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Abstract Between the 1780 and 1980s, more than half of the wetlands in the conterminous US were lost. As wetlands have been lost, numerous artificial water features (AWFs), such as stormwater retention ponds, golf course water features, and reservoirs, have been constructed. We contrasted the loss of wetland area and perimeter to the gain of AWF area and perimeter and further explored how this transformation has altered the spatial characteristics of the waterscape. We conducted this analysis in the Tampa Bay Watershed, a large coastal watershed that lost 33% of its wetland area between the 1950s-2007. Trends have been towards fewer, smaller wetlands and more, smaller AWFs. The loss of wetland area far exceeds the gain in AWF area, leading to an overall loss of 23% of the combined wetland and AWF area. However, the loss of wetland perimeter almost equals the gain in AWF perimeter, leading to an overall loss of just 2% of the combined wetland and AWF perimeter. The loss of wetlands and gain of AWFs have predominantly occurred in different geographic locations, with the loss of wetlands predominantly in the headwaters and the gain in AWFs predominantly adjacent to Tampa Bay. Wetlands became further apart, though generally retained their natural distribution, while AWFs became closer to one another and now mirror the more natural wetland distribution. Overall, the physical structure of the waterscape of today is different than in the past, which likely reflects a change in functions performed and related ecological services provided at local and landscape scales. 

There are over 700 aquatic ecological assessment approaches across the globe that meet specific institutional goals. However, in many cases, multiple assessment tools are designed to meet the same management need, resulting in a confusing array of overlapping options. Here, we look at six riverine wetland assessments currently in use in Montana, USA, and ask which tool (1) best captures the condition across a disturbance gradient and (2) has the most utility to meet the regulatory or management needs. We used descriptive statistics to compare wetland assessments (n = 18) across a disturbance gradient determined by a landscape development intensity. Factor analysis showed that many of the tools had internal metrics that did not correspond well with overall results, hindering the tool’s ability to act as designed. We surveyed regional wetland managers (n = 56) to determine the extent of their use of each of the six tools and how well they trusted the information the assessment tool provided. We found that the Montana Wetland Assessment Methodology best measured the range of disturbance and had the highest utility to meet Clean Water Act (CWA§ 404) needs. Montana Department of Environmental Quality was best for the CWA§ 303(d) & 305(b) needs. The US Natural Resources Conservation Service’s Riparian Assessment Tool was the third most used by managers but was the tool that had the least ability to distinguish across a disturbance, followed by the US Bureau of Land Management’s Proper Functioning Condition. 

The Southeastern United States has high landscape heterogeneity, with heavily managed forestlands, developed agriculture, and multiple metropolitan areas. The spatial pattern of land use is dynamic. Expansion of urban areas convert forested and agricultural land, scrub forests are converted to citrus groves, and some croplands transition to pine plantations. Previous studies have recognized that forest management is the predominant factor in structural and functional changes forests, but little is known about how forest management practices interact with surrounding land uses at the regional scale. The first step in studying the spatial relationships of forest management with surrounding landscapes is to be able to map management practices and describe their proximity to various land uses. There are two major difficulties in generating land use and land management maps at the regional scale by any method: the necessity of large training data sets and expensive computation. The combination of crowdsourced, citizen-science mapping and cloud-based computing may help overcome those difficulties. In this study, OpenStreetMap is incorporated into mapping land use and shows great potential for justifying and monitoring land use at a regional scale. Google Earth Engine enables large-scale spatial analysis and imagery processing by providing a variety of Earth observation datasets and computational resources. By incorporating the OpenStreetMap dataset into Earth observation images to map forest land management practices and determine the distribution of other nearby land uses, we develop a robust regional land-use mapping approach and describe the patterns of how different land uses may affect forest management and vice versa . We find that cropland is more likely to be near ecological forest management patches; few close spatial relationships exist between land uses and preservation forest management, which fulfills the preservation management strategy of sustaining the forests, and production forests have the strongest spatial relationships with croplands. This approach leads to increased understanding of land-use patterns and management practices at local to regional scales. 

Understanding where groundwater recharge occurs is essential for managing groundwater resources, especially source-water protection. This can be especially difficult in remote mountainous landscapes where access and data availability are limited. We developed a groundwater recharge potential (GWRP) map across such a landscape based on six readily available datasets selected through the literature review: precipitation, geology, soil texture, slope, drainage density, and land cover. We used field observations, community knowledge, and the Analytical Hierarchy Process to rank and weight the spatial datasets within the GWRP model. We found that GWRP is the highest where precipitation is relatively high, geologic deposits are coarse-grained and unconsolidated, soils are variants of sands and gravels, the terrain is flat, drainage density is low, and land cover is undeveloped. We used GIS to create a map of GWRP, determining that over 83% of this region has a moderate or greater capacity for groundwater recharge. We used two methods to validate this map and assessed it as approximately 87% accurate. This study provides an important tool to support informed groundwater management decisions in this and other similar remote mountainous landscapes. 

We hypothesized topographic features alone could be used to locate groundwater discharge, but only where diagnostic topographic signatures could first be identified through the use of limited field observations and geologic data. We built a geodatabase from geologic and topographic data, with the geologic data only covering ~40% of the study area and topographic data derived from airborne LiDAR covering the entire study area. We identified two types of groundwater discharge: shallow hillslope groundwater discharge, commonly manifested as diffuse seeps, and aquifer-outcrop groundwater discharge, commonly manifested as springs. We developed multistep manual procedures that allowed us to accurately predict the locations of both types of groundwater discharge in 93% of cases, though only where geologic data were available. However, field verification suggested that both types of groundwater discharge could be identified by specific combinations of topographic variables alone. We then applied maximum entropy modeling, a machine learning technique, to predict the prevalence of both types of groundwater discharge using six topographic variables: profile curvature range, with a permutation importance of 43.2%, followed by distance to flowlines, elevation, topographic roughness index, flow-weighted slope, and planform curvature, with permutation importance of 20.8%, 18.5%, 15.2%, 1.8%, and 0.5%, respectively. The AUC values for the model were 0.95 for training data and 0.91 for testing data, indicating outstanding model performance. 

In the United States (US), family forest owners, a group that includes individuals, families, trusts, and estates, are the largest single landowner category, owning approximately one-third of the nation's forests. These landowners' individualized decision-making on forest management has a profound impact on US forest cover and function at both local and regional scales. We sought to understand perceptions among family forest specialists of: climate impacts and adaptation options across different forested US regions; how family forest owners are taking climate adaptation into consideration in their forest management, if at all; and major barriers to more active management for adaptation among family forest owners. We conducted semi-structured interviews with 48 forest experts across the US who work with family forest owners, including extension specialists, state forestry agency employees, and consulting foresters who focus on family forest engagement. Our interviewees shared details on how both climate change impacts and forest management for climate adaptation vary across the US, and they perceived a lack of active forest management by family forest owners. They explained that western forest landowners confronting the imminent threat of catastrophic wildfires are more likely to see a need for active forest management. By contrast, in the east, where most forestland is privately owned, interviewees said that landowners see relatively fewer climate impacts on their forests and less need for forest management to respond to climate change. Perceived barriers to more active family forest management for climate adaptation include the lack of more robust markets for a wide range of forest products, a higher capacity forestry workforce, education and assistance in planning forest management, and addressing the issue of increased parcelization of family forest lands. We situate these perceptions in conversations on the role of boundary organizations in climate adaptation, how individual adaptation occurs, and how governing methods frame adaptation possibilities.