Typifying Ecosystems by Using Green Lacewing Assemblages Dominique Thierry, Bruno Deutsch, Mihaela Paulian, Johanna Villenave, Michel Canard
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Typifying ecosystems by using green lacewing assemblages Dominique Thierry, Bruno Deutsch, Mihaela Paulian, Johanna Villenave, Michel Canard To cite this version: Dominique Thierry, Bruno Deutsch, Mihaela Paulian, Johanna Villenave, Michel Canard. Typifying ecosystems by using green lacewing assemblages. Agronomy for Sustainable Development, Springer Verlag/EDP Sciences/INRA, 2005, 25 (4), pp.473-479. hal-00886302 HAL Id: hal-00886302 https://hal.archives-ouvertes.fr/hal-00886302 Submitted on 1 Jan 2005 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Agron. Sustain. Dev. 25 (2005) 473–479 473 © INRA, EDP Sciences, 2005 DOI: 10.1051/agro:2005047 Research article Typifying ecosystems by using green lacewing assemblages Dominique THIERRYa*, Bruno DEUTSCHb, Mihaela PAULIANc, Johanna VILLENAVEd, Michel CANARDe a Université Catholique de l’Ouest, Département des Sciences de la Vie et de la Terre, 44 rue Rabelais, 49000 Angers, France b Université Catholique de l’Ouest, Institut de Mathématiques Appliquées, 3 place André Leroy, 49000 Angers, France c Institutul de Cercetari pentru Protectia Plantelor, Bd. Ion Ionescu dela Brad 8, 77592 Bucuresti, Romania d Institut National d’Horticulture, Unité de Protection des Plantes, 2 rue Le Nôtre, 49045 Angers Cedex 01, France e (retired) 47 chemin Flou de Rious, 31400 Toulouse, France (Accepted 20 May 2005) Abstract – Green lacewing collection data from eleven various biotopes were used to typify different ecological landscapes. To make up the values recorded on single samples, we operated by the bootstrap method. A classifying process cluster scatterplot was then established to assess the proximity of the different habitats. Shannon’s and Hurlbert’s indices are highly sensitive parameters of the structure of assemblages. Their analysis results in a diagrammatic typological approach to the biotopes, allowing unambiguous comparisons between various chrysopid assemblages. It is possible to characterize the state of these polyvalent predators as a function of different abundance and diversity, and this state can be a standard of value of good ecological function in ecosystems. Concerning farming consultation and environmental conservation, such an approach is new and could be promising for future agricultural and landscape managers. biodiversity / green lacewing / faunistic richness / diversity index / equitability index 1. INTRODUCTION tural situations differing from one another by locality or time (Paulian et al., 2003). The aim of the present paper, based on The relation between the repair of biocoenoses and the spe- several previous field surveys of chrysopid assemblages, is to cies diversity they harbor is a well-known notion. Increasing assess the significance, the range and the accuracy of different biodiversity generally enhances the reliability of ecosystems, indices. They are based on the analyses of biotopes diversely i.e. the probability that a system will provide a consistent level or unaltered by insecticide pressure and/or other compelling of performance over a given unit of time (Naeem and Li, 1997). factors; they succeed in typifying ecological landscapes. Assessing agricultural ecosystems with respect to their current healthy condition and their ability to allow sustainable devel- opment is now a fundamental aim of scientists and advisors. 2. MATERIALS AND METHODS Several authors (e.g. Stelzl and Devetak, 1999) assumed that Neuroptera constitute a standard of value useful for judging the 2.1. Methodology good health of an agro-environment, even if a many-sided To analyze the structure of green lacewing assemblages, we approach might be theoretically better (Duelli, 1997). Green chose to determine for each habitat three indices among the lacewings occur commonly in many biotopes and they are eas- most commonly used in such quantitative descriptions of insect ily identifiable to species level. The larvae of all species and populations; namely, a species richness index proposed by adults of some of them are polyphagous predators on various Margalef (IM), plus two diversity indices proposed by Shannon soft-bodied arthropods: they are redundant in the sense of hav- (H’) and by Hurlbert (EH). ing multiple species per functional group (Lawton and Brown, For each sample, the observed values, i.e. collection data, 1993). Incidentally, they participate in controlling numerous were registered. Each index was estimated with the observed phytophagous organisms. Among their usual prey there are data. In order to evaluate the precision of the estimates we noxious arthropods to crops, often key pests such as aphids, employed the bootstrap methods (Efron, 1982; Efron and coccids, psyllids, cicadellids, caterpillars, mites and others. Tibshirani, 1993). Following the classical procedure, we com- Using value standards to characterize biodiversity is essen- puted a large number of virtual samples (10 000) that were sim- tial to quantify such a property and to compare various agricul- ulated by randomly collected sub-samples within an infinite * Corresponding author: [email protected] Article published by EDP Sciences and available at http://www.edpsciences.org/agro or http://dx.doi.org/10.1051/agro:2005047 474 D. Thierry et al. population holding the same distribution of species as the orig- with the assemblage structure; namely, the diversity of the spe- inal sample (Manly, 1991). For each simulated sample, a “sim- cies, the dominance and the equitability. ulated index” was computed. Firstly, the standard deviations of The standard Shannon’s diversity index (H’) proposed by the 10 000 “simulated indices” were computed. Secondly, a Shannon and Weaver (1963) is largely used in ecological stud- 95% confidence interval [CT1, CT2] was computed by the per- ies. It is only slightly correlated to the sample size. It gives both centile method of Efron (1982) which we adapted slightly in the relative importance of each species collected and the ratio the case of Margalef’s index. In the general case, CT1 and CT2 between the total numbers of species and individuals. Its values are the 2.5th and the 97.5th percentile values of the distribution range from 0 to log S, being maximal in stable ecosystems such of the simulated indices. In the case of Margalef’s index, the as in spontaneous forests. sub-samples cannot have more species than the original one, Hurlbert’s equitability index (EH) measures the relative het- but may have less. So the upper bound CT2 of the interval erogeneity of populations. It features the distribution of the would be the same as the estimated value of IM. In order to specimens occurring in an assemblage and gives an idea of the assess the possible upper variability of the estimations, the dominance of the more abundant species. This index is a priori upper bound CT2 was transformed into CT2’ = IM +(IM – well adapted to the study of small samples in which the ratio CT1). This kind of symmetry transformation results in almost of the number of taxa related to the total size is fairly high (Beisel the same probability of finding a new species, as there is of et al., 1997). It varies from 0 to 1, being nil when the quasi-total- missing one among the rarest species of the sample. A classi- ity of the specimens caught belongs to a single species and fying process (Cluster Scatterplot) was established in order to reaches one when each species is represented by the same assess the proximity of the different habitats. Data were statis- number of individuals. tically analyzed by using the Statgraph ® statistical graphic sys- tem (STSC Inc., Rockville, Maryland, USA). 2.4. Biotopes and collecting methods 2.2. Biocoenotic richness Several previous biotope surveys were analyzed, belonging to various European ecosystems (Fig. 1). The commonest way to characterize a group of organisms in a biotope consists of counting the number of specimens 2.4.1. Flat open fields present, giving the abundance and the biomass of the target group. The specimens collected may be either grouped (Q) or Flat open fields as typical agro-ecosystems under the Atlan- tic influence were investigated. The study was carried out in shared out across all species (qi) then constituting the actual size of the various species. Another structural parameter is the tax- Loos-en-Gohelle, in the French southern part of the Flanders onomic richness (S), which equates to the number of species Plain, Pas-de-Calais, France (50° 27’ 00” N, 02° 47’ 00” E) occurring in the biotope. Although these indicators are simple (called LOO). It is a traditionally agricultural zone where veg- etable and fruit production predominates. The target fields were and easily available, caution is needed before their use and anal- of a commercial type, but managed with ‘soft’ cultural tech- ysis. In some cases, the species status is indeed difficult to state niques: either integrated or strictly organic farming. Several Chrysoperla carnea precisely – e.g. in the (Stephens, 1836) crops: strawberry, potato, witloof, tobacco and kidney-bean complex – so that the actual abundance of every true species and their neighboring uncultivated biotopes were sampled. in some cases cannot be determined. Nevertheless, it is only from the two available parameters S and Q that we may assess Various collection methods were used: suction trap, yellow representative biocoenotic indices. traps and hand net. Adults were regularly sampled in the grow- ing season (from May to October) of 1999 (Trouvé et al., 2002). Species richness is highly dependent upon the sample size. The optimal sample sizes are conventionally defined when the 2.4.2. Mediterranean olive groves taxonomic richness reaches 95% of the theoretical value of S.