Geographically isolated wetlands (GIWs) are characterized as ‘isolated’ because they are embedded by uplands, though they potentially exhibit a gradient of hydrologic, biological, or chemical connections to other surface waters. In fact, recent field studies have begun to elucidate that GIWs exhibit varying degrees of hydrologic connectivity. In this study, we examine the influence of GIWs on streamflow, a potential indicator of GIW hydrologic connectivity with surface waters. We assess annual and seasonal spatially based statistical relationships between GIW characteristics (e.g. volume and extent) and streamflow across a dense network of subbasins using a hybrid modeling approach. Our method involves the Spatial Stream Network (SSN) model, which considers spatial autocorrelation of model covariates explicitly, and the Soil and Water Assessment Tool (SWAT), which predicts streamflow across a network of 579 subbasins in the lower Neuse River Basin, North Carolina, USA. Our study results suggest that GIWs, to some extent, influence streamflow. The further GIWs are from a stream, the greater their capacity to increase streamflow due to the physiographic setting, hypothesized transit times, and sequencing of watershed hydrologic connectivity in the study area. However, as the combined extent of GIWs and non‐GIWs increases in subbasins, seasonal and annual streamflow decreases. Results also suggest that other landscape indicators of watershed‐scale hydrology can, in aggregate with GIWs and non‐GIWs, explain variations in seasonal and annual simulated streamflow. Our study findings begin to elucidate the aggregate influence of GIWs on streamflow, providing insights for future decision‐making on GIW protection and management. Copyright © 2015 John Wiley & Sons, Ltd.

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Studies that assess the distribution of benefits provided by ecosystem services across urban areas are increasingly common. Nevertheless, current knowledge of both the supply and demand sides of ecosystem services remains limited, leaving a gap in our understanding of balance between ecosystem service supply and demand that restricts our ability to assess and manage these services. The present study seeks to fill this gap by developing and applying an integrated approach to quantifying the supply and demand of a key ecosystem service, carbon storage and sequestration, at the local level. This approach follows three basic steps: (1) quantifying and mapping service supply based upon Light Detection and Ranging (LiDAR) processing and allometric models, (2) quantifying and mapping demand for carbon sequestration using an indicator based on local anthropogenic CO2 emissions, and (3) mapping a supply-to-demand ratio. We illustrate this approach using a portion of the Twin Cities Metropolitan Area of Minnesota, USA. Our results indicate that 1735.69 million kg carbon are stored by urban trees in our study area. Annually, 33.43 million kg carbon are sequestered by trees, whereas 3087.60 million kg carbon are emitted by human sources. Thus, carbon sequestration service provided by urban trees in the study location play a minor role in combating climate change, offsetting approximately 1% of local anthropogenic carbon emissions per year, although avoided emissions via storage in trees are substantial. Our supply-to-demand ratio map provides insight into the balance between carbon sequestration supply in urban trees and demand for such sequestration at the local level, pinpointing critical locations where higher levels of supply and demand exist. Such a ratio map could help planners and policy makers to assess and manage the supply of and demand for carbon sequestration.