Urban stormwater retention capacity of nature-based solutions at different climatic conditions

Climate change and the continuing increase in human population creates a growing need to tackle urban stormwater problems. One promising mitigation option is by using nature-based solutions (NBS) – especially sustainable urban stormwater management technologies that are key elements of NBS action. We used a synthesis approach to compile available information about urban stormwater retention capacity of the most common sustainable urban drainage systems (SUDS) in different climatic conditions. Those SUDS targeting stormwater management through water retention and removal solutions (mainly by infiltration, overland flow and evapotranspiration), were addressed in this study. Selected SUDS were green roofs, bioretention systems (i.e. rain gardens), buffer and filter strips, vegetated swales, constructed wetlands, and water-pervious pavements. We found that despite a vast amount of data available from real-life applications and research results, there is a lack of decisive information about stormwater retention and removal capacity of selected SUDS. The available data show large variability in performance across different climatic conditions. It is therefore a challenge to set conclusive widely applicable guidelines for SUDS implementation based on available water retention data. Adequate data were available only to evaluate the water retention capacity of green roofs (average 56±20%) and we provide a comprehensive review on this function. However, as with other SUDS, still the same problem of high variability in the performance (min 11% and max 99% of retention) remains. This limits our ability to determine the capacity of green roofs to support better planning and wider implementation across climate zones. The further development of SUDS to support urban stormwater retention should be informed by and developed concurrently with the adaptation strategies to cope with climate change, especially with increasing frequency of extreme precipitation events that lead to high volumes of stormwater runoff

XDGGS: A community-developed Xarray package to support planetary DGGS data cube computations

Traditional map projections introduce distortions, especially for global data. Discrete Global Grid Systems (DGGS) offer an alternative by dividing the Earth into equal-area grid cells at different resolutions. This paper describes xdggs, a new Xarray extension that simplifies working with DGGS. Xdggs provides a unified API for various DGGS libraries and integrates seamlessly with the Pangeo ecosystem through extending the widely used Xarray library to use the DGGS-specific cell identifiers as an index. This development makes DGGS more accessible and will lead to facilitating data analysis on a planetary scale.Xdggs aims to provide a user-friendly API that hides the implementation complexities of different DGGS libraries. And because it integrates seamlessly with Xarray, a popular tool for geospatial data analysis, xdggs promotes FAIR data practices by simplifying data access and interoperability and can become a valuable tool for geospatial scientists and application developers working with global datasets

Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis

Context: Landscape metrics represent powerful tools for quantifying landscape structure, but uncertainties persist around their interpretation. Urban settings add unique considerations, containing habitat structures driven by the surrounding built-up environment. Understanding urban ecosystems, however, should focus on the habitats rather than the matrix. Objectives: We coupled a multivariate approach with landscape metric analysis to overcome existing shortcomings in interpretation. We then explored relationships between landscape characteristics and modelled ecosystem service provision. Methods: We used principal component analysis and cluster analysis to isolate the most effective measures of landscape variability and then grouped habitat patches according to their attributes, independent of the surrounding urban form. We compared results to the modelled provision of three ecosystem services. Seven classes resulting from cluster analysis were separated primarily on patch area, and secondarily by measures of shape complexity and inter-patch distance. Results: When compared to modelled ecosystem services, larger patches up to 10 ha in size consistently stored more carbon per area and supported more pollinators, while exhibiting a greater risk of soil erosion. Smaller, isolated patches showed the opposite, and patches larger than 10 ha exhibited no additional areal benefit. Conclusions: Multivariate landscape metric analysis offers greater confidence and consistency than analysing landscape metrics individually. Independent classification avoids the influence of the urban matrix surrounding habitats of interest, and allows patches to be grouped according to their own attributes. Such a grouping is useful as it may correlate more strongly with the characteristics of landscape structure that directly affect ecosystem function

Evaluation of potential habitat with an integrated analysis of a spatial conservation strategy for David’s deer, Elaphurus davidians

How to assess the potential habitat integrating landscape dynamics and population research, and how to reintroduce animals to potential habitats in environments highly human disturbed are still questions to be answered in conservation biology. According to behavioral research on Elaphurus davidians, we have developed a suitability index and a risk index to evaluate the potential habitats for the deer. With these indices, we conducted two transect assessments to evaluate the gradient change of the target region. Then, taking rivers as border lines, we tabulated the forest areas, high grassland area and total area and then compared the forest and high grassland area in each subregion. Furthermore, we computed the land use transfer matrix for the whole Yancheng coast during 1987–2000. We also computed human modified index (HMI) in six subregions. Lastly with a geographical information system support we obtained the spatial distribution of the indices and evaluation of the whole potential habitats from a neighborhood analysis. The transect assessment showed that the suitability of the coastal area was higher than that of the inland area for the deer, while the southern area was higher than the northern. Landscape metrics and HMI analysis showed that different landscape patterns and different anthropogenic disturbance existed within the region, and the increasing human disturbance was the key factor causing the pattern dynamics. The evaluation of potential habitats showed that there was an estimated carrying capacity of no more than 10,000 for David’s deer reintroduction into the natural area. Also the reintroduction strategy was discussed. This integrated approach linked the population research and the landscape metrics, and the dataset with different scale; thus, it is an approach likely to be useful for the protection of other large animal in a landscape highly disturbed by humans