PowerPoint Presentation · Accountancy Data Network (FADN) data and wider literature on farm ... farm type, and translated by project partners into English for analysis. Farmers will

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• Agriculture accounts for 1.7% of Gross Value

Added (0.5% in GB and 2.5% in ROI)

• Agri-Food accounts for 4.4% of total employment

• 1 million ha of agricultural land (80% of land area)

• Grassland accounts for 93% of agricultural land

• 70% of NI agricultural land is LFA

• 25,000 farms with an average size of 41ha

• NI accounts for 15% of UK dairy & beef production

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• What type of environmental public goods should be prioritisedfor delivery by land managers in the future?

• How can land managers be encouraged and helped to deliver those public goods effectively?

• What mechanisms are available for rewarding land managers for the provision of public goods?

• What changes in policy or governance are required?

Kirton Glen Scenarios:1. “Historic” (1995)

2. “The Present” (2018)

2040 Scenarios:

3. “Re-wilding/Abandonment”

4. “Woodland Expansion”

5. “Integrated Land Management”

Holland & McCracken (2018). Exploring the Perceived Impacts of Different Management Scenarios on Ecosystem Goods and Services from Two Highland Glens.

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Hein ten Berge - WR Marija Klopčič - UL

Lynn Frewer - UNEW Francis Lively - AFBI

Dina Lopes - CONSULAI

WP1 & WP7 – Management & Ethics requirements

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Hein ten Berge (WUR) and (sub)task leaders

Five biogeographical regions in Europe

Source: https://www.eea.europa.eu/data-and-maps/figures/biogeographical-regions-in-europe-1/map_2-1_biogeographical-regions.eps/image_large

Continental (incl. Pannonian)

Different grassland types due to variation in:

• Climate (biogeographic regions)

• Altitude and slope

• Soil fertility and water availability

• Farm management (cutting/grazing, type of animals fertilization) → farming system (often with a long tradition)

• Presence of trees, hedgerows, water courses etc.

• Fire management

• And many other management options

What?: intensely used grassland, only cutting, no grazing,most common type of permanent grassland in DE

Vegetation: approx. 5-10 species, rich in ryegrass & white cloverManagement: 4-5 cuts, fertilization liquid manure, mineral NAgronomical value: Biodiversity value:

How common?

Challenges: nutrient losses, upper limits for fertilizer, loss of valuable forage species, increase of weeds

Examples from Germany,

focussing on value and challenges

What? lowland & mountain hay meadows (Natura 2000)Management: 1–2 cuts (hay), no fertilizer Agronomical value: Biodiversity value:

How common?

Challenges: management restrictions (Natura 2000): no grazing allowed, late cutting date → low forage quality, no fertilizer → low yield

What? „jewels“ of nature conservation´, here: dry calcareous grasslandManagement: very extensive grazing or one cutAgronomical value: Biodiversity value:

How common?

Challenges: high costs of conservation due to poor agronomical value,lack of farmers/suitable livestock in the region

WP2 objectives and approach

• Identify important functions that PG provide

• Define what needs to be done to ensure optimal delivery of these functions

STEPS:

• Agree on EU wide Grassland Typology -> field manuals

• Define corresponding PG based Farming Systems (geography; management)

• Document ES for different PG types and Farming Systems

• Seek management approaches and emerging technologies to ensure / enhance ES delivery

• Assess their feasibility in transdisciplinary SH workshops

• Find AE indicators for benchmarking performance in farmer networks

Summarize what PG can deliver in different circumstances, and how this can be achieved

Site conditions

soil, climate, slope, …

Vegetation Management

Biodiversity &

Pollination

Carbon

storage

& GHG

Flood &

Erosion controlLandscape &

RecreationWater quality

Productivity /

Forage quality

Specific location

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Biodiversity and pollination

• What are the most abundant crops (per unit area) that rely on insect pollination in Europe? Wheat (33% of land area, Barley 13% and then Sunflowers 9%

• Both placement and abundance of pollinators are important

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0,02

0,04

0,06

0,08

0,1

0,12

% farmed crops in Europe (includes all crops) – taken from FAO data for 2016 (latest year for which data

available)

Carbon sequestration and GHG

a. b. c.

Simulated change in soil carbon stocks due to all land use changes occurring in Scotland 2000-2009. Change due to (a) conversion of grassland to arable (b) conversion of arable to grassland and (c) all land use changes. White area = no land use change. Smith et al. (2010a)

Flood and erosion controlFlooding

PG in UPLANDS versus LOWLANDS

increased water storagein soil reservoir, quantify via SWHC

possibility to floodgrasslands, versus oncroplands where floodingleads to extensive cropdamage

UPLANDS

LOWLANDS

Water quality(here N surplus)

Landscape and recreation

sports

Involving observing participants without active participation

PHOTO-SERIES ANALYSIS

NON-PARTICIPATORY AND SPATIAL EXPLICIT METHODS:

aestetics

education

tradition

Classifying and evaluating photos

Spatial distribution of photos

Biomass for feed and feedstock

Transdisciplinary workshopsTo discuss technical feasibility of ES delivery with farmers and experts (famer representatives?)

• The feasibility of management options will be investigated in in facilitated transdisciplinary workshops• MCDA EXPERTS (multi-critreria decision analysis/or multi-criteria mapping )

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• Delphi (farmers)

• In EACH of the biogeographic zones

• Continental/Pannonian

• Mediterranean

• Boreal

• Alpine

• Atlantic

• NB. Slovenia is a mixed Zone so groups will be mixed.

• Expert workshops will deliver a set of outcomes and conclusions

• Outcomes and conclusions tested in a set of face-to-face interviews (N=10 in each bioclimatic zone.

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WP3: Benchmarking and Testing

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WP3: Objectives

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WP3: Benchmarking & Testing

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1 1

C, O

3 2

C, O

3 1

C, O

1 1

C, O

1 -

C, O

2 -

C, O

1 3

C

2 3

C, O

1 1

C, O

2 1

C, O

Networks

Conventional (C) or

organic (O) networks

Experimental

platforms

3 2

C, O

Livestock

typeBiogeographic region Country

Sheep Alpine, Cont, Med,

Boreal, Pan, Atl

CH, SI, UK, SE, FR, ES, PT,

HU, ME, NL, DE

Dairy Alpine, Cont, Med,

Cont, Atl, Boreal, Pan

CH, SI, IT, NL, UK, FR, SE,

CZ, PT, HU, ME, DE, PL

Beef Alpine, Med, Boreal,

Cont, Atl

CH, SI, IT, UK, SE, ES, PT,

PL

Pigs Med, Alpine ES, PT, SI

Horses Alpine, Cont, Boreal DE, SE, SI

Goats Alpine, Cont, Med SI, PT

1 -

C- 1

C

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C, O

x x

C, O

Task 3.6. Road Testing

Lead partner: UL

• Examples of potential innovative practices and integration of new knowledge and technologies related to PG and ES are:

• Applying various grazing systems to improve productivity, grass utilisation and the delivery of other ES (e.g. C sequestration)

• Demonstrating and validating the use of canopy sensing to monitor grass growth and quality

• Testing virtual fencing for more flexible razing management

• Using a variety of seed mixes including deep-rooting herbs and legumes to investigate the potential to increase productivity in low input systems and tolerate drought and/or waterlogged conditions

• Applying certain grassland related management practices to reduce GHG emissions

• Dealing with poisonous plants

• Providing enhanced pollination

• Managing large herds with grazing

• Combining robotic milking with grazing

• Executing specific eco-services related to grassland

1st Stakeholders’ SeminarSustainable Permanent Grassland

Farming Systems & Policies

12th December 2018Europa Hotel, Belfast, Northern Ireland

WP 4. Securing [email protected]@lynnfrewerWP Lead: UNEWPartners ADAS; MENDU; UOM; SLU; WR; ETH Zurich; UCO

1st Stakeholders’ Seminar | 12th December 2018 | Europa Hotel, Belfast, Northern Ireland

WP 4. Securing performance

Overall Objective. To develop and validate methods for securing PG performance.

• Secondary objectives.• 4.1 To assess socio-economic facilitators of, and barriers to, adoption of sustainable PG

systems in different biogeographic regions• 4.2 To provide evidence for, and develop, policy options to support PG management in

each biogeographic region• 4.3 To maximise research impacts through knowledge exchange and consultation with

key stakeholders and end-users • farmers• land owners/managers and their advisers• third sector and civil society groups• non-governmental organisations• researchers• policy and business representatives

Comparative analysis of Socio-economic issues across

5 biogeographic regions addressed in SuperG

Farming System Within conventional systems

Atlantic Low input

AlpineConventional

Boreal High input

Continental/Pannonian Organic

Mediterranean

Task 4.1. Reviews of existing knowledge, policies and gap analysis

Task 4.1.a. Review of facilitators of, and barriers to, adoption and choice of PG management options to deliver specific ES (lead UNEW)

Systematic review of the peer reviewed literature

• To assess the intrinsic (e.g. benefits to nature and ecology) and extrinsic (e.g. benefits to economic functioning of agriculture) value of PG ES in Europe.

• To understand what motivates or constrains farmers and land management options to target ES delivery

• To assess common or conflicting interests of societal actors (e.g. citizens, researchers, policy makers, businesses, and third sector organizations).

• To assess the biophysical factors perceived to be relevant.

Task 4.1.b Economic drivers of farmer adoption

• A systematic review of the peer reviewed literature and meta analysis of the economic factors linked to European farmer adoption, or non-adoption, of sustainable PG systems, approaches and technologies, including the role of financial incentivisation.

• The analysis of farm household incomes in PG systems will use Farm Accountancy Data Network (FADN) data and wider literature on farm diversification and off-farm income.

• Comparisons between biogeographic regions and farming systems will be applied

4.1.c Review of existing policies and impacts.

Will review current policies including those focused on abandonment or cultivation, being applied to promote PG management for ES delivery.

• Policy documents are likely to be published in local languages, the review must be conducted by partner countries within each of the Superg biogeographic regions

• UNEW-Atlantic

• UCO-Mediterranean

• ETH-Alpine

• MENDU-Continental/Pannonian

• SLU-Boreal

• Combined internet based search and semi-structured interviews with national policy stakeholders (n=10 in each country will be applied to evaluate the effectiveness of existing policy measures.

• This will include a meta-evaluation of Rural Development Policies across the EU

• Instruments

• direct payments,

• agri-environment (e.g. PDI/PDO)

Task 4.2 Farmer priorities and preferences for ES in relation to PG

Interviews will be conducted “on farm” within each region, ensuring distribution between farm type, and translated by project partners into English for analysis. Farmers will be recruited via the networks the project interacts with and be representative of the countries and regions

Lead partner: ADAS.Participants: UNEW, ADAS, UCO, ETH Zurich, MENDU, SLU

4.3 Citizen priorities and preferences for ES in relation to PG

• Focus group interview protocols to assess citizen’s preferences and priorities regarding the adoption of ES in PG

• Younger study participants in rural communities will be specifically targeted through Rural Youth Europe, given the issue of rural-urban drift and potential for future rural depopulation.

• Qualitative methods development workshop will be held in Cordoba in month 13, involving all WP 4 partners.

• Quantitative survey (from focus group outputs)

• Quantitative methods development workshop will be held in Mendel University, month 24, to develop the survey.

• Quota sample on the basis of age, gender, socio-economic class and rural versus urban residency

• Subcontracted data collection

500 citizens in each of • Czech Republic, Spain, Sweden, Switzerland, UK

4.4. Developing policy options for ES

Assesses policy option (e.g. education and information dissemination, coproduction of policy options, legislation, regulations, taxes and subsidies) that encourage ES services.

• Maximise pathways to impact.

• Stakeholder workshops and surveys starting month 36.

Farm/Farmers

Government

Facilitators

Optimized E.S.• In each region

• That understands

intrinsic/extrinsic values for

stakeholders

• And technology readiness levels

• That balances social,

economical, bio, and env.

interests

Farm/Farmers

Socio-Economic

Bio-Environm.

RQ: What drives stakholders to

optimize E.S.?

RQ: How to optimize E.S.?

RQ: What is the impact of

”improved” E.S.?

• Economic-e.g. profits, subsidies

• Social-e.g. status

• Personal-e.g. identity

• Education-e.g. field guides

DSTs & Policy

Instruments

• Economy

• Well Being

• Sustainability

• Society

• Etc.

• Increased/decreased profitability

• Env. footprint

• New identity

• Etc.

• Health

• Revenues

• Lifestyle

• Etc.

• Diversity

• Sustainability

• Env. Footprint

• Etc.

• Education

• Tools to help facilitate

• Personal-e.g. identity

• Evidence base

• Education

• Field guides

• Education

• Financial incentives

• Knowledge portal

• Etc.

RQ: What tools should we develop & which policy instruments should we encourage to sustainably reinforce optimal E.S.

Acknowledgement. Erik Hunter, SLU

WP4

WP

4,5,6

WP 4,5,6

WP 2, 3

WP

4,5,6

WP 2, 3

WP 4

WP 7. EthicsLeads UNEW. Partners ADAS SLU, WUR• Ensures all activities are in line with ethical codes of research

conduct, including application of GDPR

• Advisory board.• Chair. Professor Bart Gremmen (WUR)• Members. Dr Paul Newell-Price (ADAS)

Professor Lynn Frewer (UNEW)Professor Per Sandin (SLU)

Thank you for your attention!

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Workshops to identify what farm tools should be developed

What DSTs are required?

What existing data sets could be

utilised?

What media should be used?

Cost / value to end user

Labour requirement to use

tool

Deliverable:Set of requirements for a

selection of DSTs that farmers & advisors want

• Web• Excel• Smart phone app• Paper based

• Herd inventories• Field inventories• Aerial / satellite

images

Workshops to identify what policy tools should be developed

Identify main policy issues

What existing data sets could be

utilised?

Consider linkages between farm &

policy tools

Deliverable:Set of requirements for a DST that would achieve maximum policy impact

• Register of designated sites

• Herd inventories• Field inventories• Aerial / satellite

images

Development of farm level and policy DSTs

Co-innovation workshops

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• Fig. 1: 2018 GrassCheck farm network

Latest info available at agrisearch.org/GrassCheck

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Discussion

HEIN TEN BERGEWUR

MARIJA KLOPČIČUL

LYNN FREWERUNEW

FRANCIS LIVELYAFBI

PAUL NEWELL PRICEADAS


Outline of working group session & topics

SANTA CLAUSESGROUPFRANCIS LIVELY

GINGERBREAD MENGROUPRUI ALMEIDA

XMAS PUDDINGS GROUPHEIN TEN BERGE

REINDEERSGROUPJASON RANKIN

PENGUINSGROUPJOHN WILLIAMS


How can SUPER-G:

Be useful to your organisation/sector?

i. In raising the profile of what grassland farmers do for society

ii. In helping identify suitable policies to support farmers in protecting and managing PG

iii. In improving the awareness and availability of relevant decision support tools for grasslandfarmers, advisers and policy makers

iv. Other aspects?


How can SUPER-G:

Apply in your country/region?

Considering:

i. The different types of:

o PG you have in your country/region

o farm you have in your country/region

ii. The policies you have to protect PG or influence management


How can SUPER-G:

Improve PG management?

In terms of:

i. Productivity and business viability

ii. Supporting biodiversity

iii. Delivering other ecosystems services(providing clean water, storing carbon, reducing flooding risk, enhancing landscape,etc.)

iv. … and what are the most important aspects of (or tasks within) SUPER-G that will helpto achieve this?

Lunch time!

Documents

PowerPoint Presentation · Accountancy Data Network (FADN) data and wider literature on farm ... farm type, and translated by project partners into English for analysis. Farmers will