Biodiversity and ecosystem functions in wetlands: A ... - Springer Link

Estuaries

Vol. 24, No. 6B, p. 1088–1096

December 2001

Biodiversity and Ecosystem Functions in Wetlands: A Case Study in the Estuary of the Seine River, France O. CHABRERIE1, I. POUDEVIGNE1, F. BUREAU1, M. VINCESLAS-AKPA1, S. NEBBACHE1, M. AUBERT1, A. BOURCIER2, and D. ALARD1,* 1

Universite´ de Rouen, Laboratoire d’Ecologie, UPRES-EA 1293, 76821 Mont Saint Aignan Cedex, France 2 Universite ´ du Havre, CIRTAI, UPRESA 6063 CNRS, 76063 Le Havre Cedex, France ABSTRACT: The integrity of estuarine wetlands is maintained by physical connections between river and sea to floodplain. Their ecological importance can be assessed through plant biodiversity and such ecosystem functions as primary productivity and nitrate removal capacity. Multivariate analysis were used to establish a hierarchy of environmental factors related to the vegetation structure and diversity. Four different measures of plant diversity (both structural and functional) were made on a Seine River wetland. Key functions of estuarine floodplain (productivity and denitrification capacity) were either measured directly or assessed using remotely sensed data. The richest plant communities correspond to mesophilous grasslands which have an intermediate position between natural and anthropogenic disturbance regimes. These species assemblages occur in ecosystems presenting both a regular productivity in time and space and the highest denitrification potentiality.

the flood disturbance regime of the Seine floodplain is no longer maintained, instigating changes in the organization and diversity of these communities. Biodiversity in wetland floodplains is generally important because of the recurrent disturbance regime caused by the variation in water level that increase environmental heterogeneity and thus diversity (Amoros and Roux 1988; Huston 1994; Reice 1994; Bornette and Amoros 1996; Vivian-Smith 1997). Estuarine communities are known to have a relatively low taxonomic diversity (Day et al. 1989; Costanza et al. 1993) because of the high amplitude unpredictable stresses, which select a limited set of species, adapted to changing salinity, osmotic stress, and oxygen deficiency. Because the major factors controlling biodiversity in estuaries are easily identifiable their wetlands are convenient for studying how biodiversity dynamics may be affecting ecosystem processes (Schulze and Mooney 1994). Biodiversity has long been considered a community attribute or a measure of community structure (Samuels and Drake 1997) as it was mostly approached by the means of species diversity or richness in a given area (Peet 1974; Duelli 1997). Common attributes of these structural indices are to be scale dependent and to consider all species as equivalent (Kolasa and Rollo 1991). Three major components of biodiversity (composition, structure, and function) have been recognized (Noss 1990). A more functional approach, by consider-

Introduction The relatively large and unpredictable variations in salinity and water level characterizing most estuarine systems tend to select particular life-forms limiting the number of species capable of adapting to these stresses (Rey Benayas and Scheiner 1993; Kittelson and Boyd 1997). As an ecotone between fresh and marine environments, estuaries and estuarine wetlands are habitats for a mixture of freshwater and halophilous plant species (Holland et al. 1990; Gosz 1993). The integrity of estuarine wetlands is maintained by hydrologic and sedimentation dynamics, environmental gradients, and lateral connections between the river or the sea and the floodplain ( Junk et al. 1989; Pasternack and Brush 1998; Ward 1998). Most of the large estuarine floodplain ecosystems in the world have been altered by human activities (Bravard and Petts 1993; Vitousek et al. 1997). Like many European rivers, the Seine River and estuary was nearly entirely channelized at the beginning of the century to enhance agricultural use of the rich alluvial soils, secure river navigation, and prevent flooding (Lefebvre et al. 1974). Up to the 20th century, the landforms of the Seine estuary were an equilibrium product of water and sediment regimes. The plant communities, in turn, had adapted to these regimes and environmental gradients and even became resistant to the disturbances occasioned by the variation in salinity and the flood pulse. Today, * Corresponding author; e-mail: [email protected]. Q 2001 Estuarine Research Federation

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ing species behaviors in the landscape, should approach the mechanisms of species coexistence and allow predictability. We tried out different measures of biodiversity chosen from the literature at different scales to account for these aspects of community structure and organization: species richness accounting for structural diversity and local heterogeneity at the community level (Smith and Wilson 1996) and factorial diversity and global heterogeneity (or beta diversity) for pattern diversity at the landscape level (Whittaker 1972; Scheiner 1992; Thioulouse and Chessel 1992). These measures and their variations were compared along an environment and management gradient in the landscape in order to understand the information brought by each measure. Functions of estuarine and wetland ecosystems can be broken down into a number of key processes. An example of such a process is the denitrification process which is an essential component of nitrogen cycling. In this process, nitrates (the result of ammonium nitrification) are transformed by denitrifier bacteria into gaseous forms. This process is often referred to as the buffer function of wetlands (Vought et al. 1995). Most denitrifier bacteria require a total absence of oxygen. The integrity of this function in wetlands is related to the water level variation: either by flooding or by rise of the water table (CNRS PIREN-nitrate 1991). Another key functional attribute of these ecosystems is primary productivity. Estuarine ecosystems and wetlands are among the most productive biomes of the world (Whittaker and Likens 1975; Fustec and Frochot 1996). One reason for the high primary productivity is the high nutrient loading rates. Estuaries function as funnels collecting nutrients of the river catchment basin. Main factors determine biodiversity and ecosystem function in the wetlands of the Seine estuary: natural disturbances such as water level and salinity variation or disturbance caused by anthropogenic activities. This paper looks at estuarine wetlands in terms of their biodiversity characteristics and ecosystem functions. It is based on the hypothesis that biodiversity affects ecosystem functioning, and that the distribution gradient of species can serve as a model to understand biodiversity. This paper aims at understanding the relationships between biodiversity and ecosystem stability (McCann 2000) and the role of biodiversity in ecosystem functioning. Study Site The study site, Le Marais du Hode, is a wetland of the Seine estuary, situated in the northwest of France (498289090N, 08239100E) under a temperate oceanic climate. The dominating structures of the floodplain relief were formed at the end of the last

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ice age on a chalk substratum. The Hode wetland is situated on the north bank of the Seine River and covers an area of 58 km2. This alluvial wetland is flat and subject to tidal and winter flooding, which is mainly occasioned by a rise of the water table level. The landscape can be divided into three main areas: to the north is a fine grain mosaic of crops and sown pastures, the center is largely composed of mesophilous and subhalophilous grasslands, and the southern area, bordering the Seine, is a large reedbed of Phragmites australis. The importance of the area as a habitat for wildlife and notably birds has been recognized on an international level (designation as an Special Protection Area under the EU’s Birds Directive). Materials and Methods SAMPLING Along a 5 km transect, oriented north-south to be representative of the main habitats of the wetland, a field survey of the vegetation every 50 m along the transect was used to determine which were the factors potentially explaining vegetation distribution in the wetland. For each record the relative abundance of species is estimated with 16 quadrats (0.25 3 0.25 m) regularly spaced in a 4 3 4 m grid. Fourteen environmental variables were collected for each location so as to provide a link between species assemblage and their environment. Nine of them are chemical and morphological soil descriptors (Aubert 1978; Buttler 1992; Duchaufour 1997; Favrot and Vizier 1998), and five are biotic and abiotic factors relative to ecosystem structure and functioning. To test the productivity function of the wetland, two variables were recorded. Aboveground biomass was sampled on a 0.25 3 0.25 m area within each site. At a larger scale, a normalized difference vegetation index (NDVI) generated from satellite data of a HRV SPOT scene of March 1997 was used to estimate biomass (CNES 1997-distribution SPOT IMAGE; CIRTAI-Groupe Environnement et Estuaire-PNRZH 1999). Centered on each record, kernels of nine pixels (60 3 60 m) were convoluted (Lillesand and Kiefer 1994) to provide a mean value per record. To assess the temporal variability, the difference between the NDVI values of two SPOT scenes (1987 and 1997) was computed. Preliminary studies using GIS support on vegetation maps of 1987 and 1997 have shown the validity of the procedure for wetlands (Bourcier 1993). Microbial denitrification is a process of nitrate removal where nitrates are reduced through different intermediate stages (NO2, NO, N2O) into nitrogen gas (N2) which is lost in the atmosphere (Pinay et al. 1994). To assess this process, soil de-

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nitrification potential (DNP) was measured in five sites representing the five major habitats of the wetland. This spatial approach is realized with the intention of providing mapable information. On each site, 3 soil samples (10 cm high and 3 cm diameter) were collected. Similar hydric conditions were previously ensured for all soil samples. To estimate DNP, the N2O released by the soil samples is measured according to the following procedure: bacterial activity is first stimulated in anaerobic conditions with a carbon (2 mg C-glucose g21 fresh soil) and a nitrate (KNO3 to 300 mg of NNO3 g21 fresh soil) input (Yeomans et al. 1992; Hallin and Mikael 1994), and then the microbial denitrification process is blocked with acetylene at the N2O stage (Tiedje et al. 1989; Aulakh and Doran 1990). N2O is then measured via a Girdel gas chromatograph equipped with Porapak Q column. DATA ANALYSIS Data were treated by multivariate analysis with the ADE-4 software (Thioulouse et al. 1997). Canonical correspondence analysis (CCA; ter Braak 1986), is a general ordination method to couple two data tables. This analysis is carried out on the vegetation data table (49 records 3 65 species) and coupled to the environmental data table (49 records 3 14 variables). CCA are realized to establish a hierarchy of independent factors related to the vegetation structure at the landscape scale. A Monte-Carlo permutation test was realized to investigate the statistical significance of the species-environment relation. The analysis was completed with a clustering by Hierarchical Clustering (Roux 1991) using Ward’s method (1963) to identify groups of records. In order to identify biodiversity variation patterns in the wetland, four measures were performed on vegetation data to account for community structure and organization. The structural diversity of the plant community is assessed with the species richness (R; Whittaker 1972). The ecological diversity of the plant community is measured with the factorial diversity index (FD). FD is based on the reciprocal ordination of species and records provided by CCA (Chessel et al. 1982). It measures the dispersion of all the species of one record along the gradient represented by a factorial axis of CCA. FD can also be considered as a measurement of the ecological diversity or coherence of the record (Chessel et al. 1982; Balent 1991). In view of assessing local and regional heterogeneity, two heterogeneity index were calculated at these two scales. They are based on the formula D 5 (1 2 S)21 where S is the Sorensen similarity index (Gower and Legendre 1986). Intrarecord heterogeneity index accounts for local

heterogeneity and inter-record heterogeneity index accounts for beta diversity (Blondel 1995), the species turnover between communites. Results VEGETATION ORDINATION ALONG ECOLOGICAL GRADIENTS A preliminary CCA only brings out reedbed species, such as P. australis, Calystegia sepium, and Sambucus nigra. The group of reedbed records, is correlated to a high level of bare soil, salinity, pH, and vegetation height. The main CCA (Fig. 1) is performed on the remaining records, to analyze grassland community structure. The Monte-Carlo permutation test confirms the CCA species-environment relation, it rejects the null hypothesis of independence with p # 0.1. Axis 1 of this analysis (inertia 0.24) opposes pioneer species (Poa annua, Plantago major, Juncus bufonius) to tall grassland species (Arrhenatherum elatius, Dactylis glomerata, Hordeum secalinum). Axis 2 (inertia 0.21) opposes hydrophilous and halophilous species (Alopecurus geniculatus, Alopecurus bulbosus) present in records in the south of the estuarine floodplain to more continental grassland species (Cynosurus cristatus, Bromus racemosus, Festuca pratensis) or ruderal species (Heracleum sphondylium, Anthriscus sylvestris, Galium aparine) north of the transect. Axis 1 suggests a gradient from disturbed environments (C.I., bare soil) to stable environments with a high vegetation cover (vegetation height, NDVI 1997) and a soil with high percentage of organic matter (%N soil, % Corg). Axis 2 is related to salinity, pH, and hydrologic disturbance regime as described by the soil morphology descriptors. Clustering identifies four groups of records (inertia ellipse drawn on Fig. 1). Group 1 is more or less recently sown pastures of the disturbed areas north of the transect, group 2 is very wet and saline grassland, group 3 is wet subhalophilous grassland, and group 4 is mesophilous grassland. DIVERSITY PATTERN ALONG THE ECOLOGICAL GRADIENT The different biodiversity measures show contrasting patterns of variation along the landscape gradient represented by the first axis of the CCA (Fig. 2). Communities with high species richness (group 4) are characterized by an important microheterogeneity (intra-record heterogeneity). These records also present a low factorial diversity and a low inter-record heterogeneity. Records with lower species diversity (group 1) present a high macro-heterogeneity at the landscape scale (high inter-record heterogeneity). These locally homogenous records (low intra-records heterogeneity) contain species with a high dispersion along the


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Fig. 1. Canonical Correspondence Analysis showing plant species and environmental variables plotted on the factorial space. The four groups of species are identified by Hierarchical Clustering (Roux 1991). Group 1: pioneer species in disturbed environment; Group 2: halophytes species in a very wet and saline environment; Group 3: wet and subhalophilous grassland species; Group 4: mesophilous grassland species. Morphological and chemical soil descriptors include total calcium carbonate by Bernard’s calcimetric method (Tot.CaCO3), active calcium carbonate by Drouineau-Galet method (Act.CaCO3), organic carbon by Anne method (%Corg), soil total nitrogen by Kjeldahl method (%N soil), C/N ratio, soil salinity, pH, depth of Go soil layer apparition (Go layer corresponds to water table fluctuation zone), and depth of Gr soil layer apparition (Gr layer corresponds to anoxic conditions). Structure and ecosystem functioning are denoted by intraheterogeneity (intra-record floristic heterogeneity based on the formula D 5 (1 2 S)21 where S is the Sorensen similarity index), vegetation height (vegetation height average in a record), bare soil (percentage of bare soil in a record), NDVI 1997 (productivity assessment by the normalized difference vegetation index (NDVI) generated from satellite data of a SPOT scene of March 1997), and C.I. (temporal variability index, Change Index, based on the difference between the NDVI values of two SPOT scenes [1987 and 1997]).

ecological gradient (high factorial diversity), i.e., species with contrasted habitat requirement. PRODUCTIVITY

IN THE LANDSCAPE IN REFERENCE TO THE GRADIENT ANALYSIS

Values of aboveground biomass, NDVI and the difference between NDVI 1987 and 1997 values along the transect are represented in Fig. 3. Records at both ends of the transect (the crops and sown pastures at the north and the reedbeds at the south) present a spatially heterogeneous productivity (biomass and NDVI 1997) and a strong temporal variability (difference between NDVI). These landscape units are submitted to natural flooding

disturbance (reedbeds) and anthropogenic disturbance (crops and sown pastures of group 1). Mesophilous grasslands (mostly groups 3 and 4) in the center of the estuarine floodplain have an intermediate position regarding disturbance regimes. They exhibit a low temporal variability and present an homogenous biomass in time and space at the landscape scale. DENITRIFICATION PROCESS IN THE MAIN LANDSCAPE UNITS Results show that denitrification enzyme activity is positively correlated whatever the soil to species richness (correlation coefficient 5 10.817; Fig. 4).

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Fig. 2. Variation patterns of four biodiversity index along axis 1 of the CCA: intra-record heterogeneity, inter-record heterogeneity, specific richness, and factorial diversity index. The four groups of records are identified by Hierarchical Clustering (Roux 1991) using Ward’s method (1963).

Measures of floristic richness along the transect show that the central part of the transect (subhalophilous pastures, essentially group 4) corresponds to species rich communities, while the ends (crops, sown pastures, and reed beds) correspond to species poor communities. Habitats with low natural or anthropogenic disturbance regimes and/or physiological stresses (subsaline soils), seem to have the highest plant species richness and the highest soil denitrification capacity. Denitrification activity is also correlated negatively to abiotic factors such as soil pH (correlation coefficient 5 20.849). This suggests that the spatial soil heterogeneity has a major role in explaining the spatial variation of DNP. Discussion EVIDENCE FROM THE EMPIRICAL DATA The north of the transect has been affected by important land use changes from 1987 to 1998; many permanent pastures were turned to croplands or temporary grassland. Management prac-

tices are intensive (drained crops, sown pastures). The communities of these grasslands (group 1) are poor and ecologically incoherent species assemblages in frequently disturbed habitats. Their particular floristic composition is a source of heterogeneity at the landscape scale. The low denitrification potential of these lands can be related to the soil properties; low water content together with low organic content control availability of oxygen and carbon. The low water content can be explained by soil texture or soil drainage. The low organic matter content can be related to tillage. The middle of the transect is under low anthropogenic influence (extensive management, no land use change within the 10-yr period) and low natural disturbance. It is dominated by mesophilous grasslands (group 4). These communities are rich and ecologically coherent species assemblages. Their small-scale heterogeneity contrasts with the homogeneity at the landscape scale. This biodiversity pattern is also related to an important denitrification capacity and a spatial homogeneous primary production at the landscape scale.


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Fig. 3. Biomass (A) and NDVI (B) and temporal variability (C corresponding to difference between NDVI 1987 and 1997) and localization of ecological groups (D) along the transect. Cr: crops; G1, G2, G3, G4: groups of records provided by CCA (Fig. 1); Re: reedbeds.

As salinity and humidity rises towards the south of the transect, the physiological stress imposed upon the species and the natural disturbances created by the tide and the floodpulse rise as well. Along this gradient, from the wet subhalophilous grasslands to the reedbeds, species richness and ecological coherence decrease and local homogeneity increases. The denitrification capacity of these grasslands diminishes as the salinity level ris-

es, an already observed phenomenon (Garcia et al. 1974). THE PROBLEM

OF SPECIES COEXISTENCE AND BIODIVERSITY

In the concept of stability as developed by Holling (1986), the notion of resilience is defined as a system’s capacity to absorb changes of state variables and parameters and to persist in a globally

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Fig. 4. Denitrification potentiality and plant species richness in the five major habitats of the estuarine floodplain. Histograms: Denitrification Enzyme Activity (N-N2O ng g21 dry soil) after 48 h of incubation; points: Floristic richness. Standard error are used in figure.

stable dynamic regime. The model developed by Holling suggests that systems evolve from the rapid colonization and exploitation phase, during which they use easily accessible resources, to the conservation stage of building and storing increasingly complex structures. Organized communities reach these complex structures through increasing complexity of the mechanisms of species coexistence (Levin 1992). Three basic mechanisms have been distinguished: non-equilibrium coexistence (instability and competitive exclusion), co-occurrence (spatial micro-heterogeneity), and true coexistence (niche partitioning; Gigon and Leutert 1996). These mechanisms differ fundamentally in the nature and strength of species interactions (i.e., assembly rules). Recent research has underlined the main role of the interactions strength to explain ecosystem stability. This suggests a new approach on the diversity-stability debate which mostly considered species richness versus stability (McCann 2000). The Hode wetland is influenced by two main factors of instability: agricultural disturbance (plowing, mowing, fertilization) and natural disturbance related to water level and salinity variation. The latter occurs regularly over long time periods and can be termed as regimes (Van Andel and Van den Bergh 1987; Van der Maarel 1996) while anthropogenic disturbances are usually more occasional and unpredictable (Waddington 1975). Agricultural practices when regular can also maintain ecological communities rather than disturb them. In the areas where disturbance is most marked, the species assemblage are constantly reset and rarely build up enough structure to make it to the conservation phase. These communities exhibit a low ecological coherence which reflects the early colonization phase. The grasslands of the northern part (group 1) represent such low taxonomic diversity systems. These recently sown grasslands are

typical examples of the unstable coexistence between weeds and typical grassland species. Their local homogeneity as well as their floristic originality is associated with recently disturbed areas. This suggests that these early successional species assemblages are an example of coexistence mechanisms based on non-equilibrium (Alard and Poudevigne in press). In the areas where natural or anthropogenic disturbance have occurred regularly in continuous regimes for at least the last 10 years, species assemblages are likely to exhibit a high ecological coherence indicating self organization (Levin 1992). In response to a given disturbance regime or management, we hypothesize that a species assemblage spontaneously reaches a dynamic equilibrium based on segregation mechanisms in order to limit negative species interactions (Alard and Poudevigne 2001). Measures on mesophilous grasslands (group 4) seem to be consistent with this hypothesis. The high level of micro-heterogeneity associated with a high species richness also suggests that the mechanism of coexistence in this community is based on spatial segregation and co-occurrence. In the light of the diversity-stability debate, our data suggest that there is a positive correlation between species richness and the stability of the system; the highest species richness is associated with stable disturbance regime while the lowest richness is associated with the more unstable environment. This correlation is not always observed (Alard and Poudevigne 2000). The correlation between organized systems and environmental stability, or between ecologically incoherent systems and recent changes in the environmental conditions, is regularly observed. THE ROLE

BIODIVERSITY IN ECOSYSTEM FUNCTIONING The analysis at the landscape scale has shown that the two functions (productivity and denitrification) are linked both to the spatial macroheterogeneity (landscape units) and to biodiversity. Our data suggest a positive correlation between soil denitrification potentiality and plant species richness. The mechanisms explaining such correlation is probably due to a complex interactions between plant and micro-organisms in the soil (Lavelle et al. 1997). There is no evidence of such correlation between productivity and species richness, mostly because the poorest communities (reedbeds and group 1) exhibit contrasted levels of productivity. In species-rich grasslands, self-organized communities based on niche complementarity (Hector et al. 1999) should enhance collective performance (Loreau 2000) for a given function (as denitrification in mesophilous grasslands). When seOF


lective factors (salinity, water table level) promote dominance by few species, the traits of these species explain a major part of performance. This appears to be the case for the high level of productivity in reedbed which is mainly explained by traits of P. australis (Grime et al. 1988). Major differences in dominant species between landscape units could explain the spatial variability of productivity and the low correlation between species richness and productivity. The spatial variation of these functions also exhibits contrasting gradients in the landscape (e.g., the reedbeds show the highest biomass but are amongst the lowest DNP). The consequent complexity of such questions related to the functional meaning of biodiversity would lead us to reformulate the issue under the question: which measure (informational or functional) of biodiversity relates to which functions of the ecosystem? Further investigation on the question related to the biodiversity-function relation in estuarine wetlands could concern the study of fine scale variation patterns of these attributes in one landscape unit. Questions remain as to whether the coincidence of hot spots of biodiversity with optimum denitrification capacity is a random or a causal relation. ACKNOWLEDGMENTS The authors would like to thank Drs. Valerie Mesnage for information on water salinity in the Hode wetland, Jean Come Bourcier for geolocalization of the Hode transect, and Alexandre Dufour and Corinne Vandamme for help in data collecting. This study was supported by a grant of the French Ministry of Environment in the context of the national program for wetlands (Programme National de Recherche sur les Zones Humides, PNRZH).

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