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Scholars have spent decades arguing that policy entrepreneurs, change agents who work individually and in groups to influence the policy process, can be crucial in introducing policy innovation and spurring policy change. How to identify policy entrepreneurs empirically has received less attention. This oversight is consequential because scholars trying to understand when policy entrepreneurs emerge, and why, and what makes them more or less successful, need to be able to identify these change agents reliably and accurately. This paper explores the ways policy entrepreneurs are currently identified and highlights issues with current approaches. We introduce a new technique for eliciting and distinguishing policy entrepreneurs, coupling automated and manual analysis of local news media and a survey of policy entrepreneur candidates. We apply this technique to the empirical case of unconventional oil and gas drilling in Pennsylvania and derive some tentative results concerning factors which increase entrepreneurial efficacy.

 

Green infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.

 

Infiltration stormwater control measures (SCMs) have the potential to contribute towards mitigating the effects of urbanization on downstream receiving waters. Infiltration SCMs are most often successful when the in‐situ saturated hydraulic conductivity (K_sat) is well characterized. In this paper numerical solutions of the Richards’ equation are used to quantify the bias of seven infiltration measurement methods, removing natural variability and random error from the analysis. The methods evaluated in this study include the double ring infiltrometer, Saturo infiltrometer, modified Philip–Dunne infiltrometer, Turf‐Tec IN2‐W infiltrometer, USBR 7300‐89 well permeameter, Philip–Dunne permeameter, and the Guelph permeameter. Seven homogenous, isotropic soil textures were simulated at four initial soil moistures for the seven methods, resulting in a total of 196 simulations. The dimensionless bias is defined as the “measured”K_satdetermined by a given method divided by theK_satinput to the numerical experiments. The “measured”K_satis in quotations to identify the measurement occurs in a numeric experiment rather than in a physical experiment. In sand through silt loam soils that are typical of infiltration SCMs, the simulated methods have a bias in the range of 0.7–6.2. The Turf‐Tec was the only infiltrometer that produced a bias >2.5 for these soils. Initial effective saturation had a minimal contribution to bias for most methods. Methods that rely on a one‐dimensional (1D) flow assumption consistently overestimated theK_sat. Borehole methods produced results with bias similar to surface methods. Long duration methods did not consistently produce more accurate results than short duration methods.

 

Roadsides are targeted for restoration of pollinator‐friendly plants. Yet, roads are sources of macronutrient, micronutrient and heavy metal pollution that may contaminate roadside plants. Adjacent landscape features such as railroads and agriculture provide additional macronutrient and heavy metal pollution that may exacerbate traffic effects. However, we lack perspective on how roads combine with rural landscape features to influence nutrition of roadside plants, which could have implications for pollinator health.

We surveyed roadsides across Minnesota, USA and measured foliar levels of dietary macronutrients (nitrogen, phosphorous and potassium), a micronutrient (sodium) and metals (iron, zinc, copper, chromium, nickel, lead, aluminium and cadmium) in six abundant roadside forb species used by insect pollinators:Asclepias syriaca,Dalea purpurea,Monarda fistulosa,Ratibida pinnata,Solidagospp. andTrifolium pratense. We aimed to determine (1) how road variables (traffic volume and distance from road) combine with adjacent land use (railroad and agriculture) to influence element content of roadside forbs and (2) whether some forb species show consistent differences in their accumulation of potentially toxic heavy metals, which could inform selection of species to plant along roadsides.

We found that foliar concentrations of nine elements increased with greater traffic volume (nitrogen, phosphorous, iron, zinc, copper, chromium, nickel, lead and aluminium), and concentrations of six elements declined with distance from the road (nitrogen, phosphorous, potassium, iron, zinc and copper). Leaves collected adjacent to railroad had less phosphorous, potassium, iron, nickel and aluminium than leaves collected from sites not adjacent to railroad. Additionally, leaves collected from sites adjacent to agriculture had lower copper levels than leaves from sites without adjacent agriculture. We found no evidence that particular ford species along roadsides consistently rank higher than other species in their accumulation of heavy metals.

Our results show that traffic alters more elements in roadside plants than does adjacent landscape context, alleviating concerns that landscape features exacerbate pollutant levels in roadside pollinator habitat. However, nutrient contamination of most roadside plants is unlikely to reach toxic levels for insect pollinators. This work is consistent with the positive conservation potential of low to moderate traffic roadsides for pollinators.

 

Excess non-point nutrient loading continues to impair urban surface waters. Because of the potential contribution of tree litterfall to nutrient pollution in stormwater, street sweeping is a promising management tool for reducing eutrophication in urban and suburban regions. However, nutrient concentrations and loads of material removed through street sweeping have not been well characterized, impeding the development of pollution reduction credits and improvement of models for stormwater management. We evaluated the role of canopy cover over streets, street sweeper type, season, and sweeping frequency in contributing to variation in concentrations and loads of nitrogen (N), phosphorus (P), and solids recovered in street sweepings, using analyses of samples collected during regular street sweeping operations in five cities in the Minneapolis-St. Paul Metropolitan Area, Minnesota, USA. We expected that nutrient concentrations and loads would be highest in seasons and places of higher tree litterfall. We also expected that regenerative-air sweepers would recover higher loads compared to mechanical broom sweepers. Total N and P concentrations in sweepings increased most strongly with canopy cover in June, October, and November. Total N and P recovered in street sweepings similarly increased with canopy cover in June, October, and November, and peaked in early summer and autumn, times of high litterfall. In contrast, total dry mass in sweepings was greatest in early spring, following winter snowmelt. However, nutrient loads and concentrations did not differ between sweeper types. Our results add to growing evidence of the importance of street trees in contributing nutrient pollution to urban surface waters. Street sweeping focused on high-canopy streets during early summer and autumn is likely an effective management tool for stormwater nutrient pollution. 

Following the murder of George Floyd, Minneapolis (MN) residents and city officials turned to Mapping Prejudice—a project that mapped every racial covenant in the city and its suburbs—to understand Minneapolis’s deep racial disparities. For this study, we investigated how data on racial covenants, clauses that were used historically to prevent the sale of a property to a person of color, had influenced planning practice in the Twin Cities. In doing so, we considered whether and how engagement with data on structural racism might meaningfully advance anti-racist planning outcomes that enhance the self-development and self-determination of racially marginalized communities. To address this question, we conducted 16 semistructured interviews with 24 planners who have used the data on racial covenants, asking specifically about how racial covenant data shaped planning practice, the planning and policy outcomes that resulted from engaging with racial covenant data, and the characteristics of the racial covenant data that made it influential. This approach assessed planners already interested in addressing racial disparities. Interviews suggest that data on racial covenants were highly influential, leading to a new understanding of structural racism, critical reflection on Whiteness and planning, and a new narrative tool for explaining and addressing racial disparities. Policy outcomes included adopting new housing policies, helping residents remove racial covenants from deeds, and implementing redistributive financial policies. Planners felt these data were important because they could be mapped and visualized and because of their fine geographic scale, narrative qualities, and the process in which they were collected. We draw insights about the kinds of data projects that other planners and researchers might produce to advance and inform anti-racist planning, including data that foreground White privilege, focus on phenomena appropriate for specific geographic and historic contexts, are produced using participatory and transparent processes, and tell a compelling story. 

Minneapolis has the twin distinctions of having one of the most highly rated park systems in the United States and some of the most pronounced racial disparities in wealth and homeownership. We argue that this coupling of urban nature and racial inequality was intentionally produced by the city’s real estate industry and local government. Drawing on Mapping Prejudice’s first complete metro-wide map of racial covenants—clauses in property deeds barring sale to anyone not considered white—we pair quantitative spatial analysis with archival research on turn-of-the century greening campaigns and local real estate practices. We use two developments, Nokomis Terrace and Walton Hills, as illustrative examples of the ways in which developers worked with civil society organizations and local government agencies to secure public investments in green amenities, including gardens and public parks, while blanketing their developments with racial covenants. To boost property values, developers paired “greenness” and legal guarantees of whiteness, engineering idealized nature while excluding racialized groups. The result was that 73 percent of park acreage added from 1910 to 1955, the period in which covenants were used in Minneapolis, had at least one racial covenant within 0.1 miles. Our research links urban greening, racialization, housing discrimination, and environmental injustice with consequences for understanding and confronting environmental inequalities today. 

This dataset is a compilation of spatially explicit, species-specific urban tree inventories from across the seven-county Minneapolis-St. Paul (MSP) metropolitan area in Minnesota, U.S.A. The dataset was compiled to examine fine-scale patterns of tree biodiversity across MSP. Existing tree inventories were solicited from all municipalities, counties, park systems, and relevant non-profit organizations in the region for which we were able to find contact information, resulting in inventories from 37 municipalities, two counties, one park system, and one non-profit, along with two datasets from prior academic research efforts. The spatial and temporal scope of the inventories varies; for example, the inventories from some municipalities include data from a subset of only street trees at one timepoint, while other municipal inventories were continuously updated datasets with spatially comprehensive data for street trees in addition to some trees in parks and private lands. No inventory was fully comprehensive of all trees in an area. Data are assumed to have been collected between 2012-2022, although the timestamp on each data point is not explicit. Individual inventories were combined into one uniform database. 

This high-resolution (1 meter) raster represents road surface area for streets (including alleys) in the seven-county Minneapolis-St. Paul Metropolitan area. Minnesota roads data contributing to this layer is compiled from several state and county agencies and accessed through the Minnesota Geospatial Commons. The Minnesota Transportation Department (MNDOT) Lane Information dataset was spatially joined with MNDOT centerlines from 2012 in order to link the Transportation Information System (TIS) ID codes for road segments with the lane information on number of through transit lanes and width of lanes. The resulting layer was then joined on the TIS code attribute with the Geospatial Advisory Council Schema road centerlines shapefile from MetroGIS. To avoid a many-to-one join, MNDOT road segments were grouped by their TIS code and the average lane width and number were summarized to make the layer compatible with the MetroGIS centerlines shapefile. Once the centerline route segment IDs were linked to the MNDOT transit lane information, the centerlines were buffered based on their average width attribute, multiplied by the number of lanes. Alleys were identified and assigned a width of 5 meters based on typical alley width measurements using satellite imagery. Due to transportation identification system scope, confidence in accuracy of private road surface area is diminished. The resulting buffered road segment vectors were rasterized and cropped to the seven-county metro area (Hennepin, Ramsey, Anoka, Washington, Dakota, Scott, and Carver County).