A contract will be awarded for the out-sourcing of a series of Farm Inspections in various “At Risk” catchments in Co. Donegal.
The specification may include carrying out of Integrated Catchment Management (ICM) and Investigative Assessment in certain agricultural catchments, as required.
The Department of Housing, Local Government and Heritage has allocated some short-term funding to local authorities to increase efforts to deal with several water quality pressures in high risk water bodies, the largest of which is agriculture, under the 2nd River Basin Management Plan and continuing into the 3rd cycle plan yet to be published.
As a first step, an increased programme of agricultural inspections will be compiled and commenced in these water bodies in the coming months. The resources for this work will be drawn from the private sector and this contract is for the engagement of suitably qualified contract staff to carry out the required inspections in various catchments within Donegal County Council’s functional area.
These inspections will focus primarily on farmyards and compliance with the Good Agricultural Practice Regulations, eg – slurry storage, silage pits, manure pits/dungsteads, minimisation of soiled water, drains and adjacent water-courses, including cattle access and farm roadways.
Initial planning, selection of sites and follow-up actions, including enforcement will be carried out by local authority staff. The Council will draw up a weekly programme of inspections in a small number of “at risk” catchments and these will be completed by the contract staff using a pre-set inspection template and recorded in electronic format. Farms to be inspected will include the full range of farm types, including, dairy, sheep and mixed farms.
Agri-Climate Rural Environment Scheme (ACRES)
Scope of services to be delivered by the successful tenderer in support of CAMG
3.1 Nature of services to be delivered
3.1.1 Development of modelling tools to assess the emissions reduction impact of national policy on the Agriculture Sector and Land Use, Land Use Change and Forestry (LULUCF)
The successful tenderer will be expected to develop and maintain an Ireland-specific land balance model to identify national agriculture and land use pathways to climate neutrality.
This model should be capable of undertaking comprehensive integrated scenarios of agricultural activities and land use combinations within biophysical constraints (for example available land area, livestock productivities, fertiliser-driven grass yields, forest growth rates, wetland and peatland rehabilitation) with an emphasis on biophysical linkages across food production, GHG emissions, and carbon sinks at a national level.
This will involve:
- ensuring the model is available on an ongoing basis as an operational modelling tool for scenario analysis to inform ongoing developments in national Agriculture and LULUCF, air quality, climate and energy policy;
- regularly improving the model to incorporate new information and requirements, for example, bioenergy production, spatial optimisation for modelled Agriculture and LULUCF scenarios and
- differing predicted climate conditions,
- incorporating, on an ongoing basis, updates of relevant sectoral, policy and macro-economic data, including prices, technologies and programme-specific data.
This model should be capable of the following minimum outputs:
- development and maintenance of annual national scenarios, aligned with official EPA inventory and projections data;
- defined alternative national scenarios to explore the interactions and synergies between Agriculture, LULUCF, Energy, Air and Climate policy;
- integrate with key sensitivity analyses, and key parameter that influence agricultural production, such as GHG fluxes, ammonia (NH3) emissions, and nutrient losses to water using methodologies aligned with Ireland’s UNFCCC reporting
- the running of sector focused scenarios on request (for example alternative agricultural scenarios) to explore abatement potentials and emission outcomes; and
- the exploration of potential national pathways.
3.1.2 Development of modelling tools for integration with other CAMG models and land cover maps
The successful tenderer will develop and maintain an Agriculture Sector and Land Use, Land Use Change and Forestry model that is capable of integration with existing climate and emissions models established under CAMG, for example energy and air quality. Spatial outputs should be compatible with national land cover maps and tools.
Agri-environment schemes (AESs) have been developed by governments to improve biodiversity, reduce pollution from farming and encourage the provision of agriculture’s non-market benefits. Despite the substantial amount of money spent on designing, implementing and monitoring AESs, their environmental effectiveness is ambiguous. The objective of this paper is to investigate the relationship between farmer participation in an AES and the quantity and quality of semi-natural habitats found on farms. This study combines socio-economic survey data from Irish farms in 2012 with farmland habitat data collected in 2015–16 from a subset of participating farms in the original 2012 socio-economic survey. Given the voluntary nature of AESs, a matching technique is applied to control for self-selection bias and test whether farmer participation in an AES is related to the quantity and quality of habitats found on Irish farms. Although farmer participation in an AES is found to be positively related to habitat quantity and quality, we are unable to reject the null hypothesis of no statistically significant differences between habitat quantity and quality of participants in an AES and non-participants. However, results highlight that the share of habitat area (proxy variable for habitat quantity) varies significantly across farm households with different socio-economic characteristics, soil type, farm structures and location. Future policies could scale up the implementation of outcome-based payments or market-based instruments to incentivize farmers in improving their environmental performance. However, such policy improvements would still require the development of robust and transparent monitoring mechanisms.
Agricultural expansion and intensification has been associated with reductions in semi-natural grasslands and other habitats, and a decline in farmland biodiversity across north-west Europe and north America (Cerezo et al., 2011). Agri-environment schemes (AESs) and market-based instruments (e.g. taxes, subsidies and tradable permits, auctions) have been developed to incentivize environmentally positive practices on farmland. The majority of recent AESs in most European countries aim to reduce biodiversity loss and achieve other environmental goals (e.g. water pollution reduction and soil protection), by compensating farmers for income loss related to certain management actions that farmers perform to mitigate environmental externalities associated with intensive agricultural practices (Batáry et al., 2015).2 Nevertheless, the ecological impact of some AESs on biodiversity conservation is widely debated in the empirical literature (Arnott et al., 2019). In light of the concerns about the effectiveness of AESs to protect biodiversity, this paper aims to assess the environmental effectiveness of AESs by combining farmland habitat data with socio-economic survey data from Irish farms.
The Republic of Ireland (hereafter referred to as Ireland), is bordered by the Atlantic Ocean, the Irish Sea, and the Celtic Sea (Fig A.1-Appendix A), hosts exceptional ecosystems that support a rich and diverse fauna and flora (EPA, 2020). In response to the European Union’s Agri-environment Regulation 2078/92/EEC, the Irish Government introduced a voluntary action-oriented AES, the Rural Environment Protection Scheme (REPS) in June 1994. REPS operated over four iterations (REPS I to REPS IV) (Finn, Ó hUallacháin, 2012). The Agri-Environment Options Scheme (AEOS) replaced REPS in 2010, followed by the Green Low-Carbon Scheme (GLAS) in 2015.
Since its inception in 1994, there has been strong demand for evidence of the environmental effectiveness of Ireland’s AESs, which have paid farmers over €3 billion up to 2010 (Finn, Ó hUallacháin, 2012). Owing to difficulties in isolating and quantifying outcomes from AESs, the lack of reliable baseline data to compare change over time, along with the complex non-linear dynamics of ecosystem features at various spatial and temporal scales, the evaluation of AESs in Ireland and other countries remains challenging. By also taking into account the potential self-selection bias induced by the voluntary (non-random) participatory nature of AESs and the criteria used in the selection procedure, the evaluation of AESs becomes extremely challenging as AESs results may substantially differ between participating and non-participating farms.
The voluntary nature of AESs makes self-selection into a scheme one of the key factors determining its environmental benefits and cost-effectiveness. AESs are expected to be more attractive for farmers who do not have to significantly change their management practices to qualify for scheme participation, than those farmers who incur a significant cost associated with participation (Kelsey and Seema, 2019). Researchers, designers and funders of AESs have long worried that environmental subsidies flow to landholders who would have adopted conservation practices even without participation in an AES, undermining the additionality and cost-effectiveness of AESs. Hence, ex-post scheme evaluations that do not control for self-selection, may produce biased estimates.
A central question in this paper is: Does quantity and quality of on-farm habitats differ between farms participating in an AES and non-participating farms? The relationship between the ecological status of habitats and participation in AESs accounting for self-selection bias has been analyzed by only a few studies. This study aims to contribute to the AES evaluation literature by combining socio-economic with farm habitat data and employing a quasi-experimental method that accounts for self-selection bias (inverse probability weighting estimator with regression adjustment) to compare the quantity and quality of habitats across farms participating in an AES and non-participating farms.
The remainder of the paper is organized as follows. Section 2 provides background information related to Ireland’s AESs. A brief review of the literature follows in Section 3, while Section 4 refers to the datasets used in this study. Section 5 introduces the conceptual framework and the econometric approach undertaken for data analysis. Results and limitations of the study are presented and discussed in Section 6. Finally, Section 7 provides some concluding observations and policy implications.
Ireland’s agri-environment schemes (AESs)
REPS was the first national AES in Ireland. The objectives of REPS were applied at farm level through 11 measures. REPS paid farmers for undertaking measures on a per hectare basis, with the subsequent iterations of REPS having differing rates of graduated payments. The highest payments were for the first 20 ha, with different rates of declining payments for additional hectares across different iterations of the scheme. This hectare-based variation in payment rates rendered farm size a strong
As scheme effectiveness may depend on sufficient farmer participation levels (along with other factors), researchers have been interested in identifying the drivers of farmer participation in an AES, by using either data on observed farmer behavior (e.g. Wąs et al., 2021; Wilson and Hart, 2000) or conducting choice experiments (e.g. Espinosa-Goded et al., 2010; McGurk et al., 2020) and meta-analyses (e.g. Lastra-Bravo et al., 2015). As shown in many studies, there is substantial heterogeneity
In late 2012, a questionnaire-based survey of 1000 Irish farms was conducted to gather information on variables including farmers’ decisions to participate in AESs, farmer socio-demographic profile, farm location and structural characteristics of farms (e.g. farm size, number of livestock units). The timing of the survey coincided with the conclusion of the AEOS scheme at a period of maximum occupancy in schemes, which had been in existence for a number of iterations, and before the launch of a
In a randomized experimental setting where participation in an AES would be randomly assigned to farmers, the effect of participation on habitat quantity or quality, would be assessed by calculating the difference Δ in outcome variables (habitat quantity, habitat quality) at time t between what is empirically observable after participation (treatment) and what one would have observed in the same period and for the same farmers, in the case of non-participation. However, calculating Δ is not
Table 2 presents descriptive statistics for the full sample of farmers, plus descriptive statistics of the variables classified by participation status. These indicate that the share of semi-natural habitats of ecological value in surveyed farms was approximately 18%. Table 2 also shows that 45% of farms have participated in REPS IV or AEOS in 2012. The average differences in the characteristics of participants and non-participants are also presented in Table 2. Statistical tests show that the
Conclusions and policy implications
The sustainable management of natural resources and the provision of public goods such as biodiversity, nature-based cultural values and climate stability are key deliverables for modern agricultural production systems. During 1990’s, following the 1992 McSharry reform of the Common Agricultural Policy (CAP), voluntary AESs became an important mechanism to safeguard a wide range of environmental and aesthetic functions in European farmed landscapes. Given the growth of AES investment, the
Declarations of interest
This work was supported by the Irish Department of Agriculture, Food and the Marine (DAFM) (RSF15_S_619).
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