Testing functional groups for the monitoring of biodiversity and habitat quality

Authors and Affiliations: 

Rocco Labadessa1, 2, Graziana Antolino3, Mirella Benedetta Campochiaro1,3, Luigi Forte2, 3, Paola Mairota1


1 Department of Agro-Environmental and Territorial Sciences, University of Bari, Via Orabona 4, 70125 Bari

2 Department of Biology, University of Bari, Via Orabona 4, 70125 Bari

3 Botanic Garden and Museum of the University of Bari, Via Orabona 4, 70125 Bari


Species richness and diversity indices are increasingly being questioned in connection to their role as biodiversity surrogates, while functional groups are gaining momentum in supplying synoptic information on community and habitat structure. An understanding of the basic roles that functional groups can play in ecosystem properties can help to inform the development of more valuable monitoring strategies. We explored the usefulness of several functional groups belonging to four taxonomic groups (plants, grasshoppers, butterflies and passerine birds) to provide insights on conservation status and biodiversity of protected semi-natural grasslands of “Murgia Alta” Natura 2000 site (southern Italy). This research fits in the comparative habitat modelling effort of the BIO_SOS project (FP7-SPA-2010-1-263435).

Thirty habitat patches, each containing one 80m x 5m linear transect, were randomly selected as representative of different degrees of habitat fragmentation and landscape matrix type. Values of species abundance were recorded along the transects, from March to September 2012, also recording estimates of environmental variables (slope, rock abundance, grass height, grass cover and grazing intensity). Species were ranked in several groups, according to life form, chorology, habitat specialization and role within principal vegetation syntaxa. Species richness and abundance were then estimated for each functional group.

In order to get an insight on the existence of recognizable vegetation groups, the thirty sample sites were classified by hierarchical cluster analysis, both using plant species and plant functional groups. While species did not provide a clear classification of the sampled communities, the use of functional groups seemed to give more straightforward and realistic information. Principal component analysis (PCA) was used to provide information on the major drivers of community assemblages, and enabled identification of main plant community clusters. The associations among plant communities, animal functional groups and environmental variables were then verified by means of canonical correspondence analysis (CCoA).

As a result, a set of functional groups belonging to different taxonomic groups was associated with the better preserved plant communities. On the other hand, changes in human pressure could be easily detected by observing those groups associated with nitrophilic and disturbed vegetation. Testing the response of a multiple set of indicators is also useful for determining the most cost-efficient indicator group and for the assessment of more straightforward sampling strategies. These results show the potential of functional groups for biodiversity and ecosystem monitoring, as valuable indicators of ecosystem change and for the evaluation of the conservation status of communities.