Nonpoint pollution sources are strongly influenced by hydrology and are therefore sensitive to climate variability. Some pollutants entering aquatic ecosystems, e.g., nitrate, can be mitigated by in‐stream processes during transport through river networks. Whole river network nitrate retention is difficult to quantify with observations. High frequency, in situ nitrate sensors, deployed in nested locations within a single watershed, can improve estimates of both nonpoint inputs and aquatic retention at river network scales. We deployed a nested sensor network and associated sampling in the urbanizing Oyster River watershed in coastal New Hampshire, USA, to quantify storm event‐scale loading and retention at network scales. An end member analysis used the relative behavior of reactive nitrate and conservative chloride to infer river network fate of nitrate. In the headwater catchments, nitrate and chloride concentrations are both increasingly diluted with increasing storm size. At the mouth of the watershed, chloride is also diluted, but nitrate tended to increase. The end member analysis suggests that this pattern is the result of high retention during small storms (51–78%) that declines to zero during large storms. Although high frequency nitrate sensors did not alter estimates of fluxes over seasonal time periods compared to less frequent grab sampling, they provide the ability to estimate nitrate flux versus storm size at event scales that is critical for such analyses. Nested sensor networks can improve understanding of the controls of both loading and network scale retention, and therefore also improve management of nonpoint source pollution.

Climate change will pose risks for the world's food supply in the coming decades; this comes at a time when the global demand for food is expected to soar based on 2050 world population estimates. It is important to recognize that climate change will necessitate temporal and geographical shifts in food production, but will most likely not result in the collapse of our food systems. However, because of differences in the severity of how climate change will affect agriculture, regional and temporal changes in production and harvest-time will challenge the existing and sometimes outdated agricultural infrastructure with respect to collection, storage, transportation, and distribution of food. Increasing regional and global urbanization will further perturb these systems. Adaptation to climate change with respect to crop and food animal production will have to occur at multiple temporal, seasonal, and geospatial levels. Other major adaptation measures will have to occur with respect to crop selection, genetics, CO 2 and temperature sensitivity, and resilience of crops and food animals, water resources, and mitigation of invasive species. Technology, including sophisticated Geographic Information Systems (GIS)-based modeling, coupled with publically available soil and weather data that help farmers optimize production and conservation will be essential toward adaptation. Communication of this type of localized technical information to agricultural stakeholders by national, federal, and state entities is beginning to occur in order to help farmers adapt and prepare for extreme events associated with climate change. As the largest agricultural state in the USA, California has developed a robust mitigation and adaptation strategy that may be useful for other nation-states. Understanding the Significance of Climate Change and AgricultureClimate change will have variable impacts on agriculture based on multiple factors including changes in temperature, precipitation, and humidity. The magnitude and significance of these changes will be dependent on geography (e.g., summer temperatures will increase more in southern Europe, while winter temperatures will increase more in northern Europe) [1]. These abiotic changes will select for different biotic organisms from micro-organisms to insects, to plants and livestock and poultry. Such changes are already affecting our current agricultural production systems. For example, increases in temperature in California's Central Valley [2,3] and a corresponding loss of winter chill hours associated with temperature increases [4,5] will lead to inhomogeneous and reduced crop yields for several major tree fruit crops [6•].A second example of the impact of climate change is phenology (i.e., seasonal timing) and the potential for phenological mismatches (i.e., shift in phenologies that negatively