Abstract
Important steps in developing reliable bioindicators for soil quality are characterising soil biodiversity and determining the response of its components to environmental factors across a range of land uses and soil types. Baseline data from a national survey in Ireland were used to explore relationships between diversity and composition of micro-organisms (bacteria, fungi, mycorrhiza), and micro-, meso- and macro-fauna (nematodes; mites; earthworms, ants) across a general gradient representing dominant land uses (arable, pasture, rough-grazing, forest and bogland). These diversity data were also linked to soil physico-chemical properties. Differences in diversity and composition of meso- and macro-fauna, but not microbes, were clear between agriculturally-managed (arable and pasture) and extensively-managed (rough-grazing and bogland) soils corresponding to a broad division between 'mineral' and 'organic' soils. The abundance, richness and composition of nematode and earthworm taxa were significantly congruent with a number of the other groups. Further analysis, using significant indicator species from each group, identified potential target taxa and linked them to soil environmental gradients. This study suggests that there is potential surrogacy between the diversity of key soil taxa groups and that different sets of bioindicators may be most effective under agricultural and extensive land use.
| Original language | English |
|---|---|
| Pages (from-to) | 55-62 |
| Number of pages | 8 |
| Journal | European Journal of Soil Biology |
| Volume | 49 |
| DOIs | |
| Publication status | Published - Mar 2012 |
Keywords
- Biodiversity
- Bioindicators
- Land use
- Physico-chemical gradients
- Soil community structure
- Soil monitoring
Fingerprint
Dive into the research topics of 'Cross-taxa congruence, indicators and environmental gradients in soils under agricultural and extensive land management'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver