CONFLICT IN CONSERVATION AND MANAGEMENT OF WILDLIFE: CONNECTING ECOLOGICAL AND SOCIO-ECONOMIC DATA

ACROSS EUROPE

Jeremy J. Cusack and Nils Bunnefeld

www.sti-cs.org @bunnefeld

Acknowledgements

•  Sarobidy Rakotonarivo

•  Brad Duthie

•  Tom Mason

•  Rocio Pozo

•  Johan Månsson

•  Lovisa Nilsson

•  Rae McKenzie

•  Ingunn Tombre

•  Jesper Madsen

•  Gail Churchill

•  Richard D. Hearn

ERC funded ConfooBio project (2016-2021)

Conservation conflicts and their management

“situations that occur when two or more parties with strongly held opinions clash over conservation objectives and when one party is perceived to assert its interests at the expense of another” (Young et al. 2010; Redpath et al. 2013)

Wildlife impacts Conflict between stakeholders

MANAGEMENT •  Mitigation strategies •  Population control •  Compensation

•  Dialog •  Participatory approaches •  Shared solutions

Is management effort adapted to current wildlife impact levels?

• Stakeholders expect managers to make decisions that match changes in wildlife impact levels with changes in management effort (e.g. harvesting quotas)

• Expected to result in a degree of synchrony between the two

Why is this important?

•  Adaptive management of conflicts relies on good monitoring (Bunnefeld et al. 2011)

•  Perceived delays or deficiencies in the implementation of management actions by affected stakeholders (e.g. farmers) may strengthen negative attitudes towards wildlife conservation (Olsen et al. 2015)

•  Delayed management actions can have unintended and potentially detrimental effects on wildlife population dynamics (Fryxell et al. 2010)

Large grazing birds and farming in Europe

•  Exponential growth and expanding distributions in recent decades

à Improved conservation status

•  Widespread conflict with farmers along flyways and at staging sites

à Calls for management of impacts on crop production

•  Development of management schemes

à Vary in spatial scale and component strategies

Case studies – time series

N

Denmark(SPFG)Norway(SPFG)Vesteralen county(SPFGandSBG)Orebrocounty(CC)Orkneyarchipelago (GG)Islay(GBGandGWFG)

Orkney, Scotland •  Greylag goose counts •  # hunting licenses

Islay, Scotland •  Barnacle and white-

fronted geese counts •  Winter hunting bags •  Compensation per

scheme participant •  Scaring expenses

Vesterålen, Norway •  Pink footed and greylag

geese counts •  Amount per subsidy

application

Norway flyway •  Pink footed goose

counts •  Winter hunting bag

Denmark •  Pink footed goose

counts •  Winter hunting bag

Örebro, Sweden •  Common crane counts •  Compensation per

damage report

•  Long-term synchrony

à Model trends using GAMMs

•  Short-term synchrony (year to year)

à Measure of synchrony borrowed from community ecology (Loreau & de Mandelbrot 2008) resulting in a measure between 0 (asymmetry) and 1 (symmetry )

•  Test for time delays of 1, 2 or 3 years in short-term synchrony

Methods – long and short-term synchrony

Results – population trends

•  Exponential growth for many populations

•  But recent stabilisation and declines

•  Possible effect of some geese on others (e.g. barnacle goose)

Long-term synchrony •  Most count and

management trends random or asynchronous over time

•  Only synchronous in

the case of hunting bags in Denmark, but rate of increase in hunting bag high with reference to population count

and dark bands

show synchronous and asynchronous time steps

Denmark Norway Islay

Orkney Vesterålen Islay

Örebro Örebro Islay

Short-term synchrony •  Contemporaneous

synchrony only for hunting bags in Denmark and Norway, and compensation in Vesterålen

•  Time lag of one year for

hunting bags on Islay, but up to 3 years for compensation or scaring effort

•  No short-term synchrony

in other case studies

Making predictions and decisions for future management Generalised Management Strategy Evaluation (GMSE)

modell ing

R-package “GMSE” https://sti-cs.org

a) geese in landscape b) land ownership c) population size d) agric . yield e) manager policy f) user (farmer) action Manager and user decisions can create unstable and fluctuating populations

Key points

•  Random associations between management effort and population counts are common

•  Potential to influence social conflicts surrounding wildlife impacts

•  Synchrony and asynchrony needs to be considered in the context of specific management aims, but randomness is not a good sign

•  Case studies in which management is supported by predictive models do better

•  Even more important now that many populations showing decline

www.sti-cs.org @bunnefeld