Jean-Claude Abadie
email: abadie@mnhn.fr

Camila Andrade

Nathalie Machon

Emmanuelle Porcher

On the use of parataxonomy in biodiversity monitoring: a case study on wild flora

Keywords: Citizen science, Inventory, Monitoring, Morphotypes, Parataxonomy, Sampling bias, Taxonomy, Wider countryside

Monitoring programs that assess species richness and turnover are now regarded as essential to document biodiversity loss worldwide. Implementation of such programs is impeded by a general decrease in the number of skilled naturalists. Here we studied how morphotypes, instead of species, might be used by unskilled participants (referred to as "volunteers") to survey common plant communities. Our main questions were: (1) Can morphotypes be used as a robust estimator of species richness (α-diversity) and assemblage turnover (β-diversity)? and (2) What is the robustness (reproducibility and repeatability) of such methods? Double inventories were performed on 150 plots in arable field margins, one by a non-expert using morphotypes, the other by a taxonomist using species. To test the robustness of morphotype identification among participants, twenty additional plots were surveyed by eight volunteers using the same protocol. We showed that (1) the number of morphotypes identified by unskilled volunteers in a plot was always strongly correlated with species richness. (2) Morphotypes were sensitive to differences among habitats but were less accurate than species to detect these differences. (3) Morphotype identification varied significantly within and between volunteers. Due to this lack of repeatability and reproducibility, parataxonomy cannot be considered a good surrogate for taxonomy. Nevertheless, assuming that morphotypes are identified with standardised methods, and that results are used only to evaluate gross species richness but not species turnover, parataxonomy might be a valuable tool for rapid biodiversity assessment of common wild flora.

Introduction

Over the last couple of centuries, Europe has been submitted to strong human pressures [START_REF] Stoate | Ecological impacts of arable intensification in Europe[END_REF], which have resulted mostly in agricultural intensification [START_REF] Tscharntke | Landscape perspectives on agricultural intensification and biodiversity -ecosystem service management[END_REF], landscape fragmentation [START_REF] Fischer | Landscape modification and habitat fragmentation: a synthesis[END_REF] and increased urbanization [START_REF] Mckinney | Urbanization as a major cause of biotic homogenization[END_REF]. As a consequence, large regions have become poor-quality habitats for wildlife, and a lot of species considered common in the beginning of the twentieth century are now experiencing severe declines, or even becoming scarce [START_REF] Smart | Large-scale changes in the abundance of common higher plant species across Britain between 1978, 1990 and 1998 as a consequence of human activity: Tests of hypothesised changes in trait representation[END_REF][START_REF] Rich | Floristic changes in vascular plants in the British Isles: geographical and temporal variation in botanical activity 1836-1988[END_REF]). These areas and the ecological communities they support, usually referred to as "the wider landscape matrix" (e.g. wider countryside, urban and suburban areas), are subsequently less attractive for conservationists and often remain excluded from conservation planning [START_REF] Gaston | Commonness, population depletion and conservation biology[END_REF]. In this context, the need for largescale, long-term monitoring programs embracing non-protected areas is now widely recognized [START_REF] Yoccoz | Monitoring of biological diversity in space and time[END_REF][START_REF] Pereira | Towards the global monitoring of biodiversity change[END_REF][START_REF] Teder | Monitoring of Biological Diversity: a Common-Ground Approach[END_REF]). Such programs however require a large number of observation points, and their implementation is often hindered by the lack of species identification skills, arising from a decrease in the number of taxonomists, both professionals [START_REF] Whitehead | Systematics: An Endangered Species[END_REF][START_REF] Noss | The Naturalists Are Dying off[END_REF][START_REF] Rivas | Natural History: Hobby or Science?[END_REF]) and amateurs [START_REF] Hopkins | Declines in the numbers of amateur and professional taxonomists: implications for conservation[END_REF]. These difficulties are less severe in the wider countryside, supporting common species, which are usually familiar to naturalists. These species remain nonetheless unattractive for the majority of naturalists, who generally prefer atypical ecosystems and/or rare species, despite the fact that the wider countryside (e.g. agricultural landscapes, covering vast areas in Europe) now experiences substantial species decline [START_REF] Perrings | Biodiversity in Agricultural Landscapes: Saving Natural Capital without Losing Interest[END_REF].

With the rise of "citizen science" [START_REF] Trumbull | Thinking scientifically during participation in a citizen-science project[END_REF][START_REF] Lundmark | BioBlitz: Getting into Backyard Biodiversity[END_REF][START_REF] Andrianandrasana | Participatory Ecological Monitoring of the Alaotra Wetlands in Madagascar[END_REF], where non-professional observers are involved in monitoring programs [START_REF] Penrose | Volunteer Monitoring of Benthic Macroinvertebrates: Regulatory Biologists' Perspectives[END_REF][START_REF] Fore | Assessing the performance of volunteers in monitoring streams[END_REF][START_REF] Engel | Volunteer biological monitoring: Can it accurately assess the ecological condition of streams?[END_REF][START_REF] Pilgrim | Bluebells for Britain -a report on the 2003 Bluebells for Britain survey[END_REF][START_REF] Stewart | People and Plants: mapping the UK's wild flora[END_REF], volunteering might be an alternative to develop the monitoring of common species. The involvement of volunteers has been shown to facilitate data collection for taxonomic studies (e.g. specimens, [START_REF] Janzen | Setting up tropical biodiversity for conservation through nondamaging use: participation by parataxonomists[END_REF] or environmental monitoring (e.g. presence of a species or environmental features, repeated over time [START_REF] Holck | Participatory forest monitoring: an assessment of the accuracy of simple cost-effective methods[END_REF]. However, the participation of volunteers in biodiversity studies also generates scepticism among the scientific community about the reliability of data collected by inexperienced observers [START_REF] Foster-Smith | The value of marine ecological data collected by volunteers[END_REF]. Some ecologists argue that these approaches may compromise data accuracy and increase biases beyond acceptable levels, in comparison with data collected by professional biologists [START_REF] Firehock | A Brief History of Volunteer Biological Water Monitoring Using Macroinvertebrates[END_REF].

In addition, taxonomists highlight that the involvement of non professional observers might act as competition and therefore be an impediment to the maintenance and renewal of the taxonomy community [START_REF] Goldstein | How Many Things Are There? A Reply to Oliver and Beattie, Beattie and Oliver, Oliver and Beattie, and[END_REF]. This however depends on the actual skills of volunteers. Many so-called 'citizen science' programs (including breeding bird surveys Julliard and Jiguet 2002b;[START_REF] Newson | Evaluating the Breeding Bird Survey for producing national population size and density estimates[END_REF], involve amateur naturalists whose skills can generally not be questioned. Other approaches, which we investigate here, may involve non-naturalist volunteers [START_REF] Evans | The Neighborhood Nestwatch Program: Participant Outcomes of a Citizen-Science Ecological Research Project[END_REF]; in this case, alternative methods for species identification (paratoxonomy) are required to compensate for their virtually complete lack of taxonomic knowledge [START_REF] Fore | Assessing the performance of volunteers in monitoring streams[END_REF].

Parataxonomy consists of using morphotypes, also referred to as parataxonomic units [START_REF] Krell | Parataxonomy vs. taxonomy in biodiversity studies -pitfalls and applicability of "morphospecies" sorting[END_REF] or recognizable taxonomic units [START_REF] Cranston | Rapid assessment of biodiversity using 'biological diversity technicians[END_REF][START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF], as a surrogate for taxonomic species.

Paratoxonomic methods have been used in tropical ecosystems, generally characterized by high species richness, including numerous undiscovered or undescribed species, where there is a chronic lack of on-site trained taxonomists [START_REF] Gaston | Taxonomy of taxonomists[END_REF][START_REF] Basset | Conservation and biological monitoring of tropical forests: the role of parataxonomists[END_REF]). These methods are usually a preliminary step towards species determination [START_REF] Wheeler | Systematics, the scientific basis for inventories of biodiversity[END_REF]: parataxonomists, also called biodiversity technicians [START_REF] Longino | Biodiversity Assessment Using Structured Inventory: Capturing the Ant Fauna of a Tropical Rain Forest[END_REF][START_REF] Janzen | Setting up tropical biodiversity for conservation through nondamaging use: participation by parataxonomists[END_REF]), sort voucher specimens on the basis of morphological similarities. Voucher specimens are then generally determined at the species level by professional taxonomists, but the morphotypes may sometimes be considered to provide sufficient information, especially in invertebrate groups, in which case species are not determined [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF]Oliver and Beattie 1996b;Oliver and Beattie 1996a;[START_REF] Oliver | Virtual Biodiversity Assessment Systems[END_REF][START_REF] Derraik | Arthropod Morphospecies versus Taxonomic Species: a Case Study with Araneae, Coleoptera, and Lepidoptera[END_REF]. So far, parataxonomic approaches have been used for taxonomic groups with significant identification difficulties, essentially invertebrates [START_REF] Pik | Taxonomic sufficiency in ecological studies of terrestrial invertebrates[END_REF][START_REF] Ward | Terrestrial invertebrate surveys and rapid biodiversity assessment in New Zealand: lessons from Australia[END_REF], such as arthropods [START_REF] Bolger | Arthropods in Urban Habitat Fragments in Southern California: Area, Age, and Edge Effects[END_REF][START_REF] Kerr | Indicator Taxa, Rapid Biodiversity Assessment, and Nestedness in an Endangered Ecosystem[END_REF] or Rotifera [START_REF] Nielsen | Ecology versus taxonomy: is there a middle ground?[END_REF], and in one instance bryophytes [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF]. With the development of "citizen science", parataxonomy could be an effective way to boost the number of biodiversity surveyors, particularly in common ecosystems supporting well-known species, where it could prove useful to counterbalance the lack of trained taxonomists. To our knowledge, such approach has never been applied to large-scale monitoring.

The goal of this paper is to evaluate the potential of parataxonomy for monitoring plant communities in the wider countryside. To achieve this, we set up a simple parataxonomic method, requiring almost no a priori knowledge of botany and using a standardized protocol based on simplified determination keys. We then performed a comparison of taxonomic and parataxonomic methods in an agricultural landscape to investigate the following questions: (1) Can morphotypes be used to generate robust estimators of species richness and turnover? (2) Does this method meet two important criteria of scientific method, i.e. reproducibility and repeatability [START_REF] Cassey | Reproducibility and repeatability in ecology[END_REF]?

Material and Methods

Field site and sampling protocol

We conducted field sampling in the Parisian region, a highly agricultural region, according to the following protocols. For all botanical inventories nomenclature follows [START_REF] Kerguélen | Base de Données Nomenclaturales de la Flore de France (BDNFF) Version 3[END_REF].

Botanist versus volunteer experiment

Fifteen fields were selected among the 1000 sites of the "Biovigilance" Biodiversity Observatory Network [START_REF] Fried | Evolution de la flore du maïs : Mauvaises herbes, ce qui a changé en 30 ans[END_REF] and sampled in spring 2006 following a standardized protocol used to monitor the abundance of flora in arable field margins. Ten 1m 2 rectangular plots were placed evenly on the margins of each field (yielding a total of 150 plots), so that a wide variety of margin types were represented: grass strip (16 plots), footpath (79 plots), fallow land (15 plots), road side (15 plots), and wood edge (25 plots). For this experiment two observers were involved in surveying each plot: a trained botanist, referred to as "botanist", and a student with no experience in plant determination, referred to as "volunteer". In each plot, the botanist inventoried all vascular plant species as exhaustively as possible, while the volunteer independently estimated the number and identity of morphotypes, using a simplified method (see below).

Multiple-volunteer experiment

To examine the variation among individual observers (both within botanists and within volunteers) and the reproducibility of parataxonomic methods when several observers are involved, we repeated the procedure above with eight volunteers and three botanists in a subsample of 20 plots, encompassing four different types of field margin: grass strip, fallow land, hedge and wood edge (5 plots per margin type). Volunteers included people of various academic levels, with a background in biology, but with no experience in field work and plant determination, so that we can assume that their qualification for parataxonomy is similar to what we might expect of non naturalists following similar protocols. During the field session, all botanists and volunteers first performed inventories independently, to avoid identification bias. Each morphotype found by a volunteer was then individually examined by a botanist and assigned to one or more species.

Defining plant morphotypes

The morphotype identification process used by volunteers was based on identification keys, but differs in that it is not based only on dichotomous choices.

Plants were first separated into forbs and graminoids, and then characterized via a number of easily observable characters. For each character, a list of the different character states, encoded by a letter or a number, was provided to the observers (Figure 1). Each morphotype was thus defined by a code corresponding to a combination of character states. For forbs, six characters were considered sufficient to discriminate the various plant morphologies: (1) leaf shape (24 states, see Figure 1), (2) growth form (two states, rosette and erected), leaf arrangement (three states, alternate, opposite, whorled), pubescence (two states, present or absent), and flower colour (if present, four states, white, yellow, red or blue). For graminoids, only leaf width was considered, with three levels (thin, intermediate and wide). A strict minimum of scientific terms was used and drawings were provided to illustrate or even replace lists of scientific terms (e.g. leaf shape).

Data analysis

In the following we define α-diversity as within habitat diversity and β-diversity as the degree of change in species diversity among habitats [START_REF] Whittaker | Evolution and Measurement of Species Diversity[END_REF]). Data analyses were similar for both experiments. We first calculated the "gross" accuracy, i.e. the number of taxonomically identified species minus the number of morphotypes, divided by the number of species [START_REF] Krell | Parataxonomy vs. taxonomy in biodiversity studies -pitfalls and applicability of "morphospecies" sorting[END_REF]. The efficiency in estimation of αdiversity using morphotypes was assessed by considering the relationship between species richness and morphotype richness per plot, using Spearman correlations.

The congruence between β-diversity measured with species vs. morphotypes was investigated indirectly by comparing dissimilarity among replicates, using the semimetric Bray-Curtis distance [START_REF] Bray | An ordination of the upland forest communities of southern Wisconsin[END_REF], generally considered one of the best measures of community dissimilarity [START_REF] Clarke | Non-parametric multivariate analyses of changes in community structure[END_REF]). As it was not possible to monitor species turnover through time, changes in plant community composition were assessed indirectly by comparing morphotype and species diversity in different habitats, to check whether changes could be detected across habitat types. We first used Mantel correlation tests to evaluate whether the estimation of species turnover between plots was correlated with that found with morphotypes. Second, we investigated species, as well as morphotype turnover among the different habitats (i.e. types of margins). This was done using a non-parametric multivariate analysis of variance (PERMANOVA) with the FORTRAN program NPMANOVA [START_REF] Anderson | PERMANOVA: a FORTRAN computer program for permutational multivariate analysis of variance[END_REF]. This method generates an F-ratio, the ratio of differences among habitat types on differences among plots within habitat type [START_REF] Anderson | A new method for non-parametric multivariate analysis of variance[END_REF]. Significance was determined from 100 random permutations with a significant level of P = 0.05. Pairwise a posteriori comparisons were performed to quantify individual differences between pairs of habitats. Similar multivariate dispersion of points among groups was checked using FORTRAN program PERMDISP [START_REF] Anderson | PERMDISP: a FORTRAN computer program for permutational analysis of multivariate dispersions (for any two-factor ANOVA design) using permutation tests[END_REF]).

In the "multiple volunteers" experiment, the following analyses were performed in addition to those listed above. First, we compared the number of morphotypes found by each volunteer with the true number of species using Wilcoxon rank test.

Second, we evaluated the "true" morphotype identification accuracy, which measures the proportion of morphotypes corresponding to a single taxonomically identified species. This measure was then compared to gross accuracy using a Wilcoxon rank test. Third, the F-ratio values obtained by non-parametric MANOVA were compared between botanists and volunteers, using Mann-Whitney rank test, to assess differences in accuracy of turnover revealed by species vs. morphotypes.

Non-metric multidimentional scaling (nMDS) was performed to provide a graphical representation of the differences among morphotype assemblages for each volunteer. This ordination method was also performed on species data and used as a reference point.

The robustness of the parataxonomic method was evaluated by two criteria: reproducibility (i.e. differences in morphotype identification among observers) and repeatability (i.e. difference in morphotype identification among replicate plots for each volunteer). This was studied as follows. To assess reproducibility, nonparametric MANOVA was performed on data collected by botanists and volunteers to test the observer effect on the variability of species and morphotypes assemblages.

To assess repeatability, we first estimated the variability within observers via a measure of diversity between replicates within the same habitat type, assuming that a volunteer who tends to change the morphotype attributed to a given species among replicates will increase this measure. Apportionment of quadratic entropy (APQE), a method allowing hierarchical decomposition of diversity [START_REF] Pavoine | The apportionment of quadratic entropy: a useful alternative for partitioning diversity in ecological data[END_REF] was used to decompose species or morphotype diversity into three hierarchical levels: among habitats types, among plots within habitat type, and within plot.

Percentages obtained were compared between botanists and volunteers, using Mann-Whitney rank tests. Second, we computed, for each volunteer, the ratio of the total number of morphotypes in all plots to the mean number of morphotypes per plot, for each species detected more than once. This ratio was then averaged across all species for each volunteer and can be considered as a "repeatability index": even though volunteers might frequently split a species into several morphotypes within a plot, they should use the same morphotypes across plots if the method is repeatable, hence yielding a repeatability index close to 1. We tested whether this index was significantly different from one using wilcoxon tests.

For all analyses involving comparisons among classes of contrasted sizes (habitat type in the "volunteer vs. botanist" experiment, and observer type in the "multiple-volunteer" experiment), a resampling procedure was performed to generate multiple samples of equal size. All analyses, except non-parametric MANOVA, were performed with the R statistical package version 2.4.1 for Windows (R Development Core Team 2004) using the vegan library version 1.8-5 [START_REF] Oksanen | vegan: Community Ecology Package[END_REF]) and the ade4 library version 1.4-2 [START_REF] Chessel | ade4: Analysis of Environmental Data : Exploratory and Euclidean method[END_REF].

Results

"Botanist vs. volunteer" experiment

In a comparison of the efficiency of an untrained volunteer and a skilled botanist, gross accuracy was 80.5%. Species richness and morphotype richness per plot were highly significantly correlated (Spearman rho=0.87; P<0.01) and not significantly different from each other. As expected, habitat type had a significant effect on both species and morphotype richness (non-parametric MANOVA, table 1), with higher species and morphotypes richness in road sides. However, species data were much more powerful than morphotype data to detect pairwise differences between habitats: all five habitat types exhibited significantly different species assemblages, whereas morphotypes revealed significant differences only between road side and two other habitats (footpath and grass strip, pair-wise a posteriori comparisons, table 1).

"Multiple-volunteer" experiment

When multiple volunteers were compared to botanists, the gross accuracy of morphotype identification (ranging between 61% and 90%) was significantly higher than real accuracy (ranging between 55% and 70%, see table 2 for detailed values).

Lumping (i.e. attribution of several morphotypes to a single species) and splitting (attribution of a same morphotype to several species) occurred for all volunteers: the average frequency of correct identification (a single morphotype corresponds to a single species and vice versa) was 61%, with 16% of lumping and 23% of splitting (figure 3). As before, the correlation between species and morphotype richness per plot was significant for all volunteers (table 2), but total morphotype richness per volunteer was significantly smaller than total species richness, as might be expected since different species may have similar morphotypes.

Significant species turnover among habitat was detected with both species and morphotypes, but with an observer-dependent accuracy, as suggested by significant Mantel correlation coefficients (measuring correlations between amonghabitat distances in botanists vs. volunteers), ranging between 0.46 and 0.77. Both species and morphotype assemblages differed significantly among habitat types, as shown by non-parametric MANOVA (table 3). F-ratios obtained with botanist data were not significantly higher than those obtained with volunteers. Nevertheless, some differences in species assemblage among habitats remain undetected by four volunteers, as demonstrated by pairwise a posteriori comparison. Hence, information based on species more accurately revealed assemblage turn-over among habitat types. This result is supported by a visual assessment of patterns in the non-metric multidimensional scaling plot of data using Bray-Curtis distances, as shown in Figure 2.

In addition to the habitat effect on morphotype assemblage, there was a strong volunteer effect, as well as a significant interaction between volunteer and habitat type (non-parametric MANOVA, table 3). This shows that morphotype identification appeared to differ significantly among volunteers. In contrast, only habitat effect was found using botanist data (table 3), so that we can assume that there was no significant differences in species identification among botanists. For this reason, botanists were represented as a consensus (i.e. based on all species found by all botanists) in nMDS graphical representation (Figure 2). Finally, no significant differences were found between botanists and volunteers in the proportion of diversity between replicates within habitat type (APQE, Table 4; Kruskal-Wallis test; P<0.05), whereas the repeatability index was much above 1 (1.95 ± 0.14, Table 4) indicating a lack of repeatability.

Discussion

In the context of large scale biodiversity monitoring, opening up to nonprofessional naturalists [START_REF] Fore | Assessing the performance of volunteers in monitoring streams[END_REF]Julliard and Jiguet 2002a;[START_REF] Stewart | People and Plants: mapping the UK's wild flora[END_REF], the aim of this study was to explore the use of parataxonomy as a surrogate for species identification. In particular, we wanted to evaluate whether α and β diversity, two essential indices in biodiversity monitoring schemes, were accurately measured using morphotypes instead of true species. We discuss the consequences of our findings for large scale biodiversity monitoring in the wider countryside.

Estimation of α and β diversity using morphotypes

Morphotypes are widely used in taxonomy as a first step before determination (for example see the INBio project in [START_REF] Janzen | Setting up tropical biodiversity for conservation through nondamaging use: participation by parataxonomists[END_REF] or in ecological studies to assess and survey species diversity, as in the present study [START_REF] Basset | Short-term effects of canopy openness on insect herbivores in a rain forest in Guyana[END_REF]). In the latter case, morphotypes are generally used with invertebrate taxa known to be speciesrich, and for which there often is limited taxonomic expertise, e.g. Araneae [START_REF] Derraik | Arthropod Morphospecies versus Taxonomic Species: a Case Study with Araneae, Coleoptera, and Lepidoptera[END_REF], Diptera [START_REF] Cranston | Rapid assessment of biodiversity using 'biological diversity technicians[END_REF], Coleoptera (Oliver and Beattie 1996a), Annelida [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF], and Formicidae [START_REF] Pik | Taxonomic sufficiency in ecological studies of terrestrial invertebrates[END_REF].

Nonetheless, as highlighted by [START_REF] Krell | Parataxonomy vs. taxonomy in biodiversity studies -pitfalls and applicability of "morphospecies" sorting[END_REF] the real accuracy of morphotype identification often remains unknown, except in few studies which systematically compared morphotype identification vs. species determination [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF]Oliver and Beattie 1996b;[START_REF] Derraik | Arthropod Morphospecies versus Taxonomic Species: a Case Study with Araneae, Coleoptera, and Lepidoptera[END_REF][START_REF] Majka | Parataxonomy: a test case using beetles[END_REF]. These studies demonstrated that the real accuracy can differ greatly among taxonomic groups, due to difficulties to separate different species on the basis of morphology. As an example, a low accuracy can be explained by intraspecific polymorphism in some groups (e.g. sexual or developmental differences leading to different colours or sizes in the same species), which leads to splitting or lumping species, whereas the diagnostic criteria remain cryptic for a non specialist (e.g. genitalia in Araneae).

Our results for vascular plants suggest an accurate estimation of species α diversity using morphotypes, as shown by the strong correlation between species and morphotype numbers in both experiments, which is consistent with earlier studies on invertebrate groups cited above [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF]Oliver and Beattie 1996b;[START_REF] Derraik | Arthropod Morphospecies versus Taxonomic Species: a Case Study with Araneae, Coleoptera, and Lepidoptera[END_REF][START_REF] Majka | Parataxonomy: a test case using beetles[END_REF]). Nevertheless, these gross correlations based only on the number of morphotypes must be considered cautiously, as suggested by significantly smaller real vs. gross accuracy. This is explained by the fact that splitting and lumping of species compensate each other in the gross accuracy value. Thus, the correlation between species number and morphotype number can be viewed as partly fortuitous, as already demonstrated on various invertebrates groups [START_REF] Derraik | Arthropod Morphospecies versus Taxonomic Species: a Case Study with Araneae, Coleoptera, and Lepidoptera[END_REF][START_REF] Barratt | Morphospecies as a substitute for Coleoptera species identification, and the value of experience in improving accuracy[END_REF]) and bryophytes [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF].

In all comparisons, species were successfully used to discriminate habitat types. In contrast, morphotypes appeared less sensitive than species to habitat differences, although they proved useful to detect the largest changes. This result is consistent with those found on spiders (Oliver and Beattie 1996b), but differs from results on other groups, such as ants [START_REF] Pik | Taxonomic sufficiency in ecological studies of terrestrial invertebrates[END_REF] or beetles (Oliver and Beattie 1996b;[START_REF] Majka | Parataxonomy: a test case using beetles[END_REF]; in the two latter cases, morphotypes were sufficient to characterise β-diversity. We thus demonstrate that plant morphotypes, although useful for assessing species turnover in some situations, is not the most relevant approach due to a lower level of habitat discrimination than species.

Can parataxonomy be considered a scientific method?

The use of parataxonomy also questions the scientific criteria of our thought process. To our knowledge no study has ever tested repeatability (within observers) or reproducibility (across observers) in morphotype identification (but see [START_REF] Oliver | A Possible Method for the Rapid Assessment of Biodiversity[END_REF], who calculated the standard deviation of real accuracy among observers). In a recent review, [START_REF] Krell | Parataxonomy vs. taxonomy in biodiversity studies -pitfalls and applicability of "morphospecies" sorting[END_REF] argued that parataxonomy cannot be considered a scientific activity due to limited reproducibility, revealed by large variation in gross accuracy for a given taxonomic group among studies, which, he hypothesized, was partly attributable to variation in morphotype identification among sorters. Our results in the 'multiple volunteers' experiment support Krell's concerns: the strong 'volunteer' effect demonstrates that we cannot assume reproducibility of morphotypes identification across observers. In addition, we also demonstrated that parataxonomy may not be repeatable. The differences among volunteers could not be detected with APQE measures (showing no significant differences between botanists and volunteers) but were obvious from the examination of repeatability indices: on average, volunteers used twice as many morphotypes to describe a species across replicate plots than within plots. The difference between APQE measures and repeatability indices may be explained by the fact that the former reflect only variation in morphotype identification in the same habitat whereas the later encompass all habitats. The only way to overcome reproducibility and repeatability problems is to use more detailed and constrained methods, such as dichotomous identification keys and collection of voucher specimens deposited in herbarium, which may be as difficult and time-consuming as true taxonomy.

However, other methods of inventory based on true taxonomy and generally considered scientific methods also exhibit limited reproducibility. Variation among botanists, although rarely tested, can be significant [START_REF] Rich | Botanical recording, distribution maps and species frequency[END_REF]Rich 1998), inducing a pseudo-turn-over effect [START_REF] Leps | How Reliable Are Our Vegetation Analyses?[END_REF][START_REF] Rich | Recording bias in botanical survey[END_REF][START_REF] Oredsson | Choice of surveyor is vital to the reliability of floristic change studies[END_REF][START_REF] Kercher | Effects of sampling teams and estimation methods on the assessment of plant cover[END_REF][START_REF] Scott | Assessing species misidentification rates through quality assurance of vegetation monitoring[END_REF][START_REF] Archaux | Effects of sampling time, species richness and observer on the exhaustiveness of plant censuses[END_REF]). Hence, variation in species detectability and reproducibility across observers are significant constraints in all inventory methods. Nevertheless, as supported by our results on reproducibility and repeatability, we can assume that parataxonomy is more liable to such problems.

Parataxonomy should thus not be used in monitoring programs, unless its main limitation (lack of robustness) can be overcome. For example, computer assisted tools might help reducing the variability among observers. This can be done in two ways: (1) by providing databases with pictures of the different morphotypes, filled in by parataxonomists themselves, who can upload their own pictures to compare morphotypes with voucher specimens [START_REF] Basset | Quantifying Biodiversity: Experience with Parataxonomists and Digital Photography in Papua New Guinea and Guyana[END_REF][START_REF] Oliver | Virtual Biodiversity Assessment Systems[END_REF], (2) by using computer-aided identification that allows automatic species identification on the basis of morphological characters [START_REF] Gaston | Automated species identification: why not?[END_REF]). To our knowledge such approaches have been mainly developed with arthropods [START_REF] Do | A test of a pattern recognition system for identification of spiders[END_REF][START_REF] Arbuckle | Automatic identification of bees' species from images of their wings[END_REF][START_REF] Watson | Automated identification of live moths (Macrolepidoptera) using Digital Automated Identification SYstem (DAISY)[END_REF] in response to the "taxonomic impediment" [START_REF] Wheeler | Taxonomy: impediment or expedient[END_REF]), but they could be used by amateurs to monitor plants in the near future, with the development of online databases (e.g. NatureGate® project, Åhlberg et al. 2006). Keeping in mind our results on accuracy, we can assume that, although these expensive methods are likely more reproducible than the one we used, they are also sensitive to the problem of intraspecific dimorphism, and must be implemented with caution, especially to monitor species turnover.

Can parataxonomic data be used for large scale monitoring of plants in common ecosystems?

Many examples of large scale biomonitoring programs in common ecosystems involve the work of hundreds of amateurs (coordinated by professionals) using standardized protocols, repeated over time [START_REF] Stewart | People and Plants: mapping the UK's wild flora[END_REF]). These programs essentially consist of recording the presence and absence of species in a given area and mapping their distribution [START_REF] Teder | Monitoring of Biological Diversity: a Common-Ground Approach[END_REF]. Data collected can be used to assess how the abundance of species (estimated e.g. as the number of replicates in which a species has been recorded) changes between successive surveys [START_REF] Smart | Large-scale changes in the abundance of common higher plant species across Britain between 1978, 1990 and 1998 as a consequence of human activity: Tests of hypothesised changes in trait representation[END_REF], thus enabling the detection of local extinction or increase in frequency of a given species. Coupling such data with information on species characteristics (e.g. life history trait, habitat preferences, global distributions) and environmental data (e.g. habitat destruction, fragmentation, nutrient enrichment, climate changes) may help assessing some of the mechanisms responsible for biodiversity loss [START_REF] Smart | National-scale vegetation change across Britain; an analysis of sample-based surveillance data from the Countryside Surveys of 1990 and 1998[END_REF][START_REF] Smart | Large-scale changes in the abundance of common higher plant species across Britain between 1978, 1990 and 1998 as a consequence of human activity: Tests of hypothesised changes in trait representation[END_REF]. For example, biotic homogenisation, i.e. the gradual replacement of specialist species by a few generalist species [START_REF] Mckinney | Biotic homogenization: a few winners replacing many losers in the next mass extinction[END_REF][START_REF] Olden | Ecological and evolutionary consequences of biotic homogenization[END_REF][START_REF] Rooney | Biotic Impoverishment and Homogenization in Unfragmented Forest Understory Communities[END_REF]) can be detected by repeated surveys [START_REF] Smart | Biotic homogenization and changes in species diversity across human-modified ecosystems[END_REF].

In comparison, the use of parataxonomic data in large scale monitoring can be a pitfall, if used without caution to address these issues. First, morphotypes are less accurate than species at detecting turnover among habitats. In addition, lack of reproducibility and repeatability in morphotype identification may artificially inflate differences among habitats or across time. Finally, species characteristics can not be incorporated in such monitoring programs, due to the impossibility of assigning a single code to a given species. Therefore, a large scale change, if detected, may not be easily interpreted due to the impossibility of assessing the direction and drivers of changes.

Conclusion

Parataxonomy can be viewed as a useful complement to taxonomic methods, enabling to quickly include the wider landscape matrix in global monitoring programs, where naturalist knowledge is often unavailable. This could allow the redeployment of skilled naturalists in « hotspots » [START_REF] Oliver | Future Taxonomic Partnerships: Reply to Goldstein[END_REF] where identification of rare species requires high levels of competence, and enable the multiplication of replicates at large scale, encompassing all habitat types [START_REF] Oliver | Virtual Biodiversity Assessment Systems[END_REF].

Nevertheless, parataxonomy cannot be considered a sustainable solution to the loss of taxonomists. In developed countries, morphotypes must be viewed only as a temporary solution, providing incomplete data, which is always better than no data, while taxonomist skills are missing. But in the long term conservationists and ecologists will not be able to do without naturalist skills. Species are more than just a code number, without biological content [START_REF] Goldstein | How Many Things Are There? A Reply to Oliver and Beattie, Beattie and Oliver, Oliver and Beattie, and[END_REF], they are essential knowledge to achieve the exploration of community processes and diversity.

Figure 1 :

 1 Figure 1: Criteria used in morphotype identification. Plants are first separated into graminoids (A) and forbs (B).A single character is considered for graminoids, whereas a list of five characters is provided for forbs. Each character is coded by a number corresponding to a given character state. A morphotype is defined as a combination of character states.

Figure 2 :

 2 Figure 2: Non-Metric Multidimensional Scaling (NMDS) plot of data using Bray-Curtis distances. Each point represents a plot surveyed by a volunteer or by botanists. Symbols indicate the four habitat types: (○), grass strip; (∆), wood edge; (×), hedge; (+), fallow land. Assuming that there are no significant differences among botanists, a consensus of species observed is presented. Stress values, measuring the disagreement between the inter-point distances on plot and these distances in the original distance matrix, are shown on the upper-right corner of each ordination scatter plot. PERMANOVA F-ratios and Mantel correlation coefficients between species assemblage and morphotype assemblage are displayed beneath each ordination. All are significant (P<0.05). Habitat type considered by PERMANOVA pairwise comparisons to contain significantly different assemblages have been outlined by curves.

Figure 3 :

 3 Figure 3: Mean ratio of species to morphotypes based on all volunteer data. The 1:1 class represents correct identifications. Classes to the right represent cases of splitting and those to the left represent cases of lumping.

Table 1 :

 1 Summary of non-parametric MANOVA in the 'botanist versus volunteer' experiment. Asterisks indicate significant differences between habitats (P<0.05).

			F-ratio
		Species Morphotype
	All habitats	3.69 *	2.27*
	Group comparison
	footpath vs. wood edge	1.71 *	1.23
	footpath vs. fallow land	1.49 *	1.04
	footpath vs. grass strip	2.00 *	1.31
	footpath vs. road side	1.94 *	1.86 *
	wood edge vs. fallow land 1.75 *	1.19
	wood edge vs. grass strip 2.32 *	1.13
	wood edge vs. road side 1.75 *	1.64 *
	fallow land vs. grass strip 1.43 *	1.24
	fallow land vs. road side	1.95 *	2.26 *
	grass strip vs. road side	2.57 *	1.69 *

Table 2 :

 2 Summary of diversity assessment by volunteers(Vol). A total of 64 species were sorted into various numbers of morphotypes (first line). The correlations between the number of species and the number of morphotypes per plot were all positive and significant; R-squared values are given on the second line. Gross accuracy is defined as 100-|(A-B) /A|, where A is the number of species and B the number of morphotypes. Real accuracy corresponds to the proportion of correct identification. In the case of lumping, one or more morphotype is assigned to one species. Splitting correspond to the opposite case.

	Source	df	SS	MS	F	P
	MORPHOTYPES
	observer	7	105610.8679	15087.2668	8.0232	0.0010
	habitat type	3	96841.6164	32280.5388	6.2146	0.0010
	observer x habitat type	21	109080.6259	5194.3155	2.7623	0.0010
	Residual	128	240697.4089	1880.4485
	SPECIES
	observer	2	1016.6018	508.3009	0.3226	0.9950
	habitat type	3	100315.6419	33438.5473	71.9597	0.0010
	observer x habitat type	6	2788.1047	464.6841	0.2949	1.0000
	Residual	48	75633.2211	1575.6921

Table 3 :

 3 Non-parametric MANOVA on Bray-Curtis distances for assemblage of morphotypes and species

Table 4 :

 4 Repeatability of morphotype identification. The first three lines are results of the apportionment of quadratic entropy. Percentages correspond to decomposition of the total diversity found with species by botanists (Bot) and morphotypes by volunteers (Vol). Diversity among plots within habitat type was compared between botanists and volunteers as a first way to assess repeatability of morphotype identification. The repeatability index is the ratio of the total number of morphotypes to the mean number of morphotypes per plot, averaged over all species.

	Diversity Source	Bot # 1 Bot # 2 Bot # 3 Vol # 1 Vol # 2 Vol # 3 Vol # 4 Vol # 5 Vol # 6 Vol # 7 Vol # 8
	Between habitat
	type	3.7	4.3	4.5	3.4	3.2	4.3	2.7	3.2	5.3	3.3	3.4
	Between plot Within
	habitat type	5.5	6.7	7.5	6.8	7.2	6.7	6.9	7.6	9	9.1	6.4
	Within plot	90.9	89	88	89.8	89.5	89	90.4	89.2	85.7	87.7	90.2
	Repeatability index				2.1	2	1.7	1.8	2.1	2	1.9	2

Acknowledgments

The authors thank Lorraine Bottin, Florence Devers, Margaret Evans, Anne-Sophie Gadot, Isabelle Le Viol, Jean-Baptist Mihoub, and Audrey Muratet for their precious help in field experiments. We also acknowledge Tim Rich and one anonymous reviewer for helpful comments which greatly improved this manuscript. This study was funded by Ile-de-France region.


Jacques Soffer

Claude Bourrely
email: claude.bourrely@cpt.univ-mrs.fr

On the flavor structure of the light-quark sea distributions

Keywords: Statistical parton model, helicity parton distributions, sea quarks

The flavor structure of the nucleon sea provides unique information to test the statistical parton distributions approach, which imposes strong relations between quark and antiquarks. These properties for unpolarized and helicity distributions have been verified up to now by recent data. We will emphasize the properties of the light-quark sea and present here some new results which are a real challenge for forthcoming accurate experimental results, mainly in the high Bjorken-x region.

Introduction

The structure of the nucleon sea is an important topic which has been the subject of several relevant review papers [1,2]. In spite of considerable progress made in our understanding, several aspects remain to be clarified, which is the goal of this paper. The properties of the light quarks u and d, which are the main constituents of the nucleon, will be revisited in the quantum statistical parton distributions approach proposed more than one decade ago. These properties worth a separate presentation not developped in the original paper [3]. It is well known that the u quark dominates over the d quark, but for antiquarks, SU(2) symmetry was assumed for a long time, namely the equality for the corresponding antiquarks, ū = d, leading to the Gottfried sum rule [4]. However, the NMC Collaboration [5] found that this sum rule is violated, giving a strong indication that d > ū.

In the statistical approach we impose relations between quarks and antiquarks and we treat simultaneously unpolarized distributions and helicity distributions, which strongly constrain the parameters, a unique situation in the literature. As we will see, this powerful tool allows us to understand, not only the flavor symmetry breaking of the light sea, but also the Bjorken-x behavior of all these distributions and to make challenging specific predictions for forthcoming experimental results, in particular, in the high-x region. The paper is organized as follow: in section 2 the main properties of the parton structure in the statistical model are explained. In section 3, we present a comparison of the results obtained by the model with unpolarized and polarized experimental data, in the case of configuration associated with light sea quarks. Our conclusions are presented in section 4.

Structure of the parton statistical model

In our model the building blocks of the parton structure are the helicity components defined by the sum of two terms: a generic quasi Fermi-Dirac function

A q Y h q x bq exp[(x -Y h q )/x] + 1 , (1)
where Y h q are the thermodynamical potentials, x plays the role of a universal temperature. The other term is a helicity independent diffractive contribution

Ãq x bq exp(x/x) + 1 , (2)
which controls the low x behavior of the distributions. This term is absent in the quark helicity distribution ∆q = q + -q -, in the quark valence contribution qq and in ud if one assumes Ãu = Ãd .

A fit of unpolarized and polarized data leads to the solution given in Ref. [3] for the Parton Distribution Functions PDFs starting at the input energy scale Q 2 0 = 1GeV 2 . For the quarks the helicity distributiions read:

xq h (x, Q 2 0 ) = A q X h q x bq exp[(x -X h q )/x] + 1 + Ãq x bq exp(x/x) + 1 , (3)
and for the antiquarks

xq h (x, Q 2 0 ) = Āq (X -h q ) -1 x bq exp[(x + X -h q )/x] + 1 + Ãq x bq exp(x/x) + 1 . (4)
X ± q are the two thermodynamical potentials of the quark q, with helicity h = ±, the temperature has the value x = 0.09. These potentials represent the fundamental parameters of the approach whose values are

X + u = 0.475±0.001, X - u = X - d = 0.307±0.001, X + d = 0.244±0.001. ( 5

) The others parameters have the values:

A q = 1.943 ± 0.005, b q = 0.471 ± 0.001 Āq = 8.915 ± 0.050, bq = 1.301 ± 0.004, Ãq = 0.147 ± 0.003, bq = 0.0431 ± 0.003 .

The number of free parameters is reduced to seven by the valence sum rule, (q(x) -q(x))dx = N q , where N q = 2, 1 for u, d, respectively. In Eqs. (3,4) the multiplicative factors X h q and (X -h q ) -1 in the numerators of the first terms of the q's and q's distributions, was justified in our attempt to generate the transverse momentum dependence of the PDFs [6].

Notice that following the chiral properties of QCD, we have X h q = -X -h q in the exponentials. In other parton models, unpolarized and polarized distributions for quarks, antiquarks, are treated as four separated quantities, while in the statistical model the appearance of the same potentials in q and q shows a strong relation between quarks and antiquarks. Looking at Eqs. ( 5) it turns out that two potentials X - u , X - d have identical numerical values, so for light quarks results the following hierarchy between the different potential components

X + u > X - u = X - d > X + d . (7)
We also notice that quark helicity PDFs increase with the potentials value, while antiquarks helicity PDFs increase when the potentials decrease.

The above hierarchy implies the following hierarchy on the quark helicity distributions for any x, Q 2 ,

xu + (x, Q 2 ) > xu -(x, Q 2 ) = xd -(x, Q 2 ) > xd + (x, Q 2 ) , (8)
and also the obvious hierarchy for the antiquarks, namely

x d-(x, Q 2 ) > x d+ (x, Q 2 ) = xū + (x, Q 2 ) > xū -(x, Q 2 ). (9)

Light sea quarks results compared with experiments

In several experiments an attempt is worked out to extract PDFs at a given x and Q 2 values, which is a difficult task but useful to check the models. In this section a comparison between the predictions of our model and the available experimental data will be discussed, with an emphasize on the antiquarks contribution.

As a preliminary description of the helicity distributions structure we show in Figs. 12, the resulting distributions at Q 2 = 54GeV 2 . This peculiar Q 2 correspond to a measurement made by the E866 experiment [7,8].

One sees in Fig. 1 that the largest distribution is indeed

xu + (x, Q 2 )
, it has a distinct maximum around x = 0.3, which is also responsible for the maximum observed in the polarized structure function g p 1 (x, Q 2 ) at the same x value.

In Fig. 2, at large x, the distribution dis slightly larger than ū-, this property implies that the ratio d/ū is larger than 1 and increasing with x, we will come back later to this point.

We have also checked that the initial analytic form Eqs. (3,4), is almost preserved by the Q 2 evolution with some small changes of the parameters value.

This general pattern displayed in Figs. 12, does not change much for different Q 2 values. In our approach one can conclude that, u(x, Q 2 ) > d(x, Q 2 ) implies a flavor symmetry breaking of the light sea, i.e. d(x, Q 2 ) > ū(x, Q 2 ), which is clearly seen in Fig. 2.

A simple interpretation of this result is a consequence of the Pauli exclusion principle, based on the fact that the proton contains two u quarks and only one d quark. It is important to note that these inequalities Eqs. (8,9) are preserved by the next-to-leading order QCD evolution, at least outside the diffractive region, namely for x > 0.1.

xf (x, Q 2 ) (f = u + , u -= d -, d + ), versus x, at Q 2 = 54GeV 2 , after NLO QCD evolution, from the initial scale Q 2 0 = 1GeV 2 .
We now turn to more significant outcomes concerning the helicity distributions which follow from Eqs. (8,9). First for the u-quark

x∆u(x, Q 2 ) > 0 x∆ū(x, Q 2 ) > 0. ( 10
)
Similarly for the d-quark

x∆d(x, Q 2 ) < 0 x∆ d(x, Q 2 ) < 0. ( 11
)
Figure 2: The different helicity components of the light antiquark distribu-

tions xf (x, Q 2 ) (f = d-, d+ = ū+ , ū-), versus x, at Q 2 = 54GeV 2 , after NLO QCD evolution, from the initial scale Q 2 0 = 1GeV 2 .
So once more, quarks and antiquarks are strongly related since opposite signs for the quark helicity distributions, imply opposite signs for the antiquark helicity distributions, (see Eqs. (3,4)), at variance with the simplifying flavor symmetry assumption x∆ū(x, Q 2 ) = x∆ d(x, Q 2 ).

Our predicted signs and magnitudes for distributions [3] have been confirmed by the measured single-helicity asymmetry A L in the W ± production at BNL-RHIC from STAR [9]. For the extraction of helicity distributions, this process is expected to be cleaner than semi-inclusive DIS, because it does not involve fragmentation functions.

Another important earlier prediction concerns the Deep Inelastic Scattering (DIS) asymmetries, more precisely (∆q(x, Q 2 ) + ∆q(x, Q 2 ))/(q(x, Q 2 ) + q(x, Q 2 )) (q = u, d), shown in Fig. 3. Note that the JLab [10] data and the COMPASS [11] data are in agreement with these predictions, in particular, in the high-x region where there is a great accuracy. Beyond x = 0.6, this is a new challenge for the JLab 12 GeV upgrade, [START_REF] Hafidi | JLAB approved proposal E[END_REF] with an extremely high luminosity, it will certainly reach a much better precision.

There are two more strong consequences of the equalities in Eqs. (8,9),

Figure 3: NLO predicted ratios (∆u(x, Q 2 )+∆ū(x, Q 2 ))/(u(x, Q 2 )+ū(x, Q 2 )) and (∆d(x, Q 2 ) + ∆ d(x, Q 2 ))/(d(x, Q 2 + d(x, Q 2 )), versus x, at Q 2 (GeV 2 ) =
1 solid, 10 dashed, 100 dashed-dotted, 1000 long-dashed. Data are from Refs.

[10] (Jlab) and [11] (COMPASS).

Figure 4: The data on x[∆u(x, Q 2 ) -∆d(x, Q 2 )] from Refs. [10] (JLab) and [11] (COMPASS), compared to the statistical model prediction at NLO, using Eq. ( 12) with the corresponding error band.

which relate unpolarized and helicity distributions, namely for quarks

xu(x, Q 2 ) -xd(x, Q 2 ) = x∆u(x, Q 2 ) -x∆d(x, Q 2 ) > 0, (12)
and similarly for antiquarks

x d(x, Q 2 ) -xū(x, Q 2 ) = x∆ū(x, Q 2 ) -x∆ d(x, Q 2 ) > 0. ( 13
)
These equalities mean that the flavor asymmetry of the light quark and antiquark distributions is the same for the corresponding helicity distributions, as noticed long time ago, by comparing the isovector contributions to the structure functions 2xg

(p-n) 1 (x, Q 2 ) and F (p-n) 2 (x, Q 2 )
, which are the differences on proton and neutron targets [START_REF] Bourrely | [END_REF].

We have checked that using Eq. ( 12) it is possible to predict the helicity distributions from the unpolarized distributions, as displayed in Fig. 4. This difference, which is indeed positive, has a pronounced maximum around x = 0.3, reminiscent of the dominance of xu + (x, Q 2 ). Similarly one can use Eq. ( 13), to predict the difference of the antiquark helicity distributions and the result is shown in Fig. 5.

Figure 5: The data on x[∆ū(x, Q 2 ) -∆ d(x, Q 2 )] from Refs. [14] (HERMES) and [11] (COMPASS), compared to the statistical model prediction at NLO, using Eq. ( 13) with the corresponding error band.

Although compatible with zero it is slightly positive, but JLab 12GeV upgrade is expected to reach a much better accuracy [START_REF] Hafidi | JLAB approved proposal E[END_REF].

Let us inspect the x-behavior of all these components xu + (x, Q 2 ), .., xū -(x, Q 2 ), which are all monotonic decreasing functions of x at least for x > 0.2, outside the region dominated by the diffractive contribution (see Figs. 12). As already said, xu + (x, Q 2 ) is the largest of the quark components and similarly x d-(x Q 2 ) is the largest of the antiquark components.

The ratio xd(x, Q 2 )/xu(x, Q 2 ) value is one at x = 0, because the diffractive contribution dominates and, due to its monotonic character, it decreases for increasing x. This x-behavior is strongly related to the values of the potentials X h 0q . This falling x-behavior has been verified experimentaly from the ratio of the DIS structure functions F d 2 /F p 2 and from the charge asymmetry of the W ± production in pp collisions [START_REF] Bourrely | [END_REF]15].

Similarly if one considers the ratio

x d(x, Q 2 )/xū(x, Q 2 )
, its value is one at x = 0, because the diffractive contribution dominates and, due to the slightly larger value of dover ū-, it increases for increasing x (see Fig. 2). An illustration on the behavior of the ratios xd(x, Q 2 )/xu(x, Q 2 ) and xū(x, Q 2 )/x d(x, Q 2 ) is given in Fig. 2 of Ref. [16]. We observe a mild dependence in Q 2 in the range 1-100GeV 2 . Now let us pay a special attention to the Drell-Yan cross section. In the introduction we have recalled the first indication by the NMC Collaboration for a flavor asymmetry of the nucleon sea d(x) > ū(x).

There is another way to probe this asymmetry, which is the ratio of the proton-induced Drell-Yan process σ(pd)/2σ(pp) on a deuterium and an hydrogen targets. At forward rapidity region, the Drell-Yan cross section is dominated by the annihilation of a u-quark in the incident proton with the ū-antiquark in the target. Assuming charge conjugaison one can show at LO the approximate expression

σ(pd)/2σ(pp) ∼ 1/2[1 + d(x 2 )/ū(x 2 )], (14)
where x 2 refers to the momentum fraction of antiquarks. The major advantage of the Drell-Yan process is that it allows to determine the x dependence of d/ū. We show in Fig. 6 the predicted ratio σ(pd)/2σ(pp) versus x target at p lab = 800GeV together with the E866 data from Refs. [7,8], the agreement is limited to x target < 0.2. On the same figure is shown the preliminary results of the SeaQuest E906 experiment at p lab = 120GeV [START_REF] Dove | Status of the measurement of the flavor dependence of lightquark sea in the SeaQuest experiment[END_REF] which are in better agreement with our model.

The slow variation of d/ū with Q 2 and the increase with x which come in our model from an analysis of a large set of experimental data implies a weak energy dependence of the ratio σ(pd)/2σ(pp), so the rapid decrease of the E866 experiment above x target > 0.2 is really unexpected. To complete the Figure 6: The Drell-Yan cross section ratios of σ(pd)/2σ(pp) versus x target (momentum fraction of the target partons) data from (E866) p lab = 800GeV Refs. [7,8], SeaQuest E906 p lab = 120GeV . The curves are the statistical model predictions at NLO. picture the extracted ratio d(x)/ū(x) for Q 2 = 54GeV 2 ( [7,8]) is displayed in Fig. 7, it shows a remarkable agreement with the statistical model prediction up to x = 0.2.

By assuming SU(3) symmetry it is possible to generate the PDFs for the baryon octet and to calculate the corresponding Drell-Yan cross section ratios. The results shown in Fig. 8 might be of interest to study the sea structure of the hyperons when future hyperon beams at LHC in a fixedtarget mode will become available.

In the Λ case one expects no flavor symmetry breaking since it contains one u-quark and one d-quark and under SU(3) symmetry one has, ūΛ = dΛ = (ū + d)/2 (see Table 1 of Ref [START_REF] Ma | [END_REF]). This is not the case for the Σ ± which under SU(3) symmetry one expects ūΣ + /s Σ + = ū/ d, and ūΣ -/s Σ -= s/ d, this effect is clearly seen in Fig. 8. The sea quark asymmetries in Σ ± for different models is discussed in Ref. [19]). If we consider the Drell-Yan cross section ratio for difference Λ 0 -Σ 0 we observe in Fig. 8 a small but non zero value.

Figure 7: The ratio d(x, Q 2 )/ū(x, Q 2 ), versus x for Q 2 = 54GeV 2 . The data from Refs. [7,8] (E866) are compared with the statistical model prediction with the corresponding error band at NLO. Figure 8: The Drell-Yan cross section ratios of σ(Bd)/2σ(Bp) versus x 2 (momentum fraction of the target partons) data from (E866) Refs. [7,8]. The curves arethe statistical model predictions for different incoming beams B = p, Λ 0 , Σ + , Σ -, Λ 0 -Σ 0 at p lab = 800GeV.

In order to obtain more information on the anti-quark the STAR experiment [START_REF] Posik | Constraining the Sea Quark Distributions Through W ± Cross Section Ratio Measurements at STAR[END_REF] at RHIC measures the ratio R W = σ(W + ) σ(W -) at the energy √ s = 500/510 GeV as a function of the W rapidity. Taking an approximate expression of the cross section ratio for W ± production at LO, we get an information on the quantity d/ū through the relation

R W = σ(W + ) σ(W -) ∼ u(x 1 ) d(x 2 ) + u(x 2 ) d(x 1 ) d(x 1 )ū(x 2 ) + d(x 2 )ū(x 1 ) . ( 15
)
A comparison of the statistical model result at NLO with preliminary data [START_REF] Posik | Constraining the Sea Quark Distributions Through W ± Cross Section Ratio Measurements at STAR[END_REF] shown in Fig. 9 gives a reasonable agreement.

Figure 9: The ratio R W = W + /W -, versus the W rapidity y W for Q 2 = M 2 W GeV 2 √ s = 500/510 GeV calculated at NLO. Preliminary data are from Ref. [START_REF] Posik | Constraining the Sea Quark Distributions Through W ± Cross Section Ratio Measurements at STAR[END_REF] 4 Conclusions

To conclude we have compared the predictions of the statistical model PDFs with respect to the results of different unpolarized and polarized experiments, the agreement obtained in different kinematical domains confirms the validity of the model, however it remains to probe the model for larger x and Q 2 values. For instance, we observe a monotonic increase of the ratio

x d(x, Q 2 )/xū(x, Q 2 ) predicted in our approach, which is a consequence of strong relations between polarized quark distributions (see Eq. ( 13)). Very recently there was a serious indication from the preliminary results of the SeaQuest collaboration [START_REF] Reimer | Invited talk at[END_REF], that this ratio rises beyond x = 0.2, at variance with several other model predictions, as reported in Figs. 7 and 8 of Ref. [2]. This prediction is a real challenge for the statistical approach, whose strong predictive power will be also confronted with several other forthcoming accurate data measured, for instance, by the STAR experiment [START_REF] Posik | Constraining the Sea Quark Distributions Through W ± Cross Section Ratio Measurements at STAR[END_REF], in the high-x region, a region which remains poorly known.

Figure 1 :

 1 Figure 1: The different helicity components of the light quark distributionsxf (x, Q 2 ) (f = u + , u -= d -, d + ), versus x, at Q 2 = 54GeV 2 , after NLO QCD evolution, from the initial scale Q 2 0 = 1GeV 2 .

Acknowledgement

J.S is very grateful to Prof. Norbert Vey and his team (Institut Paoli-Calmettes Marseille) for making possible most part of this work. Unfortunately the illness prevented him to complete the paper development.


Dr Jasmeet Lamba
email: jasmeet.kaur81@gmail.com

Dr Bhumika Gupta
email: bhumika.gupta@imt-bs.eu

Sam Dzever
email: sam.dzever@imt-bs.eu

INDUSTRIALIZATION AND GLOBAL WARMING (A BRIEF CASE ANALYSIS OF PALM OIL PRODUCTION: INDONESIA)

Keywords: Climate Change, Global Warming, Ecological Economics, Sustainability

Ever since the last decade palm oil production has increased many folds and so has the use of the oil in various industries. Indonesia is the largest producer of palm oil in the world and produced 32.5 million tonnes of crude palm oil in 2014, exporting almost 80% of it to yield a considerable USD$18.6 billion in revenue. The numbers went up even further with 36 million tonnes of palm oil produced in 2017 alone. Evidently, the surge has given major boost to the palm oil industry, which has become the biggest currency earner in Indonesia, considering it is only second to Malaysia as the world's largest exporter of palm oil. However, the flip side of it is the devastating effect it has on the environment. Destruction of forests has led to catastrophic effects on our ecosystem. Institutional investors as well as individuals play a key role in financing the expansion of palm oil industry and are able to minimize the destruction caused by deforestation. A large-scale promotion of land grab-free investment policies and practices is definitely a first step in the direction. Depletion of natural resources causing serious and immediate health issues, and in some cases, overall survival of communities is an act of human rights violation and must be dealt with seriousness and sensitivity.

Introduction -

On 28 th February 2016, at the 88 th Academy Awards ceremony held at the Dolby Theater in Los Angeles, film celebrities, ardent fans and surprisingly, environmentalists from all over the world, rejoiced in common happiness when the blue-eyed-boy of Hollywood, Leonardo DiCaprio was announced the winner in the Best Actor in a Leading role category. Of course, for environmentalists across the globe, the joy was multifold, for DiCaprio's constant efforts in raising awareness for the world's number one environmental challenge -Global Warming had put him in the league of some of the most prolific scientists, explorers and social activists.

Later that year, as United Nations Messenger for peace on Climate change and Global Warming, DiCaprio visited one of the only three remaining tropical rainforests in the world in Sumatra, Indonesia (others being the Amazon in South America and Congo Basin in Africa) and was able to bring to everyone's notice the exceedingly alarming rate with which the forests in Sumatra were being burnt in order to produce 'palm oil" which is used in a variety of processed foods in the domestic as well as international market. Used on a huge scale in cooking oils, processed foods, cosmetics, detergent, shampoo, this cheap commodity is making companies like Burger King, Doritos, PepsiCo, Cup noodles NISSIN, Quaker among others tremendous profits.

Source: Palm Oil Consumption

Statistics show how the surge in demands of palm oil worldwide, primarily due to low cost of production, has fueled interest in global corporations to replace the traditional vegetable oil sources and switch to the all-beneficial palm oil. From a meagre 13.5 million tonnes of production in 1990, to a staggering 155.8 million tonnes in 2014, the rise in demands can largely be contributed to its usage in bio fuel. As per the European Palm Oil Alliance report of 2015, India, China and EU, all major importers of palm oil, accounted for 47.9% of the total global imports.

Literature review

According to a paper written by Helen McGregor (2015) and team, the findings suggested that global warming started as early as 1830 in most tropical and arctic regions. In the years to follow, other continents -Europe, Asia and North America joined the bandwagon of climate change.

Another study by Koh & Wilcove (2016) stated that forest harvested for wood products are capable of regenerating 84% of forest species within 30 years of deforestation. However, expansion of oil palm plantations does not support regeneration, thereby causing significant loss of biodiversity.

According to the Greenpeace UK feature published in June 2017, Indonesia's rainforests are rich in biodiversity and endemic species and play a crucial part in controlling the planet's climate. Despite being such a vital part in the globe's ecosystem, the rainforests are being torn down and burnt for oil palm plantations, making Indonesia the third largest greenhouse gas emitter in the world.

As per the white paper written by [START_REF] Petrenko | Ecological Impacts of palm oil expansion in Indonesia[END_REF], Indonesia is one of the world's top five emitters of greenhouse gases, and in a reformatory act, has set a goal to reduce its emissions by 26% by 2020. However, it is nearly impossible for the country to reduce its emissions to such an extent as almost 75% of CO2-equivalent emission is due to land use change including destruction of peatlands, all attributing to BAU palm oil production.

According to an article by Ben Block (2013) of Worldwatch Institute, Indonesia is the biggest producer of palm oil in the world and, alongside Malaysia, is leading the global supply chain. In an attempt to avoid fluctuation in prices, both Indonesia and Malaysia have been urged to increase domestic supply, which resulted in Indonesia passing a mandate requiring all the cars and trucks to run on palm oil mixed bio-diesel. Handling the domestic demands in addition to meeting global requirements of palm oil accelerated its production and has resulted in massive destruction of rainforests and peatlands, carbon rich swamps responsible for 10 times more carbon emission.

The review by Earl Saxon and Sarah Roquemore, carbon emissions by palm oil industries can be significantly reduced if the land selection in the entire process is done more responsibly. Deforestation of national parks and peatlands not only poses threat to endangered animals and biodiversity, but also releases copious amounts of carbon into the atmosphere, in turn, drastically changing the climate. Also, a brief by Friends of the Earth, the magnitude of impact that conversion of peatlands to palm oil plantations has is at par with world's biggest coal and tar sands projects. The expansion of palm oil industry will continue to worsen climate change and severely affect the health and wellbeing of communities and ecosystems across the region.

A feature by Union of Concerned Scientists states that while demand for production of palm oil has increased considerably in South America and Africa, it has skyrocketed in Southeast Asia, particularly in Indonesia, the largest producer of palm oil in the world. Draining and burning of peatlands to clear the land for oil palm plantation has precariously exposed carbon rich lands capable of holding up to 28 times more carbon than usual forests. However, as of 2016, more than 60% of palm oil purchased by US based companies is deforestation and peat land-free, thanks to the intense pressure imposed by environmentalists and social activists globally. A review of above stated studies clearly reveals an ongoing debatable issue of global warming increasing due to burning of rainforests for palm oil. Even on the demand side the product is widely in depiction and has been a major source of income for countries like Indonesia.

Objectives and Research Methodology:

In lieu of the above stated literature reviews it is clear that the issue of global warming and climate change is gradually increasing pace in the modern world scenario. The question of heavy industrialization in the cost of the environment needs some extremely strong and practical answers. These answers are to be worked upon at the same pace as global warming.

The principal objective of the proposed paper is to analyze the current situation of rainforests being burnt for palm oil in Indonesia as this is one of the three remaining tropical rainforests in the world in Sumatra.

Second objective is to discuss the issue that burning of these forests is largely causing climate change through carbon emissions and are the major source of greenhouse gases. This is leading to climate change and deforestation in the region.

For the purpose of seeking holistic picture of the topic the study is based on secondary data collected from various sources such as Annual Reports of climate change forum and Research Foundation. Data is also collected and analyzed from the yearly publications of Central Statistical Organization on the basis of National aggregates. Article published through online resources were also studied for the overall view of the situation.

Analysis:

Indonesia is the largest producer of palm oil in the world and produced 32.5 million tonnes of crude palm oil in 2014, exporting almost 80% of it to yield a considerable USD$18.6 billion in revenue. The numbers went up even further with 36 million tonnes of palm oil produced in 2017 alone. Evidently, the surge has given major boost to the palm oil industry, which has become the biggest currency earner in Indonesia, considering it is only second to Malaysia as the world's largest exporter of palm oil. However, the flip side of it is the devastating effect it has on the environment. Destruction of forests has led to catastrophic effects on our ecosystem. Sumatran rainforests are the last natural habitat in the world to host orangutan, elephants, tigers and rhinos together. A major population of orangutans is dead as a result of deforestation and firedestruction with only 70,000 of them alive and still roaming in the rainforests across South East Asia. The expansion of palm oil industries in Indonesia has taken over about 80% of its forests.

In Sumatran rainforests, corporations are intentionally setting fire in large sections to clear the land for palm oil plantations. This has led to copious amounts of carbon being released in the atmosphere, in turn making Indonesia one of the world's worst emitters of greenhouse gases. The carbon emission in Indonesia due to the common slash-and-burn tactic daily is more than the entire US economy.

Source: footprints/palm oil/ foe.org

In addition to tropical rainforests, the peatlands (carbon rich swamps) containing 10 times more carbon are also used for palm oil production, and since the easiest way to clear the lands is by setting them on fire, the irresponsible approach by major corporations has led to more devastation eventually resulting in complete and utter destruction in the region. Trees capture and store CO2 and it is released when trees are burned. Tropical deforestation contributes to about 15% of total global warming pollution on an annual basis, which is way more than cars, trucks, ships and planes in the world combined. In Indonesia, deforestation to clear the land for palm oil plantations is even more devastating since it happens on peat lands. Statistically, the total stored carbon of peatlands in Indonesia is as much as the entire above surface vegetation of the Amazon. Unfortunately, 10 million acres of the country's 22.5 million acres of peat lands have already been deforested by palm oil industries and the number is expected to be doubled by 2020.

Overall projection of land harvesting not only poses a major threat to the ecosystem but is also enough to propel the rate with which we are warming our planet. Land harvesting for oil palm in Indonesia grew from 4.1 million hectares to an alarming 8.9 million hectares in 2015 and is expected to go as high as 17 million in 2025

According to a report released by the United Nations Environment program, peatland destruction could result in more than 2000 percent more greenhouse emissions than burning diesel oil.

Simply stated, if all of Indonesia's peatlands were set on fire, they would emit as much greenhouse gases into the atmosphere as carbon emissions from fossil fuel over nine years. Considering the rate with which peatlands are being destroyed to be used for oil palm plantations, the 2025 projections could easily be surpassed by 2020, thereby setting the stage for complete destruction of one of the only three remaining large rainforests in the world.

Source: Palm Oil, Root of the Problem

In a nutshell, after the boreal ecosystem, tropical forests are home to the largest terrestrial carbon sink on planet earth, holding approx. 428Gt C. Our atmosphere, in comparison, stores approx. 589Gt C, leading to the fact that a minor disruption in land carbon emission could result in perilous rise in our planet's temperature. Since its impact is so severe to the nature, many efforts have been made in the direction to not only combat the ongoing destruction of rainforests but also to set global standards in determining which companies are following the safety standards in the overall production of palm oil. The first major step was taken back in 2004 when RSPO or Round Table on Sustainable Palm Oil was founded by group of scientists, environmentalists and stakeholders to promote growth and consumption of sustainable palm oil products through an established set of global standards and their lawful enforcement. In order to get their products cleared with RSPO certification, companies must pledge to meet the globally established criterion including complete withdrawal from clearing peatlands/rainforests. However, owing to the complex process flow of palm oil production involving a vast network of companies, coupled by Indonesia's corrupt law enforcement, it became quite a challenge to put things into practice from day one. Authorities were unable to stave off the problem because of the high-level corruption. Indonesia is one of the most corrupt countries in the world and in its northernmost region in Sumatra, the law enforcement is even more challenging than the rest of the nation. In 2010, six years after its inception, the credibility of RSPO was challenged when one of the leading palm oil producing companies, the Sinar mas Group came under international scrutiny when Greenpeace report accused the conglomerate of "pulping the planet" by using slash and burn tactic to clear forests for oil palm plantations. Doing so not only posed great danger to the environment but also threatened endangered species, all in the name of profit.

Despite international pressure and protests from environmentalists, the 'slash and burn' devastation continued and by 2012, Indonesia overtook Brazil as the country with the most rapid deforestation in the world, having destroyed 8,40,000 hectares of forest. The following year, in an attempt to strengthen the lobby against inadequate oil palm plantation, Hollywood actor Harrison Ford visited the epicenter of illegal palm oil production, Indonesia. Welcomed by the thick smog, barring his visibility, he soon realized the smog was actually smoke, generated from the burning of rainforests in the region. When Ford confronted the Forestry Minister, Zulfikli Hasan, his efforts were deemed inappropriate to the extent that immigration authorities were ordered to carry out deportation of the actor. This is not the first time that international pressure has failed to make things right in the rigid presence of Indonesia's corrupt legal system.

The same year, burning of rainforests and the subsequent carbon emission reached frightening levels lasting two long months and eventually impacting the neighboring countries of Singapore and Malaysia. According to the data, the Pollutant Standard Index or PSI reached an average 800 PSI, whereas a PSI of 300 and above is considered hazardous. Singapore, in particular was hit the hardest with levels rising to 401 PSI, officially making it the highest level of pollution ever in the island country. Both Singapore and Malaysia soon realized the root of the problem and accused Indonesia for the same.

In a rare move, then Indonesian President Susilo Bambang Yodhoyono issued an apology to the neighboring nations, taking full responsibility of the exceeding levels of carbon emission and its after effects, suffered by the South East Asian nations. Interestingly and ironically, the biggest palm oil corporations such as Wilmar, Musim Mas, Sime Darby and GAR, operating in Indonesia, and partly responsible for elevated carbon emissions are all registered in Singapore and Malaysia respectively.

Paris Climate agreement 2015:

In a landmark move on December 12, 2015, a total of 196 nations signed a global treaty by United Nations Framework Convention on Climate Change (UNFCCC), pledging to follow UN recognized protocols to combat climate change. With a primary objective to keep the global climate change this century at 1.5degrees Celsius, the treaty aims to deal with greenhouse gas emission mitigation starting in the year 2020, soon after the conclusion of Kyoto protocol. One of the valid arguments in favor of oil palm plantations is the use of palm oil in environmentfriendly biofuel. Due to its low cost and mitigated effects on ecosystem, biofuel is fast becoming the No.1 choice of countries like China and India who want 15% and 20% of their fuel respectively to be grown in the fields by 2020. Similarly, EU nations have also shown considerable interest in selling 10% of fuel made from palm oil.

Ironically though, these attempts to reduce the adverse effects and impact of climate change could actually alleviate the problem. Clearing forests and burning peatlands for oil palm plantations will cause more carbon emissions than burning fossil fuels. The carbon footprint of palm oil industry is multifold, with one coming from emissions from deforestation and other from the processing of palm oil in factories. Oil palm plantations currently cover 27 million hectares of earth surface, a result of massive land use change leading to loss of biodiversity on an area the size of New Zealand.

Conclusion -

After his election in 2014 as the president of Indonesia, Joko Widodo addressed many burning issues plaguing the country including corruption and in an attempt to deliver a warning to the web of organizations for such devastation, said -"We all know the problem. Everybody knows problem. Experts, Government, law-enforcers, corporations, all know the problem. It all boils down to one question: Do we have the will? Are we serious? I am. I am very serious."

Institutional investors as well as individuals play a key role in financing the expansion of palm oil industry and are in a position to minimize the destruction caused by deforestation. A largescale promotion of land grab-free investment policies and practices is definitely a first step in the direction. Depletion of natural resources causing serious and immediate health issues, and in some cases, overall survival of communities is an act of human rights violation and must be dealt with seriousness and sensitivity. Policies such as HCV (High conservation values) assessments may not only protect species but are also capable of resulting in loss of carbon emissions As a welcome change, recent statistics show that as of 2016, over 60% of US based companies have adopted policies promoting purchases of deforestation-free and peatland-free palm oil. The same approach needs to be followed by corporations globally to act responsibly and well within the timeline to minimize the destruction of ecosystem.

And finally, effective enforcement of environmental standards in palm oil production is crucial, not just in Indonesia, but across the world to ensure the issue is dealt with carefully to prevent any further damage.

In his Academy Award winner speech, DiCaprio remembered that the most critical issue of our times needed to be stressed upon at one of the world's most recognizable stages, and said -"Climate change is real, it is happening right now. It is the most urgent threat facing our entire species, and we need to work collectively together and stop procrastinating. We need to support leaders around the world who do not speak for the big polluters, but who speak for all of humanity, for the indigenous people of the world, for the billions and billions of underprivileged people out there who would be most affected by this. For our children's children, and for those people out there whose voices have been drowned out by the politics of greed."

Through the qualitative analysis of the situation the study can put forth following suggestions as to assess the growth in industrialization and sustainability, an integrated accountability of environment and expanding markets needs to be established. This is possible with some policy measures for both economy and environment. These policy measures will improve the economic stability of the country as well as the growth of the industries. A proper environmental policy scenario for Indonesia will also analyze the ecological norms and check upon the market instruments which are causing environmental degradation. The environmental and economic policies must generate a benchmark for economic behavior and a practical framework has to be adopted to curb down the global warming issues in the country as well as in the world economy.