Predicting the impacts of bioenergy production on farmland birds

https://doi.org/10.1016/j.scitotenv.2013.12.080Get rights and content

Highlights

  • First GIS model to predict spatially the “local” impact of bioenergy policies

  • Systematic functional space models covering 19 farmland bird species

  • A 16,000 ha case study shows a synergy between bioenergy and farmland bird populations.

  • Renewable energy production strategy affects impact on farmland bird populations.

  • The model provides a method to determine the effects of policy driven land use change on biodiversity.

Abstract

Meeting European renewable energy production targets is expected to cause significant changes in land use patterns. With an EU target of obtaining 20% of energy consumption from renewable sources by 2020, national and local policy makers need guidance on the impact of potential delivery strategies on ecosystem goods and services to ensure the targets are met in a sustainable manner. Within agroecosystems, models are available to explore consequences of such policy decisions for food, fuel and fibre production but few can describe the effect on biodiversity. This paper describes the integration and application of a farmland bird population model within a geographical information system (GIS) to explore the consequences of land use changes arising from different strategies to meet renewable energy production targets. Within a 16,000 ha arable dominated case study area in England, the population growth rates of 19 farmland bird species were predicted under baseline land cover, a scenario maximising wheat production for bioethanol, and a scenario focused on mix of bioenergy sources. Both scenarios delivered renewable energy production targets for the region (> 12 kWh per person per day) but, despite differences in resultant landscape composition, the response of the farmland bird community as a whole to each scenario was small and broadly similar. However, this similarity in overall response masked significant intra- and inter-specific variations across the study area and between scenarios suggesting contrasting mechanisms of impact and highlighting the need for context dependent, species-level assessment of land use change impacts. This framework provides one of the first systematic attempts to spatially model the effect of policy driven land use change on the population dynamics of a suite of farmland birds. The GIS framework also facilitates its integration with other ecosystem service models to explore wider synergies and trade offs arising from national or local policy interventions.

Introduction

Finite fossil fuel resources and the need to reduce greenhouse gas emissions have led to a global focus on increasing energy supplies from renewable sources. The European Union has set a target of obtaining 20% of energy consumption from renewable sources by 2020 (EC, 2009). The target set for the UK is 15%, which would be equivalent to renewable energy providing the equivalent of 4.6 kWh of electricity, 3.4 kWh of transport fuel and 3.7 kWh of heat per person per day (Burgess et al., 2012). In 2011, the proportion of gross energy consumption from renewable sources was 13.4% within the EU27 but only 3.8% in the UK (EurObserv'ER, 2013). Realising the 2020 targets will require a significant change in land use patterns at local, national, European (Rounsevell et al., 2003) and even global scales. The recent revision of EU renewable energy policy (European Commission, 2012) in light of concerns over its impact on food production means that the long term implications for land use are unclear but in Britain, this may initially be an expansion or redirection of arable crops such as wheat and oilseed rape as first generation transport fuel production (Gallagher, 2008) and/or an expansion in the area under biomass crops, such as perennial grasses (e.g. miscanthus Miscanthus giganteus) and short rotation coppice (Burgess et al., 2012, Committee on Climate Change, 2011).

Large scale, often policy driven, land use changes have the potential to cause unexpected and significant detrimental environmental impacts. In Europe, for example, this is perhaps best evidenced by significant declines in farmland biodiversity and deteriorations in soil, air and water quality over recent decades associated with agricultural intensification and land abandonment and driven to a great extent by the Common Agricultural Policy (Stoate et al., 2001). There is also already evidence of unforeseen detrimental environmental impacts resulting from renewable energy policies. Rapidly increasing demand for biofuels, driven in part at least by EU policy (European Commission, 2006), has caused significant damage to biodiversity and ecosystem service provision through both direct and indirect land use changes with impact reported in parts of South America and south east Asia in particular (e.g. Fargione et al., 2008, Fitzherbert et al., 2008). In implementing EU renewable energy policy it is crucial that we learn from these past mistakes and manage the delivery of renewable energy production targets in a sustainable manner (Petersen et al., 2007). In particular this requires that renewable energy policies are integrated with other policies designed to manage issues such as food production and biodiversity conservation policies so that trade offs made between these potentially conflicting demands for finite land resources are sustainable (Murphy et al., 2011). A key component of this is developing the capability to predict any potential detrimental environmental impacts of proposed land use and management changes so that appropriate prevention or mitigation actions can be identified and implemented where necessary.

Here we focus on the effects of policy driven renewable energy options on farmland biodiversity, using the impact on birds as a proxy for the consequences for wider biodiversity. Both the UK and other European governments have identified birds as indicators of biodiversity health and have adopted indices of population trends as headline indicators of sustainable development. More broadly, bird population trends have also been used as an indicator of continued biodiversity losses at a global scale (Butchart et al., 2010). Hence the objective of this paper is to use a recently published modelling framework (Butler and Norris, 2013), integrated into a geographical information system (GIS), to predict the response of farmland bird populations to land use change scenarios associated with delivering renewable energy production targets for a landscape in the UK.

Section snippets

Method

The modelling framework uses the concept of functional cover types to link land use to the population trends of farmland birds. In brief, structural land covers (e.g. wheat, grassland, woodland) are classified into functional land covers (e.g. foraging and nesting sites) according to their capacity to provide key resources. This approach provides a more mechanistic link between land use and population growth than more traditional habitat association models, it helps to reduce content

Bioenergy production

The daily energy demand per person within Marston Vale equates to about 80 kWh. Under BASELINE land cover patterns and prioritisation of food production, the output of heat and transport energy is assumed to be zero. If surplus food products were reallocated to energy production, it was estimated that BASELINE energy output could be increased to 11.3 kWh p 1 d 1, comprising 4.9 kWh p 1 d 1 for transport fuel and 6.4 kWh p 1 d 1 for heating (Table 2). The combined value is similar value to the 2020

Discussion

Our results indicate that the strategy adopted to deliver the UK's land based renewable energy targets can affect both gross bioenergy production and farmland bird population trends. This integration of biodiversity and bioenergy production assessments for a common set of scenarios for a defined area, alongside assessments of the effect of the same land use changes on the level of food, animal feed and fibre as more fully reported by Burgess et al. (2012), serves as a prototype of the model

Conclusions

A variety of contrasting land use strategies could be employed to meet UK and European renewable energy production targets and the UK Government (2011) seeks to promote “an integrated approach to managing the natural environment, particularly at the landscape scale” when deciding on the most appropriate approach. To support this, land planners and managers need access to tools and models that can predict the impact of alternative strategies on the stocks and flow of ecosystem goods and

Conflict of interest

None to be reported.

Acknowledgements

The research described was funded by a Natural Environment Research Council (NERC) grant (reference NE/H010432/1). The group wishes to express their thanks to those who have commented and made positive suggestions about the work and all the stakeholders, colleagues and students who have assisted in the process.

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