Assessing Biodiversity in Arable Farmland by Means of Indicators: an Overview
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AGRONOMIE – ENVIRONNEMENT Assessing biodiversity in arable farmland by means of indicators: an overview Christian BOCKSTALLER Abstract: Maintaining biodiversity is one of the key issues of sustainable agriculture. It is ¸ Francoise LASSERRE-JOULIN now stated that innovation to enhance biodiversity in arable land requires operational Sophie SLEZACK-DESCHAUMES assessment tools like indicators. The goal of the article is to provide an overview of Severine PIUTTI available indicators. Besides measured indicators and simple indicators based on Jean VILLERD management data, we focus on predictive indicators derived from operational models Bernard AMIAUD and adapted to ex ante assessment in innovative cropping design. The possibility of use Sylvain PLANTUREUX for each indicator type is discussed. Key words: environmental assessment, indicator, model, validation, biodiversity, INRA, UMR 1121 ecosystemic services Nancy-Universite - INRA, IFR 110, Nancy-Colmar, BP 20507, 68021 Colmar France <[email protected]> Maintaining biodiversity is one of the intensification, among them extensifica- Indicators can be basic variables (e.g. key issues of sustainable development, tion and even suppression of chemical amount of input) or simple combination and agriculture is highly concerned in input like in organic farming (Hole et al., of these variables (balance, ratio) as well this perspective. The term was first 2005), reconsideration of field margin as field measurements, the former being suggested in 1985 at a conference on management to enhance semi-natural also called ‘‘indirect’’ and the latter biological diversity in the USA and was area of farmland (Marshall and Moonen, ‘‘direct’’ indicator regarding biodiver- popularized since the Rio Conference in 2002). It is now stated that this process of sity (Burel et al., 2008). Indicators can 1992 (Le Guyader, 2008). It is now innovation to enhance biodiversity also be derived from model outputs and commonly accepted that biodiversity in arable land requires operational assess- thus can be considered as ‘‘predictive can address the biological diversity at ment tools. These tools should evaluate indicators’’. By this way, an indicator different levels: i) the compositional, the current state at different scales, can be obtained from the average including the genetic, species, com- identify the causes of biodiversity impov- of model output, transformed into munity, habitat diversity, ii) the struc- erishment in a diagnosis phase, and scores or even expressed as the ratio tural, iii) the functional encompassing assess the effects of innovative solution of a model output and a reference processes within that level (Clergue et cropping systems (Bockstaller et al., value, as for pesticide risk indicators al., 2005). In the 2000s, the Millennium 2008b). This led many authors to plead (Bockstaller et al., 2009). This type of Ecosystems Assessment (2005) intro- for research on biodiversity indicators indicators expresses an explicit link duced the concept of ecosystemic (Carpenter et al., 2006) which have not between input variables addressing services provided by biodiversity, like to be confounded with bioindicators the causes, and an output reflecting pollination, and pest control. (Duelli and Obrist, 2003). The latter an effect on environment. Models can In arable area the change in land use, the use a component of biodiversity to assess be roughly separated in operational intensification and simplification of crop- something else, like the accumulation of models using a limited and available ping systems, as well as the drastic a pollutant. set of input variables and complex reduction of semi-natural elements From a general point of view, the term models which are too difficult to imple- (hedges, trees, wet zones, etc.) have ‘‘indicator’’ can refer to many defini- ment by non-scientists. If measured led to a significant decrease of biodiver- tions (Heink and Kowarik, 2010) as indicators are totally relevant for ex post sity in arable land (Le Roux et al., 2008). shown in figure 1 (Bockstaller et al., assessment of the state of biodiversity to Different options were developed to 2008b). Those authors set a typology evaluate e.g. the results of agri-environ- mitigate negative effect of agriculture based on the nature of the indicators. mental scheme (Kleijn et al., 2006), they To cite this article: Bockstaller C, Lasserre-Joulin F, Slezack-Deschaumes S, Piutti S, Villerd J, Amiaud B, Plantureux S. Assessing biodiversity in arable farmland by means of indicators: an overview. OCL 2011;18(3):137-44. doi : 10.1684/ocl.2011.0381 doi: 10.1684/ocl.2011.0381 OCL VOL. 18 N8 3 mai-juin 2011 137 Article disponible sur le site http://www.ocl-journal.org ou http://dx.doi.org/10.1051/ocl.2011.0381 Management* Effects on Soil* Climate biodiversity Abiltiy to trace cause-effect relationship Predictive indicator based on Predictive indicator complex model based on M(x1, …, xn, p1, pk) operational model (e.g. Vegpop2) Measured f(x , …, x ) 1 p indicator (e.g. Flora-predict) y , y Simple indicators 1 2 (e.g. number of x , x , x /x , x -x 1 2 1 2 1 2 birds species) (e.g. % semi-natural area) Integration of process Feasibility Figure 1. Typology of indicators base on the construction method and evaluation of their quality (inspired from Bockstaller et al., 2008b) do not allow trace the cause. Simple allows assess the biodiversity, whereas indicators used at different scale from indicators can complete the information the operational model Flora-Predic pro- field to national level. An exhaustive on the causes or ‘‘pressure’’. Predictive vides a probability of presence. This review of proposals for different taxa can indicators offer a compromise between output only indicates the occurrence of be found in Burel et al. (2008). Species simple indicators and measured indica- species and can be considered as an of almost all taxonomic groups have tors regarding feasibility and degree of indicator. This last group of predictive been proposed (Lindenmayer and integration of process. They can be used biodiversity indicators remains poorly Likens, 2011). The indicator may for ex ante assessment to predict effect of covered by scientific literature. In this address all the species of a given taxon simulated system. Such indicators are article, we aimed at providing an over- or a given category like the number necessary for agronomist working on view of the available biodiversity indi- threatened species given by the Red innovative cropping design (Sadok et al., cators covering the three types of Lists for a given region (see list given by 2008). indicators, with a focus on this last Delbaere (2003)). It can also focus on Since the 90s, scientific publications on group of predictive indicators. We the diversity of keystone species, i.e. a biodiversity indicators have increased to illustrate it with recent initiatives con- species supporting the functioning of a reach 100 articles per year in the last cerning predictive indicators addressing ecosystem and the survival of many years (Burel et al., 2008). In the last biodiversity for different taxa mainly other species as well as umbrella species, decade, several reviews were published plants, invertebrate and soil microbial i.e. species which needs a large area to communities, this for spatial scale rang- survive and offers possibility of existence but their scope was beyond agriculture addressing natural land (e.g. Levrel, ing from field to agricultural landscape. to many other species (Clergue et al., 2007). Others focused on agriculture 2005). However examples of such but covered only measured indicators specific species are scarce in agriculture. and secondary simple indicators derived Measured (direct) In field experiments testing new from management data (Braband et al., indicators designed cropping systems, agronomist 2003; Buchs€ et al., 2003; Delbaere, assessed biodiversity by some measured 2003; Burel et al., 2008). Clergue et al. Since the 80s, a vast number of indicators like plant diversity (Vereijken, (2005) gave two examples of models measured indictors were proposed in 1997; Pacini et al., 2003). Among which can be used to derive indicators: the literature as previously reviewed by invertebrates, indicator based on the Vegepop2 a complex model predicting Noss (1990) and more recently by diversity of carabid beetle were pro- the effect on field boundary flora and Lindenmayer and Likens (2011). Indi- posed by many authors because they Flora-predict (Amiaud et al., 2005), an cators based on species diversity and/or are relatively easy to assess by simple operational model for meadow flora. abundance among a given taxon or pitfall although they were criticized as The model Vegpop2 predicts a dynamic several taxa (e.g. birds, plants, carabid indicator of biodiversity (Duelli, 1997). of biomass for different species that beetles, etc.) are the most commonly Doring€ and Kromp, 2003 analysed the 138 OCL VOL. 18 N8 3 mai-juin 2011 ability of different carabid beetle species well know, and present a power of land (Le Roux et al., 2008) we classify to indicate the impact of change of communication to the society (Levrel, them in two groups: i) indicators related cropping systems from intensive to 2007). to management of farmland at different organic. Since diversity cannot be only be scales ii) indicators addressing cropping practices, which can be expressed in At smaller level, soil is one of the major reduced to the number of species but amount of inputs per area unit or