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Biodiversity and Ecosystem function

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Introduction

In recent years, the recognition that species may play important roles in ecosystems and the rapidly emerging interest in the biodiversity conservation have prompted ecologists to ask new questions on the relationships between `diversity' and `ecosystem function' (for example, Walker, 1992[1]; Schultze and Mooney, 1993; Jones and Lawton, 1995; Johnson et al., 1996).


Why it is important?

One reason for the interest in the functional role of biodiversity (rather than structural) in ecosystems is that society might be more likely to take action to preserve biodiversity if it could be shown that there was some direct economic gain by doing it (Bengtsson, 1998). Over the last fifteen years, an increasing number of studies have focused on biodiversity. This is principally because the world’s flora and fauna are disappearing at rates greater than during historical mass extinction events (Chapin et al, 2001). As recently suggested by Thomas et al. (2004), there is an 18 to 35% risk of species-level extinction resulting from climate changes by the year 2050. Moreover, other processes, for example, agricultural expansion in response to an increasing demand for food, have a negative impact on biodiversity as a result of habitat destruction (Tilman et al., 2001; Humbert and Dorigo, 2005).

Biodiversity and Ecosystem function are central to both community and ecosystems ecology and need to be understood to predict, for example, how communities and ecosystems respond to environmental change (Bengtsson, 1998) and on understanding how declining diversity influences ecosystem services on which humans depend (Duffy, 2003).


Research on Ecosystem Functioning

Research on Biodiversity - Ecosystem Functioning (the BEF agenda) has stimulated a new and highly productive intercourse between population, community, ecosystem, and conservation ecology (Kinzig et al. 2002; Loreau et al. 2002; Duffy, 2003). Most experimental evidence for biodiversity effects on ecosystem functioning has come from terrestrial ecosystems, particularly grasslands (Naeem et al. 1994, Tilmann et al. 1997a, Hector et al. 1999, Schmid et al. 2001; Giller et al., 2004). These studies have shown that changing biodiversity in natural ecosystems is likely to have much more complicated impacts on ecosystem functioning than predicted from changes in plant diversity alone (Duffy, 2003). For example in trophic levels of plant communities, as diversity is lost from a system, impacts will also depend from the loss of predators which will evoke change in the structure of all trophic levels (Hairston et al. 1960; Power 1990; Estes et al. 1998; Duffy, 2003).

The mosaic of habitat patches in aquatic systems often is more spatially compact than in terrestrial environments, presenting more tractable experimental systems at the landscape scale (Schindler and Scheuerell 2002). Because each aquatic ecosystem is composed of multiple habitat types, assessing the effects of biodiversity changes on the functioning of aquatic ecosystems requires experimental designs that allow a scaling up from individual homogenous patches to large scale, often highly heterogeneous areas (Giller et al. 2004).

The most influential empirical research on biodiversity-ecosystem functioning linkages has been the series of experiments manipulating diversity in grasslands (reviewed by Tilman et al. 2002) and in aquatic microbial microcosms (reviewed by Petchey et al. 2002). Typically these have tested how ecosystem-wide biomass accumulation or metabolic rates change along gradients of species richness achieved by randomly assembling experimental communities from a pool of species. The grassland experiments have manipulated plant species richness, and sometimes also

functional group richness. These studies have demonstrated significant positive correlations between species richness and plant biomass. Loreau et al. (2002) provide a global overview of concepts and debates concerning the relationships between biodiversity and ecosystem functioning (Humbert and Dorigo, 2005).

It has been clearly established that ecosystem functioning depends both on biotic factors and/or processes (such as the diversity and functions of the species, and interactions between species) and abiotic factors (such as climate or geology). However, what relative contribution these factors make is still a central question in the debate about diversity and ecosystem functioning (Huston and McBride, 2002; Humbert and Dorigo, 2005).

Species deletion stability can also be linked easily to removal experiments that address the consequences of species loss for ecosystem functioning (Thébault, et al. 2007). With a few exceptions, theoretical work on the direct impact of species loss has focused on the study of secondary extinctions but has not considered associated changes in ecosystem properties (see King and Pimm 1983, Petchey et al. 2004).


Many of the studies that dealt specifically with the mechanisms involved in the relationships between biodiversity and ecosystem functioning investigated the niche complementarity mechanism, stimulating both theoretical and experimental approaches (e.g., Naeem et al., 1994; Loreau, 1998). The sampling effect, difficult to distinguish from the niche complementarity, is defined as the greater likelihood of finding species with a strong impact on ecosystem functioning in highly diversified communities (e.g., Huston, 1997; Hector et al., 1999; Wardle, 1999). These are not either-or mechanisms, but may be viewed as concomitant processes (Naeem, 2002). Sampling effects are involved in community assembly, and thus in determining the number of phenotypic traits present in the community. Subsequently, this phenotypic diversity influences ecosystem processes through mechanisms that can be viewed as a continuum ranging from the selection of species with particular traits to complementarity among species with different traits (Loreau et al., 2001).

Mathematical modelling has also been used recently, to investigate the relationships between biodiversity and ecosystem stability. For example, McCann et al. (1998) have shown that weak to intermediate interaction strengths within food webs are important in promoting community persistence and stability (Humbert and Dorigo, 2005).


Theories and Hypothesis

In a recent review, Naeem et al. (2002) proposed three hypotheses to account for biodiversity-ecosystem functioning:

  • The first hypothesis is that species are primarily redundant, which means that one species can partially replace another. Many species have the same function, and the loss of one species can therefore be offset by some other species.
  • The second hypothesis is that species are essentially singular, and make unique contributions to ecosystem functioning. The loss or gain of species (generally referred to as Keystone or Key species) therefore has a measurable impact on ecosystem functioning.
  • The third hypothesis is that species impacts are context dependent such that the impact of the loss or gain of a species on ecosystem functioning is idiosyncratic and unpredictable.

What happens, will depend on the local conditions under which the species extinction or addition occurs (Humbert and Dorigo, 2005)


How do we measure Ecosystem Functioning?

Describing or measuring ecosystem functioning is difficult, as it encompasses a number of phenomena (Hooper et al., 2005). The overall functioning of an ecosystem is complex and involves many factors relating to the chemical, physical and biological components of the system. The way in which differences between species affect diversity-function relationships can be very complex (Lawton et al., 1998; Ricotta, 2005).

Functional diversity (FD), i.e. the diversity and range of functional traits possessed by the biota of an ecosystem (Wright et al., 2006) or else defined by Tilman (2001) as ‘‘those components of biodiversity that influence how an ecosystem operates or functions’’ (Ricotta, 2005), is likely to be the component of biodiversity most relevant to the functioning of the ecosystems (Hooper et al., 2002; 2005; Heemsbergen et al., 2004), even though, there is no clear relationship demonstrated between species diversity and ecosystem functioning (Somerfield et al., 2008).

Whereas traditional diversity indices focus on species richness (Jiguet et al. 2005), rarity (Schmera 2003) or the uncertainty of predicting species identity from abundance data (Magurran 1988), functional diversity formulae are used to measure ‘‘those components of biodiversity that influence how an ecosystem operates or functions’’ (Tilman et al. 1997; Schmera, Erös and Podani, in press). Functional Diversity relates the number, type and distribution of functions performed by organisms within an ecosystem (Diaz & Cabido, 2001). It incorporates interactions between organisms and their environment into a concept that can portray ecosystem level structure in marine environments (Bremner et al., 2003) and conjectures to be useful in predicting the consequences of changes in species richness and composition, or biodiversity in general, on ecosystem properties (Somerfield et al., 2008).

Biodiversity can influence ecosystem functioning through changes in the amount of resource use complementary among species. Functional diversity is a measure of biodiversity that aims to quantify resource use complementarity and thereby explain and predict ecosystem functioning (Petchey, Hector and Gaston, 2004). Many studies have focused on calculating Functional Diversity, in order to measure the functioning of an Ecosystem. Methods and indices have been applied and tested on a long series of data concerning abiotic and biotic measures of fresh and sea water.

Recent methods for calculating functional diversity of a community, include Functional Attribute Diversity (FAD), as used in a study of Australian rangelands by Walker et al. (1999), and Functional Diversity (FD) proposed more recently by Petchey & Gaston (2002) which is computed as the total branch length of the functional dendrogram that results from clustering the species in trait space (Ricotta, 2005). Trait variance, measured as the width of a trait distribution, has been proposed by Norberg (2004). Beyond the simple measurement of diversity, Mason et al. (2005) proposed also estimating functional richness, functional evenness and functional divergence, to enable descriptions of niche use and competitive interactions in communities. In order to take a functional approach and to use these new measures, however, we must have descriptors of the functional groups present in a community.

Most recently, based on the methodology proposed by the formers, Somerfield et al. (2008) defined average functional distinctness (X+, from χαρακτηριστικό, meaning a trait) simply as the average resemblance among species in a sample. Incidentally, the same logic may be applied to Δ+ (Clarke and Warwick, 1998). Once branch lengths are defined between taxonomic levels, a matrix of resemblances (Euclidean distances) between species becomes implicit, and the index is the average resemblance between species. In the same study, the authors concluded that the type of information we get from the functional level is complementary to the information we take from the taxonomic level.


How do we calculate Ecosystem Functioning in practice?

The categorization of species into functional groups can be done by simply assigning each species found in the assemblage to a given a priori defined functional group (Hector et al., 1999), or by standard multivariate clustering methods (Gitay & Noble, 1997; Deckers, Verheyen, Hermy, & Muys, 2004; Roscher et al., 2004)- see also Biological Trait Analysis (BTA). To cluster species into functional groups, first, a set of functional traits thought to be of significance for ecosystem functioning is measured for each species obtaining an S x τ matrix of τ functional traits measured on S species (Petchey & Gaston, 2002). Next, the trait matrix is converted into a distance matrix Δ the elements dij of which embody the functional distances between the ith and the jth species such that dii=0 and dij =dji for any i≠j. Finally, the distance matrix is clustered with standard multivariate methods to separate species from different functional groups (Ricotta, 2005). Generally, regardless of the proposed index, in most cases the information available for computing the FD of a given species assemblage is the set of pair wise species functional distances dij of a Δ matrix (Ricotta, 2005).


References

  1. Walker, B.H., 1992. Biodiversity and ecological redundancy. Conserv. Biol. 6: 18-23.


See also

The main author of this article is Vassiliki, Markantonatou
Please note that others may also have edited the contents of this article.