Plant Ecology

, Volume 192, Issue 2, pp 161–167

In search of a functional flora—towards a greater integration of ecology and taxonomy

Authors

    • Royal Botanic Garden Edinburgh
  • Jan Dick
    • Centre for Ecology and Hydrology
  • Martin R. Pullan
    • Royal Botanic Garden Edinburgh
  • Sabina G. Knees
    • Royal Botanic Garden Edinburgh
  • Anthony G. Miller
    • Royal Botanic Garden Edinburgh
  • Sophie Neale
    • Royal Botanic Garden Edinburgh
  • Mark F. Watson
    • Royal Botanic Garden Edinburgh
Article

DOI: 10.1007/s11258-007-9304-y

Cite this article as:
Pendry, C.A., Dick, J., Pullan, M.R. et al. Plant Ecol (2007) 192: 161. doi:10.1007/s11258-007-9304-y

Abstract

Large-scale biodiversity informatics projects will not properly address the needs of one important potential user group. Ecologists do not have ready access to datasets which allow them to assign plant species to functional types. We believe that information technology has developed sufficiently to allow taxonomists and ecologists to work together to address this need and develop specimen databases to combine taxonomic data with ecological and ecophysiological information so that this information will be assigned to the correct taxon in the future. Digital images provide a rapid and economical method of vouchering specimen data, reducing the need to store physical vouchers in herbaria.

Keywords

BioinformaticsTaxonomyDatabasesFunctional ecologyFunctional types

Introduction

Considerable time, effort and money have been spent in recent years on improving access to biological collection data both at the institutional level (digitisation of museum and herbarium collections and access to this information over the web) and at the international level (e.g. GBIF, the Global Biodiversity Information Facility and BioCASE, the Biological Access Service for Europe). Much of the drive for this increased access has come from taxonomists who have seen it as a way of opening up these enormous historical datasets to analysis by other disciplines, thereby enhancing the ongoing relevance of their collections at a time when financial support for Taxonomy comes under ever increasing pressure. In many cases, however, rather little attention has been paid to exactly who will use these data and what will be done with it (Neale and Pullan 2005; Neale et al. 2005). We believe that another, complementary approach is required, in which biodiversity informatics projects carefully consider the needs of their users and work with those users to develop more focused strategies to address these needs.

Rationale

Functional ecology

Ecologists have always been one of the most important user groups of taxonomic outputs and expertise, but the relationship between the disciplines has changed as they have diverged. Taxonomy has become increasingly interested in the phylogenetic history of groups and their distributions, while ecology has developed from a descriptive science (exemplified by the collection of species lists in the phytosociological approach) into a predictive functional science which is less concerned with the presence or absence of particular organisms and more interested in the physical properties of organisms and communities. For example, Grime (2002) recently noted the value of creating trait-based functional groups which allow a mechanistic understanding of ecosystems. The model of examining ecosystems by understanding the functional attributes of the assembly of species is well-established (Tilman 1988; Diaz and Cabido 1997; Gitay and Noble 1997; Lavorel et al. 1997). Rather than focusing on the species per se this approach attempts to understand the full inter-relationship (function) of a species within the landscape (Petchey and Gaston 2006) by assigning the species to a functional group on the basis of its physical or ecophysiological characteristics. No single functional classification is applicable to all situations, and there is a multidimensional continuum of possible functional classifications, with the functional groups defined dependent on the questions and scale addressed by the study. It is therefore necessary to store a wide array of data which are used to assign taxa to functional types, ranging from simple physical features such as leaf area or propagule mass to complex ecophysiological measurements such as stomatal conductance or photosynthetic charateristics. Table 1 gives a preliminary sample of traits which were suggested to be useful at the EU-funded workshop ‘Functional groupings of tropical trees’ held in Edinburgh in 2001. The list is therefore biased towards the interests of forest ecologists and should be considered as a starting point for discussions.
Table 1

Preliminary list of suggested physical and ecophysiological measurements used to assign taxa to functional groups arising from EU funded workshop ‘Functional groupings of tropical trees’ – Edinburgh, 10–13 Dec 2001

Structure

Trait

Unit

Flower

Shape

C

Length

m

Width

m

Mass

g

Pollen

Pollen dispersability (mean dispersal distance)

m

Pollination success

%

Fruit

Shape

m

Length

m

Width

m

Mass

g

Seed

Shape

m

Length

m

Width

m

Mass

g

Type

C

Seed production (fecundity)

seeds/tree/year

Dispersal distance

m

Dispersal syndrome

C

Soil seed bank (type, size)

C, num/m2/m (depth)

Dormancy

year

Tolerance to dessication

C, %

Germination

Rate

%/day

Triggers

C

Type

C

Reproduction

Seedling mortality

%

Length of reproduction event

year

Resprouting (ability & type)

C, count

Species

Periodicity of flower/fruit production

event/year, C

Size at maturity (1st reproduction)

m

Breeding system

C

Pollination type

C

Dispersal mode

C

Leaf

LAI (Leaf Area index)

NU

Respiration response to temperature

C

LAR (Leaf Area Ratio)

NU

Leaf lifespan

year

Leaf area

m2

Leaf thickness

m

Minimum leaf water potential (leaf water content)

%, g/g, Pa

Photosynthetic response (Amax)

Mol/m2/s

Respiration rate

Mol/m2/s, g/g/s

SLA (Specific Leaf Area)

m2/g

Stomatal conductance

Mol/m2/s

Transpiration rate

Mol/m2/s, g/m2/s

WUE (Water Use Efficiency) or Delta 13C

dry mass gain/unit water transpired

Leaf quality (C/N, N contents, 15N)

ratios, g/g

Fv/Fm (photoinhibition)

NU

Shoot

Seedling architecture

C

Crown depth

m

Flammability of residues

C

Reiteration

C

Leaf phenology

C

Resistance to embolism

%

Trunk

Wood density

g/cm3

Bark thickness

m

Root

Mycorrhizae

%spp/m, C

N-fixing (symbioses)

C, g/g

Root phenology

C, g/year

Rooting depth (seedling in particular)

m

Plant

Lifespan

year

Maximum size/height

m

Mortality

%/year

Allocation

%, g/g

Plant architecture (e.g. slope DBH to Height curve)

NU

Growth rate (max or 95%)

%, m/year, g/year

Growth response to CO2

%, m/year, g/year

Growth response to light

%, m/year, g/year

Growth response to nutrients

%, m/year, g/year

Growth response to water

%, m/year, g/year

Abiotic stress tolerance (temperature, flooding, light, low nutrients)

NU

Drought tolerance

NU

Resistance to herbivory/defense allocation (e.g. leaf palatability, spines)

%

Resistance to pathogens

%, C

Species

Distribution area

C

Plasticity

%

Phylogeny (ancestry)

genetic distance, C

Genetic diversity

indices, C

Specificity of mutualism (e.g. specialised pollination/dispersal, myrmecophily)

C

C, category; NU, no unit

The approach of grouping species by their function within the ecosystem has been used to investigate both fundamental ecological issues (Whitfield 2006) and more applied ecological questions including climate change and habitat restoration (Boutin and Keddy 1993; Skarpe 1996; Brooks et al. 1997; Smith et al. 1997; Diaz et al. 2004). For some aspects of ecosystem performance it is not the diversity of species which matters, but the diversity of functional types. Certain ecosystem models require information not (only) about the presence of species, but (also) about their functionality, and such information may be difficult to locate, particularly in botanically less well-known areas such as the wet tropics (Picard and Franc 2003; Gourlet-Fleury et al. 2005). Although functional ecologists are interested not in what an organism is called but what it can do, without using names it is impossible to organise and communicate this information in a meaningful and reproducible way. We therefore advocate reinforcing the links between Functional Ecology and Taxonomy, to their mutual benefit.

Floras

Floras are the primary data source about the plants of an area, and may contain not only keys and descriptions, but also information on the distribution and ecology of those plants. As primary data sources, Floras must address many audiences and are the basic tool for all who need to identify plants, from ecologists to conservationists, foresters and horticulturists. Traditional Floras may not be easy to use and their format is inflexible, so there have been attempts to modernise them by using multi-access keys, computer aided identification, multimedia formats, but in the end, all these products supply the same sort of information.

The traditional approach to Flora writing yields a static paper output with keys, descriptions, and in more comprehensive treatments, lists of specimens seen and literature consulted. While the annotations to specimens are permanently preserved, the information which was used to generate these taxonomic decisions is held in character tables that are rarely made publicly available. Therefore when the taxonomy of a group is re-evaluated, even if a list of determined specimens is available the original character identification and selection process is opaque and measurement must be carried out from first principles. These traditional Floras can only partially address the needs of ecologists taking a functional approach to understanding ecosystem processes. Space limitations restrict the amount of data which can be presented, so it is not possible to publish a complete matrix of all characteristics for all species, but only the information needed to differentiate among species. A complete data matrix is a necessary step when identifying trait-based functional groups.
https://static-content.springer.com/image/art%3A10.1007%2Fs11258-007-9304-y/MediaObjects/11258_2007_9304_Fig1_HTML.gif
Fig. 1

Diagrammatic representation of data management approach advocated to improve integration of taxonomy and ecology

An integrated approach

Databasing

Taxonomists are increasingly using information technology to create a more flexible output, with web access to preliminary accounts which are in the process of being updated, and databases storing far more information than could ever be physically published. It is now no longer necessary to wait for the final piece of data to be collected before the account is made available and users given access to this information such as is the case with the ‘Flora of China’ and the other floristic projects found at the eFloras site (www.efloras.org). However, whilst most floristic database systems operate at the taxon level, this is problematic for a number of reasons:
  • the underlying data is captured at the specimen level not the taxon level;

  • the taxon level assertions are in reality synthetic constructions from the underlying specimen level data;

  • storing just the taxon level information results in the loss of the raw data used to create the syntheses and preclude re-examination or re-working of the product; and

  • since the raw data is missing it is very difficult to make cross comparisons to other taxon level data without making some major assumptions regarding the congruence of the underlying taxon concepts.

These problems largely arise, because the information systems are not seen as an integrated part of the taxonomic process. We advocate the use of databases which encourage the gathering and storage of data at the specimen level and which can generate taxon level syntheses of the underlying data. These synthetic views can then be regenerated at any time to accommodate changes and additions to the underlying specimen level data.

Functional types can be thought of as analogous to taxa, in that they are both ways of arranging biodiversity. However, while assignment to a particular functional type is made to answer a specific question, taxonomic classifications act as a multi-purpose method of storing data for addressing numerous questions. When relating functional types to taxa we are in fact looking at mapping between two different classification systems. There are problems when both classification schemes develop independently – unless the mappings between the classifications are rigorously maintained, inaccuracies will develop progressively as taxon names inevitably change due to either refinements in taxonomic concepts or for nomenclatural reasons.

Specimens are the link between functional types and taxa. The same relationship between identification and classification exists in functional types as exists in taxa since one set of the physical characteristics of a specimen is used to assign the specimen to a taxon whilst another more or less different set determines its functional type. The ideal situation is therefore to collect specimen level physical data to assign specimens to taxa and within the same system to categorise these taxa as functional types (Fig. 1). Thus, data are collected and stored at the specimen level, but communicated at the taxon level. Within any taxon, there may be considerable physical variation among individuals, so it is important that data on all physical attributes are collected from numerous individuals from across the range of the taxon. Concentrating the management of functional data at the specimen level greatly simplifies the issues related to storing data for use in classifying functional types. Databases which operate at the specimen rather than the taxon level can accommodate extra fields in accordance with type of functional data required. Storing data at the specimen level is also amenable to taxonomic revisions as required and is a more neutral, and therefore a more appropriate method of storing information about plant diversity. Although much of the data used to assign taxa to functional groups could be collected by the non-specialist, taxonomists clearly lack the time and expertise to collect the complete spectrum of data used in functional studies. Large data-sets are currently collected by ecologists and physiologists in the course of their research, but because of its volume, much of this data will never be published and therefore is not integrated with other data. We suggest that taxonomists should manage databases containing these specimen-level data, ensuring that the data are assigned to the correct taxon and will continue to be so assigned in the future. Ideally, the ecophysiological data should reside in a single database which manages data for a country level floristic project, and this is one of the aims of the Flora of Nepal Project (www.floraofnepal.org). Maintenance of web-accessible databases at this scale should help ensure that there is no unnecessary duplication of effort in collection of data and that these data are easily accessible by non-taxonomists.

The large number of physical and ecophysiological measurements that are used to categorise species according to functional types and the need to sample numerous individuals will create enormous quantities of data. These vast data-sets are analogous to those which underlie molecular systematics, with GenBank being the sole repository for molecular data. However there is no need to create a parallel system for functional data since in GBIF and BioCASE there are already systems which can give access to diverse data held in different databases.

Vouchering

Problems with matching functional types to taxa may occur because of incorrect identification of the individual sampled and this raises the important issue of vouchering data to ensure that the functional type assigned to a taxon can be re-examined. For example, the Ecological Database of the British Isles (http://www.york.ac.uk/res/ecoflora/cfm/ecofl/) hosts ecological data from bibliographic sources on over 1,770 species of higher plants that occur in the British Isles, but there is no process by which incorrect identification of species could be addressed. At present, we are aware of no study which stores voucher specimens from the individual plants used to collect traits for functional type analysis. Herbaria can be considered as vouchering systems for taxonomic studies and they are coming under increasing pressure due to the need to maintain physical vouchers for molecular data. Cost and space constraints preclude the storage of voucher specimens for functional data, but another possibility also exists. Digital photography could provide a simple and inexpensive way to preserve sufficient information for most organisms to be reliably identified by a specialist, particularly if the specialist has prescribed what structures are most critical to identifications and how they must be photographed. Indeed, in other disciplines, such as ornithology a photograph is already considered adequate as a voucher specimen. Only in a minority of cases would a photograph be insufficient and a physical specimen is required. The images should be stored within the database which hosts the taxonomic and ecophysiological data. A potential way forward can be seen in MorphBank (www.morphbank.net) which may provide a model system for the storage of images linked to taxonomic data.

Conclusions

We believe that the collection and linking of data from diverse sources in the way which we describe could greatly strengthen both Ecology and Taxonomy. Ecology would benefit from the increase in the range and sophistication of data available and Taxonomy would reinforce its central role in biodiversity studies. There would be benefits in many areas including conservation. As habitats alter due to climate change, or land use different species within them will respond in different ways. Including the functional type approach within conservation assessments will permit a more accurate prediction of how a species will respond to its changing environment and whether threats to it will increase or diminish in the future. In the face of the global erosion of biodiversity it is essential that identities of taxa are integral to the discussions of how habitats will change, and this is one way to keep the focus on the species themselves. Information technology has now progressed to the point where full integration of taxonomic and ecological data is possible. If the approach which we outline is to succeed it will require additional investment in resources, and we hope that the ideas presented here will stimulate discussion among ecologists and taxonomists about how to work with national and international funding agencies to develop this integrated approach to tackling some global issues.

Acknowledgements

We wish to dedicate this paper to the memory of John Proctor, an ecologist with a keen appreciation of Toxonomy, and we hope that he would approve of the ideas expressed here. We would like to thank the anonymous reviewers whose comments were so useful in preparing the final version of this article.

Copyright information

© Springer Science+Business Media B.V. 2007