Mapping earthworm communities in Europe
Introduction
Monitoring soil biodiversity has been addressed by recent EU research programs (e.g. Bispo et al., 2009, Lemanceau, 2011) and national initiatives (e.g. RMQS and BiSQ: Gardi et al., 2009, Pulleman et al., 2012; Edaphobase: Burkhardt et al., 2014; and the UK Soil Indicators Consortium: Ritz et al., 2009). For instance, in the EU project EcoFINDERS a suite of indicators on soil biodiversity attributes, including microbia (bacteria and fungi), microfauna (protozoans and nematodes) and mesofauna (enchytraeids and microarthropods), was tested at 85 sites along a European transect (Stone et al., 2016). The aim was to demonstrate the feasibility of such an endeavour at a continental scale, and to collate the first set of harmonized earthworm data and maps and hence, allowing soil biodiversity to be upgraded from a theoretical to a practical issue on the environmental policy agenda at European and national levels.
A synthesis of existing data is not only timely, but also a more efficient use of limited resources for land management and decision making, than filling data gaps with additional costly surveys and monitoring. Such a database could also become a valuable source of information for awareness raising and environmental policy making, and possibly for some academic objectives, despite the fact that data were obtained from different countries, generated by different researchers using different sampling and identification methods, and with different project objectives.
Earthworms (Lumbricidae) are surprisingly under-recorded taxa (Carpenter et al., 2012) and were excluded from the aforementioned EcoFINDERS transect for practical and logistic reasons (Stone et al., 2016; B.S. Griffiths et al., in progress). However, macrofaunal groups are known to strongly reflect their habitats according to the niche modelling principles of Hutchinson (1957) and therefore, their geographical distribution can potentially be predicted from environmental data. For this reason, we collected and harmonized existing earthworm community data from several European countries and validated this information with environmental and climatic variables, generating the first continuous biodiversity map of earthworms.
The production of this first earthworm map faced a number of challenges:
- 1.
The first challenge was to track and to source earthworm data, because there is no single public facility where such data can be accessed. Some progress has been achieved recently for different national data sets on soil biodiversity via the Global Biodiversity Information Facility (www.GBIF.org), the DRYAD Digital Repository (e.g., datadryad.org/resource/doi:10.5061/dryad.g7046), the Drilobase and Macrofauna database (earthworms.info and macrofauna.org) and the NBN Gateway (data.nbn.org.uk/Datasets). In addition, much of the earthworm data are often published in grey literature, such as project reports (e.g. Römbke et al., 2000, Römbke et al., 2002, Schmidt et al., 2011, Rutgers and Dirven-Van Breemen, 2012 and references therein). Frequently, data are presented in appendices or dissertations and can only be accessed by contacting the source holders directly. We received data from earthworm inventories through personal contacts with professionals and researchers in different European countries, under the restriction to use the resulting database solely for producing these maps.
- 2.
The second challenge was to compile sufficient relevant and reliable environmental information to enable meaningful analyses. We sought to link earthworm data to environmental variables in order to produce models for predicting their habitat–response relationships and hence, the distribution of earthworms according to independent niche modelling (sensu Hutchinson, 1957).
- 3.
The third challenge was to harmonize the earthworm and environment variables as the collected information differed in relation to site selection, sampling design, collection, extraction, storage, the use of identification keys, and methods for soil analysis.
Belonging to the macrofauna, earthworms are among the few soil-dwelling organisms which are large enough to be seen by the naked eye. Earthworms are an important food source for small mammals (e.g. the mole: Talpa europaea) and birds (e.g. the black-tailed godwit Limosa limosa). Importantly, fertile soils in temperate regions are greatly dependent on the dwelling/burrowing action of earthworms and for this reason they are considered important ecosystem engineers and used as valuable indicators for soil quality (Lavelle et al., 1997, Didden, 2003, Cluzeau et al., 2012, Van Groenigen et al., 2014). Although some earthworms are invasive species in northern America (e.g. Bohlen et al., 2004), in Europe Lumbricidae are native and charismatic for the general public, farmers and academics (Darwin, 1881).
Earthworms have been traditionally classified into three functional groups, representing different traits in the soil system (Bouché, 1977, Edwards and Bohlen, 1996), i.e. dwellers in the mineral layer (endogeics), dwellers in the litter layer (epigeics) and vertical burrowers (anecics). The abundance of earthworms is strongly affected by land use (Spurgeon et al., 2013). For example, the total abundance of earthworms in nutrient-rich grasslands under a temperate climate can easily differ one order of magnitude, as it has been reported to be as low as 138 individual m−2 (Sechi et al., 2015) and as high as 1333 individuals m−2 (Cluzeau et al., 2012). When taking into account all sites with recorded earthworms, the coefficient of variation of theirs abundance (individuals m−2) at European level is high (134%) and, as expected, climate-related (a possible soil moisture deficit is known to reduce earthworm populations).
At a local scale, steep changes in the numerical abundance and diversity of earthworms can be expected at the interface between natural and agricultural land and at the edges between pastures and arable fields (Rutgers et al., 2009, Sechi et al., 2015). Consequently, digital soil mapping (DSM; McBratney et al., 2003) was utilized in the present study, building upon earlier efforts to map soil biodiversity in The Netherlands (Van Wijnen et al., 2012, Rutgers and Dirven-Van Breemen, 2012, Rutgers et al., 2012). DSM statistically correlates soil attributes with a low spatial resolution to attributes with a higher spatial resolution, such as the soil organic matter content and the land use type. In this study, earthworm community attributes (i.e. total abundance, abundance per taxon, Shannon diversity and richness) were used in a multiple regression analysis with data on soil characteristics, land use, vegetation and climate.
European maps of earthworm abundance (total and single species), richness and Shannon index were produced for areas where earthworm data were collected and subsequently harmonized, i.e. The Netherlands, Germany, Ireland, Northern Ireland, Scotland, France, Slovenia, Denmark, together with parts of Spain. The maps were created primarily to raise awareness, to advocate soil biodiversity as an environmental policy issue, and as a plea for enhancing long-term environmental monitoring, but not for analyzing earthworm community distributions in Europe. These maps and their associated raw data may enhance the recently launched Global Soil Biodiversity Atlas (www.globalsoilbiodiversity.org), a follow-up to the European Atlas of Soil Biodiversity (Jeffrey et al., 2010), and are open for future enrichment. To our knowledge no other continental scale soil biodiversity map has been generated using a DSM approach.
Section snippets
Data collection and standardisation
Total abundance of earthworms and number of species or genera, adults and juveniles, together with selected biodiversity indices, were the targeted level of resolution for mapping. Thus, all potential contributors were asked to collect and assemble earthworm data on abundance (and/or biomass) per taxon (at species level, where possible), with an indication of the collection and identification method. The primary data providers, organized per country, are the authors of this article. The final
Building a harmonized database for earthworm records in Europe
After discarding records with incomplete or unreliable data, sometimes leading to the elimination of data sets of entire countries, we were able to assemble an earthworm database with abundance and species composition and associated environmental characteristics from 3838 sites in 8 countries (minimum 71 sites, maximum 1423 sites per country: Fig. 1, Table 3). The Netherlands had the highest data density (2.1 observations per 100 km2) and the largest European country, France, had the highest
Conclusions
Earthworm communities in Europe were successfully mapped on the basis of harmonized data from 8 countries, and statistically significant multiple regression models. Our assembled database included more countries and covered a larger latitudinal span than previous studies on earthworms in Europe; therefore, we believe that these geographical patterns are representative for continental and possibly even for global biodiversity scales. In addition, we noted an inverse latitudinal gradient in
Appendix A: electronic supplementary material
The following information is supplementary to this article. The file contains national maps on the earthworm communities for The Netherlands, Germany, France and Ireland and abundances and relative abundance of two species, the endogeic Aporrectodea caliginosa and the anecic Lumbricus terrestris.
Acknowledgments
All researchers and technicians digging the insurmountable number of soil blocks, performing numerous extractions in the field, and in the lab, accomplishing harsh taxonomic identifications, provided a solid basis for the first earthworm map of Europe, and are acknowledged for their contributions. The French partners warmly thank M. Bouché for giving his huge data set and his earthworm collection to the University of Rennes. The work on data collection, harmonization, modelling and mapping was
References (93)
- et al.
A critical review of current methods in earthworm ecology: From individuals to populations
Eur. J. Soil Biol.
(2010) - et al.
The Edaphobase project of GBIF-Germany—a new online soil-zoological data warehouse
Appl. Soil Ecol.
(2014) - et al.
Integration of biodiversity in soil quality monitoring: baselines for microbial and soil fauna parameters for different land-use types
Eur. J. Soil Bio.l
(2012) - et al.
Earthworm assemblages as affected by field margin strips and tillage intensity: an on-farm approach
Eur. J. Soil Biol.
(2015) Oligochaeta
Trace Met. Contam. Environ.
(2003)- et al.
A soil change-based methodology for the quantification and valuation of ecosystem services from agro-ecosystems: a case study of pastoral agriculture in New Zealand
Ecol. Econ.
(2014) - et al.
Rapoport's rule: time for an epitaph?
Trends Ecol. Evol.
(1998) - et al.
Cross-taxa congruence, indicators and environmental gradients in soils under agricultural and extensive land management
Eur. J. Soil Biol.
(2012) - et al.
On digital soil mapping
Geoderma
(2003) - et al.
Distribution of earthworms in the north-west of the Iberian Peninsula
Eur. J. Soil Biol.
(2003)