A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

Hydrologic Controls on Nitrogen and Phosphorous Dynamics in Relict Oxbow Wetlands Adjacent to an Urban Restored Stream

Although wetlands are known to be sinks for nitrogen (N) and phosphorus (P), their function in urban watersheds remains unclear. We analyzed water and nitrate (NO₃^?) and phosphate (PO₄^3?) dynamics during precipitation events in two oxbow wetlands that were created during geomorphic stream restoration in Baltimore County, Maryland that varied in the nature and extent of connectivity to the adjacent stream. Oxbow 1 (Ox1) received 1.6‐4.2% and Oxbow 2 (Ox2) received 4.2‐7.4% of cumulative streamflow during storm events from subsurface seepage (Ox1) and surface flow (Ox2). The retention time of incoming stormwater ranged from 0.2 to 6.7 days in Ox1 and 1.8 to 4.3 days in Ox2. Retention rates in the wetlands ranged from 0.25 to 2.74 g N/m²/day in Ox1 and 0.29 to 1.94 g N/m²/day in Ox2. Percent retention of the NO₃^?‐N load that entered the wetlands during the storm events ranged from 64 to 87% and 23 to 26%, in Ox1 and Ox2, respectively. During all four storm events, Ox1 and Ox2 were a small net source of dissolved PO₄^3? to the adjacent stream (i.e., more P exited than entered the wetland), releasing P at a rate of 0.23‐20.83 mg P/m²/day and 3.43‐24.84 mg P/m²/day, respectively. N and P removal efficiency of the oxbows were regulated by hydrologic connectivity, hydraulic loading, and retention time. Incidental oxbow wetlands have potential to receive urban stream and storm flow and to be significant N sinks, but they may be sources of P in urban watersheds.     

Behavioral Traits and Airport Type Affect Mammal Incidents with U.S. Civil Aircraft

Wildlife incidents with aircraft cost the United States (U.S.) civil aviation industry >US$1.4 billion in estimated damages and loss of revenue from 1990 to 2009. Although terrestrial mammals represented only 2.3 % of wildlife incidents, damage to aircraft occurred in 59 % of mammal incidents. We examined mammal incidents (excluding bats) at all airports in the Federal Aviation Administration (FAA) National Wildlife Strike Database from 1990 to 2010 to characterize these incidents by airport type: Part-139 certified (certificated) and general aviation (GA). We also calculated relative hazard scores for species most frequently involved in incidents. We found certificated airports had more than twice as many incidents as GA airports. Incidents were most frequent in October (n = 215 of 1,764 total) at certificated airports and November (n = 111 of 741 total) at GA airports. Most (63.2 %) incidents at all airports (n = 1,523) occurred at night but the greatest incident rate occurred at dusk (177.3 incidents/hr). More incidents with damage (n = 1,594) occurred at GA airports (38.6 %) than certificated airports (19.0 %). Artiodactyla (even-toed ungulates) incidents incurred greatest (92.4 %) damage costs (n = 326; US$51.8 million) overall and mule deer (Odocoileus hemionus) was the most hazardous species. Overall, relative hazard score increased with increasing log body mass. Frequency of incidents was influenced by species relative seasonal abundance and behavior. We recommend airport wildlife officials evaluate the risks mammal species pose to aircraft based on the hazard information we provide and consider prioritizing management strategies that emphasize reducing their occurrence on airport property.     

An Exploration of Scenarios to Support Sustainable Land Management Using Integrated Environmental Socio-economic Models

Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA–DESMICE modeling framework with various scenarios for 13 global land degradation hotspots. Starting with an initial assessment representing land degradation and productivity under current conditions, options to combat instances of land degradation are explored by determining: (1) Which technologies are most biophysically appropriate and most financially viable in which locations; we term these the “technology scenarios”; (2) how policy instruments such as subsidies influence upfront investment requirements and financial viability and how they lead to reduced levels of land degradation; we term these the “policy scenarios”; and (3) how technology adoption affects development issues such as food production and livelihoods; we term these the “global scenarios”. Technology scenarios help choose the best technology for a given area in biophysical and financial terms, thereby outlining where policy support may be needed to promote adoption; policy scenarios assess whether a policy alternative leads to a greater extent of technology adoption; while global scenarios demonstrate how implementing technologies may serve wider sustainable development goals. Scenarios are applied to assess spatial variation within study sites as well as to compare across different sites. Our results show significant scope to combat land degradation and raise agricultural productivity at moderate cost. We conclude that scenario assessment can provide informative input to multi-level land management decision-making processes.     

Effects of Livestock Grazing and Well Construction on Prairie Vegetation Structure Surrounding Shallow Natural Gas Wells

Short and sparse vegetation near shallow gas wells has generally been attributed to residual effects from well construction, but other mechanisms might also explain these trends. We evaluated effects of distance to shallow gas wells on vegetation and bare ground in mixed-grass prairies in southern Alberta, Canada, from 2010 to 2011. We then tested three hypotheses to explain why we found shorter vegetation and more bare ground near wells, using cattle fecal pat transects from 2012, and our vegetation quadrats. We evaluated whether empirical evidence suggested that observed patterns were driven by (1) higher abundance of crested wheatgrass (Agropyron cristatum) near wells, (2) residual effects of well construction, or (3) attraction of livestock to wells. Crested wheatgrass occurrence was higher near wells, but this did not explain effects of wells on vegetation structure. Correlations between distance to wells and litter depth were the highest near newer wells, providing support for the construction hypothesis. However, effects of distance to wells on other vegetation metrics did not decline as time since well construction increased, suggesting that other mechanisms explained observed edge effects. Cattle abundance was substantially higher near wells, and this effect corresponded with changes in habitat structure. Our results suggest that both residual effects of well construction and cattle behavior may explain effects of shallow gas wells on habitat structure in mixed-grass prairies, and thus, to be effective, mitigation strategies must address both mechanisms.     

What Can Funders Do to Better Link Science with Decisions? Case Studies of Coastal Communities and Climate Change

Many reports and studies have noted that a significant portion of problem-oriented coastal science does not actually link to decisions. Here, three competitively funded project case studies are studied to determine what funders can and should do to better link science with decisions. The qualitative analysis used for this study indicates that the studied program was seen as being unusually attentive to the issue of linking science to decisions, as opposed to simply generating new knowledge. Nevertheless, much of the data indicate that funders can and should do more. Three ideas figured most prominently in the qualitative data: (1) funders should do more to ensure that the problem itself is defined more thoroughly with people who are envisioned as potential users of the science; (2) funders need to allocate more resources and attention to communicating effectively (with users) throughout the project; and (3) funders need to demand more engagement of users throughout the project. These findings have important implications for how funders review and support science, especially when competitive processes are used. Most importantly, funders should adjust what kind of science they ask for. Secondly, funders need to change who is involved in the review process. Currently, review processes focus on knowledge generation, which means that the reviewers themselves have expertise in that area. Instead, review panels should be balanced between those who focus on knowledge generation and those who focus on linking knowledge to decisions; this is a separate but critical discipline currently left out of the review process.     

Riverine Threat Indices to Assess Watershed Condition and Identify Primary Management Capacity of Agriculture Natural Resource Management Agencies

Managers can improve conservation of lotic systems over large geographies if they have tools to assess total watershed conditions for individual stream segments and can identify segments where conservation practices are most likely to be successful (i.e., primary management capacity). The goal of this research was to develop a suite of threat indices to help agriculture resource management agencies select and prioritize watersheds across Missouri River basin in which to implement agriculture conservation practices. We quantified watershed percentages or densities of 17 threat metrics that represent major sources of ecological stress to stream communities into five threat indices: agriculture, urban, point-source pollution, infrastructure, and all non-agriculture threats. We identified stream segments where agriculture management agencies had primary management capacity. Agriculture watershed condition differed by ecoregion and considerable local variation was observed among stream segments in ecoregions of high agriculture threats. Stream segments with high non-agriculture threats were most concentrated near urban areas, but showed high local variability. 60 % of stream segments in the basin were classified as under U.S. Department of Agriculture’s Natural Resources Conservation Service (NRCS) primary management capacity and most segments were in regions of high agricultural threats. NRCS primary management capacity was locally variable which highlights the importance of assessing total watershed condition for multiple threats. Our threat indices can be used by agriculture resource management agencies to prioritize conservation actions and investments based on: (a) relative severity of all threats, (b) relative severity of agricultural threats, and (c) and degree of primary management capacity.