Nelson Valdivia
Effects of biodiversity on ecosystem stability
Distinguishing between number and composition of species
PhD thesis
University of Bremen
Biologische Anstalt Helgoland
Alfred Wegener Institute for Polar and Marine Research Marine Station
Ph.D. thesis
Effects of biodiversity on ecosystem
stability: distinguishing between number
and composition of species
Dissertation zur Erlangung des Doktorgrades der Naturwissenschaften Vorgelegt dem Fachbereich Biologie/Chemie der Universität Bremen von
Nelson Valdivia
Gutachter: 1. Prof. Dr. Kai Bischof
2. Prof. Dr. Christian Wiencke
Abstract
Declines in biodiversity have caused concern because of ethical and aesthetic reasons, but also because of the consequences for the goods and services provided by natural ecosys-tems. Consequently, ecologists have focused for decades on testing the idea that systems with more species are more stable. The results, however, have been complex and inconsis-tent. In particular, it is still unclear whether high stability in species-rich communities is due to the number of species per se (species richness) or to the increased likelihood of including particular species or functional types (species composition). In this thesis, I evaluated the contribution of species richness and species identity to the stability of marine hard-bottom communities. Combining observational and manipulative experimental methods, I con-ducted three field studies in intertidal and shallow subtidal habitats of Helgoland Island, NE Atlantic. First, I conducted an observational study to test whether intertidal communities containing many species are more stable (i.e. do vary less over time) than communities con-taining fewer species. Species covers were estimated every 6 months for 24 months and an
index of stability was calculated for total community cover across time (S = mean SD-1).
Second, I conducted a synthetic-assemblage experiment––in which I increased the diversity of field-grown sessile suspension-feeding invertebrates––to determinate whether assem-blages containing several functional groups consume a greater fraction of resources than is caught by any of the functional types grown alone. (A functional group is a group of species with the same effect on an ecosystem property.) Finally, I conducted a removal experiment to test whether the loss of the canopy-forming alga Fucus serratus and mechanical distur-bances that provide free substratum affect the temporal variability in cover of intertidal communities. In the removal experiment, species covers were estimated every 3 months for 18 months and the temporal variance was analysed.
In general, the effects of the number of species and functional groups on ecosystem sta-bility were weaker than those of species composition. In the observational study, stasta-bility was a negative and curvilinear function of species richness, which probably resulted from the dominance of few species. In accordance, the synthetic-assemblage experiment showed that there was no relationship between resource consumption and functional group diversity per se, but that different functional groups had idiosyncratic effects. On the other hand, the removal of Fucus changed the physical environment by increasing temperature, irradiance, and amount of sediment, which depressed the abundance of sensitive species like encrusting algae and small sessile invertebrates, but raised the abundance of more tolerant species like
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abundances, but not in that of communities. The negative covariances resulting from the compensation between sensitive and tolerant species buffered the community stability against the environmental disturbances. These patterns were consistent across two sites, suggesting a consistent effect of canopies across the spatial variability of this system.
Species composition appears to be more important for ecosystem stability than taxo-nomic and functional richness. Yet, the occurrence of compensatory dynamics in the face of environmental changes (i.e. the removal of Fucus) suggests that a variety of species with differing environmental tolerances is needed to maintain the functioning of this ecosystem. Therefore, predicting the consequences of species loss requires a detailed knowledge about the effects of species on ecosystem functioning and their responses to the environment. Con-servational managers should strive (i) in identifying species with disproportional effects on ecosystem functioning, and (ii) in maintaining a redundancy of species with similar effects on ecosystem functioning and a diversity of species with different sensitivities to a suite of environmental conditions.
Keywords:
Contents
Preface ... iv
Acknowledgments... v
List of papers... vi
1 Introduction... 1
The context: the value of biodiversity ... 1
Definitions ... 1
Theory ... 3
Size of ecosystem properties... 4
Variance in species properties... 6
Observations and experiments ... 8
The model system: hard-bottom ecosystems ... 9
Aims... 9
2 Methods... 11
Study sites ... 11
Sampling and experimental designs... 11
3 Results and Discussion... 14
Species richness vs. species composition ... 14
Species’ response traits influence community stability ... 17
The role of replication in biodiversity experiments... 17
Conclusion... 18
References... 20
Glossary ... 25
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This thesis reports the outcome of field-based experiments carried out during the last three years and designed to explore the role of biological diversity in maintaining the stability of coastal ecosystems. The experiments were designed to test theoretical predictions and mechanisms that explain the effects of biodiversity. So, at the first glance, the scope of this thesis might seem confined to the academic realm. However, the ultimate aim is to predict the ecological consequences of anthropogenic impacts on biological species, and also to predict the likely consequences for human welfare. This work bites a small piece of an im-mense puzzle.
The core of this thesis comprises four peer-review papers (I-IV) that can be found in the Appendix section. The thesis summarises the major outcomes of the papers, and it is organ-ised according to the IMRAD format (Introduction, Methods, Results, and Discussion). The Introduction contains a review of the current knowledge about biodiversity and ecosystem functioning. I was interested in illustrating mechanisms instead of describing patterns al-ready described by others. The Methods section summarises briefly the characteristics of the study sites, as well as the design, the set up, and the analysis of experiments. The results and their interpretation are in the Result and Discussion section. Additionally, I provide a glos-sary of terms at the end of the thesis in order to help the reader to understand the mecha-nisms and processes mentioned in the text.
Paper I shows the results of an observational study where I compare the stability of in-tertidal communities with naturally differing number of species. I test the hypothesis that stability is a positive function of species richness. In paper II, I evaluate the role of resource complementarity as a mechanism explaining the effects of functional group richness on the rate of resource consumption of subtidal organisms. In paper III, I test the interactive effects of disturbances on the stability of intertidal communities. Finally, paper IV assesses the level of replication needed to represent the number of species occurring in intertidal hard-bottom communities, which may be important when analysing the relationship between di-versity and ecosystem stability.
Acknowledgments
Over the last three years, many friends and colleagues have contributed directly or indirectly to this thesis. Those I have worked with in designing, setting up, and analysing experiments have shared information and ideas. Summer interns have been enthusiast during long hours of field work; editors and anonymous reviewers have brought part of this work to publica-tion. Karin Boos helped me during the copy edition and printing process. Prof. Dr. Christian Wiencke found always the way to fund materials, trips, and personnel (me). Andreas Wag-ner gave valuable technical assistance, and organised coffee breaks just in the best moment. This thesis would not have been written without the constant support, encouragement, and counsel of Dr. Markus Molis, who provided invaluable guidance and friendship. I thank all these people.
I also thank my family for joining me on the adventure of moving to Helgoland. While this work was being prepared, I was saddened by the loss of a member of my family: mother-in-law Ingrid Wallberg. It is to her memory that I dedicate this contribution.
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This thesis is based on the following papers, which will be referred to in the text by their roman numerals.
I Valdivia N, Molis M (In press) Observational evidence of a negative biodiversity-stability relationship in intertidal epibenthic communities. Aquatic Biology
II Valdivia N, de la Haye K, Jenkins SR, Kimmance SA, Thompson R, Molis M (In
press) Functional composition, but not richness, affected the performance of sessile suspen-sion-feeding assemblages. Journal of Sea Research
III Valdivia N, Molis M (Under review) Species compensation buffers community
stabil-ity against the loss of an intertidal habitat-forming rockweed. Marine Ecology Progress Se-ries
IV Canning-Clode J, Valdivia N, Molis M, Thomason JC, and Wahl M (2008) Estimation
of regional richness in marine benthic communities: quantifying the error. Limnology and Oceanography: Methods. 6: 580-590
Introduction
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Introduction
The context: the value of biodiversity
Human activities are altering the global climate (IPCC 2007). In addition, destruction of habitats, over harvesting, and introduction of exotic species are changing the local biodiver-sity of terrestrial and aquatic ecosystems (Dirzo & Raven 2003, Sax & Gaines 2003, Byrnes et al. 2007). As a consequence, today’s species extinction rate is probably the highest in Earth’s history (Dirzo & Raven 2003). The question therefore is not whether we are losing species, but what the likely consequences of such biodiversity loss are. Seminal research suggests that biodiversity influences the magnitude of and variability in ecosystems proc-esses (reviewed by Cottingham et al. 2001, Stachowicz et al. 2007). In particular, the work of MacArthur (1955) and Elton (1958) inspired the assertion that communities with many interacting species are more stable than communities with fewer species. Ecologists there-fore have raised the concern that changing biodiversity can impair ecosystem properties and the goods and services provided by ecosystems, which in turn might have high societal costs (Costanza et al. 1997, Armsworth & Roughgarden 2003).
It is not surprising therefore that the biodiversity-stability relationship had drawn the at-tention of ecologists for decades (Hooper et al. 2005), and that ecosystem stability had be-come an issue for policymakers (Christensen et al. 1996). However, the actual contribution of biodiversity research to conservation is still under debate, because of the contrasting re-sults of studies testing the idea that biodiversity begets ecosystem stability (Thompson & Starzomski 2007). Specifically, there remains controversy over what constitutes a ‘richness effect’ and how to untangle the effects on ecosystem functioning based on species richness per se from the usually stronger effects of species identity and composition (Bruno et al. 2006).
Definitions
The exploration of biodiversity-stability relationships requires us to clarify the meaning of biodiversity, stability, and other terms. Biodiversity is “the sum of all biotic variation in the biosphere from the level of gene to ecosystem” (Purvis & Hector 2000). This includes, but
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is not limited to, the number of species (species richness), the distribution of their abun-dances, and the presence or absence of key species.
The influence of biodiversity on ecosystem functioning depends on the suite of func-tional characteristics of the interacting species (Chapin et al. 2000). Funcfunc-tional traits are those characteristics of species that influence ecosystem properties (functional effect traits) or species’ responses to the environment (functional response traits). Functional groups are therefore defined by either the effect of species on ecosystem functioning or their response to the environment.
The term ecosystem functioning (or ecosystem performance) is a simple contraction for ‘how ecosystems work’, but encompasses complex mechanisms that regulate the transfor-mation and transport of energy across the ecosystem. Ecosystem properties consist of sizes of pools of materials like nutrients and carbon, and rates of processes like energy fluxes across trophic levels (Christensen et al. 1996). Ecosystem goods and services are ecosystem properties that contribute to human welfare both directly and indirectly. Food and materials for construction are examples of ecosystem goods; nutrient cycling and buffering of coastal erosion are examples of ecosystem services (Costanza et al. 1997). In this thesis, I use the percent cover of benthic species as a surrogate for biomass, and filtration rates of sessile suspension-feeding invertebrates as a surrogate for resource consumption and energy flux.
Stability has several meanings in ecology; indeed, a galaxy of definitions can be found in the literature, and each of them can lead to a different conclusion about the biodiversity-stability relationship (Grimm et al. 1992, Johnson et al. 1996). The six commonest defini-tions of stability are: the magnitude of disturbances a system can tolerate (domain of attrac-tion, Holling 1973); how long a measure stays without change (persistence, Pimm 1991); how much a measure changes by a disturbance (resistance, Pimm 1991); how long a meas-ure needs to return to a specified fraction of its initial value (resilience, Pimm 1991); how likely is that a system will continue functioning (reliability, Naeem 1998); and how much a measure varies over time (variability, Pimm 1991). Pioneer biodiversity-stability researchers explicitly considered stability to be related to temporal variability in ecosystem properties (MacArthur 1955, Elton 1958). In accordance, I focus on the effects of biodiversity on the temporal variance of ecosystem properties. For example, when comparing two temporal
Introduction series of abundances, the “more stable” one will be that with the smallest fluctuations rela-tive to its mean.
Theory
Temporal variability can be calculated using the variance in time series of species abun-dances. Because average abundances can differ, variance must be scaled relative to the mean (Gaston & McArdle 1994). Usually, this is done using the coefficient of variation (CV = 100
V Pbeing V the standard deviation and P the mean), which decreases as stability
in-creases. In this thesis, stability (S) is defined as S = PV(Tilman 1999). In contrast to CV,
the magnitude of S increases as stability increases; in addition, it approaches 0 when the variation is large in relation to the mean.
On the other hand, the variance in and aggregate ecosystem property (e.g. total commu-nity abundance––the sum of the abundances of all of the species in the commucommu-nity) can be expressed using a statistical rule (Schluter 1984, Doak et al. 1998):
) , ( 2 ) ( ) ( ) ( 2 2 2 2 j i n j i i n i i n i e x x x x x V V V V 6 6 6 (1)
being xi the abundance of an individual species i, xe the aggregate community abundance
made by summing the abundance of all species, V2 the variance, V2 (xi, xj) the covariance
between species i and j, and n the number of species. Therefore, the variance of an aggre-gate ecosystem property depends on the sum of all species variances and the sum of all pair-wise species covariances. If species vary independently, their covariance is zero and the variance of the ecosystem property equals the summed species variances. However, when species do not vary independently, their nonzero summed covariances cause the overall variability to increase or decrease. Stability therefore will be defined as:
Covariance 2 Variance 6 6 P V P S (2)
In accordance with equation (2), stability will increase with increasing species richness
if the mean value of the property increases (
P
), or the summed variances decrease, or thesummed covariances decrease, or a combination of these occurs (Lehman & Tilman 2000). Consequently, the factors influencing the size of ecosystem properties, the summed
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of theoretical work on biodiversity-stability relationships (Cottingham et al. 2001, Hooper et al. 2005). 0 1000 2000 Resource A Resource B Resource C
Species a Species b Species c Mixture of all species C ons um pt ion rat e of res ourc e i a b To ta l c ons u m pt ion rat e c S pec ie s a Spec ie s b S pec ie s c M ix tur e of al l s pec ie s A v erag e m onoc ul tu re Spec ie s a S pec ie s b S pec ie s c M ix tur e of all s pec ie s A v erag e m onoc ult u re 0 200 400 600 800 1000 Transgressive overyielding Non-transgressive overyielding Figure 1
Graphical depiction of resource complementarity (a), transgressive overyielding (b), and positive sampling effects (c) in communities containing 1 (species a, b, or c), and 3 (mixture) species. Total consumption rate is the sum of the consumption rates of all resources. If species consume different resources (a), positive species interactions increase the performance of the species-rich community relative to any of the constituent species grown alone (b). On the other hand, if the species-rich community includes a species with extreme functional value, the performance of the community will reflect the performance of that species instead of an average response of all of the species in the community; in these cases, the performance of the species-rich community is larger than that of the average
monoculture, but not larger than that of the best-performing species grown alone (c).
Size of ecosystem properties
Changes in the size of an aggregate ecosystem property can affect ecosystem stability (equa-tion [2]). Theory predicts that ‘overyielding’, an increase in the size of an ecosystem prop-erty with increasing species richness, can result from resource partitioning or facilitation (complementarity effect; Tilman et al. 1997a, Loreau 2000), or by the increased probability that more diverse communities include species with extreme functional impacts (sampling effect or positive selection effect; Huston 1997, Loreau et al. 2001). Complementarity ef-fects (Fig. 1a) lead to the phenomenon called transgressive overyielding, in which
produc-Introduction tivity or resource use of species-rich mixtures exceeds (transgress) that of the best-performing species grown alone (Fig. 1b; Fridley 2001). This is because interspecific com-petition is reduced when species use different resources or use the same resource at different moments or points in space. For example, sessile suspension-feeding invertebrates that con-sume small-sized plankton can coexist with others that concon-sume larger particles (Gili & Coma 1998). Species CV= 0.3 CV= 0.19 CV= 0.09 Time A bun da n c e of s p e c ie s i 1 species 3 species 5 species T o ta l a b un da n c e Figure 2
Simulation showing the effect of statistical averaging on the variability in an aggregate community property (total abundance, heavy lines, right y-axis) made up by summing the abundance of single species (abundance of species i, left y-axis). Fluctuations in species and community abundances were simulated using Tilman’s model (1999) where species abundances are assumed to be independent, equally abundant, and with the same coefficient of variation (cv = 0.3). Average total
community abundance was held constant at 100 percent cover. Statistical averaging of individual fluctuations dampens the variability of the aggregate community property as the number of species increases (note decreasing CV for total abundance).
0 50 100 150 200 0 50 100 150 200 0 20 40 60 0 50 100 150 200 0 5 10 15 20 0 10 20 30 40 0 50 100 150 200
of benthic algae can share the resource ‘space’ and minimise competition: seaweeds need a relatively small area in the substratum in order to stay attached, but they are still able to de-velop a large canopy over an area where the substratum was monopolised by encrusting forms or turf-forming algae (e.g. Connell 2003). In addition, canopies provide settlement substratum for other smaller species, such as filamentous algae and sessile invertebrates.
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Positive selection effects occur when the performance (e.g. resource use or productivity) of the most efficient species explains that of the entire community (Fig. 1c; Ives et al. 2005). For example, plant communities are usually dominated by individuals of the largest species (e.g. Polley et al. 2007). Therefore, most of the biomass in a species-rich community may be contributed by one or few dominant species and reflects the biomass of those species instead of an average value of all species present in the community (Huston 1997).
CV= 0.28 CV= 0.21 CV= 0.05 Time Abun da nc e of s pec ie s i cor = 0.95 cor = 0 cor = -0.95 0 5 10 15 20 0 50 100 0 50 100 150 200 0 5 10 15 20 0 50 100 0 50 100 150 200 0 5 10 15 20 0 50 100 0 50 100 150 200 Figure 3
Graphical depiction of the effect of the covariance in species fluctuations on the variability an aggregate community property (total
abundance, heavy lines, right y-axis) made up by summing the abundance of single species (abundance of species i, left y-axis) in communities of 2 species (either solid or dashed lines). Fluctuations in species abundances were simulated by generating 20 pairs of normal random values with mean 50, coefficient of variation 0.3, and specified
coefficient of correlation (cor = 0.95, almost perfect positive correlation; 0, no correlation, -0.95 almost perfect negative correlation). Average total community abundance was held constant at 100 percent cover. Negative pair-wise species
covariance dampens the variability of the aggregate community property (note decreasing CV for total abundance). T o ta l abu nd anc e
Variance in species properties
As expressed in equations (1) and (2), stability in an aggregate ecosystem property like total community abundance will be affected by the variances and covariances in species
abun-Introduction dances. Statistical averaging, also called the portfolio effect, is a pivotal mechanisms leading to a negative relationship between species richness and the variability of aggregate ecosys-tem properties (Doak et al. 1998, Tilman et al. 1998). When total community abundance is the sum of the abundances of many species, each varying over time, then adding more spe-cies together will increase the probability that the fluctuations in these individual abun-dances will average out statistically (Fig. 2; Doak et al. 1998). This reduces the variability in the aggregate property in relation to that of the average individual abundances. Accordingly, whenever species fluctuations are not perfectly correlated, increasing species richness will reduce the variability of the community mainly on statistical grounds.
However, because asynchrony among species results from differential environmental tolerances, statistical averaging is due in part to ecological difference among species (Cottingham et al. 2001). Moreover, the strength of statistical averaging seems to be strongly affected by the relative abundance of species. For example, high dominance of few species can dampen the richness-stability relationship (Doak et al. 1998), and lead to nega-tive and curvilinear functions (Lhomme & Winkel 2002). Therefore, ecological processes leading to heterogeneity and temporal asynchrony in species abundances influence the effect of biodiversity on ecosystem stability.
These ecological processes affect also the covariances in species abundances, which in turn influence the stability of the community (equations [1] and [2]). Pairs of species com-peting for the same resource or with differing abilities to respond to the environment should show compensatory responses, such that when the abundance of one species increases and that of the other decreases; the resulting negative covariance decreases the variability in the total community abundance (Fig. 3; Doak et al. 1998, Yachi & Loreau 1999). If the variety of environmental tolerances increases as species richness increases, then adding more spe-cies will increase the probability that some spespe-cies compensate the function of other that failed due to changes in the environment (Yachi & Loreau 1999, Ives et al. 2000). There-fore, maintenance of species with different functional response traits can be crucial for eco-system stability. Surprising, conservation managers usually concentrate on rare species that may be unable to compensate the loss of a dominant species (Thompson & Starzomski 2007).
8 Observations and experiments
Observational and manipulative experiments support the idea that increasing species rich-ness leads to increasing ecosystem stability (e.g. McNaughton 1985, Tilman & Downing 1994, Naeem & Li 1997, Ptacnik et al. 2008), but most of these studies are confounded by other variables (Hooper et al. 2005). For example, to demonstrate that biodiversity increases drought resistance in grasslands, Tilman and Downing (1994) altered plant species richness by using nutrient additions. However, increased resistance could have resulted either from species compensation (Tilman 1996) or from differences in species composition caused by the fertilisations (Huston 1997). In the observational study of McNaughton (1985) on Ser-engeti’s grasslands, the negative correlation between proportional diversity (H’) and com-munity variability was probably influenced by differences in species composition and abiotic conditions between sites.
In order to detect confounding effects of species richness and composition, investigating the relationship between biodiversity and ecosystem functioning and stability should be complemented by different experimental methods, including assembling communities in controlled environment, manipulating diversity in the field, and observing patterns in nature (Díaz et al. 2003). There is no single best method, as not all questions can be addressed equally well by these three approaches. For example, the effects of species richness per se are better addressed by synthetic-assemblages experiments, because of the greater control of species composition across replicates and levels of species richness (e.g. Loreau & Hector 2001, Benedetti-Cecchi 2004). In these experiments, random selections of species or func-tional groups are assembled to generate different diversity treatments. However, because such experiments do not represent how natural communities are assembled or dissembled–– species extinction are rarely random, for example––, the interpretation of studies using syn-thetic communities is difficult (Wardle et al. 2000, Loreau et al. 2001).
On the other hand, the effects of non-random species extinctions are better addressed by removal experiments, in which target species or functional groups are removed from the natural community (e.g. Wardle et al. 1999, O'Connor et al. 2008). As they are based on naturally assembled communities, removal experiments allow incorporating the effects of large-scale processes like variations in climate, disturbance regime, and biotic interactions
Introduction on the regional species pool (Belyea & Lancaster 1999). However, the cost of manipulating diversity in the field restricts the size and duration of removal experiments, which in turn limits the interpretation of results to the local characteristics or context. Alternatively, obser-vational studies allow using larger spatial and time scales, and broader ranges of species usually used in manipulative experiments (e.g. Troumbis & Memtsas 2000). Observational studies require to be carefully designed to account for the diversity of the sites under inves-tigation. The number of species is related to sampling effort (Ugland et al. 2003), so proper replication may be especially important in observational studies linking ecosystem stability and species richness.
The model system: hard-bottom ecosystems
Intertidal and shallow subtidal rocky habitats offer potential to test the diversity-stability relationship. In these habitats, abiotic stressors change and biological processes occur at small temporal and spatial scales (Underwood & Chapman 1996). As a consequence, inter-tidal and shallow subinter-tidal assemblages represent tractable experimental systems at the land-scape scale and small-scale experiments are usually appropriate (Giller et al. 2004).
An example of the potential of rocky shores for biodiversity research is given by the re-lationship between community structure and canopy-forming species. These species modify the environment so that it becomes more suitable for some species, but less suitable for oth-ers (e.g. Irving & Connell 2006, Lilley & Schiel 2006, Morrow & Carpenter 2008). In sub-tidal habitats, for example, canopy loss reduces the abundance of species adapted to shaded conditions (e.g. encrusting coralline algae), yet it allows the increase of species adapted to more exposed conditions (Irving & Connell 2006). In intertidal habitats, however, the re-sponse of understorey communities to canopy disturbances is still unclear (Lilley & Schiel 2006).
Aims
The aim of this study was to determinate the effects of species richness and species compo-sition on the stability of intertidal and shallow subtidal hard-bottom communities. A
combi-10
nation of manipulative and observational approaches was used to address different but com-plementary hypotheses.
In an observational study, I tested the hypothesis that (1) ecosystem stability is positively related to species richness; in a synthetic assemblage experiment, I tested the hypotheses that (2) different functional groups use different resources and that (3) increasing number of functional groups increases the efficiency of resource consumption of the assemblage (i.e. functional richness leads to transgressive overyielding in filtration rate); in a removal ex-periment I tested the hypotheses that (4) the loss of a key canopy-forming species affects the stability of the community and that (5) the effects of canopy removal depend on the pres-ence of mechanical disturbances that provide free space. Finally, analysing species abun-dance data (here after referred to as the richness-estimation study), I tested whether the sampling effort of the observational study was enough to represent the number of species of the shores here studied. The results, reported as peer-review papers and referred to by their roman numerals (I-IV, see Appendix), suggest that species composition and identity had far stronger effects on ecosystem stability than species richness per se.
Methods
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Methods
Study sites
Observational and manipulative studies were conducted at Helgoland Island, NE Atlantic, between March 2006 and March 2008. The observational study, removal experiment, and richness-estimation study (papers I, III, and IV) were conducted in the mid-low intertidal zone. This zone is characterised by canopy-forming algae (e.g. Fucus spp. and Laminaria digitata), turf-forming algae (e.g. Ceramium virgatum, Chondrus crispus, Cladophora rupestris, Corallina officinalis, Mastocarpus stellatus), and encrusting algae (e.g. Phymato-lithon spp.). Frequent sessile invertebrates are Dynamena pumila, Spirorbis spirorbis, and Electra pilosa, and conspicuous mobile consumers include Carcinus maenas and several species of periwinkles. Temporal patterns in community structure have an important sea-sonal component, as ephemeral algae like Ulva spp. and seasea-sonal Cladophorales (e.g. Cladophora sericea) become abundant during summer (Janke 1990). In the observational study, stability was compared across five sites with naturally different number of species.
Each site was of ca. 200 m2 and adjacent sites were 100 m apart from each other. The
re-moval experiment was replicated at two intertidal sites with differing degree of wave expo-sure in order to test for generality of findings. Finally, the richness-estimation study was based on data from the northern intertidal area of Helgoland.
The synthetic-assemblage experiment (paper II) was conducted in the shallow subtidal habitat, and sessile invertebrates growing on vertical surfaces were used as experimental organisms. This assemblage is characterised by mussels (e.g. Mytilus edulis), ascidians (e.g. Ciona intestinalis, Ascidiella aspersa, and Diplosoma listerianum), barnacles (e.g. Elminius modestus and Balanus crenatus), and bryozoans like Cryptosula pallasiana, and Membrani-pora membranacea (Anger 1978, Wollgast et al. 2008).
Sampling and experimental designs
In the observational study, I compared community stability across the five sample sites. Temporal variances in species abundances were calculated from repeated estimations of
species percent covers on plots of 0.25 m2 that were marked with stainless screws and
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community cover (cover summed across all species in a sampling unit) were used to
calcu-late the S index of stability (S = PV-1). On the other hand, species-accumulation curves were
used to calculate the number of species occurring at each sample site. I used regression analyses to test the hypothesis that community stability is positively related to species rich-ness. Additionally, I partitioned the temporal variance into the sum of all species variance and the sum of all pair-wise species covariances as in equation (1). The summed covariances were used as a measure of compensatory dynamics (see Theory section) and also to test whether increases in the variance of species abundances are counterbalanced by increasingly negative species covariances.
In the removal experiment (paper III), I tested the separate and interactive effects of the removal of the canopy-forming alga Fucus serratus and mechanical disturbances on com-munity stability. As in the observational study, temporal variances were obtained from
re-peated measures of species covers, but plots were of 0.09 m2 and sampled every 3 months
for 18 months. Fucus plants were removed used a knife and mechanical disturbance treat-ments consisted of a biomass removal with 50 % of the effort required to remove all organ-isms of the plot. I analysed two aspects of community stability: the temporal variability at the community level (i.e. temporal variance of community total cover), and the temporal
variability at the species level (i.e. summed covariances and Bray-Curtis1 index).The effects
of canopy removal, disturbance, and site on all of the measures of temporal variability were analysed using 3-way mixed analyses of variance (ANOVAs) with the factors Fucus canopy (2 levels: present or removed) and disturbance (2 levels: undisturbed or disturbed) consid-ered fixed and the factor site (2 levels, Nordostwatt or Westwatt) considconsid-ered random.
The synthetic-assemblage experiment (paper II) was designed to test the effect of the number of functional groups on filtration rates of suspension-feeding invertebrates, and to separate this effect from that of functional identity. The design consisted of 3 functional groups growing alone (i.e. mono-specific assemblages of mussels, colonial ascidians and bryozoans, and barnacles) and one complete mixture containing all groups. Organisms used
1
The Bray-Curtis index (BC) measures the variability between samples in terms of species abundances. The advantage of this method is that ignores the ‘double zeros’; i.e., it downplays the similarity between samples in which the same species is absent. BC works well on ecological data, which are usually plagued by zeros.
Methods to construct the assemblages were obtained by exposing artificial substrata (3 × 25 × 25 mm PVC tiles) to colonisation in the water column for 7 months, starting on May 2006 to match with the main recruitment period of epibenthic species. After that, tiles containing one func-tional group each were used to construct the experimental assemblages (Stachowicz et al. 2002).
The synthetic assemblages were maintained in the field (1 m depth), but filtration rate assays were conducted in the laboratory. Filtration rate was measured as the volume of wa-ter cleared per unit of time from a mixed-culture microalgal suspension. Four microalgae of different size were used as food in order to allow for resource complementarity in terms of particle size. A cytometric technique allowed the identification of each species of microal-gae, and so for testing whether functional types consumed different resources. ANOVA and planned contrasts were used to tease apart the effects of functional richness (richness effect) from those of each functional group (identity effect). The hypothesis that functional richness leads to overyielding was tested using a planned contrast between the filtration rate of the mixture and the average filtration rate of the monocultures (see Fig. 1b-c). The hypothesis that functional richness leads to transgressive overyielding was tested by comparing the performance of the mixture and the best-performing functional group in monocultures (see Fig. 1b-c). Permutational multivariate analysis of variance (PERMANOVA) was used to test for resource partitioning among functional groups on the basis of consumer-specific changes in the multivariate structure of prey (Fig. 1a).
For the richness-estimation study (paper IV), I quantified the abundance of species
oc-curring on fifty-two 0.04 m2 replicate plots in spring 2006. Species-accumulation curves
were used to calculate the number of species in the maximum number of quadrats. Then, the probable regional richness was estimated by fitting a curvilinear growth model that provides the asymptotic number of species as the number of replicates approaches infinity (Morgan et al. 1975).
14
3
Results and Discussion
Biodiversity, broadly defined, significantly influenced the magnitude and variability of eco-system properties such as community biomass (measured as percent cover) and resource consumption (measured as filtration rate). Nevertheless, the effects of species composition seemed to be more important than those of species richness. Contrarily to our predictions, the observational study showed a negative and curvilinear diversity-stability relationship. In the synthetic-assemblage experiment (paper II), filtration rates differed significantly among functional groups grown alone, but their average filtration rate did not differ from that of the high-diversity mixtures––i.e. the presence of more functional groups did not increase filtra-tion rate. Finally, the removal of the canopy-forming alga Fucus serratus increased the vari-ability of species without affecting the varivari-ability of communities (paper III). Compensatory dynamics, such that the abundance of some species increases while that of other decreases, buffered the community-level stability against the environmental changes caused by the canopy removal––such patters were consistent across two sites.
Collectively, these results agree with biodiversity studies on marine macroalgal (Bruno et al. 2006), terrestrial plant (Hooper et al. 2005), and freshwater communities (Downing 2005, Weis et al. 2008). These previous studies have shown that richness effects are actually subtle and that compositional effects are strong. The loss or gain of particular species there-fore may have a stronger effect on ecosystem stability than species richness per se. Thefore, predicting the consequences of biodiversity loss remains complicated, because it re-quires an accurate knowledge of the system and natural life history and should be drawn from sound experimental evidence, not from generalised models.
Species richness vs. species composition
Overyielding, or an increase in an ecosystem property with increasing species richness, was detected in the observational study (paper I). Theory predicts that overyielding is due to resource complementarity (Tilman et al. 1997b), which may occur in benthic communities. Epibenthic species can partition the available space by forming multilayered spatial struc-tures––the experiments conducted on the intertidal areas (papers I, III, and IV) showed that
Results and discussion encrusting forms, turf-forming, and canopy-forming algae formed three biotic layers, and the observational study showed that this layering tended to increase across the richness gra-dient. Multilayered structure is a characteristic of benthic communities made up of numer-ous species (Bruno et al. 2003), so resource complementarity in terms of differential use of the space might be widespread among these communities.
However, overyielding might well have resulted from the increased probability that spe-cies-rich communities included particular (“key”) species with strong effects on community abundance––i.e. positive sampling effects. Indeed, few species dominated the communities, so the apparent pattern of the community abundance could well have reflected those of the dominant species instead of an average response of all species in the community. Moreover, one of the dominant species, the canopy former Fucus serratus, had significant effects on the species composition and stability (paper III); so the relationships between site species richness, community abundance, and stability (paper I) would have been strongly influenced by changes in the abundance of this species. On the other hand, the negative and curvilinear richness-stability relationship (paper I) may have resulted from the dominance of species–– experiments have shown that the stability of communities dominated by few species is driven by these particular taxa (Steiner et al. 2005, Polley et al. 2007), and simulations sug-gest that strong heterogeneity among species abundances may lead to negative and nonlin-ear relationships between species richness and stability (Lhomme & Winkel 2002).
In consequence, even when complementarity in the use of space may be common in natural benthic communities, there is a fair chance that selection effects also operate within these assemblages. Both, selection effects and positive species interactions (including com-plementarity and facilitation) can act simultaneously or sequentially (Hooper et al. 2005, Bruno et al. 2006). The challenge is therefore to develop analytical tools that allow quantify-ing the relative contribution of each of these mechanisms to ecosystem function (e.g. Loreau & Hector 2001, Fox 2005).
The synthetic-assemblage experiment (paper II), provided the opportunity to test whether resource complementarity occurs within subtidal suspension feeders. The experi-ment was replicated at two locations in NE Atlantic coasts, and the results from both loca-tions suggest that complementarity was actually absent: the high efficiency of mussels in filtrating most of the phytoplankton species suggests that filtration rate of the mixtures was mostly due to the activity of this functional group, which may have prevented resources
16
complementarity and led to no richness effects. These results, complemented with the cor-relative evidence of the observational study, suggest that species identity and composition may have strong effects on the functioning and stability of natural community and that the consequences of biodiversity changes can not be predicted from the number of species that are loss or gained. Identity effects may be common within benthic communities, as sug-gested by recent experiments conducted on intertidal (O'Connor et al. 2008) and shallow subtidal communities (Bruno et al. 2006, O'Connor & Bruno 2007), as well as reviews and meta analyses of published datasets (Cardinale et al. 2006, Stachowicz et al. 2007).
Because the synthetic-assemblage experiment did not represent how natural communi-ties are assembled, its interpretation in a real scenario of biodiversity change may become difficult. For example, whether species are assembled as larvae and juveniles or adults can influence the outcome of synthetic experiments (Garnier et al. 1997). The removal experi-ment (paper III) tested in natural conditions what happened with the community and species stability when a particular species went locally extinct. Interesting, the results of this ‘natu-ral’ experiment also suggest that the functional characteristics of species affect stability, al-beit it was not designed to tease richness effects apart from identity effects.
In the removal experiment, a single species had strong effects on composition and stabil-ity of species. The removal of Fucus serratus significantly influenced the physical surround-ings of the remaining species, as shown in other communities where canopies ameliorate stressors like temperature and water evaporation (Bertness et al. 1999, Moore et al. 2007), and also where canopies reduce sedimentation (Kennelly & Underwood 1993). In my ex-periment, these changes had negative effects on species sensitive to sedimentation and os-motic stress, such as encrusting algae and small sessile invertebrates, yet they had positive effects on species more tolerant, such as ephemeral green algae. Therefore, disturbance can have differing effects on species, which may play an important role in maintaining the sta-bility of the community (Micheli et al. 1999).
Results and discussion
Species’ response traits influence community stability
The compositional changes caused by the canopy removal reduced the stability of species, but, these severe disturbances did not affect the stability of communities. Probably, the negative covariance resulting from the compensation between sensitive and tolerant species maintained the stability of the community. This also may explain why the additional me-chanical disturbances significantly decreased species stability only in removal plots, without affecting the community stability. Mechanical disturbances can have significant effects on species richness and composition (Valdivia et al. 2008), species coexistence (Shea et al. 2004), and stability (Bertocci et al. 2007). So, species compensation can maintain the stabil-ity of communities in the face of strong environmental disturbances. The role of species compensation in buffering community stability against stochastic change has been shown in mathematical simulations (Fig. 3; Doak et al. 1998, Yachi & Loreau 1999) and field obser-vations (Ernest & Brown 2001).
The importance of negative covariances and compensatory dynamics was also noted in the observational study (paper I), where the lack of correlation between the summed covari-ances and species richness contributed to the negative richness-stability relationship found– –theory predicts that increasingly negative covariances should offset the increases in species variances as more species are present (equation [2]; Tilman et al. 1998). Therefore, even when the number of species seemed to have little effects on ecosystem functioning, the re-sults from the intertidal experiments agree with the assertion that the presence of a variety of responses to the environment is fundamental in maintaining community stability (Walker 1992, Yachi & Loreau 1999).
The role of replication in biodiversity experiments
In the richness-estimation study (paper IV), by extrapolating species-accumulation curves we predicted a probable regional richness similar to the maximum number of species quanti-fied in the observational study (65 vs. 72). This suggests that the sampling effort in the latter was enough to represent the number of species occurring on mid-low intertidal areas of Hel-goland. On the other hand, comprehensive inventories of species suggest that 53 (Janke
18
cies can occur in these shores. According to these values, our extrapolations of the species-accumulation curves are clearly below the actual number of species. However, these exten-sive inventories included probably species occurring in different year and habitats, so these species do not necessarily coexist at the local scale.
In observational studies linking species richness and the variability in ecosystem proper-ties, the level of replication may be particularly important: first, assuring a proper replica-tion can be critical for reducing unwanted variability derived from spatial and temporal patchiness in species distributions (Cottingham et al. 2001). Second, account of rare species might be important when rare species have disproportional effects on ecosystem properties (e.g. keystone species; Lyons et al. 2005). Therefore, the ability of an experimental design to detect compositional effects on ecosystem function can depend on sample size (Allison 1999).
Conclusion
Species composition seemed to be more important for the stability of this ecosystem than the number of species and functional groups. Consequently, predicting the consequences of the widespread human-driven changes in biodiversity needs an accurate knowledge on life history and biology of species. So, descriptive work on basic life history traits is fundamen-tal in this context. On the other hand, we should not assume that mechanisms predicted by theory to lead to positive richness-stability (and functioning) relationships are unimportant in the systems here studies. Resource complementarity influences species coexistence (Ricklefs 1990), and the impact of species richness on ecosystem properties can grow stronger through succession (Cardinale et al. 2004, Cardinale et al. 2007).
Further research should address the influence of the relative abundance of species (i.e. evenness) and different types of disturbances on the relationship between biodiversity and ecosystems stability, in addition to the occurrence of species compensation under different levels of environmental stress. We still need to unravel the relationship between taxonomic and functional diversity. Identifying those traits of species that influence ecosystem proper-ties and species’ responses to the environment requires us to assess the impacts of
environ-Results and discussion mental disturbances at the levels of communities, populations, and organisms, and to inves-tigate the variations in physiological traits across geographical scales (e.g. Dahlhoff & Menge 1996, Chown & Gaston 2008).
Management of natural communities is generally based on the conservational status of species; that is, species are usually managed if they are endangered or introduced. However, conservation managers only rarely consider the functional effects of species (Thompson & Starzomski 2007). According to the results of this thesis, conservational efforts should be directed to identify the functional traits that make species important for the functioning and stability of ecosystems. Key functional traits should be conservation priorities. Finally, man-agers should assure that natural communities contain many species with different functional responses and also many species with similar functional effects. This will allow species compensation in the face of rapid environmental changes.
20
References
Allison GW (1999) The implications of experimental design for biodiversity manipulations. Am Nat 153:26-45
Anger K (1978) Development of a subtidal epifaunal community at the island of Helgoland. Helg Mar Res 31:457-470
Armsworth PR, Roughgarden JE (2003) The economic value of ecological stability. P Natl Acad Sci USA 100:7147-7151
Belyea LR, Lancaster J (1999) Assembly rules within a contingent ecology. Oikos 86:402-416
Benedetti-Cecchi L (2004) Increasing accuracy of causal inference in experimental analyses of biodiversity. Funct Ecol 18:761-768
Bertness D, Leonard G, Levine J, Schmidt P, Ingraham A (1999) Testing the relative contribution of positive and negative interactions in rocky intertidal communities. Ecology 80:2711-2726
Bertocci I, Vaselli S, Maggi E, Benedetti-Cecchi L (2007) Changes in temporal variance of rocky shore organ-ism abundances in response to manipulation of mean intensity and temporal variability of aerial expo-sure. Mar Ecol Prog Ser 338:11-20
Bruno JF, Lee SC, Kertesz JS, Carpenter RC, Long ZT, Duffy JE (2006) Partitioning the effects of algal spe-cies identity and richness on benthic marine primary production. Oikos 115:170-178
Bruno JF, Stachowicz JJ, Bertness D (2003) Inclusion of facilitation into ecological theory. Trends Ecol Evol 18:119-125
Byrnes JE, Reynolds PL, Stachowicz JJ (2007) Invasions and extinctions reshape coastal marine food webs. PLoS ONE 2:e295
Cardinale BJ, Ives AR, Inchausti P (2004) Effects of species diversity on the primary productivity of ecosys-tems: extending our spatial and temporal scales of inference. Oikos 104:437-450
Cardinale BJ, Srivastava DS, Duffy JE, Wright JP, Downing AL, Sankaran M, Jouseau C (2006) Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443:989-992
Cardinale BJ, Wrigh JP, Cadotte MW, Carroll IT, Hector A, Srivastava DS, Loreau M, Weis JJ (2007) Impacts of plant diversity on biomass production increase through time because of species complementarity. P Natl Acad Sci USA 104:18123-18128
Chapin FS, Zavaleta ES, Eviner VT, Naylor RL, Vitousek PM, Reynolds HL, Hooper DU, Lavorel S, Sala OE, Hobbie SE, Mack MC, Diaz S (2000) Consequences of changing biodiversity. Nature 405:234-242 Chown SL, Gaston KJ (2008) Macrophysiology for a changing world. P R Soc B 275:1469-1478
Christensen NL, Bartuska AM, Brown JH, Carpenter S, D'Antonio C, Francis R, Franklin JF, MacMahon JA, Noss RF, Parsons DJ, Peterson CH, Turner MG, Woodmansee RG (1996) The report of the Ecological Society of America committee on the scientific basis for ecosystem management. Ecol Appl 6:665-691
Connell SD (2003) The monopolization of understorey habitat by subtidal encrusting coralline algae: a test of the combined effects of canopy-mediated light and sedimentation. Mar Biol 142:1065-1071
Costanza R, dArge R, deGroot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, ONeill RV, Paruelo J, Raskin RG, Sutton P, van den Belt M (1997) The value of the world's ecosystem services and natural capital. Nature 387:253-260
Cottingham KL, Brown BL, Lennon JT (2001) Biodiversity may regulate the temporal variability of ecological systems. Ecol Lett 4:72-85
References Dahlhoff EP, Menge BA (1996) Influence of phytoplankton concentration and wave exposure on the
ecophysi-ology of Mytilus californianus. Mar Ecol Prog Ser 144:97-107
Díaz S, Symstad AJ, Chapin FS, Wardle DA, Huenneke LF (2003) Functional diversity revealed by removal experiments. Trends Ecol Evol 18:140-146
Dirzo R, Raven PH (2003) Global state of biodiversity and loss. Annu Rev Env Resour 28:137-167
Doak DF, Bigger D, Harding EK, Marvier MA, O'Malley RE, Thomson D (1998) The statistical inevitability of stability-diversity relationships in community ecology. Am Nat 151:264-276
Downing AL (2005) Relative effects of species composition and richness on ecosystem properties in ponds. Ecology 86:701-715
Elton SC (1958) The ecology of invasions by animals and plants. The University of Chicago Press, Chicago, USA
Ernest SKM, Brown JH (2001) Homeostasis and compensation: the role of species and resources in ecosystem stability. Ecology 82:2118-2132
Fox JW (2005) Interpreting the 'selection effect' of biodiversity on ecosystem function. Ecol Lett 8:846-856 Fridley JD (2001) The influence of species diversity on ecosystem productivity: how, where, and why? Oikos
93:514-526
Garnier E, Navas M-L, Austin MP, Lilley JM, Gifford RM (1997) A problem for biodiversity-productivity studies: how to compare the productivity of multispecific plant mixtures to that of monocultures? Acta Oecologica 18:657-670
Gaston KJ, McArdle BH (1994) The temporal variability of animal abundances - measures, methods and pat-terns. Philos T Roy Soc B 345:335-358
Gili JM, Coma R (1998) Benthic suspension feeders: their paramount role in littoral marine food webs. Trends Ecol Evol 13:316-321
Giller PS, Hillebrand H, Berninger U-G, Gessner MO, Hawkins S, Inchausti P, Inglis C, Leslie H, Malmqvist B, Monaghan MT, Morin PJ, O'Mullan G (2004) Biodiversity effects on ecosystem functioning: emerging issues and their experimental test in aquatic environments. Oikos 104:423-436
Grimm V, Schmidt E, Wissel C (1992) On the application of stability concepts in ecology. Ecol Model 63:143-161
Holling CS (1973) Resilience and stability of ecological systems. Annu Rev Ecol Syst 4:1-23
Hooper DU, Chapin I, F. S., Ewel JJ, Hector A, Inchausti P, Lavorel S, Lawton JH, Lodge DM, Loreau M, Naeem S, Schmid B, Setälä H, Symstad AJ, Vandermeer J, Wardle DA (2005) Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr 75:3-35
Huston MA (1997) Hidden treatments in ecological experiments: re-evaluating the ecosystem function of bio-diversity. Oecologia 110:449-460
IPCC (2007) Climate Change 2007: Synthesis Report. Cambridge University Press, Cambridge
Irving A, Connell S (2006) Predicting understorey structure from the presence and composition of canopies: an assembly rule for marine algae. Oecologia 148:491-502
Ives AR, Cardinale BJ, Snyder WE (2005) A synthesis of subdisciplines: predator-prey interactions, and biodi-versity and ecosystem functioning. Ecol Lett 8:102-116
Ives AR, Klug JL, Gross K (2000) Stability and species richness in complex communities. Ecol Lett 3:399-411 Janke K (1986) Die Makrofauna und ihre Verteilung im Nordost-Felswatt von Helgoland. Helg Mar Res
40:1-55
Janke K (1990) Biological interactions and their role in community structure in the rocky intertidal of Helgo-land (German Bight, North Sea). Helg Mar Res 44:219-263
22
Johnson KH, Vogt KA, Clark H, Schmitz O, Vogt D (1996) Biodiversity and the productivity and stability of ecosystems. Trends Ecol Evol 11:372-377
Kennelly SJ, Underwood AJ (1993) Geographic consistencies of effects of experimental physical disturbance on understorey species in sublittoral kelp forests in central New South Wales. J Exp Mar Biol Ecol 168:35-58
Lehman CL, Tilman D (2000) Biodiversity, stability, and productivity in competitive communities. Am Nat 156:534-552
Lhomme JP, Winkel T (2002) Diversity-stability relationships in community ecology: Re-examination of the portfolio effect. Theor Popul Biol 62:271-279
Lilley S, Schiel D (2006) Community effects following the deletion of a habitat-forming alga from rocky ma-rine shores. Oecologia 148:672-681
Loreau M (2000) Biodiversity and ecosystem functioning: recent theoretical advances. Oikos 91:3-17
Loreau M, Hector A (2001) Partitioning selection and complementarity in biodiversity experiments. Nature 412:72-76
Loreau M, Naeem S, Inchausti P, Bengtsson J, Grime JP, Hector A, Hooper DU, Huston MA, Raffaelli D, Schmid B, Tilman D, Wardle DA (2001) Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294:804-808
Lyons KG, Brigham CA, Traut BH, Schwartz MW (2005) Rare species and ecosystem functioning. Conserv Biol 19:1019-1024
MacArthur RH (1955) Fluctuations of animal populations and a measure of community stability. Ecology 36:533-536
McNaughton SJ (1985) Ecology of a grazing ecosystem: the Serengeti. Ecol Monogr 55:259-294
Micheli F, Cottingham KL, Bascompte J, Bjornstad ON, Eckert GL, Fischer JM, Keitt TH, Kendall BE, Klug JL, Rusak JA (1999) The dual nature of community variability. Oikos 85:161-169
Moore P, Hawkins SJ, Thompson RC (2007) Role of biological habitat amelioration in altering the relative responses of congeneric species to climate change. Mar Ecol Prog Ser 334:11-19
Morgan PH, Mercer LP, Flodin NW (1975) General model for nutritional responses of higher organisms. P Natl Acad Sci USA 72:4327-4331
Morrow K, Carpenter R (2008) Shallow kelp canopies mediate macroalgal composition: effects on the distri-bution and abundance of Corynactis californica (Corallimorpharia). Mar Ecol Prog Ser 361:119-127 Naeem S (1998) Species redundancy and ecosystem reliability. Conserv Biol 12:39-45
Naeem S, Li SB (1997) Biodiversity enhances ecosystem reliability. Nature 390:507-509
O'Connor NE, Bruno JF (2007) Predatory fish loss affects the structure and functioning of a model marine food web. Oikos 116:2027-2038
O'Connor NE, Grabowski JH, Ladwig LM, Bruno JF (2008) Simulated predator extinctions: Predator identity affects survival and recruitment of oysters. Ecology 89:428-438
Pimm SL (1991) The balance of nature?: ecological issues in the conservation of species and communities. The University of Chicago Press, Chicago
Polley HW, Wilsey BJ, Derner JD (2007) Dominant species constrain effects of species diversity on temporal variability in biomass production of tallgrass prairie. Oikos 116:2044-2052
References Ptacnik R, Solimini AG, Andersen T, Tamminen T, Brettum P, Lepisto L, Willen E, Rekolainen S (2008)
Diver-sity predicts stability and resource use efficiency in natural phytoplankton communities. P Natl Acad Sci USA 105:5134-5138
Purvis A, Hector A (2000) Getting the measure of biodiversity. Nature 405:212-219
Reichert K, Buchholz F (2006) Changes in the macrozoobenthos of the intertidal zone at Helgoland (German Bight, North Sea): a survey of 1984 repeated in 2002. Helg Mar Res 60:213-223
Ricklefs RE (1990) Ecology. W. H. Freeman and Company, New York
Sax DF, Gaines SD (2003) Species diversity: from global decreases to local increases. Trends Ecol Evol 18:561-566
Schluter D (1984) A variance test for detecting species associations, with some example applications. Ecology 65:998-1005
Shea K, Roxburgh SH, Rauschert SJ (2004) Moving from pattern to process: coexistence mechanisms under intermediate disturbance regimes. Ecol Lett 7:491-508
Stachowicz JJ, Bruno JF, Duffy JE (2007) Understanding the effects of marine biodiversity on communities and ecosystems. Annu Rev Ecol Evol S 38:739-766
Stachowicz JJ, Fried H, Osman RW, Whitlatch RB (2002) Biodiversity, invasion resistance, and marine eco-system function: Reconciling pattern and process. Ecology 83:2575-2590
Steiner CF, Long ZT, Krumins JA, Morin PJ (2005) Temporal stability of aquatic food webs: partitioning the effects of species diversity, species composition and enrichment. Ecol Lett 8:819-828
Thompson R, Starzomski BM (2007) What does biodiversity actually do? A review for managers and policy makers. Biodivers Conserv 16:1359-1378
Tilman D (1996) Biodiversity: population versus ecosystem stability. Ecology 77:350–363
Tilman D (1999) The ecological consequences of changes in biodiversity: a search for general principles. Ecol-ogy 80:1455–1474
Tilman D, Downing JA (1994) Biodiversity and stability in grasslands. Nature 367:363-365
Tilman D, Knops J, Wedin D, Reich P, Ritchie M, Siemann E (1997a) The influence of functional diversity and composition on ecosystem processes. Science 277:1300-1302
Tilman D, Lehman CL, Bristow CE (1998) Diversity-stability relationships: Statistical inevitability or ecologi-cal consequence? Am Nat 151:277-282
Tilman D, Lehman CL, Thomson KT (1997b) Plant diversity and ecosystem productivity: Theoretical consid-erations. P Natl Acad Sci USA 94:1857-1861
Troumbis AY, Memtsas D (2000) Observational evidence that diversity may increase productivity in Mediter-ranean shrublands. Oecologia 125:101-108
Ugland KI, Gray JS, Ellingsen KE (2003) The species-accumulation curve and estimation of species richness. J Anim Ecol 72:888-897
Underwood AJ, Chapman MG (1996) Scales of spatial patterns of distribution of intertidal invertebrates. Oecologia 107:212-224
Valdivia N, Stehbens JD, Hermelink B, Connell SD, Molis M, Wahl M (2008) Disturbance mediates the effects of nutrients on developing assemblages of epibiota. Austral Ecol 33:951-962
Walker BH (1992) Biodiversity and ecological redundancy. Conserv Biol 6:18-23
Wardle DA, Bonner KI, Barker GM, Yeates GW, Nicholson KS, Bardgett RD, Watson RN, Ghani A (1999) Plant removals in perennial grassland: vegetation dynamics, decomposers, soil biodiversity, and eco-system properties. Ecol Monogr 69:535-568
24
Wardle DA, Huston MA, Grime JP, Berendse F, Garnier E, Laurenroth WK, Setälä H, Wilson SD (2000) Bio-diversity and ecosystem function: an issue in ecology. Bull Ecol Soc Am 81:235-239
Weis JJ, Madrigal DS, Cardinale BJ (2008) Effects of algal diversity on the production of biomass in homoge-neous and heterogehomoge-neous nutrient environments: a microcosm experiment. PLoS ONE 3:e2825 Wollgast S, Lenz M, Wahl M, Molis M (2008) Effects of regular and irregular temporal patterns of disturbance
on biomass accrual and species composition of a subtidal hard-bottom assemblage. Helg Mar Res 62:309-319
Yachi S, Loreau M (1999) Biodiversity and ecosystem productivity in a fluctuating environment: The insur-ance hypothesis. P Natl Acad Sci USA 96:1463-1468
Glossary
Glossary
Aggregate ecosystem property: a property that is calculated by summing that property across the species living in the ecosystem.
Biodiversity: the sum of all biotic variation in the biosphere from the level of gene to eco-system.
Compensation, species compensation, compensatory dynamics: a decrease in the abun-dance of one species that is accompanied by a compensatory increase in the abunabun-dance of other.
Complementarity effect: an increase in an ecosystem property due to resource complemen-tarity or facilitation among species in a species-rich community.
Ecosystem: the level of biological organisation that includes animals and plants in associa-tion, together with the physical variables of their surroundings. Ecological interactions be-tween species regulate the transformation and transport of energy across the ecosystem. Such transformations include the assimilation of carbon dioxide into organic carbonic com-pounds by plants and the consumption of plants by grazers and animals by carnivorous. Ecosystem functioning, performance: a simple contraction for ‘how ecosystems work’ and encompasses ecosystem properties, goods, and services.
Ecosystem goods and services: the ecosystem properties that contribute to human welfare both directly and indirectly.
Ecosystem properties: 1 the sizes of pools of materials like nutrients and carbon. 2 the rates of processes like energy fluxes across trophic levels.
Functional traits: the characteristics of species that influence ecosystem properties.
Functional effect traits: the characteristics of species that influence ecosystem properties; e.g., biomass, size, rate of nutrient uptake.
Functional group: a classification of species according to either their effect to ecosystem properties or their response to the environment.
26
Functional response traits: the characteristics of species that define how species respond to the environment; e.g., ranges of tolerance to salinity, temperature, solar radiation, or other environmental variables.
Observational study: a study in which a variable is measured across individuals, popula-tions, or higher levels of organisation. No attempt is made to affect the response of the ob-servational units––no treatment is applied, for example.
Overyielding: an increase in the magnitude of an ecosystem property (e.g. community bio-mass) as species richness increases.
Positive selection effects: the increased probability that more diverse communities include species with extreme functional values. The performance of the community represents then the performance of these particular species instead of the average response of all of the spe-cies in the community.
Removal experiment: an experiment in which the individuals of a species or functional group is removed from a community.
Resource complementarity, partitioning, niche partitioning: the capacity of species to use different resources or use them in different points of time or space.
Richness effect: an increase in an ecosystem property in a species-rich community relative to a species-poor one. The property in the species-rich community is larger than the average property calculated across the constituent species grown alone (monocultures).
Species accumulation curve: a graphical method used to estimate the species richness in areas where the observer is unable to sample all of the species. The procedure consists of calculating and plotting the average number of species (and its standard deviation) of the smallest sample size (1). Then all combinations of the next sample size are randomised and the mean cumulative species richness is plotted. This procedure is repeated for all sample sizes.
Species richness: the number of species living in a given area. Stability: the state of being not likely to change or fail.
Glossary Statistical averaging, portfolio effect: a reduction in the variability in an ecosystem prop-erty as species richness increases. This occurs because the ecosystem propprop-erty is the sum of that property across (temporally) fluctuating species; adding more species increases the probability that these fluctuations will ‘average out’.
Summed covariances: the sum of all of the pair-wise species covariances (calculated throughout time) within a biological community
Summed variances: the sum of all of the species variances (calculated throughout time) within a community.
Synthetic-assemblage experiment: an experiment in which the researcher constructs com-munities by placing together individuals of several species into an experimental unit. The selection of species is usually done at random from a subset of the local species pool.
Transgressive overyielding: the phenomenon in which the productivity or resource use of species-rich mixtures exceeds (transgress) that of the best-performing species grown alone. The presence of transgressive overyielding suggests that positive species interactions may be responsible for richness effects.
28
Appendix
Paper I
Paper I
Nelson Valdivia*, Markus Molis (In press) Observational evidence of a negative
biodiversity-stability relationship in intertidal epibenthic communities. Aquatic Biology
Biologische Anstalt Helgoland, Alfred Wegener Institute for Polar and Marine Research, Section Seaweed Biology, Kurpromenade 201, 27498 Helgoland, Germany
* Corresponding author
Email nelson.valdivia@awi.de
Tel. ++49(0)47258193294
