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Abstract In order to better understand manifold neural networks (MNNs), we introduce Manifold Filter-Combine Networks (MFCNs). Our filter-combine framework parallels the popular aggregate-combine paradigm for graph neural networks (GNNs) and naturally suggests many interesting families of MNNs which can be interpreted as manifold analogues of various popular GNNs. We propose a method for implementing MFCNs on high-dimensional point clouds that relies on approximating an underlying manifold by a sparse graph. We then prove that our method is consistent in the sense that it converges to a continuum limit as the number of data points tends to infinity, and we numerically demonstrate its effectiveness on real-world and synthetic data sets. 

We utilize a coupled economy–agroecology–hydrology modeling framework to capture the cascading impacts of climate change mitigation policy on agriculture and the resulting water quality cobenefits. We analyze a policy that assigns a range of United States government’s social cost of carbon estimates ($51, $76, and $152/ton of CO₂-equivalents) to fossil fuel–based CO₂emissions. This policy raises energy costs and, importantly for agriculture, boosts the price of nitrogen fertilizer production. At the highest carbon price, US carbon emissions are reduced by about 50%, and nitrogen fertilizer prices rise by about 90%, leading to an approximate 15% reduction in fertilizer applications for corn production across the Mississippi River Basin. Corn and soybean production declines by about 7%, increasing crop prices by 6%, while nitrate leaching declines by about 10%. Simulated nitrate export to the Gulf of Mexico decreases by 8%, ultimately shrinking the average midsummer area of the Gulf of Mexico hypoxic area by 3% and hypoxic volume by 4%. We also consider the additional benefits of restored wetlands to mitigate nitrogen loading to reduce hypoxia in the Gulf of Mexico and find a targeted wetland restoration scenario approximately doubles the effect of a low to moderate social cost of carbon. Wetland restoration alone exhibited spillover effects that increased nitrate leaching in other parts of the basin which were mitigated with the inclusion of the carbon policy. We conclude that a national climate policy aimed at reducing greenhouse gas emissions in the United States would have important water quality cobenefits. 

Abstract The exploitation of ecosystem services, through processes like agricultural production, is associated with myriad negative environmental impacts, which are felt by stakeholders on local, regional, and global scales. The varying type and scale of impacts leads naturally to fragmented and siloed approaches to mitigating externalities by diverse governmental and non-governmental institutions. However, policies designed to address a single impact may worsen other negative impacts. As a result, even when groups have the expertise to design policy solutions in one dimension, policies addressing single issues may conflict and result in less than ideal outcomes in combination. In this paper, we present a conceptual framework and examples of this kind of ‘policy collision,’ where policies produce mutual negative interference so that policies designed independently may fail to achieve their goals. We argue that an integrated systems perspective is needed to overcome this problem and present several positive examples where this has been put into practice. Policy collision provides a useful framework for determining how each colliding policy should be modified in improve outcomes. 

Amidst the growing population, urbanization, globalization, and economic growth, along with the impacts of climate change, decision-makers, stakeholders, and researchers need tools for better assessment and communication of the highly interconnected food–energy–water (FEW) nexus. This study aimed to identify critical periods for water resources management for robust decision-making for water resources management at the nexus. Using a 4610 ha agricultural watershed as a pilot site, historical data (2006–2012), scientific literature values, and SWAT model simulations were utilized to map out critical periods throughout the growing season of corn and soybeans. The results indicate that soil water deficits are primarily seen in June and July, with average deficits and surpluses ranging from −134.7 to +145.3 mm during the study period. Corresponding water quality impacts include average monthly surface nitrate-N, subsurface nitrate-N, and soluble phosphorus losses of up to 0.026, 0.26, and 0.0013 kg/ha, respectively, over the growing season. Estimated fuel requirements for the agricultural practices ranged from 24.7 to 170.3 L/ha, while estimated carbon emissions ranged from 0.3 to 2.7 kg CO2/L. A composite look at all the FEW nexus elements showed that critical periods for water management in the study watershed occurred in the early and late season—primarily related to water quality—and mid-season, related to water quantity. This suggests the need to adapt agricultural and other management practices across the growing season in line with the respective water management needs. The FEW nexus assessment methodologies developed in this study provide a framework in which spatial, temporal, and literature data can be implemented for improved water resources management in other areas.