Role of Neighborhood Design in Reducing Impacts of Development and Climate Change, West Sherwood, OR

We used the EPA SWMM-5. 1 model to evaluate the relative impact of neighborhood design and constructed Low Impact Development (LID) features on infiltration, evaporation, and runoff for three future scenarios. In the Current Course (CC) future, current regulations and policies remain in place under lower rates of climate change and population growth. In the Stressed Resources (SR) future, rapid rates of population growth and climate change stress water systems, and conventional development patterns and management actions fail to keep pace with a changing environment. In the Integrated Water (IW) future, with the same rapid rates of climate change and population growth as the SR future, informed water management anticipates and adapts to expected changes. The IW scenario retains public open space, extensive use of constructed LID features, and has the lowest proportion of impervious surface. Neighborhood designs varied in the number of dwelling units, density of development, and spatial extent of nature-based solutions and constructed LID features used for stormwater management. We compared the scenarios using SWMM-5.1 for a set of NRCS Type 1a design storms (2-yr, 25-yr, 20% increase over 25-yr, 30% increase over 25-yr) with precipitation input at 6-min time steps as well as a set of 10-year continuous runs. Results illustrate the importance of neighborhood design in urban hydrology. The design with the highest proportion of impervious surface (SR future) produced runoff of up to 45–50% of precipitation for all variations of the 25-year storm, compared to 34–44 and 23–39% for the CC and IW futures, respectively. Evaporation accounted for only 2–3% of precipitation in the 25-year design storm simulations for any scenario. Results of continuous 10-year simulations were similar to the results of design storms. The proportion of precipitation that became runoff was highest in the SR future (33%), intermediate in the CC (16%), and lowest in the IW future (9%). Evaporation accounted for 6, 11, and 14 of precipitation in the SR, CC, and IW futures with LID, respectively. Infiltration was higher in scenarios with LID than for the same scenario without LID, and varied with the extent of LID employed, accounting for 59, 71, and 74% of precipitation in the SR, CC, and IW scenarios with LID. In addition to differences in performance for stormwater management, the alternative scenarios also provide different sets of co-benefits. The IW and SR future designs both provide more housing than the CC, and the IW future has the lowest cost of development per dwelling unit.

Urban Development Reduces Bee Abundance and Diversity

Wild bee communities persist in cities despite major disruption of nesting and food resources by urban development. Bee diversity and abundance is key for urban agriculture and maintenance of plant diversity, and assessing what aspects of cities enhance bee populations will promote our capacity to retain and provision bee habitat. Here, we assessed how variation in land cover and neighborhood development history affected bee communities in the midwestern US urban landscape of Madison, Wisconsin. We sampled bee communities across 38 sites with relatively high (> 55%) or low (< 30%) levels of impervious surface, and assessed effects of land use and neighborhood development history on bee abundance and species richness. We show abundance and richness of bees was lower in recently developed neighborhoods, with particularly strong negative effects on soil nesting bees. Soil nesting bees and bee community richness decreased as cover of impervious surface increased, but above ground nesting bees were minimally impacted. Bee community similarity varied spatially and based on dissimilar local land cover, only for soil nesting bees, and the overall bee community. Impervious surface limited bee abundance and diversity, but new neighborhoods were associated with greater negative effects. We suggest that enhancing the structural diversity of new neighborhoods in urban ecosystems may imitate the structural benefits of older neighborhoods for bee populations.

GISD30: global 30-m impervious surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform

Accurately mapping impervious surface dynamics has great scientific significance and application value for urban sustainable development research, anthropogenic carbon emission assessment and global ecological environment modeling. In this study, a novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and pervious surface samples in the same epoch for each 5° × 5° geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious surface dynamics. Our global 30 m impervious surface dynamic model achieved an overall accuracy of 91.5 % and a kappa coefficient of 0.866 using 18,540 global time-series validation samples. Cross-comparisons with four existing global 30 m impervious surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116 × 105 km2 in 1985 to 10.871 × 105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946 × 105 km2. Therefore, it was concluded that our global 30 m impervious surface dynamic dataset is an accurate and promising product, and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at http://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b).

Characterization of polycyclic aromatic hydrocarbons in the Great Lakes Basin using dreissenid mussels

The National Oceanic and Atmospheric Administration (NOAA), National Centers for Coastal Ocean Science (NCCOS) Mussel Watch Program (MWP), conducts basin-wide monitoring and place-based assessments using dreissenid mussels as bioindicators of chemical contamination in the Laurentian Great Lakes. Polycyclic aromatic hydrocarbons (PAHs) body burden results for the period 2009–2018 were combined into one dataset from multiple MWP studies allowing for a robust characterization of PAH contamination. Patterns in PAH data were identified using descriptive statistics and machine learning techniques. Relationships between total PAH concentration in dreissenid mussel tissue, impervious surface percentages, and PAH relative concentration were identified and used to build a predictive model for the Great Lakes Basin. Significant positive correlation was identified by the Spearman’s rank correlation test between total PAH concentration and percent impervious surface. The findings support the paradigm that PAHs are primarily derived from land-based sources. Offshore and riverine locations had the lowest and highest median total PAH concentrations, respectively. PAH assemblages and ratios indicated that pyrogenic sources were more predominant than petrogenic sources and that PAHs at offshore sites exhibited relatively more weathering compared to inshore sites.

Recent Urban Development Reduces Bee Abundance and Diversity

Wild bee communities persist in cities despite major disruption of nesting and food resources by urban development. Bee diversity and abundance is key for urban agriculture and maintenance of plant diversity, and assessing what aspects of cities enhance bee populations will promote our capacity to retain and provision bee habitat. Here, we assessed how variation in land cover and neighborhood development history affected bee communities in the midwestern US urban landscape of Madison, Wisconsin. We sampled bee communities across 38 sites with relatively high (> 55%) or low (< 30%) levels of impervious surface, and assessed effects of land use and neighborhood development history on bee abundance and species richness. We show abundance and richness of bees was lower in recently developed neighborhoods, with particularly strong negative effects on soil nesting bees. Soil nesting bees and bee community richness decreased as cover of impervious surface increased, but above ground nesting bees were minimally impacted. Bee community similarity varied spatially and based on dissimilar local land cover, only for soil nesting bees, and the overall bee community. Impervious surface limited bee abundance and diversity, but new neighborhoods were associated with greater negative effects. We suggest that enhancing the structural diversity of new neighborhoods in urban ecosystems may imitate the structural benefits of older neighborhoods for bee populations.