Macroinvertebrate Community Composition and Diversity in Ephemeral and Perennial Ponds on Unregulated Floodplain Meadows in the UK

Ponds are common and abundant landscape features in temperate environments, particularly on floodplains where lateral connectivity with riverine systems persists. Despite their widespread occurrence and importance to regional diversity, research on the ecology and hydrology of temperate ephemeral and perennial floodplain ponds lags behind that of other shallow waterbodies. This study examines the aquatic macroinvertebrate diversity of 34 ponds (20 perennial and 14 ephemeral) on two unregulated riverine floodplain meadows in Leicestershire, UK. Perennial ponds supported nearly twice the diversity of ephemeral ponds. Despite frequent inundation of floodwater and connectivity with other floodplain waterbodies, ephemeral ponds supported distinct invertebrate communities when compared to perennial ponds. When the relative importance of physical and chemical, biological and spatial characteristics was examined, physical and chemical characteristics were found to account for more variation in community composition than biological or spatial variables. The results suggest that niche characteristics rather than neutral colonisation processes dominate the structure of invertebrate communities of floodplain ponds. The maintenance of pond networks with varying hydroperiod lengths and environmental characteristics should be encouraged as part of conservation management strategies to provide heterogeneous environmental conditions to support and enhance aquatic biodiversity at a landscape scale.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.