Data from PhD thesis "Ecological dynamics on old extensive green roofs: vegetation and substrates >20 years since installation"

2017-06-29T13:59:22Z (GMT) by Christine Thuring Nigel Dunnett
<div>Data for the PhD thesis: <br></div><em>Thuring, Christine (2015) Ecological dynamics on old extensive green roofs: vegetation and substrates > twenty years since installation. PhD thesis, University of Sheffield. <a href="" target="_blank"></a>.</em><div><p></p> </div><div>Extensive green roof (EGR) technology has become a popular ecological intervention for towns and cities around the world in recent years. Much is known about EGR engineered performance, but little work has studied green roofs as “novel ecosystems” subject to the laws of nature. Since roof access is typically difficult to attain, this was a unique opportunity to develop methods and gain preliminary insights into how the vegetation and substrates of commercial EGR systems develop over time. Nine of the oldest EGRs in the world (at least twenty years since installation) were surveyed using methods of applied plant ecology in southwest Germany. Species composition and abundance were quantified using a 1m2 quadrat (sampling plot) and methods of applied plant ecology. Between 12 and 18 quadrats were sampled per roof. The number and placement of quadrats was determined by site conditions, vegetation homogeneity, environmental gradients, and the statistical requirements of sampling. The random placement of quadrats gives any point within the sampling area an equal chance of being sampled but, since the aim of this work was to characterise EGR vegetation, quadrats were sampled from areas featuring characteristic vegetation. Accordingly, random placement was too simplistic for roofs with mounds or shallow gravel edges, where the vegetation differed from the greater roof expanse, so such roofs were stratified in advance of sampling. Stratifying, or dividing, vegetation into homogeneous (uniform) versus heterogeneous (non-uniform) patches prior to placing samples is beneficial for clustering major sources of variation. Functional traits were allocated to all plant species, both current and original, using adaptive life strategies described by CSR theory, and the realised niches were described using Ellenberg indicator values (EIVs).</div>