How functional is functional? Ecological groupings … · REVIEW PAPER How functional is functional? Ecological groupings in terrestrial animal ecology: towards an animal functional

REVIEW PAPER

How functional is functional? Ecological groupingsin terrestrial animal ecology: towards an animalfunctional type approach

Niels Blaum • Eva Mosner • Monika Schwager •

Florian Jeltsch

Received: 13 August 2010 / Accepted: 18 January 2011 / Published online: 30 January 2011� Springer Science+Business Media B.V. 2011

Abstract Understanding mechanisms to predict changes in plant and animal communi-

ties is a key challenge in ecology. The need to transfer knowledge gained from single

species to a more generalized approach has led to the development of categorization

systems where species’ similarities in life strategies and traits are classified into ecological

groups (EGs) like functional groups/types or guilds. While approaches in plant ecology

undergo a steady improvement and refinement of methodologies, progression in animal

ecology is lagging behind. With this review, we aim to initiate a further development of

functional classification systems in animal ecology, comparable to recent developments in

plant ecology. We here (i) give an overview of terms and definitions of EGs in animal

ecology, (ii) discuss existing classification systems, methods and application areas of EGs

(focusing on terrestrial vertebrates), and (iii) provide a ‘‘roadmap towards an animal

functional type approach’’ for improving the application of EGs and classifications in

animal ecology. We found that an animal functional type approach requires: (i) the

identification of core traits describing species’ dependency on their habitat and life history

traits, (ii) an optimization of trait selection by clustering traits into hierarchies, (iii) the

assessment of ‘‘soft traits’’ as substitute for hardly measurable traits, e.g. body size for

dispersal ability, and (iv) testing of delineated groups for validation including experiments.

N. Blaum (&) � F. JeltschPlant Ecology and Conservation Biology, University of Potsdam, Maulbeerallee 2,14469 Potsdam, Germanye-mail: [email protected]

E. MosnerConservation Biology, University of Marburg, Karl-von-Frisch-Straße 8, 35032 Marburg, Germany

Present Address:E. MosnerEcological Interactions, Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany

M. SchwagerBiodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25,60325 Frankfurt (Main), Germany

123

Biodivers Conserv (2011) 20:2333–2345DOI 10.1007/s10531-011-9995-1

Keywords Ecological classification � Functional type � Guild � Functional trait �Trait selection � Effect group � Response group � Environmental relationships

Introduction

Understanding causes and mechanisms of changes in community structure of plants and

animals is a key challenge of ecology for predicting future patterns of occurrence, abun-

dance and diversity under global change. The need to transfer knowledge gained from

single species to a more generalized approach has led to the development of categorization

systems where species’ similarities in life strategies and traits are classified into ecological

groups (EGs) like functional groups/types or guilds. The main advantage of applying EGs

over single species approaches in understanding biodiversity changes to environmental

alterations is the generalization of results. For example, developing management strategies

for biodiversity conservation requires a process based understanding of multiple species,

which is practically impossible to implement in a reasonable time and cost frame using

single species approaches. Instead, using an EG approach, where species are described by

across species traits will include the sensitivities of multiple species into a management

decision. Also the assessment of functional group richness instead of simply measuring

species richness is favourable since functional groups are directly related to traits rather

than to an evolutionary based taxonomic classification, which may not relate to the

capacity of focal organisms to provide a specific ecosystem service (Tilman et al. 1997).

EGs have been applied in several fields of ecology, e.g. to clarify general relationships

between EGs and ecosystem functioning (e.g. Du Toit and Cumming 1999; Diaz and

Cabido 2001; Brodie et al. 2009), to classify habitats (e.g. Degraaf and Chadwick 1984;

Kurosawa 2009), to predict changes due to environmental alterations (e.g. Croonquist and

Brooks 1991; Wiegand et al. 1997; Kissling et al. 2008), and in landscape management and

nature conservation (e.g. Verner 1984; Cousins and Lindborg 2004; Todd and Andrews

2008; Barbaro and van Halder 2009).

While functional classification systems have a long tradition in plant ecology their

application in animal ecology remains challenging. The first case of a functional classi-

fication system can be dated back to 300 BC when Theophrastus classified plants into trees,

shrubs and herbs. Well established schemes include structural classifications (Raunkiaer

1934), r-/K-strategies (MacArthur and Wilson 1967; Pianka 1970), C–S–R strategy types

(Grime 1979), plant functional types (PFT) (Montalvo et al. 1991; Lavorel et al. 1997;

Weiher et al. 1999; Lavorel and Garnier 2002; Diaz et al. 2004), and response (community

level) and effect (ecosystem level) groups (Hooper et al. 2002; Violle et al. 2007; Lavorel

et al. 2007).

Nevertheless, the selection criteria for setting up EGs are manifold and some studies

demonstrate that their application can also be misleading (Jaksic et al. 1996). In particular,

the integration of results from different studies on similar topics/ecosystems requires a

standardized methodology for EGs to allow for comparisons and meta-analyses. In plant

ecology, this refinement of methods to set up EGs has been the focus of recent develop-

ments (Pillar 1999; Cornelissen et al. 2003; Poschlod et al. 2003). In contrast, similar

approaches in animal ecology are scarce, and although EGs are applied continuously,

general problems in assignment and applicability have not been solved yet.

In this review, we aim to initiate a discussion on a further development of functional

classification systems in animal ecology focusing on vertebrates. We first clarify the usage

2334 Biodivers Conserv (2011) 20:2333–2345

123

of terms for different groupings. Second, we summarize the methods of species assignment

into EGs and provide application areas for these EGs (e.g. in nature conservation and

landscape management). Finally, we propose prospects for further refinement of approa-

ches in animal ecology.

Literature survey

We searched the ISI Web of Science for publications between 1960 and 2010 focusing on

ecological categorization using the terms: functional group, functional trait, functional

type, functional classification, functional response type, adaptive syndrome, and guild.

Overall, 1,487 papers matched with one of the above mentioned terms and are applied

in plant and animal ecology. EGs in animal ecology across all taxonomic groups are mostly

described by the term guild (69%, Fig. 1). While functional type is dominant in plant

ecology (38%), this term is used in only 7% of the animal ecological studies. Functional

groups, used in 19% of the animal ecological studies (31% in plant ecology) and are mostly

restricted to aquatic systems (Johnson et al. 2003; Bremner et al. 2003; Dumay et al. 2004).

The term functional trait in animal ecology was used in less than 5% (17% in plant

ecology). The terms functional classification, functional response type and adaptive syn-

drome play a minor role in both, animal and plant ecology (\5%).

Terms and definitions of EGs

Root (1967) introduced EGs to animal ecology and defined the term ‘‘guild’’ as ‘‘[…] a

group of species that exploit the same class of environmental resources in a similar way’’

and ‘‘[…] that overlap significantly in their niche requirements’’. A few years later, the

0

10

20

30

40

50

60

70

80

Guild

Functi

onal

Group

Functi

onal

Type

Functi

onal

Trait

Functi

onal

Classif

icatio

n

Functi

onal

Respo

nse T

ype

Adapt

ive S

yndr

ome

pro

po

rtio

n o

f ap

plie

d t

erm

s w

ith

in p

lan

t/an

imal

eco

log

y [%

]

plant ecology (N=844)

animal ecology (N=826)

Fig. 1 Relative amount of concepts used for ecological groupings in animal and plant ecology publications(ISI Web of Science Literature Survey, 1960–2010)

Biodivers Conserv (2011) 20:2333–2345 2335

123

term ‘‘functional type’’ was devised by Cummins (1974) to describe groups of marine

invertebrates depleting the same class of food resources. Gitay and Noble (1997) suggested

using the term ‘‘functional group’’ for a ‘‘[…] non-phylogenetic classification leading to a

grouping of organisms that respond in a similar way to a syndrome of environmental

factors’’. Other authors have applied the term to describe species that do not respond in a

similar way to ecosystem functions but perform the same ecosystem service e.g. by

influencing nutrient cycling, productivity, water uptake, or trophic levels (Box 1996; Diaz

and Cabido 1997; Blondel 2003; Diaz et al. 2004; Dumay et al. 2004).

Within these definitions, mainly two approaches constitute the basis for delineating

EGs: (i) the resource centred (Root 1967) and (ii) the functional approach (Cummins

1974). The resource centred approach is mostly associated with the term ‘‘guild’’ and

focuses on the common sharing of resources within a group of species. The functional

approach can be divided into two opposing views of species-environment interactions to

categorize groups. First, using attributes of species’ responses to environmental conditions

(functional response group/type) and second, applying attributes of species’ effects on their

environment (functional effect group/type) (Diaz and Cabido 2001).

The resource-centred approach

EGs in animal ecology are mostly based on the resource-centred guild approach (Root

1967) where resource use is either related to food or to suitable reproduction sites. This

approach assumes that guilds comprise species ‘‘that overlap significantly in their niche

requirements’’. Pianka (1980) extended this concept characterizing guilds as ‘‘arenas of

intense interspecific competition, with strong interactions within guilds but weak inter-

actions between members of different guilds’’.

These ideas have set the starting point for a number of studies investigating the intensity

of competition between and within guilds. However, ecological surveys on this topic led to

ambiguous results with all kinds of competitive relationships within (e.g. Brown et al.

1979; Adams 2007) and between guilds (e.g. Fritz et al. 2002), and even missing com-

petition within proclaimed guilds (e.g. Steffan-Dewenter and Tscharntke 2000; Westphal

et al. 2006). When resource use as the selected parameter characterizes the EGs (guilds),

competition between group members is likely (Degraaf and Chadwick 1984). On the

contrary, competition between different groups or species of different groups might occur

when species are unspecific in resource use i.e. generalists, and are thus assigned to only

one group although they should also rank among others (Hawkins and MacMahon 1989;

Elliott et al. 2007). Finally, the use of similar resources might not lead to competition, if

other factors are more influential for community structure (e.g. presence of predators,

superabundant resources). Although the consideration of interactions between species of

the same group and between groups is important, environmental changes are likely to

affect interactions and relationships between the members of an EG (Voigt et al. 2003;

Resetarits and Chalcraft 2007).

The functional type/group approach

While guilds describe the similarity in resource sharing and competition without consid-

eration of processes and functions, functional groups in animal ecology refer so far to

species that perform a similar ecosystem function/service without any relation of com-

petition (Blondel 2003). In this refined definition, functional groups are seen as effect

groups and are complemented by guilds comparable to functional response groups in plant


123

ecology, where plants are grouped in relation to their functional responses to disturbances

(e.g. fire and resprouting ability) (e.g. Lavorel and Garnier 2002). However, the similarity

between guilds and functional response groups is restricted to cases where resource use

determines the response to the environment (Blondel 2003). In cases without a focus on

resource exploitation, e.g. regarding the response to environmental perturbations, func-

tional response groups might need to be assigned differently. For example, if perturbation

leads to an increase in predator abundance, functional response groups should reflect the

ability of species to struggle with new conditions e.g. predator avoidance behaviour or a

high population growth rate.

Therefore, we suggest (i) to expand the functional group/type approach by including

both, response and effect groups, and (ii) to use the term functional group when rela-

tionships with the environment are observed, while guild is applicable when species and

their performance are studied (Lavorel and Garnier 2002; Blondel 2003).

Assignment of species to EGs

Principally, two different approaches are applied for the assignment of species to EGs

(Woodward and Cramer 1996). First, expert knowledge on species parameters of the focal

community is used for the definition of the grouping categories. However, this a priori

approach can lead to artificial assemblages of syntopic species, which are often taxo-

nomically related, whereas the type of relation remains unclear (Jaksic 1981; Terborgh and

Robinson 1986; Blondel 2003).

Second, EGs are identified a posteriori by using quantitative statistical methods, e.g.

nearest neighbour statistics, cluster analysis, principal components analysis, canonical

correlation, and Monte Carlo techniques (Hawkins and MacMahon 1989; Simberloff and

Dayan 1991; Pillar 1999). Here, a variety of species’ parameters is sampled and analyzed

to identify patterns of species aggregation, which are subsequently used to designate EGs.

Despite the ‘‘objectivity’’ of a posteriori approaches, the statistical analysis can also lead to

artificial results (Hawkins and MacMahon 1989; Simberloff and Dayan 1991), and the

decision on which parameters are measured and included into the analysis remains

ambiguous (Terborgh and Robinson 1986; Hawkins and MacMahon 1989).

Although, both approaches are commonly used in animal ecology, no clear trend for

favouring one over another can be identified. In any case, classification of species into EGs

needs rigorous testing to ensure validity of assumptions and results (Barnett et al. 2007).

Applications of EGs in animal ecology

Community comparisons

The comparison of EGs between animal communities of similar environmental conditions

derives from the idea that guilds are basic building blocks within communities (Hawkins

and MacMahon 1989). Since general ecological mechanisms are assumed to act similarly

in different regions with comparable environmental conditions, EGs are thought to recur

over these regions due to similar ecological and evolutionary pressures. Furthermore,

evolutionary trade-offs between traits should lead to similar correlations between traits

within EGs (Terborgh and Robinson 1986; Simberloff and Dayan 1991; Blondel 2003). For

example, in a study on North American desert mammal communities (MacMahon 1976)


123

functional similarity was examined using foraging habits for classification. The compari-

son of different deserts revealed fundamental differences between hot and cold deserts, but

a high functional similarity among all hot deserts. This occurred despite differences among

hot deserts in terms of abiotic and biotic features (e.g. amount of annual precipitation).

Although functional diversity of feeding guilds did not reflect all habitat characteristics in

detail, however, on a broader scale, the potential value of EG-approaches for predicting

community organization was emphasized.

The functional similarity between different areas may also depend on the spatial scale of

comparisons. Parker et al. (2001) described vertebrate communities (amphibian, reptile,

bird and mammal species) in a taxonomic and in a feeding guild categorization, both, on a

regional and subcontinental scale. On the regional scale, all measures (guild structure,

guild richness and species richness) reflected environmental conditions (vegetation struc-

ture and elevation) well. However, in a comparison between subcontinents, guild structure

and species richness showed a less clear trend where guild structure was not merely

explainable by vegetation structure, and species richness was partially unrelated to vege-

tation complexity. This lack of consistency on the subcontinental scale possibly emerged

from processes like speciation, extinction and dispersal (Parker et al. 2001).

Community comparisons are also applied to analyze habitat variables that shape

communities (e.g. Mac Nally 1994; Adamik et al. 2003; Blaum et al. 2007). For example,

species richness and composition of bird guilds in forests change substantially in relation to

horizontal and vertical structural diversity of the studied forest patch. Richness within

guilds was higher in structurally rich forests compared to monocultures (Adamik et al.

2003). Similarly, composition and species richness of carnivore guilds in Kalahari

rangelands strongly depended on the structural diversity of the vegetation (Blaum et al.

2007).

Across taxa comparisons

In plant ecology, the functional classification of EGs sensu Gitay and Noble (1997)

explicitly emphasizes ‘‘non-phylogenetic’’ groupings as a basic criterion. In contrast, in

animal ecology only few studies investigated multi- and across taxa EGs including

mammals, birds, reptiles and arthropods (MacMahon 1976; Brown et al. 1979; Jaksic

1981; Jaksic et al. 1993; Parker et al. 2001) because such studies are extremely time and

cost intensive, require data collection and analysis at different spatial scales, and are

coupled with methodological difficulties (Blondel 2003). One example where functional

effect groups across taxonomic levels were investigated was a study on fish and salamander

predators and their effects on their prey communities (Chalcraft and Resetarits 2003). In

this study, the degree of functional similarity between species that share similar traits but

originate from different taxa was assessed by classifying predator species according to

taxon, gap size or microhabitat use. Results show that a similarity in traits across taxa can

result in a similar effect on prey communities but only for specific response variables. For

example, the trait ‘‘habitat use’’ had a significant effect on prey species richness but not on

prey biomass.

Despite these limitations the classification of EGs across-taxa are crucial for detecting

climate- or land use-induced changes of ecosystems. For example, mammal and bird guilds

were used to indicate anthropogenic-induced changes in wetland areas (Croonquist and

Brooks 1991). While mammal guilds were insensitive in their response to habitat change,

habitat specificity- and seasonality-guilds of birds indicated habitat disturbances. The

contrast between the sensitivity of the different taxonomic guilds was explained by the


123

relatively higher sedentariness of mammals as compared to birds, which can readily dis-

perse into suitable habitats.

Application of EGs in nature conservation and landscape management

The application of EGs is particularly relevant in nature conservation and landscape

management where EGs are used to analyze and indicate the effects of environmental

changes on community structure as a result of anthropogenic (e.g. land use, climate) and

natural drivers (e.g. fire, windbreak) (Verner 1984; Szaro 1986; Du Toit and Cumming

1999; Thiollay 1999; Caro and O’Doherty 1999; O’Connell et al. 2000; Miller and Cale

2000; Rodewald and Yahner 2001; Schulze et al. 2004; Barlow and Peres 2004; Blaum

et al. 2007, 2009; Todd and Andrews 2008; Klingbeil and Willig 2009; Barbaro and van

Halder 2009). The advantage of using EGs in nature conservation is the reduction of

working expenditures to investigate multiple species/communities. In this context, clas-

sification criteria are mostly chosen to be simple and based on e.g. food resources and

habitat features are applied. However, too much simplification might be counterproductive

where more than simply resource use could fundamentally structure an animal’s life like

for example a particular landscape/habitat context (Ewers and Didham 2006). An approach

where resource use was included in ‘‘higher resolution’’ was the study of Verner (1984)

aiming to apply the guild concept in management of bird populations. Classifying species

by their foraging and nesting site requirements, he defined guilds distinguished between

different ‘‘zones of importance’’. For example, guilds of ‘‘primary feeding zones’’ com-

prised species using this particular area primarily for the respective function (more than

50% of their time expenditure in terms of foraging activities). As Verner himself already

realized this assignment might become difficult when species use different habitats or

structures in nearly equal amounts like generalists often do (Roberts 1987). Nevertheless, it

is important to consider not only an association between species and their environment

itself but also the strength of correlation of this association. O’Connell et al. (2000) applied

such a ‘‘detailed’’ classification system for a so called Bird Community Index (BCI) as an

indicator system for landscape-scale environmental stressors. Species were assigned to 16

behavioural and physiological guilds, which represented functional, compositional and

structural elements. Guilds were categorized as ‘‘specialist’’ or ‘‘generalist’’ depending on

their relationship to the corresponding elements. Each species was assigned to more than

one guild and thus species could be generalists for one trait while being specialist for

another. This approach appeared to be representative for landscape gradients as an inde-

pendent verification revealed.

The selection of a suitable ecological group to indicate environmental changes requires

the explicit inclusion of environment sensitive traits of species, and species with weak

abilities for adaptation (Croonquist and Brooks 1991; O’Connell et al. 2000; Reynaud and

Thioulouse 2000). Caro and O’Doherty (1999) stated that such species should have small

body sizes since small animal species often show a stronger sensitivity to environmental

changes due to shorter generation periods, smaller home ranges and lower mobility (Du

Toit and Cumming 1999). Moreover, high metabolic rates of small sized species lead to

more rapid incorporation of environmental pollutants, and shorter generation times that

allow earlier observation of changes in population dynamics. In addition to small body

size, particular taxonomic groups might appear more useful as indicators than others.

However, it seems important to know how species of all taxonomic orders respond to

environmental changes, especially since differing responses are to be expected among


123

different taxonomic groups (Voigt et al. 2003). Therefore, considering more than one

indicator group and a classification of indicators based on multiple traits is reasonable as

well as a selection of indicative species based on their ‘‘vulnerability’’ (Ewers and Didham

2006). However, when the considered species’ traits sum up to a high number of possible

trait combinations, using indicator groups might not lead to a simplification and nothing is

won (Blackburn et al. 2005). In any case, a comprehensive knowledge of species’ traits and

behaviour is necessary for a proper classification and prediction of species responses

(Elliott et al. 2007). For example, Szaro (1986) tested several ways of classifying bird

species into functional guilds by behavioural attributes and into structural guilds by habitat

use. However, the species within particular guilds might responded individually different

to environmental changes and the presence or absence of a specific guild may therefore not

always indicate a change in the environment (Szaro 1986; Miller and Cale 2000; Mac

Nally et al. 2008).

We therefore suggest to apply classification systems which (i) account for more than

just resource use where necessary and consider different species’ traits, (ii) consider a

particular resolution of species habits like differential usage of habitat, and (iii) consider

species flexibility to respond to their environment, i.e. generalists versus specialists, sen-

sitive versus insensitive species, and others.

Conclusion—towards an animal functional type approach

During the last few years EGs have made a big step in plant ecology. A clear emphasis has

been set on identifying the most important plant traits for population and community

responses to environmental changes and for the relationship between species traits and

ecosystem functioning. For that reason, much effort has been invested into analyzing

(i) how plant traits correlate to their environment and (ii) how functional trait lists and

classification systems can be improved grasping the most determining processes in plant’s

life.

The development of comparable classification systems in animal ecology beyond the

resource-centered guild approach remains a challenge.

Nevertheless, we think that further development of EG-approaches in animal ecology

can lead to fundamental insights in different ecological fields, including applied conser-

vation. Indeed, the need for multiscale and multitaxa approaches in animal ecology con-

sidering life-history traits has been highlighted recently (Summerville et al. 2006;

Cushman et al. 2008; Barbaro and van Halder 2009), also in light of the strong potential

link between functional classification, trait complementarity between species, and the

likely role of animal communities in providing ecosystem services (Philpott et al. 2009). A

first step to improve methodologies of EG-studies is to develop appropriate criteria for

their successful application in nature conservation and landscape management. In this

respect, we consider the following points important.

Application of a functional approach

In animal ecology, EGs are so far mostly defined as guilds, and the classification is based

on the usage of food resources and specific habitat structures. Although resources are

mostly important in defining the suitability of a habitat, a species’ response to environ-

mental changes may be determined by a variety of other traits, e.g. dispersal ability,

demographic rates, competitive abilities, predator avoidance etc. Assessing the response of


123

communities to environmental changes requires therefore a functional classification system

that goes beyond the resource centred guild approach (Barnett et al. 2007) using existing

functional relationships between habitats and the requirements of species with particular

life histories (McGill et al. 2006). This approach allows for the explicit consideration of

life history traits, which provides a process based understanding linking species to their

habitat.

Identification of ‘‘core traits’’

Clearly, the definition of core traits for EGs is difficult to make due to the high variability

in behaviour, foraging strategies, and morphology of animals. However, developing a core

list of traits for animal functional types is essential for generalizations and may greatly

improve the application of any kind of classification system in animal ecology. Similar to

approaches in plant ecology, a classification system must focus on the central life traits of

species. For animals, these are both, (i) traits describing species’ dependency on their

habitat as well as (ii) life history traits that are related to the processes of birth, survival and

movement. A good starting point for such a classification system may be systems com-

parable to the r-, K-strategies, the C–S–R system in plant ecology, trophic levels etc.,

which allow accounting for species’ ability to adapt to changes. However, as has been

demonstrated, so far applied approaches exposed limitations and therefore new classifi-

cation schemes should try to overcome revealed problems.

Optimization of trait selection

To keep the system as simple as possible, the most important traits should be identified and

if necessary clustered into hierarchies according to the suggestions of Lavorel et al. (1997)

for plant species groups.

Assessment of ‘‘soft traits’’

As substitute for hardly measurable traits, soft traits should be identified to allow for

feasibility of investigation. For example, body size within a taxon could be used as a

substitution for home range size (Haskell et al. 2002) and dispersal ability (Sutherland et al.

2000). For example, in mammal species of different feeding types the dispersal distance

increases with body size and allometric scaling equations can be used as a suitable soft trait

(Sutherland et al. 2000). Also other body related soft traits such as wing length and wing

shape in birds were identified as suitable substitutes for the dispersal ability of birds

(Bohning-Gaese et al. 2006; Dawideit et al. 2009).

Rigorous, objective testing of delineated groups

This is needed to approve the validity of the groups for the respective study system. This

could lead to an aggregation of the so far often exclusively applied approaches of a priori

and a posteriori methodologies in delineating groups. Moreover, experimental testing of

groupings should be carried out where possible.

Although the identification of functional groups in animal ecology is unquestionable

more complex than in plant ecology, we are convinced that improved classification systems

will provide a crucial step in understanding and predicting community changes under the


123

current threats of global changes. Given the current rates of worldwide species losses we

can no longer afford to focus on single species only. Instead, we urgently need a more

generalizing approach that enables us to link easy measurable traits of larger sets of species

with likely community responses to expected environmental changes. Only on this basis

we will be able to develop long-term strategies to successfully manage and conserve

biodiversity.

Acknowledgments We are grateful for comments on an earlier version of the manuscript by Eva Ross-manith, Stuart Pimm and an anonymous reviewer. The work was funded by the German Ministry ofEducation and Research in the framework of BIOTA Southern Africa (01LC0624I).

References

Adamik P, Kornan M, Vojtek J (2003) The effect of habitat structure on guild patterns and the foragingstrategies of insectivorous birds in forests. Biologia 58:275–286

Adams DC (2007) Organization of Plethodon salamander communities: guild-based community assembly.Ecology 88:1292–1299

Barbaro L, van Halder I (2009) Linking bird, carabid beetle and butterfly life-history traits to habitatfragmentation in mosaic landscapes. Ecography 32:321–333

Barlow J, Peres CA (2004) Avifaunal responses to single and recurrent wildfires in Amazonian forests. EcolAppl 14:1358–1373

Barnett AJ, Finlay K, Beisner BE (2007) Functional diversity of crustacean zooplankton communities:towards a trait-based classification. Freshw Biol 52:796–813

Blackburn TM, Petchey OL, Cassey P, Gaston KJ (2005) Functional diversity of mammalian predators andextinction in island birds. Ecology 86:2916–2923

Blaum N, Rossmanith E, Schwager M, Jeltsch F (2007) Responses of mammalian carnivores to land use inarid savanna rangelands. Basic Appl Ecol 8:552–564

Blaum N, Seymour CL, Rossmanith E, Schwager M, Jeltsch F (2009) Changes in arthropod diversity along aland use driven gradient of shrub cover in the southern Kalahari: identification of suitable indicators.Biodivers Conserv 18:1187–1199

Blondel J (2003) Guilds or functional groups: does it matter? Oikos 100:223–231Bohning-Gaese K, Caprano T, van Ewijk K, Veith M (2006) Range size: disentangling current traits and

phylogenetic and biogeographic factors. Am Nat 167(4):555–567Box EO (1996) Plant functional types and climate at the global scale. J Veg Sci 7:309–320Bremner J, Rogers SI, Frid CLJ (2003) Assessing functional diversity in marine benthic ecosystems: a

comparison of approaches. Mar Ecol Prog Ser 254:11–25Brodie JF, Helmy OE, Brockelman WY, Maron JL (2009) Functional differences within a guild of tropical

mammalian frugivores. Ecology 90:688–698Brown JH, Davidson DW, Reichmann OJ (1979) An experimental study of competition between seed-eating

desert rodents and ants. Am Zool 19:1129–1143Caro TM, O’Doherty G (1999) On the use of surrogate species in conservation biology. Conserv Biol

13:805–814Chalcraft DR, Resetarits WJ (2003) Mapping functional similarity of predators on the basis of trait simi-

larities. Am Nat 162:390–402Cornelissen JHC, Lavorel S, Garnier E, Diaz S, Buchmann N, Gurvich DE, Reich PB, ter Steege H, Morgan

HD, van der Heijden MGA, Pausas JG, Poorter H (2003) A handbook of protocols for standardised andeasy measurement of plant functional traits worldwide. Aust J Bot 51:335–380

Cousins SAO, Lindborg R (2004) Assessing changes in plant distribution patterns—indicator species versusplant functional types. Ecol Indic 4:17–27

Croonquist MJ, Brooks RP (1991) Use of avian and mammalian guilds as indicators of cumulative impactsin riparian wetland areas. Environ Manag 15:701–714

Cummins KW (1974) Structure and function of stream ecosystems. Bioscience 24:631–641Cushman SA, McKelvey KS, Flather CH, McGarigal K (2008) Do forest community types provide a

sufficient basis to evaluate biological diversity? Front Ecol Environ 6:13–17Dawideit BA, Phillimore AB, Laube I, Leisler B, Bohning-Gaese K (2009) Ecomorphological predictors of

natal dispersal distances in birds. J Anim Ecol 78(2):388–395


123

Degraaf RM, Chadwick NL (1984) Habitat classification—a comparison using avian species and guilds.Environ Manag 8:511–518

Diaz S, Cabido M (1997) Plant functional types and ecosystem function in relation to global change. J VegSci 8:463–474

Diaz S, Cabido M (2001) Vive la difference: plant functional diversity matters to ecosystem processes.Trends Ecol Evol 16:646–655

Diaz S, Hodgson JG, Thompson K, Cabido M, Cornelissen JHC, Jalili A, Montserrat-Marti G, Grime JP,Zarrinkamar F, Asri Y, Band SR, Basconcelo S, Castro-Diez P, Funes G, Hamzehee B, Khoshnevi M,Perez-Harguindeguy N, Perez-Rontome MC, Shirvany FA, Vendramini F, Yazdani S, Abbas-Azimi R,Bogaard A, Boustani S, Charles M, Dehghan M, Torres-Espuny L, Falczuk V, Guerrero-Campo J,Hynd A, Jones G, Kowsary E, Kazemi-Saeed F, Maestro-Martinez M, Romo-Diez A, Shaw S, SiavashB, Villar-Salvador P, Zak MR (2004) The plant traits that drive ecosystems: evidence from threecontinents. J Veg Sci 15:295–304

Du Toit JT, Cumming DHM (1999) Functional significance of ungulate diversity in African savannas andthe ecological implications of the spread of pastoralism. Biodivers Conserv 8:1643–1661

Dumay O, Tari PS, Tomasini JA, Mouillot D (2004) Functional groups of lagoon fish species in LanguedocRoussillon, southern France. J Fish Biol 64:970–983

Elliott M, Whitfield AK, Potter IC, Blaber SJM, Cyrus DP, Nordlie FG, Harrison TD (2007) The guildapproach to categorizing estuarine fish assemblages: a global review. Fish Fish 8:241–268

Ewers RM, Didham RK (2006) Confounding factors in the detection of species responses to habitat frag-mentation. Biol Rev 81:117–142

Fritz H, Duncan P, Gordon IJ, Illius AW (2002) Megaherbivores influence trophic guilds structure inAfrican ungulate communities. Oecologia 131:620–625

Gitay H, Noble IR (1997) What are functional types and how should we seek them? In: Smith TM, ShugartHH, Woodward FI (eds) Plant functional types- their relevance to ecosystem properties and globalchange. University Press, Cambridge

Grime JP (1979) Plant strategies and vegetation processes. Wiley, New YorkHaskell JP, Ritchie ME, Olff H (2002) Fractal geometry predicts varying body size scaling relationships for

mammal and bird home ranges. Nature 418:527–530Hawkins CP, MacMahon JA (1989) Guilds: the multiple meanings of a concept. Annu Rev Entomol

34:423–451Hooper DU, Solan M, Symstad A, Diaz S, Gessner MO, Buchmann N, Degrange V, Grime P, Hulot F,

Mermillod-Blondin F, Roy J, Spehn E, van Peear L (2002) Species diversity, functional diversity andecosystem functioning. In: Loreau M, Naeem S, Inchausti P (eds) Biodiversity and ecosystem func-tioning—synthesis and perspectives, 1st edn. University Press, Oxford

Jaksic FM (1981) Abuse and misuse of the term guild in ecological-studies. Oikos 37:397–400Jaksic FM, Feinsinger P, Jimenez JE (1993) A long-term study on the dynamics of guild structure among

predatory vertebrates at a semiarid Neotropical site. Oikos 67:87–96Jaksic FM, Feinsinger P, Jimenez JE (1996) Ecological redundancy and long-term dynamics of vertebrate

predators in semiarid Chile. Conserv Biol 10:252–262Johnson LB, Breneman DH, Richards C (2003) Macroinvertebrate community structure and function

associated with large wood in low gradient streams. River Res Appl 19:199–218Kissling WD, Field R, Bohning-Gaese K (2008) Spatial patterns of woody plant and bird diversity: func-

tional relationships or environmental effects? Glob Ecol Biogeogr 17:327–339Klingbeil BT, Willig MR (2009) Guild-specific responses of bats to landscape composition and configu-

ration in fragmented Amazonian rainforest. J Appl Ecol 46:203–213Kurosawa R (2009) Disturbance-induced bird diversity in early successional habitats in the humid temperate

region of northern Japan. Ecol Res 24:687–696Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from

plant traits: revisiting the Holy Grail. Funct Ecol 16:545–556Lavorel S, McIntyre S, Landsberg J, Forbes TDA (1997) Plant functional classifications: from general

groups to specific groups based on response to disturbance. Trends Ecol Evol 12:474–478Lavorel S, Diaz S, Cornelissen JHC, Garnier E, Harrison SP, McIntyre S, Pausas JG, Perez-Harguindeguy

N, Roumet C, Urcelay C (2007) Plant functional types: are we getting any closer to the Holy Grail? In:Canadell JG, Pataki D, Pitelka L (eds) Terrestrial ecosystems in a changing world, 1st edn. Springer-Verlag, Berlin

MacArthur RH, Wilson EO (1967) Theory of Island Biogeography. Princeton University Press, New JerseyMac Nally R (1994) Habitat-specific guild structure of forest birds in south-eastern Australia—a regional-

scale perspective. J Anim Ecol 63:988–1001


123

Mac Nally R, Fleishman E, Thomson JR, Dobkin DS (2008) Use of guilds for modelling avian responses tovegetation in the Intermountain West (USA). Glob Ecol Biogeogr 17:758–769

MacMahon JA (1976) Species and guild similarity of North American desert mammal faunas: a functionalanalysis of communities. In: Goodall DW (ed) Evolution of desert biota, 1st edn. University of TexasPress, Austin

McGill BJ, Enquist BJ, Weiher E, Westoby M (2006) Rebuilding community ecology from functional traits.Trends Ecol Evolut 21:178–185

Miller JR, Cale P (2000) Behavioral mechanisms and habitat use by birds in a fragmented agriculturallandscape. Ecol Appl 10:1732–1748

Montalvo J, Casado MA, Levassor C, Pineda FD (1991) Adaptation of ecological-systems—compositionalpatterns of species and morphological and functional traits. J Veg Sci 2:655–666

O’Connell TJ, Jackson LE, Brooks RP (2000) Bird guilds as indicators of ecological condition in the centralAppalachians. Ecol Appl 10:1706–1721

Parker KC, Parker AJ, Vale TR (2001) Vertebrate feeding guilds in California’s Sierra Nevada: relations toenvironmental condition and change in spatial scale. Ann Assoc Am Geogr 91:245–262

Philpott SM, Soong O, Lowenstein JH, Pulido AL, Lopez DT, Flynn DFB, DeClerck F (2009) Functionalrichness and ecosystem services: bird predation on arthropods in tropical agroecosystems. Ecol Appl19:1858–1867

Pianka ER (1970) On r- and K-selection. Am Nat 104:592–597Pianka ER (1980) Guild structure in desert lizards. Oikos 35:194–201Pillar VD (1999) On the identification of optimal plant functional types. J Veg Sci 10:631–640Poschlod P, Kleyer M, Jackel AK, Dannemann A, Tackenberg O (2003) BIOPOP—a data base of plant traits

and internet application for nature conservation. Folia Geobot 38:263–271Raunkiaer C (1934) The life-forms of plants and statistical plant geography. Oxford University Press,

OxfordResetarits WJ, Chalcraft DR (2007) Functional diversity within a morphologically conservative genus of

predators: implications for functional equivalence and redundancy in ecological communities. FunctEcol 21:793–804

Reynaud PA, Thioulouse J (2000) Identification of birds as biological markers along a Neotropical urban-rural gradient (Cayenne, French Guiana), using co-inertia analysis. J Environ Manag 59:121–140

Roberts TH (1987) Construction of Guilds for Habitat Assessment. Environ Manag 11:473–477Rodewald AD, Yahner RH (2001) Influence of landscape composition on avian community structure and

associated mechanisms. Ecology 82:3493–3504Root RB (1967) Niche exploitation pattern of blue-gray gnatcatcher. Ecol Monogr 37:317–334Schulze CH, Waltert M, Kessler PJA, Pitopang R, Shahabuddin, Veddeler D, Muhlenberg M, Gradstein SR,

Leuschner C, Steffan-Dewenter I, Tscharntke T (2004) Biodiversity indicator groups of tropical land-use systems: comparing plants, birds, and insects. Ecol Appl 14:1321–1333

Simberloff D, Dayan T (1991) The guild concept and the structure of ecological communities. Annu RevEcol Syst 22:115–143

Steffan-Dewenter I, Tscharntke T (2000) Butterfly community structure in fragmented habitats. Ecol Lett3:449–456

Summerville KS, Conoan CJ, Steichen RM (2006) Species traits as predictors of lepidopteran compositionin restored and remnant tallgrass prairies. Ecol Appl 16:891–900

Sutherland GD, Harestad AS, Price K, Lertzman KP (2000) Scaling of natal dispersal distances in terrestrialbirds and mammals. Conserv Ecol 4:16

Szaro RC (1986) Guild management- an evaluation of avian guilds as a predictive tool. Environ Manag10:681–688

Terborgh J, Robinson S (1986) Guilds and their utility in ecology. In: Kikkawa J, Anderson DJ (eds)Community ecology: pattern and process, 1st edn. Blackwell Scientific Publications, Palo Alto

Thiollay JM (1999) Responses of an avian community to rain forest degradation. Biodivers Conserv8:513–534

Tilman D, Lehman CL, Thomson KT (1997) Plant diversity and ecosystem productivity: theoretical con-siderations. Proc Natl Acad Sci USA 94:1857–1861

Todd BD, Andrews KM (2008) Response of a reptile guild to forest harvesting. Conserv Biol 22:753–761Verner J (1984) The guild concept applied to management of bird populations. Environ Manag 8:1–13Violle C, Navas ML, Vile D, Kazakou E, Fortunel C, Hummel I, Garnier E (2007) Let the concept of trait be

functional!. Oikos 116:882–892Voigt W, Perner J, Davis AJ, Eggers T, Schumacher J, Bahrmann R, Fabian B, Heinrich W, Kohler G,

Lichter D, Marstaller R, Sander FW (2003) Trophic levels are differentially sensitive to climate.Ecology 84:2444–2453


123

Weiher E, van der Werf A, Thompson K, Roderick M, Garnier E, Eriksson O (1999) Challenging Theo-phrastus: a common core list of plant traits for functional ecology. J Veg Sci 10:609–620

Westphal C, Steffan-Dewenter I, Tscharntke T (2006) Bumblebees experience landscapes at different spatialscales: possible implications for coexistence. Oecologia 149:289–300

Wiegand T, Dean WRJ, Milton SJ (1997) Simulated plant population responses to small-scale disturbancesin semi-arid shrublands. J Veg Sci 8:163–176

Woodward FI, Cramer W (1996) Plant functional types and climatic changes: introduction. J Veg Sci7:306–308


123

Documents

How functional is functional? Ecological groupings … · REVIEW PAPER How functional is functional? Ecological groupings in terrestrial animal ecology: towards an animal functional