The importance and causes of farmland heterogeneity

William Sutherland (Zoology, Cambridge)

With: Eric Audsley (Cranfield), Alison Bailey (Reading), Ira Cooke (Cambridge),Rob Freckleton (Sheffield), Anil Graves (Cranfield), Elizabeth Mattison (Reading), Joe Morris (Cranfield), Simon Queenborough (Sheffield), Daniel Sandars (Cranfield), Gavin Siriwardena (BTO), Phil Strachan (Primeag), Paul Trawick (Cranfield), Andrew Watkinson (UEA)

Conceptual framework

Climate, location, soil type etc.Social, economic, legislative and technical changes

Profitability of different farmer actions

Changes in farm management

Bird and mammal populationsWeed abundance

Physical structure e.g. hedges

Social aspects

MANAGE LAND AS YOU SEE FIT

Length of hedge (m)

Woodland area (ha)

Skylark plots (no.)

FBI bird species observed (no.)

Skylarks seen (no.)

Tall weeds(no. m-2)

Other weeds(no. m-2)

Appearance of land

Land-based income

£ year-1 from cropping +

subsidy + land-based

diversification less variable

and fixed costs

Risk

Absolute deviation in land-based income (£)

Lifestyle

Time off from core farming activity ( no. days year-1)

Recreational shooting (no. days season-1)

Management complexity

No. different crop types managed

No. different agri-environment options managed

Autonomy

No. different

regulatory constraint

sets adhered to

Measures

Objectives

Overall objective (decision context)

Approach:

Collect data on farmers’ land-use objectives using Multi-Attribute Utility Theory to describe preferences and trade-offs between multiple objectives

Hierarchy of Objectives

FBI = Farmland Bird Index

Coeff. of variation

0.100.620.660.750.730.670.880.810.980.931.031.171.571.57

Mean raw weightsn = 47; coeff. of var. = std. dev./mean

Temporal changes...

Breeding Bird Monitoring

• JNCC/BTO/RSPB Breeding Bird Survey (BBS)– 880 squares random lowland arable

squares in 2007– Bird abundance (31 species)– Habitat data: %landscape cover (e.g.

arable, wood), boundary features, cropping

1 km

100m

25m

Other variable types* 5 18 21

* >1 variable set equally important for some species

Landscapes Cropping Field boundaries Controlling for…

NO. OF SPECIES: Most important habitat variable sets

17 9 5 Geographical area only

Pareto optimal trade-offs between profit and overwintered stubble area showing the effect of location

0

50

100

150

200

250

£0 £10,000 £20,000 £30,000 £40,000 £50,000 £60,000 £70,000 £80,000 £90,000

Net farm profit, £/ 250 ha

Are

a o

f cr

op

res

idu

es s

urv

ivin

g

bey

on

g m

id F

eb.,

ha/

250

ha

Heavy clay, 670 mm annual rainfall Sand, 540 mm annual rainfall

Overwintered crop residue area, ha/ 250 ha of land in arable farming systems

Arable NUTS4

STUBBLE_AR / none

Not Modelled

0 - 4

4 - 8

8 - 12

12 - 16

16 - 20

20 - 24

24 - 28

28 - 32

32 - 36

Effect of set-aside on the cropping landscape

How will set-aside loss affect bird populations?

Rel

ativ

e ch

ange

Species

Agrochemical companies

Agronomic advisors

Arable farmers

Bird spotters

Butterfly Conservation

Contractors

CPRE

Defra

District CouncilEnglish Heritage

Farm Machine Companies

Farming Journals

FWAGGame Conservancy Trust

General Public

HGCA

Land ownersLocal community

Local Council

Millers

National Trust

Natural England

NFU

Plant Breeding Companies

Plantlife

RSPB

Supermarkets

Treasury

Wildlife Trust

CLA

BTO Life

EU DG Agriculture

Game keepers

Birdlife International

LEAF

WTOCrop Protection Association

Influence

Inte

res

t

Key Players

Context settersCrowd

Subject

Slide 2: Interest influence framework in terms of the question, which stakeholder have influence in and interest over farmland bird populations in the UK. In many respects this boils down to consideration of which stakeholders have interest in and influence over agricultural land in the UK…..