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Natural infrastructure such as parks, forests, street trees, green roofs, and coastal vegetation is central to sustainable urban management. Despite recent progress, it remains challenging for urban decision-makers to incorporate the benefits of natural infrastructure into urban design and planning. Here, we present an approach to support the greening of cities by quantifying and mapping the diverse benefits of natural infrastructure for now and in the future. The approach relies on open-source tools, within the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, that compute biophysical and socio-economic metrics relevant to a variety of decisions in data-rich or data-scarce contexts. Through three case studies in China, France, and the United States, we show how spatially explicit information about the benefits of nature enhances urban management by improving economic valuation, prioritizing land use change, and promoting inclusive planning and stakeholder dialogue. We discuss limitations of the tools, including modeling uncertainties and a limited suite of output metrics, and propose research directions to mainstream natural infrastructure information in integrated urban management. Nanyang Technological University Published version Part of this research was supported by the Marianne and Marcus Wallenberg Foundation, the Swedish research council FORMAS (2018-002371), and the LuEsther T. Mertz Charitable Trust. We acknowledge funding from Nanyang Technological University for the first author; the US Golf Association for the Twin Cities case study, the Chinese Academy of Sciences for the Shenzhen case study, and the Ministère de la Transition Écologique et Solidaire, ADEME, and AgroParisTech for the Paris case study. The first author acknowledges Nanyang Technological University for financial contribution to this research.

A diverse range of threats have been associated with managed-bee declines globally. Recent increases of two known threats, land-use change and pesticide use, have resulted from agricultural expansion and intensification notably in the top honey-producing state in the United States: North Dakota. This study investigated the dual threat from land conversion and pesticide use surrounding ~14,000 registered apiaries in North Dakota from 2001 to 2014. We estimated the annual total insecticide use (kg) on major crops within 1.6 km of apiary sites. Of the eight insecticides quantified, six showed significant increasing trends over the time period. Specifically, applications of the newly established neonicotinoids Chlothianidin, Imidacloprid and Thiamethoxam, increased annually by 1329 kg, 686 kg, 795 kg, respectively. Also, the use of Chlorpyrifos, which was well-established in the state by 2001 and is highly toxic to honey bees, increased by ~8,800 kg annually from 6,500 kg in 2001 to 115,000 kg in 2014 on corn, soybeans and wheat. We further evaluated the relative quality changes of natural/semi-natural land covers surrounding apiaries in 2006, 2010 and 2014, a period of significant increases in cropland area. In areas surrounding apiaries, we observed changes in multiple indices of forage quality that reflect the deteriorating landscape surrounding registered apiary sites due to land-use change and pesticide-use increases. Overall, our results suggest that the application of foliar-applied insecticides, including pyrethroids and one organophosphate, increased surrounding apiaries when the use of neonicotinoid seed treatments surged and the area for producing corn and soybeans expanded. Spatially, these threats were most pronounced in southeastern North Dakota, a region hosting a high density of apiary sites that has recently experienced corn and soybean expansion. Our results highlight the value of natural and semi-natural land covers as sources of pollinator forage and refugia for bees against pesticide exposure. Our study provides insights for targeting conservation efforts to improve forage quality benefiting managed pollinators.

Long-term snowfall change offers insight for understanding climate change, managing water resources, and assessing climate model performance, especially at regional scales where topography plays an important role in shaping regional climate and water availability. In this study, we examined the changes of annual snowfall using observations from 1961 to 2017 in central North America, a region with high contrast in topographic complexities. There is a general, yet distinct difference in the snowfall trends demarcated approximately along the 105&deg, W meridian. To its east, which is dominated by plains, snowfall had increased overall, except in a limited area south of 42&deg, N, where snowfall decreased slightly. To the west of 105&deg, W, which is dominated by the Rocky Mountains, there was a wide spread of decreasing trend, with only two pockets of area at an elevation of &gt, 2000 m exhibiting increasing snowfall trends. Multiple linear regression analysis showed that, in addition to the average annual snowfall, snowfall trends significantly correlated with elevation in the mountain region and with average snow season temperature in the plains region, suggesting different mechanisms potentially shaping snowfall trends in the two regions.

Watershed hydrologic models often possess different structures and distinct methods and require dissimilar types of inputs. As spatially-distributed data are becoming widely available, macro-scale modeling plays an increasingly important role in water resources management. However, calibration of a macro-scale grid-based model can be a challenge. The objective of this study is to improve macro-scale hydrologic modeling by joint simulation and cross-calibration of different models. A joint modeling framework was developed, which linked a grid-based hydrologic model (GHM) and the subbasin-based Soil and Water Assessment Tool (SWAT) model. Particularly, a two-step cross-calibration procedure was proposed and implemented: (1) direct calibration of the subbasin-based SWAT model using observed streamflow data; and (2) indirect calibration of the grid-based GHM through the transfer of the well-calibrated SWAT simulations to the GHM. The joint GHM-SWAT modeling framework was applied to the Red River of the North Basin (RRB). The model performance was assessed using the Nash–Sutcliffe efficiency (NSE) and percent bias (PBIAS). The results highlighted the feasibility of the proposed cross-calibration strategy in taking advantage of both model structures to analyze the spatial/temporal trends of hydrologic variables. The modeling approaches developed in this study can be applied to other basins for macro-scale climatic-hydrologic modeling.

Significance Global pollinator declines have raised significant concern over food security, human health, and agricultural productivity. Our work highlights how the Conservation Reserve Program (CRP) has a direct influence on landscape suitability for supporting honey bee apiaries in a region harboring >1 million colonies. Our analysis revealed recent conversion of CRP grassland to annual crops in core areas of the commercial beekeeping industry, thereby reducing forage lands for honey bees at a time when the number of colonies in this region has never been greater. Our land-use scenario models provide policy makers with direct information on how future CRP acreage caps established by the US Congress will affect the environmental carrying capacity for supporting honey bees and the US beekeeping industry., Human dependence on insect pollinators continues to grow even as pollinators face global declines. The Northern Great Plains (NGP), a region often referred to as America’s last honey bee (Apis mellifera) refuge, has undergone rapid land-cover change due to cropland expansion and weakened land conservation programs. We conducted a trend analysis and estimated conversion rates of Conservation Reserve Program (CRP) enrollments around bee apiaries from 2006 to 2016 and developed models to identify areas of habitat loss. Our analysis revealed that NGP apiaries lost over 53% of lands enrolled in the CRP, and the rate of loss was highest in areas of high apiary density. We estimated over 163,000 ha of CRP lands in 2006 within 1.6 km of apiaries was converted to row crops by 2012. We also evaluated how alternative scenarios of future CRP acreage caps may affect habitat suitability for supporting honey bee colonies. Our scenario revealed that a further reduction in CRP lands to 7.7 million ha nationally would reduce the number of apiaries in the NGP that meet defined forage criteria by 28% on average. Alternatively, increasing the national cap to 15 million ha would increase the number of NGP apiaries that meet defined forage criteria by 155%. Our scenarios also show that strategic placement of CRP lands near existing apiaries increased the number of apiaries that meet forage criteria by 182%. Our research will be useful for informing the potential consequences of future US farm bill policy and land management in the epicenter of the US beekeeping industry.

CE-QUAL-W2 is widely used for simulating hydrodynamics and water quality of the aquatic environments. Currently, the model calibration is mainly based on trial and error, and therefore it is subject to the knowledge and experience of users. The Particle Swarm Optimization (PSO) algorithm has been tested for automatic calibration of CE-QUAL-W2, but it has an issue of prematurely converging to a local optimum. In this study, we proposed an Improved Global-Best Harmony Search (IGHS) algorithm to automatically calibrate the CE-QUAL-W2 model to overcome these shortcomings. We tested the performance of the IGHS calibration method by simulating water temperature of Devils Lake, North Dakota, which agreed with field observations with R2 = 0.98, and RMSE = 1.23 and 0.77 °C for calibration (2008–2011) and validation (2011–2016) periods, respectively. The same comparison, but with the PSO-calibrated CE-QUAL-W2 model, produced R2 = 0.98 and Root Mean Squared Error (RMSE) = 1.33 and 0.91 °C. Between the two calibration methods, the CE-QUAL-W2 model calibrated by the IGHS method could lower the RMSE in water temperature simulation by approximately 7–15%.

The combined effects of climate and land-use change have changed both the hydrology and management of endorheic watersheds globally. Devils Lake (DL), North Dakota, USA, has risen nearly 10 m since 1991, resulting in a costly, lengthy and litigious water management issue in the region. With more than 1 billion US dollars already spent in mitigation, DL is less than 2 m from its uncontrolled overspill to the nearby Sheyenne River, which could lead to mounting economic, environmental and social costs. While previous studies have generally attributed the changes in the hydrology of DL to the current wet spell, the impacts of land-use changes have not been investigated. Using a hydrological model, here we develop four land-use alternatives driven by market and policy conditions in the DL watershed and investigate their effects on DL hydrology and overspill probability under historic and changed climates. Land-use scenarios under an ensemble of statistically downscaled general circulation model projections indicate a higher overspill risk (7.4–17.0 vs. 0–2 %) under historical climate. Incentivized grass and alfalfa scenarios were able to moderate the hydrological implications to DL under a changed climate, indicating their potential companion roles in DL flood mitigation strategies.

Studies have shown that the agricultural expansion and land use changes in the Midwest of the U.S. are major drivers for increased nonpoint source pollution throughout the regional river systems. In this study, we empirically examined the relationship of planted area and production of three dominant crops with nitrate flux in the Republican River, Kansas, a sub-watershed of Mississippi River Basin. Our results show that land use in the region could not explain the observed changes in nitrate flux in the river. Instead, after including explanatory variables such as precipitation, growing degree days, and well water irrigation in the regression model we found that irrigation and spring precipitation could explain >85% of the variability in nitrate flux from 2000 to 2014. This suggests that changes in crop acreage and production alone cannot explain variability in nitrate flux. Future agricultural policy for the region should focus on controlling both the timing and amount of fertilizer applied to the field to reduce the potential leaching of excess fertilizer through spring time runoff and/or over-irrigation into nearby river systems.

Summary The US Energy Independence and Security Act (EISA) of 2007 has contributed to widespread changes in agricultural land uses. The impact of these land use changes on regional water resources could also be significant. Agricultural land use changes were evaluated for the Red River of the North Basin, an international river basin shared by the US and Canada. The influence of the land use change on spring snowmelt flooding and downstream water quality was also assessed using watershed modeling. The planting areas for corn and soybean in the basin increased by 62% and 18%, while those for spring wheat, forest, and pasture decreased by 30%, 18%, and 50%, from 2006 to 2013. Although the magnitude of spring snowmelt peak flows in the Red River did not change from pre-EISA to post-EISA, our uncertainty analysis of the normalized hydrographs revealed that the downstream streamflows had a greater variability under the post-EISA land use scenario, which may lead to greater uncertainty in predicting spring snowmelt floods in the Red River. Hydrological simulation also showed that the sediment and nutrient loads at the basin’s outlet in the US and Canada border increased under the post-EISA land use scenario, on average sediment increasing by 2.6%, TP by 14.1%, nitrate nitrogen by 5.9%, and TN by 9.1%.

Summary This paper examines recent studies that estimate the impact of education on economic growth. It explains why cross-country regressions face formidable econometric problems. Recent studies are reviewed: some show strong impacts of education on economic growth; others show little effect. All have multiple estimation problems, which may explain their divergent results. Evidence shows that education quality in Sub-Saharan Africa is much lower than in other developing countries. Estimates from three influential studies are extended; the results suggest that the impact of education on economic growth in Sub-Saharan Africa is lower than in other countries, likely due to lower school quality.

The water level of Devils Lake, a terminal lake in the northeast of North Dakota, U.S., has risen nearly 10 m since 1993, inundating farm land and causing significant damages to the infrastructure and surrounding communities. The currently adopted flood adaptation policy is continuing infrastructural protection (CIP), under which the infrastructure, such as levees or roads, is raised gradually in response to the rising water. Since the Devils Lake city and the adjacent communities are built within the historical confines of the lake, we introduce and estimate potential costs of two diametrical, but long-term targeted adaptation strategies involving either buyout or relocation (B/R) to contrast against the CIP. The comparison shows that B/R, while more expensive initially, would be cheaper than CIP accumulated over longer term. We further explore the reason that policymakers prefer CIP: the near-term uncertainty regarding the future lake levels has led to significant discount of long-term potential risk. With future risk significantly discounted, not only B/R, but any other alternatives that feature long-term perspective, could become less attractive than CIP. Were we able to predict the flooding more accurately or willing to discount future less, we might have chosen a different plan of action. The ultimate choice of CIP among the possible adaptation options reveals that policymakers have privileged the present and favored near-term remedies instead of long-term solutions. Although certainly not on the same scale, the lesson we have learned in dealing with Devils Lake has far-reaching implications on climate change adaptation strategies. The passive decision to wait and ignore the full potential for disaster ultimately leaves us with no other option, but to continue to “wait and see” and then spend more.

Environmental impacts of energy use can impose large costs on society. We quantify and monetize the life-cycle climate-change and health effects of greenhouse gas (GHG) and fine particulate matter (PM 2.5 ) emissions from gasoline, corn ethanol, and cellulosic ethanol. For each billion ethanol-equivalent gallons of fuel produced and combusted in the US, the combined climate-change and health costs are $469 million for gasoline, $472–952 million for corn ethanol depending on biorefinery heat source (natural gas, corn stover, or coal) and technology, but only $123–208 million for cellulosic ethanol depending on feedstock (prairie biomass, Miscanthus , corn stover, or switchgrass). Moreover, a geographically explicit life-cycle analysis that tracks PM 2.5 emissions and exposure relative to U.S. population shows regional shifts in health costs dependent on fuel production systems. Because cellulosic ethanol can offer health benefits from PM 2.5 reduction that are of comparable importance to its climate-change benefits from GHG reduction, a shift from gasoline to cellulosic ethanol has greater advantages than previously recognized. These advantages are critically dependent on the source of land used to produce biomass for biofuels, on the magnitude of any indirect land use that may result, and on other as yet unmeasured environmental impacts of biofuels.

In the late nineteenth century and twentieth century, there was considerable interest and activity to develop the United States for agricultural, mining, and many other purposes to improve the quality of human life standards and prosperity. Most of the work to support this development was focused along disciplinary lines with little attention focused on ecosystem service trade-offs or synergisms, especially those that transcended boundaries of scientific disciplines and specific interest groups. Concurrently, human population size has increased substantially and its use of ecosystem services has increased more than five-fold over just the past century. Consequently, the contemporary landscape has been highly modified for human use, leaving behind a fragmented landscape where basic ecosystem functions and processes have been broadly altered. Over this period, climate change also interacted with other anthropogenic effects, resulting in modern environmental problems having a complexity that is without historical precedent. The challenge before the scientific community is to develop new science paradigms that integrate relevant scientific disciplines to properly frame and evaluate modern environmental problems in a systems-type approach to better inform the decision-making process. Wetland science is a relatively new discipline that grew out of the conservation movement of the early twentieth century. In the United States, most of the conservation attention in the earlier days was on wildlife, but a growing human awareness of the importance of the environment led to the passage of the National Environmental Policy Act in 1969. Concurrently, there was a broadening interest in conservation science, and the scientific study of wetlands gradually gained acceptance as a scientific discipline. Pioneering wetland scientists became formally organized when they formed The Society of Wetland Scientists in 1980 and established a publication outlet to share wetland research findings. In comparison to older and more traditional scientific disciplines, the wetland sciences may be better equipped to tackle today’s complex problems. Since its emergence as a scientific discipline, the study of wetlands has frequently required interdisciplinary and integrated approaches. This interdisciplinary/integrated approach is largely the result of the fact that wetlands cannot be studied in isolation of upland areas that contribute surface and subsurface water, solutes, sediments, and nutrients into wetland basins. However, challenges still remain in thoroughly integrating the wetland sciences with scientific disciplines involved in upland studies, especially those involved with agriculture, development, and other land-conversion activities that influence wetland hydrology, chemistry, and sedimentation. One way to facilitate this integration is to develop an understanding of how human activities affect wetland ecosystem services, especially the trade-offs and synergisms that occur when land-use changes are made. Used in this context, an understanding of the real costs of managing for a particular ecosystem service or groups of services can be determined and quantified in terms of reduced delivery of other services and in overall sustainability of the wetland and the landscapes that support them. In this chapter, we discuss some of the more salient aspects of a few common wetland types to give the reader some background on the diversity of functions that wetlands perform and the specific ecosystem services they provide to society. Wetlands are among the most complex ecosystems on the planet, and it is often difficult to communicate to a diverse public all of the positive services wetlands provide to mankind. Our goal is to help the reader develop an understanding that management options can be approached as societal choices where decisions can be made within a spatial and temporal context to identify trade-offs, synergies, and effects on long-term sustainability of wetland ecosystems. This will be especially relevant as we move into alternate climate futures where our portfolio of management options for mitigating damage to ecosystem function or detrimental cascading effects must be diverse and effective.