Evaluation of the environmental impact of agriculture at the farm level: a comparison and analysis of 12 indicator-based methods
Introduction
Sustainable agriculture is concerned with the ability of agroecosystems to remain productive in the long term. Many authors distinguish ecological (or environmental), economic and social sustainability. Ecological sustainability is defined as the maintenance of the global ecosystem or of “natural capital” (the stock of environmentally provided assets which provide a flow of useful goods or services) both as a “source” of inputs and as a “sink” for waste (Goodland, 1995). The ecological dimension of sustainability is fundamental to overall sustainability, as it is a prerequisite for the economic and social dimensions.
Farmers adjust their production practices (e.g. tillage operations, sowing, fertilisation) in order to optimally combine inputs based on natural capital (soil, solar energy, rain, fossil energy) and inputs from human-made capital (fertilisers, seeds, pesticides) yielding desired outputs (products) and undesired emissions to the environment. The level of production of agroecosystems largely depends on inputs from natural and human-made capital. Herdt and Steiner (1995) point out that it is hard to know whether current agroecosystems are sustainable in the sense of remaining productive in the long run, as the continuous increase in human-made inputs applied in most agroecosystems has increased yields but may offset reductions in the quality of the natural capital (e.g. land degradation) and thus of the underlying productive capacity.
Until the 1970s, increase of production was the dominant concern of those involved in agriculture. Agronomic researchers mainly investigated the effects of the increased use of human-made inputs on the functioning and productivity of agroecosystems.
From the seventies onwards intensification of production methods caused increasing environmental pollution. Consequently, “limiting environmental impact to an acceptable level” (i.e. worries about the sink function of natural capital) became increasingly important in agricultural research. This generated a large amount of research concerning the impacts of agriculture on the environment (e.g. Wauchope, 1978, Ryden et al., 1984). More recently, worries about a loss of quality of the source functions of natural capital for agriculture through phenomena such as erosion, the disappearance of beneficial predatory and parasitic invertebrates in crops or the decrease of soil organic matter have received increasing attention (e.g. Pimentel and Kounang, 1998, Lewis et al., 1997, Katterer and Andren, 1999).
These developments have led to a variety of methods for the evaluation of the environmental impacts of agriculture. The development of such tools is considered by many authors as a condition for the implementation of a sustainable agriculture (e.g. Hansen, 1996). These methods take into account a number of environmental issues of concern (e.g. soil erosion, emission of greenhouse gasses, water quality); in this review the term “objectives” will be used to design these issues. Such methods generally use a set of indicators as criteria to quantify the degree to which these objectives are attained. The term “indicator” has been defined as: a variable which supplies information on other variables which are difficult to access and which can be used as a benchmark to take a decision (Gras et al., 1989). According to Mitchell et al. (1995) “indicators are alternative measures that are used to identify the status of a concern when for technical or financial reasons the concern can not be measured directly”.
Such indicator-based methods for the evaluation of environmental impacts of agriculture have been developed for a range of end users. These include farmers, local councils, catchment and land protection boards, policy makers and other decision makers at community, regional, national and global levels (King et al., 2000, OECD, 1999).
Environmental impact of agriculture depends to a large extent on farmer production practices. The link however is indirect, as emissions to the environment depend on the state of the farming system, which in turn depends on farmer production practices but also on random factors such as rainfall and temperature (Fig. 1). Consequently, indicators of environmental impact may be based either on farmer production practices (“means-based”) or on the effects these practices have (“effect-based”) on the state of the farming system or on emissions to the environment. For example, for the objective quality of groundwater, indicators considering fertilisation (e.g. amount of nitrogen applied) or the establishment of cover crops (expected to decrease leaching) are means-based, whereas indicators reflecting nitrate in the soil at crop harvest or nitrate lost to groundwater are effect-based (Fig. 1). Among these two effect-based indicators the latter is more directly related to the objective quality of groundwater than the former.
This paper compares and analyses 12 recent indicator-based approaches to assessing environmental impact at the farm level. The study does not intend to rank methods, but rather provides a characterisation of their components and functioning at the farm level. Some major questions must be addressed in the design of an evaluation method. Which environmental problems of current agroecosystems should be considered, and what type of indicators are best suited to quantify these problems? Should indicators of farmer production practices or indicators of the environmental effects of these practices be used? How to validate an evaluation method? How should the trade-off between simplicity and complexity of the evaluation method be approached? The specific objectives of the study are as follows: (1) characterise the methods with respect to the objectives considered, the type of indicators used, the validity and feasibility of the method; (2) propose guidelines for the evaluation of existing methods and for the development of new methods.
Section snippets
Description of the evaluation methods
The 12 methods reviewed here were selected from a literature research. These methods all use a set of indicators to evaluate the environmental impact of agriculture at the farm level. Some of the methods do not speak of “evaluation of environmental impact” but use the expression “evaluation of ecological (or environmental) sustainability”. Although this expression is not always clearly defined, it obviously designs a situation in which environmental impact is limited to an acceptable level.
What is evaluated and why, approach used and object studied
Five methods (EP, LCAA, AEI, SD and LCAE) profess to evaluate environmental impact, whereas EMA evaluates environmental performance, i.e. compliance with codes of good agricultural practice (Table 1). Five methods (FSI, SEC, AESA, OS and IFS) claim to evaluate environmental sustainability, MOP appears to do this too, but does not use the term sustainability.
EP evaluates in order to establish payment levels, OS and MOP evaluate in order to design new production systems, EMA evaluates in order to
What is evaluated?
The methods reviewed fall in two groups: those that profess to evaluate environmental impact or environmental performance, and those claiming to assess ecological sustainability (Table 1). The evaluation of sustainability is a more wide-ranging goal, requiring the consideration of objectives concerning source functions of the global ecosystem (e.g. fossil energy, biodiversity) in addition to objectives concerning its sink functions (e.g. water quality, soil quality). Of the methods claiming to
Conclusions
Based on the preceding discussion, the following requirements for indicator-based methods for environmental evaluation at the farm level are proposed. These guidelines can be used for the evaluation of existing methods and for the development of new methods.
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In order to effectively evaluate environmental impact, evaluation methods should take into account a range of objectives covering both local and global effects. The number of objectives should be sufficiently large to avoid the inadvertent
Acknowledgements
The paper greatly benefited from extensive comments on a draft by Ch. Bockstaller and J.M. Meynard. J. Baudry, Ph. Girardin, P. Robin, D. Vermersch and two anonymous reviewers also gave useful comments.
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