Different bioindicators measured at different spatial scales vary in their response to agricultural intensity
McMahon, Barry J.
- Publisher: Elsevier
Indicator | Agro-ecology | Livestock farming | Biodiversity | Agri-environment policy | Habitat heterogeneity
Ecologically, potential bioindicator taxa operate at different scales within agricultural ecosystems, and thereby provide a means to investigate the influence of changing management practice on biological diversity at different scales within the agro-ecosystem. Surveys of grassland plant species at field level, parasitoid Hymenoptera at the field and farm scale, and bird populations and habitats at farm scale were carried out on 119 grass-based farms across three regions in the Republic of Ireland. In addition, habitat richness and aquatic macroinvertebrates were quantified at landscape scale. Agricultural intensity on the surveyed farms was quantified by mean farm stocking rate, calculated as livestock units per ha (LU/ha), and generalised linear mixed models used to evaluate relationships between stocking rate and the incidence of chosen bioindicator groups. Field scale bioindicators (plant species richness and parasitoid taxon richness and abundance) were negatively associated with mean farm stocking rate. Over much of its observed range, mean farm stocking rate was positively associated with total bird species richness and abundance, and the species richness and abundance of farmland bird indicator species recorded in the winter season. However, these relationships were quadratic, and above a relatively high upper limit of 2.5–3.5 LU/ha, further increase in farm stocking rate had a negative influence. Results demonstrate that different bioindicators measured at different spatial scales vary in their response to agricultural intensity. The lack of a consistent bioindicator response to farm stocking rate suggests that within predominantly farmed regions, maximising biodiversity requires a careful targeting and monitoring with bioindicator taxa that are informative of influences at relevant operational scales. The insights provided may then be much more informative for the design and implementation of agri-environment measures that maximise biodiversity within farmed landscapes.