Ecology and Society (Mar 2021)

Management of high nature value farmland in the Republic of Ireland: 25 years evolving toward locally adapted results-orientated solutions and payments

  • James Moran,
  • Dolores Byrne,
  • Julien Carlier,
  • Brendan Dunford,
  • John A. Finn,
  • Daire Ó hUallacháin,
  • Caroline A. Sullivan

DOI
https://doi.org/10.5751/ES-12180-260120
Journal volume & issue
Vol. 26, no. 1
p. 20

Abstract

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The effective conservation of high nature value farmland (HNV) will be crucial for the conservation of European and Irish biodiversity, and to meet the growing demand for a wide range of private and public goods and services from farmland. Here, we describe the evolution of policy and management of HNV farmland in the Republic of Ireland over the last 25 years and describe the emerging locally adapted, results-based payment approach that is valorizing a broad range of ecosystem services from these areas, which helps to underpin the future social, ecological, and financial viability of HNV farmland. HNV farmland in the Republic of Ireland covers approximately 33% of the agricultural land, and 50% of these areas coincide with Natura 2000 land. A broad diversity of landscape types dominated by seminatural vegetation from upland areas to lowland areas is a key challenge when designing policy support for HNV farmland areas. To date, action-based agri-environment schemes have struggled to adapt to these conditions, and to provide sufficient incentive and flexibility to deliver the desired environmental outcomes. In response, several projects and programs have implemented results-based payments, which we illustrate using three case studies from the Burren Programme, the Results Based Agri-environment Pilot Scheme (RBAPS), and European Innovation Partnership Operational Groups: The Hen Harrier and Pearl Mussel Projects. We highlight choices in the design and implementation of these case studies that aimed to better achieve the environmental objectives. We conclude with general lessons from the Irish experience with results-based approaches, and how they may be scaled up for wider implementation.

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