limited with publications mainly in English and French. It is not an

exhaustive list, but a collection of relevant literature in relation to the project and a more targeted

bibliography at the country level.

The next steps are the following:

Search for publications in other scientific journals, research on Science Direct

(http://www.sciencedirect.com/) by keyword,

Contribution of different countries to provide more targeted products at the national level,

and sometimes unpublished in English or French (as for Turkey).

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SESSION 4: Common Day C1/C2

What will be the impact of climate change on forest ecosystems in the Mediterranean, especially in

the five pilot sites (modelling future changes)? How to anticipate future changes, particularly at the

management level? What will be the change in terms of provision of goods and services? What goods

and services should be taken into account?

The goal of a common day between Component 1 and Component 2 is to develop synergies in terms

of available data or data to be collected (deadlines, synthesis) and in terms of transfer of knowledge

and skills (capitalization) exchanges between national experts, identifying possible synergies by

country, work plan 2014, next steps, support needed, etc.

Presentation of the first activities carried out, work plan 2014 and description of the types of data produced by component 1

Valentina Garavaglia

The several activities:

Workshop in Solsona (Spain) in May 2013 with focal points and national experts, as

well as the two technical partners GIZ and VITO: definition and adoption of a common

methodology

Workshop in Tunis (Tunisia) in April 2014 for National Experts on the multifactorial

spatial analysis approach of the vulnerability of ecosystems, in cooperation with GIZ

Tunisia

Training Workshop in Mol (Belgium) in May 2014 for national experts about the

production of cartographic materials on changes in forest cover, land use and climatic

conditions of the pilot sites using free data image Landsat, QGIS software, pktool

(VITO), Collect Earth (FAO), climate data MARS, ASIS, in cooperation with VITO

Work of INRA: "Ecological niche" approach regional mapping of actual distribution

of areas limits and modelling of areas of future distribution of the 24 main species

present in the pilot sites (distribution in terms of presence/absence + identification of

the level of marginality)

Work of FAO: collection of all available scientific articles on the subject, for each

component create a descriptive sheet for each article and establish a database to

make information available to the partners involved in the FFEM project

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Presentation of the first activities, work plan 2014 and description of the types of data generated by component 2 Marion Duclercq

The objective of Component 2 is “the estimation of the social and economic value of goods and

services provided by Mediterranean forest ecosystems by studying multiple issues related to changes

in the environment and their potential effects on the socio-economic development"

The various stages of the work carried out for Component 2 are:

Phase 1: State of the art, at the level of the Mediterranean region, of methods and

tools of socio-economic evaluation of goods and services provided by an ecosystem

(forest or other), and development of methodologies to be implemented in the pilot

sites (February-December 2013):

Production of a report and methodology sheets with a range of methods and tools

used for the economic evaluation of forest goods and services, their strengths and

limitations in relation to the specificities of the Mediterranean context, and

recommendations

For each country, finalizing the economic evaluation methodology adapted to the

specificities of the pilot site

Phase 2: Assessment of economic and social value of goods and services provided by

forest ecosystems in selected pilot sites (from the end of 2013):

Implementation of the approach on four pilot sites (Chréa National Park (Algeria0,

Jabal Moussa Biosphere Reserve (Lebanon), Maamora Forest (Morocco),

Duzlercami Forest (Turkey));

Regional workshop to support the implementation of methodological approaches

aiming at discussing difficulties encountered and methodological issues still to be

clarified.

How to assess the social and economic value of ecosystem services? Thanks to the cost-benefit

analysis (Cost-Benefit Analysis - CBA). The Cost Benefit Analysis (CBA) is a method for the

description and aggregation of the expected effects of a decision. It is an analysis with respect to an

investment and not with respect to a good. CBA will help deepen the existing analyses and thus go

further in the production of useful and relevant information to the decision:

What are the changes in the economic and social value of goods and services based on

different scenarios of climate change and management options?

What are the costs and benefits associated with the production of these goods and

services? How are they distributed between the different stakeholders?

CBA will allow the analysis of the evolution of marginal flow of costs and benefits by type of actors

(households, industry, agriculture, communities, etc.) according to alternative management of

woodlands.

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Synergies C1/C2 in Algeria Assia Azzi

On the Chréa pilot site, goods and services selected for component 2 are:

Recreational aspect related to the Barbary macaque;

Production of Arbutus unedo;

Water purification

The main possibility of synergy is the use of the methodology for creating a vulnerability map to

predict possible changes on ecosystems and their capacity to provide goods and services assessed.

However, the main constraints are the following:

The pilot sites for component 1 and component 2 are not the same: Senalba (semi-

arid) for C1 and Chréa for C2 (from subhumid to humid);

The parameters used in planning methodology of the vulnerability map on the site of

Senalba may not be adapted to the case of Chréa.

In terms of opportunities, thanks to the activities of Component 1, two Algerian managers were

trained in the use of the methodology for producing vulnerability maps in the framework of the

forest administration (DGF). Moreover, the organization of a national workshop combining the 4

components for improved interaction and sharing of data is scheduled for September 2014.

Synergies C1/C2 in Lebanon Carla Jamous

Many data will be exchanged between the two components.

From component 1 to component 2:

Demographic and socio-economic data: population since 1995 (grazing pressure

estimation, harvest of timber and collection of medicinal and aromatic plants);

Forest data: forest inventory (distribution of tree species on the site), logging (cuts);

Biodiversity data: endangered species with a map of their distribution on site (Quercus

cerris and Juniperus drupacea)

From component 2 to component 1:

Data on grazing: forage units, types of forage

This information will be obtained through a field survey, to be conducted as soon as possible (from

June 2014 to be continued until spring 2015)

The economic analysis is expected from October/November 2014, following the collection of data.

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Synergies C1/C2 in Morocco Abdelmohssin El Mokaddem

Ten goods and services were selected for the pilot site of the Maâmora forest.

Useful data that can be exchanged between components 1 and 2 are as follows: slope maps, maps on

the state of development, contribution of forests to the generation of income to household,

exchange of data on cork collection (for the period 1992-2009 and 2011-2014), crimes recorded,

WWF study on acorns, route maps.

Under component 2, two scenarios of evolution will be used for the cost-benefit analysis. They are

produced by component 1 (projection of the state of vulnerability), with the hypothesis 0 (reference:

normal development without planning/response) compared with an evolution with intervention.

Synergies C1/C2 in Turkey Özge Balkiz and Murat Turkes

Limitations for Component 2:

There is a lack of accurate data on the costs of managing the production of industrial

wood in the pilot sitel;

The function of protection of biodiversity is being evaluated at the moment;

The budgets of public and private organizations for the protection of biodiversity are

unknown;

It is difficult to assess the impact of increased recreational use of forest biodiversity

areas (lack of data on long-term monitoring of species);

There is a lack of reliable information on tourist visits on the site and on the net

income of organizations for recreational areas;

There is a lack of specific data on carbon sequestration (this could be solved using the

case of Lebanon);

There is a lack of detailed information on the number of hunters in the region and a

lack of long-term data on the activities of big game hunting.

Possible synergies between component 1 and component 2 are as follows:

Review of the literature on changes in annual growth of pine forests in the

Mediterranean (by the end of June 2014);

Review of the literature on the evolution of diseases and pests in pine forests in the

Mediterranean (end of June 2014);

Predictions of wildfire risk specifically for the pilot site (to be produced by mid-October

2014);

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Results of the vulnerability analysis on the pilot site: changes in terms of climatic

conditions and species distribution (by mid-October 2014) and link with Component 2

(e.g., the most sensitive areas (with strongest changes) will be those where the

production of wood industry of Pinus brutia will decrease).

In terms of timetable: the data collection and vulnerability analysis will occur until October. From

that date, the cost-benefit analysis can be made.

Synthesis Valentina Garavaglia and Christophe Besacier

This common day allowed having time for working and brainstorming together. Data collections in

the two components are very complementary. The coordination and undertsnding of the project in

each country is quite good. With regard to component 1, this common day allowed focused better

focus of the activities on the overall results and objectives of the project, after two highly technical

workshops in April 2014 (GIZ) and May 2014 (VITO).

Such work in synergy is also planned for components 1 and 4, particularly during the debriefing

workshop of C1 at the end of 2014 in Antalya (Turkey).

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Presentation of results of the first workshop for capacity building organized in collaboration with VITO Valentina Garavaglia (FAO - Silva Mediterranea)

This first one-week workshop, held in Mol (Belgium) from 19 to 23 May 2014, aimed to analyse the

"Remote sensing techniques and classification of changes in forest cover, land use and climatic

conditions of the pilot sites selected for Component 1".

A second week of training will be held in Rabat (Morocco) from 22 to 26 September 2014.

The objective of the work in cooperation with VITO is the production of maps on the evolution of

forest cover (and other wooded ands/other lands) using processing tools of free information (QGIS:

free mapping software; PkTools: a tool for image processing developed by VITO; Collect Earth:

Google Earth plugin developed by FAO for the systematic analysis of a sample of forest plots; OSGeo-

Live: system to try a wide variety of open source geospatial software without installing anything) and

free data (Landsat images in particular).

The approach is presented here below in a diagram:

Source: Fouad Mounir (Morocco).

The classification is the most complicated part of the study; it will be further discussed during the

workshop in Rabat. Before the workshop in Rabat, the data must be collected. At the end of the

workshop, the final maps and the results (analysis of changes in land use in particular) will be

produced.

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The approach is also presented here below in more detail:

Source: VITO.

Notes:

Some national experts are not part of forest administrations. How can we sustain this expertise?

In the case of Lebanon, the methodology of VITO is useful for using free tools, but it is not very

appropriate given the small size of the pilot site.

A service contract was signed with VITO (assistance online or on-site assistance).

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Presentation of GIZ activities on the vulnerability of ecosystems in Tunisia Abdelmajid Jemaï (GIZ)

The conceptual approach of the methodology used: multifactor spatial modelling is presented in the

following diagram:

Source: GIZ.

The methodology is explained in more detail in the report of the workshop of Solsona.

The results of the multifactor spatial modelling will allow assessing risks and estimate losses of

goods and services provided by forest ecosystems in pilot sites and it will answer to the following

questions:

What are the consequences of climate change impacts on woodlands and on their provision

of goods and services (2020 and 2050 projections)?

From which level we can speak of risk of loss for different tree species?

What is the shift of favourable conditions for the presence of a given ecosystem (e.g.

Suber)?

How to take into account future climate data (not just the current climate data) in future

management plans?

What are the concrete actions to implement in order to improve the adaptation of

woodlands to climate change?

Capacity building for different stakeholders (awareness, training) is necessary.

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SESSION 5: Summary of exchanges in each pilot site to identify next steps and overcome difficulties to finalize the vulnerability analysis by the end of 2014

Concerning the multifactor spatial analysis:

- take two new scenarios of the 5th IPCC report: RCP4.5 (optimistic - old B1) and RCP8.5 (pessimistic -

old A2) timeline is from 2016 to 2035 and from 2046 to 2065

-take the models of WorldClim (http://worldclim.org/cmip5_30s): in Turkey, after tests by

meteorologists for choosing the best model, the one selected is HadGEM2-ES. Unless meteorologists

disagree, it will be removed from the pilot sites model.

- in WorldClim, timelines proposed are 2050 and 2070

- move the timeline to 2050 (which corresponds to an average of 2041-2060; this correspond more

or less to the second term proposed by the 5th IPCC report)

Concerning the 5th and last IPCC report (2013), see the following articles:

http://www.climatechange2013.org/images/report/WG1AR5_SPM_FINAL.pdf

http://leclimatchange.fr/

Regarding the second week of training with VITO:

- Rabat (Morocco) from 22 to 26 September 2014

- 3 participants per country: 2 participants of the first workshop in Mol (Belgium) + 1 other expert

(from the preferred forest administration)

- Support for participants will not be charged on LoA underway in each country but will be funded

by a portion of the budget of component 4 (logistics: FAO)

- Name of a third participant to be provided by the end of June 2014

- Focal point for the organization of the workshop: Mustapha Bengueddour

- Before the workshop in Rabat: gathering necessary data, if concern: contact VITO

The most significant drivers (agents and drivers of degradation and deforestation) should be

involved in the vulnerability analysis of ecosystems. Factors taken into account should match the

results of the report produced by component 4 for the main factors of degradation. However, data of

poor quality/low accuracy should not be taken into account in order to minimize the risk of reducing

the quality of the final product.

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Regarding the problems, and the selection of factors:

Case of Lebanon:

- Lack of data on grazing. Now this is a major problem on the site of Jabal Moussa: lack of natural

regeneration, etc. Data collection on grazing is provided under component 2.

- Available data on forest fires (occurrence of fire, types of fuel).

- These two factors factor could be eliminated, assuming that the combination of data on grazing and

fire is antagonistic (collinearity of the two factors). However: there is not a systematic reduction in

the risk of fire in case of overgrazing, as shepherds often set fire during the path…

The factor of grazing and fires in the vulnerability analysis of ecosystems and multifactor spatial

modelling will be kept.

Case of Turkey:

- Grazing is not a major problem on the site of Duzlercami. This factor will not therefore be taken into

account.

- However, the risk of forest fires is to be considered and to connect with the increase numbers of

tourist on this site (due to its location in the suburbs of Antalya). It is also important to consider

increased risk of fire in the future.

Only the forest fires factor is kept (and its future evolution).

Case of Algeria:

- The risk of forest fires is not a major problem on the site of Senalba. This factor will not therefore be

taken into account.

- The site presents big problems of natural regeneration and reforestation has a high failure rate.

- The risk of desertification is not negligible and therefore to integrate. This factor is the combination

of factors that lead to degradation or even disappearance of forest cover (silting? livestock farming?

diseases?). This factor will be taken into account with maps of desertification sensitivity

(identification of sensitive areas).

- Finally, the health aspects of forests should be integrated (see study of CTFC on forest health in

Djelfa due to the presence of bark beetles and other pests).

The risk factor of desertification and forest health factor will be kept.

Case of Morocco and Tunisia:

All necessary data (all main agents and drivers of degradation and deforestation) are available.

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Generally it is important to integrate the evolution of fire hazards (depending on factors such as

changes in forest management, land abandonment, changes in tourist numbers, etc.) in the model

(see article of JRC in the state of Mediterranean forests on the evolution of risk of forest fires).

Concerning the control of the GIZ methodology:

- Algeria, Morocco, Tunisia, Turkey: OK (no problem raised for implementation in 2014)

- Lebanon: methodology needs to be adapted a little, otherwise OK

In addition, a few days post-training for online support are provided by the two Tunisians consultants

(Kamel Tounsi and Ali Aloui).

GIZ and the FAO will work on the English translation of the methodological note on the analysis of

ecosystems vulnerability. Murat Turkes (Turkey) offered to translate the document into Turkish (for

his Turkish colleagues of the other components). Moreover, Ali Aloui and Kamel Tounsi offered

additional training on GIZ methodology for the General Directorate of Forests of Tunisia.

Concerning exchanges with Component 2:

- Algeria: apply the methodology C1 for the production of maps on the site of Chréa

- Turkey: sharing data and maps produced

- Lebanon: sharing data on grazing

- Morocco: future scenarios

- Tunisia: no activities for Component 2

Regarding the minimum format of the final position paper:

- Structured as a traditional scientific article: Introduction and Objectives, Materials and Methods,

Results, Discussion (plan of the final report common to all countries)

- Materials and Methods: Detailed description of the methodology by country

- Results: Maps + interpretation (descriptive analysis)

- Explanation of the choice of factors, advantages and disadvantages of the dataset available in the

pilot site

+ Production of a sheet with a synthetic presentation

- VITO and GIZ will be involved in drafting this final report for each pilot site

The last part of the report will focus on recommendations. These will be described by type of user

(managers, policy makers, researchers, etc.).

A poster could be prepared and submitted by each country especially during Fourth Mediterranean

Forest Week in Barcelona (Spain) in March 2015 and the World Forestry Congress in Durban (South

Africa) in September 2015.

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It is also possible to publish articles in various newspapers (Unasylva, Forêt Méditerranéenne, etc.) or

scientific journals.

Concerning the last practical and financial aspects:

Morocco, Tunisia and Lebanon: LoA with local associations. The first instalment was paid (30% of the

total amount equal to € 15,000). Countries can make the request for the second instalment (50%

equal to € 25,000). For the second payment, there is no need for detailed documentation. The third

payment (20% equal to € 10,000) will be made once the work is completed. That thus requires a cash

advance at project completion by the partner organizations. For this third payment a detailed

justification of the total expenditure is needed.

For minor expenses, the allocation of expenses among the budget lines is flexible. A simple email to

inform FAO is enough. In case of major changes or questions, FAO/Silva Mediterranea should be

contacted.

Regarding the payment of national consultants recruited outside the LoA (through FAO

representations in Algiers, Ankara and Beirut), they must complete their working time declaration

form on the system to manage consultants and staff (Global Resource Management System - GRMS)

and send it for approval to FAO before the payment. The payment is not monthly, but it will be when

results are produced in accordance with Terms of Reference.

Algeria, Turkey: no contract with local associations FBA (Field Budget Authorization): Permanent

Representations of FAO in Algiers and Ankara are authorized to make expenditures.

Finally, Algeria and Tunisia, there is a limit for the release of foreign currency abroad which can cause

problems during missions outside the country show a certificate?

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ANNEX 1: Agenda of the workshop in Tunis

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Mid-term workshop

Project: Optimizing the production of goods and services of Mediterranean forests

in a context of global changes

Component 1: Production of data and development of tools to support decision and management of

vulnerable Mediterranean forest ecosystems affected by climate change and the ability of these forest

ecosystems to adapt to global change

2 - 5 June 2014

Hotel Belvédère Fourati, Tunis

Objectives

Main objectives of the mid-term workshop of Component 1 organized in Tunis on 2-5 June 2014 in

collaboration of the General Directorate of Forests (Government of Tunisia) are:

• Illustrate the first results produced by the partner countries on vulnerability assessment of

Mediterranean forest ecosystems to climate change in the pilot sites

• Illustrate the results produced by INRA Avignon on the state of the art of climate change impacts on

selected Mediterranean forest species in the pilot sites for the implementation of activities of the

project

• Discuss with the coordinators, experts, focal points and thematic referents of Component 2: (i) the

first results produced by Component 1, (ii) the data expected by end of 2014 by experts of

component 2 on the impacts of climate change on goods and services and (iii) future collaborations

and exchanges of results obtained by the end of 2014; iv) next steps for all activities scheduled for

Component 1

Participants

Focal points

Thematic experts

National experts

One expert from INRA Avignon

One expert from GIZ Tunisia

FAO – Silva Mediterranea: Moderator

Others: Representatives of the Tunisian General Directorate of Forests

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Arrival of participants on 1/6/2014 – departure on 6/6/2014

Day 1 : 2/6/2014

9h00 – 9h45

Welcome (Tunisian General Directorate of Forests)

Round table to introduce participants (Valentina Garavaglia/FAO)

Objectives of the workshop (Valentina Garavaglia/FAO)

Review of activities scheduled for Component 1 (Valentina Garavaglia / FAO)

9h45 – 10h30 First results and program for 2014 : pilot site of Djelfa (Algeria)

Coffee break

11h00-11h45 First results and work plan 2014: pilot site of Jabal Moussa (Lebanon)

11h45-12h30 First results and work plan 2014: pilot site of Maamora (Morocco)

Lunch break

14h00 – 14h45 First results and work plan 2014: pilot site of Senalba (Tunisia)

14h45 – 15h30 First results and work plan 2014: pilot site of Düzlerçami (Turkey)

Coffee break

16h00-16h45

State of the art of climate change impacts on selected Mediterranean forest species in

the pilot sites of Component 1: first results and workplan for 2014 (Nadine Wazen,

INRA Avignon)

16h45-17h30

State of the art of activities/studies/projects on adaptation of Mediterranean forests

to climate change in areas similar to the pilot sites selected for Component

1 (Valentina Garavaglia/FAO)

17h30 – 18h00 Synthesis of the day and preparation of the joint day of Component 1 and 2

Day 2 : 3/6/2014 Joint day Component 1/Component 2

9h – 9h30 Welcoming and clarification of the objectives of Components 1 and 2 joint day

9h30 – 10h30 Presentation of ongoing activities, workplan 2014 and description of data produced in

the framework of component 1 (Valentina Garavaglia and Christophe Besacier/FAO)

Coffee break

11h00 – 12h00 Presentation of ongoing activities, workplan 2014 and description of data required for

the implementation of component 2 (Marion Duclerq/Plan Bleu)

12h00 - 13h00 Round table: initial exchange on potential synergies between Components 1 and 2

Lunch break

14h30 – 16h00 Exchange with countries to identify expected results and synergies to be developed

between component 1 and component 2

Coffee break

16h30 – 18h00 Outputs of countries, expectations and synergies to be developed between component

1 and component 2, and synthesis of the joint day (Christophe Besacier/ FAO)

Day 3 : 4/6/2014

9h00 – 10h30

Next steps to be taken for the compilation of the state of the art by INRA Avignon/

data to achieve the objectives of this study by the end of 2014 (Nadine Wazen/INRA

Avignon)

Coffee break

11h00 – 12h30

Presentation of the results achieved during the workshop organized in collaboration

with VITO Vision on Technology on "Production of cartographic material on the

evolution of forest cover, land uses and climatic conditions of the pilot sites"

(Valentina Garavaglia/ VITO)

Lunch break

14h00 – 14h45 Presentation of the activities implemented by GIZ Tunis on the activities performed to

assess the vulnerability of ecosystems in Tunisia (Abdelmajid Jemaï /GIZ)

14h45 – 15h30 Presentation of the results of the workshop organized in collaboration with GIZ Tunis

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on ”Multifactorial spatial analysis of the vulnerability of pilot sites to climate change

selected for Component 1’’ (Kamel Tounsi/Ali Aloui/GIZ)

Coffee break

16h00 – 17h30

Next steps to be implemented after the first week of workshop organized in

collaboration with VITO on the production of cartographic material on the evolution of

forest cover, land uses and climatic conditions of the pilot sites

17h30 – 18h00 Presentation of MOSAICC, FAO Modelling System for Agricultural

Impactes of Climate Change (Renaud Colmant/FAO)

Day 4 : 5/06/2014

9h00 – 12h30

Exchange at each pilot-site level to identify next steps and overcome difficulties to

finalize vulnerability assessments by 2014

Lunch break

14h00-14h30 Next steps and workplan 2014: pilot site of Djelfa (Algeria)

14h30-15h00 Next steps and workplan 2014: pilot site of Maamora (Morocco)

15h00-15h30 Next steps and workplan 2014: pilot site of Jabal Moussa (Lebanon)

Coffee break

16h00-16h30 Next steps and workplan 2014: pilot site of Siliana (Tunisia)

16h30-17h30 Next steps and workplan 2014: pilot site of Düzlerçami (Turkey)

17h30-18h30 Summary of next activities and conclusion of the workshop

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ANNEX 2: Methodology "Impacts of climate change on the distribution of native tree species in Lebanon potential projections by 2050"

the introduction and presentation of the objectives and methodology of the study conducted in

Lebanon. The full report is available - contact Miguel Ángel Navarrete Poyatos: [email protected].

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON:

POTENTIALITY PROJECTIONS TO 2050

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 2

CENTER FOR APPLIED RESEARCH IN AGROFORESTRY DEVELOPMENT (IDAF) - UNIVERSITY OF CÓRDOBATechnical Staff

Project Coordinator, IDAF Miguel Ángel Navarrete PoyatosForest Management Expert, IDAF Miguel Ángel Lara GómezGIS and Remote Sensing Expert, IDAF Jesús Trujillo ToroGeneral Manager and Director, IDAF Guillermo Palacios RodríguezHead of ERSAF Research Group, University of Córdoba Rafael María Navarro CerrilloPermanent Teacher and Researcher, Lebanese University Dr. Salim KattarProgramming Expert, University of Córdoba Joaquín Duque Lazo

The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government.

CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON:

POTENTIALITY PROJECTIONS TO 2050

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 3

INDEX

1. INTRODUCTION

2. OBJECTIVES2.1 GENERAL OBJECTIVE2.2 SPECIFIC OBJECTIVES

3. METHODOLOGY3.1 SCOPE3.2 SCHEME OF WORK

4. CLIMATE VARIABLES4.1 CURRENT CLIMATE VARIABLES4.2 FUTURE CLIMATE VARIABLES4.3 VARIABLES SELECTION

5. SPECIES DISTRIBUTION MODELS (SDM)

6. IDENTIFICATION OF SPECIES PRESENCE / ABSENCE

7. SPECIES POTENTIALITY7.1 OBTAINED RASTER FILES7.2 OBTAINED SPECIES DISTRIBUTION MODEL

7.2.1 Abies cilicica7.2.2 Acer syriacum7.2.3 Acer tauricolum7.2.4 Arbutus andrachne7.2.5 Arceuthos drupacea7.2.6 Cedrus libani7.2.7 Ceratonia siliqua 7.2.8 Cercis siliquastrum7.2.9 Crataegus spp.7.2.10 Cupressus spp.7.2.11 Juniperus excelsa7.2.12 Juniperus oxycedrus7.2.13 Pinus brutia7.2.14 Pistacia spp.7.2.15 Prunus ursina7.2.16 Pyrus syriaca7.2.17 Quercus calliprinos7.2.18 Quercus cerris7.2.19 Quercus infectoria7.2.20 Styrax officinalis

8. POTENTIAL SPECIES RICHNESS8.1 MAPS OF POTENTIAL SPECIES RICHNESS

8.1.1 CURRENT POTENTIAL SPECIES RICHNESS8.1.2 FUTURE POTENTIAL SPECIES RICHNESS. B1 SCENARIO8.1.3 FUTURE POTENTIAL SPECIES RICHNESS. A2 SCENARIO

8.2 LOSS/GAIN POTENTIAL SPECIES RICHNESS8.2.1 LOSS/GAIN POTENTIAL SPECIES RICHNESS. B1 SCENARIO8.2.2 LOSS/GAIN POTENTIAL SPECIES RICHNESS. A2 SCENARIO

8.3 CRITICAL AREAS8.3.1 CRITICAL AREAS MAP

9. APPLICATION OF RESULTS TO RESTORATION AND ADAPTIVE MANAGEMENT IN A CONTEXT OF GLOBAL CHANGE9.1 ADAPTATION MEASURES PER SPECIES

9.1.1 Abies cilicica9.1.2 Acer syriacum9.1.3 Acer tauricolum9.1.4 Arbutus andrachne9.1.5 Arceuthos drupacea

................................................................................................................................................................... 6

........................................................................................................................................................................ 7 ............................................................................................................................................ 7

.......................................................................................................................................... 7

................................................................................................................................................................... 8........................................................................................................................................................... 8

....................................................................................................................................... 8

........................................................................................................................................................... 9................................................................................................................... 9

...................................................................................................................... 9.............................................................................................................................. 10

........................................................................................................................... 11

....................................................................................................... 12

.................................................................................................................................................... 13........................................................................................................................... 13

............................................................................................... 13.................................................................................................................................. 14................................................................................................................................ 16

............................................................................................................................. 18......................................................................................................................... 20....................................................................................................................... 22

.................................................................................................................................. 24............................................................................................................................ 26

........................................................................................................................ 28............................................................................................................................... 30.............................................................................................................................. 32

........................................................................................................................... 34...................................................................................................................... 36

.................................................................................................................................... 38............................................................................................................................... 40................................................................................................................................ 42................................................................................................................................. 44

........................................................................................................................ 46............................................................................................................................... 48

.......................................................................................................................... 50............................................................................................................................ 52

....................................................................................................................................... 54................................................................................................ 55

.................................................................................. 55............................................................ 56............................................................ 57

.............................................................................................. 58....................................................... 59....................................................... 60

......................................................................................................................................... 61................................................................................................................... 62

........ 64 ...................................................................................................... 64

.................................................................................................................................. 66................................................................................................................................ 67.............................................................................................................................. 68

......................................................................................................................... 69....................................................................................................................... 70

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 4

INDEX

.................................................................................................................................. 71............................................................................................................................ 72

........................................................................................................................ 73............................................................................................................................... 74.............................................................................................................................. 75

.......................................................................................................................... 76...................................................................................................................... 77

.................................................................................................................................... 78.......................................................................................................................... 79

................................................................................................................................. 80

................................................................................................................................. 81........................................................................................................................ 82

............................................................................................................................... 83......................................................................................................................... 84

............................................................................................................................ 85 ........................................................................................ 86

................................................................................................................................................................. 87

......................................................................................... 90.................................................................................................................. 90

..................................................................................................................... 91............................................................................................................................... 92

................................................................................................ 92.......................................................................................... 93

................................................................................... 94

................................................................................... 95...................................................................................... 96

............................................................................... 97

............................................................................... 98...................................................................................................... 99

............................................................................................. 100

............................................................................................. 101

......................................................... 102.............................................................................................................................. 103............................................................................................................................. 103.............................................................................................................................. 105

..................................................................................................................... 106

....................................................................................................................................... 107.............................................................................................................................................. 109............................................................................................................................................ 109.......................................................................................................................................... 110

..................................................................................................................................... 110................................................................................................................................... 111

.............................................................................................................................................. 111........................................................................................................................................ 112

.................................................................................................................................... 112........................................................................................................................................... 113.......................................................................................................................................... 113

...................................................................................................................................... 114.................................................................................................................................. 114

............................................................................................................................................... 115..................................................................................................................................... 115

............................................................................................................................................ 116 ............................................................................................................................................. 116

.................................................................................................................................... 117........................................................................................................................................... 117

...................................................................................................................................... 118........................................................................................................................................ 118

9.1.6 Cedrus libani9.1.7 Ceratonia siliqua 9.1.8 Cercis siliquastrum9.1.9 Crataegus spp.9.1.10 Cupressus spp.9.1.11 Juniperus excelsa9.1.12 Juniperus oxycedrus9.1.13 Pinus brutia9.1.14 Pistacia palaestina9.1.15 Prunus ursina9.1.16 Pyrus syriaca9.1.17 Quercus calliprinos9.1.18 Quercus cerris9.1.19 Quercus infectoria9.1.20 Styrax officinalis

9.2 ADAPTATION MEASURES PER CRITICAL AREAS

10. BIBLIOGRAPHY

11. ANNEX I. CLIMATE VARIABLES. ANALYSIS AND SELECTION11.1 CURRENT CLIMATE VARIABLES11.2 FUTURE CLIMATE VARIABLES11.3 VARIABLES SELECTION11.4 CURRENT AND FUTURE VARIABLES MAPS

11.4.1 Winter Minimum Temperature: Current11.4.2 Winter Minimum Temperature: B1 Scenario11.4.3 Winter Minimum Temperature: A2 Scenario11.4.4 Summer Maximum Temperature: Current11.4.5 Summer Maximum Temperature: B1 Scenario11.4.6 Summer Maximum Temperature: A2 Scenario11.4.7 Summer Precipitation: Current11.4.8 Summer Precipitation: B1 Scenario11.4.9 Summer Precipitation: A2 Scenario

12. ANNEX II. SPECIES DISTRIBUTION MODELS. DESCRIPTION AND EVALUATION12.1 STATISTICAL MODELS12.2 MODELS DESCRIPTION12.3 MODELS EVALUATION12.4 POTENTIALITY THRESHOLD

13. ANNEX III. CLASSIFIED MAPS13.1 Abies cilicica13.2 Acer syriacum13.3 Acer tauricolum13.4 Arbutus andrachne13.5 Arceuthos drupacea13.6 Cedrus libani13.7 Ceratonia siliqua 13.8 Cercis siliquastrum13.9 Crataegus spp.13.10 Cupressus spp.13.11 Juniperus excelsa13.12 Juniperus oxycedrus13.13 Pinus brutia13.14 Pistacia palaestina13.15 Prunus ursina13.16 Pyrus syriaca13.17 Quercus calliprinos13.18 Quercus cerris13.19 Quercus infectoria13.20 Styrax officinalis

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 5

EXECUTIVE SUMMARY

Numerous studies conducted during the past decade show that climate change is most likely attributable to increased concentrations of anthropogenic greenhouse gases producing effects on climatic patterns. Under this new and changing situation, forest management and policies require new approaches that take into consideration the effects of climate change.

In recent years, governments, institutions, and NGOs in Lebanon are making huge efforts to carry out reforestation programs throughout the country. Taking into account the future potentiality of species currently used in reforestation by placing them under different climate change scenarios is a useful tool to understand which species will thrive in future conditions.

For this purpose, almost seven thousand points of presence and twelve thousand points of absence were identified in Lebanon. Ensemble projections for each species were obtained by adding climatic variables for current conditions and running models with Biomod2 R-package platform for future scenarios.

This study shows the Species Distribution Model for 2050. It takes into account twenty main native species commonly used in Lebanese reforestation, and places them under A2 and B1 IPCC scenarios. In addition, vulnerability classification of Lebanese territory was conducted in terms of species richness loss caused by climate change. This determines the critical areas to be restored and/or protected in terms of species diversity.

Finally, general guidelines for future management and measures for adaptation and mitigation to climate change are proposed for each species and case of potentiality status in the future. In terms of potential species richness loss, specific actions are set for the considered critical areas.

The generated maps and raster files will help the forest manager in decision-making regarding the priority areas for restoration or management and the potential species to be used considering the future effects of climate change.

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 6

1. INTRODUCTION

According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2007), climate change is unequivocal and most likely attributable to increased concentrations of anthropogenic greenhouse gases. The same report relates warming for the last three decades to the changes in many physical and biological systems at a global level. Forecasts suggest the effects will persist in the future.

This new and changing situation requires forest policies and management to be reoriented towards species adaptation to climate change. In Lebanon, where global models predict severe climate change and where numerous species grow in one of the most biologically diverse ecosystems, the Mediterranean forest, the knowledge of future climate behavior is an important management tool for the preservation of natural resources.

Therefore, priority should be to expand the knowledge of the vulnerability to and impacts of climate change on Lebanese species richness, so that adaptation can be designed and integrated into policy planning and management of biodiversity. It is with this knowledge that the actions for preservation in a world of changing climate will have the highest impact. However, it is important to keep in mind that the success of any adaptation measures will eventually be conditioned by the correction of the climate-altering causes.

Overall, this work analyzes the potential effects of climate change on key vegetal components in Lebanese ecosystems. It has been carried out with the best available knowledge on climate projections for the 21st century, taking into account the current distribution of target species.

This work aims at supporting the national reforestation program launched in 2010 by the United States Forest Service (USFS) office of International Programs (IP) through the support and funding of the United States Agency for International Development (USAID), implemented through the Lebanon Reforestation Initiative (LRI). This project also continues the collaborations between IDAF and LRI that started in 2012 regarding climate change and species richness.

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 7

2. OBJECTIVES

2.1 GENERAL OBJECTIVE

The identification of key areas to be restored and adapted to climate change effects, securing the level of biodiversity, setting a vulnerability classification of Lebanese territory in terms of species richness loss caused by climate change and development of ensemble projections under different climate change scenarios.

2.2 SPECIFIC OBJECTIVES

• Assessment of species richness in Lebanon determining the areas that could sustain more biodiversity than their current status;

• Identification of key areas that will lose more species richness due to climate change;

• Development of ensemble projections under different climate change scenarios (present till 2050) for each selected species, up to a total of around 20 species including endemic and indicator species if possible;

• Proposition of possible treatments and actions to be implemented, aiming at improving the adaptation of these species in key areas.

For this purpose and due to the scope of this project, twenty of the most important species for forest restoration in Lebanon have been assessed:

• Abies cilicica • Juniperus excelsa• Acer syriacum • Juniperus oxycedrus• Acer tauricolum • Pinus brutia• Arbutus andrachne • Pistacia palaestina• Arceuthos drupacea • Prunus ursina• Cedrus libani • Pyrus syriaca• Ceratonia siliqua • Quercus calliprinos• Cercis siliquastrum • Quercus cerris• Crataegus spp. • Quercus infectoria• Cupressus spp. • Styrax officinalis

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 8

3. METHODOLOGY

3.1 SCOPE

The study area covers the entire territory of Lebanon, ranging up to 10,452 Km2. The spatial resolution of the results is 1 Km2, derived from the characteristics of the climatic raster files used in this study. Presence/absence and current/future potentiality of species has been developed for a grid of 1 x 1 km.

3.2 SCHEME OF WORK

In order to generate ensemble projections, models for the twenty selected species, climate variables, and points of presence/absence were gathered. After treating data, future models were run using a script designed with Biomod2 R-package under A2 and B1IPCC scenarios.

Current and future Species Distribution Models (SDMs) for species potentiality were obtained. A potentiality threshold was calculated for each species depending on whether it is a generalist species or a species with specific needs. The Model also takes into consideration whether the identified presence points are spread throughout the entire potential distribution range of the species or conversely, if the species grow in relict populations without covering all environmental variability. Using this threshold, classified maps of potential/non-potential areas were obtained.

Depending on the possible combinations of potentiality status in current and future scenarios, maps of management guidelines per species were proposed.

To assess vulnerability classification of the Lebanese territory, species richness maps were developed for current and future scenarios. The maps show the number of species that could potentially occur on each cell. Maps of potential loss/gain species richness were generated by subtracting future predictions from current status in both scenarios.

Once these maps were developed, critical areas were identified by making the arithmetic mean of both future scenarios and segmenting the resulting map into severe, important, and moderate classes by applying 75th and 90th percentiles. Areas where severe or important loss occurs are considered critical areas for adaptive management and restoration. Figure 1 shows the flowchart of this study.

Figure 1. Study Flowchart

 

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 9

4. CLIMATE VARIABLES

4.1 CURRENT CLIMATE VARIABLES

Current climate data were obtained from WorldClim (Hijmans et al., 2005), a set of global climate layers with a 30 arc-second spatial resolution generated through interpolation of real data from weather stations for the period 1950 - 2000.

Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These variables represent annual trends (e.g., mean annual temperature, annual precipitation), seasonality (e.g., annual range in temperature and precipitation), and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A total of 19 bioclimatic variables were used.

In addition to this, a new set of variables was generated clustering climatic information in seasonal periods, obtaining the minimum, maximum, and average temperature of each season and seasonal total precipitation.

The species distribution models were built upon the bioclimatic variables. These models were used to obtain the current potential surface.

4.2 FUTURE CLIMATE VARIABLES

To obtain more significant climatic variables, a mixed climate model was generated from predictions made by CCCMA-CGCM3 and ECHAM5 global models.

Once the model is defined, the conditions of the factors influencing climate evolution (i.e. the emission scenarios) should be determined. There are four families of scenarios defined by the IPCC (Intergovernmental Panel on Climate Change): A1, A2, B1 and B2. Each one is a combination of demographic, social, economic, technological, and environmental trends.

A2 and B1 scenarios were selected for this study, representing unfavorable conditions and less climate change impact respectively.

The horizon for the prediction of potential distribution is 2050.

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 10

4. CLIMATE VARIABLES

4.3 VARIABLES SELECTION

Collinearity analyses were run to eliminate repetitive variables with a strong correlation. The correlation coefficient and the variance inflation factor (VIF) were calculated. The analysis of collinearity was done within the full list of original variables. Variables with R2>0.90 and VIF>9 produced a poor estimation of the correlation coefficient due to collinearity and were deleted (Graham, 2003; Heikkinen et al., 2006).

Three common non collinear variables were selected:

• Winter minimum temperature; • Summer maximum temperature; • Summer precipitation.

For further information regarding climatic variables and statistical analysis, see Annex I.

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 11

5. SPECIES DISTRIBUTION MODELS (SDM)

The variety of techniques accessible to model species distribution can be classified in three groups, depending on the input data:

• Profile techniques which require species presence-only data (i.e. environmental hype-space inhabited by species methods as BIOCLIM, among others);

• Discriminative techniques which require species presence-absence data (i.e. General Linear Model (GLM), Maximum Entropy (MaxEnt), among others);

• Mix modeling approach which uses combined techniques (i.e. Biomod, among others).

To deal with model technique election, Biomod2 R-package (Thuiller et al., 2013) which includes ten SDMs techniques was selected for this assessment. Default settings of biomod2 (version 2.1.15) were used. Biomod2 R-package is a computer platform for developing ensemble SDMs, which works with presence-absence data.

In order to select the most accurate SDM and avoid drawbacks of different individual statistical models, only ensemble models obtained from the linear combination of the ten models evaluated by R-package biomod2 were used.

Models were run ten times per each species and only those that presented higher statistical parameters in all cases were selected. The final SDM was obtained by assembling selected models.

Obtained SDMs are graphical representations of the probability of the presence of a species in a particular geographical location. Each pixel represents the percentage of probability of presence for the species. In order to assist managers in decision making, these maps were reclassified indicating the probability threshold of the species.

This limit is calculated separately for each species from different statistical methods. The choice of appropriate statistical method depends on particular characteristics of the species distribution, the dispersion of its points of presence and absence, and their distribution on the generated model.

See Annex II for SDM detailed information.

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 12

6. IDENTIFICATION OF SPECIES PRESENCE / ABSENCE

The R-package requires information about current species distribution within the study area. For each species, points of presence were georeferenced. The number of points referenced was dependent on site accessibility, species populations, and security risks. Collection was spread throughout Lebanon and, absence points were evenly distributed in areas presenting unfavorable conditions for species to grow.

Spatial data resolution was respected while establishing presence/absence points by setting only one point per species inside each 1 x 1 Km2 cell; the same spatial resolution as the climatic data grid.

Points of presence were sampled on the field identifying as many populations possible for each species. To reach areas not accessible by vehicle, field trips were designed covering large areas through dense forests and riversides. A large amount of points were obtained with GPS devices. After processing and downloading points to a GIS platform, cells of the 1 x 1 Km2 grid were analyzed to ensure that only one point per species was located inside each cell. By using recent orthophotos of Lebanon, homogeneous forest areas were located and additional points of major species were set nearby sampled areas.

In areas not accessible due to the political situation, historical records and analysis of high-resolution images such as Google Earth or Bing Maps were studied. Interviews were conducted with botanical experts in Lebanese flora. Pictures taken in situ by locals were also analyzed to identify species occurring in these remote areas.

A total of 6,767 points of presence and 11,851 points of absence were set. Figure 2 shows the main location where points of presence were identified.

Figure 2. Principal Locations for Presence Points

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CLIMATE CHANGE IMPACTS ON NATIVE TREE SPECIES DISTRIBUTION IN LEBANON: POTENTIALITY PROJECTIONS TO 2050 13

7. SPECIES POTENTIALITY

7.1 OBTAINED RASTER FILES

Attached to this document are the raster files. Metadata can be delivered on computer format. The information found in these files is listed below:

• Metadata file identifier • Language • Character set • Contact • Metadata date stamp • Metadata standard name • Metadata standard version • Spatial representation information • Identification information • Distribution information • Application schema information

7.2 OBTAINED SPECIES DISTRIBUTION MODEL

The following maps show the current potentiality for the studied species versus the expected future potentiality in 2050.

The map legend shows the points of presence/absence identified for the species, the potential threshold and the total potential surface for present situation under both B1 and A2 scenarios.

These maps are classified into six different potentiality classes expressed in percent. In some cases, potentiality threshold is located within the range of values of one class and the limits of potential areas are not defined clearly. For classified maps showing potential or non-potential areas for the species without discerning between potentiality ranges, see Annex III.