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Revising Green Infrastructure: Concepts Between Nature and Design - CRC Press Book. Revising Green Infrastructure: Concepts Between Nature and Design [Daniel Czechowski, Thomas Hauck, Georg Hausladen] on giuliettasprint.konfer.eu *FREE* shipping.
Articles Cited by. Journal of Landscape Architecture 6 1 , , Journal of Landscape Architecture 1 1 , , Landschap: tijdschrift voor landschapsecologie en milieukunde 32 2 , , Landschap: tijdschrift voor Landschapsecologie en Milieukunde 30 4 , , Stedebouw en Ruimtelijke Ordening 89 1 , , Journal of Landscape Architecture, spring , pag, , 0.
First Published Imprint CRC Press. Pages pages. Export Citation. Get Citation. Czechowski, D. Consider this … How do we handle the convergence of landscape architecture, ecological planning, and civil engineering?
What are convenient terms and metaphors to communicate the interplay between design and ecology? What are suitable scientific theories and technological means? What innovations arise from multidisciplinary and cross-scalar approaches? Table 1. A range of ecosystem services are provided by GI features, though optimizing these services relies on the selection of locally-appropriate and resilient plant cover as well as the use of engineered soil Technosols; Deeb et al.
Environmental and structural characteristics of GI features, particularly soil texture, greatly influence local microclimatic conditions by regulating the availability of surface water films for soil microbes and water retention for plants and meso — macrofauna Huang et al. Additionally, variations in organic matter, pH, and salts, can influence soil microbial community composition, and function Cosandey et al.
Soil microbial communities maintain essential roles that are responsible for nutrient cycling processes which support plant growth and other ecosystem services of GI features Wall, ; Young and Crawford, ; Hostetler et al. Furthermore, biodiversity, particularly within the soil microbiome, has been found to be important for maintaining overall ecosystem function and resilience Allison and Martiny, ; Reese et al. Analysis of the microbial communities in GI features is fundamental to understanding the role of the microbial community and as a guide for future GI designs.
The microbial community of Technosols can be an indicator of the nature and extent of anthropogenic impact on GI features, including pollutants in urban runoff. Studies across a range of locations and soil types show that the Phyla Acidobacteria, Actinobacteria, and Proteobacteria regularly dominating the soil microbiome, including in urban soils Fierer and Jackson, ; McGuire et al. These Phyla provide a baseline for evaluating the composition of bacterial communities in Technosols. These changes can be attributed to introductions of atypical soil microbiota as well as enrichment of specific, indigenous bacteria.
For example, gram-negative bacteria typically increase in soils contaminated with petroleum MacNaughton et al. Some gram-positive bacteria, i. Biological contamination through animal feces can introduce Clostridium and Ruminococccus species and, more broadly, the Phyla Firmicutes, Bacteroidetes, and Actinobacteria into the soil Handl et al. Knowing whether these, and other bacteria, are found in GI features is important because it can help to guide urban planning for the purposes of improving urban biodiversity or bioremediation, such as influencing the location, design, construction of GI features.
Previous studies have characterized correlations between anthropogenic impacts on soil microbial communities, however, limited research has explored the dynamics influencing the Technosol microbial communities in GI features Mukherjee et al. The objective of this study was to describe the bacterial community of Technosols in GI features, which differ in their design for managing urban runoff infiltration and retention in NYC.
Focal bacterial groups were selected because of their essential role in nutrient cycling and the degradation of pollutants.
Relationships between bacterial communities, composition and diversity, with soil physical properties and biogeochemical parameters were evaluated by comparing results with data from a companion study conducted on the same sites Deeb et al. Modifications to the road drainage system i. Both ETP and SSIS are prototypes of bioswales and were constructed within sidewalks adjacent to streets, directly connected to street drainage. The VS are vegetated areas of variable size and shape, constructed in open areas e. The area of ETP are typically 9.
The surface area of SSIS are typically The VS sample sites had an average surface area of One VS site served as an urban reference site GI. The UF site was sampled as a reference of a non-Technosol urban soil and was an irregularly shaped forest stand of native hardwood trees oak and hickory established in Figure 1.
The area of impervious urban surface creating runoff water to be managed by a GI feature differed across the GI sites in this study. Since VS sites had unstructured design criteria including the size of the GI feature, the area of impervious surfaces each VS site served varied from 73 to m 2. The initial plant cover for all designs was a combination of herbaceous perennials, grasses, and trees.
The herbaceous plant cover at all sites included American boneset Eupatorium perfoliatium , New England aster Aster novae angiliae syn.
Symphyotrichum novae-angliae , and oxeye sunflower Heliospsis helianthoides. The grasses at all sites were switch grass Panicum virgatum and Virginia wild rye Elymus virginicus. Trees planted varied by site and were selected from the following resilient species — black gum Nyssa sylvatica , sweet gum Liquidambar styraciflua , shadblow Amelanchier canadensis , and swamp white oak Quercus bicolor. At the time of sampling, vegetation cover was generally present and ROWB sites were consistent with the planned selection of species Supplementary Figure 1.
GI sites were sampled over a period of 48 h in July, Multiple surface samples were collected at each GI site from random locations within the site distributed throughout the center, periphery, etc. All surface samples from a single GI site were pooled into a larger collection barrel and mixed thoroughly as a collective representation of that site.
Bacterial DNA was extracted from soil 0. In a companion study Deeb et al. A suite of additional measurements for biogeochemical parameters microbial biomass carbon and nitrogen content, potential net nitrogen mineralization and nitrification, microbial respiration, and denitrification potential were also completed Supplementary Table 1.
Sequence data were received as paired forward and reverse reads with adapters removed. Non-bacterial e.
Throughout processing the sequence data, the sequence average for each sample remained about 50, sequences Supplementary Table 2. Final bacterial communities were normalized by rarefying to the lowest number of the sample sequence counts, 44, sequences rarefaction curves, Supplementary Figure 2 Sequence counts of replicates were averaged to better represent the bacterial community of each GI design R Core Team analysis package Phyloseq; McMurdie and Holmes, Several biodiversity metrics were calculated using the normalized sequence data.
Alpha diversity represents bacterial diversity within each sample and GI design; richness of unique organisms is presented as the observed OTUs and estimated richness of OTUs Chao1 , while the Shannon diversity index accounts for unique OTU richness and abundance. Beta diversity represents the bacterial diversity between GI samples, calculated with a Bray-Curtis and Unifrac weighted and unweighted distance matrix of the bacterial community similarities represented by a principal coordinate analysis, PCoA Phyloseq.
The biogeochemical parameters measured Deeb et al. Predominant bacterial Orders related to biogeochemical parameters were determined with linear correlations; significance determined with p -values of less than 0. Additionally, the most abundant bacteria at the Order level Orders with greater than a total of 50 sequences for all samples were evaluated for associations with biogeochemical factors common to pollutants using ANOVAs followed by Tukey HSD tests. Results from this study were compared with a previous sampling of natural not-engineered urban surface soils from non-GI features in NYC Huot et al.
The analysis methods were the same as described above except that new OTU clusters were identified using the Uclust algorithm to reduce computational demand Edgar, Sequences for all samples were normalized to control for sequencing variation between samples as well as machine runs for the different data sets. Differential abundances for bacterial Orders were evaluated by averaging the number of sequences for the Orders at each site then comparing the proportion of the urban surface soil bacterial community to the proportion within the Technosol bacterial community.
Microbial biomass C and N and metabolic functioning potential net N mineralization and nitrification, microbial respiration, denitrification potential were all positively correlated with C-org, N-total, pH, MC, TPH, and watershed contributing area Deeb et al. The pH was markedly lower in the UF 4. ETP sites had higher levels of organic carbon that likely drove higher levels of microbial biomass and activity in these sites compared to the SSIS and VS sites.
For most biogeochemical parameters evaluated, SSIS had higher levels of activity than VS sites, but these differences were not always statistically significant. Specific community composition of bacterial Orders was only significantly unique for the UF site as well as for the VS urban reference site, GI. Figure 2. Bacterial communities were normalized to the lowest sequence count of the samples 44, Taxa of the bacteria communities are represented by the top 20 Orders with the remaining Orders clustered into the Other category.
Local contribution to beta diversity LCBD indicates the uniqueness of a community with the black circles along the x-axis, size corresponds to the scaled difference. The GI bacterial communities all had levels of diversity in a range that is similar to the diversity associated with non-urban soils Fierer and Jackson, ; McGuire et al. No other abundant nor prevalent bacterial Order significantly varied in abundance between GI designs. GI designs had unique bacterial community beta diversity when considering both the phylogenetic relatedness of bacteria present as well as the abundance of each taxon.
One key difference was the high relative abundance of Synechoccales, which was rare in the other VS sites. Table 4.
Figure 3. The beta diversity comparison of bacterial communities. PCoA analysis plots for Weighted Unifrac left, incorporates phylogenetic relatedness and abundance within communities , Unweighted Unifrac center; incorporates phylogenetic relatedness within communities , and Bray-Curtis right distance matrices. There were significant trends between specific biogeochemical parameters and the top 10 Orders of bacteria in the GI sites Supplementary Figure 4 , however, none of the biogeochemical parameters were consistently correlated across bacterial Orders or GI design.
Chromatales and A21b were among the 10 abundant Orders across all GI designs. The salt concentration within the Technosols had a wide range and higher concentrations correlated with a decrease in abundance and an overall decrease in diversity for VS and SSIS designs, while ETP design increased in diversity Supplementary Figure 5.
Figure 4. Alpha diversity metrics of the rarefied sample dataset with key biogeochemical parameters. ETP1 and UF are not replicated so there is no regression model but they are included for comparison. When Technosols were compared with natural urban surface soils, some differences in community composition were apparent after normalizing for sequence variation 3, sequences for each sample.