Variation in wetland invertebrate communities in lowland acidic fens and swamps

1. Invertebrates were collected semi‐quantitatively from four relatively undisturbed wetlands in the west coast of New Zealand’s South Island: two acidic fens and two swamps. Samples were collected from up to four discrete habitats within each wetland: large open‐water channels, small leads (small, ill‐defined channels with emergent vegetation in them) and large (>10 m diameter) or small (<10 m diameter) ponds. Samples were also collected from different plant species within each wetland, each with different morphology, and from areas without vegetation. This was done to determine whether invertebrate communities varied more between‐wetlands than within‐wetlands, as the results had implications for future wetland monitoring programmes. 2. Principal components analysis of water chemistry data revealed striking differences in pH, conductivity and nutrients between the four wetlands. Not surprisingly, pH was lowest in one of the acidic fens, and highest in one of the swamps, where conductivity was also high. Midges (Tanytarsus, Tanypodinae, Orthocladiinae and Ceratopogonidae), nematodes, harpactacoid copepods and the damselfly Xanthocnemis dominated the invertebrate fauna. Orthoclad midges and mites were the most widespread taxa, found in 91 of 94 samples. Diptera were the most diverse invertebrate group, followed by Trichoptera and Crustacea. 3. Ordination analysis of the invertebrate data showed that the four wetlands supported different invertebrate communities. However, species composition did not change completely along the ordination axes, suggesting that a relatively species‐poor invertebrate fauna was found in the wetlands. Taxa such as molluscs were restricted to wetlands with high pH. Multi‐response permutation procedures (MRPP) was used to analyse resultant ordination scores to see how they differed according to five terms: ‘Wetland’, ‘Habitat’, ‘Growth Form’, ‘Morphology’ and ‘Plant’. Most of the sample separation along ordination axes reflected differences between wetland, although the ‘Habitat’ and ‘Plant’ terms also explained some of the variation. The ‘Growth Form’ and ‘Morphology’ terms had only minor effects on community composition. 4. A multivariate regression tree modelled invertebrate assemblages according to the five predictor terms. The resultant model explained 54.8% of the species variance. The ‘Wetland’ term contributed most to the explanatory power, followed by ‘Habitat’. ‘Growth type’ and ‘Morphology’ explained only a small amount of variance to the regression tree, while the different plant species explained none of the variation. 5. Variation in these New Zealand wetland invertebrate communities appears to be controlled most by large‐scale factors operating at the level of individual wetlands, although different habitats within individual wetlands contributed slightly to this variation. Based on these results, sampling programmes to describe wetland invertebrate communities do not need to sample specific habitats or plant types within a wetland. Instead, samples can be collected from a wide range of habitats within individual wetlands, and pooled. Within each habitat, it is unnecessary to collect individual samples from different macrophytes or un‐vegetated areas. Our results suggest that collecting replicate pooled samples from different habitats within each wetland will be sufficient to characterize the invertebrate assemblage of each wetland.